A Knowledge Management (KM) System plays a crucial role in every industry as well as in Higher Learning Institutions. A RESTful resource is anything that is addressable over the Web. The resources can be accessed and transferred between clients and server. The resources can be accessed and transferred between clients and servers. Based on our earlier research works, we have developed a comprehensive KM System framework, evaluation method, mult-dimensional metric model and useful metrics which are helpful to assess any given knowledge management system. In this proposed work, we first describe the actual implementation steps for building the KM System metric database using the multi-dimensional metric model. Secondly we describe the approaches for designing a multi-dimensional Restful Resources and Web Services using the mutli-dimensional metric model and demonstrate how the KM system can be ranked and rated for its effectiveness using WAM and RESTful Resources.
1) The document describes a web-based monitoring and executive information system for PT Telekomunikasi Indonesia Tbk East Regional to monitor the performance of partners.
2) It aims to develop a web-based application to allow managers to easily monitor partners' sales performance from any location in real-time.
3) The proposed system would display key performance indicators and data visualizations to help managers analyze partners' performance and identify any issues.
1) The document discusses ERP systems in the construction industry, including a literature review on ERP concepts and case studies of ERP implementations.
2) A survey of construction contractors found that over half were aware of ERPs and felt they could provide benefits like improved customer responsiveness and decision making, but many contractors also expressed concerns about costs and technical requirements.
3) Contractors currently using ERPs reported systems from vendors like Oracle and J.D. Edwards that perform functions such as accounting, project management, and scheduling, though further integration was still needed.
SIMPLIFIED CBA CONCEPT AND EXPRESS CHOICE METHOD FOR INTEGRATED NETWORK MANAG...IJCNCJournal
This document proposes a simplified method for evaluating and selecting a network management system (NMS) for integration into an existing computer network. The method evaluates NMS options based on 3 criteria: 1) the level of integration risk, 2) the expected increase in network maintenance effectiveness, and 3) the level of management tasks completed by the system. Each criterion is evaluated on a standardized scale of 0 to 2. The scores are combined to calculate an overall value for each NMS, with the highest scoring option selected for integration. The method aims to provide a rapid evaluation that does not require extensive expertise, resources or time.
A refined metric suite for a multi agent systemeSAT Journals
Abstract
Metrics are the basic factor for the evaluation process of an agent software .The evaluation process are complex and the available metrics for measuring the agent characteristic are in sufficient. This is due to the factor that the agents are unpredictable in a multi-agent system (MAS).In this paper we have done a detailed study about the agent-oriented methodologies and agent-oriented metrics in a suitable environment.
Keywords: agent metrics; MAS; AOSE;
This document summarizes a study on facilities management (FM) managers' perceptions of implementing and using Computer Aided Facilities Management (CAFM) systems in Malaysia. It conducted a survey of 61 FM managers to evaluate CAFM functions across operational, tactical, and strategic management levels. The study found that most respondents had over 6 years of FM experience and were familiar with CAFM. It identified reducing response time, improving service delivery and communication as top CAFM strengths. Budget and lack of understanding were main barriers to CAFM adoption. The study met its objectives to determine key CAFM functions, compare perceptions across management levels, and found no significant differences between levels in CAFM use. It recommends the study
This document discusses dynamic resource allocation using virtual machines. It begins by introducing cloud computing and how it allows scaling of resource usage based on demand through virtualization technology. It then analyzes the existing system of mapping virtual machines to physical resources and proposes an automated resource management system to achieve a balance between overload avoidance and green computing. The key modules of the proposed system are described as the cloud computing module, resource management module, and virtualization module. It further discusses system requirements, feasibility analysis, various UML diagrams including use case diagrams and sequence diagrams, and concludes with describing the software technologies used.
Delivering IT as A Utility- A Systematic Reviewijfcstjournal
Utility Computing has facilitated the creation of new markets that has made it possible to realize the longheld
dream of delivering IT as a Utility. Even though utility computing is in its nascent stage today, the
proponents of utility computing envisage that it will become a commodity business in the upcoming time
and utility service providers will meet all the IT requests of the companies. This paper takes a crosssectional
view at the emergence of utility computing along with different requirements needed to realize
utility model. It also surveys the current trends in utility computing highlighting diverse architecture
models aligned towards delivering IT as a utility. Different resource management systems for proficient
allocation of resources have been listed together with various resource scheduling and pricing strategies
used by them. Further, a review of generic key perspectives closely related to the concept of delivering IT
as a Utility has been taken citing the contenders for the future enhancements in this technology in the form
of Grid and Cloud Computing.
Contributors to Reduce Maintainability Cost at the Software Implementation PhaseWaqas Tariq
This document discusses factors that can reduce software maintenance costs during the implementation phase. It identifies that maintenance costs are highest during software development phases. The objective is to define criteria to assess software quality characteristics and assist during implementation. This will help reduce maintenance costs by creating criteria groups to support writing standard code, developing a model to apply criteria, and increasing understandability. Student groups will study code standardization, write programs, and test software maintenance on programs to validate the model and proposed criteria.
1) The document describes a web-based monitoring and executive information system for PT Telekomunikasi Indonesia Tbk East Regional to monitor the performance of partners.
2) It aims to develop a web-based application to allow managers to easily monitor partners' sales performance from any location in real-time.
3) The proposed system would display key performance indicators and data visualizations to help managers analyze partners' performance and identify any issues.
1) The document discusses ERP systems in the construction industry, including a literature review on ERP concepts and case studies of ERP implementations.
2) A survey of construction contractors found that over half were aware of ERPs and felt they could provide benefits like improved customer responsiveness and decision making, but many contractors also expressed concerns about costs and technical requirements.
3) Contractors currently using ERPs reported systems from vendors like Oracle and J.D. Edwards that perform functions such as accounting, project management, and scheduling, though further integration was still needed.
SIMPLIFIED CBA CONCEPT AND EXPRESS CHOICE METHOD FOR INTEGRATED NETWORK MANAG...IJCNCJournal
This document proposes a simplified method for evaluating and selecting a network management system (NMS) for integration into an existing computer network. The method evaluates NMS options based on 3 criteria: 1) the level of integration risk, 2) the expected increase in network maintenance effectiveness, and 3) the level of management tasks completed by the system. Each criterion is evaluated on a standardized scale of 0 to 2. The scores are combined to calculate an overall value for each NMS, with the highest scoring option selected for integration. The method aims to provide a rapid evaluation that does not require extensive expertise, resources or time.
A refined metric suite for a multi agent systemeSAT Journals
Abstract
Metrics are the basic factor for the evaluation process of an agent software .The evaluation process are complex and the available metrics for measuring the agent characteristic are in sufficient. This is due to the factor that the agents are unpredictable in a multi-agent system (MAS).In this paper we have done a detailed study about the agent-oriented methodologies and agent-oriented metrics in a suitable environment.
Keywords: agent metrics; MAS; AOSE;
This document summarizes a study on facilities management (FM) managers' perceptions of implementing and using Computer Aided Facilities Management (CAFM) systems in Malaysia. It conducted a survey of 61 FM managers to evaluate CAFM functions across operational, tactical, and strategic management levels. The study found that most respondents had over 6 years of FM experience and were familiar with CAFM. It identified reducing response time, improving service delivery and communication as top CAFM strengths. Budget and lack of understanding were main barriers to CAFM adoption. The study met its objectives to determine key CAFM functions, compare perceptions across management levels, and found no significant differences between levels in CAFM use. It recommends the study
This document discusses dynamic resource allocation using virtual machines. It begins by introducing cloud computing and how it allows scaling of resource usage based on demand through virtualization technology. It then analyzes the existing system of mapping virtual machines to physical resources and proposes an automated resource management system to achieve a balance between overload avoidance and green computing. The key modules of the proposed system are described as the cloud computing module, resource management module, and virtualization module. It further discusses system requirements, feasibility analysis, various UML diagrams including use case diagrams and sequence diagrams, and concludes with describing the software technologies used.
Delivering IT as A Utility- A Systematic Reviewijfcstjournal
Utility Computing has facilitated the creation of new markets that has made it possible to realize the longheld
dream of delivering IT as a Utility. Even though utility computing is in its nascent stage today, the
proponents of utility computing envisage that it will become a commodity business in the upcoming time
and utility service providers will meet all the IT requests of the companies. This paper takes a crosssectional
view at the emergence of utility computing along with different requirements needed to realize
utility model. It also surveys the current trends in utility computing highlighting diverse architecture
models aligned towards delivering IT as a utility. Different resource management systems for proficient
allocation of resources have been listed together with various resource scheduling and pricing strategies
used by them. Further, a review of generic key perspectives closely related to the concept of delivering IT
as a Utility has been taken citing the contenders for the future enhancements in this technology in the form
of Grid and Cloud Computing.
Contributors to Reduce Maintainability Cost at the Software Implementation PhaseWaqas Tariq
This document discusses factors that can reduce software maintenance costs during the implementation phase. It identifies that maintenance costs are highest during software development phases. The objective is to define criteria to assess software quality characteristics and assist during implementation. This will help reduce maintenance costs by creating criteria groups to support writing standard code, developing a model to apply criteria, and increasing understandability. Student groups will study code standardization, write programs, and test software maintenance on programs to validate the model and proposed criteria.
Multi-Dimensional Framework in Public Transport PlanningSharu Gangadhar
This document proposes a three-layer model for a multi-dimensional evaluation framework to measure public transit service performance. The framework uses both subjective and objective measures, allowing input from stakeholders. It is built on a three-tier architecture for flexibility, a good user interface, and resistance to change. The three tiers are the system level, route level, and data storage level. The framework evaluates performance at different levels of detail using criteria, indicators, and a weighting process to reflect importance.
Software size estimation at early stages of project development holds great significance to meet
the competitive demands of software industry. Software size represents one of the most
interesting internal attributes which has been used in several effort/cost models as a predictor
of effort and cost needed to design and implement the software. The whole world is focusing
towards object oriented paradigm thus it is essential to use an accurate methodology for
measuring the size of object oriented projects. The class point approach is used to quantify
classes which are the logical building blocks in object oriented paradigm. In this paper, we
propose a class point based approach for software size estimation of On-Line Analytical
Processing (OLAP) systems. OLAP is an approach to swiftly answer decision support queries
based on multidimensional view of data. Materialized views can significantly reduce the
execution time for decision support queries. We perform a case study based on the TPC-H
benchmark which is a representative of OLAP System. We have used a Greedy based approach
to determine a good set of views to be materialized. After finding the number of views, the class
point approach is used to estimate the size of an OLAP System The results of our approach are
validated.
Software size estimation at early stages of project development holds great significance to meet the competitive demands of software industry. Software size represents one of the most
interesting internal attributes which has been used in several effort/cost models as a predictor of effort and cost needed to design and implement the software. The whole world is focusing
towards object oriented paradigm thus it is essential to use an accurate methodology for measuring the size of object oriented projects. The class point approach is used to quantify classes which are the logical building blocks in object oriented paradigm. In this paper, we propose a class point based approach for software size estimation of On-Line Analytical
Processing (OLAP) systems. OLAP is an approach to swiftly answer decision support queries based on multidimensional view of data. Materialized views can significantly reduce the
execution time for decision support queries. We perform a case study based on the TPC-H benchmark which is a representative of OLAP System. We have used a Greedy based approach
to determine a good set of views to be materialized. After finding the number of views, the class point approach is used to estimate the size of an OLAP System The results of our approach are validated.
OPTIMIZATION APPROACHES IN OPTIMAL INTEGRATED CONTROL, COMPUTATION AND COMMUN...ijctcm
This paper studies the existing approaches in optimal integrated control, computation and communication
problems. It concentrates on joint optimization problems aimed at finding communication/computation
policy and control signal. Different aspects including computational complexity, convexity, proposed
methods to find optimum and other issues related to control performance are studied and compared for different approaches.
The document is a request for fully solved SMU MBA assignments from Spring 2014. It provides contact information for students to send their semester and specialization to obtain the assignments. It notes that sample assignments can be found in blog archives or by searching. The document then provides several MBA assignments related to software engineering, database management systems, computer networks, and other topics. Students are to answer the questions and provide explanations and examples.
SOA-A GENERIC APPROACH FOR INTEGRATING LOOSELY COUPLED SYSTEMS WITH OTHER SYS...ijwscjournal
Various organizations generate data in various domains which is queried and analyzed by users. This limits the possibility of database integration with other systems. We describes a generalized approach comprising a loosely couples system and integrate with other system. It deals with the setting up the environment for implementing the system. User Interface screen shows how the user will interact with the system and the data
entry forms required to gather data for the system.
SOA-A GENERIC APPROACH FOR INTEGRATING LOOSELY COUPLED SYSTEMS WITH OTHER SYS...ijwscjournal
The document discusses integrating loosely coupled systems using a service-oriented architecture (SOA) approach. It proposes a generalized model to integrate various data sources related to a student admission process. The model uses SOA and web services to integrate student application, merit list generation, admission, and banking modules without changing their underlying business logic. This allows retrieving a student's application status, checking if they are on the merit list, assessing financial status, and recommending an education loan from compared banking options if needed. The integrated system provides a single interface to get information previously spread across different platforms and applications.
This document presents a taxonomy for selecting recommender systems based on problem characteristics. It outlines six dimensions for characterizing recommendation problems: problem structure, domain, user relationship, user input, background knowledge, and recommendation output. It also describes three dimensions of recommender technologies: algorithms, user interaction models, and user profiling approaches. The taxonomy can help researchers and developers select the most appropriate recommender system technology by mapping the problem characteristics to the underlying technologies.
The IT-GRC platform is a solution that is based on
the paradigm of distributed systems, based on multi-agent systems
(MAS) in its different parts namely the user interface, the static
and dynamic configuration of the organization management
profiles, the choice of the best repository and the processing of
processes, it takes advantage of the autonomy and learning aspect
of ADMs as well as their high-level communication and
coordination. However, these technological components are
difficult to manipulate, or users lack the necessary skills to use
them correctly. In this situation, the modeling of a communication
architecture is necessary, in order to adapt the functionalities of
the platform to the needs of the users. To help achieve these goals,
it is necessary to develop a functional and intelligent
communication architecture, adaptable and able to provide a
support framework, allowing access to system functionalities
regardless of physical and time constraints.
This document describes the development of a web-based job fair information system using the waterfall model of software development. The system allows users to access information on job vacancies, registration for vacancies, and test schedules. It was developed using requirements collection, specification and design, implementation, and testing phases of the waterfall model. The system provides information to both job seekers and administrators. For job seekers, it allows viewing of information and online registration for vacancies. Administrators can manage all data and information on the system. The system was tested on different browsers and needs further improvement for use on mobile devices.
Presenting an Excusable Model of Enterprise Architecture for Evaluation of R...Editor IJCATR
The document presents a method for creating an executable model of enterprise architecture diagrams to evaluate reliability. It transforms UML collaboration diagrams into colored Petri nets using an algorithm. This allows simulation of the diagrams to identify potential reliability issues early in the planning process. It aims to avoid high costs of implementation by improving architectural artifacts. The key steps are:
1) Using C4ISR framework and UML diagrams to describe enterprise architecture.
2) Transforming collaboration diagrams to colored Petri nets using a algorithm that represents messages as transitions and senders/receivers as places.
3) Annotating the Petri net model with reliability data to enable simulation and evaluation of reliability.
The document provides an overview of the topics covered in a systems analysis and design course, including software used, information system components, analyzing the business case, managing projects, requirements modeling, data modeling, object modeling, development strategies, output and interface design, data design, and system architecture. Key concepts discussed include SWOT analysis, business cases, feasibility studies, project management techniques, UML, data flow diagrams, use cases, object-oriented analysis, cost-benefit analysis methods, user interface design, data structure, normalization, and entity relationship diagrams.
Services Modeling based on SOA and BPM for Information System Flexibility Imp...IJECEIAES
The lack of identify services mechanism which is related to the development of information systems could be impact in wasting time, over budget and can not adapt to the changing environment. This phenomenon is happened by the belief that lack of capturing user requirement. This is due to consider the business environment is always running normally. In fact, the development of the system needs a way to anticipate the business environment that unpredictable changes.Therefore, the phenomenon on the need for modeling services can able to respond to the changing needs of users still have a chancein this study. It explores modeling services to synergize SOA and BPM.Several previous studies generally use a business driven approach, technical partially driven to develop the service modeling. This leads to the question of how a service should be modeled so that it can be applied in different contexts and business processes also. It is support user needs in diversity and heterogeneous system environments. This Conditions occurs in corporate university. The case studies in this research is a Learning Management System (LMS) in Academic Enterprise System (EAS). The research stages are: (1) Analysis of Synergy in SOA and BPM, (2) Analysis of User Experience in LMS Academic Enterprise System (L-EAS), (3) Analysis of Modeling Framework, (4) Proposed Framework that aligning SOA and BPM. The result of this study is proposed system framework based on services to increase the flexibility of information systems at LMS Academic Enterprise System (L-EAS).
General Methodology for developing UML models from UI ijwscjournal
In recent past every discipline and every industry have their own methods of developing products. It may be software development, mechanics, construction, psychology and so on. These demarcations work fine as long as the requirements are within one discipline. However, if the project extends over several disciplines, interfaces have to be created and coordinated between the methods of these disciplines.
Performance is an important quality aspect of Web Services because of their distributed nature. Predicting the performance of web services during early stages of software development is significant. In Industry, Prototype of these applications is developed during analysis phase of Software Development Life
Cycle (SDLC). However, Performance models are generated from UML models. Methodologies for predicting the performance from UML models is available. Hence, In this paper, a methodology for developing Use Case model and Activity model from User Interface is presented. The methodology is illustrated with a case study on Amazon.com.
Algorithm ExampleFor the following taskUse the random module .docxdaniahendric
Algorithm Example
For the following task:
Use the random module to write a number guessing game.
The number the computer chooses should change each time you run the program.
Repeatedly ask the user for a number. If the number is different from the computer's let the user know if they guessed too high or too low. If the number matches the computer's, the user wins.
Keep track of the number of tries it takes the user to guess it.
An appropriate algorithm might be:
Import the random module
Display a welcome message to the user
Choose a random number between 1 and 100
Get a guess from the user
Set a number of tries to 0
As long as their guess isn’t the number
Check if guess is lower than computer
If so, print a lower message.
Otherwise, is it higher?
If so, print a higher message.
Get another guess
Increment the tries
Repeat
When they guess the computer's number, display the number and their tries count
Notice that each line in the algorithm corresponds to roughly a line of code in Python, but there is no coding itself in the algorithm. Rather the algorithm lays out what needs to happen step by step to achieve the program.
Software Quality Metrics for Object-Oriented Environments
AUTHORS:
Dr. Linda H. Rosenberg Lawrence E. Hyatt
Unisys Government Systems Software Assurance Technology Center
Goddard Space Flight Center Goddard Space Flight Center
Bld 6 Code 300.1 Bld 6 Code 302
Greenbelt, MD 20771 USA Greenbelt, MD 20771 USA
I. INTRODUCTION
Object-oriented design and development are popular concepts in today’s software development
environment. They are often heralded as the silver bullet for solving software problems. While
in reality there is no silver bullet, object-oriented development has proved its value for systems
that must be maintained and modified. Object-oriented software development requires a
different approach from more traditional functional decomposition and data flow development
methods. This includes the software metrics used to evaluate object-oriented software.
The concepts of software metrics are well established, and many metrics relating to product
quality have been developed and used. With object-oriented analysis and design methodologies
gaining popularity, it is time to start investigating object-oriented metrics with respect to
software quality. We are interested in the answer to the following questions:
• What concepts and structures in object-oriented design affect the quality of the
software?
• Can traditional metrics measure the critical object-oriented structures?
• If so, are the threshold values for the metrics the same for object-oriented designs as for
functional/data designs?
• Which of the many new metrics found in the literature are useful to measure the critical
concepts of object-oriented structures?
II. METRIC EVALUATION CRITERIA
While metrics for the traditional functional decomposition and data analysis design appro ...
Designing Financial Information System Using Structured System Analysis and D...ijcnac
In the following research, the financial information system for the studied company
which had various sub-systems of accounting, payment, storage, properties, salary and
wages systems were analyzed properties system is developed as one of the sub-systems
subsequent to sub-systems problems identification. In both stages of analysis and
designing, Structured System Analysis and Design Method methodology, which has a
Top-Down approach, is used. Based on the studied methodology in analysis stage, system
requirements including needs (determined through studying present system problems)
and obligations (determined by the designer and according to experiences obtained from
similar systems) were identified and considering such requirements, the proper
information system concept model was designed. Some suggestions are represented for
organizations use and information systems development fans, in the final part to the
article.
The document discusses metrics for measuring IT service management. It introduces the concept of a "metrics tree" which aggregates different levels of metrics to provide a comprehensive picture of service quality. The metrics tree considers component, process, and service-level metrics to measure an organization's capability as a service provider. A key point is that effective organizations know their capabilities, processes, and overall service quality through aggregating different levels of metrics.
This document proposes a methodology for evaluating statistical classification models for churn prediction using a composite indicator. It considers factors beyond just accuracy, like robustness, speed, interpretability and ease of use. The methodology will be tested on classification models applied to real customer data from a Spanish retail company. It also analyzes the impact of different variable selection methods on model performance.
The peer-reviewed International Journal of Engineering Inventions (IJEI) is started with a mission to encourage contribution to research in Science and Technology. Encourage and motivate researchers in challenging areas of Sciences and Technology.
Information systems planning using a synthesis of modelling techniquesTony Toole
The document discusses using three modeling techniques - Enterprise Architecture, Viable Systems, and Soft Systems modeling - to plan improvements to a university's student information management system. It provides examples of "as is" models created for several processes using Enterprise Architecture modeling to identify issues. Viable Systems modeling examines communications and control, identifying bottlenecks. A synthesis of the techniques aims to design practical, achievable solutions for the "to be" system that recognize human factors. The modeling approaches collectively provide a richer picture than any single technique alone.
Information systems planning using a synthesis of modelling techniquesTony Toole
This document discusses using three modeling techniques - Enterprise Architecture, Viable Systems, and Soft Systems - to plan improvements to a university's student information management system. It provides an overview of each technique and examples of Enterprise Architecture models created for the existing system. The models identify issues like inconsistent processes for student attendance monitoring. The modeling aims to develop a richer understanding of the system to design a more effective "to-be" system that addresses identified problems and inefficiencies.
This chapter discusses the importance of performance measurement in supply chains. It explains that establishing metrics allows companies to understand how they are performing and identify areas for improvement. Good metrics should be consistent with company strategies and focus on customer needs. The chapter provides examples of different types of metrics companies can use to measure costs, inventory levels, customer service, and overall supply chain performance. These metrics can be classified in various categories and should be integrated both within and across companies to effectively drive improvement.
Multi-Dimensional Framework in Public Transport PlanningSharu Gangadhar
This document proposes a three-layer model for a multi-dimensional evaluation framework to measure public transit service performance. The framework uses both subjective and objective measures, allowing input from stakeholders. It is built on a three-tier architecture for flexibility, a good user interface, and resistance to change. The three tiers are the system level, route level, and data storage level. The framework evaluates performance at different levels of detail using criteria, indicators, and a weighting process to reflect importance.
Software size estimation at early stages of project development holds great significance to meet
the competitive demands of software industry. Software size represents one of the most
interesting internal attributes which has been used in several effort/cost models as a predictor
of effort and cost needed to design and implement the software. The whole world is focusing
towards object oriented paradigm thus it is essential to use an accurate methodology for
measuring the size of object oriented projects. The class point approach is used to quantify
classes which are the logical building blocks in object oriented paradigm. In this paper, we
propose a class point based approach for software size estimation of On-Line Analytical
Processing (OLAP) systems. OLAP is an approach to swiftly answer decision support queries
based on multidimensional view of data. Materialized views can significantly reduce the
execution time for decision support queries. We perform a case study based on the TPC-H
benchmark which is a representative of OLAP System. We have used a Greedy based approach
to determine a good set of views to be materialized. After finding the number of views, the class
point approach is used to estimate the size of an OLAP System The results of our approach are
validated.
Software size estimation at early stages of project development holds great significance to meet the competitive demands of software industry. Software size represents one of the most
interesting internal attributes which has been used in several effort/cost models as a predictor of effort and cost needed to design and implement the software. The whole world is focusing
towards object oriented paradigm thus it is essential to use an accurate methodology for measuring the size of object oriented projects. The class point approach is used to quantify classes which are the logical building blocks in object oriented paradigm. In this paper, we propose a class point based approach for software size estimation of On-Line Analytical
Processing (OLAP) systems. OLAP is an approach to swiftly answer decision support queries based on multidimensional view of data. Materialized views can significantly reduce the
execution time for decision support queries. We perform a case study based on the TPC-H benchmark which is a representative of OLAP System. We have used a Greedy based approach
to determine a good set of views to be materialized. After finding the number of views, the class point approach is used to estimate the size of an OLAP System The results of our approach are validated.
OPTIMIZATION APPROACHES IN OPTIMAL INTEGRATED CONTROL, COMPUTATION AND COMMUN...ijctcm
This paper studies the existing approaches in optimal integrated control, computation and communication
problems. It concentrates on joint optimization problems aimed at finding communication/computation
policy and control signal. Different aspects including computational complexity, convexity, proposed
methods to find optimum and other issues related to control performance are studied and compared for different approaches.
The document is a request for fully solved SMU MBA assignments from Spring 2014. It provides contact information for students to send their semester and specialization to obtain the assignments. It notes that sample assignments can be found in blog archives or by searching. The document then provides several MBA assignments related to software engineering, database management systems, computer networks, and other topics. Students are to answer the questions and provide explanations and examples.
SOA-A GENERIC APPROACH FOR INTEGRATING LOOSELY COUPLED SYSTEMS WITH OTHER SYS...ijwscjournal
Various organizations generate data in various domains which is queried and analyzed by users. This limits the possibility of database integration with other systems. We describes a generalized approach comprising a loosely couples system and integrate with other system. It deals with the setting up the environment for implementing the system. User Interface screen shows how the user will interact with the system and the data
entry forms required to gather data for the system.
SOA-A GENERIC APPROACH FOR INTEGRATING LOOSELY COUPLED SYSTEMS WITH OTHER SYS...ijwscjournal
The document discusses integrating loosely coupled systems using a service-oriented architecture (SOA) approach. It proposes a generalized model to integrate various data sources related to a student admission process. The model uses SOA and web services to integrate student application, merit list generation, admission, and banking modules without changing their underlying business logic. This allows retrieving a student's application status, checking if they are on the merit list, assessing financial status, and recommending an education loan from compared banking options if needed. The integrated system provides a single interface to get information previously spread across different platforms and applications.
This document presents a taxonomy for selecting recommender systems based on problem characteristics. It outlines six dimensions for characterizing recommendation problems: problem structure, domain, user relationship, user input, background knowledge, and recommendation output. It also describes three dimensions of recommender technologies: algorithms, user interaction models, and user profiling approaches. The taxonomy can help researchers and developers select the most appropriate recommender system technology by mapping the problem characteristics to the underlying technologies.
The IT-GRC platform is a solution that is based on
the paradigm of distributed systems, based on multi-agent systems
(MAS) in its different parts namely the user interface, the static
and dynamic configuration of the organization management
profiles, the choice of the best repository and the processing of
processes, it takes advantage of the autonomy and learning aspect
of ADMs as well as their high-level communication and
coordination. However, these technological components are
difficult to manipulate, or users lack the necessary skills to use
them correctly. In this situation, the modeling of a communication
architecture is necessary, in order to adapt the functionalities of
the platform to the needs of the users. To help achieve these goals,
it is necessary to develop a functional and intelligent
communication architecture, adaptable and able to provide a
support framework, allowing access to system functionalities
regardless of physical and time constraints.
This document describes the development of a web-based job fair information system using the waterfall model of software development. The system allows users to access information on job vacancies, registration for vacancies, and test schedules. It was developed using requirements collection, specification and design, implementation, and testing phases of the waterfall model. The system provides information to both job seekers and administrators. For job seekers, it allows viewing of information and online registration for vacancies. Administrators can manage all data and information on the system. The system was tested on different browsers and needs further improvement for use on mobile devices.
Presenting an Excusable Model of Enterprise Architecture for Evaluation of R...Editor IJCATR
The document presents a method for creating an executable model of enterprise architecture diagrams to evaluate reliability. It transforms UML collaboration diagrams into colored Petri nets using an algorithm. This allows simulation of the diagrams to identify potential reliability issues early in the planning process. It aims to avoid high costs of implementation by improving architectural artifacts. The key steps are:
1) Using C4ISR framework and UML diagrams to describe enterprise architecture.
2) Transforming collaboration diagrams to colored Petri nets using a algorithm that represents messages as transitions and senders/receivers as places.
3) Annotating the Petri net model with reliability data to enable simulation and evaluation of reliability.
The document provides an overview of the topics covered in a systems analysis and design course, including software used, information system components, analyzing the business case, managing projects, requirements modeling, data modeling, object modeling, development strategies, output and interface design, data design, and system architecture. Key concepts discussed include SWOT analysis, business cases, feasibility studies, project management techniques, UML, data flow diagrams, use cases, object-oriented analysis, cost-benefit analysis methods, user interface design, data structure, normalization, and entity relationship diagrams.
Services Modeling based on SOA and BPM for Information System Flexibility Imp...IJECEIAES
The lack of identify services mechanism which is related to the development of information systems could be impact in wasting time, over budget and can not adapt to the changing environment. This phenomenon is happened by the belief that lack of capturing user requirement. This is due to consider the business environment is always running normally. In fact, the development of the system needs a way to anticipate the business environment that unpredictable changes.Therefore, the phenomenon on the need for modeling services can able to respond to the changing needs of users still have a chancein this study. It explores modeling services to synergize SOA and BPM.Several previous studies generally use a business driven approach, technical partially driven to develop the service modeling. This leads to the question of how a service should be modeled so that it can be applied in different contexts and business processes also. It is support user needs in diversity and heterogeneous system environments. This Conditions occurs in corporate university. The case studies in this research is a Learning Management System (LMS) in Academic Enterprise System (EAS). The research stages are: (1) Analysis of Synergy in SOA and BPM, (2) Analysis of User Experience in LMS Academic Enterprise System (L-EAS), (3) Analysis of Modeling Framework, (4) Proposed Framework that aligning SOA and BPM. The result of this study is proposed system framework based on services to increase the flexibility of information systems at LMS Academic Enterprise System (L-EAS).
General Methodology for developing UML models from UI ijwscjournal
In recent past every discipline and every industry have their own methods of developing products. It may be software development, mechanics, construction, psychology and so on. These demarcations work fine as long as the requirements are within one discipline. However, if the project extends over several disciplines, interfaces have to be created and coordinated between the methods of these disciplines.
Performance is an important quality aspect of Web Services because of their distributed nature. Predicting the performance of web services during early stages of software development is significant. In Industry, Prototype of these applications is developed during analysis phase of Software Development Life
Cycle (SDLC). However, Performance models are generated from UML models. Methodologies for predicting the performance from UML models is available. Hence, In this paper, a methodology for developing Use Case model and Activity model from User Interface is presented. The methodology is illustrated with a case study on Amazon.com.
Algorithm ExampleFor the following taskUse the random module .docxdaniahendric
Algorithm Example
For the following task:
Use the random module to write a number guessing game.
The number the computer chooses should change each time you run the program.
Repeatedly ask the user for a number. If the number is different from the computer's let the user know if they guessed too high or too low. If the number matches the computer's, the user wins.
Keep track of the number of tries it takes the user to guess it.
An appropriate algorithm might be:
Import the random module
Display a welcome message to the user
Choose a random number between 1 and 100
Get a guess from the user
Set a number of tries to 0
As long as their guess isn’t the number
Check if guess is lower than computer
If so, print a lower message.
Otherwise, is it higher?
If so, print a higher message.
Get another guess
Increment the tries
Repeat
When they guess the computer's number, display the number and their tries count
Notice that each line in the algorithm corresponds to roughly a line of code in Python, but there is no coding itself in the algorithm. Rather the algorithm lays out what needs to happen step by step to achieve the program.
Software Quality Metrics for Object-Oriented Environments
AUTHORS:
Dr. Linda H. Rosenberg Lawrence E. Hyatt
Unisys Government Systems Software Assurance Technology Center
Goddard Space Flight Center Goddard Space Flight Center
Bld 6 Code 300.1 Bld 6 Code 302
Greenbelt, MD 20771 USA Greenbelt, MD 20771 USA
I. INTRODUCTION
Object-oriented design and development are popular concepts in today’s software development
environment. They are often heralded as the silver bullet for solving software problems. While
in reality there is no silver bullet, object-oriented development has proved its value for systems
that must be maintained and modified. Object-oriented software development requires a
different approach from more traditional functional decomposition and data flow development
methods. This includes the software metrics used to evaluate object-oriented software.
The concepts of software metrics are well established, and many metrics relating to product
quality have been developed and used. With object-oriented analysis and design methodologies
gaining popularity, it is time to start investigating object-oriented metrics with respect to
software quality. We are interested in the answer to the following questions:
• What concepts and structures in object-oriented design affect the quality of the
software?
• Can traditional metrics measure the critical object-oriented structures?
• If so, are the threshold values for the metrics the same for object-oriented designs as for
functional/data designs?
• Which of the many new metrics found in the literature are useful to measure the critical
concepts of object-oriented structures?
II. METRIC EVALUATION CRITERIA
While metrics for the traditional functional decomposition and data analysis design appro ...
Designing Financial Information System Using Structured System Analysis and D...ijcnac
In the following research, the financial information system for the studied company
which had various sub-systems of accounting, payment, storage, properties, salary and
wages systems were analyzed properties system is developed as one of the sub-systems
subsequent to sub-systems problems identification. In both stages of analysis and
designing, Structured System Analysis and Design Method methodology, which has a
Top-Down approach, is used. Based on the studied methodology in analysis stage, system
requirements including needs (determined through studying present system problems)
and obligations (determined by the designer and according to experiences obtained from
similar systems) were identified and considering such requirements, the proper
information system concept model was designed. Some suggestions are represented for
organizations use and information systems development fans, in the final part to the
article.
The document discusses metrics for measuring IT service management. It introduces the concept of a "metrics tree" which aggregates different levels of metrics to provide a comprehensive picture of service quality. The metrics tree considers component, process, and service-level metrics to measure an organization's capability as a service provider. A key point is that effective organizations know their capabilities, processes, and overall service quality through aggregating different levels of metrics.
This document proposes a methodology for evaluating statistical classification models for churn prediction using a composite indicator. It considers factors beyond just accuracy, like robustness, speed, interpretability and ease of use. The methodology will be tested on classification models applied to real customer data from a Spanish retail company. It also analyzes the impact of different variable selection methods on model performance.
The peer-reviewed International Journal of Engineering Inventions (IJEI) is started with a mission to encourage contribution to research in Science and Technology. Encourage and motivate researchers in challenging areas of Sciences and Technology.
Information systems planning using a synthesis of modelling techniquesTony Toole
The document discusses using three modeling techniques - Enterprise Architecture, Viable Systems, and Soft Systems modeling - to plan improvements to a university's student information management system. It provides examples of "as is" models created for several processes using Enterprise Architecture modeling to identify issues. Viable Systems modeling examines communications and control, identifying bottlenecks. A synthesis of the techniques aims to design practical, achievable solutions for the "to be" system that recognize human factors. The modeling approaches collectively provide a richer picture than any single technique alone.
Information systems planning using a synthesis of modelling techniquesTony Toole
This document discusses using three modeling techniques - Enterprise Architecture, Viable Systems, and Soft Systems - to plan improvements to a university's student information management system. It provides an overview of each technique and examples of Enterprise Architecture models created for the existing system. The models identify issues like inconsistent processes for student attendance monitoring. The modeling aims to develop a richer understanding of the system to design a more effective "to-be" system that addresses identified problems and inefficiencies.
This chapter discusses the importance of performance measurement in supply chains. It explains that establishing metrics allows companies to understand how they are performing and identify areas for improvement. Good metrics should be consistent with company strategies and focus on customer needs. The chapter provides examples of different types of metrics companies can use to measure costs, inventory levels, customer service, and overall supply chain performance. These metrics can be classified in various categories and should be integrated both within and across companies to effectively drive improvement.
This chapter discusses the importance of performance measurement in supply chains. It explains that establishing metrics allows companies to understand how they are performing and identify areas for improvement. Good metrics should be consistent with company strategies and focus on customer needs. The chapter provides examples of different types of metrics companies can use to measure costs, inventory levels, customer service, and overall supply chain performance. These metrics can be classified in various categories and should be integrated both within and across companies to effectively drive improvement.
Decision Making Framework in e-Business Cloud Environment Using Software Metr...ijitjournal
Cloud computing technology is most important one in IT industry by enabling them to offer access to their
system and application services on payment type. As a result, more than a few enterprises with Facebook,
Microsoft, Google, and amazon have started offer to their clients. Quality software is most important one in
market competition in this paper presents a hybrid framework based on the goal/question/metric paradigm
to evaluate the quality and effectiveness of previous software goods in project, product and organizations
in a cloud computing environment. In our approach it support decision making in the area of project,
product and organization levels using Neural networks and three angular metrics i.e., project metrics,
product metrics, and organization metrics
IJERD (www.ijerd.com) International Journal of Engineering Research and Devel...IJERD Editor
This document summarizes a study that aimed to identify value co-creation attributes that influence the UTM Institutional Repository (UTM IR), an e-service application. The study used interviews with UTM IR providers and users to collect data on the e-service based on the DART model of value co-creation. The DART model examines dialogue, access, risk, and transparency between customers and providers. Interview responses were coded according to the DART building blocks. A gap analysis of the coded provider and user responses identified attributes influencing the UTM IR from a value co-creation perspective. The findings aimed to help evaluate the UTM IR e-service based on customer and provider value co-creation.
Design and Evaluation of Information Systems and Services: principles of designing information systems, strategies for Information system evaluation, Information Systems Effectiveness Measures.
An Empirical Evaluation of Capability Modelling using Design Rationale.pdfSarah Pollard
This study evaluated a capability modeling meta-model by having two designers independently model capabilities for the same use case. The designers' modeling processes and rationales were documented using a design reasoning framework. Analysis found differences in how the designers defined key concepts like capability and context, and in their modeling processes due to lack of guidance from the meta-model. The study provided feedback on improving the meta-model and capability-driven design methodology.
Size and Time Estimation in Goal Graph Using Use Case Points (UCP): A SurveyIJERA Editor
In order to achieve ideal status and meet demands of stakeholders, each organization should follow their vision and long term plan. Goals and strategies are two fundamental basis in vision and mission. Goals identify framework of organization where processes, rules and resources are designed. Goals are modelled based on a graph structure by means of extraction, classification and determining requirements and their relations and in form of graph. Goal graph shows goals which should be satisfied in order to guarantee right route of organization. On the other hand, these goals can be called as predefined sub projects which business management unit should consider and analyse them. If we know approximate size and time of each part, we will design better management plans resulting in more prosperity and less fail. This paper studies how use case points method is used in calculating size and time in goal graph.
A software system continues to grow in size and complexity, it becomes increasing difficult to
understand and manage. Software metrics are units of software measurement. As improvement in coding tools
allow software developer to produce larger amount of software to meet ever expanding requirements. A method
to measure software product, process and project must be used. In this article, we first introduce the software
metrics including the definition of metrics and the history of this field. We aim at a comprehensive survey of the
metrics available for measuring attributes related to software entities. Some classical metrics such as Lines of
codes LOC, Halstead complexity metric (HCM), Function Point analysis and others are discussed and
analyzed. Then we bring up the complexity metrics methods, such as McCabe complexity metrics and object
oriented metrics(C&K method), with real world examples. The comparison and relationship of these metrics are
also presented.
Applying systemic methodologies to bridge the gap between a process-oriented ...Panagiotis Papaioannou
This work is an application of the Soft Systems Methodology (SSM) to improve an information system to fully support the related process-based management system and help its internal improvement. Design and Control Systemic Methodology (DCSYM) is used as a modelling tool to facilitate conceptual models comparison within the SSM context.
The document discusses using a three-phase modeling approach to plan improvements to a university's student information management system. The phases included: 1) evaluating the existing "as is" system, 2) analyzing it to identify areas for improvement and design a proposed "to be" system, and 3) adding real-world considerations to create practical solutions. A case study on improving an inconsistent student attendance monitoring system demonstrated applying the modeling techniques. The modeling led to the conclusion that sub-systems for different functional areas were needed, but core data sharing between them was important for effective management.
This document discusses tools and techniques for evaluating risks to IT assets and prioritizing risk mitigation efforts. It proposes integrating various applications that contain relevant asset data, such as inventory, procurement and project management systems, to automatically value assets and services. This would help risk managers understand the potential costs of vulnerabilities and quantify risks to prioritize remediation activities based on solid metrics. The document emphasizes using all aspects of the Common Vulnerability Scoring System (base, temporal and environmental scores) to accurately assess vulnerability risk levels for an organization.
Towards Benchmarking User Stories Estimation with COSMIC Function Points-A Ca...IJECEIAES
The document summarizes research on linking user story estimation in Agile/DevOps projects to the COSMIC functional size measurement method. It discusses related work benchmarking user stories with COSMIC function points. A survey found practitioners commonly use WBS and lines of code over parametric estimation. Case studies showed COSMIC estimation was within -4% to 14% of actual effort for 9 industry projects. The document also presents mappings of user stories to COSMIC functional processes for 2 case studies.
LEAN LEVEL OF AN ORGANIZATION ASSESSED BASED ON FUZZY LOGIC csandit
To determine the lean level of an organization a methodology was developed. It was based on a
qualitative assessment approach, including quantitative basis, whose development was
supported using fuzzy logic. Recourse to the use of fuzzy logic is justified by its ability to cope
with uncertainty and imprecision on the input data, as well as, could be applied to the analysis
of qualitative variables of a system, turning them into quantitative values. A major advantage of
the developed approach is that it can be adjusted to any organization regardless of their nature,
size, strategy and market positioning. Furthermore, the proposed methodology allows the
systematically identification of constraint factors existing in an organization and, thus, provide
the necessary information to the manager to develop a holistic plan for continuous
improvement. To assess the robustness of the proposed approach, the methodology was applied
to a maintenance and manufacturing aeronautical organization.
Semelhante a KM System Evaluation using Four dimensional Metric Model, Database and RESTful Resources (20)
Embedded machine learning-based road conditions and driving behavior monitoringIJECEIAES
Car accident rates have increased in recent years, resulting in losses in human lives, properties, and other financial costs. An embedded machine learning-based system is developed to address this critical issue. The system can monitor road conditions, detect driving patterns, and identify aggressive driving behaviors. The system is based on neural networks trained on a comprehensive dataset of driving events, driving styles, and road conditions. The system effectively detects potential risks and helps mitigate the frequency and impact of accidents. The primary goal is to ensure the safety of drivers and vehicles. Collecting data involved gathering information on three key road events: normal street and normal drive, speed bumps, circular yellow speed bumps, and three aggressive driving actions: sudden start, sudden stop, and sudden entry. The gathered data is processed and analyzed using a machine learning system designed for limited power and memory devices. The developed system resulted in 91.9% accuracy, 93.6% precision, and 92% recall. The achieved inference time on an Arduino Nano 33 BLE Sense with a 32-bit CPU running at 64 MHz is 34 ms and requires 2.6 kB peak RAM and 139.9 kB program flash memory, making it suitable for resource-constrained embedded systems.
TIME DIVISION MULTIPLEXING TECHNIQUE FOR COMMUNICATION SYSTEMHODECEDSIET
Time Division Multiplexing (TDM) is a method of transmitting multiple signals over a single communication channel by dividing the signal into many segments, each having a very short duration of time. These time slots are then allocated to different data streams, allowing multiple signals to share the same transmission medium efficiently. TDM is widely used in telecommunications and data communication systems.
### How TDM Works
1. **Time Slots Allocation**: The core principle of TDM is to assign distinct time slots to each signal. During each time slot, the respective signal is transmitted, and then the process repeats cyclically. For example, if there are four signals to be transmitted, the TDM cycle will divide time into four slots, each assigned to one signal.
2. **Synchronization**: Synchronization is crucial in TDM systems to ensure that the signals are correctly aligned with their respective time slots. Both the transmitter and receiver must be synchronized to avoid any overlap or loss of data. This synchronization is typically maintained by a clock signal that ensures time slots are accurately aligned.
3. **Frame Structure**: TDM data is organized into frames, where each frame consists of a set of time slots. Each frame is repeated at regular intervals, ensuring continuous transmission of data streams. The frame structure helps in managing the data streams and maintaining the synchronization between the transmitter and receiver.
4. **Multiplexer and Demultiplexer**: At the transmitting end, a multiplexer combines multiple input signals into a single composite signal by assigning each signal to a specific time slot. At the receiving end, a demultiplexer separates the composite signal back into individual signals based on their respective time slots.
### Types of TDM
1. **Synchronous TDM**: In synchronous TDM, time slots are pre-assigned to each signal, regardless of whether the signal has data to transmit or not. This can lead to inefficiencies if some time slots remain empty due to the absence of data.
2. **Asynchronous TDM (or Statistical TDM)**: Asynchronous TDM addresses the inefficiencies of synchronous TDM by allocating time slots dynamically based on the presence of data. Time slots are assigned only when there is data to transmit, which optimizes the use of the communication channel.
### Applications of TDM
- **Telecommunications**: TDM is extensively used in telecommunication systems, such as in T1 and E1 lines, where multiple telephone calls are transmitted over a single line by assigning each call to a specific time slot.
- **Digital Audio and Video Broadcasting**: TDM is used in broadcasting systems to transmit multiple audio or video streams over a single channel, ensuring efficient use of bandwidth.
- **Computer Networks**: TDM is used in network protocols and systems to manage the transmission of data from multiple sources over a single network medium.
### Advantages of TDM
- **Efficient Use of Bandwidth**: TDM all
CHINA’S GEO-ECONOMIC OUTREACH IN CENTRAL ASIAN COUNTRIES AND FUTURE PROSPECTjpsjournal1
The rivalry between prominent international actors for dominance over Central Asia's hydrocarbon
reserves and the ancient silk trade route, along with China's diplomatic endeavours in the area, has been
referred to as the "New Great Game." This research centres on the power struggle, considering
geopolitical, geostrategic, and geoeconomic variables. Topics including trade, political hegemony, oil
politics, and conventional and nontraditional security are all explored and explained by the researcher.
Using Mackinder's Heartland, Spykman Rimland, and Hegemonic Stability theories, examines China's role
in Central Asia. This study adheres to the empirical epistemological method and has taken care of
objectivity. This study analyze primary and secondary research documents critically to elaborate role of
china’s geo economic outreach in central Asian countries and its future prospect. China is thriving in trade,
pipeline politics, and winning states, according to this study, thanks to important instruments like the
Shanghai Cooperation Organisation and the Belt and Road Economic Initiative. According to this study,
China is seeing significant success in commerce, pipeline politics, and gaining influence on other
governments. This success may be attributed to the effective utilisation of key tools such as the Shanghai
Cooperation Organisation and the Belt and Road Economic Initiative.
Introduction- e - waste – definition - sources of e-waste– hazardous substances in e-waste - effects of e-waste on environment and human health- need for e-waste management– e-waste handling rules - waste minimization techniques for managing e-waste – recycling of e-waste - disposal treatment methods of e- waste – mechanism of extraction of precious metal from leaching solution-global Scenario of E-waste – E-waste in India- case studies.
Electric vehicle and photovoltaic advanced roles in enhancing the financial p...IJECEIAES
Climate change's impact on the planet forced the United Nations and governments to promote green energies and electric transportation. The deployments of photovoltaic (PV) and electric vehicle (EV) systems gained stronger momentum due to their numerous advantages over fossil fuel types. The advantages go beyond sustainability to reach financial support and stability. The work in this paper introduces the hybrid system between PV and EV to support industrial and commercial plants. This paper covers the theoretical framework of the proposed hybrid system including the required equation to complete the cost analysis when PV and EV are present. In addition, the proposed design diagram which sets the priorities and requirements of the system is presented. The proposed approach allows setup to advance their power stability, especially during power outages. The presented information supports researchers and plant owners to complete the necessary analysis while promoting the deployment of clean energy. The result of a case study that represents a dairy milk farmer supports the theoretical works and highlights its advanced benefits to existing plants. The short return on investment of the proposed approach supports the paper's novelty approach for the sustainable electrical system. In addition, the proposed system allows for an isolated power setup without the need for a transmission line which enhances the safety of the electrical network
Comparative analysis between traditional aquaponics and reconstructed aquapon...bijceesjournal
The aquaponic system of planting is a method that does not require soil usage. It is a method that only needs water, fish, lava rocks (a substitute for soil), and plants. Aquaponic systems are sustainable and environmentally friendly. Its use not only helps to plant in small spaces but also helps reduce artificial chemical use and minimizes excess water use, as aquaponics consumes 90% less water than soil-based gardening. The study applied a descriptive and experimental design to assess and compare conventional and reconstructed aquaponic methods for reproducing tomatoes. The researchers created an observation checklist to determine the significant factors of the study. The study aims to determine the significant difference between traditional aquaponics and reconstructed aquaponics systems propagating tomatoes in terms of height, weight, girth, and number of fruits. The reconstructed aquaponics system’s higher growth yield results in a much more nourished crop than the traditional aquaponics system. It is superior in its number of fruits, height, weight, and girth measurement. Moreover, the reconstructed aquaponics system is proven to eliminate all the hindrances present in the traditional aquaponics system, which are overcrowding of fish, algae growth, pest problems, contaminated water, and dead fish.
Using recycled concrete aggregates (RCA) for pavements is crucial to achieving sustainability. Implementing RCA for new pavement can minimize carbon footprint, conserve natural resources, reduce harmful emissions, and lower life cycle costs. Compared to natural aggregate (NA), RCA pavement has fewer comprehensive studies and sustainability assessments.
Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapte...University of Maribor
Slides from talk presenting:
Aleš Zamuda: Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapter and Networking.
Presentation at IcETRAN 2024 session:
"Inter-Society Networking Panel GRSS/MTT-S/CIS
Panel Session: Promoting Connection and Cooperation"
IEEE Slovenia GRSS
IEEE Serbia and Montenegro MTT-S
IEEE Slovenia CIS
11TH INTERNATIONAL CONFERENCE ON ELECTRICAL, ELECTRONIC AND COMPUTING ENGINEERING
3-6 June 2024, Niš, Serbia
Understanding Inductive Bias in Machine LearningSUTEJAS
This presentation explores the concept of inductive bias in machine learning. It explains how algorithms come with built-in assumptions and preferences that guide the learning process. You'll learn about the different types of inductive bias and how they can impact the performance and generalizability of machine learning models.
The presentation also covers the positive and negative aspects of inductive bias, along with strategies for mitigating potential drawbacks. We'll explore examples of how bias manifests in algorithms like neural networks and decision trees.
By understanding inductive bias, you can gain valuable insights into how machine learning models work and make informed decisions when building and deploying them.
KM System Evaluation using Four dimensional Metric Model, Database and RESTful Resources
1. International Journal on Web Service Computing (IJWSC), Vol.3, No.3, September 2012
DOI : 10.5121/ijwsc.2012.3302 17
KM System Evaluation using Four dimensional
Metric Model, Database and RESTful Resources
D.Venkata Subramanian1
, Angelina Geetha1
, K.M. Mehata1
,
K.Mohammed Hussain2
1
Department of Computer Science and Engineering
2
Department of Computer Applications
B.S. Abdur Rahman University, Chennai, India
ABSTRACT
A Knowledge Management (KM) System plays a crucial role in every industry as well as in Higher Learning
Institutions. A RESTful resource is anything that is addressable over the Web. The resources can be
accessed and transferred between clients and server. The resources can be accessed and transferred
between clients and servers. Based on our earlier research works, we have developed a comprehensive KM
System framework, evaluation method, mult-dimensional metric model and useful metrics which are helpful
to assess any given knowledge management system. In this proposed work, we first describe the actual
implementation steps for building the KM System metric database using the multi-dimensional metric model.
Secondly we describe the approaches for designing a multi-dimensional Restful Resources and Web Services
using the mutli-dimensional metric model and demonstrate how the KM system can be ranked and rated for
its effectiveness using WAM and RESTful Resources.
KEYWORDS
Knowledge Management Systems (KMS), Metrics Model, KM Metrics, Multi-dimensional model,
Evaluation, Metrics Database, Ranking, Rating, Weighted Average Mean(WAM), RESTful Resources
1. INTRODUCTION
Knowledge Management (KM) provides an innovative methodology for creating and modifying to
promote knowledge creation and sharing. Many companies and institutions are working towards
building an effective KMS as well as using collaborative tools for increasing the knowledge
sharing with their knowledge workers. One of the key challenges with the KMS’s is evaluation of
the knowledge available within the organization and assessing the capabilities and effectiveness of
the KMS infrastructure [1]. Assessing the worth of the information and the infrastructure within
the organization is a crucial step if an organization wants to change the knowledge capture
methods and rewarding system for employees who have contributed the best knowledge asset.
Considering the intangible nature of the knowledge asset, complexity and dynamics of building the
KM System infrastructure, one of an approach is, to determine the strengths and weakness through
metrics. Metrics can be collected through an evaluation methodology such as Goal Question
Metrics (GQM), Weighted Balanced Score Card and/or using Hybrid methodology [2]. Based on
many research works, it has been identified that there are no proven reliable metric model and
metric database to estimate and report the worth of the knowledge being shared and also the worth
of KM Systems. This paper first describes a comprehensive KM System framework, Metrics and
2. International Journal on Web Service Computing (IJWSC), Vol.3, No.3, September 2012
18
Measurement Process which are critical for conducting an evaluation exercise on a KM System.
Secondly this paper describes the process of building metric database using the multi-dimensional
metric model for capturing the measures and metrics which are collected through evaluation
methods and illustrate how to apply WAM Method to rank and rate the effectiveness of a given
KM system. This paper finally describes the process of building RESTful Resources and Web
Services for evaluating KM Systems.
2. KMS FRAMEWORK
Knowledge management (KM) system is a collective term that is used to describe the creation of
knowledge repositories, respective interface components, improvement of knowledge access and
sharing as well as communication through collaboration, enhancing the knowledge environment
and managing knowledge as an asset for an organization. Considering the fundamental
capabilities of KMS and typical KMS infrastructure topology, we have identified a suitable KMS
framework [2] which is mentioned in the below figure (Figure 1). This framework represents all
the components which make up the KMS for industries as well as higher learning institutions and
in particular focused on the needed quality factors to develop a measurement model based which
are helpful for measuring the effectiveness of KMS.
Figure 1: KMS Framework
3. KM SYSTEM EVALUATION PROCESS
3.1 Metrics
A useful metric should be measurable, independent, accountable & precise. As much as possible,
the KM measures should be related to, or the same as, existing measures in the organization that
are used to monitor the success of performing mission objectives. For evaluating the capability of
the KM system, the metric must indicate the capabilities of the KMS.
3. International Journal on Web Service Computing (IJWSC), Vol.3, No.3, September 2012
19
3.2 Evaluation
An experiment process deliberately imposes a treatment on a group of objects or subjects in the
interest of observing the response. As illustrated in the Figure 2, the basic KM System evaluation
process consist of selection of the quality dimensions and classify them in to subjective or
objective and then applying the hybrid method of using GQM and Score card for data collection.
The selected measures which are generated manually or through system way should be stored in
any available database and later those will be retrieved for ranking and rating using Weighted
Average Mean Method.
Figure 2: Evaluation Process of KM Systems
3.3 Quality Factors
The factors whose effects need to be quantified are called primary quality factors. The features
often discussed concerning the overall quality of the knowledge management system are
capability, availability, reliability, usability, maintainability and completeness. In the proposed
metric model, these quality factors are considered as dimensions. We categorized the factors in
two groups such as primary and secondary and evaluators can choose the factors based on the
evaluation consideration and outcomes. Continuous Inputs for the KMS Measurement process
can be done through standard system programs or tools to monitor the usefulness and
responsiveness of supporting technology or the framework or components used for the KMS. The
system generated factors may also indicate usability problems and supporting policies for the KMS
by introducing the agents which collect these measures.
3.4 Output Metrics
Output metrics measure characteristics at the project or task level, such as the effectiveness of
lessons-learned for future operations. Direct process output for users provides a picture of the
extent to which personnel are drawn to actually using the knowledge system. For a given subject
present in the KMS the metric database can be queried and provide the outcomes such as
OverallFunctionalityRating, OverallUsabilityRating, OverallAvailabilityRating and
OverallEfficiencyRating with respect to the subject or Knowledge Asset available in the
KMS/knowledge repository. The output metrics can be calculated or derived based on the
4. International Journal on Web Service Computing (IJWSC), Vol.3, No.3, September 2012
20
objective and subjective feedback analysis from the knowledge sharing portal or the whole
knowledge infrastructure. Some of these measures can be calculated using system level statistics
and also by developing some background agents or web services or through a manual process.
4. FOUR-DIMENSIONAL METRIC MODEL
As described in the KM System Evaluation process in the earlier section, there are factors and
measures which play a critical role for producing the desired outcomes in the KMS evaluation. So,
KM dimensions also called as categories or view-points should be extensively correlated to many
factors influencing the results as much as possible. The Knowledge management quality factors
enable organizations to strongly indicate what they consider to be important. There are many
forces within an organization and Knowledge Management Systems affecting people’s learning,
sharing, and efficiency, so, it is important to consider the secondary factors as well (Quality Sub
Factors). In this section we describe some of the quality dimensions and the respective measures
and explain the chosen multi-dimensional metric model [3]. The key is selecting appropriate
Quality dimension through factors as represented in the figure (Figure 3) which contains KM
quality dimensions such as Functionality, Usability, Availability and Efficiency. The following
section discusses about measures and metrics corresponding to some of the prime quality factors
which will be given weights in the 80% category. The diagram below represents the four key
dimensions considered for the evaluation of the KM systems. The needed dimensions and
attributed can be added as per the evaluation or prediction.
Figure 3: Four-Dimensional KM Metric Model
4.1 Functionality Measures
The functionality of KMS can be considered as an entity object in the metric model and its
expected behavior will be captured as requirements or attributes of an entity object.
5. International Journal on Web Service Computing (IJWSC), Vol.3, No.3, September 2012
21
4.2 Usability Measures
The knowledge component should be easily understandable, learnable, and applicable. Usability
attribute are the features and characteristics of the software/product/sites that influence the
effectiveness, efficiency and satisfaction with which users can achieve specified goals.
4.3 Availability Measures
In the context of KMS, Knowledge Availability is whether (or how often) a given knowledge asset
is available for use by its intended users.
4.4 Efficiency Measures
The knowledge component should state the quickest solution with the least resource requirements.
4.5 KM Metric Database
The implementation of metric database is shown in the figure (Figure 4) below which was created
to hold the user and expert feedback of the considered dimensions and measures from the database.
The database used in the existing infrastructure can be also considered for storing the metrics and
measurements. As the volume of data and amount of transactions used for the KM System
measurement is very less, there is no need for a dedicated or high performance database and
existing database used for infrastructure maintenance or application database can be used to store
the schema and data. If the models and databases are systematically developed to be flexible,
effective, scalable and surely the data can be explored using mining technique or using WAM
Method. The metric database can be created using any industry specific database systems. There
are four Key steps in implementing the multi-dimensional metric database:
1. Gather the evaluation factors for assessment.
2. Decide the Quality Factor and Sub Factors
3. Create Data Objects (Tables/XML to hold the Quality Factors and Measures)
4. Upon collecting the measures, store them in the data objects
The metric database for our evaluation experiment, has been implemented using Microsoft
Sqlserver 2008 and the data were collected the metrics through Hybrid Approaches [2], manual
feeds and also through customized programs. The data got generated based on the inputs from
user, expert and system. As you see from the below database ER diagram, our metric database is
designed to be flexible to hold any and metric as per the rating from normal user or expert.
6. International Journal on Web Service Computing (IJWSC), Vol.3, No.3, September 2012
22
Figure 3: KM Metric Database ER Diagram
The KM Metric database consists of five key tables namely, KA_BASE_TBL which is the base
table which contains the knowledge asset created/modified in the knowledge portal or repository.
The KA_USER_TBL hold the information about the user name, type and their details.
KA_USER_RATING table holds the user feedback on the given measure. The
KA_METRIC_BASE_TBL which is our key table which holds the attributes like metric id (MID),
Description (MDESC), weight (MWEIGHT) and the corresponding quality factor (DIMENSION).
5. THE EXPERIMENT – KM SYSTEM ANALYSIS
The participants were selected from multiple departments of top two engineering colleges with
moderate and frequent usage of knowledge portals and knowledge repositories. Initially 360
candidates were selected, but only 162 candidates, with similar profiles, were actually used in the
experiment. Prior to conducting the actual experiment, the pilot tests were conducted to validate
the approaches and tasks involved. The main aspects of the normal user profiles of the
participants used were similar in the following ways:
• Computing knowledge, knowledge of using collaborative tools and basic knowledge in
the subject areas present in the KM systems
• Above 20 years of age and below 23 years of age, with English as their learning
language for all the subjects
The main aspects of the expert user profiles of the participants used were similar in the following
ways:
• Teaching or Training skills; Expert knowledge in the subject area
• Willingness to review and provide feedback of the knowledge assets
• Less than 69 years of age and above 27 years of age with apt qualification
For this experiment, we have considered four important dimensions and allocated evaluation
percentage as below:
• 30% for Functionality; 20% for Usability
• 20% for Availability; 20% for Efficiency
The Table-1 for functionality dimension shows how the evaluation percentage (30%) is
distributed among multiple functionality measures. The third column contains the captured rating
which contains aggregated value which is stored in the metric database based on user, expert and
International Journal on Web Service Computing (IJWSC), Vol.3, No.3, September 2012
22
Figure 3: KM Metric Database ER Diagram
The KM Metric database consists of five key tables namely, KA_BASE_TBL which is the base
table which contains the knowledge asset created/modified in the knowledge portal or repository.
The KA_USER_TBL hold the information about the user name, type and their details.
KA_USER_RATING table holds the user feedback on the given measure. The
KA_METRIC_BASE_TBL which is our key table which holds the attributes like metric id (MID),
Description (MDESC), weight (MWEIGHT) and the corresponding quality factor (DIMENSION).
5. THE EXPERIMENT – KM SYSTEM ANALYSIS
The participants were selected from multiple departments of top two engineering colleges with
moderate and frequent usage of knowledge portals and knowledge repositories. Initially 360
candidates were selected, but only 162 candidates, with similar profiles, were actually used in the
experiment. Prior to conducting the actual experiment, the pilot tests were conducted to validate
the approaches and tasks involved. The main aspects of the normal user profiles of the
participants used were similar in the following ways:
• Computing knowledge, knowledge of using collaborative tools and basic knowledge in
the subject areas present in the KM systems
• Above 20 years of age and below 23 years of age, with English as their learning
language for all the subjects
The main aspects of the expert user profiles of the participants used were similar in the following
ways:
• Teaching or Training skills; Expert knowledge in the subject area
• Willingness to review and provide feedback of the knowledge assets
• Less than 69 years of age and above 27 years of age with apt qualification
For this experiment, we have considered four important dimensions and allocated evaluation
percentage as below:
• 30% for Functionality; 20% for Usability
• 20% for Availability; 20% for Efficiency
The Table-1 for functionality dimension shows how the evaluation percentage (30%) is
distributed among multiple functionality measures. The third column contains the captured rating
which contains aggregated value which is stored in the metric database based on user, expert and
International Journal on Web Service Computing (IJWSC), Vol.3, No.3, September 2012
22
Figure 3: KM Metric Database ER Diagram
The KM Metric database consists of five key tables namely, KA_BASE_TBL which is the base
table which contains the knowledge asset created/modified in the knowledge portal or repository.
The KA_USER_TBL hold the information about the user name, type and their details.
KA_USER_RATING table holds the user feedback on the given measure. The
KA_METRIC_BASE_TBL which is our key table which holds the attributes like metric id (MID),
Description (MDESC), weight (MWEIGHT) and the corresponding quality factor (DIMENSION).
5. THE EXPERIMENT – KM SYSTEM ANALYSIS
The participants were selected from multiple departments of top two engineering colleges with
moderate and frequent usage of knowledge portals and knowledge repositories. Initially 360
candidates were selected, but only 162 candidates, with similar profiles, were actually used in the
experiment. Prior to conducting the actual experiment, the pilot tests were conducted to validate
the approaches and tasks involved. The main aspects of the normal user profiles of the
participants used were similar in the following ways:
• Computing knowledge, knowledge of using collaborative tools and basic knowledge in
the subject areas present in the KM systems
• Above 20 years of age and below 23 years of age, with English as their learning
language for all the subjects
The main aspects of the expert user profiles of the participants used were similar in the following
ways:
• Teaching or Training skills; Expert knowledge in the subject area
• Willingness to review and provide feedback of the knowledge assets
• Less than 69 years of age and above 27 years of age with apt qualification
For this experiment, we have considered four important dimensions and allocated evaluation
percentage as below:
• 30% for Functionality; 20% for Usability
• 20% for Availability; 20% for Efficiency
The Table-1 for functionality dimension shows how the evaluation percentage (30%) is
distributed among multiple functionality measures. The third column contains the captured rating
which contains aggregated value which is stored in the metric database based on user, expert and
7. International Journal on Web Service Computing (IJWSC), Vol.3, No.3, September 2012
23
system feed. The tables 2, 3 and 4 are populated for Usability, Availability and Efficiency
Dimension using the aggregated value from the metric database. As mentioned in the earlier
sections, for evaluation purpose, we have also considered non-weighted measures and added 10%
to our overall calculation. For an effective and successful KM system, the organization must have
multiple support factors such as Environment, Infrastructure, Domain Knowledge and
participant’s thrust for knowledge sharing. So, we have taken the feedback on these parameters
and added to the metric database and populated in the Table 5.
[
TABLE 1: WEIGHTAGE TABLE FOR FUNCTIONALITY
KM Functionality
Measure/Metric
Weight
(30%)
Captured Rating(from
Metric DB)
Weighted
Calculation
F_M1 OverallFunctionalityRating 20% 3.5 0.7
F_M2 RequirementVerified 10% 3.2 0.32
F_M3 RequirementValidated 10% 3.6 0.36
F_M4 RequirementSeverity 10% 2.1 0.21
F_M5 TacitCategory 10% 4.1 0.41
F_M6 ExplicitCategory 10% 2.4 0.24
F_M7 InnovativeCategory 30% 3.1 0.93
100% Total Score 3.17
KM Dimension Score 0.951
TABLE 2: WEIGHTAGE TABLE FOR USABLITY
KM Usability Measure/Metric Weight
(20%)
Captured Rating(from
Metric DB)
Weighted
Calculation
U_M1 OverallUsability_Rating 20% 3.8 0.76
U_M2 RatingOnOperability 20% 4 0.8
U_M3 RatingOnCommunicativeness 10% 2.9 0.29
U_M4 RatingOnAccessibility 20% 3.5 0.7
U_M5 UserRatingOnUI 20% 4 0.8
U_M6 ExpertRatingOnUI 10% 3.6 0.36
100% Total Score 3.71
KM Dimension Score 0.742
TABLE 3. WEIGHTAGE TABLE FOR AVAILABILITY
KM Availability Measure/Metric Weight
(20%)
Captured Rating(from
Metric DB)
Weighted
Calculation
A_M1 OverallAvailablityRating 20% 3.2 0.64
A_M2 AccessCount 10% 3.9 0.39
A_M3 UpdateCount 10% 3.2 0.32
A_M4 PositiveCommentsCount 10% 4.2 0.42
A_M5 NegativeCommentsCount 10% 1 0.1
A_M6 NeutralCommentsCount 10% 3.7 0.37
A_M7 ActiveThreadsCount 30% 4.1 1.23
100% Total Score 3.27
KM Dimension Score 0.654
8. International Journal on Web Service Computing (IJWSC), Vol.3, No.3, September 2012
24
TABLE 4. WEIGHTAGE TABLE FOR EFFICIENCY
KM Efficiency Measure/Metric Weight
(20%)
Captured Rating(from
Metric DB)
Weighted
Calculation
E_M1 OverallEfficencyRating 20% 3.9 0.78
E_M2 StorageEfficiencyRating 20% 3.5 0.7
E_M3 UserRatingOnEfficiency 30% 4.1 1.23
E_M4 ExpertRankingOnEfficiency 30% 3.6 1.08
100% Total Score 3.79
KM Dimension Score 0.758
TABLE 5. NON-WEIGHTED MEASURES TABLE
KM Non Weighted Measure/Metric (10%) Captured Rating(from Metric DB)
NW_M1Supporting KM Infrastructure 3
NW_M2 Management Support 2
NW_M3 Condusive Environment 1
NW_M4 Particpant’s Subject Knowledge 2
NW_M5 Participants Thrust for Knowledge
Collabration 3
Total Non Weight Value 11
Average 2.2
10 % of Non Weighted Dimension Score 0.22
TABLE 6. OVERALL EFFECTIVENESS TABLE
Allocation Type Derived Score
90% Weighted Dimension
Group 2.79
10% Non Weighted
Dimension Group 0.22
Overall KM System Score 3.01
TABLE 7. RANKING AND RATING TABLE
Rank Category Rating
1 Outstanding 5
2 Extremely Effective 4
3 Effective 3
4 Below Effective 2
5 Not Effective 1
The Table 6 is the summary table and contains both weighted and non-weighted dimension group.
The weighted dimension group score is 2.79, which has been derived by adding all the four
quality dimension scores. The non-weighted dimension group was given 0.22 and both derived
scores were added to make up overall KM System Effectiveness Score. The KM system was
evaluated by the users and experts with the score 3.01. The data obtained for this experiment
concerned with the effectiveness of the KM system of the engineering subjects/knowledge assets.
9. International Journal on Web Service Computing (IJWSC), Vol.3, No.3, September 2012
25
6.RESTFUL RESOURCES
The term REST comes from Roy Fielding's PhD dissertation, published in 2000, and it stands for
REpresentational State Transfer. REST by itself is not an architecture; REST is a set of
constraints that, when applied to the design of a system, creates a software architectural style. A
RESTful resource is anything that is addressable over the Web. The resource can be accessed
and transferred between clients and servers and it is a logical, temporal mapping to a concept in
the problem domain for which we are implementing a solution. Because we are using HTTP to
communicate, we can transfer any kind of information that can be passed between clients and
servers. A Uniform Resource Identifier, or URI, in a RESTful web service is a hyperlink to a
resource, and it's the only means for clients and servers to exchange representations.
In modern web application development we limit design and implementation ambiguity, because
we have four specific actions that we can take upon resources—Create, Retrieve, Update, and
Delete (CRUD). Therefore, with the delineated roles for resources and representations, we can
now map our CRUD actions to the HTTP methods POST, GET, PUT, and DELETE. The
method GET is used to RETRIEVE resources. We need to determine what a resource is in the
context of our web service and what type of representation we're exchanging.
Figure 5: KM System Evaluation Framework using RESTful Architecture
The above framework has been redefined based on our KMS technology Framework [2] found in
Figure-1, to adapt RESTful Architecture to evaluate any KM System using RESTful resources
and Web services. The metrics based on the feedback from Knowledge Workers, Experts, IT
International Journal on Web Service Computing (IJWSC), Vol.3, No.3, September 2012
25
6.RESTFUL RESOURCES
The term REST comes from Roy Fielding's PhD dissertation, published in 2000, and it stands for
REpresentational State Transfer. REST by itself is not an architecture; REST is a set of
constraints that, when applied to the design of a system, creates a software architectural style. A
RESTful resource is anything that is addressable over the Web. The resource can be accessed
and transferred between clients and servers and it is a logical, temporal mapping to a concept in
the problem domain for which we are implementing a solution. Because we are using HTTP to
communicate, we can transfer any kind of information that can be passed between clients and
servers. A Uniform Resource Identifier, or URI, in a RESTful web service is a hyperlink to a
resource, and it's the only means for clients and servers to exchange representations.
In modern web application development we limit design and implementation ambiguity, because
we have four specific actions that we can take upon resources—Create, Retrieve, Update, and
Delete (CRUD). Therefore, with the delineated roles for resources and representations, we can
now map our CRUD actions to the HTTP methods POST, GET, PUT, and DELETE. The
method GET is used to RETRIEVE resources. We need to determine what a resource is in the
context of our web service and what type of representation we're exchanging.
Figure 5: KM System Evaluation Framework using RESTful Architecture
The above framework has been redefined based on our KMS technology Framework [2] found in
Figure-1, to adapt RESTful Architecture to evaluate any KM System using RESTful resources
and Web services. The metrics based on the feedback from Knowledge Workers, Experts, IT
International Journal on Web Service Computing (IJWSC), Vol.3, No.3, September 2012
25
6.RESTFUL RESOURCES
The term REST comes from Roy Fielding's PhD dissertation, published in 2000, and it stands for
REpresentational State Transfer. REST by itself is not an architecture; REST is a set of
constraints that, when applied to the design of a system, creates a software architectural style. A
RESTful resource is anything that is addressable over the Web. The resource can be accessed
and transferred between clients and servers and it is a logical, temporal mapping to a concept in
the problem domain for which we are implementing a solution. Because we are using HTTP to
communicate, we can transfer any kind of information that can be passed between clients and
servers. A Uniform Resource Identifier, or URI, in a RESTful web service is a hyperlink to a
resource, and it's the only means for clients and servers to exchange representations.
In modern web application development we limit design and implementation ambiguity, because
we have four specific actions that we can take upon resources—Create, Retrieve, Update, and
Delete (CRUD). Therefore, with the delineated roles for resources and representations, we can
now map our CRUD actions to the HTTP methods POST, GET, PUT, and DELETE. The
method GET is used to RETRIEVE resources. We need to determine what a resource is in the
context of our web service and what type of representation we're exchanging.
Figure 5: KM System Evaluation Framework using RESTful Architecture
The above framework has been redefined based on our KMS technology Framework [2] found in
Figure-1, to adapt RESTful Architecture to evaluate any KM System using RESTful resources
and Web services. The metrics based on the feedback from Knowledge Workers, Experts, IT
10. International Journal on Web Service Computing (IJWSC), Vol.3, No.3, September 2012
26
Infrastructure Staff, management staff and also from the System Agents can be stored in the KMS
Metric/Evaluation database or in the form of XML. The RESTFul Webserver can be designed in
such a way, to retrieve the metrics from the KM Metric database and produce the results in the
form of RDF Message.
The Reporting Agent can be used to transform the metric database through RESTful server to
represent in a Text or Graphical or XML form. The agents can be developed to feed the data
through messages to RESTful Web server first and then it can be stored in a traditional metric
database. In order to handle the KM System evaluation, we need to construct a web service first.
The XML representation of the key dimensions from the four dimensional model is given below:
<KM-Functionality>
<Metric-Id> F_M1 </Metric-Id>
<Metric-Name> OverallFunctionalityRating </Metric-Name>
<Metric-Weight> 20 </Metric-Weight>
<Actual-Score> 3.5 </Actual-Score>
</KM-Functionality>
<KM-Usability>
<Metric-Id> U_M1 </Metric-Id>
<Metric-Name> OverallUsabilityRating </Metric-Name>
<Metric-Weight> 20 </Metric-Weight>
<Actual-Score> 3.8 </Actual-Score>
</KM-Usability>
<KM-Availability>
<Metric-Id> A_M1 </Metric-Id>
<Metric-Name> OverallAvailabilityRating </Metric-Name>
<Metric-Weight> 20 </Metric-Weight>
<Actual-Score> 3.2 </Actual-Score>
</KM-Availability>
<KM-Efficiency>
<Metric-Id> E_M1 </Metric-Id>
<Metric-Name> OverallEfficiencyRating </Metric-Name>
<Metric-Weight> 20 </Metric-Weight>
<Actual-Score> 3.9 </Actual-Score>
</KM-Efficiency>
With the representations defined, we now assume URIs of the form http://KM-System-
Eval.com/KM-Functionality to access a list of functionality metrics, and http://KM-System-
Eval.com/KM-Functionality/{Metric-Id} to access a Metric that has the unique identifier of value
Metric-Id. For instance, if we wanted the retrieve or record for a metric with the metric id U_M1,
we make a request to the URI http://KM-System-Eval.com/KM-Functionality/U_M1.
The method GET is used to RETRIEVE resources, the method POST is used to CREATE
resources, the method PUT is used to UPDATE resources and the method DELETE is used to
DELETE representations. The table 8 contains the URI and HTTP verb mapping for business
operations of the KM System Evaluation.
11. International Journal on Web Service Computing (IJWSC), Vol.3, No.3, September 2012
27
TABLE 8: URI-HTTP MAPPING TABLE
URI HTTP
Method
COLLECTION OPERATION EVALUATION OPERATION
/ F_M1 GET /KM-Functionality RETRIEVE GET SCORES
/F_M1 POST /KM-Functionality CREATE STORE SCORES
/ U_M1 GET /KM-Usability RETRIEVE GET SCORES
/U_M1 POST /KM-Usability CREATE STORE SCORES
/ A_M1 GET /KM-Availability RETRIEVE GET SCORES
/A_M1 POST /KM-Availability CREATE STORE SCORES
/ E_M1 GET /KM-Relevance RETRIEVE GET SCORES
/E_M1 POST /KM-Relevance CREATE STORE SCORES
Designing RESTful web services is not different from designing traditional web applications. We
can think of RESTful web service design as being similar to Object Oriented Design (OOD).
The underlying RESTful web service design principles can be summarized in the following four
steps:
1. Requirements gathering for KM System Evaluation
2. Resource identification based on proposed multi-dimensional model
3. Resource representation definition—between clients (User Interfaces or Agents) and
servers (KM metric database or Web Server). For KM metrics, we can use XHTML.
4. URI definition—with resources in place, we need to define the API, which consists of
URIs for clients and servers to exchange resources' representations.
CONCLUSION
In this research work, we have attempted to build a four dimensional model, the metric database
and a proven statistical technique Weighted Average Mean to validate the effectiveness of the
knowledge sharing in the KM systems. By referring to Table 6 and the guideline Table 7 for
ranking and rating, it is clear, that the evaluated KM system is effective as the KM system got the
overall KM System Score of 3.01. The results obtained through the experiment, proves that the
combination of Metric Database with a Statistical technique such as WAM could be useful to
predict the usefulness and effectiveness of the KM Systems. In complex KM Systems, the KM
System Infrastructure is heterogeneous and contains multiple social and economic factors [2] and
hence more dimensions have to be considered. Automation would be flexible and cost effective
using RESTful Resources and Web Services when used in conjunction with the metric database
for better metrics collection and reporting.
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