Network of Excellence in Internet Science (JRA6, Virtual Communities, C. Marsden, UESSEX)

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Jake wallis faculty phd forum 2011

Jake Wallis

Establishment of sustainable data ecosystems(1)

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Open Data initiatives are increasingly considered as defining elements of emerging smart cities. However, few studies have attempted to provide a better understanding of the nature of this convergence and the impact on both domains. This paper presents findings from a detailed study of 18 open data initiatives across five smart cities – Barcelona, Chicago, Manchester, Amsterdam and Helsinki. Specifically, the study sought to understand how open data programs are shaped by the different smart cities contexts and concomitantly what kinds of innovations are enabled by open data in these cities. The findings highlight the specific impacts of open data innovation on the different smart cities domains, governance of the cities, and the nature of datasets available in the open data ecosystem.

A Tale of Open Data Innovations in Five Smart Cities

Adegboyega Ojo

Open Data initiatives are increasingly considered as defining elements of emerging smart cities. However, few studies have attempted to provide a better understanding of the nature of this convergence and the impact on both domains. This paper presents findings from a detailed study of 18 open data initiatives across five smart cities – Barcelona, Chicago, Manchester, Amsterdam, and Helsinki. Specifically, the study sought to understand how open data initiatives are shaped by the different smart cities contexts and concomitantly what kinds of innovations are enabled by open data in these cities. The findings highlight the specific impacts of open data innovation on the different smart cities domains, governance of the cities, and the nature of datasets available in the open data ecosystem. Link to the paper: http://conferences.computer.org/hicss/2015/papers/7367c326.pdf

A tale of open data in five smart cities

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Digital Democracy and Data Commons. This pilot will involve the Barcelona City Council and the city’s digital democracy software Decidim.org, which has more than 60K users. The platform will integrate a DECODE module which allows petitions to be signed anonymously but still in line with authentication requirements, such as place of residence. This new system for citizen petitions that gives people more granular control over their data. It will enhance privacy (via the DECODE app), allow data sharing and visualization (via the BCNOW dashboard) and transparency (via the DECODE distributed ledger). The pilot will also open a deliberative, participatory process on the politics and economics of data, and how Barcelona could constitute a democratic city data commons. You can keep up to date with the pilot or participate here. Citizen Science Data Governance. In this pilot residents will use environmental sensors which record factors such as noise levels and pollution. The sensors will be located inside their homes and in their neighbourhood. DECODE technology will enable them to share this encrypted data anonymously with their communities, on their own terms. The pilot will run sessions to train and support participants to help them setup and use the sensors to gather and analyse data to influence city-level decisions. The pilot tackles the technical challenges of collating and storing a stream of citizen-sensed data, while also enabling those citizens to control what information is shared with whom, and under which conditions. This pilot will be run in collaboration with Barcelona community organisations Ideas for Change and FabLab Barcelona.

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Here is the full reference: Calzada, I. & Cobo, C. (2015), Unplugging: Deconstructing the Smart City, Journal of Urban Technology. DOI: 10.1080/10630732.2014.971535. http://dx.doi.org/10.1080/10630732.2014.971535 This is an Author's Original Manuscript of an article published by Taylor & Francis in the JOURNAL OF URBAN TECHNOLOGY on March 16, 2015, available online: http://www.tandfonline.com/doi/full/10.1080/10630732.2014.971535#abstract DOI: 10.1080/10630732.2014.971535 This version will be shared on author’s personal website ONLY. This article may not exactly replicate the final version published in this journal. It is not the copy of record.

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fsdfgList of Course Work Subjects S.NO SEM SUBJECT CODE SUBJECT TITLE ELECTIVE/CORE CREDIT 1 1 22MC202 MACHINE LEARNING TECHNIQUES CORE 3 2 1 22PRM01 RESEARCH METHODOLOGY AND IPR CORE 3 3 1 22MC302 ADVANCED ARTIFICIAL INTELLIGENCE ELECTIVE 3 4 3 22MC209 ADVANCED INTERNET OF THINGS CORE 3 5 3 22PVD30 SYSTEM LEVEL HARDWARE SOFTWARE CODESIGN ELECTIVE 3 6 3 22MC324 INFORMATION RETRIEVAL TECHNIQUES ELECTIVE 3 22MC202 MACHINE LEARNING TECHNIQUES Course Objective 1. To introduce students to the basic concepts and techniques of Machine Learning. 2. To have a thorough understanding of the Supervised and Unsupervised learning techniques 3. To implement linear and non-linear learning models 4. To implement distance-based clustering techniques 5. To understand graphical models of machine learning algorithms Unit I FUNDAMENTALS OF MACHINE LEARNING 9 Learning – Types of Machine Learning – Supervised Learning – The Brain and the Neuron – Design a Learning System – Perspectives and Issues in Machine Learning – Concept Learning Task – Concept Learning as Search – Finding a Maximally Specific Hypothesis – Version Spaces and the Candidate Elimination Algorithm – Linear Discriminants – Perceptron – Linear Separability – Linear regression. Unit II LINEAR MODELS 9 Multi-layer Perceptron – Going Forwards – Going Backwards: Back Propagation Error – Multi-layer Perceptron in Practice – Examples of using the MLP – Overview – Deriving Back-Propagation – Radial Basis Functions and Splines – Concepts – RBF Network – Curse of Dimensionality – Interpolations and Basis Functions – Support Vector Machines Unit III DISTANCE-BASED MODELS 9 Nearest neighbor models – K-means – clustering around medoids – silhouettes – hierarchical clustering – Density based methods- Grid based methods- Advanced cluster analysis- k-d trees – locality sensitive hashing – non-parametric regression – bagging and random forests – boosting – meta learning Unit IV TREE AND RULE MODELS 9 Decision trees – learning decision trees – ranking and probability estimation trees – regression trees – clustering trees – learning ordered rule lists – learning unordered rule lists – descriptive rule learning – Mining Frequent patterns, Association and Correlations, advanced association rule techniques-first order rule learning Unit V REINFORCEMENT LEARNING AND GRAPHICAL MODELS 9 Reinforcement Learning – Overview – Getting Lost Example – Markov Decision Process, Markov Chain Monte Carlo Methods – Sampling – Proposal Distribution – Markov Chain Monte Carlo – Graphical Models – Bayesian Networks – Markov Random Fields – Hidden Markov Models – Tracking Methods. TOTAL HOURS: 45 PERIODS CO1 Understanding distinguish between, supervised, unsupervised and semi- supervised learning CO2 Apply the appropriate machine learning strategy for any given problem Course Outcome CO3 Suggestion of using supervised, unsupervised or semi-superv

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This is the presentation of the keynote I gave to the The "Software Codes of Democracy: Web Platforms for New Politics Workshop, which was held in Milan, Italy 13-15 Sept 2013 http://codicidellademocrazia.partecipate.it/ Abstract Social media are increasingly used to support online debate and facilitate citizens’ engagement in policy and decision-making. Nevertheless the online dialogue spaces we see on the Web today typically provide flat listings of comments, or threads that can be viewed by ‘subject’ line. These are fundamentally chronological views which offer no insight into the logical structure of the ideas, such as the coherence or evidential basis of an argument. This hampers both quality of citizens’ participation and effective assessment of the state of the debate. Within the landscape of existing community debate and ideation tools, the talk will introduce a new class of emerging online deliberation platforms – coming from research on Hypermedia, Collective Intelligence and Argumentation – that enable more structured, engaging and transparent online deliberation processes. The talk will focus on the description of some of these technologies and summarise research studies in which they have been used to effectively support online deliberation in the Education, Healthcare and Public sector. The talk will conclude proposing reflections and future research on collective intelligence and online deliberation platforms to socially innovate and to re-engage citizens with the democratic process.

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Online social networks (OSNs) contain data about users, their relations, interests and daily activities and the great value of this data results in ever growing popularity of OSNs. There are two types of OSNs data, semantic and topological. Both can be used to support decision making processes in many applications such as in information diffusion, viral marketing and epidemiology. Online Social network analysis (OSNA) research is used to maximize the benefits gained from OSNs’ data. This paper provides a comprehensive study of OSNs and OSNA to provide analysts with the knowledge needed to analyse OSNs. OSNs’ internetworking was found to increase the wealth of the analysed data by depending on more than one OSN as the source of the analysed data. Paper proposes a generic model of OSNs’ internetworking system that an analyst can rely on. Two different data sources in OSNs were identified in our efforts to provide a thorough study of OSNs, which are the OSN User data and the OSN platform data. Additionally, we propose a classification of the OSN User data according to its analysis models for different data types to shed some light into the current used OSNA methodologies. We also highlight the different metrics and parameters that analysts can use to evaluate semantic or topologic OSN user data. Further, we present a classification of the other data types and OSN platform data that can be used to compare the capabilities of different OSNs whether separate or in a OSNs’ internetworking system. To increase analysts’ awareness about the available tools they can use, we overview some of the currently publically available OSNs’ datasets and simulation tools and identify whether they are capable of being used in semantic, topological OSNA, or both. The overview identifies that only few datasets includes both data types (semantic and topological) and there are few analysis tools that can perform analysis on both data types. Finally paper present a scenario that shows that an integration of semantic and topologic data (hybrid data) in the OSNA is beneficial.

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The challenges posed by the complexity of our times requires the Design discipline to understand the many complex relationships behind the social, business, technology and territory dimensions of each project. Such nature of complex systems lays not only inside design projects, but also inside the design processes that generate them, and the ability of organizing them through meta-design approaches is becoming strategic. Since the turn of the century, the design discipline has increasingly moved its scope from single users to local and online communities, from isolated projects to system of solutions. This shift has brought researchers and practitioners to investigate tools and strategies to enable mass- scale interactions by adopting several models and tools coming from software development and web-based technologies: Open Source, P2P, DDD (Diffuse, Distributed, and Decentralized) systems. This influence has matured over the years, and if we observed in the past how such systemic models can be applied in the design practice (part 1), we are facing now a new phase where Design will have an increasing role in enabling such systems through the analysis, visualization and design of their collaborative tools, platforms, processes and organizations (part 2). This scope falls into the Meta-Design domain, where designers build environments for the collaborative design of open processes and their resulting organizations (part 3). In this paper, we address this phenomena by elaborating the Open Meta-Design framework (part 4), that provides a way for designing open, collaborative and distributed processes (including those in the professional design domain). The paper positions the framework among current meta-design and design approaches and develops its features of modeling, analysis, management and visualization of processes. This framework is based on four dimensions: conceptual (describing the philosophy, context and limitations of the approach), data (describing the ontology of design processes), design (visualizing designing processes) and software (managing the connections between the ontology and the visualization, the data and design dimensions). We believe that such a framework could potentially facilitate the participation and the creation of open, collaborative and distributed processes, enabling therefore more relevant interactions for communities. As a conclusion, the paper provides a roadmap for developing and testing the Open Meta-Design framework, and therefore evaluating its relevance in supporting complex projects (part 5).

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Created by Mozilla Research in 2012 and now part of Linux Foundation Europe, the Servo project is an experimental rendering engine written in Rust. It combines memory safety and concurrency to create an independent, modular, and embeddable rendering engine that adheres to web standards. Stewardship of Servo moved from Mozilla Research to the Linux Foundation in 2020, where its mission remains unchanged. After some slow years, in 2023 there has been renewed activity on the project, with a roadmap now focused on improving the engine’s CSS 2 conformance, exploring Android support, and making Servo a practical embeddable rendering engine. In this presentation, Rakhi Sharma reviews the status of the project, our recent developments in 2023, our collaboration with Tauri to make Servo an easy-to-use embeddable rendering engine, and our plans for the future to make Servo an alternative web rendering engine for the embedded devices industry. (c) Embedded Open Source Summit 2024 April 16-18, 2024 Seattle, Washington (US) https://events.linuxfoundation.org/embedded-open-source-summit/ https://ossna2024.sched.com/event/1aBNF/a-year-of-servo-reboot-where-are-we-now-rakhi-sharma-igalia

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