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Articles 1 - 8 of 8
Full-Text Articles in Science and Technology Studies
Brave New World: Privacy, Data Sharing And Evidence Based Policy Making, Rhonda S. Binda
Brave New World: Privacy, Data Sharing And Evidence Based Policy Making, Rhonda S. Binda
Open Educational Resources
The trifecta of globalization, urbanization and digitization have created new opportunities and challenges across our nation, cities, boroughs and urban centers. Cities in particular are in a unique position at the center of commerce and technology becoming hubs for innovation and practical application of emerging technology. In this rapidly changing 24/7 digitized world, governments are leveraging innovation and technology to become more effective, efficient, transparent and to be able to better plan for and anticipate the needs of its citizens, businesses and community organizations. This class will provide the framework for how cities and communities can become smarter and more …
A New Data Driven Long-Term Solar Yield Analysis Model Of Photovoltaic Power Plants, Biplob Ray, Rakibuzzaman Shah, Md Rabiul Islam, Syed Islam
A New Data Driven Long-Term Solar Yield Analysis Model Of Photovoltaic Power Plants, Biplob Ray, Rakibuzzaman Shah, Md Rabiul Islam, Syed Islam
Faculty of Engineering and Information Sciences - Papers: Part B
Historical data offers a wealth of knowledge to the users. However, often restrictively mammoth that the information cannot be fully extracted, synthesized, and analyzed efficiently for an application such as the forecasting of variable generator outputs. Moreover, the accuracy of the prediction method is vital. Therefore, a trade-off between accuracy and efficacy is required for the data-driven energy forecasting method. It has been identified that the hybrid approach may outperform the individual technique in minimizing the error while challenging to synthesize. A hybrid deep learning-based method is proposed for the output prediction of the solar photovoltaic systems (i.e. proposed PV …
On Masking And Releasing Smart Meter Data At Micro-Level: The Multiplicative Noise Approach, John Brackenbury, P. Y. O'Shaughnessy, Yan-Xia Lin
On Masking And Releasing Smart Meter Data At Micro-Level: The Multiplicative Noise Approach, John Brackenbury, P. Y. O'Shaughnessy, Yan-Xia Lin
Faculty of Engineering and Information Sciences - Papers: Part B
Smart meter electricity data presents privacy risks when malicious agents gain insights of private information, including residents’ lifestyle and daily habits. When allowing access to record-level data, we apply the multiplicative noise method to mask individual smart meter data, which simultaneously aims to minimise disclosure of a dwelling’s consumption signal to any third party and to enable accurate estimation of the sum of a cluster of households. Three testing criteria are introduced to measure the performance of multiplicative noise masking approach relevant to the smart meter data. We propose a novel ‘Twin Uniform’ noise distribution and derive relevant theoretical results. …
Apex2s: A Two-Layer Machine Learning Model For Discovery Of Host-Pathogen Protein-Protein Interactions On Cloud-Based Multiomics Data, Huaming Chen, Jun Shen, Lei Wang, Chi-Hung Chi
Apex2s: A Two-Layer Machine Learning Model For Discovery Of Host-Pathogen Protein-Protein Interactions On Cloud-Based Multiomics Data, Huaming Chen, Jun Shen, Lei Wang, Chi-Hung Chi
Faculty of Engineering and Information Sciences - Papers: Part B
No abstract provided.
Refinement And Augmentation For Data In Micro Learning Activity With An Evolutionary Rule Generators, Geng Sun, Jiayin Lin, Tingru Cui, Jun Shen, Dongming Xu, Mahesh Kayastha
Refinement And Augmentation For Data In Micro Learning Activity With An Evolutionary Rule Generators, Geng Sun, Jiayin Lin, Tingru Cui, Jun Shen, Dongming Xu, Mahesh Kayastha
Faculty of Engineering and Information Sciences - Papers: Part B
Improving both the quantity and quality of existing data are placed at the center of research for adaptive micro open learning. To cover this research gap, our work targets on the current scarcity of both data and rules that represent open learning activities. An evolutionary rule generator is constructed, which consists of an outer loop and an inner loop. The outer loop runs a genetic algorithm (GA) to produce association rules that can be effective in the micro open learning scenario from a small amount of available data sources; while the inner loop optimizes generated candidates by taking into account …
A Framework Towards Data Analysis On Host-Pathogen Protein-Protein Interactions, Huaming Chen, Jun Shen, Lei Wang, Jiangning Song
A Framework Towards Data Analysis On Host-Pathogen Protein-Protein Interactions, Huaming Chen, Jun Shen, Lei Wang, Jiangning Song
Faculty of Engineering and Information Sciences - Papers: Part B
With the rapid development of high-throughput technologies, systems biology is now embracing a great opportunity made possible by the increased accumulation of data available online. Biological data analytics is considered as a critical means to contribute to a better understanding on such data through extraction of the latent features, relationships and the associated mechanisms. Therefore, it is important to evaluate how to involve data analytics from both computational and biological perspectives in practice. This paper has investigated interaction relationships in the proteomics area, which provide insights of the critical molecular processes within infection mechanisms. Specifically, we focused on host–pathogen protein–protein …
Tools For Data Governance, Michael J. Madison
Tools For Data Governance, Michael J. Madison
Articles
This article describes the challenges of data governance in terms of the broader framework of knowledge commons governance, an institutional approach to governing shared knowledge, information, and data resources. Knowledge commons governance highlights the potential for effective community- and collective-based governance of knowledge resources. The article focuses on key concepts within the knowledge commons framework rather than on specific law and public policy questions, directing the attention of researchers and policymakers to critical inquiry regarding relevant social groups and relevant data “things.” Both concepts are key tools for effective data governance.
Data Governance And The Emerging University, Michael J. Madison
Data Governance And The Emerging University, Michael J. Madison
Book Chapters
Knowledge and information governance questions are tractable primarily in institutional terms, rather than in terms of abstractions such as knowledge itself or individual or social interests. This chapter offers the modern research university as an example. Practices of data-intensive research by university-based researchers, sometimes reduced to the popular phrase “Big Data,” pose governance challenges for the university. The chapter situates those challenges in the traditional understanding of the university as an institution for understanding forms and flows of knowledge. At a broad level, the chapter argues that the new salience of data exposes emerging shifts in the social, cultural, and …