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Regulating Digital Security by Design?:Implications of The Perspectives From DSbD Programme Stakeholders
Get PDFAs part of the growing necessity for inter-organisational and multi-disciplinary interaction to facilitate complex innovation in digital security, there needs to be greater engagement with regulation in the innovation process. This is particularly true in the case of security technologies that are embedded within wider systems and that are largely invisible to most of the users of that system. This paper describes stakeholders’ perspectives on regulation in the digital security innovation process and evaluates the implications of these perspectives on anticipatory regulation in digital security.Using a qualitative methodology based on semi-structured expert interviews and ethnographic participant-observation, the study draws on the authors’ involvement in a formally organised programme of academia-industry-government collaboration called Digital Security by Design (DSbD).The study highlights a relational dimension to establishing regulatory responsibilities that is enabled through interdisciplinary dialogue. The study contributes to understanding the multifaceted roles of regulation in digital security innovation across organisations and areas of expertise. It does so by identifying four themes in how regulation is perceived in the DSbD programme: ethical imperative, adding value, adoption lever and passive compliance.Incorporating regulatory responsibilities through dialogue early in the innovation process, rather than only once a security technology’s deleterious effects are noticeable, could make digital innovation and transformation safer and better regulated. It can also make regulation successfully adopted, rather than an exercise in damage control or an adversarial process between regulators and organisations.This paper presents original empirical research on how regulation is considered by stakeholders in a novel multi-disciplinary digital security innovation process. It then uses these findings as a basis to evaluate the implications for establishing regulatory responsibilities for a class of security technologies that are embedded within wider systems and that are largely invisible to most of the users of those wider systems
Does Gas-Phase Sulfur Dioxide Remove Films of Atmosphere-Extracted Organic Material from the Aqueous Aerosol Air-Water Interface?
Get PDFThe reaction of gas-phase SO2 with unsaturated carbon-carbon double bonds forms organosulfates. Previous works have focused on reaction products and not the fate of organic films in the atmosphere. Neutron reflectometry was used to study the interaction of gas-phase SO2 at the air-water interface with organic material extracted from atmospheric particulate matter and pure proxy chemicals to determine whether the reaction of organic films with SO2 removes the film and is there a product film. Films formed from atmospheric aerosol collected in urban and woodland environments typically produced a layer of approximately 0.6 nm thickness, whereas a thick (>40 nm) film was formed by the woodsmoke sample. Fitting of this thicker woodsmoke film suggested a three-layered structure at the interface that has been interpreted to be consistent with a surfactant-rich layer next to the air-water interface, a mid-layer rich in PAH and topped with a more aliphatic region. The multilayer structure of atmospheric extracted material at the air-water interface is potentially an exciting result that requires further study. Gas-Phase SO2 was confirmed to react with pure insoluble surfactant molecules at the air-water interface that contained carbon-carbon double bonds (oleic acid) and did not react with a similar saturated surfactant (stearic acid). No reaction was observed during the interaction of SO2 and atmospheric material extracted from urban and woodland environments, and no material appeared to be removed from the interface; however, films made from woodsmoke-extracted material did appear to be altered by SO2 suggesting a reaction with Poly Aromatic Hydrocarbons (PAHs) but no material was lost from the interface. In addition, the gas-phase ozone levels in the neutron blockhouse, which have historically been of some concern for reactions with organics, were found to be of the order 15ppb, with no evidence of additional production in the neutron beam-path. Owing to a lack of substantial removal of material from real atmospheric extracted films, SO2 is not considered atmospherically significant for the removal of organic films from the air-water interfac
Stability or Stagnation:Non-Monotonic Association Between Party System Closure and Satisfaction with Democracy
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Inductive Venn-Abers Predictive Distributions:New Applications & Evaluation
Get PDFVenn-Abers predictors offer a distribution-free probabilistic framework that generates calibrated predictions from the outputs of scoring classifiers, relying on minimal assumptions about the data distribution. This paper explores the extension of this framework from classification to regression, producing predictive distributions. We show how to evaluate the efficacy of the framework by comparing various metrics that assess the accuracy and informativeness of the predictions. We also show that the framework can be used for real-time prediction, using datasets from predictive maintenance and energy consumption forecasting
Fluidity of Sharīʿa and the Modern State:Inheritance Rights of Childless Widows under Shīʿa Personal Law in British India and Pakistan
Get PDFThe Qurʾān grants a childless widow a one-fourth share in the inheritance of her husband. However, this right is limited to movable property under the Ithnā ʿAsharīyya school in South Asia (India, Pakistan, and Bangladesh). In December 2021, Pakistan’s parliament extended a childless widow’s inheritance right to include immovable property under the Ithnā ʿAsharīyya school. This paper examines the historical processes that contributed to the formulation and subsequent reformulation of the legal rule governing the inheritance right of a childless widow under the Ithnā ʿAsharīyya school. It identifies distinct but interconnected phases in which sharīʿa was transformed within the institutional structure of the modern state during the colonial and post-colonial periods. By doing so, the paper highlights the fluidity of sharīʿa as a legal tradition, which adapted to changing circumstances in different historical contexts
Speech Emotion Recognition Using Convolutional Recurrent Neural Networks
Get PDFResearch suggests that various machine learning and deep learning models can be used for implementation of speech emotion recognition (SER) using different acoustic properties, such as voice, pitch, loudness, intensity, Mel-frequency cepstral coefficients, and spectral characteristics. This chapter conducts speech emotion recognition using deep neural networks, such as long short-term memory, gated recurrent units, and convolutional recurrent neural network. These different acoustic features are investigated in our studies owing to their great efficiency in representing key events in audio representations. A cross-validation evaluation has been conducted with the data from different actors for model evaluation to check the robustness of each proposed network. The proposed models show impressive performances in comparison with those of existing state-of-the-art methods for evaluating several speech emotion datasets
“Unveiling the Invisible”:Deep Learning-based Semantic Segmentation for Analyzing Activity Patterns
Get PDFThe ubiquity of internet-enabled devices has led to a rapid increase in the use of connected cameras for real-time monitoring, creating a high demand for (automated) visual data analytics across various industries. The prospect of automating visual data analysis to drive positive change involves extracting actionable insights from data that will inform decision-making processes, improving efficiency, and contributing to evidence-based strategies across diverse applications and industries. This research explores and compares well-known semantic segmentation models such as DeepLabV3+ and UNet, determining the best-suited for use in a visual analytics and scene understanding, culminating in a proof of concept program capable of automating video analysis, plotting detections, average trajectories, and identifying outliers
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