A Systematic review of ontology-based approach and decision-making (DM) to improve public service delivery (PSD)

A systematic review of the DM literature on PSD was performed with the aim to build an operational ontology-based for decision makers. Five public administration journals were screened on the subject with more than 200 articles found. 29 articles were shortlisted, categorised, summarised, and applied to outline the influential factors in DM for PSD. The result of the systematic reviews also provided a brief clarification on the requirement for the creation of a more citizen-centric and coordinated eco-system for efficient PSD underpinned by effective DM

The Curious Country

By definition scientists are an inquisitive lot. But what are the scientific curiosities and concerns on the minds of Australians? What worries them, baffles them, and sets their curiosity meter to 10 out of 10? To find out, the Office of the Chief Scientist (OCS) took the nation’s intellectual temperature, surveying 1186 Australians: men and women aged 18 to 65, from all education levels and locations around Australia. The results frame this book: a collection of essays covering the diverse areas of science Australians are curious about. Edited by eminent science writer Leigh Dayton and including a foreword from Australia’s Chief Scientist, Ian Chubb. The collection covers a range of issues, including food and farming technology, environmental upheaval, health, fuel and energy technology and space exploration

Implementation of SiC Power Electronics for Green Energy Based Electrification of Transportation

Increase in greenhouse gas emission poses a threat to the quality of air thus threatening the future of living beings on earth. A large part of the emission is produced by transport vehicles. Electric vehicles (EVs) are a great solution to this threat. They will completely replace the high usage of hydrocarbons in the transport sector. Energy efficiency and reduced local pollution can also be expected with full implementation of electrification of transportation. However, the current grid is not prepared to take the power load of EV charging if it were to happen readily. Moreover, critics are doubtful about the long-term sustainability of EVs in terms of different supply chain issues. The first step for tackling this problem from a research perspective was to do a thorough review of the details of charging in modern day grid. The downsides and lack of futuristic vision. Findings showed that implementing end to end DC based on green energy aided by SiC power electronics. To prove the findings analysis and modelling was done for SiC based charging network. A similar approach was implemented in EV powertrain development. The implementation of SiC power electronics in charging network showed lesser losses, higher thermal conductivity, lesser charging time. The effect on long term battery health and additional circuit was also observed. The cost of production can be reduced by volume manufacturing that has been discussed. In powertrain analysis and simulation the loss and heat reduction one shown on a component-by-component basis. Therefore, this research proposes a Silicon Carbide based end to end DC infrastructure based completely on solar and wind power. The pollution will further be reduced, and energy demands will be met

The State of AI Ethics Report (June 2020)

These past few months have been especially challenging, and the deployment of technology in ways hitherto untested at an unrivalled pace has left the internet and technology watchers aghast. Artificial intelligence has become the byword for technological progress and is being used in everything from helping us combat the COVID-19 pandemic to nudging our attention in different directions as we all spend increasingly larger amounts of time online. It has never been more important that we keep a sharp eye out on the development of this field and how it is shaping our society and interactions with each other. With this inaugural edition of the State of AI Ethics we hope to bring forward the most important developments that caught our attention at the Montreal AI Ethics Institute this past quarter. Our goal is to help you navigate this ever-evolving field swiftly and allow you and your organization to make informed decisions. This pulse-check for the state of discourse, research, and development is geared towards researchers and practitioners alike who are making decisions on behalf of their organizations in considering the societal impacts of AI-enabled solutions. We cover a wide set of areas in this report spanning Agency and Responsibility, Security and Risk, Disinformation, Jobs and Labor, the Future of AI Ethics, and more. Our staff has worked tirelessly over the past quarter surfacing signal from the noise so that you are equipped with the right tools and knowledge to confidently tread this complex yet consequential domain

Anomaly detection for IoT networks using machine learning

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonThe Internet of Things (IoT) is considered one of the trending technologies today. IoT affects various industries, including logistics tracking, healthcare, automotive and smart cities. A rising number of cyber-attacks and breaches are rapidly targeting networks equipped with IoT devices. This thesis aims to improve security in IoT networks by enhancing anomaly detection using machine learning. This thesis identified the challenges and gaps related to securing the Internet of Things networks. The challenges are network size, the number of devices, the human factor, and the complexity of IoT networks. The gaps identified include the lack of research on signature-based intrusion detection systems used for anomaly detection, in addition to the lack of modelling input parameters required for anomaly detection in IoT networks. Furthermore, there is a lack of comparison of the performance of machine learning algorithms on standard and real IoT datasets. This thesis creates a dataset to test the anomaly binary classification performance of the Neural Networks, Gaussian Naive Bayes, Support Vector Machine, and Decision Trees machine learning algorithms and compares their results with the KDDCUP99 dataset. The results show that Support Vector Machine and Gaussian Naive Bayes perform lower than the other models on the created IoT dataset. This thesis reduces the number of features required by machine learning algorithms for anomaly detection in the IoT networks to five features only, which resulted in reduced execution time by an average of 58%. This thesis tests CNNwGFC, which is an enhanced Convolutional Neural Network model, in detecting and classifying anomalies in IoT networks. This model achieves an increase of 15.34% in the accuracy for IoT anomaly classification in the UNSW-NB15 compared to the classic Convolutional Neural Network. The CNNwGFC multi-classification accuracy (96.24%) is higher by 7.16 than the highest from the literature

The Curious Country

By definition scientists are an inquisitive lot. But what are the scientific curiosities and concerns on the minds of Australians? What worries them, baffles them, and sets their curiosity meter to 10 out of 10? To find out, the Office of the Chief Scientist (OCS) took the nation’s intellectual temperature, surveying 1186 Australians: men and women aged 18 to 65, from all education levels and locations around Australia. The results frame this book: a collection of essays covering the diverse areas of science Australians are curious about. Edited by eminent science writer Leigh Dayton and including a foreword from Australia’s Chief Scientist, Ian Chubb. The collection covers a range of issues, including food and farming technology, environmental upheaval, health, fuel and energy technology and space exploration

Toward a Bio-Inspired System Architecting Framework: Simulation of the Integration of Autonomous Bus Fleets & Alternative Fuel Infrastructures in Closed Sociotechnical Environments

Cities are set to become highly interconnected and coordinated environments composed of emerging technologies meant to alleviate or resolve some of the daunting issues of the 21st century such as rapid urbanization, resource scarcity, and excessive population demand in urban centers. These cybernetically-enabled built environments are expected to solve these complex problems through the use of technologies that incorporate sensors and other data collection means to fuse and understand large sums of data/information generated from other technologies and its human population. Many of these technologies will be pivotal assets in supporting and managing capabilities in various city sectors ranging from energy to healthcare. However, among these sectors, a significant amount of attention within the recent decade has been in the transportation sector due to the flood of new technological growth and cultivation, which is currently seeing extensive research, development, and even implementation of emerging technologies such as autonomous vehicles (AVs), the Internet of Things (IoT), alternative xxxvi fueling sources, clean propulsion technologies, cloud/edge computing, and many other technologies. Within the current body of knowledge, it is fairly well known how many of these emerging technologies will perform in isolation as stand-alone entities, but little is known about their performance when integrated into a transportation system with other emerging technologies and humans within the system organization. This merging of new age technologies and humans can make analyzing next generation transportation systems extremely complex to understand. Additionally, with new and alternative forms of technologies expected to come in the near-future, one can say that the quantity of technologies, especially in the smart city context, will consist of a continuously expanding array of technologies whose capabilities will increase with technological advancements, which can change the performance of a given system architecture. Therefore, the objective of this research is to understand the system architecture implications of integrating different alternative fueling infrastructures with autonomous bus (AB) fleets in the transportation system within a closed sociotechnical environment. By being able to understand the system architecture implications of alternative fueling infrastructures and AB fleets, this could provide performance-based input into a more sophisticated approach or framework which is proposed as a future work of this research

Social work with airports passengers

Social work at the airport is in to offer to passengers social services. The main methodological position is that people are under stress, which characterized by a particular set of characteristics in appearance and behavior. In such circumstances passenger attracts in his actions some attention. Only person whom he trusts can help him with the documents or psychologically