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Capability-based IoT access control using blockchain

Digital Communications and Networks 2021年第4期7卷 463-469页

作者： Yue Liu Qinghua Lu Shiping Chen Qiang Qu Hugo’Connor Kim-Kwang Raymond Choo He Zhang School of Computer Science and Engineering University of New South WalesAustralia Data61 CSIROAustralia Shenzhen Institutes of Advanced Technology Chinese Academy of SciencesChina Department of Information Systems and Cyber Security University of Texas at San AntonioUSA Software Institute Nanjing UniversityChina

Internet of Things(IoT)devices facilitate intelligent service delivery in a broad range of settings,such as smart offices,homes and ***,the existing IoT access control solutions are mainly based on conventional identity management schemes and use centralized *** are knowm security and privacy limitations with such schemes and architectures,such as the single-point failure or surveillance(e.g.,device tracking).Hence,in this paper,we present an architecture for capability-based IoT access control utilizing the blockchain and decentralized identifiers to manage the identity and access control for IoT ***,we propose a protocol to provide a systematic view of system interactions,to improve *** also implement a proof-of-concept prototype of the proposed approach and evaluate the prototype using a real-world use *** evaluation results show that the proposed solution is feasible,secure,and scalable.

关键词： Blockchain Internet of things Capability-based access control Identity management Architecture design

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Career Aura-Smart Resume and Employment Recommender 3

Career Aura-Smart Resume and Employment Recommender

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3rd International Conference on Advancements in Computing, ICAC 2021

作者： Dissanayake, Kavindi Mendis, Senidu Subasinghe, Randula Geethanjana, Dineth Lunugalage, Dilani Kasthurirathna, Dharshana Sri Lanka Institute of Information Technology Computer Systems Engineering Department Malabe Sri Lanka Sri Lanka Institute of Information Technology Information Technology Department Malabe Sri Lanka Sri Lanka Institute of Information Technology Computer Science and Software Engineering Department Malabe Sri Lanka

ISBN: (纸本)9781665408622

Recruitment and Job seeking are two major factors that are directly proportional to each other. Due to the competitive nature of the present world, the process of acquiring the best resource effectively and efficiently has become a challenging aspect for the companies. As a result, modern job portals have become increasingly popular to address the challenges identified in the early recruitment and job search process. The purpose of this research is to introduce an optimal solution to address the ineffective areas identified in the job and recruitment domain which can further enhance the recruitment and job seeking decisions by utilizing deep learning and sentiment analytic approach along with descriptive analysis. The proposed system recommends the relevant job opportunities by omitting the irrelevant job advertisements for job hunters who are interested in the IT job domain while they input their resume to the system and additionally, they can improve their career decisions by adhering to the prediction schemes. Moreover, the system facilitates recruiters to headhunt top talents efficiently once they input job requirements to the system and candidate suggestions are not only made depending on their resume information but also analyzing their LinkedIn endorsements. © 2021 IEEE.

关键词： Deep learning

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Multi-Scale U-Shape MLP for Hyperspectral Image Classification

arXiv

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arXiv 2023年

作者： Lin, Moule Jing, Weipeng Di, Donglin Chen, Guangsheng Song, Houbing The College of Information and Computer Engineering Northeast Forestry University Harbin150040 China The Baidu Co. Ltd Beijing100085 China The Department of Electrical Computer Software and Systems Engineering Embry-Riddle Aeronautical University Daytona BeachFL32114 United States

Hyperspectral images have significant applications in various domains, since they register numerous semantic and spatial information in the spectral band with spatial variability of spectral signatures. Two critical challenges in identifying pixels of the hyperspectral image are respectively representing the correlated information among the local and global, as well as the abundant parameters of the model. To tackle this challenge, we propose a Multi-Scale U-shape Multi-Layer Perceptron (MUMLP) a model consisting of the designed MSC (Multi-Scale Channel) block and the UMLP (U-shape Multi-Layer Perceptron) structure. MSC transforms the channel dimension and mixes spectral band feature to embed the deep-level representation adequately. UMLP is designed by the encoder-decoder structure with multi-layer perceptron layers, which is capable of compressing the large-scale parameters. Extensive experiments are conducted to demonstrate our model can outperform state-of-the-art methods across-the-board on three wide-adopted public datasets, namely Pavia University, Houston 2013 and Houston 2018. Copyright © 2023, The Authors. All rights reserved.

关键词： Image classification

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Automated Test Case Repair Using Language Models

arXiv

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arXiv 2024年

作者： Yaraghi, Ahmadreza Saboor Holden, Darren Kahani, Nafiseh Briand, Lionel School of Electrical Engineering and Computer Science University of Ottawa OttawaONK1N 5N6 Canada Lero The Research Ireland Centre for Software University of Limerick Ireland Department of Systems and Computer Engineering Carleton University OttawaONK1S 5B6 Canada

Ensuring the quality of software systems through testing is essential, yet maintaining test cases poses significant challenges and costs. The need for frequent updates to align with the evolving system under test often entails high complexity and cost for maintaining these test cases. Further, unrepaired broken test cases can degrade test suite quality and disrupt the software development process, wasting developers’ time. To address this challenge, we present TARGET (TEST REPAIR GENERATOR), a novel approach leveraging pre-trained code language models for automated test case repair. TARGET treats test repair as a language translation task, employing a two-step process to fine-tune a language model based on essential context data characterizing the test breakage. To evaluate our approach, we introduce TARBENCH, a comprehensive benchmark we developed covering 45,373 broken test repairs across 59 open-source projects. Our results demonstrate TARGET’s effectiveness, achieving a 66.1% exact match accuracy. Furthermore, our study examines the effectiveness of TARGET across different test repair scenarios. We provide a practical guide to predict situations where the generated test repairs might be less reliable. We also explore whether project-specific data is always necessary for fine-tuning and if our approach can be effective on new projects. © 2024, CC BY.

关键词： software design

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Leveraging Digital Twins and Demand Side Recommender Chatbot for Optimizing Smart Grid Energy Efficiency

Leveraging Digital Twins and Demand Side Recommender Chatbot...

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IEEE Innovative Smart Grid Technologies - Asia (ISGT Asia)

作者： Abiodun E. Onile Juri Belikov Eduard Petlenkov Yoash Levron Department of Software Science Tallinn University of Technology Akadeemia tee 15a Tallinn Department of Computer Systems Tallinn University of Technology Akadeemia tee 15a Tallinn Faculty of Electrical & Computer Engineering Technion—Israel Institute of Technology Haifa Israel

Electricity consumers often face the challenge of selecting an optimal plan for saving energy. Strategic energy management and monitoring plays a key role in overcoming these challenges. Developments around Industry 5.0 powered smart grid proffers adequate solutions which allows end-consumers to monitor their energy performance towards effecting demand side recommendation services. Specific problems where end-users are likely to ignore recommended advice exists, thereby contributing to widening ‘knowledge-action gap’. An ensemble of hybrid digital twins (DT) asset modelling based on ordinary differential equation (ODE) physics engine and data driven recurrent neural network (RNN) prediction approach alongside PageRank based asset behavior scoring algorithm deployed for demand side recommender and generative pre-trained transformers (GPT) based conversational chatbot technology show effectiveness in engaging and extending end-consumers interests in recommended advice. The novelty of the study lies in extending current scope of demand side recommender scheme via conversational chatbot interface for DT of electricity grid assets that better engage and monitors end-user’s energy behavior while offering appropriate energy efficiency advice towards achieving energy conservation goals of smart grid consumers. Extensive experiments, including evaluation of end-user studies, revealed the effectiveness of proposed approach in terms of improved recommendation quality and user engagement towards net electricity demand reduction.

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Applications of Digital Twins for Demand Side Recommendation Scheme with Consumer Comfort Constraints

Applications of Digital Twins for Demand Side Recommendation...

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IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT Europe)

The next evolution of traditional energy systems towards smart grid will require end-consumers to actively participate and make informed decisions regarding their energy usage. Industry 4.0 facilitates such progress by allowing more advanced analytics and creating means for end-consumers and distributed grid assets to be modelled as their Digital twins (DT) equivalents, paving the way for asset-level analytics. Note-worthily, consumers’ comfort is crucial towards promotion of easy adoption of such models from consumers’ perspectives. This study presents the application of hybrid DT and multiagent reinforcement learning models for real-time estimation of end-consumers future energy behaviors while generating actionable recommendation feedback for improving their energy efficiency and enhancing end-user comfort.

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Emerging Role of Industry 5.0 Digital Twins in Demand Response Electricity Market and Applications

Emerging Role of Industry 5.0 Digital Twins in Demand Respon...

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IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT Europe)

Traditional power system is facing challenges demanding new operational requirements to meet targets of Net Zero Emissions by 2050. Aggregators are playing progressively important role in the demand response (DR) electricity market but are often riddled with deep level of market monopoly and lack of transparency/secrecy. Emerging real-time information technology (IT) applications and novel modelling of digital twins (DT) of individual electricity assets are challenging this position by promising improvements and openness that allows TSO direct access to available demand side flexibility. Additionally, DT technologies are facilitating how demand response services are delivered to end-users by allowing individual assets participation at the atomic level. In this study, the application potentials of assets’ DT in participating in the demand response electricity market was examined. Again, an overview of DT applications for DR was conducted. The novelty of this study is highlighted in development of new approach that facilitates individual end-user assets’ contribution to demand response efforts. The research identifies key useful questions that might serve as inspiration for stakeholders and policy-makers to further close existing gaps in the field of DT, smart-grid and demand response.

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Speech Master: Natural Language Processing and Deep Learning Approach for Automated Speech Evaluation 12

Speech Master: Natural Language Processing and Deep Learning...

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12th IEEE Annual Information Technology, Electronics and Mobile Communication Conference, IEMCON 2021

作者： Kooragama, K.G.C.M. Jayashanka, L.R.W.D. Munasinghe, J.A. Jayawardana, K.W. Tissera, Muditha Buddhika, Thilini Sri Lanka Institue of Information Technology Department of Information Technology Malabe Sri Lanka Sri Lanka Institute of Information Technology Department of Computer Systems Engineering Malabe Sri Lanka Sri Lanka Institute of Information Technology Department of Computer Science and Software Engineering Malabe Sri Lanka

ISBN: (纸本)9781665400664

Every English speaker wishes to expertise his/her public speaking skills sharply. However, it is extremely difficult and requires a significant amount of practice and experience on an individual basis. This paper introduces a novel online tool 'Speech Master' to practice and improve public English speech delivering skills in a professional manner. Using natural language processing, machine learning, and deep learning approaches, the proposed system analyzes the user's speech in terms of content, grammatical accuracy, grammatical richness, facial expressions, and flow. The accuracy was checked by comparing actual results taken from experts with the predicted results obtained from the tool. 'Speech Master' achieves an average accuracy of more than 80% and produces a better overall result. This novel tool benefits English speakers all over the world by meeting the demand for a simple and easy-to-use solution for improving or practicing English speech delivery skills;enhancing oratory skills, boosting confidence, and delivering well-articulated speeches. © 2021 IEEE.

关键词： Sentiment analysis

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Nanoinformatics: Opportunities and challenges in the development and delivery of healthcare products in developing countries 4

Nanoinformatics: Opportunities and challenges in the develop...

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4th International Conference on Science and Sustainable Development: Advances in Sciences and Technology for Sustainable Development, ICSSD 2020

作者： Nwankwo, Wilson Ukhurebor, Kingsley Eghonghon Software Engineering and Cyberphysical Systems Unit Department of Computer Science Edo University Iyamho Edo State Nigeria Environmental AndTelecommunication Unit Department of Physics Edo University Iyamho Edo State Nigeria

The world is witnessing sustained effects of information technologies across all works of life. Though some of these influences are markedly negative and detrimental to the socio-economic prospects and progress of the society, the positive effects are often impressive especially where they are integrated for the betterment and greater good of the larger society. One of the fastest growing technologies is nanotechnology. Nanotechnology has numerous prospects and applicability across various sectors ranging from electronics, telecommunications, agriculture and food production, biotechnology and genetics, oil prospecting and production, remote sensing, drug production, to name a few. This novel technology readily finds usefulness and several researches are ongoing, geared at developing new tools and techniques that would improve its acceptance across the concerned domains. It is this quest that has culminated into the ongoing effort in nanoinformatics, an interdisciplinary study and a subdomain of informatics simply regarded as the conscientious application of informatics tools and technologies to the analysis, design and development of systems on the broad spectrum of nanomaterials including their physicochemical and environmental characteristics as well as their interactions, interrelationships, and applications within a given domain. This paper presents a review of some opportunities for individuals, experts, and the society especially in the production of cost-effective nanotechnology-based healthcare products. Notwithstanding the aforesaid opportunities which could be harnessed and sustained in any developing country like Nigeria, this paper identifies and buttresses core challenges that could confront the adoption of good nanoinformatics methodologies. This paper concludes that a developing country (Nigeria in perspective) could benefit from nanoinformatics if there are stronger ties among the key stakeholders involved in healthcare products delivery in the socie

关键词： Developing countries

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The Reliability of Information Sources: Student Perceptions and Educational Opportunities

The Reliability of Information Sources: Student Perceptions ...

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International IEEE Conference and Workshop: Óbuda on Electrical and Power engineering (CANDO-EPE)

作者： Anita Mihalovicsne Kollar Jozsef Katona Department of Software Development and Application Institute of Computer Engineering University of Dunaujvaros Dunaujvaros Hungary Institute of Electronics and Communication Systems Kandó Kálmán Faculty of Electrical Engineering Obuda University Budapest Hungary GAMF Faculty of Engineering and Computer Science John Von Neumann University Kecskemet Hungary Department of Applied Quantitative Methods Faculty of Finance and Accountancy Budapest Business University Budapest Hungary

ISBN: (数字)9798331531119

ISBN: (纸本)9798331531126

The modern digital age demands the skills to be able to assess information. In the current world, access to information and knowledge is abundant from different sources. Indeed, high-quality data are much needed in education and professional development, as the quality and accuracy of information directly influence the process of learning and decision-making. The study aims to investigate the perceptions of computer science students at the University of Dunaújváros related to the credibility of diverse information sources. Within a questionnaire, on a voluntary answer basis, 68 students took part, 59 males and nine females. This work is aimed at assessing the degree to which the surveyed students evaluate information sources based on a five-point Likert scale. The data shows that students find print books and textbooks as the most reliable sources; social media are the least reliable. The study also supports the importance of source credibility evaluation, for which lateral reading techniques and AI-based news source credibility identification systems can be helpful. These findings suggest the necessity of bettering the educational approaches to foster better source criticism skills in the students, especially for online content and social media. The study generally contributes to understanding the information society and helps prepare students to obtain and use reliable and accurate information in their future careers. Using AI-based tools and systems can then further support these educational efforts with robust mechanisms to evaluate information credibility in an ever more complex digital landscape.

关键词： Economics Power engineering Accuracy Social networking (online) engineering profession Education Reliability engineering Information filters Information age Reliability

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