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International Conference on Green engineering Technology and Applied Computing 2019, IConGETech2 019 and International Conference on Applied Computing 2019, ICAC 2019

作者： Nor Azhar, A. Rahmah, M. Roslina, A.H. Fauziah, Z. Department of Computer Science Faculty of Computer Systems and Software Engineering Universiti Malaysia Pahang Lebuhraya Tun Razak Gambang Pahang Kuantan26300 Malaysia Department of Graphic and Multimedia Technology Faculty of Computer Systems and Software Engineering Universiti Malaysia Pahang Lebuhraya Tun Razak Gambang Pahang Kuantan26300 Malaysia Department of Software Engineering Faculty of Computer Systems and Software Engineering Universiti Malaysia Pahang Lebuhraya Tun Razak Gambang Pahang Kuantan26300 Malaysia

In a green environment, air quality is among the prominent aspects to be considered to prevent pollution and in turn maintain safe air. Sick Building Syndrome (SBS) and Building Related Illness (BRI) are the problems that must be encountered by building occupants. Existing devices are quite expensive, and more attention is needed on monitoring air quality. Therefore, this paper discusses a software-hardware architecture proposal to overcome the existing IAQ data retrieval performance problem. The objective of this work is to analyse the most recent IAQ sensing device developed by the researcher, to evaluate the performance attribute, and to implement the software-hardware architecture based on the Performance-Driven software Architecture Refactoring (PDSAR) method. In order to assess the overall performance of the architecture proposed, the prototype of the Indoor Air Quality (IAQ) sensing device was developed. The testing was performed during a period of six months. The results demonstrate that the average performance for 540 readings is 76.67%. This shows that the architecture can be accepted as a generic IAQ sensing device development structure. The device act as an alternative, cheaper and safer device which can be employed by all building owners in the future. © 2019 Published under licence by IOP Publishing Ltd.

关键词： Air quality

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When Quantum Information Technologies Meet Blockchain in Web 3.0

arXiv

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arXiv 2022年

作者： Xu, Minrui Ren, Xiaoxu Niyato, Dusit Kang, Jiawen Qiu, Chao Xiong, Zehui Wang, Xiaofei Leung, Victor C.M. School of Computer Science and Engineering Nanyang Technological University Singapore College of Intelligence and Computing Tianjin University Tianjin300072 China Shenzhen518000 China School of Automation Guangdong University of Technology China Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore487372 Singapore College of Computer Science and Software Engineering Shenzhen University Shenzhen518061 China Department of Electrical and Computer Engineering The University of British Columbia VancouverBCV6T 1Z4 Canada

With the drive to create a decentralized digital economy, Web 3.0 has become a cornerstone of digital transformation, developed on the basis of computing-force networking, distributed data storage, and blockchain. With the rapid realization of quantum devices, Web 3.0 is being developed in parallel with the deployment of quantum cloud computing and quantum Internet. In this regard, quantum computing first disrupts the original cryptographic systems that protect data security while reshaping modern cryptography with the advantages of quantum computing and communication. Therefore, in this paper, we introduce a quantum blockchain-driven Web 3.0 framework that provides information-theoretic security for decentralized data transferring and payment transactions. First, we present the framework of quantum blockchain-driven Web 3.0 with future-proof security during the transmission of data and transaction information. Next, we discuss the potential applications and challenges of implementing quantum blockchain in Web 3.0. Finally, we describe a use case for quantum non-fungible tokens (NFTs) and propose a quantum deep learning-based optimal auction for NFT trading to maximize the achievable revenue for sufficient liquidity in Web 3.0. In this way, the proposed framework can achieve proven security and sustainability for the next-generation decentralized digital society. © 2022, CC BY.

关键词： Blockchain

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Bias-corrected peaks-over-threshold estimation of the CVaR

arXiv

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arXiv 2021年

作者： Troop, Dylan Godin, Frédéric Yu, Jia Yuan Department of Computer Science and Software Engineering Concordia University Montreal Canada Department of Mathematics and Statistics Concordia University Montreal Canada Concordia Institute of Information Systems Engineering Concordia University Montreal Canada Quantact Actuarial and Financial Mathematics Laboratory Montreal Canada

The conditional value-at-risk (CVaR) is a useful risk measure in fields such as machine learning, finance, insurance, energy, etc. When measuring very extreme risk, the commonly used CVaR estimation method of sample averaging does not work well due to limited data above the value-at-risk (VaR), the quantile corresponding to the CVaR level. To mitigate this problem, the CVaR can be estimated by extrapolating above a lower threshold than the VaR using a generalized Pareto distribution (GPD), which is often referred to as the peaks-over-threshold (POT) approach. This method often requires a very high threshold to fit well, leading to high variance in estimation, and can induce significant bias if the threshold is chosen too low. In this paper, we derive a new expression for the GPD approximation error of the CVaR, a bias term induced by the choice of threshold, as well as a bias correction method for the estimated GPD parameters. This leads to the derivation of a new estimator for the CVaR that we prove to be asymptotically unbiased. In a practical setting, we show through experiments that our estimator provides a significant performance improvement compared with competing CVaR estimators in finite samples. As a consequence of our bias correction method, it is also shown that a much lower threshold can be selected without introducing significant bias. This allows a larger portion of data to be be used in CVaR estimation compared with the typical POT approach, leading to more stable estimates. As secondary results, a new estimator for a second-order parameter of heavy-tailed distributions is derived, as well as a confidence interval for the CVaR which enables quantifying the level of variability in our estimator. Copyright © 2021, The Authors. All rights reserved.

关键词： Value engineering

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A Brief Review of Explainable Artificial Intelligence in Healthcare

arXiv

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arXiv 2023年

作者： Sadeghi, Zahra Alizadehsani, Roohallah Cifci, Mehmet Akif Kausar, Samina Rehman, Rizwan Mahanta, Priyakshi Bora, Pranjal Kumar Almasri, Ammar Alkhawaldeh, Rami S. Hussain, Sadiq Alatas, Bilal Shoeibi, Afshin Moosaei, Hossein Hladík, Milan Nahavandi, Saeid Pardalos, Panos M. Institute for Big Data Analytics Faculty of Computer Science Dalhousie University Canada Deakin University Geelong Australia The Institute of Computer Technology Tu Wien University Vienna1040 Austria University of Kotli Azad Jammu and Kashmir Azad Kashmir Kotli Pakistan Centre for Computer Science and Applications Dibrugarh University Assam India Department of Management Information Sys Al-Balqa Applied University Salt19117 Jordan Department of Computer Information Systems The University of Jordan Aqaba77110 Jordan Examination Branch Dibrugarh University Assam Dibrugarh India Department of Software Eng. Firat University Elazig23100 Turkey Data Science and Computational Intelligence Institute University of Granada Spain Department of Informatics Faculty of Science Jan Evangelista Purkyně University in Ústí nad Labem Czech Republic Department of Applied Mathematics School of Computer Science Faculty of Mathematics and Physics Charles University Prague Czech Republic Harvard Paulson School of Engineering and Applied Sciences Harvard University AllstonMA02134 United States Center for Applied Optimization Department of Industrial and Systems Engineering University of Florida Gainesville32611 United States

XAI refers to the techniques and methods for building AI applications which assist end users to interpret output and predictions of AI models. Black box AI applications in high-stakes decision-making situations, such as medical domain have increased the demand for transparency and explainability since wrong predictions may have severe consequences. Model explainability and interpretability are vital successful deployment of AI models in healthcare practices. AI applications' underlying reasoning needs to be transparent to clinicians in order to gain their trust. This paper presents a systematic review of XAI aspects and challenges in the healthcare domain. The primary goals of this study are to review various XAI methods, their challenges, and related machine learning models in healthcare. The methods are discussed under six categories: Features-oriented methods, global methods, concept models, surrogate models, local pixel-based methods, and human-centric methods. Most importantly, the paper explores XAI role in healthcare problems to clarify its necessity in safety-critical applications. The paper intends to establish a comprehensive understanding of XAI-related applications in the healthcare field by reviewing the related experimental results. To facilitate future research for filling research gaps, the importance of XAI models from different viewpoints and their limitations are investigated. © 2023, CC BY-NC-ND.

关键词： Decision making

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Automatic Programming: Large Language Models and Beyond

引用

ACM Transactions on software engineering and Methodology 2025年第5期34卷

作者： Lyu, Michael R. Ray, Baishakhi Roychoudhury, Abhik Tan, Shin Hwei Thongtanunam, Patanamon Department of Computer Science and Engineering The Chinese University of Hong Kong Hong Kong Hong Kong Computer Science Columbia University New YorkNY United States Computer Science National University of Singapore Singapore Singapore Computer Science and Software Engineering Concordia University Montreal Canada School of Computing and Information Systems University of Melbourne Melbourne Australia

Automatic programming has seen increasing popularity due to the emergence of tools like GitHub Copilot which rely on Large Language Models (LLMs). At the same time, automatically generated code faces challenges during deployment due to concerns around quality and trust. In this article, we study automated coding in a general sense and study the concerns around code quality, security, and related issues of programmer responsibility. These are key issues for organizations while deciding on the usage of automatically generated code. We discuss how advances in software engineering such as program repair and analysis can enable automatic programming. We conclude with a forward looking view, focusing on the programming environment of the near future, where programmers may need to switch to different roles to fully utilize the power of automatic programming. Automated repair of automatically generated programs from LLMs can help produce higher assurance code from LLMs, along with evidence of assurance. © 2025 Association for Computing Machinery. All rights reserved.

关键词： Automatic programming

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The Importance Of Security In Cyber-Physical System

The Importance Of Security In Cyber-Physical System

引用

IEEE World Forum on Internet of Things (WF-IoT)

作者： Faisal alrefaei Department of Electrical Computer Software and Systems Engineering Embry-Riddle Aeronautical University Daytona Beach FL

ISBN: (数字)9781728155036

ISBN: (纸本)9781728155043

There is a term more common and used on the full range between industries and authors, which is a cyber-physical system(CPS). It is a system that applied to smart grid, medical devices, and manufactory and civil infrastructure. CPS consists of three main components, which are sensors, actuators that connected by a network. Recently, we have seen there is a vast increase by using cyber-physical system, so the security of this system is critical at design more than any policy. The security of this sort of operation must be vital and reaching a high level of protection [2],[3],[13]. The security of this system includes some techniques to be used, such as attack detection attack design and secure estimation. As a result of that, the necessitate of security in this system is required. Hence, we address and collected issues and solutions. This paper analyzes and shows how we can prevent this system from unauthorized access or damages that would happen during the process. Also, it shows some examples and how some solutions are useful and valuable [21].

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Federated Learning-Based Intelligent Indoor Smoke and Fire Detection System for Smart Buildings

Federated Learning-Based Intelligent Indoor Smoke and Fire D...

引用

Telecommunications and Intelligent systems (ICTIS), International Conference on

作者： Mohamed Rafik Aymene Berkani Ammar Chouchane Yassine Himeur Anes Abdennebi Seref Sagiroglu Abbes Amira Research Laboratory in Advanced Electronics Systems (LSEA) University Yahia Fares of Medea Medea Algeria Laboratory of LI3C University Biskra University Center of Barika Barika Algeria College of Engineering and Information Technology University of Dubai Dubai United Arab Emirates Software and Information Technology Engineering École de Technologie Supérieure Montréal Canada Artificial Intelligence and Big Data Analytics Security R&D Center Gazi University Ankara Turkey Department of Computer Science University of Sharjah Sharjah United Arab Emirates

ISBN: (数字)9798331527396

ISBN: (纸本)9798331527402

Ensuring safety in smart buildings is crucial due to the increasing prevalence of smoke and fire hazards in modern environments. This paper introduces a novel privacy-preserving FL approach based on a CNN1D for smoke and fire detection in smart buildings. Our system integrates data from wearable environmental sensors to train a lightweight, edge-deployable DL-CNN1D model, ensuring data privacy while enabling collaborative learning across distributed clients using Federated Averaging (FedAvg) aggregation. Experiments conducted on a comprehensive air measurement dataset for smoke and fire detection demonstrate exceptional performance, with the global model achieving 99.97% accuracy, 99.96% precision, in smoke and fire recognition. Our model demonstrates a low communication cost of 0.4 MB, underscoring its efficiency for real-time applications. Our FL-based approach represents a significant step towards balancing the need for robust safety systems with growing privacy concerns in smart building environments.

关键词： Privacy Smart buildings Costs Federated learning Atmospheric modeling Data models Convolutional neural networks Wearable sensors Monitoring Intelligent sensors

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Innovation, Research and Development in engineering Education. Activities of the Spanish Chapter of the IEEE Education Society: Directive Board of the IEEE Education Society Spanish Chapter 2020-2021

Innovation, Research and Development in Engineering Educatio...

引用

Technologies Applied to Electronics Teaching (TAEE)

作者： Ó scar Martí nez Bonastre Cristina Ferná ndez Lluí s Vicent Francisco Mur Manuel Castro Gabriel Diaz Jose Carpio Elio Sancristobal Sergio Martin Jose Sá nchez Francisco Javier Arcega Solsona Juan Suardiaz Muro Manuel Caeiro-Rodrí guez Martí n Llamas Inmaculada Plaza Baltasar Ferná ndez Manjó n Pedro Muñ oz-Merino Edmundo Tovar Telmo Zarraonandia Ayo Javier Garcia Zubia José Antonio Delgado Pení n Department of Statistics Mathematics and Computing Science Operations Research Centre Universidad Miguel Hern&#x00E1 ndez Elche Spain Department of Electronic Technology Universidad Carlos III de Madrid Madrid Spain UPF Barcelona School of Management Barcelona Spain Department of Electrical Electronic and Control Engineering UNED Madrid Spain Department of Electrical Engineering Universidad de Zaragoza Zaragoza Spain Department of Automatics Electrical Engineering and Electronic Technology Technical University of Cartagena Cartagena Spain atlanTTic Research Center University of Vigo Vigo Spain Department of Electronics and Communication Universidad de Zaragoza Zaragoza Spain Department of Software Engineering and Artificial Intelligence Complutense University of Madrid Madrid Spain Department of Telematic Engineering Universidad Carlos III de Madrid Madrid Spain Department of Computer Languages and Systems and Software Engineering Universidad Polit&#x00E9 cnica de Madrid Madrid Spain Department of Computer Science and Engineering Universidad Carlos III de Madrid Madrid Spain Department of Electronic Engineering Universidad de Deusto Bilbao Spain Universitat Polit&#x00E8 cnica de Catalunya Barcelona Spain

ISBN: (数字)9781665421614

ISBN: (纸本)9781665421621

The Technical Committee of the CESEI (Spanish Chapter of the IEEE Education Society) is focused on the Innovation, Research and Development (I+R+D) of the education in engineering, mainly Electric and computer engineering. As in other interdisciplinary fields, the I+R+D involves several sources of information and different stakeholders, each one with its own focus and purpose. As a result, sometimes it may be complex for practitioners and researchers to identify the more appropriate entities for their interests. This paper shows how the CESEI Technical Committee tries to solve this difficulty by providing updated information regarding the main publications (journals), events (conferences) and awards to the best academic works. The paper focuses special attention on the activities held during 2020–2021.

关键词： Technological innovation Collaboration Stakeholders engineering education Research and development

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Quantum-optimal Frequency Estimation of Stochastic AC Fields

arXiv

引用

arXiv 2024年

作者： Dey, Anirban Mouradian, Sara Lupo, Cosmo Huang, Zixin School of Mathematical and Physical Sciences Macquarie University NSW2109 Australia ARC Centre of Excellence for Engineered Quantum Systems Macquarie University NSW2109 Australia Department of Electrical and Computer Engineering University of Washington 98195 United States Dipartimento Interateneo di Fisica Politecnico di Bari Bari70126 Italy Dipartimento Interateneo di Fisica Università di Bari Bari70126 Italy INFN Sezione di Bari Bari70126 Italy Centre for Quantum Software and Information Faculty of Engineering and Information Technology University of Technology SydneyNSW2007 Australia

Classically, measurement bandwidth limits the achievable frequency resolution of stochastic time-dependent fields. We frame the problem of frequency measurement as the estimation of the noise parameter of a dephasing quantum channel. Using this framework, we find an exact upper bound for estimating frequency centroids and separations. In particular, given two closely separated frequencies with separation ωr, the quantum Fisher information (QFI) upper bound is approximately 2/ωr2, inversely proportional to the separation parameter. We show that this is achievable with a superposition of Dicke states, and show that GHZ states improve precision over unentangled states, achieving Heisenberg scaling in the low-bandwidth limit. This work established a robust framework for stochastic AC signal sensing and can be extended to an arbitrary number of frequencies. Copyright © 2024, The Authors. All rights reserved.

关键词： Bandwidth

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A framework for managing enterprise architecture debts - Outline and research directions 10

A framework for managing enterprise architecture debts - Out...

引用

10th International Workshop on Enterprise Modeling and Information systems Architectures, EMISA 2020

作者： Alexander, Peter Hacks, Simon Jung, Jürgen Lichter, Horst Steffens, Ulrike Uludağ, Ömer RWTH Aachen University Research Group Software Construction Aachen Germany KTH Royal Institute of Technology Network and Systems Engineering Stockholm Sweden Frankfurt University of Applied Sciences Faculty of Computer Science and Engineering Frankfurt Germany Hamburg University of Applied Sciences Department of Computer Science Hamburg Germany Technical University of Munich Department of Informatics Munich Germany

Even though enterprise architecture management (EAM) offers a wide range of methods and tools for aligning business with IT, an architect’s work is challenged by reality. The evolution of enterprise architecture (EA) and given constraints (e.g. legacy systems and processes) lead to debts which may complicate and hinder opportunities;however, the management of such debts has not been considered in EAM research. This paper presents a framework for strategically managing EA-debt-related issues and propose open questions as well as future research directions in this field. Copyright © 2020 for this paper by its authors.

关键词： Legacy systems

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