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2nd International Conference on computing and Information Technology, ICCIT 2022

作者： Shahid, Muhammad Rehman Munir, Asim Ifraheem, Layeba Aldabbas, Hamza Wadood, Abdul Alwada'n, Tariq University of Faisalabad Departmental of Computational Sciences Faislabad Pakistan International Islamic University Department of Computer Science and Software Engineering Islamabad Pakistan Al-Balqa Applied University Prince Abdullah Bin Ghazi Faculty of Information and Communication Technology Al-Salt Jordan School of Computing Engineering Digital Technologies Teesside University Middlesbrough United Kingdom

ISBN: (纸本)9781665436052

A forensic autopsy is a surgical process in which experts collect a deceased body's internal and external information. These death certificates are the source of timely warnings of an increase in disease activity. It's only helpful if accurate and quantitative data is available. Therefore, the Classification of plain text medical autopsy reports reduces the time consumption and irregularities. The motive is to design an automatic text classification system that classifies plain text autopsy reports. Therefore, a methodology proposes using different Automatic Text Classification Techniques (ATC). This technique has embedded Feature Extraction, Feature Representation, and Feature Reduction techniques. These techniques use for the construction of classification models that classify the text of autopsy reports. Data sets collected from these types will be helpful in future experiments. Finally, the performance of the classifier measures by using different Evaluation parameters. These Evaluation Measures are Precision, Recall, Accuracy, and F-measure. © 2022 IEEE.

关键词： Support vector machines

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Effective Entry-Wise Flow for Molecule Generation

Effective Entry-Wise Flow for Molecule Generation

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International Conference on Data engineering

作者： Qifan Zhang Junjie Yao Yuquan Yang Yizhou Shi Wei Gao Xiaoling Wang School of Computer Science and Technology East China Normal University Software Engineering Institute East China Normal University Shanghai Key Laboratory of Trustworthy Computing Department of Chemistry University of Massachusetts Boston University of Michigan Ann Arbor.

ISBN: (数字)9798350317152

ISBN: (纸本)9798350317169

Molecule generation is a critical process in the fields of drug discovery and materials science. Recently, generative models based on normalizing flows have demonstrated significant potential in this domain. These models are particularly suited for handling the symmetrical and complex chemical structures often encountered in molecular datasets. Despite their promising nature, normalizing flow-based models for molecule generation face considerable challenges. The complexity of molecule representation, the rigorous demands of optimization, and the scarcity of training labels in molecular datasets contribute to these difficulties. Additionally, adequately and comprehensively learning the distribution of molecular datasets remains a formidable task. In this paper, we delve into the intricate entry-wise modules in vanilla flows, introducing an effective variation of flow-based models. Our proposed approach innovatively encapsulates affine coupling transformations within normalizing flows. Furthermore, we deconstruct existing invertible flow models, integrating them with newly developed entry-wise transformations. Our experimental studies demonstrate that these proposed entry-wise modules, when incorporated into standard flow-based models, surpass other generative models in performance on various representative datasets and generation tasks. Notably, in the context of low-resourced molecular graph generation, our model achieves remarkable performance compared to its counterparts.

关键词： Training Couplings Materials science and technology Interpolation Data engineering Drug discovery Task analysis

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Metaverse: A Vision, Architectural Elements, and Future Directions for Scalable and Realtime Virtual Worlds

arXiv

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arXiv 2023年

作者： Ismail, Leila Buyya, Rajkumar Lab School of Computing and Information Systems The University of Melbourne Australia Lab Department of Computer Science and Software Engineering National Water and Energy Center United Arab Emirates University United Arab Emirates

With the emergence of Cloud computing, Internet of Things-enabled Human-Computer Interfaces, Generative Artificial Intelligence, and high-accurate Machine and Deep-learning recognition and predictive models, along with the Post Covid-19 proliferation of social networking, and remote communications, the Metaverse gained a lot of popularity. Metaverse has the prospective to extend the physical world using virtual and augmented reality so the users can interact seamlessly with the real and virtual worlds using avatars and holograms. It has the potential to impact people in the way they interact on social media, collaborate in their work, perform marketing and business, teach, learn, and even access personalized healthcare. Several works in the literature examine Metaverse in terms of hardware wearable devices, and virtual reality gaming applications. However, the requirements of realizing the Metaverse in realtime and at a large-scale need yet to be examined for the technology to be usable. To address this limitation, this paper presents the temporal evolution of Metaverse definitions and captures its evolving requirements. Consequently, we provide insights into Metaverse requirements. In addition to enabling technologies, we lay out architectural elements for scalable, reliable, and efficient Metaverse systems, and a classification of existing Metaverse applications along with proposing required future research *** Codes ***, *** © 2023, CC BY.

关键词： Energy efficiency

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Expediting In-Network Federated Learning by Voting-Based Consensus Model Compression

Expediting In-Network Federated Learning by Voting-Based Con...

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IEEE Annual Joint Conference: INFOCOM, IEEE Computer and Communications Societies

作者： Xiaoxin Su Yipeng Zhou Laizhong Cui Song Guo College of Computer Science and Software Engineering Shenzhen University Shenzhen China School of Computing Faculty of Science and Engineering Macquarie University Sydney Australia Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ) Shenzhen University Shenzhen China Department of Computer Science and Engineering The Hong Kong University of Science and Technology HKSAR

ISBN: (数字)9798350383508

ISBN: (纸本)9798350383515

Recently, federated learning (FL) has gained momentum because of its capability in preserving data privacy. To conduct model training by FL, multiple clients exchange model updates with a parameter server via Internet. To accelerate the communication speed, it has been explored to deploy a programmable switch (PS) in lieu of the parameter server to coordinate clients. The challenge to deploy the PS in FL lies in its scarce memory space, prohibiting running memory consuming aggregation algorithms on the PS. To overcome this challenge, we propose Federated Learning in-network Aggregation with Compression (FediAC) algorithm, consisting of two phases: client voting and model aggregating. In the former phase, clients report their significant model update indices to the PS to estimate global significant model updates. In the latter phase, clients upload global significant model updates to the PS for aggregation. FediAC consumes much less memory space and communication traffic than existing works because the first phase can guarantee consensus compression across clients. The PS easily aligns model update indices to swiftly complete aggregation in the second phase. Finally, we conduct extensive experiments by using public datasets to demonstrate that FediAC remarkably surpasses the state-of-the-art baselines in terms of model accuracy and communication traffic.

关键词： Training Data privacy Quantization (signal) Federated learning Computational modeling Memory management Collaboration

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INNSE: Invertible neural network-based DNA image storage with self-correction encoding

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Computational and Structural Biotechnology Journal 2025年 27卷 2492-2502页

作者： Zheng, Yanfen Zhang, Xiaokang Sun, Lijun Cao, Ben Wang, Bin Zhang, Qiang Zheng, Pan School of Computer Science and Technology Dalian University of Technology Liaoning Dalian116024 China The Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education School of Software Engineering Dalian University Liaoning Dalian116622 China Department of Accounting and Information Systems University of Canterbury Upper Riccarton Christchurch8140 New Zealand

DNA storage has become an alternative to silicon-based storage of media. However, when used to store multimodal data such as images, it fails to take full advantage of the characteristics of high correlation and variability present in such data, and currently remains inferior in terms of encoding density and time complexity. It also has the shortcoming of weak performance in terms of error correction methods to address insertion and deletion errors caused by error crosstalk. Therefore, we proposed an invertible neural network-based DNA image storage self-correction encoding method (INNSE) that uses the invertibility of network to perform up-down sampling processing on image and video data, thereby greatly reducing the number of DNA sequences required for data storage. A codebook generator was then designed to encode low-dimensional vectors into DNA sequences that meet various constraints. Finally, a self-correction method was constructed to achieve DNA sequence error correction at the base level without adding any redundant information. Our experimental results showed that, compared to the Yin-Yang algorithm, the encoding density of INNSE was increased by 3×, encoding time complexity was reduced by 95.26%. Under a simulated error rate of 2%, PSNR and SSIM were raised by 80.88% and 63.82%, respectively, proving that INNSE has significant advantages in encoding performance and error correction ability. © 2025

关键词： Network coding

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Innovative Urban Planning for Harnessing Blockchain and Edge Artificial Intelligence for Smart City Solutions

Innovative Urban Planning for Harnessing Blockchain and Edge...

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Intelligent Cyber Physical Systems and Internet of Things (ICoICI), International Conference on

作者： K. E. Purushothaman N. Ragavendran S. P. Ramesh V. Ganesh Karthikeyan G. Uma Maheswari R. Saravanakumar Department of Electronics and Communication Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai Tamil Nadu India Department of Artificial Intelligence and Data Science Engineering RMK College of Engineering and Technology Chennai Tamil Nadu India Department of Computer Science and Engineering School of Computing Science & Engineering Galgotias University Greater Noida Uttar Pradesh India School of Computing (SoC) SASTRA Deemed to be University Thanjavur Tamil Nadu India RMK College of Engineering and Technology Chennai Tamil Nadu India Iconix Software Solution Tirunelveli Tamil Nadu India

ISBN: (数字)9798331540661

ISBN: (纸本)9798331540678

This research explores the potential of blockchain and edge AI to revolutionize smart city planning and management. By incorporating these emerging technologies, cities can address current urban challenges, including traffic congestion, energy management, and data security. This research study highlights the benefits of blockchain, such as simplified processes, reduced costs, enhanced security, and transparency. Additionally, this study reviews the applications of edge AI in smart transportation, focusing on vehicle detection, counting, and identification algorithms. The potential of blockchain technology in smart energy trading, vehicle transfer, and encrypted communication is also discussed. Overall, this research study provides valuable insights for researchers to explore new application areas for blockchain and edge AI in the context of smart cities.

关键词： Smart cities Vehicle detection Scalability Urban planning Edge AI Blockchains Smart transportation Energy management Sustainable development Traffic congestion

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software Development Practice: How Organisation Dynamics Inhibit the Utilization of Process Tools in Small software Companies 10

Software Development Practice: How Organisation Dynamics Inh...

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10th International Conference on software and Information engineering, ICSIE 2021

作者： Tuape, Micheal Hasheela-Mufeti, Victoria Iiyambo, Petrus Kayanda, Anna Kasirinen, Jussi Department of Software Engineering Lappeenranta-Lahti University of Technology Finland Department of Computing Mathematical and Statistical Sciences University of Namibia Namibia Information Systems Department College of Business Education Dar-es Salaam Tanzania United Republic of

ISBN: (纸本)9781450384315

Low-quality software products are synonymous with small software companies, yet thousands of process tools and methods are available, although unfortunately, they remain unutilized. The utilization of these process tools are said to be very challenging to small software companies with the difficulty of adaptability tagged to the context in which the companies operate since the process tools are not designed to take care of the operational context of the small software companies. This survey study was undertaken to empirically investigate the implication of the organizational dynamics on using process tools in SSCs. A total of 115 respondents from Tanzania, Namibia, and Ghana were reached through a structured questionnaire. Our findings reveal that the ad-hoc behaviors and attitude breed a culture that inhibits procedural and process-intensive practices synonymous with most software engineering process tools. This finding is interesting because this area has been underestimated while looking at software practice, yet it is significant in understanding practice in relation to software process tools, significantly how small software companies can be helped to adopt the different tools and also provide a mechanism to help the designers of process tools make tools that are usable in the context of the practice of SSCs. © 2021 ACM.

关键词： Surveys

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Internet Connected Modern Fire Fighting Robot 1

Internet Connected Modern Fire Fighting Robot

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1st International Conference on Advances in Computational Science and engineering, ICACSE 2020

作者： Sabhanayagam, T. Senthil Kumar, T. Narendra, M. Martin Sahayaraj, J. Department of Software Engineering School of Computing SRM Institute of Science and Technology Tamil Nadu Kattankulathur India Department of Electronics and Communication Engineering Siddharth Institute of Engineering and Technology Andhra Pradesh Puttur India Department of Information Technology CMR Engineering College Telangana Hyderabad India Department of Electronics and Communication Engineering Sri Indu College of Engineering and Technology Telangana Sheriguda India

When technological development progresses, human interference has become less common, and machines are being used for diverse activities and humans' health. Currently, fire misfortunes still keep happenings running, place human life and properties at risk, and find fires impossible to save lives. In these situations, a robot is used to defend human lives, property and the world from the flames. This model is an IoT robot which detects fire. The robot may be told regarding its activity and disabled. An air pump or a fire style carbon dioxide pump small stretches. Medium lengths. The combination of fire and carbon monoxide is identified via the mounted sensors that generate a graph. The research is often valuable for supplying supplementary details health officials inhaled over the quantity of hazardous gas the inhabitants of the impacted region over a span such that adequate steps can be taken to repair the injury. © Published under licence by IOP Publishing Ltd.

关键词： Fires

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Novel Approach of Designing of a Low-Cost Artificial Ventilators 1

Novel Approach of Designing of a Low-Cost Artificial Ventila...

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1st International Conference on Advances in Computational Science and engineering, ICACSE 2020

作者： Narendra, M. Sabhanayagam, T. Martin Sahayaraj, J. Senthil Kumar, T. Department of Information Technology CMR Engineering College Telangana Hyderabad India Department of Software Engineering School of Computing SRM Institute of Science and Technology Tamil Nadu Kattankulathur India Department of Electronics and Communication Engineering Sri Indu College of Engineering and Technology Telangana Sheriguda India Department of Electronics and Communication Engineering Siddharth Institute of Engineering and Technology Andhra Pradesh Puttur India

In addition to expected ventilator scarcity, induced by the disease outbreak of COVID-19, several organizations have Low-cost emergency breathing apparatuses have been developed. Pressure-cycled pneumatic ventilators are some of these devices that are easy to be using. The signaling or alert features are produced but often not included, on industrial ventilators. This article reports a simplified, simple electronic pressure-cycled respirator sensor & alert device that measures theoretically efficient parameters such as strain & respiratory rate & sounds of alarm;when the respirator malfunctions. A signal processing is for low complexity. A set of time-varying recursive envelope trackers are used in the algorithm to Signal control from a wired digital pressure sensor Trachea of the client. Measurements on each specimen such that it can operate on virtually every test on a microcontroller. © Published under licence by IOP Publishing Ltd.

关键词： Microcontrollers

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Report from Dagstuhl Seminar 21442: Ensuring the Reliability and Robustness of Database Management Systems

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Datenbank-Spektrum 2022年第3期22卷 261-263页

作者： Rigger, Manuel Böhm, Alexander Christakis, Maria Lo, Eric Department of Computer Science National University of Singapore 13 Computing Drive Singapore Singapore Google Germany GmbH ABC-Str. 19 Hamburg Germany Max Planck Institute for Software Systems Paul-Ehrlich Strasse G 26 Kaiserslautern Germany Department of Computer Science and Engineering The Chinese University of Hong Kong Ho Sin-Hang Eng. Building Hong Kong

In November 2021, Dagstuhl seminar 21442 was bringing together researchers and practitioners from various domains such as of databases, automatic testing, and formal methods to build a common ground and to explore possibilities for systematically improving the state of the art in database management system engineering. The outcome of the seminar was a joint understanding of the specific intricacies of building stateful system software, as well as the identification of several areas of future work. In particular, we believe that database system engineering can both be significantly improved by adopting additional verification techniques and testing tools, and can provide important feedback and additional challenges (e.g. related to state management) to neighboring domains. © 2022, Gesellschaft für Informatik e.V. and Springer-Verlag GmbH Germany, part of Springer Nature.

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