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1st Mohammad Ali Jinnah University International Conference on Computing, MAJICC 2021

作者： Kanwal, Samina Rashid, Junaid Nisar, Muhammad Wasif Kim, Jungeun Hussain, Amir COMSATS University Islamabad Department of Computer Science Wah Campus Pakistan Kongju National University Department of Computer Science and Engineering Korea Republic of Edinburgh Napier University Data Science and Cyber Analytics Research Group EdinburghEHI 4DY United Kingdom

ISBN: (纸本)9781665424134

Heart disease is the world's leading cause of increasing death rates. Although there is a lot of research in the medical sector, an efficient and reliable model to predict this disease at an early stage is still required. So, early diagnosis of heart disease is the most promising strategy for effective treatment. In this paper, we utilize the Genetic algorithm (GA) to select attributes, which are used as input for the machine learning algorithms Deep Learning(DL), Support Vector Machine (SVM), Neural network (NN), Naive Bayes (NB), and Logistic regression (LR). The two datasets of heart disease are used for model implementation. The results evaluation is measured using accuracy, precision, and f-measure. The proposed model achieves the 92% result in the term of accuracy. In terms of precision, 96% result is achieved. © 2021 IEEE.

关键词： Genetic algorithms

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Managing dynamic enterprise and urgent workloads on clouds using layered queuing and historical performance models

Managing dynamic enterprise and urgent workloads on clouds u...

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作者： Bacigalupo, David A. Van Hemert, Jano Chen, Xiaoyu Usmani, Asif Chester, Adam P. He, Ligang Dillenberger, Donna N. Wills, Gary B. Gilbert, Lester Jarvis, Stephen A. School of Electronics and Computer Science University of Southampton United Kingdom Data-Intensive Research Group School of Informatics University of Edinburgh United Kingdom BRE Centre for Fire Safety Engineering School of Engineering University of Edinburgh United Kingdom IBM T.J. Watson Research Centre Yorktown Heights NY United States High Performance Systems Group Department of Computer Science University of Warwick United Kingdom

The automatic allocation of enterprise workload to resources can be enhanced by being able to make what-if response time predictions whilst different allocations are being considered. We experimentally investigate an historical and a layered queuing performance model and show how they can provide a good level of support for a dynamic-urgent cloud environment. Using this we define, implement and experimentally investigate the effectiveness of a prediction-based cloud workload and resource management algorithm. Based on these experimental analyses we: (i) comparatively evaluate the layered queuing and historical techniques;(ii) evaluate the effectiveness of the management algorithm in different operating scenarios;and (iii) provide guidance on using prediction-based workload and resource management. © 2011 Elsevier B.V. All rights reserved.

关键词： Resource allocation

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Enhancing Android Storage Management and Efficiency with Network Block Device (Nbd) Protocol: An Empirical Analysis

SSRN

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SSRN 2024年

作者： Rahman, Tanvir Ahmed, Tanjid Sakibur, Md. Rahman Hossain, Amreen Noor, Jannatun Research Group Department of Computer Science and Engineering School of Data and Sciences BRAC University Dhaka Bangladesh

The NBD (Network Block Device) protocol is crucial for enhancing the Android ecosystem's storage management and power efficiency, particularly on ARM devices. The study addresses storage limitations on ARM devices and explores how NBD can provide a solution. By leveraging NBD, Android devices can connect to remote storage resources and expand storage capacity without physical upgrades. This enables Android devices to be used as controllers for IoT networks and smart home appliances. The study includes statistical comparisons of NBD with alternative protocols like sFTP, iSCSI, NFS, SMB, and HTTP. Through read-and-write tests, NBD exhibits superior performance in bandwidth speed and operation duration, with speeds more than twice as fast as other protocols. Furthermore, the evaluation compares NBD's cloud storage capabilities with popular services such as Google Drive, Dropbox, OneDrive, and GCP. NBD outperforms these services regarding read and write speeds, completing operations much faster. The study also examines NBD's power consumption, demonstrating its energy efficiency compared to other protocols and cloud storage services. NBD consumes significantly less power, making it an ideal choice for energy-conscious Android devices. In conclusion, the integration of NBD into the Android ecosystem enhances efficiency, storage flexibility, and adaptability. It empowers ARM-based Android devices with increased capabilities and versatility. © 2024, The Authors. All rights reserved.

关键词： Energy efficiency

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Design of Blockchain based e-Voting System for Vote Requirements

Design of Blockchain based e-Voting System for Vote Requirem...

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5th International Conference on data Mining, Communications and Information Technology, DMCIT 2021

作者： Choi, Seiwoong Kang, Jihun Chung, Kwang Sik Graduate School Dept. of Information Science Korea National Open University Jongno-gu Dongsung-Dong Seoul Korea Republic of BK 21 Data-Driven Science Future Talent Education Research Group Dept of Computer Science and Engineering Korea University Seoul Korea Republic of Dept. of Computer Science Korea National Open University Jongno-gu Dongsung-Dong Seoul Korea Republic of

Voting refers to the submission of an election or an opinion on a specific matter by expressing an intention on the ballot to a certain place. The existing voting method has the burden of counting time and cost. For this reason, research has been conducted to introduce an e-voting system. However, despite the advantages of e-voting, it is not widely used due to the risk of manipulation of voting results and various requirements. Recently, in order to reduce the risk of data manipulation, research is being conducted to apply the blockchain, a technology that guarantees data integrity, to e-voting. Blockchain guarantees the integrity of data, but has a weakness in secrecy. This paper applies the critical encryption technique to the blockchain and satisfies the requirements for voting such as verifiability, anonymity, fairness, non-reusability, competence, safety, transparency, and non-ticketing. We propose a system design and implementation method. The proposed blockchain-based e-voting system provides voter anonymity by issuing a voter certificate based on a blockchain address. The e-voting election monitoring committee generates a threshold group encryption key, and the proposed blockchain-based e-voting system guarantees confidentiality by a threshold group encryption algorithm during the voting process. The voting result is encrypted through a homomorphic encryption algorithm and stored in the blockchain. Thus, the released voting results ensure safety, confidentiality, transparency, and non-vote ticketing. In addition, the proposed blockchain-based e-voting system guarantees the unity and competence of voting through the blockchain's smart contract. © Published under licence by IOP Publishing Ltd.

关键词： Transparency

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Aerial Flood Scene Classification Using Fine-Tuned Attention-based Architecture for Flood-Prone Countries in South Asia

arXiv

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arXiv 2024年

作者： Hassan, Ibne Mujahid, Aman Al Hasib, Abdullah Shagoto, Andalib Rahman Mondal, Joyanta Jyoti Manab, Meem Arafat Noor, Jannatun Research Group Department of Computer Science and Engineering School of Data and Sciences BRAC University Dhaka Bangladesh

Countries in South Asia experience many catastrophic flooding events regularly. It takes time to execute Search and Rescue (SAR) missions in such flooded areas. With the help of image classification, it is possible to expedite such initiatives by classifying flood zones and other locations of interest like houses and humans within such regions. In this paper, we propose a new dataset to enhance SAR by collecting various aerial imagery of flooding events across South Asian countries. For the classification, we propose a fine-tuned Compact Convolutional Transformer (CCT) based approach and some other cutting-edge transformer-based and Convolutional Neural Network-based architectures (CNN). We also implement the YOLOv8 object detection model and detect houses and humans within the imagery of our proposed dataset, and then compare the performance with our classification-based approach. Since the countries in South Asia have similar topography, housing structure, the color of flood water, and vegetation, this work can be more applicable to such a region as opposed to the rest of the world. The images are divided evenly into four classes: 'flood', 'flood with domicile', 'flood with humans', and 'no flood'. After experimenting with our proposed dataset on our fine-tuned CCT model, which has a comparatively lower number of weight parameters than many other transformer-based architectures designed for computer vision, it exhibits an accuracy and macro average precision of 98.62% and 98.50%. The other transformer-based architectures that we implement are the Vision Transformer (ViT), Swin Transformer, and External Attention Transformer (EANet), which give an accuracy of 88.66%, 84.74%, and 66.56% respectively. We also implement DCECNN (Deep Custom Ensembled Convolutional Neural Network), which is a custom ensemble model that we create by combining MobileNet, InceptionV3, and EfficientNetB0, and we obtain an accuracy of 98.78%. The architectures we implement are fine-tuned to

关键词： Aerial photography

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Multi-scale Variable Window Attention Network for Continuous Sign Language Recognition

Multi-scale Variable Window Attention Network for Continuous...

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2024 International Conference on Cyber-Physical Social Intelligence, ICCSI 2024

作者： Zhang, Nan Wei, Chao Guo, Leming Cheng, Zeyu Zhao, Zhao Wu, Yangcan Xue, Wanli Tianjin University of Technology School of Computer Science and Engineering Tianjin China Tianjin Emergency Centre Tianjin China Tianjin University of Technology School of Mechanical Engineering Tianjin China Shaanxi Big Data Group Co. Ltd Shaanxi China Industry Research Institute Co Shaanxi Logistics Group Shaanxi China

ISBN: (纸本)9798350376739

Sign language is primarily conveyed through hands and face movements. Therefore, a pivotal challenge in continuous sign language recognition (CSLR) is the meticulous modeling and interpreting of visual cues emanating from hands and facial movements. However, contemporary CSLR methods have exhibited limitations in adequately capturing information from both the hands and facial regions, often overlooking the continuity, and correlations across multiple consecutive frames. To mitigate these shortcomings, we propose the Multi-scale Variable Window Attention Network (MVAN). This framework fuses the strengths of an improved Efficient Multi-scale Attention (iEMA) with Variable Window Adaptation (VWA) attention. Specifically, iEMA first scans information spatially at multiple scales to simultaneously capture information from areas such as hands and faces, and models spatial continuity interactions between them, enhancing spatial features. Secondly, VWA dynamically changes its window size at the temporal level to adaptively capture complex temporal changes in hands and face movements in successive frames. Thus, VWA can effectively model the continuity and correlation between hands and face movements to have the ability to capture sign language movements of different lengths. Comprehensive experimental results demonstrate that our proposed MVAN strengthens the visual feature extraction of hands and face, improving the recognition performance. © 2024 IEEE.

关键词： Convolutional neural networks

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A two-sided iterative framework for model reduction of linear systems with quadratic output

A two-sided iterative framework for model reduction of linea...

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IEEE Conference on Decision and Control

作者： Ion Victor Gosea Athanasios C. Antoulas Data-Driven Reduction and Identification Group Max Planck Institute for Dynamics of Complex Technical Systems Magdeburg Germany Department of Electrical and Computer Engineering Rice University Houston USA

ISBN: (数字)9781728113982

ISBN: (纸本)9781728113999

We propose a model reduction procedure for approximating large-scale linear systems with quadratic output by means of lower dimensional systems with the same structure. The framework is based on an iteration that, at each step, computes left and right projections matrices (hence two-sided). This is done by means of solving two linear Sylvester equations.

关键词： Linear systems Mathematical model Computational modeling Observability Symmetric matrices Kernel Numerical models

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Singular perturbation control for vibration rejection in HDDs with a PZT active suspension

Singular perturbation control for vibration rejection in HDD...

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45th IEEE Conference on Decision and Control 2006, CDC

作者： Pang, Chee Khiang Lewis, Frank L. Ge, Sam Shuzhi Guo, Xiao Chen, Ben M. Lee, Tong Heng IEEE Central Research Laboratory Research and Development Group Hitachi Ltd. 2880 Kozu Odawara Kanagawa 256-8510 Japan A STAR Data Storage Institute Singapore Singapore Department of Electrical and Computer Engineering National University of Singapore Singapore Singapore Advanced Controls and Sensors Group Automation and Robotics Research Institute University of Texas Arlington United States

ISBN: (纸本)1424401712

In this paper, the SPT (Singular Perturbation Theory) is applied to decompose the VCM's (Voice Coil Motor) and induced PZT active suspension's dynamics into fast and slow subsystems, respectively. The control system is decomposed into fast and slow time scale for controller designs, and control effectiveness is increased to tackle more DOFs (Degrees-Of-Freedom) via inner loop vibration suppression with measured high frequency VCM's and PZT active suspension's dynamics from the piezoelectric elements in the suspension. Experimental results on a commercial HDD with LDV (Laser Doppler Vibrometer) show effective suppression of the VCM and PZT active suspension's flexible resonant modes as well as an improvement of 39.9% in 3σ PES (Position Error Signal) during track following when compared to conventional notch-based servos. © 2006 IEEE.

关键词： Hard disk storage

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Knowledge Science, engineering and Management 1

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丛书名： Lecture Notes in computer Science

1000年

作者： Robert Buchmann Claudiu Vasile Kifor Jian Yu

ISBN: (数字)9783319120966

ISBN: (纸本)9783319120959

This book constitutes the refereed proceedings of the 7th International Conference on Knowledge Science, engineering and Management, KSEM 2014, held in Sibiu, Romania, in October 2014. The 30 revised full papers presented together with 5 short papers and 3 keynotes were carefully selected and reviewed from 77 submissions. The papers are organized in topical sections on formal semantics; content and document analysis; concept and lexical analysis; clustering and classification; metamodeling and conceptual modeling; enterprise knowledge; knowledge discovery and retrieval; formal knowledge processing; ontology engineering and management; knowledge management; and hybrid knowledge systems.

关键词： Artificial Intelligence data Mining and Knowledge Discovery Information Storage and Retrieval Software engineering database Management Information Systems Applications (incl. Internet)

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SocialWeb Communities Executive Summary of the Dagstuhl Seminar

SocialWeb Communities Executive Summary of the Dagstuhl Semi...

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Social Web Communities 2008

作者： Alani, Harith Staab, Steffen Stumme, Gerd Address Harith Research Group ISWeb - Information Systems and Semantic Web University of Koblenz-Landau Univ.str. 1 Koblenz56016 Germany Knowledge & Data Engineering Group Department of Mathematics and Computer Science University of Kassel Wilhelmshöher Allee 73 Kassel34121 Germany

Blogs, Wikis, and Social Bookmark Tools have rapidly emerged on the Web. The reasons for their immediate success are that people are happy to share information, and that these tools provide an infrastructure for doing so without requiring any specific skills. At the moment, there exists no foundational research for these systems, and they provide only very simple structures for organising knowledge. Individual users create their own structures, but these can currently not be exploited for knowledge sharing. The objective of the seminar was to provide theoretical foundations for upcoming Web 2.0 applications and to investigate further applications that go beyond bookmark- and file-sharing. The main research question can be summarized as follows: How will current and emerging resource sharing systems support users to leverage more knowledge and power from the information they share on Web 2.0 applications? research areas like Semantic Web, Machine Learning, Information Retrieval, Information Extraction, Social Network Analysis, Natural Language Processing, Library and Information Sciences, and Hypermedia Systems have been working for a while on these questions. In the workshop, researchers from these areas came together to assess the state of the art and to set up a road map describing the next steps towards the next generation of social software. © 2008 Dagstuhl Seminar Proceedings. All rights reserved.

关键词： Natural language processing systems

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