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Building a Winning Business Case for Standards Adoption

IEEE engineering Management Review 2020年第1期48卷 14-17页

作者： Bishop, David David Bishop (Senior Member IEEE) received the Bachelor of Computer Engineering degree from the Georgia Institute of Technology Atlanta GA USA and the M.B.A. degree with a concentration in IT management and a doctorate degree in business administration from Georgia State University Atlanta GA USA. He is a Technologist Consultant Researcher Entrepreneur and Instructor with more than 25 years of experience in telecommunications transportation government and utility industries. He is the author of Metagility: Managing Agile Development for Competitive Advantage Elizabeth's Song The Big Brother's Guides and numerous other books and articles. He is a frequent contributor to Ieee's Engineering Management Review and an inventor of several U.S. patents. He is the CEO and Founder of Agile Worx LLC a firm that provides program and project management software tools training and consulting services. He is a member and Committee Chair for the International Electrotechnical Commission (IEC) based in Geneva Switzerland a member of ANSI and the Association for Computing Machinery. David is also a Research Associate with the Center for Engaged Business Research Georgia State University and the Founding Chair for the Atlanta chapter of the IEEE Technology and Engineering Management Society.

In a recent issue of Ieee engineering Management Review, we explored the problem of building a winning business case and the elements that can differentiate an 'average' business case from a 'winning' one. For this second installment, we will show how these winning elements were applied in practice. To make it even more interesting, we will illustrate how this can be accomplished with arguably one of the most difficult cases to make: adoption of technical standards. Our stakeholder is a large power utility. © 1973-2011 IEEE.

关键词： Task analysis Acceleration

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Using Machine Learning to Study the Effects of Genetic Predisposition on Brain Aging in the UK Biobank

Using Machine Learning to Study the Effects of Genetic Predi...

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IEEE International Symposium on Biomedical Imaging

作者： Karen Ardila Emily Munro Fernando Vega Aashka Mohite Charlotte Curtis Amanda V. Tyndall M. Ethan MacDonald Department of Electronic and Automation Biomedical Engineering Universidad Autónoma de Manizales Manizales Colombia Department of Biomedical Engineering University of Calgary Calgary Canada Department of Electrical & Software Engineering University of Calgary Calgary Canada Department of Radiology University of Calgary Calgary Canada Hotchkiss Brain Institute University of Calgary Calgary Canada Mitacs Globalink Research Internship Program Canada Department of Chemical Engineering University of Calgary Calgary Canada Department of Mathematics and Computing Mount Royal University Calgary Canada Department of Medical Genetics University of Calgary Calgary Canada

The influence of genetic predisposition on changes in brain morphology during aging remains largely unknown. This study explores the effects of genetic predisposition on three key brain regions: total brain volume (TBV), lateral ventricular volume (LVV), and total hippocampal volume (THV). The brain age gap estimate (BrainAGE) biomarker is used as an input to a genome-wide association study to determine which single nucleotide polymorphisms (SNPs) and genes are associated with accelerated brain aging. Six independent significant SNPs were found to contribute to accelerated morphological changes: TBV had associations on chromosome 17 linked with brain aging, and the total THV had independent significant associations in the APOC1 and TOMM40 gene regions related to neurodegeneration. Lastly, LVV presented a possible novel discovery in the gene NUAK1, known to play a role in cellular senescence. This study provides a framework to uncover complex associations between brain aging physiology and genetics.

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Document Image Retrieval Using Deep Features

Document Image Retrieval Using Deep Features

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International Joint Conference on Neural Networks (IJCNN)

作者： Kelly L. Wiggers Alceu S. Britto Laurent Heutte Alessandro L. Koerich Luiz Eduardo S. Oliveira Postgraduate Program in Informatics Pontifical Catholic University of Paraná Curitiba Brazil Laboratoire d’Informatique du Traitement de l’Information et des Systèmes (LITIS) Rouen University Rouen France Dep. of Software and IT Engineering École de Technologie Supérieure Montreal Canada Dep. of Informatics University Federal of Paraná Curitiba Brazil

This paper proposes a novel approach for content based graphical object retrieval in document images. The challenge is to search for occurrences of a queried graphical objects in document images that can vary in terms of color, shape, texture and quality, increasing considerably the level of difficulty of the retrieval process. To that end, the manual feature engineering is avoided by learning the image representation for the retrieval task using a Convolutional Neural Network (CNN). However, such a representation should be as compact as possible to allow a fast document image retrieval and storage. Thus, a pretrained CNN model is used to cope with the lack of training data, which is fine tuned to achieve a compact yet discriminant representation of the graphical objects. From experiments conducted on the public Tobacco800 document image collection, we show that the proposed method compares favorably against state-of-the-art document image retrieval methods, reaching 0.72 of average precision (mAP). In addition, an increase of 4 percentage points in the average precision is observed using a compact deep representation in which the number of features is reduced by 16 times, thus allowing a reduction of 47% in terms of computation time by the image retrieval task.

关键词： Image retrieval Feature extraction Task analysis Search problems Image color analysis Shape Image representation

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The space-ground functionality tradeoff revisited

The space-ground functionality tradeoff revisited

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作者： Hinners, T.A. Kowalski, Stephen V. Blanchette Jr., Stephen Stein, Ethan Northrop Grumman Redondo Beach CA 90278 United States Acquisition Support Program Software Engineering Institute 4500 Fifth Avenue Pittsburgh PA 15213 United States Northrop Grumman 14320 Sullyfield Cir. Chantilly VA 20151 United States Mail Station R2/1104A Northrop Grumman Corporation 1 Space Park Dr. United States Mail Station R2/1028B Northrop Grumman Corporation 1 Space Park Dr. United States

ISBN: (纸本)9781563479793

The decision on how to split functionality between space and ground segments is a significant factor in the resulting architecture quality of a space mission system. Weight and power constraints onboard the spacecraft are often a driving consideration but with recent advances in areas such as available processing power, other criteria such as end-to-end system performance and maintainability are increasingly relevant. These criteria are sometimes referred to as architecture quality attributes. It is important to consider that the overall quality of the space system architecture involves both the space and ground segments and nowhere is this better illustrated than in the space-ground functionality trade. In this paper, we consider a generic space mission system, identify likely architecture quality attributes and analyze how the allocation of functionality between the space and ground segments may affect them and subsequently affect the overall quality of the architecture. An initial step in performing a space-ground trade study is the identification of the relevant architecture quality attributes that will be used to evaluate the options. Quality attributes that are often drivers for the space-ground functionality trade include maintainability, performance, availability, modifiability, and security although these attributes and their relative importance often vary somewhat from mission to mission. Maintainability is the ease of keeping the system operational and the ability to diagnose anomalies and correct faults. Performance is a measure of the ability to meet performance requirements under stressing conditions. Availability is the percentage of time the system is able to provide its service to users. Modifiability is the ability to make changes to the system over time which is increasing important for longer-life space vehicles. Security is the ability to protect the system from attack and to prevent unauthorized access to information or services. The next step

关键词： Maintainability

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Deep Learning in Smart Healthcare: A GAN-based Approach for Imbalanced Alzheimer's Disease Classification

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Procedia Computer Science 2024年 241卷 146-153页

作者： Hina Tufail Abdul Ahad Ira Puspitasari Ibraheem Shayea Paulo Jorge Coelho Ivan Miguel Pires Department of Computer Science University of Management and Technology Sialkot Pakistan Information System Study Program Faculty of Science and Technology Universitas Airlangga School of Software Northwestern Polytechnical University Xian Shaanxi P.R. China Department of Electronics and Communication Engineering Istanbul Technical University(ITU) Turkey Polytechnic University of Leiria Leiria Portugal Institute for Systems Engineering and Computers at Coimbra (INESC Coimbra) Coimbra Portugal Instituto de Telecomunicações Escola Superior de Tecnologia e Gestão de Águeda Universidade de Aveiro Águeda Portugal

Alzheimer's disease (AD) is a type of dementia that leads to memory loss and impairment, which afects patients’ lives badly. It is not curable yet, but its progression can be slowed down if detected at earlier stages. In this research study, we propose a transfer learning-based convolutional neural network (CNN) model to classify magnetic resonance imaging (MRI) into one of four stages of Alzheimer's disease. One of the major limitations of the deep learning-based classification model is the non-availability of healthcare datasets related to AD. The widely used Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset has a major class imbalance issue. We propose a generative adversarial network (GAN) based data augmentation technique to overcome the data imbalance. This promotes the investigation of applying GANs to generate synthetic samples for minority classes in Alzheimer's disease datasets to enhance classification performance. The results show the progression in the overall classification process of AD.

关键词： Alzheimer disease (AD) Deep learning Convolutional Neural Network (CNN) Computer-aided diagnosis (CAD)

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Energy Efficient Election Protocol for Wireless Sensor Networks

Energy Efficient Election Protocol for Wireless Sensor Netwo...

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International Conference on Circuits, Power and Computing Technologies

作者： P. Udayakumar Ranjana Vyas O.P. Vyas Department of Computer Science CCEM Raipur Chhattisgarh State India School of IT MATS University Raipur Chhattisgarh State India Professor Program Coordinator (Software Engineering) IIIT-Allahabad (UP) India

ISBN: (纸本)9781467349215

Wireless a sensor network, which typically consist of large number of sensor nodes, is deployed in environmental fields for sensing and actuating applications. The protocols in WSNs play an important role in energy savings and the performance of WSNs could be improved by designing suitable MAC protocols. Energy efficiency is one of the important research themes while designing wireless sensor network nodes as WSNs are battery powered. MAC protocols are also used to minimize latency and maximize throughput in wireless sensor networks. Observably there are many MAC protocols available nowadays for WSNs but the actual objective is minimizing the energy consumption so that the lifetime is maximized. This paper is aimed at to summarize the key requirements for MAC protocol design and we have proposed a new protocol: Energy Efficient Election protocol (EEE-MAC) for WSNs. Our protocol is based on cluster based election algorithm and it can be implemented with any existing protocols. We have compared our proposed protocol with the existing contention-based S-MAC and T-MAC protocols. The simulation results show that our protocol has achieved better energy saving than the other three protocols.

关键词： EEE-MAC OMNeT++ S-MAC energy-efficient wireless sensor

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NSF/IEEE CAEME center. An exciting opportunity to align electromagnetic education with the nineties

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Computer Applications in engineering Education 1992年第1期1卷 33-33页

作者： Iskander, M.F. CAEME Director Electrical Engineering Department University of Utah Salt Lake City Utah 84112 Dr. Iskander edited two special issues of theJournal of Microwave Power one on “Electromagnetics and Energy Applications” March 1983 and the other on “Electromagnetic Techniques in Medical Diagnosis and Imaging” September 1983. He authored one book onElectromagnetic Fields and Waves published by Prentice Hall in 1992 he edited theCAEME Software Book Vol. I 1991 and he coedited a third book onMicrowave Processing of Materials published by the Materials Research Society in 1991. The holder of seven patents he has contributed 16 chapters to eight research books published more than 90 papers in technical journals and made numerous presentations in technical conferences. In 1983 he received the College of Engineering Outstanding Teaching Award and the College Patent Award for creative innovative and practical invention. In 1984 he was selected by the Utah Section of the IEEE as Engineer of the Year. In 1984 he received the Outstanding Paper Award from the International Microwave Power Institute and in 1985 he received the Curtis W. McGraw ASEE National Research Award for outstanding early achievements by a university faculty member. In 1991 he received the ASEE George Westinghouse National Award for innovation in engineering education. In 1986 Dr. Iskander established the Engineering Clinic Program in the College of Engineering at the University of Utah. Since then the program has attracted more than 45 research projects from 18 companies throughout the United States. He is also the director of the NSF/IEEE Center for Computer Applications in Electromagnetics Education (CAEME). He co-organized symposia on “Microwave Processing of Materials” held in conjunction with Materials Research Society meetings in the Springs of 1990 and 1992 in San Francisco. He also organized several workshops and special sessions in conjunction with IEEE symposia. Dr. Iskander is the editor of the journalComputer Applications i

The National Science Foundation/Institute of Electrical and Electronic Engineers (NSF/IEEE) Center for Computer Applications in Electromagnetic (EM) Education (CAEME) was funded in early 1990 by the National Science Foundation to stimulate and accelerate the use of computers and software tools in EM education. The Center is managed by the Executive Office of IEEE on behalf of the Antennas and Propagation Society. This organizational structure provided avenues for broad participation by universities, professional societies, and corporations in the Center's activities. In two years of operation, CAEME has organized several workshops and special sessions in international meetings, published its first software book, prepared a lesson on “Electromagnetic Waves” using interactive video, and raised over $ 130,000 from university membership, participating societies, and corporate sponsors. This article summarizes CAEME activities, outlines its organizational structure, and briefly describes the contents of its first software book. Future developments are discussed and avenues for participation are outlined.

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INNOVATIONS IN COMPUTER-AIDED-DESIGN OF MARINE TURBINES USING INTERACTIVE GRAPHICS

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NAVAL ENGINEERS JOURNAL 1980年第2期92卷 207-217页

作者： GINGRICH, JK WINTER, RL Mr. John K. Gingrich joined the General Electric Company after his graduation from Lafayette College in 1948. His early assignments were with the General Engineering Laboratory and the Knolls Atomic Power Laboratory in Schenectady. N. Y. He joined the Marine Turbine and Gear Department in 1968 as Manager Engineering Administration. and assumed his present assignment as Manager Engineering Resource Planning & Administration in 1976. Mr. Gingrich was instrumental in procuring the Interactive Graphics System for the Medium Steam Department. having headed up the Study Team and is now responsible for the Interactive Graphics Systems management including new procurements. He is a member of the American Institute of Design Drafting and is currently the Chairman of the Computer-Aided Drafting Committee in that organization. Mr. Reinhold L. Winter is a graduate of the General Electric Apprentice Program and Salem State College from which he received his B.S. degree in Business Administration. He has nineteen years experience with the General Electric Company including eight years in Business Systems and Programming two years in Computer Operations Management and six years in his present position as Manager Engineering Business Systems. He was a member of the original Study Team that investigated and selected the present Applicon Interactive Graphics (IAG) equipment and currently is responsible for the management of software and hardware support for the ZAG Facility.

This paper discusses the Interactive Graphics System used by the General Electric Company, Medium Steam Turbine Department (engineering & Manufacturing) for designing, drafting, and manufacturing applications. A brief overview of the hardware malting up the system is described, followed by a more detailed description of the actual applications. Two-dimensional applications described include a Heat Balance Analysis, Flow Diagrams, and Electrical Schematics. A more fruitful area for increased productivity gains is described in the three-dimensional or mechanical applications including turbine design & layout and bucket design. coordination of the design with manufacturing for numerical control tape generation is described through CAM and Plate Frame Cutting applications. Finally, a short review of the engineering design work using Interactive Graphics is discussed. Productivity gains of 2.6 to 1 are being realized, and the overall savings to the Medium Steam Department are outlined.

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Optimized Security Mechanism for publicly Secret Key Sharing over Cloud using Blockchain

Optimized Security Mechanism for publicly Secret Key Sharing...

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2024 International Symposium on Securing Next Generation Systems Using Future Artificial Intelligence Technologies, SNSFAIT 2024

作者： Byeon, Haewon Quraishi, Aadam Thuniki, Praveen Keshta, Ismail Soni, Mukesh Shabaz, Mohammad Department of AI and Software Inje University Gimhae50834 Korea Republic of Inje University Medical Big Data Research Center Gimhae50834 Korea Republic of Intervention Treatment Institute HoustonTX United States Sr Program Analyst Georgia CummingGA30040 United States Computer Science and Information Systems Department College of Applied Sciences Al Maarefa University Riyadh Saudi Arabia Dr. D. Y. Patii Vidyapeeth Pune Dr. D. Y. Patii School of Science & Technology Tathawade Pune India Model Institute of Engineering and Technology J&K Jammu India

A publicly verifiable key sharing mechanism based on threshold key sharing is provided to explore the security of users' private keys on the blockchain. Participating nodes check the key fragment after receiving it, effectively preventing it from being abused. The crucial sections of the nodes that participated in the critical splicing are made public during the critical recovery stage to prevent them from performing harmful things during the critical recovery stage. Add IDs to the nodes that participated in the crucial splicing during the key distribution stage;a dynamic threshold system is intended to track and update the status of malicious nodes in real time. When the node that possesses the crucial component fails, the owner of the critical component and the main node relocate a key element to the new participating nodes. To safeguard sensitive information. The experimental results show that this system has a key recovery rate of 80% and threshold qualities such as traceability, enforceability, and recoverability. © 2024 Copyright for this paper by its authors.

关键词： Blockchain Encryption Key sharing mechanism Privacy Secret key Security

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k-mer-based approaches to bridging pangenomics and population genetics

arXiv

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arXiv 2024年

作者： Roberts, Miles D. Davis, Olivia Josephs, Emily B. Williamson, Robert J. Genetics and Genome Sciences Program Michigan State University East LansingMI48824 United States Department of Computer Science and Software Engineering Rose-Hulman Institute of Technology Terre HauteIN47803 United States Department of Biology and Biomedical Engineering Rose-Hulman Institute of Technology Terre HauteIN47803 United States Department of Plant Biology Michigan State University East LansingMI48824 United States Ecology Evolution and Behavior Program Michigan State University East LansingMI48824 United States Plant Resilience Institute Michigan State University East LansingMI48824 United States

Many commonly studied species now have more than one chromosome-scale genome assembly, revealing a large amount of genetic diversity previously missed by approaches that map short reads to a single reference. However, many species still lack multiple reference genomes and correctly aligning references to build pangenomes is challenging, limiting our ability to study this missing genomic variation in population genetics. Here, we argue that k-mers are a crucial stepping stone to bridging the reference-focused paradigms of population genetics with the reference-free paradigms of pangenomics. We review current literature on the uses of k-mers for performing three core components of most population genetics analyses: identifying, measuring, and explaining patterns of genetic variation. We also demonstrate how different k-mer-based measures of genetic variation behave in population genetic simulations according to the choice of k, depth of sequencing coverage, and degree of data compression. Overall, we find that k-mer-based measures of genetic diversity scale consistently with pairwise nucleotide diversity (π) up to values of about π = 0.025 (R2 = 0.97) for neutrally evolving populations. For populations with even more variation, using shorter k-mers will maintain the scalability up to at least π = 0.1. Furthermore, in our simulated populations, k-mer dissimilarity values can be reliably approximated from counting bloom filters, highlighting a potential avenue to decreasing the memory burden of k-mer based genomic dissimilarity analyses. For future studies, there is a great opportunity to further develop methods to identifying selected loci using k-mers. © 2024, CC BY.

关键词： Genome

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