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Performance Analysis of ZCC-Optical-CDMA over SMF for Fiber-To-The-Home Access Network

Journal of Physics: Conference Series 2020年第2期1529卷

作者： Alaan Ghazi S. A. Aljunid Alaa Fareed Syed Zulkarnain Syed Idrus C. B. M Rashidi Marwa albayaty Aras Al-dawoodi Ahmed M. Fakhrudeen School of Human Development & Techno Communication University Malaysia Perlis Malaysia School of Computer and Communication Engineering University Malaysia Perlis Malaysia Computer Technical Engineering Alkitab University Iraq Internet Research Laboratory School of Computing University Utara Malaysia Malaysia Computer Science Department College of Computer Science and Information Technology Kirkuk University Iraq Networks Department College of Computer Science and Information Technology Kirkuk University Iraq

To provide a sustainable fiber-to-the-home (FTTH), several multiplexing techniques have been developed for this purpose. The correlation features are the main obstacle behind the network performance limitation, which imposes to a high level of multiple access interference. However, the development of multiplexing techniques helps to overcome these limitations, such as optical-code division multiple access (Optical-CDMA). Optical-CDMA is considered as one of the most powerful solutions for FTTH. This paper aims to enhance FTTH network performance by applying Zero cross-correlation code (ZCC) with Optical-CDMA with maximum link single-mode fiber. In the simulation, the system performance is demonstrated in terms of bit error rate, Q-Factor and eye diagram measurements.

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The 5th International Conference on Biomedical Engineering and Biotechnology (ICBEB 2016) Abstracts

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BMC MEDICAL IMAGING 2016年第SUPPL 1期16卷 65-65页

作者： [Anonymous] Department of MRI Shandong Medical Imaging Research Institute Affiliated to Shandong University Jinan Shandong 250021 People’s Republic of China Department of Interventional Radiology Shandong Provincial Hospital Affiliated to Shandong University Jinan Shandong 250021 People’s Republic of China College of Information Science and Technology Engr. Research Center of Digitized Textile & Fashion Tech. for Ministry of Education Donghua University Shanghai 201620 China Intelligent multimedia information processing Lab College of Software Northeastern University Shenyang Liaoning Province 110004 China Institute of Biomedical and Health Engineering Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 China School of Computer Science and Technology Nanjing Normal University Nanjing China Department of Electrical Engineering The City College of New York CUNY New York USA Jiangsu Key Laboratory of 3D Printing Equipment and Manufacturing Nanjing China School of Electronic Science and Engineering Nanjing University Nanjing Jiangsu 210046 China College of Engineering Nanyang Technological University Singapore 639798 Singapore School of Electronic Information Shanghai Dianji University Shanghai China School of Natural Sciences and Mathematics Shepherd University Shepherdstown WV 25443 USA Davis College of Agriculture Natural Resources and Design West Virginia University Morgantown WV 26505 USA State Key Laboratory of Millimeter Waves Southeast University Nanjing 210096 China Center of Medical Physics and Technology Hefei Institutes of Physical Science Chinese Academy of Sciences Hefei China College of Agricultural and Life Sciences University of Florida Gainesville FL 32611 USA Courant Institute of Mathematical Sciences New York University New York NY 10012 USA Translational Imaging Division & MRI Unit Columbia University and New York State Psychiatric Institute New York NY 10032 USA Guangxi Key Laboratory of Manufacturing System & Adv

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An ecologically valid examination of event-based and time-based prospective memory using immersive virtual reality: The influence of attention, memory, and executive function processes on real-world prospective memory.

arXiv

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arXiv 2021年

作者： Kourtesis, Panagiotis MacPherson, Sarah E. Human Cognitive Neuroscience Department of Psychology University of Edinburgh Edinburgh United Kingdom Department of Psychology University of Edinburgh 7 George Square EdinburghEH8 9JZ United Kingdom Lab of Experimental Psychology Suor Orsola Benincasa University of Naples Naples Italy Interdepartmental Centre for Planning and Research "Scienza Nuova" Suor Orsola Benincasa University of Naples Naples Italy National Research Institute of Computer Science and Automation INRIA Rennes France Univ Rennes Rennes France Research Institute of Computer Science and Random Systems IRISA Rennes France French National Centre for Scientific Research CNRS Rennes France

Studies on prospective memory (PM) predominantly assess either event- or time-based PM by implementing non-ecological laboratory-based tasks. The results deriving from these paradigms have provided findings that are discrepant with ecologically valid research paradigms that converge on the complexity and cognitive demands of everyday tasks. The Virtual Reality Everyday Assessment Lab (VR-EAL), an immersive virtual reality (VR) neuropsychological battery with enhanced ecological validity, was implemented to assess everyday event- and time-based PM, as well as the influence of other cognitive functions on everyday PM functioning. The results demonstrated the importance of delayed recognition, planning, and visuospatial attention on everyday PM. Delayed recognition and planning ability were found to be central in event- and time-based PM respectively. In order of importance, delayed recognition, visuospatial attention speed, and planning ability were found to be involved in event-based PM functioning. Comparably, planning, visuospatial attention accuracy, delayed recognition, and multitasking/task-shifting ability were found to be involved in time-based PM functioning. These findings further suggest the importance of ecological validity in the study of PM, which may be achieved using immersive VR paradigms. © 2021, CC BY.

关键词： Ecology

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Using social media to perform local influenza surveillance in an inner-city hospital: A retrospective observational study

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JMIR Public Health and Surveillance 2015年第1期1卷 e5页

作者： Broniatowski, David Andre Dredze, Mark Paul, Michael J. Dugas, Andrea Department of Engineering Management and Systems Engineering The George Washington University Washington DC United States Human Language Technology Center of Excellence Johns Hopkins University Baltimore MD United States Department of Computer Science Johns Hopkins University Baltimore MD United States Department of Emergency Medicine Johns Hopkins University Baltimore MD United States

Background: Public health officials and policy makers in the United States expend significant resources at the national, state, county, and city levels to measure the rate of influenza infection. These individuals rely on influenza infection rate information to make important decisions during the course of an influenza season driving vaccination campaigns, clinical guidelines, and medical staffing. Web and social media data sources have emerged as attractive alternatives to supplement existing practices. While traditional surveillance methods take 1-2 weeks, and significant labor, to produce an infection estimate in each locale, web and social media data are available in near real-time for a broad range of locations. Objective: The objective of this study was to analyze the efficacy of flu surveillance from combining data from the websites Google Flu Trends and HealthTweets at the local level. We considered both emergency department influenza-like illness cases and laboratory-confirmed influenza cases for a single hospital in the City of Baltimore. Methods: This was a retrospective observational study comparing estimates of influenza activity of Google Flu Trends and Twitter to actual counts of individuals with laboratory-confirmed influenza, and counts of individuals presenting to the emergency department with influenza-like illness cases. Data were collected from November 20, 2011 through March 16, 2014. Each parameter was evaluated on the municipal, regional, and national scale. We examined the utility of social media data for tracking actual influenza infection at the municipal, state, and national levels. Specifically, we compared the efficacy of Twitter and Google Flu Trends data. Results: We found that municipal-level Twitter data was more effective than regional and national data when tracking actual influenza infection rates in a Baltimore inner-city hospital. When combined, national-level Twitter and Google Flu Trends data outperformed each data source ind

关键词： Social computing Time series analysis Web mining

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Prioritizing Strategies for Building the Resilience of Public Health Systems to Disasters Across Multiple Communities and Countries

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International Journal of Disaster Risk science 2024年第1期15卷 1-17页

作者： Benjamin J.Ryan Mayumi Kako Shelby Garner Rok Fink Ismail Tayfur Jonathan Abrahams Sanjaya Bhatia Adriana Campelo Matthew Fendt Alicia Fontenot Nahuel Arenas Garcia Tim Hatch Ryoma Kayano LaShonda Malrey‑Horne Makiko MacDermot Md Moshiur Rahman Chaverle Noel Shuhei Nomura Jeremy P.Novak Maria Opazo Kendell Oliver Luciana Peters Sohel Rahman PerihanŞimşek Andrew Stricklin Raymond Swienton Bryan W.Brooks Frist College of Medicine Belmont UniversityNashvilleTN 37212USA Department of Environmental Science Environmental Health Science ProgramCollege of Arts and SciencesBaylor UniversityWacoTX 76798USA Division of Nursing Science School of Biomedical and Health SciencesHiroshima UniversityHiroshima 734-8553Japan Gordon E.Inman College of Health Sciences and Nursing Belmont UniversityNashvilleTN 37212USA Faculty of Health Sciences University of Ljubljana1000 LjubljanaSlovenia Department of Emergency Medicine University of Health Sciences34668 IstanbulTurkey Monash University Accident Research Center MelbourneVIC 3800Australia Global Education and Training Institute United Nations Ofce for Disaster Risk ReductionIncheon 22004Republic of Korea Regional Ofce for the Americas and Caribbean United Nations Ofce for Disaster Risk ReductionPanama City 0843-03441Panama Engineering and Computer Science Baylor UniversityWacoTX 76798USA Department of Public Health Robbins College of Health and Human SciencesBaylor UniversityWacoTX 76798USA Alabama Department of Public Health MontgomeryAL 36092USA World Health Organization Centre for Health Development(WHO Kobe Centre) Kobe 651-0073Japan Waco-McLennan County Public Health District WacoTX 76707USA Department of Health Policy and Management School of MedicineKeio UniversityTokyo 160-8582Japan Department of Global Health Policy Graduate School of MedicineThe University of TokyoTokyo 113-0033Japan Tokyo Foundation for Policy Research Tokyo 106-6234Japan Global Development College BrisbaneQLD 4000Australia Municipality of Pudahuel 13124 PudahuelChile City Hall of Porto Alegre Porto Alegre 90010-170Brazil Ministry of Health and Family Welfare Government of the People’s Republic of BangladeshDhaka 1000Bangladesh Department of Emergency Aid and Disaster Management Trabzon University61335 TrabzonTurkey Department of Emergency Medicine UT SouthwesternDallasTX 75390USA

The COVID-19 pandemic highlighted the urgent need to strengthen public health *** response,the United Nations Disaster Risk Reduction(UNDRR) Public Health System Resilience Scorecard(Scorecard) was applied in workshops across multiple *** aim of our research was to explore the workshop findings to develop priority strategies for strengthening public health system *** conducted a workshop from 14 to 16 March 2023,at the UNDRR Global Education and Training Institute in Incheon,Republic of Korea.A sequential modified Delphi method was utilized to develop a set of prioritized resilience *** were drawn from 70 strategies identified from 13 distinct workshops in eight *** two surveys,23 strategies were *** received ratings of "High" or Very High" from89% of *** related to the inclusion of public health risks in emergency plans,integrating multidisciplinary teams into public health,enabling local transport mechanisms,and improving the ability to manage an influx of *** Scorecard provides an adaptable framework to identify and prioritize strategies for strengthening public health system *** leveraging this methodology,our study demonstrated how resilience strategies could inform disaster risk reduction funding,policies,and actions.

关键词： Health system resilience Public policy Resilience scorecard Workshops

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Preface

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in computer science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2021年 12856 LNCS卷 v页

作者： Hernández-Leo, Davinia Hishiyama, Reiko Zurita, Gustavo Weyers, Benjamin Nolte, Alexander Ogata, Hiroaki Department of Information and Communication Technologies Universitat Pompeu Fabra Barcelona Spain Department of Management Control and Information Systems University of Chile Santiago Chile Institute of Computer Science University of Tartu Tartu Estonia School of Creative Science Waseda University Tokyo Japan Human-Computer Interaction Group University of Trier Trier Germany Academic Center for Computing and Media Studies Kyoto University Kyoto Japan

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Stabilization of Axisymmetric Airy Beams by Means of Diffraction and Nonlinearity Management in Two-Dimensional Fractional Nonlinear Schrödinger Equations

arXiv

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arXiv 2022年

作者： Li, Pengfei Wei, Yanzhu Malomed, Boris A. Mihalache, Dumitru Department of Physics Taiyuan Normal University Jinzhong030619 China College of computer science and technology Taiyuan Normal University 030619 China Department of Physical Electronics School of Electrical Engineering Faculty of Engineering Center for Light-Matter Interaction Tel Aviv University Tel Aviv69978 Israel Instituto de Alta Investigación Universidad de Tarapacá Casilla 7D Arica Chile Horia Hulubei National Institute of Physics and Nuclear Engineering Magurele Bucharest077125 Romania

The propagation dynamics of two-dimensional (2D) ring-Airy beams is studied in the framework of the fractional Schrödinger equation, which includes saturable or cubic self-focusing or defocusing nonlinearity and Lévy index ((LI) alias for the fractionality) taking values 1 ≤ α ≤ 2. The model applies to light propagation in a chain of optical cavities emulating fractional diffraction. Management is included by making the diffraction and/or nonlinearity coefficients periodic functions of the propagation distance, ζ. The management format with the nonlinearity coefficient decaying as 1/ζ is considered, too. These management schemes maintain stable propagation of the ring-Airy beams, which maintain their axial symmetry, in contrast to the symmetry-breaking splitting instability of ring-shaped patterns in 2D Kerr media. The instability driven by supercritical collapse at all values α © 2022, CC BY.

关键词： Diffraction

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Self-supervised learning of a tailored Convolutional Auto Encoder for histopathological prostate grading

arXiv

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arXiv 2023年

作者： Tabatabaei, Zahra Colomer, Adrián Engan, Kjersti Oliver, Javier Naranjo, Valery Instituto Universitario de Investigación en Tecnología Centrada en el Ser Humano HUMAN-tech Universitat Politècnica de València Spain ValgrAI – Valencian Graduate School Research Network for Artificial Intelligence Spain Department of Electrical Engineering and Computer Science University of Stavanger Norway Department of Artificial Intelligence Tyris Tech S.L. Valencia Spain

According to GLOBOCAN 2020, prostate cancer is the second most common cancer in men worldwide and the fourth most prevalent cancer overall. For pathologists, grading prostate cancer is challenging, especially when discriminating between Grade 3 (G3) and Grade 4 (G4). This paper proposes a Self-Supervised Learning (SSL) framework to classify prostate histopathological images when labeled images are scarce. In particular, a tailored Convolutional Auto Encoder (CAE) is trained to reconstruct 128×128×3 patches of prostate cancer Whole Slide Images (WSIs) as a pretext task. The downstream task of the proposed SSL paradigm is the automatic grading of histopathological patches of prostate cancer. The presented framework reports promising results on the validation set, obtaining an overall accuracy of 83% and on the test set, achieving an overall accuracy value of 76% with F1-score of 77% in G4. © 2023, CC BY-NC-SA.

关键词： Grading

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A layered architectural model for music: Malaysian music on the World Wide Web

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Organised Sound 1998年第2期3卷 101-115页

作者： MINNI ANG ABU TALIB OTHMAN A. K. RAMANI GAN SIOWCK-LEE PATRICIA MATUSKY Music Department Faculty of Human Ecology University Putra Malaysia 43400 UPM Serdang Selangor Malaysia. E-mail: minni@music.upm.edu.my Computer Science Department Faculty of Science and Environmental Studies University Putra Malaysia 43400 UPM Serdang Selangor Malaysiaramani@fsas.upm.edu.my Institute for Distance Learning University Putra Malaysia 43400 UPM Serdang Selangor Malaysia. E-mail: gansl@ideal.upm.edu.my PO Box 1102 Davis CA 95617 USAPatriciaMatusky@***

The design and development of a layered Web architecture for Malaysian music can be applied as a model of Web architecture for music education, specifically for the introduction of the music of a particular country or region. The model is designed and developed in two phases: the building of the subject architecture and the design and development of the application architecture. The complete Web architecture is analysed and tested to determine its suitability for delivery of music-related content. Research findings indicate that the Web architecture is reliable, efficient and suitable for its purpose. The classification scheme proposed is found to provide a firm foundation for the building of the Web architecture. In conclusion, the prototype model provides a suitable extensible platform for the delivery of music content, which may be packaged for the purpose of education.

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A SSIM Guided cGAN Architecture For Clinically Driven Generative Image Synthesis of Multiplexed Spatial Proteomics Channels

A SSIM Guided cGAN Architecture For Clinically Driven Genera...

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IEEE Symposium on Computational Intelligence and Bioinformatics and Computational Biology (CIBCB)

作者： Jillur Rahman Saurav Mohammad Sadegh Nasr Helen H Shang Paul Koomey Michael Robben Manfred Huber Jon Weidanz Bríd Ryan Eytan Ruppin Peng Jiang Jacob M. Luber Department of Computer Science University of Texas at Arlington Multi-Interprofessional Center for Health Informatics University of Texas at Arlington Division of Internal Medicine Ronald Reagan University of California Los Angeles Medical Center Department of Bioengineering University of Texas at Arlington Department of Kinesiology University of Texas at Arlington Laboratory of Human Carcinogenesis Center for Cancer Research National Cancer Institute National Institutes of Health Cancer Data Science Laboratory Center for Cancer Research National Cancer Institute National Institutes of Health

Histopathological work in clinical labs often relies on immunostaining of proteins, which can be time-consuming and costly. Multiplexed spatial proteomics imaging can increase interpretive power, but current methods cannot cost-effectively sample the entire proteomic retinue important to diagnostic medicine or drug development. To address this challenge, we developed a conditional generative adversarial network (cGAN) that performs image-to-image (i2i) synthesis to generate accurate biomarker channels in multiplexed spatial proteomics images 1 . We approached this problem as missing biomarker expression generation, where we assumed that a given n-channel multiplexed image has p channels (biomarkers) present and q channels (biomarkers) absent, with p+q=n, and we aimed to generate the missing q channels. To improve accuracy, we selected p and q channels based on their structural similarity, as measured by a structural similarity index measure (SSIM). We demonstrated the effectiveness of our approach using spatial proteomic data from the human BioMolecular Atlas Program (HuBMAP) 2 , which we used to generate spatial representations of missing proteins through a U-Net based image synthesis pipeline. Channels were hierarchically clustered by SSIM to obtain the minimal set needed to recapitulate the underlying biology represented by the spatial landscape of proteins. We also assessed the scalability of our algorithm using regression slope analysis, which showed that it can generate increasing numbers of missing biomarkers in multiplexed spatial proteomics images. Furthermore, we validated our approach by generating a new spatial proteomics data set from human lung adenocarcinoma tissue sections and showed that our model could accurately synthesize the missing channels from this new data set. Overall, our approach provides a cost-effective and time-efficient alternative to traditional immunostaining methods for generating missing biomarker channels, while also increasing t

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