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32nd International Conference on computers and Their Applications, CATA 2017

作者： Dos Lima, Aline F. Costa, Thiago S.A. Oliveira, Sandro R.B. Melo, Pamella B. Rodrigues, Juan P. P. Graduate Program in Computer Science Federal University of Pará Belém Pará Brazil Graduate Program in Information Technology Management Ideal College - Devry Belém Pará Brazil

ISBN: (纸本)9781943436064

The importance of adopting the evolutionary maintenance is becoming increasingly long life of a software without it losing its quality and its functionalities, however performing evolutionary maintenance of legacy systems is not always an easy task, considering that these systems often have incomplete and inconsistent documentation or even that was lost over time. We want to understand what software process assets can help in the implementation of requirements development practices in evolutionary maintenance in adherence to CMMI-DEV model, how these assets can be used by requirements team and how this team evaluate this application. This paper aims to present an implementation approach of the RD (Requirements Development) process area of CMMI-DEV (Capability Maturity Model Integration for Development) in the Brazilian company, called Vibe Desenvolvimento, for evolutionary maintenance projects with data collection from reverse engineering, and perform the adherence analysis of the model implemented in relation to the process area studied, through the application of questionnaires to Requirements Analyst team of this company, and the analysis of the work products generated in each specific practice of RD process area. © ISCA, CATA 2017.

关键词： Legacy systems

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Data mining technique with cluster anaysis use K-means algorithm for LQ45 index on Indonesia stock exchange 1

Data mining technique with cluster anaysis use K-means algor...

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1st International Conference on information and Communications technology, ICOIACT 2018

作者： Condrobimo, A. Raharto Abbas, Bahtiar Saleh Trisetyarso, Agung Suparta, Wayan Kang, Chul-Ho Computer Science Department BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta11480 Indonesia Information System Department School of Information System Bina Nusantara University Jakarta11480 Indonesia Civil Engineering Department University of Technology Yogyakarta Yogyakarta Indonesia Department of Electronic and Communication Engineering Kwangwoon University Korea Republic of

ISBN: (纸本)9781538609545

This study aims to apply data mining techniques with cluster analysis on stock data registered in LQ45 in Indonesia Stock Exchange. The cluster analysis used in this method is k-means algorithm, the data in this research is taken from Indonesia Stock Exchange. The cluster analysis in this study analyzed the characteristics of data volumes and stock values, while the results in this study were presented in the form of cluster members visually. Therefore, this cluster analysis in this research can be used for quick and efficient identifier for each member of LQ45 index cluster based on share value for each cluster and its volume. The identification results can be used by beginner-level investors that begun to be interested in stock investments to help make informed decisions about stock trading on desired cluster groups. © 2018 IEEE.

关键词： Cluster analysis

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Combined effects of hydrometeorological hazards and urbanisation on dengue risk in Brazil: a spatiotemporal modelling study

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The Lancet Planetary Health 2021年第4期5卷 e209-e219页

作者： Lowe, Rachel Lee, Sophie A Brady, Oliver J Bastos, Leonardo Carrasco-Escobar, Gabriel de Castro Catão, Rafael Colón-González, Felipe J Barcellos, Christovam Carvalho, Marilia Sá Blangiardo, Marta Rue, Håvard Gasparrini, Antonio Centre for Mathematical Modelling of Infectious Diseases London School of Hygiene & Tropical Medicine London United Kingdom Centre on Climate Change and Planetary Health London School of Hygiene & Tropical Medicine London United Kingdom Department of Infectious Disease Epidemiology London School of Hygiene & Tropical Medicine London United Kingdom Department of Public Health Environments and Society London School of Hygiene & Tropical Medicine London United Kingdom Centre for Statistical Modelling London School of Hygiene & Tropical Medicine London United Kingdom Scientific Computing Program Oswaldo Cruz Foundation Rio de Janeiro Brazil Health Information and Communication Institute Oswaldo Cruz Foundation Rio de Janeiro Brazil Scripps Institution of Oceanography University of California San Diego San Diego CA United States Health Innovation Laboratory Institute of Tropical Medicine Alexander von Humboldt Universidad Peruana Cayetano Heredia Lima Peru Department of Geography Federal University of Espírito Santo Vitória Brazil MRC Centre for Environment and Health Department of Epidemiology and Biostatistics Imperial College London London United Kingdom Statistics Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal Saudi Arabia

Background: Temperature and rainfall patterns are known to influence seasonal patterns of dengue transmission. However, the effect of severe drought and extremely wet conditions on the timing and intensity of dengue epidemics is poorly understood. In this study, we aimed to quantify the non-linear and delayed effects of extreme hydrometeorological hazards on dengue risk by level of urbanisation in Brazil using a spatiotemporal model. Methods: We combined distributed lag non-linear models with a spatiotemporal Bayesian hierarchical model framework to determine the exposure-lag-response association between the relative risk (RR) of dengue and a drought severity index. We fit the model to monthly dengue case data for the 558 microregions of Brazil between January, 2001, and January, 2019, accounting for unobserved confounding factors, spatial autocorrelation, seasonality, and interannual variability. We assessed the variation in RR by level of urbanisation through an interaction between the drought severity index and urbanisation. We also assessed the effect of hydrometeorological hazards on dengue risk in areas with a high frequency of water supply shortages. Findings: The dataset included 12 895 293 dengue cases reported between 2001 and 2019 in Brazil. Overall, the risk of dengue increased between 0–3 months after extremely wet conditions (maximum RR at 1 month lag 1·56 [95% CI 1·41–1·73]) and 3–5 months after drought conditions (maximum RR at 4 months lag 1·43 [1·22–1·67]). Including a linear interaction between the drought severity index and level of urbanisation improved the model fit and showed the risk of dengue was higher in more rural areas than highly urbanised areas during extremely wet conditions (maximum RR 1·77 [1·32–2·37] at 0 months lag vs maximum RR 1·58 [1·39–1·81] at 2 months lag), but higher in highly urbanised areas than rural areas after extreme drought (maximum RR 1·60 [1·33–1·92] vs 1·15 [1·08–1·22], both at 4 months lag). We also found the den

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Erratum: Extended Drude Model for Intraband-Transition-Induced Optical Nonlinearity [Phys. Rev. Applied 11, 064062 (2019)]

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Physical Review Applied 2020年第3期14卷 039901-039901页

作者： Heng Wang Kang Du Chuhao Jiang Zhiqiang Yang Lixia Ren Wending Zhang Soo Jin Chua Ting Mei MOE Key Laboratory of Material Physics and Chemistry under Extraordinary Conditions and Shaanxi Key Laboratory of Optical Information Technology School of Physical Science and Technology Northwestern Polytechnical University Xi’an 710129 China Department of Electrical and Computer Engineering National University of Singapore 4 Engineering Drive 3 Singapore 117583 LEES Program Singapore-MIT Alliance for Research & Technology (SMART) 1 CREATE Way #10-01 CREATE Tower Singapore 138602

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Enhancing Supervised Classifications with Metamorphic Relations

Enhancing Supervised Classifications with Metamorphic Relati...

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IEEE/ACM International Workshop on Metamorphic Testing (MET)

作者： Liming Xu Dave Towey Andrew P. French Steve Benford Zhi Quan Zhou Tsong Yueh Chen International Doctoral Innovation Centre University of Nottingham Ningbo China Ningbo Zhejiang China AIOP Group University of Nottingham Ningbo China Ningbo Zhejiang China School of Computer Science University of Nottingham Nottingham UK School of Computing and Information Technology University of Wollongong Wollongong NSW Australia Dept. of Computer Science and Software Engineering Swinburne University of Technology Hawthorn VIC Australia

We report on a novel use of metamorphic relations (MRs) in machine learning: instead of conducting metamorphic testing, we use MRs for the augmentation of the machine learning algorithms themselves. In particular, we report on how MRs can enable enhancements to an image classification problem of images containing hidden visual markers (“Artcodes”). Working on an original classifier, and using the characteristics of two different categories of images, two MRs, based on separation and occlusion, were used to improve the performance of the classifier. Our experimental results show that the MR-augmented classifier achieves better performance than the original classifier, algorithms, and extending the use of MRs beyond the context of software testing.

关键词： Machine learning Testing Software Forestry Histograms Visualization computer science

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AIRR community curation and standardised representation for immunoglobulin and T cell receptor germline sets

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Immunoinformatics (Amsterdam, Netherlands) 2023年 10卷 100025页

作者： William D Lees Scott Christley Ayelet Peres Justin T Kos Brian Corrie Duncan Ralph Felix Breden Lindsay G Cowell Gur Yaari Martin Corcoran Gunilla B Karlsson Hedestam Mats Ohlin Andrew M Collins Corey T Watson Christian E Busse Institute of Structural and Molecular Biology Birkbeck College London England. Human-Centered Computing and Information Science Institute for Systems and Computer Engineering Technology and Science Porto Portugal. Peter O'Donnell Jr. School of Public Health UT Southwestern Medical Center Dallas TX USA. Bioengineering Program Faculty of Engineering Bar-Ilan University Ramat Gan Israel. Department of Biochemistry and Molecular Genetics School of Medicine University of Louisville KY USA. Department of Biological Sciences Simon Fraser University Burnaby BC Canada. Fred Hutchinson Cancer Research Center Seattle WA USA. Peter O'Donnell Jr. School of Public Health Department of Immunology School of Biomedical Sciences UT Southwestern Medical Center Dallas TX USA. Department of Microbiology Tumor and Cell Biology Karolinska Institutet Stockholm Swede. Department of Immunotechnology and SciLifeLab Lund University Lund Sweden. School of Biotechnology and Biomolecular Sciences University of New South Wales Sydney NSW Australia. Division of B Cell Immunology German Cancer Research Center Heidelberg Germany.

Analysis of an individual's immunoglobulin or T cell receptor gene repertoire can provide important insights into immune function. High-quality analysis of adaptive immune receptor repertoire sequencing data depends upon accurate and relatively complete germline sets, but current sets are known to be incomplete. Established processes for the review and systematic naming of receptor germline genes and alleles require specific evidence and data types, but the discovery landscape is rapidly changing. To exploit the potential of emerging data, and to provide the field with improved state-of-the-art germline sets, an intermediate approach is needed that will allow the rapid publication of consolidated sets derived from these emerging sources. These sets must use a consistent naming scheme and allow refinement and consolidation into genes as new information emerges. Name changes should be minimised, but, where changes occur, the naming history of a sequence must be traceable. Here we outline the current issues and opportunities for the curation of germline IG/TR genes and present a forward-looking data model for building out more robust germline sets that can dovetail with current established processes. We describe interoperability standards for germline sets, and an approach to transparency based on principles of findability, accessibility, interoperability, and reusability.

关键词： AIRR-seq Immune receptor Immune receptor germline Immune receptor repertoire Rep-seq

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Polaritonic frequency-comb generation and breather propagation in a negative-index metamaterial with a cold four-level atomic medium

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Physical Review A 2019年第5期99卷 051802(R)-051802(R)页

作者： Saeid Asgarnezhad-Zorgabad Pierre Berini Barry C. Sanders Department of Physics Sharif University of Technology Tehran 11365 11155 Iran Institute for Quantum Science and Technology University of Calgary Calgary Alberta Canada T2N 1N4 Department of Physics University of Ottawa 150 Louis-Pasteur Ottawa Ontario Canada K1N 6N5 Centre for Research in Photonics University of Ottawa 25 Templeton St. Ottawa Ontario Canada K1N 6N5 School of Electrical Engineering and Computer Science 700 King Edward St. Ottawa Ontario Canada K1N 6N5 Program in Quantum Information Science Canadian Institute for Advanced Research Toronto Ontario Canada M5G 1M1

We develop a concept for a waveguide that exploits spatial control of nonlinear surface-polaritonic waves. Our scheme includes an optical cavity with four-level N-type atoms in a lossless dielectric placed above a negative-index metamaterial layer. We propose exciting a polaritonic Akhmediev breather at a certain position of the interface between the atomic medium and the metamaterial by modifying laser-field intensities and detunings. Furthermore, we propose generating position-dependent polaritonic frequency combs by engineering widths of the electromagnetically induced transparency window commensurate with the surface-polaritonic modulation instability. Therefore, this waveguide acts as a high-speed polaritonic modulator and position-dependent frequency-comb generator, which can be applied to compact photonic chips.

关键词： Metamaterials Nonlinear optics Plasmonics Quantum optics

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A novel CAD system for detecting acute rejection of renal allografts based on integrating imaging-markers and laboratory biomarkers

A novel CAD system for detecting acute rejection of renal al...

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2018 IEEE International Conference on Imaging Systems and Techniques, IST 2018

作者： Shehata, Mohamed Ghazal, Mohammed Khalifa, Fahmi El-Ghar, Mohamed Abou Khalil, Ashraf Dwyer, Amy C. El-Giziri, Ahmed El-Melegy, Moumen El-Baz, Ayman BioImaging Lab University of Louisville LouisvilleKY40292 United States Electrical and Computer Engineering Department Abu Dhabi University Abu Dhabi United Arab Emirates Radiology Department Urology and Nephrology Center University of Mansoura Mansoura35516 Egypt Computer Science and Information Technology Department Abu Dhabi University Abu Dhabi United Arab Emirates Kidney Disease Program University of Louisville LouisvilleKY40202 United States Department of Electrical Engineering Assiut University Assiut71516 Egypt

ISBN: (纸本)9781538666289

The goal of this paper is to determine the parameters that are correlated with the biopsy diagnosis of acute renal rejection (AR) post-transplantation, using laboratory biomarkers and (3D+-value) diffusion weighted MR (DW-MR) image-markers. 16 patients with non-rejection (NR) and 45 patients with AR renal allografts determined by their renal biopsy as a gold standard were included. All kidneys were evaluated using both laboratory biomarkers (e.g., creatinine clearance (CrCl) and serum creatinine (SCr)) and DW-MR image-markers. To extract the latter, DW-MR kidney images were first segmented using a geometric deformable model, then, DW-MR image-markers known as apparent diffusion coefficients (ADCs), were estimated for segmented kidneys at multiple b-values (i.e. strength and timing, of, the, field, gradients, (b50,b 100,...,b 1000 s/mm2)). A statistical analysis investigating possible correlations between potential biomarkers of AR and the biopsy diagnosis was firstly performed. Two categories of parameters were mainly examined: (i) laboratory biomarkers (CrCl and SCr) and (ii) the average ADC (aADC) at individual b-values. Analysis of Variance(ANOVA) and the likelihood ratio (χ2) tests found that both CrCl and SCr affected significantly the likelihood of AR, as did the aADC for the individual b-values of b 100, b 500, b 600, b 700, and b 900s/mm2. Nevertheless, patient demographics (i.e. age and sex) and the aADC at the remaining b-values had no significant effect. The statistical analysis results encouraged us to investigate if this can lead to building a computer-aided diagnostic (CAD) system with the ability to classify AR from NR renal allografts. To achieve this goal, stacked auto-encoders (SAEs) based on deep learning approach were trained using the fusion of the statistically significant DW-MR image-markers and laboratory biomarkers for the classification purposes. Preliminary results obtained (92% accuracy, 92% sensitivity, and 94% specificity) hold a lot of

关键词： Creatinine

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FINDING CONTINUITY AND DISCONTINUITY IN FISH SCHOOLS VIA INTEGRATED information THEORY

arXiv

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arXiv 2018年

作者： Niizato, Takayuki Sakamoto, Kotaro Mototake, Yoh-ichi Murakami, Hisashi Tomaru, Takenori Hoshika, Tomotaro Fukushima, Toshiki Faculty of Engineering Information and Systems University of Tsukuba Japan Human Biology Program University of Tsukuba Japan Graduate School of Frontier Sciences University of Tokyo Japan Research Center for Advanced Science and Technology University of Tokyo Japan Department of Computer Science and Engineering Toyohashi University of Technology Japan

Collective behaviour is known to be the result of diverse dynamics and is sometimes likened to a living system. Although many studies have revealed the dynamics of various collective behaviours, their main focus was on the information process inside the collective, not on the whole system itself. For example, the qualitative difference between two elements and three elements as a system has rarely been investigated. Tononi et al. have proposed Integrated information Theory (IIT) to measure the degree of consciousness Φ. IIT postulates that the amount of information loss caused by certain partitions is equivalent to the degree of information integration in the system. This measure is not only useful for estimating the degree of consciousness but can also be applied to more general network systems. Here we applied IIT (in particular, IIT 3.0 using PyPhi) to analyse real fish schools (Plecoglossus altivelis). Our hypothesis in this study is a very simple one: a living system evolves to raise its Φ value. If we accept this hypothesis, IIT reveals the existence of continuous and discontinuous properties as group size varies. For example, leadership in the fish school emerged for a school size of four or above;but not below three. Furthermore, this transition was not observed by measuring mutual information or in a simple Boids model. This result suggests that integrated information Φ can reveal some inherent properties which cannot be observed using other measures. We also discuss how the fish recognition of the figure-ground relation, that is, what determines the relevant ON and OFF states, may reveal various optimal paths for obtaining the functional evolution of collective behaviour. Copyright © 2018, The Authors. All rights reserved.

关键词： information theory

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Author Correction: BigNeuron: a resource to benchmark and predict performance of algorithms for automated tracing of neurons in light microscopy datasets

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Nature methods 2024年第10期21卷 1959页

作者： Linus Manubens-Gil Zhi Zhou Hanbo Chen Arvind Ramanathan Xiaoxiao Liu Yufeng Liu Alessandro Bria Todd Gillette Zongcai Ruan Jian Yang Miroslav Radojević Ting Zhao Li Cheng Lei Qu Siqi Liu Kristofer E Bouchard Lin Gu Weidong Cai Shuiwang Ji Badrinath Roysam Ching-Wei Wang Hongchuan Yu Amos Sironi Daniel Maxim Iascone Jie Zhou Erhan Bas Eduardo Conde-Sousa Paulo Aguiar Xiang Li Yujie Li Sumit Nanda Yuan Wang Leila Muresan Pascal Fua Bing Ye Hai-Yan He Jochen F Staiger Manuel Peter Daniel N Cox Michel Simonneau Marcel Oberlaender Gregory Jefferis Kei Ito Paloma Gonzalez-Bellido Jinhyun Kim Edwin Rubel Hollis T Cline Hongkui Zeng Aljoscha Nern Ann-Shyn Chiang Jianhua Yao Jane Roskams Rick Livesey Janine Stevens Tianming Liu Chinh Dang Yike Guo Ning Zhong Georgia Tourassi Sean Hill Michael Hawrylycz Christof Koch Erik Meijering Giorgio A Ascoli Hanchuan Peng Institute for Brain and Intelligence Southeast University Nanjing China. Microsoft Corporation Redmond WA USA. Tencent AI Lab Bellevue WA USA. Computing Environment and Life Sciences Directorate Argonne National Laboratory Lemont IL USA. Kaya Medical Seattle WA USA. University of Cassino and Southern Lazio Cassino Italy. Center for Neural Informatics Structures and Plasticity Krasnow Institute for Advanced Study George Mason University Fairfax VA USA. Faculty of Information Technology Beijing University of Technology Beijing China. Beijing International Collaboration Base on Brain Informatics and Wisdom Services Beijing China. Nuctech Netherlands Rotterdam the Netherlands. Janelia Research Campus Howard Hughes Medical Institute Ashburn VA USA. Department of Electrical and Computer Engineering University of Alberta Edmonton Alberta Canada. Ministry of Education Key Laboratory of Intelligent Computation and Signal Processing Anhui University Hefei China. Paige AI New York NY USA. Scientific Data Division and Biological Systems and Engineering Division Lawrence Berkeley National Lab Berkeley CA USA. Helen Wills Neuroscience Institute and Redwood Center for Theoretical Neuroscience UC Berkeley Berkeley CA USA. RIKEN AIP Tokyo Japan. Research Center for Advanced Science and Technology (RCAST) The University of Tokyo Tokyo Japan. School of Computer Science University of Sydney Sydney New South Wales Australia. Texas A&M University College Station TX USA. Cullen College of Engineering University of Houston Houston TX USA. Graduate Institute of Biomedical Engineering National Taiwan University of Science and Technology Taipei Taiwan. National Centre for Computer Animation Bournemouth University Poole UK. PROPHESEE Paris France. Department of Neuroscience Columbia University New York NY USA. Mortimer B. Zuckerman Mind Brain Behavior Institute Columbia University New York NY USA. Department of Computer Science Northern Illinois Universit

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