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Correction to: Dependability enhancing mechanisms for integrated clinical environments

The Journal of Supercomputing 2018年第7期74卷 3486-3487页

作者： Zhao, Wenbing Yang, Mary Q. Department of Electrical Engineering and Computer Science Cleveland State University Cleveland USA Department of Information Science George Washington Donaghey College of Engineering and Information Technology Little Rock USA Joint Bioinformatics Program of University of Arkansas at Little Rock University of Arkansas for Medical Sciences Little Rock USA

The Acknowledgements published in the original article contain errors. The correct version is given below.

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The Form of High-Performance Computing: A Survey

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IOP Conference Series: Materials Science and Engineering 2019年第5期662卷

作者： Priati Assiroj H L H S Warnars R Kosala B Ranti S Supangat A I Kistijantoro E Abdurrachman Binus Graduate Program Doctor of Computer Science Bina Nusantara University Jakarta Information System Dept. Buana Perjuangan University Karawang Computer Science Department BINUS Graduate Program Doctor of Computer Science Bina Nusantara University Jakarta Information System Department Bina Nusantara University Jakarta Information System Technology Department Institut Teknologi Bandung School of Electronics Engineering and Informatics Institut Teknologi Bandung

Computational technology is an important thing that needed in the whole of human life. Along with the development of computer technology, there are a significant data created and wait to be processed; we will get more advantages if it well-processed, if not we will see the data explosion, the data is just a useless stack. Research mitigates the other research paper and makes a conclusion and a report by PRISMA method. The development of computer technology will support the development of an organization. Considering any factors in choosing the right and suitable high-performance computer resource due to our organization is a must. The existing high-performance computing forms are Supercomputer, Grid Computing, Cluster Computing, and Cloud Computing. Based on this work, the last form of high-performance computing, Cloud Computing is one of the most used forms thus we mitigate its advantages and disadvantages. Recently, to process this vast data, we must have a high-performance computer and to provide it, this is not a cheap resource.

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Eavesdropper's ability to attack a free-space quantum-key-distribution receiver in atmospheric turbulence

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Physical Review A 2019年第6期99卷 062315-062315页

作者： Poompong Chaiwongkhot Katanya B. Kuntz Yanbao Zhang Anqi Huang Jean-Philippe Bourgoin Shihan Sajeed Norbert Lütkenhaus Thomas Jennewein Vadim Makarov Institute for Quantum Computing University of Waterloo Waterloo ON Canada N2L 3G1 Department of Physics and Astronomy University of Waterloo Waterloo ON Canada N2L 3G1 NTT Basic Research Laboratories NTT Corporation Atsugi Kanagawa 243-0198 Japan NTT Research Center for Theoretical Quantum Physics NTT Corporation Atsugi Kanagawa 243-0198 Japan Institute for Quantum Information and State Key Laboratory of High Performance Computing College of Computer National University of Defense Technology Changsha 410073 People's Republic of China Department of Electrical and Computer Engineering University of Waterloo Waterloo ON Canada N2L 3G1 Aegis Quantum Waterloo ON Canada Department of Electrical and Computer Engineering University of Toronto Toronto Canada M5S 3G4 Quantum Information Science Program Canadian Institute for Advanced Research Toronto ON Canada M5G 1Z8 Russian Quantum Center Skolkovo Moscow 143025 Russia Shanghai Branch National Laboratory for Physical Sciences at Microscale and CAS Center for Excellence in Quantum Information University of Science and Technology of China Shanghai 201315 People's Republic of China NTI Center for Quantum Communications National University of Science and Technology MISiS Moscow 119049 Russia

The ability of an eavesdropper (Eve) to perform an intercept-resend attack on a free-space quantum-key-distribution (QKD) receiver by precisely controlling the incidence angle of an attack laser has been previously demonstrated. However, such an attack could be ineffective in the presence of atmospheric turbulence due to beam wander and spatial mode aberrations induced by the air's varying index of refraction. We experimentally investigate the impact turbulence has on Eve's attack on a free-space polarization-encoding QKD receiver by emulating atmospheric turbulence with a spatial light modulator. Our results identify how well Eve would need to compensate for turbulence to perform a successful attack by either reducing her distance to the receiver or using beam wavefront correction via adaptive optics. Furthermore, we use an entanglement-breaking scheme to find a theoretical limit on the turbulence strength that hinders Eve's attack.

关键词： Quantum cryptography

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DEA Model with Hesitant Fuzzy Polyhedral Set in Benchmarking 1

DEA Model with Hesitant Fuzzy Polyhedral Set in Benchmarking

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1st International Conference of SNIKOM 2018, ICoSNIKOM 2018

作者： Abdullah, Dahlan Hartono, H. Erliana, Cut Ita Irwansyah, Defi Siregar, Nurintan Asyiah Sari, Ayu Esteka Hasibuan, Abdurrozzaq Abdussakir Kurniasih, Nuning Mas'Ut Rangkuti, Irma Yanti Nurmawati Buston, Erni Abdurrahman, Apridar Handayani, Tita Septi Hadikurniawati, Wiwien Winarno, Edy Department of Informatics Universitas Malikussaleh Aceh Indonesia Department of Computer Science STMIK IBBI Medan Indonesia Department of Industrial Engineering Universitas Malikussaleh Aceh Indonesia Department of Management STIE Labuhanbatu Sumatera Utara Indonesia Department of Management STIE Sakti Alam Kerinci Jambi Indonesia Faculty of Engineering Universitas Islam Sumatera Utara Medan Indonesia Department of Mathematics Education State Islamic University of Malang Malang Indonesia Faculty of Communication Sciences Library and Information Science Program Universitas Padjadjaran Bandung Indonesia Faculty of Economic Universitas Islam Sumatera Utara Medan Indonesia Faculty of Medical Universitas Islam Sumatera Utara Medan Indonesia Faculty of Industry Technique University of 45 Surabaya Indonesia Departement of Nursing Politeknik Kesehatan Kementerian Bengkulu Indonesia Department of Management Universitas Malikussaleh Aceh Indonesia Departemen of Nursing Universitas Dehasen Bengkulu Indonesia Faculty of Information Technology Universitas Stikubank Semarang Indonesia

Data Envelopment Analysis (DEA) method is a linear programming approach that has been widely used as a framework for evaluating efficiency and measurement. DEA decision making is often faced with situations where the existing DMU has input and output that contains fuzzy and hesitant elements so that it is difficult to make efficiency measurements. This study will design a DEA model in the state of inputs and outputs that contain hesitant elements by using polyhedral uncertainty sets. The results of this study are expected to produce a benchmarking model with DEA that can overcome the hesitant element and have the advantage of using a polyhedral uncertainty set that can measure the linearity of the nominal problem. © Published under licence by IOP Publishing Ltd.

关键词： Data envelopment analysis

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Business Platform Model for Smart Home for technology Planning Task Force

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IOP Conference Series: Materials Science and Engineering 2019年第2期662卷

作者： Melyani Melyani Raymond Kosala Benny Ranti Suhono Supangkat Ford Lumban Gaol System Information STMIK Nusa Mandiri Bekasi Indonesia Computer Science Department Binus Graduated Program- Doctor of Computer Science Bina Nusantara University Jakarta Indonesia STEI Bandung Institute of Technology Bandung Indonesia

In this study we used an architectural research method based on the Open Services Gateway Initiative and Mobile Agent technology, which is a model for analyzing smart home business platforms for technology governance planning tasks that include the recommended decision flow process and as recommendations from established business models and expanded to include a series of additional parameters needed to produce a business platform so that it can analyze the business model offered by the developer and detailed analysis of proposed governance in the service sector. And finally this research produces a Framework that presents a technology governance model for updating strategic plans and governance models for technology and frameworks designed to meet the needs of the elderly population and as recommendations for smart home management that aim to measurably improve the welfare of people in Indonesia. The proposed model and strategy recognizes the diversity of the community with existing providers of household tools and developers to optimize resources to achieve the goals and objectives of elderly smart home residents

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Understanding and applying biological resilience, from genes to ecosystems

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NPJ Biodiversity 2023年第1期2卷 16页

作者： Thorogood, Rose Mustonen, Ville Aleixo, Alexandre Aphalo, Pedro J. Asiegbu, Fred O. Cabeza, Mar Cairns, Johannes Candolin, Ulrika Cardoso, Pedro Eronen, Jussi T. Hällfors, Maria Hovatta, Iiris Juslén, Aino Kovalchuk, Andriy Kulmuni, Jonna Kuula, Liisa Mäkipää, Raisa Ovaskainen, Otso Pesonen, Anu-Katriina Primmer, Craig R. Saastamoinen, Marjo Schulman, Alan H. Schulman, Leif Strona, Giovanni Vanhatalo, Jarno HiLIFE Helsinki Institute of Life Science University of Helsinki Helsinki Finland Research Programme in Organismal & Evolutionary Biology Faculty of Biological and Environmental Sciences University of Helsinki Helsinki Finland Department of Computer Science Faculty of Science University of Helsinki Helsinki Finland Helsinki Institute for Information Technology University of Helsinki Helsinki Finland Institute of Biotechnology HiLIFE Helsinki Institute for Life Science University of Helsinki Helsinki Finland LUOMUS Finnish Museum of Natural History University of Helsinki Helsinki Finland Viikki Plant Science Centre University of Helsinki Helsinki Finland Department of Forest Sciences Faculty of Agriculture and Forestry University of Helsinki Helsinki Finland HELSUS Helsinki Institute of Sustainability Science University of Helsinki Helsinki Finland CE3C - Centre for Ecology Evolution and Environmental Changes CHANGE—Global Change and Sustainability Institute Faculty of Sciences University of Lisbon Lisbon 1749-016 Portugal Research Programme in Ecosystems and Environment Faculty of Biological and Environmental Sciences University of Helsinki Helsinki Finland BIOS Research Unit Helsinki Finland Research Centre for Ecological Change Faculty of Biological and Environmental Sciences University of Helsinki Helsinki Finland Syke Finnish Environment Institute Helsinki Finland SleepWell Research Program Faculty of Medicine University of Helsinki Helsinki Finland Department of Psychology and Logopedics Faculty of Medicine University of Helsinki Helsinki Finland Neuroscience Center HiLIFE Helsinki Institute for Life Science University of Helsinki Helsinki Finland VTT Technical Research Centre of Finland Ltd Espoo Finland Department of Evolutionary and Population Biology Institute for Biodiversity and Ecosystem Dynamics University of Amsterdam Amsterdam Netherlands Natural Resources Institute Finland (Luke) Helsinki Finland Centre for Biodiversity Dynamics

The natural world is under unprecedented and accelerating pressure. Much work on understanding resilience to local and global environmental change has, so far, focussed on ecosystems. However, understanding a system’s behaviour requires knowledge of its component parts and their interactions. Here we call for increased efforts to understand ‘biological resilience’, or the processes that enable components across biological levels, from genes to communities, to resist or recover from perturbations. Although ecologists and evolutionary biologists have the tool-boxes to examine form and function, efforts to integrate this knowledge across biological levels and take advantage of big data (e.g. ecological and genomic) are only just beginning. We argue that combining eco-evolutionary knowledge with ecosystem-level concepts of resilience will provide the mechanistic basis necessary to improve management of human, natural and agricultural ecosystems, and outline some of the challenges in achieving an understanding of biological resilience. © The Author(s) 2023.

关键词： Ecology Biodiversity Community ecology Ecological modelling Ecosystem ecology Evolutionary ecology Molecular ecology Palaeoecology

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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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Retraction notice to "A deep learning approach based on graphs to detect plantation lines" [Heliyon Volume 10, Issue 11, 15 June 2024, e31730]

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Heliyon 2024年第23期10卷 e40689页

作者： Diogo Nunes Gonçalves José Marcato Junior Mauro Dos Santos de Arruda Vanessa Jordão Marcato Fernandes Ana Paula Marques Ramos Danielle Elis Garcia Furuya Lucas Prado Osco Hongjie He Lucio André de Castro Jorge Jonathan Li Farid Melgani Hemerson Pistori Wesley Nunes Gonçalves Faculty of Computer Science Federal University of Mato Grosso do Sul Av. Costa e Silva Campo Grande 79070-900 MS Brazil. Faculty of Engineering Architecture and Urbanism and Geography Federal University of Mato Grosso do Sul Av. Costa e Silva Campo Grande 79070-900 MS Brazil. Faculty of Agricultural Sciences Federal University of Grande Dourados Av. Costa e Silva Dourados 79070-900 MS Brazil. Faculty of Science and Technology São Paulo State University (UNESP) R. Roberto Simonsen 305 Presidente Prudente 19060-900 SP Brazil. Program of Environment and Regional Developement University of Western São Paulo Raposo Tavares km 572 Presidente Prudente 19067-175 SP Brazil. Department of Geography and Environmental Management University of Waterloo Waterloo ON N2L 3G1 Canada. National Research Center of Development of Agricultural Instrumentation Brazilian Agricultural Research Agency (EMBRAPA) 13560-970 R. XV de Novembro 1452 São Carlos SP Brazil. Department of Information Engineering and Computer Science University of Trento Trento 38122 Italy. INOVISAO Dom Bosco Catholic University Avenida Tamandaré 6000 Campo Grande 79117-900 MS Brazil.

[This retracts the article DOI: 10.1016/***.2024.e31730.].

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A deep learning approach based on graphs to detect plantation lines

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Heliyon 2024年第11期10卷 e31730页

Identifying plantation lines in aerial images of agricultural landscapes is re-quired for many automatic farming processes. Deep learning-based networks are among the most prominent methods to learn such patterns and extract this type of information from diverse imagery conditions. However, even state-of-the-art methods may stumble in complex plantation patterns. Here, we propose a deep learning approach based on graphs to detect plantation lines in UAV-based RGB imagery, presenting a challenging scenario containing spaced plants. The first module of our method extracts a feature map throughout the backbone, which consists of the initial layers of the VGG16. This feature map is used as an input to the Knowledge Estimation Module (KEM), organized in three concatenated branches for detecting 1) the plant positions, 2) the plantation lines, and 3) the displacement vectors between the plants. A graph modeling is applied considering each plant position on the image as vertices, and edges are formed between two vertices (i.e. plants). Finally, the edge is classified as pertaining to a certain plantation line based on three probabilities (higher than 0.5): i) in visual features obtained from the backbone; ii) a chance that the edge pixels belong to a line, from the KEM step; and iii) an alignment of the displacement vectors with the edge, also from the KEM step. Experiments were conducted initially in corn plantations with different growth stages and patterns with aerial RGB imagery to present the advantages of adopting each module. We assessed the generalization capability in the other two cultures (orange and eucalyptus) datasets. The proposed method was compared against state-of-the-art deep learning methods and achieved superior performance with a significant margin considering all three datasets. This approach is useful in extracting lines with spaced plantation patterns and could be implemented in scenarios where plantation gaps occur, generating lines with few-to-no

关键词： Aerial imagery Convolutional neural networks Object detection Remote sensing UAV

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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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