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Metasurfaces: Coherent Perfect Diffraction in Metagratings (Adv. Mater. 36/2020)

Advanced Materials 2020年第36期32卷

作者： Ziying Zhang Ming Kang Xueqian Zhang Xi Feng Yuehong Xu Xieyu Chen Huifang Zhang Quan Xu Zhen Tian Weili Zhang Alex Krasnok Jiaguang Han Andrea Alù Center for Terahertz Waves College of Precision Instrument and Optoelectronics Engineering Key Laboratory of Optoelectronics Information and Technology Tianjin University Tianjin 300072 P. R. China Department of Electrical and Computer Engineering The University of Texas at Austin Austin TX 78712 USA School of Electrical and Computer Engineering Oklahoma State University Stillwater OK 74078 USA Photonics Initiative Advanced Science Research Center City University of New York New York NY 10031 USA Physics Program Graduate Center City University of New York New York NY 10016 USA

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Load balancing factor using greedy algorithm in the routing protocol for improving internet access

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IOP Conference Series: Materials Science and Engineering 2018年第1期420卷

作者： Ady Satria Poltak Sihombing Sawaluddin Informatics Engineering Study Program Magister Faculty of Computer Science and Information Technology University of Sumatera Utara

Load Balancing is very well applied to the distribution of internet access at any point of the Wi-Fi area so that the use of limited devices can be optimal and on target. The proper use of the Greedy Algorithms when applied to an access point device is very capable in resolving excessive loading in a single resource to take the best choice at every stage in an optimum process. Access point device is also a success factor in running the optimization of the distribution of Wi-Fi access on the Access Point is strongly influenced by the parameters set. In this research, user access factor in one very high Wi-Fi area also influences the possibility of incoming access failure. For the application of the results of this study can be utilized on all access point devices that have limits, but for speed internet access remains at the capacity provided bandwidth.

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Role of Integrating Diffusion Mr Image-Markers with Clinical-Biomarkers For Early Assessment of Renal Transplants

Role of Integrating Diffusion Mr Image-Markers with Clinical...

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IEEE International Conference on Image Processing

作者： Mohammad Shehata Mohammed Ghazal Garth Beache Mohamed Abou EI-Ghar Amy Dwyer Hassan Hajjdiab Ashraf Khalil Ayman EI-Baz Bioengineering Department University of Louisville Louisville KY USA Radiology Department University of Louisville Louisville KY USA Radiolozy Department Mansoura University Mansoura Egypt Kidney Disease Program University of Louisville Louisville KY USA Electrical and Computer Engineering Department Abu Dhabi University Abu Dhabi UAE Computer Science and Information Technology Department Abu Dhabi University Abu Dhabi UAE

Recently, diffusion-weighted magnetic resonance imaging (DW-MRI) has been explored for non-invasive assessment of renal transplant functions. In this paper, a computer-aided diagnostic (CAD) system is developed to assess renal transplant functionality, which integrates both clinical and diffusion MRI -derived markers extracted from 4D DW-MRI (i.e. 3D + b-value). To extract the DW-MR image-markers, our framework performs multiple image processing steps, including kidney segmentation using a level-set approach and estimation of image-markers. To extract these image-markers, apparent diffusion coefficients (ADCs) are estimated from the segmented DW-MRIs and cumulative distribution functions (CDFs) of the ADCs are constructed at different b-values (i.e. gradient field strengths and duration). Finally, these markers (i.e. CDFs) are integrated with clinical biomarkers (e.g., creatinine clearance and serum plasma creatinine) to assess transplant status using stacked auto-encoders with non-negativity constraints based on deep learning classification approach. Our CAD system consists of two consecutive classification stages. The first stage classifier achieved a 96% accuracy, a 95% sensitivity, and a 100% specificity in distinguishing non-rejection (NR) from dysfunctional (DF) transplanted kidneys. Additionally, an overall accuracy of 94% has been obtained in the second stage in separating DF to acute rejection (AR) and different renal disease (DRD) transplants. Our preliminary results hold strong promise that the presented CAD system is of a high reliability to non-invasively diagnose renal transplant status.

关键词： Kidney Diseases Three-dimensional displays Image segmentation Magnetic resonance imaging Machine learning Radio frequency

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QU-BraTS: MICCAI BraTS 2020 Challenge on Quantifying Uncertainty in Brain Tumor Segmentation - Analysis of Ranking Scores and Benchmarking Results

arXiv

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arXiv 2021年

作者： Mehta, Raghav Filos, Angelos Baid, Ujjwal Sako, Chiharu McKinley, Richard Rebsamen, Michael Dätwyler, Katrin Meier, Raphael Radojewski, Piotr Murugesan, Gowtham Krishnan Nalawade, Sahil Ganesh, Chandan Wagner, Ben Yu, Fang F. Fei, Baowei Madhuranthakam, Ananth J. Maldjian, Joseph A. Daza, Laura Gómez, Catalina Arbeláez, Pablo Dai, Chengliang Wang, Shuo Reynaud, Hadrien Mo, Yuanhan Angelini, Elsa Guo, Yike Bai, Wenjia Banerjee, Subhashis Pei, Linmin Murat, A.K. Rosas-González, Sarahi Zemmoura, Ilyess Tauber, Clovis Vu, Minh H. Nyholm, Tufve Löfstedt, Tommy Ballestar, Laura Mora Vilaplana, Veronica McHugh, Hugh Talou, Gonzalo Maso Wang, Alan Patel, Jay Chang, Ken Hoebel, Katharina Gidwani, Mishka Arun, Nishanth Gupta, Sharut Aggarwal, Mehak Singh, Praveer Gerstner, Elizabeth R. Kalpathy-Cramer, Jayashree Boutry, Nicolas Huard, Alexis Vidyaratne, Lasitha Rahman, Md Monibor Iftekharuddin, Khan M. Chazalon, Joseph Puybareau, Elodie Tochon, Guillaume Ma, Jun Cabezas, Mariano Llado, Xavier Oliver, Arnau Valencia, Liliana Valverde, Sergi Amian, Mehdi Soltaninejad, Mohammadreza Myronenko, Andriy Hatamizadeh, Ali Feng, Xue Dou, Quan Tustison, Nicholas Meyer, Craig Shah, Nisarg A. Talbar, Sanjay Weber, Marc-André Mahajan, Abhishek Jakab, Andras Wiest, Roland Fathallah-Shaykh, Hassan M. Nazeri, Arash Milchenko, Mikhail Marcus, Daniel Kotrotsou, Aikaterini Colen, Rivka Freymann, John Kirby, Justin Davatzikos, Christos Menze, Bjoern Bakas, Spyridon Gal, Yarin Arbel, Tal McGill University MontrealQC Canada Group University of Oxford Oxford United Kingdom University of Pennsylvania PhiladelphiaPA United States Department of Radiology Perelman School of Medicine The University of Pennsylvania PhiladelphiaPA United States Department of Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States University Institute of Diagnostic and Interventional Neuroradiology University of Bern Inselspital Bern University Hospital Bern Switzerland Department of Radiology University of Texas Southwestern Medical Center DallasTX United States Department of Bioengineering University of Texas DallasTX United States Advanced Imaging Research Center University of Texas Southwestern Medical Center DallasTX United States Universidad de los Andes Bogotá Colombia Data Science Institute Imperial College London London United Kingdom NIHR Imperial BRC ITMAT Data Science Group Imperial College London London United Kingdom Department of Brain Sciences Imperial College London London United Kingdom Machine Intelligence Unit Indian Statistical Institute Kolkata India Department of CSE University of Calcutta Kolkata India Department of Information Technology Uppsala University Uppsala Sweden Department of Diagnostic Radiology The University of Pittsburgh Medical Center PittsburghPA United States UMR U1253 iBrain Université de Tours Inserm Tours France Department of Radiation Sciences Umeå University Umeå Sweden Department of Computing Science Umeå University Umeå Sweden Signal Theory and Communications Department Universitat Politècnica de Catalunya Barcelona Tech Barcelona Spain Faculty of Medical and Health Sciences University of Auckland Auckland New Zealand Radiology Department Auckland City Hospital Auckland New Zealand Auckland Bioengineering Institute University of Auckland New Zealand Athinoula A. Martinos Center for Biomedical Imaging Department of Radiology

Deep learning (DL) models have provided state-of-the-art performance in various medical imaging benchmarking challenges, including the Brain Tumor Segmentation (BraTS) challenges. However, the task of focal pathology multi-compartment segmentation (e.g., tumor and lesion sub-regions) is particularly challenging, and potential errors hinder translating DL models into clinical workflows. Quantifying the reliability of DL model predictions in the form of uncertainties could enable clinical review of the most uncertain regions, thereby building trust and paving the way toward clinical translation. Several uncertainty estimation methods have recently been introduced for DL medical image segmentation tasks. Developing scores to evaluate and compare the performance of uncertainty measures will assist the end-user in making more informed decisions. In this study, we explore and evaluate a score developed during the BraTS 2019 and BraTS 2020 task on uncertainty quantification (QU-BraTS) and designed to assess and rank uncertainty estimates for brain tumor multi-compartment segmentation. This score (1) rewards uncertainty estimates that produce high confidence in correct assertions and those that assign low confidence levels at incorrect assertions, and (2) penalizes uncertainty measures that lead to a higher percentage of under-confident correct assertions. We further benchmark the segmentation uncertainties generated by 14 independent participating teams of QU-BraTS 2020, all of which also participated in the main BraTS segmentation task. Overall, our findings confirm the importance and complementary value that uncertainty estimates provide to segmentation algorithms, highlighting the need for uncertainty quantification in medical image analyses. Finally, in favor of transparency and reproducibility, our evaluation code is made publicly available at https://***/RagMeh11/QU-BraTS. © 2021, CC BY.

关键词： Benchmarking

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Implementation of Apriori Algorithm for Analysis of Consumer Purchase Patterns

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Journal of Physics: Conference Series 2019年第1期1255卷

作者： Suprianto Panjaitan Sulindawaty Muhammad Amin Sri Lindawati Ronal Watrianthos Hengki Tamando Sihotang Bosker Sinaga Teknik Informatika STMIK Pelita Nusantara Medan Sumatera Utara Indonesia Doctoral Program Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan-Indonesia Program Doctoral Vocational Technology Education Postgraduate Engineering Faculty Padang State University Padang West Sumatera-Indonesia Manajemen Informatika AMIK Logika Sumatera Utara Indonesia Manajemen Informatika AMIK Labuhan Batu Sumatera Utara indonesia

Consumer purchasing patterns are a form of purchases made by consumers, whether someone or a lot of people to get the desired item by making a purchase transaction. One characteristic of the purchase pattern is the existence of acquiring something through exchanging money. This study aims to create an application that is used in determining consumer purchasing patterns by applying a priori algorithms and using Visual Basic 2010 as a tool for determining consumer purchase patterns. This application uses a priori algorithm calculation method where the sample consumer purchase data will be sorted and calculated by providing the value of the minium support and configuration parameters and based on the results of confidence the largest number of conclusions such as: can be used as information for determining sales, the application of a priori algorithms can provide information pattern combination item set from consumer purchase data that is with support above 15% and confidence above 50% on item set.

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Web based testing application security system using semantic comparison method 2

Web based testing application security system using semantic...

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2nd Nommensen International Conference on technology and Engineering, NICTE 2018

作者： Iskandar, Akbar Fahlepi Tuasamu, Muhammad Resa Syamsu, Suryadi Mansyur, M. Listyorini, Tri Sallu, Sulfikar Supriyono, S. Saddhono, Kundharu Napitupulu, Darmawan Rahim, Robbi Informatics Engineering STMIK AKBA Makassar Indonesia Graduate Program Universitas Negeri Makassar Makassar Indonesia Informatics Engineering Universitas Maria Kudus Central Java Indonesia Computer Information Systems Universitas Sembilan Belas November Kolaka Indonesia Department of Geography Education Universitas Prof Dr Hazairin SH Bengkulu Indonesia Indonesian Language Education Departement Faculty of Teacher Training and Education Universitas Sebelas Maret Surakarta Indonesia Research Center for Quality System and Testing Technology Indonesian Institute of Sciences Indonesia Sekolah Tinggi Ilmu Manajemen Sukma Medan Indonesia

computer and web security system is an attempt to avoid attacks from crackers because a form and method of crime on internet network can not be predicted. Therefore, we just keep trying to use various methods in securing the system that is running. It is the same in web testing that can be accessed online by people who are not responsible from along distance to change and remove the test results or even damage the web testing system. So, the purpose of this paper is to design and implement web security testing system by using semantic comparison method to avoid structured query language injection (SQLI) attack and to do security on web testing application using Message Digest 5 encryption (MD5). Research data were obtained by using direct observation and documentation and literature review. After the design and application of the system, it can be obtained that by using semantic comparison method in web testing can prevent the occurrence of SQL injection attacks and can secure account from web testing users by using MD5. © Published under licence by IOP Publishing Ltd.

关键词： Semantics

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The gap values in the profile matching method by fuzzy logic

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Journal of Physics: Conference Series 2018年第1期978卷 012061-012061页

作者： Sitepu, S A Efendi, S Situmorang, Z Master Program (S2) of Informatics Engineering Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan Indonesia. Master Program of Informatics Engineering Faculty of Computer Science and Information Technology Universitas of Sumatera Utara Medan Indonesia. Department of Computer Science Faculty of Computer Science and Information Technology Universitas St. Thomas Medan Indonesia.

In this research, the determination of the appropriate values of Gap for the assessment of promotion criteria of position in an institution / company. In this study the authors use Fuzzy Sugeno logic on the determination of Gap values used in Profile Matching method. Test results of 5 employees obtained the eligibility of promotion with the position of Z* values between in 3.20 to 4.11.

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Designing an Institutional Research Management System Framework for Higher Education

Designing an Institutional Research Management System Framew...

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International Conference on information Management and technology (ICIMTech)

作者： Noerlina Siti Elda Hiererra Bahtiar Saleh Abbas Brilly Andro Makalew Desi Maya Kristin Tirta Nugraha Mursitama David Information Systems Department Bina Nusantara University Jakarta Indonesia Industrial Engineering Department Bina Nusantara University Jakarta Indonesia Mobile Application & Technology Program Bina Nusantara University Jakarta Indonesia International Relations Department Bina Nusantara University Jakarta Indonesia Computer Science Department Bina Nusantara University Jakarta Indonesia

The following topics are dealt with: Internet; organisational aspects; data analysis; educational institutions; information systems; knowledge management; statistical analysis; further education; computer aided instru... 详细信息

关键词： Manuals Education Proposals information systems Requirements engineering System analysis and design Conferences

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Application of Message Security Application Using Vigenere Cipher Algorithm Utilizing One Time Pad (OTP) Algorithm as a Key Generator

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Journal of Physics: Conference Series 2019年第1期1363卷 012080-012080页

作者： Pardede, A M H Lorena Perbina Br Sitepu Zarlis, Muhammad Tulus Iskandar, Akbar Sriadhi, S Manurung, Rosida Tiurma Nurintan Asyiah Siregar Sari, Ayu Esteka Yunawati, Sri Mursyidah, M Mursalin, M Kurniasih, Nuning Kurniawan, Citra Winarno, Edy STMIK Kaputama Binjai Sumatera Utara Indonesia Department of Computer Science Universitas Sumatera Utara Medan Indonesia Department of Mathematics Universitas Sumatera Utara Medan Indonesia Department of Electrical Engineering Universitas Negeri Medan Indonesia Graduate Program in Scientific Psychology Universitas Kristen Maranatha Indonesia Department of Management STIE Labuhanbatu Sumatera Utara Indonesia Department of Management STIE Sakti Alam Kerinci Jambi Indonesia Program Study of Accounting Pasir Pengaraian University Riau Indonesia Departement of Information Technology and Computer Politeknik Negeri Lhokseumawe Aceh Indonesia Department of Mathematics Education Universitas Malikussaleh Aceh Indonesia Faculty of Communication Sciences Library and Information Science Program Universitas Padjadjaran Bandung Indonesia Department of Electrical Engineering Sekolah Tinggi Teknik Malang Indonesia Faculty of Information Technology Universitas Stikubank Semarang Indonesia

Cryptography is the science and art of maintaining the security of messages when messages are sent from one place to another. One of the ways securing the form of text message information is by the encryption process using the Vigenere Cipher algorithm and utilizing the One Time Pad (OTP) algorithm as a key generator, where the message will be random when it is opened. The message encryption process used the vigenere cipher algorithm while OTP is used to secure the key with the same formula. After this research has been done, an application was designed to secure text messages by converting the text message into a random message so that the message was unreadable due to a secret message that could not be known by others. The results achieved can secure an encrypted message that cannot be reopened and if those messages were reopened, they must be decrypted.

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Analysis backpropagation methods with neural network for prediction of children's ability in psychomotoric

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Journal of Physics: Conference Series 2018年第1期978卷 012085-012085页

作者： Izhari, F Dhany, H W Zarlis, M Sutarman Informatics Engineering Study Program Master Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan Indonesia

A good age in optimizing aspects of development is at the age of 4-6 years, namely with psychomotor development. Psychomotor is broader, more difficult to monitor but has a meaningful value for the child's life because it directly affects his behavior and deeds. Therefore, there is a problem to predict the child's ability level based on psychomotor. This analysis uses backpropagation method analysis with artificial neural network to predict the ability of the child on the psychomotor aspect by generating predictions of the child's ability on psychomotor and testing there is a mean squared error (MSE) value at the end of the training of 0.001. There are 30% of children aged 4-6 years have a good level of psychomotor ability, excellent, less good, and good enough.

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