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IEEE International Conference on Intelligent Transportation Systems

作者： David Jimenez Fabian Munoz Sebastian Arias Juan Hincapie Faculty of Engineering Program of Computer Science Member of the Sirius Research Group Universidad Tecnologica de Pereira Faculty of Engineering Program of Computer Science Director of the Sirius Research group Universidad Tecnologica de Pereira

ISBN: (纸本)9781509018901

Calibration is an important process in traffic microsimulation modelling since it enables to represent reality more accurately. In this research we present a general methodology for the calibration process and develop a calibration software for Transmodcler traffic microsimulation. This software follows this methodology and has specific methods for its main steps. We propose an experiment design model to select parameters. In addition we used two genetic algorithms to search the optimal values for the parameters. Besides, this software presents an innovative module to explore and visualize the output of the calibration process. In this paper we present the general design of the software which we tested, alongside our methodology, in a case of study in the city of Pereira, Colombia. The results show that it can find optimal values for the parameters and give the user a global view of the process. It indicates that this software has the capability to calibrate traffic microsimulation models.

关键词： computer software Microsimulation computer programs Calibration Traffic Software design overall design Genetic Algorithm (GA)

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Author Correction: Federated learning enables big data for rare cancer boundary detection

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Nature communications 2023年第1期14卷 436页

作者： Sarthak Pati Ujjwal Baid Brandon Edwards Micah Sheller Shih-Han Wang G Anthony Reina Patrick Foley Alexey Gruzdev Deepthi Karkada Christos Davatzikos Chiharu Sako Satyam Ghodasara Michel Bilello Suyash Mohan Philipp Vollmuth Gianluca Brugnara Chandrakanth J Preetha Felix Sahm Klaus Maier-Hein Maximilian Zenk Martin Bendszus Wolfgang Wick Evan Calabrese Jeffrey Rudie Javier Villanueva-Meyer Soonmee Cha Madhura Ingalhalikar Manali Jadhav Umang Pandey Jitender Saini John Garrett Matthew Larson Robert Jeraj Stuart Currie Russell Frood Kavi Fatania Raymond Y Huang Ken Chang Carmen Balaña Jaume Capellades Josep Puig Johannes Trenkler Josef Pichler Georg Necker Andreas Haunschmidt Stephan Meckel Gaurav Shukla Spencer Liem Gregory S Alexander Joseph Lombardo Joshua D Palmer Adam E Flanders Adam P Dicker Haris I Sair Craig K Jones Archana Venkataraman Meirui Jiang Tiffany Y So Cheng Chen Pheng Ann Heng Qi Dou Michal Kozubek Filip Lux Jan Michálek Petr Matula Miloš Keřkovský Tereza Kopřivová Marek Dostál Václav Vybíhal Michael A Vogelbaum J Ross Mitchell Joaquim Farinhas Joseph A Maldjian Chandan Ganesh Bangalore Yogananda Marco C Pinho Divya Reddy James Holcomb Benjamin C Wagner Benjamin M Ellingson Timothy F Cloughesy Catalina Raymond Talia Oughourlian Akifumi Hagiwara Chencai Wang Minh-Son To Sargam Bhardwaj Chee Chong Marc Agzarian Alexandre Xavier Falcão Samuel B Martins Bernardo C A Teixeira Flávia Sprenger David Menotti Diego R Lucio Pamela LaMontagne Daniel Marcus Benedikt Wiestler Florian Kofler Ivan Ezhov Marie Metz Rajan Jain Matthew Lee Yvonne W Lui Richard McKinley Johannes Slotboom Piotr Radojewski Raphael Meier Roland Wiest Derrick Murcia Eric Fu Rourke Haas John Thompson David Ryan Ormond Chaitra Badve Andrew E Sloan Vachan Vadmal Kristin Waite Rivka R Colen Linmin Pei Murat Ak Ashok Srinivasan J Rajiv Bapuraj Arvind Rao Nicholas Wang Ota Yoshiaki Toshio Moritani Sevcan Turk Joonsang Lee Snehal Prabhudesai Fanny Morón Jacob Mandel Konstantinos Kamnitsas Ben Glocker Luke V M Dixon Matthew Williams Peter Zamp Center for Biomedical Image Computing and Analytics (CBICA) University of Pennsylvania Philadelphia PA USA. Department of Radiology Perelman School of Medicine University of Pennsylvania Philadelphia PA USA. Department of Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania Philadelphia PA USA. Department of Informatics Technical University of Munich Munich Bavaria Germany. Intel Corporation Santa Clara CA USA. Department of Neuroradiology Heidelberg University Hospital Heidelberg Germany. Clinical Cooperation Unit Neuropathology German Cancer Consortium (DKTK) within the German Cancer Research Center (DKFZ) Heidelberg Germany. Department of Neuropathology Heidelberg University Hospital Heidelberg Germany. Division of Medical Image Computing German Cancer Research Center Heidelberg Germany. Pattern Analysis and Learning Group Department of Radiation Oncology Heidelberg University Hospital Heidelberg Germany. Neurology Clinic Heidelberg University Hospital Heidelberg Germany. Department of Radiology & Biomedical Imaging University of California San Francisco San Francisco CA USA. Symbiosis Center for Medical Image Analysis Symbiosis International University Pune Maharashtra India. Department of Neuroimaging and Interventional Radiology National Institute of Mental Health and Neurosciences Bangalore Karnataka India. Department of Radiology School of Medicine and Public Health University of Wisconsin Madison WI USA. Department of Medical Physics School of Medicine and Public Health University of Wisconsin Madison WI USA. Leeds Teaching Hospitals Trust Department of Radiology Leeds UK. Department of Radiology Brigham and Women's Hospital Harvard Medical School Boston MA USA. Athinoula A. Martinos Center for Biomedical Imaging Massachusetts General Hospital Charlestown MA USA. Catalan Institute of Oncology Badalona Spain. Consorci MAR Parc de Salut de Barcelona Catalonia Spain. Department of Radiology (IDI

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How I Got into Microwaves-By Chance ...

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IEEE MICROWAVE MAGAZINE 2016年第9期17卷 130-130页

作者： Gardiol, Fred Biomedical Engineering Program and the Department of Electrical and Computer Engineering (ECE) Western University Informatics Center Federal University of Pernambuco - UFPE Recife Brazil

Reports on the author's experiences and education in the field of microwave engineering.

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Brains as Optimal Emergent Turing Machines

Brains as Optimal Emergent Turing Machines

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International Joint Conference on Neural Networks

作者： Juyang Weng Department of Computer Science and Engineering Cognitive Science Program and Neuroscience Program Michigan State University East Lansing 48824 USA

ISBN: (纸本)9781509006212

The theory and experiments outlined in Weng 2015 [1] modeled brains as naturally emerging Turing Machines (TMs) inside Developmental Networks (DNs) - a new class of brain inspired neural networks. However, TMs originally proposed by Alan Turing 1936 [2] were deterministic. If they involved probability to handle uncertainty, the probability was in the mind of the human programmer for a specific task. Although the task-specific program will run on a Universal TM - a model of the popular Von Neumann computers - the Universal TM itself had no imbedded probability. Yet, each brain samples from infinitely many stimuli and actions through the real word, unlike a TM that deals with only tape-symbols from a finite and static alphabet. Computationally, is a brain optimal? If the answer is yes, in what sense? This theoretical work reports the overall brain optimality. It shows that a biological brain, modeled by the DN, is optimal in the sense of maximum likelihood, conditioned on (1) the genome program - the Developmental program (DP) that regulates the development of body, sensors, effectors and the limited computational resource (e.g., brain size and types of neural transmitters), and (2) the incremental lifetime experience - including teaching from the environments and self exploration and discovery through the real world.

关键词： Brain modeling Computational modeling Hidden Markov models Turing machines Biological neural networks computers Neurons

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Iterative segmented least square method for functional microRNA-mRNA module discovery in breast cancer

Iterative segmented least square method for functional micro...

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IEEE International Conference on Bioinformatics and Biomedicine

作者： Sungmin Rhee Sangsoo Lim Sun Kim Computer Science and Engineering Seoul National University Republic of Korea Interdisciplinary Program in Bioinformatics Seoul National University Republic of Korea Computer Science and Engineering Interdisciplinary Program in Bioinformatics Seoul National University Republic of Korea

ISBN: (纸本)9781509016129

MicroRNAs (miRNAs) have significant biological roles at the molecular level by regulating genes post-transcriptionally. To understand the functional effects of miRNAs in different biological contexts, it is essential to elucidate miRNA -mRNA regulatory modules (MRMs). The computational complexity for inferencing MRMs is very high due to the many-to-many relationships between miRNAs and mRNAs and inferencing MRMs is still a challenging unresolved problem. In this paper, we propose a novel iterative segmented least square method for functional MRM discovery. Our method operates in two steps: 1) grouping and ordering the miRNAs and mRNAs to build per-sample matrices representing miRNA-mRNA regulations, and 2) determining maximum sized modules from structured miRNA-mRNA matrices. In experiments with human breast cancer data sets from TCGA, we show that our method outperforms existing methods in terms of both GO similarity and cluster evaluation. In addition, we show that modules determined by our method can be used for breast cancer survival prediction and subtype classification.

关键词： Optimization microRNA Regulatory network inference

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A Taxonomy on Accountability and Privacy Issues in Smart Grids

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IOP Conference Series: Earth and Environmental Science 2017年第1期73卷

作者： Ameya Naik Hamid Shahnasser Electrical & Computer Engineering Program San Francisco State University San Francisco U.S.A

Cyber-Physical Systems (CPS) are combinations of computation, networking, and physical processes. Embedded computers and networks monitor control the physical processes, which affect computations and vice versa. Two applications of cyber physical systems include health-care and smart grid. In this paper, we have considered privacy aspects of cyber-physical system applicable to smart grid. Smart grid in collaboration with different stockholders can help in the improvement of power generation, communication, circulation and consumption. The proper management with monitoring feature by customers and utility of energy usage can be done through proper transmission and electricity flow; however cyber vulnerability could be increased due to an increased assimilation and linkage. This paper discusses various frameworks and architectures proposed for achieving accountability in smart grids by addressing privacy issues in Advance Metering Infrastructure (AMI). This paper also highlights additional work needed for accountability in more precise specifications such as uncertainty or ambiguity, indistinct, unmanageability, and undetectably.

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Systematic literature review: comparison study of symmetric key and asymmetric key algorithm

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

作者： Priasnyomo Prima Santoso Elkin Rilvani Ahmad Budi Trisnawan Krisna Adiyarta Darmawan Napitupulu Tata Sutabri Robbi Rahim Program Studi Magister Ilmu Komputer Universitas Budi Luhur Jakarta Indonesia Research Center for Quality System and Testing Technology Indonesian Institute of Sciences Banten Indonesia Fakultas Teknologi Informasi Universitas Respati Indonesia Jakarta Indonesia School of Computer and Communication Engineering Universiti Malaysia Perlis Malaysia

Cryptography is a science that studies how to keep data or messages safe when sent, from sender to recipient without interference from third parties. This paper presents a comparison of cryptographic algorithms of simetris keys and asymmetric keys. Cryptographic research related journals are collected and analyzed to find the correct comparison of cryptographic algorithms to implement. The results of this study, namely: symmetric and asymmetric keys have differences in the process of encryption and decryption. There are many cryptographic algorithms that can be applied to symmetric and asymmetric keys, but the selection and use of certain algorithms cannot be said to be forever the best because they depend on the circumstances encountered in developing the applied system.

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Genetic variation of somaclonal mutants from the 8th generation of Pekalongan accession rodent tuber (typhonium flagelliforme lodd.) based on RAPD-PCR analysis

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IOP Conference Series: Earth and Environmental Science 2018年第1期195卷

作者： Ragapadmi Purnamaningsih Nesti Fronika Sianipar Khoirunnisa Assidqi Harco Leslie Hendric Spits Warnars Indonesia Center for Agricultural Biotechnology and Genetic Resources Research and Development (BB-Biogen) Bogor 16111 Indonesia Food Technology Department Faculty of Engineering Bina Nusantara University Jakarta Indonesia 11480 Research Interest Group Food Biotechnology Bina Nusantara University Jakarta 11480 Indonesia Computer Science Department BINUS Graduate Program – Doctor of Computer Science Bina Nusantara University Jakarta 11480 Indonesia

Rodent tuber is a potential plant which can be developed as an anticancer drug. The rodent tuber plant has a low anticancer compound which does not have an economic value to be utilized on an industrial scale, particularly to explore as an anticancer drug. The material plant was used 30 clones of Rodent Tuber Pekalongan to increase its bioactive compounds using a combination of in vitro culture with gamma-ray irradiation. The selection process has been done until the 8th generation and obtained 14 somaclonal mutants that have higher bioactive compounds than control plant (non-mutant). This study aimed to analyze the genetic variation of 14 somaclonal mutants of rodent tuber using RAPD with 14 primers. The results were produced 513 total bands with the size of 200-5000 bp and 380 polymorphic bands between somaclonal mutants. OPB-18 primer produced the most polymorphic bands and five specific polymorphic bands of 1336 bp, 1070 bp, 901 bp, 861 bp and 728 bp in the somaclonal mutant M23 (20-4-2-1-1-1). OPD-20 primer produced seven specific polymorphic bands of 1574 bp, 1557 bp, 1501 bp, 1496 bp, 1234 bp, 1229 bp and 1086 bp in the M23 somaclonal mutant. The phylogenetic analysis showed that there were two main groups with the coefficient similarity between 0.77 and 0.83. The highest genetic variation obtained was found in the M23 somaclonal mutant with a genetic difference of 23% compared with control. There are five somaclonal mutants (M24, M22, M21, M16, M14) that have a genetic variation of up to 22% over the control. This study shows that OPB-18 and OPD-20 primers were efficient in detecting somaclonal mutant variants.

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Organization model for information system project: a literature review & blended learning case

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

作者： Krisna Adiyarta Mohammad Syafrullah Darmawan Napitupulu Tata Sutabri Robbi Rahim Program Studi Magister Ilmu Komputer Universitas Budi Luhur Jakarta Indonesia Research Center for Quality System and Testing Technology Indonesian Institute of Sciences Banten Indonesia Fakultas Teknologi Informasi Universitas Respati Indonesia Jakarta Indonesia School of Computer and Communication Engineering Universiti Malaysia Perlis Malaysia

Along with the development of information technology today, the development of information systems is also increasing. Organizations and personal competitions to make an information system. A reliable information system is produced by a team that has the ability to design, design and validate. With the increasing number of students at XYZ College and limited existing building facilities then one of the solutions that will be applied is the development of e-learning system to support teaching and learning activities. One important element in project management is determining the organizational model to be used. The purpose of this study is to determine whether the organization model is effective to manage the e-learning system project in the PT. The research method used is literature study and interviews with key stakeholders, especially leaders of universities. The results show that the effective organizational model for the blended learning information system project is to use functional organizational structure, since functional organization is more appropriate for small to medium scale projects, focusing on the division of tasks based on the function of each part, the difficulty level is low and the limitationof resources.

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Information Extraction to Improve Link Prediction in Scientific Social Networks

Information Extraction to Improve Link Prediction in Scienti...

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IEEE International Conference on computer Supported Cooperative Work in Design

作者： Victor Stroele Fernanda Campos Crystiam K. Pereira Geraldo Zimbrao Jano M. Souza PGCC - Postgraduate Program in Computer Science UFJF - Federal University of Juiz de Fora COPPE - Systems Engineering and Computer Program UFRJ - Federal University of Rio de Janeiro

ISBN: (纸本)9781509019168

Link Prediction is a classic social networks analysis problem. Knowing in advance future actions in social network can help, for example, agents decision. Link Prediction techniques are based on metrics that have different approaches. In this paper, we model a multi-relational scientific social network to assess the impact of content extraction on topological metrics. Thus, a metric composed of topological and semantic approach is proposed to solve link prediction problem. The results were compared with those presented by Katz metric.

关键词： Information Extraction Link Prediction Scientific Social Network

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