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IEEE International Conference on Computational Science and engineering, CSE

作者： Elisa Margareth Sibarani Mhd. Nadial Evy Panggabean S. Meryana Informatics Engineering Study Program Del Institute of Technology North Sumatra Indonesia Inf. Eng. Study Program Del Inst. of Technol. Sitoluama Indonesia

Research on Natural Language Processing (NLP) in Indonesian is still limited and the results of available research that can be used for further research are also limited. In a series of natural language processing, the initial step is parsing the sentence in a particular language based on the grammar in order to help understanding the meaning of a sentence. This research aims to produce a simulation of Indonesian parser by adapting the process which was conducted by using Collins Algorithm. The three main stages are: 1) preprocessing to generate corpus and events files, 2) lexical analysis to convert the corpus into tokens, and 3) syntax analysis to build parse tree that requires file events to calculate the probability of the grammar by count the occurrence frequency on file events to determine the best sentence trees. An evaluation was performed to the parser using 30 simple sentences and the outcomes were able to generate a corpus file, file events, parse-tree and probability calculations. Nevertheless some sentences could not be parsed completely true because of the limitations of the Tree bank file in Indonesian. Some future works are to develop complete and valid Tree bank and Lexicon files.

关键词： Grammar Natural language processing Probability Production Probabilistic logic Dictionaries Adaptation models

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Proposed model of Vocational University Governance and measurement model by utilizing the ISO 38500 framework and COBIT 5 enabler

Proposed model of Vocational University Governance and measu...

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International Conference on ICT For Smart Society (ICISS)

作者： Heru Nugroho Kridanto Surendro Computer Engineering Study Program Telkom Polytechnic Bandung Indonesia School of Electrical Engineering and Informatics Bandung Institute of Technology Bandung Indonesia

Enterprise governance basically is a framework, principles and policies, structures, processes and practices, information, skills, culture, ethics, and behavior to determine direction and monitoring related to compliance and performance that align with enterprise goals. COBIT 5 provides guidance that enterprise governance is influenced by individual and collective factors. The existence of this factor will influence process ini scope of governance enterprise either for governance and management area. University governance is a behavior, manner or method used by the college to utilize full potential and optimization elements, in order to achieve the vision and mission that has been set. Model of Vocational University Governance are built based on governance university components and principles of good university governance with reference models that exist within ISO 38500 framework. Enablers that exist within COBIT 5 framework will be used as a determining factor in the preparation of the proposed model of governance and measurement model of vocational university governance.

关键词： Educational institutions Business ISO standards Ethics Monitoring

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Multilayer processing architecture of RAM based neural network with memory optimization for navigation system

Multilayer processing architecture of RAM based neural netwo...

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Joint International Conference on Rural Information & Communication Technology and Electric-Vehicle Technology (rICT & ICeV-T)

作者： Ahmad Zarkasi Aciek Ida Wuryandari Rizki Fauzian Study Program Computer System Sriwijaya University South Sumatera Indonesia School of Electrical Engineering and Informatics Bandung Institute of Technology Bandung Indonesia

Robots also have been trusted to help human to complete difficult jobs, for example, finding for the earthquake, a fire, or a sinking ship victims. The robot must be reliable, clever and moving automatically. The aim of this study is to develop and apply the application of artificial RAM-based neural networks (WNNs) on a mobile robot using a multilayer processing architecture with memory optimizations on to address and input pattern, so that producing smart navigation model which it has a simpler computational load and faster execution time. The gained result from the first study was the percentage of memory optimization in the amount of 50%. This result obtained from the formerly RAM using 8 bit data width has been optimized to 4 bits. Both of the percentage of data optimization pattern is 93.75%. This percentage is obtained from the optimization pattern (pattern taken is 4 bits MSB), each 1 bit data can handle 15 unseen patterns.

关键词： Random access memory Optimization Sensors Nonhomogeneous media Mobile robots Decoding Biological neural networks

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Low cost vision-based 3D localization system for indoor unmanned aerial vehicles

Low cost vision-based 3D localization system for indoor unma...

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IEEE International Conference on Robotics, Biomimetics, and Intelligent Computational Systems (ROBIONETICS)

作者： Stefio Yosse Andrean Endra Joelianto Augie Widyotriatmo Widyawardana Adiprawita Faculty of Industrial Technology Engineering Physics Study Program Bandung Indonesia Instrumentation & Control Research Group ITB Bandung Indonesia School of Electrical Engineering and Informatics Institute of Technology Bandung Bandung Indonesia

The paper presents a method to determine a position of objects in three dimentional coordinates. The proposed method uses a vision-based localization using two low cost cameras. The formulation is derived by using a pin-hole camera principal to project a location of a point in a 2D image into 3D space. This method can be used for indoor unmanned aerial vehicles localization to provide position information for control and navigation purposes.

关键词： Cameras

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Proceedings from the 9th annual conference on the science of dissemination and implementation: Washington, DC, USA. 14-15 December 2016

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Implement Sci 2017年第SUPPL 1期12卷 48-48页

作者： David Chambers Lisa Simpson Gila Neta Ulrica von Thiele Schwarz Antoinette Percy-Laurry Gregory A. Aarons Ross Brownson Amanda Vogel Shannon Wiltsey Stirman Kenneth Sherr Rachel Sturke Wynne E. Norton Allyson Varley Cynthia Vinson Lisa Klesges Suzanne Heurtin-Roberts M. Rashad Massoud Leighann Kimble Arne Beck Claire Neely Jennifer Boggs Carmel Nichols Wen Wan Erin Staab Neda Laiteerapong Nathalie Moise Ravi Shah Susan Essock Margaret Handley Amy Jones Jay Carruthers Karina Davidson Lauren Peccoralo Lloyd Sederer Todd Molfenter Ashley Scudder Sarah Taber-Thomas Kristen Schaffner Amy Herschell Eva Woodward Jeffery Pitcock Mona Ritchie JoAnn Kirchner Julia E. Moore Sobia Khan Shusmita Rashid Jamie Park Melissa Courvoisier Sharon Straus Daniel Blonigen Allison Rodriguez Luisa Manfredi Andrea Nevedal Joel Rosenthal David Smelson Christine Timko Nicole Stadnick Jennifer Regan Miya Barnett Anna Lau Lauren Brookman-Frazee Erick Guerrero Karissa Fenwick Yinfei Kong Gregory Aarons Rebecca Lengnick-Hall Benjamin Henwood Nina Sayer Craig Rosen Robert Orazem Brandy Smith Lindsey Zimmerman David Lounsbury Rachel Kimerling Jodie A. Trafton Steven Lindley Rahul Bhargava Hal Roberts Laura Gibson Gabriel J. Escobar Vincent Liu Benjamin Turk Arona Ragins Patricia Kipnis Ashley Ketterer Gruszkowski Michael W. Kennedy Emily Rentschler Drobek Lior Turgeman Aleksandra Sasha Milicevic Terrence L. Hubert Larissa Myaskovsky Youxu C. Tjader Robert J. Monte Kathryn G. Sapnas Edmond Ramly Diane R Lauver Christie M Bartels Shereef Elnahal Andrea Ippolito Hillary Peabody Carolyn Clancy Randall Cebul Thomas Love Douglas Einstadter Shari Bolen Brook Watts Vera Yakovchenko Angela Park William Lukesh Donald R. Miller David Thornton Mari-Lynn Drainoni Allen L. Gifford Shawna Smith Julia Kyle Mark S Bauer Daniel Eisenberg Celeste Liebrecht Michelle Barbaresso Amy Kilbourne Elyse Park Giselle Perez Jamie Ostroff Sarah Greene Michael Parchman Brian Austin Eric Larson Stefanie Ferreri Chris Shea Megan Smith Kea Turner Jennifer Bacci Kyle Bigham Geoffr Division of Cancer Control and Population Sciences National Cancer Institute Rockville MD 20850 USA AcademyHealth Washington DC 20009 USA Department of Learning Informatics Management and Ethics Karolinska Institutet Stockholm 17177 Sweden Department of Psychiatry University of California San Diego San Diego CA 92093 USA George Warren Brown School of Social Work Washington University in St. Louis St. Louis MO 63130 USA Center for Global Health National Cancer Institute Rockville MD 20850 USA Dissemination and Training Division VA National Center for PTSD Palo Alto CA 94305 USA Department of Global Health University of Washington Seattle WA 98105 USA Center for Global Health Studies Fogarty International Center National Institutes of Health Bethesda MD 20912 USA School of Public Health University of Alabama at Birmingham Birmingham AL 35243 USA School of Public Health University of Memphis Memphis TN 38152 USA USAID Applying Science to Strengthen and Improve Systems (ASSIST) Project Bethesda Maryland 20814 USA Institute for Health Research Kaiser Permanente Denver CO 80231 USA ICSI Institute for Clinical Systems Improvement Bloomington MN 55425 USA Medicine University of Chicago Chicago IL 60637 USA Medicine Columbia University Medical Center New York NY 10032 USA Psychiatry Columbia University New York NY 10032 USA General Internal Medicine Epidemiology and Biostatistics University of California San Francisco San Francisco CA 94110 USA New York State Office of Mental Health New York NY 10001 USA Medicine Icahn School of Medicine at Mount Sinai New York NY 10029 USA Center for Health Enhancement System Studies University of Wisconsin Madison WI 53706 USA Department of Psychiatry University of Pittsburgh Pittsburgh PA 15213 USA Psychology University at Buffalo Buffalo NY 14260 USA Department of Psychology West Virginia University Morgantown WV 26506 USA MIRECC VA North Little Rock AR 72114 USA QUERI for Team-Based Behavioral Health Centr

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Clustering spatial on the GSTAR model for replacement new oil well

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AIP Conference Proceedings 2013年第1期1554卷 205-209页

作者： Budi Nurani Ruchjana Atje Setiawan Abdullah Toni Toharudin I Gede Nyoman Mindra Jaya Department of Mathematics Faculty of Mathematics and Natural Sciences Universitas Padjadjaran Indonesia Informatics Engineering Study Program Faculty of Mathematics and Natural Sciences Universitas Padjadjaran Indonesia Department of Statistics Faculty of Mathematics and Natural Sciences Universitas Padjadjaran Jl Raya Bandung Sumedang Km 21 Jatinangor Sumedang 45363-West Java Indonesia

Space time models such as the Generalized Space Time Autoregressive (GSTAR) is an important theoretical research topics with many applications in large number of areas ranging from the spread of diseases, mining, economic growth, ecology, agriculture and population development. In this paper we introduce a clustering spatial for determining a group of locations for weight matrix of the GSTAR model. We use Ordinary Least Squares method to estimate the parameters of model and apply the result to develop a GSTAR-Kriging model for replacement new oil wells at volcanic field in Jatibarang, West Java-Indonesia.

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Sequence data and association statistics from 12,940 type 2 diabetes cases and controls

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Scientific data 2017年第1期4卷 170179页

作者： Jason Flannick Christian Fuchsberger Anubha Mahajan Tanya M Teslovich Vineeta Agarwala Kyle J Gaulton Lizz Caulkins Ryan Koesterer Clement Ma Loukas Moutsianas Davis J McCarthy Manuel A Rivas John R B Perry Xueling Sim Thomas W Blackwell Neil R Robertson N William Rayner Pablo Cingolani Adam E Locke Juan Fernandez Tajes Heather M Highland Josee Dupuis Peter S Chines Cecilia M Lindgren Christopher Hartl Anne U Jackson Han Chen Jeroen R Huyghe Martijn van de Bunt Richard D Pearson Ashish Kumar Martina Müller-Nurasyid Niels Grarup Heather M Stringham Eric R Gamazon Jaehoon Lee Yuhui Chen Robert A Scott Jennifer E Below Peng Chen Jinyan Huang Min Jin Go Michael L Stitzel Dorota Pasko Stephen C J Parker Tibor V Varga Todd Green Nicola L Beer Aaron G Day-Williams Teresa Ferreira Tasha Fingerlin Momoko Horikoshi Cheng Hu Iksoo Huh Mohammad Kamran Ikram Bong-Jo Kim Yongkang Kim Young Jin Kim Min-Seok Kwon Juyoung Lee Selyeong Lee Keng-Han Lin Taylor J Maxwell Yoshihiko Nagai Xu Wang Ryan P Welch Joon Yoon Weihua Zhang Nir Barzilai Benjamin F Voight Bok-Ghee Han Christopher P Jenkinson Teemu Kuulasmaa Johanna Kuusisto Alisa Manning Maggie C Y Ng Nicholette D Palmer Beverley Balkau Alena Stančáková Hanna E Abboud Heiner Boeing Vilmantas Giedraitis Dorairaj Prabhakaran Omri Gottesman James Scott Jason Carey Phoenix Kwan George Grant Joshua D Smith Benjamin M Neale Shaun Purcell Adam S Butterworth Joanna M M Howson Heung Man Lee Yingchang Lu Soo-Heon Kwak Wei Zhao John Danesh Vincent K L Lam Kyong Soo Park Danish Saleheen Wing Yee So Claudia H T Tam Uzma Afzal David Aguilar Rector Arya Tin Aung Edmund Chan Carmen Navarro Ching-Yu Cheng Domenico Palli Adolfo Correa Joanne E Curran Dennis Rybin Vidya S Farook Sharon P Fowler Barry I Freedman Michael Griswold Daniel Esten Hale Pamela J Hicks Chiea-Chuen Khor Satish Kumar Benjamin Lehne Dorothée Thuillier Wei Yen Lim Jianjun Liu Marie Loh Solomon K Musani Sobha Puppala William R Scott Loïc Yengo Sian-Tsung Tan Herman A Taylor Farook Thameem Gregory Wilson Tien Yin Wong Pål Rasmu Department of Molecular Biology Massachusetts General Hospital Boston Massachusetts USA. Program in Medical and Population Genetics Broad Institute Cambridge Massachusetts USA. Department of Biostatistics and Center for Statistical Genetics University of Michigan Ann Arbor Michigan USA. Wellcome Trust Centre for Human Genetics Nuffield Department of Medicine University of Oxford Oxford UK. Harvard-MIT Division of Health Sciences and Technology Massachusetts Institute of Technology Cambridge Massachusetts USA. Department of Statistics University of Oxford Oxford UK. Genetics of Complex Traits University of Exeter Medical School University of Exeter Exeter UK. MRC Epidemiology Unit Institute of Metabolic Science University of Cambridge Cambridge UK. Department of Twin Research and Genetic Epidemiology King's College London London UK. Oxford Centre for Diabetes Endocrinology and Metabolism Radcliffe Department of Medicine University of Oxford Oxford UK. Department of Human Genetics Wellcome Trust Sanger Institute Hinxton Cambridgeshire UK. School of Computer Science McGill University Montreal Quebec Canada. McGill University and Génome Québec Innovation Centre Montreal Quebec Canada. Human Genetics Center The University of Texas Graduate School of Biomedical Sciences at Houston The University of Texas Health Science Center at Houston Houston Texas USA. Department of Biostatistics Boston University School of Public Health Boston Massachusetts USA. National Heart Lung and Blood Institute's Framingham Heart Study Framingham Massachusetts USA. Medical Genomics and Metabolic Genetics Branch National Human Genome Research Institute National Institutes of Health Bethesda Maryland USA. Department of Biostatistics Harvard School of Public Health Boston Massachusetts USA. Chronic Disease Epidemiology Swiss Tropical and Public Health Institute University of Basel Basel Switzerland. Institute of Genetic Epidemiology Helmholtz Zentrum München German R

To investigate the genetic basis of type 2 diabetes (T2D) to high resolution, the GoT2D and T2D-GENES consortia catalogued variation from whole-genome sequencing of 2,657 European individuals and exome sequencing of 12,940 individuals of multiple ancestries. Over 27M SNPs, indels, and structural variants were identified, including 99% of low-frequency (minor allele frequency [MAF] 0.1-5%) non-coding variants in the whole-genome sequenced individuals and 99.7% of low-frequency coding variants in the whole-exome sequenced individuals. Each variant was tested for association with T2D in the sequenced individuals, and, to increase power, most were tested in larger numbers of individuals (>80% of low-frequency coding variants in ~82 K Europeans via the exome chip, and ~90% of low-frequency non-coding variants in ~44 K Europeans via genotype imputation). The variants, genotypes, and association statistics from these analyses provide the largest reference to date of human genetic information relevant to T2D, for use in activities such as T2D-focused genotype imputation, functional characterization of variants or genes, and other novel analyses to detect associations between sequence variation and T2D.

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Compressed sensing for thoracic MRI with partial random circulant matrices

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Telkomnika 2012年第1期10卷 147-154页

作者： Swastika, Windra Haneishi, Hideaki Informatics Engineering Study Program Ma Chung University Villa Puncak Tidar N/01 Malang Indonesia Research Center for Frontier Medical Engineering Chiba University 1-33 Yayoi-cho Inage-ku Chiba 263-8522 Japan

The use of circulant matrix as the sensing matrix in compressed sensing (CS) scheme has recently been proposed to overcome the limitation of random or partial Fourier matrices. Aside from reducing computational complexity, the use of circulant matrix for magnetic resonance (MR) image offers the feasibility in hardware implementations. This paper presents the simulation of compressed sensing for thoracic MR imaging with circulant matrix as the sensing matrix. The comparisons of reconstruction of three different type MR images using circulant matrix are investigated in term of number of samples, number of iteration and signal to noise ratio (SNR). The simulation results showed that circulant matrix works efficiently for encoding the MR image of respiratory organ, especially for smooth and sparse image in spatial domain. © 2012 Universitas Ahmad Dahlan.

关键词： Magnetic resonance

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Text and file encryption application for blackberry using cipher feedback 8-bit mode

Text and file encryption application for blackberry using ci...

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2011 International Conference on Electrical engineering and informatics, ICEEI 2011

作者： Wangsadiredja, Matthew Munir, Rinaldi Informatics Engineering Study Program Bandung Institute of Technology Ganesha Street 10 Bandung 40235 Indonesia

ISBN: (纸本)9781457707520

BlackBerry is not just an ordinary smartphone which rich in its multimedia features. BlackBerry also has very reliable internet services, include BlackBerry Messenger, e-mail, other instant messaging, and other internet service that Blackberry Internet Service (BIS) covers. However, there's an open question that all services that go through BIS is safe or not;considering the data includes text and files which is sent through BIS have to pass through the main server which is located in Canada. Therefor in this paper we chose to make software that can encrypt and decrypt text and even files, which will be sent through BlackBerry's internet or just to be stored in the BlackBerry device. In this paper, we use cipher block encryption algorithm with Cipher Feedback (CFB) 8-bit mode. This mode is chosen because it suits with the data inside BlackBerry device which is 8-bit aligned. The encryption algorithm uses cipher block encryption with 64-bit block size. We designed the algorithm based on Feistel network combined with some encryption/decryption algorithm. Then the cipher block encryption algorithm is implemented in software based on Java for BlackBerry. In this software development, we use the IDE Eclipse Ganymede with certain plugins. The expected result is software for BlackBerry capable to encrypt and decrypt some texts, either directly typed or saved as files on the BlackBerry device. This software also handles specific file types, such as picture and audio by preserving their file header, and also handles text encryption by transforming the ciphertext data to hex digits. After conducting some experiments, we conclude that the software has good compatibility with many kinds of BlackBerry devices and has good security level. © 2011 IEEE.

关键词： Metadata

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Collaboration model of software development

Collaboration model of software development

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2011 International Conference on Electrical engineering and informatics, ICEEI 2011

作者： Kusumasari, Tien Fabrianti Supriana, Iping Surendro, Kridanto Sastramihardja, Husni Information System Program Study STMIK im Bandung Jl.Jakarta No.79 Bandung Indonesia School of Electrical Engineering and Informatics Bandung Institute of Technology Jl. Ganessa No.10 Bandung Indonesia

ISBN: (纸本)9781457707520

Software development is a series of processes activity involving more than one person, especially in medium to large software projects. Each activity of software development is carried out by various combination of different individual. Collaboration occurs in every phase of the process software development. The right team collaboration method is one of the important things in success software development. This research is focused to develop collaboration model of software development to meet time schedule, budget, scope, and software *** collaboration model of software development is generated from survey of collaboration method (about face to face and virtual collaboration) and software development methodology especially agile methodology. The direct collaboration was used in the software specification processes, and combination (with a direct and virtual) collaboration was used during software design, implementation, and validation. Team coordination in every process of software development was done with face to face method. The same artifacts were used in this collaboration model with some collaboration software tools. Combination between face to face and virtual communication was used in this model. The model is implemented in small case software development project. During the software development, some measurement is carried out. The measurement included the measurement of project completion time, cost, software specification, and software quality. The software is developed in time schedule (two months), cost under budged, and meet specification. In addition, the software has built a fairly good quality. Thus, this collaboration model good use in software development to achieved accuracy of schedule, cost, scope, and quality. © 2011 IEEE.

关键词： Software design

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