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Wireless Disturbance Mapping and Path Selection for Placement of Network Control System Components

Journal of Physics: Conference Series 2019年第1期1230卷 012025-012025页

作者： Joelianto, Endra Ghazali, Muhammad Zhaka Tutun Juhana Instrumentation and Control Research Group Faculty of Industrial Technology Institut Teknologi Bandung Jl. Ganesha 10 Bandung 40132 Indonesia. Engineering Physics Study Program Faculty of Industrial Technology Institut Teknologi Bandung Jl. Ganesha 10 Bandung 40132 Indonesia. Telecommunication Engineering School of Electrical and Informatics Institut Teknologi Bandung Jl. Ganesha 10 Bandung 40132 Indonesia.

Wireless transmitters in measurement instruments act for transmitting data or signals using radio frequency or currently better known as WIFI by means of 2.4 GHz. WIFI is a wireless local area network (WLAN) communication network. With the existence of telecommunications, measurement and control in industrial processes are heading to a high level of reliability compared to the conventional wired instruments in reaching hard locations or dangerous and hazardous areas. However, this cannot be done easily especially in maintaining the communication performances. Research is needed on the reliability of the wireless transmitter itself. Several factors such as communication disruptions are new challenges for the industry of wireless technology manufacturers to be able to prevent or to minimize errors that can arise in wireless network control systems. Signal strength mapping is needed in designing wireless network control systems. In this paper, the mapping is performed by measuring the signal strength parameters (Power Level) and the use of channels (Channel Usage) at planned locations. The measurement results are then used as sample points in the mapping. Data show that the signal strength measurement at each channel has a maximum of - 60 dBm and a minimum of -105 dBm. Mapping is performed by using two methods, namely Inverse Distance Weight (IDW) and Spline Interpolation (SI) methods. The paper proposes an algorithm to select the appropriate wireless communication paths from the planned locations. The mapping results indicate the appropriate area to place the transmitter and the receiver devices in a wireless data transmission network. With good placement, it is expected that measurements using wireless transmitters have minimum disruptions.

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The epidemic of Tuberculosis on vaccinated population

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Journal of Physics: Conference Series 2017年第1期890卷

作者： Syahrini, Intan Sriwahyuni Halfiani, Vera Yuni, Syarifah Meurah Iskandar, Taufiq Rasudin Ramli, Marwan Department of Mathematics Syiah Kuala University Banda Aceh 23111 Indonesia Dynamic Application and Optimization Groups Syiah Kuala University Banda Aceh 23111 Indonesia Management and Informatics Study Program Syiah Kuala University Banda Aceh 23111 Indonesia

Tuberculosis is an infectious disease which has caused a large number of mortality in Indonesia. This disease is caused by Mycrobacterium tuberculosis. Besides affecting lung, this disease also affects other organs such as lymph gland, intestine, kidneys, uterus, bone, and brain. This article discusses the epidemic of tuberculosis through employing the SEIR model. Here, the population is divided into four compartments which are susceptible, exposed, infected and recovered. The susceptible population is further grouped into two which are vaccinated group and unvaccinated group. The behavior of the epidemic is investigated through analysing the equilibrium of the model. The result shows that administering vaccine to the susceptible population contributes to the reduction of the tuberculosis epidemic rate.

关键词： Epidemiology

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Conceptual: Digital Book in the Era of Digital Learning Approaches (DLA)

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IOP Conference Series: Earth and Environmental Science 2019年第1期243卷

作者： A Mashfufah J Nurkamto Sajidan Wiranto I L Novenda Doctoral program of Education Science of Sebelas Maret University Jalan Ir Sutami No 36-A Kentingan Surakarta Indonesia Faculty of Education Science IKIP PGRI Jember Jl. Jawa No.10 Tegal Boto Lor Sumbersari Jember East Java 68121 Indonesia Faculty of Teacher Training and Education of Sebelas Maret University Jalan Ir Sutami No 36-A Kentingan Surakarta Indonesia Postgraduate program of Science Education of Sebelas Maret University Jalan Ir Sutami No 36-A Kentingan Surakarta Indonesia Informatics Study Program of Sebelas Maret University Jalan Ir Sutami No 36-A Kentingan Surakarta Indonesia Faculty of Teacher Training and Education of Jember University Kalimantan Street 37 Jember Indonesia

Nowadays, the advancement of ICT has been reached all over the world with tremendous influences, particularly in an educational world. In this digital age, for instance, there is an innovation of learning resources based on technology. They are electronic books (e-books) or digital books. The features of digital books such as multimodal components (text, audio, animation, and video) become more desirable than the printed books, although the current research often shows the constraint toward the effectiveness of the electronic books in reading comprehension. The digital books provide an interactive aspect of self-regulated learning in the context of distance learning. This article proposes a literature review of the existing studies around digital books in an educational environment. The result of review revealed that the effectiveness of the digital book for learning purposes depends on several factors that are the curriculum development appropriateness, students' prior knowledge of technology, and adults' role as facilitators in a learning activity.

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Deciphering colorectal cancer genetics through multi-omic analysis of 100,204 cases and 154,587 controls of European and east Asian ancestries (vol 55, pg 89, 2023)

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NATURE GENETICS 2023年第3期55卷 519-520页

作者： Fernandez-Rozadilla, Ceres Timofeeva, Maria Chen, Zhishan Law, Philip Thomas, Minta Schmit, Stephanie Diez-Obrero, Virginia Hsu, Li Fernandez-Tajes, Juan Palles, Claire Sherwood, Kitty Briggs, Sarah Svinti, Victoria Donnelly, Kevin Farrington, Susan Blackmur, James Vaughan-Shaw, Peter Shu, Xiao-ou Long, Jirong Cai, Qiuyin Guo, Xingyi Lu, Yingchang Broderick, Peter Studd, James Huyghe, Jeroen Harrison, Tabitha Conti, David Dampier, Christopher Devall, Mathew Schumacher, Fredrick Melas, Marilena Rennert, Gad Obon-Santacana, Mireia Martin-Sanchez, Vicente Moratalla-Navarro, Ferran Oh, Jae Hwan Kim, Jeongseon Jee, Sun Ha Jung, Keum Ji Kweon, Sun-Seog Shin, Min-Ho Shin, Aesun Ahn, Yoon-Ok Kim, Dong-Hyun Oze, Isao Wen, Wanqing Matsuo, Keitaro Matsuda, Koichi Tanikawa, Chizu Ren, Zefang Gao, Yu-Tang Jia, Wei-Hua Hopper, John Jenkins, Mark Win, Aung Ko Pai, Rish Figueiredo, Jane Haile, Robert Gallinger, Steven Woods, Michael Newcomb, Polly Duggan, David Cheadle, Jeremy Kaplan, Richard Maughan, Timothy Kerr, Rachel Kerr, David Kirac, Iva Bohm, Jan Mecklin, Lukka-Pekka Jousilahti, Pekka Knekt, Paul Aaltonen, Lauri Rissanen, Harri Pukkala, Eero Eriksson, Johan Cajuso, Tatiana Hanninen, Ulrika Kondelin, Johanna Palin, Kimmo Tanskanen, Tomas Renkonen-Sinisalo, Laura Zanke, Brent Mannisto, Satu Albanes, Demetrius Weinstein, Stephanie Ruiz-Narvaez, Edward Palmer, Julie Buchanan, Daniel Platz, Elizabeth Visvanathan, Kala Ulrich, Cornelia Siegel, Erin Brezina, Stefanie Gsur, Andrea Campbell, Peter Chang-Claude, Jenny Hoffmeister, Michael Brenner, Hermann Slattery, Martha Potter, John Tsilidis, Konstantinos Schulze, Matthias Gunter, Marc Murphy, Neil Castells, Antoni Castellvi-Bel, Sergi Moreira, Leticia Arndt, Volker Shcherbina, Anna Stern, Mariana Pardamean, Bens Bishop, Timothy Giles, Graham Southey, Melissa Idos, Gregory McDonnell, Kevin Abu-Ful, Zomoroda Greenson, Joel Shulman, Katerina Lejbkowicz, Flavio Offit, Kenneth Su, Yu-Ru Steinfelder, Robert Keku, Temitope van Guelpen, Bethany Hudson, Thomas Hampel, Heather Pearlman, Edinburgh Cancer Research Centre Institute of Genomics and Cancer University of Edinburgh Edinburgh UK Genomic Medicine Group Instituto de Investigacion Sanitaria de Santiago Santiago de Compostela Spain Colon Cancer Genetics Group Medical Research Council Human Genetics Unit Institute of Genetics and Cancer University of Edinburgh Edinburgh UK Danish Institute for Advanced Study Department of Public Health University of Southern Denmark Odense Denmark Division of Epidemiology Department of Medicine Vanderbilt-Ingram Cancer Center Vanderbilt Epidemiology Center Vanderbilt University Medical Center Nashville TN USA Division of Genetics and Epidemiology Institute of Cancer Research London UK Public Health Sciences Division Fred Hutchinson Cancer Research Center Seattle WA USA Genomic Medicine Institute Cleveland Clinic Cleveland OH USA Population and Cancer Prevention Program Case Comprehensive Cancer Center Cleveland OH USA Colorectal Cancer Group ONCOBELL Program Bellvitge Biomedical Research Institute Barcelona Spain Oncology Data Analytics Program Catalan Institute of Oncology Barcelona Spain Consortium for Biomedical Research in Epidemiology and Public Health Madrid Madrid Spain Department of Clinical Sciences Faculty of Medicine University of Barcelona Barcelona Spain Department of Biostatistics School of Public Health University of Washington Seattle WA USA Institute of Cancer and Genomic Sciences College of Medical and Dental Sciences University of Birmingham Birmingham UK Department of Public Health Richard Doll Building University of Oxford Oxford UK Department of Biomedical Informatics Vanderbilt University School of Medicine Nashville TN USA Department of Preventive Medicine USC Norris Comprehensive Cancer Center Keck School of Medicine University of Southern California Los Angeles CA USA Center for Public Health Genomics Department of Public Health Sciences University of Virginia Charlottesville VA USA Department of Populat

Colorectal cancer (CRC) is a leading cause of mortality worldwide. We conducted a genome-wide association study meta-analysis of 100,204 CRC cases and 154,587 controls of European and east Asian ancestry, identifying 205 independent risk associations, of which 50 were unreported. We performed integrative genomic, transcriptomic and methylomic analyses across large bowel mucosa and other tissues. Transcriptome- and methylome-wide association studies revealed an additional 53 risk associations. We identified 155 high-confidence effector genes functionally linked to CRC risk, many of which had no previously established role in CRC. These have multiple different functions and specifically indicate that variation in normal colorectal homeostasis, proliferation, cell adhesion, migration, immunity and microbial interactions determines CRC risk. Crosstissue analyses indicated that over a third of effector genes most probably act outside the colonic mucosa. Our findings provide insights into colorectal oncogenesis and highlight potential targets across tissues for new CRC treatment and chemoprevention strategies.

关键词： Colorectal cancer Epigenomics Genome-wide association studies Transcriptomics

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Scheduling model for air traffic in Indonesia

Scheduling model for air traffic in Indonesia

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IEEE Region 10 Symposium

作者： Maureen Linda Caroline Yudistira Asnar Achmad Imam Kistijantoro Informatics Study Program SEEI - Bandung Institute of Technology

ISBN: (纸本)9781509009329

Congestion because of increasing demand of air transportation occurs at several airports in Indonesia especially Soekarno-Hatta International Airport. In 2013, Soekarno-Hatta International Airport ranked 25th busiest airports in the world by Airports Council International. One of several ways to enlarge capacity of airports is to improve efficiency current infrastructure utilization with optimizing schedule. Three referred optimization models are model of Beasley et al. which optimizes runway utilization, Bertsimas and Stock Patterson's model which optimizes air space capacity allocation and Lulli and Odoni's model which are macroscopic model of Bertsimas and Stock Patterson's model. Unfortunately, Lulli and Odoni's model cannot studied further because of lack information about increasing convex function. The other models modified from integer program to constraint satisfaction optimization program (CSOP) so that the models are flexible to modify and the solution can be local optimum. Because of these advantages, rescheduling can be performed when there was little change in flight schedule. In addition, several constraints are added to modification of model of Beasley et al. such as flight continued constraint. Based on tests, modification of model of Beasley et al. success to reduce delays and modification of Bertsimas and Stock Patterson's model success to do a simulation.

关键词： Atmospheric modeling Airports Optimization Aircraft Linear programming Schedules Resource management

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***: Dissemination platform for deep learning models

arXiv

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arXiv 2019年

作者： Hosny, Ahmed Schwier, Michael Berger, Christoph Örnek, Evin P. Turan, Mehmet Tran, Phi V. Weninger, Leon Isensee, Fabian Maier-Hein, Klaus H. McKinley, Richard Lu, Michael T. Hoffmann, Udo Menze, Bjoern Bakas, Spyridon Fedorov, Andriy Aerts, Hugo J.W.L. Program Brigham and Women's Hospital Harvard Medical School BostonMA United States Department of Radiation Oncology Dana-Farber Cancer Institute Harvard Medical School BostonMA United States Department of Radiology Brigham and Women's Hospital Dana-Farber Cancer Institute Harvard Medical School BostonMA United States Harvard Medical School BostonMA United States Institute for Advanced Study Department of Informatics Technical University of Munich Munich Germany Max Planck Institute for Intelligent Systems Stuttgart Germany Booz Allen Hamilton McLeanVA United States Institute of Imaging & Computer Vision RWTH Aachen University Aachen Germany Heidelberg Germany Support Centre for Advanced Neuroimaging University Institute of Diagnostic Interventional Neuroradiology Inselspital Bern University Hospital Bern Switzerland Cardiovascular Imaging Research Center Massachusetts General Hospital Harvard Medical School Boston United States Cardiac MR PET CT Program Department of Radiology Massachusetts General Hospital BostonMA United States Center for Biomedical Image Computing and Analytics University of Pennsylvania PhiladelphiaPA United States Radiology & Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Radiology and Nuclear Medicine GROW CARIM Maastricht University Maastricht Netherlands

Recent advances in artificial intelligence research have led to a profusion of studies that apply deep learning to problems in image analysis and natural language processing among others. Additionally, the availability of open-source computational frameworks has lowered the barriers to implementing state-of-the-art methods across multiple domains. Albeit leading to major performance breakthroughs in some tasks, effective dissemination of deep learning algorithms remains challenging, inhibiting reproducibility and benchmarking studies, impeding further validation, and ultimately hindering their effectiveness in the cumulative scientific progress. In developing a platform for sharing research outputs, we present *** (***), a community-driven container-based software engine and platform for the structured dissemination of deep learning models. For contributors, the engine controls data flow throughout the inference cycle, while the contributor-facing standard template exposes model-specific functions including inference, as well as pre- and post-processing. Python and RESTful Application programming interfaces (APIs) enable users to interact with models hosted on *** and allows both researchers and developers to utilize models out-of-the-box. *** is domain-, data-, and framework-agnostic, catering to different workflows and contributors' preferences. Copyright © 2019, The Authors. All rights reserved.

关键词： Containers

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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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Comparison of simple additive weighting (SAW) and composite performance index (CPI) methods in employee remuneration determination

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IOP Conference Series: Materials Science and Engineering 2017年第1期166卷

作者： L. Karlitasari D. Suhartini Benny Computer Science Study Program Pakuan University Bogor INDONESIA Informatics Management D3 Study Program Pakuan University Bogor INDONESIA

The process of determining the employee remuneration for PT Sepatu Mas Idaman currently are still using Microsoft Excel-based spreadsheet where in the spreadsheet there is the value of criterias that must be calculated for every employee. This can give the effect of doubt during the assesment process, therefore resulting in the process to take much longer time. The process of employee remuneration determination is conducted by the assesment team based on some criterias that have been predetermined. The criteria used in the assessment process are namely the ability to work, human relations, job responsibility, discipline, creativity, work, achievement of targets, and absence. To ease the determination of employee remuneration to be more efficient and effective, the Simple Additive Weighting (SAW) method is used. SAW method can help in decision making for a certain case, and the calculation that generates the greatest value will be chosen as the best alternative. Other than SAW, also by using another method was the CPI method which is one of the calculating method in decision making based on performance index. Where SAW method was more faster by 89-93% compared to CPI method. Therefore it is expected that this application can be an evaluation material for the need of training and development for employee performances to be more optimal.

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Casting and Welding of Aluminium Matrix Composite Materials Reinforced by SiC Particles

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IOP Conference Series: Materials Science and Engineering 2018年第1期434卷

作者： P H Tjahjanti F Hermansyah L H Prasetya M P T Sulistyanto Department of Mechanical Engineering Universitas Muhammadiyah Sidoarjo Kampus 2 Jalan Raya Gelam nomer 250 Candi Sidoarjo Jawa Timur Indonesia Informatics Study Program Universitas Kanjuruan Malang Jalan S. Supriadi no.48 Malang Jawa Timur Indonesia

Aluminium casting is often done, but for the casting of composite materials base on aluminium is very rare. The purpose of this research is make composite material based on aluminium reinforced by SiC particles by casting. This research method use three different casting molds that are permanent cast, ceramic (chamotte sand / Al2O3-SiO2) molds and sand molds. The best casting product that has a small porosity is the AlMg10Si make of permanent molding. The small porosity effect causes the AlMg10Si material to become harder. The oxy-acetylene welding results show that the AlMg10Si + composite material reinforced by 15% SiC particles, has a fine discontinuity when the liquid penetrant test, which means that very small cracks occur, and potholes result from casting. This composite material has enormous energy to break is 0.94 Joule at impact test.

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Scoreboard wireless universal based on microcontroller

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

作者： Sindak Hutauruk Pandapotan Siagian Libianko Sianturi Department of Electrical Engineering University of HKBP University 4 A Sutomo Street Medan Indonesia. Institut Teknologi Del Faculty of Informatics and Electrical Engineering Computer Network Management Study Program Jl. Sisingamangaraja Sitoluama Toba Samosir Sumatera Utara 22381 Indonesia

The scoreboard is designed and made for a universal use that can be used in matches in some sports such as basketball, futsal, ping pong, badminton, and others. The scoreboard is designed and made based on the needs of several sports in the Student Activity Unit at HKBP Nommensen University which can be easily moved. Scores displayed on the scoreboard is not only the result of the game but also displayed time in the countdown. This scoreboard can be operated by using a cable and can also without using a cable by using a mobile phone through communication using bluetooth. This scoreboard is based on a microcontroller and uses backup power through rechargeable batteries that can be automatically charged. In trials in several games, this tool works well with a few drawbacks in case of a match that takes more than 100 minutes because the time display can only display a maximum time of 99 minutes.

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