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22ND ANNUAL SYMP OF THE ASSOC OF COMPUTING MACHINERY : THEORY OF COMPUTING

作者： EVEN, S RAJSBAUM, S Department of Computer Science Technion-Israel Institute of Technology Haifa Israel 32000 and Computer Science Program University of Texas at Dallas Richardson TX

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An intelligent applied Fuzzy Logic to prediction the Parts per Million (PPM) as hydroponic nutrition on the based Internet of Things (IoT) 4

An intelligent applied Fuzzy Logic to prediction the Parts p...

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4th International Conference on Informatics and Computing, ICIC 2019

作者： Musa, Purnawarman Sugeru, Herik Mufza, Haya Fadhila Faculty of Computer Science and Information Technology Universitas Gunadarma Indonesia Faculty of Industrial Technology Study Program of Agrotechnology Universitas Gunadarma Indonesia

ISBN: (纸本)9781728122076

Hydroponic plants require regular monitoring of plants that grow well and can even cause plants to die. Because too late in providing nutrition or getting too little or too little food or routine monitoring in the hydroponic system. The innovation proposed in the agricultural sector that we suggest is the process of monitoring hydroponic plants in real-time. This study aims to predict the excess or lack of nutrient content based on the results of routine monitoring and has the analytical ability to determine the prediction of the value of Parts per Million (PPM) to find the nutritional value of plant media. Measurement of nutritional value using Electrical Conductivity (EC) and the potential of Hydrogen (pH) in hydroponic plant media. In this research, using the NFT hydroponic system as the application of fuzzy logic with the Mamdani method to determine the predictions of PPM values in providing nutrients at plants to adjusting the nutritional at each plant (e.g., for water spinach plants are need 1050 until 1400 PPM). The implemented is method Internet of Things (IoT) to remote sensing on measure using a smartphone as the representation of the measurement results on the hydroponic system. © 2019 IEEE.

关键词： Hydroponics

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5-Fold Cross Validation on Supporting K-Nearest Neighbour Accuration of Making Consimilar Symptoms Disease Classification 2

5-Fold Cross Validation on Supporting K-Nearest Neighbour Ac...

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2nd International Conference on computer science and Engineering, IC2SE 2021

作者： Satria, Andy Sitompul, Opim Salim Mawengkang, Herman Universitas Sumatera Utara Program of Computer Science and Information Technology Medan Indonesia Universitas Sumatera Utara Department of Computer Science and Information Technology Medan Indonesia Universitas Sumatera Utara Department of Mathematics and Natural Science Medan Indonesia

ISBN: (纸本)9781665400459

Classification is a technique in machine learning that is used to built the group of data. The data that consist of class and target are grouped based on the data attachment to the sample data, so that the data group can be used as a basis for making decisions at a later stage. This study aims to find a classification of two diseases, dengue fever and typhus which have similar symptoms using a combination of two techniques, 5-Fold Cross Validation and K-Nearest Neighbor. The combination of these techniques is done to improve the accuracy of the classification, feature selection is done in preprocessing phase to collect verified feature to get information gain to measure which feature is kept and continue to next stage of classification process. A confusion matrix will be applied to test the performance in terms of the accuracy of the constructed classification. K-Nearest Neighbor (KNN) is a classification method that applies a supervised algorithm, while 5-Fold Cross Validation is a statistical method that is applied to test the performance of a method or technique. This investigation resulted in an increase in the value of accuracy and recall, with a score of 1.79 points and a recall value of 96.43%. © 2021 IEEE.

关键词： Classification (of information)

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Multilevel modeling and value of information in clinical trial decision support

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BMC systems biology 2014年第1期8卷 6-6页

作者： Cui, Yuanyuan Murphy, Brendan Gentilcore, Anastasia Sharma, Yugal Minasian, Lori M. Kramer, Barnett S. Coates, Paul M. Gohagan, John K. Klenk, Juergen Tidor, Bruce Computer Science and Artificial Intelligence Laboratory and Program in Computational and Systems Biology Massachusetts Institute of Technology Cambridge 02139 MA United States

BACKGROUND: Clinical trials are the main method for evaluating safety and efficacy of medical interventions and have produced many advances in improving human health. The Women's Health Initiative overturned a half-century of harmful practice in hormone therapy, the National Lung Screening Trial identified the first successful lung cancer screening tool and the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial overturned decades-long assumptions. While some trials identify unforeseen safety issues or harms, many fail to demonstrate efficacy. Large trials require substantial resources;to ensure reliable outcomes, we must seek ways to improve the predictive information used as the basis of trials.;CONCLUSION: Using machine learning methods, we identified the parameters of the model that are most predictive of trial outcome and found that the top four are directly related to the rates of reactions producing methylselenol and transporting extracellular selenium into the cell as selenide. This modeling process demonstrates how the approach can be used in advance of a large clinical trial to identify the best targets for conducting further research to reduce the uncertainty in the trial outcome.;RESULTS: Here we demonstrate a modeling framework for linking knowledge of underlying biological mechanism to evaluate the expectation of trial outcomes. Key features include the ability to propagate uncertainty in biological mechanism to uncertainty in trial outcome and mechanisms for identifying knowledge gaps most responsible for unexpected outcomes. The framework was used to model the effect of selenium supplementation for prostate cancer prevention and parallels the Selenium and Vitamin E Cancer Prevention Trial that showed no efficacy despite suggestive data from secondary endpoints in the Nutritional Prevention of Cancer trial and found increased incidence of high-grade prostate cancer in certain subgroups.

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Hotel Information System Management Audit Using COBIT 2019 - APO12 2

Hotel Information System Management Audit Using COBIT 2019 -...

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2nd International Conference for Innovation in technology, INOCON 2023

作者： Utamajaya, Joy Nashar Supangat, Suhono Harso Gaol, Ford Lumban Ranti, Benny BINUS University BINUS Graduate Program School of Information System Jakarta Indonesia Bandung Institute of Technology School of Electrical Engineering and Informatic Bandung Indonesia Bina Nusantara University Computer Science Department BINUS Graduate Program Computer Science Jakarta Indonesia University of Indonesia Computer Science Department Faculty of Computer Science Depok Indonesia

ISBN: (纸本)9798350320923

In general, public or private organizations or companies have used information-based technology as a support to improve business performance to be more effective and efficient in order to achieve a company's business goals. Given the large contribution of information technology in the application of hotel applications as a supporting information system, it is a vital system that must avoid risks that can hinder and cause harm to the hotel management business processes. Therefore, it is necessary to carry out risk management using the COBIT 5 framework to manage possible risks that may occur based on the APO12 (Manage Risk) domain. From the evaluation results of the data obtained through observation and interviews as well as the calculation of the results of the questionnaire based on 6 APO12 subdomains, the results of the risk management level capability assessment in hotel applications are still at level 3 or have reached the level of established process with the target to be achieved at level 4 resulting in a gap of 1 level. Based on the results obtained, it is necessary to propose recommendations that can be used by hotels in improving the application of information technology risk management so that in the future it can achieve the expected target level so that the APO12 level of capability can increase and become more optimal. © 2023 IEEE.

关键词： Risk management

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An Analysis Air Traffic Prediction during a Pandemic 4

An Analysis Air Traffic Prediction during a Pandemic

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4th International Conference on Cybernetics and Intelligent System, ICORIS 2022

作者： Nasution, Darmeli Mawengkang, Herman Fahmi Zarlis, Muhammad Universitas Sumatera Utara Doctoral Program Departmen of Computer Science and Information Technology Medan Indonesia Universitas Sumatera Utara Departmen of Math and Science Medan Indonesia Universitas Sumatera Utara Departmen of Computer Science and Information Technology Medan Indonesia Universitas Bina Nusantara Departmen of Computer Science and Information Technology Jakarta Indonesia

ISBN: (纸本)9781665453950

Air transportation during the covid-19 pandemic experienced a very drastic decline. The decrease in the number of passengers was caused by national and international restrictions. The troublesome administration makes passengers discouraged from traveling using Air transportation. Based on the National Statistics Agency, air transportation experienced a decline from early 2020 to 2021. This study focuses on air traffic predictions, namely the number of aircraft passengers during the COVID-19 pandemic at Indonesia's main airports, namely Kuala Namu, Sukarno Hatta, and Juanda airports., Ngurah Rai and Hasanuddin. The method used to predict the number of airplane passengers during a pandemic is the backpropagation algorithm using the Fletcher Reeves method. © 2022 IEEE.

关键词： Air transportation

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Cardiovascular Disease Analysis Using Correlational Analysis and Association Rules Mining for In-depth Analysis to Identify Predominant Variables

Cardiovascular Disease Analysis Using Correlational Analysis...

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2023 International Conference on computer science, Information technology and Engineering, ICCoSITE 2023

作者： Siswanto, Boby Soeparno, Haryono Sianipar, Nesti F. Budiharto, Widodo Bina Nusantara University BINUS Graduate Program- Computer Science Computer Science Department Jakarta Indonesia Bina Nusantara University Engineering Faculty Food Technology Department Jakarta Indonesia Bina Nusantara University School of Computer Science Computer Science Department Jakarta Indonesia

ISBN: (纸本)9798350320954

Cardiovascular disease is one of the dangerous non-communicable disorders or diseases that has become one of the causes of death worldwide. Various studies have been conducted to prevent cardiovascular disease in the world. This study analyzed cardiovascular disease medical record data from the Kaggle public dataset by implementing correlational analysis combined with association rule mining to identify variables that are the predominant cause of cardiovascular disease. Correlational analysis can analyze the interrelationships between variables in a dataset, but not in depth. Association rule mining can identify the interrelationships of variables in the form of frequent item sets, which can be calculated for their support and confidence values. The result of this study is a combination of correlation analysis with association rule mining that can identify predominant variables to cause cardiovascular disease. Found that the variable gender=woman, height=short ( © 2023 IEEE.

关键词： Association rules

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Optimization and Computing Model of Fish Resource Supply Chain Distribution Network 5

Optimization and Computing Model of Fish Resource Supply Cha...

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5th International Conference on Computing and Applied Informatics, ICCAI 2020

作者： Nurdin Zarlis, M. Tulus Efendi, S. Graduate Program of Computer Science Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan Indonesia Department of Computer Science Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan Indonesia Department of Mathematics Fakultas Matematika Dan Ilmu Pengetahuan Alam Universitas Sumatera Utara Medan Indonesia

Aceh is a province that is rich in fishery resource potential. Fish resources become one of the leading commodities, therefore we need a supply chain optimization model. Optimization is one of the technologies widely used in supply chain network management. Fish resource supply chain becomes very important because it is caused by several factors, including the diversity of types of products from fish resources and their short expiry. The steps used in this research is literature review, determine parameters and decision variables, formulate the objective function and constraint function, modeling and model implementation. The purpose of this research is to get an optimization model in planning and managing the fish resource supply chain by using mixed integer linear programming, so that the resulting model can solve problems in the limitations of fish resources in certain areas, can distribute all consumer demand quickly. This new model can minimize transportation costs to suppliers, minimize transportation costs from suppliers to distribution centers and minimize transportation costs from distribution centers to consumers, and minimize product inventory costs to suppliers and to distribution centers. © Published under licence by IOP Publishing Ltd.

关键词： Supply chains

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StarBus+: Distributed object middleware practice for internet computing

StarBus+: Distributed object middleware practice for interne...

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作者： Wang, Huai-Min Wang, Yu-Feng Tang, Yang-Bin School of Computer Science National University of Defense Technology Changsha 410073 China Computer School National University of Defense Technology Editorial Board of Chinese Journal of Computers and Journal of Computer Science and Technology Expert Committee for Computer Software and Hardware National High Technology Research and Development 863 Program of China National University of Defense Technology

In the past decade, the booming of Internet challenges the middleware in three aspects: quality of service, balance of changes and stabilization, and across-Internet integration. This paper presents our work on distributed object computing middleware technology for these challenges, as well as the research and development on StarBus+, which is a CORBA standard-compliant middleware suite with the features such as object request broker supporting multi-*quality of service, component model, and integration with Web Service. This paper comprehensively presents the design and characteristics of StarBus+, and demonstrates how StarBus+ is enhanced to address the challenges of Internet computing through three case studies: inter-enterprise integration over Internet, application evolution through dynamic reconfiguration, and great massive information system building. The paper also suggests some research directions which are important for Internet computing.

关键词： Internet

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Outside-in design for interdisciplinary hri research

Outside-in design for interdisciplinary hri research

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Experimental Design for Real-World Systems - Papers from the AAAI Spring Symposium

作者： Šabanovic, Selma Meisner, Eric Caporael, Linnda R. Isler, Volkan Trinkle, Jeff Program in Science Technology and Society Stanford University United States Department of Computer Science Rensselaer Polytechnic Institute United States Department of Science and Technology Studies Rensselaer Polytechnic Institute United States Department of Computer Science University of Minnesota United States

ISBN: (纸本)9781577354109

This paper introduces "outside-in design" as a collaborative approach to social robot design and human-robot interaction research. As an interdisciplinary group of social and computer scientists, we follow an iterative practice of collecting and analyzing data from real-world interaction, designing appropriate robotic perception and control mechanisms, developing models of interaction through automatic coding of behaviors and evaluation by human subjects, and validating the models in embodied human-robot interaction. We apply this approach in the context of shadow puppeteering, a constrained interaction space which allows us to study the foundational elements of synchronous interaction and apply them to a robot. We contribute to both social and computer sciences by combining the study of human social interaction with the design of socially responsive robot control algorithms. © 2009, Association for the Advancement of Artificial Intelligence.

关键词： Human robot interaction

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