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4th International Conference on information Management and technology, ICIMTech 2019

作者： Satria, Thomas Galih Sardjono, Wahyu Panggabean, Francisco Maruli Game Application Technology Program School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Information Systems Management Department Bina Nusantara University Jakarta11480 Indonesia

ISBN: (纸本)9781728133331

Special needs children have a tendency to play more games than children with development in general. Game play activities are often carried out by children with special needs can be a support learning and therapy due to his players the game has interaction without having to meet with his co-star in person. Starting from these data, this study aims to create a model of the System Dynamics approach. Data collected will be simulated by variables other support. The simulation results of the model will be seen autistic children therapy behavior. The results are then analyzed to create an alternative to the existing model. The benefit of this research is to know the description of game play to treatment of children with special needs. The results of simulation showed that playing games in an average time children with autism play therapy can help improve the quality of children with autism if children with autism play the game in a long time actually showed a decrease. © 2019 IEEE.

关键词： System theory

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Outliers detection in time series data: Case study: Provincial waterworks authority 4

Outliers detection in time series data: Case study: Provinci...

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4th Joint International Conference on Digital Arts, Media and technology and 2nd ECTI Northern Section Conference on Electrical, Electronics, computer and Telecommunications Engineering, ECTI DAMT-NCON 2019

作者： Khongsrabut, Isara Waiyamai, Kitsana Science Program in Information Technology Computer Engineering Kasetsart University 343/313 Plum Condo Chaengwattana Chaengwattana Rd. Talat Bang Khen Lak Si10210 Thailand

ISBN: (纸本)9781538680728

One main cause of inaccurate forecasts is that data may contain noises and outliers. In the case of the Provincial Waterworks Authority (PWA), the inaccuracy of analyzing and forecasting the number of water users is due to outliers contained in data sources. Some branches of PWA collected errors such as the very high or very low number of water users. This has a direct impact on the quality and reliability of the predictive accuracy output. The removal of the 'outliers' is thus critical for accurate interpretation of the data. The purpose of this paper is to detect outliers in water consumption time series data. We examined two techniques: (1) a method based on autoregressive integrated moving average (ARIMA) time series modeling and (2) median absolute deviation (MAD). A clustering technique (K-Mean) is used as a pre-processing step in order to identify appropriate parameters for the two outliers detection techniques. The results showed that, with the precise parameter values obtained from K-Mean, both ARIMA and MAD performed very well on water consumption time series data. The two techniques are able to generate high sensitivity and specificity outputs. © 2019 IEEE.

关键词： Time series

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A pretrained transformer model for decoding individual glucose dynamics from continuous glucose monitoring data

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National science Review 2025年第5期 362-381页

作者： Yurun Lu Dan Liu Zhongming Liang Rui Liu Pei Chen Yitong Liu Jiachen Li Zhanying Feng Lei M.Li Bin Sheng Weiping Jia Luonan Chen Huating Li Yong Wang Center for Excellence in Mathematical Sciences National Center for Mathematics and Interdisciplinary Sciences Hua Loo-Keng Center for Mathematical Sciences Key Laboratory of Management Decision and Information System Academy of Mathematics and Systems ScienceChinese Academy of Sciences School of Mathematics University of Chinese Academy of SciencesChinese Academy of Sciences Department of Endocrinology and Metabolism Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of MedicineShanghai Diabetes InstituteShanghai Clinical Center for Diabetes Shanghai Key Laboratory of Diabetes Mellitus Key Laboratory of Systems Health Science of Zhejiang Province School of Life ScienceHangzhou Institute for Advanced StudyUniversity of Chinese Academy of Sciences BGI-Research School of Mathematics South China University of Technology Department of Statistics Department of Biomedical Data Science Bio-X ProgramStanford University Department of Computer Science and Engineering Shanghai Jiao Tong University State Key Laboratory of Cell Biology Center for Excellence in Molecular Cell Science Shanghai Institute of Biochemistry and Cell Biology Chinese Academy of Sciences Guangdong Institute of Intelligence Science and Technology Pazhou Laboratory (Huangpu)

Continuous glucose monitoring(CGM) technology has grown rapidly to track real-time blood glucose levels and trends with improved sensor accuracy. The ease of use and wide availability of CGM will facilitate safe and effective decision making for diabetes management. Here, we developed an attention-based deep learning model, CGMformer, pretrained on a well-controlled and diverse corpus of CGM data to represent individual's intrinsic metabolic state and enable clinical applications. During pretraining, CGMformer encodes glucose dynamics including glucose level, fluctuation, hyperglycemia, and hypoglycemia into latent space with self-supervised learning. It shows generalizability in imputing glucose value across five external datasets with different populations and metabolic states(MAE = 3.7 mg/d L). We then fine-tuned CGMformer towards a diverse panel of downstream tasks in the screening of diabetes and its complications using task-specific data, which demonstrated a consistently boosted predictive accuracy over direct fine-tuning on a single task(AUROC = 0.914 for type 2 diabetes(T2D) screening and 0.741 for complication screening). By learning an intrinsic representation of an individual's glucose dynamics,CGMformer classifies non-diabetic individuals into six clusters with elevated T2D risks, and identifies a specific cluster with lean body-shape but high risk of glucose metabolism disorders, which is overlooked by traditional glucose measurements. Furthermore, CGMformer achieves high accuracy in predicting an individual's postprandial glucose response with dietary modelling(Pearson correlation coefficient = 0.763)and helps personalized dietary recommendations. Overall, CGMformer pretrains a transformer neural network architecture to learn an intrinsic representation by borrowing information from a large amount of daily glucose profiles, and demonstrates predictive capabilities fine-tuned towards a broad range of downstream applications, holding promise for the ear

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Effects of mutations on MUC1-C/ED protein stability and antibody Binding: Structural insight

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Biochemical and Biophysical Research Communications 2025年 775卷

作者： Dwipanjan Sanyal Danny Muzata Vladimir N. Uversky Surender Kharbanda Sourav Chowdhury Ravi Jasuja XYone Therapeutics Canton MA USA Department of Computer Science and Information Systems Birla Institute of Technology and Science-Pilani Hyderabad India USF Health Byrd Alzheimerʼs Research Institute Morsani College of Medicine University of South Florida Tampa FL 33612 USA Department of Biological Sciences Birla Institute of Technology and Science-Pilani Hyderabad India Research Program in Men's Health: Aging and Metabolism Brigham and Women's Hospital Harvard Medical School Boston MA USA

Antibody-drug conjugates (ADCs) represent a transformative approach in cancer therapy, combining the specificity of monoclonal antibodies with targeted delivery of potent cytotoxic drugs to tumors. Discovery of novel antigens has been the hallmark for development of ADC therapeutics and MUC1 is one such oncoprotein, which has garnered renewed interest recently. The 3D1 antibody, engineered to bind specifically to the alpha 3 (α3) helix of the MUC1-C/extracellular domain, is being actively developed towards clinical translation. The study examined the conformational coupling in the residues spanning the MUC1 sea urchin sperm protein, enterokinase, and agrin domain (SEA), which incorporates MUC1-C. 3D1 has been shown to be sensitive to three specific point mutations—D85E, V86A, and T88A— at the interaction surface between MUC1-C and the 3D1 antibody. Our findings reveal that D85E and T88A mutations cause significant conformational shifts and reduced binding affinity due to altered electrostatic interactions and hydrogen bonding. The V86A mutation, while maintaining the overall conformation, disrupts local hydrophobic interactions, leading to decreased binding efficiency. Further, residue 85 in the wild-type (WT) MUC1 SEA domain interacts with other residues, contributing to local frustration and destabilization. Mutants D85E, V86A, and T88A exhibited similar frustration patterns but with increased local energy, indicating reduced stability. Frustration calculations highlighted the crucial role of the α3 helix in protein stability and antibody interaction. Collectively, these data highlight the importance of specific residues contributing to the local frustration in maintaining effective antibody binding and suggest that mutations impacting these residues can significantly alter antigen binding dynamics.

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Closed ASL Interpreting for Online Videos

arXiv

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arXiv 2019年

作者： Kushalnagar, Raja Seita, Matthew Glasser, Abraham Information Technology Program Gallaudet University Computer Science Department Rochester Institute of Technology

Deaf individuals face great challenges in today’s society. It can be very difficult to be able to understand different forms of media without a sense of hearing. Many videos and movies found online today are not captioned, and even fewer have a supporting video with an interpreter. Also, even with a supporting interpreter video provided, information is still lost due to the inability to look at both the video and the interpreter simultaneously. To alleviate this issue, we came up with a tool called closed interpreting. Similar to closed captioning, it will be displayed with an online video and can be toggled on and off. However, the closed interpreter is also user-adjustable. Settings, such as interpreter size, transparency, and location, can be adjusted. Our goal with this study is to find out what deaf and hard of hearing viewers like about videos that come with interpreters, and whether the adjustability is beneficial. Copyright © 2019, The Authors. All rights reserved.

关键词： Audition

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Developing the Pointer Backward-Forward Algorithm in Token of Test in Text to Know the Level of Individual Depression 1

Developing the Pointer Backward-Forward Algorithm in Token o...

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1st International Conference of SNIKOM 2018, ICoSNIKOM 2018

作者： Fahmi, Hasanul Zarlis, Muhammad Situmorang, Zakarias Nababan, Adli A Dalimunthe, Yulia A Annisah, Yessi F Khairani, Mufida Departement of Computer Science Doctoral Program Faculty of Computer Science and Information Technology Sumatera Utara University St. Universitas No.9A Medan Indonesia Computer Science Departement Universitas Katolik Santo Thomas Indonesia STMIK Pelita Nusantara Sumatera Utara Indonesia Teknik Informatika-Universitas Harapan Medan Indonesia

The way you move and sleep, interact with people around you, depression change everything. This even looks at the way you talk and express yourself in writing. Sometimes this "depression language" can have a strong effect to others. Natural Language Processing (NLP) is one of the fields of computer science, artificial intelligence, and language (linguistics) related to the interaction between computers and natural human languages, such as Indonesian or English. The main objective of the NLP study is to make a machine that is able to know and understand the meaning of language, lexical analysis has the role of reading input characters and generating output tokens and making spaces, tabs, newlines and connecting rows of programs. However, the problems will occur when lexical analyzers where lexical is not able to determine when there are misspellings on tokens. Therefore, with the development of the backward-forward pointer algorithm, it is expected that in the future it will be easier to analyze both the words in front, in the middle and behind, so that the machine can quickly determine the individual depression level of speech tokens and speech tones. © Published under licence by IOP Publishing Ltd.

关键词： Natural language processing systems

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Sport Field Reservation Based on Mobile Application

Sport Field Reservation Based on Mobile Application

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International Conference on ICT For Smart Society (ICISS)

作者： Tonto Claudinus Made Prayoga Wicaksana Nicolas Kornelius Sitorus Marsa Ariqi Gustiandza Tanty Oktavia Ford Lumban Gaol Takaaki Hosoda School of Computer Science Bina Nusantara University Jakarta Indonesia School of Information Systems Bina Nusantara University Jakarta Indonesia Binus Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Advanced Institute of Industrial Technology Tokyo Japan

ISBN: (数字)9781665404228

ISBN: (纸本)9781665404235

This paper presents the sports apps based on a mobile application that has a function to help the provider or the owner of the sports field and sports vendor to promote their business in the apps. Due to the popularity and convenience that mobile applications had and high interest from many people in having a healthy life, it is a great opportunity to combine both of them. Therefore, this study focusses to build mobile sports application using object-oriented analysis and design method, that could meet the demand of lots of peoples that wants to do a sport especially a ball sport. Otherwise, the application can help and support the community and public, especially for ball sports fans, to make reservations for the sports field easier without having to come to the location and also meet their sporting needs.

关键词： Sports Mobile applications Business Schedules computer science Real-time systems IEEE merchandise

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LOCI: A Mobile Q&A System with Multimodal Motivation Scheme for Local Intent Questions in Dynamic Social Networks

LOCI: A Mobile Q&A System with Multimodal Motivation Scheme ...

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IEEE Conference on Vehicular technology (VTC)

作者： Imad Ali Ronald Y. Chang Cheng-Hsin Hsu Chi-Han Lee Taiwan International Graduate Program in Social Networks and Human-Centered Computing Institute of Information Science Academia Sinica Taipei Taiwan Research Center for Information Technology Innovation Academia Sinica Taipei Taiwan Department of Computer Science National Tsing Hua University Hsinchu Taiwan

ISBN: (数字)9781728152073

ISBN: (纸本)9781728140537

Recent research has shown that people are frequently searching for information with local intent. The existing systems fail to answer this class of questions as they are not mainly designed to handle it. In this paper, we propose LOCI, a mobile question & answer system with a multimodal motivation scheme for local intent questions where users provide timely and accurate answers in a dynamic social network. LOCI mines users' shared and contextual information to identify the most relevant users for each question. The proposed multimodal motivation scheme exploits users' social ties and monetary rewards to raise their basic motivation levels. LOCI assigns questions to the best answerers via our three proposed algorithms: (i) LOCI-RT, which immediately assigns newly arrived questions/users to available users/questions, (ii) LOCI-LO, which uses short-time batches for locally optimal questions-users assignment, and (iii) LOCI-AD, which assigns short- and long-deadline questions immediately and via batching, respectively. We conduct: (i) a survey to support our assumptions regarding the proposed multimodal motivation scheme, and (ii) trace-driven experiments to evaluate the performance of the three proposed LOCI's algorithms.

关键词： Social networking (online) Resource management Heuristic algorithms Real-time systems computer science Search engines Servers

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CRED: Credibility-Enabled Social Network Based Q&A System for Assessing Answers Correctness

CRED: Credibility-Enabled Social Network Based Q&A System fo...

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IEEE Conference on Wireless Communications and Networking

作者： Imad Ali Ronald Y. Chang Cheng-Hsin Hsu Taiwan International Graduate Program in Social Networks and Human-Centered Computing Institute of Information Science Academia Sinica Taipei Taiwan Research Center for Information Technology Innovation Academia Sinica Taipei Taiwan Department of Computer Science National Tsing Hua University Hsinchu Taiwan

ISBN: (数字)9781728131061

ISBN: (纸本)9781728131078

In a question & answer (Q& A) system, credible users provide answers of higher correctness. However, in a distributed social network based Q& A (SNQ& A) system, an asker does not know a k-hop answerer's credibility, thus making it difficult for the asker to assess the answer correctness. Therefore, a credibility-enabled distributed SNQ& A system is crucial for determining the correctness of the answers. To this end, we propose CRED, a credibility-enabled distributed SNQ& A system, which facilitates each user to assess the correctness of the provided answers. CRED utilizes subjective logic to build interestwise friend-to-friend credibility opinions under uncertainties. The developed opinions are then accumulated by CRED to get each user's aggregated credibility opinion, which may reflect the user's real credibility. CRED forwards a question to users with highest credibility beliefs in the question interest category. Our evaluation results show that, on average, CRED accomplishes higher success ratio, higher answer correctness, and lower answer uncertainty by 12.1%, 16.4%, and 22.2%, respectively, as compared to the best-performing baseline systems.

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The matter of deep reinforcement learning towards practical ai applications 12

The matter of deep reinforcement learning towards practical ...

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12th International Conference on Ubi-Media Computing, Ubi-Media 2019

作者： Thaipisutikul, Tipajin Chen, Yi-Cheng Hui, Lin Chen, Sheng-Chih Mongkolwat, Pattanasak Shih, Timothy K. Department of Computer Science and Information Engineering National Central University Taiwan Department of Information Management National Central University Taiwan Department of Innovative Information and Technology Tamkang University Taiwan Master's Program of Digital Content and Technologies College of Communication National ChengChi University Taiwan Faculty of Information and Communication Technology Mahidol University Thailand

ISBN: (纸本)9781728128207

Reinforcement Learning (RL) is an extraordinarily paradigm that aims to solve a complex problem. This technique leverages the traditional feedforward networks with temporal-difference learning to overcome supervised and unsupervised real-world problems. However, RL is one of state-of-the-art topic due to the opaque aspects in design and implementation. Also, in which situation we will get performance gain from RL is still unclear. Therefore, This study firstly examines the impact of Experience Replay in Deep Q-Learning agent with Self-Driving Car application. Secondly, The impact of Eligibility Trace in RNN A3C agents with Breakout AI game application is studied. Our results indicated that these two techniques enhance RL performance by more than 20 percent as compared with traditional RL methods. © 2019 IEEE.

关键词： Reinforcement learning

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