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IEEE Latin American Robotics Symposium, LARS

作者： João Alberto Fabro Matheus Biscaya Gutierrez Fernando Henrique Ratusznei Caetano DAINF - Academic Department of Informatica PPGCA - Graduate Program on Applied Computing LASER-Laboratory for Advanced Robotics and Embedded Systems UTFPR - Federal University of Technology - Paraná Curitiba PR - Brazil Information Systems academic - UTFPR - Federal University of Technology - Paraná Curitiba PR - Brazil Computer Engineering academic - UTFPR - Federal University of Technology - Paraná Curitiba PR - Brazil

ISBN: (数字)9781665462808

ISBN: (纸本)9781665462815

In this paper, an approach to aid in introductory programming courses is presented, focused on students that had never had any contact with computer programming. The approach, that was introduced in a previous paper [3], presents programming concepts using icons and “flowcharts”, and a 3D robotics simulator (CoppeliaSim), that has free educational use. This time, a real version of the simulated robot, built using Arduino and cheap, easily obtainable electronic components, is also presented. The programs to control the robot are developed by graphically constructing flowcharts on the visual editor, and then following the execution of programs using the simulated (or real) robot, step by step. This graphic program editor is named “FluxProg”, and its 2nd version is now available online, with new features comprising variables, arithmetic and logic expressions, thus providing a complete programming environment.

关键词： Flowcharts Visualization Three-dimensional displays Conferences Education Electronic components Robots

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Improving performance of federated learning based medical image analysis in non-IID settings using image augmentation

arXiv

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arXiv 2021年

作者： Cetinkaya, Alper Emin Akin, Murat Sagiroglu, Seref Information Security Program Gazi University Ankara Turkey Gazi AI Center of Gazi University Basarsoft Information Systems Inc Ankara Turkey Computer Engineering Dept. Gazi AI Center Gazi University Ankara Turkey

Federated Learning (FL) is a suitable solution for making use of sensitive data belonging to patients, people, companies, or industries that are obligatory to work under rigid privacy constraints. FL mainly or partially supports data privacy and security issues and provides an alternative to model problems facilitating multiple edge devices or organizations to contribute a training of a global model using a number of local data without having them. Non-IID data of FL caused from its distributed nature presents a significant performance degradation and stabilization skews. This paper introduces a novel method dynamically balancing the data distributions of clients by augmenting images to address the non-IID data problem of FL. The introduced method remarkably stabilizes the model training and improves the model’s test accuracy from 83.22% to 89.43% for multi-chest diseases detection of chest X-ray images in highly non-IID FL setting. The results of IID, non-IID and non-IID with proposed method federated trainings demonstrated that the proposed method might help to encourage organizations or researchers in developing better systems to get values from data with respect to data privacy not only for healthcare but also other fields. Copyright © 2021, The Authors. All rights reserved.

关键词： Data privacy

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Learner Action Patterns in the Problem-Solving Process Related to program Code Composition Based on Tracking System Activities

Learner Action Patterns in the Problem-Solving Process Relat...

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International Conference on Informatics and Computing (ICIC)

作者： Aulia Akhrian Syahidi Ahmad Afif Supianto Tsukasa Hirashima Yutaka Watanobe Smart City Information System Applied Undergraduate Program Politeknik Negeri Banjarmasin Banjarmasin City Indonesia Research Center for Data and Information Sciences National Research and Innovation Agency (BRIN) Bandung City Indonesia Learning Engineering Laboratory Graduate School of Advanced Science and Engineering Hiroshima University Kagamiyama Higashihiroshima Japan Department of Computer Science and Engineering Division of Information Systems University of Aizu Aizu-Wakamatsu City Fukushima Japan

ISBN: (纸本)9798350345728

Learning activities are an indicator of the learner's desire to learn during the learning process. The pattern of learner action is related to learning activities. In this case, in extracting the learning process, it is necessary to collect a lot of data through analysis of the learning process. The purpose of this study is to recommend and report the performance of an activity tracking system equipped with visual artifacts as an educational data mining approach to analyze action patterns when learners complete the arrangement of program code lines in each programming problem. In this study, data were taken from activity recordings when learners used interactive learning media for a basic programming subject called TOLSYASUPI-EduMed which had problem-solving learning models embedded in their interactions. Learning Analytics is used as a method of this research and data relationships from learner actions during the learning process using the “if-then” rule. Log data is used for recording and detecting activities carried out by learners. We confirm that the results of the study are based on the findings of the data relationship that if the lines of program code are too long (more than five lines) then almost all learners experience a bottleneck condition. The completion time of each question and the number of iterations in completing the program code lines for each question have also been recorded and have a pattern of connection between the data. The information that has been obtained is then forwarded to teachers or stakeholders as key information to make appropriate feedback to learners based on the results as a means of analyzing and evaluating the programming learning process.

关键词： Visualization Codes Media Data models Recording Data mining Problem-solving

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Deep Learning in Smart Healthcare: A GAN-based Approach for Imbalanced Alzheimer's Disease Classification

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Procedia computer Science 2024年 241卷 146-153页

作者： Hina Tufail Abdul Ahad Ira Puspitasari Ibraheem Shayea Paulo Jorge Coelho Ivan Miguel Pires Department of Computer Science University of Management and Technology Sialkot Pakistan Information System Study Program Faculty of Science and Technology Universitas Airlangga School of Software Northwestern Polytechnical University Xian Shaanxi P.R. China Department of Electronics and Communication Engineering Istanbul Technical University(ITU) Turkey Polytechnic University of Leiria Leiria Portugal Institute for Systems Engineering and Computers at Coimbra (INESC Coimbra) Coimbra Portugal Instituto de Telecomunicações Escola Superior de Tecnologia e Gestão de Águeda Universidade de Aveiro Águeda Portugal

Alzheimer's disease (AD) is a type of dementia that leads to memory loss and impairment, which afects patients’ lives badly. It is not curable yet, but its progression can be slowed down if detected at earlier stages. In this research study, we propose a transfer learning-based convolutional neural network (CNN) model to classify magnetic resonance imaging (MRI) into one of four stages of Alzheimer's disease. One of the major limitations of the deep learning-based classification model is the non-availability of healthcare datasets related to AD. The widely used Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset has a major class imbalance issue. We propose a generative adversarial network (GAN) based data augmentation technique to overcome the data imbalance. This promotes the investigation of applying GANs to generate synthetic samples for minority classes in Alzheimer's disease datasets to enhance classification performance. The results show the progression in the overall classification process of AD.

关键词： Alzheimer disease (AD) Deep learning Convolutional Neural Network (CNN) computer-aided diagnosis (CAD)

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Automated Fidelity Assessment for Strategy Training in Inpatient Rehabilitation using Natural Language Processing

arXiv

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arXiv 2022年

作者： Osterhoudt, Hunter Schneider, Courtney E. Mohammad, Haneef A. Shih, Minmei Harper, Alexandra E. Zhou, Leming Skidmore, Elizabeth R. Wang, Yanshan Department of Computer Science School of Computing and Information University of Pittsburgh United States Department of Occupational Therapy School of Health and Rehabilitation Sciences University of Pittsburgh United States Department of Information Science School of Computing and Information University of Pittsburgh United States Department of Health Information Management School of Health and Rehabilitation Sciences University of Pittsburgh United States Department of Biomedical Informatics University of Pittsburgh PittsburghPA United States Intelligent Systems Program University of Pittsburgh PittsburghPA United States

Strategy training is a multidisciplinary rehabilitation approach that teaches skills to reduce disability among those with cognitive impairments following a stroke. Strategy training has been shown in randomized, controlled clinical trials to be a more feasible and efficacious intervention for promoting independence than traditional rehabilitation approaches. A standardized fidelity assessment is used to measure adherence to treatment principles by examining guided and directed verbal cues in video recordings of rehabilitation sessions. Although the fidelity assessment for detecting guided and directed verbal cues is valid and feasible for single-site studies, it can become labor intensive, time consuming, and expensive in large, multi-site pragmatic trials. To address this challenge to widespread strategy training implementation, we leveraged natural language processing (NLP) techniques to automate the strategy training fidelity assessment, i.e., to automatically identify guided and directed verbal cues from video recordings of rehabilitation sessions. We developed a rule-based NLP algorithm, a long-short term memory (LSTM) model, and a bidirectional encoder representation from transformers (BERT) model for this task. The best performance was achieved by the BERT model with a 0.8075 F1-score. This BERT model was verified on an external validation dataset collected from a separate major regional health system and achieved an F1 score of 0.8259, which shows that the BERT model generalizes well. The findings from this study hold widespread promise in psychology and rehabilitation intervention research and practice. Copyright © 2022, The Authors. All rights reserved.

关键词： Video recording

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Gaussian Mixture Model Implementation for Population Stratification Estimation from Genomics Data

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Procedia computer Science 2021年 179卷 202-210页

作者： Arif Budiarto Bharuno Mahesworo Alam Ahmad Hidayat Ika Nurlaila Bens Pardamean Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Information Systems Department BINUS Online Learning Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480

Genomics study, as opposed to socio-anthropology, has been demonstrated as an excellent tool to picture biological relatedness and disease risk factors. To analyze the data obtained from the study, Genome-wide Association Study (GWAS) has been more than decades known as the mainstay approach., is the most popular approach in analysing genomics data. The confounding variables selection, being that ancestry estimation or population stratification, is substantial to maintain the quality of GWAS. Researchers have developed various methods in extracting the population stratification information from high dimensional genomics data, especially Single Nucleotide Polymorphisms (SNPs) data. In the present study, we proposed an implementation of Principal Component Analysis (PCA)-complemented Gaussian Mixture Model (GMM) as an unsupervised model to estimate population stratification from samples. The results derived from this approach was further compared to that resulted from K-means and from the commonly used ancestry estimation software, fast STRUCTURE. We figured out that our recent improved approach outperformed the two later mentioned as shown by the average cluster and population scores. Furthermore, it was able to generate the probability distribution of each sample across all population, despite its limited quality. These intriguing results worth further investigations with much more comprehensive population coverage and more advanced algorithm.

关键词： Population Stratification Ancestry Estimation Gaussian Mixture Model Genomics SNPs

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Performance comparison of CATA's information retrieval system application vs WTS

Performance comparison of CATA's information retrieval syste...

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International Conference on Engineering, Technology and Innovative Researches 2019, ICETIR 2019

作者： Purnama, Jajang Jaya Rahayu, Sri Sfenrianto Nugraha, Fitra Septia Nurfalah, Ridan Nawawi, Hendri Mahmud Shidiq, Muhammad Ja'Far Ichsan, Nurul Fatah, Haerul Master of Computer Science Postgraduate Program STMIK Nusa Mandiri Jakarta Indonesia Information Systems Management Department BINUS Graduate Program Master of Information Systems Management Bina Nusantara University Indonesia Information Systems Bina Sarana Informatika University Indonesia

Searching for data or documents that are always a necessity in the world of education, work, research an others requires convenience so that time efficiency occurs. This is supported by the emergence of various information Retrieval system applications, one of which is cata, which is built on the Java programming language and applies the Generalized Vector Space Model method which can search based on similar keywords. Other facilities need to be developed, one of which is by applying the stemmer porter algorithm applied to the WTS (Web Tokenization Stemming) web which is built with the laravel framework that can search data or documents simply by typing the basic words so that searches are easier and faster. © 2019 IOP Publishing Ltd. All rights reserved.

关键词： Search engines

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Queue Management Priority-Based Traffic Engineering Method

Queue Management Priority-Based Traffic Engineering Method

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International Scientific-Practical Conference Problems of Infocommunications Science and Technology

作者： Oleksandr Lemeshko Oleksandra Yeremenko Anatoliy Persikov Maryna Yevdokymenko Amal Mersni Serhii Harkusha V.V. Popovskyy Department of Infocommunication Engineering Kharkiv National University of Radio Electronics Kharkiv Ukraine Department of Engineering Computer Sciences and Engineering Program International University of Sarajevo Sarajevo Bosnia and Herzegovina Department of Document Studies and Information Activities in Economic Systems Poltava University of Economics and Trade Poltava Ukraine

The work proposes the improvement of queue management priority-based Traffic Engineering method. It is based on the interaction prediction principle to coordinate decisions at various levels. The lower level of calculations is responsible, firstly, for the distribution and aggregation of packet flows between the macro queues and sub-queues organized on the router interface (congestion management task), and, secondly, for the balanced distribution of interface bandwidth among sub-queues, weighted relative to their priorities (resource allocation task). The upper level of the method's calculations is accountable for distributing the interface's bandwidth between macro queues by performing the iterative procedure. The numerical research results of the proposed two-level queue management method confirmed its effectiveness in ensuring high scalability, balanced priority- based distribution of packet flows and interface bandwidth between the macro queues and sub-queues organized on it. The method demonstrated high coordination procedure convergence and the final quality of centralized calculations.

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Financial transaction database design for jamu small-medium enterprises

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AIP Conference Proceedings 2023年第1期2594卷

作者： R. Rahutomo A. Permatasari Y. Lie B. Pardamean Information Systems Department School of Information Systems Bina Nusantara University Jakarta Indonesia 11480 Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480

As jamu small-medium enterprises (SMEs) concentrate on establishing online sales and computerized systems, Point of Sales (PoS) becomes a strategic solution to maintain financial ...

As jamu small-medium enterprises (SMEs) concentrate on establishing online sales and computerized systems, Point of Sales (PoS) becomes a strategic solution to maintain financial stability with its capabilities in recording electronic transactions accurately. As the initial step in technology empowerment for jamu SMEs, the research proposes a concept in facilitating jamu SMEs to adapt in online business. A combination of Connolly and Begg's database design principles and McCarthy's Marketing Mix 4P generates a conceptual design of PoS database targeted specifically for jamu SMEs. The database design manages online purchasing transactions for jamu products by involving not only jamu SMEs and consumers but also a system administrator who manages data verification and extraction.

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Questionnaire design for analyzing important risk factors of cervical cancer

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AIP Conference Proceedings 2023年第1期2594卷

作者： K. Purwandari D. Sudigyo A. S. Perbangsa A. Irwan B. Pardamean Bioinformatics & Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Information Systems Department School of Information Systems Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480

Cervical cancer is Indonesia's second leading cause of death, following only breast cancer. According to the World Health Organization (WHO), non-communicable disorders will be blamed for 70% of all deaths and illnesses in 2020, while other disease types will account for 60%. Cervical cancer can be detected earlier, lowering the chance of death. This study aims to validate and check the pap smear test results obtained from the previously conducted pap smear screening program. The pap smear questionnaire developed would help in the compilation of a patient's habit history that has undergone a pap smear test during his life based on the factors associated with the occurrence of cervical cancer. Specific details, social-demographic features, diet, genital hygiene activities, reproductive background and behaviors, and health care and cancer prevention behavior are also included in the questionnaire template. The consequence of this design is the completeness of evidence on the theory of anomalies dependent on the findings of pap smear sampling.

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