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International Conference on Informatics, Multimedia, Cyber and Information System (ICIMCIS)

作者： Faisal Asadi Joko Pebrianto Trinugroho Alam Ahmad Hidayat Reza Rahutomo Bens Pardamean Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia Information System Department School of Information Systems Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program Master of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (纸本)9781665473286

Tropical disease is one of the infectious diseases that affect Indonesia. Many people die because of tropical diseases, such as dengue hemorrhagic fever (DHF), chikungunya, leprosy, lymphatic, and filariasis. The Indonesian government's lack of public policy is the main problem in treating and preventing tropical diseases. The paper aims to describe the analysis results of the incidence of DHF in Jakarta, Indonesia. The analysis used the DHF incidences data from the Jakarta Health service surveillance office representative and combined it with the meteorological parameters data. The meteorological parameters were collected from the Bureau of Meteorological Climatology and Geophysics (BMKG). The statistical analysis of this research used Pearson's correlation. The results show that the meteorological parameters affecting DHF incidences are temperature, humidity, and wind speed.

关键词： Correlation Statistical analysis Wind speed Surveillance Multimedia systems Sociology Humidity

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A Design of Childhood Stunting Assessment Feature with Agile UX Approach

A Design of Childhood Stunting Assessment Feature with Agile...

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HCI and UX Conference in Indonesia (CHIuXiD), International

作者： Reza Rahutomo Anzaludin Samsinga Perbangsa Faisal Asadi Rudi Nirwantono Bens Pardamean Information Systems Department School of Information Systems Bina Nusantara University Jakarta Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program – Master of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (纸本)9781665476652

multidisciplinary collaboration between public health, system engineering, and UX is able to generate a solution in healthcare problem like stunting. The principle of Agile UX gathers requirements to generate an application design. Currently, various website and mobile applications are available to be utilized for stunting research. StuntingDB is one of many web-based applications that specialized in stunting data management. The application required several types of users to operate hierarchically. This research focused on Public Health Officers’ workflow that require a solution to in the form of assessment module for stunting DBMS by using Agile UX principle. The method collaborates agile team and UX team to solve Public Health Officer's difficulty in changing stunting status at pre-saved child patient's profile. Collaboration of both agile team and UX team successfully proposed an application design that system design.

关键词： Human computer interaction Pediatrics Collaboration Companies Mobile applications Public healthcare System analysis and design

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High‐Order Synchrosqueezed Chirplet Transforms for Multicomponent Signal Analysis

SSRN

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SSRN 2024年

作者： Yen, Yi-Ju Lu, De-Yan Yeh, Sing-Yuan Ding, Jian-Jiun Shen, Chun-Yen Graduate Institute of Communication Engineering National Taiwan University No. 1 Sec. 4 Roosevelt Rd. Taipei10617 Taiwan Graduate Institute of Mathematics National Taiwan University No. 1 Sec. 4 Roosevelt Rd. Taipei10617 Taiwan Data Science Degree Program National Taiwan University Academia Sinica No. 1 Sec. 4 Roosevelt Rd. Taipei10617 Taiwan

This study focuses on the analysis of signals containing multiple components with crossover instantaneous frequencies (IF). This problem was initially solved with the chirplet transform (CT). Also, it can be sharpened by adding the synchrosqueezing step, which is called the synchrosqueezed chirplet transform (SCT). However, we found that the SCT goes wrong with the high chirp modulation signal due to the wrong estimation of the IF. In this paper, we present the improvement of the post-transformation of the CT. The main goal of this paper is to amend the estimation introduced in the SCT and carry out the high-order synchrosqueezed chirplet transform. The proposed method reduces the wrong estimation when facing a stronger variety of chirp-modulated multi-component signals. The theoretical analysis of the new reassignment ingredient is provided. Numerical experiments on some synthetic signals are presented to verify the effectiveness of the proposed high-order SCT. © 2024, The Authors. All rights reserved.

关键词： Chirp modulation

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The Technology Behind Genomic database

The Technology Behind Genomic Database

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International Conference on Cybernetics and Intelligent System (ICORIS)

作者： Joko Pebrianto Trinugroho Anzaludin Samsinga Perbangsa Bens Pardamean Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia Information Systems Department School of Information Systems Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (纸本)9781665453967

In this digital era, we are exposed to a large amount of data. This includes biological data, which stores information about living organisms, including Deoxyribonucleic acid (DNA), genes, and proteins. With the development of information technology and information system, most of available biological data are stored in an online public database. Many of the databases are free-access and easily used, which helps the users, especially researchers, to make use of the data. Among the known public biological databases are the University of California Santa Cruz (UCSC) Genome Browser database and the Rat Genome database (RGD). These two databases provide access to the biological data from different organisms. This paper aims to describe the technology of public biological databases. Also elucidated in this paper are the differences features between UCSC Genome Browser database and the RGD. Our results showed that the UCSC contains much more biological data and features than the RGD. However, the genome browser of UCSC has a complex display, while the RGD has a simple display. Overall, both databases give the users the option to choose the most suitable database for them.

关键词： Proteins databases Genomics DNA Rats Biology Organisms

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Performance Prediction in Major League Baseball by Long Short-Term Memory Networks

arXiv

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arXiv 2022年

作者： Sun, Hsuan-Cheng Lin, Tse-Yu Tsai, Yen-Lung Center for Information Systems and Technology Claremont Graduate University Claremont United States Data Science Degree Program National Taiwan University Taipei Taiwan Department of Mathematical Sciences National Chengchi University Taipei Taiwan

Player performance prediction is a serious problem in every sport since it brings valuable future information for managers to make important decisions. In baseball industries, there already existed variable prediction systems and many types of researches that attempt to provide accurate predictions and help domain users. However, it is a lack of studies about the predicting method or systems based on deep learning. Deep learning models had proven to be the greatest solutions in different fields nowadays, so we believe they could be tried and applied to the prediction problem in baseball. Hence, the predicting abilities of deep learning models are set to be our research problem in this paper. As a beginning, we select numbers of home runs as the target because it is one of the most critical indexes to understand the power and the talent of baseball hitters. Moreover, we use the sequential model Long Short-Term Memory as our main method to solve the home run prediction problem in Major League Baseball. We compare models' ability with several machine learning models and a widely used baseball projection system, sZymborski Projection System. Our results show that Long Short-Term Memory has better performance than others and has the ability to make more exact predictions. We conclude that Long Short-Term Memory is a feasible way for performance prediction problems in baseball and could bring valuable information to fit users' needs. Copyright © 2022, The Authors. All rights reserved.

关键词： Baseball

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High-Order Synchrosqueezed Chirplet Transforms for Multicomponent Signal Analysis

arXiv

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arXiv 2024年

关键词： Chirp modulation

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Quality of dental treatments under intravenous sedation among patients with disability: A self-matching study

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Journal of Dental sciences 2023年第2期18卷 761-766页

作者： Chen, Hsiu-Hsien Lin, Po-Yen Lin, Ching-Kai Hsu, Le-Yin Hung, Ming-Hua Lin, Ping-Yi Chi, Lin-Yang Department of Dentistry School of Dentistry National Yang Ming Chiao Tung University Taipei Taiwan Department of Dentistry National Defense Medical Center Taipei Taiwan Department of Dentistry New Taipei Municipal Tucheng Hospital New Taipei City Taiwan Institute of Epidemiology and Preventive Medicine College of Public Health National Taiwan University Taipei Taiwan Graduate Program of Data Science National Taiwan University and Academia Sinica Taipei Taiwan Department of Dentistry Far Eastern Memorial Hospital New Taipei City Taiwan Department of Stomatology Kaohsiung Veterans General Hospital Kaohsiung Taiwan

Background/purpose: Patients with disabilities usually have difficulties in communication and mobility, and the quality of the dental treatments are often inferior. This study uses the Taiwan National Health Insurance database to analyze the quality of dental treatment for patients with disabilities who receive intravenous sedation (IVS). Materials and methods: This study selected patients with disabilities who received dental treatment under IVS. Their oral cavity was divided into three major sections: anterior teeth, upper posterior teeth, and lower posterior teeth. Self-matching of the same section was conducted to observe whether operative dental treatment (OD) with or without IVS affected the occurrence of dental retreatment. This study observed the occurrence of refilling and the duration from the end of treatment until retreatment to compare treatment differences with or without IVS. Results: After self-matching, this study found 158 patients who received dental treatment within the same section with and without IVS. During a follow-up period of 17 years, 75.18% of the patients who received OD treatment required refilling, 10.87% required endodontic treatment, and 5.67% required tooth extraction. After OD treatment with IVS, the risks of refilling, endodontic treatment, and tooth extraction were 0.71 (95% CI: 0.58–0.87, P < 0.001), 0.77 (95% CI: 0.48–1.23, P = 0.28), and 0.64 (95% CI: 0.32–1.27, P = 0.20), respectively. Conclusion: For patients with disabilities, OD treatment with IVS significantly reduces the risk of refilling compared with OD treatment without IVS. IVS can be ideal for people with disabilities who receive dental treatment. © 2023 Association for Dental sciences of the Republic of China

关键词： Intravenous sedation National health insurance database Patients with disabilities

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Trends, Opportunities, and Challenges in Detecting Depressive Disorders Through Mobile Devices: A Review

Trends, Opportunities, and Challenges in Detecting Depressiv...

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Computer System, Information Technology, and Electrical Engineering (COSITE), International Conference on

作者： Gregorius Natanael Elwirehardja Mahmud Isnan Anzaludin Samsinga Perbangsa Kahlil Muchtar Bens Pardamean Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia Information System Department School of Information Systems Bina Nusantara University Jakarta Indonesia Department of Electrical and Computer Engineering Universitas Syiah Kuala Banda Aceh Indonesia Computer Science Department BINUS Graduate Program -Master of Computer Science Bina Nusantara University Jakarta Indonesia

Depressive Disorders (DD) is one of the most prevalent mental disorders in the world that may lead to suicide cases. To prevent the latter, ubiquitous early detection systems may be effective. Recent studies have since researched the development of such systems by exploiting several forms of data, including video, audio, Ecological Momentary Assessments (EMA), and passive sensing data using sensors embedded in mobile devices. To summarize the trends, opportunities, and existing challenges in this field, this study reviewed 15 papers to answer four research questions. EMA was the most popular data to be used in this task, but other approaches, such as using video, audio, and typing behaviors, may be considered due to the subjectivity of EMA. These data were typically recorded using smartphones and analyzed using Machine Learning (ML). However, most of the developed systems had yet to be implemented. Overall, it was concluded that further studies may need to explore usages of more objective data in multimodal approaches as well as consider using Mobile Cloud Computing (MCC) to deploy these systems to provide more effective and efficient diagnoses. Future studies must also take into account the existing challenges of the data and infrastructures, such as the weaknesses of several data types, limitations of mobile devices, as well as the challenges of diagnosis approaches.

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Genome data mining approach to identify potential protein in crop plants

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AIP Conference Proceedings 2024年第1期3026卷

作者： Joko Pebrianto Trinugroho Faisal Asadi Bens Pardamean Bioinformatics & Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program - Master of Computer Science Program Bina Nusantara University Jakarta Indonesia 11480

There is a need to produce more crop plants to meet the future global demand. However, the climate change has affected the global crop yield. Consequently, finding an alternative approach to improve crop yield becomes essential. The development of sequencing techniques, as well as information technologies, have enabled us to perform genome data mining. Using genome data mining approach, it is possible to identify or discover a protein which has a particular characteristic. This study aims to identify a protein, which could potentially improve crop yield, using genome data mining approach. D1 protein was used as the target, as this protein is highly involved in photosynthesis. Then, protein sequences of various crop plants were collected from biological database. After conducting data trimming and filtering, sequence analysis was performed. The analysis was used to construct phylogenetic tree and create a 3D protein model. Sequence analysis displayed variation in amino acid sequence in D1 protein. Protein modelling located the variations, which scattered within D1 protein. Furthermore, we highlighted the amino acid residues that are the targets for genetic engineering. The research findings may provide a reference to improve crop production through genome mining approach.

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Sensing accident-prone features in urban scenes for proactive driving and accident prevention

arXiv

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arXiv 2022年

作者： Mishra, Sumit Rajendran, Praveen Kumar Vecchietti, Luiz Felipe Har, Dongsoo The Robotics Program Korea Advanced Institute of Science and Technology Daejeon Korea Republic of Division of Future Vehicle Korea Advanced Institute of Science and Technology Daejeon Korea Republic of Data Science Group Institute for Basic Science Daejeon Korea Republic of The CCS Graduate School of Green Transportation Korea Advanced Institute of Science and Technology Daejeon Korea Republic of

In urban cities, visual information on and along roadways is likely to distract drivers and lead to missing traffic signs and other accident-prone (AP) features. To avoid accidents due to missing these visual cues, this paper proposes a visual notification of AP-features to drivers based on real-time images obtained via dashcam. For this purpose, Google Street View images around accident hotspots (areas of dense accident occurrence) identified by a real-accident dataset are used to train a novel attention module to classify a given urban scene into an accident hotspot or a non-hotspot (area of sparse accident occurrence). The proposed module leverages channel, point, and spatial-wise attention learning on top of different CNN backbones. This leads to better classification results and more certain AP-features with better contextual knowledge when compared with CNN backbones alone. Our proposed module achieves up to 92% classification accuracy. The capability of detecting AP-features by the proposed model were analyzed by a comparative study of three different class activation map (CAM) methods, which were used to inspect specific AP-features causing the classification decision. Outputs of CAM methods were processed by an image processing pipeline to extract only the AP-features that are explainable to drivers and notified using a visual notification system. Range of experiments was performed to prove the efficacy and AP-features of the system. Ablation of the AP-features taking 9.61%, on average, of the total area in each image increased the chance of a given area to be classified as a non-hotspot by up to 21.8%. © 2022, CC BY.

关键词： Accidents

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