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37th International Conference on Advanced Information Networking and Applications, AINA 2023

作者： Barbosa, Bryan C. M. Garan, Steven A. Quintela, Barbara Melo Dantas, Mario R. Universidade Federal de Juiz de Fora Juiz de Fora Brazil Center for Research and Education in Aging University of California Berkeley and Lawrence Berkeley National Laboratory BerkeleyCA United States Computational Physiology and High Performance Computing Laboratory and Computer Science Department at Universidade Federal de Juiz de Fora Juiz de Fora Brazil Computer Science Graduate Program at Universidade Federal de Juiz de Fora Juiz de Fora Brazil

ISBN: (纸本)9783031290558

It is being observed that the use of Internet of Medical Things (IoMT) in health sciences research grows as the technology and miniaturization of devices occur. Those devices often times suffer from several issues such as: being invasive, lacking the ability to collect many signals concurrently and communication. The present work proposes an approach to the use of an ultra-small IoMT device to fulfill the functions of a bio-signals data collector, a mathematical models processor, a data transmitter-receptor through the network, and a mechanical actuators controller. Our test environment was conceived to be used in animal models. This is an ongoing project from which partial results indicate that, when functioning, the device will use real-time data for monitoring bio-signals and helping with decision-making as it interacts with the organism. The data collection is going to be made through low-cost non-invasive sensors. Therefore, it can favor installation, maintenance, access, and promote a better quality of life for the user. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Decision making

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The effect of real-time pose recognition on badminton learning performance

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Interactive Learning Environments 2023年第8期31卷 4772-4786页

作者： Lin, Kuo-Chin Ko, Cheng-Wen Hung, Hui-Chun Chen, Nian-Shing Center for Physical and Health Education National Sun Yat-sen University Kaohsiung Taiwan Department of Computer Science and Engineering National Sun Yat-sen University Kaohsiung Taiwan Graduate Institute of Network Learning Technology National Central University Chung-Li Taiwan Institute for Research Excellence in Learning Sciences and Program of Learning Sciences National Taiwan Normal University Taipei Taiwan

Badminton is a very popular subject in Physical Education (PE). Many students enroll badminton courses in every semester which pose a tremendous teaching load to the instructors. The one-on-one guiding/feedback time provided by the instructor to each student is also greatly reduced. To overcome this challenge, some studies have tried to adopt pose recognition technique in teaching badminton. However, the lack of mobility and recognition accuracy problems hinder its applicability. To address this issue, a new pose recognition technique, OpenPose, was employed to develop a real-time pose recognition badminton teaching APP in this study. The APP was then installed on a mobile device to enhance badminton smash skill learning performance. The scores distribution of the experimental group shows majority of students achieved satisfactory performance, this implies the badminton teaching APP is helpful to all students no matter what their initial skill levels are. © 2021 Informa UK Limited, trading as Taylor & Francis Group.

关键词： badminton teaching motor skill learning physical education Pose recognition real-time feedback

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Development of Automated Detection Methods for Calculating Blood Vessel Width and Stenosis Rate in Cardiac Catheterization Imaging 24

Development of Automated Detection Methods for Calculating B...

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8th International Conference on Medical and Health Informatics, ICMHI 2024

作者： Huang, Hsien-Cheng Chang, Hsiao-Huang Ke, Xiang-Wei Chien, Ting-Ying Department of Computer Science and Engineering Yuan Ze University Taoyuan City Taiwan Cardiovascular Surgery Department Taipei Veterans General Hospital Taipei City Taiwan Taipei Medical University Taipei City Taiwan Graduate Program in Biomedical Informatics Yuan Ze University Taoyuan City Taiwan Innovation Center for Big Data and Digital Convergence Yuan Ze University Taoyuan City Taiwan

ISBN: (纸本)9798400716874

Coronary artery disease is the most prevalent type of heart disease and has a considerable mortality rate. In diagnosing and assessing coronary artery disease, physicians must integrate a variety of clinical information and test results to evaluate the degree of coronary artery obstruction and continually learn and improve their skills in clinical practice to ensure the most accurate assessment of patients. Currently, the use of information technology to assist medical staff allows more effective and accurate analysis of symptoms. This approach not only serves as an auxiliary standard for physician diagnosis, thereby reducing the possibility of misdiagnosis, but also significantly improves patient treatment outcomes and medical quality while reducing the time burden on physicians for diagnosing patients. This study utilized image processing techniques and thinning algorithms to automate the detection of coronary artery width and, following the recommended methods of physicians in related fields, used specific vessel widths to calculate the degree of coronary artery narrowing. This provides a more accurate and efficient assessment method for evaluating the degree of vascular constriction in patients with coronary artery disease. © 2024 Copyright ACM.

关键词： Patient treatment

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Chiral exceptional point enhanced active tuning and non reciprocity in micro-resonators

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光：科学与应用（英文版） 2025年第2期14卷 401-410页

作者： Hwaseob Lee Lorry Chang Ali Kecebas Dun Mao Yahui Xiao Tiantian Li Andrea Alù Sahin K.Özdemir Tingyi Gu Department of Electrical and Computer Engineering University of DelawareNewarkDelaware 19716USA Department of Engineering Science and Mechanics Pennsylvania State UniversityUniversity ParkPA 16802USA Photonics Initiative Advanced Science Research CenterCity University of New YorkNew YorkNY 10031USA Physics Program Graduate CenterCity University of New YorkNew YorkNY 10016USA Department of Engineering Science and Mechanics Pennsylvania State UniversityUniversity ParkPA 16802USA Department of Electrical and Computer Engineering Saint Louis UniversitySaint LouisMO 63103USA

Exceptional points(EPs)have been extensively explored in mechanical,acoustic,plasmonic,and photonic ***,little is known about the role of EPs in tailoring the dynamic tunability of optical devices.A specific type of EPs known as chiral EPs has recently attracted much attention for controlling the flow of light and for building sensors with better responsivity.A recently demonstrated route to chiral EPs via lithographically defined symmetric Mie scatterers on the rim of resonators has not only provided the much-needed mechanical stability for studying chiral EPs,but also helped reduce losses originating from nanofabrication imperfections,facilitating the in-situ study of chiral EPs and their contribution to the dynamics and tunability of ***,we use asymmetric Mie scatterers to break the rotational symmetry of a microresonator,to demonstrate deterministic thermal tuning across a chiral EP,and to demonstrate EP-mediated chiral optical nonlinear response and efficient electro-optic *** results indicate asymmetric electro-optic modulation with up to 17 dB contrast at GHz and CMOS-compatible voltage *** wafer-scale nano-manufacturing of chiral electro-optic modulators and the chiral EP-tailored tunning may facilitate new micro-resonator functionalities in quantum information processing,electromagnetic wave control,and optical interconnects.

关键词： active point micro chiral enhanced exceptional reciprocity resonators tuning

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Demonstration of a Polarization-Agnostic Geometric Phase in Nonlocal Metasurfaces

arXiv

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arXiv 2023年

作者： Overvig, Adam Kasahara, Yoshiaki Xu, Gengyu Alù, Andrea Photonics Initiative Advanced Science Research Center Graduate Center of the City University of New York United States Department of Electrical and Computer Engineering The University of Texas Austin United States Physics Program Graduate Center City University of New York United States

Symmetry-driven phenomena arising in nonlocal metasurfaces supporting quasi-bound states in the continuum (q-BICs) have been opening new avenues to tailor enhanced light-matter interactions via perturbative design principles. Geometric phase concepts—observed in many physical systems—are particularly useful in nonlocal metasurfaces, as they enable to locally pattern the q-BIC scattering rate and phase across the metasurface aperture without affecting the delocalized nature of the q-BIC resonance. However, this control typically comes with stringent limitations in terms of efficiency and/or of polarization operation. Here, we unveil a new form of geometric phase control, accumulated along a continuous contour of geometric perturbations that parametrically encircle a singularity associated with a bound state. This response is obtained regardless of the chosen polarization state, which can be rationally specified by a judicious choice of the perturbation geometry. Our findings extend geometric phase concepts to arbitrary polarizations, including linear and elliptical states, with near-unity scattering efficiency. This polarization-agnostic geometric phase offers new opportunities for wavefront manipulation, multifunctional operation and light emission, with applications in augmented reality, secure communications, wireless systems, imaging, lasing, nonlinear and quantum optics. © 2023, CC BY.

关键词： Polarization

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Data Mining and Bioinformatics Approaches to Elucidate Bacterial Communities in the Extreme Environment

Data Mining and Bioinformatics Approaches to Elucidate Bacte...

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

作者： Joko Pebrianto Trinugroho Alam Ahmad Hidayat Rudi Nirwantono Faisal Asadi Bens Pardamean Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia Mathematics Department School of Computer Science Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia Biotechnology Department Faculty of Engineering Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia Computer Science Department School of Computer Science 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

Bacteria are microscopic organisms that can be found in many environments. They are abundant and have many roles in our life. Studying bacteria is essential so that we can identify the bacteria that are needed for many industrial applications. However, the main problem is that majority of the bacteria are unculturable, hampering the exploration of bacteria from different environments. Metagenomics approach which employs Next Generation Sequencing technology could help study bacteria by utilizing 16S rRNA marker gene. This study aims to demonstrate data mining and bioinformatics approaches to analyze 16S rRNA sequencing data. The raw sequencing data of 16S rRNA was collected from biological database. Then, the data were trimmed, denoised, and clustered to generate Amplicon Sequence Variants (ASVs). Diversity (alpha and beta) and taxonomic analyses were then conducted to elucidate the bacterial diversity and taxonomic profile of ASVs. The results of this work showed that Shannon and PD indices in China's hot spring were higher than Singapore and the USA. Furthermore, a significant difference was observed in the PD index. The unweighted UniFrac distance also showed there was a significant difference of the bacterial communities between the three locations. In addition, the taxonomic investigation unveiled prevalent bacterial groups in the ecosystem, namely Proteobacteria, Chloroflexi, Cyanobacteria, and Crenarchaeota. The research outcomes have the potential to serve as a foundational resource for subsequent bacterial metagenomic research, particularly the hot spring environment.

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UAV-Aided Data Acquisition Using Gaining-Sharing Knowledge Optimization Algorithm

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computers, Materials & Continua 2022年第9期72卷 5999-6013页

作者： Rania M Tawfik Hazem A.A.Nomer M.Saeed Darweesh Ali Wagdy Mohamed Hassan Mostafa Wireless Intelligent Networks Center(WINC) School of Engineering and Applied SciencesNile UniversityGiza12677Egypt School of Information Technology and Computer Science(ITCS) Nile UniversityGiza12677Egypt Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt Department of Mathematics and Actuarial Science School of Science and EngineeringThe American University in CairoEgypt Electronics and Communications Engineering Department Cairo UniversityEgypt University of Science and Technology Nanotechnology and Nanoelectronics ProgramZewal City of Science and TechnologyOctober Gardens6th of OctoberGiza12578Egypt

Unmanned Aerial Vehicles(UAVs)provide a reliable and energyefficient solution for data collection from the Narrowband Internet of Things(NB-IoT)***,the UAV’s deployment optimization,including locations of the UAV’s stop points,is a necessity to minimize the energy consumption of the UAV and the NB-IoT devices and also to conduct the data collection *** this regard,this paper proposes GainingSharing Knowledge(GSK)algorithm for optimizing the UAV’s *** GSK,the number of UAV’s stop points in the three-dimensional space is encapsulated into a single individual with a fixed length representing an entire *** superiority of using GSK in the tackled problem is verified by simulation in seven *** provides significant results in all seven scenarios compared with other four optimization algorithms used before with the same ***,the NB-IoT is proposed as the wireless communication technology between the UAV and IoT devices.

关键词： NB-IoT UAV GSK stop points optimization

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A Bioinformatics Analysis and Homology 3D Modeling of Dihydroxy-orotate-dehydrogenase of Plasmodium ovale

A Bioinformatics Analysis and Homology 3D Modeling of Dihydr...

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

作者： Rudi Nirwantono Khoirunnisa Assidqi Alam Ahmad Hidayat Joko Pebrianto Trinugroho Bens Pardamean Biotechnology Department Faculty of Engineering Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia Biotechnology Department Faculty of Engineering Food Biotechnology Research Center Bina Nusantara University Jakarta Indonesia Mathematics Departement School of Computer Science Bioinformatics and Data Science Research Center 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 Program Bina Nusantara University Jakarta Indonesia

The infection of Plasmodium vivax is relatively less virulent than the deathliest Plasmodium falciparum. However, it still can lead to a fatal case and often induces recurring malaria due to dormant parasites in the liver. Thus, the research to study the drug to treat Plasmodium vivax is essential, where the enzyme dihydroorotate dehydrogenase (DHODH) has recently become a new drug target. However, the drug-enzyme interaction study has only recently been conducted in Plasmodium falciparum (pfDHODH) due to the lack of the 3D structure of enzyme DHODH from Plasmodium vivax that is crucial for the study. Therefore, this study aimed to perform the modelling study of Plasmodium vivax DHODH (PvDHODH) to create a 3D structure as a basis for drug-protein interaction study in upcoming studies. Sequence pvDHODH (Accession: SCO68359.1) was used in homology modelling using Modeller 10.2 with the crystal structure of DHODH from DHODH (Accession: 7KZY) as a template. Overall, the model generated from the homology modelling was considered a good model, and the 3D structure was close to the native state according to several parameters, including DOPE score, GA341 score, QMEAN4 value, 3D-1D score, ERRAT2 score, and ProSA score. Ramachandran plot also revealed that almost all amino acids were distributed in the desirable and allowed area (99.1%), and only 0.9% were in generously allowed regions. Superimposition of the model with the template also indicated that the model has an almost similar structure and amino acids positioning, including in the binding pocket and active site. Therefore, the model can be used for downstream analysis in drug-protein interaction studies. Nevertheless, some improvements can still be performed to upgrade the quality of the model by deleting unaligned residues on the C-terminal and realigning the residues at the doubting site.

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Automatic Smart Crawling on Twitter for Weather Information in Indonesia

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Procedia computer science 2023年 227卷 795-804页

作者： Kartika Purwandari Reza Bayu Perdana Join W.C. Sigalingging Reza Rahutomo Bens Pardamean Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta 11480 Indonesia Database Center Division of BMKG Meteorological Climatological and Geophysical Agency Jakarta 10720 Indonesia Information Systems Department School of Information Systems Bina Nusantara University Jakarta 11480 Indonesia Computer Science Department BINUS Graduate Program – Master of Computer Science Bina Nusantara University Jakarta 11480 Indonesia

Although Twitter is a popular platform for social interaction analysis and text data mining, it faces challenges with geolocation automation. To address this problem, the researchers propose the utilization of a Support Vector Machine (SVM) model to develop an automated Twitter crawling system. The system aims to collect data related to weather in Indonesia by employing Twin, a Python-based Twitter scraping software. To overcome null geolocations, the study incorporates aliases created based on the common practice of Indonesian users mentioning the country's location in tweets. The results demonstrate that the SVM model, combined with automated smart crawling, achieves an 85% accuracy rate.

关键词： Social media Twitter SVM smart crawling weather

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Towards a Reliable Hierarchical Android Malware Detection Through Image-based CNN

Towards a Reliable Hierarchical Android Malware Detection Th...

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Consumer Communications and Networking Conference, CCNC IEEE

作者： Jhonatan Geremias Eduardo K. Viegas Altair O. Santin Alceu Britto Pedro Horchulhack Pontificia Universidade Catolica do Parana (PUCPR) - Graduate Program in Computer Science (PPGIa) Brazil Secure Systems Research Center - Technology Innovation Institute (TII) Abu Dhabi

The number of Android malicious applications keeps growing as time passes, even paving their way to official app markets. In recent years, a promising malware detection approach makes use of the compiled app source codes (dex), through convolutional neural networks (CNN) as an image classification task. Unfortunately, current proposals often rely on unrealistic datasets, focusing their detection on the mal-ware families, while neglecting the detection of malware apps in the first place. In this paper, we propose a reliable and hierarchical Android malware detection through an image-based CNN scheme, implemented twofold. First, Android malware classification is performed in a hierarchically-structured local manner, initially identifying malware apps, then, their related family. Second, to ensure reliability and improve classification accuracy, only highly confident classified apps are reported, in a classification with reject option rationale. Experiments performed in a new dataset with over 26 thousand Android apps, divided into 29 malware families, compounding over 13 GB of app dex images, have shown that current image-based CNN for malware detection is unable to provide high detection accuracies. In contrast, our proposed model is able to reliably detect malware apps, improving the true-negative rates by up to 5.5%, and the average true-positive rate of the malware families of accepted apps by up to 12.7%, while rejecting only 10% of Android apps.

关键词： Source coding Focusing Malware Convolutional neural networks Reliability Proposals Task analysis

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