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38th IEEE Region 10 Conference, TENCON 2023

作者： Nunome, Toshiro Takada, Yoshiyuki Computer Science Program Graduate School of Engineering Nagoya Institute of Technology Department of Engineering Nagoya466-8555 Japan

ISBN: (纸本)9798350302196

In this paper, we exploit caches on intermediate nodes for QoE enhancement of multi-view video and audio transmission over ICN/CCN by controlling the content request start timing of consumers. We assume the selected single viewpoint transmission method;a consumer receives video and audio streams of a requested viewpoint. We perform a simple experiment with two consumers. When the consumers play video and audio with the time difference, we assess the effect of cached content by the former consumer's request on the output quality of the latter consumer. We deal with two types of viewpoint change strategies for the former consumer, which affect the efficiency of cache utilization. From the assessment results, we see that cache utilization has an important factor in enhancing QoE. © 2023 IEEE.

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Detecting Cancer through Analysis of Histopathological Images 4

Detecting Cancer through Analysis of Histopathological Image...

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4th International Conference on Expert Clouds and Applications, ICOECA 2024

作者： Nikalje, Anita Vijay Tajane, Sharad Timaji Kocharekar, Archana Vekariya, Daxa Natrayan, L. Patil, Harshal Deogiri Institute of Engineering and Management Studies Department of Electronic and Telecommunication Engineering Maharashtra Aurangabad431 005 India Department of Chemistry Andheri West Mumbai India Parul institute of Engineering and Technology Parul University Department of Computer Science & Engineering Gujarat 391760 India Saveetha School of Engineering SIMATS Department of Mechanical Engineering Tamil Nadu Chennai602105 India Computer Science and Engineering Maharashtra Pune412 115 India

ISBN: (纸本)9798350385793

Prostate cancer stands out as one of the most prevalent cancers, ranking second in cancer-related male fatalities on a global scale. Early diagnosis and effective treatment are pivotal in halting the proliferation and dissemination of cancer cells within the body. The gold standard for prostate cancer detection remains histopathological image diagnosis, distinguished by its unique visual attributes. Nonetheless, the interpretation of these images necessitates a high level of expertise and is often time-consuming. One promising field to expedite this diagnostic process lies in the utilization of Artificial Intelligence (AI), particularly through the utilization of computer-Aided Diagnosis (CAD) systems. This study is dedicated to the categorization of histopathological images into 'normal' and 'prostate cancer-affected' categories, utilizing the extensive PANDAS dataset. In this study, Convolutional Neural Networks (CNN) are employed to extract relevant features, and three distinct machine learning (ML) models-Support Vector Machine (SVM), k-Nearest Neighbors (KNN), and Naïve Bayes (NB)-are applied. The experimental findings of this study highlight the superior performance of the SVM model, which achieves an impressive accuracy rate of 98%, while also exhibiting minimal false negative and positive rates of 1.98% and 2.01%, respectively. This research underscores the potential of AI technology in prostate cancer identification. © 2024 IEEE.

关键词： Lung cancer

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Bioinformatics exploration into potential mechanisms of Calamus draco for colorectal cancer treatment 9th

Bioinformatics exploration into potential mechanisms of Cala...

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9th International Conference on computer science and Computational Intelligence, ICCSCI 2024

作者： Kenneth, Christian Nirwantono, Rudi Pardamean, Bens Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia Biotechnology Department Faculty of Engineering Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program Computer Science Program Bina Nusantara University Jakarta11480 Indonesia

As one of the cancer types with the highest incidence rates, colorectal cancer (CRC) would benefit from treatments with fewer side effects and reduced treatment-resistant potential. One of the options is to harness the anti-CRC potential of natural products. Previous studies have shown that Calamus draco exudate, dragon's blood, has anticancer activity in liver cancer and acute myeloid leukemia, but its bioactivity has not been studied in CRC. Here we conduct a bioinformatics study based on network pharmacology to explore the anti-CRC potential and mechanism of C. draco-derived compounds. The bioinformatics pipeline is composed of compound and target collection, biological network evaluation, and enrichment analysis. We found that there are 43 bioactive compounds from C. draco targeting 91 CRC-related targets, of which most compounds target MEN1, PTGS2, and IDH1. Further analyses show that the targets of C. draco are involved in the cellular response to hypoxia. By inhibiting those targets, C. draco bioactive compounds can potentially hinder angiogenesis and increase treatment response efficacy. © 2024 The Authors.

关键词： Lung cancer

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Advances in 3D fusion of multimodal medical images: 3D reconstruction of bone, muscle, and ligament structures under load from radiographs and magnetic resonance imaging

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Research on Biomedical engineering 2025年第1期41卷 1-35页

作者： da Silva, Daniel S. Astolfi, Rodrigo S. Jagatheesaperumal, Senthil K. Selvaraj, Priyadharsini Russel, Newlin Shebiah de Albuquerque, Victor Hugo C. Post-Graduation Program of Medical Surgical Sciences Federal University of Ceara CE Fortaleza60455-970 Brazil Department of Teleinformatics Engineering Federal University of Ceara CE Fortaleza60455-970 Brazil Department of Electronics and Communication Engineering Mepco Schlenk Engineering College TN Sivakasi626005 India Department of Computer Science and Engineering Mepco Schlenk Engineering College TN Sivakasi626005 India

Purpose: Foot and ankle pathologies are among the most prevalent conditions within the human locomotor system. Imaging examinations are crucial for diagnosing, treating, and achieving satisfactory functional outcomes for these conditions. However, conventional imaging exams often fail to capture all the necessary details for precise analysis, necessitating the use of multiple imaging modalities to evaluate bones, ligaments, cartilage, and other structures. Objective: This research aims to explore computational technologies and algorithms for 3D reconstruction and fusion of foot and ankle images, alongside the analysis, segmentation, classification, and evaluation techniques applied to these images. Methods: The study investigates different computational approaches for 3D reconstruction and multimodal image fusion, integrating X-ray and MRI data. Advanced segmentation and classification techniques are applied to enhance the precision of structural assessment. Additionally, we assess the availability and quality of databases for training and validating these models. Results: Our findings highlight a significant gap in research concerning these specific applications, as well as a shortage of suitable databases for 3D reconstruction and fusion of images from X-rays and MRI. Conclusion: The study emphasizes the need for dedicated datasets and further research to develop effective computational solutions for multimodal foot and ankle imaging. © The Author(s), under exclusive licence to The Brazilian Society of Biomedical engineering 2025.

关键词： Magnetic resonance imaging

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Outage behavior of the downlink reconfigurable intelligent surfaces-aided cooperative non-orthogonal multiple access network over Nakagami-m fading channels

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Wireless Networks 2024年第6期30卷 5093-5110页

作者： Chen, Hsing-Chung Widodo, Agung Mulyo Lin, Jerry Chun-Wei Weng, Chien-Erh Do, Dinh-Thuan Department of Computer Science and Information Engineering Lioufeng Rd. Wufeng Taichung41354 Taiwan Department of Medical Research China Medical University Hospital China Medical University Jingmao Rd. Beitun Dist. Taichung406040 Taiwan Department of Computer Science Esa Unggul University Jalan Arjuna Utara Kebon Jeruk Jakarta11510 Indonesia Department of Computer Science Electrical Engineering and Mathematical Sciences Western Norway University of Applied Sciences Inndalsveien Hordaland Bergen5063 Norway Department of Telecommunication Engineering National Kaohsiung University of Science and Technology Haijhuan Rd. Nanzih Dist. Kaohsiung81157 Taiwan

Although the non-orthogonal multiple access network (NOMA) network has already been used in 5G in wireless communication, it still needs to be supplied with large enough energy, especially for the amplify-and-forward (AF) process. Reconfigurable intelligence surface (RIS)-aided NOMA answers this weakness because it can relay without an AF process so that it could reduce the energy required for NOMA. This is conducted by vigorously relaying communication signals via transmitted signal reflection. In addition, the decode-and-forward process is dispatched to increase the signal coverage performance. It is thus expected that the RIS-aided NOMA will substantially ensure the obtainment of a lower outage probability towards the signal to noise ratio, relative channel estimation error, and distance between a base station and near users. Despite its potential, RIS might encounter a challenge to being effectively incorporated with communication networks regarding channel estimation error. This study evaluates the RIS-aided NOMA to address the issues mentioned above, and carefully derives the closest-form expressions of outage probability for a pair of users by applying perfect channel statistic information over Nakagami-m fading channel. The performance of cooperative relaying scenarios during outages is thoroughly analyzed. According to the simulation results, RIS-aided NOMA has a lower outage probability than conventional NOMA. Additionally, the optimal location for user relaying in RIS-aided NOMA and conventional NOMA networks should be closest to the base station. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2023.

关键词： Signal to noise ratio

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Internet of Medical Things: A Bibliometric Analysis of Research Publications from 2018–2022 4th

Internet of Medical Things: A Bibliometric Analysis of Resea...

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4th International Conference on Electronics, Biomedical engineering, and Health Informatics, ICEBEHI 2023

作者： Maulana, Fairuz Iqbal Lestari, Dian Adi, Puput Dani Prasetyo Arifin, Mohammad Nazir Purnomo, Agung Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Faculty of Medicine Universitas Airlangga Surabaya60132 Indonesia Telecommunication Research Center National Research and Innovation Agency Jakarta11480 Indonesia Informatics Engineering Study Program University of Madura Pamekasan Indonesia Entrepreneurship Department BINUS Business School Undergraduate Program Bina Nusantara University Jakarta11480 Indonesia

ISBN: (纸本)9789819714629

The field of the Internet of Medical Things (IoMT) is experiencing significant growth as it involves the integration of medical devices and systems with the internet and various digital technologies. This study provides a bibliometric analysis of scholarly articles pertaining to the Internet of Medical Things (IoMT) during the time frame of 2018 to 2022. The analysis is conducted using data sourced from the Scopus database. A total of 1165 documents were identified and analyzed to gain insights into the current state of research in this field. The analysis includes trends in publication output, top authors and institutions, and key research topics. The results of the analysis indicate a steady increase in publication output on IoMT over the past five years, with the highest number of publications in 2022. The top authors in this field were Mohanty, S.P., Kougianos, E., and Pirbhulal, S., while the top institutions were King Saud University, Chinese Academy of sciences, and University of North Texas. Co-citation analysis revealed that wearable devices, telemedicine, and data analytics were among the key research topics in IoMT. This bibliometric analysis offers useful insights into the present research landscape of the Internet of Medical Things (IoMT) spanning the years 2018 to 2022. The findings can be beneficial for researchers, practitioners, policymakers, and funding agencies in understanding the trends and priorities in this field. The top authors and institutions identified in this analysis can serve as valuable resources for collaboration and staying updated on the latest developments in IoMT. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Digital devices

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Auto-Handover Gateway LoRaWAN based on Autonomous Vehicles 10

Auto-Handover Gateway LoRaWAN based on Autonomous Vehicles

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10th IEEE Information Technology International Seminar, ITIS 2024

作者： Purnama, Iwan Pane, Rahmadani Sooai, Adri Gabriel Edi, Firman Chamid, Ahmad Abdul Adi, Puput Dani Prasetyo Universitas Labuhanbatu Faculty of Science and Technology Department of Information Technology Labuhanbatu Indonesia Universitas Katolik Widya Mandira Faculty of Computer Science Department of Computer Engineering NTT Kupang Indonesia Batam Institute of Technology Faculty of Industrial Technology Department of Engineering Management Batam City Indonesia Muria Kudus University Department of Informatics Engineering Kudus Indonesia Department of Telecommunication Bandung Indonesia

ISBN: (纸本)9798331521295

This article presents a simulation study on the use of LoRaWAN technology in autonomous vehicles. The research focuses on developing an Auto-Handover Gateway for Autonomous Vehicles, utilizing LoRaWAN parameters such as bit rates, spreading factor (SF), packet loss, and received signal strength. These parameters are tested in simulations of autonomous vehicle movements, which include both regular and random motion patterns. The aim is to assess the performance of LoRaWAN in different scenarios and its impact on communication in autonomous vehicle systems. The simulation results show several key trends. As the vehicle moves further, the spreading factor (SF) increases, and bit rates tend to decrease, indicating a drop in communication performance over longer distances. The research also identifies that the gateway with the closest proximity to the vehicle is selected, both in random and non-random movement scenarios. Additionally, packet loss increases as the distance between the vehicle and the gateway grows, highlighting the challenges of maintaining reliable communication over long distances. These findings provide insights into optimizing LoRaWAN parameters for real-time communication in autonomous vehicles, contributing to the development of intelligent vehicle networks. © 2024 IEEE.

关键词： Packet loss

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Optimizing Patient Flow and Resource Allocation in Hospitals using AI 1

Optimizing Patient Flow and Resource Allocation in Hospitals...

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1st International Conference on Artificial Intelligence for Innovations in Healthcare Industries, ICAIIHI 2023

作者： Rathore, Yogesh Sinha, Upasana Haladkar, Jaysing Pandurang Mate, Nilesh R. Bhosale, Supriya Ashok Chobe, Santoshkumar Vaman Shri Shankaracharya Institute of Professional Management and Technology Raipur Dept of Computer Science & Engineering Chhattisgarh India Dept of Computer Science & Engineering India Sant Gajanan Maharaj College of Engineering Department of Electronics and Telecommunication Engineering M.S. Mahagaon416503 India Centre for Distance and Online Education Pune India Sandip University Department of Computer Science & Engineering Nashik India Department of Computer Engineering Pune Ravet India

ISBN: (纸本)9798350330915

The present study investigates the incorporation of artificial intelligence (AI) into healthcare administration, with a specific focus on optimizing patient flow as well as allocating resources in various hospital environments. Using a descriptive research methodology with secondary data gathering, the study adopts an interpretivist philosophy and a deductive technique. The findings show that applying AI-driven techniques significantly improves patient wait times, the efficiency of resource utilization, and patient outcomes. The contrast between AI-enhanced practices and traditional procedures demonstrates how much better they are at optimizing patient flow. On the other hand, implementation-critical elements include initial investment expenses and ethical considerations. Investing in AI infrastructure, resolving algorithmic biases, including protecting data privacy are among the recommendations. Future research ought to concentrate on the scalability, long-term effects, and enhancements to AI systems for objective forecasts © 2023 IEEE.

关键词： artificial intelligence healthcare management interpretivism patient flow optimization resource allocation

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Machine Learning Approach to LULC Forecasting

Machine Learning Approach to LULC Forecasting

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2024 IEEE Mediterranean and Middle-East Geoscience and Remote Sensing Symposium, M2GARSS 2024

作者： Riche, Abdelkader Ricci, Riccardo Melgani, Farid Drias, Ammar Souissi, Boularbah University of Sciences and Technology Houari Boumediene Department of Geography and Territorial Planning Algeria University of Trento Department of Information Engineering and Computer Science Italy University of Sciences and Technology Houari Boumediene Department of Telecommunication Algeria

ISBN: (纸本)9798350358582

This study explores the prediction of changes in Land Use and Land Cover (LULC) over the period of 2000 to 2040 in a region of Algeria. The research combines remote sensing data and machine learning techniques. Landsat image classification is applied to assess LULC changes for the years 2000 to 2020. In addition, a novel approach is employed to account for temporal factors influencing LULC changes in 2025, 2030, and 2040. Promising results are reported and discussed. © 2024 IEEE.

关键词： Remote sensing

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Comments on a Key Agreement Scheme for the V2G System 14th

Comments on a Key Agreement Scheme for the V2G System

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14th International Conference on Frontier Computing, FC 2024

作者： Chang, Ya-Fen Chang, Wen-Ting Tai, Wei-Liang Department of Computer Science and Information Engineering National Taichung University of Science and Technology Taichung Taiwan Bachelor Degree Program of Artificial Intelligence National Taichung University of Science and Technology Taichung Taiwan

ISBN: (纸本)9789819623945

Vehicle-to-grid (V2G) technology supporting bidirectional power transfer allows electric vehicles (EVs) to contribute and consume energy bidirectionally. Because the specific properties and requirements of V2G, Khan et al. proposed a key agreement scheme for the V2G system to ensure the security of communication between a vehicle user and the grid server. However, after analyzing Khan et al.’s scheme, we find that it suffers from some flaws such that it cannot ensure anonymity, resist impersonation attack, man-in-the-middle attack and denial-of-service attack, and work as expected. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Anonymity

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