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6th International Conference on Computing and informatics, ICCI 2024

作者： Elbagoury, Bassant M. Maskeliuans, Rytis Zaghow, Marwa Kamel, Nabil Faculty of Computer and Information Sciences Ain Shams University Computer Science and Artificial Intelligence Programs Egypt Faculty of Computer Science and Engineering King Salman International University KSIU Egypt Kaunas University of Technology Faculty of Informatics Department of Multimedia Engineering Lithuania Dell Technologies EMEA Egypt

ISBN: (纸本)9798350373875

Artificial intelligence technologies for the mobile health and smart hospitals are important, by applying predictive Analytics and Deep Learning algorithms and developing new models. The main objective is applying artificial Intelligence methods in the medical field, especially for heart/brain stroke diseases diagnosis and prediction for emergency patients' cases. Thus, to save patients' lives, also through the integration with IoT and wearable technologies, which are integrated with AI and DL algorithms that help to make sense of bio signals predictive analytics such as biomedical sensors processing. and complex diseases predictions and early detection like heart and stroke diseases. Also dealing with EMG sensors for stroke prediction. Moreover, Intelligent Mobile Health based on our previously introduced project of AI smart hospital and Mobile AI stroke prediction system for connected health and stroke emergencies. In this paper, a new deep learning model has been built and tested for Stroke EMG signal prediction by modifying the Inception-v3 architecture and other deep learning models. Also, this paper compares current results of Mobile AI health Inception model with our previous developed Mobile AI stroke engine that depends on hybrid LSTM deep learning for EMG signals prediction. Both models have achieved high accuracies. Moreover, the inception model is more stable and higher average accuracies that reaches 98%. Moreover, AI research and future industry implementations for Generative AI Dell Technologies servers is discussed. © 2024 IEEE.

关键词： Learning systems

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Development of Village Open Data using DevOps Approach 6

Development of Village Open Data using DevOps Approach

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6th International Conference on informatics and Computational sciences, ICICoS 2022

作者： Yusuf, Muhammad Sophan, Moch Kautsar Satoto, Budi Dwi Anamisa, Devie Rosa Alamsyah, Nurwahyu Syarif, Iwan Universitas Trunojoyo Madura Informatics Engineering Department Bangkalan Indonesia National Taiwan University of Science and Technology Information Management Department Taipei Taiwan Politeknik Elektronika Negeri Surabaya Informatics Engineering Department Surabaya Indonesia

ISBN: (数字)9781665460996

ISBN: (纸本)9781665460996

Open data is one of the important e-government implementations as part of digital transformation. This research aims to survey Open Data applications in various cities, bodies, and ministries of Indonesia and overseas. The survey results are important for developing an open data application in Alang-Alang village, Bangkalan, Madura, Indonesia. The research contributes by presenting survey results for preparing the Open data implementation for the digital village in Indonesia. Moreover, the novelty of this research is the survey results from various institutions and countries, including Indonesia. This is a research in progress paper in the early stages;The research is still ongoing now. Many institutions in numerous countries have been implementing the Open Data application, including Indonesian institutions. There are also various menus, data formats, and published data in the Open Data applications. The various menus are from basic to advance. We also have designed a Use Case and Activity diagrams of the Open Data Application for Alang-Alang village. Also, the Open data application for the village is still limited. This research has some implications, such as for theory, it extends the body of knowledge of Open Data, Digital Village, and Digital Government fields. In practice, this research supports the village government publishing public data, improving transparency, and enhancing public trust. Hopefully, it also helps citizens to get access to public data easily. © 2022 IEEE.

关键词： Open Data

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Development of Slotted Array Antenna Using SIW Structure for WLAN Communications 2

Development of Slotted Array Antenna Using SIW Structure for...

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2nd IEEE International Conference on Integrated Circuits and Communication Systems, ICICACS 2024

作者： Munir, Achmad Muhammad, Rivaldi Aulia Nurmantris, Dwi Andi Maulana, Muhammad Farhan Institut Teknologi Bandung Radio Telecommunication and Microwave Laboratory School of Electrical Engineering and Informatics Bandung Indonesia Uin Sunan Gunung Djati Bandung Faculty of Science and Technology Department of Electrical Engineering Bandung Indonesia Itb Radio Telecommunication and Microwave Laboratory School of Electrical Engineering and Informatics Bandung Indonesia Telkom University School of Applied Sciences Bandung Indonesia

ISBN: (纸本)9798350317558

The development of a slot array antenna based on Substrate Integrated waveguide (SIW) has been carried out. The antenna, consisting of 4 rectangular slots, is designed to operate at a frequency of 2.4 GHz. The design process includes SIW and slot array structure design, microstrip to SIW transition structure design, and microstripline structure design. The final design results were then fabricated on an FR4 Epoxy substrate with a substrate thickness of 1.6 mm for measurements. From the measurement results, it was found that the antenna resonates at a frequency of 2.385 GHz with a bandwidth of 1.67%. The measurement results, in general, also agree with the simulation results. The manufactured antenna is suitable for use in WLAN applications. © 2024 IEEE.

关键词： slotted array antenna substrate integrated waveguide (SIW) wavegudie Wireless Local Area Networks (WLAN) communications

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Numerical solution of the problem of turbulent currents that occur in the case of edge hardening 15

Numerical solution of the problem of turbulent currents that...

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15th International Conference on Electronics, Computers and Artificial Intelligence, ECAI 2023

作者： Codrean, Marius Novac, Mihaela Cornelia Codrean, Mihaela Gordan, Cornelia Emilia Novac, Ovidiu Constantin Bujdoso, Gyongyi Slovac, Francisc University of Oradea Department of Electrical Engineering Electrical Engineering and Information Technology Faculty Oradea Romania National Geothermal Research Center Technology Transfer Center NGRC-TTC University of Oradea Oradea Romania University of Oradea Department of Electronics and Telecommunications Electrical Engineering and Information Technology Faculty Oradea Romania University of Oradea Department of Computers and Information Technology Electrical Engineering and Information Technology Faculty Oradea Romania University of Debrecen Faculty of Informatics Department of Computer Science and Library and Information Science Debrecen Hungary

ISBN: (纸本)9798350321388

The aim of this work is to develop numerical procedures for analyzing edge hardening using induction heating by turbulent currents. The section through the steel bar, whose lower edge needs to be hardened, is presented. For the inductor adapted to the piece configuration, the 2D model is assumed. The surface treatment of the piece must be differentiated: in the tip area, the heating must be greater than in the rest of the surface. Only the tip area needs to be subjected to hardening, while the rest of the piece must remain elastic to ensure the desired mechanical strength. The main purpose of this work is to propose inductor models for achieving differentiated heating of the blade. © 2023 IEEE.

关键词： Induction heating

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A Comprehensive View on the Progress of Organoid Research with an Emphasis on its Relevance to Disease Characterization

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Biomedical and Environmental sciences 2023年第10期36卷 959-971页

作者： Chandra KISHORE Vaishali Ji Saurav Mallik Ayan MUKHERJI Namrata TOMAR Soumen Kumar Pati LI Ai Min Sinthia Roy BANERJEE Soumadip GHOSH Raza Ali NAQVI University of California Irvine Medical CenterOrangeCA 92868USA Department of Botany J.D.Women’s CollegeBailey RoadPatna-800023India Harvard T.H.Chan School of Public Health BostonMA 02115USA Department of Information Technology Haldia Institute of TechnologyHaldiaWest BengalIndia Medical College of Wisconsin MilwaukeeWI 53226USA Department of Bioinformatics Maulana Abul Kalam Azad University of TechnologyNadiaWest BengalIndia Center for Precision Health School of Biomedical InformaticsThe University of Texas Health Science Center at HoustonHoustonTX 77030USA School of Computer Science and Engineering Xi’an University of TechnologyXi'an 710048ShaanxiChina Department of Information Technology Guru Nanak Institute of TechnologyKolkataWest BengalIndia Department of Computer Science and Engineering Sister Nivedita UniversityKolkataWest BengalIndia Center for Precision Health School of Biomedical InformaticsUniversity of IllinoisChicago60612USA

INTRODUCTION Organoids are primary tissue or stem cells derived cell aggregates that have the capacity for self-organization,self-renewal,and the capacity to mimic cellular and tissue level *** can overcome the shortc... 详细信息

关键词： functions. overcome shortcomings

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SSANet: Side-by-Side Additive Network for Knee Osteoarthritis Severity Detection from X-Ray Images 4th

SSANet: Side-by-Side Additive Network for Knee Osteoarthrit...

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4th International Conference on Frontiers in Computing and Systems, COMSYS 2023

作者： Tewari, Rakhi Bhattacharjee, Debotosh Roy, Hiranmoy Krejcar, Ondrej Department of Computer Science and Engineering Jadavpur University Kolkata700032 India Department of Information Technology RCC Institute of Information Technology Canal South Road Beliaghata Kolkata700015 India Faculty of Informatics and Management Center for Basic and Applied Science University of Hradec Kralove Rokitanskeho 62 Hradec Kralove50003 Czech Republic

ISBN: (纸本)9789819726103

Knee Osteoarthritis (KOA) is becoming one of the most frequent degenerative and irreversible diseases in elderly people. Its early detection and diagnosis is also a difficult and time-intensive task. The recent advances in Machine Learning (ML) and Computer Vision (CV) created new paths to automatically detect KOA in the early stages. Detecting and grading the severity of KOA requires a dedicated ML model. This paper proposes a Side-by-Side Additive Network (SSANet)-based model for detecting and grading the severity of KOA. Since KOA affects the knee joint space by narrowing the gap between the joints, we preprocess the X-ray images to detect the Region of Interest (ROI) before the training of the model. From experimental results, it is evidenced that the ROI selection is really improving the detection accuracy of the model. Unlike sequentially connected convolution layer-based deep learning models, the proposed SSANet is based on a parallel convolution layer to reduce the degradation of feature quality. Again, to enhance the edge feature maps, we apply an additive layer that couples the previous layers’ convolutional output. SSANet captures both high-level and low-level features to predict the KOA severity effectively. The presence of a smaller number of layers and fewer numbers of learnable parameters than the existing popular deep learning models, make SSANet a time and space-efficient network. Moreover, the performance of the proposed SSANet in detecting KOA severity is significantly superior to that of other popular state-of-the-art networks. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Convolution

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Efficient Power Control for UAV Based on Trajectory and Game Theory

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Computers, Materials & Continua 2023年第3期74卷 5589-5606页

作者： Fadhil Mukhlif Ashraf Osman Ibrahim Norafida Ithnin Roobaea Alroobaea Majed Alsafyani Information Assurance and Security Research Group(IASRG) School of ComputingFaculty of EngineeringUniversiti Teknologi MalaysiaJohorMalaysia Faculty of Computing and Informatics University Malaysia SabahKota KinabaluMalaysia Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaifSaudi Arabia

Due to the fact that network space is becoming more limited,the implementation of ultra-dense networks(UDNs)has the potential to enhance not only network coverage but also network *** Aerial Vehicle(UAV)communications have recently garnered a lot of attention due to the fact that they are extremely versatile and may be applied to a wide variety of contexts and purposes.A cognitive UAV is proposed as a solution for the Internet of Things ground terminal’s wireless nodes in this *** the IoT system,the UAV is utilised not only to determine how the resources should be distributed but also to provide power to the wireless *** quality of service(QoS)offered by the cognitive node was interpreted as a price-based utility function,which was demonstrated in the form of a non-cooperative game theory in order to maximise customers’net utility *** energyefficient non-cooperative game theory power allocation with pricing strategy abbreviated as(EE-NGPAP)is implemented in this study with two trajectories Spiral and Sigmoidal in order to facilitate effective power management in Internet of Things(IoT)wireless *** has also been demonstrated,theoretically and by the use of simulations,that the Nash equilibrium does exist and that it is one of a *** proposed energy harvesting approach was shown,through simulations,to significantly reduce the typical amount of power thatwas *** is taken into consideration to agree with the objective of 5G *** order to converge to Nash Equilibrium(NE),the method that is advised only needs roughly 4 iterations,which makes it easier to utilise in the real world,where things aren’t always the same.

关键词： UAV spiral&sigmoid trajectory drones IoT game theory energy efficiency 6G

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Estimating the AGV load and a battery lifetime based on the current measurement and random forest application

Estimating the AGV load and a battery lifetime based on the ...

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2023 IEEE International Conference on Big Data, BigData 2023

作者： Hanzel, Krzysztof Grzechca, Damian Ziebinski, Adam Chruszczyk, Lukas Janus, Artur Silesian University of Technology Faculty of Automatic Control Electronics and Computer Science Department of Telecommunications and Teleinformatics Gliwice Poland Silesian University of Technology Faculty of Automatic Control Electronics and Computer Science Department of Electronics Electrical Engineering and Microelectronics Gliwice Poland Silesian University of Technology Faculty of Automatic Control Electronics and Computer Science Department of Distributed Systems and Informatics Devices Gliwice Poland Silesian University of Technology Student of Electrical EngineeringFaculty of Electrical Engineering Gliwice Poland

ISBN: (纸本)9798350324457

The paper describes the energy consumption from the battery based on the current measurements for various cases, i.e., speed (PWL adjustment) and loads. The main purpose of the research is to have additional and reliable information about power consumption and battery life estimation for autonomous guided vehicles (AGV). The authors propose a two-step algorithm. In the first step, a linear classifier was proposed. Then, the KNN classifier was tested;however, it did not give satisfactory results, so it was finally decided to use the random forest to estimate the load and PWL. The time domain current measurement is evaluated, and the beforementioned algorithms process the selected statistical measures. It has been proven that a two-step algorithm allows for achieving high accuracy. Based on the current observation, the paper is a good starting point for further investigation of the AGV because it is usually implemented in the AGV - so it does not require additional hardware. Moreover, it can lead to better energy management and increase battery lifetime. © 2023 IEEE.

关键词： AGV load estimation machine learning Prediction of energy consumption random forest

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Comfort Shoulder (Rhomboid Major) Muscles Chair Identifier System 6

Comfort Shoulder (Rhomboid Major) Muscles Chair Identifier S...

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6th International Conference on Communications, Information System and Computer engineering, CISCE 2024

作者： Moshayedi, Ata Jahangir Yu, Yuexin Savoji, Kimia Andani, Mehran Emadi School of Information Engineering Jiangxi University of Science and Technology Jiangxi Ganzhou China School of Computing Clemson University Biomedical Data Science and Informatics ClemsonSC United States University of Verona Department of Neurosciences Biomedicine and Movement Sciences Verona Italy

ISBN: (纸本)9798350353174

Nowadays, Sitting is one of the frequent activities of humans. particularly with the rise of office work, which is leading to an increase in the sitting periods for many individuals. Research highlights the importance of studying sitting posture to enhance seat quality, correct sitting methods, and prevent various health issues like neck and shoulder strains, etc. This article focuses on designing an IoT-based system that enables web-based data visualization without specialized software that can enable distance sampling. Through temperature sensors (DS18b20 and SHT11) and an FSR sensor, the system can identify distinct patterns in the main rhomboid muscles (the most important muscles of humans). The results show a significant relationship between individuals' body mass (BMI) and the observed muscle patterns, highlighting the importance of this correlation for researchers and industry designers alike. © 2024 IEEE.

关键词： Seats

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Improving DL-Learner on a Malware Detection Use Case 36

Improving DL-Learner on a Malware Detection Use Case

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36th International Workshop on Description Logics, DL 2023

作者： Bisták, Tomáš Švec, Peter Kluka, Ján Šimko, Alexander Balogh, Štefan Homola, Martin Department of Applied Informatics Faculty of Mathematics Physics and Informatics Comenius University Mlynská dolina Bratislava842 48 Slovakia Institute of Computer Science and Mathematics Faculty of Electrical Engineering and Information Technology Slovak University of Technology Ilkovicova 3 Bratislava812 19 Slovakia

Automation of malware characterization has become increasingly important for early malware detection over the past decades. Since it is crucial to be able to perform malware detection transparently, explainable machine-learning methods may be considered particularly suitable for this application. In our previous work, we thus employed algorithms for learning description-logics concept expressions to obtain structured characterizations of malicious software. The results of our initial experiments, however, lead us to several inconsistencies in the behaviour of the studied algorithms included in DL-Learner, a widely adopted framework for concept learning. Hence, in this work, we make a couple of corrections to DL-Learner, along with a few further enhancements, and repeat the experiments to empirically assess the effects of our changes. The outcomes show that the modified algorithms can mark an improvement in terms of the predictability of their behaviour as well as evaluation metrics. © 2023 CEUR-WS. All rights reserved.

关键词： Malware

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