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9th International Conference on Intelligent Informatics and BioMedical sciences, ICIIBMS 2024

作者： Nagashima, Masaharu Kim, Hyun-Woo Cho, Myungjin Lee, Min-Chul Kyushu Institute of Technology Graduate School of Computer Science and Systems Engineering Iizuka city Japan Iitc Hankyong National University School of Ict Robotics and Mechanical Engineering Anseong-si Korea Republic of

ISBN: (纸本)9798350363043

Digital Holographic Microscopy (DHM) can obtain three-dimensional (3D) information about the fine structure of an object by utilizing the phase information of coherent light. In DHM, during the process of reconstructing the shape of an object, phase information is extracted by windowing the sideband containing the phase information. The 3D information of the object is then obtained from the acquired phase information. When windowing the sideband in a narrow range, it can remove noise caused by the DC spectrum, but detailed shape information of the object is lost. On the other hand, when windowing in a wide range, detailed shape information of the object can be obtained, but noise from the DC spectrum increases. To solve this trade-off relationship, we propose a method of determining the range for windowing the sideband using a function and then averaging the windowed sidebands. This proposed method can reduce the impact of noise from the DC spectrum and enables the acquisition of the detailed shape information. In this paper, we explain the reconstruction algorithm of this method and compare it with conventional methods and the previous study, phase differences averaging (PDA). © 2024 IEEE.

关键词： Noise abatement

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Pain Classification Using Statistical Feature Extraction Using Machine Learning Approach: A Pilot Study 13

Pain Classification Using Statistical Feature Extraction Usi...

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13th IEEE International Conference on Control System, Computing and engineering, ICCSCE 2023

作者： Sudimanto Trisetyarso, Agung Kartowisastro, Iman Herwidiana Budiharto, Widodo Bina Nusantara University Binus Graduate Program Computer Science Computer Science Department Jakarta11480 Indonesia Bina Nusantara University School of Computer Science Mathematics Department Jakarta11480 Indonesia Bina Nusantara University Computer Science Department Binus Graduate Program Computer Science Computer Engineering Department Jakarta11480 Indonesia Bina Nusantara University School of Computer Science Computer Science Department Jl. K. H. Syahdan No. 9 Kemanggisan Palmerah Jakarta11480 Indonesia

ISBN: (纸本)9798350323184

Electrodermal activity (EDA) is a general term for all electrical phenomena occurring on the skin, both passive and active. EDA measurements are used by researchers to measure levels of stress, emotion, mental strain, and so on. Measuring human stress levels, emotions, and mental strain are generally associated with the skin conductance response. The function GSR sensor is not only used to read people's psychology but also can be used as a pain sensor used to read the degree of pain in the skin. This pilot study uses sample data from ***. The *** data is galvanic skin response sensor data. The output of this sensor is the conductivity value that occurs in the skin. The data obtained from *** will be extracted using the mean, standard deviation, maximum, minimum, RMS, skewness, and peak-to-peak characteristics. The extracted functions are selected using the forward selection method. The results of the feature selection are three features with an accuracy percentage greater than 50%, namely the mean feature, the RMS feature, and the skewness feature. The machine learning models used are bagged tree, SVM, and K-NN models. Of the three models used, the bagged tree model has the highest accuracy rate, at 98.05%, with an F1 score is 0.9807. The KNN model with k=10 has the lowest level of accuracy compared to other models, at 96.75%. © 2023 IEEE.

关键词： Extraction

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Relationship Between Mechanical Deformation and Contact Force Applied by Catheter Tip on Cardiac Muscle: Experimentation and computer Modeling 5

Relationship Between Mechanical Deformation and Contact Forc...

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5th IEEE Eurasia Conference on Biomedical engineering, Healthcare and Sustainability, ECBIOS 2023

作者： Ijima, Yukako Masnok, Kriengsak Perez, Juan J. Gonzalez-Suarez, Ana Berjano, Enrique Watanabe, Nobuo Master's Program Global Course of Engineering and Science Graduate School of Engineering and Science Shibaura Institute of Technology Saitama Japan Functional Control Systems Graduate School of Engineering and Science Shibaura Institute of Technology Biofluid Science and Engineering Laboratory Saitama Japan Universitat Politecnica de Valencia BioMIT Department of Electronic Engineering Valencia Spain School of Engineering University of Galway Translational Medical Device Lab Galway Ireland Functional Control Systems Graduate School of Engineering and Science College of Systems Engineering and Science Shibaura Institute of Technology Biofluid Science and Engineering Laboratory Department of Bio-Science and Engineering Saitama Japan

ISBN: (纸本)9798350320978

The cardiac muscle is elastic and deformable. Pushing a catheter in contact with the cardiac muscle surface to conduct focal energy-based ablative therapies, such as RF ablation, requires an adequate electrode-tissue contact surface to transfer the energy to the target site. In this regard, the relationship between the contact force (CF) and the resulting mechanical response is still unclear, in particular, the insertion depth (ID) and the diameter of the surface deformation. The objective of this study was to quantify these relationships using an ex vivo model and a computational model. A rigid bar with a 2.3 mm diameter blunt tip (mimicking a 7Fr standard ablation catheter) was placed at a perpendicular orientation on a fragment of the porcine heart. CF values ranged from 10 to 80g. We used ANSYS to build a Mooney-Rivlig model of 3 parameters based on hyperelastic material and to simulate the same conditions as in the experiments. The experimental results showed a strong linear correlation between CF and insertion depth ID ($\mathrm{R}^{2}=0.97, \mathrm{P} © 2023 IEEE.

关键词： Catheters

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AI-Powered Precision: Revolutionizing Skin Cancer Detection with Advanced Machine Learning 6

AI-Powered Precision: Revolutionizing Skin Cancer Detection ...

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6th IEEE Novel Intelligent and Leading Emerging sciences Conference, NILES 2024

作者： Abd-Elaziz, Mariam M. Elshafie, Basma M. Abdullah, Hagar Gerges, Karen Y. Ghanem, Ingy A. Fouad, Khaled M. El-Ghamry, Amir Moawad, Ibrahim F. El-Metwally, Sara New Mansoura University Faculty of Computer Science and Engineering Dakahlia Egypt Mansoura University New Mansoura University Faculty of Engineering Computer and Communication Program Faculty of Computer Science and Engineering Egypt Benha University Information Systems Faculty of Computers and Artificial Intelligence Egypt Mansoura University New Mansoura University Faculty of Computer and Information Sciences Faculty of Computer Science and Engineering Egypt School of Engineering and Computer Science University of Hertfordshire Gaf Egypt Ain Shams University Faculty of Computer and Information Sciences Cairo Egypt College of Computer Science and Engineering Taibah University Department of Artificial Intelligence Medina42353 Saudi Arabia

ISBN: (纸本)9798350378511

Skin cancer's increasing incidence rates necessitate advanced diagnostic tools. This research uses MobileNet architecture to develop an enhanced system for skin cancer detection. MobileNet's efficient CNN architecture, combined with Keras for model lifecycle management and TensorFlow for real-time inference, forms the foundation of this study. Using 10,015 dermatoscopic pictures from seven different classifications of skin cancer in the HAM10000 dataset, the methodology includes several key stages: image preprocessing to correct illumination and adjust resolution, data augmentation to balance the dataset, and model training using Transfer Learning. The MobileNet model was trained over 50 epochs with a comprehensive architecture incorporating multiple specialized layers. By combining large-scale data analysis and adaptive learning, this methodology demonstrates The revolutionary possibilities of AI and ML in improving skin cancer diagnostics and public health outcomes. Keywords Skin Cancer Detection, Dermatoscopic Images, Machine Learning, Deep Learning © 2024 IEEE.

关键词： Adversarial machine learning

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Mapping the Landscape of Social Learning: Integrating Key Success Factors, Challenges, and Digital Platforms 9

Mapping the Landscape of Social Learning: Integrating Key Su...

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9th International Conference on Information Management and Technology, ICIMTech 2024

作者： Marcel Meyliana Warnars, Harco Leslie Hendric Spits Mursitama, Tirta Nugraha BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia School of Information Systems Bina Nusantara University Information Systems Department Jakarta11480 Indonesia BINUS Business School Doctor of Research in Management Bina Nusantara University Management Department Jakarta11480 Indonesia

ISBN: (纸本)9798350390025

This research develops a conceptual model to understand the influence of digitalization on social learning, especially in the context of community empowerment. This model maps the relationship between factors that influence success, challenges faced, and variations in the use of digital platforms in social learning. By using a literature study approach, the research results show that effective communication, collaboration and empowerment are the main keys to the success of social learning in society. Key challenges identified include limited access to information, resource constraints, and digital literacy barriers, all of which require specific strategies to overcome. By examining the relationship between success factors, challenges, and use of digital platforms, this research provides new insights that support the development of more effective strategies for using digital technology to support social learning that leads to community empowerment. This research has great potential to increase people's access to learning opportunities and information, allowing them to be more active in the social learning process. © 2024 IEEE.

关键词： Federated learning

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ICT-Based Conceptual Model for Local Culture Communities using Soft System Methodology 7

ICT-Based Conceptual Model for Local Culture Communities usi...

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7th International Conference on Information Management and Technology, ICIMTech 2022

作者： Nindito, Hendro Prabowo, Harjanto Sfenrianto Hendric, Spits Warnars Harco Leslie BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia BINUS Graduate Program - Master of Information Systems Management Bina Nusantara University Information Systems Management Department Jakarta11480 Indonesia

ISBN: (数字)9781665450904

ISBN: (纸本)9781665450904

The problems that exist in the field of art and culture preservation experienced by the arts and culture community side are the limitations on physical facilities for disseminating works, exchanging information between arts and culture communities, as well as the need to increase professionalism so that they can be independent in order to help improve the economy, where the role of regulation in this regard also affects this condition. Based on the facts above, this community requires an interaction model that is integrated with the use of information technology. This study uses a Soft System Methodology approach to create a model that is suitable for the arts and cultural community. The result is an ICI-based conceptual model for a local culture community. (Abstract) © 2022 IEEE.

关键词： Information use

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The Adoption of Artificial Intelligence Technology in Parking Security System 7th

The Adoption of Artificial Intelligence Technology in Parkin...

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7th International Conference on Inventive systems and Control, ICISC 2023

作者： Alhafizh, Muhammad Rifqi Adriawan, Albertus Baskara Yunandito Fernaldy, Darryl Gaol, Ford Lumban Matsuo, Tokuro Information Systems Department School of Information Systems Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program—Doctor of Computer Science Bina Nusantara University Jakarta11480 Indonesia Advanced Institute of Industrial Technology Tokyo Japan

ISBN: (纸本)9789819916238

Artificial intelligence (AI) refers to human-like intelligence exhibited by computers, robots, or other machines. In popular use, artificial intelligence refers to the ability of a computer or machine to mimic the ability of the human mind to learn from examples and experiences, recognize objects, understand and respond to language, make decisions, solve problems, and combine these and other abilities to perform functions that humans might perform. Artificial intelligence requires experience and data to smarten up the technology. The most important things in making artificial intelligence are learning, reasoning, and self-correction. At the learning stage, AI gives machines the ability to learn tasks without requiring a defined programming language. Then, the reasoning stage is the stage where the reason AI is applied in a technology. The self-correction stage is the stage where the AI is refining itself from and learning from experience in order to minimize errors or problems that exist. Then, this matter is concerned with the parking lot to be discussed. Parking can be interpreted as public facilities available in agencies or offices that serve to store vehicles. Vehicles entering the parking area become tens or even thousands, because it requires a parking system and management area. Such arrangements are capable of parking procedures and even other support systems such as adequate parking facilities and infrastructure, and another function is to create and develop parking systems in general to provide safety and comfort. The methodology obtained from this problem is checking the research model to check and find out the comparison of vehicle user’s Parking System Security between cars or motorcycles, as well as the usual parking lots visited. Then, we created a questionnaire. This study used questionnaires with the aim to get respondents’ results about the Parking Security System. Our sampling method is based on respondents aged 17–20 years. Questionnaires are su

关键词： Security systems

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Incremental Learning with Pseudo Labels for Enhanced Glomeruli Segmentation Using SAM

Incremental Learning with Pseudo Labels for Enhanced Glomeru...

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2024 IEEE International Conference on E-Health Networking, Application and Services, HealthCom 2024

作者： Liu, Xinkai Peng, Boyuan Zhu, Xin Iwasaki, Tsuyoshi Sato, Atsuya Kazama, Junichiro James Huang, Jie Graduate Department of Computer Science and Engineering The University of Aizu Fukushima Aizu-Wakamatsu Japan Department of AI Technology Development M&D Data Science Center Institute of Science Tokyo Tokyo Japan Department of Nephrology and Hypertension Fukushima Medical University Fukushima Japan Graduate Department of Computer Science and Engineering Division of Information Systems The University of Aizu Fukushima Aizu-Wakamatsu Japan

ISBN: (纸本)9798350350548

The advent of the Segment Anything Model (SAM) marks a significant milestone in deep learning semantic segmentation tasks. In this study, an incremental learning model based on pseudo labels is proposed. The model generates bounding box prompts for SAM, enhancing the accuracy of glomeruli segmentation in renal pathology images. The model uses DenseNet-121 along with contrastive learning to enable self-supervised pre-training using mouse glomeruli images. Transfer learning is then conducted using labeled human renal pathology images to develop a binary classification model for glomeruli. Unlabeled images of human renal pathology are subsequently introduced for incremental learning. Class activation maps (CAMs) generated by the incremental learning model are post-processed to extract bounding rectangles for connected regions. These rectangles are then used as prompts for SAM segmentation. The proposed approach resulted in an average Dice similarity coefficient (DSC) of 0.825 in the glomeruli segmentation task. This result demonstrates the effectiveness of the incremental learning model and post-processing algorithms in improving SAM’s segmentation accuracy for renal pathology. © 2024 IEEE.

关键词： Contrastive Learning

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Investing in Products with the Greatest Demand on Online Stores During the Pandemic 7th

Investing in Products with the Greatest Demand on Online Sto...

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7th International Conference on Inventive systems and Control, ICISC 2023

作者： Hassya, Titan Hanif, Muhammad Fauzi Alvian Gaol, Ford Lumban Matsuo, Tokuro Information Systems Department School of Information Systems Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program—Doctor of Computer Science Bina Nusantara University Jakarta11480 Indonesia Advanced Institute of Industrial Technology Tokyo Japan

ISBN: (纸本)9789819916238

From the year 2019, every aspect of our lives has been negatively impacted as a result of the spread of a deadly disease known as COVID-19, particularly the health and business domains. The primary goal of this study is to develop a solution, or at the very least an overall analysis, to the readers on how to overcome the economic crisis during pandemic. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： COVID-19

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A Low Cost Triple-Node-Upset Self-Recoverable Latch Design for Nanoscale CMOS

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IEEE Transactions on Device and Materials Reliability 2025年第2期25卷 296-307页

作者： Bai, Na Zhang, Pengshuai Xu, Yaohua Guo, Yunhui Li, Hang Wang, Yi Wen, Xiaoqing Anhui University Information Materials and Intelligent Sensing Laboratory of Anhui Province Anhui Hefei230601 China National University of Defense Technology College of Computers Hunan Changsha410073 China Kyushu Institute of Technology Graduate School of Computer Science and Systems Engineering Fukuoka8208502 Japan

Due to the constant reduction of semiconductor feature sizes, the charge sharing effect is getting worse. The occurrence probability of triple-node upset (TNU), which has a significant impact on the circuit’s reliability, is rising in nanoscale digital circuits. This paper proposes a low overhead and TNU self-recovery latch (TNU-SR) based on the 28 nm CMOS technology to efficiently tolerate TNU and reduce the power dissipation and latency of the latch. The latch design proposed in this article adopts stacked transistors to reduce sensitive nodes and area overhead. The TNU-SR latch uses clock gating and high-speed transfer path technology, resulting in low power dissipation and low delay. For simulation results, compared with existing latches, it can be known that the TNU-SR latch performs well in terms of delay, power consumption, and area, so it is a good choice for radiation-hardened design for space applications. In addition, compared with the latest TNU self-recovery latch (HLTNURL), the TNU-SR latch proposed in this paper reduces the Power-Area-Delay Product (PADP) metric by 111.13%. © 2001-2011 IEEE.

关键词： CMOS integrated circuits

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