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46th Annual International Conference of the IEEE engineering in Medicine and Biology Society, EMBC 2024

作者： Mousavi, Seyedeh Somayyeh Guo, Yuting Robichaux, Chad Sarker, Abeed Sameni, Reza Emory University Department of Biomedical Informatics Atlanta United States Georgia Institute of Technology Department of Biomedical Engineering Atlanta United States

ISBN: (纸本)9798350371499

Hypertension is a global health concern with an increasing prevalence, underscoring the need for effective monitoring and analysis of blood pressure (BP) *** analyzed a substantial BP dataset comprising 75,636,128 records from 2,054,462 unique patients collected between 2000 and 2022 at Emory Healthcare in Georgia, USA, representing a demographically diverse population. We examined and compared population-wide statistics of bivariate changes in systolic BP (SBP) and diastolic BP (DBP) across sex, age, and race/ethnicity. The analysis revealed that males have higher BP levels than females and exhibit a distinct BP profile with age. Notably, average SBP consistently rises with age, whereas average DBP peaks in the forties age group. Among the ethnic groups studied, Blacks have marginally higher BPs and a greater standard deviation. We also discovered a significant correlation between SBP and DBP at the population level, a phenomenon not previously *** results highlight the importance of demography-specific BP analysis for clinical diagnosis and provide valuable insights for developing personalized, demography-specific healthcare interventions. © 2024 IEEE.

关键词： Blood pressure

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Possibilities of Migration of GSM-R System to FRMCS in Polish Conditions 28

Possibilities of Migration of GSM-R System to FRMCS in Polis...

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28th International Scientific Conference on Transport Means 2024

作者： Chrzan, M. Pniewski, R. Kornaszewski, M. Kazimierz Pulaski University of Technology and Humanities in Radom Faculty of Transport Electrical Engineering and Informatics Malczewskiego 29 Radom26-600 Poland

In the article, the authors will present a transmission model based on fifth-generation radio communication technology, which is the basis for the creation of FRMCS (Future Railway Mobile Communication System) for railroad radio communication in Poland. The article indicates the areas of use of 5G technology in terms of the possibility of increasing the safety of rail transport, presents the built transmission model based on MATLAB software where signal fluctuations and fading were studied, the system interference analysis from the LTE system was carried out using various methods, signal modeling was carried out for different areas of train movement. © 2024 Kaunas University of technology. All rights reserved.

关键词： MATLAB

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DIGITAL TWIN DRIVEN ASSEMBLY LINE RE-BALANCING AND DECISION SUPPORT 38

DIGITAL TWIN DRIVEN ASSEMBLY LINE RE-BALANCING AND DECISION ...

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38th ECMS International Conference on Modelling and Simulation, ECMS 2024

作者： Lugaresi, Giovanni Laszlo, Kovacs Tamas, Kornel Department of Mechanical Engineering KU Leuven Leuven Belgium Department of Automation and Applied Informatics Budapest University of Technology and Economics Budapest Hungary

ISBN: (纸本)9783937436845

Recent investments in industrial digitization together with the concrete need for short-term planning capabilities mean digital twins can effectively aid enterprises in the management of their production systems and value chains. This paper introduces a conceptual framework for assembly line re-balancing in the context of Industry 5.0, focusing on manual assembly processes. The framework aims to leverage a digital twin for obtaining a synchronized representation of the current task allocations in the assembly line, and uses data-driven scenario generation methods for investigating alternative balancing solutions that are proposed to operators in real time. A proof-of-concept platform is implemented in a laboratory environment, utilizing an assembly line with industrial components. Preliminary results demonstrate the compatibility of the proposed components within the digital twin framework. The potential applicability to various manual assembly scenarios is discussed, along with considerations for incorporating additional constraints in the evaluation process. ©ECMS Daniel Grzonka, Natalia Rylko, Grazyna Suchacka, Vladimir Mityushev (Editors) 2024.

关键词： Production control

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Comparative Evaluation of Resampling Techniques on Machine Learning for Predicting Customer Purchasing Behavior 8

Comparative Evaluation of Resampling Techniques on Machine L...

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8th International Conference on Information technology, InCIT 2024

作者： Diwandari, Saucha Permanasari, Adhistya Erna Hidayah, Indriana Universitas Gadjah Mada Department of Electrical and Information Engineering Indonesia Universitas Teknologi Yogyakarta Faculty of Science and Technology Informatics Department Indonesia

ISBN: (纸本)9798350366303

In the era of subscription-based services, customer purchasing behavior presents a significant challenge for organizations because customer retention is essential to long-term success. Imbalanced datasets, where the majority class significantly outweighs the minority class, often cause models to favor the dominant class, leading to biased predictions. This study investigates customer purchasing behavior, focusing specifically on the issue of class imbalance. It offers a comparative analysis of various classification techniques and includes widely used resampling methods such as the Synthetic Minority Over-sampling Technique (SMOTE), Edited Nearest Neighbors, Tomek Links, and several hybrid sampling approaches. Our research findings demonstrate the competitive effectiveness of using the Random Forest algorithm with undersampling methods such as TomekLinks and Edited Nearest Neighbors (ENN), which have shown the highest F1 scores. However, the hybridization of oversampling and undersampling yields unsatisfactory results, below our expectations. This suggests that the dataset used in this study exhibits a high degree of overlap between the two classes. Consequently, undersampling proves to be an effective method for mitigating the negative impact of class overlap. This research makes a substantial contribution to the field of predicting customer purchasing behavior. © 2024 IEEE.

关键词： Adversarial machine learning

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Enhancing Smart Mobility Through Machine Learning and Neural Networks 7

Enhancing Smart Mobility Through Machine Learning and Neural...

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7th Edition Global Conference on Wireless and Optical Technologies, GCWOT 2024

作者： Nadeem, Muhammad Haider, Waleej Ahmed, Haris Khan, Sallar Sir Syed University of Engineering & Technology Department of Computer Science & Information Technology Karachi Pakistan School of Informatics & Cybersecurity Technological University Dublin Dublin Ireland

ISBN: (纸本)9798331534271

This study investigates the prediction of taxi trip durations in New York City using machine learning (ML) models and neural networks (NN). Three models Linear Regression, Random Forest Regressor, and a Neural Network were developed and evaluated on a dataset containing various trip details. The analysis highlighted the importance of geographic and temporal features in predicting trip durations. The Neural Network model outperformed others, achieving a mean squared error (MSE) of 12,577,211 and a root mean squared error (RMSE) of 3,546, significantly better than the comparative models. These results underscore its capacity to capture complex urban mobility patterns effectively. The superior performance of the Neural Network supports its potential to optimize traffic flow and reduce congestion in dense urban environments, offering substantial improvements to urban transportation systems. © 2024 IEEE.

关键词： Neural network models

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Advancing Color Perception: An IoT-driven Pedagogical System for Visually Impaired Children 1

Advancing Color Perception: An IoT-driven Pedagogical System...

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1st IEEE International Conference on Advances in Signal Processing, Power, Communication, and Computing, ASPCC 2024

作者： Balage, Prasandika Jayawardene, Nuwan University of Westminster School of Computer Science and Engineering London United Kingdom Informatics Institute of Technology Department of Computing Colombo Sri Lanka

ISBN: (纸本)9798350355093

Visual impairment is characterized by the loss of vision, encompassing both complete blindness and partial vision loss. Studies reveal a notable prevalence of visual impairment among school-aged children. The significance of colors in acquiring and discerning visual information is crucial, aiding children in effectively perceiving and comprehending their surroundings. This study presents an Internet of Things (IoT) system designed for teaching colors to visually impaired children. The system achieved an accuracy rate surpassing 77.8%, and it is operated effectively regardless of surrounding lighting conditions. Given that the target users of the system are visually impaired children, this research was conducted in close alignment with Human-Computer Interaction (HCI) principles. © 2024 IEEE.

关键词： Color vision

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Concierge: Towards Accuracy-Driven Bandwidth Allocation for Video Analytics Applications in Edge Network 8

Concierge: Towards Accuracy-Driven Bandwidth Allocation for ...

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8th IEEE International Conference on Edge Computing and Communications, EDGE 2024

作者： Huang, Yuyang Zharfan, Faishal Hendrawan, Hendrawan Gunawi, Haryadi S. Jiang, Junchen University of Chicago Department of Computer Science Chicago United States Bandung Institute of Technology School of Electrical Engineering and Informatics Bandung Indonesia

ISBN: (纸本)9798350368499

When performing inference on sensor data, edge video analytics applications may not always need high-fidelity data, since important information may not appear all the time. Consequently, each edge AI application's bandwidth demand is highly dynamic. Thus, a shared edge system should dynamically allocate more bandwidth to the applications in need to reach high accuracy at each moment. However, previous bandwidth allocators are ill-suited because they are agnostic to the timevarying impact of bandwidth on each application's *** short paper explores a new accuracy-driven approach to bandwidth allocation, which periodically re-allocates bandwidth across edge AI applications based on the sensitivity of each application's accuracy to its bandwidth share. To examine its practical benefit and technical challenges, we present a concrete accuracy-driven bandwidth allocator called ConciERGE, which exposes a simple yet efficient interface to estimate each application's sensitivity to a small change in its bandwidth *** run CONCIERGE on state-of-the-art video-analytics applications with real video streams and show its early promise in greatly improving the inference accuracy of video analytics. © 2024 IEEE.

关键词： Bandwidth

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Intensive Interrupted Sampling Repeater Jamming Detection Based on Transformer-CFAR Fusion Detection Model

IEEE Transactions on Radar Systems

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IEEE Transactions on Radar Systems 2024年 2卷 936-949页

作者： Zhang, Haonan Wei, Shaopeng Wei, Song Zhang, Lei Ren, Peng Zhou, Yejian College of Oceanography and Space Informatics Qingdao266580 China Sun Yat-sen University School of Electronics and Communication Engineering Guangzhou510275 China Zhejiang University of Technology College of Information Engineering Hangzhou310023 China

Interrupted sampling repeater jamming (ISRJ) is an effective way to suppress normal radar probing in modern electronic warfare, and ISRJ suppression is essential in the radar signal processing stage. Accurately locating the position of the jamming signal is the first step to suppress the jamming signal. However, the traditional constant false alarm rate (CFAR) has performance loss with the characteristics of intensive distribution, extensive dynamic power range, and nonperiodical transmitting. This article proposes an ISRJ detection method based on a fusion Transformer and CFAR. First, the feature extraction model based on the Transformer is built to extract the continuous distribution features of ISRJ, forming rough detection results. Then, a CFAR detector is derived based on the rough detection result to estimate detector parameters. Third, the jamming features obtained by the Transformer, CFAR detector, and other features (such as instantaneous power and average power) are fused by a decision tree to realize robust detection in a low jamming-to-signal noise ratio (JSNR). Finally, we conducted simulated experiments to verify the effectiveness of the proposed method. ©2024 IEEE.

关键词： Signal to noise ratio

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3D Semantic Mapping based on RGB-D Camera and LiDAR Sensor in Beach Environment 1

3D Semantic Mapping based on RGB-D Camera and LiDAR Sensor i...

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1st International Conference on Robotics, engineering, Science, and technology, RESTCON 2024

作者： Tan, Chi Jie Ogawa, Shintaro Hayashi, Takamasa Janthori, Titan Tominaga, Ayumu Hayashi, Eiji Kyushu Institute of Technology Department of Creative Informatics Fukuoka Japan National Institute of Technology Kitakyushu College Department of Creative Engineering Robotics and Mechatronics Kitakyushu Japan

ISBN: (纸本)9798350348842

The increasing amount of sea garbage proving to be a huge problem not only for marine life but also causing a tremendous number of troubles to humans living along the coastlines. Especially Japan, that is surrounded by the ocean which has a long coastline that spans thousands of kilometers, and this provides ample opportunities for marine debris to accumulate. This paper proposes a 3D mapping system utilizing the semantic information from the RGBD sensor extracted from a specifically trained state-of-Art deep learning neural network to merge with the spatial information from the LiDAR sensor using Max Fusion Technique. This paper also aims to contribute to the implementation of deep learning and autonomous driving in beach cleaning-related robots and spark interest and raise awareness of the public in beach clean-up activities. It is also shown that the proposed system can achieve a mean accuracy of 98% approximately with the uniquely trained deep learning model. © 2024 IEEE.

关键词： Autonomous vehicles

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Atomic Lifecycle for Cyber Threat Intelligence 17

Atomic Lifecycle for Cyber Threat Intelligence

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17th International Conference on Information Security and Cryptology, ISCTurkiye 2024

作者： Arikan, Suleyman Muhammed Kocak, Aynur Alkan, Mustafa Computer Forensics Institute of Informatics Gazi University Ankara Turkey Electrical and Electronics Engineering Faculty of Technology Gazi University Ankara Turkey

ISBN: (纸本)9798331533649

The utilisation of cyber threat intelligence provides a multitude of advantages in the assurance of security. A growing body of research is being published on the subject of cyber threat intelligence. However, the precise sequence of steps involved in the cyber threat intelligence life cycle remains unclear. The life cycle presented in each study is not consistent. Moreover, the transition from data to intelligence throughout the life cycle is not sufficiently delineated. The intelligence produced in many studies can be of different types. In our study, all existing lifecycles were examined and their naming approaches were analysed. The objective was to present a cyber threat intelligence life cycle that is as atomic as possible, with each step clearly expressed. This should facilitate a more rigorous comparison of studies in the existing literature on cyber threat intelligence. Furthermore, the life cycle can be utilised in new cyber threat intelligence studies. Researchers who aspire to implement best practices in their study are able to run more effective processes by following the life cycle. © 2024 IEEE.

关键词： Phishing

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