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IEEE Internatonal Conference on Mobile Adhoc and Sensor systems (MASS)

作者： Anis Elgabli Mohammed S. Elbamby Cristina Perfecto Mounssif Krouka Mehdi Bennis Vaneet Aggarwal *Department of Industrial and Systems Engineering Interdisciplinary Research Center for Communication Systems and Sensing (IRC-CSS) Interdisciplinary Research Center for Intelligent Secure Systems (IRC-ISS) King Fahd University of Petroleum and Minerals (KFUPM) Dhahran Saudi Arabia Telefónica Research Spain Bilbao School of Engineering University of the Basque Country (UPV/EHU) Spain Centre for Wireless Communications University of Oulu Finland School of Industrial Engineering Purdue University USA

ISBN: (数字)9798350363999

ISBN: (纸本)9798350364002

Wirelessly streaming high quality 360 degree videos is still a challenging problem. When there are many users watching different 360 degree videos and competing for the computing and communication resources, the streaming algorithm at hand should maximize the average quality of experience (QoE) while guaranteeing a minimum rate for each user. In this paper, we propose a cross layer optimization approach that maximizes the available rate to each user and efficiently uses it to maximize users' QoE. Particularly, we consider a tile based 360 degree video streaming, and we optimize a QoE metric that balances the tradeoff between maximizing each user's QoE and ensuring fairness among users. We show that the problem can be decoupled into two interrelated subproblems: (i) a physical layer subproblem whose objective is to find the download rate for each user, and (ii) an application layer subproblem whose objective is to use that rate to find a quality decision per tile such that the user's QoE is maximized. We prove that the physical layer subproblem can be solved optimally with low complexity and an actor-critic deep reinforcement learning (DRL) is proposed to leverage the parallel training of multiple independent agents and solve the application layer subproblem. Extensive experiments reveal the robustness of our scheme and demonstrate its significant performance improvement compared to several baseline algorithms.

关键词： Wireless communication Measurement Cross layer design Streaming media Physical layer Ad hoc networks Robustness Quality of experience Optimization Videos

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An ultra thin,bright,and sensitive interactive tactile display based on organic mechanoluminescence for dual-mode handwriting identification

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InfoMat 2024年第6期6卷 76-87页

作者： Tingting Hou Wenlang Li Haoyu Wang Yuantian Zheng Chaojie Chen Haoran Zhang Kai Chen Huilin Xie Xin Li Shaoshuai He Siwei Zhang Dengfeng Peng Cheng Yang Jacky W.Y.Lam Ben Zhong Tang Yunlong Zi Department of Mechanical and Automation Engineering The Chinese University of Hong KongHong Kongthe People's Republic of China Department of Chemistry Hong Kong Branch of Chinese National Engineering Research Center for Tissue Restoration and Reconstruction and Institute for Advanced StudyThe Hong Kong University of Science and TechnologyHong Kongthe People's Republic of China Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong Province College of Physics and Optoelectronic EngineeringShenzhen UniversityShenzhenthe People's Republic of China Thrust of Sustainable Energy and Environment The Hong Kong University of Science and Technology(Guangzhou)Guangzhouthe People's Republic of China The Hong Kong University of Science and Technology Interdisciplinary Program Office Hong Kong SARthe People's Republic of China Institute of Materials Research Tsinghua Shenzhen International Graduate SchoolTsinghua UniversityShenzhenthe People's Republic of China School of Science and Engineering Shenzhen Institute of Aggregate Science and TechnologyThe Chinese University of Hong KongShenzhenthe People's Republic of China HKUST Shenzhen-Hong Kong Collaborative Innovation Research Institute Shenzhenthe People's Republic of China Guangzhou HKUST Fok Ying Tung Research Institute Guangzhouthe People's Republic of China

Visible light-based human–machine interactive media is capable of transmitting electrical readouts to machines and providing intuitive feedback to users ***,many inorganic mechanoluminescent(ML)materials-based interactive media,typically ZnS-loaded phosphors(ZLPs),have been successfully ***,organic ML materials-based solutions were rarely exploited despite their huge merits of strong structural modification,abundant luminescence property,low cost,easy preparation,and so ***,we propose a novel interactive tactile display(ITD)based on organic ML materials(Cz-A6-dye)and triboelectric nanogenerator,with ultra-brightness(130%enhancement)and ultra-low threshold pressure(57%reduction)as compared to *** proposed ITD achieves the conversion of weak mechanical stimuli into visible light and electrical signals simultaneously,without extra power ***,the relationship between the luminous performance of organic ML materials and mechanical force is quantified,benefiting from the uniform ML layer *** by convolutional neural networks,the high-accuracy recognition(97.1%)for handwriting and identity of users is realized at the same ***,the ITD has great potential for intelligent wearable electronics and classified military applications.

关键词： interactive media organic mechanoluminescence triboelectric nanogenerators

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Development of Automatic Recognition and Gripping System of Beekeeping Auxiliary Device Using Stereo Camera and Object Detection Algorithm

Development of Automatic Recognition and Gripping System of ...

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2022 ASABE Annual International Meeting

作者： Wang, Pingan Wiku, Kuswidiyanto Lukas Saiful, Hanif Adhitya Mo, Changyeon Kim, Subae Han, Xiongzhe Department of Biosystems Engineering Kangwon National University Korea Republic of Interdisciplinary Program in Smart Agriculture Kangwon National University Korea Republic of Apiculture Division National Institute of Agricultural Sciences Korea Republic of

Apiculture has been thriving and improving as a part of the agricultural industry. Many advanced tools have been invented to support beekeeping management processes. However, hive handling has always been the most challenging problem for apiarists in daily beekeeping processes. This paper aims to solve the daily beekeeping bee box transport problem by developing an automatic recognition and gripping device based on a stereo camera ranging method and object detection algorithm. Firstly, a hive recognition model was established based on the YOLOv5s detection model. The three-dimensional location of the hive was able to be determined in real-time inference by using the oak-D Lite Stereo Camera. The position information required for the grasping action was provided to the uArm manipulator through simple relation transformation calculation. In this way, the uArm was controlled to operate self-recognition and automatic clamping of the bee box. The cost-effective stereo camera module and lightweight object detection model used in this paper will significantly promote the automation and practical application of apiculture auxiliary devices. © 2022 ASABE. All Rights Reserved.

关键词： Object detection

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A Conjoint-based Approach on Determining the Factors Affecting on Preference of Subscribing a Netflix Plan

A Conjoint-based Approach on Determining the Factors Affecti...

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IEEE International Conference on Industrial engineering and engineering Management

作者： Ji Yong Park Yogi Tri Prasetyo Maela Madel L. Cahigas Reny Nadlifatin School of Industrial Engineering and Engineering Management Mapúa University Manila Philippines International Bachelor Program in Engineering Yuan Ze University Taoyuan Taiwan Department of Industrial Engineering and Management Yuan Ze University Taoyuan Taiwan Department of Information Systems Institut Teknologi Sepuluh Nopember Surabaya Indonesia

ISBN: (数字)9798350386097

ISBN: (纸本)9798350386103

This study uses a conjoint analysis approach to determine the key factors influencing subscriber preferences for subscribing to Netflix plan. In a rapidly evolving industry, understanding the drivers of subscription choices is critical for market success. Through a designed survey, respondents are presented with different hypothetical Netflix subscription plans characterized by attributes such as price, resolution, same time watch device, downloadable device and device specs. By analyzing respondents’ answers from these attributes, researchers aim to find out the relatedness of each attribute and levels with the subscription preference. The study’s findings can help Netflix make more strategic decisions about plan options and pricing policies, so that it can better serve the wide range of demands and tastes of customers in the cutthroat streaming market.

关键词： Industries Surveys engineering management Pricing Companies Watches Industrial engineering Fish

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Diversity and Suitability of the State-of-the-Art Wearable and Wireless EEG systems Review

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IEEE Journal of Biomedical and Health Informatics 2023年第8期27卷 3830-3843页

作者： He, Congying Chen, Yu-Yi Phang, Chun-Ren Stevenson, Cory Chen, I-Ping Jung, Tzyy-Ping Ko, Li-Wei Institute of Bioinformatics and Systems Biology National Yang Ming Chiao Tung University Hsinchu30010 Taiwan Institute of Applied Arts National Yang Ming Chiao Tung University Hsinchu30010 Taiwan International Ph.D. Program in Interdisciplinary Neuroscience National Yang Ming Chiao Tung University Hsinchu30010 Taiwan Institute for Neural Computation and Institute of Engineering in Medicine University of California San DiegoCA90093 United States National Yang Ming Chiao Tung University Hsinchu30010 Taiwan Institute of Electrical and Control Engineering Department of Electronics and Electrical Engineering Department of Biological Science and Technology National Yang Ming Chiao Tung University Hsinchu30010 Taiwan Department of Biomedical Science and Environment Biology Drug Development and Value Creation Research Center Kaohsiung Medical University Kaohsiung80708 Taiwan

Wireless electroencephalography (EEG) systems have been attracting increasing attention in recent times. Both the number of articles discussing wireless EEG and their proportion relative to general EEG publications have increased over years. These trends indicate that wireless EEG systems could be more accessible to researchers and the research community has recognized the potential of wireless EEG systems. To explore the development and diverse applications of wireless EEG systems, this review highlights the trends in wearable and wireless EEG systems over the past decade and compares the specifications and research applications of the major wireless systems marketed by 16 companies. For each product, five parameters (number of channels, sampling rate, cost, battery life, and resolution) were assessed for comparison. Currently, these wearable and portable wireless EEG systems have three main application areas: consumer, clinical, and research. To address this multitude of options, the article also discussed the thought process to find a suitable device that meets personalization and use cases specificities. These investigations suggest that low-price and convenience are key factors for consumer applications, wireless EEG systems with FDA or CE-certification may be more suitable for clinical settings, and devices that provide raw EEG data with high-density channels are important for laboratory research. This article presents an overview of the current state of the wireless EEG systems specifications and possible applications and serves as a guide point as it is expected that more influential and novel research will cyclically promote the development of such EEG systems. © 2023 IEEE.

关键词： Electroencephalography

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Minimizing the Number of Stunting Prevalence Using the Euclid Algorithm Clustering Approach 7

Minimizing the Number of Stunting Prevalence Using the Eucli...

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7th IEEE International Conference of Computer Science and Information Technology, ICOSNIKOM 2023

作者： Zarlis, Muhammad Oktavia, Tanty Buaton, Relita Ernawan, Ferda Andrian, Kevin Bina Nusantara University Information System Management Department BINUS Graduate Program - Master of Information System Management Jakarta11480 Indonesia STMIK Kaputama Informatics Engineering Binjai20714 Indonesia Universiti Malaysia Pahang Al-Sultan Abdullah Faculty of Computing Pekan26600 Malaysia BINUS Graduate Program-Master of Information Systems Management Bina Nusantara University Department of Information Systems Management Jakarta Indonesia

ISBN: (纸本)9798350360752

Superior and quality human resources are based on healthy human resources with indicators of adequate nutritional intake according to age development. However, the world still faces the problem of hunger and malnutrition today. According to a UNICEF report, the number of people suffering from malnutrition in the world will reach 767.9 million people in 2021. The World Health Organization (WHO) said that malnutrition is a dangerous threat to the health of the world's population. Stunting also has an impact in Indonesia, the prevalence of toddlers experiencing stunting in Indonesia is 24.4% in 2021. The solution created is to classify and cluster the prevalence of stunting to produce a pattern that can be used as best practice to be transmitted to other affected areas. The algorithm used is Euclid. The Euclid algorithm can cluster stunting prevalence data into 4 clusters with the very little category at 79%, the little category at 67%, the many categories at 51%, and the very much category at 21%. The results of the classification and clustering of the best stunting prevalence in cluster one with a very small number, can be used as a source of accurate and updated information that can be used by the government in its efforts to optimize stunting handling in each district/city based on artificial intelligence which can provide handling and optimization patterns. stunting in every district/city. © 2023 IEEE.

关键词： Classification (of information)

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Correction to: NeXtSRGAN: enhancing super-resolution GAN with ConvNeXt discriminator for superior realism (The Visual Computer, (2025), 10.1007/s00371-024-03797-2)

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Visual Computer 2025年 1-1页

作者： Park, Sung-Wook Jung, Se-Hoon Sim, Chun-Bo Interdisciplinary Program in IT-Bio Convergence System Sunchon National University Suncheon57922 Korea Republic of Department of Computer Engineering Sunchon National University Suncheon57922 Korea Republic of

The publication of this article unfortunately contained mistakes. The assignment of the affiliations was not correct. The corrected affiliation is given below. Wrong assignment: Chun-Bo Sim 1,2 1 interdisciplinary program in IT-Bio Convergence System, Sunchon National University, Suncheon 57922, Republic of Korea 2 department of Computer engineering, Sunchon National University, Suncheon 57922, Republic of Korea Correct assignment: Chun-Bo Sim 1 1 interdisciplinary program in IT-Bio Convergence System, Sunchon National University, Suncheon 57922, Republic of Korea The original article has been corrected. © The Author(s) 2025.

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Bagging System Performance Analysis Using Artificial Neural Network, Random Forest Regression, Linear Regression, and Support Vector Regression

Bagging System Performance Analysis Using Artificial Neural ...

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IEEE International Symposium on Consumer Electronics (ISCE)

作者： Ari Primantara Udisubakti Ciptomulyono Berlian Al Kindhi Interdisciplinary School of Management Technology Institut Teknologi Sepuluh Nopember Surabaya Indonesia Department of Industrial and Systems Engineering Institut Teknologi Sepuluh Nopember Surabaya Indonesia Department of Electrical Automation Engineering Institut Teknologi Sepuluh Nopember Surabaya Indonesia

ISBN: (数字)9798350365191

ISBN: (纸本)9798350365207

Agriculture is one of the most important sectors in the world because it provides commodities such as rice, cassava, corn, rubber, and palm oil. Urea fertilizer is essential for use in crops, and the demand for this product increases every year due to rapid globalization. Fertilizer firms must reduce production costs and product losses to remain competitive. This study introduces the use of machine learning to predict which algorithm could give the best result in predicting fertilizer weight losses. The algorithms studied were linear regression, artificial neural network, random forest regression, and support vector regression. The results show R2, MAE, and RMSE for each method. The R2 values for ANN, Random Forest, Linear Regression, and Support Vector Regression are 0.9509; 0.9759; 0.9507; and 0.9367, respectively. Random Forest shows the best result compared with the three other algorithms, implying that it is the most accurate algorithm for this research, followed by the supporting result MAE value of 0.0829, which is smaller than the other.

关键词： Support vector machines Accuracy Machine learning algorithms Costs Linear regression Artificial neural networks Predictive models Prediction algorithms Random forests Fertilizers

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Data-Driven Power Flow Estimation for MVDC Distribution systems Based on Physics-Embedded FCN

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IEEE Transactions on Smart Grid 2025年

作者： Sun, Pingyang Wu, Rongcheng Shen, Zhiwei Wang, Hongyi Li, Gen Khalid, Muhammad Konstantinou, Georgios School of Electrical Engineering and Telecommunications UNSW Sydney Australia University of Technology Sydney Data Science Institute Australia Aalborg University Department of AAU energy Denmark Energy Technology and Computer Science Section Department of Engineering Technology Ballerup2750 Denmark King Fahd University of Petroleum and Minerals Electrical Engineering Department Interdisciplinary Research Center for Sustainable Energy Systems Dhahran31261 Saudi Arabia

Maintaining high prediction accuracy with varying grid topologies poses a significant challenge to adopting neural network (NN)-based approaches for power flow (PF) estimation in medium-voltage direct current (MVDC) distribution systems. This paper proposes a physics-embedded fully convolutional network (PEFCN) to improve the accuracy. Physics-embedded techniques are incorporated in the proposed PEFCN through 1) architecture reconstruction, and 2) loss function reformulation. Architecture is reconstructed by input channel conversion calculation in a new physics operation layer. This process offers physical connections among the three input matrix channels (voltage, current, and line conductance). Three new physics loss terms are included in the loss function to restrict the outliers violating the limits of converter power ratings and terminal MVDC voltages. The two operations enable the FCN to achieve improved prediction accuracy and strong generalization capabilities. Five MVDC distribution systems, characterized by different dc voltage levels and topology configurations, serve to validate the superiority of the proposed PEFCN over other NNs in the PF estimation for scenarios involving both fixed and varying system structures. Moreover, a modified IEEE 69-bus distribution system is further used to demonstrate the applicability of the proposed PEFCN for larger systems. © 2010-2012 IEEE.

关键词： DC distribution systems

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A Low Complexity ML-Based Methods for Malware Classification

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Computers, Materials & Continua 2024年第9期80卷 4833-4857页

作者： Mahmoud E.Farfoura Ahmad Alkhatib Deema Mohammed Alsekait Mohammad Alshinwan Sahar A.El-Rahman Didi Rosiyadi Diaa Salama Abd Elminaam Cybersecurity Department Al-Zaytoonah University of JordanAmman11733Jordan Department of Computer Science and Information Technology Applied CollegePrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Faculty of Information Technology Applied Science Private UniversityAmman11931Jordan Computer Systems Program-Electrical Engineering Department Faculty of Engineering-ShoubraBenha UniversityCairo11629Egypt Research Center for Artificial Intelligence and Cybersecurity Electronics and Informatics OrganizationNational Research and Innovation Agency(BRIN)KST Samaun SamadikunBandung40135Republic of Indonesia Jadara Research Center Jadara UniversityIrbid21110Jordan MEU Research Unit Middle East UniversityAmman11831Jordan

The article describes a new method for malware classification,based on a Machine Learning(ML)model architecture specifically designed for malware detection,enabling real-time and accurate malware *** an innovative feature dimensionality reduction technique called the Interpolation-based Feature Dimensionality Reduction Technique(IFDRT),the authors have significantly reduced the feature space while retaining critical information necessary for malware *** technique optimizes the model’s performance and reduces computational *** proposed method is demonstrated by applying it to the BODMAS malware dataset,which contains 57,293 malware samples and 77,142 benign samples,each with a 2381-feature *** the IFDRT method,the dataset is transformed,reducing the number of features while maintaining essential data for accurate *** evaluation results show outstanding performance,with an F1 score of 0.984 and a high accuracy of 98.5%using only two reduced *** demonstrates the method’s ability to classify malware samples accurately while minimizing processing *** method allows for improving computational efficiency by reducing the feature space,which decreases the memory and time requirements for training and *** new method’s effectiveness is confirmed by the calculations,which indicate significant improvements in malware classification accuracy and *** research results enhance existing malware detection techniques and can be applied in various cybersecurity applications,including real-timemalware detection on resource-constrained *** and scientific contribution lie in the development of the IFDRT method,which provides a robust and efficient solution for feature reduction in ML-based malware classification,paving the way for more effective and scalable cybersecurity measures.

关键词： Malware detection ML-based models dimensionality reduction feature engineering

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