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Dynamic Terrain Data Exchange in a Collaborative Terrain Editor

Informatica (Slovenia) 2022年第4期46卷 575-582页

作者： Tarigan, Jos Timanta Sitompul, Opim Salim Zarlis, Muhammad Nababan, Erna Budhiarti Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan Indonesia Information Systems Management Department BINUS Graduate Program Bina Nusantara University Jakarta Indonesia

In a computer supported cooperative work (CSCW), data consistency between collaborating users is a crucial issue. Based on the type of the application, ensuring data consistency can be a lengthy process that takes time and affects the system’s performance. In most 3D application, terrain data are massive due to its size. Exchanging this data may be expensive and may cause significant delay. In a real-time collaborative terrain editor, this issue becomes more significant due to terrain data exchange is consistently occurred between collaborating users. We present a solution to perform a conflict-free dynamic terrain data exchange in a real-time collaborative terrain editor. Our objective is to develop a method that able to ensure data consistency amongst collaborating peers in real-time manner. The main idea of our method is to split the terrain into smaller patches and synchronize the changes efficiently by only exchanging the modified patches. We applied our solution to a collaborative terrain editor application to test its performance in a real-time collaborative editing session. The tests were done in multiple scenarios, using different patch model, brush size (in the terrain editor), and connection setup between server and collaborating clients. The result shows that our protocol is capable to maintain data consistency between collaborating clients in a real-time terrain edition session. The delay is varied and highly depends on the data size and client-server environment setup. The overall test shows that it is possible to perform a collaborative terrain editing with an acceptable response time delay. In this paper, we present our proposed method, the implementation, and the result data from the test. © 2022 Slovene Society Informatika. All rights reserved.

关键词： Electronic data interchange

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Cloud-Driven Wearables using Naive Bayes Algorithm and Advanced Sensors in Smart Fabrics 3

Cloud-Driven Wearables using Naive Bayes Algorithm and Advan...

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3rd International Conference for Innovation in technology, INOCON 2024

作者： Praveena, M.D. Anto Gupta, Nukala Sujata Marin, V. Bini Jeslin, J Gnana Meenakshi, R. Muthulekshmi, M. Sathyabama Institute of Science and Technology Department of Computer Science and Engineering Tamil Nadu Chennai India Chaitanya Bharathi Institute of Technology Department of Computer Engineering and Technology Telangana Hyderabad India Srm Institute of Science and Technology Faculty of Management Studies Tamil Nadu Chennai India Rmk College of Engineering and Technology Department of Computer Science and Engineering Tamil Nadu Chennai India Chennai Institute of Technology Department of Computer Science and Engineering Tamil Nadu Chennai India Saveetha Institute of Medical and Technical Sciences Saveetha University Department of Biomedical Engineering Saveetha School of Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350381931

In the realm of fashion technology, the introduction of smart textiles and wearable sensors may be attributed to the fast progression of technology and the rising need for customized, interactive, and intelligent apparel. This study investigates the interface of electronics and textiles to develop cutting-edge, multifunctional, and flexible apparel. This research digs into the fascinating world of smart textiles. It investigates the many different kinds of sensors, such as temperature sensors, heart rate monitors, motion detectors, and chemical sensors that may be easily incorporated into the fabric. These sensors make a wide variety of applications possible, such as improved user experiences, monitoring of health conditions, and data collecting on the surrounding environment. In addition, to assure the practicability and usage of smart textiles, it addresses the problems and possibilities connected with various power sources, connection choices, and data processing units. The purpose of this study is to contribute to the continuous development of intelligent clothing, which has the potential to revolutionize the fashion industry by producing clothes that not only represent an individual's sense of style but also give useful insights, functionality, and connectedness to the digital world. © 2024 IEEE.

关键词： Smart textiles

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Grape Guard:A YOLO-based mobile application for detecting grape leaf diseases

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Journal of Electronic science and technology 2025年第1期23卷 60-75页

作者： Sajib Bin Mamun Israt Jahan Payel Md.Taimur Ahad Anthony S.Atkins Bo Song Yan Li Department of Computer Science and Engineering Daffodil International UniversityDhaka1207Bangladesh Department of Computer Science University of Southern QueenslandToowoomba4350Australia Faculty of Digital TechnologyInnovationand BusinessStaffordshire UniversityStoke-on-TrentST42DEUnited Kingdom School of Engineering University of Southern QueenslandToowoomba4350Australia School of Mathematics Physics and ComputingUniversity of Southern QueenslandToowoomba4350Australia

Grape crops are a great source of income for *** yield and quality of grapes can be improved by preventing and treating *** farmer’s yield will be dramatically impacted if diseases are found on grape *** detection can reduce the chances of leaf diseases affecting other healthy *** studies have been conducted to detect grape leaf diseases,but most fail to engage with end users and integrate the model with real-time mobile *** study developed a mobile-based grape leaf disease detection(GLDD)application to identify infected leaves,Grape Guard,based on a TensorFlow Lite(TFLite)model generated from the You Only Look Once(YOLO)v8 model.A public grape leaf disease dataset containing four classes was used to train the *** results of this study were relied on the YOLO architecture,specifically YOLOv5 and *** extensive experiments with different image sizes,YOLOv8 performed better than ***8 achieved 99.9%precision,100%recall,99.5%mean average precision(mAP),and 88%mAP50-95 for all classes to detect grape leaf *** Grape Guard android mobile application can accurately detect the grape leaf disease by capturing images from grape vines.

关键词： Bacterial diseases Grape Guard Mobile-based application YOLOv5 YOLOv8

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Propagation of EM Waves Through Biomaterial Based on Harvest Waste - Influence of Biomaterial Density, Moisture and Temperature 33rd

Propagation of EM Waves Through Biomaterial Based on Harvest...

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33rd International Conference on Organization and technology of Maintenance, OTO 2024

作者： Mandrić, Vanja Rupčić, Slavko Pavković, Bogdan Bogdanović, Nataša Faculty of Electrical Engineering Computer Science and Information Technology Osijek Osijek Croatia Faculty of Technical Sciences University of Novi Sad Novi Sad Serbia Department of Information and Communication Technologies Academy of Applied Technical and Preschool Studies Niš Serbia

ISBN: (纸本)9783031805967

This paper deals with the simulation calculation of the transmission (S21) parameter in a biomaterial calculated parametrically on the basis harvest waste (residues) as a function of the density, moisture and temperature of the material. Since this material is essentially wood, empirical and semi-empirical models are used to determine the electromagnetic parameters of the wood material as a function of the density, moisture and temperature of the material according to the available literature. The structural - geometric and environmental parameters of the material that are the subject of the research are: density, moisture and temperature of the material, and the electromagnetic parameters that "describe" them are: relative permittivity Εr, loss tangent tan δ and electrical conductivity σ. The simulation model is based on a system for measuring coupling parameters in free space, which consists of two antennas, between which a 600 × 600 mm sample of the biomaterial is placed, and a network analyzer. With increasing density and moisture significantly increases the relative dielectric constant, the loss tangent and the electrical conductivity of the measured biosamples. The temperature change in a wide temperature range (20 ℃–100 ℃) has no significant influence on the electromagnetic parameters. The measured results were used to verify the simulation model. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Electric conductivity

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FACE UNLOCK SYSTEM FOR VEHICLES 2

FACE UNLOCK SYSTEM FOR VEHICLES

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2nd International Conference on Advancements in Smart, Secure and Intelligent Computing, ASSIC 2024

作者： Navya, Soleti Suresh, Juttu Sangeetha, A. Praveen, G. Nabi, Shaik Abdul Kumar, Dilip Mlr Institute of Technology Department of Computer Science and Information Technology India Malla Reddy Engineering College and Management Sciences Department of Information Technology Hyderabad India Mlr Institute of Technology Department of Computer Science and Engineering Hyderabad India Cse Dept Avniet Jntuh India Mlr Institute of Technology Dept. of Electrical and Electronics Engineering Hyderabad India

ISBN: (纸本)9798350370188

Currently, all vehicles are key operated. Our intention is therefore to develop an intelligent unlocking system based on facial recognition technology. In Today's era of automation and smart devices, privacy and security are important issues in information technology so to information system, so it is urgent to change system security measures. In previous systems, many vehicle doors had mechanical locks with a limited number of keys. To enhance security, we propose an intelligent vehicle door unlocking system based on facial recognition the system uses camera sensor to recognize faces and image matching algorithms to recognize authenticated faces. Only people with matching faces can open the door this system not only provides additional security but also useful for systems without physical keys. © 2024 IEEE.

关键词： Network security

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Computational Investigation of Multiband EMNZ Metamaterial Absorber for Terahertz Applications

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computers, Materials & Continua 2022年第5期71卷 3905-3920页

作者： Ismail Hossain Md Samsuzzaman Mohd Hafiz Baharuddin Norsuzlin Binti Mohd Sahar Mandeep Singh Jit Singh Mohammad Tariqul Islam Space Science Center Universiti Kebangsaan Malaysia43600UKM BangiSelangorMalaysia Department of Computer and Communication Engineering Faculty of Computer Science and EngineeringPatuakhali Science and Technology UniversityBangladesh Department of Electrical Electronic and Systems EngineeringFaculty of Engineering and Built EnvironmentUniversiti Kebangsaan MalaysiaMalaysia

This study presents an Epsilon Mu near-zero(EMNZ)nanostructured metamaterial absorber(NMMA)for visible regime *** resonator and dielectric layers are made of tungsten(W)and quartz(fused),where the working band is expanded by changing the resonator layer’s *** to perfect impedance matching with plasmonic resonance characteristics,the proposed NMMA structure is achieved an excellent absorption of 99.99%at 571 THz,99.50%at 488.26 THz,and 99.32%at 598 THz *** absorption mechanism is demonstrated by the theory of impedance,electric field,and power loss density distributions,*** geometric parameters are explored and analyzed to show the structure’s performance,and a near-field pattern is used to explain the absorption mechanism at the resonance frequency *** numerical analysis method describes that the proposed structure exhibited more than 80%absorbability between 550 and 900 *** computer Simulation technology(CST Microwave Studio 2019)software is used to design the proposed ***,CSTHFSS interference is validated by the simulation data with the help of the finite element method(FEM).The proposed NMMA structure is also exhibits glucose concentration sensing capability as *** the proposed broadband absorber may have a potential application in THz sensing,imaging(MRI,thermal,color),solar energy harvesting,light modulators,and optoelectronic devices.

关键词： Metamaterial absorber terahertz applications multiband EM near zero nanostructured visible regime applications

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GPGPU-based randomized visual secret sharing (GRVSS) for grayscale and colour images

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International Journal of computers and Applications 2022年第6期44卷 552-560页

作者： Holla, Raviraja Mhala, Nikhil C. Pais, Alwyn R. Information Security Research Lab Department of Computer Science and Engg National Institute of Technology Karnataka Surathkal India

Visual Secret Sharing (VSS) is a technique used for sharing secret images between users. The existing VSS schemes reconstruct the original secret image as a halftone image with only a 50% contrast. The Randomized Visual Secret Sharing (RVSS) scheme overcomes the disadvantages of existing VSS schemes. Although RVSS extracts the secret image with better contrast, it is computationally expensive. This paper proposes a General Purpose Graphics Processing Unit (GPGPU)-based Randomized Visual Secret Sharing (GRVSS) technique that leverages data parallelism in the RVSS pipeline. The performance of the GRVSS is compared with the RVSS in a generic and PARAM Shavak supercomputer architecture. The GRVSS outperforms the RVSS in both architectures. © 2020 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Graphics processing unit

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Prediabetes Detection Using Non-Laboratory Data with Extreme Gradient Boosting Algorithm 11

Prediabetes Detection Using Non-Laboratory Data with Extreme...

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11th International Conference on Electrical Engineering, computer science and Informatics, EECSI 2024

作者： Rizqie, Muhammad Qurhanul Liberty, Iche A Septadina, Indri S Putra, Pacu Rini, Dian Palupi Universitas Sriwijaya Department of Informatics Faculty of Computer Science South Sumatera Indonesia Universitas Sriwijaya Department of Public Health and Community Medicine Faculty of Medicine South Sumatera Indonesia Universitas Sriwijaya Department of Anatomy Faculty of Medicine South Sumatera Indonesia Universitas Sriwijaya Department of Information System Faculty of Computer Science South Sumatera Indonesia

ISBN: (纸本)9798350355314

Diabetes Mellitus (DM), characterized by high blood glucose levels, is a dangerous condition that leads to severe long-term health issues. Meanwhile, prediabetes is a condition where individuals have an increased risk of developing type 2 DM. Early detection of prediabetes is crucial for effective DM management. Traditional detection relies on medical records and family history, but laboratory tests are not always practical. This study proposes using non-laboratory data, processed by the Extreme Gradient Boosting (XGBoost) algorithm, to identify individuals with prediabetes. The dataset used in this research includes attributes like blood pressure, weight, height, waist size, food intake, and age. Preprocessing involved removing irrelevant data and transforming numeric data into categories. The XGBoost model, applied to this dataset, achieved 0.91 for average accuracy, precision, recall, and F1-score. AUC values of the model is 0.93, demonstrating its effectiveness in distinguishing between normal and prediabetic individuals. These results suggest the potential for non-laboratory data and XGBoost in early prediabetes detection, aiding in timely intervention and improved health outcomes. © 2024 IEEE.

关键词： Electronic health record

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Evaluating Patient Satisfaction Through Validated Predictive Classification Models 16

Evaluating Patient Satisfaction Through Validated Predictive...

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16th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2024

作者： Chemkomnerd, Nittaya Pannakkong, Warut Huynh, Van Nam Tanantong, Tanatorn School of Knowledge Science Japan Advanced Institute of Science and Technology Ishikawa Japan Sirindhorn International Institute of Technology Thammasat University Pathum Thani Thailand Thammasat University Faculty of Science and Technology Department of Computer Science Pathum Thani Thailand

ISBN: (纸本)9798350377903

Patient satisfaction plays a crucial role in evaluating healthcare service quality. This study explores the field of predicting patient satisfaction in healthcare settings. The research aims to develop a predictive and validated model for patient satisfaction scores to improve patient satisfaction through simulation-optimization. Factors related to patient satisfaction were identified, including length of stay (LOS) and patient sociodemographic characteristics. A survey was conducted to collect relevant data. Several predictive modeling techniques were employed, i.e., ordinal logistic regression, decision trees, gradient boosted trees, and neural networks. The models were trained on the survey data to predict patient satisfaction scores. A simulation was then used to generate synthetic data, which was fed into the predictive models to obtain predicted satisfaction scores. The predicted scores were validated against the actual survey scores using the Mann-Whitney U test to evaluate each model's ability to represent the simulated system accurately. Findings suggest that ordinal logistic regression provides the best performance for predicting satisfaction across various LOS. The validated predictive model can be integrated into a simulation-optimization framework to identify strategies for improving patient satisfaction in healthcare systems, facilitating informed decision-makina and the allocation of resources. © 2024 IEEE.

关键词： Logistic regression

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Predictive maintenance using AI for Motor health prediction system

Predictive maintenance using AI for Motor health prediction ...

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2022 International Electrical Engineering Congress, iEECON 2022

作者： Bundasak, Supaporn Wittayasirikul, Pawin Kasetsart University Sriracha Campus Faculty of Science at Sriracha Computer Science and Information Technology Department Chonburi Thailand

ISBN: (纸本)9781665402064

Predictive maintenance using AI for Motor health prediction system (PdMA AI System) is a system developed to predict damage and lifespan of motors, which motors are responsible for converting electricity into mechanical energy for machines in the production process. PdMA AI System allows operators and maintenance personnel to be informed about damage to the motor in advance. The system's process working with a motor that has a malfunction is detected. The system will automatically notify operators and maintainers through the website. It is able to plan maintenance effectively in advance. As a result, it helps to reduce downtime of the machines that math the production process to stop, and support prolong the service life of the motor. The researchers compared test the k-nearest neighbor, logistic regression, naïve bayes and support vector machine algorithms, which found that logistic regression is suitable for all test data groups. Logistic regression algorithm was used to develop a model for predicting motor abnormalities with an accuracy of 98% of motor health forecasts. © 2022 IEEE.

关键词： Health

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