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Advancements in Computing (ICAC), International Conference on

作者： B.G.J Gamage R. P. S. D Paranagama R M S H Ranaweera A.V.R. Dilshan Ishara Weerathunga Dharshana Kasthurirathna Department of Software Engineering Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka

This research paper addresses the challenge of bridging the communication gap between sign language users and non-users through a comprehensive study on sign language translation. The focus is on Sinhala Sign Language (SSL), and the research problem encompasses various innovative components. These include the conversion of Sinhala Sign Language (SSL) into text, emotion recognition and representation, personalized sign language learning, and accurate identification and translation of sign language gestures. By leveraging machine learning, deep learning, 3D modeling, and image/video processing techniques, the system enhances accessibility, communication, and education for the deaf and hard-of-hearing community. The outcomes of this research encompass an accurate and visually appealing sign language translation system, personalized learning interfaces, and the integration of emotions into sign language communication. The research contributes by providing insights into SSL grammar and lexicon, developing a tailored sign language learning curriculum, implementing reinforcement learning algorithms for personalized feedback, utilizing 3D components for enhanced visual quality, and optimizing deployments and models for improved performance. The proposed system has significant implications for improved accessibility, education, and inclusivity, fostering effective communication and understanding between sign language users and non-users.

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Optimizing Results in Aerial Images through Post-Processing Techniques on YOLOv7 23

Optimizing Results in Aerial Images through Post-Processing ...

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12th International Symposium on information and Communication technology, SOICT 2023

作者： Vo, Nguyen D. Nguyen, Thu M. Nguyen, Triet H.M. Nguyen, Khang Multimedia Communications Laboratory University of Information Technology Vietnam National University Ho Chi Minh City Ho Chi Minh city Viet Nam Faculty of Computer Science University of Information Technology Vietnam National University Ho Chi Minh City Ho Chi Minh city Viet Nam Faculty of Software Engineering University of Information Technology Vietnam National University Ho Chi Minh City Ho Chi Minh city Viet Nam

ISBN: (纸本)9798400708916

Object detection in aerial images has garnered significant attention from the research community in recent years. The challenges posed by small objects, diverse orientations, and complex backgrounds have spurred extensive research efforts. In this paper, we focus on object detection in a YOLOv7-based framework, to address the issue of overlapping predicted regions, we introduce and apply the Soft-NMS (Non-Maximum Suppression) technique, a post-processing method known for its effectiveness in improving detection accuracy in such scenarios. Soft-NMS adjusts bounding box scores based on the extent of overlap, allowing for more accurate localization of objects in densely populated regions. Furthermore, we present comprehensive experimental results to validate the efficacy of our proposed approach. The analyses encompass a thorough evaluation on the UCAS Aerial Object Detection (UCAS AOD) dataset, comprising over 1500 aerial images captured from diverse perspectives. Our method has demonstrated an improvement in object detection performance, particularly in scenarios with closely positioned objects. The proposed framework showcases its ability to handle complex aerial scenes with higher precision and recall rates compared to conventional methods. © 2023 ACM.

关键词： Object detection

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Message Verification Protocol Based on Bilinear Pairings and Elliptic Curves for Enhanced Security in Vehicular Ad Hoc Networks

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Computers, Materials & Continua 2024年第10期81卷 1029-1057页

作者： Vincent Omollo Nyangaresi Arkan A.Ghaib Hend Muslim Jasim Zaid Ameen Abduljabbar Junchao Ma Mustafa A.Al Sibahee Abdulla J.Y.Aldarwish Ali Hasan Ali Husam A.Neamah Department of Computer Science and Software Engineering Jaramogi Oginga Odinga University of Science and TechnologyBondo40601Kenya Department of Applied Electronics Saveetha School of EngineeringSIMATSChennaiTamilnadu602105India Information Technology Department Management Technical CollegeSouthern Technical UniversityBasrah61004Iraq Department of Computer Science College of Education for Pure SciencesUniversity of BasrahBasrah61004Iraq College of Big Data and Internet Shenzhen Technology UniversityShenzhen518118China Huazhong University of Science and Technology Shenzhen InstituteShenzhen518000China National Engineering Laboratory for Big Data System Computing Technology Shenzhen UniversityShenzhen518060China Computer Technology Engineering Department Iraq University CollegeBasrah61004Iraq Department of Mathematics College of Education for Pure SciencesUniversity of BasrahBasrah61004Iraq Institute of Mathematics University of DebrecenDebrecenH-4002Hungary Department of Electrical Engineering and Mechatronics Faculty of EngineeringUniversity of DebrecenDebrecen4028Hungary

Vehicular ad hoc networks(VANETs)provide intelligent navigation and efficient route management,resulting in time savings and cost reductions in the transportation ***,the exchange of beacons and messages over public channels among vehicles and roadside units renders these networks vulnerable to numerous attacks and privacy *** address these challenges,several privacy and security preservation protocols based on blockchain and public key cryptography have been proposed ***,most of these schemes are limited by a long execution time and massive communication costs,which make them inefficient for on-board units(OBUs).Additionally,some of them are still susceptible to many *** such,this study presents a novel protocol based on the fusion of elliptic curve cryptography(ECC)and bilinear pairing(BP)*** formal security analysis is accomplished using the Burrows–Abadi–Needham(BAN)logic,demonstrating that our scheme is verifiably *** proposed scheme’s informal security assessment also shows that it provides salient security features,such as non-repudiation,anonymity,and ***,the scheme is shown to be resilient against attacks,such as packet replays,forgeries,message falsifications,and *** the performance perspective,this protocol yields a 37.88%reduction in communication overheads and a 44.44%improvement in the supported security ***,the proposed scheme can be deployed in VANETs to provide robust security at low overheads.

关键词： Attacks bilinear elliptic curve cryptography(ECC) privacy security vehicular ad hoc network(VANET)

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KidSwatch: Children Development Observation System

KidSwatch: Children Development Observation System

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Advancements in Computing (ICAC), International Conference on

作者： P.A.L.N Oshadhini K.A.D.H.O Siriwardana H.K Peshala Ranmini S.R Sandeepa Lokesha Weerasinghe Thamali Kelegama Department of Information Technology Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka Department of Software Engineering Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka

The kidSwatch is a mobile application designed specifically for grade 1 children aged six years. It serves as a comprehensive framework for observing and evaluating children's developmental progress. The application focuses on the main components of children's development: Cognitive development, Emotional development, Language development, and Learning development. By analyzing the results obtained from observing these four components, parents can gain valuable insights into their children's development within a matter of minutes. The kidSwatch employs a range of observational techniques, including direct observation, structured interviews, and standardized tests, to gather information on a child's talents, skills, and behaviors. Trained observers proficient in the kidSwatch framework carefully record and analyze the child's interactions, activities, problem-solving abilities, emotional expressions, and social interactions. Ultimately, the kidSwatch empowers parents with a quick and effective means of understanding and assessing their child's development. To satisfy the above features there are a Hand number detection algorithm, letter recognition algorithm, Emotion recognition algorithm, and voice-based answering algorithm They perform an accuracy between 75%-90% on CNN.

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Quality Obstacles of Distance Learning: Experiences from Students of the University of Benghazi

Quality Obstacles of Distance Learning: Experiences from Stu...

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Sciences and Techniques of Automatic Control and Computer engineering MI-STA, IEEE International Maghreb Meeting of the Conference on

作者： Osamah Sulayman Yahya Suweel Abdelsalam M. Maatuk Mohamed A E Abdalla Dept. of Information Systems Faculty of Information Technology Benghazi University Benghazi Libya Faculty of Information Technology Libyan International Medical University Benghazi Libya Dept. of Software Engineering Faculty of Information Technology Benghazi University Benghazi Libya

Adopting distance learning with a high level of quality in universities and educational institutions is a real challenge. Therefore, several studies and organizations have provided different standards to evaluate the quality of long-distance and to measure the obstacles. This study examines the quality obstacles of the long-distance learning techniques applied at the faculty of information technology at the University of Benghazi, Libya. The British Quality Assurance Agency (BQAA) standards are utilized and presented as a questionnaire to the students at the faculty. The total participant number is 223 respondents. The study findings show that the students face severe challenges in all categories of the BQAA of technical, social, and organizational obstacles. The level of challenges is represented in the negativity of the response 69.1%, 60.1%, and 59.44% of the determined categories.

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A Soft Tissue Acupuncture Model Based on Mass-Spring Force Ne

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Computers, Materials & Continua 2021年第10期69卷 727-745页

作者： Xiaorui Zhang Tong Xu Wei Sun Jiali Duan Sunil Kumar Jha Jiangsu Engineering Center of Network Monitoring Engineering Research Center of Digital ForensicsMinistry of EducationSchool of Computer and SoftwareNanjing University of Information Science&TechnologyNanjing210044China Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology(CICAEET) Nanjing University of Information Science&TechnologyNanjing210044China Faculty of Information Technology University of Information Technology and ManagementRzeszow35-225Poland

In the simulation of acupuncture manipulation,it is necessary to accurately capture the information of acupuncture points and particles around ***,a soft tissue modeling method that can accurately track model particles is *** this paper,a soft tissue acupuncture model based on the mass-spring force net is *** is used as the auxiliary model and the SHF model is *** is used to establish a three-layer soft tissue model of skin,fat,and muscle,and a layer of the MSM based force network is covered on the surface of soft tissue to realize the complementary advantages and disadvantages of spherical harmonic function and *** addition,a springback algorithm is designed to simulate the springback phenomenon of soft tissue skin during *** evaluation results show that the soft tissue acupuncture modeling method based on mass-spring force net can effectively simulate the springback phenomenon of soft tissue surface during acupuncture surgery,and has good comprehensive performance in the application of virtual acupuncture surgery simulation.

关键词： Mass-spring model puncture simulation virtual surgery soft tissue simulation

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Parameter Optimization of the Random Forest Algorithm for Predicting Corn Yields in Toba Regency

Parameter Optimization of the Random Forest Algorithm for Pr...

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International Seminar on Research of information technology and Intelligent Systems (ISRITI)

作者： Tegar Arifin Prasetyo Tiurma Lumban Gaol Rudy Chandra Yohanssen Pratama Herlina Nikita Purba Albert Arta Danyoan Manik Olyvia Siahaan Information Technology Faculty of Vocational Study Institut Teknologi Del Laguboti Indonesia Software Engineering Faculty of Vocational Study Institut Teknologi Del Laguboti Indonesia

ISBN: (数字)9798331519643

ISBN: (纸本)9798331519650

Maize (Zea mays L.) is one of the important agricultural commodities in Indonesia. Maize crop processing is widely managed by farmers in North Sumatra, particularly in Toba Regency. However, Indonesia has not been able to meet the demand for corn production from 2009 to 2021, so there is an urgent need to increase production to avoid dependence on imports. In this research, a website is developed to predict corn yield using Random Forest algorithm. This website aims to help farmers and related parties in planning corn production better, utilizing historical data that includes data on seeds, fertilizers, land area, medicines, and crop yields from 2010 to 2023. Based on the implementation of the algorithm used and the parameter values obtained, this website is able to predict corn yields with a Mean Absolute Percentage Error (MAPE) value of 9.04%, which falls into the excellent category. The results of this study indicate that the Random Forest algorithm can be relied upon to predict corn yields in Toba Regency, so that it can help improve efficiency and effectiveness in the agricultural sector.

关键词： Seminars Accuracy Production Predictive models Prediction algorithms Data models Seeds (agriculture) Planning Tuning Optimization

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H2P×PKD: Progressive Training Pipeline with Knowledge Distillation for Lightweight Backbones in Pedestrian Detection 7

H2P×PKD: Progressive Training Pipeline with Knowledge Disti...

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7th International Conference on Multimedia Analysis and Pattern Recognition, MAPR 2024

作者： Le, Duc-Nhuan Nguyen, Hoang-Phuc Vong, Vinh-Toan Luong, Nguyen-Khoa Do, Trong-Le University of Science VNU-HCM Faculty of Information Technology Ho Chi Minh City Viet Nam Vietnam National University Ho Chi Minh City Viet Nam University of Science VNU-HCM Software Engineering Laboratory Ho Chi Minh City Viet Nam

ISBN: (纸本)9798350368437

Pedestrian Detection, an instance of Object Detection, has many applications, especially in autonomous driving and surveillance. While many methods are tailored for pedestrian detection, studies suggest that general object detection approaches can also be effective with the appropriate training settings. The large domain unsimilarity between general object data and pedestrian-specific data is a significant challenge. To address this, Pedestron introduces a progressive training pipeline that begins with pre-training on a large and diverse general human dataset, followed by fine-tuning on pedestrian-specific data. However, this transition remains too abrupt. Additionally, the model's size and computational cost are also not receiving much attention. Therefore, we propose H2P, a new training pipeline based on Pedestron. The pipeline includes IDSS, an intermediate training step for detecting general humans in traffic-related contexts before fine-tuning on pedestrian datasets. Moreover, we leverage PKD, a knowledge distillation method via Pearson Correlation Coefficient, to improve lightweight models using FPN features from large-scale, general teacher models. To evaluate the effectiveness of our H2P with PKD approach, we experiment on two lightweight backbones: a traditional MobileNetV2 and a downscaled variant of InternImage, named InternImage-M. Our best result is 8.59% MR-2 on CityPersons' validation set. Our lightweight InternImage-M backbone gives the promising result of 11.53% MR-2 © 2024 IEEE.

关键词： Personnel training

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GAN-based Symmetric Embedding Costs Adjustment for Enhancing Image Steganographic Security 24

GAN-based Symmetric Embedding Costs Adjustment for Enhancing...

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32nd ACM International Conference on Multimedia, MM 2024

作者： Ye, Miaoxin Zhou, Saixing Luo, Weiqi Tan, Shunquan Huang, Jiwu Guangdong Provincial Key Laboratory of Information Security Technology Sun Yat-Sen University Guangzhou China Shenzhen Key Laboratory of Media Security College of Computer Science and Software Engineering Shenzhen University Shenzhen China Guangdong Laboratory of Machine Perception and Intelligent Computing Faculty of Engineering Shenzhen MSU-BIT University Shenzhen China

ISBN: (纸本)9798400706868

Designing embedding costs is pivotal in modern image steganography. Many studies have shown adjusting symmetric embedding costs to asymmetric ones can enhance steganographic security. However, most existing methods heavily depend on manually defined parameters or rules, limiting security performance improvements. To overcome this limitation, we introduce an advanced GAN-based framework that transitions symmetric costs to asymmetric ones without the need for the manual intervention seen in existing approaches, such as the detailed specification of cost modulation directions and magnitudes. In our framework, we firstly achieve symmetric costs for a cover image, which is randomly split into two sub-images, with part of the secret information embedded into one. Subsequently, we design a GAN model to adjust the embedding costs of the second sub-image to asymmetric, facilitating the secure embedding of the remaining secret information. To support our phased embedding approach, our GAN's discriminator incorporates two steganalyers with different tasks: distinguishing the generator's final output, i.e., the stego image, from both the input cover image and the partially embedded stego image, providing diverse guidance to the generator. In addition, we introduce a simple yet effective update strategy to ensure a stable training process. Comprehensive experiments demonstrate that our method significantly enhances security over existing symmetric steganography techniques, achieving state-of-the-art levels compared to other methods focused on embedding costs adjustments. Additionally, detailed ablation studies validate our approach's effectiveness. © 2024 ACM.

关键词： Steganography

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Anomaly Event Retrieval System from TV News and Surveillance Cameras 23

Anomaly Event Retrieval System from TV News and Surveillance...

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12th International Symposium on information and Communication technology, SOICT 2023

作者： Tran, Mai-Khiem Tran, Minh-Triet Software Engineering Laboratory John von Neumann Institute University of Science VNU-HCM Viet Nam National University Ho Chi Minh City Viet Nam Faculty of Information Technology Software Engineering Lab John von Neumann Institute VNU-HCM Viet Nam National University Ho Chi Minh City Viet Nam

ISBN: (纸本)9798400708916

In an era defined by the proliferation of digital content and a growing reliance on video data, the need for effective anomaly detection systems has never been more pressing. This paper introduces a sophisticated system architecture designed to address the complex challenges associated with acquiring, processing, and presenting anomaly videos. At its core, our architecture prioritizes openness and modularity, allowing for seamless upgrades and customization. This approach ensures adaptability to evolving technology trends and user preferences. We emphasize the crucial aspects of component interfacing and user interaction, highlighting the integration of feedback mechanisms for ongoing system refinement. Additionally, we contribute significantly to the research community by extending an established anomaly event dataset using proven methods and techniques. This extension enhances the dataset's breadth and depth, providing a valuable resource for training and evaluating anomaly event retrieval systems. Our paper presents a forward-looking system architecture poised to meet the demands of anomaly video detection while also enriching the available resources for anomaly event research. Subsequent sections will delve into architecture components and methodologies, showcasing its potential to revolutionize modern anomaly detection systems. © 2023 ACM.

关键词： Computer architecture

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