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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Shonali Romeshika, H.D. Dasanayaka, Dilshan Deeghayu Alwis, D.C. Herath, Hashini Wijendra, Dinuka Dassanayake, Thamali Sri Lanka Institute of Information Technology Department of Software Engineering Malabe Sri Lanka Sri Lanka Institute of Information Technology Department of Information Technology Malabe Sri Lanka

ISBN: (纸本)9798350370249

This research investigates the transformative potential of deep learning in revolutionizing home interior design through the development of a web application with three core functionalities: object replacement within an existing interior design image, object removal from the interior design image, and text-to-image design generation based on user inputs. Leveraging deep learning models like ControlNet, DeepFill, and stable diffusion, as well as YOLOv8 for object detection and image classification (home interior/non-home interior), the proposed system is an innovative approach to democratizing design knowledge and expediting interior design procedures. This research advances interior design practices and shapes the future of personalized and effective home interior design solutions by offering effective design modifications and design suggestions. © 2024 IEEE.

关键词： Architectural design

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Enhancing STEM Education Accessibility for Blind and Low Vision Students 15

Enhancing STEM Education Accessibility for Blind and Low Vis...

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： De Silva, D.I. Jayasooriya, M.N.N.J. Vidhanaarachchi, S. Jayawardhana, D.M.P.S. Ranasinghe, R.A.K.M. Savishka, D.K.S. Department of Information Technology Sri Lanka Institute of Information Technology Malabe Sri Lanka Department of Software Engineering Sri Lanka Institute of Information Technology Malabe Sri Lanka

ISBN: (纸本)9798350370249

This study focuses on enhancing STEM education accessibility for blind and low vision students through the development of innovative assistive technologies. The primary challenge addressed is the limited engagement and effectiveness of traditional teaching methods for visually impaired students, particularly in science and mathematics. Leveraging advancements in computer vision, machine learning, and internet of things technologies, the proposed solution includes a mobile application integrated with YOLO-based object detection and real-time audio feedback. Methods employed involve capturing and preprocessing images of geometric shapes, educational materials, and currency, followed by rigorous model training using Google Colab. The system's architecture incorporates YOLOv8 for real-time object detection, combined with text-to-speech and speech-to-text technologies to provide comprehensive audio descriptions and interactive feedback. Results demonstrate significant improvements in detection accuracy and user engagement, with YOLOv8 achieving high precision in object recognition tasks. Performance standards were evaluated through confusion matrices, highlighting the model's robustness across various educational scenarios. The developed system effectively enhances independent learning and engagement among visually impaired students, promoting inclusivity and equity in STEM education. © 2024 IEEE.

关键词： Students

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On Campus Low-cost FSO Communication Link Analysis for Backhaul Connectivity in B5G Communications 37

On Campus Low-cost FSO Communication Link Analysis for Backh...

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Free-Space Laser Communications XXXVII 2025

作者： Saeed, Saad Khan, Abdullah Nafis Younis, Usman Faculty of Engineering Information Technology University of the Punjab Arfa Software Technology Park Ferozepur Road Lahore54600 Pakistan

ISBN: (纸本)9781510684584

Increasing demand of high-speed connectivity has challenged the future technologies (5G/B5G) in terms of large bandwidth, ultralow latency, massive coverage, reliable connectivity and rapid deployment. Free space optical (FSO) communication addresses these challenges in a cost effective way due to its unlicensed spectrum, high data-rate and long range. To develop a low-cost indoor FSO link, we present high-speed transceivers based on laser diode and photodiode. The transceiver link has achieved signal transmission up to 65 MHz providing minimum data rate of 130 Mbps using NRZ modulation. Link measurements are performed in an indoor campus environment by employing an optical assembly consisting plano-convex lenses, to achieve a range of 50 meters. An experimental demonstration of a square wave transmission up to 1 MHz is presented along with 53% improved quality of retrieved signal. Moreover, OSNR (13.6 dB) and BER (10−9) parameters are studied to enhance the performance of future FSO networks. © 2025 SPIE.

关键词： Space optics

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Boosting Adversarial Training with Learnable Distribution

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Computers, Materials & Continua 2024年第3期78卷 3247-3265页

作者： Kai Chen Jinwei Wang James Msughter Adeke Guangjie Liu Yuewei Dai School of Electronics and Information Engineering Nanjing University of Information Science and TechnologyNanjing210044China Key Laboratory of Intelligent Support Technology for Complex Environments Ministry of EducationNanjing210044China School of Computer and Software Nanjing University of Information Science and TechnologyNanjing210044China Nanjing Center for Applied Mathematics Nanjing211135China

In recent years,various adversarial defense methods have been proposed to improve the robustness of deep neural *** training is one of the most potent methods to defend against adversarial ***,the difference in the feature space between natural and adversarial examples hinders the accuracy and robustness of the model in adversarial *** paper proposes a learnable distribution adversarial training method,aiming to construct the same distribution for training data utilizing the Gaussian mixture *** distribution centroid is built to classify samples and constrain the distribution of the sample *** natural and adversarial examples are pushed to the same distribution centroid to improve the accuracy and robustness of the *** proposed method generates adversarial examples to close the distribution gap between the natural and adversarial examples through an attack algorithm explicitly designed for adversarial *** algorithm gradually increases the accuracy and robustness of the model by scaling ***,the proposed method outputs the predicted labels and the distance between the sample and the distribution *** distribution characteristics of the samples can be utilized to detect adversarial cases that can potentially evade the model *** effectiveness of the proposed method is demonstrated through comprehensive experiments.

关键词： Adversarial training feature space learnable distribution distribution centroid

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Dynamic defenses in cyber security:Techniques,methods and challenges Author links open overlay panel

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Digital Communications and Networks 2022年第4期8卷 422-435页

作者： Yu Zheng Zheng Li Xiaolong Xu Qingzhan Zhao School of Computer and Software Nanjing University of Information Science and TechnologyNanjing210044JiangsuChina Key Laboratory for Novel Software Technology Nanjing UniversityNanjing210023JiangsuChina College of Information Science and Technology Shihezi University Geospatial Information Engineering Research CenterChina

Driven by the rapid development of the Internet of Things,cloud computing and other emerging technologies,the connotation of cyberspace is constantly expanding and becoming the fifth dimension of human ***,security problems in cyberspace are becoming serious,and traditional defense measures(e.g.,firewall,intrusion detection systems,and security audits)often fall into a passive situation of being prone to attacks and difficult to take effect when responding to new types of network attacks with a higher and higher degree of coordination and *** constructing and implementing the diverse strategy of dynamic transformation,the configuration characteristics of systems are constantly changing,and the probability of vulnerability exposure is ***,the difficulty and cost of attack are increasing,which provides new ideas for reversing the asymmetric situation of defense and attack in ***,few related works systematically introduce dynamic defense mechanisms for cyber *** related concepts and development strategies of dynamic defense are rarely analyzed and *** bridge this gap,we conduct a comprehensive and concrete survey of recent research efforts on dynamic defense in cyber ***,we firstly introduce basic concepts and define dynamic defense in cyber ***,we review the architectures,enabling techniques and methods for moving target defense and mimic *** is followed by taxonomically summarizing the implementation and evaluation of dynamic ***,we discuss some open challenges and opportunities for dynamic defense in cyber security.

关键词： Cyber security Dynamic defense Moving target defense Mimic defense

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OTFS on Overspread Doubly Selective Channel

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China Communications 2024年第11期21卷 205-215页

作者： Qing Hua Liu Yun Shi Xiayang Yu Hua Ji Fei Cui Yinming College of Software Engineering Zhengzhou University of Light IndustryZhengzhou 450002China School of Internet Finance and Information Engineering Guangdong University of FinanceGuangzhou 510520China School of Electronic and Information Engineering South China University of TechnologyGuangzhou 510641China

The orthogonal time frequency space(OTFS)modulation proposed in recent years is considered to have superior performance than orthogonal frequency division multiplexing(OFDM)for the doubly selective(DS)*** works in the existing literature on OTFS mainly focus on the cases where the channels are underspread(i.e.,the product of the delay spread and the Doppler spread is less than 1).In the scenario of overspread DS channel,which has large delay spread and severe Doppler spread,such as underwater acoustic(UWA)channel,the channel model in delay-Doppler(DD)Domain derived by existing work is no longer *** this paper,we derive a more generalized expression of the channel model in delay-Doppler domain,which allows the product of the delay spread and Doppler spread to be larger *** result shows that the existing channel model is just a special case of the one we *** the proposed channel matrix in DD domain,we build the OTFS detectors with the minimum mean square error(MMSE)and message passing(MP)algorithms on overspread doubly selective ***,simulation results are presented to verify the theoretical derivation and the effectiveness of the detectors.

关键词： delay-Doppler domain doubly selective channel OTFS overspread underwater acoustic communications

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How far are we to GPT-4V?Closing the gap to commercial multimodal models with open-source suites

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Science China(information Sciences) 2024年第12期67卷 5-22页

作者： Zhe CHEN Weiyun WANG Hao TIAN Shenglong YE Zhangwei GAO Erfei CUI Wenwen TONG Kongzhi HU Jiapeng LUO Zheng MA Ji MA Jiaqi WANG Xiaoyi DONG Hang YAN Hewei GUO Conghui HE Botian SHI Zhenjiang JIN Chao XU Bin WANG Xingjian WEI Wei LI Wenjian ZHANG Bo ZHANG Pinlong CAI Licheng WEN Xiangchao YAN Min DOU Lewei LU Xizhou ZHU Tong LU Dahua LIN Yu QIAO Jifeng DAI Wenhai WANG State Key Laboratory for Novel Software Technology Nanjing University Shanghai AI Laboratory School of Computer Science Fudan University SenseTime Research Department of Information Engineering The Chinese University of Hong Kong Department of Electronic Engineering Tsinghua University

In this paper, we introduce InternVL 1.5, an open-source multimodal large language model(MLLM) to bridge the capability gap between open-source and proprietary commercial models in multimodal understanding. We introduce three simple improvements.(1) Strong vision encoder: we explored a continuous learning strategy for the large-scale vision foundation model — InternViT-6B, boosting its visual understanding capabilities, and making it can be transferred and reused in different LLMs.(2) Dynamic high-resolution: we divide images into tiles ranging from 1 to 40 of 448×448 pixels according to the aspect ratio and resolution of the input images, which supports up to 4K resolution input.(3) High-quality bilingual dataset: we carefully collected a high-quality bilingual dataset that covers common scenes, document images,and annotated them with English and Chinese question-answer pairs, significantly enhancing performance in optical character recognition(OCR) and Chinese-related tasks. We evaluate InternVL 1.5 through a series of benchmarks and comparative studies. Compared to both open-source and proprietary commercial models, InternVL 1.5 shows competitive performance, achieving state-of-the-art results in 8 of 18 multimodal benchmarks. Code and models are available at https://***/OpenGVLab/InternVL.

关键词： multimodal model open-source vision encoder dynamic resolution bilingual dataset

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Virtual Assembly Collision Detection Algorithm Using Backpropagation Neural Network

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Computers, Materials & Continua 2024年第10期81卷 1085-1100页

作者： Baowei Wang Wen You School of Computer Nanjing University of Information Science and TechnologyCollaborative Innovation Center of Jiangsu Atmospheric Environment and Equipment TechnologyDigital Forensics Engineering Research Center of Digital Forensics Ministry of EducationNanjing210044China School of Software Nanjing University of Information Science and TechnologyNanjing210044China

As computer graphics technology continues to advance,Collision Detection(CD)has emerged as a critical element in fields such as virtual reality,computer graphics,and interactive *** is indispensable for ensuring the fidelity of physical interactions and the realism of virtual environments,particularly within complex scenarios like virtual assembly,where both high precision and real-time responsiveness are *** ongoing developments,current CD techniques often fall short in meeting these stringent requirements,resulting in inefficiencies and inaccuracies that impede the overall performance of virtual assembly *** address these limitations,this study introduces a novel algorithm that leverages the capabilities of a Backpropagation Neural Network(BPNN)to optimize the structural composition of the Hybrid Bounding Volume Tree(HBVT).Through this optimization,the research proposes a refined Hybrid Hierarchical Bounding Box(HHBB)framework,which is specifically designed to enhance the computational efficiency and precision of CD *** HHBB framework strategically reduces the complexity of collision detection computations,thereby enabling more rapid and accurate responses to collision *** experimental validation within virtual assembly environments reveals that the proposed algorithm markedly improves the performance of CD,particularly in handling complex *** optimized HBVT architecture not only accelerates the speed of collision detection but also significantly diminishes error rates,presenting a robust and scalable solution for real-time applications in intricate virtual *** findings suggest that the proposed approach offers a substantial advancement in CD technology,with broad implications for its application in virtual reality,computer graphics,and related fields.

关键词： Collision detection virtual assembly backpropagation neural network real-time interactivity

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Digital Restoration of Historical Buildings by Integrating 3D PC Reconstruction and GAN Algorithm

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Journal of Artificial Intelligence and technology 2024年第2期4卷 179-187页

作者： Tianke Fang Zhenxing Hui William P.Rey Aihua Yang Bin Liu Zhiying Xie School of Information Technology Mapua UniversityManilaPhilippines School of Computing and Information Engineering Xiamen University of TechnologyXiamenChina School of Information Media Zhangzhou Vocational College of Science and TechnologyZhangzhouChina College of Software Engineering Xiamen University of TechnologyXiamenChina

Historical architecture is an important carrier of cultural and historical heritage in a country and region,and its protection and restoration work plays a crucial role in the inheritance of cultural ***,the damage and destruction of buildings urgently need to be repaired due to the ancient age of historical buildings and the influence of natural environment and human ***,an artificial intelligence repair technology based on three-dimensional(3D)point cloud(PC)reconstruction and generative adversarial networks(GANs)was proposed to improve the precision and efficiency of repair ***,in-depth research on the principles and algorithms of 3D PC data processing and GANs should be ***,a digital restoration frameworkwas constructed by combining these two artificial intelligence technologies to achieve precise and efficient restoration of historical buildings through continuous adversarial learning *** experimental results showed that the errors in the restoration of palace buildings,defense walls,pagodas,altars,temples,and mausoleums were 0.17,0.12,0.13,0.11,and 0.09,*** technique can significantly reduce the error while maintaining the high-precision repair *** technology with artificial intelligence as the core has excellent accuracy and stability in the digital *** provides a new technical means for the digital restoration of historical buildings and has important practical significance for the protection of cultural heritage.

关键词： 3D PC reconstruction artificial intelligence repair GAN algorithm stereoscopic vision historical buildings

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Recent Developments in Authentication Schemes Used in Machine-Type Communication Devices in Machine-to-Machine Communication: Issues and Challenges

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Computers, Materials & Continua 2024年第4期79卷 93-115页

作者： Shafi Ullah Sibghat Ullah Bazai Mohammad Imran Qazi Mudassar Ilyas Abid Mehmood Muhammad Asim Saleem Muhmmad Aasim Rafique Arsalan Haider Ilyas Khan Sajid Iqbal Yonis Gulzar Kauser Hameed Department of Computer Engineering Balochistan University of Information TechnologyEngineering and Management SciencesQuetta87300Pakistan Department of Information Technology Balochistan University of Information TechnologyEngineeringand Management SciencesQuetta87300Pakistan Department of Information Systems College of Computer Sciences and Information TechnologyKing Faisal UniversityHofuf in Al-Ahsa31982Saudi Arabia Department of Management Information Systems College of Business AdministrationKing Faisal UniversityHofuf in Al-Ahsa31982Saudi Arabia Department of Software Engineering College of ComputingRiphah International UniversityFaisalabad44000Pakistan Department of Electrical Engineering Balochistan University of Information Technology Engineeringand Management SciencesQuetta87300Pakistan Department of Mathematics College of Science Al-ZulfiMajmaah UniversityAl-Majmaah11952Saudi Arabia

Machine-to-machine (M2M) communication plays a fundamental role in autonomous IoT (Internet of Things)-based infrastructure, a vital part of the fourth industrial revolution. Machine-type communication devices(MTCDs) regularly share extensive data without human intervention while making all types of decisions. Thesedecisions may involve controlling sensitive ventilation systems maintaining uniform temperature, live heartbeatmonitoring, and several different alert systems. Many of these devices simultaneously share data to form anautomated system. The data shared between machine-type communication devices (MTCDs) is prone to risk dueto limited computational power, internal memory, and energy capacity. Therefore, securing the data and devicesbecomes challenging due to factors such as dynamic operational environments, remoteness, harsh conditions,and areas where human physical access is difficult. One of the crucial parts of securing MTCDs and data isauthentication, where each devicemust be verified before data transmission. SeveralM2Mauthentication schemeshave been proposed in the literature, however, the literature lacks a comprehensive overview of current M2Mauthentication techniques and the challenges associated with them. To utilize a suitable authentication schemefor specific scenarios, it is important to understand the challenges associated with it. Therefore, this article fillsthis gap by reviewing the state-of-the-art research on authentication schemes in MTCDs specifically concerningapplication categories, security provisions, and performance efficiency.

关键词： Authentication cyber security internet of things machine-type communication devices machine-to-machine communication

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