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IEEE Transactions on Green Communications and Networking 2024年

作者： Liu, Zhan Liao, Zhiyuan Li, Chunquan Zhang, Zhijun Yu, Junzhi Liu, P.X. Hunan University of Humanities Science and Technology School of Information Loudi417000 China Nanchang University School of Information Engineering Nanchang330031 China Jiangxi Provincial Key Laboratory of Intelligent Systems and Human-Machine Interaction Nanchang330031 China South China University of Technology School of Automation Science and Engineering Guangzhou510640 China Peking University State Key Laboratory for Turbulence and Complex Systems Department of Advanced Manufacturing and Robotics College of Engineering Beijing100871 China Carleton University Department of Systems and Computer Engineering OttawaONK1S 5B6 Canada

In this paper, we investigate the total system energy efficiency (EE) of full-duplex (FD) device-to-device (D2D) communications underlaying distributed antenna systems (DAs), where remote access units (RAUs), D2D users (DUs), and cellular users (CUs) are all capable of FD operation. specifically, we jointly optimize subcarrier assignment and power allocation under the quality of service (Qos) requirements of CUs and DUs and the maximum power constraints of RAUs, CUs, and DUs. In addition, we propose a novel spectrum sharing strategy that allows each subcarrier to be assigned to multiple CUs and/or multiple D2D pairs (DPs) for flexibility. To solve the formulated non-convex optimization problem, we first employ fractional programming to transform the objective function in the optimization problem from the fractional form into the equivalent subtractive form. Then, an efficient iterative resource allocation algorithm is proposed, which needs to solve an inner problem in each iteration. After relaxing the variables and introducing penalty factors, the non-convex inner problem is transformed into a convex problem through the successive convex approximation (sCA) method and solved by iterative algorithm. simulation results demonstrate that the proposed algorithm can considerably improve the system EE compared to other benchmark schemes. Furthermore, the proposed spectrum sharing strategy is superior to the existing sharing strategies. © 2017 IEEE.

关键词： Convex optimization

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Language-based document image retrieval for Trilingual system

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International Journal of Information Technology (singapore) 2020年第4期12卷 1217-1226页

作者： Dixit, Umesh D. shirdhonkar, M.s. Department of Electronics and Communication Engineering B.L.D.E.A’s V. P. Dr. P.G. Halakatti College of Engineering and Technology Vijayapur 586103 India Department of Computer Science and Engineering B.L.D.E.A’s V. P. Dr. P. G. Halakatti College of Engineering and Technology Vijayapur 586103 India

Language-based document image retrieval (LbDIR) is an essential need for a multi-lingual environment. It provides an ease of accessing, searching and browsing of the documents pertaining to a particular language. This paper proposes a method for LbDIR using multi-resolution Histogram of Oriented Gradient (HOG) features. These features are obtained by computing HOG on the sub-bands of Discrete Wavelet Transform. The Canberra distance is used for matching and retrieval of the documents. The proposed scheme is investigated on the three datasets (Dataset1, Dataset2 and Dataset3) consisting of 1437 document images of Kannada, Marathi, Telugu, Hindi and English languages. The objective of this work is to provide an efficient LbDIR for the government and non-government organizations of Karnataka, Maharashtra and Telangana states with the context of the tri-lingual model adopted. An average precision (AP) of 96.2%, 95.4%, 94.6%, 99.4% and 99.6% for Kannada, Marathi, Telugu, Hindi and English language documents is achieved while retrieving top 50 documents with the proposed method. The proposed feature extraction scheme provided promising results compared to existing techniques. © 2019, bharati vidyapeeth's Institute of computer Applications and Management.

关键词： Canberra distance Document image retrieval DWT HOG similarity metric

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Efficient Detection Framework Adaptation for Edge Computing: A Plug-and-play Neural Network Toolbox Enabling Edge Deployment

arXiv

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arXiv 2024年

作者： Wu, Jiaqi Zhang, shihao Chen, simin Wang, Lixu Wang, Zehua Chen, Wei He, Fangyuan Tian, Zijian Yu, F. Richard Leung, victor C.M. Beijing100083 China Department of Electrical and Computer Engineering University of British Columbia Vancouver 2332 Main Mall VancouverBCV6T 1Z4 Canada University of Texas at dallas 800 W Campbell Rd RichardsonTX75080 United States Northwestern University 633 Clark St EvanstonIL60208 United States School of Computer Science and Technology China University of Mining and Technology Jiangsu province Xuzhou221116 China Department of Electrical and Computer Engineering The University of British Columbia Vancouver 2332 Main Mall VancouverBCV6T 1Z4 Canada Department of Systems and Computer Engineering Carleton University OttawaONK1S 5B6 Canada Artificial Intelligence Research Institute Shenzhen MSU-BIT University Shenzhen518172 China College of Computer Science and Software Engineering Shenzhen University Shenzhen528060 China Department of Electrical and Computer Engineering The University of British Columbia VancouverBCV6T 1Z4 Canada College of Applied Science and Technology Beijing Union University Beijing100012 China

Recently, edge computing has emerged as a prevailing paradigm in applying deep learning-based object detection models, offering a promising solution for time-sensitive tasks. However, existing edge object detection faces several challenges: 1) These methods struggle to balance detection precision and model lightweightness. 2) Existing generalized edge-deployment designs offer limited adaptability for object detection. 3) Current works lack real-world evaluation and validation. To address these challenges, we propose the Edge Detection Toolbox (ED-TOOLbOX), which leverages generalizable plug-and-play components to enable edge-site adaptation of object detection models. specifically, we propose a lightweight Reparameterized Dynamic Convolutional Network (Rep-DConvNet) that employs a weighted multi-shape convolutional branch structure to enhance detection performance. Furthermore, ED-TOOLbOX includes a sparse Cross-Attention (sC-A) network that adopts a localized-mapping-assisted self-attention mechanism to facilitate a well-crafted Joint Module in adaptively transferring features for further performance improvement. In real-world implementation and evaluation, we incorporate an Efficient Head into the popular You-Only-Look-Once (YOLO) approach to achieve faster edge model optimization. Moreover, we identify that helmet detection—one of the most representative edge object detection tasks—overlooks band fastening, which introduces potential safety hazards. To address this, we build a Helmet band Detection Dataset (HbDD) and apply an edge object detection model optimized by the ED-TOOLbOX to tackle this real-world task. Extensive experiments validate the effectiveness of components in ED-TOOLbOX. In visual surveillance simulations, ED-TOOLbOX-assisted edge detection models outperform six state-of-the-art methods, enabling real-time and accurate detection. These results demonstrate that our approach offers a superior solution for edge object detection. Copyright © 2024, T

关键词： Deep learning

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sky sentinel: Pioneering Real-Time Facial Recognition in Intelligent Drones

Sky Sentinel: Pioneering Real-Time Facial Recognition in Int...

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smart Electronics and Communication (ICOsEC), International Conference on

作者： L. visalatchi Praveena Anjelin Malathi Eswaran vijayalakshmi K sathish Kumar L. Chinmay Inamdar Department of IT Dr.Umayal Ramanathan College for women Karaikudi Tamil Nadu India Department of CSE B. S. Abdur Rahman Crescent Institute of Science and Technology Kongu Engineering College Perundurai Erode Tamil Nadu India Department of Computational intelligence School of Computing College of Engineering and Technology SRM Institute of Science and Technology Kattankulathur Chennai India SCSE VIT Bhopal University Madhya Pradesh India Department of Computer Science and Engineering VIT Bhopal University Madhya Pradesh India

The goal of this article is to provide a method that makes use of a face recognition-powered unmanned aerial vehicle (UAv). The goal of this approach is to make it easier for law enforcement to identify suspects, track down missing persons, verify identities, and carry out age-based monitoring. A facial recognition system is an electronic tool that uses AI to recognise people by their faces. Identity verification often makes use of facial recognition technologies. The facial features of a picture are analysed in this procedure. This research details the steps required to design, build, and test an unmanned aerial vehicle (UAv) integrated with a camera and face recognition software. The UAv is used as a remote control for a robot equipped with bluetooth technology. The suggested method proves it can adapt to different drone orientations. Drone camera angles in all 37 directions have an accuracy of 99.3 percent, proving this point. Recovery activities, rescue missions, occurrence inquiries, offender assessment, and crowd surveillance are just a few examples of how specialised software may aid law enforcement in their investigative work.

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Learning impact of recent ICT advances based on virtual reality IoT sensors in a metaverse environment

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Measurement: sensors 2023年 27卷

作者： brahma, Mahul Rejula, M. Anline srinivasan, bhavana Kumar, s.N. banu, W. Aisha Malarvizhi, K. Priya, s. sharon Kumar, Abhishek Bath Business School Bath Spa University United Kingdom Department of Computer Application Scott Christian College Tamilnadu Nagercoil India Bangalore India Department of EEE Amal Jyothi College of Engineering Kerala India Department of CSE B.S. Abdur Rahman Crescent Institute of Science and Technology Tamilnadu Chennai India Department of CSE JCT College of Engineering and Technology Tamil Nādu Coimbatore India India

The use of avatars in the Metaverse and virtual reality technology in education is a rapidly developing field that has the potential to revolutionize the way students learn. In the context of the Indian EdTech market, virtual reality could play a significant role in enhancing the learning experience for students, although more research is needed to explore its full *** has already made a significant impact on education, with academic programming, technical instruction, and theoretical concepts being taught through digital platforms. virtual reality has the potential to take this a step further, allowing students to experience immersive and interactive learning environments that simulate real-world ***, as mentioned in the paragraph, there is still limited research on the use of virtual reality in education, particularly in the Indian context. Further studies are needed to assess the effectiveness of this technology and ensure that it can be integrated effectively into the educational ***, the use of virtual reality in education is an exciting development in the ICT industry and has the potential to make a significant impact on the learning experience for students. various non-governmental organizations (NGOs) seek to improve women's lives and provide them with self-sufficiency training. The government is likewise concerned about this issue and has established a number of programs to assist women. Information and communication technology (ICT) is significant in this context. ICT has improved the security, knowledge, education, employability, confidence, and popularity of women. The significance of ICT for the empowerment of women is highlighted in this study. To illuminate the various facets of ICT's impact on society, various examples have been addressed. because of ICT, new generations of women all over the globe have defied all expectations and proven themselves in every aspect of life, even the most complicated and time-consumin

关键词： virtual reality

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Integration of Artificial Intelligence in software Defined Networking Technology through Developing Machine Learning Algorithms

Integration of Artificial Intelligence in Software Defined N...

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Advance Computing and Innovative Technologies in engineering (ICACITE), International Conference on

作者： Lamhot Naibaho Pulkit Raj saxena Kuldeep sharma badria sulaiman Alfurhood L. Pallavi bhasker Pant English Language Education Study Program Faculty of Letters and Languages Christian University of Indonesia College of Computing Science and Information Technology Teer Thanker Mahaveer University Moradabad Uttar Pradesh India Department of Computer Science and Engineering Lovely Professional University Phagwara Jalandhar Punjab India Department of Computer Sciences College of Computer Information Sciences Princess Nourah Bint Abdulrahman University Saudi Arabia CSE B V Raju Institute of Technology Narsapur Telangana India Computer Science & Engineering Graphic Era Deemed to be University Dehradun Uttarakhand India

A future networking design called "software-defined networking" combines network programmability with centralized administration (sDN). Network administration is currently handled by sDN, which, at the regulator, which acts as the cable network processor and divides the data plane into a control plane and a data aircraft. Recent breakthroughs in artificial intelligence (Al) have shown a stronger inclination for the science community to benefit from their ability to give learning capabilities and enhance Indicator. The author of this research provides a comprehensive analysis of initiatives underway to incorporate Al with sDN. The study concluded that the three primary Al thread where scientific research was centered were computer science, conceptual, and fuzzy reasoning systems. The authors of this paper explore the several fields in which these approaches may be used, their potential future applications, and the innovations made possible by the integration of AI-based methods into the sDN paradigm. by choosing the right sDN controller, any large organization may lower network complexity, implementation expenses, and maintenance costs. The focus of this article is software defined networking's benefits and downsides (sDN). Following is a basic explanation of artificial intelligence and a list of some of its most significant applications in sDN.

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super-resolution Radial Fluctuations Enables Polarization-resolved Nonlinear Optical Nanoscopy

arXiv

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arXiv 2025年

作者： Harvey, MacAulay Cisek, Richard Al-Turk, sarry Ruda, Harry E. Kreplak, Laurent Tokarz, Danielle Department of Chemistry Saint Mary’s University 923 Robie Street HalifaxNSB3H 3C3 Canada Centre for Advanced Nanotechnology University of Toronto 170 College Street TorontoONM5S 3E4 Canada Department of Materials Science and Engineering University of Toronto 184 College Street TorontoONM5S 3E4 Canada Department of Electrical and Computer Engineering University of Toronto 10 Kings College Road TorontoONM5S 3G4 Canada Department of Physics and Atmospheric Science School of Biomedical Engineering Dalhousie University HalifaxNSB3H 4J5 Canada

second harmonic generation microscopy (sHG) is a powerful imaging modality which has found applications in investigating both biological and synthetic nanostructures. Like all optical microscopy techniques, the resolution of sHG is limited to approximately half the wavelength of the excitation light. because of this several groups have proposed techniques to enable super-resolution sHG imaging. However, these techniques often involve quite complicated optical setups compared to standard sHG microscopes, a major impediment towards more widespread utilization. Here we apply super-resolution radial fluctuations (sRRF), a commonly used technique for super-resolution fluorescence imaging, to enable super-resolution sHG microscopy. by imaging individual nanostructures, we demonstrate that sRRF can provide resolution enhancement of up to 3× compared to a laser scanning sHG microscope, which is comparable to the best resolution enhancement reported in the literature. Additionally, we show that sRRF maintains the polarization dependence of sHG, therefore enabling super-resolution polarization sHG imaging. Finally, we perform sRRF processing on third harmonic generation images to demonstrate the significant potential of sRRF for other super-resolution nonlinear optical microscopy. Importantly, since sRRF can achieve super-resolution purely through image processing, the technique demonstrated here could be used to enhance the resolution of images obtained using a wide variety of nonlinear optical microscopy setups including both laser scanning and widefield configurations. Copyright © 2025, The Authors. All rights reserved.

关键词： Nonlinear optics

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Performance optimization of hybrid nano-engineered geopolymer binders-based ultra-high-performance concrete

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Nano-structures and Nano-Objects 2025年 42卷

作者： Raut, Jayant M. Pande, Prashant b. Madurwar, Kamlesh v. bahoria, boskey v. bhagat, Rajesh M. Kakade, Niteen T. Karmore, Pravin Y. Pinjarkar, Latika Muley, Manjushree Department of Civil Engineering Yeshwantrao Chavan College of Engineering Maharashtra Nagpur 441110 India Department of Civil Engineering Priyadarshini Bhagwati College of Engineering Maharashtra Nagpur 440024 India Department of Mechanical Engineering Tulsiramji Gaikwad Patil College of Engineering and Technology Maharashtra Nagpur 441108 India Department of Computer Science and Applications Ramdeobaba University Maharashtra Nagpur 440013 India Symbiosis Institute of Technology Nagpur Campus Symbiosis International (Deemed) University Maharashtra Pune 440008 India Department of Mathematics S. B. Jain Institute of Technology Management and Research Maharashtra Nagpur 441501 India

Ultra-high-performance and sustainable construction materials have given the thrust to the development of geopolymer technology. This work presents a nano-engineered geopolymer binder incorporating hybrid nano-reinforcements of nano-silica and graphene oxide at optimized ultrasonication and mechanical milling for improved dispersion and prevention of agglomeration. The resulting specimen exhibits a compressive strength exceeding 120 MPa at 24 h and a water absorption below 3 %. A microwave-assisted novel curing method accelerates geopolymerization, achieving this strength in less than 1 h and a reduction of the curing duration by 70 %. Further employing doped CNTs for structural health sensing has even greater potential, creating a self-sensing system with a gauge factor of over 25. synchrotron XRD analysis supplies information about phase evolution, thus ensuring a crystallinity index greater than 50 %. Molecular dynamics simulations predict robust interactions with bond energies beyond 320 KJ/mol, whereas kinetic modeling optimizes reaction rates of up to 80 % polymerization within 8 h. ballistic Impact testing shows over 50 percent enhancement in impact resistance, proving to be very robust under a severe loading condition. The overall picture created by inter alia superior mechanical properties, durability, self-sensing ability, and environmental benefits (20 % energy saving) should be considered as a paradigm shift for constructions with high performance and sustainability, stretching its applications to aerospace and defenses. © 2025 Elsevier b.v.

关键词： ballistic impact resistances microwave-assisted curing Nano-geopolymer self-sensing materials ultra-high-performance concrete

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Photoalignment and photopatterning of highly concentrated quantum rods embedded in liquid crystal polymer matrix

Photoalignment and photopatterning of highly concentrated qu...

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International Conference on Display Technology, ICDT 2020

作者： Kang, Chengbin Gupta, swadesh K. Prodanov, Maksym F. Gao, Yiyang vashchenko, valerii v. srivastava, Abhishek K. State Key Laboratory of Advanced Displays and Optoelectronics Technologies Department of Electronics and Computer Engineering The Hong Kong University of Science and Technology Hong Kong Department of Physics D B S College Kanpur Uttar Pradesh India

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Query-Efficient Adversarial Attack Against vertical Federated Graph Learning

arXiv

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arXiv 2024年

作者： Chen, Jinyin Mu, Wenbo Zhang, Luxin Huang, Guohan Zheng, Haibin Cheng, Yao The Institute of Cyberspace Security The College of Information Engineering Zhejiang University of Technology Hangzhou310023 China The College of Information Engineering Zhejiang University of Technology Hangzhou310023 China National Key Laboratory of Electromagnetic Space Security Jiaxing China The College of Computer Science and Technology The Institute of Cyberspace Security Zhejiang University of Technology Hangzhou310023 China The Digital Service TÜV SÜD Asia Pacific Pte. Ltd. 609937 Singapore

Graph neural network (GNN) has captured wide attention due to its capability of graph representation learning for graph-structured data. However, the distributed data silos limit the performance of GNN. vertical federated learning (vFL), an emerging technique to process distributed data, successfully makes GNN possible to handle the distributed graph-structured data. Despite the prosperous development of vertical federated graph learning (vFGL), the robustness of vFGL against the adversarial attack has not been explored yet. Although numerous adversarial attacks against centralized GNNs are proposed, their attack performance is challenged in the vFGL scenario. To the best of our knowledge, this is the first work to explore the adversarial attack against vFGL. A query-efficient hybrid adversarial attack framework is proposed to significantly improve the centralized adversarial attacks against vFGL, denoted as NA2, short for Neuron-based Adversarial Attack. specifically, a malicious client manipulates its local training data to improve its contribution in a stealthy fashion. Then a shadow model is established based on the manipulated data to simulate the behavior of the server model in vFGL. As a result, the shadow model can improve the attack success rate of various centralized attacks with a few queries. Extensive experiments on five real-world benchmarks demonstrate that NA2 improves the performance of the centralized adversarial attacks against vFGL, achieving state-of-the-art performance even under potential adaptive defense where the defender knows the attack method. Additionally, we provide interpretable experiments of the effectiveness of NA2 via sensitive neurons identification and visualization of t-sNE. The code and datasets are available at https://***/hgh0545/NA2. Copyright © 2024, The Authors. All rights reserved.

关键词： Adversarial machine learning

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