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1st International Conference on Emerging Technologies for Dependable Internet of Things, ICETI 2024

作者： Mohammed, Awadh Ali Abdo Obaid, Abdulrahman Mohammed Hussein Alsabry, Ayman Filist Sergey, A. Alhaj, Yousif A. Department of Biomedical Engineering 21 September University of Medical and Applied Sciences Sana’a University Sana’a Yemen Department of Information Technology 21 September University of Medical and Applied Sciences Sana’a Yemen Department of Computer Science International University of Technology Twintech Sana’a Yemen Department of Biomedical Engineering Southwest State University Kursk Russia

ISBN: (纸本)9798331533557

The development of telemedicine technology indicates a shift in access to healthcare services and patients’ desire for more convenient healthcare makes it a key tool in healthcare delivery. However, the process of transmitting and processing data with a high level of speed, security, privacy, performance, and reliability is an issue of utmost importance. Recently, researchers have focused on the quantum internet, which represents the pinnacle of technological progress, opens up new horizons and forms a fundamental pillar in improving the quality of healthcare services and providing healthcare constantly. This research aims to explore the impact of the quantum internet on the functions, processes, and applications of telemedicine technology. The importance of this topic is to reshape the ways of interaction with healthcare. By exploring this impact, the improvements brought by integrating of quantum internet with telemedicine technologies are highlighted to ensure the speed of transmission, processing, security of medical information, and data exchange. The results show the quantum internet improves processes, functions, and applications of telemedicine technology to provide medical services at quantum speed. Finally, the authors discuss the integration challenges of quantum internet with telemedicine technology to provide researchers with a wide area of research. © 2024 IEEE.

关键词： Telemedicine

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A Comprehensive Review Analysis of Image Similarity Detection Techniques in Deep Learning to Detect the Image Plagiarism

A Comprehensive Review Analysis of Image Similarity Detectio...

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2024 International Conference on Artificial Intelligence and Emerging Technology, Global AI Summit 2024

作者： Naudiyal, Anjali Singh, Vineeta Rastogi, Ritesh Joshi, Kapil Kumar, Amit School of Applied and Life Sciences Uttaranchal University Premnagar Dehradun India Chhatrapati Shahu Ji Maharaj University Department of Computer Science and Engineering Kalyanpur Uttar Pradesh U.P. Kanpur208024 India Noida Institute of Engineering and Technology Department of Computer Science Greater Noida India Uttaranchal University Department of Computer Science & Engineering Premnagar Dehradun India Graphic Era deemed to be university Dehradun India

ISBN: (纸本)9798350379716

The proliferation of images on the internet in the era of artificial intelligence has increased the risk of image plagiarism. Image plagiarism is the most serious problem in the field of research. Using artificial intelligence (AI) tools, writers and scholars now modify text, codes, and images. While these artificial intelligence systems have certain advantages, the writers gain more in the research domain. Machine learning includes deep learning, while artificial intelligence includes machine learning. The majority of Deep Learning's attention is directed towards images with several characteristics. Deep learning uses a variety of techniques to process images. Once image plagiarism has been found in a document with the help of plagiarism detection tools, it should be eliminated. In order to make the Internet of Things more environmentally friendly, plagiarism must also be found and eliminated. Finding plagiarism in the source code is also a difficult task. In the presented paper, various methods of similarity detection are discussed and compared in order to determine which method of image similarity detection is most effective in detecting plagiarism in images or in the text of images. If the similarity index between the images is lower, then there is a greater likelihood of plagiarism. Different types of distances are calculated in order to check the image similarity. These methods are also used to check the similarity index with their accuracy. Anyone is able to select the most accurate and user-friendly Deep Learning method for image similarity with ease after going over all of the available ways for detecting image plagiarism. © 2024 IEEE.

关键词： Contrastive Learning

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Anomaly detection using deep learning approach for IoT smart city applications

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Multimedia Tools and Applications 2025年第17期84卷 17929-17949页

作者： Shibu, S. Kirubakaran, S. Remamany, Krishna Priya Ahamed, Suhail Chitra, L. Kshirsagar, Pravin R. Tirth, Vineet Department of Electronics and Communication Engineering Panimalar Engineering College Tamil Nadu Chennai600123 India Department of Computer Science and Engineering CMR College of Engineering and Technology Telangana Hyderabad501401 India Engineering Department College of Engineereing and Technology University of Technology an Applied Sciences PC Musandam811 Oman Machine Learning Software Engineer Paragon Semvox GmbH Saarland Kirkel Germany Department of Electrical and Electronics Engineering Aarupadai Veedu Institute of Technology Vinayaka Missions Research Foundation Tamil Nadu Chennai603104 India Department of Electronics & Telecommunication Engineering J D College of Engineering & Management Maharashtra Nagpur India Department of Mechanical Engineering College of Engineering King Khalid University Asir Abha61421 Saudi Arabia

With the advancements of IoT devices, many smart applications start to rule this era. In particular, smart cities has been adapted and realized by many countries around the world. In smart cities, vas amount of data is generated at every second. This vast data need a transmission medium which could be wireless standard. However, security is the main concern in such applications since the smart transmission always binds with anomalies. The existing anomaly detection systems need improvement in accuracy due to inefficient feature extraction and selection procedure. This paper proposes an accurate anomaly detection technique that built upon deep learning approach. We proposed a Combined Deep Q-Learning (CDQL) algorithm for anomaly detection. Priory, optimal features are selected by using Spider Monkey Optimizer (SMO). With the optimal features, CDQL detects anomalies accurately. In addition, the CDQL algorithm learns the environment in order to monitor the network data continuously. This continuous monitoring and optimum features helps in accuracy improvement up to 98%. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Reinforcement learning

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Learning-based model using unpaired datasets for super-resolution confocal microscopy

Learning-based model using unpaired datasets for super-resol...

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3D Image Acquisition and Display: Technology, Perception and Applications, 3D 2024 - Part of Optica Imaging Congress

作者： Trujillo, Carlos Thompson, Lauren Skalli, Omar Doblas, Ana Applied optics group School of Applied Science and Engineering Universidad EAFIT Medellín Colombia Department of Biological Sciences University of Memphis MemphisTN38152 United States Department of Electrical and Computer Engineering University of Massachusetts DartmouthMA02747 United States

One of the major drawbacks of confocal microscopy is its limited spatial resolution. This work assesses the performance of an unpaired learning-based model to provide confocal images with improved resolution. © 2... 详细信息

关键词： Confocal microscopy

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Analysis and design of general bridge crane structure using CAD technology

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computer-Aided Design and Applications 2022年第S2期19卷 15-25页

作者： Chang, Xinzhong Sharma, Amit Henan Vocational College of Applied Technology Henan Zhengzhou450042 China Department of Computer Science and Engineering Chitkara University Punjab India

In order to reduce the workload of mechanical designers, this paper takes the general bridge crane as an example. Based on the traditional design mode, the parametric technology such as CAD technology, CAE technology and other design methods are tested. The aim of this study is to reduce the complex calculation and heavy workload of the bridge structure;therefore the secondary development is carried out with C programming language. This paper introduces the function of each step and the related functions. Through the case analysis of bridge structure, combined with the traditional structure design theory, the analysis results are compared. The experimental results show that the software realizes the functions of structural design, parametric modeling, parametric automatic assembly and parametric finite element analysis. © 2022 CAD Solutions, LLC.

关键词： C (programming language)

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Optimization of Bowl Feeders Structure for Arbitrary Parts with Machine Learning 8

Optimization of Bowl Feeders Structure for Arbitrary Parts w...

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8th International Conference on Smart and Sustainable Technologies, SpliTech 2023

作者： Hensel, Stefan Marinov, Marin Fischer, Jeremy Offenburg Germany Technical University of Sofia Department of Electronics Sofia Bulgaria University of Applied Sciences Department of Electrical Engineering and Computer Science Offenburg Germany

ISBN: (纸本)9789532901283

Modern industrial production is heavily dependent on efficient workflow processes and automation. The steady flow of raw materials as well as the separation of vital parts and semi-finished products are at the core of these automated procedures. Commonly used systems for this work are bowl feeders, which separate the parts and material by a combination of mechanical vibration and friction. The production of these tools, especially the design of the ramping spiral, is delicate and time-consuming work, as the shape, slope, and material must be carefully adjusted for the corresponding parts. In this work, we propose an automated approach, making use of optimization procedures from artificial intelligence, to design the spiral ramps of the bowl feeders. Therefore, the whole system and considered parts are physically simulated and the optimized geometry is subsequently exported into a CAD system for the actual building, respectively printing. The employment of evolutionary optimization gives the need to develop a mathematical model for the whole setup and find an efficient representation of integral features. © 2023 University of Split, FESB.

关键词： Optimization

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Prescribing Decision Conservativeness in Two-Stage Power Markets: A Distributionally Robust End-to-End Approach 59

Prescribing Decision Conservativeness in Two-Stage Power Mar...

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59th Annual Conference on Information sciences and Systems, CISS 2025

作者： Liang, Zhirui Li, Qi Liu, Anqi Dvorkin, Yury Johns Hopkins University Department of Applied Mathematics and Statistics BaltimoreMD United States Johns Hopkins University Department of Computer Science BaltimoreMD United States Johns Hopkins University Department of Electrical and Computer Engineering BaltimoreMD United States Johns Hopkins University Department of Civil and System Engineering BaltimoreMD United States

ISBN: (纸本)9798331513269

This paper presents an end-to-end framework for calibrating wind power forecast models to minimize operational costs in two-stage power markets, where the first stage involves a distributionally robust optimal power flow (DR-OPF) model. Unlike traditional methods that adjust forecast parameters and uncertainty quantification (UQ) separately, this framework jointly optimizes both the forecast model parameters and the decision conservativeness, which determines the size of the ambiguity set in the DR-OPF model. The framework aligns UQ with actual uncertainty realizations by directly optimizing downstream operational costs, a process referred to as cost-oriented calibration. The calibration is achieved using a gradient descent approach. To enable efficient differentiation, the DR-OPF problem is reformulated into a convex form, and the Envelope Theorem is leveraged to simplify gradient derivation in the two-stage setting. Additionally, the framework supports distributed implementation, effectively reducing computational overhead and enhancing efficiency. By proactively calibrating forecast parameters and prescribing optimal decision conservativeness, the framework significantly enhances cost efficiency and reliability in power system operations. Numerical experiments on an IEEE 5-bus system demonstrate the effectiveness and efficiency of the proposed approach. © 2025 IEEE.

关键词： Wind forecasting

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Single-bit full adder and logic gate based on synthetic antiferromagnetic bilayer skyrmions

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Rare Metals 2022年第7期41卷 2249-2258页

作者： Kai Yu Mak Jing Xia Xi-Chao Zhang Li Li Mouad Fattouhi Motohiko Ezawa Xiao-Xi Liu Yan Zhou School of Science and Engineering The Chinese University of Hong KongShenzhen 518172China College of Physics and Electronic Engineering Sichuan Normal UniversityChengdu 610068China Department of Electrical and Computer Engineering Shinshu UniversityNagano 380-8553Japan Department of Applied Physics University of SalamancaSalamanca 37008Spain Department of Applied Physics University of TokyoTokyo 113-8656Japan

Skyrmion-based devices are promising candi-dates for non-volatile memory and low-delay time *** skyrmion-based devices execute operation by controlling skyrmion trajectory,which can be impeded by the skyrmion Hall ***,the design of skyrmion-based arithmetic devices built on synthetic antiferromag-netic(SyAF)structures is presented,where the structure can greatly suppress skyrmion Hall *** this study,the operations of skyrmion-based half adder,full adder,and XOR logic gate are executed by introducing geometric notches and tilted edges,which can annihilate or diverge *** of these skyrmion-based devices is evaluated,where the delay time and energy-delay product of the single-bit full adder are 1.95 ns and 2.50×10^(-22)Js,which are only 12%and 79%those of the previously proposed skyrmion-based single-bit full *** improvement is significant in the construction of ripple-carry adder and ripple-carry ***,our skyrmion-based SyAF arithmetic device is a promising candidate to develop high-speed spintronic devices.

关键词： Skyrmion Full adder Synthetic antiferromagnet Lowdelaytime electronics Micromagnets

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Complex-frequency waves:beat loss and win sensitivity

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Light(science & Applications) 2024年第2期13卷 181-183页

作者： Qingqing Cheng Tao L School of Optical-Electrical and Computer Engineering University of Shanghai for Science and TechnologyShanghai200093China Department of Respiratory Diseases and Critical Medicine Quzhou Hospital Affiliated to Wenzhou Medical UniversityQuzhou324000China National Laboratory of Solid State Microstructures College of Engineering and Applied SciencesNanjing UniversityNanjing210093China

Recent experiments have demonstrated that synthesized complex-frequency waves can impart a virtual gain to molecule sensing systems,which can effectively restore information lost due to intrinsic molecular *** enhancement notably amplifies the signal of trace molecular vibrational fingerprints,thereby substantially improving the upper limit of sensitivity.

关键词： thereby Complex limit

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Classification of Real and Deepfakes Visual Samples with Pre-trained Deep Learning Models 7th

Classification of Real and Deepfakes Visual Samples with Pre...

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Proceedings of the 7th International Conference on Advances in Computing and Data sciences, ICACDS 2023

作者： Nawaz, Marriam Javed, Ali Nazir, Tahira Khan, Muhammad Attique Rajinikanth, Venkatesan Kadry, Seifedine Department of Software Engineering UET Taxila Taxila47050 Pakistan Department of Computing Riphah International University Islamabad Pakistan Department of Computer Science HITEC University Taxila Pakistan Department of Computer Science and Engineering Division of Research and Innovation Saveetha School of Engineering SIMATS Chennai602105 India Department of Applied Data Science Noroff University College Kristiansand4612 Norway Department of Electrical and Computer Engineering Lebanese American University Byblos Lebanon

ISBN: (纸本)9783031379390

Serious security and privacy problems have arisen as a result of significant advancements in the creation of deepfakes. Attackers can easily replace a person’s face with the target person’s face in an image using sophisticated Deep learning (DL) algorithms to spoof their identity. Deepfakes detection algorithms have been proposed in response to the growing concerns about the potential harm caused by deepfakes. However, a reliable deepfakes detector that can keep up with contemporary deepfakes creation techniques is required. In this work, we have proposed an end-to-end methodology for detecting manipulated visual content. We used multiple CNN models i.e., ResNet18, ResNet50, DenseNet65, DenseNet77, and DenseNet100 along with the SVM classifier to compute effective cues from the input facial faces to distinguish between actual and altered content. We have also applied the concept of transfer learning to solve the issue of model over-fitting and improve generalizability against different manipulation algorithms. A comparison study is carried out to evaluate the performance of several feature extractors. Through thorough experiments performed using the Deepfakes Detection Challenge dataset, our results demonstrated that DenseNet100 surpasses the other CNN models by better recognizing deepfakes. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Learning algorithms

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