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Exploring Potential Barrier Estimation Mechanism Based on Quantum Dynamics Framework

Chinese Journal of Electronics 2025年第1期34卷 350-364页

作者： Quan Tang Peng Wang Chengdu Institution of Computer Application Chinese Academy of Science University of Chinese Academy of Sciences School of Computer Science and Engineering Southwest Minzu University

Due to the probability characteristics of quantum mechanism, the combination of quantum mechanism and intelligent algorithm has received wide attention. Quantum dynamics theory uses the Schr?dinger equation as a quantum dynamics equation. Through three approximation of the objective function, quantum dynamics framework(QDF) is obtained which describes basic iterative operations of optimization algorithms. Based on QDF, this paper proposes a potential barrier estimation(PBE) method which originates from quantum mechanism. With the proposed method, the particle can accept inferior solutions during the sampling process according to a probability which is subject to the quantum tunneling effect, to improve the global search capacity of optimization *** effectiveness of the proposed method in the ability of escaping local minima was thoroughly investigated through double well function(DWF), and experiments on two benchmark functions sets show that this method significantly improves the optimization performance of high dimensional complex functions. The PBE method is quantized and easily transplanted to other algorithms to achieve high performance in the future.

关键词： Potential energy Electric potential Shape Heuristic algorithms Estimation Tunneling Linear programming Approximation algorithms Iterative algorithms Optimization

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Adaptive coupled-sliding-variable-based finite-time control of composite formation for multi-robot systems

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science China(Information sciences) 2024年第10期67卷 244-260页

作者： Xinru MA Hengyu LI Jun LIU Yueying WANG Shaorong XIE Jun LUO School of Mechatronic Engineering and Automation Shanghai University School of Mathematics and Computer Application Technology Jining University School of Computer Science Shanghai University College of Mechanical and Vehicle Engineering Chongqing University

This paper focuses on the finite-time control(FTC) of the composite formation consensus(CFC)problems for multi-robot systems(MRSs). The CFC problems are firstly proposed for MRSs under the complex network topology of cooperative or cooperative-competitive networks. Regarding the problems of FTC and CFC on multiple Lagrange systems(MLSs), coupled sliding variables are introduced to deal with the robustness and consistent convergence. Then, the adaptive finite-time protocols are given based on the displacement approaches. With the premised FTC, tender-tracking methods are further developed for the problems of tracking information disparity. Stability analyses of those MLSs mentioned above are clarified with Lyapunov candidates considering the coupled sliding vectors, which provide new verification for tender-tracking systems. Under the given coupled-sliding-variable-based finite-time protocols, MLSs distributively adjust the local formation error to achieve global CFC and perform uniform convergence in time-varying tracking. Finally, simulation experiments are conducted while providing practical solutions for the theoretical results.

关键词： composite formation time-vary tracking information disparity tender-tracking finite-time control nonlinear robots complex networks symmetry consensus

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Proposing a digital twin-based sustainable water governance system for rural Indian villages

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International Journal of Information Technology (Singapore) 2025年第3期17卷 1777-1783页

作者： Singh, Dineshkumar Sharma, Vishnu Department of Computer Science and Engineering Faculty of Computer Science & Engineering (FCE) Poornima University Jaipur India Department of Computer Science and Application Faculty of Computer Science & Engineering (FCE) Poornima University Jaipur India

A sustainably governed water-ecosystem at village-level is crucial for the community's well-being. It requires understanding natures’ limits to store and yield water and balance it with the stakeholders’ needs, in the context of population growth, climate change, and unsustainable agricultural practices. Maharashtra villages like Randullabad and Karanjkhop are impacted by limited groundwater availability due to the geological structure of the Deccan Traps basaltic rock formation and are recharged by the most rainfall during the monsoon season. Traditional water management practices are inadequate, with old wells causing conflicts among villagers due to fluctuating water levels. In order to achieve a sustainable water system for rural Indian villages, this paper proposes a Digital Twin-Based Water Governance System (DToWGS) with the aim of balancing nature's boundaries with stakeholders' interests to provide real-time water insights, encourage community engagement, transparency in water allocation and decision-making, and promote sustainable practices. These measured indicators can potentially link local governance outcomes to global goals like Viksit Bharat 2047 and UN Sustainable Development Goal 6 (SDG 6). © Bharati Vidyapeeth's Institute of computer applications and Management 2025.

关键词： Digital twin Empathy map Remote sensing SDG6 Stakeholders Village water environment

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application of adaptive guard channel reservation under hard handoff constraint in wireless cellular network

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International Journal of Wireless and Mobile Computing 2025年第2期28卷 170-185页

作者： Sahu, Promod Kumar Pati, Hemanta Kumar Pradha, Sateesh Kumar Department of Computer Science and Application Utkal University Vani Vihar Odisha Bhubaneswar India Department of Computer Science and Engineering International Institute of Information Technology Bhubaneswar Odisha Bhubaneswar India

Voice is the king of communication in wireless cellular network (WCN). Again, WCNs provide two types of calls, i.e., new call (NC) and handoff call (HC). Generally, HCs have higher priority than NCs because call dropping gives negative impact to users as compared to call blocking. So, to handle this problem some channels are reserved for HCs. If more channels are reserved for HCs, then handoff call dropping probability (HCDP) decreases at the same time as new call blocking probability (NCBP) increases;if fewer channels are reserved for HCs, HCDP increases and NCBP decreases. If channels are reserved for HCs by considering target HCDP then HCDP will be below the target and NCBP will be minimum for that target. So, keeping this in mind in this paper, we propose a mathematical model that estimates optimal number of guard channels (GCs) for HCs by considering target HCDP and keeping NCBP minimum. The mathematical model proposed assume static traffic parameters. However, in reality, the user traffic is dynamic and usually inherited through its testbed implementation. To obtain optimal performance we propose an adaptive GC reservation scheme by considering hard handoff constraint while implementing this model through testbed. Finally, we have verified testbed results with those of the model-based approach applying the parameters of different Global System for Mobile Communication (GSM) standards to evaluate its applicability to real systems. Copyright © 2025 Inderscience Enterprises Ltd.

关键词： Testbeds

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A Collaborative Framework for Intrusion Detection in Cloud Computing Based on HLA-CNN-BiLSTM-SVM Model

A Collaborative Framework for Intrusion Detection in Cloud C...

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2024 Asian Conference on Intelligent Technologies, ACOIT 2024

作者： Mogal, Amit K. Sonaje, Vaibhav P. Department of Computer Science & Application School of Computer Science and Engineering Sandip University Nashik India

ISBN: (纸本)9798350374933

In addition to describing a way to make better use of preexisting computer infrastructures, the phrase "cloud computing" describes a technology that facilitates the sale of access to shared computer resources and services. The flip side is that these dispersed and convoluted infrastructures are attractive targets for attackers. Because cyberattacks can reduce the quality of service offered to clients, the system constitute a substantial risk. This proposed method consists of three steps like preprocessing, feature selection, and model training. Data preprocessing, which includes both feature discretization and feature normalization, is a critical step in any knowledge discovery process. In this proposed to evaluate the impact of feature selection on improving classifier algorithm accuracy by comparing two feature selection methods: one that takes linear correlation into account, and another that takes mutual information into account. When training the model, an HLA-CNN-BiLSTM-SVM was utilized. With a 92.35 percent average accuracy, the suggested method surpasses CNN-SVM and BiLSTM. © 2024 IEEE.

关键词： Network intrusion

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Automatic Image Acquisition and Matching in Control System of Near-Field Beam Shaping 8

Automatic Image Acquisition and Matching in Control System o...

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8th International Symposium on computer science and Intelligent Control, ISCSIC 2024

作者： Li, Suicheng Shen, Wenwen He, Zizhou Zhou, Chen Li, Li Luo, Jun Institute of Computer Application Caep Department of Computer Engineering and Science Mianyang China

ISBN: (纸本)9798350380286

In the high power laser system of inertial Confinement fusion (ICF), in order to improve the safe operation flux of the system, near-field beam shaping is necessary to output the laser beam with uniform and smooth intensity distribution. Therefore, how to use optical control systems to automatically and efficiently accomplish near-field beamforming is an important issue. The optical control system based on liquid crystal spatial light modulator can control the beam shape and intensity distribution in real time. The control system of near-field beam shaping algorithm mainly includes the modules of light path control, image loading on liquid crystal spatial light modulator, Charge Coupled Device (CCD) nearfield light spot perception and image processing. There is a lot of data exchange between those modules. In the laser system, the manual operation mainly involves two parts: one is the interaction and data exchange between different modules. In the past work, the image data is collected by the operator on different devices, and then the compensation image is calculated on the computing device, and finally loaded into the display device. The whole process is complex, tedious and repetitive. The other is the image matching of input image on spatial light modulator and near-field light spot. This work requires staff to manually match feature points on computing equipment, and the accuracy of matching is difficult to guarantee, which is very time-consuming and labor-intensive. This paper will address the above problems and propose a distributed network architecture to connect different devices in near-field beam shaping and carry out image acquisition from them. In addition, a new image matching algorithm is proposed to extract and match the feature points of input image on spatial light modulator and near-field light spot. It enables the compensation algorithm to be completed automatically to avoid manual operation. © 2024 IEEE.

关键词： Light modulators

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Optimized graph transformer with molecule attention network based multi class attack detection framework for enhancing privacy and security in WSN

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Multimedia Tools and applications 2025年第15期84卷 14273-14304页

作者： Anoop, M. Mary, L. William Wilson, Allan J. Kiran, W.S. Department of Computer Science and Application SRM Institute of Science and Technology Ramapuram campus Chennai600089 India Department of Electronics and Communication Engineering Amrita College of Engineering and Technology Nagercoil India

In today's rapidly evolving network landscape, cybersecurity has become increasingly crucial. However, wireless sensor networks face unique challenges due to their limited resources and diverse composition, high computational demands, diminished accuracy rates, making them susceptible to a wide array of cyber threats. To tackle these challenges, this research introduced a novel method known as Optimized Graph Transformer with Molecule Attention Network (OGTMAN) on the fusion of Secure Multi-party Computation (SMC) and differential privacy aimed at enhancing privacy and security. This approach starts with data preprocessing, employing min–max normalization to address dataset imbalances. N-Tuple Contrastive Learning with Generative transformer(N-TCLG)feature extractor distinguish between different classes of data instances and effectively learns representations that capture relevant information about network traffic patterns Further, feature selection by enhanced chi-square statistics with kepler algorithm, is utilized to assess the significance of each feature in characteristic between normal network behavior and malicious activities further refines the feature selection method by optimizing the selection criteria based on the statistical properties of the dataset. Finally, the proposed OGTMAN classifies various attacks based on their behavioural patterns with the help of enhanced ant aphid optimization with adaptive step factor. Ultimately, this fine-tuning yield superior model training outcomes, resulting more accurate attack classification outcomes. To evaluate the effectiveness of this approach, datasets encompassing with KDD Cup 99 datasets are employed. The efficiency of the introduced method is demonstrated when compared with prevailing attack detection methods in terms of accuracy, recall, precision and F-measure of 99.98%, 99.5%.,99.9% and 99.5% respectively. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer N

关键词： Molecules

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Integrated fuzzy-based gamma adaptive for image enhancement with color attenuation prior

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Multimedia Tools and applications 2025年第12期84卷 11249-11267页

作者： Harne, Sachin Choubey, Siddhartha Choubey, Abha Department of Computer Application Shri Shankaracharya Group of Institution Chhattisgarh Bhilai India Department of Computer Science and Engineering Shri Shankaracharya Group of Institution Chhattisgarh Bhilai India

Images Quality in the Transportation industry is considered the most significant term and gains more attention among the higher authorities and researchers. Therefore, the accuracy level of the image has been evaluated with IQA (Image Quality Assessment). Most images are substantially affected by ambient lights that affect the quality of the image. In the existing research, the HVS (Human Visual System) has been utilized in order to identify the quality of images that occurred in both night and day time that affects the loss of luminance and information. In the current research, we proposed an integrated fuzzy-based Gamma Adaptive enhanced with Color Attenuation prior (IFGECAP) techniques that help capture the image's local characteristics. Eventually, the performance evaluation of the image whereas both input and output, has been evaluated with Natural image quality evaluator (NIQE), Blind/Reference less Image Spatial Quality Evaluator (BRISQUE), structural similarity index measure (SSIM), Signal-to-noise ratio (SNR), and Peak signal-to-noise ratio (PSNR). Hence, the fog removal will be classified as seasonal, such as rainy and foggy, utilizing CNN—Convolutional Neural Network. The proposed hybrid technique—IFGECAP, procured an efficient result when compared with the existing techniques. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Signal to noise ratio

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An Analytical Survey on Credit Scoring Mechanism in India 2nd

An Analytical Survey on Credit Scoring Mechanism in India

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2nd International Conference on Cyber Intelligence and Information Retrieval, CIIR 2023

作者： Bhowmik, Ankan Basu, Arkajyoti Basu, Arittra Paul, Anish Roy, Atrri Department of Computer Application and Science Institute of Engineering and Management Kolkata India

ISBN: (纸本)9789819735938

Credit score is an important indicator to lenders of your capability to repay loans. A consumer's creditworthiness is indicated by a number between 300 and 850 called a credit score. The advanced the score, the better a borrower looks to implicit lenders. It is predicated on data gathered from lenders and is consolidated in the Credit Information Report or CIR. This paper reviews to check one’s report regularly, also helps you to identify any disagreement that may be lowered your score, and helps to recover the lower score to advanced situations score. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Credit ratings Credit score Loan Net profit

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Skin Lesion Segmentation Using Deep Learning 2nd

Skin Lesion Segmentation Using Deep Learning

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2nd International Conference on Cyber Intelligence and Information Retrieval, CIIR 2023

作者： Sarkar, Kaustav Haralalka, Varun Shaw, Vishal Singh, Rishav Raj Jaiswal, Rayirth Pramanick, Tridip Department of Computer Application and Science Institute of Engineering and Management Kolkata India

ISBN: (纸本)9789819735938

Dermoscopic image analysis has gained significant importance for dermatological applications due to its potential in eliminating observer bias. Segmenting lesion areas automatically in these images is crucial for expedited disease diagnosis. In this study, an innovative deep learning-based approach for precise lesion delineation has been proposed. Leveraging a deep convolutional neural network, where input images are included after appropriate preprocessing. Pedro Hispano Hospital (PH2) 2013 dataset has been employed, comprising dermoscopic images and lesion binary masks as ground truth for evaluation. The approach uses the SegNet architecture, which achieves remarkable accuracy of 99.14%, surpassing benchmark standards (DC 96.94, JI 99.11).This research offers a promising solution for automated lesion segmentation in dermoscopic images, advancing the field of medical image analysis. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Image analysis

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