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2nd International Conference on Computational Intelligence, Communication technology and Networking, CICTN 2025

作者： Patni, Jagdish Chandra Naik, S. Vinay Harika, K. Bahadure, Nilesh Bhaskarrao Verma, Kamal Kant Dept. of CSE Alliance School of Advanced Computing Alliance University Bengaluru India Department of Computer Science and Engineering School of Technology GSFC University Gujarat Vadodara India School of Computer Science IILM University Greater Noida India

ISBN: (纸本)9798331530389

Natural language processing (NLP) methods can be used to identify phishing websites in addition to static and dynamic features. Phishing sites frequently include certain phrases, misspellings, or misleading text patterns in their material, as well as other visual cues and language that match those of authentic websites. Through the examination of textual components such anchor texts, meta-descriptions, and homepage titles. The proposed model is able to comprehend the linguistic traits that are frequently seen in phishing websites using NLP-based features like sentiment analysis, keyword matching, and phrase frequency to increase model's sensitivity. In addition, we use real-time URL parsing to detect possible dangers as users come across them, guaranteeing prompt notifications and lowering the possibility that phishing attempts would be successful. Our study emphasizes how crucial it is to keep improving and upgrading phishing detection models because attackers usually change their strategies. © 2025 IEEE.

关键词： Phishing

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Resolving Attached USBs: Analysis of Windows 11 Artifacts 2

Resolving Attached USBs: Analysis of Windows 11 Artifacts

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2nd International Conference for Advancement in technology, ICONAT 2023

作者： Budhrani, Akash Singh, Upasna Singh, Bhupendra Defence Institute of Advanced Technology School of Computer Engineering and Mathematical Science Pune India Indian Institute of Information Technology Computer Science and Engineering Department Pune India

ISBN: (纸本)9781665475174

The Windows Operating System is known for its convenience which tends to breed more and more user information in form of Artifacts. Artifacts are important repository of potential evidence while conducting any computer investigation. This paper thus provides an analysis of artifacts that will bring out the inside of USB devices attached or mounted on a particular system. Moreover, this paper will parse the data out into usable information and helps to interpret the findings of forensic examiner. In this work, Image file of the suspected system has been exported from the system for further analysis to bring out relevant information. © 2023 IEEE.

关键词： Windows operating system

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Efficient On-Chip Waveguide Characterization Using Image Processing Algorithm in Optical Lithography 22

Efficient On-Chip Waveguide Characterization Using Image Pro...

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22nd International Conference on Optical Communications and Networks, ICOCN 2024

作者： Huang, Quankeng Jiang, Wenchao Huang, Quandong School of Computer Science and Technology Guangdong University of Technology Guangzhou China Institute of Advanced Photonics Technology School of Information Engineering Guangdong University of Technology Guangzhou China

We demonstrate an image processing algorithm for fast measuring waveguide chip dimensions during the optical lithography processing as an assistant tool for adjusting the fabrication parameters and improving the yield... 详细信息

ISBN: (纸本)9798350367652

关键词： Image enhancement

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MEVTR: A Multilingual Model Enhanced With Visual Text Representations 30

MEVTR: A Multilingual Model Enhanced With Visual Text Repres...

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Joint 30th International Conference on Computational Linguistics and 14th International Conference on Language Resources and Evaluation, LREC-COLING 2024

作者： Wang, Xiaohua Fei, Wenlong Hu, Min Zhang, Qingyu Zhu, Aoqiang School of Computer Science and Information Engineering HeFei University of Technology China Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine China

ISBN: (纸本)9782493814104

The goal of multilingual modelling is to generate multilingual text representations for various downstream tasks in different languages. However, some state-of-the-art pre-trained multilingual models perform poorly on many low-resource languages due to the lack of representation space and model capacity. To alleviate this issue, we propose a Multilingual model Enhanced with Visual Text Representations (MEVTR), which complements textual representations and extends the multilingual representation space with visual text representations. First, the visual encoder focuses on the glyphs and structure of the text to obtain visual text representations, and the textual encoder obtains textual representations. Then, multilingual representations are enhanced by aligning and fusing visual text representations and textual representations. Moreover, we propose similarity constraint, a self-supervised task to prompt the visual encoder to focus on more additional information. Prefix alignment and multi-head bilinear module are designed to acquire an improved integration effect of visual text representations and textual representations. Experimental results indicate that MEVTR benefits from visual text representations and achieves significant performance gains in downstream tasks. In particular, in the zero-shot cross-lingual transfer task, MEVTR achieves results that outperform the state-of-the-art adapter-based framework without the target language adapter. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.

关键词： Signal encoding

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QoI-Aware Configuration Adaptation and Heterogeneous Resource Allocation for Edge Video Analytics

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IEEE Internet of Things Journal 2025年第12期12卷 19215-19230页

作者： He, Zixuan Sun, Yanjing Zhang, Beibei Dong, Kaiwen Wang, Bowen Xu, Hongli China University of Mining and Technology School of Information and Control Engineering Xuzhou221116 China China University of Mining and Technology IoT Perception Mine Research Center Xuzhou221116 China School of Information and Control Engineering China University of Science and Technology of China School of Computer Science and Technology Anhui Hefei230027 China University of Science and Technology of China Suzhou Institute for Advanced Research Jiangsu Suzhou215123 China

Edge video analytics enables agile responses of machine-centric applications by streaming videos from end devices to edge servers (ESs) for resource-intensive Deep Neural Network (DNN) inference. Quality of Inference (QoI), reflected by end-to-end analytics delay and inference accuracy, is crucial for the high-quality real-time decision-making. Due to the limited ES resources and dynamic network conditions, video configuration adaptation and fine-grained resource allocation are necessary to enhance the QoI of video streams, which involves a delicate balance between delay and accuracy. In this paper, we propose an edge-enabled multi-video analytics framework, in which performing DNN inference relies on heterogeneous resources, including CPU, GPU, and memory. Considering the different impacts of heterogeneous resources on QoI and double-queue backlogs, we formulate the joint video configuration adaptation, CPU-GPU resource allocation, and batch size selection (JCCGB) problem based on semi-Markov Decision Process to maximize the long-term average QoI. Then, Lyapunov optimization is applied to transform the original problem into one that minimizes the Lyapunov drift-plus-penalty upper bound, thereby ensuring the stability of both the transmission and computation queues. To tackle the potential multimodality of the optimal configuration adaptation and resource allocation policy, we propose the diffusion deep reinforcement learning based JCCGB (DD-JCCGB) scheme. This approach effectively enhances the policy performance and accelerates the training process. Experiments driven by real-world network traces demonstrate that the DD-JCCGB algorithm improves the long-term average QoI and outperforms baseline schemes. © 2025 IEEE.

关键词： Markov processes

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Enhancing Energy Efficiency with a Dynamic Trust Measurement Scheme in Power Distribution Network

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computers, Materials & Continua 2024年第3期78卷 3909-3927页

作者： Yilei Wang Xin Sun Guiping Zheng Ahmar Rashid Sami Ullah Hisham Alasmary Muhammad Waqas Zhejiang Electric-Power Corporation Research Institute Zhejiang310014China Faculty of Information Technology Beijing University of TechnologyBeijing100124China Beijing Trusty Cloud Technology Co. Ltd.Beijing100022China Department of Computer Science and Engineering Ghulam Ishaq Khan Institute of Engineering Sciences and EngineeringTopi23640Pakistan Department of Computer Science Shaheed Benazir Bhutto UniversitySheringalUpper Dir18050Pakistan Department of Computer Science College of Computer ScienceKing Khalid UniversityAbha61421Saudi Arabia School of Computing and Mathematical Science Faculty of Engineering and ScienceUniversity of GreenwichLondonSE109LSUK School of Engineering Edith Cowan UniversityPerth6027Australia

The application of Intelligent Internet of Things(IIoT)in constructing distribution station areas strongly supports platform transformation,upgrade,and intelligent *** sensing layer of IIoT comprises the edge convergence layer and the end sensing layer,with the former using intelligent fusion terminals for real-time data collection and ***,the influx of multiple low-voltage in the smart grid raises higher demands for the performance,energy efficiency,and response speed of the substation fusion ***,it brings significant security risks to the entire distribution substation,posing a major challenge to the smart *** response to these challenges,a proposed dynamic and energy-efficient trust measurement scheme for smart grids aims to address these *** scheme begins by establishing a hierarchical trust measurement model,elucidating the trust relationships among smart IoT *** then incorporates multidimensional measurement factors,encompassing static environmental factors,dynamic behaviors,and energy *** comprehensive approach reduces the impact of subjective factors on trust ***,the scheme incorporates a detection process designed for identifying malicious low-voltage end sensing units,ensuring the prompt identification and elimination of any malicious ***,in turn,enhances the security and reliability of the smart grid *** effectiveness of the proposed scheme in pinpointing malicious nodes has been demonstrated through simulation ***,the scheme outperforms established trust metric models in terms of energy efficiency,showcasing its significant contribution to the field.

关键词： IIoT trusted measure energy efficient

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Identifying illicit transactions in Bitcoin Tumbler services using Supervised Machine Learning Algorithms 12

Identifying illicit transactions in Bitcoin Tumbler services...

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12th IEEE International Conference on advanced computing, ICoAC 2023

作者： Ezhilmathi, S. Selvakumara Samy, S. Srm Institute of Science and Technology School of Computing Department of Computer Science and Engineering Tamilnadu Kattankulathur603203 India

ISBN: (纸本)9798350318210

Digital currencies have emerged as a new platform for money laundering as the first blockchain platform to support smart contracts, and the number of transaction records for Bitcoin has expanded substantially in recent years. Due to privacy services such as tumblers, which conceal the identities of payers and payees, pseudonymous digital currencies are frequently referred to as anonymous address and untraceable. A large proportion of accounts participating in Bitcoin transactions are engaging in illegal activity. According to the digital ledger, a transaction was transferred from one of many potential payers to one of many possible payees. As a consequence, it is vital to have a dependable system for classifying accounts and keeping track of the transactions linked with each account. We utilized machine learning techniques to apply multi-class classification methods to a Bitcoin transaction record obtained from *** in order to improve the model's accuracy. Experiment results show that ML algorithms like logistic regression, random forests, and multilayer perceptron's with the macro-average F1 score for bitcoin tumblers outperform state-of-the-art approaches for identifying unknown digital currency accounts, with the RF model outperforming LR and MLP by 97% accuracy. © 2023 IEEE.

关键词： Blockchain

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A three-stage novel framework for efficient and automatic glaucoma classification from retinal fundus images

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Multimedia Tools and Applications 2024年第37期83卷 85421-85481页

作者： Singh, Law Kumar Khanna, Munish Garg, Hitendra Singh, Rekha Iqbal, Md. Department of Computer Engineering and Applications GLA University Mathura India School of Computing Science and Engineering Galgotias University Greater Noida203201 India Department of Physics Uttar Pradesh Rajarshi Tandon Open University Uttar Pradesh Prayagraj India Department of Computer Science and Engineering Meerut Institute of Engineering and Technology Meerut India

Glaucoma is one of the leading causes of visual impairment worldwide. If diagnosed too late, the disease can irreversibly cause severe damage to the optic nerve, resulting in permanent loss of central vision and blindness. Therefore, early diagnosis of the disease is critical. Recent advancements in machine learning techniques have greatly aided ophthalmologists in timely and efficient diagnosis through the use of automated systems. Training the machine learning models with the most informative features can significantly enhance their performance. However, selecting the most informative feature subset is a real challenge because there are 2n potential feature subsets for a dataset with n features, and the conventional feature selection techniques are also not very efficient. Thus, extracting relevant features from medical images and selecting the most informative is a challenging task. Additionally, a considerable field of study has evolved around the discovery and selection of highly influential features (characteristics) from a large number of features. Through the inclusion of the most informative features, this method has the potential to improve machine learning classifiers by enhancing their classification performance, reducing training and testing time, and lowering system diagnostic costs by incorporating the most informative features. This work aims in the same direction to propose a unique, novel, and highly efficient feature selection (FS) approach using the Whale Optimization Algorithm (WOA), the Grey Wolf Optimization Algorithm (GWO), and a hybridized version of these two metaheuristics. To the best of our knowledge, the use of these two algorithms and their amalgamated version for FS in human disease prediction, particularly glaucoma prediction, has been rare in the past. The objective is to create a highly influential subset of characteristics using this approach. The suggested FS strategy seeks to maximize classification accuracy while reducing the t

关键词： Image classification

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Observer-Structured PID Controller: Flight Controller Design Examples 4

Observer-Structured PID Controller: Flight Controller Design...

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4th International Conference on Electrical, computer, Communications and Mechatronics engineering, ICECCME 2024

作者： Sato, Masayuki Sebe, Noboru Faculty of Advanced Science and Technology Kumamoto University Kumamoto Japan Graduate School of Computer Science and Systems Engineering Kyushu Institute of Technology Iizuka Japan

ISBN: (纸本)9798350391183

This note shows two design examples of PID con-Trollers, whose state variables estimate the selected state vari-Ables of the controlled plant systems, for LTI Parametrically Dependent (LTIPD) systems. The authors have already proposed observer-structured controllers, whose structure is not the same as but is very similar to the well-established Luenberger observer-based controllers, and have also proposed a conversion method from a priori designed unstructured LTI or Linear Parameter-Varying (LPV) controllers to observer-structured LTI/LPV con-Trollers with the plant state estimation ability implemented. How-ever, the successful conversion has been reported only for full-order controllers. In this note, we show two examples, in which a priori designed LTI PID controllers are successfully converted to observer-structured PID controllers, and the designed observer-structured PID controllers well estimate the selected plant state variables in numerical simulations. © 2024 IEEE.

关键词： Three term control systems

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advanced Medical Question and Answering Chatbot Powered by Llama-2 For Precis Health Answer 2

Advanced Medical Question and Answering Chatbot Powered by L...

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2nd International Conference on Computational Intelligence, Communication technology and Networking, CICTN 2025

作者： Patni, Jagdish Chandra Anup, S.B. Swetha Chitra, K.S. Poornima, B.M. Raviprakash, B.P. Kant Verma, Kamal Dept. of CSE Alliance School of Advanced Computing Alliance University Bengaluru India Department of Computer Science and Engineering School of Technology GSFC University Gujarat Vadodara India School of Computer Science IILM University Greater Noida India

ISBN: (纸本)9798331530389

LLaMA-2 model, which is known for having the best capabilities in natural language processing at the core of our system. With respect to symptom diagnosis, it ranked among the most accurate in being able to give the chances of as many conditions possible as per the information that it receives from the user. Creating custom responses to unique user queries all the time, which may potentially increase user satisfaction and engagement. We have tested and perfected our chatbot to ensure that the capabilities stood out at a level of accuracy as high as 85 percent-showing outstanding care in the matters of healthcare assistance issues under numerous medical topics. Our work adds advanced features with the improvement techniques to the conventional medical Q and A chatbot. The new deep learning chatbot is not only great for symptom diagnosis but also uses its capabilities to provide context-aware responses based on user health history, lifestyles, and preferences with adjustment of its advice for a more personal healthcare experience. © 2025 IEEE.

关键词： Chatbot LLaMA-2 model medical Question and Answers Natural language processing (NLP) symptom identification

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