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12th International Conference on System Modeling and Advancement in Research Trends, SMART 2023

作者： Agrawal, Atul Jain, Vishal Astya, Rani Computer Science & Engineering Sharda School of Engineering & Technology Sharda University UP Greater Noida India

ISBN: (纸本)9798350369861

DDoS attacks are becoming more prevalent, which poses serious problems for network performance and security. This investigation makes use of the OPNET Modeler to thoroughly analyze how DDoS attacks affect network performance and investigate efficient discovery techniques. Three scripts are closely investigated, including an original network, a DoS assault, and a DDoS attack. DDoS attacks can result in significant packet loss rates, according to the report, underscoring the crucial importance of network security measures. The paper also examines several DDoS discovery techniques, emphasizing the demand for uniform simulation environments. As the digital geography evolves, visionary security strategies are imperative to insure network adaptability and optimal functionality. © 2023 IEEE.

关键词： Network security

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Towards a Comprehensive Metric for Evaluating Text Simplification Systems 14

Towards a Comprehensive Metric for Evaluating Text Simplific...

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14th International Conference on Information and Communication Systems, ICICS 2023

作者： Ajlouni, AlMotasem Bellah Al Li, Jinlong Ajlouni, Mo'ataz A. School of Computer Science and Technology University of Science and Technology of China Hefei China Jordan University of Science and Technology Department Biomedical Engineering Irbid Jordan

ISBN: (纸本)9798350307870

Accurately evaluating text simplification (TS) systems is a major challenge in optimizing existing models and developing new TS approaches. Human evaluation stands as the gold standard for TS quality assessment, it involves expert human annotators who assess simplified texts based on grammaticality (G), meaning preservation (M), and simplicity (S) criteria. Typically, the overall quality of a TS system is calculated by taking the arithmetic mean of these criteria. However, this method can be misleading due to the complex relationships between these criteria. This study investigates the nuanced relationships between the G, M, and S criteria and introduces two new formulas for combining them into a unified metric that more accurately reflects the overall quality of a TS system. The experimental results highlight the effectiveness of BERTscore and BLEU in evaluating TS systems, particularly when high-quality references are available, and their strong correlations with the unified metrics we propose to express overall system performance. © 2023 IEEE.

关键词： Natural language processing systems

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Autonomous Aspect-Image Instruction A2II: Q-Former Guided Multimodal Sentiment Classification 30

Autonomous Aspect-Image Instruction A2II: Q-Former Guided Mu...

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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： Feng, Junjia Lin, Mingqian Shang, Lin Gao, Xiaoying State Key Laboratory for Novel Software Technology Nanjing University China Department of Computer Science and Technology Nanjing University China School of Engineering and Computer Science Victoria University of Wellington New Zealand

ISBN: (纸本)9782493814104

Multimodal aspect-oriented sentiment classification (MABSC) task has garnered significant attention, which aims to identify the sentiment polarities of aspects by combining both language and vision information. However, the limited multimodal data in this task has become a big gap for the vision-language multimodal fusion. While large-scale vision-language pretrained models have been adapted to multiple tasks, their use for MABSC task is still in a nascent stage. In this work, we present an attempt to use the instruction tuning paradigm to MABSC task and leverage the ability of large vision-language models to alleviate the limitation in the fusion of textual and image modalities. To tackle the problem of potential irrelevance between aspects and images, we propose a plug-and-play selector to autonomously choose the most appropriate instruction from the instruction pool, thereby reducing the impact of irrelevant image noise on the final sentiment classification results. We conduct extensive experiments in various scenarios and our model achieves state-of-the-art performance on benchmark datasets, as well as in few-shot settings. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.

关键词： Sentiment analysis

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Underwater Image Color Analysis and Indicators Based on Statistical Characteristics 4

Underwater Image Color Analysis and Indicators Based on Stat...

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4th International Conference on computer Vision, Image and Deep Learning, CVIDL 2023

作者： Peng, Jin Yu, Haiyang Wang, Zhe School of Computer Science and Information Engineering Hefei University of Technology Anhui Hefei China

ISBN: (纸本)9798350326444

When light propagates in water, different wavelengths of light have different degrees of attenuation, resulting in the color cast of underwater images. Color characteristics are important to solve the problem of color cast. Therefore qualitative and quantitative analysis of underwater image color characteristics and color indicators studies in RGB space are carried out in this paper. A qualitative comparative analysis between underwater images and land color cast-free images is carried out. It is concluded that there are differences in histogram and statistical characteristics between RGB channels of underwater images. Then a set of color characteristics indicators is established that can measure the degree of color cast and the differences between color channels of the underwater images. Finally, experiments on quantitative analysis of color characteristics are carried out. Different turbidity levels and colors of the water environment are set up to analyze the changes and differences of color characteristics. Underwater image color characteristics are obtained by comprehensive analysis. © 2023 IEEE.

关键词： Color

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State-of-the-Art Techniques for Detecting the Onset of Parkinson's Disease 10

State-of-the-Art Techniques for Detecting the Onset of Parki...

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17th INDIACom;2023 10th International Conference on Computing for Sustainable Global Development, INDIACom 2023

作者： Hamid, Taezeen Nand, Parma Chhabra, Megha School of Engineering and Technology Sharda University Department of Computer Science and Engineering UP Greater Noida India

ISBN: (纸本)9789380544472

Parkinson's disease which is a neurodegenerative disease tends to deteriorate muscle control steadily. Although Parkinson's disease primarily affects elderly people, but adults can also be affected by this disease. The symptoms are caused by the gradual nerve cell loss in the area of the brain that regulates movement. Patients' quality of life is greatly reduced because it shows motor, cognitive, and other sorts of symptoms. Parkinson's disease is usually diagnosed based on a patient's medical history and physical symptoms. However, it has a subjective nature and a poor prognosis. In the diagnosis of Parkinson's disease, artificial intelligence (AI) has shown promising results. Yet because of the small sample size, poor validation and lack of big data design, it introduces bias. This paper outlines the state-of-the-art methods that have been used to detect Parkinson's disease. The findings of the literature, as well as frequent methodological flaws that may skew results, are identified. The question is can AI alone be successful in clinical settings for Parkinson's disease identification? By incorporating AI algorithms with Internet of Things (IoT) treatment can be improved effectively while reducing related healthcare expenditures. © 2023 Bharati Vidyapeeth, New Delhi.

关键词： Decision trees

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Sensitive Information Protection Model Based on Bayesian Game

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computers, Materials & Continua 2022年第10期73卷 883-898页

作者： Yuzhen Liu Zhe Liu Xiaoliang Wang Qing Yang Guocai Zuo Frank Jiang School of Computer Science and Engineering Hunan University of Science and TechnologyXiangtan411201China Hunan Key Laboratory for Service computing and Novel Software Technology Xiangtan411201China College of computer and information engineering Hunan University of Technology and BusinessChangshaChina School of Computer Science and Information Engineering Guangzhou Maritime UniversityGuangzhouChina Hunan Software Vocational and Technical University XiangtanChina School of Engineering and IT University of New South WalesNSWAustralia

A game measurement model considering the attacker’s knowledge background is proposed based on the Bayesian game theory aiming at striking a balance between the protection of sensitive information and the quality of *** quantified the sensitive level of information according to the user’s personalized sensitive information protection *** on the probability distribution of sensitive level and attacker’s knowledge background type,the strategy combination of service provider and attacker was analyzed,and a game-based sensitive information protection model was *** the combination of strategies under Bayesian equilibrium,the information entropy was used to measure the leakage of sensitive ***,in the paper the influence of the sensitive level of information and the attacker’s knowledge background on the strategy of both sides of the game was considered *** on,the leakage of the user’s sensitive information was ***,the feasibility of the model was described by experiments.

关键词： Sensitive information game theory Bayesian equilibrium sensitive level information entropy

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A Novel Approach for Tomato Quality Evaluation: computer Vision in Maturity Assessment and Disease Detection 5

A Novel Approach for Tomato Quality Evaluation: Computer Vis...

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5th IEEE International Conference for Emerging technology, INCET 2024

作者： Arya, Prarthana K.Y. Kulkarni, Tejas P. Pushpa, B.R. Rani, N. Shobha Sangamesha, M.A. Department of Computer Science Amrita School of Computing Amrita Vishwa Vidyapeetham Mysore India Department of Computer Science and Engineering Gitam School of Technology Gitam University Bengaluru India Department of Chemistry National Institute of Engineering Mysore India

ISBN: (纸本)9798350361155

Tomatoes (Solanum lycopersicum) are one of the most widely consumed fruits globally. Fruit maturity and disease estimation is a criticalfactors in determining its quality and marketability. Traditional maturity assessment requires huge labor, slow, subjective, and time-consuming activities. To address these challenges, the agriculture industry is subjected to automation using computer vision models. Accurate prediction of tomato maturity and diseases is important to decide on harvesting time. Several features such as color, shape, texture, and size are considered to predict the different maturity stages of fruits using deep learning and machine learning models. Assessing the maturity level and disease detection in the early stage of tomatoes is crucial. The proposed work explores the application of the VGG16 architecturefor tomato maturity classification and disease detection. The study leverages transfer learning with VGG16focusing on feature extraction and model optimization to achieve accurate classification. The datasets used in this work are self-created using the images that are collected from agricultural farms. The dataset consists of image samples of six different maturity stagesand diseased fruit images. The experiment results in an accuracy range between 95%-99% for six maturity stages of tomatoes and disease prediction resulted in 90%-97% accuracy. © 2024 IEEE.

关键词： Fruits

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Digital-twin-based Substation Operation Safety Monitoring System 8

Digital-twin-based Substation Operation Safety Monitoring Sy...

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8th International Conference on Intelligent Informatics and Biomedical sciences, ICIIBMS 2023

作者： Jiang, Ying Yao, Aihong Ma, Haifeng Zhang, Yu Cui, Liu Liu, Yunxiang Shanghai Institute of Technology School of Computer Science and Information Engineering Shanghai201418 China

ISBN: (纸本)9798350369564

As a place for receiving electric energy transmitted by the power grid and secondary distribution of electric energy in the power system, the substation includes primary equipment for transforming voltage and current and secondary equipment for measuring and comprehensive protection of system operating conditions. When carrying out duty work and patrol work to maintain the normal operation of the substation, the staff shall maintain a safe clear distance from the exposed high-voltage live parts. In this paper, using digital twin technology, a spatio-temporal model describing operation behavior and the calculation model of the safe clear distance of the operation are proposed and embedded in the substation digital twin system. The operation safety monitoring system combined with electrical equipment status, real-time environmental conditions, and operator location information is designed. The feasibility and effectiveness of this method are verified by simulation analysis. © 2023 IEEE.

关键词： Electric substations

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A Novel GPS based Blood Bank Management System 7

A Novel GPS based Blood Bank Management System

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7th International Conference on Trends in Electronics and Informatics, ICOEI 2023

作者： Jha, Sonal Raghav, Siddharth Chauhan, Kartik Kumar Agarwal, Ambuj Kumar School of Engineering and Technology Sharda Univesity Department of Computer Science and Engineering UP Greater Noida India

ISBN: (纸本)9798350397284

The Blood Bank website is an honest attempt to simplify all aspects of receiving and donating blood. Users can readily access information about the availability of blood types in various blood banks throughout the state, as well as the day of donating blood and the option to plan a voluntary blood donation through the website. Almost every medical procedure and emergency circumstance necessitate the use of blood. Because of medical advancements and technology, the number of patients who require blood is increasing so, this is an all-screen-size-supportive internet system that will be utilized to save people's lives by providing information about blood availability, blood seekers, donors, and blood banks. The major goal of the website is to facilitate and speed up communication among users because the blood supply is limited. The GPS (Global positioning system) location of each user in the surrounding region will be displayed to another user. This can assist users in a variety of ways, the most important of which is that blood seekers can simply contact donors and banks or check the nearby availability of blood Blood donors can also contribute easily and communicate via the website's information and discussion sections. Blood donors who intend to donate can check to see if there is an emergency registered and provide assistance in addition to depending on the blood bank. Every registered account's data will be stored in a backend database. The proposed system is designed and further it will be developed with easy-to-use user interface and be helpful to users. It should also make searching process simple and interesting. © 2023 IEEE.

关键词： Websites

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An Efficient Detection and Classification of Plant Diseases using Deep Learning Approach

An Efficient Detection and Classification of Plant Diseases ...

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2023 International Conference on Evolutionary Algorithms and Soft Computing Techniques, EASCT 2023

作者： Jagadeesan, S. Deepakraj, E. Ramalingam, Venkadeshan Venkatachalam, Ilayaraja Vivekanandan, Manojkumar Manjula, R. Vellore Institute of Technology School of Computer Science Engineering and Information Systems Vellore India University of Technology and Applied Sciences - Shinas Branch Information Technology Department Oman Vellore Institute of Technology School of Computer Science and Engineeing Vellore India School of Engineering and Applied Sciences Srm University-AP Department of Computer Science & Engineering Andhra Pradesh Amaravati India Srm Institute of Science and Technology College of Engineering and Technology Department of Computing Technology Kattankulathur India

ISBN: (纸本)9798350313413

Crop failure caused by disease-causing pests is an important problem. Farmers struggle with disease management and detection due to inadequate interventions. The goal is to create an automatic system to efficiently identify plant diseases from photos while reducing crop losses and increasing productivity. Machine learning algorithms offer a faster and cheaper alternative to visual inspection by experts. The main goal is to perform image analysis for early diagnosis and effective disease control. The use of CNN architecture for plant disease classification and detection offers a promising solution for plant health monitoring and risk mitigation. Given the threats to crop productivity and global food security, reliable methods for early detection and accurate classification are essential. CNNs enable efficient analysis of vast plant image databases, enabling accurate plant disease identification with speed and accuracy. The multi-layer CNN approach extracts feature and refines the representation, facilitating accurate prediction and accurate diagnosis. Transfer learning methods accelerate system development and allow adaptation to plant disease-specific databases. Combining computer vision algorithms with CNN architecture enables real-time monitoring, early disease detection and targeted intervention, reducing yield losses and improving crop management. This approach uses AI, image analysis, and plant pathology to solve the challenges of sustainable agriculture and plant diseases. System performance is measured by various performance metrics. © 2023 IEEE.

关键词： CNN-Based Approach Error Rate Plant disease Precision ROC

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