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5th International Conference on Inventive Research in Computing Applications, ICIRCA 2023

作者： Ananthi, P. Sangavi, N. Ashish, G. Jabeen Begum, S. Mahalakhsmi, V. Kongu Engineering College Computer Science and Design Erode India Bannari Amman Institute of Technology Computer Science and Engineering Erode India Sengunthar College of Engineering Information Technology Thriuchangode India Velalar College of Engineering and Technology Computer Science and Engineering Erode India

ISBN: (纸本)9798350321425

Supply chain management plays a pivotal role in business operations, specifically with regard to the distribution network and ensuring the pristine condition of delivered products. Damages that may occur during shipping pose significant concerns, encompassing accidents, improper cargo handling, and related factors. To address this challenge, the implementation of machine learning algorithms, particularly through motion detection, emerges as a promising solution. By meticulously analyzing spectral features and accelerometric properties, the algorithm proficiently classifies motions across three-dimensional axes. Leveraging a K-Nearest Neighbor classifier, the system accurately categorizes these motions based on a carefully curated dataset of labeled non-damaging motions. Through the identification of outlier motions, the system effectively detects potential risks, thus facilitating the implementation of streamlined and optimized transportation mechanisms. This refined approach harnesses the power of machine learning to mitigate damages and elevate overall transportation practices within the supply chain. By enhancing the accuracy of motion classification and identifying deviations, proactive measures can be taken to prevent damage during transportation. This ultimately leads to improved efficiency and customer satisfaction throughout the supply chain. © 2023 IEEE.

关键词： Classification (of information)

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Robust Technique for Detecting and Blocking of VPN over Networks 9

Robust Technique for Detecting and Blocking of VPN over Netw...

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9th International Conference on science, technology, engineering and Mathematics, ICONSTEM 2024

作者： Vijaya, G. Dhiyanesh, M.S. Hashmi, M.D. Junaith Rehaan, K. Kavennesh, B.V. Sri Krishna College of Engineering And Technology Computer Science And Engineering Tamil Nadu Coimbatore India

ISBN: (纸本)9798350365092

In computer networks, data and information may be exchanged between linked devices through network communication. Networks are the backbone of the digital world, allowing data to be sent between computers, servers, and other devices. Standards and protocols like HTTP (Hypertext Transfer Protocol), which provide the guidelines for data interchange control this communication. The effectiveness and dependability of network communication, whether via wired or wireless connections, directly influences file sharing, real-time collaboration, and internet surfing. Organizations heavily rely on firewalls to safeguard internal networks from external threats. These firewalls enforce access rules, filter content, and scan for intrusions, providing robust protection. Virtual Private Networks (VPN) mask their real traffic under SSL (Secure Sockets Layer)/TLS (Transport Layer Security). Detecting such VPN services requires the use of firewalls that can analyze SSL/TLS actively. These features aren't cost-efficient and may not be suitable for every organization. VPN services may be used by users to bypass organizational compliance for accessing geo-restricted platforms, personal browsing, and connecting to personal network infrastructures that may be deemed off-limits within an organization. This usage poses a significant risk. The anonymity VPN services offer may influence users to engage in restricted content, and visit malicious sites, thereby posing a threat of inviting malware. Furthermore, these actions may expose the organization to legal consequences. Organizations may want to block the usage of VPN services to avoid sensitive information being exfiltrated, server compromization, and network jeopardization. In this paper, we have proposed an effective approach to detect VPN activity and block the user from accessing VPN services. Packet Sniffing is a process through which source IP addresses and destination IP addresses can be determined, and the source IP address and the d

关键词： HTTP

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Clustered Wireless Sensor Network in Precision Agriculture via Graph Theory

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Intelligent Automation & Soft Computing 2023年第5期36卷 1435-1449页

作者： L.R.Bindu P.Titus D.Dhanya Department of Science and Humanities Mar Ephraem College of Engineering and TechnologyTamil Nadu629171India. Department of Science and Humanities University College of Engineering NagercoilAnna University Constituent CollegeKonamNagercoil629004India Department of Computer Science and Engineering Mar Ephraem College of Engineering and TechnologyTamil Nadu629171India

Food security and sustainable development is making a mandatory move in the entire human *** attainment of this goal requires man to strive for a highly advanced state in theﬁeld of agriculture so that he can produce crops with a minimum amount of water and *** though our agricultural methodol-ogies have undergone a series of metamorphoses in the process of a present smart-agricultural system,a long way is ahead to attain a system that is precise and accurate for the optimum yield and proﬁ*** such a futuristic method of cultivation,this paper proposes a novel method for monitoring the efﬁcientﬂow of a small quantity of water through the conventional irrigation system in cultiva-tion using Clustered Wireless Sensor Networks(CWSN).The performance measure is simulated the creation of edge-ﬁxed geodetic clusters using Mat lab’s Cup-carbon tool in order to evaluate the suggested irrigation process model’s ***ﬁndings of blocks 1 and 2 are *** signal takes just a little amount of energy to communicate,according to the *** is feasible to save energy while maintaining uninterrupted communication between nodes and cluster ***,the need for proper placement of a dynamic control station in WSN still exists for maintaining connectivity and for improving the lifetime fault tolerance of *** on the minimum edgeﬁxed geodetic sets of the connected graph,this paper offers an innovative method for optimizing the placement of control *** edge-ﬁxed geodetic cluster makes the network fast,efﬁcient and ***,it also solves routing and congestion problems.

关键词： Wireless sensor networks edgeﬁxed geodetic set agriculture cluster control station precision agriculture

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Automated Handwritten Letter Recognition using Optimized Deep Learning Model

Automated Handwritten Letter Recognition using Optimized Dee...

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2024 International Conference on Knowledge engineering and Communication Systems, ICKECS 2024

作者： Indira, C.K. Gayathrilahari, N. Jyoshna, J. Jyothi, A. Sruthi, M. Siri Chandhana Saranya, D. Venkata G Pullaiah College of Engineering and Technology Computer Science and Engineering Andhra Pradesh Kurnool India

ISBN: (纸本)9798350359688

Forensic evidence, bank signature validation, and postal code recognition are just a few of the growing number of applications for handwritten charm recognition technology. The prevalence of numerous mysterious handwritten characters, massively characters, and a lack of academic focus mean that Pashto hand-written character acknowledgement (PHCR) remains largely unresolved despite advances in object recognition technology. For the first time in a controlled setting, we offer an efficient DeepNet model for recognizing Pashto hand-written characters. To begin, a new Pashto handwritten character data set called 'Poha' is built, which has 44 characters. Noise reduction and deep fusion image processing methods are used to prepare the text for optimization. The suggested model contains of 11 layers, eighter of which are three of which (FC). When applied to a DeepNet model, Adaptive Elephant Herd Optimization (AEHO) improved the accuracy of the parameters above that of standard deep models. Additionally, the suggested model is compared and contrasted with a number of benchmark Deep Learning (DL) models that have been applied to Poha. With a test accuracy of 97% for PHCR, the acquired experimental findings demonstrate that the suggested model is superior to existing models. The findings suggest that our approach has potential for use in automated PHCR and handwritten character recognition. © 2024 IEEE.

关键词： Deep learning

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Intelligent Blockchain: Use of Blockchain and Machine Learning Algorithm for Smart Contract and Smart Bidding 3rd

Intelligent Blockchain: Use of Blockchain and Machine Learni...

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3rd International Conference on Machine Learning, Internet of Things and Big Data, ICMIB 2023

作者： Rout, Jyotiranjan Pani, Susmita Mishra, Sibashis Panda, Bhagyashree Kar, Satya Swaroop Paramanik, Sanjay Department of Computer Science and Engineering Balasore College of Engineering and Technology Sergarh Odisha Balasore India

ISBN: (纸本)9789819939312

With the growth of population, there is an increase in demand in food, as well as growth in agribusiness and hence, an increase in contract farming. Contract farming provides the farmers with the benefits such as enhanced agricultural production and a rise in incomes of contract farmers, giving them an exposure to services and resources inculcated with opportunities to participate in markets. However, time and again contract farming is criticised for the uneven bargaining power that may lead to the exploitation of farmers by contractors or large agribusiness firms. The presence of middlemen or brokers in the supply chain further coerces the farmers to rely on them to sell their products. Again, there is another issue of differentiating among bids. So, the solution for all these problems lies in "BidBlock", a bidding integrated e-commerce platform, having built over blockchain and machine learning. Blockchain, with smart contracts, helps in restoring the trust of the farmers with its decentralization and machine learning, by interpreting and simplifying bids, helps them gaining maximum profit. Results show that most buyers prefer to have deals directly with the farmers and with a ease of doing business (like easy contract and payment). The addition of delivery services will be better too, but in this paper, it provides emphasis on how to simplify bidding with smart contracts, both for farmers and farms. Hence, introduction to BidBlock. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Smart contract

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A Proactive Method Using Machine Learning Models to Detect Phishing Attacks in Thread Sharing Network 10

A Proactive Method Using Machine Learning Models to Detect P...

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10th International Conference on Advanced Computing and Communication Systems, ICACCS 2024

作者： Ajay Kumar, K.V. Deepalakshmi, R. Balasubramaniyamoorthy, P.S. Murugan, K.R. Senthil Velammal College of Engineering and Technology Department of Computer Science and Engineering Tamil Nadu Madurai India

ISBN: (纸本)9798350384369

Phishing attacks present an enduring and pervasive threat in the digital realm, with cybercriminals continuously devising innovative techniques to deceive users and compromise sensitive information. This paper focuses on the crucial task of detecting phishing using advanced machine learning techniques. Recognized as a critical challenge in the digital landscape, phishing detection is imperative due to its potential to undermine trust, compromise security, and inflict financial and reputational damage. The paper employs feature extraction from diverse datasets as a pivotal step in the process, ensuring that relevant attributes are identified and utilized effectively. Moreover, it highlights the system's capability for real-time interpretation of websites, enhancing its responsiveness and efficacy in detecting phishing attempts promptly. The approach integrates machine learning models to enhance accuracy and robustness, achieving a notable accuracy of 97.5% through the utilization of the Gradient Boosting algorithm. This paper contributes to ongoing cybersecurity efforts by offering a multifaceted approach to phishing detection, leveraging the capabilities of machine learning. The findings underscore the importance of continuous research in adapting to evolving phishing tactics and improving the overall security posture of digital environments. Moving forward, the integration of real-time interpretation and adaptive machine learning models promises to further strengthen cybersecurity measures, ensuring a safer digital environment for users worldwide. © 2024 IEEE.

关键词： Phishing

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OAAFormer:Robust and Efficient Point Cloud Registration Through Overlapping-Aware Attention in Transformer

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Journal of computer science & technology 2024年第4期39卷 755-770页

作者： Jun-Jie Gao Qiu-Jie Dong Rui-An Wang Shuang-Min Chen Shi-Qing Xin Chang-He Tu Wenping Wang School of Computer Science and Technology Shandong UniversityQingdao 266237China School of Information and Technology Qingdao University of Science and TechnologyQingdao 266061China College of Engineering Texas A&M UniversityTexasTX 77843U.S.A.

In the domain of point cloud registration,the coarse-to-fine feature matching paradigm has received significant attention due to its impressive *** paradigm involves a two-step process:first,the extraction of multilevel features,and subsequently,the propagation of correspondences from coarse to fine ***,this approach faces two notable ***,the use of the Dual Softmax operation may promote one-to-one correspondences between superpoints,inadvertently excluding valuable ***,it is crucial to closely examine the overlapping areas between point clouds,as only correspondences within these regions decisively determine the actual *** these issues,we propose OAAFormer to enhance correspondence *** the one hand,we introduce a soft matching mechanism to facilitate the propagation of potentially valuable correspondences from coarse to fine *** the other hand,we integrate an overlapping region detection module to minimize mismatches to the greatest extent ***,we introduce a region-wise attention module with linear complexity during the fine-level matching phase,designed to enhance the discriminative capabilities of the extracted *** on the challenging 3DLoMatch benchmark demonstrate that our approach leads to a substantial increase of about 7%in the inlier ratio,as well as an enhancement of 2%-4%in registration ***,to accelerate the prediction process,we replace the Conventional Random Sample Consensus(RANSAC)algorithm with the selection of a limited yet representative set of high-confidence correspondences,resulting in a 100 times speedup while still maintaining comparable registration performance.

关键词： point cloud registration coarse-to-fine overlapping region feature matching Transformer

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X-OODM:Leveraging Explainable Object-Oriented Design Methodology for Multi-Domain Sentiment Analysis

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computers, Materials & Continua 2025年第3期82卷 4977-4994页

作者： Abqa Javed Muhammad Shoaib Abdul Jaleel Mohamed Deriche Sharjeel Nawaz Department of Computer Science University of Engineering and TechnologyLahore54890Pakistan Department of Computer Science(RCET Campus GRW)University of Engineering and TechnologyLahore52250Pakistan Artificial Intelligence Centre(AIRC) Ajman UniversityAjman346United Arab Emirates Smith School of Business University of MarylandCollege ParkMD 20742-5151USA

Incorporation of explainability features in the decision-making web-based systems is considered a primary concern to enhance accountability,transparency,and trust in the ***-domain Sentiment Analysis is a significant web-based system where the explainability feature is essential for achieving user *** design methodologies such as object-oriented design methodology(OODM)have been proposed for web-based application development,which facilitates code reuse,quantification,and security at the design ***,OODM did not provide the feature of explainability in web-based decision-making systems.X-OODM modifies the OODM with added explainable models to introduce the explainability feature for such *** research introduces an explainable model leveraging X-OODM for designing transparent applications for multidomain sentiment *** proposed design is evaluated using the design quality metrics defined for the evaluation of the X-OODM explainable model under user *** design quality metrics,transferability,simulatability,informativeness,and decomposability were introduced one after another over time to the evaluation of the X-OODM user *** metrics of accessibility and algorithmic transparency were added to increase the degree of explainability for the *** study results reveal that introducing such explainability parameters with X-OODM appropriately increases system transparency,trustworthiness,and user *** experimental results validate the enhancement of decision-making for multi-domain sentiment analysis with integration at the design level of *** work can be built in this direction by extending this work to apply the proposed X-OODM framework over different datasets and sentiment analysis applications to further scrutinize its effectiveness in real-world scenarios.

关键词： Measurable explainable web-based application object-oriented design sentiment analysis multi-domain

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Machine Learning for Air Quality Prediction: Random Forest Classifier 4

Machine Learning for Air Quality Prediction: Random Forest C...

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4th International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies, ICAECT 2024

作者： Vaishnavi, Kasula Sreya, Gummalla Reddy, Kishor Kumar Anisha, P.R. Stanley College of Engineering and Technology for Women Department of Computer Science and Engineering Telangana Hyderabad India

ISBN: (纸本)9798350343670

Air Pollution is the contamination of air due to the presence of substances in the atmosphere that are major issue to human life as well as to the other living organisms. Air quality is the result of the composite interactions of many elements, including the chemical reactions, meteorological parameters, and emissions from natural & anthropogenic (man-kind). The study implies that the forecasting performance differs across diverse regions & cities in India. Utilization of the Random Forest algorithm to anticipate the air quality index bucket is done in multiple locations across India annually, depending on air pollutants like PM2.5, PM10, NOx, CO, SO2, O3, NH3, and NO2 © 2024 IEEE.

关键词： Air Pollutants Air Quality Index Machine Learning Random Forest Statistics

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JPEG Reversible Data Hiding via Block Sorting Optimization and Dynamic Iterative Histogram Modification

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IEEE Transactions on Multimedia 2025年 27卷 3729-3743页

作者： Li, Fengyong Wang, Qiankuan Cheng, Hang Zhang, Xinpeng Qin, Chuan Shanghai University of Electric Power College of Computer Science and Technology Shanghai201306 China Fuzhou University School of Mathematics and Statistics Fuzhou Fujian350108 China Fudan University School of Computer Science Shanghai200433 China University of Shanghai for Science and Technology School of Optical-Electrical and Computer Engineering Shanghai200093 China

JPEG reversible data hiding (RDH) refers to covert communication technology to accurately extract secret data while also perfectly recovering the original JPEG image. With the development of cloud services, a large number of private JPEG images can be efficiently managed in cloud platforms by embedding user ID or authentication labels. Nevertheless, data embedding operations may inadvertently disrupt the encoding sequence of the original JPEG image, resulting in severe distortion of the host image when it is re-compressed to JPEG format. To address this problem, this paper proposes a new JPEG RDH scheme based on block sorting optimization and dynamic iterative histogram modification. We firstly design a block ordering optimization strategy by combining the number of zero coefficients and the quantization table values of non-zero coefficients in a DCT block. Subsequently, a dynamic iterative histogram modification scheme is proposed by considering the local features and embedding capability of histograms generated from different texture images. According to the given payloads, we introduce different parameters to control the iterations of two-dimensional histogram and then adaptively generate the optimal histogram modification mapping, which can realize low JPEG file size increments by guaranteeing most of the AC coefficients unchanged as much as possible. Numerous experiments have shown that our scheme can achieve an effective balance among embedding capacity, visual quality, file size increment, computational complexity, and outperforms the state-of-the-arts in terms of the above metrics. © 1999-2012 IEEE.

关键词： Embeddings

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