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Automated cervical cancer classification using stacked BI-LSTM and optimized spiking neural network with deer hunting optimization algorithm

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International Journal of Information Technology (Singapore) 2025年 1-10页

作者： Vanam, Harika Vijaylaxmi, G. Kumar, Vanam Sravan Computer Science and Engineering Gokaraju Lailavathi Women’s Engineering College (GLWEC) Hyderabad India Vaagdevi College of Engineering Warangal Bollikunta India Department of Computer Science & Engineering Balaji Institute of Technology & Sciences Narsampet Warangal India

Diagnostic systems constantly improve medical image analysis and diagnosis techniques to boost the speed and precision of cancer detection. One of the most difficult issues in classifying cervical cancer using deep learning algorithms is the accessibility and quality of data and changes in the images' size, shape, and physical appearance. This study presents important approaches for overcoming these hurdles and developing an improved diagnostic system. In this work, we utilize data from the Herlev dataset, including cervical cell images, disease symptoms, and their impact on cervical cancer classification and diagnosis. The data is pre-processed by employing imputation to handle missing values. Cropping, resizing, flipping, and rotation are common techniques to prepare images for analysis. Feature extraction using Stacked Bi-LSTM plays a vital role in deep learning by removing irrelevant and redundant features. A Spiking Neural Network with the Deer Hunting Optimization Algorithm (SNN-DHOA) is utilized for cervical cancer classification. The performance of the suggested technique is analysed using various metrics, achieving an accuracy of 98.21%, sensitivity of 98.27%, specificity of 98.15%, and an F1-score of 98.54%. © Bharati Vidyapeeth's Institute of computer Applications and Management 2025.

关键词： Cervical cancer Herlev dataset Spiking Neural Network with Deer Hunting Optimization Algorithm (SNN-DHOA) Stacked Bi-LSTM

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Blockchain Integrated Cloud Architecture for Surveillance Systems 3

Blockchain Integrated Cloud Architecture for Surveillance Sy...

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3rd International Conference on Disruptive Technologies, ICDT 2025

作者： Kumar, Vinay Raghuvanshi, Varun Singh Sharma, Shashwat Yadav, Yash Goutam, Arvind Ajay Kumar Garg Engineering College Department of Computer Science and Engineering Ghaziabad India

ISBN: (纸本)9798331519582

The speedy growth of data-pushed programs, especially in surveillance and IoT systems, has underscored the need for steady, green, and privateness-retaining records control answers. While cloud computing gives scalability, it poses sizeable safety risks, making it liable to records breaches and unauthorized access. Blockchain technology, with its decentralized and immutable ledger, offers promising answers to these challenges, yet it struggles with scalability and computational demands while implemented to high-frequency, actual-time applications. This research paper proposes an technique to address those limitations through an integration of blockchain generation with cloudprimarily based surveillance systems. Through a hybrid version of selective storage and optimized consensus mechanisms, the proposed solution addresses the demanding situations of latency, scalability, and privacy maintenance at the same time while enhancing real-time access control. © 2025 IEEE.

关键词： Real time control

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A Review on AI-Powered Digital Identity Authentication for Remote Examination 6

A Review on AI-Powered Digital Identity Authentication for R...

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6th International Conference on Mobile Computing and Sustainable Informatics, ICMCSI 2025

作者： Srivastava, Shubhi Kumar, Nayana N. Khushi, M. Varshini, C. Githamrutha Bhumika, P.M. Sree Snigdha, T. Department of Information Science and Engineering New Horizon College of Engineering Karnataka Bengaluru India Department of Computer Science and Engineering New Horizon College of Engineering Karnataka Bengaluru India

ISBN: (纸本)9798331522667

With the growth of online education, ensuring integrity in remote examinations has become a critical challenge. This research explores AI-driven dual-proctoring systems that utilize both single and dual-camera setups, incorporating a laptop's webcam and a mobile camera, to enhance monitoring during student examinations. By systematically reviewing recent advancements in the literature, the study identifies key modules that can be integrated into an effective proctoring system. In addition, it provides details regarding tools and technologies that could ensure the practical, real-time execution of the said systems toward providing security issues with fairness online. © 2025 IEEE.

关键词： Cameras

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UniManage - An All-in-One Platform for Empowering Businesses 2

UniManage - An All-in-One Platform for Empowering Businesses

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

作者： Pandey, Geetansh Saxena, Kushagra Tyagi, Simran Singh, Arya Prabha, Sneh Department of Computer Science Inderprastha Engineering College Ghaziabad India

ISBN: (纸本)9798331530389

UniManage is basically all packaged into one, fully-fledged SaaS solution that has been designed to bring together major business functions into one excellent system that optimizes organizational processes. Its modules are flexible and span meetings, collaboration, accounting, finance, and supply chain management. With this, it can attend to many business needs. By being modular, UniManage will allow organizations to create solutions that fit the requirements of their operations and workflows specifically. This has been a major advantage for UniManage. Software laundry will significantly decline, workflows will be optimized and increased overall productivity across organizations will be achieved. Flexibility, robust features, and user-centric design make UniManage certainly an essential tool for businesses intent on streamlining operations. It increases efficiency while also allowing teams to work better, so they stay in sync and can meet their goals. This is how well UniManage is positioned as a solution that is flexible or scalable according to the demands of today's business scenarios: a reliable foundation for growth and innovation. © 2025 IEEE.

关键词： Cost reduction

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Innovative Approach for Early Heart Disease Prediction: Gaussian Mixture Model and K-Nearest Neighbour 3

Innovative Approach for Early Heart Disease Prediction: Gaus...

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3rd International Conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Surendran, R. Anandaraj, B. Deepa, P. Mageshwari, M. Balamurugan, K.S. Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai India Department of Computer Science and Engineering Madnapalle Institute of Technology & Science Andhra Pradesh Madanapalle India Department of Computer Science and Engineering Panimalar Engineering College Chennai India Department of Computer science and engineering Karpaga Vinayaga College of Engineering and Technology Tamil Nadu Chengalpattu India Department of Electronics and communication engineering Karpaga Vinayaga College of Engineering and Technology Tamil Nadu Chengalpattu India

ISBN: (数字)9798331527549

ISBN: (纸本)9798331527549

An Electrocardiogram (ECG) contributes significantly to early diagnosis and classification of heart diseases, arrhythmia which means irregular heart rate. Regrettably, the process became difficult due to asymmetric and minimal amplitude from recordings of ECG and cannot do the extraction from multiple signals. By using machine learning technology, it can classify and extract multiple samples, but cannot extract the data features from complex data structures. To overcome the limitations, previously introduced metaheuristic optimization (MHO) to improve the classification and extraction. Proposed a method which supports and K-Nearest Neighbour (KNN) Gaussian Mixture Model (GMM) algorithms for determine the abnormalities, predicting cardiac events, and improve diagnostic accuracy. As a result, this can help us to get results more quickly and accurately with sensitivity 99.7% and accuracy 99.2%, for helping healthcare professionals in diagnosing arrythmias, myocardial infarction and any other heart conditions. © 2025 IEEE.

关键词： Adversarial machine learning

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Integrating Deep Learning Frameworks for Automated Medical Image Diagnosis 8th

Integrating Deep Learning Frameworks for Automated Medical I...

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8th IFIP TC 12 International Conference on computer, Communication and Signal Processing, ICCCSP 2024

作者： Gayatri, K. Kumar, K. M. Anand Padmavathi, B. Shankar Department of Computer Science and Engineering Easwari Engineering College Ramapuram Chennai600089 India

ISBN: (纸本)9783031736162

In today’s healthcare system, medical image analysis is essential for diagnosis, treatment planning, and condition monitoring. In this study, the four well-known tools in the field are 3D Slicer, MONAI, SAMM, and YOLOv8 are examined and contrasted. The study’s scope includes its ability to process a variety of 2D and 4D medical imaging datasets, which contain images, segmentation, annotations, and transformations. The process entails a comprehensive prehensive examination of every tool’s feature, with particular emphasis on their capacity to read and write DICOM images, accommodate multiple file formats, offer interactive 3D Slicer. Key findings show that 3D Slicer performs exceptionally well when using deep learning techniques for segmentation and interactive visualization. While SAM Model exhibits adaptability in managing diverse segmentation prompts, MONAI provides a comprehensive end-to-end medical data processing solution. YOLOv8 shows potential for effective object detection. The study’s implications include the possibility of using these instruments in clinical practices and medical research contexts. The research results provide insight into the current discussion about how to strategically integrate state-of-the-art methods to improve overall healthcare outcomes, diagnostic accuracy, and treatment planning efficiency as medical image analysis continues to advance. © IFIP International Federation for Information Processing 2025.

关键词： Clinical research

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Generative AI in Real-Time E-Commerce Fraud Detection: A Comparative and Ethical Analysis

Generative AI in Real-Time E-Commerce Fraud Detection: A Com...

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2025 International Conference on Intelligent Control, Computing and Communications, IC3 2025

作者： Tyagi, Rashi Goyal, Gauri Tyagi, Shiva Ajay Kumar Garg Engineering College Department of Computer Science and Engineering Ghaziabad India

ISBN: (纸本)9798331527495

This paper will discuss generative AI models, such as GANs, VAEs, and a hybrid GAN-VAE, towards real-time fraud detection in e-commerce. GANs perform outstandingly in synthesizing fraudulent data, while VAEs detect complex patterns of fraud. The proposed hybrid method combines the respective strengths and achieves higher accuracy and adaptability. Also, issues regarding ethical concerns related to privacy in data and biases are taken care of, illustrating the future possibility of generative AI in upgrading the frameworks for fraud detection in e-commerce. © 2025 IEEE.

关键词： Marketplaces

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DCS Implementation of Hot Air Bag Filter Cleaning System With Controls Using Yokogawa

DCS Implementation of Hot Air Bag Filter Cleaning System Wit...

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2025 International Conference on Emerging Technologies for Intelligent Systems, ETIS 2025

作者： Krishna, Karthika Syamraj, B.S. Providence College of Engineering Department of Computer Science and Engineering Kerala Chengannur Alappuzha India

ISBN: (数字)9798331507541

ISBN: (纸本)9798331507541

Dispersed Control Systems (DCS) are a vital enhancement in commercial automation enabling central control plus tracking to boost effectiveness. Lots of Indian plants still make use of analog systems. Some additionally depend on PLC-based systems. Nevertheless, DCS fostering is expanding. It incorporates plant manages right into a solitary console. This paper provides the layout coupled with application of a Hot Air Bag Filter Cleaning System making use of the Yokogawa Centum VP DCS. The system utilizes heat technology to enhance bag filter cleansing guaranteeing far better purification coupled with bit elimination. The Yokogawa Centum VP DCS offers exact control, real-time tracking as well as effective automation. Its application increases performance, decreases downtime, and also makes sure conformity with ecological requirements, establishing a requirement in automation. © 2025 IEEE.

关键词： Air cleaners

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Mitigating Website Vulnerabilities: A Comprehensive Analysis of Security Mechanisms and Emerging Technologies 4

Mitigating Website Vulnerabilities: A Comprehensive Analysis...

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4th IEEE International Conference on ICT in Business Industry and Government, ICTBIG 2024

作者： Ghatkamble, Rajlakshmi Rath, Subhashree Shruthi, G.R. Sandep, J.G. Farooq, Sarim Shafi, Mursaleen Mohammed, Emaduddin Asdaq Syed New Horizon College of Engineering Department of Information Science and Engineering Karnataka Bengaluru India New Horizon College of Engineering Department of Computer Science and Engineering Karnataka Bengaluru India New Horizon College of Engineering Department of Information Science & Engineering Karnataka Bengaluru India New Horizon College of Engineering Department of Computer Science & Engineering Karnataka Bengaluru India

ISBN: (纸本)9798331518981

The worldwide community now places a great deal of importance on the Internet. The biggest issue facing the corporate sector right now is web security. It is thought to be the main foundation for the global data society. Security flaws can affect web applications. An online application layer is shielded from attacks by unauthorized users by means of web security. Erroneous client input is the root cause of a lot of web application issues. This essay discusses the various components of online security as well as its shortcomings. The main components of online security mechanisms, including passwords, encryption, authentication, and integrity, are also covered in this essay. There is a thorough discussion of the attack techniques and the structure of a web application attack. This study investigates a variety of approaches for combating this type of danger and evaluates why they have not been more effective. This research provides a more effective method for reducing these types of website vulnerabilities. It also provides the most effective security methods against these kinds of assaults. © 2024 IEEE.

关键词： Websites

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Machine Learning Vigilance: Safeguarding Networks Through Cyber Attack Detection 12th

Machine Learning Vigilance: Safeguarding Networks Through Cy...

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12th International Conference on Frontiers of Intelligent Computing: Theory and Applications, FICTA 2024

作者： Sangeam, Ruchitha Ala, Rajitha Punyamurthy, Bheemeshwar Kanagala, Sai Sriharsha Kesari Swain, Nirmal Swetha, Rame Department of Information Technology Vardhaman College of Engineering Hyderabad India Department of Computer Science and Engineering Vardhaman College of Engineering Hyderbad India

ISBN: (纸本)9789819601424

Embracing the latest technological strides holds immense promise for individuals, organizations, and governments. However, divergent perspectives exist on these advancements, particularly regarding safeguarding critical information, securing stored data platforms, and ensuring data accessibility. A pivotal challenge in the contemporary landscape is the escalating threat of digital terror ism, causing disruptions for individuals and institutions. This form of cybercrime, orchestrated by diverse entities like criminal organizations, skilled individuals, and digital activists, now poses a significant risk to public and national security. Intrusion Detection Systems (IDS) have been developed to address this pressing issue. The study leverages the recently introduced UNSWNB dataset to evaluate the efficacy of the chosen approach. The SVM algorithm demonstrated a commendable accuracy of 83.29. The company demonstrated its ability to effectively counter cyber threats by showcasing its potential. Moreover, they utilized a convolutional neural network (CNN) to achieve this feature outperformed, and achieved an accuracy level of 99.52 with your cybersecurity project. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Network intrusion

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