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检索条件"任意字段=12th International Conference on Intelligent and Adaptive Systems and Software Engineering"

共 6048 条记录，以下是71-80 订阅

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Insights into K-means Clustering: Unraveling the Significance of Initial Centroid Placement 12th

Insights into K-means Clustering: Unraveling the Significanc...

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12th international conference on Frontiers of intelligent Computing: theory and Applications, FICTA 2024

作者： Mohan, Ankita Mishra, Arbind Chandel, Atika Nayak, Satyakam Bisen, Arshita Satapathy, Suresh Chandra School of Computer Engineering KIIT Deemed to Be University Odisha Bhubaneswar751024 India

ISBN: (纸本)9789819601387

K-means clustering is a fundamental technique in unsupervised learning, renowned for its straightforwardness and effectiveness in organizing datasets into clusters based on feature similarities. Despite its widespread acceptance, the algorithm faces a significant hurdle: its sensitivity to the initial placement of centroids, which often leads to inconsistent clustering results. this study delves into a comprehensive analysis to assess how different methods of initializing centroids impact the performance of K-means clustering. through meticulous examination of inter-cluster and intra-cluster distances across a diverse array of datasets, this research provides a detailed quantitative evaluation of clustering efficacy under varying initialization conditions. the results of this analysis shed light on a critical aspect of K-means clustering: its performance, as gauged by accuracy and correlation metrics, is notably affected by the positioning of initial centroids. this observed variability underscores the necessity of strategic centroid initialization in enhancing the reliability and effectiveness of the algorithm. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： K-means clustering

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Decision systems Optimization for Cybersecurity Resilience 12th

Decision Systems Optimization for Cybersecurity Resilience

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12th international conference on Frontiers of intelligent Computing: theory and Applications, FICTA 2024

作者： Ikhar, Sharayu Mondal, Dipannita Khubalkar, Deepti Yadav, Ranjeev Deshpande, Pallavi Patil, Sonali Vrushabhasagar Yashika Journal Publications Pvt. Ltd Maharashtra Wardha India Artificial Intelligence and Data Science Department Dr. Y. Patil College of Engineering and Innovation Telegaon410507 India Nagpur Campus Pune India Computer Science and Engineering Arya College of Engineering Jaipur India EnTC VIIT Pune India Nutan Maharashtra Institute of Engineering and Technology Maharashtra Pune India

ISBN: (纸本)9789819601424

the increasing danger in the online environment highlights the necessity for strong and durable cybersecurity solutions. this study aims to improve Intrusion Detection systems (IDS) by introducing a new hybrid method that merges Variational Autoencoders (VAEs) and Ant Colony Optimization (ACO) to enhance anomaly detection. the main goal is to enhance decision-making systems in IDS to attain a high level of accuracy, with a proven success rate of 99.3%. the Variational Autoencoder (VAE) functions as a tool for extracting features and reducing dimensionality by capturing latent representations of typical network behavior. the model can detect anomalous activities more accurately by using VAE to identify subtle patterns and deviations in network traffic. the Ant Colony Optimization (ACO) algorithm is incorporated into the decision-making process of the IDS to complement the VAE. Ant Colony Optimization (ACO) is used to optimize the parameters of Intrusion Detection systems (IDS) and adjust the decision boundaries to improve the detection performance. the combined interaction of VAE and ACO forms a robust framework that can accurately detect anomalies and adjust in real-time to changing cyber threats. the hybrid model proposed was assessed with real-world cybersecurity datasets, showing an impressive accuracy of 99.3%. the experimental results highlight the VAE-ACO hybrid’s effectiveness in achieving high detection accuracy while remaining efficient in terms of computational resources. Combining Variational Autoencoders with Ant Colony Optimization shows great potential for enhancing decision systems in Intrusion Detection systems. the 99.3% accuracy demonstrates the capability of this hybrid approach to greatly enhance cybersecurity resilience against advanced and evolving cyber threats. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Ant colony optimization

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Collaborative Decision-Making for adaptive Cybersecurity Policies 12th

Collaborative Decision-Making for Adaptive Cybersecurity Pol...

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12th international conference on Frontiers of intelligent Computing: theory and Applications, FICTA 2024

作者： Deshmukh, Anand B. Chopade, Pallavi Devidas Yadav, Rajeev Chavhan, Gajanan H. Ingle, Pravin E. Ajani, Samir N. Department of Information Technology Sipna College of Engineering and Technology Amravati MS Amravati India Institute of Management and Entrepreneurship Development Pune411038 India Computer Science and Engineering Arya College of Engineering Jaipur India E&TC VIIT Pune India Department of Mechanical Engineering Dr. D. Y. Patil Institute of Technology Pimpri Maharashtra Pune India Shri Ramdeobaba College of Engineering and Management Maharashtra Nagpur India

ISBN: (纸本)9789819601462

Static cybersecurity policies aren’t working well enough to protect businesses from dynamic and complex attacks in today's fast-changing cyber threat environment. It is becoming clearer that we need cybersecurity policies that can change with new threats and changing business needs in order to deal with this problem. the skills and ideas of many people are needed to make cybersecurity protection more flexible and effective. this is why collaborative decision-making is so important for making and enforcing these kinds of rules. Collaboration for making decisions about changing hacking policies is looked at in great detail in this study. the article looks at how decision-making theories and the creation of cybersecurity policies relate to each other by looking at a lot of current literature, theoretical models, and real-life case studies. What are the ideas behind making decisions together? they are explained using hacking as an example. this shows how important it is for stakeholders to be involved, for people to be able to talk to each other, for trust to exist, and for the organization's culture to shape good policy results. this paper suggests a way to include joint decision-making principles in the creation of flexible cybersecurity policies by looking at examples of successful applications and problems that different organizations have had. To successfully deal with problems that change, this framework stresses the need for flexible decision-making, open lines of communication, and regularly updated partner involvement. this paper also looks at how new tools can help people make decisions together and make it easier to use rules that change over time. Finally, the paper talks about the problems and possible futures in this area, pointing out obstacles to acceptance and suggesting more study and work in this area. Organizations can be more resistant to cyber dangers and better adapt to changes in the security scene if they encourage stakeholders to work together

关键词： Cyber attacks

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Evaluating the Efficiency of Index-Based Exchange-Traded Funds in the Indian Stock Market: A Case Study with Emphasis on BSE 12th

Evaluating the Efficiency of Index-Based Exchange-Traded Fun...

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12th international conference on Frontiers of intelligent Computing: theory and Applications, FICTA 2024

作者： Rambabu, Undabatla Bethu, Kalyan Kumar Ogirala, Naresh Deepika, K. Varalakshmi, Saikam Ravi Kiran Yasaswi, K. Navandar, Rajesh Kedarnath Andhra Pradesh Mylavaram India Affiliated to JNTUK Vijayawada India Department of Electronic and Telecommunication Engineering JSPM Jayawantrao Sawant College of Engineering Hadapsar Pune India

ISBN: (纸本)9789819601462

Exchange-traded funds (ETFs) have gained popularity among both retail and professional investors due to their cost-efficiency and high liquidity. A comprehensive study has been conducted on ETFs, with a focus on their correlation with benchmark indices such as the NSE/BSE in order to replicate market performance. By utilizing various statistical methods including mean, standard deviation, range, skewness, kurtosis, t-test, alpha, and beta values, the research aims to uncover the complex relationship between the performance of each fund and its benchmark. Moreover, performance models like the Sharpe index, Treynor, Jensen, and Sortino are utilized to calculate ratios, enabling the assessment and ranking of fund performance. Out of the 34 exchange-traded funds analysed, the study identifies LIC MF Exchange Traded Fund—Nifty 50 as the top performer. the findings of this research offer valuable insights for investors looking to select the most appropriate exchange-traded funds for their investment portfolios. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Decentralized finance

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A Inventive and Practical Method for Increasing the Precision of Machine Learning-Based Skin Disease Detection 12th

A Inventive and Practical Method for Increasing the Precisio...

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12th international conference on Frontiers of intelligent Computing: theory and Applications, FICTA 2024

作者： Usharani, G. Prabhakar, M. Rao Chintalapudi, S. Siddamma Narasimha, V. Rath, Dipika Department of IT CMR Engineering College Telangana Hyderabad India CMR Technical Campus Telangana Hyderabad India Department of CSE CMR Technical Campus Telangana Hyderabad India Department of CSE CMR College of Engineering and Technology Telangana Hyderabad India

ISBN: (纸本)9789819601424

Numerous individuals deal with numerous skin-related issues. Numerous people suffer from different skin conditions, which have historically been a prevalent human difficulty. Conventional approaches to skin condition diagnosis involve numerous tests, are thought to be time-consuming, and necessitate a deep grasp of the field. For the diagnosis, visual evaluation in conjunction with clinical data may be beneficial. Convolutional neural networks (CNNs) and an assembly representation built with VGG16, DenseNet, and Inception are the methods used in this technique. the particular skin disorders that have been taken into account are Actinic Keratoses, Basal Cell Carcinoma, Benign Keratosis, Dermatofibroma, Melanoma, Melanocytic Nevi, and Venous Lesions. the accuracy varies from 71 to 75% when using CNN, 80.3, 82.3, and 80.4% for VGG16, DenseNet, and Inception, respectively, while a mixture of VGG16, DenseNet, and Inception achieves 83–85% accuracy. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Convolutional neural networks

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Employing SVM and ANN for Feature Selection in Network Intrusion Detection Analysis 12th

Employing SVM and ANN for Feature Selection in Network Intru...

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12th international conference on Frontiers of intelligent Computing: theory and Applications, FICTA 2024

作者： Tiwari, Rajesh Rani, G S Sandhya Raju, K. Srujan Okali, Rakshitha Gurumoorthi, E. Sarkar, Nayan Department of CSE CMR Engineering College Telangana Hyderabad India CMR Engineering College Telangana Hyderabad India Department of CSE CMR Technical Campus Telangana Hyderabad India Department of CSE CMR College of Engineering & Technology Hyderabad India

ISBN: (纸本)9789819601387

the task of identifying unwanted or legitimate network traffic is to be performed by a supervised machine learning system. A mix of choosing features technique and supervised learning algorithm has been utilized to determine the optimal model taking detection effectiveness into account. this study shows that when it comes to network traffic classification, Artificial Neural Network (ANN) dependent machine learning enhanced wrapper choice of features performs better than Support Vector Machine (SVM) method. ANN and SVM supervised machine learning algorithms are employed to categorize network traffic employing the NSL-KDD dataset in order to assess performance. IDS has recently been deployed as an additional line of protection to effectively safeguard the networks. An intrusion detection system (IDS) is an application or equipment that keeps an eye on and evaluates data flow via the network in order to spot unusual or invasive data in the system. A comparison of approaches reveals that, in terms of intrusion detection effectiveness rate, the suggested model is more effective than other models already in use. Particularly now that technology is so important, we must advance with an upgrading mentality. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Network intrusion

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A Novel Investigation on Employing Deep Learning Techniques for Vehicle Monitoring and Identification in Real-Time Analysis 12th

A Novel Investigation on Employing Deep Learning Techniques ...

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12th international conference on Frontiers of intelligent Computing: theory and Applications, FICTA 2024

作者： Srinivasula Reddy, A. Sravanthi, G.S. Lavanya, R. Bhagyashree, B.K. Kirubakaran, S. Saidulu, G. Department of EEE CMR Engineering College Telangana Hyderabad India Department of CSE CMR Engineering College Telangana Hyderabad India CMR Technical Campus Telangana Hyderabad India Department of CSE CMR Technical Campus Telangana Hyderabad India Department of CSE CMR College of Engineering & Technology Telangana Hyderabad India

ISBN: (纸本)9789819601424

the study uses a variety of deep learning methods to address the issue of vehicle detection using aerial pictures. the photographs are taken by unmanned aerial vehicles (UAVs), providing us with a clear picture of every vehicle. the primary goal of this endeavor is to identify every kind of vehicle that is visible in the picture, making it helpful for a variety of tasks like counting cars, parking system empty slots, and analysis of traffic. Numerous deep learning methods are in use to detect automobiles. Deep learning techniques like You Look But Once (YOLO), Faster region-based convolutional neural network (Faster R-CNN), convolutional neural network–support vector machine (CNN–SVM), and single shot detector (SSD) are among them. Comparing the strategies employed by CNN–SVM, YOLO, SSD, and Faster R-CNN algorithms is the research's main goal. this report highlights both differences and parallels across various approaches and discusses the difficulties that lie ahead. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Convolutional neural networks

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Multiobject Detection and Distance Estimation System for Enhanced Spatial Awareness in the Visually Impaired People 12th

Multiobject Detection and Distance Estimation System for Enh...

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12th international conference on Frontiers of intelligent Computing: theory and Applications, FICTA 2024

作者： Reddy Muley, Rajesh BalaChowdeswari, M. Reshma, Sk. Siva Prakash, P. Jaya Prakash, Budeti Desai, Smita Department of Information Technology Lakireddy Bali Reddy College of Engineering Andhra Pradesh Mylavaram521230 India Electronics and Telecommunication Department Dr.D.Y Patil Institute of Technology Pune India

ISBN: (纸本)9789819601424

this research study introduces cutting-edge assistive technology that provides precise distance calculation and real-time object identification to enable people with vision impairments. With the help of the MobileNetV3 trained model, the system can recognize up to 91 distinct items at once, providing a thorough awareness of the user's surroundings. In addition to identifying particular items, the system evaluates the distances between various things in the field of vision and between the user and those objects. It utilizes sophisticated computer vision algorithms to provide reliable object detection and depth estimates, therefore mitigating the difficulties encountered by those with visual impairments. By using a well-crafted aural interface to provide distance information, the audio feedback function improves the user experience. through the provision of accurate and timely spatial layout information, our technology seeks to enhance the ability of visually impaired people to navigate and to become independently mobile. In order to guarantee successful integration into the everyday life of the visually handicapped, the research also addresses the difficulties in designing such systems, such as the requirement for real-time processing, environmental adaptation, and user-friendly aural feedback. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Real time systems

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Foreign Object Debris Detection Using YOLOv5 12th

Foreign Object Debris Detection Using YOLOv5

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12th international conference on Frontiers of intelligent Computing: theory and Applications, FICTA 2024

作者： Varshitha, Puttapaka Anvesh, Kachi Sai Yashwanth, N. Varun Prasad, Y. Ramesh Babu, A. Department of Information Technology Vardhaman College of Engineering Telangana Hyderabad501218 India

ISBN: (纸本)9789819601424

this research describes a technique for detecting the foreign object debris (FOD). foreign object debris (FOD) constitutes a significant and pressing challenge within the aviation industry, presenting a formidable threat to the safety of aviation operations. For ensuring the safety and cleanliness of airport runways is paramount for smooth aviation operations. Detecting and removing foreign object debris (FOD), especially the tiny and hard-to-spot varieties, is vital. An effective system capable of accurately identifying and swiftly removing FOD is necessary for the efficient maintenance of runway safety. there are different types of technologies available to detect foreign object debris. the most efficient method for detecting foreign object debris is millimeter-wave radar technology and it is resistant to weather. Additionally, millimeter-wave radar offers an affordable way to find (FOD) at a frequency of 96 GHz in less than 10 s while integrating with radio over fiber technology. To put it simply, the study emphasizes the necessity for a trustworthy method for identifying various FOD objects. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Convolutional neural networks

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CampusSight—College Management Automation Using Full Stack and RPA 12th

CampusSight—College Management Automation Using Full Stack ...

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12th international conference on Recent Trends in Computing, ICRTC 2024

作者： Manohar, Eashaan Duraimurugan, N. Vijay, K. Narayana, K.E. Department of Computer Science and Engineering Rajalakshmi Engineering College Chennai India Department of Artificial Intelligence and Machine Learning Rajalakshmi Engineering College Chennai India Department of Information Technology Rajalakshmi Engineering College Chennai India

ISBN: (纸本)9789819789450

the college management diaspora encapsulates various stakeholders such as students, faculty members, administrative personnel, and other staff. Unfortunately, most of the management workflows are undertaken manually, leading to silos, long paper work and admin overhauls. the pivotal aim of this research project is to digitalize the college management by bringing the entire setup into an intelligent application, leveraging key technologies like Automation, data analytics, full stack development. this application ultimately streamlines cumbersome tasks and enhance working across the college environment, promoting transparency and facilitating seamless interfaces for the entire user base. Swapping the monotonous manual workings with state-of-art digital platform will elevate the overall student experience by bringing down the high latency issue with the manual undertakings. Prime features of the application features management in terms of attendance, absences, on-duty requests, result disbursement, course registration, and facilitation of placement processes. Also, the system will promote enhanced organizing of events related to campus, industrial visits, increasing the net student engagement within the college and opening new opportunities. the system prioritizes core functionalities such as maintaining clean design and nimble experience, aligning with the increasing trend of digital transformation, granting greater college management autonomy. the application not only brings down the complexities prevailing in the existing college administration but also helps the higher education and placement processes alike, by leveraging key concepts like Data Analysis, Machine Learning and Artificial Intelligence from the data and insights stored, thereby adopting agile college management practices and emphasizing rapid digital growth, contributing to the entire education community. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Students

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