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AMachine Learning Approach to User Profiling for Data Annotation of Online Behavior

computers, Materials & Continua 2024年第2期78卷 2419-2440页

作者： Moona Kanwal Najeed AKhan Aftab A.Khan Computer Science and Information Technology Department NED University of Engineering and TechnologyKarachiPakistan Computer Engineering Department Sir Syed University of Engineering and TechnologyKarachiPakistan College of Education Health and Human ServicesLongwood UniversityFarmvilleVAUSA

The user’s intent to seek online information has been an active area of research in user *** profiling considers user characteristics,behaviors,activities,and preferences to sketch user intentions,interests,and *** user characteristics can help capture implicit and explicit preferences and intentions for effective user-centric and customized content *** user’s complete online experience in seeking information is a blend of activities such as searching,verifying,and sharing it on social ***,a combination of multiple behaviors in profiling users has yet to be *** research takes a novel approach and explores user intent types based on multidimensional online behavior in information *** research explores information search,verification,and dissemination behavior and identifies diverse types of users based on their online engagement using machine *** research proposes a generic user profile template that explains the user characteristics based on the internet experience and uses it as ground truth for data *** feedback is based on online behavior and practices collected by using a survey *** participants include both males and females from different occupation sectors and different *** data collected is subject to feature engineering,and the significant features are presented to unsupervised machine learning methods to identify user intent classes or profiles and their *** techniques are evaluated,and the K-Mean clustering method successfully generates five user groups observing different user characteristics with an average silhouette of 0.36 and a distortion score of *** average is computed to identify user intent type *** user intent classes are then further generalized to create a user intent template with an Inter-Rater Reliability of 75%.This research successfully extracts different user types based on th

关键词： User intent cluster user profile online search information sharing user behavior search reasons

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Multisensor information Fusion for Condition Based Environment Monitoring

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Intelligent Automation & Soft Computing 2023年第4期36卷 1013-1025页

作者： A.Reyana P.Vijayalakshmi Department of Computer Science and Engineering Hindusthan College of Engineering and TechnologyCoimbatore641050India Department of Electronics and Communication Engineering Hindusthan College of Engineering and TechnologyCoimbatore641050India

Destructive wildﬁres are becoming an annual event,similar to climate change,resulting in catastrophes that wreak havoc on both humans and the *** result,however,is disastrous,causing irreversible damage to the *** location of the incident and the hotspot can sometimes have an impact on earlyﬁre detection *** the advancement of intelligent sen-sor-based control technologies,the multi-sensor data fusion technique integrates data from multiple sensor *** primary objective to avoid wildﬁre is to identify the exact location of wildﬁre occurrence,allowingﬁre units to respond as soon as *** to predict the occurrence ofﬁre in forests,a fast and effective intelligent control system is *** proposed algorithm with decision tree classiﬁcation determines whetherﬁre detection parameters are in the acceptable range and further utilizes a fuzzy-based optimization to optimize the complex *** experimental results of the proposed model have a detection rate of ***,providing real-time monitoring of certain environ-mental variables for continuous situational awareness and instant responsiveness.

关键词： Decision tree communication wildﬁre data fusion wireless sensor networks

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Introduction

Signals and Communication Technology

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Signals and Communication technology 2024年 Part F1492卷 3-17页

作者： Tian, Yu-Chu Gao, Jing School of Computer Science Queensland University of Technology BrisbaneQLD Australia College of Computer and Information Engineering Inner Mongolia Agricultural University Hohhot China

The main theme of this book is network analysis and architecture design for network planning. While there are various types of networks, this book specifically focuses on computer networks for data communication. Therefore, it uses the term networks to specifically refer to computer networks unless specified explicitly otherwise. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Skin lesion classification using transfer learning

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Soft Computing 2024年第20期28卷 12337-12343页

作者： Nivedhitha, G. Kalpana, P. Sidthik, A. Sheik Rani, V. Anusha Singh, Ajith B. Rajagopal, R. Department of Computer Science and Engineering Sri Krishna College of Technology Tamil Nadu Coimbatore India Department of Electrical and Electronics Engineering VSB College of Engineering and Technical Campus Tamilnadu Coimbatore642109 India Department of Electronics and Instrumentation Engineering Saveetha Engineering College Tamilnadu Chennai India Department of Electrical and Electronics Engineering Sri Krishna College of Technology Tamil Nadu Coimbatore India Department of Electrical and Electronics Engineering Francis Xavier Engineering College Tirunelveli India

This work presents an essential module for the Transfer Learning approach's classification of melanoma skin lesions. Melanoma, a highly lethal form of skin cancer, poses a significant health threat globally. Image analysis plays a crucial role in enhancing the accuracy of malignant skin lesion classification. Although neural networks trained on extensive datasets have emerged as the latest solution, their scalability remains a challenge. This study proposes an efficient method for classifying skin lesions utilizing labelled data from open sources, leveraging EfficientNet as the foundational model to robustly capture discriminative features from diverse visual perspectives. Validation of the proposed algorithms relies on the classifier's capacity to distinguish between classes is measured by the Area Under the Receiver Operating Characteristic (AUC-ROC) curve. AUC-ROC score greater than zero denotes better classification performance. Our proposed model achieves an impressive score of 98.65%. In contrast to existing approaches, our method demonstrates swift and accurate identification and segmentation of melanoma skin lesions, showcasing its efficacy in advancing the field of skin lesion classification. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Dermatology

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Resource Allocation and Task Offloading for Slicing-Based Communication and Computing in Space-Air-Ground Integrated Networks 21

Resource Allocation and Task Offloading for Slicing-Based Co...

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21st Annual IEEE International Conference on Sensing, Communication, and Networking, SECON 2024

作者： Song, Yueqian Yuan, Guiyuan Zeng, Qingtian Chen, Geng College of Electronic and Information Engineering Shandong University of Science and Technology China College of Computer Science and Engineering Shandong University of Science and Technology China

ISBN: (纸本)9798331519186

In the upcoming 6G era, the demand for network communication and computing is expected to surge and diversify. A Space-Air-Ground Integrated Network (SAGIN) is introduced as a solution to provide seamless global connectivity. Meanwhile, network slicing technology can further enhance network capabilities by supporting customized services. However, the joint optimization of multi-dimensional resource allocation and task offloading decisions presents a significant challenge in dynamic and complex environments with diverse task types. In this work, we establish an SAGIN paradigm that integrates network slicing. A multi-level optimization scheme for resource allocation and task offloading is proposed to improve Key Performance Indicators (KPIs) and Quality of Service (QoS). Specifically, we propose a State Encoding-based Multi-Agent Soft Actor-Critic algorithm (SE-MASAC) within a Centralized Training with Decentralized Execution (CTDE) architecture. This algorithm processes current sensing states and historical information, leveraging reinforcement learning to make inter-slice resource and offloading scheduling decisions. Intra-slice decisions for intelligent User Equipments (iUEs) are determined based on their sensing data-driven priority. Simulation results demonstrate that our approach outperforms baselines in terms of system utility, QoS satisfaction, and various KPIs. © 2024 IEEE.

关键词： Quality of service

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A deep learning-based early alzheimer’s disease detection using magnetic resonance images

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Multimedia Tools and Applications 2025年第16期84卷 16561-16582页

作者： Suchitra, S. Krishnasamy, Lalitha Poovaraghan, R.J. Department of Computer Science and Engineering Vel Tech Rangarajan Dr. Sagunthala R &D Institute of Science and Technology Avadi Tamil Nadu Chennai India Department of Information Technology Nandha Engineering College Tamil Nadu Erode India Department of Information Technology Jaya Engineering College Tamil Nadu Thiruninravur Chennai India

Alzheimer’s Disease (AD) is a degenerative, chronic condition of the brain for which there is now no effective treatment. However, there are medications that can slow its development. In order to stop and control the development of AD, earlier diagnosis of the disease is quintessential. Our proposed method’s primary objective is to establish a comprehensive model for the prior detection of Alzheimer’s disease and the categorization of distinct AD stages. This work employs a deep learning methodology, especially CNN. The proposed approach makes use of well-known models that have already been trained to classify medical images, like the EfficentNetB7 model, by applying the transfer learning principle. In order to achieve greater accuracy, convolutional neural networks (CNNs) are frequently scaled up as new resources become available at a fixed cost throughout the construction phase. A compound coefficient is used by the CNN architecture and scaling approach, which is the foundation of the pre-trained EfficientNetB7 model, to scale the dimensions equally. This proposed EfficientNetB7 model is quicker, easier, and more effective than other pre-trained models like VGG19 and InceptionV3. The proposed model includes simple structures that have memory requirements, provide manageable time, overfitting, and low computational complexity as well as training and inference speeds. The Alzheimer’s disease Neuroimaging Initiative (ADNI) dataset was employed for a comprehensive assessment of the method proposed, utilizing well-known performance metrics including sensitivity, specificity, and accuracy. The findings revealed that the improvised results achieved the accuracy metric when compared to existing methods. The EfficientNetB7 model has been enhanced, and this model achieves a sensitivity of 98.08%, specificity-98%, accuracy-98.2%, and F-score-98.95%, for multi-class AD stage classifications. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, par

关键词： Magnetic resonance

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Hybrid Approach for Privacy Enhancement in Data Mining Using Arbitrariness and Perturbation

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computer Systems science & engineering 2023年第3期44卷 2293-2307页

作者： B.Murugeshwari S.Rajalakshmi K.Sudharson Department of Computer Science and Engineering Velammal Engineering CollegeChennai600066India Department of Information Technology Velammal Institute of TechnologyChennai601204India

Imagine numerous clients,each with personal data;individual inputs are severely corrupt,and a server only concerns the collective,statistically essential facets of this *** several data mining methods,privacy has become highly *** a result,various privacy-preserving data analysis technologies have ***,we use the randomization process to reconstruct composite data attributes ***,we use privacy measures to estimate how much deception is required to guarantee *** are several viable privacy protections;however,determining which one is the best is still a work in *** paper discusses the difficulty of measuring privacy while also offering numerous random sampling procedures and statistical and categorized data ***-more,this paper investigates the use of arbitrary nature with perturbations in privacy *** to the research,arbitrary objects(most notably random matrices)have"predicted"frequency *** shows how to recover crucial information from a sample damaged by a random number using an arbi-trary lattice spectral selection *** system's conceptual frame-work posits,and extensive practicalfindings indicate that sparse data distortions preserve relatively modest privacy protection in various *** a result,the research framework is efficient and effective in maintaining data privacy and security.

关键词： Data mining data privacy arbitrariness data security perturbation

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Brain Tumor Diagnosis Using Sparrow Search Algorithm Based Deep Learning Model

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computer Systems science & engineering 2023年第2期44卷 1793-1806页

作者： G.Ignisha Rajathi R.Ramesh Kumar D.Ravikumar T.Joel Seifedine Kadry Chang-Won Jeong Yunyoung Nam Department of Computer Science and Business Systems Sri Krishna College of Engineering and TechnologyCoimbatore641008India Department of Information Technology Sri Krishna College of TechnologyCoimbatore641008India Department of Electronics and Communication Engineering Kings Engineering CollegeChennai602117India Department of Electronics and Communication Engineering R.M.K.Engineering CollegeChennai601206India Deparmtent of Applied Data Science Noroff University CollegeKristiansandNorway Medical Convergence Research Center Wonkwang UniversityIksanKorea Department of Computer Science and Engineering Soonchunhyang UniversityAsanKorea

Recently,Internet of Medical Things(IoMT)has gained considerable attention to provide improved healthcare services to *** earlier diag-nosis of brain tumor(BT)using medical imaging becomes an essential task,auto-mated IoMT and cloud enabled BT diagnosis model can be devised using recent deep learning *** this motivation,this paper introduces a novel IoMT and cloud enabled BT diagnosis model,named *** IoMTC-HDBT model comprises the data acquisition process by the use of IoMT devices which captures the magnetic resonance imaging(MRI)brain images and transmit them to the cloud ***,adaptive windowﬁltering(AWF)based image preprocessing is used to remove *** addition,the cloud server executes the disease diagnosis model which includes the sparrow search algorithm(SSA)with GoogleNet(SSA-GN)*** IoMTC-HDBT model applies functional link neural network(FLNN),which has the ability to detect and classify the MRI brain images as normal or ***ﬁnds useful to generate the reports instantly for patients located in remote *** validation of the IoMTC-HDBT model takes place against BRATS2015 Challenge dataset and the experimental analysis is car-ried out interms of sensitivity,accuracy,and speciﬁ*** experimentation out-come pointed out the betterment of the proposed model with the accuracy of 0.984.

关键词： Internet of medical things healthcare brain tumor disease classiﬁcation deep learning metaheuristics

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Hybrid Optimization Algorithm for Handwritten Document Enhancement

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computers, Materials & Continua 2024年第3期78卷 3763-3786页

作者： Shu-Chuan Chu Xiaomeng Yang Li Zhang Václav Snášel Jeng-Shyang Pan College of Computer Science and Engineering Shandong University of Science and TechnologyQingdao266590China School of Information and Control Engineering Qingdao University of TechnologyQingdao266520China Faculty of Electrical Engineering and Computer Science VŠB-TU OstravaOstrava70080Czech Republic Department of Information Management Chaoyang University of TechnologyTaichung41349Taiwan

The Gannet Optimization Algorithm (GOA) and the Whale Optimization Algorithm (WOA) demonstrate strong performance;however, there remains room for improvement in convergence and practical applications. This study introduces a hybrid optimization algorithm, named the adaptive inertia weight whale optimization algorithm and gannet optimization algorithm (AIWGOA), which addresses challenges in enhancing handwritten documents. The hybrid strategy integrates the strengths of both algorithms, significantly enhancing their capabilities, whereas the adaptive parameter strategy mitigates the need for manual parameter setting. By amalgamating the hybrid strategy and parameter-adaptive approach, the Gannet Optimization Algorithm was refined to yield the AIWGOA. Through a performance analysis of the CEC2013 benchmark, the AIWGOA demonstrates notable advantages across various metrics. Subsequently, an evaluation index was employed to assess the enhanced handwritten documents and images, affirming the superior practical application of the AIWGOA compared with other algorithms.

关键词： Metaheuristic algorithm gannet optimization algorithm hybrid algorithm handwritten document enhancement

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Intelligent Orchestrating of IoT Microservices Based on Reinforcement Learning

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Chinese Journal of electronics 2022年第5期31卷 930-937页

作者： WU Yuqin SHEN Congqi CHEN Shuhan WU Chunming LI Shunbin WEI Ruan College of Computer Science and Technology Zhejiang University College of Information and Electrical Engineering Ningde Normal University Zhejiang Lab College of Control Science and Engineering Zhejiang University

With the recent increase in the number of Internet of things(IoT) services, an intelligent scheduling strategy is needed to manage these services. In this paper, the problem of automatic choreography of microservices in IoT is explored. A type of reinforcement learning(RL) algorithm called TD3 is used to generate the optimal choreography policy under the framework of a softwaredefined network. The optimal policy is gradually reached during the learning procedure to achieve the goal, despite the dynamic characteristics of the network environment. The simulation results show that compared with other methods, the TD3 algorithm converges faster after a certain number of iterations, and it performs better than other non-RL algorithms by obtaining the highest reward. The TD3 algorithm can effciently adjust the traffic transmission path and provide qualified IoT services.

关键词： software-defined network telecommunication scheduling intelligent orchestrating nonRL algorithms reinforcement learning software defined networking optimal choreography policy reinforcement learning algorithm Internet of things services network environment IoT microservices TD3 algorithm traffic transmission path Internet of Things qualified IoT services intelligent scheduling strategy dynamic characteristics

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