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An Improved K-means Clustering Algorithm Towards an Efficient Data-Driven Modeling

Annals of Data Science 2024年第5期11卷 1525-1544页

作者： Zubair, Md. Iqbal, MD. Asif Shil, Avijeet Chowdhury, M.J.M. Moni, Mohammad Ali Sarker, Iqbal H. Department of Computer Science and Engineering Chittagong University of Engineering & ampTechnology Chittagong4349 Bangladesh Department of Computer Science and Information Technology La Trobe University Victoria3086 Australia School of Health and Rehabilitation Sciences Faculty of Health and Behavioural Sciences The University of Queensland St Lucia QLD4072 Australia

K-means algorithm is one of the well-known unsupervised machine learning algorithms. The algorithm typically finds out distinct non-overlapping clusters in which each point is assigned to a group. The minimum squared distance technique distributes each point to the nearest clusters or subgroups. One of the K-means algorithm’s main concerns is to find out the initial optimal centroids of clusters. It is the most challenging task to determine the optimum position of the initial clusters’ centroids at the very first iteration. This paper proposes an approach to find the optimal initial centroids efficiently to reduce the number of iterations and execution time. To analyze the effectiveness of our proposed method, we have utilized different real-world datasets to conduct experiments. We have first analyzed COVID-19 and patient datasets to show our proposed method’s efficiency. A synthetic dataset of 10M instances with 8 dimensions is also used to estimate the performance of the proposed algorithm. Experimental results show that our proposed method outperforms traditional kmeans++ and random centroids initialization methods regarding the computation time and the number of iterations. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022.

关键词： Principal component analysis

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Semantic Search Engine, Thai Traditional Medicine Knowledge Graph Application 13

Semantic Search Engine, Thai Traditional Medicine Knowledge ...

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13th International Electrical engineering Congress, iEECON 2025

作者： Sakulpakdee, Natthinan Narischat, Nattavee Srisomboon, Kanabadee Lee, Wilaiporn Pipanmekaporn, Luepol Prayote, Akara King Mongkut's University of Technology North Bangkok Faculty of Apply Science Department of Computer and Information Science Bangkok Thailand King Mongkut's University of Technology North Bangkok Faculty of Engineering Department of Electrical and Computer Engineering Bangkok Thailand

ISBN: (纸本)9798331543952

In this paper, a semantic information retrieval framework is presented to improve the precision of search results by concentrating on the context of concepts is presented. Instead of the keyword matching technique, the graph theory is used for leveraging the relationships and meanings of search terms. information is represented as a knowledge graph for semantic searching performed by the inference engine and results are passed to the NLP technique for interpreting entity, relationship and property to their relevancy query. In the current system, we focused on healthcare system to helping the foundation recommendations of Thai Traditional Medicine. Once Thai Traditional Medicine contains a numerous of words which have the same meaning, the traditional keyword based cannot retrieve all relevant document. In our proposed semantic architecture, the query is performed an context-based understanding for retrieving all relevant document, therefore, it can retrieve the same number of documents for the queries which have the same meaning. © 2025 IEEE.

关键词： Online searching

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Invariant of Enhanced AES Algorithm Implementations Against Power Analysis Attacks

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computers, Materials & Continua 2022年第7期72卷 1861-1875页

作者： Nadia Mustaqim Ansari Rashid Hussain Sheeraz Arif Syed Sajjad Hussain Department of Electronic Engineering Dawood University of Engineering&TechnologyKarachiPakistan Faculty of Engineering Sciences and Technology Hamdard UniversityKarachiPakistan Faculty of Information Technology Salim Habib UniversityKarachiPakistan Faculty of Computer Sciences SZABISTKarachiPakistan

The security of Internet of Things(IoT)is a challenging task for researchers due to plethora of IoT *** Channel Attacks(SCA)are one of the major *** prime objective of SCA is to acquire the information by observing the power consumption,electromagnetic(EM)field,timing analysis,and acoustics of the ***,the attackers perform statistical functions to recover the *** Encryption Standard(AES)algorithm has proved to be a good security solution for constrained IoT *** paper implements a simulation model which is used to modify theAES algorithm using logicalmasking *** invariant of the AES algorithm hides the array of bits during substitution byte transformation of *** model is used against SCAand particularly Power Analysis Attacks(PAAs).Simulation model is designed on MATLAB *** will give better solution by hiding power profiles of the IoT devices against *** future,the lightweight AES algorithm with false key mechanisms and power reduction techniques such as wave dynamic differential logic(WDDL)will be used to safeguard IoT devices against side channel attacks by using Arduino and field programmable gate array(FPGA).

关键词： Side channel attacks power analysis attacks network security masking advance encryption standard

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DaC-GANSAEBF:Divide and Conquer-Generative Adversarial Network-Squeeze and Excitation-Based Framework for Spam Email Identification

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computer Modeling in engineering & Sciences 2025年第3期142卷 3181-3212页

作者： Tawfeeq Shawly Ahmed A.Alsheikhy Yahia Said Shaaban M.Shaaban Husam Lahza Aws I.Abu Eid Abdulrahman Alzahrani Department of Electrical Engineering Faculty of Engineering at RabighKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Electrical Engineering College of EngineeringNorthern Border UniversityArar91431Saudi Arabia Center for Scientific Research and Entrepreneurship Northern Border UniversityArar73213Saudi Arabia Department of Information Technology College of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Information and Communication Technology College of Computing StudiesArab Open UniversityKuwait BranchKuwait City13033Al-SafatState of Kuwait Department of Information Systems and Technology College of Computer Science and EngineeringUniversity of JeddahJeddah23218Saudi Arabia

Email communication plays a crucial role in both personal and professional contexts;however,it is frequently compromised by the ongoing challenge of spam,which detracts from productivity and introduces considerable security *** spam detection techniques often struggle to keep pace with the evolving tactics employed by spammers,resulting in user dissatisfaction and potential data *** address this issue,we introduce the Divide and Conquer-Generative Adversarial Network Squeeze and Excitation-Based Framework(DaC-GANSAEBF),an innovative deep-learning model designed to identify spam *** framework incorporates cutting-edge technologies,such as Generative Adversarial Networks(GAN),Squeeze and Excitation(SAE)modules,and a newly formulated Light Dual Attention(LDA)mechanism,which effectively utilizes both global and local attention to discern intricate patterns within textual *** approach significantly improves efficiency and accuracy by segmenting scanned email content into smaller,independently evaluated *** model underwent training and validation using four publicly available benchmark datasets,achieving an impressive average accuracy of 98.87%,outperforming leading methods in the *** findings underscore the resilience and scalability of DaC-GANSAEBF,positioning it as a viable solution for contemporary spam detection *** framework can be easily integrated into existing technologies to enhance user security and reduce the risks associated with spam.

关键词： Email spam fraud light dual attention squeeze and excitation divide and conquer-generative adversarial network-squeeze and excitation-based framework security

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Anomaly Detectionin Network Traffic Scenarios by Resampling and Majority Voting with Concept Drift: A Hybrid Approach 11

Anomaly Detectionin Network Traffic Scenarios by Resampling ...

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11th International Conference on Reliability, Infocom Technologies and Optimization, ICRITO 2024

作者： Singh, Richa Srivastava, Nidhi Kumar, Ashwani Amity Institute of Information Technology Amity University Lucknow Campus Lucknow India Srm Institute of Science & Technology Computer Science and Engineering Faculty of Engineering & Technology Ghaziabad India

ISBN: (纸本)9798350350357

Addressing data imbalance is a critical difficulty in the setting of a heavily skewed dataset because the dominant class disproportionately influences classifier accuracy, especially when inadequate data impede the learning of minority class characteristics. For multi-class cases, traditional binary classification approaches are inadequate. The suggested architecture uses a Weighted Majority Voting Classifier (WMVC), noise cleaning, limited under-sampling, and oversampling to overcome this. One important step is to set an average class size limit by dividing the entire sample number by the number of classes. One or more majority classes receive Random Under sampling, all minority classes receive an up sample using the Adaptive Synthetic Sampling Approach, and noise reduction is achieved via Tomek Link. The resulting WMVC is contrasted with Convolutional Neural Network (CNN) classifiers, XGBoost, and six additional ensemble techniques by utilizing tree-based ensemble algorithms. Comparative study shows that balanced data performs better than unbalanced data. WMVC significantly beats CNN, XGBoost, and the other ensemble methods, and it improves performance for difficult minority classes while successfully decreasing classifier bias towards the majority class. © 2024 IEEE.

关键词： Anomaly detection

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6G Non-Terrestrial Networks for Intelligent IoT Services

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IEEE Network 2024年第4期38卷 6-8页

作者： Jia, Min Chen, Hsiao-Hwa Chang, Zheng Zhang, Ning Wu, Zhibin Harbin Institute of Technology School of Electronics and Information Engineering National Cheng Kung University Department of Engineering Science University of Jyvaskyla Faculty of Information Technology University of Windsor Department of Electrical and Computer Engineering CETC Potevio Science & Technology Company Ltd.

Recently, the Internet of Things (IoT) has been considered for its applications in diverse settings, such as intelligent urban environments, advanced manufacturing facilities, and environmental surveillance. However, significant obstacles exist in the implementation of these IoT solutions due to various issues, such as heterogeneity, diverse application requirements, restricted resources, and massive connectivity. To tackle these issues, merging satellite-based networks with conventional ground-based networks has been proposed as an effective and affordable option for enhancing IoT device connectivity.

关键词： Special issues and sections 6G mobile communication Internet of Things Security Sensors Semantics Resource management computer architecture Collaboration Intelligent systems

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Multi-objective Cluster-head-based Energy-aware Routing using a Separable Convolution Neural Network in a Wireless Sensor Network

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IEIE Transactions on Smart Processing and Computing 2024年第2期13卷 105-112页

作者： Ather, Danish Mary, J. Prisca Singh, Pooja Garg, Kanika Priyadharshini, T.R. Princy, B. Anni Tiwari, Mohit Department of IT and Engineering Amity University in Tashkent Uzbekistan Department of Computer Science and Engineering NPR College of Engineering and Technology Tamil Nadu Dindigul India Department of Physics Faculty of Science SGT University Haryana Gurugram India Department of Computer Science and Engineering SRM Institute of Science and Technology NCR Campus Ghaziabad Modinagar India Department of Information Technology Hindusthan College of Engineering and Technology Pollachi main road Coimbatore India Department of Computer and Communication Panimalar Engineering College Tamil Nadu Chennai India Department of Computer Science and Engineering Bharati Vidyapeeth’s College of Engineering Delhi India

Wireless sensor network (WSN) applications are added day by day owing to numerous global uses (by the military, for monitoring the atmosphere, in disaster relief, and so on). Here, trust management is a main challenge. Sensor nodes are important in wireless sensor networks, but they are easily depleted because of their short lifespan from continuous sensing activity and low battery capacity. So efficient energy utilization is a challenging task in a WSN. To minimize energy loss, clustering with an optimum path selection process is needed to retain energy in sensor nodes. This manuscript proposes multi-objective Pelican Optimization Algorithm (POA) routing to maintain energy efficiency and minimize transmission distances in wireless sensor networks. A cluster head (CH) is selected by using a Separable Convolution Neural Network (SCNN). Simulation outcomes prove the proposed technique attains 22.3% and 25.04% improvements in energy consumption when compared to the Multi-Objective CH Energy-aware Optimized Routing Approach at WSN (MOCH-EORA-WSN) and Multiple Optimum Cluster Head Multi-Objective Grasshopper Optimization with Harmony-search at WSN (MOCH-MOGOH-WSN), respectively. © 2024 Institute of Electronics Engineers of Korea. All rights reserved.

关键词： Energy utilization

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Proposed 3D chaos-based medical image cryptosystem for secure cloud-IoMT eHealth communication services

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Journal of Ambient Intelligence and Humanized Computing 2024年第1期15卷 1-28页

作者： El-Shafai, Walid Khallaf, Fatma El-Rabaie, El-Sayed M. El-Samie, Fathi E. Abd Department of Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University Menouf32952 Egypt Security Engineering Lab Computer Science Department Prince Sultan University Riyadh11586 Saudi Arabia Department of Electrical Engineering Faculty of Engineering Ahram Canadian University Giza 6th October City Egypt Department of Information Technology College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University Riyadh84428 Saudi Arabia

Medical image encryption is a mandatory process in various healthcare, Internet of Medical Things (IoMT) and cloud services. This paper provides a robust cryptosystem based on a 3D chaotic map for the medical image encryption in secure IoMT and cloud services. The proposed encryption method depends on a 3D chaotic map. With this map, a nonlinear ciphering process is implemented for pixel value diffusion and position permutation. Five operations are conducted in the suggested cryptosystem on the medical images to be transmitted in order to attain a high security level. These operations are 3D chaos generation, chaos histogram equalization, row rotation, column rotation, and XOR operation. To validate the suggested cryptosystem, different medical images with different characteristics are tested. Moreover, the suggested cryptosystem and more recent state-of-the-art security systems are discussed and analyzed in a comparative study. Different assessment parameters are adopted to assess the suggested cryptosystem, which reveals high security performance. The simulation outcomes show that the suggested cryptosystem is trustworthy. Furthermore, it offers high robustness levels and recommended security levels for utilization in healthcare, IoMT and cloud service applications. It is observed that the amount of average entropy obtained by the proposed 3D chaos cryptosystem is 7.95 which is very close to its best value of 8, and the average NPCR value is 99.62% which is also much close to its supreme value of 99.60%. In addition, all other results scored for the test evaluation parameters on the suggested cryptosystem are superior to those of the traditional security systems. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022.

关键词： Cryptography

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Transmission scheme based on collaborative AUV communication 16

Transmission scheme based on collaborative AUV communication

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16th International Conference on Signal Processing Systems, ICSPS 2024

作者： Sun, Jiahao Qi, Chao Liu, Zengli Zhao, Xuanzhi Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming650500 China Computer Center Kunming University of Science and Technology Kunming China

ISBN: (纸本)9781510689251

Underwater wireless sensor networks can monitor ocean information, which provides a new approach to marine environmental monitoring, disaster warning and resource exploration. However, the development of underwater wireless sensing networks is limited by factors such as ocean currents and limited energy of the sensors themselves. Based on this situation, this paper proposes a transmission scheme based on collaborative communication with autonomous underwater vehicles (AUVs), in which autonomous underwater vehicles (AUVs) are used as a tool for distributed data collection and forwarding, which can solve the problem of imbalanced energy consumption of sensor nodes in the traditional multi-hop underwater communication network. At the same time, we consider the influence of ocean currents on the node positions to maximize the imitation of the real underwater environment, and the simulation results show that the proposed transmission scheme for collaborative communication with AUVs can significantly prolong the service life of underwater sensor networks. © 2025 SPIE.

关键词： Autonomous underwater vehicles

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Smart Street Lighting for Enhancing Energy Efficiency in Urban Environments 32

Smart Street Lighting for Enhancing Energy Efficiency in Urb...

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32nd International Conference on Software, Telecommunications and computer Networks, SoftCOM 2024

作者： Krizanovic, Visnja Pejkovic, Ana Pracny, Patrik J.J. Strossmayer University of Osijek Faculty of Electrical Engineering Computer Science and Information Technology Osijek Croatia

ISBN: (纸本)9789532901382

In the ever-evolving landscape of urban development, innovative solutions are constantly sought to improve the quality of life of residents. Moving away from conventional static street lighting, one such transformative solution for residential environments is smart street lighting. This intelligent solution brings an increase in energy efficiency. In this paper, the goal is to analyze the implementation of smart street lighting within the concept of a smart city based on the possibilities of saving and efficient use of energy. In selected case studies of urban scenarios, through simulation procedures, the possibility of implementing smart lighting was analyzed from the point of view of energy saving, indicating the importance of this aspect in the context of building smart energy lighting systems in urban environments. The discussions given in the paper show a quantitative assessment of energy savings in urban areas by replacing traditional lighting systems. The results of the analyzes show that the analyzed solutions provide useful guidelines for the application of the concept of smart lighting in urban environments and the selection of suitable solutions with regard to possible reductions in energy costs. © 2024 University of Split, FESB.

关键词： energy efficiency smart cities Smart street lighting

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