FEDERATED LEARNING-BASED INTRUSION DETECTION FOR 6 G-ENABLED INTERNET OF THINGS IN SMART CITIES
The high rate of Internet of Things (IoT) device proliferation in smart cities, along with the emergence of 6G technology, has tremendously augmented the network traffic and the issue of security. This paper proposes a Federated Learning-based Intrusion Detection System (FL-IDS) specifically designed for 6G-enabled IoT networks. The new system help...
By Sanjay Kumar, Sapna Bawankar, Sindhusaranya Balraj
METARFM: A META-LEARNING FRAMEWORK FOR THE ADAPTIVE SELECTION OF RFM MODEL ARIANTS IN CUSTOMER SEGMENTATION
The Recency-Frequency-Monetary (RFM) model is a widely used method for customer segmentation, but its effectiveness depends on selecting the appropriate variant (e.g., weighted or entropy-based) for a given dataset. This selection process is typically manual and task-specific, leading to inconsistent results and limited generalizability. To address...
By F. Mary Magdalene Jane
AN ECOLOGICAL FRAMEWORK OF STUDENT RESILIENCE IN THE POST-PANDEMIC CONTEXT
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By Bobby Pudukaden, A. Martin Jayaraj
INTEGRATION OF IOT IN SMART BUILDING SYSTEMS FOR SUSTAINABLE URBAN DEVELOPMENT
The rapid growth of urban populations has exacerbated energy waste, resource inefficiency, and environmental degradation in contemporary cities, necessitating crucial, smart building solutions. This paper examines the incorporation of the Internet of Things (IoT) in intelligent buildings to facilitate sustainable urban development. The study helps ...
By Dawakit Lepcha, Kanchan Thakur
MARITIME TOURISM TRANSPORTATION MANAGEMENT AND DEVELOPMENT IN MALAYSIA: A BIBLIOMETRIC ANALYSIS
This study presents a bibliometric analysis of maritime tourism transportation management and development, emphasizing Malaysia’s contribution to global scholarship. Data were extracted from the Scopus database using title-based searches covering maritime tourism, island tourism, and transportation studies. A sample of 176 publications (1983 ...
By Shamsul Nazim Jaffar, Mohd Saiful Izwaan Saadon, Dina Azleema Mohamed Nor, Mohd Rizal Ismail, Loke Keng Bin, Nik Muhamad Afiz Harom @ Junoh
EXPLORING ABG IMBALANCES IN ICU PATIENTS USING MACHINE LEARNING SUPERVISED ALGORITHMS
Arterial Blood Gas (ABG) analysis is an important diagnostic tool in intensive care unit (ICU) settings that provides valuable information about the patient's respiratory and metabolic status. However, in the absence of predictive information, when testing is over-utilized or not planned, it can cause discomfort to the patient, costs to the healthc...
By S. Ramadoss, A. Kumaravel
HIGH-PERFORMANCE ONE-STAGE BOOSTING PFC CONVERTERS WITH ADVANCED CONTROL FOR ENHANCED POWER QUALITY AND STABILITY
This article introduces an advanced controller technique, as well as a One-Stage Boosting Power Factor Correction (OSBPFC) converter. The proposed approach is oriented towards the creation of more powerful features (PQ), more desirable stability, and adherence to fundamental principles for input interfaces. This technique, which distinguishes it fr...
By M. Devi, S. Lakshmi
DISASTER RECOVERY IN LARGE-SCALE DATABASES: DESIGNING EFFECTIVE FAILOVER AND BACKUP STRATEGIES
Within the database infrastructures of large-scale enterprises and government organizations, preserving swift and dependable disaster recovery processes continues to be particularly challenging with increasing data volumes and greater complexity in systems. This study conducts an evaluative analysis of advanced failover and backup methods, comparin...
By Harsha Vardhan Reddy Kavuluri
ONTOLOGY-ENABLED DIGITAL TWIN DESIGN WITH AI-BASED DATA MANAGEMENT AND PRIVACY-PRESERVING MECHANISMS FOR SECURE 6G COMMUNICATION SYSTEMS
Sixth generation (6G) communication networks are anticipated to facilitate the achievement of ultra-low latency, massive device connections, intelligent automation, and high-security in the end-to-end connectivity to accommodate new applications, including autonomous systems, immersive communications, and massive infrastructures of cyber-physical u...
By A. Mummoorthy, M. Rajeswari, K.S. Krishnapriya, S. Krithika, S. Suganya, Gafur Namazov, M. Nalini
A COMPARATIVE STRATIFICATION OF FISH SPECIES USING TRANSFER LEARNING ON PRE-TRAINED DEEP LEARNING NETWORKS JUXTAPOSED WITH SHUFFLERES – A HYBRID DEEP NETWORK CLASSIFIER
The marine ecoculture is an evolving realm that necessitates thorough scrutiny of the diverse species it comprises, along with the explicit identification of the species classes that form, to be crucial for aquaculture and the ecological conservation of fish diversity. The stratification through image classification is a well-studied area of resear...
By R.P. Selvam, R. Devi