MECHANICAL ANALYSIS OF STRESS AND DEFORMATION IN LITHIUM BATTERY ELECTRODES DURING CHARGE–DISCHARGE CYCLES
Problem: Lithium-ion batteries are normally inhibited by mechanical degradation under the influence of diffusion that leads to rapid charging of the batteries. The non-uniform lithium concentration gradients, which trigger internal strain, bending, and interfacial failure, contribute to this problem in thick, porous electrodes. While these risks ar...
By Israa Meften Hashim
VILLAGE ROOMS AS LIVING HERITAGE ARCHITECTURAL SPACE SOCIAL MEMORY AND INTANGIBLE PRACTICES IN RURAL TÜRKIYE
Village rooms (KÖY ODALARI) in the village of SUSUZOSMANIYE/AFYONKARAHISAR are a significant feature of the rural heritage of Anatolia, combining architectural features and sociocultural values like hospitality, solidarity, collective memory, and local governance. Though the village rooms have been analyzed from an architectural and typologica...
By Melike Gürman, Şerife Ebru Okuyucu
A MACHINE LEARNING FRAMEWORK FOR EVALUATING CONSUMER PERCEPTIONS OF AI-GENERATED INFLUENCERS COMPARED TO HUMAN INFLUENCERS IN BRAND PROMOTION
The growing popularity of AI-generated virtual influencers on platforms like Instagram, TikTok, and YouTube has brought about changes in digital marketing through scalable and controllable promotion strategies for brands. Unfortunately, there is still a lack of quantitative models to help compare and measure consumer perceptions about AI-generated ...
By P. Saravanan, V.M. Shenbagaraman, Saravanan Devadoss, N. Arunfred
EXAMINING THE RELATIONSHIP BETWEEN ARTIFICIAL INTELLIGENCE AND EMPLOYEE WELL BEING IN CUSTOMER CENTRIC ORGANIZATIONS
AI is rapidly redefining how customer-oriented companies conduct their businesses through process automation, decision-making, and improved customer service. However, the influence of AI is lacking regarding employee well-being. This paper is focused on researching the connection between AI adoption and employee well-being by assessing the effects ...
By K.R. Sowmya, Bhuvaneswari Gowthaman, R. Santhiya, J. Sathish Kumar, R. Elavarasan
QUANTUM BOLTZMANN MACHINES FOR HIGH DIMENSIONAL FEATURE SELECTION AND SPARSE REPRESENTATION IN AUTISM SPECTRUM DISORDER CLASSIFICATION
The classification of ASD from neuroimaging and behavioral information has not been easy owing to factors such as high dimensionality, non-linearity, and overfitting, among others. In this research, propose an innovative framework based on QBMs for feature selection and efficient representation for ASD classification. QBMs have been used to leverag...
By V. John Peter, P. Renukadevi, S. Annamalai, P. Manikandan
PSYCHOLOGICAL FACTORS INFLUENCING TOURISM BUSINESS PROMOTION AND SALES WITH AN AI-ASSISTED PROMOTIONAL FRAMEWORK
In recent times, tourism organizations have been requiring personalized promotional plans based on the preferences, behavior, and psychology of tourists. Traditional methods of promotion often target larger customer segments, which may not always suit individual tourism contexts. In such scenarios, this study will try to bridge the gap by consideri...
By L. Chandni, R Sangeetha
AN AI-DRIVEN DIGITAL TWIN FRAMEWORK LEVERAGING ONTOLOGIES, INTELLIGENT DATA MANAGEMENT, AND SIMULATION FOR SECURITY AND RESILIENCE IN 6G NETWORKS
The 6G wireless networks will be used in autonomous systems, extended reality, digital healthcare, and large-scale cyber-physical infrastructures, making it possible to provide applications they previously did not know to be intelligent and ultra-reliable communication. Nevertheless, 6G networks are quite complicated and heterogeneous, which are ch...
By P. Karunakaran, Ali Bostani, Salomov Gulom, S. Shantha Kumar, V. Manimala, T. Velmurugan, R. Praveenkumar
INTERPRETABLE TRANSFORMER-BASED VIBRATION ANALYSIS FOR ANOMALY DETECTION IN INDUSTRIAL SYSTEMS
The concept of monitoring conditions with the help of AI has become a significant aspect of Industry 4.0 that enhances machine reliability and provides predictive maintenance. However, the models of anomaly detection based on deep learning are not readily implemented because of their lack of interpretability. The article introduces a novel anomaly ...
By M. Mohamed Musthafa, A. Aafiya Thahaseen, R. Arulmozhi, S. Mohammed Ibrahim, S. Sangeetha, M. Rabiyathul Fathima, M. Gowthami, P. Esaiyazhini
E-VOTING SYSTEM USING BLOCK CHAIN TECHNOLOGY AND CONSENSUS ALGORITHMS FOR SECURE AND FAST TRANSACTIONS OF VOTES
This paper introduces a new E-voting system that uses the consensus algorithms to ensure secure, efficient, and transparent voting processes on the basis of blockchain. The suggested model combines a number of cryptographic methods and consensus algorithms to overcome the current issues related to the traditional voting systems, including slow proc...
By V. Malathi, R. Jaichandran
A ROBUST FEATURE ENGINEERING ARCHITECTURE INCORPORATING HYBRID SAMPLING AND SEMANTIC-STRUCTURAL CODE AUGMENTATION
The sophistication of the contemporary code has augmented defect prediction (SDP) with vital concerns like severe imbalance in classes, high redundancy of features and failure of conventional techniques to gain the rich semantic and structural context of a source code. The model suggested within the current paper is HDA-SE-GFF that has Semantic-Enr...
By P. Bhavani, N. Danapaquiame