VISION TRANSFORMER USING FRACTIONAL GRADIENT ATTENTION TOOLS FOR ROBUST IMAGE CLASSIFICATION
Vision Transformers (ViTs) have attained very promising results in the field of computer vision, but those models continue to face several critical issues such as gradient saturation and poor generalization on smaller datasets. The current attention mechanisms are inefficient to resolve issues by the leading to ineffective feature extraction and an...
By S. Shalini, P.S. Eliahim Jeevaraj
IMPROVED STRESS STATE CALCULATION FOR GEOSYNTHETIC-ENCASED COLUMNS USING GRANULAR MEDIA MECHANICS
The paper is aimed at enhancing the computational method of Geosynthetic-Encased Columns (GECs) that enhance the engineering structures' foundations on weak soils. This method has proven to be effective in many projects, and the current technique fails to consider the distribution of stresses in the soil-filler, especially in loose soils. This stud...
By Kadhim A. Al-Abbas, Ali A. Al-Robay, Sura A. Saadoon
OPTIMIZED GIS-BASED RISK MAPPING OF WATER WALLS IN KIRKUK CITY
In Kirkuk City, Iraq, groundwater pollution is increasingly a problem due to intense urbanization, population growth, and unregulated water well drilling. Although the systematic assessment of groundwater pollution is essential to domestic and agricultural applications, the systematic analysis of its contamination has not been conducted, and the cu...
By Amel Nashat Shakir, Omar Falah Mirdan, Arjan Sharfuldeen Omar
ENERGY-EFFICIENT LOAD BALANCING AND INTERFERENCE-AWARE USER ASSOCIATION IN LARGE-SCALE HETNETS USING DISTRIBUTED MULTI-AGENT RL
Large-Scale Heterogeneous Networks (HetNets) are needed to deliver high capacity and reliable connectivity, as wireless communication demands. Nevertheless, the high density and diversity of base stations in the settings pose a great challenge in terms of Energy Efficiency (EE), Load Balancing (LB), and Interference Management (IM). Conventional ce...
By Pothula Pavan Kumar Reddy, C. Kamalanathan
NEURO ADAPTIVE METACOGNITIVE PROMPTING STRATEGIES FOR IMPROVING SELF REGULATED LEARNING AND CRITICAL THINKING IN PSYCHOLOGICAL SCIENCE EDUCATION
The growing recognition of Psychological Science education as a domain that demands higher-level thinking has revealed that students still exhibit chronic shortcomings in self-regulated learning (SRL) and critical thinking. Reports indicate that about 42% of undergraduate psychology students have low metacognitive monitoring accuracy, and more than...
By Nodira Fazilova, Khurshida Komilova, Olmos Avezov, Fatima Nazarova, Salima Akhmedova, Muzaffar Xaydarov, Rano Alimardanova
ENHANCING VOCABULARY ACQUISITION FOR NEURODIVERGENT LANGUAGE LEARNERS USING COGNITIVE LOAD OPTIMIZATION IN AUGMENTED REALITY
This paper examines whether or not Augmented Reality (AR) is effective in the acquisition of vocabulary in neurodivergent language learners using the Cognitive Load Theory. The conventional teaching methods tend to cause a lot of extraneous cognitive load that poses a great obstacle to students with ADHD and Autism Spectrum Disorder. To combat this...
By Durdona Niyozova, Doston Mizrobov, Akmal Allakuliev, Shakhnoza Khamdamova, Azizbek Ismailov, Zafarjon Toshboev, Shukhrat Khasanov
TECHNO-ECONOMIC ANALYSIS OF AN INTEGRATED SUGARCANE PROCESSING COMPLEX IN INDIA
This study focuses on a systematic techno-economic feasibility analysis of an integrated sugarcane processing complex in India. The comprehensive process modelling was performed using SuperPro Designer. The economic viability of an integrated sugarcane processing complex was assessed with significant economic parameters and other financial indices....
By ADITYA YADAV, Mithilesh Kumar Jha, Sachin Kumar
SECNET ARCHITECTURE FOR AI-DRIVEN ACCESS CONTROL AND REAL-TIME THREAT DETECTION IN BLOCKCHAIN SYSTEMS
Storage systems must be verifiably secure, and access control must be fine grained and transparent, and must provide audit trails for modern cyber-physical and cloud ecosystems. While blockchain ensures immutability and traceability of data, it does not have the ability to make real-time authorization decisions, identify abnormal behavior, or...
By Kummara Sruthi, N. Mallikharjuna Rao
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