Search
260 articles for “pre-trained models”
-
Impact of Adaptive Learning, LMS, and Personalized Skill Development on Industry Recruitment Alignment
Abstract: This paper discusses the impact of adaptive learning on the development of skill and self-learning, and it portrays a methodology framework to design an adaptive learning system that works with industry recruitment objectives. The paper distinguishes different approaches to learning, namely teacher-centric and student-centric, rigid and adaptive, competitive and collaborative, and explains that each learner has their own learning style, preference, and level of knowledge and skill acquisition. The paper …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 12, Issue 1, 2025 Read article
-
Machine Learning-Based Channel Estimation in 5G, Beyond-5G, and 6G Networks: Recent Advances and Future Directions
Abstract: Accurate channel estimation is one of the most fundamental challenges in modern wireless communication systems. In fifth- generation (5G) New Radio (NR) and emerging sixth-generation (6G) networks, precise knowledge of the wireless channel is essential for achieving reliable data transmission, high spectral efficiency, and low Bit Error Rate (BER). Conventional estimation techniques such as Least Squares (LS) and Minimum Mean Square Error (MMSE) rely on mathematical channel models and predefined …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 13, Issue 2, 2026 Read article
-
Improving Supply Chain Resilience through Predictive Analytics and Real-Time Data Integration
Abstract: Demand forecasting has under gone major changes because to the incorporation of automated analytics into supply chain management (SCM), which has improved company productivity, accuracy, and responsiveness. Central to this transformation is the application of machine learning (ML), which enables the analysis of large and complex datasets to identify patterns, detect trends, and generate precise forecasts. Conventional methods for predicting frequently rely on linear models and historical sales data, which …
Published in International Journal of Industrial and Product Design Engineering · Vol. 3, Issue 2, 2025 · pp. 8–17 Read article
-
Advancing Brain Tumor MRI Segmentation
Abstract: Segmentation of brain tumors in MRI scans is an integral part of neuroimaging carried out for diagnostic and therapeutic interventions. Given that manual segmentation is cumbersome and highly variable, there arises a need for automated, more precise segmentation solutions. This project, ‘Machine Learning and Deep Neural Networks to Advance Brain Tumor MRI Segmentation’ will develop a better, efficient, and accurate segmentation model to help clinicians identify brain tumors with greater …
Published in Recent Trends in Electronics Communication Systems · Vol. 12, Issue 2, 2025 · pp. 28–33 Read article
-
Face Aging Using Generative Adversarial Network
Abstract: This project addresses the challenge of predicting how a person may look in the future or how they appeared in the past using a single photograph. While existing methods mainly focus on altering texture, they often neglect changes in head shape that naturally occur during the aging process, limiting their effectiveness, especially when applied to images of children. To tackle this issue, a novel approach is introduced that employs a …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 1, 2025 · pp. 41–52 Read article
-
Integrated Qualitative Response Assessment System
Abstract: Examinations for universities and yearboards are traditionally administered offline, with a significant number of students opting for subjective exams. This preference stems from the labor-intensive nature of evaluating subjective responses, which requires considerable time and effort from educators. Additionally, subjective grading can be influenced by the evaluator’s mood, leading to inconsistencies. In contrast, multiple-choice and objective questions are prevalent in entrance and competitive exams due to their ease of automated …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 11, Issue 3, 2024 · pp. 18–24 Read article
-
Advancements in Intrusion Detection: Tackling Imbalanced Network Traffic with Machine Learning and Deep Learning Techniques
Abstract: Malicious cyberattacks can frequently hide enormous amounts of typical data in unbalanced network traffic. It is very stealthy and obfuscating in cyberspace, which makes it challenging for Network Intrusion Detection Systems (NIDS) to guarantee the precision and promptness of detection. This essay investigates. Machine learning and deep learning are utilized for intrusion detection in imbalanced network traffic. It offers a novel method for addressing the problem of class imbalance termed …
Published in Recent Trends in Electronics Communication Systems · Vol. 11, Issue 2, 2024 · pp. 18–24 Read article
-
Enhancing Credit Card Fraud Detection Using Device Fingerprinting and Behavioral Biometrics
Abstract: Credit card fraud is a growing global concern, with financial losses projected to reach $ 43.47 billion by 2028. Credit card fraud poses a major challenge in the financial industry, resulting in substantial financial losses and security risks. This research introduces a Machine Learning-based Credit Card Fraud Detection System designed to improve the accuracy of fraud identification. Due to the imbalanced nature of fraud datasets, SMOTE (Synthetic Minority Over-sampling Technique) …
Published in Journal Of Network security · Vol. 13, Issue 2, 2025 · pp. 40–50 Read article
-
Sign Language and Face Expression Recognition Using Neural Networks: Deep Learning Approach to Break Communication Barriers
Abstract: Our study proposes a multimodal gesture recognition system specifically designed to aid communication for the deaf community. By employing neural network concepts, we utilize 3D convolutional neural networks (3D CNNs) to extract features from both hand and face images, focusing on relevant regions. Preprocessing techniques are applied to isolate these areas of interest prior to feature extraction. Unique 3D CNN architectures are then trained for each modality to capture the …
Published in Current Trends in Signal Processing · Vol. 14, Issue 3, 2024 · pp. 1–10 Read article
-
Artificial Intelligence–Assisted Reduced-Order Modeling and Stability Control in Granular Couette Flow
Abstract: This study develops a reduced-order and stability-aware modeling framework for dense granular Couette flow by integrating continuum mechanics, bifurcation analysis, and data-driven stability estimation. Starting from coupled governing equations for momentum, granular temperature, and microstructural evolution, the system is nondimensionalized and reduced using a Galerkin projection consistent with shear-driven boundary conditions. This yields a low-dimensional nonlinear dynamical system that preserves the essential coupling between velocity, fluctuation energy, and structural relaxation. …
Published in Emerging Trends in Chemical Engineering · Vol. 13, Issue 3, 2026 Read article
-
Machine Learning Driven Mobile Price Prediction Using Feature Selection and Parameter Optimization
Abstract: Machine learning calculations are utilized in many fields like money, training, industry, medication, and online business. Machine learning calculations show execution contrasts relying upon the dataset and handling steps. Picking the right calculation, preprocessing and post-handling techniques have incredible significance in accomplishing great outcomes. The Random Forest classifier, K-nearest neighbor classifier, and support vector machine methods are evaluated to forecast mobile phone price categories. The “prediction” dataset which is taken …
Published in Current Trends in Information Technology · Vol. 14, Issue 3, 2024 · pp. 18–25 Read article
-
Impact of E-Learning on Secondary Education in Patna District: The Role of Teachers in Supporting Higher Secondary Students during the COVID-19 Crisis
Abstract: This study assesses the impact of e-learning on secondary education in the Patna district during the unprecedented COVID-19 crisis, focusing on the vital role of teachers in supporting higher secondary students. Utilizing a quantitative survey design with a sample of 150 higher secondary teachers from various schools in Patna, the research identifies both the benefits and significant challenges of the rapid transition to digital education. The findings confirm a major …
Published in Journal of Advancements in Library Sciences · Vol. 13, Issue 1, 2026 · pp. 28–32 Read article
-
AI Evaluator – Automated Examination Evaluation
Abstract: An AI system for automated exam grading is proposed. It tackles inefficiencies in human evaluation. The system uses TrOCR for accurate handwritten text recognition and a GPT model trained on graded responses for evaluation. This approach offers efficiency and reduced bias, but challenges remain. Evaluating open-ended questions and ensuring explainability require further development. It starts by looking at how AI technologies, such as machine learning, deep learning, and natural language …
Published in Trends in Opto-electro & Optical Communication · Vol. 14, Issue 1, 2024 · pp. 1–9 Read article
-
Investigating the Effect of Rational Emotional Behavioral Therapy Training on Sensitivity in Women’s & Mutual Relationships
Abstract: The topic of Haaz's research is to investigate the effect of rational-emotional behavioral therapy training on sensitivity in women's mutual relationships. The purpose of this research is to prepare and compile a program in which the concepts of the rational-emotional behavioral therapy approach are used in order to investigate sensitivity in women's mutual relationships after the implementation of its training to women. The statistical population includes 120 women with risky …
Published in International Journal of Behavioral Sciences · Vol. 1, Issue 2, 2024 · pp. 18–25 Read article
-
Electromagnetic Transients in Compensated Overhead Lines with Multiple Tower Spans
Abstract: This paper addresses the analysis of the electromagnetic transients developed in an important class of non-uniform high-voltage power lines. It deals particularly with compensated long overhead high- voltage transmission lines composed of several tower spans, which are connected in cascade. The derived mathematical model leads to a system composed of simultaneous partial differential and algebraic equations, which can be solved numerically in terms of parametric functions using the software Mathematica’s …
Published in Trends in Electrical Engineering · Vol. 15, Issue 2, 2025 · pp. 1–9 Read article
-
Analyzing The Electromagnetic Transients and Corona Performance of Long Overhead Lines with Multiple Tower Spans
Abstract: This paper addresses the simulation of the electromagnetic transients developed in an important class of non-uniform high voltage power lines. The resulting information is of paramount importance for the proper planning, design, operation and protection of electric power networks. It deals particularly with long overhead high voltage transmission lines composed of several tower spans which are connected in cascade. The presented approach considers eventually existing localized corona discharges at some …
Published in International Journal of Electrical and Communication Engineering Technology · Vol. 3, Issue 1, 2025 · pp. 35–44 Read article
-
Analysis and Identification of Malicious Mobile Applications Using Machines Learning
Abstract: Over the past few years, malware attacks on the Android platform have surged, posing significant risks to users' financial security, personal information, and device integrity. In the first half of 2019 alone, approximately 25 million smartphones were infected, highlighting the severity of these threats. The model ranks manifest features based on their frequency in normal and malicious apps, identifying key components that distinguish benign from malicious applications. To improve detection …
Published in Journal of Microcontroller Engineering and Applications · Vol. 12, Issue 2, 2025 · pp. 17–24 Read article
-
The Impact of Geographical Indications on Sustainable Rural Development: Comprehensive Economic and Cultural Insights from Wayanad, Kerala
Abstract: Geographical Indications (GIs) play a vital role in fostering sustainable rural development by linking unique local products to their geographic origins. This study explores the impact of GIs on economic growth, cultural preservation, and environmental sustainability in Wayanad, Kerala. Drawing from extensive secondary data and detailed case studies including Wayanad Coffee, Jeerakasala Rice, and traditional handicrafts, the research highlights how GI certification enhances market value, improves income levels, and preserves …
Published in International Journal of Rural and Regional Development · Vol. 3, Issue 2, 2025 · pp. 18–29 Read article
-
Adoption of Major Improved Crop Varieties in Selected Districts of the Southwest Ethiopia Region
Abstract: Agriculture forms the backbone of the Ethiopian economy and significantly contributes to the livelihoods of the majority of the population. It remains a central pillar of food security, employment, and rural development across the country.The present study aims to examine the adoption of improved major crop varieties and to identify the key factors influencing their uptake in the southwest Ethiopia region. The research was carried out in the districts of …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 15, Issue 2, 2026 · pp. 18–31 Read article
-
A Study of Clinical Education Practice of Clinical Instructors Accompanying Nursing Students of Kashmir Division, Deployed for Clinical Posting in SKIMS Soura
Abstract: Introduction: Clinical education also called clinical teaching, is one of the practical based approaches whereby the students are exposed to natural and practical settings. Clinical education refers to the process of educating and training healthcare professionals, such as medical students, nurses, or other allied health professionals, in a real-world clinical setting. This form of teaching is crucial for translating theoretical knowledge into practical skills and fostering the development of clinical …
Published in Journal of Nursing Science & Practice · Vol. 14, Issue 2, 2024 · pp. 32–38 Read article