Search
1967 articles for “P-dA” (ranking capped at the first 2,000 matches — narrow the search to see the rest)
-
Development and Characterization of Pseudo-Elastic Ternary Cu-Al-Be Shape Memory Alloy and Its Scope as Shape Memory Hybrid Composites
Abstract: This research investigated the potential of the Cu-11.95Al-0.51Be shape memory alloy (SMA) for vibration damping applications. This specific composition of the alloy was selected to ensure the presence of the austenite phase (ß-phase) and to evaluate the pseudo-elastic (SE) behavior. This research explores the design, fabrication, and characterization of a pseudo-elastic ternary alloy. The key parameters examined in this study were the alloy phase and pseudo-elastic behavior. Other important factors, …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 370–385 Read article
-
Optimization of Structural Health Monitoring Using Artificial Neural Network and Comparison with Traditional Method: A Comprehensive Review
Abstract: Structural health monitoring (SHM) has a critical role in ensuring civil infrastructure safety, reliability, and durability through real-time, condition-based monitoring. Traditional SHM systems employ hundreds of sensors such as accelerometers, strain gauges, and displacement transducers for monitoring vast amounts of data for structural inspection, but do not effectively manage complicated nonlinear data. This research paper, “Optimization of Structural Health Monitoring Using Artificial Neural Network and Comparison with Traditional Methods,” investigates …
Published in Journal of Structural Engineering and Management · Vol. 13, Issue 1, 2026 · pp. 23–33 Read article
-
Design and Implementation of an IoT-Enabled Autonomous Hexapod Robot for Enhanced Navigation and Remote Operations
Abstract: This system develops an autonomous hexapod robot using an ESP32 microcontroller and IoT technology. This robot can move on its own, avoiding obstacles without human help. It's equipped with various sensors like distance and ground slope sensors. These sensors provide data to the microcontroller, helping it control the robot's movements and steer clear of obstacles. The robot runs on a battery, ensuring it can operate for extended periods without human …
Published in Trends in Opto-electro & Optical Communication · Vol. 14, Issue 2, 2024 · pp. 14–20 Read article
-
Enhanced Multimodal Disease Prediction Using Hybrid Ensemble Learning and AutoML Techniques
Abstract: The integration of hybrid ensemble learning and automated machine learning (AutoML) is revolutionizing disease prediction by addressing the complexity, imbalance, and high dimensionality inherent in medical datasets. This paper proposes an advanced pipeline that combines diverse ensemble learning models with AutoML-based optimization to predict chronic diseases such as kidney diseas-e, Parkinson’s disease, and lung cancer. Publicly available datasets from UCI and PhysioNet repositories were preprocessed using outlier removal, normalization, and …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 1, 2026 Read article
-
A Study on the Role of Women’s Involvement in Fisheries and Aquaculture with Reference to the Mumbai Region
Abstract: Women play a crucial role in the fisheries and aquaculture sector, engaging in activities such as fish processing, marketing, and aquaculture management. Although they make major contributions, they frequently encounter socio-economic difficulties, such as limited access to funding, technological tools, and skill development opportunities. In the Mumbai region, women’s involvement in the fisheries industry is essential for economic sustainability, yet financial constraints and inadequate infrastructure restrict their growth and leadership …
Published in International Journal of Marine Life · Vol. 3, Issue 1, 2026 · pp. 1–5 Read article
-
Tank Water Quality Analysis Using Machine Learning
Abstract: Tank Water quality is a critical factor for public health, agriculture, as well as industry. Continuous monitoring of tank water quality: temperature, humidity, water level, CO2 concentration, and pH, is vital for safe usage. Using machine learning, real-time data analysis can detect anomalies, predict issues, and optimize water management, ensuring timely responses and improved safety. This intelligent approach enhances decision-making and maintains water quality effectively in various environments.We develop an …
Published in Journal of Control & Instrumentation · Vol. 16, Issue 2, 2025 · pp. 27–34 Read article
-
Perspectives on ‘Kamsaharitaki’: an Ayurvedic Formulation for COVID-19 related Multisystem Inflammatory Syndrome (MIS)
Abstract: Background and Aim: Angiotensin-converting enzyme 2 receptor (ACE2), together with Transmembrane protease serine 2 (TMPRSS2), is a protein receptor for SARS-CoV-2 virus in the host subject; expression of ACE2 and TMPRSS2 reveals the multidimensional character of COVID-19 infection. SARS-CoV-2 Prominently induces pulmonary and systemic injury with other synergistic mechanisms. Preexisting chronic inflammatory conditions markedly sustain and aggravate the severity and cytokine storm. Inflammatory responses are closely linked with COVID-19 severity …
Published in Journal of AYUSH: Ayurveda, Yoga, Unani, Siddha and Homeopathy Read article
-
4D Printing in Drug Delivery: Application of Shape- Morphing Materials in Controlled Drug Release
Abstract: Four-dimensional printing technology has transformed the pharmaceutical landscape, offering unprecedented opportunities for innovation in drug development and delivery. This emerging technology enables the creation of complex geometries and customized structures, facilitating the design of personalized medications tailored to individual patient needs. Personalized dosing and drug release profiles, customized pill shapes and sizes for improved swallowability. Enhanced drug solubility and bioavailability, rapid prototyping and testing of pharmaceutical products. Development of complex …
Published in Trends in Drug Delivery · Vol. 12, Issue 3, 2025 · pp. 08–16 Read article
-
Development of a Generative AI Model for Early Detection and Prevention of Electrical Faults in Thermal Power Plants
Abstract: Electrical faults in thermal power plants can lead to severe equipment damage, production downtime, and safety hazards if not detected in advance. This study presents the development of a Generative Artificial Intelligence (GenAI) model for the early detection and prevention of electrical faults using predictive analytics. The proposed framework integrates Generative Adversarial Networks (GANs) with deep learning (CNN) and machine learning algorithms (Random Forest, Logistic Regression) to enhance data diversity, …
Published in International Journal of Energy and Thermal Applications · Vol. 4, Issue 1, 2026 · pp. 1–10 Read article
-
Artificial Intelligence in Pharmacovigilance: Improving Drug Safety
Abstract: Artificial intelligence (AI) is revolutionizing pharmacovigilance (PV) by enhancing the detection, assessment, and prevention of adverse drug reactions (ADRs). This review examines how AI technologies – such as machine learning (ML), natural language processing (NLP), and big data analytics – tackle existing challenges in pharmacovigilance (PV), including issues like underreporting, large data volumes, and inefficiencies in data processing. AI improves drug safety by automating data collection, enabling real-time adverse event …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 1, 2025 · pp. 1–16 Read article
-
Impact of a Nurse-Led Work-Based Intervention on Job Performance and Job Satisfaction Among Nurses in Selected Hospitals in Erode
Abstract: Job satisfaction is a critical aspect of nurses’ professional lives, influencing patient safety, staff morale, productivity, performance, and overall quality of care. Higher levels of job satisfaction have been linked to improved patient outcomes. This study aimed to assess the level of job satisfaction among staff nurses before and after a nurse-led work-based intervention, evaluate the effectiveness of the intervention, and examine the association between posttest job satisfaction scores and …
Published in International Journal of Evidence Based Nursing And Practices · Vol. 4, Issue 1, 2026 · pp. 19–27 Read article
-
A Review of Machine Learning Applications in Web Data Mining
Abstract: The rapid development of Internet technology has resulted in a rapidly changing and intricate digital environment that requires new methods for organizing and evaluating online data. This study examines the use of machine learning (ML) in web data mining, focusing on its ability to extract relevant insights from huge amounts of online data. Web data mining, which is divided into three categories: content mining, structure mining, and use mining, uses …
Published in International Journal of Data Structure Studies · Vol. 3, Issue 1, 2025 · pp. 39–47 Read article
-
A Comprehensive Review on Impact of Natural Selection Leading to Convergence
Abstract: This tale explores the complex relationship between genetic creativity, adaptation and common ecological problems that is arranged by the master sculptor, natural selection. Convergence reveals the adaptive genius that runs throughout the structure of evolution and is an acknowledgment to the continued power of natural selection. This journey aims to solve the enigma of convergent evolution. Natural selection has been influencing every link in the complex web of life on …
Published in Research and Reviews : A Journal of Biotechnology · Vol. 14, Issue 1, 2024 · pp. 1–7 Read article
-
Blockchain Adoption in Indian Public Services: A Holistic Empirical Investigation
Abstract: The Indian public sector is pivotal in the country’s governance and public welfare. It is worth noting that there is a significant number of intermediaries involved in the execution of tasks that are compromising data transparency. Currently, the public sector banks lack standardization and validation as major obstacles in the deployment of blockchain technology. The research paper explores the scope and effectiveness of blockchain technology in India’s public sector through …
Published in Journal of Operating Systems Development & Trends · Vol. 11, Issue 3, 2024 · pp. 48–57 Read article
-
Cloud-based Application Development and Optimization
Abstract: As cloud computing powers today’s applications, optimizing cloud-based development is crucial to achieve performance, cost effectiveness, and scalability. This research focuses on enhancing the design, deployment, and maintenance of cloud applications, tackling challenges in resource management, scalability, and resilience. We specifically explore dynamic resource allocation algorithms that use predictive analytics for auto-scaling based on workload variations, aiming to cut costs while preserving high performance. The study also investigates cross-cloud optimization …
Published in Journal of Open Source Developments · Vol. 12, Issue 1, 2025 · pp. 37–42 Read article
-
Ethical Challenges in Natural Language Processing: A Comparative Study of Solutions Across Multiple Domains
Abstract: This comparative analysis investigates the ethical challenges associated with natural language processing (NLP) by reviewing and synthesizing insights from ten influential and widely cited publications in the field. As NLP technologies are increasingly integrated into domains such as healthcare, finance, education, and governance, ethical concerns related to algorithmic bias, data privacy, fairness, accountability, and system transparency have become more prominent. This paper systematically examines how different researchers conceptualize and address …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 13, Issue 1, 2026 · pp. 01–07 Read article
-
Diabetes Risk & Al Nutrition Assistant
Abstract: The rising prevalence of diabetes mellitus has emerged as a major global health challenge. Early identification of individuals at risk, combined with personalized lifestyle-based interventions, can significantly reduce future complications. This study presents an AI-driven Nutrition Assistant integrated with a Diabetes Risk Prediction model. The system uses a machine learning classification approach to estimate the likelihood of diabetes based on clinical and nutritional factors, including body mass index, glucose levels, …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 13, Issue 1, 2026 · pp. 31–38 Read article
-
Role of Satellite Data Assimilation on ERA-Interim and ERA5 Wave Parameter Ratios – A Case Study based on Year-long In-Situ Observations in the Bay of Bengal
Abstract: The rapid decline in the energy resources forced mankind to tap other forms of natural energy resources in the light of exponential increase in the demand due to over-population. The energy from ocean waves is one of the cleanest sources of energy available perennially that changes seasonally and is site-specific. To assess the wave power potential at any site, knowledge of the wave parameters such as wave height, period and …
Published in Journal of Remote Sensing & GIS · Vol. 16, Issue 1, 2025 · pp. 1–20 Read article
-
Scaling of Machine Learning Techniques in Medical Imagining and Biomedical Applications Concerning Healthcare
Abstract: Machine learning refers to a field within computer science enabling computers to learn without explicit programming. Stemming from artificial intelligence's study of pattern recognition and computational learning theory, machine learning develops algorithms capable of learning from vast datasets and making predictions. Its applications span diverse computing tasks like email filtering, network intrusion detection, optical character recognition, and computer vision, where conventional algorithm design proves challenging. Notably, in computer vision, a …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 1, 2024 · pp. 41–44 Read article
-
AI-Based Sentiment Analysis of Public Perception Under Bangabandhu Sheikh Mujibur Rahman
Abstract: Sheikh Mujibur Rahman, known as Bangabandhu, played a pivotal role in Bangladesh’s post-liberation period (1971–1975). Understanding public sentiment during his leadership is crucial for historical analysis. This study employs Artificial Intelligence (AI)-based Sentiment Analysis to examine public perception through archived newspapers, parliamentary speeches, and historical records. Using Natural Language Processing (NLP) techniques, including sentiment classification and opinion mining, we analyze textual data to assess the prevailing public mood during his …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 3, Issue 2, 2025 · pp. 21–29 Read article