Search
1143 articles for “research performance”
-
Morphological, Phenological and Yield assessment of Cosmic Yantras on Solanum lycopersicum L. and Pisum sativum L. crop plants under normal climatic conditions
Abstract: Vegetables are edible plants or parts of plants (roots, stems, leaves, flowers and seeds) that are consumed for their nutritional value. They are rich in vitamins, fiber and antioxidants. The study was conducted in cropping season (April to October 2024) to observe the comparative effect of cosmic yantras and organic manures on growth and morphology of Pisum sativum and Solanum lycopersicum under normal climatic conditions. The objective of this research …
Published in Research & Reviews : Journal of Botany · Vol. 15, Issue 3, 2026 Read article
-
Evaluation of Antenna Performance using a Novel Measurement Device: Methodology and Results
Abstract: In the last decade, the field of On Chip Antennas (OCA) has experienced unprecedented growth due to the introduction of small, low-cost, low-power System-on-Chip (SoC) wireless communication devices. OCAs are superior to conventional off-chip antennas in a number of ways. They first reduce the overall size of the wireless communication system since the presence of an OCA eliminates the need for an impedance matching network between the antenna and RF …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 11, Issue 1, 2024 · pp. 24–29 Read article
-
Ocular Films as a Drug Delivery System Against Fungal Infections: Current Insights and Future Directions
Abstract: Fungal infections of the eye, including keratitis, endophthalmitis, and blepharitis, represent a challenging class of ocular diseases due to their potential for vision loss and the limited efficacy of existing treatments. These infections are caused by a range of pathogenic fungi, such as Aspergillus, Candida, and Fusarium species, and often require long-term therapeutic intervention. Conventional topical antifungal therapies, such as eye drops and ointments, suffer from poor ocular bioavailability due …
Published in Trends in Drug Delivery · Vol. 12, Issue 2, 2025 · pp. 101–109 Read article
-
Critical Review on Photocatalytic Polymer Nanocomposites for Indoor Air Purification in Hotels
Abstract: The indoor air quality has become a key measure of health, comfort, and customer satisfaction of a hospitality setting. The challenges that continually affect hotels especially because of volatile organic compounds (VOCs), particulate matter, and microbial pollutants that are present in cleaning agents, furnishing, and human activity. In this regard, the photocatalytic polymer nanocomposites are one of the sustainable and efficient means of purifying indoor air. These materials combine photocatalysts …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 527–541 Read article
-
Investigation of Exergy and Energy with Fibre Reinforced Plastic Composite (FRP) Tube Based Solar Still using PCM material via Theoretical and Computational Approach
Abstract: A FRP (Fibre Reinforced Polymer) material-based solar still is an advanced design approach in solar desalination systems, where the traditional construction materials (like metal or concrete) are replaced or enhanced with FRP composites. A FRP composite material tubular solar still is a lightweight desalination equipment with a substantial condensing area in comparison to other types of solar stills. Nonetheless, their effectiveness is often limited by fluctuating climatic circumstances. This study …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 66–78 Read article
-
Enhancing Image Classification Performance with Deep Neural Networks
Abstract: Classifying images is useful in many domains, including the study of plant diseases and the analysis of human expressions. Image categorization employing the idea of a “deep neural network” helps to compact otherwise cumbersome photos. It is possible to classify images by using the idea of a “deep neural network”. Self-driving cars, medical diagnosis, automatic translation, etc., all make use of Deep Neural Networks. Recently, excellent results have been achieved …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 11, Issue 1, 2024 · pp. 13–23 Read article
-
IoT-enhanced Real-time Monitoring and Hazard Detection
Abstract: This research explores the innovative application of internet of things (IoT) technology within occupational health and safety management systems (OHSMS) to substantially improve real-time monitoring and hazard detection in industrial settings. IoT sensors and wearable devices are deployed to enable continuous and thorough collection of data on environmental conditions, equipment status, and worker health. Real-time data analysis facilitated by IoT technology allows for the rapid identification and mitigation of potential …
Published in Journal of Industrial Safety Engineering · Vol. 11, Issue 2, 2024 · pp. 20–24 Read article
-
Need For EPDS in Indian High-Rise Constructions for Reduced Greenwashing and Sustainable Future with Green Polymer and Composites
Abstract: Environmental product declarations (EPDs) are a globally recognized means of communicating the environmental impacts of a product or service across its entire lifecycle. They evaluate various items' environmental performance and pinpoint enhancement chances. EPDs are very useful in the construction industry since they may be used to choose environmentally friendly building materials and techniques. India is undergoing a swift construction surge, with high-rise towers becoming progressively prevalent.. However, the construction …
Published in Journal of Polymer & Composites · Vol. 12, Issue 7, 2024 · pp. 54–66 Read article
-
Cybersecurity in Web Automation: A Machine Learning Approach to Lightweight Intrusion Detection
Abstract: Launch-Attack is a lightweight and practical threat-detection framework designed specifically for smaller web-automation environments, including setups that rely on tools such as Selenium. Rather than aiming to replace large enterprise-grade security platforms, the framework focuses on offering an accessible option for developers, testers, and researchers who need real-time monitoring without the heavy resource demands of traditional systems. The model relies on machine-learning techniques implemented through Scikit-learn, enabling it to detect …
Published in Journal of Web Engineering & Technology · Vol. 13, Issue 1, 2026 · pp. 34–40 Read article
-
Cutting-edge Deep Learning Methods for Predicting and Detecting Cardiovascular Diseases
Abstract: Cardiovascular diseases (CVDs) remain a major global health issue, highlighting the need for improved early detection and risk assessment methods. This research investigates the efficacy of both deep learning and traditional machine learning methods in forecasting cardiovascular diseases (CVDs). We evaluate a variety of models, including Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Multilayer Perceptrons (MLPs), Long Short-Term Memory (LSTM) networks, as well as Logistic Regression (LR), Decision Trees …
Published in Recent Trends in Parallel Computing · Vol. 11, Issue 2, 2024 · pp. 36–42 Read article
-
High Expectations, Low Outcomes: Exploring Coping Mechanisms and Psychological Adaptation
Abstract: This review paper explores the psychological impact of high expectations and low outcomes, focusing on coping mechanisms to manage the resulting emotional and mental challenges. The anticipation of a guaranteed future often elevates self-esteem and brings a state of emotional ecstasy. When individuals perceive the future in alignment with their personal terms and conditions, they experience heightened happiness and acceptance of life. This sense of assurance often influences risk-taking capacity, …
Published in International Journal of Trends in Humanities · Vol. 2, Issue 2, 2025 · pp. 31–38 Read article
-
Exploration of Advanced Phase Change Materials for Thermal Energy Storage in Renewable Energy Systems: An Overview
Abstract: Phase Change Materials (PCMs) are increasingly vital for improving thermal energy storage (TES) systems. Their ability to absorb and release heat efficiently makes them ideal for renewable energy applications, enhancing energy efficiency, reducing waste, and supporting sustainable energy solutions across various sectors like solar power and building temperature regulation. Their ability to store and release latent heat during phase transitions makes them ideal for addressing the intermittency of renewable energy …
Published in Journal of Thermal Engineering and Applications · Vol. 12, Issue 3, 2025 · pp. 10–14 Read article
-
Assessing the Robustness of Machine Learning Models for Wireless Intrusion Detection Under Adversarial Traffic Perturbations
Abstract: As the Internet of Things (IoT) devices and wireless communication networks continue to grow rapidly, protecting systems from cyber threats has become increasingly important. Machine learning–based intrusion detection systems (IDS) have shown strong potential in detecting abnormal and malicious network activities, yet their effectiveness and resilience when facing adversarial attacks are still not sufficiently explored. This research evaluates Machine Learning (ML) models–XGBoost, random forest, and multi-layer perceptron (MLP)—in detecting attacks …
Published in International Journal of Wireless Security and Networks · Vol. 4, Issue 1, 2026 · pp. 29–34 Read article
-
Utilization and Socioeconomic Impact of Biofuel Adoption Among Farming Communities in Fatehgarh Sahib, Punjab
Abstract: With the increasing consumption of energy and environmental issues, transformation toward renewable energy is being considered as a trend globally. Biofuels such as biogas and biodiesel provide potential alternative to fossil based fuel, particularly, in the rural parts of India, including Punjab. These clean sources, however, are not only contributing to environment but also have a potential to improve the rural economy by saving costs and having better health. Despite …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 15, Issue 1, 2026 · pp. 38–45 Read article
-
Thermally Adaptive Bio-Inspired VLSI Interconnect Model for Next-Generation Embedded Systems
Abstract: The increasing complexity of next-generation embedded systems has intensified the challenges associated with power dissipation, thermal instability, signal integrity, and interconnect reliability in Very Large- Scale Integration (VLSI) architectures. This research proposes a thermally adaptive bio-inspired VLSI interconnect model designed to enhance communication efficiency and thermal resilience in advanced embedded platforms. The proposed model integrates bio-inspired adaptive routing principles with dynamic thermal-aware interconnect management to optimize data transmission under varying …
Published in Journal of VLSI Design Tools and Technology · Vol. 16, Issue 2, 2026 Read article
-
Explainable Artificial Intelligence in Personalized Medicine: Emerging Clinical Perspectives
Abstract: The convergence of artificial intelligence (AI) and precision medicine has transformed contemporary healthcare by enabling data-driven clinical decision-making, individualized therapeutic interventions, and predictive diagnostics. However, despite remarkable advances in machine learning (ML) and deep learning (DL), the widespread adoption of AI in healthcare remains constrained by the “black-box” nature of many computational systems. Clinicians, regulatory agencies, and patients increasingly demand transparency, interpretability, and trustworthiness in AI-guided medical recommendations. Explainable Artificial …
Published in Emerging Trends in Personalized Medicines · Vol. 3, Issue 2, 2026 · pp. 13–29 Read article
-
Nitrosamine Accumulation, Processing Variables, and Indigenous Plant Inhibitors in Nigerian Traditionally Processed Meats
Abstract: N-nitrosamines are classified as probable or possible human carcinogens by the International Agency for Research on Cancer. Carcinogenic N-nitrosamines — principally N-nitrosodimethylamine (NDMA) and N-nitrosodiethylamine (NDEA) — are formed in abundance during the preparation of widely consumed Nigerian traditional processed meats including suya, kilishi, and balangu. This original investigation combined a six geopolitical zone of Nigerian market survey with laboratory-controlled model system experiments, effects of processing parameters on N-Nitrosamine formation …
Published in Journal of Modern Chemistry & Chemical Technology · Vol. 17, Issue 1, 2026 · pp. 61–72 Read article
-
The Heat of Competition: Assessing Climate Vulnerabilities and Adaptive Governance in Endurance, Winter, and Youth Sports
Abstract: Background: Climate change is fundamentally reshaping the environmental parameters of global sport, posing unprecedented risks to athlete health, safety, and performance. As rising temperatures, frequent extreme heat events, and deteriorating air quality become the new normal, athletic environments from community fields to elite international arenas face an existential threat. Purpose: This study provides an interdisciplinary synthesis of the multifaceted impacts of climate change on athletes, integrating evidence from sports medicine, …
Published in International Journal of Climate Conditions · Vol. 2, Issue 2, 2025 · pp. 9–17 Read article
-
Design and Performance Assessment of Light Weight Data Security System for Secure Data Transmission in IoT
Abstract: The Internet of Things (IoT) is expected to provide an interface for future technologies’ small processing tools. It is expected to provide more communication data and information security can risky. Data pinnacles and information security can be a risk. This size of the gadget in this engineering is essentially little, low power utilization. Many rounds of encryption are essentially a misuse of requirements Gadget vitality. Less convoluted calculation, be that …
Published in Journal Of Network security Read article
-
Enzyme Stability Prediction using BERT and CNN-A Deep Learning Approach for Enhanced Biocatalysis
Abstract: An important factor in determining the efficacy of industrial enzymes used in various biotechnological applications is their stability. The goal of this study is to develop a predictive model for industrial enzyme stability, which is essential to the efficiency of these enzymes in biotechnological applications. The research takes a comprehensive strategy to comprehend the parameters affecting enzyme stability by combining statistical analysis, deep learning algorithms (BERT and CNN), and molecular …
Published in Research and Reviews : A Journal of Life Sciences · Vol. 14, Issue 2, 2024 · pp. 19–35 Read article