Search
206 articles for “perforation patterns”
-
Scholarly Communications of Annamalai University on Web of Science in Global Perspective: A Scientometric Assessment
Abstract: Annamalai University has a prolific research output spanning various fields such as agriculture, medicine, engineering, humanities, and social sciences. With state-of-the-art facilities and dedicated faculty, the university consistently produces impactful research findings that contribute to advancements in knowledge and address societal challenges. Its research endeavors are characterized by innovation, interdisciplinary collaboration, and a commitment to excellence, making Annamalai University a significant hub for cutting-edge research in India and beyond. The …
Published in Journal of Advancements in Library Sciences · Vol. 12, Issue 3, 2025 · pp. 1–10 Read article
-
Interest Level Prediction in Rental Properties Using Data Science
Abstract: A key component of forecasting home prices and rental patterns is real estate market analysis. Data science, data mining methodologies, and statistical models are some of the strategies that have been created in recent years to solve this problem. A few problems are still required to be resolved, such as the obstacles caused by the availability and quality of the data; the presence of outliers, missing values, and inconsistent formats …
Published in Recent Trends in Parallel Computing · Vol. 11, Issue 1, 2024 · pp. 28–34 Read article
-
Development of Polymer–Micro-Aluminum Composites for Lightweight Engineering Applications
Abstract: This research focuses on the systematic development of polymer–micro aluminum composites, with polypropylene (PP) and epoxy selected as representative polymer matrices. Micro aluminum fillers in the range of 5–25 wt.% were incorporated through melt blending (PP) and casting (epoxy), and the resulting composites were evaluated in terms of mechanical performance, microstructural integrity, and crystalline characteristics. Tensile strength of the composites increased significantly, from 31 MPa in neat PP to 44 …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 1–12 Read article
-
High-Velocity Impact Response of CFRP and Hybrid Composites: A Comprehensive Review on Ballistic Resistance and Damage Mechanisms
Abstract: This review consolidates recent advances in the study of high-velocity impact response of carbon fiber reinforced polymer and hybrid composites. Carbon fiber reinforced polymer composites are widely applied in aerospace, automotive, and defense due to their high strength-to-weight ratio, stiffness, and durability. However, their susceptibility to impact damage such as delamination, matrix cracking, and fiber breakage limits their performance under dynamic loading. To overcome these challenges, researchers have explored reinforcement …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 100–122 Read article
-
Optimizing Power Generation from Building Ventilation Systems: A Study on Exhaust Fan Efficiency
Abstract: Due to population growth, the world's energy consumption has increased dramatically in both wealthy and developing nations in recent years, and by 2042, it is predicted to have doubled or more. Since a few years ago, the use of innovative sustainable power sources to meet energy demands has been gradually increasing. We've chipped away at a different idea because of this. As an alternative energy source, renewable energy (RE) resources …
Published in International Journal of Electrical Power and Machine Systems · Vol. 1, Issue 2, 2023 · pp. 22–27 Read article
-
Noise-Driven Collective Behavior in Mean-Field Coupled Lorenz Oscillator Networks
Abstract: This work investigates the spatiotemporal dynamics of an ensemble of 100 identical Lorenz oscillators coupled through a mean-field scheme in the presence of additive noise. Building on prior studies of spatiotemporal chaos in coupled Lorenz arrays and mean-field coupled chaotic oscillators, the focus is on how the competition between deterministic coupling and stochastic forcing shapes collective behavior, including complete synchronization, desynchronization, clustered states, and noise-modified spatiotemporal chaos. The governing equations …
Published in International Journal of Advanced Control and System Engineering · Vol. 4, Issue 2, 2026 Read article
-
Assessing the Performance of DL Methods in Handwritten Digit Recognition
Abstract: Handwritten digit recognition is a computer vision task that involves the automatic identification and classification of hand-written digits. The objective is to develop models capable of accurately recognizing and distinguishing digits handwritten by humans. With the development of machine learning and deep learning techniques, this field has advanced remarkably. The convolutional neural network (CNN) is the most often used technique for this purpose. By utilizing CNN, the model can learn …
Published in International Journal of Data Structure Studies · Vol. 1, Issue 1, 2023 · pp. 25–32 Read article
-
Intersection Safety in Urban Environments: A Review of Risk Factors and Crash Patterns
Abstract: Urban intersections are critical points of interaction between multiple road users, including cars, buses, two-wheelers, cyclists, and pedestrians. As cities continue to expand rapidly, the density and complexity of traffic at intersections increase, making them among the most dangerous segments of the roadway network. Numerous studies show that intersections account for nearly half of all urban road crashes, making them central to safety research and planning. This review paper synthesizes …
Published in Journal of Industrial Safety Engineering · Vol. 13, Issue 1, 2026 · pp. 31–35 Read article
-
Database-Driven Energy Management in Electric Vehicles
Abstract: With the growing concern over environmental pollution, there is an increasing demand for sustainable and eco-friendly technologies. Among these, electric vehicles (EVs) have emerged as a promising alternative to conventional fossil-fuel-based transportation. However, as EV adoption accelerates, efficient energy management becomes critical to enhance vehicle performance, extend battery life, and ensure overall system reliability. This research presents a Database-Driven Energy Management System (DBEMS) that leverages real-time data from EV components …
Published in Journal of Automobile Engineering and Applications · Vol. 12, Issue 3, 2025 · pp. 19–24 Read article
-
Hybrid Intelligence in Cyber Security: A Study
Abstract: The digital landscape is a battlefield of escalating complexity, where the volume, velocity, and sophistication of cyber threats have exponentially outpaced human-centric defense models. Traditional rule-based security systems and siloed artificial intelligence (AI) solutions, while valuable, are increasingly brittle, overwhelmed by zero-day exploits, polymorphic malware, and coordinated, state-sponsored campaigns that operate in the shadows of big data. This paper posits that the paradigm of cybersecurity must fundamentally shift from one …
Published in International Journal of Wireless Security and Networks · Vol. 4, Issue 1, 2026 · pp. 01–09 Read article
-
Development Of Ai-Driven Systems for Real-Time Joint Movement Detection and Correction in Frozen Shoulder Therapy Using Sensor-Based Shoulder Rehabilitation Devices
Abstract: Frozen shoulder, or adhesive capsulitis, is a common musculoskeletal disorder characterized by progressive pain, stiffness, and restricted range of motion that significantly impairs functional ability and quality of life. Recent advancements in artificial intelligence and sensor-based technologies have enabled the development of intelligent rehabilitation systems capable of real-time joint movement detection and correction. Wearable sensors such as inertial measurement units, electromyography sensors, and flexible strain sensors capture continuous biomechanical data …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 15, Issue 1, 2026 Read article
-
Comprehensive Thermal and Environmental Investigation of An Enhanced Evacuated Tube Solar Water Heater with Wavy Tape and Latent Heat Storage
Abstract: Evacuated tube solar collectors (ETSCs) are widely used for thermal energy applications; however, enhancing their thermal and exergetic efficiency remains a challenge. This study investigates performance enhancements through structural and material alterations. Four ETSC cases were tested experimentally, case-1: a standard ETSC, case-2: Wavy tape (WT) inserted ETSC, case-3: Phase change material (PCM) integrated ETSC, and case-4: Dual-Enhanced ETSC (PCM + WT). A binary eutectic PCM was utilized for latent …
Published in Journal of Refrigeration, Air conditioning, Heating and ventilation · Vol. 12, Issue 2, 2025 · pp. 1–16 Read article
-
Morphological Heterogeneity and Ethnic Patterning of Anthropometric Traits in Ethiopian Inter-Scholastic Athletes
Abstract: Introduction: Anthropometric characteristics such as body size, proportions, and composition are fundamental determinants of morphological suitability for sport. Ethiopia’s significant ethnic diversity suggests potential variability in these traits; however, systematic data on anthropometric differences among adolescent athletes from different ethnic and demographic backgrounds remain limited. Understanding these variations is critical for talent identification and sports specialization at the school level. Methods: A cross-sectional study was conducted among inter-scholastic athletes representing …
Published in Recent Trends in Sports · Vol. 3, Issue 1, 2026 · pp. 25–34 Read article
-
Enhance Thermal and Conductive Properties through Graph Neural Network-Based Machine Learning-Driven Advanced Polymer Material Design
Abstract: Advanced polymer materials are widely used in modern engineering and manufacturing because of their lightweight nature, flexibility, durability, and adaptability to different applications. However, designing polymer materials with enhanced thermal and electrical properties remains a challenging task. The performance of polymers is influenced by a complex combination of molecular structures, filler materials, processing parameters, and nanoscale interactions. Conventional optimization methods often require extensive experimental trials and computational resources, making it …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 Read article
-
Gypsum Addition in Moulding Sand to Manufacture Defect Free Tin Castings
Abstract: Sand molding is a versatile casting process that provides freedom of design with respect to size, shape, and product quality. Plaster casting is similar to sand molding process except that a plaster is substituted instead of sand. Plaster compound is composed of gypsum, which strengthens the mould. Parts made by this process are gears, valves, fittings, tooling, and ornaments. The finished product of plaster casting has a very high surface …
Published in International Journal of Fracture Mechanics and Damage Science · Vol. 1, Issue 2, 2023 · pp. 7–15 Read article
-
Advances in Analytical Chemistry Research Methodology: Trends and Applications
Abstract: Analytical chemistry is critical to scientific study because it allows for the accurate identification, measurement, and characterization of chemical compounds. Recent advances in methodology have improved accuracy, sensitivity, and efficiency, with techniques such as High-Performance Liquid Chromatography (HPLC), Gas Chromatography (GC), Mass Spectrometry (MS), and Nuclear Magnetic Resonance (NMR) spectroscopy transforming analytical procedures. The combination of Artificial Intelligence (AI) and Machine Learning (ML) has enhanced data processing, pattern recognition, and …
Published in Journal of Thin Films, Coating Science Technology & Application · Vol. 12, Issue 2, 2025 · pp. 10–18 Read article
-
AI/ML-Based Approach to Solar Irradiance Prediction and Energy Suitability
Abstract: In this paper, due to challenges in precisely predicting solar irradiance, which is essential for solar power system optimization, we employed six diverse machine learning (ML) techniques: Linear Regression, Decision Tree, Random Forest, Gradient Boosting methods (including XGBoost), and Neural Networks—to analyze and predict outcomes using a dataset containing meteorological and temporal features. Key variables include wind speed, humidity, and temperature, which significantly influence the model’s predictive capability. Each method …
Published in Journal of Alternate Energy Sources & Technologies · Vol. 16, Issue 3, 2025 · pp. 36–48 Read article
-
Assessment of Matrix Cracking and Fiber Breakage in Hybrid Composite Materials.
Abstract: Hybrid composite materials, combining two or more distinct fiber or matrix constituents, have emerged as advanced structural solutions for aerospace, automotive, marine, and civil engineering applications. However, their complex microstructure makes them susceptible to multiple interacting damage mechanisms, particularly matrix cracking and fiber breakage. This study provides a comprehensive assessment of these damage modes, emphasizing their initiation, evolution, and combined effects on the mechanical integrity of hybrid composites. Matrix cracking …
Published in International Journal of Fracture Mechanics and Damage Science · Vol. 3, Issue 2, 2025 · pp. 1–5 Read article
-
Formulation Challenges in Long-acting Injectable Small Molecules: Emerging Strategies and Perspectives
Abstract: Long-acting injectable (LAI) formulations represent a transformative approach in pharmacotherapy, particularly for conditions demanding sustained drug exposure over weeks to months. Although biologics have dominated this space historically, the adaptation of LAI technology to small molecules presents a distinct and complex set of challenges rooted in physicochemical properties, manufacturing scalability, and regulatory expectations. This review systematically addresses the principal formulation barriers encountered in developing LAI small-molecule products, including aqueous solubility …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 13, Issue 2, 2026 Read article
-
Olfactory Intelligence in Bio-Hybrid UAVs: Integrating Living Lepidoptera Sensors for High-Precision Environmental Monitoring
Abstract: Autonomous aerial systems still face major challenges when attempting to locate airborne volatile organic compounds because many conventional gas sensors react slowly and cannot reliably follow turbulent chemical plumes. To address this limitation, a bio-hybrid sensing approach was explored using the antenna of the silkworm moth, Bombyx mori, as a natural chemical detector. The antenna was connected to an Electroantennogram (EAG) system that converts biological nerve signals into digital signals …
Published in International Journal of Electrical and Communication Engineering Technology · Vol. 4, Issue 2, 2026 Read article