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674 articles for “patterns”
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A Comparative Study of Deep Learning Methods for Depression Detection in Social Media Data
Abstract: With the rise of social media platforms like Twitter, Reddit, and Facebook, individuals increasingly share personal information about their moods, behaviors, and mental states. This trend provides a unique opportunity to leverage large-scale textual data for understanding and monitoring mental health conditions, particularly depression, a prevalent and challenging mental health issue. Traditional depression assessments are often confined to clinical environments and lack the capacity for real-time monitoring. In contrast, social …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 3, 2025 · pp. 55–65 Read article
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Solid acidity of MoO3 synthesized by solution combustion method and acetalization of formaldehyde using it
Abstract: MoO 3 nanoparticles were synthesized via solution combustion approach. Ammonium nitrate was used as oxidant and ammonium molybdate as fuel in combustion reaction. XRD, FTIR and Raman spectroscopy results showed that MoO 3 nanoparticles were successfully synthesized by the solution combustion reaction. The SEM analysis showed that synthesized MoO 3 nanoparticles have rod-like shape with width and thickness of 50-200nm and length of 0.2-1μm, respectively. The XRD pattern and morphology …
Published in Journal of Catalyst & Catalysis · Vol. 12, Issue 3, 2025 · pp. 01–09 Read article
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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
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Progression of Health and Wellness: Artificial Intelligence (AI) and Deep Learning (DL) for Precision Medicines
Abstract: Deep learning and artificial intelligence in the field of precision medicine is revolutionizing healthcare to make personalized therapeutic approaches desirable based on the unique characteristics of the patient. AI technologies improve diagnostic accuracy by analyzing medical data, spotting patterns and anomalies that human experts may miss. AI-driven models are instrumental in precision medicine, where they can predict patient response to therapies to tailor treatment plans, enhancing outcomes and reducing adverse …
Published in Emerging Trends in Personalized Medicines · Vol. 2, Issue 2, 2025 · pp. 1–5 Read article
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Cybersecurity of AI and IoT Integrated for Mechanical Industries
Abstract: By facilitating the concept of Industry 4.0, the intersection of artificial intelligence (AI) and the Internet of Things (IoT) has changed the mechanical industries. When combined, these technologies are advancing process optimization, predictive maintenance, real-time condition monitoring, and smarter automation. In order to give proactive system control and intelligent decision-making, AI algorithms mine large datasets generated via IoT devices for relevant patterns. In the meanwhile, IoT guarantees smooth communication between …
Published in Journal of Mechatronics and Automation · Vol. 12, Issue 2, 2025 · pp. 27–33 Read article
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Deep Learning Architectures for Predictive Modeling in Financial Time Series
Abstract: This study investigates the application of deep learning architectures, particularly convolutional neural networks (CNNs), to the challenging task of financial time series forecasting. Financial markets are inherently complex and influenced by a range of factors, making accurate prediction of price movements a difficult problem. In this research, historical financial data including stock prices, volumes, and other relevant indicators are used to train CNN models aimed at capturing the underlying patterns …
Published in Current Trends in Signal Processing · Vol. 15, Issue 3, 2025 · pp. 45–55 Read article
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Feature Extraction and Analysis of Bearing Faults: A Review
Abstract: One of the most important steps in identifying bearing problems is feature extraction. In order to provide a more meaningful dataset, it entails locating and extracting pertinent features from raw bearing vibration signals. Tasks involving categorization and prediction can then make use of these attributes. In many practical applications, such as monitoring rotating machinery or electronic components, the raw signals collected (e.g., vibration, current, temperature) are often complex, high-dimensional, and …
Published in Trends in Mechanical Engineering & Technology · Vol. 15, Issue 2, 2025 · pp. 20–28 Read article
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IoT Sensors to Monitor Pipeline Pressure and Flow Rate Combined with ML-Algorithms to Detect Leakages
Abstract: In the field of fluid mechanics, pipelines are the lifeblood of industries, transporting everything from natural gas and oil to water and chemicals. Maintaining their integrity is paramount for safety, economic efficiency, and environmental protection. Traditional leak detection methods explained in fluid mechanics can be slow, expensive, and sometimes fail to identify small leaks early enough to prevent significant damage. However, the convergence of Internet of Things (IoT) and Machine …
Published in Recent Trends in Fluid Mechanics · Vol. 12, Issue 2, 2025 · pp. 40–48 Read article
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Real-Time Analysis of E-Waste Monitoring Using Data Visualization in Power BI
Abstract: The exponential growth of electronic waste (e-waste) in India poses significant environmental and public health challenges, necessitating robust monitoring, management, and disposal strategies. This project, Real-time analysis of e-waste generated across different countries in the world and also survey report of India, seeks to provide a comprehensive assessment of e-waste production patterns, utilizing real-time data to capture dynamic shifts in waste generation and collection. By leveraging Power BI for advanced …
Published in Journal of Remote Sensing & GIS · Vol. 16, Issue 2, 2025 · pp. 1–7 Read article
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Lifestyle Factors and Perceptions of Diabetes Among Individuals in North India
Abstract: Background: Diabetes mellitus is influenced by a complex interplay of genetic, environmental, and lifestyle factors. In North India, unique socio-cultural and dietary patterns shape individual behaviors and perceptions toward diabetes. Understanding these lifestyle choices and cultural beliefs is critical for designing interventions that improve adherence to medical treatment and promote healthier outcomes. Methods: A cross-sectional survey was conducted among 1,500 individuals diagnosed with diabetes across selected urban and rural districts …
Published in International Journal of Tropical Medicines · Vol. 2, Issue 2, 2025 · pp. 1–7 Read article
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Estimation of Soil Erosion Using GIS in Pune District, Maharashtra
Abstract: The Varandha Ghats pans approximately 14.62 km 2 , where changes in temperature, vegetation, topography, and soil characteristics are causing continuous soil erosion. Catchment heterogeneity and climatic variations cause spatial variability in hydrological processes. Differences in land use, soil type, topography, and rainfall patterns influence how water moves and accumulates across regions, resulting in diverse hydrological responses. This complexity challenges accurate modeling and effective water resource management strategies across variable …
Published in Journal of Remote Sensing & GIS · Vol. 16, Issue 2, 2025 · pp. 26–33 Read article
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Computational Study of Sombor Index on Generalized Abid–Waheed Graphs for Polymer Modeling
Abstract: This study investigates the topological properties of generalized Abid Waheed graphs. Development of theoretical models in chemistry, reducing computational complexity while analysing large molecules or networks Abid Waheed graphs play a significant role. Motivated by these findings, the research was extended to encompass generalized Abid Waheed graphs, characterized by r cycles of order s. A notable similarity between Abid Waheed graphs and Jahangir graphs was observed. The potential applications of …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 267–274 Read article
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VHDL Programming for Side-Channel Attack Countermeasures in IoT Security
Abstract: The Internet of Things (IoT) landscape is expanding rapidly, connecting billions of devices across diverse domains. This interconnectedness, while offering unprecedented convenience and efficiency, also creates a fertile ground for security vulnerabilities. Among these threats, side-channel attacks (SCAs) pose a significant risk, particularly targeting the cryptographic implementations that underpin IoT security. SCAs exploit information leaked from the physical execution of cryptographic algorithms, such as power consumption, timing variations, and electromagnetic …
Published in Journal of VLSI Design Tools and Technology · Vol. 15, Issue 2, 2025 · pp. 20–33 Read article
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AI for Cybersecurity: Deploying Machine Learning for Network Traffic Anomaly Detection
Abstract: The growing sophistication of cyberattacks and the growth of network traffic necessitate sophisticated anomaly detection methods. This study overviews the use of artificial intelligence (AI) and machine learning (ML) to counter these challenges, as noted in current studies. It analyses supervised learning (SVM, Decision Trees), unsupervised learning (K-means, DBSCAN), and deep learning (CNNs, RNNs, Auto-encoders) approaches, considering their strengths and weaknesses. The research integrates current developments in AI/ML-based network anomaly …
Published in International Journal of Computer Science Languages · Vol. 3, Issue 2, 2025 · pp. 1–10 Read article
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A study on Public Perception and self-medication practices with Over-the-counter (OTC) Drugs
Abstract: Over-the-counter (OTC) medications are commonly used by individuals for self-medication due to their easy availability and the general belief that they are safe. However, misuse can lead to negative health outcomes such as adverse reactions, drug interactions, and delays in seeking professional medical care. In a country like India, where enforcement of drug regulations can vary and socioeconomic factors play a major role, the practice of self-medication is especially widespread. …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 16, Issue 3, 2025 · pp. 01–07 Read article
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Support Vector Machine Inspired Load Forecasting of a State University in Haryana
Abstract: Estimating the possible environmental impact and determining probable capital requirements are made easier with a solid grasp of electricity demand. Beginning in the middle of the 20th century, demand forecasting for electric power networks was studied theoretically. Prior to that, the study of demand forecasting had not developed because of the small scale of power networks. With the use of statistical prediction techniques, plans for the electric power industry have …
Published in Trends in Electrical Engineering · Vol. 15, Issue 2, 2025 · pp. 33–40 Read article
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Drug Utilisation and Cost Analysis in End-Stage Renal Disease Patients: A Prospective Observational Study
Abstract: Chronic Kidney Disease (CKD) is a condition in which the kidneys are damaged and unable to efficiently remove waste and excess fluid from the blood. Dialysis serves as a treatment for CKD by artificially carrying out the kidney’s filtering functions. This prospective observational cross-sectional study was conducted to evaluate drug utilization patterns, economic burden, and health-related quality of life (HRQoL) among patients with end-stage renal disease (ESRD) undergoing dialysis. Over …
Published in Research and Reviews: A Journal of Health Professions · Vol. 15, Issue 2, 2025 · pp. 1–12 Read article
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Accelerating Unsupervised Feature Learning: Parallelized Training of Denoising Autoencoders
Abstract: Unsupervised representation learning has become a cornerstone of contemporary machine learning, enabling algorithms to extract informative features from un-labelled, high-dimensional data. This work investigates the efficacy of stacked denoising autoencoders (SDAEs) trained via parallelized stochastic gradient descent (SGD) as a scalable approach to feature extraction. By strategically leveraging multi-threaded computation, our study systematically examines the trade-offs between increased parallelism, training efficiency, and the preservation of model accuracy. Experiments on the …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 3, 2025 · pp. 56–64 Read article
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Study of Diurnal Anisotropy Variation in Cosmic Ray Intensity During Minimum Solar Activity Period
Abstract: we present a comprehensive study of cosmic ray variations over the period from 1964 to 2018, encompassing solar cycles 20, 21, 22, 23, and 24. Both annual average and day-to-day variations have been analyzed to capture the temporal dynamics of cosmic ray intensity across multiple solar cycles. The study focuses particularly on periods of minimum solar activity, namely the years 1965, 1976, 1986, 1996, and 2008, when cosmic ray modulation …
Published in Research & Reviews : Journal of Physics · Vol. 14, Issue 2, 2025 · pp. 30–37 Read article
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Optimizing Marketing Campaigns Using Random Forest and A/B Testing
Abstract: Marketing initiatives play a vital role in driving business growth by reaching targeted consumer segments through tailored strategies across multiple channels. The success of these initiatives is influenced by various factors, including the type and duration of the campaign, the characteristics of the target audience, the communication channels employed, and the overall efficiency of each strategy. These factors collectively impact key performance metrics such as conversion rates, customer acquisition costs, …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 3, 2025 · pp. 01–09 Read article