Search
1673 articles for “identification”
-
A Study on Mental Health, Psychological Support and Life Satisfaction For Tribal Community In Nilgiris-TN
Abstract: This research investigates the mental health challenges, psychological support systems, and overall life satisfaction among tribal communities in the Nilgiris district of Tamil Nadu. These indigenous groups, including the Todas, Kotas, Irulas, and Kurumbas, are undergoing significant social transitions due to modernization, environmental change, and cultural shifts: factors that increasingly influence their mental well-being. The primary objectives of this study are to assess the prevalence of mental health issues such …
Published in International Journal of Community Health Nursing And Practices · Vol. 3, Issue 2, 2025 · pp. 41–45 Read article
-
Smart Agriculture in India: Advancements in Image Processing for Automated Plant Disease Detection and Crop Analysis
Abstract: The adoption of image processing technologies in agriculture is emerging as a revolutionary method for tackling persistent challenges in the farming industry. These techniques are increasingly used for different tasks such as detecting plant diseases, assessing crop health, and predicting yields, especially in the framework of smart agriculture systems. This study paints a detailed picture of the latest progress in image processing techniques applied to automated disease detection and detailed …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 3, 2025 · pp. 13–19 Read article
-
Bridging the digital divide for school students with Specific Learning Disability in India: A Systematic Literature Review
Abstract: This systematic literature review aims to investigate the educational materials now utilized in inclusive classrooms in India to close the digital divide for children with specific learning disabilities (SLD). With an emphasis on policy, assistive technology, and teacher preparedness, the goal is to assess how well these resources work to create inclusive learning environments and look at how they might be tailored to help different learners. The review followed PRISMA …
Published in International Journal of Education Sciences · Vol. 2, Issue 2, 2025 · pp. 17–25 Read article
-
Understanding the Impact of GMO on Hormones and Their Effect on Mood: A Review Paper
Abstract: The research evaluates how consuming genetically modified organisms affects endocrine functioning that can potentially lead to mood changes or disorders. This is a systematic review paper that analysed sixty publications before selecting thirty which were obtained from Sciencedirect, Frontiers, Springer, Oxfordacadamic, Cabidigitallibrary, Wileyonlinelibrary, Cambridgeuniversitypress, Scijournals, Mdpi, Metabolismjournal; while using Prisma Flow Diagram as the research tool; acknowledging that human hormonal health risks from GMO consumption remain largely unknown due to …
Published in Research & Reviews : Journal of Food Science & Technology · Vol. 14, Issue 3, 2025 Read article
-
Pharmacokinetic Profiling and Molecular Docking of Carvacrol and Structural Analogs: Targeting Quorum Sensing Proteins to Disrupt Biofilm-Mediated Antimicrobial Resistance in Multidrug-Resistant Bacterial Pathogen
Abstract: Antibiotic resistance, particularly in Pseudomonas aeruginosa, has become a major global health threat, exacerbated by the organism's ability to form biofilms and regulate virulence through quorum sensing (QS). The LuxR and LasR receptors are key regulators in this process, influencing both pathogenicity and antibiotic resistance. This study investigates potential QS inhibitors targeting these receptors as a strategy to mitigate antibiotic resistance. The primary objective was to identify novel ligands that …
Published in International Journal of Biochemistry and Biomolecule Research · Vol. 3, Issue 2, 2025 · pp. 43–61 Read article
-
Clone-Specific Drug Delivery Systems: Targeted Approaches and Future Clinical Applications
Abstract: Clone-specific drug delivery systems represent a transformative frontier in personalized medicine, addressing the longstanding challenge of clonal heterogeneity within diseases such as cancer, infectious diseases, and autoimmune disorders. Traditional drug delivery platforms often fail to discriminate between pathogenic and healthy cells, leading to systemic toxicity and reduced therapeutic efficacy. In contrast, clone-specific systems aim to selectively target and eliminate disease-driving cellular clones based on unique molecular signatures, thereby improving treatment …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 12, Issue 2, 2025 · pp. 21–29 Read article
-
Advancements in Machine Learning: A Comprehensive Review of Algorithms, Applications, and Future Directions
Abstract: Gaining knowledge of Machine learning (ML)-guided format algorithms leverage predictive models to generate novel devices with optimized properties across several domains, which include drug discovery, fabric synthesis, and biomolecular engineering. Selecting an effective format set of policies consists of identifying appropriate hyperparameters, predictive models, and generative mechanisms to maximize format fulfilment. This study introduces an established method for set of policies requirements, ensuring that generated designs meet predefined fulfilment criteria, …
Published in Recent Trends in Programming languages · Vol. 12, Issue 2, 2025 · pp. 17–33 Read article
-
Clinicians’ role in the prevention and management of neonatal candidiasis in Punjab: challenges and opportunities.
Abstract: Background: Neonatal candidiasis is a growing concern in Punjab, particularly among newborns in neonatal intensive care units. The increasing prevalence poses significant risks to neonatal health, highlighting the need for effective management and prevention strategies. Objective: This study aims to explore the role of clinicians in preventing and managing neonatal candidiasis in Punjab while identifying the key challenges they face in clinical practice. Methods: A structured questionnaire was distributed to …
Published in Recent Trends in Infectious Diseases · Vol. 2, Issue 2, 2025 · pp. 26–33 Read article
-
AI, Robotics, and the Future of Waste Management: A Systematic Review of Advanced Collection and Sorting Systems
Abstract: The rapid growth of cities and rise in population have made waste management a major concern that calls for innovative and efficient solutions. Conventional waste collecting techniques are dangerous, time-consuming, and frequently ineffective. The development of automated waste management systems powered by cutting-edge technology like robotics, deep learning, artificial intelligence (AI), and the Internet of Things (IoT) is examined in this study. Vision-based systems, convolutional neural networks (CNN) for garbage …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 3, Issue 1, 2025 · pp. 1–6 Read article
-
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
-
Parametric Optimization of Aluminum Alloy 6061 Using Wire-EDM for Automotive Applications: A Taguchi-Based Approach
Abstract: Machining hard materials with complex geometries presents numerous challenges, often requiring the use of non-traditional methods such as wire Electric Discharge Machining (EDM). However, wire EDM machines operate at slow speeds, and increasing the speed can negatively impact surface finish, making it a difficult task. The ongoing research investigates the machinability study of Aluminum Alloy 6061 using wire EDM, emphasizing the optimization of process parameters to enhance machining performance and …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 293–302 Read article
-
Fuzzy Probability Distributions and Their Applications in Uncertain Data Analysis
Abstract: This study explores the use of fuzzy probability distributions in data analysis under uncertain conditions, with a specific focus on their implementation in evaluating call center customer satisfaction. Traditional probability models rely on precise parameters, often failing to account for the inherent variability and subjectivity present in real-world data. In contrast, fuzzy probability distributions, which integrate fuzzy logic principles, offer a more adaptable and realistic framework for addressing such complexities. …
Published in Research & Reviews : Journal of Statistics · Vol. 13, Issue 3, 2024 · pp. 1–8 Read article
-
Innovations in Targeted Drug Discovery for Personalized Medicine
Abstract: Personalized medicine is revolutionizing modern healthcare by custoizing treatment plans to match an individual’s genetic makeup, protein expression, and metabomlic characteristics. Also referred to as precision medicine, this approach seeks to improve therapeutic outcomes, reduce adverse effects, and make efficient use of healthcare resources. The incorporation of various omics technologies—including genomics, proteomics, transcriptomics, metabolomics, and epigenomics—has greatly advanced our ability to understand disease biology and molecular variations specific to each …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 12, Issue 3, 2025 · pp. 19–41 Read article
-
Ai-Driven Healthcare System for Enhanced Diagnosis and Patient Interaction
Abstract: Deep learning techniques are used in an AI-driven healthcare system to improve disease identification and medical picture analysis. Data collection, preprocessing, model training, and evaluation are all part of the system's systematic workflow. Various deep learning architectures, such as ResNet50, VGG-16, and U-Net, are employed for precise classification and segmentation of medical images. The approach incorporates advanced techniques such as optimization, transfer learning, and data augmentation to significantly enhance the …
Published in Research and Reviews: A Journal of Health Professions · Vol. 15, Issue 2, 2025 Read article
-
An Expected Cardiovascular Disease Detection Using Deep Learning Techniques
Abstract: Many avoidable deaths globally are caused by CVD, often due to individuals remaining unaware of their risk factors until severe symptoms, such as heart attacks or strokes, appear. This study utilizes retinal images as the dataset to explore the potential of retinal imaging as a non-invasive diagnostic tool for early detection of cardiovascular diseases (CVD). The delay in diagnosis and treatment highlights the need for sophisticated diagnostic instruments that can …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 14, Issue 2, 2024 Read article
-
Application of Metabolomics in Pharmacognosy
Abstract: In the field of pharmacognosy, the identification, quality control, and bioactivity evaluation of medicinal plants and natural products have become significantly more effective thanks to the development of a strong tool known as metabolomics, which is the complete study of small-molecule metabolites in biological systems. Metabolomics offers more in-depth insights into phytochemical composition, plant metabolism, and the mechanisms that underlie medicinal benefits. It does this by enabling high-throughput analysis and …
Published in Research & Reviews: A Journal of Pharmacognosy · Vol. 12, Issue 3, 2025 · pp. 01–07 Read article
-
Pharmacogenomics: Unlocking the Genetic Basis of Drug Response for Precision Medicine
Abstract: Pharmacogenomics, a fusion of pharmacology and genomics, explores how genetic variations influence individual responses to medications. This field is revolutionizing modern medicine by moving away from a one-size-fits-all approach toward personalized treatment strategies. By identifying specific genetic markers, pharmacogenomics aims to enhance drug efficacy, minimize adverse drug reactions, and improve overall patient outcomes. Key methodologies in this discipline include candidate gene analysis, genome-wide association studies, and haplotype analysis, all of …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 12, Issue 2, 2025 · pp. 52–59 Read article
-
Smart Service Solutions AI: AI-driven Multimodal Search for Home Appliance Support
Abstract: The global home appliance services market is projected to reach USD 1,203.11 billion by 2032, driven by smart household appliances. Essential services like installations, maintenance, and repairs ensure optimal performance and longevity, leading to higher customer satisfaction and loyalty. The service station partner ecosystem is crucial for ongoing support and profitability. However, challenges such as identifying the right manuals, finding relevant parts, and providing accurate instructions must be addressed to …
Published in Journal of Instrumentation Technology & Innovations · Vol. 15, Issue 3, 2025 · pp. 27–43 Read article
-
Gradient Boosted Regression Tree Approach to Predicting Toxic Interactions on X and YouTube
Abstract: In the digital age, social media platforms play a vital role in facilitating user engagement, encompassing both positive interactions and avenues for negative, often harmful behaviors. Recognizing and addressing toxic exchanges is paramount to nurturing healthy online communities and preserving users’ well-being. This study introduces a novel method for identifying toxic interactions by utilizing Gradient Boosting Regression Trees (GBRT) algorithm, a machine learning approach renowned for its exceptional accuracy and …
Published in Trends in Opto-electro & Optical Communication · Vol. 15, Issue 3, 2025 · pp. 7–14 Read article
-
Hybrid DL-ML Approach for Android Malware Detection
Abstract: The widespread growth of Android malware has become a significant mobile security threat during the past few years thus requiring the development of strong detection solutions. The primary tool applied in this research for Android malware detection consists of app permissions. The main indicator in the dataset for identifying malicious and benign applications functions through displaying application permission information. The evaluation of particular permission relationships with malware behavior leads to …
Published in Journal Of Network security · Vol. 13, Issue 3, 2025 · pp. 18–25 Read article