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588 articles for “identification”
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How Scientists Look for New Pathogens Before They Spread
Abstract: Emerging infectious illnesses are a persistent danger to global health. They often come from unexpected places, such wildlife reservoirs, changes in the climate, or human activities. Finding new diseases before they create epidemics is one of the biggest problems in modern epidemiology. This article talks about how scientists use genetic monitoring, field sampling, and real-time data processing to find, track, and describe new infectious organisms in a way that works …
Published in International Journal of Pathogens · Vol. 3, Issue 1, 2026 · pp. 11–17 Read article
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A Study on “Clean" in Beauty: A Machine LearningApproach to Ingredient Transparency and ConsumerTrust
Abstract: The burgeoning "clean beauty" market, while driven by consumer demand for safer and more sustainable products, is plagued by ambiguous definitions and the pervasive challenge of "greenwashing". This ambiguity hinders informed consumer choices and complicates brand authenticity. This study addresses these complexities by developing a novel machine learning (ML) framework designed to objectively analyze cosmetic ingredient lists, classify products based on their "cleanliness" profile, and identify key ingredient attributes that …
Published in Recent Trends in Cosmetics · Vol. 3, Issue 1, 2026 · pp. 1–12 Read article
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Assessment of Hygiene Degradation and Expiry Indicators in Household Bedding Products
Abstract: Household bedding products such as pillows, bedsheets, blankets, and mattresses play a crucial role in ensuring comfort, sleep quality, and overall health. However, prolonged use without timely replacement or proper maintenance can result in hygiene degradation, leading to the accumulation of dust, allergens, microorganisms, and chemical wear. This study aims to assess the factors contributing to hygiene decline and to identify reliable indicators of expiry for common bedding items. The …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 4, Issue 1, 2026 · pp. 33–47 Read article
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Assessing Digital Literacy among the Oraon Tribe of Jharkhand: A Study
Abstract: Digital literacy is essential for inclusion and socioeconomic empowerment in the digital era. This study examines the digital literacy levels of the Oraon tribe in Jharkhand, with a focus on identifying skill gaps, demographic disparities, and barriers to digital access. A mixed-methods approach was employed to gather data from respondents in the Ranchi district, utilizing structured questionnaires and interviews. Male respondents made up the majority (61.5%), with the largest age …
Published in Recent Trends in Social Studies · Vol. 3, Issue 1, 2026 · pp. 06–12 Read article
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Multilingual Education and Language Policy in a Globalized World: Toward Inclusive and Equitable Learning Systems
Abstract: Multilingual education involves teaching and learning in two or more languages, promoting linguistic diversity and enhancing educational outcomes. It acknowledges learners’ native languages and integrates them with dominant or global languages to foster inclusivity and cognitive development. Multilingual education (MLE) serves as a critical framework for promoting inclusivity and equity within increasingly globalized and culturally diverse classrooms. This paper explores the role of MLE and the influence of language policies …
Published in International Journal of Education Sciences · Vol. 3, Issue 1, 2026 · pp. 64–74 Read article
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Perception and Implementation of Sports Safety Measures Among University Physical Education Instructors in Punjab: A Cross-Sectional Study
Abstract: Introduction: Considerable attention must be focused on sports safety as it is a constituent of thephysical education (PE) curriculum at the university level, in view of the frequent and vigorous engagement in physical activities. While there is general acknowledgement of the existence of safetymeasures, the extent to which such measures are put into practice may differ. This research examines the perceptions and practices related to sports safety of university PE …
Published in Recent Trends in Sports · Vol. 2, Issue 2, 2025 · pp. 45–55 Read article
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Artificial Intelligence in Entomology: Global Advances, Applications, and Future Directions in Insect Research and Pest Management
Abstract: Artificial Intelligence (AI) is transforming entomology by enabling scalable, data-driven approaches to insect identification, ecological monitoring, and sustainable pest management. This review synthesizes recent global advances in AI applications across taxonomy, behavioral ecology, predictive modeling, and precision agriculture. Machine learning and deep learning techniques—including convolutional neural networks, acoustic classification models, and ensemble predictive algorithms—have demonstrated high classification accuracies (often exceeding 90% under controlled conditions) and improved early detection of pest …
Published in International Journal of Insects · Vol. 3, Issue 1, 2026 · pp. 29–40 Read article
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Impacts of Climate Change and Anthropogenic Stressors on Marine Ecosystems: A Comparative Study of Coral Reefs, Kelp Forests, and Arctic Fjords
Abstract: The accelerating impacts of climate change and human activities are profoundly reshaping marine ecosystems, threatening biodiversity, and altering trophic dynamics. This study synthesizes recent research on the responses of marine flora and fauna to temperature fluctuations, ocean acidification, pollution, and overfishing, highlighting the cascading effects on primary production, nutrient cycling, and ecosystem resilience. Using a combination of field surveys, remote sensing data, and meta-analytical approaches, we quantified biodiversity shifts across …
Published in International Journal of Marine Life · Vol. 3, Issue 1, 2026 · pp. 17–24 Read article
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Transforming Hospital Environments: The Role of Sound Detection
Abstract: Hospitals are sanctuaries of healing, yet they are often paradoxically exposed to a pervasive, often underestimated threat: excessive noise. While internal hospital sounds pose their own challenges, the impact of external sounds – traffic, construction, sirens, and urban clamor – can profoundly compromise patient safety, recovery, and overall well-being. This article explores the critical role of advanced sound detection systems in mitigating this external acoustic intrusion, leveraging technology to create …
Published in International Journal of Electrical and Communication Engineering Technology · Vol. 4, Issue 1, 2026 · pp. 28–40 Read article
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Divorced Women Attitudes Towards Remarriage: A Qualitative Approach
Abstract: The current study aimed to investigate the attitudes of divorced women regarding remarriage and to comprehend the diverse factors that shape their viewpoints. The research population comprised divorced women, and a purposive sampling method was employed to select participants. Data were collected from ten divorced women through semi-structured interviews, allowing for in-depth exploration of personal experiences and viewpoints. A qualitative research design was adopted to capture the complexity of individual …
Published in International Journal of Behavioral Sciences · Vol. 3, Issue 1, 2026 · pp. 1–14 Read article
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Challenges And Constraints Affecting Female-Owned Rural Farm Businesses in Plateau State, Nigeria
Abstract: This study examined the challenges and constraints affecting female-owned rural farm businesses in Plateau State, Nigeria. No prior study had conducted a comprehensive, quantitative, state-wide investigation covering all 17 local government areas (LGAs) of the state, and this study addressed that gap. The objectives were to identify the challenges faced by female-owned rural farm businesses, assess their relationship with business performance, and determine how strongly these challenges predicted performance outcomes. …
Published in International Journal of Rural and Regional Development · Vol. 4, Issue 1, 2026 · pp. 1–13 Read article
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Predictive Analytics and Adaptive Learning: A Machine Learning Framework for Reducing Learning Gaps
Abstract: Most contemporary digital learning environments encounter persistent challenges when it comes to accurately identifying students who are at-risk of academic underperformance. These challenges often arise due to limited visibility in learners’ engagement levels and gaps in conceptual understanding, particularly during the early stages of a course. To address this issue, the present study proposes an early prediction framework that leverages comprehensive student-related data through the application of machine learning techniques. …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 4, Issue 1, 2026 · pp. 16–21 Read article
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Importance of Thesaurus in Natural Language Processing for Scholarly Data Extraction
Abstract: The exponential growth of scholarly literature needs advanced methods for efficient data extraction and knowledge discovery. Natural Language Processing (NLP) has emerged as a crucial technology in automating the analysis and organization of academic texts. Among various linguistic resources, thesauri serve as important tool for enhancing semantic understanding by providing structured vocabularies, synonyms, and hierarchical relationships between terms. This paper examines the importance of thesauri in enhancing NLP-based scholarly data …
Published in Emerging Trends in Languages · Vol. 3, Issue 1, 2026 · pp. 19–24 Read article
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Comparative Analysis and Future Research Directions in AI in Healthcare: Medical Imaging and Diagnostics
Abstract: Artificial intelligence (AI) is reshaping healthcare, particularly in the areas of medical imaging and diagnostic practice. By using advanced techniques like machine learning and deep learning, AI systems help improve the accuracy, speed, and effectiveness of identifying diseases and analyzing medical images. This paper provides a comprehensive overview of the application of artificial intelligence in medical imaging and highlights its growing importance in clinical diagnostics. It discusses how AI-based systems …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 4, Issue 1, 2026 · pp. 8–13 Read article
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DFT/Data Guided Predictive Modelling of Absorption Maxima in the OLED Rubrene Derivatives
Abstract: This study investigates the optical properties of rubrene derivatives to develop an accurate predictive model for absorption maxima using computational chemistry and chemoinformatic techniques. We benchmarked various quantum chemical methods, identifying that the M06-2X/aug-cc-pVDZ method in dichloromethane (DCM) provided the strongest correlation with experimental data. Key molecular descriptors such as band gap, ionization potential, and electrophilicity index were calculated and analyzed using principal component analysis (PCA) to identify significant factors …
Published in International Journal of Cheminformatics · Vol. 4, Issue 1, 2026 · pp. 41–56 Read article
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A Study on AI-Driven Multi-Layered Defense in 6G Ecosystems
Abstract: The 6G networks bring about new degrees of possible functions related to connectivity, latency, data throughput, and integration with artificial intelligence (AI). This enables advances within healthcare, autonomous systems, and smart cities. The positive impact of rapid advancements must also be balanced with heightened risks due to the sheer volume of gaps that can be exploited, and the complex nature of the alignments and breaches. This results in the breaches …
Published in International Journal of Radio Frequency Innovations · Vol. 4, Issue 1, 2026 Read article
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A Review on Artificial Intelligence Techniques for Analyzing Deforestation and Illegal Logging Using Satellite Imagery
Abstract: Deforestation and illegal logging remain critical environmental threats, driving biodiversity loss, climate change, and socio-economic disruption. Conventional monitoring techniques frequently do not yield real-time, large-scale insights. Recent developments in Artificial Intelligence (AI), especially in deep learning and computer vision, have revolutionized the ability to analyze high-resolution satellite images for detecting deforestation and monitoring illegal logging. This review synthesizes recent developments in AI-driven approaches, highlighting convolutional neural networks (CNNs), anomaly detection …
Published in International Journal of Satellite Remote Sensing · Vol. 4, Issue 1, 2026 · pp. 1–9 Read article
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Differential Gene Expression Analysis of Human Atrial Fibroblasts Reveals Dysregulation of RNA Metabolism and Translational Machinery in Atrial Fibrillation
Abstract: Atrial fibrillation (AF) is a complex cardiac arrhythmia characterized by extensive structural remodeling and the activation of atrial fibroblasts, which drive the progression of fibrosis. To identify the underlying transcriptomic alterations, we analyzed six human atrial fibroblast RNA-Seq datasets (three control and three AF) retrieved from the Sequence Read Archive. After performing rigorous quality control and adapter trimming, we aligned the reads to the GRCh38 human reference genome using a …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 2, 2026 · pp. 15–25 Read article
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Analysis and Detection of Fingerprint Patterns Across Three Generations in Families of the Vidarbha Region Population
Abstract: Fingerprint patterns are unique and reliable for identification. This study focuses on a comparative analysis to determine the inheritance of fingerprint patterns across three generations in families of the Vidarbha region population. The sample collection process for this comparative analysis involved working with 100 families. The study aims to gain insights into the hereditary aspects of fingerprint characteristics among three generations. The research methodology involves the collection of fingerprint samples …
Published in International Journal of Genetic Modifications and Recombinations · Vol. 4, Issue 2, 2026 Read article
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ML Analysis of Factors Affecting Vaccination in Rural Children: A Machine Learning Approach
Abstract: Vaccination remains one of the most effective public health interventions for preventing childhood diseases, yet rural regions in India continue to experience uneven immunization coverage due to multiple socioeconomic and geographic barriers. This research applies machine learning techniques to identify and analyze the major determinants influencing childhood vaccination uptake in rural communities. The study utilizes survey-based demographic, socioeconomic, and healthcare-related parameters to build predictive models that classify children as vaccinated …
Published in International Journal of Vaccines · Vol. 3, Issue 2, 2026 Read article