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231 articles for “Generational identification”
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Sustainable Approaches for Examining the potential use of nanoparticles in future research
Abstract: Theoretical stagnation can always be an eminent danger for any research field. Therefore, the contemporary research themes are constantly explored and examined through battery of examination. Based on the aforesaid rationale, this study examined the counterfeit purchase intention of the youth based on different constructs such as Market mavenism, Cool consumption, Postmodernism, Schadenfreude, Public self-consciousness, Generational norms, and Generational Identification. The questionnaire was administered for collecting the data the responses …
Published in Journal of Polymer & Composites · Vol. 12, Issue 1, 2024 · pp. 1–8 Read article
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Neuro-Symbolic Agentic AI for Autonomous Scientific Discovery: Integrating Deep Reinforcement Learning, Quantum Simulation, and XAI-Audited LLM Hypothesis Generation in Drug Target Identification
Abstract: The exponential growth of multi-omics data and the increasing complexity of disease-associated protein interactomes have rendered conventional drug target identification pipelines computationally and epistemologically inadequate. This paper presents the Neuro-Symbolic Agentic AI for Scientific Discovery (NS-AASD) framework, a unified architecture that cohesively integrates deep reinforcement learning (DRL) exploration strategies, variational quantum simulation (VQS) of protein conformational dynamics, and XAI-audited large language model (LLM) hypothesis generation within an autonomous scientific discovery …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 2, 2026 Read article
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Log Identification and Monitoring System Using Generative AI
Abstract: In contemporary software ecosystems, application and infrastructure logs play a vital role in ensuring system reliability, performance optimization, fault diagnosis, and security compliance. As applications become increasingly distributed and cloud native, the volume, velocity, and variety of generated log data have grown dramatically. This rapid expansion makes traditional manual log inspection inefficient, error-prone, and largely impractical. To address these challenges, this paper proposes an artificial intelligence (AI) driven log monitoring …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 · pp. 08–16 Read article
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The Role of Generative AI in Enhancing Administrative Efficiency: Innovations in Workforce Support Systems
Abstract: Generating AI is the primary form of artificial intelligence that disrupts administrative work across multiple industries by redesigning and promoting the automation of traditional tasks and improving the workforce efficiency of decision-making. In a conventional setting, executive positions have been equally associated with paper-bound responsibilities, common with tedious activities like appointment making, filing, data input, etc. However, improvement in the area of generative AI makes these natural functions assignable, thus …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 1, 2025 · pp. 47–68 Read article
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Vocational Education in Higher Secondary Schools: A Review of Factors Influencing Student Interest and Attitudes
Abstract: The study investigates the essential aspects influencing students' motivation and attitudes toward vocational education in higher secondary schools, emphasizing its changing importance in current educational systems. Vocational education, which focuses on hands-on training and real-world applications, is critical in closing the gap between academic learning and the labor market. Despite its promise to promote employment, diversity, and economic development, vocational education faces considerable obstacles, such as societal stigma, insufficient resources, …
Published in International Journal of Education Sciences · Vol. 2, Issue 2, 2025 · pp. 1–10 Read article
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Earthquake Detection and Monitoring System
Abstract: Earthquakes continue to be one of the major natural hazards affecting human life and infrastructure. The development of affordable monitoring systems is essential for increasing preparedness and reducing the impact of such disasters. This work presents an Earthquake Detection and Monitoring System based on a vibration sensor and Arduino controller. The system continuously observes ground movements and evaluates the detected vibration levels against a predefined threshold. Whenever unusual vibrations are …
Published in Journal of Instrumentation Technology & Innovations · Vol. 16, Issue 2, 2026 Read article
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Innovative strategies in capsule formulation from concept to market
Abstract: Innovative strategies in capsule formulation have revolutionized drug delivery and nutraceutical development, offering advanced solutions from initial concept to market release. This report explores the transformative techniques at each stage of capsule formulation, detailing novel approaches in ingredient selection, encapsulation technology, and manufacturing processes. By leveraging advancements in artificial intelligence, encapsulation methods, such as liposomal and nanoparticle technologies, and materials science, formulators can optimize the bioavailability, stability, and targeted delivery …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 12, Issue 1, 2025 · pp. 1–8 Read article
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Artificial Intelligence in Microbiological Research: Methods, Applications and Implications
Abstract: Artificial Intelligence (AI) is revolutionising microbiological research by enabling the rapid analysis of complex biological data and improving the accuracy, efficiency, and reliability of scientific investigations. Recent advances in machine learning, deep learning, and bioinformatics have transformed AI into a powerful tool for studying microorganisms, their genetic composition, evolutionary patterns, and interactions with hosts and the environment. AI-driven computational models can process large and complex datasets far more efficiently than …
Published in Research and Reviews: A Journal of Microbiology and Virology · Vol. 16, Issue 2, 2026 Read article
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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
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Piezoelectricity: For Power Generation
Abstract: Undeniably, piezoelectric materials are an exciting possibility for serving as a workable energy source; the question is whether technologies at this point in their development are ready for wide-scale application. This requires considering their value in the real context of modern urban environments and ecological conditions. A critical literature review has been carried out in this paper for the identification of the most successful piezoelectric generation techniques that have been …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 3, Issue 2, 2025 · pp. 1–5 Read article
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Identification of Hub Genes and Enriched Gene Ontology & Pathways in Idiopathic Pulmonary Fibrosis Through Bioinformatics Approaches
Abstract: Idiopathic Pulmonary Fibrosis (IPF) is a progressive interstitial lung disease marked by aberrant remodeling of lung tissue and excessive extracellular matrix deposition, ultimately leading to respiratory failure. Despite ongoing research, the molecular mechanisms underlying IPF remain incompletely understood. This research aims to uncover differentially expressed genes (DEGs) and related biological pathways through an integrated analysis of microarray data. Two publicly available datasets, GSE110147 and GSE53845, were obtained from the Gene …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 13, Issue 1, 2026 · pp. 1–13 Read article
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First Insights into Whole Genome Sequencing of the Mycobacterium tuberculosis Complex: Molecular Diversity and Drug Susceptibility Patterns in Senegal
Abstract: Background: We conducted a bibliographic analysis of the Mycobacterium tuberculosis complex (MTBC) in sub-Saharan Africa, which included the analysis of 8,139 genomic sequences from 34 of the 49 sub-Saharan African countries. Notably, only one complete sequence from Senegal was identified, which had been generated in the United States. Our primary objective was to utilize whole genome sequencing (WGS) to detect resistance in anti-tuberculous strains of the MTBC in Senegal. This …
Published in Recent Trends in Infectious Diseases · Vol. 2, Issue 1, 2025 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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Geospatial Measurement of Shrinking Lake Mead Using Multi-Temporal Datasets From 1987 to 2020 and Its Relationship with the Climate Change
Abstract: The study provides an overview of the relation between climate change and its harsh consequences, and thereby revealing evidence of extremes conditions such as drought. Lake Mead of USA is one such example which is a readily contracting lake. The reason is fast temperature increment, human exploitation, etc. therefore leading to jeopardized and devastating effects on life structure. GIS and Remote Sensing has emerged as an extraordinary key instrument for …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 13, Issue 2, 2024 · pp. 18–27 Read article
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A Comparison of Different Generative AI Models
Abstract: Generative models have significantly advanced the field of artificial intelligence by allowing machines to produce complex and realistic outputs such as images, text, and other forms of data. Among the leading frameworks in this domain are generative adversarial networks (GANs), variational autoencoders (VAEs), and architectures based on Transformers. Each model offers specific benefits and drawbacks concerning design structure, training demands, and range of applications. This paper provides a detailed comparison …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 1, 2025 · pp. 16–22 Read article
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Management of Ship-Generated Pollution in Nigerian Seaports
Abstract: The impact of ship-borne pollution in Nigeria’s seaport is alarming. Following the guidelines of the International Convention for the Prevention of Pollution from Ships (MARPOL). This study identifies the types of ship-generated waste; evaluates the availability of waste reception facilities in Nigerian seaports, examining the costs of operation waste reception facilities in the Nigerian Seaports; examines the management of ship waste collection processes in the Nigerian Seaports; investigates the implementation …
Published in International Journal of Pollution: Prevention & Control · Vol. 3, Issue 2, 2025 · pp. 23–42 Read article
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Enhancing Smart Grid Security: Machine Learning Approaches for Detecting Anomalies
Abstract: The integration of Information and Communication Technology (ICT) with traditional electric grids has led to the development of smart grids. However, this integration has also increased the risk of anomalies, such as cyber-attacks, metering fraud, electricity theft etc. False Data Injection Attacks are a class of cyber-attacks against power grid monitoring systems, where adversaries can inject false data to manipulate the grid’s operation. Metering frauds pertain to malicious customers com- …
Published in Trends in Electrical Engineering · Vol. 14, Issue 2, 2024 · pp. 10–19 Read article
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Improving Supply Chain Resilience through Predictive Analytics and Real-Time Data Integration
Abstract: Demand forecasting has under gone major changes because to the incorporation of automated analytics into supply chain management (SCM), which has improved company productivity, accuracy, and responsiveness. Central to this transformation is the application of machine learning (ML), which enables the analysis of large and complex datasets to identify patterns, detect trends, and generate precise forecasts. Conventional methods for predicting frequently rely on linear models and historical sales data, which …
Published in International Journal of Industrial and Product Design Engineering · Vol. 3, Issue 2, 2025 · pp. 8–17 Read article
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Photosynthetic Living Plant–Integrated Cybernetic Sensors for Autonomous Environmental Intelligence
Abstract: The increasing demand for sustainable and autonomous environmental monitoring systems has motivated the development of biologically integrated sensing technologies that combine living organisms with advanced cybernetic intelligence. This study proposes a novel framework of Photosynthetic Living Plant–Integrated Cybernetic Sensors for Autonomous Environmental Intelligence, where living plants act as self-sustaining sensing platforms capable of continuously monitoring environmental conditions without external energy sources. By integrating bioelectrical signal acquisition modules, flexible nanomaterial electrodes, …
Published in Recent Trends in Sensor Research & Technology · Vol. 13, Issue 2, 2026 Read article
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Computer-aided Drug Design Method for Anti-hepatitis C Drug Design
Abstract: Hepatitis C is a disease caused by the hepatitis C virus and can cause serious liver damage. There is currently no vaccine for this disease and the number of infections continues to increase worldwide. Currently used antiviral drugs are interferon alfa-2a and ribavirin, but about half of patients do not respond to therapy. Therefore, new drugs that protect against hepatitis C need to be investigated. Computational drug methods have been …
Published in Research and Reviews : A Journal of Immunology · Vol. 14, Issue 2, 2024 · pp. 1–8 Read article