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108 articles for “Gene prediction”
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Fruit Adulteration Detection Utilizing Machine Learning Methods
Abstract: A device utilizing Internet of Things (IoT) technology was developed for the identification of fruit adulteration through machine learning methods, specifically targeting formalin content assessment. The identification of the fruits based on their extracted traits has been accomplished using a variety of machine-learning techniques. The formalin concentration can be detected as an estimate of the generated voltage of any fruit via an Arduino Uno board 3 and a volatile compound …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 1, Issue 1, 2023 · pp. 32–45 Read article
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Understanding Leukemogenesis: Challenges and Advancements in Diagnostic Approaches
Abstract: Leukaemia development, or leukemogenesis, is a multifactorial process driven by a complex interplay of environmental, genetic, and epigenetic factors. Despite substantial advancements in technology and medicine, which have enhanced our understanding of the contributing factors, early and accurate diagnosis remains a major challenge due to the overlapping clinical features shared by the various leukaemia subtypes. This study explores the molecular and cellular mechanisms underlying leukemogenesis, while also addressing the difficulties …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 3, Issue 1, 2025 · pp. 11–22 Read article
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Analyzing and Predicting Academic Behavior from Peer Pressure Indicators Using Machine Learning
Abstract: The academic achievement of a student is determined by their capability, but also by the companions with whom they associate. Friends can have a positive impact on students' motivation for school, and at times friends are distractions leading to a lack of attention on their school assignments. This particular study focuses on the number and quality of companions students associate with and to what extent that could be used as …
Published in International Journal of Education Sciences · Vol. 3, Issue 2, 2026 Read article
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Integrating Digital Twins, Smart Materials, and Human Machine Collaboration for Sustainable Smart Manufacturing: Smart CNC & Industry 4.0 Applications
Abstract: The rapid evolution of Industry 4.0 and the emerging transition toward Industry 5.0 have been catalyzed by the convergence of intelligent digital technologies such as digital twins, cyber–physical systems (CPS), artificial intelligence (AI), the Internet of Things (IoT), and human-in-the-loop (HITL) frameworks. These technologies have transformed traditional manufacturing into adaptive, data-centric ecosystems capable of real-time optimization and predictive decision-making. In recent years, the fusion of computer numerical control (CNC) machines, …
Published in International Journal of Manufacturing and Production Engineering · Vol. 3, Issue 2, 2025 · pp. 1–8 Read article
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Advanced Lithium-Ion Battery Prognostics: A Comprehensive Review of Machine Learning Approaches for Remaining Useful Life Prediction
Abstract: The lithium-ion battery (LIB), as one of the main sources for portable power systems, has been increasingly popular owing to its widespread applications in electric vehicles, consumer electronics, aerospace and renewable energy. Despite their advantages in high energy density and long cycle life, LIBs suffer from degradation over time of aging and cycling, resulting in loss of performance, safety issues, and economic bottlenecks. Predicting their Remaining Useful Life (RUL) is …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 3, Issue 2, 2025 · pp. 12–27 Read article
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Screening Phytocompounds of Tinospora cordifolia to Find Potential Drug Targets for Cystic Fibrosis
Abstract: This study aimed to evaluate the therapeutic potential of phytocompounds derived from Tinospora cordifolia in treating cystic fibrosis (CF), a genetic disorder caused by mutations in the CFTR gene that lead to severe respiratory and digestive complications. Phytocompounds were retrieved from the IMPPAT database and subjected to molecular docking simulations using PyRx to assess their binding affinity to the CFTR protein. The top-scoring compounds – sterol, magnoflorine, tembetarine, kaempferol, and …
Published in International Journal of Genetic Modifications and Recombinations · Vol. 3, Issue 1, 2025 · pp. 16–24 Read article
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AI-Based Intelligent Traffic Signal Management System: A Review
Abstract: Traffic congestion is a growing problem in urban areas worldwide, leading to economic losses, increased pollution, and commuter frustration. Traditional traffic management systems rely on fixed timing cycles and lack adaptability to real-time traffic conditions. Intelligent traffic light control systems based on artificial intelligence (AI) have become a viable substitute for traditional techniques. These systems are able to evaluate large volumes of traffic data in real time, identify patterns, and …
Published in International Journal of Electronics Automation · Vol. 3, Issue 2, 2025 · pp. 1–5 Read article
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Molecular Docking of Arjuna Tree Phytocompounds for Ischemic Heart Disease
Abstract: Heart disease is a serious condition that can be caused by several lifestyle changes and sometimes genetic problems. The primary protein component of apolipoprotein is the LDL receptor, which indicates that a reduction in LDL levels can reduce the risk of ischemic heart disease. Apolipoprotein levels are associated with increased levels of ischemic heart disease. Using ADMET analysis, drug likelihood prediction, and molecular docking, this work attempted to find natural …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 3, Issue 1, 2025 · pp. 42–52 Read article
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In Silico Exploration of Podophyllum Hexandrum-Derived Phytocompounds as Potential Therapeutics Against Small Cell Lung Cancer (SCLC): A Molecular Docking Approach
Abstract: Small Cell Lung Cancer (SCLC) is a fast-growing and aggressive type of lung cancer that spreads quickly strongly associated with smoking. It is characterized by symptoms, such as persistent cough, breathing difficulties, or hoarseness, though it can sometimes be asymptomatic which makes early detection challenging. The tumor suppressor gene TP53 is critical in regulating the cell cycle and preventing uncontrolled cell division. Mutations in TP53 result in the loss of …
Published in International Journal of Molecular Biotechnological Research · Vol. 3, Issue 1, 2025 · pp. 1–11 Read article
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Iron Oxide/Chitosan Nanocomposite: Properties and Design for AI Enhanced Immunotherapy and Regenerative Medicine
Abstract: Biopolymers are valuable complex materials. They attract attentions of many scientists, engineers, and medical professionals’ due to their distinguished properties for various applications. In this research, emphasis is given to Fe3O4/Chitosan nanocomposite which has desirable biophysical properties compared to pure Chitosan nanoparticles. Following the green synthesis procedures and characterization methods including thermo gravimetric analysis, AI assisted biomedical application of; Fe3O4/Chitosan nanocomposite is presented. The effect of alkali typically, KOH, in …
Published in International Journal of Cheminformatics · Vol. 3, Issue 2, 2025 · pp. 22–32 Read article
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Artificial Intelligence in Early Diagnosis and Personalized Treatment of Alzheimer’s Disease
Abstract: Artificial intelligence (AI) has become a disruptive technology in the medical care industry, with potential solutions to early diagnosis and customized treatment of Alzheimer’s disease (AD), a progressive neurodegenerative disease and the most prevalent cause of dementia globally. Conventional diagnostic techniques, such as cognitive, neuroimaging and biomarker techniques, are usually limited in the ability to detect disease at its most susceptible stage when treatment interventions are most effective. The recent …
Published in International Journal of Brain Sciences · Vol. 3, Issue 2, 2026 · pp. 15–27 Read article
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Predicting Student Placement Readiness: A Machine Learning Approach Using Coding Activities and Multi-Dimensional Performance Indicators
Abstract: In the modern information-driven academic world, identifying student employability and placement preparedness has predicted. be made a part and parcel of academic planning and career. development. This study provides a machine learning-based. structure to evaluate and forecast student placement pre-paredness by combining various performance aspects-academic achieve- ment, coding activity, aptitude and behavioral engage-ment metrics. Multi-source was gathered and preprocessed in the study. student information, such as student records (CGPA, attendance), …
Published in International Journal of Education Sciences · Vol. 3, Issue 2, 2026 Read article
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Spatiotemporal Modeling of Soil Erosion Under Agricultural Expansion in the Amravati Basin, India Using RUSLE–GIS
Abstract: Agricultural expansion and soil erosion are important environmental issues in areas where agriculture is a major source of livelihood. This study analyzes the spatial and temporal patterns of soil erosion in the Amravati Basin of Maharashtra and evaluates the impact of agricultural expansion using the Revised Universal Soil Loss Equation (RUSLE) integrated with Geographic Information System (GIS) techniques. Multi-source data, such as satellite imagery, rainfall records, soil characteristics, and topography …
Published in International Journal of Land · Vol. 3, Issue 1, 2026 · pp. 50–62 Read article
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The Role of Artificial Intelligence and Machine Learning in Redefining Global Healthcare Systems and Advancing Medical Innovation
Abstract: Health Services are being revolutionized with AI and ML through improved accuracy, efficiency and accessibility in the delivery of health care. With AI and ML, it is now possible for health care professionals to assess varying amounts of complex clinical data in a relatively short amount of time, therefore, creating opportunities for early detection of disease, increasing the odds of accurate diagnosis, and improving the ability to make informed clinical …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 4, Issue 1, 2026 · pp. 14–19 Read article
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NeoVax: Smart Child Vaccination and Monitoring Platform
Abstract: Child vaccination plays a crucial role in preventing life-threatening diseases and ensuring long-term public health. Despite the availability of structured immunization programs, many children miss scheduled vaccinations due to lack of awareness, busy lifestyles of parents and absence of effective reminder systems. This research paper presents NeoVax, a smart and user-friendly child vaccination reminder and management system designed to address these challenges using digital technology.NeoVax is an Application that enables …
Published in International Journal of Children · Vol. 3, Issue 2, 2026 · pp. 14–20 Read article
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A Survey of Role-Based Access Control Implementation in HMI Systems for Industrial Automation
Abstract: The convergence of Role-Based Access Control (RBAC) and Human-Machine Interface (HMI) systems presents a transformative approach to secure and efficient industrial automation in Industry 4.0. By integrating RBAC with Multi-Factor Authentication (MFA), this framework enhances cybersecurity while maintaining operational flexibility, mitigating both external threats and internal vulnerabilities. Modern adaptive HMIs further optimize user experience through personalized and intuitive interfaces, though challenges remain in balancing functionality with simplicity in complex industrial …
Published in International Journal of Advanced Control and System Engineering · Vol. 3, Issue 2, 2025 · pp. 10–19 Read article
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AI-Enabled Feedback Management for Enhancing Education
Abstract: Institutions are becoming more aware of the importance of student input in improving learning experiences in the current educational environment. However, the intricate and complex patterns found in this feedback are frequently missed by conventional techniques like manual reviews and simple statistics. Our proposal suggests a novel method for analyzing student input and more accurately predicting sentiment by utilizing Long Short-Term Memory (LSTM) algorithms. We can learn more about student …
Published in International Journal of Electronics Automation · Vol. 3, Issue 2, 2025 · pp. 21–27 Read article
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Sensors-Based Electric Machine Design for Industry
Abstract: The integration of advanced sensors is fundamentally changing the economics and reliability of electric machines. It moves design focus from minimizing material cost and adhering to conservative standards toward maximizing operational availability and energy efficiency. In the industry of tomorrow, the electric motor will not be a passive collection of coils and steel, but a self-diagnosing, self-optimizing, and perhaps even self-healing asset—a sentient motor—driven by its highly refined sixth sense, …
Published in International Journal of Electrical Machine Analysis and Design · Vol. 4, Issue 1, 2026 · pp. 1–10 Read article
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Intelligent Power Quality Enhancement Strategies for PV-Integrated Smart Distribution Networks: A State-of-the-Art Review
Abstract: The rapid integration of photovoltaic (PV) systems into modern power distribution networks has introduced significant challenges related to power quality. Issues such as voltage fluctuations, harmonic distortion, flicker, and reactive power imbalance arise due to the intermittent and nonlinear nature of solar energy generation. This paper presents a concise literature review of various power quality enhancement techniques employed in PV-integrated networks. Key approaches include the use of active power filters …
Published in International Journal of Electrical Power and Machine Systems · Vol. 4, Issue 1, 2026 · pp. 30–53 Read article
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Effect of Adverse Childhood Experiences on Adult Attachment Styles and Help Seeking Behaviour Among Youth
Abstract: Psychological development is deeply influenced by early environments, where personal experiences, cultural norms, and structural factors intersect. Beyond individual adversity, societal conditions shape cognitive, emotional, and social functioning, ultimately influencing attachment patterns and help-seeking behaviour in adulthood. The current study explores the influence of adverse childhood experiences on adult attachment styles and help-seeking behaviour among youth. 140 participants (70= males, 70= females) aged 18-25 years were involved in the study. …
Published in International Journal of Children · Vol. 2, Issue 2, 2025 · pp. 25–34 Read article