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611 articles for “interpreter”
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Solving Optimization Problems Using the Graphical Method of Linear Programming
Abstract: Linear programming is a mathematical optimization technique used for maximizing or minimizing a linear objective function while satisfying a set of linear constraints. This method plays a crucial role in various industries, including manufacturing, finance, transportation, and supply chain management. Among the different approaches to solving linear programming problems, the graphical method provides a simple and intuitive way to visualize and solve problems involving two decision variables. By plotting constraints …
Published in Research & Reviews : Journal of Statistics · Vol. 14, Issue 2, 2025 · pp. 01–08 Read article
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Pathophysiology Reimagined: Integrating Systems Biology and AI for Disease Understanding
Abstract: Pathophysiology, the study of disease mechanisms at molecular, cellular, and systemic levels, has traditionally relied on reductionist approaches that often fail to capture the complex, dynamic, and interconnected nature of biological systems. Diseases such as cancer, neurodegenerative disorders, and infectious diseases arise from intricate interactions among genetic, epigenetic, metabolic, and environmental factors, necessitating integrative, data-driven methodologies for a deeper understanding. Systems biology has emerged as a powerful approach by leveraging …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 16, Issue 2, 2025 · pp. 63–71 Read article
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QSAR Modeling Techniques A Comprehensive Review of Tools and Best Practices
Abstract: Quantitative Structure–Activity Relationship (QSAR) modeling has become an essential tool in drug discovery, toxicity assessment, and environmental chemistry. By correlating chemical structure with biological activity or toxicity, QSAR enables the prediction of compound behavior without extensive experimental testing. This approach not only saves time and resources but also supports ethical practices by reducing reliance on animal studies. The evolution of QSAR from basic linear models to advanced machine learning and …
Published in International Journal of Cheminformatics · Vol. 3, Issue 1, 2025 · pp. 56–63 Read article
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Artificial Intelligence in Robotics: Current Trends, Applications, and Future Challenges
Abstract: The incorporation of artificial intelligence (AI) into robotics has transformed the industry by greatly improving robots' capacity to carry out complex and autonomous functions in a wide range of sectors. This paper explores the evolution, applications, and challenges associated with AI-driven robotics. It examines key AI methodologies employed in robotics, including machine learning, natural language processing (NLP), computer vision, and planning/control algorithms, which enable robots to perceive, learn, and interact …
Published in Journal of Advancements in Robotics · Vol. 12, Issue 2, 2025 · pp. 31–43 Read article
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U-Net Based Approach for Automated Brain Tumor Classification
Abstract: Brain tumor detection and identification play vital roles in diagnostic procedures in the field of medicine, with the conventional analysis of MRI images requiring a lot of time and also subject to variability. The proposed study involves the use of a CNN-U-Net based approach for brain tumor detection and identification automatically. The study uses a database of 3,064 contrast-enhanced T1-weighted MRI images from 233 patients with the tumors of meningioma, …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 14, Issue 2, 2025 Read article
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Neuroimaging in Clinical Trials for Huntington’s Disease: Emerging Research Findings: The Advancement Directions and Implications
Abstract: Neuroimaging is very important in coordinating and conducting Huntington’s disease clinical trials as a tool in selecting patients, managing safety concerns, and assessing the benefits of interventions. This review presents the current uses and potential future uses of structural and functional magnetic resonance imaging (MRI), diffusion imaging, positron emission tomography (PET), proton magnetic resonance spectroscopy (MRS), perfusion imaging, and magneto encephalography (MEG) in HD trials. We describe how these modalities …
Published in International Journal of Brain Sciences · Vol. 2, Issue 2, 2025 · pp. 32–44 Read article
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Machine Learning-Based Disease Prediction: A Comparative Analysis for Diabetes, Brain Tumor, and Parkinson's Disease
Abstract: This paper presents a web-based disease prediction system that integrates machine learning and deep learning techniques to assist in the early detection of Parkinson’s Disease, Diabetes, and Brain Tumors. By utilizing clinical data and MRI images, the platform provides rapid and interpretable predictions to support proactive health management. Logistic Regression models are applied to classify structured datasets for predicting Parkinson’s disease and Diabetes, making use of their effectiveness in binary …
Published in Current Trends in Signal Processing · Vol. 15, Issue 2, 2025 · pp. 44–54 Read article
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AI Application in the Creation of Medications for COPD
Abstract: The crippling lung condition known as chronic obstructive pulmonary disease (COPD) is typified by a continuous restriction of airflow, which results in increased respiratory dysfunction and a reduced quality of life. The rising incidence of COPD worldwide emphasizes the pressing need for innovative pharmaceutical approaches to address the illness. Even though COPD care has advanced significantly, most current medications concentrate on symptom relief rather than disease change. This gap in …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 12, Issue 2, 2025 · pp. 01–05 Read article
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Enabling Intelligent Interoperability: Advancing Sensor Networks Through the Semantic Sensor Web (SSW)
Abstract: The Semantic Sensor Web (SSW) is an evolution of the traditional Sensor Web, integrating semantic web technologies to enhance the discovery, interpretation, and integration of heterogeneous sensor data. By embedding semantic annotations into sensor observations and metadata, SSW enables automated reasoning, improved interoperability, and more sophisticated querying capabilities across diverse sensor networks. This approach addresses key challenges in handling large-scale, distributed, and dynamic sensor data, particularly in domains such as …
Published in Recent Trends in Sensor Research & Technology · Vol. 12, Issue 2, 2025 · pp. 21–37 Read article
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Role of Generative AI in Redefining Data Analytics
Abstract: The rapid evolution of data-driven technologies has introduced both significant challenges and promising opportunities within the field of data analytics. Among the most impactful advancements is Generative Artificial Intelligence (Generative AI), a groundbreaking subset of AI that is reshaping how data is interpreted, generated, and utilized. Unlike traditional analytical tools that rely solely on existing data patterns, generative AI possesses the capability to create synthetic data, simulate complex scenarios, and …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 3, Issue 2, 2025 · pp. 01–07 Read article
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KSK Approach: An AI-Driven IoT Based Decision Making System’s Study
Abstract: Internet of Things (IoT) has promised a world of interrelated devices, generating vast amounts of data. Traditionally, IoT systems trusted on preprogrammed procedures and human intervention to process data and make decisions. This approach often struggled to hold the sheer size and density of IoT data, leading to inefficiencies and missed opportunities. However, the true budding of that data lies not simply in its collection, but in its interpretation and …
Published in Current Trends in Signal Processing · Vol. 15, Issue 2, 2025 · pp. 14–25 Read article
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Channel Estimated Modulation Techniques for Wireless Communication Systems: Review
Abstract: The high spectrum and energy capabilities of Multiple Input Multiple Output systems make them a propitious technology for 5th-generation wireless communication systems. The acquisition of channel information is crucial for utilizing the potential gains of the multi-modal systems. Numerous studies have established channel estimation techniques and are still in research which faced several challenges with downlink-uplink overheads, complexities, and pilot contamination. This work discusses the insights obtained from the reviewed …
Published in Trends in Opto-electro & Optical Communication · Vol. 15, Issue 2, 2025 · pp. 1–10 Read article
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Digital Psychiatry: A Narrative Review on AI Positive Role in Mental Health
Abstract: Artificial Intelligence has rapidly evolved into a formidable instrument within the domain of mental healthcare, fundamentally altering the way we understand awareness, diagnosis, intervention and emotional regulation. This narrative review explores AI’s potential to foster positive mental health through tools such as natural language processing, machine learning, deep learning and computer vision. These technologies promise earlier detection of mental disorders, customized treatment plans and responsive emotional support. Yet, alongside these …
Published in Current Trends in Signal Processing · Vol. 15, Issue 3, 2025 · pp. 1–13 Read article
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The Role of Optimization and Probability in Shaping Artificial Intelligence
Abstract: This study discusses the basic roles of optimization algorithms and the theory of probability in the process of evolution and development of Artificial intelligence (AI). First, we introduce the role played by the next generation of leading-edge optimization algorithms developed since gradient descent to evolutionary strategies with respect to the learning of high-level AI models and how to enable them to learn to effectively explore high-dimensional parameter spaces. At the …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 123–128 Read article
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Intelligent Design Approaches in Microwave Engineering Using Machine Learning Techniques
Abstract: In microwave engineering, machine learning (ML) has become a potent technology allowing quicker design cycles, improved modelling accuracy, and automatic optimisation of complicated systems. Recent developments in the use of ML methods to microwave components and systems, including antennas, filters, and high-frequency circuits, are summarised in this study. In the framework of electromagnetic simulation, surrogate modelling, and parameter extraction, supervised and unsupervised learning algorithms are addressed. Moreover, the study looked …
Published in Journal of Microwave Engineering and Technologies · Vol. 12, Issue 2, 2025 · pp. 31–38 Read article
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Predictive Modeling of Polymer Composites for Medical Implants Using Artificial Intelligence Techniques
Abstract: The use of polymers in biomaterials was now key to designing the next generation of medical implants, which need to be strong and also compatible with living tissue. Tests for biocompatibility, such as those done in the laboratory and by doing experiments on animals, require much time and many resources, so the need for computer-based approaches becomes clear. An artificial intelligence approach was provided in this study to determine how …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 665–692 Read article
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The Role of Artificial Intelligence in Mental Health: Applications in Neurodegenerative Disorders
Abstract: Artificial intelligence (AI) has significantly changed many aspects of medical care, particularly the early evaluation, therapy, and management of neurodegenerative illnesses like Alzheimer's, disease, Parkinson's diseases, and Huntington's diseases. The current research explores the application of AI in mental health with respect to neurological disorders, especially advancements in cognitive examination, neuroimaging analysis, predictive modeling, and customized therapy modalities. Artificial intelligence (AI) systems have shown enormous potential in detecting minute biomarkers …
Published in Research and Reviews : A Journal of Biotechnology · Vol. 15, Issue 3, 2025 · pp. 34–40 Read article
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Tactile Sensing Technologies in Robotics: A Review of Sensors, Materials, and Applications
Abstract: Tactile sensing, which closely resembles the human sense of touch, is an essential capability in modern robotics. It enables robots to detect and interpret physical interactions with objects, surfaces, and living beings, thereby allowing them to operate more intelligently and adaptively in complex environments. Unlike visual or auditory sensors, tactile sensors provide direct feedback about contact, pressure, texture, force, temperature, and even vibration. These sensory cues are vital for improving …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 3, Issue 1, 2025 · pp. 17–23 Read article
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Smart Bionic Hand: Combining Hardware and AI For Adaptive Prosthetic Functionality
Abstract: This research paper presents the development and integration of a bionic arm that leverages both hardware components and artificial intelligence (AI) models for enhanced functionality and user interaction. The hardware design includes key components such as servo motors, an Arduino UNO microcontroller, electromyography (EMG) sensors, and a lithium-ion battery. The EMG sensors detect muscle signals, which serve as inputs for controlling the arm's movements, while the servo motors are responsible …
Published in Journal of Mechatronics and Automation · Vol. 12, Issue 2, 2025 · pp. 1–7 Read article
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Study of Social Trends Prediction Using AI
Abstract: AI (Artificial Intelligence) has fundamentally changed the ability to analyze social trends by using large datasets to develop predictions about human behavior, public sentiment, and global events. Using methodologies such as Natural Language Processing (NLP), Time-Series Forecasting, and Graph-Based Social Network Analysis, AI is able to find hidden correlations in a variety of available datasets, from social media to economic indicators to public records, and fundamentally changes decision-making based on …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 3, 2025 · pp. 19–29 Read article