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1916 articles for “Modeler” (ranking capped at the first 2,000 matches — narrow the search to see the rest)
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An Insight to Animal Models of Drug Induced Schizophrenia
Abstract: Schizophrenia is a mental disorder that generally shows in early adulthood or late adolescence characterized by hallucinations, delusions, and other cognitive dysfunctions, schizophrenia can often be a lifelong problem. Schizophrenia affects approx. 1% of all adults, universally. The purpose of this article is to review several drug induced schizophrenia animal models. The scientific study of human disorders has required the development of suitable animal models. The prevailing recent view of …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 6, Issue 1, 2019 · pp. 21–33 Read article
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Review on Zebrafish Model: A Novel Research Tool
Abstract: Zebrafish (Danio rerio) are a small‐bodied tropical, freshwater fish species originally from South Asia. The ease of care, year‐round prolific breeding, and transparent, external development have made these fish a popular model vertebrate for many fields of biology. Over the past 40years, the development methods for genetics, CNS system, CVS system and cancer and other researches have shown rapid development. This review provides an orientation to the zebrafish as a …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 6, Issue 3, 2019 · pp. 18–30 Read article
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Cost Model of Acquisition and Merger in Construction Industry
Abstract: Merger and Acquisition in India is at an all-time high with more buyers now than before; it has been accounting for 80% of closed deals in 2020–2021, up from 70% in 2017–2019. To determine the Merger and Acquisition of the company, this article explores the main factors in the Merger and Acquisition process. And also study the main framework of the Merger and Acquisition. And, also, the article discusses the …
Published in International Journal of Architectural Design and Planning · Vol. 1, Issue 2, 2023 Read article
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An Adaptive Approach for Real-Time Embedded System Design, Analysis and Optimization
Abstract: Real-time embedded systems are critical components in various domains, such as automotive, aerospace, healthcare, and industrial automation. The design, analysis, and optimization of these systems are vital to ensure their reliable and efficient operation. In this paper, we propose an adaptive approach for real-time embedded systems that aims to address the challenges faced during the development process while maintaining high-quality results. Our approach leverages adaptive techniques to dynamically adjust the …
Published in International Journal of Solid State Innovations & Research · Vol. 1, Issue 1, 2023 · pp. 8–14 Read article
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Survey of Predictive Models for Safe Route Predicting Using Machine Learning Techniques
Abstract: Safe route prediction is essential for the well-being and security of individuals in urban and rural environments. Machine learning techniques leverage historical data, real-time information, and algorithms to estimate the safety levels of different routes. The objective of safe route planning is to minimize risks, including crime-prone areas and accidents, reducing potential harm, property damage, and emotional distress. However, challenges arise from the complex and dynamic nature of urban environments, …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 11, Issue 1, 2024 · pp. 13–22 Read article
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Time Series Sales Forecasting Using ARIMA Model
Abstract: Sales forecasting is a critical application in various industries and presents one of the most challenging problems worldwide. One method of prediction involves identifying patterns in historical data, where the outcome is known in advance and can be validated using more recent data. If a pattern consistently leads to the same outcome, it can be considered a genuine relationship. This method is highly flexible and can be utilized with diverse …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 2, Issue 1, 2024 · pp. 17–27 Read article
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Thermo-mechanical Modeling and Analysis of Heat Exchangers for Enhanced Performance in Renewable Energy Systems
Abstract: A comprehensive review of the thermo-mechanical properties of heat exchangers used in renewable energy facilities is presented in this research study. Heat exchangers are essential components of many renewable energy resources like biomass boilers, geothermal power plants, and solar thermal systems. It is crucial to comprehend their thermo-mechanical behavior in order to maximize efficiency, guarantee dependability, and increase operational lifespan. This work explores the complex interactions between mechanical stresses and …
Published in Journal of Experimental & Applied Mechanics · Vol. 15, Issue 1, 2024 · pp. 13–19 Read article
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Designing an Educational Mentoring Model in Line with the Professional Development of Female Primary School Teachers with a Fuzzy Logic Approach
Abstract: The teacher is one of the most important elements known to have a close relationship with students and develop their various talents. If a teacher steps into the education scene with a new, creative and well-equipped attitude, he will naturally deliver capable, creative and new-thinking students to face life wisely and solve the problems of the human world. Therefore, the main goal of this research is to design an educational …
Published in International Journal of Education Sciences · Vol. 1, Issue 1, 2024 · pp. 35–50 Read article
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Identification of Papaya Fruit Ripening Process Using AI
Abstract: Identifying the ripening process of papaya fruit using artificial intelligence involves employing machine learning algorithms to analyze various features such as color changes, texture alterations and chemical compositions. This model is capable of analyzing visual cues to determine the stage of ripeness. The dataset compares images of papaya at various ripening stages, and our AI model demonstrated high accuracy in classifying these stages. Employing machine learning algorithms and image processing …
Published in Research & Reviews : Journal of Food Science & Technology · Vol. 13, Issue 2, 2024 · pp. 23–30 Read article
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Time Series Methods in Meteorology: A Review of Predictive Models and Applications
Abstract: The accurate prediction of time series data holds substantial significance in various fields, enabling informed decision-making and resource optimization. In this study, temperature variations over time are predicted using the Autoregressive Integrated Moving Average (ARIMA) model. Reliable temperature projections are more important now than ever because of climate change and its effects. For time series prediction problems, the ARIMA model—which is well-known for its ability to capture temporal dependencies in …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 13, Issue 2, 2024 · pp. 35–46 Read article
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Advancing Grid Integration: Maximum Power Point Tracking-Based Model Predictive Current Control Technique for Photovoltaic Systems
Abstract: Tracking a PV system's maximum power point is necessary as demand for grid-connected solar systems rises, regardless of utility demand. Since the PV system's output is D.C., a converter serving as a middleman between the PV system and the D.C. link capacitor is necessary to track the maximum power at all loads. Since the firing angle of the IGBT in the boost converter is between 0 and 1 at maximum …
Published in International Journal of Electrical Machine Analysis and Design · Vol. 1, Issue 2, 2023 · pp. 31–35 Read article
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The Poisson–Uma Distribution with Properties and Applications to Model Thunderstorm Events
Abstract: The discrete data available in any field of knowledge is influenced by several known and unknown factors and the factors which affect the discrete data are stochastic. The stochastic nature of discrete data is a challenge for statisticians to model and analyze with the existing discrete distributions. In the present paper, Poisson-Uma distribution, the Poisson compound of Uma distribution, has been proposed to model over-dispersed data of thunderstorm events. The …
Published in Research & Reviews : Journal of Statistics · Vol. 13, Issue 1, 2024 · pp. 20–30 Read article
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Modelling Electronic Diode Networks with PSPICE Simulation
Abstract: The dual of Thevenin, Norton equivalent circuit is used in place of any circuit/network of linear sources and immittances at at a given frequency. Both Thevenin with Norton theorem is useful for analyses and modification of circuits, to study /obtain network’s steady state response and initial condition. Methods to represent different circuits with Thevenin/Norton impedances connected at desired nodes are given using Spice/Pspice. The Thevenin/Norton impedances connected are of other …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 2, Issue 2, 2024 · pp. 17–37 Read article
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An Intelligent Modelling system for Automotive Vehicles
Abstract: In this paper it’s about the development of artificial intelligence that has fuelled technological advancements. Self-driving automobiles are an example of an innovative development. Nowadays, you may work or sleep in your car while driving to your destination without touching the steering wheel or accelerator. This project aims to create a workable model of a self-driving car capable of traveling on multiple tracks, including curved, straight, and straight followed by …
Published in Journal of Instrumentation Technology & Innovations · Vol. 15, Issue 1, 2025 · pp. 32–40 Read article
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Mathematical Models of Agricultural Cycles in Tribal Astronomy
Abstract: This paper delves into the intricate connection between traditional tribal agricultural practices and astronomical observations, showcasing how indigenous communities have historically relied on celestial movements to guide essential farming activities. By observing the phases of the moon, solar cycles, and the positions of star constellations, tribes have developed precise methods for determining the optimal timing for planting, harvesting, and seasonal planning. These astronomical practices are deeply embedded in their cultural …
Published in Research & Reviews : Journal of Statistics · Vol. 13, Issue 3, 2024 · pp. 9–17 Read article
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CNN-Based Wound Segmentation: A Review of Models and Performance Evaluation
Abstract: Deep learning, particularly convolutional neural networks (CNNs), has altered medical image processing by automating and precisely segmenting complex medical pictures. Wound segmentation, a critical application in automated wound assessment, is essential for wound size estimation, classification, and healing progress monitoring. This study presents a comprehensive review of CNN-based wound segmentation models, focusing on their architectures, methodologies, and performance on diverse datasets. Four deep learning models, including two U-Net variants (5-layer …
Published in Current Trends in Signal Processing · Vol. 15, Issue 1, 2025 · pp. 33–46 Read article
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Overview of Ionic Polarization: A Model Based Novel Approach
Abstract: This study presents a comprehensive analysis of ionic polarization through a novel model-based approach that integrates theoretical, computational, and experimental methodologies. Ionic polarization, which significantly influences the dielectric properties of materials, is examined through the lens of the Clausius-Mossotti equation and the Debye relaxation model, providing a theoretical framework for understanding the relationship between ionic displacement and dielectric behavior. To explore ionic displacement and polarization at the atomic level, advanced …
Published in International Journal of Cheminformatics · Vol. 2, Issue 2, 2024 · pp. 18–25 Read article
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Enhancing Dimensional Accuracy of Affordable 3D-Printed Objects Via Solid Model Tuning For Industrial Manufacturing
Abstract: In the industrial applications of 3D printing (3DP) technologies, achieving precise dimensional accuracy and precision as well as improving surface quality are essential goals. With a focus on cost-effective engineering applications, this experimental research examines how solid model geometry tuning improves the internal and exterior dimensional accuracy of inexpensive 3DP technologies. Dimensional errors in the X, Y, and Z directions were meticulously measured on 3D parts made using Material Extrusion/Fused …
Published in Journal of Polymer & Composites · Vol. 13, Issue 3, 2025 · pp. 201–210 Read article
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Enhanced Diabetes Prediction: A Comparative Study of Machine Learning Models
Abstract: Excessively high blood glucose levels lead to diabetes, a condition that can be better managed with early detection, resulting in a longer life and improved health. Machine learning models are essential tools in diagnosing diabetes, especially when trained on appropriate and relevant datasets. In this study, a combination of ensemble methods and nine distinct machine learning algorithms were utilized to develop a predictive model for diabetes diagnosis based on a …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 2, 2025 · pp. 1–10 Read article
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Mathematical Modelling on Unsteady Blood Flow and Unsteady Heat Transfer Through a Stenosed Artery with Hematocrit and Slip Velocity
Abstract: A theoretical investigation concerning variable viscosity dependent on percentage concentration of red blood cell interm of total volume of blood (hematocrit) and slip velocity on unsteady flow of blood and heat transfer has been carried out. The analytical expressions for the flow characteristics and the heat transfer rate, including the velocity profile, volumetric flow rate, flow resistance, wall shear stress, and temperature profile, were obtained using the weighted residual method, …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 12, Issue 2, 2025 · pp. 16–36 Read article