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1966 articles for “havriliak–negami modeling” (ranking capped at the first 2,000 matches — narrow the search to see the rest)
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Designing a Model of Waste Management for Sustainable Rural Development (Case study: villages of Gilan Province)
Abstract: Paying attention to waste management is one of the most important tasks defined for urban and rural officials around the world. These days, every small and large city or every village and hamlet you visit is faced with a problem called waste and waste management. This is all the more important when we know that most of this waste comes from seasonal streams and rivers; On the other hand, the …
Published in Recent Trends in Social Studies · Vol. 1, Issue 2, 2024 · pp. 30–46 Read article
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Exploring the Dynamics of Memristors: Mechanisms, Models, and Multifaceted Applications
Abstract: Memristors, a fundamental electronic component first proposed by Leon Chua in 1971, have garnered significant attention due to their unique electrical behavior and promising applications in various fields. This paper provides a comprehensive overview of memristors, covering their basic principles, characteristics, fabrication methods, and applications of Memristor and it’s significance with flux charge linkage. The paper also shows study of a grounded memristor emulator and it’s working as a memristor …
Published in Journal of VLSI Design Tools and Technology · Vol. 14, Issue 1, 2024 · pp. 1–7 Read article
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Insilico Structural Analysis and Homology Modeling of Crustin Protein from Fiddler Crab Species
Abstract: In terms of biomass and ecological or economic importance, the crustacea are the largest, most noticeable, and possibly, the most significance group of marine or aquatic arthropods. Because of their enormous commercial value and the necessity to prevent disease outbreaks in the shellfish aquaculture industry, decapods are the experimental animals of choice for practically all biological studies involving immune responses. Antimicrobial host-defense peptides (AMPs) are major components of metazoan immunity, …
Published in International Journal of Cheminformatics · Vol. 1, Issue 1, 2023 · pp. 1–7 Read article
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Examining Job Satisfaction and its Effect on Employee Productivity of a Textile Industrial Unit
Abstract: Productivity, especially the productivity of human resources, which is one of the necessities of the growth and development of every society and organization; It is not achieved by simply increasing salaries and benefits and amenities. Rather, making people productive depends on creating satisfaction and increasing job satisfaction. The current research is a descriptive-correlation method; The purpose of the research is to investigate the relationship between job satisfaction (Powell-e Specter model) …
Published in International Journal of Behavioral Sciences · Vol. 1, Issue 1, 2024 · pp. 26–38 Read article
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A Linear Regression Model Used to Analysis the Tesla Stock Price Prediction Using Machine Learning
Abstract: The stock market is a fascinating sector of the economic research. It comes in a number of varieties. Several specialists have been examining and investigating the several patterns that the stock market experiences fluctuations. Predicting the stock values of different companies using historical data has been one of the primary research projects. Stock price prediction can help people a great deal by helping them understand where and how to invest, …
Published in Journal of Advanced Database Management & Systems · Vol. 11, Issue 2, 2024 · pp. 8–13 Read article
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InSilico Analysis and Homology Modeling of Tetrahydroprotoberberine Oxide involved in the Berberine Biosynthesis
Abstract: Objective: Berberine, a bioactive compound found in various plant species, exhibits diverse pharmacological properties with potential applications in pharmaceutical research. The biosynthesis of berberine involves several enzymatic steps, with (S)-tetrahydroprotoberberine oxidase playing a pivotal role. This study aimed to elucidate the structural and functional characteristics of (S)-tetrahydroprotoberberine oxidase to better understand its role in berberine biosynthesis and its potential biotechnological applications. Methods: Using bioinformatics tools and computational methods, the physicochemical …
Published in Emerging Trends in Metabolites · Vol. 1, Issue 1, 2024 · pp. 7–26 Read article
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Development of a Machine Learning and Artificial Intelligence Based Model Aimed at Forecasting the Prognostic Impact of C-Reactive Protein in Myocarditis
Abstract: The specific role of inflammation markers in myocarditis remains uncertain. We investigated the diagnostic and prognostic significance of C-reactive protein (CRP) levels at the initial diagnosis among myocarditis patients. Our retrospective study enrolled patients clinically suspected (CS) or biopsy-proven (BP) with myocarditis, with available CRP data at diagnosis. We collected patient information, including clinical, laboratory, and imaging findings at diagnosis and follow-up visits. We utilized machine learning methods, specifically random …
Published in Research and Reviews: A Journal of Health Professions · Vol. 14, Issue 2, 2024 · pp. 12–24 Read article
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Visual Recognition with Convolutional Neural Networks for Object Detection
Abstract: Various research and development have taken place over the years on computer vision which is a branch of AI. AI disciplines like a vision system is applied in various fields like self-driving cars, face detection by social media apps and law enforcement software’s google lens and so on. The proposed system deals with design and implementation of an efficient way of training a GPU using python libraries to process and …
Published in Trends in Opto-electro & Optical Communication · Vol. 14, Issue 2, 2024 · pp. 07–13 Read article
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Exploring the State-of-the-art in Plug-in Hybrid Electric Vehicle Design and Modeling: A Review
Abstract: This document provides a thorough explanation of the process involved in designing and developing plug-in hybrid electric vehicles (PHEVs). A viable way to lessen greenhouse gas emissions and reliance on conventional internal combustion engine vehicles is through plug-in hybrid electric vehicles (PHEVs), which have gained popularity in response to growing concerns about environmental sustainability and the depletion of fossil fuels. The main elements, design factors, difficulties, and developments in the …
Published in International Journal of Electrical Machine Analysis and Design · Vol. 1, Issue 2, 2023 · pp. 8–15 Read article
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A Comparative Analysis of Machine Learning Techniques for Fruit Defect Detection Systems
Abstract: With evolving technologies in machine learning, significant advancements have been made in the livestock industry, helping to reduce waste, increase yield, achieve cost savings, and improve competitiveness in the marketplace. Fruit defect detection models support precision agriculture by providing valuable data for decision-making and enhancing overall efficiency through automated inspection processes. This study implements and comparatively evaluates machine learning models including MobileNetV2, a custom-designed convolutional neural network (CNN) model, ResNet50, …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 11, Issue 3, 2024 · pp. 37–47 Read article
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A Split and Merge UNet: A Deep Learning Assisted UNet Model to Segment Corpus Callosum of Brain for Automatic Autism Detection
Abstract: In recent years, deep learning techniques have shown remarkable performance in various image analysis applications, particularly in the domain of medical image processing. Among these, image segmentation plays a critical role, as it helps in isolating and analyzing specific regions within medical images. The proposed study focuses on segmenting the corpus callosum, a vital structure in the human brain, using a novel optimization technique known as the Split and Merge …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 11, Issue 3, 2024 · pp. 1–9 Read article
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Hybrid Techniques in Mango Leaf Disease Identification: Evaluating Neural Networks and Support Vector Machines
Abstract: Mango leaf diseases pose a significant threat to mango production, impacting both yield and fruit quality. Early and accurate detection of these diseases is crucial for effective management. This paper evaluates the use of hybrid techniques, specifically the integration of neural networks (NNs) and support vector machines (SVM), in the identification and classification of mango leaf diseases. NN excel in extracting complex features from images, while SVMs are robust classifiers, …
Published in Trends in Opto-electro & Optical Communication · Vol. 14, Issue 3, 2024 · pp. 19–27 Read article
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Physico-Chemical Assessment of River Benue to Determine Pollution Levels Using Chemometric Models.
Abstract: The effects of pollution on water have been reviewed. This study is aimed at determining the level of pollution of the River Benue, with the view of assessing its use as potable water. Different analytical techniques including titrimetry, gravimetry, potentiometry, and spectrophotometry were used for the study. The total hardness gave (22.28 mg/L and 41.87 mg/L) for dry and rainy season respectively. Electrical conductivity gave (91.35 mg/L and 54.10 mg/L) …
Published in International Journal of Pollution: Prevention & Control · Vol. 2, Issue 2, 2024 · pp. 43–76 Read article
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A Comparative Study of different Techniques to predict Maternal Morbidity and Mortality Model
Abstract: Artificial intelligence (AI) encompasses a range of techniques, including machine learning and deep learning, which are increasingly utilized in the healthcare sector for tasks such as disease diagnosis and drug discovery. To achieve accurate disease diagnosis through AI, it is essential to integrate data from multiple medical sources, including ultrasound imaging, magnetic resonance imaging (MRI), mammography, genomics, and computed tomography (CT) scans, among others. This article presents a comprehensive review …
Published in Research and Reviews: A Journal of Health Professions · Vol. 15, Issue 1, 2025 Read article
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Health Risk and Evaluation of Atmospheric Pollutants in Owerri Metropolis and Sub-Urban Areas of Imo State, Nigeria Using Chemometric Models
Abstract: Concern about health risk from atmospheric pollutants; Particulate Matter (PM10), Sulphur dioxide (SO2), Nitrogen dioxide (NO2) and Carbon Monoxide (CO) prompted atmospheric monitoring and inhalation health risk assessment for residents of Owerri Metropolis and its Sub-urban areas. Field measurements were carried out in 35 select locations within Imo State. Monitoring was carried out using Chemometric methods as Matrix Laboratory (MATLAB) and Artificial Neural Network (ANN). According to the experiment results, …
Published in Research & Reviews : Journal of Statistics · Vol. 13, Issue 1, 2024 · pp. 47–79 Read article
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AI For Climate Vulnerability Assessment
Abstract: Climate change is one of the biggest problems we face every day. The main problems are high temperatures, rising sea levels, and changes in weather, which will be worse in the upcoming years. To predict and adapt to these impacts, we need to create data-driven solutions. The main tool for predicting climate change was artificial intelligence, which can also be utilised to predict the weather and alert people of impending …
Published in International Journal of Radio Frequency Innovations · Vol. 3, Issue 1, 2025 · pp. 18–33 Read article
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A research study into the interactions between the monoherbal formulations of arjuna and Aloe vera in a rat model of isoproterenol-induced cardiotoxicity
Abstract: Aloe vera is a herbal dietary supplement, and arjuna is used for its cardioprotective properties. Rats were given isoproterenol hydrochloride subcutaneously to cause myocardial infarction. The purpose of the study was to identify any potential pharmacodynamic interactions between the commercially available formulations of Aloe vera and arjuna. Materials and Procedures: The electrocardiogram (heart rate, ST segment elevation time, QRS complex amplitude), serum cardiac markers (creatine kinase, isoform of creatine kinase, …
Published in International Journal of Toxins and Toxics · Vol. 2, Issue 2, 2025 · pp. 1–10 Read article
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KVS Approach for IoT Network Security: A Novel Approach to IoT Network Security With B-Cell Inspired Models
Abstract: Internet of Things (IoT) is rapidly expanding, connecting billions of devices that collect, process, and transmit data. This interconnectedness, while offering immense opportunities, also presents significant security challenges. Customary security mechanisms often scuffle to retain stride with the vibrant and assorted form of IoT environments. In response, innovative security concepts are being explored, and one promising approach is the B-Cell concept called as KVS approach for IoT security. In immunology, …
Published in Journal Of Network security · Vol. 13, Issue 2, 2025 · pp. 16–25 Read article
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Harnessing Hydrolgeological Parametrs: Prediction of Water Probability and Levels for Water Well Construction Using Ai-Enabled Models
Abstract: The AI-Based Decision Support System for Water Well Construction utilizes data from the National Aquifer Mapping and Management System (NAQUIM) and employs advanced AI techniques like regression analysis, decision trees, and neural networks. This system predicts crucial parameters for water well construction, including location suitability, water-bearing zone depths, and groundwater quality. By integrating large datasets such as lithology, geophysical logs, and aquifer maps provided by the Central Ground Water Board …
Published in Journal of Water Resource Engineering and Management · Vol. 12, Issue 1, 2025 · pp. 16–28 Read article
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Modelling and Interpretation of A Novel Battery-Motor amalgamated Thermal Management System using rGO/CO3O4 based Hybrid Nano-composite Coolant for Electric Vehicle Applications
Abstract: Battery and motor have to be given equivalent importance to maintain the lifetime, thermal characteristics, efficiency and safety of Electric Vehicles (EVs). Thermal management of EVs need to be considered for battery and motor because of dynamic loading conditions. This research proposes a novel Battery-Motor Integrated Thermal Management System (BMITMS) for EV applications. An EV assembled with LiFePO4 battery pack and a three-phase induction motor has been considered on this …
Published in Journal of Polymer & Composites · Vol. 13, Issue 4, 2025 · pp. 225–243 Read article