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786 articles for “model-based approach”
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Process Mapping and Bottleneck Analysis of the Wellness Provider Deployment Cycle
Abstract: This Study focuses on understanding how a wellness service provider company currently manages the process of assigning wellness professionals—such as fitness trainers, doctors, and mental health experts—to corporate clients, and where delays tend to occur within that process. As the organization follows an aggregator-based service model, it works with a wide network of freelance professionals spread across multiple cities. While this approach allows flexibility and rapid expansion, it also makes …
Published in Journal of Production Research & Management · Vol. 16, Issue 2, 2026 · pp. 26–32 Read article
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Modelling of Large Elasto-plastic Deformations by EFGM
Abstract: Current work reports modelling and simulation of geometric and material nonlinearities arising due large elasto-plastic displacements in structural specimens by invoking enriched element free Galerkin method (EFGM). The displacement approximations are constructed by using moving least square approach. Standard displacement based approximations are modified by incorporating suitable enrichment functions depending on the nature of interfaces present in the components. Large deformations give rise to geometric nonlinearities which have been modelled …
Published in Journal of Polymer & Composites · Vol. 12, Issue 2, 2024 · pp. 130–143 Read article
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Rating Based Sentimental prediction: A Six Gram Statistical Mean-Median Approach
Abstract: Revolution in internet has opened a new platform for expressing the user opinions on various aspects openly in various Business domains. The expressed views include very useful information with which analysis of the user expectation and requirements can be done. Analyzing the user views and its prediction will help the business people to enhance their services to the customers as per user requirement. In this paper a novel approach is …
Published in Journal of Advanced Database Management & Systems · Vol. 5, Issue 2, 2018 · pp. 33–42 Read article
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Parkinson’s Disease Detection on Spiral Images Using CNN with Meta-Classifiers
Abstract: In this work, we provide a detailed method for identifying Parkinson’s Disease (PD) by integrating Convolutional Neural Network (CNN) and meta-classifiers. Through the utilization of a varied dataset consisting of handwritten spiral images, our methodology demonstrates commendable accuracy across a range of models. Specifically, our CNN model with meta-classifiers surpasses alternative approaches, achieving an impressive accuracy rate of 95.07%. By utilizing pre-established VGG16 and ResNet50 architectures as bases, the region-based …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 1, 2025 · pp. 55–66 Read article
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A Comprehensive Review of CNN-Based Framework for Multi-Sign Detection of Diabetic Retinopathy in Fundus Images Using Public Datasets
Abstract: Diabetic retinopathy (DR) is one of the main causes of vision impairment. Blindness prevention and effective treatment depend on early detection. A thorough deep learning-based framework for the automatic segmentation and simultaneous detection of exudates, hemorrhages, and microaneurysms – three important DR indicators – from retinal fundus images is presented in this work. These three pathological signs’ corresponding annotated image patches, along with background (no-sign) areas, were used to train …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 3, 2025 · pp. 14–23 Read article
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Recipe-Fusion: Multimodal Food Recipe Recommendation System
Abstract: The food recipe recommendation system using data science is a software solution designed to help users discover new and delicious food options based on their food history and other relevant data. This system recommends various recipes based on the input given by the user and it helps to filter out the recipes on course type, diet type, and nature of the food (including non-veg, and veg) using a recommendation technique. …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 3, 2024 · pp. 82–91 Read article
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Age, Gender And Emotion Detection
Abstract: The main reason is the development of a method to automatically estimate the age and gender of the human face. It continues to play an important role in computer vision and pattern recognition. In addition to age determination, facial emotion recognition also plays an important role in computer vision. Nonverbal communication methods such as facial expressions, eye movements, and gestures are used in many human-computer interaction applications. Much research has …
Published in Recent Trends in Sensor Research & Technology · Vol. 9, Issue 1, 2022 · pp. 1–6 Read article
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Advanced Anomaly Detection in Cloud Infrastructures Using Deep Learning Algorithms
Abstract: It is critical to guarantee the stability and security of cloud environments as cloud computing is becoming the backbone of contemporary IT infrastructures. Neglecting to quickly identify and resolve anomalies, which might point to security breaches, performance problems, or system breakdowns, can lead to disastrous outcomes. The increasing size and complexity of cloud infrastructures are challenging the effectiveness of traditional anomaly detection methods. These approaches often depend on rule-based systems …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 1, 2025 · pp. 1–11 Read article
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Creating a “Sustainable Future” Through Secure AI
Abstract: It is imperative in the present world that we figure out a way to move toward a sustainable future. However, a sustainable future from an energy standpoint can only be built by a sustainably intelligent society. Yet, individuals who come together to form a society tend to neglect discussions around sustainability, considering it something that should be driven in a top-down manner. In reality, with the rapid emergence of artificial …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 13, Issue 1, 2026 · pp. 1–7 Read article
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Study on Single-Slope Solar Still for Experimental and Data-Driven Analysis for Improving Productivity with Different Basin Materials.
Abstract: This study investigates the single-slope solar still under the diurnal variation of water temperature and distillate yield under identical operating conditions. Experimental analysis was conducted to evaluate the performance enhancement through the incorporation of natural basin materials, namely hemp and sand. The water distillation process is focused on improving potable water productivity and thermal behaviour. The inclusion of hemp and sand in the basin leads to noticeable differences in productivity …
Published in Emerging Trends in Chemical Engineering · Vol. 13, Issue 2, 2026 · pp. 31–46 Read article
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A Graph Theoretic Approach to quantify the Conflict of Traffic Streams in a Traffic Intersection
Abstract: A traffic intersection can be modelled by a graph by considering the streams as vertices and assigning an edge based on the mutually non-conflict streams. In this paper we propose a spectral approach to arrange the steams in order of their conflict and hence determine the most conflicted stream in a traffic intersection.
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 5, Issue 2, 2018 · pp. 22–25 Read article
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Zoom Based Image Super-Resolution: Using Two Level DWT as Feature Model
Abstract: AbstractIn this paper we present an algorithm of super-resolution (SR) imaging to reconstruct high-resolution (HR) image from sequence of low-resolution (LR) images of static scene captured at the different camera zoom factor. The resultant HR image is constructed at the resolution of the most zoomed LR image. In the proposed approach algorithm uses LR images of the static scene captured at three distinct zoom-factors. Learning based SR technique is used …
Published in Journal of Communication Engineering & Systems · Vol. 9, Issue 2, 2019 · pp. 95–105 Read article
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A Lightweight Cost-Sensitive Explainable Ensemble Framework for Early Heart Disease Risk Prediction
Abstract: Cardiovascular disease is still one of the leading causes of death, and hence, the early prediction of risk is a very important task in preventive medicine. Although recent studies have shown encouraging results in the application of machine learning algorithms to the prediction of heart disease, it has been noticed that most of the algorithms are more concerned with accuracy-driven optimization than the concerns of safety and false negatives. In …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 2, 2026 · pp. 26–40 Read article
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Study of Anti-Leishmanial Activities of Metabolites on Leishmania major: A Structure-Based Drug Designing Approach
Abstract: Cutaneous Leishmaniasis is one of the major problem all over the world and has no suitable treatment to treat this disease. However, the range of drugs is limited and increased use of these drugs lead to multiple drug resistance and has posed a major concern. Here the genome sequences of Leishmania major (responsible for cutaneous Leishmaniasis) is identified for having few drug targets that are unique to these parasites. GPI …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 4, Issue 3, 2017 · pp. 30–40 Read article
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Modulation of Receptor Proteins: A Recent Paradigm in Drug Discovery and Target
Abstract: The main aim in drug discovery is to design different ligands those work on specific drug targets. However, various effective drugs work through the modulation of many proteins than single target. Advancement in system biology are establishing a phenotypic strength and a network structure, which suggests that, the excellent selective compounds may be performed less than desired clinical efficacy in comparison to multi-target drugs. In this new appreciation of the …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 5, Issue 1, 2018 · pp. 14–24 Read article
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Fertilizer Prediction Using Machine Learning
Abstract: Fertilizer prediction is a critical aspect of modern agriculture, aimed at optimizing resource utilization while maximizing crop yields. In recent years, machine learning (ML) techniques have emerged as powerful tools for addressing this challenge by leveraging data-driven approaches to predict the optimal type and quantity of fertilizer required for different crops and soil conditions. This research paper provides a comprehensive review of the existing literature and methodologies employed in fertilizer …
Published in Journal of Mechatronics and Automation · Vol. 11, Issue 2, 2024 · pp. 26–35 Read article
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A Review of AI-Based Intrusion Detection Systems for Mobile Ad Hoc Networks (MANETs)
Abstract: Mobile Ad Hoc Networks (MANETs) comprise wireless networks that lack any conventional infrastructure . Their chief features include highly changing network topologies, lack of centralized administration, and open nature of communication, which collectively result in making MANETs of the wireless kind very susceptible to a diverse range of cyber-attacks like blackhole, greyhole, wormhole, flooding, Sybil and denial-of-service (DoS) among others. Conventionally, Intrusion Detection Systems (IDS) relying on static rule-based methods …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 3, 2025 Read article
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Creating a ‘Sustainable Future’ through Secured-AI
Abstract: It is imperative in the present world that we need to figure out a way to move to a ‘Sustainable future’. However, a ‘Sustainable future’ from an energy standpoint can only be built by a ‘Sustainably intelligent’ society. But the individuals who come together to form a society tend to neglect any discussion around ‘Sustainability’ considering it as something to be driven in top-down manner. In reality, with the massive …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 12, Issue 3, 2025 Read article
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The Application of Python Programming Language in the Automation of a Mathematical Model for Well Trajectory Selection Optimisation for a Given Field
Abstract: Directional drilling plays a major role in the exploration and recovery of hydrocarbons. There are three basic trajectories that a well may follow. They include; Build-and-Hold, Build-Hold-andDrop and Continuous-Build Trajectories. The selection of a trajectory is usually based on experience/trial and error approach and may be associated with errors. This work has therefore developed a mathematical model that optimised the automatic selection of a well trajectory type for a given …
Published in Journal of Petroleum Engineering & Technology · Vol. 12, Issue 3, 2022 · pp. 1–9 Read article
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From Cattle to Capital: A Review on SHGs, Dairy Farming, and Gender Empowerment in Rural India
Abstract: Self-Help Groups (SHGs) have emerged as a platform for encouraging women to start their own ventures in rural India, particularly through dairy-based enterprises. This review explores the role of SHGs in enhancing financial support, skill development, market access, and social empowerment among rural women. By utilizing savings and providing microcredit, SHGs enable women to establish and expand dairy ventures, contributing to household income and organized milk production. The integration of …
Published in Research and Reviews : Journal of Dairy Science and Technology · Vol. 15, Issue 2, 2026 · pp. 1–13 Read article