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132 articles for “task specific”
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Taskpro AI: Redefining Small Business Content Creation Through Advanced AI Innovation
Abstract: TaskPro AI is a chatbot made using the GPT-4.0 API key to revolutionize textual content creation for small businesses. Harnessing the power of generative AI, TaskPro AI is a versatile tool for generating various writing works, including blog posts, product articles, social media captions, and more. The chatbot streamlines content creation by providing users with an intuitive interface, making it effortless to articulate their ideas, thanks to its advanced capabilities. …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 11, Issue 1, 2024 · pp. 7–13 Read article
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Encoder-Decoder Based Fine-Tuned Model for Code Doubt Solver
Abstract: As we are growing in technology, more technologically skilled persons are needed in industry. They all often rely on programming in their daily work, and when some doubts arise, they seek help from teachers to LLMs like GPT to Deepseek. However, when errors arise, then comes hectic part to troubleshoot and resolve the error. Usually, people seek help from some LLMs like GPT, or Deepseek for the solution; they give …
Published in Recent Trends in Programming languages · Vol. 12, Issue 3, 2025 · pp. 35–42 Read article
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Designing Self-Optimizing Operating Systems: Information-Theoretic Approaches to Thread Scheduler Implementation
Abstract: Thread Level Scheduling (TLS) in multi-core and many-core processor environments represents a critical frontier in next-generation operating system design. As computing systems grow increasingly heterogeneous and concurrent, traditional scheduling strategies often rely on heuristics or localized resource metrics, frequently overlooking the deeper, quantifiable relationships and uncertainties inherent in complex concurrent workloads. This study explores the application of information-theoretic approaches, specifically entropy-based task allocation, mutual information-driven dependency analysis, and channel capacity-inspired …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 3, 2025 · pp. 31–39 Read article
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The Impact of Using High-Resolution Satellite Images on Improving Geographic Maps
Abstract: By integrating high-resolution satellite images into pre-existing mapping frameworks, this study tackles the problem of guaranteeing correctness and dependability in geospatial data updates. The main goal is to assess which satellite imagery sources—SuperView, Ikonos, QuickBird, and WorldView—are appropriate for updating maps at 1:2500 and 1:5000 scales. The process entails evaluating radiometric quality, geometric dependability, spatial correctness, and picture resolution and comparing the results to the specifications of different mapping tasks. …
Published in Journal of Remote Sensing & GIS · Vol. 17, Issue 1, 2026 · pp. 36–44 Read article
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Support of Knowledge-oriented Business Processes through Workflow Management Systems
Abstract: A major challenge in implementing business process-related knowledge management is to encourage employees to participate in knowledge processes. On the one hand, the educational work should be integrated harmoniously into the work context and, on the other hand, information must be presented and actively distributed as needed. In order to be able to introduce systematic knowledge management in companies, the design dimensions that a knowledge management project encompasses must first …
Published in E-Commerce for Future & Trends Read article
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Face Detection and Recognition Using MTCNN and FaceNet
Abstract: Face detection and face recognition are major tasks in the field of computer vision with several real-world applications and many products being developed in the same field. This study gives a detailed implementation of the product that is developed for accurate detection and recognition of faces along with audio output of the face detected. This development would act as a base for a few future products that can be developed …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 2, 2024 · pp. 132–140 Read article
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AI and Machine Learning Approaches for Estimating Depression Severity: Techniques, Trends, and Applications
Abstract: Depression is a very common mental health disorder that results in a disorder of a person’s behavior, emotions, and cognitive abilities. Depression can be caused by environmental factors or hereditary factors. The person suffering from depression might have symptoms of suicidal thoughts, altering food patterns as well as sleeping issues. Depression is a global issue that has impacted millions of people globally having more effect on women worldwide. The complexity …
Published in Journal of Electronic Design Technology · Vol. 15, Issue 3, 2024 · pp. 29–38 Read article
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Multimodal Disease Detection Using Deep Learning
Abstract: Artificial Intelligence (AI) is playing an increasingly pivotal role in modern healthcare, particularly in improving the speed and accuracy of disease detection. With the evolution of Machine Learning (ML), Deep Learning (DL), and high-performance computing, AI-based solutions are now capable of processing extensive medical datasets, ranging from patient records to diagnostic images, with remarkable efficiency. These systems offer immense potential for early intervention, improved clinical decision-making, and alleviating pressure on …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 129–139 Read article
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Detection and Classification of Brain Tumor from MRI And CT Images using Harmony Search Optimization and Deep Learning
Abstract: Primary brain tumor detection and classification are critical factors in ensuring effective treatment and, ultimately, improving patient well-being. This paper describes a novel method for detecting and classifying brain tumors with the help of magnetic resonance imaging (MRI) and computed tomography (CT) images. The suggested method combines harmony search optimization (HSO) and Convolution Neural Networks (CNN) based on deep learning techniques, yielding an impressive accuracy rate of 99.13% for both …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 3, 2024 · pp. 31–49 Read article
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Optimizing Multi-Cloud Infrastructure: Advanced Bash-Based Automation for Automated Security Patching and Health Monitoring in Hybrid Linux Environments
Abstract: The proliferation of multi-cloud and hybrid Linux environments has introduced significant operational complexity, particularly in maintaining security compliance and system reliability across diverse infrastructure silos. Traditional patch management approaches, relying on manual interventions or disparate vendor-specific tools, suffer from latency, configuration drift, and limited visibility. This article presents a novel, lightweight automation framework constructed entirely in advanced Bash scripting to address automated security patching and real-time health monitoring across hybrid …
Published in Journal of Advances in Shell Programming · Vol. 13, Issue 2, 2026 Read article
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A Survey on PLC in industrial Safety
Abstract: Programmable Logic Controllers (PLC) plays an important role in providing integrated safety functionalities which allows it to control all other systems. The complexity in various methodologies requires the correctness of software for the applications which are very critical. The PLC software has to abide by the specification and it is a very challenging task. The current study introduces various methodologies and techniques which provide reliability and safety to control systems. …
Published in Journal of Industrial Safety Engineering · Vol. 6, Issue 3, 2019 · pp. 19–24 Read article
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Optimizing Multi-Cloud Infrastructure: Advanced Bash-Based Automation for Automated Security Patching and Health Monitoring in Hybrid Linux Environments
Abstract: The proliferation of multi-cloud and hybrid Linux environments has introduced significant operational complexity, particularly in maintaining security compliance and system reliability across diverse infrastructure silos. Traditional patch management approaches, relying on manual interventions or disparate vendor-specific tools, suffer from latency, configuration drift, and limited visibility. This article presents a novel, lightweight automation framework constructed entirely in advanced Bash scripting to address automated security patching and real-time health monitoring across hybrid …
Published in Journal of Advances in Shell Programming · Vol. 13, Issue 1, 2026 · pp. 16–28 Read article
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Application of GIS Web Based in Construction Management
Abstract: Project management is the process and task of planning, organizing, motivating, and controlling resources, procedures, and protocols to achieve specific goals in scientific or daily problems. In the construction world, it is crucial to monitor project management because each project has its duration and every contractor needs to complete the project within the given time. Moreover, exceeding the duration given will cause the penalty to the contractor which in turn …
Published in Journal of Geotechnical Engineering · Vol. 4, Issue 2, 2017 · pp. 17–25 Read article
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Fake News Detection System Using MultinomialNB and Django Framework
Abstract: The emergence of the World Wide Web and the rapid growth of online platforms have transformed the landscape of news dissemination. However, the rise of social media has also led to an overwhelming influx of potentially unreliable information, making it increasingly challenging to verify the truthfulness of articles. This verification process has become a daunting task, necessitating a thorough examination of various domain-specific aspects to ascertain the credibility of news …
Published in Current Trends in Information Technology · Vol. 15, Issue 1, 2025 · pp. 23–32 Read article
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Optimization of Robotic Path Planning Algorithms for Autonomous Material Handling Systems
Abstract: For autonomous systems for handling materials (AMHS) to operate as efficiently as possible in industrial and logistical settings, robotic route planning is essential. This study examines many robotic route planning algorithms, emphasizing their use, ways of optimization, and difficulties in material handling systems. To improve the effectiveness, precision, and computational viability of these algorithms, the study also examines a number of optimization strategies, including machine learning, parallelization, heuristic search, and …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 2, Issue 2, 2024 · pp. 15–20 Read article
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A Review on Transformer Design and Innovative Aspects of Optimization
Abstract: Transformer is the most costly and important component of power system. It is more than 100 years old technology. Technology has not changed drastically but the challenges are continuous increase in size and rating, competition in global market, accurate prediction of performance parameters, updating of design baseline and many more. Transformer design optimization (TDO) is a complex task in which designer have to ensure that the imposed specifications are met, …
Published in Journal of Instrumentation Technology & Innovations · Vol. 6, Issue 1, 2016 · pp. 10–22 Read article
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MentaLLaMA: Advancing Mental Health Insights with Instruction-Finetuned Large Language Models
Abstract: The growing prevalence of mental health challenges in contemporary society has highlighted the urgent need for advanced, interpretable, and reliable artificial intelligence solutions that can support mental health assessment and intervention. In response to this need, this research introduces a novel collection of open-source, instruction-tuned large language models (LLMs) specifically designed to facilitate transparent and accurate mental health evaluations. Leveraging a newly developed dataset, which integrates multiple tasks and diverse …
Published in Recent Trends in Programming languages · Vol. 12, Issue 3, 2025 · pp. 08–15 Read article
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Using Machine Learning for Key phrase Extraction in Digital Libraries
Abstract: Machine learning has revolutionized various aspects of information retrieval, including key phrase extraction in digital libraries. Key phrase extraction is crucial for summarizing and categorizing vast amounts of textual data, enabling efficient search and retrieval processes. This study explores the application of machine learning techniques for automatic key phrase extraction in digital libraries. We review various supervised and unsupervised learning algorithms, including deep learning models, that are employed to identify …
Published in International Journal of Cheminformatics · Vol. 1, Issue 2, 2023 · pp. 8–13 Read article
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Enhancing Glaucoma Diagnosis with Deep Learning: A Study Using ResNet-50 and DenseNet-121
Abstract: Glaucoma is a leading cause of irreversible blindness worldwide, mainly resulting from progressive optic nerve damage, often related to elevated intraocular pressure. Early detection is essential to prevent vision loss, but traditional diagnostic methods rely on specialized equipment and trained professionals, making large-scale screening difficult. This study uses a publicly available fundus imaging dataset to explore the effectiveness of deep learning models for glaucoma detection. These datasets provide medical images, …
Published in International Journal of Brain Sciences · Vol. 2, Issue 2, 2025 · pp. 9–18 Read article
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DESIGN AND FABRICATION OF THERMAL INSULATED OVERHEAD WATER TANKS
Abstract: Overhead water containers are essential for storing water in residential and commercial structures, but because of varying weather, they are sometimes subject to extreme temperature swings. During the summer, the average temperature regularly surpasses 50°C. In residential and commercial structures, above water tanks are essential for water garages; but, due to changing climate conditions, they may be subjected to high temperature changes on a regular basis. The tanks are primarily …
Published in International Journal of Energy and Thermal Applications · Vol. 3, Issue 2, 2025 · pp. 32–40 Read article