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567 articles for “Training”
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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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Infection Control awareness among Nursing students: Descriptive Insights from Ongoing Clinical Orientations in Odisha
Abstract: Background: Effective infection control practices are critical in preventing healthcare-associated infections (HAIs). Aim: This study aimed to assess the awareness regarding effective infection control measures among student nurses undertaking their initial clinical orientations at Hospitals. Method: The study accepted 64 respondents from II-year BSc Nursing, sampled in clusters from selected Hospitals, Odisha. Results: The students yielded a mean awareness score of 0.69, categorized as Good. A comparison revealed that female …
Published in International Journal of Evidence Based Nursing And Practices · Vol. 3, Issue 2, 2025 · pp. 15–20 Read article
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Joint Estimation of CSI and IQ Imbalance, and Compensation of IQ Imbalance in Spatialy Multiplexed MIMO-OFDM Receivers
Abstract: This study presents a novel method for estimating Channel State Information (CSI) and IQ imbalance and compensating IQ imbalance in a spatially multiplexed MIMO OFDM receiver. Our approach integrates estimation of IQ imbalance with CSI estimation using an OFDM training frame, thus eliminating the need for additional pilot symbols for IQ imbalance estimation. This technique streamlines the process and avoids extra overhead. We conducted simulations on a 2×2 spatially multiplexed …
Published in Journal of Microwave Engineering and Technologies · Vol. 12, Issue 2, 2025 · pp. 11–17 Read article
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Smart Agriculture in India: Advancements in Image Processing for Automated Plant Disease Detection and Crop Analysis
Abstract: The adoption of image processing technologies in agriculture is emerging as a revolutionary method for tackling persistent challenges in the farming industry. These techniques are increasingly used for different tasks such as detecting plant diseases, assessing crop health, and predicting yields, especially in the framework of smart agriculture systems. This study paints a detailed picture of the latest progress in image processing techniques applied to automated disease detection and detailed …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 3, 2025 · pp. 13–19 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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The Effect of Attachment Styles on Emotional Regulation Impacting Relationship Satisfaction: An Exploratory Case Study Design
Abstract: This study explores the impact of early attachment experiences, emotional regulation, and relationship dynamics among six participants through a qualitative case study approach. Using thematic and narrative analyses, the research identifies key patterns in emotional suppression, fear of abandonment, trust issues, and self-awareness. Participants' narratives reveal how childhood experiences with caregivers influenced their emotional regulation strategies and attachment styles in adulthood. Findings indicate that those with secure emotional upbringings exhibited …
Published in International Journal of Behavioral Sciences · Vol. 2, Issue 2, 2025 · pp. 1–17 Read article
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Communication Pathways and Project Success: Analyzing Stakeholder Coordination Impacts on Construction Outcomes
Abstract: It is very critical to have effective communication and coordination among stakeholders for the successful delivery of the projects. Effective communication keeps stakeholders well-informed about project progress, promoting transparency, trust, and collaboration. Coordination ensures that responsibilities and resources are efficiently allocated, reducing the risk of misunderstandings and enhancing decision-making processes. Inadequate stakeholder engagement can lead to confusion, delays, rework, and the failure to meet key project milestones. The impact of …
Published in Journal of Construction Engineering, Technology & Management · Vol. 15, Issue 3, 2025 · pp. 104–126 Read article
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Utilization of 3D Printing Techniques in the Prosthetics Manufacturing: Historical, Current, and Future
Abstract: Prosthetics for people with upper-limb differences have an intriguing and extensive history, yet problems that have not been resolved still exist. Children's prosthesis requirements are more complicated because of their rapid growing. A child's psychological development can be significantly impacted by their access to a technology. Children frequently cannot access technologies that support both cosmetic form and user function because of their high cost, insurance policies, medical availability, perceived durability, …
Published in Journal of Nanoscience, NanoEngineering & Applications · Vol. 15, Issue 3, 2025 · pp. 15–26 Read article
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Machine Learning Approach to Predict the Performability and Emissions of Diesel Engine Fueled with Doped Biodiesel Blend
Abstract: Enhancing the performability and emission characteristics of diesel engines has been a difficult task in light of growing concerns about global warming and other negative effects, as diesel accounts for 70% of global energy demand. In this study, engine performance and exhaust emissions for various fuel blends were thoroughly evaluated using machine learning techniques to predict engine emission and performance behavior. We focused on biodiesel blend and nanoparticle additive concentration …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 3, Issue 1, 2025 · pp. 1–12 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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AI and ML in the Chemical Industry: A Review of Transformative Applications and Future Prospects
Abstract: The chemical industry, a key growth indicator of the global manufacturing ecosystem, is experiencing a digital transformation driven mainly by advancements in Artificial Intelligence (AI) and Machine Learning (ML) in this sector. These technologies are totally revolutionizing current and traditional methodologies by significantly improving process efficiency, reducing costs of manufacturing, accelerating R&D, and improving safety and sustainability standards. Proper utilization of Artificial intelligence (AI) and machine learning (ML) in chemical …
Published in International Journal of Cheminformatics · Vol. 3, Issue 2, 2025 · pp. 1–6 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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Brain Tumor Detection by Aggregating Deep Learning and GAN Models for Faster MRI image Synthesis
Abstract: Brain tumors comprise a global health challenge that, in order to be treated and organized, need early and accurate diagnosis. Usually conducted through medical imaging, brain tumor detection techniques have problems of accuracy, efficiency, and confidentiality. Issues of limited datasets, strict privacy laws that provide restrictions on data sharing, and the necessity for specialized expertise on medical image analysis relegates modern methodologies to vulgar charades. For patient prognosis, treatment planning, …
Published in International Journal of Brain Sciences · Vol. 2, Issue 2, 2025 · pp. 45–53 Read article
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The Impact of Quran Memorisation on Wellbeing: Lived Experiences of Bohra Huffaz
Abstract: The Quran, revealed over 1400 years ago, remains central to Muslims' daily lives, particularly through recitation during prayers. Quran memorisation (QM), known as Hifz, is a centuries-old tradition requiring intense cognitive engagement, discipline, and spiritual dedication. While many studies explore the psychological benefits of spiritual practices, few have examined the profound impact of full Quran memorisation on personal well-being. This study examines how Quran memorisation influences psychological well-being, particularly among …
Published in International Journal of Trends in Humanities · Vol. 2, Issue 2, 2025 · pp. 1–13 Read article
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The Influence of Self-Efficacy on Anxiety and Perfectionism among Dancers
Abstract: The world of dance, while driven by creativity, often imposes significant psychological demands on performers. This study explored how self-efficacy influences anxiety and perfectionism—both adaptive (excellencism) and maladaptive—among dancers, with a focus on gender differences. A sample of 120 dancers (60 males, 60 females) was assessed using standardized scales. Relationships and predictive effects were assessed using statistical techniques, such as regression, Pearson correlation, and t-tests. Findings revealed no significant gender …
Published in International Journal of Behavioral Sciences · Vol. 2, Issue 2, 2025 Read article
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Mind-Machine Synergy: The Evolution and Future of Brain-Computer Interfaces
Abstract: Brain-Computer Interfaces (BCIs) represent a transformative technology that enables the direct communication between the human brain and external devices, bypassing the traditional output mechanisms, such as speech or physical movement. BCIs hold the potential to revolutionize fields, such as healthcare, neuroscience, and human-computer interaction by providing new ways to restore lost functions, enhance cognitive abilities, enable seamless communication, and create novel user experiences across various platforms and environments. This article …
Published in International Journal of Brain Sciences · Vol. 2, Issue 2, 2025 · pp. 19–31 Read article
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Machine Learning-Assisted Design and Optimization of Lightweight Polymer Composites for IoT-Enabled Automotive Applications
Abstract: This study aims to develop an integrated machine learning and optimization framework for the intelligent design of lightweight polymer composites suited for IoT-enabled automotive applications. The goal is to enhance material performance while satisfying multiple design constraints such as mechanical strength, thermal stability, and process compatibility. A curated dataset of polymer composite formulations was used to train a Random Forest Regression (RFR) model capable of predicting tensile strength, thermal conductivity, …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 12–27 Read article
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Analyzing the Role of Fiber Composition in Drying Behavior: A Comparative and Predictive Approach
Abstract: This research presents a comprehensive analysis of the drying behavior and thermal response of three distinct fabric types: 100% Cotton, 100% Polyester, and a Polyester blend (65/35), under meticulously controlled environmental conditions. The Polyester blend (65/35) consists of 65% Polyester and 35% Cotton, combining characteristics of both fibers. The investigation focuses on understanding how fiber composition impacts drying time, moisture retention, and thermal characteristics. Experimental trials were conducted using standardized …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 1–11 Read article
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Plant Disease Detection Using Machine Learning
Abstract: Plant diseases significantly threaten global crop yields and affect both nutritional safety and farmer income. Accurate and early detection of plant diseases is essential for effective intervention and treatment. In this study, we used the CNN model (convolutional neural network) to explore a deep learning-based approach for plant disease classification. The model was trained and evaluated on a large dataset encompassing 38 different classes of plant disease, including healthy leaves. …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 12, Issue 2, 2025 · pp. 07–19 Read article
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Randomized Latent Vectors for Enhanced Reinforcement Learning Exploration
Abstract: This paper investigates Random Latent Exploration (RLE), a novel reinforcement learning technique that enhances exploration using randomized latent vector conditioning. I evaluate RLE’s performance across various environments, including discrete control tasks (FourRoom), continuous control (IsaacLab), and complex visual domains (Atari games). The core approach augments traditional reward functions with intrinsic rewards, calculated as the dot product between state features and periodically resampled latent vectors. The policy and value networks are …
Published in Current Trends in Signal Processing · Vol. 15, Issue 3, 2025 · pp. 19–25 Read article