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199 articles for “benchmarking”
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Microplastics Contaminated Mullet (Mugil cephalus) (Linnaeus, 1758) from the Lower Forcados River, Burutu, Delta State, Nigeria
Abstract: The increasing contamination of the environment by microplastics (MP) in various forms is a consequence of modern lifestyle advancements and has emerged as a significant environmental hazard. The digestive tracts of 36 specimens of the economic mullet (Mugil cephalus) were investigated between March 2022 and March 2023 from the lower Forcados River, Burutu, Delta State, Nigeria. A total of 96 MP particles were extracted from 18 fish out of the …
Published in Journal of Water Pollution & Purification Research · Vol. 11, Issue 3, 2024 · pp. 29–37 Read article
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Emerging Trends in Civil Engineering: Sustainability and Digital Transformation
Abstract: Civil engineering has long played a pivotal role in shaping society’s infrastructure, focusing traditionally on construction, design, and the structural integrity of buildings, roads, and bridges. However, recent years have witnessed a profound transformation in the field, driven by the urgent need for sustainable practices and the rapid evolution of technology. This paper provides an in-depth analysis of the latest trends that are redefining civil engineering, with a particular emphasis …
Published in Recent Trends in Civil Engineering & Technology · Vol. 14, Issue 3, 2024 · pp. 8–11 Read article
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Automating Compiler Optimization: A Machine Learning Approach
Abstract: This study reports on an ML-based approach to compiler optimization, complementing traditional optimization methods that rely strongly on hand-tuned settings. Compiler optimization plays a key role in performance-speedup and energy optimization of complex contemporary software systems. However, the traditional approach to optimizer settings involves laborious, error-prone, and scale-insensitive human-in-the-loop intervention, especially in the complex and high-demand environments in which today's computing application thrives. By integrating RL and GA, we can …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 1, 2025 · pp. 12–16 Read article
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Educating Compilers to Learn: Utilizing Machine Learning for More Brilliant Code Optimization
Abstract: This study explores the use of machine learning (ML) approaches to compiler optimization. The now-traditional static compilation techniques are transformed into adaptive, dynamic systems capable of making context-specific advancements. Traditional compilers rely mostly on heuristic or rule-based optimization techniques. While these techniques work well in general cases, they consistently fail to adapt well within the limits of code structures that modern machines display. This limitation is especially acute in today's …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 1, 2025 · pp. 50–54 Read article
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Transforming Human Resources Leveraging AI Across the Associate Lifecycle for Strategic Success
Abstract: AI is taking the lead in changing the game in human resources by mitigating challenges and optimizing processes throughout the entire associate lifecycle. From pre-hire, AI helps with interview bias, enhances hire projections, and supports talent acquisition with predictive analytics. Once onboarded, AI helps with compensation benchmarking, automates performance feedback with the mitigation of bias, and analyzes associate sentiment through NLP and LLMs. In the middle of the life cycle, …
Published in Recent Trends in Programming languages · Vol. 12, Issue 1, 2025 · pp. 30–36 Read article
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Cloud-based Application Development and Optimization
Abstract: As cloud computing powers today’s applications, optimizing cloud-based development is crucial to achieve performance, cost effectiveness, and scalability. This research focuses on enhancing the design, deployment, and maintenance of cloud applications, tackling challenges in resource management, scalability, and resilience. We specifically explore dynamic resource allocation algorithms that use predictive analytics for auto-scaling based on workload variations, aiming to cut costs while preserving high performance. The study also investigates cross-cloud optimization …
Published in Journal of Open Source Developments · Vol. 12, Issue 1, 2025 · pp. 37–42 Read article
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Advancing IoT Security through Blockchain-based Approaches
Abstract: The emergence of blockchain technology has revolutionized various industries, including the Internet of Things (IoT), by providing a decentralized and secure platform for data management and transaction processing. However, securing IoT devices and networks remains a significant challenge due to inherent vulnerabilities and the increasing sophistication of cyberattacks. Blockchain-based security approaches have shown promise in addressing these challenges, yet their adoption is hindered by a lack of comprehensive taxonomy and …
Published in Trends in Electrical Engineering · Vol. 15, Issue 1, 2025 · pp. 1–34 Read article
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Voice Controlled Wheelchair Along with Health Monitoring
Abstract: In recent years, mobility aids like wheelchairs have been essential for enhancing the independence of individuals with physical disabilities. However, traditional wheelchairs, often controlled manually or via joysticks, pose challenges for those with severe impairments. This project introduces a voice-controlled wheelchair integrated with health monitoring capabilities, addressing these limitations. The system features an ESP32 microcontroller that processes voice commands, such as "move forward" or "stop," captured by a microphone and …
Published in Journal of Instrumentation Technology & Innovations · Vol. 15, Issue 1, 2025 · pp. 1–6 Read article
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Sustainable Electromagnetic Culinary Interface with Dual-Phase Filtration for Energy Efficiency and Environmental Impact Reduction
Abstract: Induct Net is an innovative kitchen appliance that seamlessly integrates advanced cooking technology with an inbuilt chimney system, marking a significant step towards sustainable culinary environments. This space-efficient device prioritizes energy efficiency, user safety, and environmental responsibility through its incorporation of internet of things (IoT) technology. Induct Net features a dual-filtration system with removable grease and charcoal filters, ensuring optimal performance while reducing waste. The IoT connectivity facilitates real-time monitoring, …
Published in International Journal of Electrical Machine Analysis and Design · Vol. 3, Issue 1, 2025 · pp. 45–50 Read article
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Under-Nutrition Among Rural Women of Eastern Uttar Pradesh, India: Results from a Survey
Abstract: The present article shows some light on various nutritional aspects of a rural society in eastern Uttar Pradesh, India. The findings are based on a sample survey conducted in 2003-04 by Centre of Population Studies, Department of Statistics, Banaras Hindu University, Varanasi, Uttar Pradesh, India in which data were collected from 1800 households of the study area. Various nutritional aspects include anthropometric measurements, consumption of various foods in a day, …
Published in Research and Reviews: A Journal of Health Professions · Vol. 15, Issue 1, 2025 · pp. 22–45 Read article
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CredBud: The Ultimate Student Platform
Abstract: In the rapidly evolving educational landscape, effective management of student performance, attendance, and engagement is essential for fostering accountability, motivation, and academic growth. Addressing the limitations of traditional methods, CredBud introduces an innovative digital platform designed to revolutionize academic management. This secure, user-friendly ecosystem empowers both students and faculty to enhance efficiency and collaboration. CredBud’s key features include a credit allocation and grading system to monitor academic progress, a theoretical …
Published in Journal of Microcontroller Engineering and Applications · Vol. 12, Issue 2, 2025 · pp. 1–9 Read article
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MIRDcalc & OLINDA/EXM Dosimetry Software Analysis by SPECT/CT Scan Data of Lu-177 DOTATATE Radionuclide Therapy of NET Patients
Abstract: Accurate dosimetry is essential in nuclear medicine for optimizing radionuclide therapies and ensuring patient safety. In Radiopharmaceutical dosimetry the Medical Internal Radiation Dosimetry (MIRD)Society is the pioneer in organ-level dosimetry providing the fundamental basis for commonly used clinical and research dosimetry software like MIRDOSE and OLINDA/EXM. Recently, in MIRD Pamphlet No. 28, Part 1, the MIRD committee of the Society of Nuclear Medicine and Medical Imaging presented a new Software …
Published in Journal of Nuclear Engineering & Technology · Vol. 15, Issue 2, 2025 · pp. 48–63 Read article
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Enhancing MRO Documentation Through Automated Translation of Non-Standard English to Simplified Technical English Using Offline LLMS
Abstract: Maintenance, Repair, and Overhaul (MRO) operations rely heavily on accurate and consistent documentation to ensure operational safety and compliance. However, the presence of non-standard English in technical documents often leads to ambiguity, misinterpretation, and inefficiencies in maintenance processes. This study presents an innovative solution that leverages an offline Large Language Model (LLM) to automatically translate non-standard English in MRO documents into standardized and technically precise language. By integrating predefined linguistic …
Published in Journal of Aerospace Engineering & Technology · Vol. 15, Issue 2, 2025 · pp. 9–15 Read article
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A Review of Blocking Side-Channel Threats in Parallel Cloud Systems
Abstract: Side-channel attacks (SCAs) pose a critical security threat to parallel computing systems, particularly in shared cloud environments where multi-tenancy and resource contention create exploitable vulnerabilities. This study presents a comprehensive review of SCAs in parallel architectures, analyzing attack vectors such as cache-based exploits (e.g., Prime + Probe, Flush + Reload), timing attacks, power analysis, and network-based covert channels. We examine real-world cases including Spectre and Meltdown vulnerabilities that exposed fundamental …
Published in Recent Trends in Parallel Computing · Vol. 12, Issue 2, 2025 · pp. 15–25 Read article
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Innovative Approaches to Reactive Power Management and Optimization in Modern Power systems
Abstract: Reactive power management and optimization are necessary for the effective, stable, and reliable working of modern power systems. Without proper management, reactive power is responsible for additional losses in transmission, reduced capability of power transfer, and poor voltage stability conditions, thus forming a basis for developing advanced techniques of optimization. This paper discusses the innovative methods in Reactive Power Optimization (RPO) using met heuristic algorithms, namely the Self-Balanced Differential Evolution …
Published in Journal of Power Electronics and Power Systems · Vol. 15, Issue 3, 2025 · pp. 44–50 Read article
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Building Scalable Microservices with Micronaut, Kotlin, and AWS DynamoDB: A Comprehensive Architecture Study
Abstract: The evolution of enterprise software has trended steadily toward microservice architectures due to their inherent scalability and resilience advantages over monolithic systems. This research explores a comprehensive implementation approach using Micronaut, an innovative JVM-based framework specifically designed for resource-efficient microservices. The study combines Micronaut with Kotlin programming language and leverages AWS DynamoDB as a scalable NoSQL persistence layer, with Apache Kafka providing event-driven communication capabilities. We explore the critical role …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 12, Issue 2, 2025 · pp. 40–57 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
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Enhancing Customer Engagement with AI-Driven Movie Recommenders: Integrating Neural Collaborative Filtering, Sentiment Analysis, and Conversational Agents
Abstract: In today’s competitive digital landscape, user engagement is a critical factor for the success of entertainment platforms, especially those offering movie recommendations. This study introduces a comprehensive AI-driven framework designed to enhance customer interaction, satisfaction, and loyalty through the intelligent integration of multiple deep learning models. The system combines three core components: Neural Collaborative Filtering (NCF) for generating personalized movie recommendations based on user behavior and preferences, Long Short-Term Memory …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 3, 2025 · pp. 45–54 Read article
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Accelerating Unsupervised Feature Learning: Parallelized Training of Denoising Autoencoders
Abstract: Unsupervised representation learning has become a cornerstone of contemporary machine learning, enabling algorithms to extract informative features from un-labelled, high-dimensional data. This work investigates the efficacy of stacked denoising autoencoders (SDAEs) trained via parallelized stochastic gradient descent (SGD) as a scalable approach to feature extraction. By strategically leveraging multi-threaded computation, our study systematically examines the trade-offs between increased parallelism, training efficiency, and the preservation of model accuracy. Experiments on the …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 3, 2025 · pp. 56–64 Read article
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Ai-Driven Healthcare System for Enhanced Diagnosis and Patient Interaction
Abstract: Deep learning techniques are used in an AI-driven healthcare system to improve disease identification and medical picture analysis. Data collection, preprocessing, model training, and evaluation are all part of the system's systematic workflow. Various deep learning architectures, such as ResNet50, VGG-16, and U-Net, are employed for precise classification and segmentation of medical images. The approach incorporates advanced techniques such as optimization, transfer learning, and data augmentation to significantly enhance the …
Published in Research and Reviews: A Journal of Health Professions · Vol. 15, Issue 2, 2025 Read article