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199 articles for “benchmarking”
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Polymer Composite-Integrated Food Waste Management Across the Supply Chain: Quantification, Process Modelling, and Techno-Economic Valorization
Abstract: Food waste produced throughout the global food supply chain constitutes one of the most impactful forms of inefficiency within the current food production system, producing roughly 931 million tons per year and resulting in economic losses above $1 trillion worldwide each year. One aspect that has not been sufficiently studied systematically is how polymer composite materials, such as membrane separation systems, polymer-coated extraction equipment, fiber-reinforced polymer (FRP) biorefinery infrastructure, and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 819–836 Read article
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Automated Machine Learning System for Model Selection and Hyperparameter Optimization
Abstract: The proliferation of machine learning applications in various scientific and industrial domains has given rise to an urgent need for developing principled, automated techniques for optimal architecture selection and hyperparameter tuning for machine learning models without human expert intervention. In this paper, we introduce the Automated Machine Learning System for Model selection and hyperparameter Optimization (AMLSMO)—a state-of-the-art, all-encompassing AutoML system that combines the power of meta-learning-based warm-starting, Bayesian Optimization with …
Published in Recent Trends in Mathematics · Vol. 3, Issue 2, 2026 · pp. 15–23 Read article
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Linux vs FreeBSD: a comparative evaluation
Abstract: Linux and FreeBSD are both favorite, full featured, advanced open-source operating systems. They present many similarities owning mainly to their common UNIX heritage and their monolithic structure. Both systems support dynamically loaded kernel modules that expand their functionality. Also, they provide a similar set of system calls, and their interrupt handling, and virtual memory management systems adopt many common patterns. However, there are also significant differences. In particular Linux tends …
Published in Journal of Operating Systems Development & Trends · Vol. 5, Issue 1, 2018 · pp. 1–10 Read article
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Liquid Fertilizer from Food Waste
Abstract: Food waste primarily includes a smart potential if it's processed into organic liquid plant food rather throws away. the present analysis study deals with conversion of garbage generated from restaurants, wedding halls and hotels into organic liquid plant food through anaerobic method within the Cherlapally Industrial space for up service level benchmarks as thought-about by the Ministry of atmosphere and Forest. The garbage was processed in a very closed instrumentality …
Published in Research & Reviews : Journal of Food Science & Technology · Vol. 8, Issue 1, 2019 · pp. 5–8 Read article
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Agentic AI-Driven Negative Emission Optimization: Large Language Model Orchestration and Quantum Annealing for Real-Time Carbon Capture Policy Simulation Beyond 1.5°C Thresholds
Abstract: The convergence of agentic artificial intelligence, large language model (LLM) orchestration, and quantum annealing presents a transformative paradigm for climate policy computation. This paper introduces Nega Optima a multi-agent computational architecture that integrates LLM-driven policy parsing, quantum annealing-based combinatorial optimization, and real-time integrated assessment model (IAM) feedback loops to simulate negative emission technology (NET) deployment strategies in a post-1.5°C overshoot scenario. Existing carbon capture optimization frameworks suffer from three systemic …
Published in International Journal of Climate Conditions · Vol. 3, Issue 2, 2026 · pp. 7–14 Read article
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An Investigative Study on Cache-Oblivious Data Structures
Abstract: Cache-oblivious data structures and data management systems have emerged as critical components in modern computing environments, aiming to optimize memory access patterns across different levels of the memory hierarchy without explicit knowledge of cache sizes or configurations. This study presents an overview of cache-oblivious techniques, including adaptive data structures, compression, parallel processing, and security considerations. The workexplores future directions in cache-oblivious systems, such as non-volatile memory support, graph processing, edge …
Published in International Journal of Data Structure Studies · Vol. 1, Issue 2, 2023 · pp. 33–37 Read article
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An Automation Detection for Sign Language Using AI
Abstract: Sign language recognition has attracted considerable interest because of its ability to facilitate communication between the deaf community and the public, thereby bridging communication divides. Traditional approaches to sign language recognition often face challenges in accurately interpreting the complex and nuanced gestures inherent in sign languages. However, recent advancements in deep learning techniques have shown promising results in improving the accuracy and robustness of sign language recognition systems. This study …
Published in Recent Trends in Programming languages · Vol. 11, Issue 1, 2024 · pp. 1–14 Read article
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Economic Development: A Challenge with Sustainability
Abstract: The fast pace of Economic Development is the need and expectation of every economy but it must fine tune with sustainability is an urgent need considering the present situation. Developmental matters should be managed in such a way that it can be fruitful for the generation to come. The way we are moving in building infrastructure for the comforts and better living or to put the benchmark with the competitive …
Published in OmniScience: A Multi-disciplinary Journal · Vol. 14, Issue 1, 2024 · pp. 86–90 Read article
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Safety Analysis of High Rise Buildings
Abstract: In the construction sector, safety and accidents are important factors that have a big impact on the well-being of workers, project schedules, and project overall expenses. In addition to being required by law, putting safety first in construction is a wise strategic move with broad ramifications. The comparative safety study of high-rise structures presented in this work focuses on assessing how safety precautions, construction costs, and project schedules interact. The …
Published in Journal of Construction Engineering, Technology & Management · Vol. 14, Issue 1, 2024 · pp. 22–34 Read article
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Review on Local News’s Transition Towards Digital Media
Abstract: The development of a contemporary news web application is centered around delivering a captivating user experience replete with advanced functionalities for consuming news. Tailored for daily newspaper readers, the application offers a seamless blend of reading and auditory experiences, allowing users to listen to news articles. Its dynamic homepage algorithmically curates content based on users' historical searches, presenting them with articles that align with their interests. A real-time comment section …
Published in International Journal of Information Security Engineering · Vol. 2, Issue 1, 2024 · pp. 22–28 Read article
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Hardware Synchronization for Embedded Multi-core Processors
Abstract: The focus is not on whether multi-core systems are becoming prevalent, but on how microcontroller architectures should be designed to comply with stringent field requirements. This paper illustrates the transition from single to multiple cores, ensuring coherence and consistency in shared memory through hardware mechanisms. Hardware barriers are implemented to allow for point-to-point synchronization between processor cores. Practical experiments center on the initial stages of transforming single-core systems into dual-core …
Published in Journal of VLSI Design Tools and Technology · Vol. 14, Issue 1, 2024 · pp. 33–42 Read article
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Automated Plant Disease Detection and Treatment Advisor Using Artificial Intelligence
Abstract: Automated plant disease detection and treatment advisors using artificial intelligence represent a significant advancement in modern agriculture. The identification of plant leaf diseases is essential to maintaining food security and agricultural output. Machine learning models, particularly deep learning algorithms like convolutional neural networks (CNNs), are trained on labeled datasets containing images of healthy and diseased plants. These models learn to classify images into different disease categories with high accuracy. Convolutional …
Published in International Journal of Cheminformatics · Vol. 1, Issue 2, 2023 · pp. 1–7 Read article
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Botnet Beacon: Unveiling Covert Networks with Advanced AI Detection Strategies
Abstract: Securing information technology systems is paramount in today's interconnected world, where the reliability and security of networks and applications are of utmost importance. In this context, the development of a Botnet Detection System (BDS) that harnesses the power of AI classification algorithms becomes a critical endeavor. The primary objective of this work is to construct a comprehensive framework for a BDS that can efficiently gather network data and subject it …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 12, Issue 2, 2024 · pp. 26–32 Read article
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Maintain Attendance Using Image Processing Technique
Abstract: Attendance tracking stands as a pivotal pillar in organizational management, bearing significant implications for operational efficiency, resource allocation, and fostering accountability. Traditional methodologies for attendance maintenance frequently exhibit deficiencies in terms of precision, security, and scalability, thus necessitating the exploration of avant-garde solutions. This research endeavors to introduce a pioneering approach to attendance upkeep, harnessing the prowess of image processing techniques synergized with artificial intelligence (AI) algorithms to surmount prevailing …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 11, Issue 2, 2024 · pp. 29–34 Read article
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Enhancing Profanity Detection in Dravidian Languages: Leveraging Language Models for Optimization and Improvement
Abstract: Detecting and documenting instances of abusive behaviour can significantly improve the quality of virtual environments. Given the vast amount of content published daily on social media, it is impractical for human annotators to manually identify potentially harmful content. Recent algorithmic initiatives, especially on platforms like Twitter, have advanced in abuse detection. However, for Dravidian texts, there remains a need to understand the context better and build robust language models for …
Published in Recent Trends in Programming languages · Vol. 11, Issue 2, 2024 · pp. 17–23 Read article
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Early Autism Diagnosis: Machine Learning Models and Their Effectiveness
Abstract: Diagnosis is of utmost importance for timely intervention and support. However, traditional diagnosis methods, which are based on subjective assessment, are delayed. This project explores the role that machine learning techniques might play in enhancing the accuracy and effectiveness of ASD detection. Several state-of-the-art classification algorithms were benchmarked using a dataset from Kaggle. Logistic Regression, XG Boost, Random Forest, Decision Tree, and Gradient Boosting were taken into consideration. Other performance …
Published in Journal of Instrumentation Technology & Innovations · Vol. 14, Issue 2, 2024 Read article
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A Study on Distribution of Acridoidea (Orthoptera) of Patna District, Bihar (India)
Abstract: A thorough study of species shows that 12 types of grasshoppers fall into 3 families: Acridoidae, Catantopidae, and Pyrgomorphidae. These families have 7, 3, and 2 species, respectively. The survey places with rich plants and different weather conditions – like rainfall, humidity, and temperature. Researchers did an extensive survey. They checked many crops and habitats to gather grasshoppers from various agricultural spots. These insects were observed in their natural habitat. …
Published in Research & Reviews : Journal of Ecology · Vol. 13, Issue 3, 2024 · pp. 1–5 Read article
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Hybrid Approach for Community Detection Using Deep Learning Techniques
Abstract: Community detection in complex networks is a fundamental problem with applications across diverse domains, ranging from social networks to biological systems and beyond. Traditional methods based on graph theory have been widely used for identifying communities within networks. However, the intricate and evolving nature of modern networks demands more sophisticated approaches. This research work proposes a hybrid approach that combines the strengths of deep learning techniques with traditional community detection …
Published in Recent Trends in Electronics Communication Systems · Vol. 11, Issue 3, 2024 · pp. 18–26 Read article
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Energy-efficient Image Classification on Edge Devices: Implementation and Evaluation
Abstract: Image classification is a computer vision problem where an algorithm determines a class or label for a given image. Various real-time applications like object recognition, medical diagnosis, person recognition, etc. Image classification property on edge devices is useful for autonomous vehicles, surveillance, and healthcare and internet of things deployments. The advancement of deep learning based methods and graphics processing units (GPU) devices allows efficient processing locally. The study utilizes a …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 11, Issue 3, 2024 · pp. 10–18 Read article
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Comparative Analysis of Modern Programming Paradigms: Evaluating Language Efficiency and Compiler Design Technique
Abstract: This paper attempts to provide some insights into the efficiency of modern programming paradigms via a comparative study and explore the important role played by compiler design in the optimization of these languages. Programming languages have been evolving quickly over time and different paradigms: imperative, functional, or object-oriented programming come with their idiosyncrasies and optimization techniques. The study starts by defining the foundational principles of each paradigm. It then goes …
Published in Recent Trends in Programming languages · Vol. 11, Issue 3, 2024 · pp. 1–9 Read article