Search
182 articles for “benchmarks”
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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