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1688 articles for “accuracy”
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AI Driven IoT Based Decision Making System for Brain wave study: KSK approach for Brain wave study
Abstract: The rapid convergence of Internet of Things (IoT) architectures and deep learning has unlocked unprecedented potential for real-time neuro-diagnostic monitoring. This paper presents a novel framework for an AI-driven IoT ecosystem designed to capture, transmit, and interpret human electroencephalography (EEG) signals with minimal latency. Traditional brain-computer interface (BCI) studies are often constrained by localized computing power and the high dimensionality of neural data. Our proposed architecture integrates low-power EEG sensors …
Published in International Journal of Brain Sciences · Vol. 3, Issue 2, 2026 Read article
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Parametric Study of Cylindrical Grinding Machine: Review
Abstract: Manufacturing industry has undergone various changes to meet the requirement of customers and to manufacture the components with accuracy and within time limit. For that, study of different parameters that directly or indirectly affect the manufacturing process need to be studied. This paper is review to study the different parameters of cylindrical grinding machine which affect the final outcome (surface roughness and material removal rate) of the component.
Published in Journal of Materials & Metallurgical Engineering · Vol. 5, Issue 3, 2015 · pp. 36–40 Read article
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A Review on Metal Additive Manufacturing Techniques and its Applications
Abstract: Additive manufacturing is a manufacturing technique that focusses on producing the parts from the computer aided engineering drawings obtained from detailed modelling. The advances in additive manufacturing has led to the development of essential technological innovations with state of the art research prospectus which facilitates the development of parts that are complex to manufacture using other manufacturing technologies. The current paper aims to provide a review of the process characteristics …
Published in Journal of Polymer & Composites · Vol. 7, Issue 3, 2019 · pp. 24–31 Read article
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Benchmarking Cost Overruns in Transportation Infrastructure Investments
Abstract: Highway projects have historically experienced significant cost overruns, with front end implications for the sustainability of transportation investments. However, the criteria for assessing cost overruns continues to elicit diverse opinions and has become a debatable issue in the literature. Some studies allude to detailed design stage estimates, while others tag conceptual stage estimates, as the ideal benchmark for quantifying the project cost deviations. A survey of the literature, principally from …
Published in Trends in Transport Engineering and Applications · Vol. 7, Issue 2, 2020 · pp. 29–37 Read article
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Utilizing Machine Learning to Combat Plant Disease
Abstract: Plant diseases are a significant source of lost income and time for the agricultural industry. Accurately diagnosing an illness requires a high level of experience and dedication. Symptoms of plant diseases, such as spots or streaks of a different colour, are sometimes visible on the leaves of infected plants. Many fungal, bacterial, and viral organisms may also cause illness in plants. The indications and symptoms of a plant disease are …
Published in Journal of Computer Technology & Applications · Vol. 14, Issue 2, 2023 · pp. 20–28 Read article
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Behavioral and Electrophysiological Correlates of Semantic Processing in Kannada
Abstract: Semantics is one of the fundamentals of language components, encoding of which helps in understanding the meaning of the spoken or written language. The processing pattern of semantics has been studied extensively in different languages using either the conventional psycholinguistic experiments or advanced neuroimaging techniques. Previous studies have documented the behavioral and electrophysiological correlates of semantic processing in different languages. However, the correlation between these measures has not been well …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 9, Issue 2, 2019 · pp. 1–9 Read article
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Heart Disease Prediction Using ANN Based Ensemble Framework (ANNEF) Approach
Abstract: The heart is the most important organ in the human body. One of the deadliest illnesses, heart disease is to blame for countless deaths worldwide. Because of the formation of fatty plaques in arteries, the heart fails to supply enough blood to other body areas to carry out its usual functions in heart disease (atherosclerosis). Age, a sedentary lifestyle, a family history of heart disease, stress, and other factors are …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 9, Issue 3, 2022 · pp. 38–45 Read article
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A Comparative Study on Various Machine Learning Techniques for the Prediction of Cardiac Ailment
Abstract: Over the last couple of decades, cardiovascular complexities have become the leading source of death in impoverished regions. With heart attack rates on the acceleration at a youthful age, it is necessary to put in place a process to recognize the symptoms of a heart attack early and thus limit it. It is impossible for a common man to often undergo expensive tests such as an ECG and thus there …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 10, Issue 3, 2023 · pp. 25–30 Read article
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Complementary Approach of SVM for Heart Disease Prediction
Abstract: To the point, Coronary-Heart-Disease is in records of killing huge number of lives every year. India contributes to 32% of deaths among all countries. In terms of data, 85% of them resulted from either heart attacks or strokes. In other terms, ⅘ people are risked to heart strokes. Over 75% of CHD deaths occur in low- and middle-income countries, where high blood pressure is one of the most important risk …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 10, Issue 3, 2023 · pp. 38–44 Read article
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Music Recommendation System Using Big Data and Machine Learning
Abstract: In comparison to earlier times, there is now a wealth of music available thanks to the development of music streaming services that can be used from mobile devices. Classifying digital music can be timeconsuming and cause fatigue. Obtaining one’s favorite music from the huge music selection has become a problem. The creation of a music recommendation system that can search through music libraries and make song recommendations to users based …
Published in Journal of Open Source Developments · Vol. 9, Issue 3, 2022 · pp. 18–24 Read article
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A Review on Software Simulation of Mechanical Structures Using FEA
Abstract: In this paper author aims to study the various researches based on simulation using various FEA software to design and analyze mechanical structures, which can be helpful to identify the suitability of particular software for its specific application, and to evaluate the best suitable methodology used by software for design and analysis of complex geometry. This study is helpful to reduce a computation requirements and improves accuracy in result.Cite this …
Published in Trends in Mechanical Engineering & Technology · Vol. 5, Issue 3, 2015 · pp. 1–7 Read article
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“Experimental Analysis of Smart Solar Grass Cutter”
Abstract: Abstract:-In the experimental investigation of a smart photovoltaic grass cutter, a self-driving mowingpowered by sunlight from solar cells makes use of cutting-edge gadgets like GPS, sensors, and artificialintelligence. The device is intended to remove grass effectively while using a smaller amount of electricityand emitting less pollutants than conventional gasoline-fueled clippers. The experiment involves testing theefficiency of the solar panel in charging the battery of the grass cutter as well as …
Published in Journal of Refrigeration, Air conditioning, Heating and ventilation · Vol. 10, Issue 1, 2023 · pp. 1–6 Read article
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Landscape Classification of Sariska National Park (India) and its Environments using Geospatial Technology
Abstract: The relationship between land use/land cover (LULC) changes and land degradation over a period of 20 years (1989–2009) at Sariska National Park (India), and its environment was investigated using remotely sensed and ancillary data. The study analyzed the magnitude and direction of temporal LULC changes for two consecutive periods; 1989–2009. The temporal change patterns of LULC were analyzed through interpretation of LANDSAT imagery. Final land cover maps produced under four …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 7, Issue 1, 2018 · pp. 5–14 Read article
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Data Mining Methods for Large Data
Abstract: High dimensional data classification becomes a challenging task because data are large, complex to handle, heterogeneous and hierarchical. In order to reduce the data set without affecting the classifier accuracy, the feature selection plays a vital role in large datasets and which increases the efficiency of classification to choose the important features for high dimensional classification, when those features are irrelevant or correlated. Therefore feature selection is considered to be …
Published in Research & Reviews : Journal of Statistics · Vol. 7, Issue 1, 2018 · pp. 30s–35s Read article
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AI-Driven IoT-Based Decision-Making System for Brainwave Study: The KSK Approach
Abstract: The rapid convergence of Internet of Things (IoT) architectures and deep learning has unlocked unprecedented potential for real-time neuro-diagnostic monitoring. This paper presents a novel framework for an AI-driven IoT ecosystem designed to capture, transmit, and interpret human electroencephalography (EEG) signals with minimal latency. Traditional brain–computer interface (BCI) studies are often constrained by localized computing power and the high dimensionality of neural data. Our proposed architecture integrates low-power EEG sensors …
Published in International Journal of Brain Sciences · Vol. 3, Issue 2, 2026 · pp. 28–35 Read article
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Evaluation of Machine Learning Classifiers for Sentiment Analysis
Abstract: Sentiment in social media refers to users’ emotions and opinions through their posts and interactions. Sentiment analysis (SA) refers to relating and classifying the sentiments expressed as engagement and interactions between users. When analyzed, tweets frequently produce a large source of clustered data. These data help determine people’s opinions about a variety of motifs. Thus, this study presents an Automated Machine Learning (ML) Sentiment Analysis Model to detect media sentiment. …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 2, 2024 · pp. 141–154 Read article
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Innovative Approaches for Exploring Software Testing Techniques for Electrical Equipments
Abstract: Software testing is critical to assuring the success and reliability of a software product or service, yet it is frequently regarded as uninteresting work when compared to design or development. Human factors influence the final software product's outcome, just like in any human-based activity. For software development companies, this means that finding practical ways to boost testers' motivation and job happiness is a major challenge. Our research focuses on how …
Published in International Journal of Electrical Machine Analysis and Design · Vol. 1, Issue 2, 2023 · pp. 1–7 Read article
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Transfer Learning in Deep Learning Models for Medical Imaging: Utilizing Pretrained Models to Improve Performance in Medical Image Analysis
Abstract: Transfer learning is now a trending technique in deep learning, especially in medical imaging. This technique solves landmark problems by utilizing the pre-trained models, including the limited availability of the annotated medical data and the time-consuming computational costs of training deep learning models from scratch. The generalizability of deep models could increase diagnostic precision for specific medical tasks, require fewer samples to train, and take less time to train due …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 1, 2025 · pp. 67–85 Read article
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GreenDiagnosis: Intelligent Crop Disease Detection Using Deep Learning Algorithm
Abstract: Agriculture in parts of India relies on labour-intensive traditions, maintaining disease-free crops is crucial. Manual methods can be inaccurate, driving farmers towards AI-based solutions. AI offers a proactive approach to address real-time farming challenges. Among these is the invasion of pests, which diminishes crop quality. Combating pest-related diseases poses a challenge, prompting innovation. Effective surveillance and early detection of crop diseases play a pivotal role in ensuring global food security …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 2, 2025 · pp. 8–18 Read article
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Algorithm for the prediction of cardiovascular disease (CVD)
Abstract: cardiovascular diseases (CVD) still claim a significant number of deaths globally and remain the number one killer with an annual death toll of nearly 17.9 million. While several medical advancements have been made, an early diagnosis is still hard to obtain, which often leads to worsening conditions and intricate treatment options. With the advancement of modern technology, Machine learning has demonstrated to be a miraculous tool which can greatly impact …
Published in Research and Reviews : A Journal of Immunology · Vol. 15, Issue 2, 2025 Read article