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795 articles for “Data Types”
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Looking into how modern technology combines sensors and Artificial Intelligence
Abstract: The combination of sensors and Artificial Intelligence (AI) is changing modern technology by making it possible to collect, analyse, and make decisions based on data in real time. Sensors are the main link between the real and digital worlds. They collect several types of data, like temperature, motion, pressure, and visual information. When used with AI methods like machine learning and deep learning, this data may be processed in a …
Published in Recent Trends in Sensor Research & Technology · Vol. 13, Issue 1, 2026 · pp. 14–26 Read article
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Real Time Analysis of Twitter Data
Abstract: In last two decades, big data has emerged as one of the most trending fields of research. In today’s world, every minute, huge amount of structured and unstructured data is produced via various platforms. This data includes texts, images, and forums gathered from social media platforms. This increasing data implies a fundamental change in the way we analyze data since it is unable to analyze data using conventional methodologies and …
Published in Current Trends in Information Technology · Vol. 6, Issue 1, 2016 · pp. 6–14 Read article
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Big Data Tools: A Survey
Abstract: AbstractNowadays, a large volume of data is generated in the form of text, voice, video, images, and sound. It is a very challenging job to handle and to get processed these different types of data. It is a very laborious process to analyze big data by using traditional data processing applications. Due to huge scattered file systems, a big data analysis is a difficult task. So, to analyze big data, …
Published in E-Commerce for Future & Trends · Vol. 7, Issue 3, 2020 · pp. 23–34 Read article
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Melody Extraction from Polyphonic Music Using Deep Neural Network: A Literature Survey
Abstract: Abstract: Melody extraction plays an important role in the field of Music Information Retrieval (MIR). It has emerged as one of the active research problems in the MIR applications. Nowadays, the music providers have to facilitate searching of music based on their contents or recommend music based on user’s interest having similar contents. Melody extraction is necessary to fulfil these user-interest driven searching and recommendation. The main objective of melody …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 6, Issue 3, 2019 · pp. 16–21 Read article
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Litterfall Dynamics in different Forest Types of Kumaun Himalaya
Abstract: Litterfall and forest floor data was collected seasonally from 11 different forest types including degraded forests and 3 plantations in Kumaun Himalaya. Litterfall in different forest types varied from 1.25 t/ha for Degraded sal forest to 6.97 t/ha for High altitude oak forest. Among plantations poplar plantation showed highest litter fall (7.24 t ha-1). Most of the forest types were observed with maximum litterfall during summer season. Temperate Conifer forest …
Published in Research & Reviews : Journal of Ecology · Vol. 9, Issue 1, 2020 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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Depression Detection Using Machine Learning: A Comprehensive Review
Abstract: Depression remains one of the most prevalent mental health conditions globally, yet it frequently goes undiagnosed due to the reliance on subjective evaluation methods. With the growing availability of digital behavioral data and significant progress in machine learning (ML), new possibilities have emerged for the automated detection of depression. This review offers a detailed examination of recent advancements in ML-driven approaches to identifying depressive symptoms. It covers a range of …
Published in Journal of Advanced Database Management & Systems · Vol. 12, Issue 3, 2025 · pp. 27–32 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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A Hybrid model of ResNet50 integrated U-Net for image Denoising for Polymer and Composite Microstructure Analysis
Abstract: In digital era a high-quality imaging plays a very important role in polymer and composite material characterization features such as fiber-matrix interfaces, voids, microcracks cause problems in mechanical and functional properties. Polymer imaging includes optical microscopy and scanning electron microscopy, due to sensor limitation, environmental conditions add noise to the image and reduce quality of image. The noise degrades image quality, and it leads to reduce reliability in material analysis. …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 592–602 Read article
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Optimizing Sampling Techniques Using Fuzzy Set Theory: A Comprehensive Approach
Abstract: Sampling is a critical process in statistics, used to estimate population parameters without needing to examine the entire population. Traditional sampling methods, such as simple random sampling, stratified sampling, and cluster sampling, face limitations when applied to complex or heterogeneous populations with imprecise boundaries. These methods often fail to accurately represent populations with overlapping characteristics or missing data, resulting in sampling bias and reduced accuracy. To address these challenges, this …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 12, Issue 1, 2025 · pp. 29–43 Read article
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Soft Sensor for Estimation and Identification of Reduced Dimensional Quality Control Inputs
Abstract: AbstractAdvances in instrumentation technology have equipped us with better process controlling set-ups for error detection and control that occurs in the industrial process plants. This in turn generates a large amount of data that is not always information rich. Additional sensor like a soft sensor can be used to modify the sensor to generate information rich data. Soft sensor are computational models that aid in the continuous or partial estimation …
Published in Journal of Instrumentation Technology & Innovations · Vol. 7, Issue 3, 2017 · pp. 24–29 Read article
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Radial Basis Function Neural Networks for Rainfall-Runoff Modeling
Abstract: Rainfall-runoff process is purely nonlinear and varies spatially as well as temporally. Any hydrological model requires many parameters which represent different components of the process. Availability of all the parameters is difficult for any catchment and probabilistic generation of such type of data is impossible. Under such circumstances, artificial neural networks (ANNs) have proven to be a better tool to model the rainfall-runoff process with minimum available data. The present …
Published in Journal of Water Resource Engineering and Management · Vol. 1, Issue 2, 2014 · pp. 11–18 Read article
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Li-Fi’s Marketplace in the Future
Abstract: In this work, we are describing our project on the Li-Fi system. The full form of Li-Fi is “light fidelity”. It is the forerunner of Wi-Fi. Li-Fi is a type of data transmission technology that will be used in the future because of its causes and benefits. Wi-Fi and Li-Fi are not similar to each other. There are many differences between them in every aspect. In terms of speed, Li-Fi …
Published in Journal of Communication Engineering & Systems · Vol. 12, Issue 3, 2022 · pp. 1–5 Read article
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A Research Paper on Web Application Development Using CMS (Xampp/PHP)
Abstract: It is known that design patterns of object-oriented programming are used in the design of Web applications, but there is no sufficient information that which types of data patterns are used, how frequently they are used, and what the level of quality at which they are used. This research paper discusses the various useful tools and techniques that are used in a development of web applications. In addition we discuss …
Published in Journal of Web Engineering & Technology · Vol. 6, Issue 1, 2019 · pp. 37–43 Read article
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Encryption-Decryption RGB Color Image Using Matrix Multiplication
Abstract: The most commonly used type of data on the Internet are RGB color images. To encrypt the color image the separation is done on the red and blue channels (R, G, B). Each channel is encrypted using a method called random matrix coding. After encryption a new image code is created. The functionality of this application compares with the performance of other techniques and demonstrates the benefits of using this …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 8, Issue 3, 2021 · pp. 30–37 Read article
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Experimental Performance Testing of Separable Reversible Data Hiding Techniques
Abstract: Now a day, for authentication of the image and hiding data within image, different types of separable reversible data hiding techniques are available. In this paper, authors give experimental based performance analysis of separable reversible data hiding techniques based on lossless image compression. Comparative analysis is given on the basis of basic two parameters, that is, quality of image after hiding data within image and time taken by both the …
Published in Current Trends in Information Technology · Vol. 7, Issue 1, 2017 · pp. 15–23 Read article
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Review of Dominance Analysis: An Approach for Determining the Relative Importance of Predictors
Abstract: A lot of methods had been developed to explain the unclear concept of relative importance for independent variables. One of the most important methods for determining the relative importance of predictors is dominance analysis, which is a technique that determines variable importance, based on comparisons of unique variance contributions of all pairs of variables involving all possible subsets of predictors. The aim of this paper is to take a closer …
Published in Research & Reviews : Journal of Statistics · Vol. 9, Issue 3, 2020 · pp. 23–35 Read article
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Exploring Traditional Wedding Ceremony of Majangir
Abstract: This study attempts to explore the traditional wedding ceremonies of Majangir. It tries to give a description and analysis of the traditional wedding ceremony of the Majangir people, called “wawan” by the people themselves. The study attempted to explore and identify the most important cultural elements of the traditional wedding ceremony of the Majangir community and show how it is performed. Moreover, it intends to show the value system of …
Published in OmniScience: A Multi-disciplinary Journal · Vol. 6, Issue 2, 2016 · pp. 16–29 Read article
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Automated Crop Disease Detection Using Convolutional Neural Networks
Abstract: Crop diseases contribute to major losses in agricultural production worldwide generating enormous economic costs. This study investigates the possibility of Convolutional Neural Networks (CNN) imaging techniques to auto-detect diseases associated with plants through image processing. A model was developed and trained on a publicly available plant disease dataset containing labeled images of several diseases. The CNN could classify various plant diseases with accuracy of 95%, precision of 92%, and recall …
Published in International Journal of Cheminformatics · Vol. 3, Issue 2, 2025 · pp. 7–15 Read article
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Efficient Identification of Complex Diseases Through Epistasis Computational Models: A Review
Abstract: AbstractGenome-Wide Association Studies (GWAS) identify and characterize the genes that are associated with human diseases. One of the significant ongoing researches in GWAS is to identify the disease susceptible genes through Epistasis. The gene that masks the effects of other genes is called Epistasis. The gene interacts with another gene is known as epistatic or genetic interactions (GGIs). GWAS identifies the genetic variants of Single Nucleotide Polymorphism and also the …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 7, Issue 2, 2020 · pp. 21–32 Read article