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22 articles for “vector map”
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Common Fixed-Point Results for Weakly Increasing Dominating Maps on Vector b-Metric Spaces
Abstract: AbstractIn this paper, we consider E-b-metric space, which is a generalized vector metric space. This is a Riesz space valued metric space. Here, we prove some results concerning common fixed point for four mappings on E-b-metric space. This generalizes the results of Rahimi, Abbas and Rad [16]. Keywords: Dominating map, E-b-metric space, Weak annihilators, Weakly compatible, Weakly increasing Cite this ArticleMamta Kamra, Kumari Sarita, Renu Chugh. Common Fixed-Point Results for …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 6, Issue 2, 2019 · pp. 7–23 Read article
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A GIS Based Tool to Digitize Polygon and Line Segments of a Black and White Map
Abstract: In this paper a GIS based tool has been proposed to digitize polygon and line objects throughefficient usage of RGB values of the segments of raster maps. For digitization of polygon,initially a closed loop is drawn inside the polygon segment. Beginning from the initial point ofthe closed loop, eight connected pixels calculation is incorporated to obtain the pointsexisting in between the loop and the actual boundary. The points which exist …
Published in Journal of Remote Sensing & GIS · Vol. 7, Issue 1, 2016 · pp. 27–41 Read article
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An Overview on Microwave Remote Sensing for Earth Observation
Abstract: To understand the Earth from space, one must look beyond the visible eye. While optical satellites rely on the Sun’s reflection much like the human eye they are frequently blinded by the curtain of cloud cover, smoke, or the dark veil of night. To bypass these limitations, we turn to Microwave Satellite Sensing. By utilizing electromagnetic waves with wavelengths ranging from 1 millimeter to 1 meter, we can see through …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 15, Issue 1, 2026 · pp. 21–25 Read article
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DESIGN PERSONALIZATION CLASSIFICATION MODEL USING SEMI-SUPERVISED SUPPORT VECTOR MACHINES
Abstract: Abstract Internet user is growing everyday as an outcome of this huge volume of data is being produced constantly. Thus Mining and evaluating such data can support an organization in services extending from website personalization and usage classification. The pre-existing machine learning algorithms are unable to solve this in a better way. The current application for data classification is really expensive in nature. Improve the recommendation technique using map reduce …
Published in Journal of Web Engineering & Technology · Vol. 5, Issue 1, 2018 · pp. 17–24 Read article
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PAPR Reduction using Selective Mapping Method for OFDM Communication Systems
Abstract: AbstractSelective mapping method (SLM) is one of the most important techniques used for peak-to-average power ratio (PAPR) reduction of orthogonal frequency division multiplexing (OFDM) communication system. It is simple in implementation, gives distortionless transmission and reduces PAPR significantly. Mathematical modelling and Matlab simulation have been carried out to analyse its performances. At of CCDF, PAPR values for OFDM signal without applying any reduction technique is 11.5, 11.8, 12.1, 12.4 and …
Published in Journal of Communication Engineering & Systems · Vol. 5, Issue 3, 2015 · pp. 50–57 Read article
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Molecular Cloning, Expression, Purification, and Characterization of Methionine Aminopeptidase
Abstract: MAP enzyme can efficiently remove N-terminal methionine from recombinant proteins. In the present study, MAP gene from genomic DNA of Escherichia coli was amplified, cloned into pET 11b vector and transformed into E.coli DH5a cloning strain to confirm the insertion of MAP gene, then plasmid was transformed into E. coli BL21 (DE3) expression strain. The protein was eluted with 25 mM NaCl and showed a purity of ~ 95% which …
Published in Research and Reviews: A Journal of Microbiology and Virology · Vol. 2, Issue 2, 2012 Read article
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Offline Handwritten Sanskrit Character Recognition System
Abstract: Despite technological improvements, computers still lag behind in language recognition. The majority of character recognition systems are incapable of reading cracked documents or handwritten characters or words. Sanskrit, an alphabetic script, is spoken by more than 100 million people worldwide. This study is about converting scanned handwriting images into text. This contains the steps below. The scanned image is initially segmented using a spatial space detection approach, after which the …
Published in Recent Trends in Sensor Research & Technology · Vol. 9, Issue 1, 2022 · pp. 32–37 Read article
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Geo AI-Powered Urban Footprints
Abstract: In the contemporary era, building footprints are of paramount importance for accurate and current inventories in the development of infrastructure and geospatial analysis. Traditional methods, relying on manual digitization, were largely unsustainable as the urban regions were growing rapidly. Manual digitization was expensive and lacked geometric precision. This paper introduces an automated, end-to-end GEO AI-powered framework for high-end fidelity building footprint extraction from Google Satellite Data. Our approach for this …
Published in Journal of Remote Sensing & GIS · Vol. 17, Issue 2, 2026 Read article
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Comparing Algorithm Performance in Machine Learning for Landslide Susceptibility Studies: An Overview
Abstract: Machine learning algorithms have gained popularity over the past years, and with this comes the rise in their efficiencies; this study demonstrated that machine learning algorithms could successfully be used to identify landslide susceptibility areas. Machine learning algorithms like decision trees, support vector machines, K-Means, Hierarchical Clustering, Self-Organizing Maps (SOMs), artificial neural networks, and Bayesian networks have been used in recent studies. This study thus reviews several studies and results …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 10, Issue 1, 2023 · pp. 71–89 Read article
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Electric Vehicle Range Prediction
Abstract: The introduction of new energy vehicles has emerged as a new trend in the automotive industry inresponse to growing energy and environmental issues. The electric vehicle (EV) is the driving force behind newenergy vehicles. The one major problem electric vehicles have always been the distance(range) of the travel and mapto the nearby charging stations. For range prediction in the present study, four machine learningalgorithms—multiple linear regression, random forest regression, polynomial …
Published in Trends in Electrical Engineering · Vol. 13, Issue 3, 2023 · pp. 24–32 Read article
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Predicting Dielectric Constants of Polymers Using Molecular Structural Descriptors and Explainable Machine Learning: A Data-Driven Approach
Abstract: Accurate prediction of dielectric constants in polymeric materials is fundamental to the rational design of advanced electronic components, energy storage capacitors, flexible substrates, and high-frequency communication circuits. Conventional approaches to identifying suitable polymer dielectrics rely on extensive experimental synthesis and characterisation, which are both time-consuming and resource-intensive. In this work, an explainable machine learning framework is developed to predict the dielectric constant of polymers directly from molecular structural descriptors derived …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 297–304 Read article
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Avalanche Hazard Mapping along Manali-patsio Road Axis (Himachal Pradesh, India) Using Advanced Geo-Informatics Techniques
Abstract: Avalanche occurrence is quite a hazardous and unpredictable natural phenomenon. A large number of factors that are associated with its occurrence make it quite difficult to assess hazard in hilly areas. There are two main groups of variables that define the avalanche hazard – meteorological conditions and terrain characteristics. Due to the stable nature along the time, terrain parameters are easier to map. The purpose of this work is to …
Published in Journal of Remote Sensing & GIS · Vol. 3, Issue 1, 2012 Read article
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Extraction of Road from Satellite Images Using Morphology and Active Contours
Abstract: AbstractRoad extraction from a satellite image plays a vital role in traffic management, urban planning and GPS navigation after updating maps. Many methods are available for road extraction, which include mathematical morphology, LEGION networks, road vectors, level set and mean shift, etc. A novel method is presented in this paper which uses mathematical morphology, filtering and active contours for extraction of selected part of road. The proposed algorithm is tested …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 6, Issue 1, 2019 · pp. 1–7 Read article
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Web Mapping Comparison of Open Layers Map and Google Map: A Web GIS based Big Spatial Data Approach
Abstract: Big data sharing and manipulation of geospatial data such a GIS web-based system has become a challenge. Due to the rapid development technology in web based geographical information systems, the uses of web based geospatial application, effective utilization and representation varies from Geo-spatial capabilities and functionalities. In this paper, a web GIS framework was explored to provide a practical solution for the display and manipulations of geospatial data, visualization of …
Published in Journal of Geotechnical Engineering · Vol. 2, Issue 3, 2015 · pp. 41–45 Read article
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Predictive Modeling of Polymer Composites for Medical Implants Using Artificial Intelligence Techniques
Abstract: The use of polymers in biomaterials was now key to designing the next generation of medical implants, which need to be strong and also compatible with living tissue. Tests for biocompatibility, such as those done in the laboratory and by doing experiments on animals, require much time and many resources, so the need for computer-based approaches becomes clear. An artificial intelligence approach was provided in this study to determine how …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 665–692 Read article
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Machine Learning-Based Quantification of Polymer Structure Property Relationships for Predictive Material Design
Abstract: Polymer structures exhibit complex, hierarchical arrangements that strongly influence macroscopic properties, yet consistent quantification remains challenging due to nonlinear interactions and limited unified modeling strategies. Existing approaches inadequately capture generalized structure–property mappings across diverse polymer systems. This research aims to establish a machine learning-based quantification model for polymer structure–property relationships to support predictive material design. A Polymer Structure Property Dataset of 5,000 polymer samples includes structural descriptors and experimentally measured …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 737–754 Read article
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Drones in Precision Livestock Farming: Advancing Health, Welfare, and Resilience in Dairy Production Systems
Abstract: The integration of drone technology in precision livestock farming represents a transformative advancement in modern dairy production systems. Drones offer innovative solutions for monitoring, managing, and optimizing livestock health, welfare, and productivity while addressing challenges related to environmental sustainability and resource efficiency. This study explores the diverse applications of drones in dairy farming, including health monitoring, disease detection, reproductive assessment, and real-time herd tracking. By leveraging thermal imaging and advanced …
Published in Journal of Aerospace Engineering & Technology · Vol. 15, Issue 2, 2025 · pp. 16–25 Read article
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Texture Segmentation Using Multichannel Filtering And Kohonen’s Self Organizing Map
Abstract: The texture is very important cue in region based segmentation of images. Texture features play a very important role in computer vision and pattern recognition. Texture segmentation can be broken down into two areas, feature extraction and clustering. In this paper, we implement two stage of feature extraction technique using multichannel filter and Self Organizing Map (SOM). Firstly, we go through channel filters, also known as 2-D Gabor functions. The …
Published in Journal of Alternate Energy Sources & Technologies · Vol. 3, Issue 3, 2012 · pp. 17–30 Read article
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Integration of Multispectral Satellite data with Ensemble Machine Learning Models for Wetland Classification: a new Ramsar Site in Central India
Abstract: For biodiversity conservation, several wetlands in India have been classified as Ramsar sites, and Sirpur Lake is a recent addition to the list. The objective of this paper is to use Sentinel optical data with 10-meter resolution to prepare a robust and accurate classified map which will be crucial for further analysis. The data on thirteen spectral bands along with four essential spectral indices, Normalized Difference Vegetation Index (NDVI), Normalized …
Published in Journal of Remote Sensing & GIS · Vol. 16, Issue 3, 2025 Read article
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Comparative Analysis of Supervised Learning Algorithms
Abstract: Supervised learning is a fundamental and widely used branch of machine learning in which models are trained on labeled datasets, meaning that each input is associated with a known output. Supervised learning algorithms develop predictive capability by understanding the mapping between input variables and corresponding output labels, enabling them to accurately forecast outcomes for previously unseen data. Due to this capability, supervised learning has found extensive applications across diverse domains …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 · pp. 25–30 Read article