Search Results - (( data application using algorithm ) OR ( variables extraction sensor algorithm ))
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Simultaneous measurement of multiple soil properties through proximal sensor data fusion: a case study
Published 2019“…Predictions of pH and LBC were only feasible using MARS and PLSR, respectively. In this field, it was not possible to predict extractable P and K using all tested sensor combinations or algorithms. …”
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Multi-sensor fusion and deep learning framework for automatic human activity detection and health monitoring using motion sensor data / Henry Friday Nweke
Published 2019“…This is further worsen by the use of single sensors modality and machine learning algorithms. …”
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Google the earth: what's next?
Published 2010“…Considering the exponential growth of data volumes driven by the rapid progress in sensor and computer technologies in recent years, the future of remotely sensed data should ideally be in automated data processing, development of robust and transferable algorithms and processing chains that require little or no human intervention. …”
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Wavelet based fault tolerant control of induction motor / Khalaf Salloum Gaeid
Published 2012“…The fault detection algorithm identifies the time and location of each fault. …”
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Oil palm female inflorescences anthesis stages identification using selected emissivities through thermal imaging and Machine Learning
Published 2022“…This research studies different Machine Learning (ML) classification and ensemble techniques for the assessment of the four pollination stages consist of pre-anthesis I, pre-anthesis II, pre-anthesis III, and anthesis using thermal imaging. Different ML algorithms such as Random Forest (RF), k Nearest Neighbor (kNN), Support Vector Machine (SVM), Artificial Neural Network (ANN) as well as an ensemble method are used on data extracted from thermal images collected during infield oil palms pollination stages monitoring. …”
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Evaluation of multiple In Situ and remote sensing system for early detection of Ganoderma boninense infected oil palm
Published 2018“…In the next phase, the SVM classifier was trained to achieve the best classification using training data and test data integrated with selected features. …”
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Workflow optimization in distributed computing environment for stream-based data processing model / Saima Gulzar Ahmad
Published 2017“…To avoid such overheads many techniques have been used, however in this thesis stream-based data processing model is used in which data is processed in the form of continuous instances of data items. …”
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Algorithm Development of Bidirectional Agglomerative Hierarchical Clustering Using AVL Tree with Visualization
Published 2024thesis::doctoral thesis -
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Cluster Analysis of Data Points using Partitioning and Probabilistic Model-based Algorithms
Published 2014“…Exploring the dataset features through the application of clustering algorithms is a viable means by which the conceptual description of such data can be revealed for better understanding, grouping and decision making. …”
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New global maximum power point tracking and modular voltage equalizer topology for partially shaded photovoltaic system / Immad Shams
Published 2022“…Despite the effective proposed GMPPT algorithm, the PSCs reduce the maximum power extraction capability of the PV system heavily due to the activation of bypass diodes. …”
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Enhancing Secure Sockets Layer Bulk Data Trnsfer Phase Performance With Parallel Cryptography Algorithm
Published 2007“…The proposed algorithm performs the encryption of the data and the calculation of the MAC in parallel. …”
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Two objectives big data task scheduling using swarm intelligence in cloud computing
Published 2016“…The proposed method is evaluated using CloudSim and big data applications are used as sample of applications. …”
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Data discovery algorithm for scientific data grid environment
Published 2005“…By using this model, we study various discovery algorithms for locating data sets in a data grid system. …”
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Development of heuristic task scheduling algorithm in cloud computing
Published 2016“…As the immense growth of data have affected many organizations, there have been a need to adopt the cloud resources for processing big data applications which could cost highly by using traditional storage. …”
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Spatial Clustering Algorithm for Time Series Rainfall Data Using X-Means Data Splitting
Published 2017“…Therefore, a clustering algorithm by introducing data transformation using X-means data splitting is proposed to investigate the spatial homogeneity of time series rainfall data. …”
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Image Encrytion Using Block Based Transformation Algorithm
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