Search Results - (( time realization path algorithm ) OR ( variable extractions sensor algorithm ))
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Nonlinear FXLMS algorithm for active noise control systems with saturation nonlinearity
Published 2012“…However, NLFXLMS cannot be implemented in real time because the modeling of the SEF cannot be realized. …”
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Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization
Published 2019“…BST inserts the nodes in the way that the Dijkstra’s can find the empty parking in fastest way. Dijkstra’s algorithm initials the paths to finding the shortest path while ACO optimizes the paths. …”
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Adaptable decentralized orchestration engine for block structured non-transactional workflow in service oriented architecture.
Published 2011“…The latter considers the frequent-path adaptability and both of them together satisfy both frequent-path and proportionalfragment adaptability aspects; v) A Fuzzy Decentralization Decision Making algorithm (FDDM) is presented based on the fuzzy logic to choose a suitable method of decentralization that satisfies the three adaptability aspects frequent-path,proportional- fragment and available-bandwidth; and, vi) an algorithm is introduced for wiring of dynamic fragments. …”
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Development of Path Loss Models for Smooth and Convex Surfaces Terrains in Malaysian Environment
Published 2004“…The UPMPL program provides the utility for calculating the signal characteristics of radio propagation paths and is realized in the run time format version. …”
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Intelligent guidance parking system using modified Dijkstra's algorithm
Published 2014“…The best parking system is the system that provides customers the ease of finding the available spaces, user friendly and less time consuming. This paper presents the intelligent parking system which apply Dijkstra’s algorithm in finding the shortest path. …”
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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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Simultaneous measurement of multiple soil properties through proximal sensor data fusion: a case study
Published 2019“…In this field, it was not possible to predict extractable P and K using all tested sensor combinations or algorithms. …”
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Google the earth: what's next?
Published 2010“…Technologically, the challenge is to design sensors that exhibit high sensitivity to the parameters of interest while minimizing instrument noise and impacts of other natural variables. …”
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Surface defect detection and polishing parameter optimization using image processing for G3141 cold rolled steel
Published 2016“…This techniques will enables the polishing to be done at specific scratch defect area without necessary to develop polishing path throughout the whole surface which is time consuming. …”
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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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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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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 first phase, spectral features and structural features were extracted for feature extraction. In the spectral features part, the descriptors include red (R), green (G), blue (B), near-infrared (NIR) digital numbers and a vegetation index (VI) was considered. …”
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