Search Results - (( data identification sensor algorithm ) OR ( java implementation path algorithm ))
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Heavy Transportation Shortest Route using Dijkstra’s algorithm (HETRO) / Nurul Aqilah Ahmad Nezer
Published 2017“…The development tools used in developing this project is NetBeans by using Java for the implementation of the coding. The methodology that used for developing this system is the Dijkstra’s algorithm. …”
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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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Path planning for unmanned aerial vehicle (UAV) using rotated accelerated method in static outdoor environment
Published 2021“…In this study, a fast iterative method known as Rotated Successive Over-Relaxation (RSOR) is introduced. The algorithm is implemented in a self-developed 2D Java tool, UAV Planner. …”
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Smart appointment organizer for mobile application / Mohd Syafiq Adam
Published 2009“…The main component of this prototype is the use of Dijkstra algorithm to compute the shortest path from source of appointment to the 6 points of destinations within UiTM Shah Alam. …”
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Investigating optimal smartphone placement for identifying stairs movement using machine learning
Published 2023“…The inertial sensor data was collected from the smartphone at two different positions and two different orientations. …”
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Flow regime identification of particles conveying in pneumatic pipeline using electric charge tomography and neural network techniques
Published 2006“…A high speed data acquisition card DAS1800HC is used to interface the sensors to a personal computer which processes the data using linear back projection algorithm (LBPA) and filtered back projection algorithm (FBPA). …”
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Development of damage identification scheme using de-noised modal frequency response function data with artificial neural network / Mohamad Izzudin Hussein Shah
Published 2018“…Vibration based damage identification scheme which utilise vibrational modal data is popular due to its non-destructive nature. …”
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Water Pollution Source Identification Based on Real-Time Monitoring System in Siak River
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Abnormal data detection model based on autoencoder and random forest algorithm: camera sensor data in autonomous driving systems
Published 2025“…In the field of autonomous driving, abnormal data will directly affect the safety of autonomous driving systems, especially in terms of abnormal camera sensor data. …”
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The identification of oreochromis niloticus feeding behaviour through the integration of photoelectric sensor and logistic regression classifier
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Fault Detection and Identification in Quadrotor System (Quadrotor Robot)
Published 2016“…Kalman filter recognized data from the system sensors and can indicate the fault of the system in the sensor reading. …”
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A systematic literature review on outlier detection in wireless sensor networks
Published 2020“…Therefore, an efficient local/distributed data processing algorithm is needed to ensure: (1) the extraction of precise and reliable values from noisy readings; (2) the detection of anomalies from data reported by sensors; and (3) the identification of outlier sensors in a WSN. …”
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Vibration-based structural damage detection and system identification using wavelet multiresolution analysis / Seyed Alireza Ravanfar
Published 2017“…Therefore, a new reference-free damage detection algorithm is proposed. The RWPE measurements of different sensor-to-sensor pairs are applied for defining the reference-free damage index (RDI) of each sensor location. …”
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Performance comparison of classification algorithms for EEG-based remote epileptic seizure detection in wireless sensor networks
Published 2014“…Identification of epileptic seizure remotely by analyzing the electroencephalography (EEG) signal is very important for scalable sensor-based health systems.Classification is the most important technique for wide-ranging applications to categorize the items according to its features with respect to predefined set of classes.In this paper, we conduct a performance evaluation based on the noiseless and noisy EEG-based epileptic seizure data using various classification algorithms including BayesNet, DecisionTable, IBK, J48/C4.5, and VFI.The reconstructed and noisy EEG data are decomposed with discrete cosine transform into several sub-bands.In addition, some of statistical features are extracted from the wavelet coefficients to represent the whole EEG data inputs into the classifiers.Benchmark on widely used dataset is utilized for automatic epileptic seizure detection including both normal and epileptic EEG datasets.The classification accuracy results confirm that the selected classifiers have greater potentiality to identify the noisy epileptic disorders.…”
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Gas Identi cation by Using a Cluster-k-Nearest-Neighbor
Published 2009“…Among the most serious limitations facing the success of future consumer gas identification systems are the drift problem and the real-time detection due to the slow response of most of todays gas sensors. …”
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Self-calibration algorithm for a pressure sensor with a real-time approach based on an artificial neural network
Published 2018“…To verify the proposed model’s capability to build a self-calibration algorithm, the model was tested using an untrained input data set. …”
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Real time self-calibration algorithm of pressure sensor for robotic hand glove system
Published 2019“…This study investigates the use of a novel Proposed Self-Calibration Algorithm (PSCA) of multi pressure sensors in real time on robotic hand glove system. …”
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Data fusion and multiple classifier systems for human activity detection and health monitoring: Review and open research directions
Published 2019“…For instances, combination of inertial sensors provide mechanism to differentiate activity of similar patterns and accurate posture identification while other multimodal sensor data are used for energy expenditure estimations, object localizations in smart homes and health status monitoring. …”
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