Search Results - (( java application path algorithm ) OR ( model selection sensor algorithm ))
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Smart appointment organizer for mobile application / Mohd Syafiq Adam
Published 2009“…In creating this application, NetBeans IDE 6.5and Java Micro Edition (Java ME) are used. …”
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Performance of various forecasting algorithms to reduce the number of transmitted packets by sensor node in wireless sensor networks
Published 2018“…The simulation experiments are done using MATLAB software for a variety of algorithms. The selected algorithms for the reduction algorithm in the transmissions include Move Average algorithm (MA), Autoregressive all-pole model parameters — Burg’s algorithm. …”
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Visdom: Smart guide robot for visually impaired people
Published 2025“…The system architecture integrates ROS 2 on a Raspberry Pi, with TCP/IP connectivity enabling remote operation. An Android mobile application, developed using Java and the java.net.Socket library, provides an intuitive and accessible user interface for seamless interaction with the robot. …”
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Final Year Project / Dissertation / Thesis -
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Visdom: Smart guide robot for visually impaired people
Published 2025“…The system architecture integrates ROS 2 on a Raspberry Pi, with TCP/IP connectivity enabling remote operation. An Android mobile application, developed using Java and the java.net.Socket library, provides an intuitive and accessible user interface for seamless interaction with the robot. …”
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Final Year Project / Dissertation / Thesis -
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VHDL modeling of optimum measurement selection by using genetic algorithm
Published 2009“…A Genetic Algorithm (GA) that is going to be a part of a system for obtaining optimum sensor measurements for a specific process. …”
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An energy-efficient spectrum-aware reinforcement learning-based clustering algorithm for cognitive radio sensor networks
Published 2015“…The problem of selecting an optimal cluster is formulated as a Markov Decision Process (MDP) in the algorithm and the obtained simulation results show convergence, learning and adaptability of the algorithm to dynamic environment towards achieving an optimal solution. …”
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A survey on signal processing methods in fiber optic sensor for oxidized carbon steel
Published 2019“…We selected these two algorithms because our focus is on these methods. …”
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A survey on signal processing methods in fiber optic sensor for oxidized carbon steel
Published 2019“…We selected these two algorithms because our focus is on these methods. …”
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Hybridization of enhanced ant colony system and Tabu search algorithm for packet routing in wireless sensor network
Published 2020“…This research proposes a hybridization of Enhanced ACS and Tabu Search (EACS(TS)) algorithm for packet routing in WSN. The EACS(TS) selects sensor nodes with high pheromone values which are calculated based on the residual energy and current pheromone value of each sensor node. …”
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Indoor occupancy detection using machine learning and environmental sensors / Akindele Segun Afolabi ... [et al.]
Published 2025“…Hence, it is crucial to determine ML models that are robust against such disruptions. In this paper, three algorithms were developed: the first was for outlier removal from features, the second was for feature selection, and the third was for partial-features-availability-aware ML model selection. …”
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A survey of simulators, emulatots and testbeds for Wireless Sensor Network
Published 2010“…Simulators, emulators and testbeds are invaluable tools for performance evaluation of algorithms and protocols in wireless sensor networks (WSNs). …”
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Conference or Workshop Item -
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Class binarization with self-adaptive algorithm to improve human activity recognition
Published 2018“…However, the learning complexity of classification is increased due to the expansion number of learning model. Therefore, feature selection using Relief-f with self-adaptive Differential Evolution (rsaDE) algorithm is proposed to select the most significant features. …”
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Algorithm enhancement for host-based intrusion detection system using discriminant analysis
Published 2004“…Misuse detection algorithms model know attack behavior. They compare sensor data to attack patterns learned from the training data. …”
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Artificial neural network (ANN) as post-processing stage for chemically selective field effect transistor (CHEMFET) sensor selectivity based-on ion concentration / Nurhakimah Abd A...
Published 2016“…The sensor voltage response used has been measured and also generated based on CHEMFET sensor modeling by using MATLAB software. …”
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Maximizing Lifetime of Homogeneous Wireless Sensor Network through Energy Efficient Clustering Method
Published 2010“…Energy efficiency is a very important issue for sensor nodes which affects the lifetime of sensor networks. …”
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Citation Index Journal -
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Design and development of cooperative simultaneous localization and mapping integrated with neural network for mobile robot
Published 2024“…By training the ANN using sensor measurements, it learns to model the data and reduce the error or uncertainties present in the measurements obtained from the low-cost sensors. …”
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Using artificial intelligence search in solving the camera placement problem
Published 2022“…The chapter also carries out an analytical review of three main searching algorithms namely, generate and test, uninformed search, and hill climbing search algorithms. …”
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Book -
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Combining data mining algorithm and object-based image analysis for detailed urban mapping of hyperspectral images
Published 2014“…The high accuracy of object-based classification can be linked to the knowledge discovery produced by the DM algorithm. This algorithm increased the productivity of OBIA, expedited the process of attribute selection, and resulted in an easy-to-use representation of a knowledge model from a decision tree structure.…”
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Smart agriculture: precision farming through sensor-based crop monitoring and control system
Published 2024“…Subsequently, four distinct algorithms are trained with the collected dataset to ascertain the most optimal algorithm for predicting crop growth and harvesting time, resulting in the selection of the Random Forest Regression model, which attains the highest model score of 86%. …”
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