Search Results - (( developing quantify selection algorithm ) OR ( java application optimisation algorithm ))

Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

“…The system is essentially a three-part development, utilising Android, Java Servlets, and Arduino platforms to create an optimised and automated urban-gardening system. …”
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Development of saliency metric for autonomous landmark selection in cognitive robot navigation / Gao Hanyang by Gao , Hanyang

“…The dissertation follows three objectives; to segment urban landmarks in an image, to develop an algorithm to quantify visual salience indicators for urban landmarks extraction, and to compare the performance of proposed algorithm in extracting urban landmarks between robot and human. …”
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Implementation of Color Filtering on FPGA by Mohd Shukor, Mohd Nasir, Lo, H. H., Sebastian, Patrick

“…The chosen image processing algorithm is a single Color Filtering algorithm. This work utilizes Altera DE2 development board empowered by the Cyclone II FPGA paired with a 1.3 Mega pixel CMOS camera from Terasik Technologies. …”
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Web-based expert system for material selection of natural fiber- reinforced polymer composites by Ahmed Ali, Basheer Ahmed

“…Finally, the developed expert system was deployed over the internet with central interactive interface from the server as a web-based application. As Java is platform independent and easy to be deployed in web based application and accessible through the World Wide Web (www), this expert system can be one stop application for materials selection.…”
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Implementation of color filtering on FPGA by P., Sebastian, M.N.B.M., Shukor, H.H., Lo

“…The chosen image processing algorithm is a single Color Filtering algorithm. This work utilizes Altera DE2 development board empowered by the Cyclone II FPGA paired with a 1.3 Mega pixel CMOS camera from Terasik Technologies. …”
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Leveraging mechanomyography signal for quantitative muscle spasticity assessment of upper limb in neurological disorders using machine learning by Daud, Muhamad Aliff Imran, Ahmad Puzi, Asmarani, Sidek, Shahrul Na'im, Zainuddin, Ahmad Anwar, Mohd Khairuddin, Ismail, Abd Mutalib, Mohd Azri

“…The test results determined the selection of twenty-five features from a total of forty-eight which be used to train an optimum classifier algorithm for the purpose of quantifying the level of muscle spasticity. …”
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Monitoring the drying process of glutinous rice using hyperspectral imaging coupled with multivariate analysis by Jimoh, Kabiru Ayobami, Hashim, Norhashila, Shamsudin, Rosnah, Che Man, Hasfalina, Jahari, Mahirah

“…The model prediction performance shows an accuracy (R²P) of 0.9206 with RMSEP of 1.1410. Using CARS algorithm resulted in the selection of 21 optimal wavelengths that are highly associated with the moisture content of glutinous rice during the drying process and the developed PLS model based on the selected wavelength gave an increased model accuracy with R2CV and RMSECV of 0.9176 and 1.0986 respectively. …”
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Leveraging mechanomyography signal for quantitative muscle spasticity assessment of upper limb in neurological disorders using machine learning by Muhamad Aliff Imran, Daud, Asmarani Ahmad Puzi, asmarani@iium.edu.my, Shahrul Na’im, Sidek, Ahmad Anwar, Zainuddin, Ismail, Mohd Khairuddin, Mohd Azri, Abd Mutalib

“…The test results determined the selection of twenty-five features from a total of forty-eight which be used to train an optimum classifier algorithm for the purpose of quantifying the level of muscle spasticity. …”
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Tracking using normalized cross correlation and color space by P., Sebastian, V.V., Yap

“…In addition to the TDR being used as a metric to determine the accuracy of a tracking method, another metric was formulated to quantify the accuracy of a tracking algorithm. The metric developed was object tracking variance (OTV) and object tracking standard deviation (OTStd). …”
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Optimal design of low-voltage distribution networks for CO2 emission minimisation. Part II: Discrete optimisation of radial networks and comparison with alternative design strategi... by Gan, Chin Kim

“…In particular, a specific algorithm is developed to apply the proposed circuit design for CO2 emission minimisation to radial networks, the great majority of low-voltage ones, taking into account the presence of only discrete capacities available for cable selection. …”
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A computational framework for predicting software quality-in-use from software reviews by Atoum, Issa

“…In semantic similarity area, we proposed a novel Weighted Sentence Similarity Measure (WSSM) and developed an algorithm to predict a review-sentence QinU topic (QinU characteristic or software aspect). …”
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Quantitative spasticity assessment model of neurological disorder patients / AA Puzi … [et al.] by Ahmad Puzi, Asmarani, Aliff-Imran, M.D., Zainuddin, Ahmad Anwar, Basri, Atikah Balqis, Mohd Khairuddin, Ismail

“…The cues from the MMG signals pattern will be used to select the sampling features for the development of the classification algorithm model. …”
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Perturbation stochastic model updating of a bolted structure / Mohamad Azam Shah Aziz Shah by Aziz Shah, Mohamad Azam Shah

“…In this study, a new scheme using the perturbation SMU method with multidimensional analysis was proposed to estimate appropriate initial values for the high-dimensional uncertain parameters in a FE model of a bolted structure. The scheme was developed by introducing a multidimensional analysis consisting of a systematic quasi-random sampling algorithm. …”
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A semi-automated requirements prioritisation technique for scalable requirements with stakeholder quantification and prioritisation by Hujainah, Fadhl Mohammed Omar

“…RP is considered as a vital role in ensuring the development of a quality system with defined constraint. …”
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PREDICTIVE MODELING OF DIMENSIONAL ACCURACIES IN 3D PRINTING USING ARTIFICIAL NEURAL NETWORK by Sivaraos, Kumaran K., Dharsyanth R., Amran M., Shukor S.M., Pujari S., Ramasamy D., Vatesh U.K., Mahdi Al-Obaidi A.S.H., Ramesh S., Lee K.Y.S.

“…Experimental data consisting of 27 sets of control parameters and corresponding dimensional outputs were used to train and validate the ANN model. The ANN model was developed using MATLAB software, employing training functions and learning algorithms to optimize the neural network architecture. …”

The new enhancement of OLSR energy-saving system in ADHOC network / Suhazlan Suhaimi by Suhaimi, Suhazlan

“…As such, this study was undertaken with the main aim to enhance the energy-saving system of MANET, with which nodes can function without failure by using a newly developed algorithm of the OLSR protocol. Specifically, the study involved the developments of three schemes, namely a new Load Balance Energy Distributed (LBED) scheme, a new enhancement energy-saving (NEES) scheme, and a New Enhanced OLSR Willingness Calculation (NEWC) scheme. …”
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Potential impacts of climate change on water resources of Haro River Watershed in Pakistan by Nauman, Saima

“…The baseline and future meteorological parameters from the selected GCM are then bias corrected using the observed meteorological dataset. …”
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Ageing oil well integrity assessment and rehabilitation / Ramesh Ramasamy by Ramesh , Ramasamy

“…A coherent decision-making methodology is developed and presented in this thesis to further consolidate the repairs/rehabilitations planning of the selected wells. …”
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Initial assessment of facial nerve paralysis based on motion analysis using optical flow method by Wan Syahirah, Wan Samsudin

“…Distance and area were selected as two measurement parameters which were investigated in this research. …”
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Predictive modeling of dimensional accuracies in 3D printing using artificial neural network by Subramonian, Sivarao, Kumaran, K., Dharsyanth, R., Md Ali, Mohd Amran, Salleh, Mohd Shukor, Pujari, Satish, Ramasamy, Devarajan, Vatesh, Umesh Kumar, Mahdi Al-Obaidi, Abdulkareem Sh, Ramesh, S., Lee, Kit Yee Sara

“…Experimental data consisting of 27 sets of control parameters and corresponding dimensional outputs were used to train and validate the ANN model. The ANN model was developed using MATLAB software, employing training functions and learning algorithms to optimize the neural network architecture. …”
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