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Implementation of Parallel K-Means Algorithm to Estimate Adhesion Failure in Warm Mix Asphalt by Akhtar, M.N., Ahmed, W., Kakar, M.R., Bakar, E.A., Othman, A.R., Bueno, M.

“…The results showed that the PKIP algorithm decreases the execution time up to 30 to 46 if compared with the sequential k means algorithm when implemented using multiprocessing and distributed computing. …”
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Pairwise testing tools based on hill climbing algorithm (PTCA) by Lim, Seng Kee

“…The actual implementation of the algorithm which is in Java programming language, the program is implemented on Net Bean 7.0.1. …”
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CNN-SVO: improving the mapping in semi-direct visual odometry using single-image depth prediction by Loo, Shing Yan, Amiri, Ali Jahani, Mashohor, Syamsiah, Tang, Sai Hong, Zhang, Hong

“…Reliable feature correspondence between frames is a critical step in visual odometry (VO) and visual simultaneous localization and mapping (V-SLAM) algorithms. …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Alzaeemi, Shehab Abdulhabib, Tay, Kim Gaik, Huong, Audrey, Sathasivam, Saratha, Majahar Ali, Majid Khan

“…Each of these methods is presented in the steps in the flowchart form which can be used for its straightforward implementation in any programming language. With the use of SRBFNN-2SAT, a training method based on these algorithms has been presented, then training has been compared among algorithms, which were applied in Microsoft Visual C++ software using multiple metrics of performance, including Mean Absolute Relative Error (MARE), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), Mean Bias Error (MBE), Systematic Error (SD), Schwarz Bayesian Criterion (SBC), and Central Process Unit time (CPU time). …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Shehab Abdulhabib Alzaeemi, Shehab Abdulhabib Alzaeemi, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majahar Ali, Majid Khan

“…Each of these methods is presented in the steps in the flowchart form which can be used for its straightforward implementation in any programming language. With the use of SRBFNN-2SAT, a training method based on these algorithms has been presented, then training has been compared among algorithms, which were applied in Microsoft Visual C++ software using multiple metrics of performance, including Mean Absolute Relative Error (MARE), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), Mean Bias Error (MBE), Systematic Error (SD), Schwarz Bayesian Criterion (SBC), and Central Process Unit time (CPU time). …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Shehab Abdulhabib Alzaeemi, Shehab Abdulhabib Alzaeemi, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majid Khan bin Majahar Ali, Majid Khan bin Majahar Ali

“…Each of these methods is presented in the steps in the flowchart form which can be used for its straightforward implementation in any programming language. With the use of SRBFNN-2SAT, a training method based on these algorithms has been presented, then training has been compared among algorithms, which were applied in Microsoft Visual C++ software using multiple metrics of performance, including Mean Absolute Relative Error (MARE), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), Mean Bias Error (MBE), Systematic Error (SD), Schwarz Bayesian Criterion (SBC), and Central Process Unit time (CPU time). …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Shehab Abdulhabib Alzaeemi, Shehab Abdulhabib Alzaeemi, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majahar Ali, Majid Khan

“…Each of these methods is presented in the steps in the flowchart form which can be used for its straightforward implementation in any programming language. With the use of SRBFNN-2SAT, a training method based on these algorithms has been presented, then training has been compared among algorithms, which were applied in Microsoft Visual C++ software using multiple metrics of performance, including Mean Absolute Relative Error (MARE), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), Mean Bias Error (MBE), Systematic Error (SD), Schwarz Bayesian Criterion (SBC), and Central Process Unit time (CPU time). …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Shehab Abdulhabib Alzaeemi, Shehab Abdulhabib Alzaeemi, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majahar Ali, Majid Khan

“…Each of these methods is presented in the steps in the flowchart form which can be used for its straightforward implementation in any programming language. With the use of SRBFNN-2SAT, a training method based on these algorithms has been presented, then training has been compared among algorithms, which were applied in Microsoft Visual C++ software using multiple metrics of performance, including Mean Absolute Relative Error (MARE), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), Mean Bias Error (MBE), Systematic Error (SD), Schwarz Bayesian Criterion (SBC), and Central Process Unit time (CPU time). …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Alzaeemi, Shehab Abdulhabib, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majahar Ali, Majid Khan

“…Each of these methods is presented in the steps in the flowchart form which can be used for its straightforward implementation in any programming language. With the use of SRBFNN-2SAT, a training method based on these algorithms has been presented, then training has been compared among algorithms, which were applied in Microsoft Visual C++ software using multiple metrics of performance, including Mean Absolute Relative Error (MARE), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), Mean Bias Error (MBE), Systematic Error (SD), Schwarz Bayesian Criterion (SBC), and Central Process Unit time (CPU time). …”
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Simulation of shortest path using a-star algorithm / Nurul Hani Nortaja by Nurul Hani , Nortaja

“…This thesis also provides an explanation about the advantages. functions, characteristics. the degree of complexity in A • algorithm and its implementation in real-world application. …”
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Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization by Mohammad Ata, Karimeh Ibrahim

“…The circuits have been designed by proteus, the microcontrollers have been programmed by micro C, and the Graphical User Interface (GUI) has been implemented in Java. Few by electronic components such as RFID, multiplexer, XBee, and servo motors have been used to realize the system. …”
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3D graphics visualization for interactive mobile users navigation by Mantoro, Teddy, Abubakar, Adamu, Ayu, Media Anugerah

“…The solutions will be provided through implementing an efficient, scalable dynamic entity navigation solution by means of Bi-A* path finding algorithm. …”
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Virtual GIS walkthrough Innovation Center / Mohd Sufean Abu Samah by Abu Samah, Mohd Sufean

“…Nowadays advances in computer graphics hardware and algorithms, visualization and interactive techniques for analysis offer the components for a high integrated, efficient real-time 3d Virtual GIS. …”
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Mathematical simulation for 3-dimensional temperature visualization on open source-based grid computing platform by Alias, Norma, Satam, Noriza, Abd. Ghaffar, Zarith Safiza, Darwis, Roziha, Hamzah, Norhafiza, Islam, Md. Rajibul

“…The development of this architecture is based on several programming language as it involves algorithm implementation on C, parallelization using Parallel Virtual Machine (PVM) and Java for web services development. …”
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Exploring employee working productivity: initial insights from machine learning predictive analytics and visualization / Mohd Norhisham Razali ... [et al.] by Razali, Mohd Norhisham, Ibrahim, Norizuandi, Hanapi, Rozita, Mohd Zamri, Norfarahzila, Abdul Manaf, Syaifulnizam

“…Experimental results revealed that the linear regression model achieved the best performance in terms of Mean Absolute Error (MAE) and Mean Squared Error (MSE), with values of 0.4878 and 0.4682, respectively. …”
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Denoising of digital images using second generation wavelet transforms-hidden markov model by Khmag, Asem Ib Mohamed

“…After applying the denoising algorithm on the contaminated image, the cycling spinning algorithm is applied to increase the visual quality of the restored image. …”
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Talkout : Protecting mental health application with a lightweight message encryption by Gavin Teo Juen

“…The investigation of lightweight message encryption algorithms is conducted with systematic quantitative literature and experiment implementation in Java and Android running environment. …”
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Design & Development of a Robotic System Using LEGO Mindstorm by Abd Manap, Nurulfajar, Md Salim, Sani Irwan, Haron, Nor Zaidi

“…The system is capable in operating an off-line programming method, starting from its programming sequences until robotic implementation of the program. During early stages, the research is emphasis more towards designing a robotic system using RoboLab software and C++ programming language. …”
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Industrial Training Kit for Education by Ahmad Syahmi Naqiuddin Mohamad

Generating vulnerability maps of dengue incidences for Petaling district in Malaysia by Mathur, N., Asirvadam, V.S., Dass, S.C., Gill, B.S.

“…This work develops and implements visualization and predictive modelling for dengue in Malaysia. …”
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