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Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak by Dak, Ahmad Yusri

“…The first stage is to apply reverse engineering method to obtain the specific patterns of individual jammers. …”
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An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

“…In comparison to different single algorithms for feature selection,experimental results show that the proposed ensemble method is able to reduce dimensionality, the number of irrelevant features and produce reasonable classifier accuracy. …”
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Region duplication forgery detection technique based on keypoint matching / Diaa Mohammed Hassan Uliyan by Diaa , Mohammed Hassan Uliyan

“…The average detection rate of our algorithm maintained 96 % true positive rate and 7 % false positive rate which outperform several current detection methods. …”
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Optimizing the performance of mobile malware detection using the indexing rule by Ahmad I.N., Farida Hazwani Mohd Ridzuan, Madihah Mohd Saudi

Seismic attribute feasibility study for fault and fracture analysis and integration with spectral decomposition: Application in Sarawak basin by Hamidi, R., Ghosh, D.

“…Consequently, new strategies and algorithms are needed to improve the information obtained from the calculated attributes. …”
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Development Of Stereo-Matching Algorithm Based On Adaptive Weighted Prediction by Abd Razak, Siti Safwana

“…Therefore, to overcome the causes of effected accuracy, new Stereo Matching Algorithm (SMA) based on Adaptive Weighted Bilateral Filter (AWBF) was introduced together with characterize the SMA based on quantitative and qualitative measurements and produced SMA performance were evaluate using standard taxonomy of SM. …”
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A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem by Mohd Pozi, Muhammad Syafiq

“…In addition, the classifier is also optimized such that it has a good generalization property. The main keys of the new classifier are based on the new kernel method, new learning metric and a new optimization algorithm in order to optimize the SVM decision function. …”
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Outbreak detection model based on danger theory by Mohamad Mohsin, Mohamad Farhan, Abu Bakar, Azuraliza, Hamdan, Abdul Razak

“…Two outbreak diseases, dengue and SARS, are subjected to a danger theory algorithm; namely the dendritic cell algorithm.To evaluate the model, four measurement metrics are applied: detection rate, specificity, false alarm rate, and accuracy. …”
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Particle track finding using hough transform in a central drift chamber detector / Khasmidatul Akma Mohamed Kamal Azmi by Khasmidatul Akma , Mohamed Kamal Azmi

“…The assessment of charged particle track findings have improved significantly. The method of the Hough Transform became an iconic method to trace and identify the pattern of the charged track in the HEP based on the evaluation of the track finding in the cloud chamber experiment. …”
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Defect detection based on extreme edge of defective region histogram by Wakaf, Zouhir, Jalab, Hamid Abdullah

“…To evaluate the proposed defect-detection method, common standard images for experimentation were used. …”
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New global maximum power point tracking and modular voltage equalizer topology for partially shaded photovoltaic system / Immad Shams by Immad , Shams

“…Only one dynamic variable is used as a tuning parameter reducing the complexity of the algorithm. The search space skipping method has been proposed to improve the CS. …”
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Image segmentation method for boundary detection of breast thermography using random walkers by Moghbel, Mehrdad

“…The performance of the proposed method was evaluated by a board of three professional radiologists and the final decision was based on the majority agreement. …”
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Classification of credit card holder behavior using K Nearest Neighbor algorithm / Ahmad Faris Rahimi by Rahimi, Ahmad Faris

“…The second one is to develop prototype for classification of credit cardholder behavior based on k Nearest Neighbors Algorithm. The third one is to evaluate the accuracy of the k Nearest Neighbors algorithm in the classification credit card holder behavior. …”
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Liver segmentation on CT images using random walkers and fuzzy c-means for treatment planning and monitoring of tumors in liver cancer patients by Moghbel, Mehrdad

“…The proposed method is based on a hybrid method integrating random walkers algorithm with integrated priors and particle swarm optimized spatial fuzzy c-means (FCM) algorithm with level set method and AdaBoost classifier. …”
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Iban Plaited Mat Motif Classification using Adaptive Smoothing by Silvia, Joseph

“…To address this issue, an improved classification method with adaptive smoothing is proposed. This method utilizes dynamic thresholds for edge detection and uses morphological operations to enhance the smoothed edges. …”
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Local-based stereo matching algorithm using multi-cost pyramid fusion, hybrid random aggregation and hierarchical cluster-edge refinement by Kadmin, Ahmad Fauzan

“…The stereo vision algorithm computes disparity using local, global, and semiglobal optimisation methods established by the researcher. …”
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A study on component-based technology for development of complex bioinformatics software by Ali Shah, Zuraini, Deris, Safaai, Othman, Muhamad Razib, Zakaria, Zalmiyah, Saad, Puteh, Hassan, Rohayanti, Muda, Mohd. Hilmi, Kasim, Shahreen, Roslan, Rosfuzah

“…It will detect up to fold in SCOP hierarchy. They evaluated the results obtained using mean ROC and mean MRFP. …”
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Hybrid vehicle engine misfire detection using Piezo-film Sensors and analysing with Z-freq / Nor Azazi Ngatiman and Mohd Zaki Nuawi by Ngatiman, Nor Azazi, Nuawi, Mohd Zaki

“…This paper explores the application of standard deviation and kurtosis to formulate a new statistical method for hybrid electric vehicle (HEV) engine misfire detection named as Z-freq. …”
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Toward Predicting Student�s Academic Performance Using Artificial Neural Networks (ANNs) by Baashar Y., Alkawsi G., Mustafa A., Alkahtani A.A., Alsariera Y.A., Ali A.Q., Hashim W., Tiong S.K.

“…This study also attempts to capture a pattern of the most used ANN techniques and algorithms. …”

Crypt Edge Detection Using PSO,Label Matrix And BI-Cubic Interpolation For Better Iris Recognition(PSOLB) by Hashim, Nurul Akmal

“…Recently,there has been renewed interest in iris features detection.Gabor filter,cross entrophy, upport vector,and canny edge detection are methods which produce iris codes in binary codes representation.However,problems have occurred in iris recognition since low quality iris images are created due to blurriness,indoor or outdoor settings, and camera specifications.Failure was detected in 21% of the intra-class comparisons cases which were taken between intervals of three and six months intervals.However,the mismatch or False Rejection Rate (FRR) in iris recognition is still alarmingly high.Higher FRR also causes the value of Equal Error Rate (EER) to be high.The main reason for high values of FRR and EER is that there are changes in the iris due to the amount of light entering into the iris that changes the size of the unique features in the iris.One of the solutions to this problem is by finding any technique or algorithm to automatically detect the unique features.Therefore a new model is introduced which is called Crypt Edge Detection which combines PSO,Label Matrix,and Bi-Cubic Interpolation for Iris Recognition (PSOLB) to solve the problem of detection in iris features.In this research, the unique feature known as crypts has been chosen due to its accessibility and sustainability.Feature detection is performed using particle swarm optimisation (PSO) as an algorithm to select the best iris texture among the unique iris features by finding the pixel values according to the range of selected features.Meanwhile, label matrix will detect the edge of the crypt and the bi-cubic interpolation technique creates sharp and refined crypt images.In order to evaluate the proposed approach,FAR and FRR are measured using Chinese Academy of Sciences' Institute of Automation (CASIA) database for high quality images.For CASIA version 3 image databases, the crypt feature shows that the result of FRR is 21.83% and FAR is 78.17%.The finding from the experiment indicates that by using the PSOLB,the intersection between FAR and FRR produces the Equal Error Rate (EER) with 0.28%,which indicated that equal error rate is lower than previous value, which is 0.38%.Thus,there are advantages from using PSOLB as it has the ability to adapt with unique iris features and use information in iris template features to determine the user.The outcome of this new approach is to reduce the EER rates since lower EER rates can produce accurate detection of unique features.In conclusion,the contribution of PSOLB brings an innovation to the extraction process in the biometric technology and is beneficial to the communities.…”
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