Search Results - (( java implementation modified algorithm ) OR ( data classification window algorithm ))

Text Extraction Algorithm for Web Text Classification by Theab, Mustafa Muwafak

“…This study provides a text extraction algorithm for web text classification. The extraction algorithm consists of three phases namely web page extraction, rule formulation, and algorithm validation. …”
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Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

“…The thesis also provides a two different implementation of the modified FLEX algorithm using a java based parsers and XQuery implementation. …”
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An improved pixel-based and region-based approach for urban growth classification algorithms / Nur Laila Ab Ghani by Ab Ghani, Nur Laila

“…The urban growth images obtained are analysed to improve existing classification algorithms. The improved algorithm is constructed by adding new parameter and classification rule to existing algorithm. …”
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Analyzing land surface temperature in response to massive urbanization by using single window algorithm in Penang Island / Ainna Naeemah Zainal Abidin by Zainal Abidin, Ainna Naeemah

“…This study involved the Landsat 5 TM and Landsat 8 OLI satellite imagery to be used as data to achieve the aim. Apart from classification process. …”
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Non-fiducial based electrocardiogram biometrics with kernel methods by Hejazi, Maryamsadat

“…The highest window and subject predictive accuracies achieved are approximately 92% and 77% on KPCA data set with the lowest biometric error and overfitting. …”
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OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT by Murad S.S., Badeel R., Alsandi N.S.A., Alshaaya R.F., Ahmed R.A., Muhammed A., Derahman M.

“…To achieve this, we propose a new noble mechanism called Optimized Min-Min (OMin-Min) algorithm, inspired by the Min-Min algorithm. The objectives of this work are: i) to provide a comprehensive review of the cloud and scheduling process; ii) to classify the scheduling strategies and scientific workflows; iii) to implement our proposed algorithm with various scheduling algorithms (i.e., Min-Min, Round-Robin, Max-Min, and Modified Max-Min) for performance comparison, within different cloudlet sizes (i.e., small, medium, large, and heavy) in three scientific workflows (i.e., Montage, Epigenomics, and SIPHT); and iv) to investigate the performance of the implemented algorithms by using CloudSim. …”

Arabic Speaker Identification System for Forensic Authentication Using K-NN Algorithm by Abdulwahid S., Mahmoud M.A., Abdulwahid N.

Random subspace K-NN based ensemble classifier for driver fatigue detection utilizing selected EEG channels by Rashid, Mamunur, Mahfuzah, Mustafa, Norizam, Sulaiman, Nor Rul Hasma, Abdullah, Rosdiyana, Samad

“…In the present framework, a new channel selection algorithm based on correlation coefficients and an ensemble classifier based on random subspace k-nearest neighbour (k-NN) has been presented to enhance the classification performance of EEG data for driver fatigue detection. …”
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Prevention And Detection Mechanism For Security In Passive Rfid System by Khor, Jing Huey

“…The proposed protocol is designed with lightweight cryptographic algorithm, including XOR, Hamming distance, rotation and a modified linear congruential generator (MLCG). …”
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A voting-based hybrid machine learning approach for fraudulent financial data classification / Kuldeep Kaur Ragbir Singh by Kuldeep Kaur , Ragbir Singh

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Automatic generation of content security policy to mitigate cross site scripting by Mhana, Samer Attallah, Din, Jamilah, Atan, Rodziah

“…It can be extended to support generating CSP for contents that are modified by JavaScript after loading. Current approach inspects the static contents of URLs.…”
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Radar - Acoustic Vehicle Classification System based on shallow Convolutional Neural Network by Yasmin, Aida

“…The proposed multimodal SCNN achieved a maximum classification accuracy of 96.7% with a 1-second time window, 128x 128 spectrogram, and late-fusion concatenation. …”
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Deep learning object detector using a combination of Convolutional Neural Network (CNN) architecture (MiniVGGNet) and classic object detection algorithm by Ismail, Asmida, Ahmad, Siti Anom, Che Soh, Azura, Hassan, Mohd Khair, Harith, Hazreen Haizi

“…MiniVGGNet is an architecture network used to train an object classification, and the data used for this purpose was collected from specific indoor environment building. …”
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Direct least squares fitting of ellipses segmentation and prioritized rules classification for curve-shaped chart patterns by Lei, I. L., Teh, Phoey Lee *, Si, Yain-Whar

“…To further enhance the efficiency of classifying chart patterns from real-time streaming data, we propose a novel algorithm called Accelerating Classification with Prioritized Rules (ACPR). …”
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Enhanced AI-based anomaly detection method in the intrusion detection system (IDS) / Kayvan Atefi by Atefi, Kayvan

“…This strategy includes a number of components that are a novel approach to clustering generation. In fact a data clustering method is proposed consisting of separate outputs: (i) To select a relevant subset of original features based on our proposed algorithm; which is Enhanced Binary Particle swarm Optimization (EBPSO), (ii) To mine data using various data chunks (windows) and overcome a failure of single clustering. …”
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Adaptive multi-parent crossover GA for feature optimization in epileptic seizure identification by Al-Sharhan, Salah, Bimba, Andrew

“…It encodes the temporal and spatial filter estimates and optimize the feature selection with respect to the classification error. The classification was done using a Support Vector Machine (SVM). …”
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The identification of oreochromis niloticus feeding behaviour through the integration of photoelectric sensor and logistic regression classifier by Mohamad Radzi, Mohd Sojak, Mohd Azraai, Mohd Razman, Anwar, P. P. Abdul Majeed, Rabiu Muazu, Musa, Ahmad Shahrizan, Abdul Ghani, Ismed, Iskandar

“…It was shown that the LR model is able to yield a classification accuracy for tested data during the day at three dif- ferent time windows (4 hours each) is 100%, 88.7% and 100%, respectively, whilst the for-night data it was shown to demonstrate 100% classification accu- racy.…”
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Intelligent motion planning of a mobile robot by using convolutional neural network / Siti Asmah Abdullah by Siti Asmah, Abdullah

“…Several algorithms are used to create the Windowing Grid in capturing the informative and relevant current position of the mobile robot. …”
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Intelligent Fuzzy Classifier for Pre-Seizure Detection from Real Epileptic Data by Shakir, Mohamed, Malik, Aamir Saeed, Kamel, Nidal S., Qidwai, Uvais

“…In this paper, a classification method is presented using an Fuzzy Inference Engine to detect the incidences of preseizures in real/raw Epilepsy data. …”
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Intelligent Fuzzy Classifier for pre-seizure detection from real epileptic data by Shakir, M., Malik, A.S., Kamel, N., Qidwai, U.

“…In this paper, a classification method is presented using an Fuzzy Inference Engine to detect the incidences of pre-seizures in real/raw Epilepsy data. …”
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