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Cloud Worm Detection and Response Technique By Integrating The Enhanced Genetic Algorithm An Threat Level by Hasan Mahmoud Sha'ban Kanaker

REAL TIME ABNORMAL SOUND DETECTION AND CLASSIFICATION FOR HOME ENVIRONMENT by MOHAMED AMIN, SITI NUR AZIMAH

“…In this project, a system is designed to have abnormal sound detection and classification. For abnormal sound detection, mean signal approach being used while for classification process, there two main methods being used which are features extraction using Mel-Frequency Cepstral Coefficient (MFCC) and classifier using Gaussian Mixture Model (GMM). …”
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POWER QUALITY CLASSIFICATION WITH DE-NOISING SCHEME USING WAVELET TRANSFORM AND RULE- BASED METHOD by HENG KEOW, CHUAH

“…A comparative study with Probabilistic Neural Network system has proved that the proposed system is better because it needs less memory space and shorter code execution time. Thus it is a suitable model to be used in real time implementation through a Digital Signal Processor (DSP)- based embedded system for power quality disturbances detection and classification.…”
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Learner’s emotion prediction using production rules classification algorithm through brain computer interface tool by Nurshafiqa Saffah, Mohd Sharif

“…From the data analysis using WEKA software, the production rules classifier (PART) is found to be the most accurate classification algorithm in classifying the emotion which yields the highest precision percentage of 99.6% compared to J48 (99.5%) and Naïve Bayes (96.2%). …”
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Malay festive seasons food recognition for calorie detection / Nurul Hafiza Basiruddin by Basiruddin, Nurul Hafiza

“…Then the result from the Color Feature Extraction Method is used to identify the type of food by using Error-Correcting Output Codes (ECOC) classification which is the part of the Support Vector Machine (SVM) algorithm. …”
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Malay festive seasons food recognition for calorie detection using SVM and ECOC approaches / Nurul Hafiza Binti Basiruddin, Zalikha Zulkifli and Samsiah Ahmad by Basiruddin, Nurul Hafiza, Zulkifli, Zalikha, Ahmad, Samsiah

“…Then the result from the Color Feature Extraction Method is used to identify the type of food by using Error-Correcting Output Codes (ECOC) classification, which is part of the Support Vector Machine (SVM) algorithm. …”
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Android Malware classification using static code analysis and Apriori algorithm improved with particle swarm optimization by Adebayo, Olawale Surajudeen, Abdul Aziz, Normaziah

“…In this method, features were extracted from Android applications byte-code through static code analysis, selected and were used to train supervised classifiers. …”
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Static code analysis of permission-based features for android malware classification using apriori algorithm with particle swarm optimization by Adebayo, Olawale Surajudeen, Abdul Aziz, Normaziah

“…However, supervised learning technique has limitations for malware classification task. This paper presents a classification approach on android malware using candidate detectors generated from an unsupervised association rule of Apriori Algorithm. …”
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Network Traffic Classification Analysis on Differentiated Services Code Point Using Deep Learning Models for Efficient Deep Packet Inspection by Ahmed Khan, Fazeel, Abubakar, Adamu

“…This study develops and analyze using neural network-based models for effective classification of data packets using the DSCP header field. …”
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Source code classification using latent semantic indexing with structural and frequency term weighting by Yusof, Yuhanis, Alhersh, Taha, Mahmuddin, Massudi, Mohamed Din, Aniza

“…Furthermore,it is also learned that the use of structural information in the weighting scheme contribute to a better classification.…”
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Image classification based on sparse-coded features using sparse coding technique for aerial imagery: a hybrid dictionary approach by Qayyum A., Saeed Malik A., Saad N.M., Iqbal M., Abdullah M.F., Rasheed W., Abdullah T.A.B.R., Bin Jafaar M.Y.

Algorithm enhancement for host-based intrusion detection system using discriminant analysis by Dahlan, Dahliyusmanto

“…Algorithms for building detection models are usually classified into two categories: misuse detection and anomaly detection. …”
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Chain coding and pre processing stages of handwritten character image file by Suliman, Azizah, Sulaiman, Md. Nasir, Othman, Mohamed, O. K. Rahmat, Rahmita Wirza

“…This paper discusses in detail some of the algorithms used in the pre-processing stages of an offline handwritten character image file. …”
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A study on advanced statistical analysis for network anomaly detection by Ngadi, Md. Asri, Idris, Mohd. Yazid, Abdullah, Abd. Hanan

“…Algorithms for building detection models are usually classified into two categories: misuse detection and anomaly detection. …”
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Scene classification for aerial images based on CNN using sparse coding technique by Qayyum, A., Malik, A.S., Saad, N.M., Iqbal, M., Faris Abdullah, M., Rasheed, W., Rashid Abdullah, T.A., Bin Jafaar, M.Y.

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SEDF: a spoofed email detection framework employed by a lightweight web browser plug-in for detecting the spoofed email / Al Ya@Geogiana Buja...[et al.] by Buja, Al Ya@Geogiana, Ahmad, Illiasaak, Zolkeply, Mohd Syafiq

“…The method used to detect fake e-mail is by tracing back the email header. …”
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Phishing attack detection using machine learning method by Jupin, John Arthur

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Content adaptive fast motion estimation based on spatio-temporal homogeneity analysis and motion classification by Nisar, Humaira, Malik, Aamir Saeed, Choi, Tae-Sun

“…This is the basis of the proposed algorithm. The proposed algorithm involves a multistage approach that includes motion vector prediction and motion classification using the characteristics of video sequences. …”
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Scene classification for aerial images based on CNN using sparse coding technique by Qayyum A., Malik A.S., Saad N.M., Iqbal M., Faris Abdullah M., Rasheed W., Rashid Abdullah T.A., Bin Jafaar M.Y.

Crow Search Freeman Chain Code (CS-FCC) feature extraction algorithm for handwritten character recognition by Muhammad Arif, Mohamad, Zalili, Musa, Amelia Ritahani, Ismail

“…The algorithm experiments are carried out using the chain code representation created from previous research of the Centre of Excellence for Document Analysis and Recognition (CEDAR) dataset, which consists of 126 upper-case letter characters. …”
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