Search Results - (( mobile evaluation a algorithm ) OR ( based classification based algorithm ))

A New Mobile Malware Classification for SMS Exploitation by Zaizi, NJM, Khailani, A, Madihah Mohd Saudi

A new mobile malware classification for SMS exploitation by Zaizi N.J.M., Khailani A., Madihah Mohd Saudi

“…Dynamic analysis was used to extract the system calls from each application in a controlled lab environment. This research has developed a new mobile malware classification for Android smartphone using a covering algorithm. …”

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

“…The fourth stage is to design evaluation methodology of Max-Min Rule-Based Classification Algorithm using classifier model. …”
Get full text
Get full text

Maldroid- attribute selection analysis for malware classification by Rahiwan Nazar, Romli, Mohamad Fadli, Zolkipli, Mohd Zamri, Osman

“…The experiment evaluated 8000 real data samples and the result showed that InfoGainEval and KNN algorithm are the most selected in attribute selection and classification process.…”
Get full text
Get full text
Get full text

A new system call classification of mobile malwares for SMS exploitation by Zaizi N.J.M., Madihah Mohd Saudi

The classification of wink-based eeg signals by means of transfer learning models by Jothi Letchumy, Mahendra Kumar

“…Whilst it was observed that the optimized k-NN model based on the aforesaid pipeline could achieve a classification accuracy of 100% for the training, validation, and tes t data. …”
Get full text
Get full text

A new mobile malware classification for call log exploitation by Madihah Mohd Saudi, Nurlida Basir, Mohd N.F.

“myHerbs”: A mobile based application for herbal leaf recognition using sift / Nur Nabilah Abu Mangshor …[et al.] by Abu Mangshor, Nur Nabilah, Abdul Rahman, Mohamed Al Arabee, Sabri, Nurbaity, Ibrahim, Shafaf, Ibrahim, Zaidah, Shari, Anis Amilah

“…In addition, it also contributes to the exploration and implementation of learning algorithm in mobile-based application.…”
Get full text
Get full text
Get full text

Convolutional neural network based mobile application for poisonous mushroom detection by Amirul, Shazlin Nizam, Mohd Sabri, Norlina, Gloria, Jennis Tan, Redwan, Nurul Ainina, Zhiping, Zhang

“…The application leverages a Convolutional Neural Network (CNN) algorithm to accurately classify mushrooms based on user-submitted images. …”
Get full text
Get full text
Get full text

Mental stress classification based on selected EEG channels using Correlation Coefficient of Hjorth Parameters by Hag, Ala, Fares, Al-Shargie, Handayani, Dini Oktarina Dwi, Houshyar, Asadi

“…These findings strongly indicate that the CCHP algorithm shows great promise in the design of a wearable application for mental stress detection, utilizing a minimal number of EEG channels.…”
Get full text
Get full text
Get full text
Get full text
Get full text

Hybrid intelligent approach for network intrusion detection by Al-Mohammed, Wael Hasan Ali

“…Due to the prevailing limitations of finding novel attacks, high false detection, and accuracy in previous intrusion detection approaches, this study has proposed a hybrid intelligent approach for network intrusion detection based on k-means clustering algorithm and support vector machine classification algorithm. …”
Get full text
Get full text
Get full text

Classification for Quran authentication using characters and diacritics hashed values by Farida Hazwani Mohd Ridzuan, Madihah Mohd Saudi, Shirzad Z., Azni A.H.

Reverse migration prediction model based on machine learning / Azreen Anuar by Anuar, Azreen

“…In addition, the results from the three (3) algorithms that were tested showed that Random Forest outperforms other algorithms by acquiring an accuracy and classification error to predict reverse migration. …”
Get full text
Get full text

ios Mobile Malware Deep Analysis And Classification For Social Media And Online Banking Exploitation by Muhammad ‘Afif Bin Husainiamer

Development of a new robust hybrid automata algorithm based on surface electromyography (SEMG) signal for instrumented wheelchair control by Mohd Hanafi, Muhammad Sidik

“…Based on algorithm evaluation, it shows that one control method couldn’t fit to all persons as per proven in method selection experiment. …”
Get full text
Get full text

A wheelchair sitting posture detection system using pressure sensors by Mohamad Yusoff, Muhammad Annuar Alhadi, Azmi, Nur Liyana, Nordin, Nor Hidayati Diyana

“…All the classification algorithms were evaluated by using the k-fold cross validation method. …”
Get full text
Get full text
Get full text
Get full text
Get full text

Image classification of Aedes mosquitoes using transfer learning / Zetty Ilham Abdullah by Abdullah, Zetty Ilham

“…With roughly 3,500 distinct species of mosquitoes on the planet today, classification is a time-consuming and difficult operation. …”
Get full text
Get full text

The use of artificial neural network in the classification of EMG signals by Ahsan, Md. Rezwanul, Ibrahimy, Muhammad Ibn, Khalifa, Othman Omran

“…A back-propagation neural network with Levenberg-Marquardt training algorithm has been employed for the classification of EMG signals. …”
Get full text
Get full text
Get full text

Performance evaluation for compression-accuracy trade-off using compressive sensing for EEG-based epileptic seizure detection in wireless tele-monitoring by Abualsaud, Khalid, Mahmuddin, Massudi, Hussein, Ramy, Mohamed, Amr

“…DCT is combined with the best basis function neural networks for EEG signals classification.Extensive experimental work is conducted, utilizing four classification models.The obtained results show an improvement in classification accuracies and an optimal classification rate of about 95% is achieved when using NN classifier at 85% of CR in the case of no SNR value.The satisfying results demonstrate the effect of efficient compression on maximizing the sensor lifetime without affecting the application’s accuracy.…”
Get full text
Get full text
Get full text

Human activity and posture classification using smartphone sensors and Matlab mobile by Jamian, Syahirah, Gunawan, Teddy Surya, Kartiwi, Mira, Ahmad, Robiah, Kadir, Kushairy, Nordin, Muhammad Noor

“…Activity recognition has been used in various ways as technology has advanced, particularly using a smartphone-based approach. This work aims to evaluate the accuracy of the triaxial accelerometer in the Matlab Mobile and examine the development and performance of the algorithms in identifying human motions on individuals of similar ages and physical appearances. …”
Get full text
Get full text
Get full text
Get full text