Search Results - (( java application optimization algorithm ) OR ( learning usage classification algorithm ))

A New Mobile Botnet Classification based on Permission and API Calls by Yusof, M, Saudi, MM, Ridzuan, F

“…As a result, 16 permissions and 31 API calls that are most related with mobile botnet have been extracted using feature selection and later classified and tested using machine learning algorithms. The experimental result shows that the Random Forest Algorithm has achieved the highest detection accuracy of 99.4% with the lowest false positive rate of 16.1% as compared to other machine learning algorithms. …”

BFEDroid: A Feature Selection Technique to Detect Malware in Android Apps Using Machine Learning by Chimeleze C., Jamil N., Ismail R., Lam K.-Y., Teh J.S., Samual J., Akachukwu Okeke C.

“…Android (operating system); Android malware; Classification (of information); Feature Selection; Learning systems; Mobile security; Android apps; Classification models; Feature weight; Features selection; Machine learning algorithms; Machine-learning; Malware detection; Malwares; Memory usage; Selection techniques; Learning algorithms…”

A new mobile botnet classification based on permission and API calls by Yusof M., Madihah Mohd Saudi, Farida Hazwani Mohd Ridzuan

Particle swarm optimization for neural network learning enhancement by Abdull Hamed, Haza Nuzly

“…In this study, the latest optimization algorithm, Particle Swarm Optimization (PSO) is chosen and applied in feedforward neural network to enhance the learning process in terms of convergence rate and classification accuracy. …”
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Optimization of blood vessel detection in retina images using multithreading and native code for portable devices by Tran, Duc Ngoc, Hussin, Fawnizu Azmadi, Yusoff, Mohd Zuki

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Performance evaluation of real-time multiprocessor scheduling algorithms by Alhussian, H., Zakaria, N., Abdulkadir, S.J., Fageeri, S.O.

“…These results suggests that optimal algorithms may turn to be non-optimal when practically implemented, unlike USG which reveals far less scheduling overhead and hence could be practically implemented in real-world applications. …”
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Automated system for concrete damage classification identification using various classification techniques in machine learning / Nur Haziqah Mat ... [et al.] by Mat, Nur Haziqah, Ahmad Zahida, Athifa Aisha, Abdul Malik, Siti Nurhaliza, Azmadi, Nur Athirah Syuhada, Senin, Syahrul Fithry

“…This invention can recognize a certain damage while the classification of defects is classified according to the features extracted from the images by using GLCM algorithm. …”
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Design of a pattern classification system using extreme learning machine by Sakthivel Thangavelu

A COLLABORATIVE FRAMEWORK FOR ANDROID MALWARE IDENTIFICATION USING DYNAMIC ANALYSIS by Thayaaleni, Rajandran

“…Lastly, the classification result is generated. The proposed project will extract the features of system calls, network packets, CPU usage and battery usage of the application. …”
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Route Optimization System by Zulkifli, Abdul Hayy

“…After much research into the many algorithms available, and considering some, including Genetic Algorithm (GA), the author selected Dijkstra's Algorithm (DA). …”
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Development and usage of self-organising maps in high energy physics analysis with high performance computing / Mohd Adli Md Ali by Mohd Adli , Md Ali

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Diabetes Diagnosis And Level Of Care Fuzzy Rule-Based Model Utilizing Supervised Machine Learning For Classification And Prediction by Mohd Aris, Teh Noranis, Abu Bakar, Azuraliza, Mahiddin, Normadiah, Zolkepli, Maslina

“…Most computer applications use machine learning and data mining techniques to aid classification and prediction of a disease. …”
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Design of a pattern classification system using extreme learning machine by Sakthivel Thangavelu

Automatic Number Plate Recognition on android platform: With some Java code excerpts by ., Abdul Mutholib, Gunawan, Teddy Surya, Kartiwi, Mira

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A novel framework for potato leaf disease detection using an efficient deep learning model by Mahum, R., Munir, H., Mughal, Z.-U.-N., Awais, M., Sher Khan, F., Saqlain, M., Mahamad, S., Tlili, I.

“…Thus, an accurate automated technique for timely detection and classification is needed to cope with the aforementioned challenges.There exist techniques grounded on machine learning and deep learning procedures that use the existing dataset i.e., â��The Plant Village Datasetâ�� and perform classification into only two classes in potato leaves. …”
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A novel framework for potato leaf disease detection using an efficient deep learning model by Mahum, R., Munir, H., Mughal, Z.-U.-N., Awais, M., Sher Khan, F., Saqlain, M., Mahamad, S., Tlili, I.

“…Thus, an accurate automated technique for timely detection and classification is needed to cope with the aforementioned challenges.There exist techniques grounded on machine learning and deep learning procedures that use the existing dataset i.e., â��The Plant Village Datasetâ�� and perform classification into only two classes in potato leaves. …”
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Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection by Nwogbaga, Nweso Emmanuel, Latip, Rohaya, Affendey, Lilly Suriani, Abdul Rahiman, Amir Rizaan

“…Enhance hybrid genetic algorithm and particle Swarm optimization are developed to select the optimal device in either fog or cloud. …”
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Automated feature selection using boruta algorithm to detect mobile malware by Che Akmal, Che Yahaya, Ahmad Firdaus, Zainal Abidin, Salwana, Mohamad, Ernawan, Ferda, Mohd Faizal, Ab Razak

“…Boruta algorithm is used to select features automatically for assisting the machine learning. …”
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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. …”
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Differential evolution for neural networks learning enhancement by Ismail Wdaa, Abdul Sttar

“…In this study, DE is chosen and applied to feed forward neural network to enhance the learning process and the network learning is validated in terms of convergence rate and classification accuracy. …”
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