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  1. 1
    DEVELOPMENT AND TESTING OF UNIVERSAL PRESSURE DROP MODELS IN PIPELINES USING ABDUCTIVE AND ARTIFICIAL NEURAL NETWORKS

    DEVELOPMENT AND TESTING OF UNIVERSAL PRESSURE DROP MODELS IN PIPELINES USING ABDUCTIVE AND ARTIFICIAL NEURAL NETWORKS by AYOUB MOHAMMED, MOHAMMED ABDALLA

    Published 2011
    “…It was found that (by the Group Method of Data Handling algorithm), length of the pipe, wellhead pressure, and angle of inclination have a pronounced effect on the pressure drop estimation under these conditions. …”
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  2. 2
    A lightweight graph-based pattern recognition scheme in mobile ad hoc networks.

    A lightweight graph-based pattern recognition scheme in mobile ad hoc networks. by Raja Mahmood, Raja Azlina, Muhamad Amin, Anang Hudaya, Amir, Amiza, Khan, Asad I.

    Published 2012
    “…This paper discusses the operations of the proposed three stage cooperative IDS in detecting packet drop attacks. The comparison study between DGHN and the iterative, highly computational self organizing map (SOM) is also reviewed. …”
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  3. 3
    Machine Learning Based Detection for Compromised Accounts on Social Media Networks

    Machine Learning Based Detection for Compromised Accounts on Social Media Networks by K., Swapna, M., Rithika, K., Rukmini, S., Swachitha, Y., Komali

    Published 2025
    “…Behavioral features include changes in posting frequency, interaction patterns, and location data. We employ machine learning algorithms to train models that can accurately classify accounts as compromised or legitimate based on these features. …”
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  4. 4
    End to end performance analysis over IP RAN network / Armi Shahran Mohamad

    End to end performance analysis over IP RAN network / Armi Shahran Mohamad by Mohamad, Armi Shahran

    Published 2011
    “…The expected result from the test experiment is able to produce set of information such as uplink and downlink duration time, throughput downlink pattern comparison, bytes received comparison and data transfer time taken. …”
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  5. 5
    Simulation performance comparison of A*, GLS, RRT and PRM path planning algorithms

    Simulation performance comparison of A*, GLS, RRT and PRM path planning algorithms by Muhammad, Aisha, Nor Rul Hasma, Abdullah, Mohammad A.H., Ali, Shanono, Ibrahim Haruna, Rosdiyana, Samad

    Published 2022
    “…In this study, four robust path planning algorithms, namely: Probabilistic Roadmaps (PRMs), A-star, the Rapidly Exploring Random Trees (RRTs), and Generalized Laser Simulator (GLS), were simulated and their performance was measured and compared according to the total path distance covered, search time and path smoothness. …”
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  6. 6
    A generalized laser simulator algorithm for optimal path planning in constraints environment

    A generalized laser simulator algorithm for optimal path planning in constraints environment by Aisha, Muhammad

    Published 2022
    “…The suggested algorithm outperforms the competition in terms of improving path cost, smoothness, and search time. …”
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  7. 7
    A Scalable Algorithm for Constructing Frequent Pattern Tree

    A Scalable Algorithm for Constructing Frequent Pattern Tree by Noraziah, Ahmad, Herawan, Tutut, Zailani, Abdullah, Mustafa, Mat Deris

    Published 2014
    “…Frequent Pattern Tree (FP-Tree) is a compact data structure of representing frequent itemsets. …”
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  8. 8
    Scheduling of batch process plant / Abdul Aziz Abu Bakar

    Scheduling of batch process plant / Abdul Aziz Abu Bakar by Abu Bakar, Abdul Aziz

    Published 1995
    “…Batch production is used throughout the process industries for the manufacture of fine chemical, plastics, pharmaceuticals, paints, ceramics, cosmetics, or whatever production quantities are small, product value is very high or product demand pattern is changeable. This research work is devoted to software development of scheduling and control algorithm of batch process plant using shortest path method developed by Dijkstra and K* shortest path method developed by Jin Y. …”
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  9. 9
    An empirical study of pattern leakage impact during data preprocessing on machine learning-based intrusion detection models reliability

    An empirical study of pattern leakage impact during data preprocessing on machine learning-based intrusion detection models reliability by Bouke, Mohamed Aly, Abdullah, Azizol

    Published 2023
    “…Additionally, we find that some algorithms are more sensitive to data leakage than others, as seen by the drop in model accuracy when built without leakage. …”
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  10. 10
    Hybrid model to improve the river streamflow forecasting utilizing multi-layer perceptron-based intelligent water drop optimization algorithm

    Hybrid model to improve the river streamflow forecasting utilizing multi-layer perceptron-based intelligent water drop optimization algorithm by Pham Q.B., Afan H.A., Mohammadi B., Ahmed A.N., Linh N.T.T., Vo N.D., Moazenzadeh R., Yu P.-S., El-Shafie A.

    Published 2023
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  11. 11
    Rain streak removal using emboss and spatial-temporal depth filtering technique in video keyframes

    Rain streak removal using emboss and spatial-temporal depth filtering technique in video keyframes by Shariah, Sawsan Kamel

    Published 2012
    “…Each drop when falling in high speed will create a streak motion blurred illusion based on the background intensity that reflects the environment creating higher intensity pattern in an image. …”
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  12. 12
    Feature extraction: hand shape, hand position and hand trajectory path

    Feature extraction: hand shape, hand position and hand trajectory path by Bilal, Sara Mohammed Osman Saleh, Akmeliawati, Rini

    Published 2011
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  13. 13
    Animal voice recognition for identification (ID) detection system

    Animal voice recognition for identification (ID) detection system by Yeo, Che Yong, Syed Mohamed, Syed Abdul Rahman Al-Haddad, Ng, Chee Kyun

    Published 2011
    “…In this paper, an animal identification (ID) detection system based on animal voice pattern recognition algorithm has been developed. …”
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  14. 14
    Dog voice identification (ID) for detection system

    Dog voice identification (ID) for detection system by Yeo, Che Yong, Syed Mohamed, Syed Abdul Rahman Al-Haddad, Ng, Chee Kyun

    Published 2012
    “…In this paper, an animal identification (ID) detection system based on animal voice pattern recognition algorithm has been developed. …”
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  15. 15
    Development of behavior-based reactive navigation system for mobile robot

    Development of behavior-based reactive navigation system for mobile robot by Mohd Hamami, Mohd Ghazali

    Published 2013
    “…The repeatability tests shown that the developed navigation algorithm able the robot to reach the target with the similar navigation path pattern outcome in each simulation tests. …”
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  16. 16
    A comparative sales forecast study between supervised and unsupervised learning algorithm on restaurant / Azhar Tamby

    A comparative sales forecast study between supervised and unsupervised learning algorithm on restaurant / Azhar Tamby by Tamby, Azhar

    Published 2006
    “…In this research, there are two algorithm of neural network will be used. It is coming from supervised and unsupervised learning algorithm. …”
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  17. 17
    Comparison between Lamarckian Evolution and Baldwin Evolution of neural network

    Comparison between Lamarckian Evolution and Baldwin Evolution of neural network by Taha, Imad, Inazy, Qabas

    Published 2006
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  18. 18
    Land Use Changes in Jeli, Kelantan

    Land Use Changes in Jeli, Kelantan by Muhammad Firdaus Abdul Karim

    Published 2013
    “…The highest dropped in forest area was in 2004 with a decrease of -0.76% from the year before. …”
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    Undergraduate Final Project Report
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  19. 19
    Ant colony algorithm for text classification in multicore-multithread environment / Ahmad Nazmi Fadzal

    Ant colony algorithm for text classification in multicore-multithread environment / Ahmad Nazmi Fadzal by Fadzal, Ahmad Nazmi

    Published 2017
    “…Pheromone concept is the main criterion that distinguish ACO to other algorithms. Based on the concept, pheromone saturation is used to combine stackable solution pattern that is discovered while straying to different term node to build a path. …”
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  20. 20
    Destination prediction based on past movement history

    Destination prediction based on past movement history by Waheed, Mihsaan

    Published 2020
    “…Matching of the history with the user's movement is done through a simple pattern recognition technique. The system includes an algorithm that simulates incoming data from a user and matches on a window by window basis to the history. …”
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