Search Results - machine ((((learning programming) OR (learning problems))) OR (learning program))

Different mutation and crossover set of genetic programming in an automated machine learning by Masrom, S., Mohamad, M., Hatim, S.M., Baharun, N., Omar, N., Abd. Rahman, A.S.

“…One of the progressing works for automated machine learning improvement is the inclusion of evolutionary algorithm such as Genetic Programming. …”
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Different mutation and crossover set of genetic programming in an automated machine learning by Masrom, S., Mohamad, M., Hatim, S.M., Baharun, N., Omar, N., Abd. Rahman, A.S.

“…One of the progressing works for automated machine learning improvement is the inclusion of evolutionary algorithm such as Genetic Programming. …”
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Teaching and learning via chatbots with immersive and machine learning capabilities by Nantha Kumar Subramaniam

“…Each of these chatbots focuses on different programming concepts or constructs. These chatbots support learning of Java via problem-solving steps through “learning by doing”. …”
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Rapid software framework for the implementation of machine learning classification models by Rahman, A.S.A., Masrom, S., Rahman, R.A., Ibrahim, R.

“…Reseachers have acknowledged that machine learning is useful to be utilized in many different domains of complex real life problem. …”
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Measuring GPU-accelerated parallel SVM performance using large datasets for multi-class machine learning problem by Sulaiman M.A.H.B., Suliman A., Ahmad A.R.

“…Artificial intelligence; Computer graphics; Computer graphics equipment; Data mining; Learning systems; Parallel processing systems; Program processors; Quadratic programming; Computational time; GPU-accelerated; Graphics Processing Unit; Machine learning problem; Performance measurements; Real-time forecasting; Support vector machine (SVMs); Viable solutions; Support vector machines…”

Novice programmers’ emotion and competency assessments using machine learning on physiological data / Fatima Jannat by Fatima, Jannat

“…There is also growing interest in modeling machine learning and deep learning algorithms that can learn from user’s data, understand and react to that individual’s affective state. …”
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An overview on common mistakes by students for introduction, basic elements and selection control structure in Fundamentals of Computer Problem Solving (CSC128) course / Naemah Abd... by Abdul Wahab, Naemah, Wan Mohammad, Wan Anisha, Mohd Mydin, Azlina Mohd Mydin

“…According to Robins et. al (2003), they stated that du Boulay (1989) describe five domains that a novice programmers must mastered in learning programming are the general orientation of a program, the notational machine model, the notation of a programming language, programming structures and pragmatics In view of the above research on the key aspects of learning to program, the following section will discuss on the background of computer problem solving course that is offered in our university to a non-major of computer course learners, what are the common mistakes that these novice programmers done according to the first three chapters in our syllabus and a summarisation of suggestion for the learners to ponder.…”
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Common mistakes in writing basic elements of C++ programming for dummies / Syarifah Adilah Mohamed Yusoff, Rozita Kadar and Saiful Nizam Warris by Mohamed Yusoff, Syarifah Adilah, Kadar, Rozita, Warris, Saiful Nizam

“…All of the students are categories as novice programmers due to has no official learning both in programming and computer essential. …”
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Applying machine learning using Case-Based Reasoning (CBR) and Rule-Based Reasoning (RBR) approaches to object-oriented application framework documentation by Jani H.M., Peck L.S.

“…We have studied various documenting approaches and concluded that the current approaches are not very effective in overcoming the above challenges, especially on the efficiency problem. So, in this paper we are going to apply machine learning using case-based reasoning (CBR) and rule-based reasoning (RBR) to framework documentation. …”

Convergence of meta-controlled Boltzmann machine and its application for bilevel programming problem by Nishiigami, Wataru, Watada, Junzo, Prof. Dr., Shamshul Bahar, Yakoob, Assoc. Prof. Dr.

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Designing story card in extreme programming using machine learning technique by Yasin, Azman, Gaber, Shamsan, Omar, Mazni, Mohd, Haslina, Baharom, Fauziah, Md Din, Marina

“…Story card is one of the software development artifacts that can be used to gather requirements in extreme programming (XP).It can assists developers to translate and develop the system based on activities and rules stated in the story card.However, conventional XP story card framework or template is not well defined and only supports requirements in two or three sentences.It also does not states any information rather than system functionality.This may lead to conflicts, missing, and ambiguous requirements.In order to overcome this problem, Machine Learning is one of the techniques that can be used to extract the content from the list of requirements and produce the story cards based on the priority and rules of requirements.Thus, this study aims to to propose a new technique of designing story cards based on user requirements.The finding from the study is a conceptual model of designing story cards using machine learning technique.Future research will investigate how the technique adapt with the iterative changes of the requirements.…”
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PLC-based water filling machine simulator for teaching and learning activities / Kamaru Adzha Kadiran … [et al.] by Kadiran, Kamaru Adzha, Rifin, Rozi, Hussin, Mohamad Zhafran, Mat Saat, Ezril Hisham

“…The Omron PLC-Based Water Filling Machine Simulator has demonstrated remarkable success in enhancing teaching and learning activities in industrial automation. …”
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PLC-based water filling machine simulator for teaching and learning activities / Kamaru Adzha Kadiran … [et al.] by Kadiran, Kamaru Adzha, Rifin, Rozi, Hussin, Mohamad Zhafran, Mat Saat, Ezril Hisham

“…The Omron PLC-Based Water Filling Machine Simulator has demonstrated remarkable success in enhancing teaching and learning activities in industrial automation. …”
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Programming learning style recommendation using fuzzy logic / Nur Fadhilah Ain Susen by Susen, Nur Fadhilah Ain

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Impact learning: A learning method from feature's impact and competition by Prottasha, Nusrat Jahan, Murad, Saydul Akbar, Abu Jafar, Md Muzahid, Rana, Masud, Kowsher, Md, Adhikary, Apurba, Biswas, Sujit, Bairagi, Anupam Kumar

“…This paper introduced a new machine learning algorithm called impact learning. …”
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Educational learning: E-Java chatbot using rule-based technique / Siti Hawa Mad Daud by Mad Daud, Siti Hawa

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Impact learning : A learning method from feature’s impact and competition by Prottasha, Nusrat Jahan, Murad, Saydul Akbar, Abu Jafar, Md Muzahid, Rana, Masud, Kowsher, Md, Adhikary, Apurba, Biswas, Sujit, Bairagi, Anupam Kumar

“…This paper introduced a new machine learning algorithm called impact learning. …”
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Banana recognition system using convolutional neural network / Mohamad Shafiq Rosli by Rosli, Mohamad Shafiq

“…With the rise of mobile technology and internet access, recent development in machine learning have designed many algorithms to solve diverse human problems. …”
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Impact learning: A learning method from feature’s impact and competition by Prottasha, Nusrat Jahan, Murad, Saydul Akbar, Muzahid, Abu Jafar Md, Rana, Masud, Kowsher, Md, Adhikary, Apurba, Biswas, Sujit, Bairagi, Anupam Kumar

“…This paper introduced a new machine learning algorithm called impact learning. …”
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A review on recent progress in machine learning and deep learning methods for cancer classification on gene expression data by Mazlan, A. U., Sahabudin, N. A., Remli, M. A., Ismail, N. S. N., Mohamad, M. S., Nies, H. W., Warif, N. B. A.

“…However, the most challenging task in predictive modeling is to construct a prediction model, which can be addressed using machine learning (ML) methods. The methods are used to learn and trained the model using a gene expression dataset without being programmed explicitly. …”
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