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1st International Conference on Applied computing Research to Support Industry: Innovation and technology, ACRIT 2019

作者： Basori, Ahmad Hoirul Mansur, Andi Besse Firdausiah Riskiawan, Hendra Yufit Faculty of Computing and Information Technology Rabigh King Abdulaziz University RabighMakkah21911 Saudi Arabia Information Technology Department Politeknik Negeri Jember PO BOX 164 Mastrip Jember Indonesia

ISBN: (纸本)9783030387518

Plant disease can become a serious threat toward food production and security since the demand for food increased significantly over the year. The big data and deep learning have been discussed and explored highly in recent years due to its capability to detect certain features in smart ways. Whilst, crop disease that attack leaves can be cured if farmer detects the early symptoms and avoid the spreading of the disease. This paper presents the capability of big data and deep learning to give predictive analytic toward the plant crop disease. Some features such as leaves, weather, soil and other landscapes condition are taken as an input for the system. Smart farming will utilize IoT technology on capturing the data and localize the position of the infected plant. The combination of computer vision and GPS technology will be able to pinpoint the disease location in efficient ways. The experimental result has shown that deep learning is superior compare to logistic regression with 72% accuracy of identification of an infected leaf. Of course, this result can be augmented further by involving the extra of the leaf. Overall, the Smart Farming framework is able to give a better solution for plant disease spreading prevention by early detection and localization of the disease. A farmer might get advantage by this notification, especially for wide-scale farming. The future work might involve real-time data from the drone or CCTV camera in the real farming field. © 2020, Springer Nature Switzerland AG.

关键词： Big data

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Using Speech Recognition in Learning Primary School Mathematics via Explain, Instruct and Facilitate Techniques

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Journal of Software Engineering and Applications 2014年第4期7卷 233-255页

作者： Ab Rahman Ahmad Sami M. Halawani Samir K. Boucetta Faculty of Computing and Information Technology-Rabigh King Abdulaziz University Rabigh KSA

The application of information and Communication Technologies has transformed traditional Teaching and Learning in the past decade to computerized-based era. This evolution has resulted from the emergence of the digital system and has greatly impacted on the global education and socio-cultural development. Multimedia has been absorbed into the education sector for producing a new learning concept and a combination of educational and entertainment approach. This research is concerned with the application of Window Speech Recognition and Microsoft Visual Basic 2008 Integrated/Interactive Development Environment in Multimedia-Assisted Courseware prototype development for Primary School Mathematics contents, namely, single digits and the addition. The Teaching and Learning techniques—Explain, Instruct and Facilitate are proposed and these could be viewed as instructors’ centered strategy, instructors’—learners’ dual communication and learners' active participation. The prototype is called M-EIF and deployed only users' voices;hence the activation of Window Speech Recognition is required prior to a test run.

关键词： Explain Instruct and Facilitate Techniques Multimedia-Assisted Courseware Primary School Mathematics Visual Natural Language Window Speech Recognition

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An adaptive normalized google distance similarity measure for extractive text summarization 2

An adaptive normalized google distance similarity measure fo...

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2nd International Conference on Computer and information Sciences, ICCIS 2020

作者： Abuobieda, Albaraa Osman, Ahmed Hamza Faculty of Computer Studies International University of Africa Khartoum Sudan Faculty of Computing and Information Technology King Abdulaziz University Rabigh Saudi Arabia

ISBN: (纸本)9781728154671

No doubt, for each clustering algorithm running improper similarity calculation, that can lead to reduce the clustering accuracy. Hence, several applications that employ such algorithm are affected negatively and generate improper results. In a previous work, we found that employing the Normalized Google Distance (NGD) similarity measure to cluster document's sentences for text summarization problem is unreasonable;since NGD was basically designed to work with large databases. On the other hand, a term-weighting approach is used widely to define document's contents. In this paper, a term-weighting approach is integrated with the NGD similarity measure to adopt the latter from being able to work in small database (single document). Differential Evolution (DE) algorithm is used to train and test the proposed method. The DUC2002 dataset is preprocessed and used as a test bed. The results showed that our proposed method could outperform the previous work in terms of F-score evaluation measure as well as outperformed the standard baseline methods Microsoft Word and Copernic Summarizer. © 2020 IEEE.

关键词： Clustering algorithms

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RETRACTED ARTICLE: Contractor selection for maintenance in Small and Medium Industries using Analytical Hierarchy Process

RETRACTED ARTICLE: Contractor selection for maintenance in S...

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作者： Burhanuddin, M.A. Halawani, Sami M. Ahmad, A.R. Tahir, Zulkifli Faculty of Information and Communication Technology Technical University of Malaysia Melaka Ayer Keroh 75450 Melaka Malaysia Faculty of Computing and Information Technology King Abdul Aziz University Rabigh Saudi Arabia

ISBN: (纸本)9781424455386

The research based on the fact that the investment of information technology is needed for supporting daily operation and maintenance management in commonly industries. Although many models with varieties optimization and techniques have been proposed, there are limited actions to be linked into the actual industrial maintenance process. This paper introduce Analytical Hierarchical Process (AHP) method to provide important maintenance decision strategy for Small and Medium Industries (SMIs). The method is suitable for maintenance decision based on multiple maintenance criteria's and their alternatives. In case study, the maintenance contractor's selection problem have been demonstrated and the best decision result using maintenance decision support been achieved. The goal of this paper is to illustrate on how SMIs can use AHP to aid maintenance decision in the production plant. © 2010 IEEE.

关键词： Maintenance

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Estimation of Missing Values Using Hybrid Fuzzy Clustering Mean and Majority Vote for Microarray Data 16

Estimation of Missing Values Using Hybrid Fuzzy Clustering M...

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16th International Learning and technology Conference, L and T 2019

作者： Kumaran, Shamini Raja Othman, Mohd Shahizan Yusuf, Lizawati Mi Yunianta, Arda School of Computing Faculty Engineering Universiti Teknologi Malaysia Skudai Johor81310 Malaysia Faculty of Computing and Information Technology Rabigh King Abdulaziz University Jeddah Makkah Saudi Arabia

Rapid development in microarray experiments leads toward generating a large amount of genes expressions. Handling such a massive amount of gene expressions is a challenge using traditional methods especially multiple missing expression values exist. This article proposed a novel hybrid fuzzy clustering mean and majority vote to yield better performance. The proposed method will be evaluated with other three imputation methods and trained with four publicly available microarray datasets. The experimental results show that the proposed method has promising results that able to replace the missing data as well as achieves high accuracy rates and low root mean square error values. © 2019 The Authors. Published by Elsevier B.V.

关键词： Gene expression

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Map Clustering for Student Browsing Behaviour Analysis 16

Map Clustering for Student Browsing Behaviour Analysis

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16th International Learning and technology Conference, L and T 2019

作者： Ahmad, Nor Bahiah Alias, Umi Farhana Mohamad, Nadirah Yusof, Norazah School of Computing Faculty of Engineering Universiti Teknologi Malaysia Johor Bahru Johor81310 Malaysia Faculty of Computing and Information Technology King Abdulaziz University Rabigh21911 Saudi Arabia

Using e-learning as the learning platform provides flexibility to student to learn anywhere without limitation of time and space. Moodle, currently become one of the leading learning management system that deliver e-learning easily by providing customized tool for educators to deploy learning materials in various forms. The students behavior is important to be identified in order for educators to improve the teaching approach and to enhance the students performances. However, the flexibility in the learning environment cause student behaviour more challenging to be identified. In Moodle, the student's interactions and activities while learning online are captured in the log files. The data stored in the log files contain meaningful information such as the student behavior, their preferences and their knowledge level. In this study, the raw dataset captured in the log file undergo pre-processing phase such as data cleaning, transformation and selection to prepare the dataset for the analysis purposes. Principal Component Analysis (PCA) that is known for improvement of accuracy for unsupervised learning technique is used to identify the most significant features of students attributes from the log file. Course view, notes, exercises, examples and assignments are the features selected using PCA to be feed into Self-Organizing Map (SOM) in order to cluster students based on the behavior. The result shows that the technique is able to cluster the student browsing behavior using the total number of browsing frequency in 14 weeks study session, which form two cluster groups;high browsing behavior and low browsing behavior. The quality of SOM clustering technique is validated through the internal clustering evaluation and the results show that SOM produces better quality of cluster groups compared to k-mean and Partition Around Medoids (PAM). © 2019 The Authors. Published by Elsevier B.V.

关键词： Principal component analysis

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Interaction between sunlight and the sky colour with 3D objects in the outdoor virtual environment

Interaction between sunlight and the sky colour with 3D obje...

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Asia Modelling Symposium 2010: 4th International Conference on Mathematical Modelling and Computer Simulation, AMS2010

作者： Halawani, Sami M. Sunar, Mohd Shahrizal Faculty of Computing and Information Technology King Abdulaziz University Rabigh Saudi Arabia ViCubeLab Faculty of Computer Science and Information System Universiti Teknologi Malaysia Skudai Johor Malaysia

ISBN: (纸本)9780769540627

The sky has always been the crucial element in modeling the background of an outdoor scene. The position of the sun during the day gives a different impact on the sky colour. The sky colour indirectly affects the colour of the objects which were exposed to the lighting, such as the orangish red colour of the clouds seen during sunsets. Consequently, this study will emphasize on how to produce illuminated 3D objects based upon the effects of interaction between the sunlight and sky. A two-part program was developed for this study. The first part of the program concentrates on producing the correct sky colour depending on the position of the sun using Perez's function. The sky colour will be plotted on the sky dome which in turn will become a closed environment for the clouds. The interaction will occur in the second part of the program where the energy transfer in the dome environment with color of the sky as the main source illumination, resulting in the colour bleeding effect when using the radiosity approach. The result from this study is applicable to daylight modeling of building by showing the lighting effects from the sun and the sky. © 2010 IEEE.

关键词： Color

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IMars: Intelligent Municipality Augmented Reality Service for Efficient information Dissemination based on Deep Learning algorithm in Smart City of Jeddah 16

IMars: Intelligent Municipality Augmented Reality Service fo...

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16th International Learning and technology Conference, L and T 2019

作者： Basori, Ahmad Hoirul Abdul Hamid, Ahmad Luqman Bin Firdausiah Mansur, Andi Besse Yusof, Norazah Faculty of Computing and Information Technology Rabigh King Abdulaziz University Rabigh Makkah21911 Saudi Arabia Fakulti Sains Komputer Dan Matematik Universiti Teknologi Mara Segamat Johor Malaysia

A smart city is one of a huge transformation in these millennia, where it combines latest and advanced technology to overcome the daily basis problem of humans. Artificial intelligence with augmented reality has been highlighted as the potential solution along with IOT and another system to support the smart city system. The smarter Jeddah is part of Saudi Vision 2030 where Saudi government tends aims to transform this second biggest city in the kingdom to be a smart city with a ton of applications that connected with IOT and they can monitor people inside the city in real time. The proposed system focused on providing the resident of the Jeddah city with smart apps that can help them on conducting their daily basis activities (tourism) or even in an emergency situation. The geo-location data and other information will be used as a feeder for deep learning to make the system learn and getting smarter to disseminate information to the user based on their needs, location, emergency factors, etc. Resident can access the municipality public facilities such as Jeddah waterfront location and see what the event happens inside. They also can find the location of other attractive location such as Al-Fakieh aquarium and observe the content of aquarium facilities with virtual reality technology. In term of emergency cases: accident, car stopping and another incident;the proposed apps will be able to inform the police patrol nearby or nearest workshop for tyre or car workshop. This app is capable for wide range utilization to support program of the Ministry of Municipal and Rural Affairs to apprehend the smart city integrated application. The simulation test has confidently proved that deep learning algorithm overcome other classifier Naïve Bayes and Random forest with 67.5% recognition rate. The future work can be integrated with IOT sensor based system to enhance the municipality service in smart city. © 2019 The Authors. Published by Elsevier B.V.

关键词： Application programs

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Educational business intelligence framework visualizing significant features using metaheuristic algorithm and feature selection

Educational business intelligence framework visualizing sign...

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2019 International Conference on Advances in the Emerging computing Technologies, AECT 2019

作者： Kumaran, Shamini Raja Othman, Mohd Shahizan Yusuf, Lizawati Mi Yunianta, Arda Universiti Teknologi Malaysia Skudai 81310 School of Computing !!!Faculty of Engineering Johor Bahru Johor Malaysia King Abdulaziz University Faculty of Computing and Information Technology Rabigh Jeddah Saudi Arabia

ISBN: (纸本)9781728144528

Educational business intelligence concerns the decision-making in the education sector and this article intends to analyse the student's attributes' contribution toward graduating within the duration. In this research, the framework identifies the best set of attributes and evaluates the performance of the model with the help of 22 input features. This article discussed the development of the business intelligence (BI) framework for the higher education that is able to explore, analyse and visualize the relevant data into information. This is to assist the top management in improving the methodologies in teaching and learning. In this case study, the framework used metaheuristic algorithm, Ant Colony Optimization (ACO) technique mainly to identify the best set of attributes, and the performance was validated using Support Vector Machine (SVM). The framework consists of four layers which are data source, data integration, analytics, and access layers. In this study, 46, 658 input data were processed for the identification of postgraduate students who completed their studies within a specified period. The performance evaluation of the data achieved accuracy, sensitivity and precision of 87.44% for PhD dataset and t-test has been conducted to prove that the selected features are significant. Based on the findings, the results from the proposed educational business intelligence framework produced BI dashboard as an output from the framework is capable to act as a decision-making tool for education management and educational technology system. © 2020 IEEE.

关键词： Decision making

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Personalized Learning Model based on Deep Learning Algorithm for Student Behaviour Analytic

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Procedia Computer Science 2019年 163卷 125-133页

作者： Andi Besse Firdausiah Mansur Norazah Yusof Ahmad Hoirul Basori Faculty of Computing and Information Technology Rabigh King Abdulaziz University Rabigh Makkah 21911 Saudi Arabia

The learning processes are unique for each individual. Thus, the appropriate learning methods are essential to boost the student performance and success in their study. The current e-learning system is focusing on producing tools for collaborative study or facilitating the course for the discussion forum and direct communication such as chat service. However, the problem of boosting up individual achievements remains challenging. This paper proposed a personalized learning model to find suitable learning methods based on a deep learning algorithm. The factors of personalized learning such as adaptive, individualized, differentiated and competence-based learning have been taken into account when build and tested the model. These factors will act as a feeder for the network then it will be processed to identify which model of learning has the biggest chance on augmenting student achievement. The testing result has shown that the proposed model with deep learning approach has overcome other classifier with 72% success rate The model is believed to bring a great benefit for student and the teacher as well to manage the studying process more convenient for both parties.

关键词： Personalized based learning Deep Learning e-learning student achievement

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