Comparison New Algorithm Modified Euler Based on Harmonic-Polygon Approach for Solving Ordinary Differential Equation

There are many benefits to improve Euler scheme for solving the Ordinary Differential Equation problems. Among the benefits are simple implementation and low-cost computation. However, the problem of accuracy in the Euler scheme persuades scholar to use the complex method. Therefore, the main purpose of this research is to show the development of a new modified Euler scheme that improves the accuracy of the Polygon scheme in various step sizes. The implementation of the new scheme is by using the Polygon scheme and then Harmonic mean concept that is called the Harmonic-Polygon scheme. This Harmonic-Polygon scheme can provide new advantages more than the Euler scheme could offer by solving Ordinary Differential Equation problem. Four set of problems are solved via Harmonic-Polygon. Findings showed that new scheme or Harmonic-Polygon scheme can produced much better accuracy result

Statistical Validation of ACO-KNN Algorithm for Sentiment Analysis

This research paper aims to propose a hybrid of ant colony optimization (ACO) and k-nearest neighbour (KNN) algorithms as feature selections for selecting and choosing relevant features from customer review datasets. Information gain (IG), genetic algorithm (GA), and rough set attribute reduction (RSAR) were used as baseline algorithms in a performance comparison with the proposed algorithm. This paper will also discuss the significance test, which was used to evaluate the performance differences between the ACO-KNN, the IG-GA, and the IG-RSAR algorithms. The dependency relation algorithm was used to identify actual features commented by customers by linking the dependency relation between product feature and sentiment words in customers sentences. This study evaluated the performance of the ACOKNN algorithm using precision, recall, and F-score, which was validated using the parametric statistical significance tests. The evaluation process has statistically proven that this ACO-KNN algorithm has been significantly improved compared to the baseline algorithms. In addition, the experimental results have proven that the ACO-KNN can be used as a feature selection technique in sentiment analysis to obtain quality, optimal feature subset that can represent the actual data in customer review data

Cube Polygon: A New Modified Euler Method to Improve Electric Circuit Efficiency

Euler method is a numerical order process for solving problems with the Ordinary Differential Equation (ODE). It is a fast and easy way. While Euler offers a simple procedure for solving ODEs, problems such as complexity, processing time and accuracy have driven others to use more sophisticated methods. Improvements to the Euler method have attracted much attention resulting in numerous modified Euler methods. This paper proposes Cube Polygon, a modified Euler method with improved accuracy and complexity. In order to demonstrate the accuracy and easy implementation of the proposed method, several examples are presented. Cube Polygon’s performance was compared to Polygon’s scheme and evaluated against exact solutions using SCILAB. Results indicate that not only Cube Polygon has produced solutions that are close to identical solutions for small step sizes, but also for higher step sizes, thus generating more accurate results and decrease complexity. Also known in this paper is the general of the RL circuit due to the ODE problem

An Android Attendance Solution for Eco-Campus Life.

In UMS, signing attendance is very inefficient. Usually the signing of attendance starts when the lecturer gives out the attendance sheet in the lecture hall. If class is huge, it will take almost the whole lecture time to complete the process. The method used in UMS for signing attendance is basically passing the attendance sheet around. This will not only distract the class, it will also cause someone to miss the attendance sheet because of the passing process is not consistent. There is also potential of data loss due to human’s mistake such as misplacing the attendance sheet. In order to solve these problems, this project proposed an Android-based application integrated with a web application to make the process of recording attendance more efficient. The objectives for this project are to develop Android-based application with interface for students to record attendance as well as another interface, which allows lecturers to track the students’ attendance. The database for the content management system was developed to integrate with the Android Attendance Solution (AAS). The expected outcome for this project would be a fully functional attendance recording application. With this application, the whole process of recording attendance can be made easier and thus saves time as well as resources such as pen and paper

Designing Engaging Community Learning Application with Children Using Gamification

This research presents an approach to engage the children with a learning mobile application. The interest in education and learning process are increasing significantly due to the emerging of digital technologies. The use of e-learning in particularly for children to improve the learning process has been an issue as educators are facing problems on how to promote and to stay engaged with them. Due to the new technology that applies the new method into the e-learning process they able to overcome the problem. The aim of this study is to identify the features and guidelines for designing engaging for community learning with children using gamification technique. Hopefully the proposed community learning application can engage the children using the proposed technique. The research finding revealed that the gamification technique could help the student to engage with the learning material effectively

Semantic graph knowledge representation for Al-Quran verses based on word dependencies

Semantic approaches present an efficient, detailed and easily understandable representation of knowledge from documents. Al-Quran contains a vast amount of knowledge that needs appropriate knowledge extraction. A semantic based approach can help in designing an efficient and explainable knowledge representation model for Al-Quran. This research aims to propose a semantic-graph knowledge representation model for verses of Al-Quran based on word dependencies. These features are used in the proposed knowledge representation model allowing the semantic graph matching to improve Al-Quran search applications' accuracy. The proposed knowledge representation model is essentially a formalism for generating a semantic graph representation of Quranic verses, which can be applied for knowledge base construction for other applications such as information retrieval system. A set of rules called Semantic Dependency Triple Rules are defined to be mapped into the semantic graph representing the verse's logic. The rules translate word dependencies and other NLP metadata into a triple form that holds logical information. The proposed model has been tested with English translation of Al-Quran on a document retrieval prototype The basic system has been enhanced with anaphoric pronouns correction, which has shown improvement in retrieval performance. The results have been compared with a closely related system and evaluated on the accuracy of the document retrieval in Precision, Recall and F-score measurements. The proposed model has achieved 65%, 60% and 62.4% for the measurements, respectively. It has also improved the overall accuracy of previous system by 43.8%