Math E-Tutor: Towards A Better Self-Learning Environment.

Math E-Tutor is a web-based tutoring system which aims to create a virtual teaching and learning environment that suits today's trend. This system focuses on the mathematical syllabus of lower secondary school which uses multiple choice questions (MCQ) as the mode of evaluation, known as Penilaian Menengah Rendah (PMR) in Malaysia

Application Of Exact String Matching Algorithms Towards SMILES Representation Of Chemical Structure.

Bioinformatics and Cheminformatics use computer as disciplines providing tools for acquisition, storage, processing, analysis, integrate data and for the development of potential applications of biological and chemical data. A chemical database is one of the databases that exclusively designed to store chemical information

Credit Card Fraud Detection Using Machine Learning As Data Mining Technique

The rapid participation in online based transactional activities raises the fraudulent cases all over the world and causes tremendous losses to the individuals and financial industry. Although there are many criminal activities occurring in financial industry, credit card fraudulent activities are among the most prevalent and worried about by online customers. Thus, countering the fraud activities through data mining and machine learning is one of the prominent approaches introduced by scholars intending to prevent the losses caused by these illegal acts. Primarily, data mining techniques were employed to study the patterns and characteristics of suspicious and non-suspicious transactions based on normalized and anomalies data. On the other hand, machine learning (ML) techniques were employed to predict the suspicious and non-suspicious transactions automatically by using classifiers. Therefore, the combination of machine learning and data mining techniques were able to identify the genuine and non-genuine transactions by learning the patterns of the data. This paper discusses the supervised based classification using Bayesian network classifiers namely K2, Tree Augmented Naïve Bayes (TAN), and Naïve Bayes, logistics and J48 classifiers. After preprocessing the dataset using normalization and Principal Component Analysis, all the classifiers achieved more than 95.0% accuracy compared to results attained before preprocessing the dataset

Security attacks taxonomy on bring your own devices (BYOD) model

Mobile devices, specifically smartphones, have become ubiquitous. For this reason, businesses are starting to develop “Bring Your Own Device” policies to allow their employees to use their owned devices in the workplace. BYOD offers many potential advantages: enhanced productivity, increased revenues, reduced mobile costs and IT efficiencies. However, due to emerging attacks and limitations on device resources, it is difficult to trust these devices with access to critical proprietary information. Therefore, in this paper, the potential attacks of BYOD and taxonomy of BYOD attacks are presented. Advanced persistent threat (APT) and malware attack are discussed in depth in this paper. Next, the proposed solution to mitigate the attacks of BYOD is discussed. Lastly, the evaluations of the proposed solutions based on the X. 800 security architecture are presented

Localizing user experience for mobile application: A case study among USM undergraduates

The increasing number of mobile devices consumptions, especially mobile phones and smartphones had caused a growing interest in the user experience research on the mobile platform. However, it is difficult to gain an encompassing understanding of the user experience especially from a localized context.This paper presents our survey finding on the understanding of user experience among USM undergraduates.The research finding identifies that a respondents’ field of study has some influence on their understanding of user experience.Overall, the respondents tend to agree that user experience is subjective and based on the individual’s interaction with an application. The ISO definition of user experience is discussed and compared with the survey results. The comparison highlights that the definition of user experience is similar with the ISO’s definition of user experience

DeepNC: a framework for drug-target interaction prediction with graph neural networks

The exploration of drug-target interactions (DTI) is an essential stage in the drug development pipeline. Thanks to the assistance of computational models, notably in the deep learning approach, scientists have been able to shorten the time spent on this stage. Widely practiced deep learning algorithms such as convolutional neural networks and recurrent neural networks are commonly employed in DTI prediction projects. However, they can hardly utilize the natural graph structure of molecular inputs. For that reason, a graph neural network (GNN) is an applicable choice for learning the chemical and structural characteristics of molecules when it represents molecular compounds as graphs and learns the compound features from those graphs. In an effort to construct an advanced deep learning-based model for DTI prediction, we propose Deep Neural Computation (DeepNC), which is a framework utilizing three GNN algorithms: Generalized Aggregation Networks (GENConv), Graph Convolutional Networks (GCNConv), and Hypergraph Convolution-Hypergraph Attention (HypergraphConv). In short, our framework learns the features of drugs and targets by the layers of GNN and 1-D convolution network, respectively. Then, representations of the drugs and targets are fed into fully-connected layers to predict the binding affinity values. The models of DeepNC were evaluated on two benchmarked datasets (Davis, Kiba) and one independently proposed dataset (Allergy) to confirm that they are suitable for predicting the binding affinity of drugs and targets. Moreover, compared to the results of baseline methods that worked on the same problem, DeepNC proves to improve the performance in terms of mean square error and concordance index

Applications of Brain Computer Interface in Present Healthcare Setting

Brain-computer interface (BCI) is an innovative method of integrating technology for healthcare. Utilizing BCI technology allows for direct communication and/or control between the brain and an external device, thereby displacing conventional neuromuscular pathways. The primary goal of BCI in healthcare is to repair or reinstate useful function to people who have impairments caused by neuromuscular disorders (e.g., stroke, amyotrophic lateral sclerosis, spinal cord injury, or cerebral palsy). BCI brings with it technical and usability flaws in addition to its benefits. We present an overview of BCI in this chapter, followed by its applications in the medical sector in diagnosis, rehabilitation, and assistive technology. We also discuss BCI’s strengths and limitations, as well as its future direction

Library advisor - an information management system on standard cell library

Integrated Circuit (IC) Design has always been a challenge to designers.There are two approaches that can be used to draft architecture of an integrated circuit which are the old approach of using Custom and a new one using ASIC.ASIC has been preferred by IC designers as it manipulates liberty files to provide suggestion on the architecture design faster than the Custom approach that relies on tailor-made designs. Tailor-made designs are difficult to draft and not flexible nor scalable.In fact, the time required for an IC to be build based on Custom design is longer than the one using ASIC.Furthermore, ASIC works on a higher-level of the IC Design in which liberty libraries can be sought to find suitable cells for the IC.However, these liberty libraries are huge that it is quite impossible to browse through manually for intensive comparisons to be made.This has been the obstacle in the ASIC design.Therefore, we proposed a system that stores these liberty libraries as a database and is able to intelligently suggest possible candidate components for IC design sought by the system user.This is a new and novel system that would benefit all designers in the IC design field

Carian persamaan pangkalan data drug : satu ulasan

Carian persamaan merupakan asas aplikasi dalam bidang informatik kimia yang mengguna kaedah informatik untuk menyelesai masalah kimia. Kertas ini membincang komponen prinsip dalam carian persamaan yang menumpu kepada penyaringan maya 2D. Perbincangan juga menekankan latar belakang sejarah tentang prinsip dan kaedah yang diguna dalam bidang ini