ISO 9126 Quality Model For Evaluating of Student Portal: Al-Madinah International University (Case study)

E-learning is a teaching system that involves electronic resources such as computers and the Internet, and the student portal is an essential tool that supports learning in universities. However, there is a limited evaluation model for educational websites. Therefore, a framework is required to guide the creation of such a model. The study conducted evaluates the quality of the student portal at Al-Madinah International University based on ISO 9126 quality model from the student's perspective, and the results show a good quality portal. Nonetheless, students suggest improvements to enhance its effectiveness, ease of use, and learning process. Keywords: ISO 9126; Al-Madinah International University; Quality Model; Student Portal. eISSN: 2398-4287 © 2023. The Authors. Published for AMER and cE-Bs by e-International Publishing House, Ltd., UK. This is an open-access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer–review under the responsibility of AMER (Association of Malaysian Environment-Behaviour Researchers), and cE-Bs (Centre for Environment-Behaviour Studies), College of Built Environment, Universiti Teknologi MARA, Malaysia DOI:  https://doi.org/10.21834/e-bpj.v8iSI15.510

Easy determination of radiation absorption in brain tissue from mobile phones using finite element method

ZULKIFLY BIN ABBAS////// Abu Bakar Yakubu,Zainab Yunus

Projecting named entity tags from a resource rich language to a resource poor language

Named Entities (NE) are the prominent entities appearing in textual documents.Automatic classification of NE in a textual corpus is a vital process in Information Extraction and Information Retrieval research. Named Entity Recognition (NER) is the identification of words in text that correspond to a pre-defined taxonomy such as person, organization, location, date, time, etc.This article focuses on the person (PER), organization (ORG) and location (LOC) entities for a Malay journalistic corpus of terrorism.A projection algorithm, using the Dice Coefficient function and bigram scoring method with domain-specific rules, is suggested to map the NE information from the English corpus to the Malay corpus of terrorism.The English corpus is the translated version of the Malay corpus.Hence, these two corpora are treated as parallel corpora. The method computes the string similarity between the English words and the list of available lexemes in a pre-built lexicon that approximates the best NE mapping.The algorithm has been effectively evaluated using our own terrorism tagged corpus; it achieved satisfactory results in terms of precision, recall, and F-measure.An evaluation of the selected open source NER tool for English is also presented

Centre-based hard clustering algorithms for Y-STR data

This paper presents Centre-based hard clustering approaches for clustering Y-STR data. Two classical partitioning techniques: Centroid-based partitioning technique and Representative object-based partitioning technique are evaluated. The k-Means and the k-Modes algorithms are the fundamental algorithms for the centroid-based partitioning technique, whereas the k-Medoids is a representative object-based partitioning technique. The three algorithms above are experimented and evaluated in partitioning Y-STR haplogroups and Y-STR Surname data. The overall results show that the centroid-based partitioning technique is better than the representative object-based partitioning technique in clustering Y-STR data

TERMS VISUAUZATION FOR MALAY TRANSLATED QURAN DOCUMENT

A web-based visualization system is developed to visualize the similarity between root words in Malay translated Quran Documents. The visualization of terms used is based on their similarities measures using Cosine and Dice coefficients. The degree of similarity of a term (A) with a processed term (B), can be easily determined by observing the location of term A from term B. The term that is located closer to the processed term is considered more similar to the processed term compared to other terms that are located farther away. The terms created in the processing of one term can be used as potential queries to search relevant documents in the Malay translated Quran manually or electronically. The flexibility of this system to visualize different terms will be discussed. The development of the system involves two stages. The first stage is the processing of 6236 documents of the Malay translated Quran to create a database of all terms. The second stage is the creation of the web-based system using the preprocessing data created in the first stage. Both stages are explored. The visualization will help to improve the understanding of relationship between the terms in this specific domain

Arabic text summarization using pre-processing methodologies and techniques

Recently, one of the problems that has arisen due to the amount of information and its availability on the web, is the increased need for effective and powerful tools to automatically summarize text. For English and European languages an intensive works has been done with high performance and nowadays they look forward to multi-document and multi-language summarization. However, Arabic language still suffers from the little attention and research done in this field. In our research we propose a model to automatically summarize Arabic text using text extraction. Various steps are involved in the approach: preprocessing text, extract set of features from sentences, classify sentence based on scoring method, ranking sentences and finally generate an extract summary. The main difference between our proposed system and other Arabic summarization systems are the consideration of semantics, entity objects such as names and places, and similarity factors in our proposed system. In recent years, text summarization has seen renewed interest, and has been experiencing an increasing number of research and products especially in English language. However, in Arabic language, little work and limited research have been done in this field. will be adopted Recall-Oriented Understudy for Gisting Evaluation (ROUGE) as an evaluation measure to examine our proposed technique and compare it with state-of-the-art methods. Finally, an experiment on the Essex Arabic Summaries Corpus (EASC) using the ROUGE-1 and ROUGE-2 metrics showed promising results in comparison with existing methods

The Optimal Performance of Multi-Layer Neural Network for Speaker-Independent Isolated Spoken Malay Parliamentary speech

This paper describes speech recognizer modeling techniques which are suited to high performance and robust isolated word recognition in speaker-independent manner. In this study, a speech recognition system is presented, specifically for an isolated spoken Malay word recognizer which uses spontaneous and formal speeches collected from Parliament of Malaysia. Currently the vocabulary is limited to ten words that can be pronounced exactly as it written and control the distribution of the vocalic segments. The speech segmentation task is achieved by adopted energy based parameter and zero crossing rate measure with modification to better locates the beginning and ending points of speech from the spoken words. The training and recognition processes are realized by using Multi-layer Perceptron (MLP) Neural Networks with two-layer feedforward network configurations that are trained with stochastic error back-propagation to adjust its weights and biases after presentation of every training data. The Mel-frequency Cepstral Coefficients (MFCCs) has been chosen as speech extraction approach from each segmented utterance as characteristic features for the word recognizer. The MLP performance to determine the optimal cepstral orders and hidden neurons numbers are analyzed. Recognition results showed that the performance of the two-layer network increased as the numbers of hidden neurons increased. Experimental result also showed that the cepstral orders of 12 to 14 were appropriate for the speech feature extraction for the data in this study

Soil remediation for contaminated soil from heavy metals by electrokinetic process / Sabariah Arbai ... [et al.]

Contaminated sites with heavy metals, organic compounds and hazardous materials added with inefficient waste handling techniques, leakages and untreated abandoned mines made enormous impact to groundwater quality, soils and ecosystems. Electro-chemical principle, known as electrokinetic method is a greatly potential treatment of heavy metal in contaminated soils, including soils of low permeable clays (Rutigliano et.al 2008); and groundwater (Cherifi et.al., 2009). (Colletta et.al., 1997) stated that purging liquids of certain pH is important for heavy metal migration and molar concentration, while Fabienne et.al. (1999) stated that temperature mainly influences the ionic velocities with changes in partitioning of heavy metals. The study will identify and evaluate the amount of heavy metals in the collected contaminated soil samples, investigate physical characteristics of soils and relate to the chemical concentration levels of heavy metals, thus recommending the optimum temperature for efficient removal of heavy metals with appropriate pH. In this study, there are two types of specimen, i) site specimen, and ii) prepared specimen. For the site specimen, the physical characteristics and chemical concentration will be identified. For chemical concentration of both site and prepared samples, samples are digested and analyzed using ICP-MS equipment. For the prepared specimen, fresh clay specimen are spiked, compacted of low concentration heavy metals and will be run using electrokinetic under controlled pH and temperature. The purging liquids will be prepared in the electrode reservoirs to provide an appropriately-controlled pH for heavy metals adsorption. The electrokinetic tests will be performed onto 80 prepared spiked samples with initial concentration to a final concentration, each set of 240 hrs duration, temperature set and observed with daily pH monitored and recorded. The removal efficiency for optimal heavy-metal desorption, initial and final pH of the slurry specimen at 5 positions on the test-cell will be recorded, computed and analyzed

Ethylene conversion to higher hydrocarbon over copper loaded BZSM-5 in the presence of oxygen

The successful production of higher hydrocarbons from methane depends on the stability or the oxidation rate of the intermediate products. The performance of the BZSM-5 and modified BZSM-5 catalyst were tested for ethylene conversion into higher hydrocarbons. The catalytic experiments were carried out in a fixed-bed micro reactor at atmospheric pressure. The catalysts were characterized using XRD, NH3-TPD and IR for their structure and acidity. The result suggests that BZSM-5 is considered a weak acid. The introduction of copper into BZSM-5 improved the acidity of BZSM-5. The conversion of ethylene toward higher hydrocarbon is dependent on the acidity of the catalyst. Only weaker acid site is needed to convert the ethylene to higher hydrocarbons. Loading of Cu on BZSM-5 improved the selectivity of higher hydrocarbons especially at lower percentage. The reactivity of ethylene is dependent on the number of acidity as well as the presence of metal on the catalyst surface. Cu 1%BZSM-5 is capable of converting ethylene to higher hydrocarbons. Balances between metal and acid sites influence the performance of ethylene conversion and higher hydrocarbon selectivity. Higher loading of Cu leads to the formation of COx