Competency assessment of short free text answers

The increased adoption of competency-based education has posed the need of an automated competency assessment. Most of the existing assisted assessment does not cater for competency assessment. The high percentage on the use of short free text answer as competency assessment shows that the need of the competency assisted assessment is urgent. This paper studies on the need and also review on existing assisted assessments focusing on short free text answer. A Node Link (NL) Scoring technique is proposed as an alternative automated solution to assess learners’ competency in short free text answers. Keyword: competency assessment; short free text answers; Node Link Scoring techniqu

Improved Malware detection model with Apriori Association rule and particle swarm optimization

The incessant destruction and harmful tendency of malware on mobile devices has made malware detection an indispensable continuous field of research. Different matching/mismatching approaches have been adopted in the detection of malware which includes anomaly detection technique, misuse detection, or hybrid detection technique. In order to improve the detection rate of malicious application on the Android platform, a novel knowledge-based database discovery model that improves apriori association rule mining of a priori algorithm with Particle Swarm Optimization (PSO) is proposed. Particle swarm optimization (PSO) is used to optimize the random generation of candidate detectors and parameters associated with apriori algorithm (AA) for features selection. In this method, the candidate detectors generated by particle swarm optimization form rules using apriori association rule. These rule models are used together with extraction algorithm to classify and detect malicious android application. Using a number of rule detectors, the true positive rate of detecting malicious code is maximized, while the false positive rate of wrongful detection is minimized. The results of the experiments show that the proposed a priori association rule with Particle Swarm Optimization model has remarkable improvement over the existing contemporary detection models. © 2019 Olawale Surajudeen Adebayo and Normaziah Abdul Aziz

The trend of mobile malwares and effective detection techniques

The usefulness of mobile phones nowadays has gone beyond making calls and sending text messages. In fact, most of applications available on desktop computer are presently easily accessible on mobile devices, especially smartphone based on Androids, iOS, and Windows phone platforms. However, at the same time, malware is increasingly becoming pervasive on a mobile platform for financial, social and political exploitation. This chapter examines the trends of mobile malware and different efforts of anti-malware writers and researchers in addressing mobile malware on smartphones. Chapter Previe

Corpus-based readability formula for Arabic texts: a prototype

This research aims to produce a readability formula for Arabic texts. There are already a few formulae used for measuring the readability level of English texts. Among them are Flesch, Gunning Fox and Dale-Chall formulae. Flesch Reading Ease scale is based on sentence length and the number of syllables per hundred words, Gunning Fox Index counts sentence length and percentage of multi-syllabic words and Dale-Chall formula counts sentence length and whether a word appears on a list of acceptable words. However, Arabic has its own language rules. Hence there is a need to develop a readability formula for Arabic. This will greatly assist in the production of texts for comprehension and for testing. A study on readability is therefore crucial in the development of Arabic reading and testing materials and also in language teaching and learning. This paper will present a prototype of a readability formula which is based on word frequency for calculating the level of Arabic texts difficulty

Mobile device forensics: extracting and analysing data from an android-based smartphone

The advancement of wireless technology and mobile devices have change our life tremendously. The number of smartphone users increases and majority people rely on it for communication and business related matters. While smartphones are used for positive aspects of our life, it is also used by criminals as medium for their modus operandi. Therefore, there are potential information stored in smartphones that can be used for digital evidence as part of an investigation. However, investigators may face challenges in extracting crucial information and the vital data stored in the smartphone. In this paper, we share on how we studied and experimented several methods on how data in smartphones can be extracted and analysed using the Sleuth Kit Autopsy. The aim of this work is to discover methods of extracting and analysing data from an Android based smartphone. We managed to obtain email, contact, messages, calendar, and images data that can be of used asdigital evidence in an investigation

A Corpus-Based Readability Formula for Estimate of Arabic Texts Reading Difficulty

The present study is aimed at designing a formula for estimating the difficulty of reading Arabic texts. Flesch, Gunning Fox and Dale-Chall are some of the formulae that have been used for measuring English texts difficulty. Some of them have been automated making it easy for users to check the readability level of a particular text. A few scholars have attempted to come up with a readability formula for Arabic, but none has been automated. This study is thus conducted to find the formula that would make it possible for users to measure the difficulty level of Arabic texts online. This will greatly help in materials selection for reading comprehension and testing. This paper will present the prototype of a readability formula which is based on a corpus for estimating the difficulty of Arabic written documents