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The result of substantial investment and the formulation of impressive policies for e-government implementations has transitioned Ghana from a mediocre to a high e-government readiness in the latest United Nations Biannual E-Government Development Index (EGDI). Ghana is the only African country to achieve this feat. However, how e-government service delivers benefits to Ghanaians and the challenges this technology is encountering seems to be overlooked by researchers in extant academic discourses. As a result, important scientific knowledge about this topic in the context of Ghana is missing. This paper aims to review articles on e-government to identify its merits to the Ghanaian public and businesses and single out the challenges it faces. The narrative review method was employed to search, review, and synthesise the extant literature. The review showed that there is a paucity of e-government related literature in the context of Ghana. Among the few articles that were found and reviewed, the benefits associated with e-government are; (1) reduction of corruption prospects, (2) efficiency of government services delivery, (3) access to government services, and (4) cost reduction. Moreover, the challenges associated with e-government are; (1) digital divide and its four dimensions, (2) culture challenge, (3) sabotaging of government infrastructure, (4) power interruptions, (5) citizens trust issues, (6) security threats, and (7) low public knowledge. This article contributes to the limited body of research on e-government in developing countries, particularly Ghana, by mapping a potential field of research, synthesising the current knowledge of e-government in Ghana, and creating an agenda for further research. Also, the up-to-date knowledge provided by this paper could assist the authorities in making prudent e-government policies.

Facing an unprecedented explosion of digital content, many organisations have been left with a large repository of unstructured information. Huge volumes of electronic content have been captured and stored within organisations’ repositories, depriving organisations of the ability to analyse this data properly. As a result, many organisations are facing crucial problems, such as (1) employees wasting 30% of their time looking for relevant information; (2) operational and maintenance cost increases to handle large amounts of data; and (3) loss of opportunities to gain a strategic advantage through proper analysis of organisational data. To overcome these problems, the Enterprise Content Management System (ECMS) was introduced in the early 2000s. Having been researched for a period of 25 years, most prior studies on ECMS focus on a bottom-up approach with the intention of achieving immediate benefits such as cost-reduction, meaningful knowledge work and re-use of previous content. A top-down approach that aims to improve decision-making, resource allocation and competitive intelligence are ignored due to a lack of awareness about the importance of such benefits. Therefore, this research will explore the relationship between ECMS and how it can facilitate decision-making processes. Grounded on previous literature, the contributions of this paper are as follows: first, the paper provides insight into the research from the perspective of ECMS; second, the paper proposes a research model for further exploration of the topic; finally, implications and future directions for research is outlined.

Automated cancer cell and tumor segmentation and detection for 3D modeling are still an unsolved research problem in computer vision, image processing and pattern recognition research domains. Human body is complex three-dimensional structure where numerous types of cancer and tumor may exist regardless of shape or position. A three-dimensional (3D) reconstruction of cancer cell and tumor from body parts does not lead to loss of information like 2D shape visualization. Various research methodologies for segmentation and detection for 3D reconstruction of cancer cell and tumor were performed by previous research. However, the pursuit for better methodology for segmentation and detection for 3D reconstruction of cancer cell and tumor are still unsolved research problem due to lack of efficient feature extraction for details surface information, misclassification during training phases and low tissue contrast which causes low detection and precision rate with high computational complexity during detection and segmentation. This research addresses comprehensive and critical review of various segmentation and detection research methodologies for cancer affected cell and tumor in human body in the basis of three-dimensional reconstruction from MRI or CT images. At first, core research background is illustrated highlighting various aspects addressed by this research. After that, various previous methods with advantages and disadvantages followed by various phases used as frameworks exist in the previous research demonstrated by this research. Then, extensive experimental evaluations done by previous research are demonstrated by this research with various performance metrics. At last, this research summarized overall observation on previous research categorized into two aspects, i.e. observation on common research methodologies and recommended area for further research. Overall reviews proposed in this paper have been extensively studied in various research papers which can significantly contribute to computer vision research and can be potential for future development and direction for future research.

In this research, the concept of Game Refinement Theory is applied to quantify the entertainment value of the game of TIGERS AND GOATS. This paper explores the game to get some compelling estimates of Game Refinement (GR) value of the game at various stages. The comparison of value is done for the two popular variants of the game. Also, we have compared the value with respect to the difficulty level of the game and the winning scenario. The results indicate that the game becomes more of a serious game with the increasing difficulty. The paper focuses on one main question - Why did we lose one of the game variants while the other one is still well sought-after and if there is any history behind this? After doing some research, we found that the game variant AADU PULI ATTAM which has lost its popularity has much lower game refinement value than the popular variant (BAGH CHAL). With this, we also present the hypothesis on their timeline that BAGH CHAL is an evolved version of AADU PULI ATTAM.

IT Risk Management is the application of risk management methods to information technology in order to manage IT risk. The business risk associated with the use, ownership, operation, involvement, influence and adoption of IT within an enterprise or organization. The purpose of this paper is to overcome the issue in implementing the IT Risk Management at Tasik Chini Research Centre (PPTC), Universiti Kebangsaan Malaysia. This paper aimed to enhance the risk management awareness by promoting active involvement of the workers in the daily affairs and the decision-making process. This paper used both quantitative and qualitative methods. Data was collected by interviewing the community living at the edge of the lake as well as collecting on-site at the rivers's monitoring station. The negative feedback include no framework of IT risk management at PPTC, lack of understanding in IT risk management concept among the PPTC staffs, and the need to promote a few aspects of the risk management policy, for instance, by introducing the development of risk management system or a customized model to register risk and data collection. The positive side was not limited to IT solely. They include the interest shown by PPTC top managements in implementing the full IT risk management in order to achieve the objectives of research centre. The results were also used in the development of the early warning system in water quality prototype as an early warning to the PPTC staffs and Orang Asli living in the vicinity of Tasik Chini. The study began by identifying the problems faced by the PPTC staffs to the usability of the risk management system that are available from the interviews. Usability characteristics of risk management system and early warning system that are suitable to the PPTC staffs and Orang Asli are identified and a guideline for the users interface usability of information systems is constructed.

Feature selection is an important issue in data mining, and it is used to reduce dimensions of features set. Web spam detection is one of research fields of data mining. With regard to increasing available information in virtual space and the need of users to search, the role of search engines and used algorithms are important in terms of ranking. Web spam is an illegal method to increase mendacious rank of internet pages by deceiving the algorithms of search engines, so it is essential to use an efficient method. Up to now, many methods have been proposed to face with web spam. An ensemble feature selection method has been proposed in this paper to detect web spam. Content features of standard dataset of WEBSPAM-UK2007 are used for evaluation. Bayes network classifier is used along with 70-30% training-testing spilt of dataset. The presented results show that AUC of this method is higher than the other methods reported in this paper. Moreover, the best values of evaluation metrics in our proposed method are optimal in comparison to the other methods reported in this paper. In addition, it improves classification metrics in comparison to basic feature selection methods.

The steganography is prone to number of attacks such as geomatical, salt & pepper, gaussian, median filtering, attacks. To overcome these problems, the cryptography and error correction codes are comes in the pictures and hybrid with steganography algorithms. The cryptography algorithms add one layer of security on steganography algorithms and error correction codes improves the robustness of steganography algorithms. On the other side, the hybridization of the algorithms, increase memory complexity and increase computation time for data embedding. Thus, in this paper a review on multi-layer algorithms for video steganography is done. This paper comprehensively reviews the steganography, spatial and frequency domain techniques hybrid with cryptography and error correction techniques. In-depth analysis on published literatures revealed that the spatial domain techniques require shorter computation time for data embedding and provide higher data hiding capacity than frequency domain methods. Performance of such techniques was evaluated in terms of visual quality and robustness parameters. Present challenges and future trends towards the improvement of the multi-layer data security in video steganography are discussed to provide the taxonomy for further navigation.

The speed of technology adaptations has made it necessary to provide the latest tools to facilitate students in academic libraries. However, the available library services are not used effectively and efficiently by the students. Unattractive library services have been identified as the problems that make the library incompetent in serving and delivering successful library services to the students. This paper attempted to explore the perception of undergraduate students regarding possible use of tablet computer for library services in the academic library. Quantitative approach is adopted with the structured questionnaire has been distributed to 155 undergraduate students. The result shows that the acceptance of a tablet computer by the students is satisfactory and has a good perception to enhance library services. Many students have responded that the tablet computer is an interactive and innovative way to use library services. This paper makes a significant contribution to the academic library services by clarifying the usefulness of tablet computer and the importance of having ICT application for enhancing library services in Malaysia. This paper provides evidence on the use of ICT application by the undergraduate students in retrieving information and their attitudes toward applying ICT application in the academic library.

With increasing demand on digital images, there is a need to compress the image to entertain the limited bandwidth and storage capacity. Recently, there is a growing interest among researchers focusing on compression of various types of images and data. Amongst various compression algorithms, transform-based compression is one of the promising algorithms. Despite the technological advances in transmission and storage, the demands placed on the bandwidth of communication and storage capacities by far outstrips its availability. This paper presents a review of image compression principle, compression techniques and various thresholding algorithms (pre-processing algorithms) and quantization algorithm (post-processing algorithms). This paper intends to give an overview to the relevant parties to choose the suitable image compression algorithms to suit with the need.

Biomedical Named Entity Recognition (Bio-NER) is an essential step of biomedical information extraction and biomedical text mining. Although, a lot of researches have been made in the design of rule-based and supervised tools for general NER, Bio-NER still remains a challenge and an area of active research, as still there is huge difference in F-score of 10 points between general newswire NER and Bio-NER. The complex structures of the biomedical entities pose a huge challenge for their recognition. To handle this, this paper explores different effective word representations with Support Vector Machine (SVM) to deal with the complex structures of biomedical named entities. First, this paper identifies and evaluates a set of morphological and contextual features with SVM learning method for Bio-NER. This paper also presents an extended distributed representation word embedding technique (EDRWE) for Bio-NER. These models are evaluated on widely used standard Bio-NER dataset namely GENIA corpus. Experimental results show that EDRWE technique improves the overall performance of the Bio-NER and outperforms all other representation methods. Results analysis shows that the new EDRWE is satisfactory and effective for Bio-NER especially when only a small-sized data set is available.

Semantic measures between concepts require some of cognitive capabilities such as categorization and reasoning to estimate semantic association among concepts. For this reason, this problem has numerous applications in artificial intelligence, natural language processing, information retrieval, text clustering, text categorization and many other related fields. Measuring lexical semantic relatedness generally requires certain background information about the concept or terms. Semantic measures between concepts are divided into two main sources: knowledge based and unstructured corpora. Both resources play important role in the task of measuring lexical semantic relatedness. Knowledge-based semantic measures have been proposed to estimate semantic similarity between two concepts using several approaches such as ontology-based, graph-based and concept's vector approaches. This paper reviews existing semantic similarity measures which depend on the lexical source and discusses the various approaches on semantic measures which include the path-based, information content, gloss-based and feature-based measures. This paper also focuses on semantic measures that are based on features using lexical knowledge sources and discusses some issues that arise in these measures

This paper aims to propose an automated sentiment lexicon generation model specifically designed for the Malay language. Lexicon-based Sentiment Analysis (SA) models make use of a sentiment lexicon for SA tasks, which is a linguistic resource that comprises a priori information about the sentiment properties of words. A sentiment lexicon is an indispensable resource for SA tasks. This is evident in the emergence of a large volume of research focused on the development of sentiment lexicon generation algorithms. This is not the case for low-resource languages such as Malay, for which there is a lack of research focused on this particular area. This has brought up the motivation to propose a sentiment lexicon generation algorithm for this language. WordNet Bahasa was first mapped onto the English WordNet to construct a multilingual word network. A seed set of prototypical positive and negative terms was then automatically expanded by recursively adding terms linked via WordNet's synonymy and antonymy semantic relations. The underlying intuition is that the sentiment properties of newly added terms via these relations are preserved. A supervised classifier was employed for the word-polarity tagging task, with textual representations of the expanded seed set as features. Evaluation of the model against the General Inquirer lexicon as a benchmark demonstrates that it performs with reasonable accuracy. This paper aims to provide a foundation for further research for the Malay language in this area.

In this paper a stemming algorithm for morphological analysis for less popular or minor language like Pashto language is presented. Pashto, as a less popular language, lacks the resources and tools that can be applied in different applications such as in document indexing, clustering, language processing, text analysis, database search systems, information retrieval, linguistic applications, and so forth. The review of literature shows that only very few morphological studies have been conducted on Pashto language and Pashto has not yet been fully analyzed. In addition, no stemming algorithm has been proposed in extracting Pashto root words from the Pashto corpus. In this paper, Pashto corpus is directly used as the input, and accordingly the stemming algorithm uses both inflectional and derivational morphemes. The output is in the form of meaningful root word without affixes. Furthermore, the accuracy and strength of the proposed algorithm is evaluated. To validate the function of the developed algorithm, two native speakers of Pashto were recruited to evaluate the algorithm in terms of its accuracy and strength.

Rapidly Exploring Random Trees (RRT) are regarded as one of the most efficient tools for planning feasible paths for mobile robots in complex obstacle cluttered environments. The recent development of its variant: RRT* is considered as a major breakthrough as it makes it possible to achieve optimality in paths planning. However, its limitations include the infinite time it takes to reach the optimal solution and a very slow rate of convergence. Just recently the authors have introduced RRT*-Smart which is a rapid convergence implementation of RRT* for improved efficient path planning both in terms of planning time as well as path cost. This paper presents a new scheme for RRT*-Smart that helps it to adapt to various types of environments by tuning its parameters during planning based on the information gathered online. The paper also includes detailed explanation of the algorithm�s characteristics and statistical analysis of its behavior in different environment types including mazes, narrow passages and obstacle cluttered environments in comparison with RRT*. Navigation experiments using the real Pioneer 3-AT Mobile Robot provide a proof of the concept.

Simultaneous localization and mapping (SLAM), also known as concurrent mapping and localization (CML), is an important topic or robotics files. This method produces a real-time map of an environment and finds the current position of a robot on that map. This method is generally used to solve the problem of �Where am I?� for localization, �Where do I go?� for goal determination, and �How do I go there?� for robot motion planning. Recently, the number of studies in this area has increased rapidly and expanded to different areas. In this paper analyzes SLAM or CML, which is currently a hot topic in the field of robotic research. In addition, this paper describes methods for solving SLAM problems, presents evaluation methods for SLAM, analyzes recent research on SLAM worldwide, and studies the academic importance of SLAM. This paper also reviews the use of SLAM for humanoid robots and aims to address the issue of the significance of SLAM engine in the future of stereo vision on humanoid robots.

Despite several initiatives taken by the Government of Malaysia to bridge the digital divide, more effort is needed, especially in raising the economic and educational status in rural areas. Digital divide refers to the inequal opportunities to access Information and Communication Technology (ICT) facilities between urban and rural areas. This paper examines whether ICT skills do contribute in narrowing the gap between the rural and urban areas via a case study in a rural area i.e. Kundang Ulu, Muar Johor. Survey employing questionnaire was adopted to collect data on the respondent’s background, ICT usage, and the competency of ICT skills involving 585 students at Sekolah Menengah Kebangsaan Tengku Temenggung Ahmad (SMKTTA). The results show a small percentage of computer ownership, low ICT usage, and moderate levels in acquiring basic ICT skills. These findings reveal that digital gap is a persistent issue in rural areas like Kundang Ulu. This paper seeks to help policy makers to write relevant policies and also other authorities in identifying strategies for bridging the digital divide in Malaysia.

Boundary value problems are problems that are frequently encountered in the wave transmission. This paper discusses three numerical methods of type overrelaxation for solving boundary value problems. The methods discussed are Successive overrelaxation (SOR), Accelerative overrelaxation (AOR) and Rotated Successive Over-relaxation (RSOR). In this paper, generalized formulations for these three methods were developed. Results showed that the Generalized SOR and AOR method produce the highest accuracy, whereas Generalized RSOR method is the fastest solver.

This paper describes a new algorithm called Bi-Directional Monte Carlo Tree Search. The essential idea of Bi-directional Monte Carlo Tree Search is to run an MCTS forwards from the start state, and simultaneously run an MCTS backwards from the goal state, and stop when the two searches meet. Bi-Directional MCTS is tested on 8-Puzzle and Pancakes Problem, two single-agent search problems, which allow control over the optimal solution length d and average branching factor b respectively. Preliminary results indicate that enhancing Monte Carlo Tree Search by making it Bi-Directional speeds up the search. The speedup of Bi-directional MCTS grows with increasing the problem size, in terms of both optimal solution length d and also branching factor b. Furthermore, Bi-Directional Search has been applied to a Reinforcement Learning algorithm. It is hoped that the speed enhancement of Bi-directional Monte Carlo Tree Search will also apply to other planning problems.

Image classification is generally about the understanding of information in the images concerned. The more the system able to understand the image contains, the more effective it will be in classifying desired images. Recent work has shown that the convolutional neural network (CNN) paradigm is useful for obtaining more accurate image classification results. A crucial component in the CNN is the convolution filters which consist of a series of predefined filter weight initialization values. The filter weights are then automatically learned by the neural network throughout the back- propagation training algorithm. However, most initialization schemes used in the deep convolutional neural networks are mainly to deal with vanishing gradient problems. Thus, selecting optimal weights are crucial to improve convergence and minimize the complexity which can enhance the generalization performance. One possible solution is to replace the standard weights with parameterized filters that proven to be efficient in extracting useful features such as Gabor filter bank. The Gabor filter bank is popular due to its ability in dealing with spatial transformation, especially on edges and texture information of different scales and directions. Thus, in this paper, we investigate the effect of utilizing Gabor and convolutional filters on small size kernels of deep VGG-16 architecture. The standard VGG-16 filter is replaced with the Gabor filter bank to obtain uniform distribution at all layers of the network. The result shows that the orientation and scale weights initialization scheme outperforms the standard filter weights on an image classification problem.

Due to its rich and diverse biodiversity of flora and fauna, Tasik Chini, a UNESCO Bisosphere Reserve, is a national heritage that must be preserved and protected. Ensuring healthy water quality here is vital for the survival of the ecosystem. Water quality was constantly being monitored through the use of a network of sensors and telemetry system that collect parameters to determine Water Quality Index since 2004. However, two events have rendered the setup to be inadequate: the economic activities around the lake and the big flood of 2014. Both events has proven that the IoT infrastructure at Tasik Chini is inadequate to mitigate major disaster. The risk of both natural and man-made disasters happening always increased yearly and has a huge impact on water quality monitoring as well as the dissemination and sharing of data and results. A proper management plan to mitigate these risks is needed. The purpose of this paper is to highlight a successful research methodology that has been proposed and done in monitoring and improving Tasik Chini water quality. First, needs analysis were carried out through face-to-face interaction with researchers and the indigenous community living within the vicinity of the lake. Historical water quality data were also compiled and analyzed to validate the degradation of water quality over the years. Second, a proper risk registers and risk respond plan was developed. The current telemetry and network of sensors were reengineered by introducing new online tools for sharing and disseminating of water quality data to more diverse stakeholders. Cloud and 4G services are now the integral part of monitoring. Third, an early warning system has been developed to complete the setup.

Sustainable supply chain management is becoming increasingly noticeable and takes place in various industries. It is also applied in the company to improve the performance of the company. However, the standard of sustainable supply chain management is not identical, although in the same industry. Sustainability standards usually focus on service or product management to minimize costs. Most studies focused on a single aspect or two aspects of sustainability, such as on the environment only or focused on the environment and economy only; not many studies focused on all aspects of sustainability. The lack of a common standard that incorporates all three sustainability (environmental, economic, and social) to serve as an essential guide to achieving sustainable supply chain management leads to this study. This paper discussed the overview of supply chain management sustainability in Malaysia. The concept of supply chain management, the sustainability of supply chain management, the importance and relationship between sustainability and supply chain management are thoroughly discussed. The challenges and issues in sustainable supply chain management generally and in Malaysia are also deliberated. Finally, a suitable suggestion for analyzing the sustainability of supply chain management is proposed and concluded.

In today's education, the use of social media to support teaching and learning is widely accepted and practiced. This development is in line with students’ life style that represents Generation Z in accessing information and communicating. Not much research has been conducted on the use of social media to support meaningful learning that can provide a deeper understanding of its implementation in Higher Education Institutions. Therefore, this paper aims to identify the characteristics of social media in education and meaningful learning and to propose a model of meaningful learning using social media in Higher Learning Institutions. This study applies a qualitative approach using literature review by conducting content analysis of previous research. The results show that social media has many useful features such as freedom, flexibility, authenticity, individual and real-time. These features potentially stimulate students to interact with learning materials and learning environment to enhance their conceptual understanding and inspire concepts application in real life. The proposed model is expected to guide educators and researchers on the compatibility of these two approaches to be implemented in Higher Learning Institutions.

Building a robust Optical Character Recognition (OCR) system for languages, such as Arabic with cursive scripts, has always been challenging. These challenges increase if the text contains diacritics of different sizes for characters and words. Apart from the complexity of the used font, these challenges must be addressed in recognizing the text of the Holy Quran. To solve these challenges, the OCR system would have to undergo different phases. Each problem would have to be addressed using different approaches, thus, researchers are studying these challenges and proposing various solutions. This has motivate this study to review Arabic OCR dataset because the dataset plays a major role in determining the nature of the OCR systems. State-of-the-art approaches in segmentation and recognition are discovered with the implementation of Recurrent Neural Networks (Long Short-Term Memory-LSTM and Gated Recurrent Unit-GRU) with the use of the Connectionist Temporal Classification (CTC). This also includes deep learning model and implementation of GRU in the Arabic domain. This paper has contribute in profiling the Arabic text recognition dataset thus determining the nature of OCR system developed and has identified research direction in building Arabic text recognition dataset.

Computer Science subject have been introduced as a new subject in the Secondary School Standard Curriculum (KSSM) to equip students with problem solving and computational thinking skills. This Computer Science subject consists of three modules, namely Computer Programming, Database, and Human and Computer Interaction modules. As a new subject, two major problems that the teachers facing are the material and approach for teaching. Thus, the MyJavaSchool module was developed as an alternative teaching material for the form four Computer Programming modules. MyJavaSchool is a module to teach Java programming using Turtle Graphic and competency-based learning approach. This paper discusses the results of a study designed to examine students\' perceptions of the MyJavaSchool module as well as their perceptions and levels of motivation on the subject of Computer Programming. This study uses a quantitative approach where questionnaires are used to collect the data. The respondents were 126 form four students. The module and a guideline were given to the teacher to implement. After a few weeks of teaching, the questionnaire was distributed to the respondents. The findings showed that the students\' perceptions on the use of this module was at a good level with an average mean of 2.74. This indicates that students are still skeptical of the use of the MyJavaSchool module in learning computer programming. However, they are motivated by the learning approach used and intend to further their studies in Computer Science after they finish their secondary school. In conclusion it can be said that this module needs to be improved further. Examples for each topic need to be added because through the example, students can understand how their concepts and usage. The finding also shows that learning approaches are very important in motivating students.

This paper examines the impact of Sifteo Cube Technology in engaging children with attention deficit hyperactivity disorder (ADHD). ADHD is an early childhood neurodevelopmental disorder which starts as early as five years of age. The core symptoms are inattentiveness, impulsiveness, and hyperactivity. By identifying the history of games development and ADHD, the researchers explored the viability of using the kinesthetic technology of Sifteo Cubes to engage these children. Engaging children with ADHD can lead to better management of the children, administering of learning materials, or aid other therapeutic methods. To carry out this research, an adventure game playable on the Sifteo Cubes using open-source games development kit called Wildflower was developed and evaluated with children with ADHD for qualitative analysis. Results obtained from video capture and ethnography proved favourable. Sifteo Cubes can effectively engage the children for an average of 20 minutes. The results show that Sifteo Cubes is effective is in engaging children with ADHD.

This paper reports on the development of a web based virtual forest environment to raise the awareness of threatened plant species in particular for the family of Dipterocarpaceae. Tropical forests in Malaysia consists of unique ecosystems which are home to flora and fauna including the threatened plant species that are listed in the Red List by the Forest Research Institute of Malaysia. However, the lack of awareness on the threatened plant species somehow can jeopardise on the effort on conservation of the forest. A web based utilizing virtual environment were developed that focussed on threatened plant species. User experiments were conducted to evaluate the user acceptance on the developed application. 30 participants were divided into two groups, brochures and web version. Results showed that participants who completed the experiments with web based virtual environment increased their level of awareness as compared to the usage of conventional brochures on threatened plant species.

Sentiment Analysis (SA) is the computational treatment of opinions, sentiments and subjectivity of text. Aspect-based Sentiment Analysis (ABSA) is a specific SA that aims to extract most important aspects of an entity and predict the polarity of each aspect from the text. A review of the recent state-of-the-art in ABSA, shows the remarkable growing in finding both aspect, and the corresponding sentiment. Current methods are categorized based on their proposed algorithms and models. For each discussed study, aspect extraction method and sentiment prediction method, the dataset, domain and the reported performance is included. The main goal of this work is to review ABSA techniques with brief details. The main contributions of this paper consist of the refined categorizations of a great number of recent articles, comparing them and the illustration of the recent trend of research in the ABSA.

Named Entity Recognition (NER) research based on rule is widely investigated and is used in various languages mainly English. However, the English NER rules are different with Malay language due to different morphology. Some of challenging issue in Malay is cross reference between named entities, and entity repetition. This paper proposes to solve the issues in Malay NER. This study starts by providing Malay online news corpus, gazeteer development, rules development and evaluation. This study focus on nine name entities i.e person, organization, position, date, time, currency, measurement and percentage. Overall the experimental result shows 90.23% precision, 92.13% recall and 91.05% f-measure. The outcome from this research is expected to help other researchers in implementing the Malay NER using rule based approach through the addition of new rules to achieve higher accuracy.

With the fast development of World Wide Web 2.0 has resulted in huge number of reviews where the consumers share their opinion about a variety of products in the websites, forum and social media such as Twitter and Instagram. For the organizations, they have to analyze customer's behavior to find new market trends and insights. Sentiment analysis concept used to extract the positive, negative or neutral sentiment of the features from the unstructured data of product reviews. In this paper, we explore the techniques and tools used to enhance the ontology-based approach. Combination of ontology-based on Formal Concept Analysis (FCA) which a process of obtaining a formal ontology or a concept hierarchy from a group of objects with their properties and K-Nearest Neighbor (KNN) to classify the reviews. We believe with these techniques, we are able to view the strength and weakness of the product in more detail where the feature selection process will more be systematic and will result in the highest feature set.

This paper explores the attractiveness and sophistication of Realm of Valor (ROV) using game refinement theory and analyzes its business model by gamification. ROV is one of the most attractive and popular MOBA games in mobile platform. It is free-to-play (F2P) game which is the most popular business model for mobile platform. The result shows that ROV has game refinement value in sophisticated zone that implies entertainment and competitiveness experiences. Moreover, the results are used to make a comparison of platform transformation of MOBA genre which causes from quick time battle characteristics. We also present the result of evolution skin revenue essentially increase over the year due to number of mobile users. Finally, ROV is one of the best examples in monetization while introducing suitable characteristics for the mobile platform such that players can feel entertainment and excitement.

Serious games are games that educate, train and enlighten by using the entertainment principle, creativity and technology. Serious games can provide efficient training in a safe and relatively inexpensive immersive environment. Therefore, it is believed that serious games have the potential to be used in flood training. Flood is a common disaster that happens every year in Malaysia. However, the level of civilians' awareness of flood preparation is still low, while the existing method does not achieve the objectives of The Malaysia Civil Defence Force (APM). The objective of this paper is to present an analysis of flood awareness training preparation among the Malaysians, the existing method on dissemination flood information awareness and the need for technology requirements to carry out the flood awareness training preparation from the experts' perspective. Data was gathered in this study by using the semi structured interview method. Future studies will provide further evidence on the positive impact of using a serious game for flood training preparation, and take into a consideration for the best approach to develop a serious game for flood training to provide and create awareness to the civilians regarding the importance of flood preparedness.

The Board and senior management use internal controls and IT risk governance to ensure that the corporation�s directives such as security policies, standards, procedures, guidelines, administrative rules and practices at all organizational levels are properly chosen and adapted to the organization, implemented and enforced. There were three research problems identified in this paper, lack of involvement of the board and senior management in understanding IS/IT security problems, unbalanced implementation of IS/IT security within the Formal, Technical and Informal components and lack of internal control applications over IS/IT security. This had led to the development of a conceptual framework of IT Security Governance and Internal Controls. Interviews were undertaken with eight Malaysian Publicly Listed Companies to identify the issues that relate to IS/IT Security Governance in Malaysia. The findings reported in the data analysis were consistent with the conceptual framework of IT Security Governance and Internal Controls.

This paper investigates the pedagogical factors affecting the implementation of ICT applications on teaching and learning English from the instructors' point of view. It also discusses the instructors' practices in using online tools for English departments. Using a mixed method approach, this study selected 57 instructors from various universities in Iraq to be involved in the survey and 7 respondents were selected for in-depth interview. The study has shown that the instructors have demonstrated positive attitudes towards ICT application in EFL classroom as they claimed that the technology helps in creating conducive environment for effective teaching and learning. However, in order for the universities in Iraq to use ICT applications comprehensively, there is a need for the teachers to be trained to use computers, online facilities, graphic and multimedia, electronic communication, video and animation in classroom environment.

Using technology has proven to be effective in teaching and learning the English language. With the emergence of the fourth industrial revolution mentioned in Davos 2016, the use of technology in learning and teaching the English language needs to be explored. There is an increasing pressure exercised by the advancements of technology in education. Recently, the use of technology for teaching has become an integral part of successful learning and teaching languages in many parts of the world. Researchers suggested that successful implementation and usage of educational technologies depends mainly on the willingness of teachers as they are the main component in the classroom, who eventually decide on whether to integrate them or not and on how they are to be used in the classroom. The purpose of this qualitative study, therefore, is to measure the English language teachers' readiness and willingness to use the technology in teaching the English language in the era of the fourth industrial revolution. Ten in-service English language teachers participated in the structured and semi-structured interviews. The findings of the interview showed that the English language teachers are not ready yet to use the technology in teaching the English language some ideas were revealed through the interviews 1) traditional and cultural ways of teaching 2) the understanding and attitudes towards technology 3) obstacles hinder teachers from using technology. Finally, the paper presented a number of implications and recommendations that include providing training programs for teachers and forums with experts of the fourth industrial revolution. The policy must be formulated to encourage teachers to use technology to improve the Arab teachers and students' use of the new technology in teaching and learning spaces.

Software has become one of the most critical parts of a measuring instrument. Despite the sophistication and complexity of measuring instruments, legal metrology framework on the software are still poor. Several legal cases related to manipulation and modification of software used in measuring instrument have been discovered in ASEAN countries particularly in Malaysia. A survey has been conducted and shows that most ASEAN countries have yet to implement and enforce legal metrology control on the software in their metrological system. This paper discussed an approach to legalizing software for measuring instrument in the Malaysian context.

Automatic gender identification is one of the appealing fields of research with numerous practical applications. However, this issue has not gained its deserved attention, in particular in the presence of environmental noises. In this paper, using the empirical mode decomposition (EMD), some new and improved mel-frequency cepstral coefficient (MFCC) features are developed to address this problem. In the proposed approach, EMD is employed as a filter bank to decompose the speech signal into its frequency bands. Furthermore, another variant is also developed in which the complete ensemble EMD (CEEMD) supersedes the EMD. Moreover, support vector machine (SVM) with radial basis function (RBF) kernel is employed for classification. Performance of these methods is examined for gender identification, in noise-free environments as well as in the presence of various Gaussian and non-Gaussian noises. Simulation results show that, although with fewer features used, utilizing the improved EMD-based cepstral features in noiseless situations leads to the same accuracy as that of the original MFCCs. However, in noisy environments the proposed methods outperform the conventional way of extracting the MFCCs.

Software as a Service (SaaS) model has been frequently applied in organisation that used cloud services. SaaS is a new Information Technology that provides dynamic services through Internet to the user. Alhough this technology is beneficial and cost-effective for information technology hosting, it also introduced new threats and risks, particularly in user's information security. The paper identifies risk in data security of the SaaS Model and their respective mitigation control based on ISO/IEC 27001:2013 standard. A qualitative case study was conducted at a public sector agency involving three types of data collection, interviews, observations and document analysis. We identified seven risk of data security for SaaS Model namely data privacy, data integrity, data availability, data control, data encryption, data violation, and data access. The findings can be used to develop SaaS implementation guidelines or policies, particularly in data security.

A free conversation system that can freely talk with users is a typical human-like computer that can enrich our daily life. As knowledge used for the free conversation system, this paper proposes a method to automatically acquire anecdotes of various people from Web. First, passages that are related to a given person are retrieved by search of relevant web pages and segmentation of the obtained pages. Then, each passage is judged whether it is the anecdote by several rules based on linguistic features of the anecdotes. The experimental results showed that the precision of our method was increased by 25% comparing to the baseline.

This paper explores the effects of the winning streak on users' motivation and engagement in Duolingo's language course. The winning streak has been used in sport and video games to describe a consecutive number of successful actions and increase players' attention to complete their goal. Similarly, in gamified education system, the winning streak is employed as a game element to boost up motivation of learners. By applying game refinement theory as an assessment method, enjoyment of two user groups in Duolingo is measured to compare. The results indicate that the winning streak can boost up learners' motivation and attention to complete their goals. It also expressed that the winning streak is more significant for advanced learners who are in the high level of milestone than those who are in the low level of milestone.

Integrating the new technologies to improve the healthcare services can be seen as one of the research trends nowadays, as earlier studies have recommended the potential of emerging technologies in enhancing healthcare service practices by means of providing more opportunities to carry out activities essential for prevention, diagnosis, monitoring, and treatment of the disease. Involving the cloud computing services in healthcare domain can offer a way for handling and maintaining health data by making use of software applications hosted on the Internet. To ensure successful cloud computing utilization, a pre-examination on the context of usage should be applied in order to collect the real needs to guarantee getting all the possible benefits of this technology. In Iraq, the health records of public hospitals consist of various types of data which continue to increase in velocity, volume, and variety progressively. This has led to several major issues to the health sectors from two perspectives, data complexity and low IT integrity. For that reason, managing and maintaining all these health data are essential to healthcare organizations. In this paper, we collected the success factors that may influence the healthcare professionals to utilize cloud computing services for the health sector in Iraq. This is done by conducting an interview with 30 physicians and technicians from four hospitals in Iraq, then a literature survey was carried out to verify that all the gathered factors are within the circumstance of healthcare. It has been found that eight factors may affect the perspective of healthcare professionals to utilize cloud computing services. Finally, a conceptual model was developed based on the findings.

Automatic text categorization (ATC) has attracted the attention of the research community over the last decade as it frees organizations from the need of manually organized documents. The ensemble techniques, which combine the results of a number of individually trained base classifiers, always improve classification performance better than base classifiers. This paper intends to compare the effectiveness of ensemble with that of base classifiers for Malay text classification. Two feature selection methods (being the Gini Index (GI) and Chi-square) with the ensemble methods are applied to examine Malay text classification, with the intention to efficiently integrate base classifiers algorithms into a more accurate classification procedure. Two types of ensemble methods, namely the voting combination and meta-classifier combination, are evaluated. A wide range of comparative experiments are conducted to assess manually classified Malay corpus. The applied experiments reveal that meta-classifier ensemble framework performed better than the best individual classifiers on the tested datasets.

The factual software architectures that are actually implemented of distributed systems do not conform the planned software architectures (Beck 2010). It happens due to the complexity of distributed systems. This problem begets two main challenges; First, how to extract the factual software architectures with the proper techniques and second, how to compare the planned software architecture with the extracted factual architecture. This study aims to use process mining to discover factual software architecture from codes and represents software architecture model in Petri Net to evaluate model by the linear temporal logic and process mining. In this paper, the applicability of process mining techniques, implemented in the ProM6.7 framework is shown to extract and evaluate factual software architectures. Furthermore, capabilities of Hierarchical Colored Petri Net implemented in CPN4.0 are exploited to model and simulate software architectures. The proposed approach has been conducted on a case study to indicate applicability of the approach in the distributed data base system. The final result of the case study indicates process mining is able to extract factual software architectures and also to check its conformance.

The elderly population is growing every year. Most of them are retirees. The number of elderly are significantly increasing in the near future. Therefore, it is important to see them as a large scale users of technology. However, the information system that exists is mostly general and not specific to a particular group. For the elderly, this is a constraint for those who have certain deficiencies such as having reduced visibility, movement, and deterioration of cognitive skills. It is essential to conduct a study to identify the problems faced by the elderly in using existing information system. Therefore, the objective of this paper is to discuss the construction of a usability guideline for elderly website interface. The study began by identifying the problems faced by the elderly to the usability of the current information systems that are available interviews. Usability characteristics of information systems that are suitable to the elderly are identified and a guideline for the elderly interface usability of information systems is constructed. These guideline illustrates that a friendly website interface for elderly are sites that provide usage facilities to the elderly such as simple language, large font size, navigation that is easy to use and has a combination of media such as video and audio. These guidelines are used to develop usability's website interface for elderly. The website evaluation is conducted to assess the usability features used in the design. The website is tested by target users. Feedback from the elderly is used to enhance the interface to become more usable and can serve as a reference for web developers.

Postgraduate Student Management Information System (PSMI) is developed for managing the academic matters of postgraduate students, such as registration, appointment of supervisor, proposal defence, appointment of examiners and managing oral defence examination. The system which is known as SMASH was developed in the Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia to facilitate the task of the Graduate Management Unit. However, SMASH is rarely used due to usability problems. Among the problems are, the administrative staffs are not aware of the graduate programs applications which are made through SMASH. There is a lack of functionality especially on the menu and the design of the interface. SMASH provides functionality that is limited to only download the application form. This paper discusses the usefulness model development that can be used as a guideline to improve the system. The usefulness model is developed by adapting IS0 9241 and ISO 9126 usability standards. This study employs User-Centered Design method which involves students and faculty administrative staffs. This study starts by identifying the usability problems through Heuristic Evaluation and analysing the user requirements through the system analysis and interview. The preliminary study discovers that there is a need for improvement in the interface design and the functionality of the system to meet user requirements. The user requirement analysis and the proposed improvement serves as the basis in redesigning the system prototype. The usefulness model is then verified by 30 respondents through survey.

In a natural user interface (NUI) interaction, users no longer need to use the input device to interact with a computer such as a keyboard or remote control. There are a number of issues mainly on misinterpretations of gestures that are often reported in NUI research. Among the user group is children. A study was conducted to explore the needs among children in understanding NUI interaction. This paper presents a NUI prototype in learning prayers among children. Event Driven Gesture Sequence Mechanism (EDGSM) was implemented in the prototype to address misinterpretations of gestures. This study aims to evaluate the ability of NUI prototype in learning and experience of children in learning prayers. The analysis found that the assessment of learning of NUI able to improve the learning performance and a better experience compared to traditional learning via video. However, the NUI prototype, which is not equipped with EDGSM mechanism, showed no significant increase in learning performance. The prototype equipped with EDGSM showed a significant result and managed to reduce misinterpretation of gestures by 43.27% compared to the prototype using standard mechanisms. This study indirectly encourages NUI designers and developers to focus on the problem of gestures misinterpretation and concern on the needs and capabilities of users, especially children.

Sentiment lexicon is a list of vocabularies that consists of positive and negative words. In opinion mining, sentiment lexicon is one of the important source in text polarity classification task in sentiment analysis model. Studies in Malay sentiment analysis is increasing since the volume of sentiment data is growing on social media. Therefore, requirement in Malay sentiment lexicon is high. However, Malay sentiment lexicon development is a difficult task due to the scarcity of Malay language resource. Thus, various approaches and techniques are used to generate sentiment lexicon. The objective of this paper is to develop Malay sentiment lexicon generation algorithm based on WordNet. In this study, the method is to map the WordNet Bahasa with English WordNet to get the offset value of a seed set of sentiment words. The seed set is used to generate the synonym and antonym semantic relation in English WordNet. The highest result achives 86.58% agreement with human annotators and 91.31% F1-measure in word polarity classification. The result shows the effectiveness of the proposed algorithm to generate Malay sentiment lexicon based on WordNet.

Aspect-Oriented Software Engineering provides new ways to produce and deliver products and ultimately leads to reliable software. Reliability is an extremely important issue contributing to the quality of software. Thus, software engineers need proven mechanisms to determine the extent of software reliability. In this paper, a method for assessing reliability is proposed which takes advantage of a multilayer perceptron neural network. Furthermore, an imperialist competitive algorithm is used to optimize the weights to improve network performance. Finally, relying on root square mean error, the proposed approach is compared to a hybrid neural network-genetic algorithm method. The results show that the proposed approach exhibits lower error.

Most ICT projects failed due to various factors including organizational issues and leaders who did not sufficiently assess organizational readiness for change. Although various perspectives and criteria have been used by researchers to measure organizational readiness, reported evidence on its measurement in information systems (IS) adoption is still limited and unclear, which calls for clarification and further studies. The purpose of the paper is to discuss the evaluation of IS adoption in organizational readiness using an extended organizational readiness framework and to identify the factors that influence organizational readiness in IS adoption. A case study was conducted on the Human Resource Management Information System (HRMIS) based on the Framework of Organizational Readiness at the Public Service Department (PSD) of Malaysia. This qualitative study involved interviews, observations and document analysis. The study found that the PSD is set to implement the HRMIS but the issues and problems identified as pertaining to the HRMIS must be addressed and dealt with immediately in order to achieve the system objectives. A number of factors influencing organizational readiness were identified in the adoption of the HRMIS: Attributes of the Change (vision clarity, change appropriateness and change efficacy), Leadership Support (top management support, presence of an effective champion, and IT support), Internal Context (organizational history of change, organizational conflicts and policies, and organizational flexibility) and Attributes of the Change Targets (collective self-efficacy and user training). Although our case study focused on a specific setting, the identified factors and proposed framework extension is potentially useful for assessing other information systems in different settings; the findings could act as a guide for assessing organizational readiness prior to the adoption of information systems.

Malay language is an agglutinative language which rich morphology. Affixation to a root word is the most common morphological processes used to derive a new word for other meaning that would affect the change in their part of speech (POS). Malay annotated corpus is not freely available, so there is no publication report on the comparison of the performance of POS tagging using Hidden Markov Model (HMM), Maximum Entropy (ME) and Support Vector Machine (SVM), especially to look into the effect of Malay morphology for tagging unknown words. This paper aims to present the evaluation of TnT using HMM, MaxEnt using ME and SVMTool using SVM. In order to train and test such methods in tagging Malay language, efforts has been taken to annotate the Malay corpus in health domain. Modifications has been done to TnT to fit in prefix and circumfix features. The results of the experiments shows that SVMTool outperforms TnT and MaxEnt for overall accuracy (99.23% for SVMTool, 94% for TnT and 96% for Maxent) and tagging unknown words accuracy (96.78% for SVMTool, 67% for TnT and 86.23% for MaxEnt ). MaxEnt outperforms TnT for the overall accuracy and tagging unknown words. As the tagging accuracy of SVMTool to unknown word succeeds 96.78%, it would be the best tool for tagging Malay language for a specific domain.

The expansion of communication systems is the undeniable advantage of the most contemporary digital technologies. However, when a specialist user such as an inventor or an idea owner communicates through a communication system, their intellects are exposed to theft. Upon the analysis of the requirements of such users, it became evident that in order to implement a global, reliable, yet secure system for specialist users, designing a network architecture that provides centralized private connectivity is crucial. This paper proposes a network architecture that provides centralized private connectivity and accommodates the requirements of the network infrastructure of such a system. The proposed virtual private network (VPN) architecture is designed to provide a trusted environment with centralized control and distributed networking, which is different from existing VPN models. It is entitled as Inventor-Investor Network (IINet) and the name is derived from its significant benefits for inventor and investor sets of users. The real experimental IINet prototype is implemented using OpenVPN. For the purpose of evaluation, round trip time (RTT) is measured and reported as the performance metric based on the different encryption ciphers and digest ciphers as the network metrics.