Interacted Multiple Ant Colonies Optimization (IMACO) is a newly proposed framework. In this framework several colonies of artificial ants are utilized. These colonies are working cooperatively to solve an optimization problem using some interaction technique. Exploration technique is doing an essential job in this framework. This technique is responsible for directing the activity of utilized colonies towards the different parts of the huge search space. This paper describes the newly proposed IMACO framework and proposes an effective exploration technique. Computational tests show that the new exploration technique can furthermore improve the IMACO performance. These tests also show the capability of IMACO to outperform other well known ant algorithms like ant colony system and max-min ant system.

In Information Technology related programs, computer programming courses are made compulsory subjects in most institutions of learning. However there are many reports on poor performance among students in such courses. Previous studies examined some of the variables influencing students' performance using statistical data analysis. The critical point of this study is the use of classification algorithm to extract patterns which are examined from the cognitive factor specific learning style. The findings show that that student's good performance in programming courses has a visual, active and sequential learning style.

Technological advancements and rapid growth in the use of the Internet by the society have had a huge impact on information security. It has triggered the need for a major shift in the way web applications are developed. The high level security of these applications is crucial to their success. Therefore, information security has become a core requirement for producing trustworthy software driven by the need to guard critical assets. To develop a web application with adequate security features, it is highly recommended to capture security requirements early in the development lifecycle. In this paper, we propose a way of extending the V-Model requirements engineering phase to aid developers to engineer security requirements for a web application being developed, as well as, handling the security test planning. The aim is to support the proactive definition of security requirements by integrating security requirements engineering ( SRE) activities with requirements engineering ( RE) activities of the V-model.

Intrusion Detection Systems (IDS) are very important in determining how secure a system is, and to discover several types of attack such as Denial of Service (DOS), Probes and User to Root (U2R) attacks. However, recently false alarm rates and accuracy of detection are happens to be the most important issues and challenges in designing effective IDS. Therefore, this study is aimed at detecting denial of services attack and normal traffic using Knowledge Discovery and Data Mining Cup 99(KDD CUP 99) dataset to reduce the false alarm rates. Data mining is used to extract the useful information from large databases. The results have shown that the data mining technique reduces the false alarm rates and increase the accuracy of the system.

With the proliferation of the digital crime around the world, numerous digital forensic investigation models are already being developed. In fact, many of the digital forensic investigation models focus on technical implementation of the investigation process as most of it were developed by traditional forensic expert and technologist. As an outcome of this problem, most of the digital forensic practitioners focus on technical aspect and forget the core concept of digital forensic investigation model. In this paper, we are introducing a new digital forensic investigation model which will capture a full scope of an investigation process based on Malaysian cyber law. The proposed model is also compared with the existing model which is currently available and being applied in the investigation process.

Reservoir is one of the emergency environments that required fast an accurate decision to reduce flood risk during heavy rainfall and contain water during less rainfall. Typically, during heavy rainfall, the water level increase very fast, thus decision of the water release is timely and crucial task. In this paper, intelligent decision support model based on neural network (NN) is proposed. The proposed model consists of situation assessment, forecasting and decision models. Situation assessment utilized temporal data mining technique to extract relevant data and attribute from the reservoir operation record. The forecasting model utilize NN to perform forecasting of the reservoir water level, while in the decision model, NN is applied to perform classification of the current and changes of reservoir water level. The simulations have shown that the performances of NN for both forecasting and decision models are acceptably good.

This paper proposes Hybrid Intelligent Water Drops (HIWD) algorithm to solve Tamhidi programs uncapacitated examination timetabling problem in Universiti Sains Islamic Malaysia (USIM). Intelligent Water Drops algorithm (IWD) is a population-based algorithm where each drop represents a solution and the sharing between the drops during the search lead to better drops. The results of this study prove that the proposed algorithm can produce a high quality examination timetable in shorter time in comparison with the manual timetable.

The Internet of Things (IoT) is the interconnection of uniquely identifiable embedded computing devices within the existing Internet infrastructure. Typically, internet of things (IoT) is expected to offer advanced connectivity of devices, systems, and services that goes beyond machine-to-machine communications (M2M) and covers a variety of protocols, domains, and applications. The interconnection of these embedded devices including smart objects, is expected to usher in automation in nearly all fields, while also enabling advanced applications like a Smart Grid. The main research challenge in Internet of things (IoT) for the forensic investigators is based size of the objects of forensic interest, relevancy, blurry network boundaries and edgeless networks, especially on method for conducting the investigation. The aim of this paper is to identify the best approach by designing a novel model to conduct the investigation situations for digital forensic professionals and experts. There was existing research works which introduce models for identifying the objects of forensics interest in investigations, but there were no rigorous testing for accepting the approach. Currently in this work, an integrated model is designed based on triage model and 1-2-3 zone model for volatile based data preservation.

Reservoir water release decision is one of the critical actions in determining the quantity of water to be retained or released from the reservoir. Typically, the decision is influenced by the reservoir inflow that can be estimated based on the rainfall recorded at the reservoir's upstream areas. Since the rainfall is recorded at several different locations, the use of temporal pattern alone may not be appropriate. Hence, in this study a spatial temporal pattern was used to retain the spatial information of the rainfall's location. In addition, rainfall recorded at different locations may cause fuzziness in the data representation. Therefore, a hybrid computational intelligence approach, namely the Adaptive Neuro Fuzzy Inference System (ANFIS), was used to develop a reservoir water release decision model. ANFIS integrates both the neural network and fuzzy logic principles in order to deal with the fuzziness and complexity of the spatial temporal pattern of rainfall. In this study, the Timah Tasoh reservoir and rainfall from five upstream gauging stations were used as a case study. Two ANFIS models were developed and their performances were compared based on the lowest square error achieved from the simulation conducted. Both models utilized the spatial temporal pattern of the rainfall as input. The first model considered the current reservoir water level as an additional input, while the second model retained the existing input. The result indicated that the application of ANFIS could be used successfully for modeling reservoir water release decision. The first model with the additional input showed better performance with the lowest square error compared to the second model.

Reservoir is one of the structural approaches for flood mitigation and water supply. During heavy raining season, reservoir operator has to determine fast and accurate decision in order to maintain both reservoir and downstream river water level. In contrast to less rainfall season, the reservoir needs to impound water for the water supply purposes. This study is aimed to model human expert decision making specifically on reservoir water release decision. Reservoir water release decision is crucial as reservoir serve multi purposes. The reservoir water release decision pattern that comprises of upstream rainfall and current reservoir water level has been form using sliding window technique. The computational intelligence method called artificial neural network was used to model the decision making.

The reservoir is one of flood mitigation methods that aim to reduce the effect of flood at downstream flood prone areas. At the same time the reservoir also serves other purposes. Through modelling, how the reservoir operator made decisions in the past can be revealed. Consequently, the information can be used to guide reservoir operator making present decision especially during emergency situations such as flood and drought. This paper discussed modelling of reservoir water release decision using Neural Network (NN) and the temporal pattern of reservoir water level. Temporal pattern is used to represent the time delay as the rainfall upstream may not directly raise the reservoir water level. The flow of water may take some time to reach the reservoir due to the location. Seven NN models have been developed and tested. The findings show that the NN model with 5-25-1 architecture demonstrate the best performance compare to the other models.

Student's placement in industry for the industrial training is difficult due to the large number of students and organizations involved. Further the matching process is complex due to the various criteria set by the organization and students. This paper will discuss the results of a pattern extraction process using a clustering algorithm that is k-means. The data use consists of Bachelor of Information Technology and Bachelor in Multimedia students of Universiti Utara Malaysia from the year 2004 till 2005. The experiments were conducted using undirected data and directed data. The pattern extracted gave information on the previous matching process done by the university.

Digital Quran is a natural language document that use either Arabic font or images of the verses. In the Al-Quran there are 18994 unique words. Thus, the image approach uses a significant amount of memory space. However there is not much work has been done using machine translation (MT) technique for the Quranic representation. This paper will proposed Arabic information retrieval based on keywords search in Hexadecimal Representation using Al-Quran verses as the test case. All Quranic words will transliterate into machine language in the form of binary format after removing diacritic and duplication. This machine language approach in representing Digital Quran reduces the size of storage around 47-54% and retrieval time up to 20% hence reduce the query cost for Arabic information retrieval in general.

Scheduling university timetabling for large numbers of students is a difficult task especially to ensure no overlapping. Most of timetables are prepared manually, or at best with the help of a spreadsheet program. However, a manual process requires numbers of verification by domain experts (for example lecturers, supervisors) before it can be approved. In this research, we focus on a solution to the university timetabling problem. We will consider various soft and hard constraints of time tabling parameters such as a number of subjects ("subject"), a number of lecture or tutorial sessions ("time slots"), a number of classrooms ("sessions"), number of teachers ("teacher"), number of students ("student") and number of workloads ("workload"). We use methods based on simulated annealing to obtain optimal and sub-optimal solutions to scheduling problems. We will illustrate our work on timetabling issues of Tamhidi Programme at Universiti Sains Islam Malaysia as our case study. (C) 2013 The Authors. Published by Elsevier Ltd.

This research article aims at proposing Intelligent Water Drops (IWD) algorithm to solve the university examination timetabling problems (UETP). IWD is a recent metaheuristic population-based algorithm belonging to swarm intelligent category which simulate river system. Examination timetabling is a combinatorial optimization problem that is concerned with allocating exams to timeslots efficiently. As an initial study, the IWD Algorithm is tailored to solve uncapacitated examination timetabling problem by using carter 1996 dataset and is able to produce acceptable results, though they were not better than the the results that already reported in the literature. Some examination timetabling heuristic methods such as Saturation degree concepts have been embedded in IWD to ensure the feasibility, while the IWD operators have been trigged to iteratively improve the results.

Digital Quran is a common application today in smart devices such as hand phones and tablet. The verses are usually presented using images of verses on written in an Arabic font. This raise issues related to storage when representing the whole Quran text. This study proposed a hexadecimal digital representation technique for words in Arabic using UTF-8 for character encoding which is backward compatible with ASCII code. This paper will explain three approaches used in representing the digital Quran. They are the hexadecimal representation for each Quranic words, sparse matrix in representing verses of Al-Quran and double offset indexing for transforming the sparse matrix to efficiently use the space. This representation proof more than 50% reduction in the memory space for storage thus will increase the searching speed. The storage of words being optimized through the use of one memory space for that particular word rather than one memory space for each Arabic character in the words. This technique helps optimized memory management for the whole digital Quran. Due to the smaller size, the digital Quran can be conveniently installed in the future as standard applications in mobile devices.

In recent years, web security has been viewed in the context of securing the web application layer from attacks by unauthorized users. The vulnerabilities existing in the web application layer have been attributed either to using an inappropriate software development model to guide the development process, or the use of a software development model that does not consider security as a key factor. Therefore, this systematic literature review is conducted to investigate the various security development models used to secure the web application layer, the security approaches or techniques used in the process, the stages in the development model in which the approaches or techniques are emphasized, and the tools and mechanism used to detect vulnerabilities. The study extracted 499 publications from respectable scientific sources, i.e. the IEEE Computer Society, ACM Digital Library, Google-Scholar, Science Direct, Scopus, Springer Link and ISI Web. After investigation, only 43 key primary studies were considered for this review based on defined inclusion and exclusion criteria. From the review, it appears that no one development model is referred to as a standard or preferred model for web application development. However, agile development models seem to have gained more attention, probably due to the multiple stakeholders that are involved in discussing security viewpoints, rather than a few members of the development team. It appears also that there is consistency in the use of the threat-modeling technique, probably due to its effectiveness in dealing with different kinds of vulnerabilities.

Information Security Management System (ISMS) goal is to provide a comprehensive approach to information security in the organization where timely detection and reporting will improve preventive measures and responses to incidents that could lead to organization good name and minimize financial losses. This paper presents a study on the current awareness of university hospitals on ISMS and the role of management in the decision policy of its implementation. In the literature review explain the importance of ISMS in the industry. The focus of the study is on data protection. Based on the findings, the awareness level is still unsatisfactory and need to improve to protect customers or patients' data. It required the full commitment from the management to implement the ISMS.

Social Networking Sites (SNSs) have become a global experience, with communities such as Facebook, MySpace and Friendster which they are reporting user figures in the hundreds of millions. People, have been invited into or chosen to join these communities are able to publish multimedia content about themselves, their interests and concerns. With intensive information been shared, privacy concern are rising up because Social networks privacy is different from the classic privacy setting that cause a lot of problems such as exposing sensitive information. On the other hand privacy model should be designed to facilitate user's requirements, which mean that users are, supposed to set up their own privacy setting. Since it's still not well defined and need to be improved and studied further. However, to solve this is by providing a more private platform with the ability for users to set their own privacy settings. The privacy model can be so general to more complicated, but all of them are still not clear for users to be aware off. The new model we are proposing will solve the privacy issues since it's done by users and monitored by developers. This research will point out some problems, and how to solve these problems by proposing a new user oriented privacy model for social networks. (C) 2014 The Authors. Published by Elsevier Ltd.

One of the most challenges facing the developing countries and standing in the way of their growth are remnants of war and landmines. These countries have inherited this legacy during the World War I and II which represents a major threat to lives. Furthermore, it hinders reconstruction and development efforts. The aim of this research is to find a low cost alternative for protecting and warning people about landmines risk during practicing their daily lives. In this context, this paper presented the design and development of a Wireless Landmines Tracking System (WLTS) using smart phone. The Android software development kit (SDK) has been used to develop this system. This system is really very helpful for the users who live near mine affected areas to track their children and themselves through mobile phones from landmines risk.