In this paper, classification of brain wave using real-world data from Parkinson's patients in producing an emotional model is presented. Electroencephalograph (EEG) signal is recorded on eleven Parkinson's patients. This paper aims to find the "best" classification for brain wave patterns in patients with Parkinson's disease. This work performed is based on the four phases, which are first phase is raw data and after data processing using statistical features such as mean and standard deviation. The second phase is the sum of hertz, the third is the sum of hertz divided by the number of hertz, and last is the sum of hertz divided by total hertz. We are using five attributes that are patients, class, domain, location, and hertz. The data were classified using WEKA. The results showed that BayesNet gave a consistent result for all the phases from multilayer perceptron and K-Means. However, K-Mean gave the highest result in the first phase. Our results are based on a real-world data from Parkinson's patients.

Mobile reporting applications are useful mainly for reporting real-time issues related to public infrastructure, environmental or social incidents through smart mobile devices. The credibility of the cases reported are often a great challenge because users may report false information and as a result this affects the response team in the aspect of time, energy and other resources. Researchers in the past have developed many report trust estimation algorithms that focuses on user's location, behavior and reputation. We aim to analyze the textual part of a report. Text analyses have been used for email spam filtering and sentiment analysis but have not been used for false report identification. Therefore, the purpose of this study is to compare different text classification algorithms and propose a suitable classifier for distinguishing the genuine and fake reports. The comparative analysis can be used by other researchers in the area of false report or fake message identification.

In this research, a false report identification algorithm for mobile application is developed using a text classification technique. This algorithm is proposed to be applied to a reporting service application in an IoT environment. The algorithm is aimed to distinguish reports into true and false information. Support Vector Machine (SVM) is used as the text classifier because it has proven to be the most popularly used due to its good performance and higher accuracy compared to the other techniques such as Naive Bayes, Decision Tree and K-Nearest Neighbours. The algorithm is designed and developed in R Studio and we built a framework to show how the algorithms can be adapted into a reporting service application. The results show that the algorithm has successfully classified the reports.

Individual user and organizations benefit from cloud computing services, which allow permanent online storage of files. The problem occurs when companies store highly confidential documents in cloud servers. Therefore, this paper aims to introduce a backbone structure for a cloud storage system where the security and personal privacy is highly maximized. It is very obvious that cloud computing servers are highly protected against unauthorized access, but in some cases these files stored can be accessible by the maintenance staffs. Fully protection is needed to ensure that the files stored in the server are only accessible to owners. This paper proposes a system that will employ Rivest-Shamir-Adleman (RSA) and Advanced Encryption Standard (AES) combination encryption process using USB device. The files may be accessed in the cloud but all the files will remain encrypted till the USB device is plugged into the computer. The point of applying such method is to fully protect the files and avoid using one single password. The randomly generated passkeys are very complex combinations thus user will not be able to fully memorize them. The proposed system will detect the USB that contains the private-key used for the files to be downloaded from the cloud.

RE as an alternative source of energy in Malaysia is still at premature stage of its development and adoption. This is mainly due to lack of public awareness and participation toward new technology advancement. Therefore, the objective of this paper is to determine and present a proposed theoretical model on the relationship between public participation by measuring their willingness to pay for energy generated from RE resources and its determinants that influenced the willingness to pay level. Awareness on RE, degree of knowledge on RE, willingness to adopt RE technology, environmental concern and attitude toward RE usage are constructed as the five selected determinants. The relationship between the determinants and public participation is illustrated using theoretical framework because it allows the reader to understand how public participation that measured by willingness to pay level are being influenced. Thus, ten hypotheses on the correlation and causal effect between the dependent and independent variables are developed. Quantitative research methods will be used to achieve the research objectives. A questionnaire on 5-point likert scale will be developed and collected from 500 respondents through systematic sampling method at Kiang Valley, Malaysia. Correlation of the variables will be analyzed using SPSS version 20.0 and ordered probit model will be used to measure the causal effect between the variables. These efforts are useful to ensure future success of RE development in Malaysia.

Image segmentation is an important phase in the image recognition system. In medical imaging such as blood cell analysis, it becomes a crucial step in quantitative cytophotometry. Currently, blood cell images become predominantly valuable in medical diagnostics tools. In this paper, we present an adaptive hybrid analysis based on selected segmentation algorithms. Three designates common approaches, that are Fuzzy c-means, K-means and Mean-shift are adapted. Blood cell images that are infected with malaria parasites at various stages were tested. The most suitable method will be selected based on the lowest number of regions. The selected approach will be enhanced by applying Median-cut algorithm to further expand the segmentation process. The proposed adaptive hybrid method has shown a significant improvement in the number of regions.

Agent-based IDS is a powerful technique used by network administrator to monitor traffic activities in their network. However, the widespread network coverage has introduced a possibility of a hacker installing unauthorized agents or fake agents secretly within the network. This is considered as a very serious threat to the network security. This paper proposes a protocol that is used to detect the presence of a fake agent upon its installation. The technique is a combination of Elgamal encryption, Elgamal digital signature, and SHA-1 message digest function. A simple implementation was developed to test the proposed protocol.

The paper studied the integration of logarithmic singularity problem J ((y) over bar) = integral integral(del) zeta((y) over bar) log vertical bar(y) over bar = (y) over bar (0)*vertical bar dA, where (y) over bar = (alpha, beta), (y) over bar (0) = (alpha(0), beta(0)), the domain del is rectangle (y) over bar [r(1), r(2)] x [r(3), r(4)]; the arbitrary point (y) over bar is an element of del and the fixed point (y) over bar (0) is an element of del. The given density function zeta((y) over bar), is smooth on the rectangular domain del and is in the functions class C-2,C-tau (del). Cubature formula (CF) for double integration with logarithmic singularities (LS) on a rectangle del is constructed by applying type (0, 2) modified spline function D-Gamma(P). The results obtained by testing the density functions zeta((y) over bar) as linear and absolute value functions shows that the constructed C-F is highly accurate.

Leukemia is a cancer of white blood cells that affect the blood forming cells in the body. Acute Myeloid Leukemia (AML) is a form of leukemia and are caused by replacement of normal bone marrows with leukemic cells, which cause a drop in red blood cells, platelets, and normal white blood cells. Early classification of the subtype of AML cells is necessary for proper treatment management. We classify the subtype based on the features of AML cells, which include the nuclei and cytoplasm. In this paper, we developed an automate method for the nuclei and cytoplasm detection from the blood cells images that are captured as microscope images. In contrast to other methods that focus on identifying the nuclei, we proposed a method based on the color conversion, intensity threshold and gradient magnitude. Our method detected both the nuclei and the cytoplasm at the same time. We test our method on 301 images, which contain 643 AML cells. The accuracy of both nuclei and cytoplasm detection is over 82.9% (increase 17% when was compared with the existent method).

Prior conducting malware analysis, many researchers were facing difficulties to clean up the dataset and they took longer time to complete these processes due to lack of malware dataset that are free from any noise or any irrelevant data and lack of malware analysis skill. Therefore, an efficient Easy Computer Emergency Response Team Malware Reservoir System (eZCERT) has been developed to overcome such problems. It is a comprehensive and an efficient malwares incident handling system where it consists of standard operating procedures (SOP) for malware incident handling. It also has the capability to detect and respond to malware attacks. Furthermore, the novelty of this system is based on the integration of the incident response, apoptosis, case-based reasoning (CBR) and Knowledge Data Discovery (KDD). The evaluation testing result showed that the eZCERT managed to produce a better accuracy detection rate. Hence, this eZCERT can he used as the basis guideline for malware researchers in building malware dataset and doing malware analysis.

Ontology analysis has been shown to be an effective first step in the construction of robust knowledge based system. Moreover, the popularity of semantic technologies and the semantic web has provided several beneficial opportunities for the modeling and computer security communities of interest. This paper describes the role of ontologies in facilitating network security modeling. It outlines the technical challenges in distributed network security simulation modeling and describes how ontology-based methods may be applied to address these challenges. The paper concludes by describing an ontology-based solution framework for network security simulation modeling and analysis and outlining the benefits of this solution approach.

Authentication plays a significant role in computer security to validate human users. CAPTCHA is one of human interaction proof test to verify whether user is a human or a computer program. It has become a very popular security mechanism used to prevent any automated abuse of online services which is intended for human user. The test usually is provided in the authentication phase where the user will be directed to the next page if they are authorized. From the login site, an attacker creates a program exploiting the username and password to get into a website. Recently, there are a lot of different types of CAPTCHA available on the internet. However, most of them have been successfully attacked by automated programs. Thus, this paper investigates existing related works on CAPTCHA which focus on login authentication and authorization by proposes a different approach using Jawi script. Based on investigations of the systematic review and preliminary findings, it shows that this is the first work that proposed using a different script and possible future directions for producing more reliable human/computer distinguishers. Future works will develop an alternative and stronger CAPTCHA to prevent breaking cyber-attack such as dictionary attack while maintaining ease of implementation on website and ease of use for human by reducing the difficulties on reading the CAPTCHA.

Immune system is essential to human body as it protects our bodies from pathogens in an orchestrated manner. From a computational viewpoint, the immune system has much to offer by way of inspiration. Recently, there has been growing interest in the use of natural immune system as inspiration for the creation novel approaches to computational problem. This field of research is referred as Immunological Computation or Artificial Immune System. The use of artificial system computer security is an appealing concept for two reasons. Firstly, the human immune system provides human body with a high level protection from invading pathogens in robust manner. Secondly, current techniques used in computer security are not able to cope with the dynamic and increasingly complex nature of computer systems and their security. This paper introduces the concept of apoptosis for computer security. This term is borrowed from cell biology and designates the programmed cell death.

One of the goals of the Malaysian lower secondary EFL curriculum is to prepare students for EFL reading at a higher level of education. In line with this goal, the purpose of the current study was to examine the design of reading tasks in terms of the types with regards to reading in academic areas at the tertiary level. The study was conducted in the Malaysian setting at the secondary school level. The data for the study were collected by reviewing curriculum documents such as the Malaysian Form Three English Language Curriculum Specifications and the Form Three English language textbook. Reading tasks extracted from the curriculum documents were coded using Anderson et al.'s (1991) three major reading task types and an additional category for reading tasks that do not fall into the three major reading task categories. The data for this study were analyzed using manifest content analysis. In terms of preparing students for academic reading in English at the tertiary level, the reading task types in the selected curriculum seems to include training students on major reading task types such as identifying main, ideas, identifying details and making inference. However, statistically, the findings show that the provision for the major task types is much lower than the provision in training students on other skills such as fluency. Such finding has implications on the effectiveness of the curriculum at the instructional implementation level. Hence, based on the findings of this study, there is a need for a curriculum revision in order to achieve the respective curriculum goal.

The goal of the Malaysian EFL secondary reading curriculum is to prepare students for the reading skills that they need to have at the university level. The purpose of the current study was to compare if the designs of two EFL Malaysian secondary reading curricular are in conformant to the curriculum goal. The instruments were the government mandated EFL textbooks for two high school grade-levels. The data were collected via document review using manifest content analysis. Passages in the textbooks under study were selected based on the purpose of the passages. Only passages that are provided for reading comprehension purpose were included in the study. The passages were analyzed in terms of the types and length with regards to the types and length of texts that are frequently encountered at the university level. Based on the review of past studies, the types of passages were analyzed in terms of either narrative or expository texts. The length of passages was analyzed using Leslie and Caldwell's (2004; 2006) Qualitative Reading Inventory (QRI 3 & 4). The findings indicate that the majority of reading comprehension passages in both textbooks is narrative rather than expository. Regardless of text types, the majority of passages are also not at grade-level. Hence, in terms of curriculum design for reading comprehension passages, based on the evidence in this study, it is concluded that the design of both curricular is only partially preparing students for reading in content areas at the university level. With regards to the curriculum goal to prepare students for reading in English at the university level, such design of the Malaysian EFL reading curriculum in terms of reading comprehension materials may enable to partially achieve the curriculum goal.

The holy Quran is the holy book of the Muslims. It contains information about many domains. Often people search for particular concepts of holy Quran based on the relations among concepts. An ontological modeling of holy Quran can be useful in such a scenario. In this paper, we have modeled nature related concepts of holy Quran using OWL (Web Ontology Language) / RDF (Resource Description Framework). Our methodology involves identifying nature related concepts mentioned in holy Quran and identifying relations among those concepts. These concepts and relations are represented as classes/instances and properties of an OWL ontology. Later, in the result section it is shown that, using the Ontological model, SPARQL queries can retrieve verses and concepts of interest. Thus, this modeling helps semantic search and query on the holy Quran. In this work, we have used English translation of the holy Quran by Sahih International, Protege OWL Editor and for querying we have used SPARQL.

There is an ongoing phenomenon among non-English speaking students, particularly at the university level who struggle with reading in English in content areas. One way to alleviate reading problems in English among non-native speaking students is by ensuring that the English language reading curriculum is coherent at all levels. The purpose of the present study was to explore the type of EFL reading comprehension instruction reflected in the Malaysian English language reading curriculum at the levels of Approach and Design and its alignment with the communicative label. The data for the study were collected from the related curriculum documents, which were the Form Five English Language Curriculum Specifications document and also from the Form Five English language textbook. A document review was conducted in order to obtain the data, which were in the form of reading tasks elicited from the selected curriculum documents. Manifest content analysis was used to analyze the data. The findings show that noncommunicative whole Language instructional approach was the most prominent type of SLA instructional approach while for the second language reading instructional approach, the non-interactive reading instructional approach was highly reflected with teacher role primarily inferred as a director. The findings suggest that the instructional approaches reflected in the Malaysian secondary English language reading curriculum is not in alignment with the communicative grounding as an approach to instruction.

This paper focuses on User-Generated (UG) photos in the understudied Arab Muslim World. Over four million public photos on Flickr.com represent Arab countries' UG presence, with Egypt and Palestine the top countries for the respective keywords of travel and Muslim. The findings also reveal varied United Arab Emirates' presence, with ten times more Dubai photos than the next highest emirate Abu Dhabi and two hundred times more than three emirates. At the country level, the results of hypotheses testing showed significant relationships between the presences of public Flickr photos with Arabian Internet connectivity, tourist arrivals and Muslim population.

Panoramic radiographs or dental X-rays are still a prominent tool used by the dentists for dental diagnosis. Accurate segmentation and reconstruction of each tooth from panoramic radiographs can play very significant role in early diagnosis and treatment that helps physicians to make a better decision. Panoramic radiographs contain regions outside of the jaw, which make segmentation of teeth very time consuming and complex. Automatic segmentation of jaw is necessary to avoid such complexity and to reduce time. Due to the absence of substantial difference of pixel intensity between different structures and absence of strong edges in panoramic radiographs, segmentation of jaw is still perplexing. In this paper, we use the gradient information to segment the jaw regardless of the position and size of the jaw. Our algorithm for segmentation of jaw has four steps: k-means clustering, detection of points around the jaw (proposed), gradient vector flow (GVF) snakes and correction by making the shape of the segmented area oval. K-means clustering followed by thresholding and detection of points around the jaw (proposed) is used to find suitable points for initialization of the GVF snakes. Then, GVF snakes are initialized with the detected points to segment the jaw. Finally, correction is performed by making the shape of the segmented area oval.

The focus of this paper is on the implementation of Bluetooth as a tool to provide m-advertising (mobile advertising). The paper attempts to introduce the implementation of Bluelooth m-advertising system based on user-driven concept using pull-based approach. User-driven concept gives flexibility to end users to select the preferred advertisements from the server while pull-based m-advertising provides advertisement to users based on their willingness and request. This paper also will address two issues in push-based m-advertising systems, which are spamming and time limit.