Nowadays, search engines tend to use latest technologies in enhancing the personalization of web searches, which leads to better understanding of user requirements. This paper aims to address the problem of enhancing the efficiency of search system by mining data logs. Search logs are associated with all the interactions that have been done between the user and the search engine including the query, the resulted pages and the selection. The paper also aims minimize the ambiguity within the query whilst the partitioning-based clustering aims to reduce the search space by dividing the data into groups that contain similar objects. To do so, this paper conduct several experiments to evaluate correlation clustering method. The method of this paper includes a pre-processing phase, which in turn involves tokenization, stop-words removal, and stemming. In addition, we evaluates the impact of the two similarity/distance measures (Cosine similarity and Jaccard coefficient) on the results of the correlation clustering method. Experimental results obtained are quite satisfactory in terms of the Precision, Recall and F-score. � 2005-2016 JATIT & LLS. All rights reserved.

Ontology as a knowledge representation have contributed in providing the platform for sharing the common ideas and understanding among the members of similar domain. Ontology has a tree structure to ease the presentation of information for the users. This paper presents the building of Dates ontology by using the OASys approaches. The Dates ontology is focusing on the Dates' attributes, the developing stages, defect and diseases of dates, health benefits, its compositions, and the Dates chain of operation. Formation of this Dates ontology can be used to answer user queries, integrate data to other applications as well as expand the ontology. � 2016 IEEE.

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. � 2009 IEEE.

The main purpose of intrusion detection system (IDS) is to find out intrusions among normal audit data and this can be considered as a classification problem. This problem is brought about by the user datagram protocol (UDP) which is a connectionless protocol that means it does not require a formal handshake to get the data flowing and has no need for SYNs, ACKs, FINs flags, or any other handshaking. Worms also make use of UDP protocol to connect or scan with other hosts. In this research, UDP scanning worm detection (UDPSWD) was proposed to detect UDP worm scanning by checking the failure message connections. UDPSWD focuses on the internet control message protocol (ICMP) unreachable, ICMP time exceeded and UDP is not responded to. The results show that UDPSWD is faster in comparison to other techniques, with no false positive or negative alarm. Copyright 2019 Inderscience Enterprises Ltd.

An early warning system is one of the best solutions for flood management. It enhances the reservoir floodgate operation, flood proofing, flood insurance, and flood plain zoning processes. The timeline and accuracy of the decision to open the reservoir gate are critical. Any delay might damage the dam caused by the excess water, leading to flash flood to the surrounding areas. Consequently, huge losses could be incurred, such as the loss of lives, properties, and financial ruins. At this point, the reservoir floodgate operator would sometimes be hesitant to make an early decision due to inconsistency in getting heavy rainfall data readings, which are under manual control. Therefore, this paper proposes the use of an autonomous agent-based system based on the Artificial Immune Systems (AIS). This system would immediately send readings to the reservoir operator so that gradual release of water from the reservoir can be done to prevent it from bursting. This task requires a certain level of experience and expertise in decision making to ensure no water shortage due to the volume of water to be released. This proposed early warning system is based on the immune negative selection and intelligent agent to monitor the changes in the reservoir water level. This autonomous early detection mechanism can support the domain expert's job to recognise the threats early on, which is required to improve the monitoring procedure. � Published under licence by IOP Publishing Ltd.

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. � 2014 IEEE.

Denial of Service (DoS) attacks is one of the security threats for computer systems and applications. It usually make use of software bugs to crash or freeze a service or network resource or bandwidth limits by making use of a flood attack to saturate all bandwidth. Predicting a potential DOS attacks would be very helpful for an IT departments or managements to optimize the security of intrusion detection system (IDS). Nowadays, false alarm rates and accuracy become the main subject to be addressed in measuring the effectiveness of IDS. Thus, the purpose of this work is to search the classifier that is capable to reduce the false alarm rates and increase the accuracy of the detection system. This study applied Artificial Immune System (AIS) in IDS. However, this study has been improved by using integration of rough set theory (RST) with Artificial Immune Recognition System 1 (AIRS1) algorithm, (Rough-AIRS1) to categorize the DoS samples. RST is expected to be able to reduce the redundant features from huge amount of data that is capable to increase the performance of the classification. Furthermore, AIS is an incremental learning approach that will minimize duplications of cases in a knowledge based. It will be efficient in terms of memory storage and searching for similarities in Intrusion Detection (IDS) attacks patterns. This study use NSL-KDD 20% train dataset to test the classifiers. Then, the performances are compared with single AIRS1 and J48 algorithm. Results from these experiments show that Rough-AIRS1 has lower number of false alarm rate compared to single AIRS but a little bit higher than J48. However, accuracy for this hybrid technique is slightly lower compared to others. � 2011 IEEE.

Reservoir provides many benefits to human life generally and public society specifically. It leads to the generalization of energy, supplying and irrigating water for human use, hence improving human daily basis activities and fulfilling human needs. Yet, everything has its own weaknesses. As for the reservoir situation, there is a possibility of the operation to be failed and will leads to the creation of flood that is very harmful for the area of the reservoir. This research had been conducted with the implementation of information visualization, data mining and case based reasoning techniques in order to help the process of generating visualization result in opening or closing the gate of the dam to channel out excessive water. As a conclusion, the process of visualizing numerical values is proven to be faster than the normal process. Using visualization, people tend to make fewer mistakes for a large quantity of data. However, for upcoming time-being, it is advised that some methods of calculating the similarity of these visualize cases is implemented since visualization alone is still not enough to provide precise results. � 2010 IEEE.

Security in e-commerce is becoming an important issue to deal with as several cases of attacks to users' data are increasing exponentially. Therefore, there is absolute need for proper checks and balances to mitigate the lapses using the appropriate development framework. This paper provides as a candidate, Improve Extreme Programming Methodology by tightening security controls across the development stages without necessarily extending the process. � 2011 IEEE.

Worms are widely regarded to be a major security threat faced by the Internet today. Active worms spread in an automated fashion, which can flood the Internet in a very short time, Incidents such as Conficker worm, detected in November 2008, a computer worm targeting the Microsoft Windows operating system, once infected 15 million hosts. In this study, we detect DNA signature by scanning internet worm using three algorithms. The first part, Intelligent Failure Connection Algorithm (IFCA) by using Artificial Immune System, is concerned with detecting the internet worm and stealthy worm in which computer infected by the worm. The second part, Traffic Signature Algorithm (TSA), is concerned with capturing traffic signature for the worm from infector computer. Finally, the third stage is DNA Converter Signature (DNACS) which converts traffic signature to DNA signature and sends it to DNA Filtering. In this study, we show that our proposed technique can detect DNA signature for MSBlaster worm. � 2012 Asian Network for Scientific Information.

The children who have disability in their social interaction and communication are categorized as children with autism. Often autistic children are facing challenges in independent living causing many concerns toward teaching and learning for the autistic children. As a result, therapists and educators of autistic children are facing distress when teaching the autistic children as it is harder to retain their attention during the learning process. Hence, there are some researchers suggest robotic approach as clinical tool to assist therapist especially teachers in teaching session with autistic children. Therefore, this research is focusing on developing a robot to teach the basic Jawi modules to the autistic children. The objective of this paper is twofold, presenting: (1) the ways Jawi Alphabot is programmed to perform teaching, and 2) the attentive assessment results that shows the effectiveness of robotics intervention in learning Jawi among the autistics. Besides, a module for the teacher and the children is also available as a guideline for them to implement this robotic learning process. During the experimental design testing, the autistic children are divided into two groups (i.e. control group and experimental group) and were given different intervention in learning Jawi. The intervention in learning Jawi are: 1) traditional method and 2) robotics intervention method. The results are discussed with evidences that highlights how robotics intervention could alleviate attentiveness in learning among the autistic children. � 2019, World Academy of Research in Science and Engineering. All rights reserved.

Traditional gardening requires labor to control the environmental parameters. The manual intervention method requires high labor cost and it is less effective especially for busy people. This paper introduces the concept of a smart edible garden with the integration of the Internet of Things (IOT). IOT is a smart farming concept that is able to monitor the parameters thus, reducing the need for manual intervention. For controlling the environment in a smart edible garden, different sensors are proposed such as temperature, moisture, humidity, light dependent resistor (LDH) and pH. These sensors collect parameters from the environment to help in the decision making. Data will be sent to a cloud server and is accessed using IOT. IOT approach eliminates the need for constant manual monitoring. It uses a cloud server to store and perform data analytics to control connected devices. This concept provides cost-effective and optimal solutions to the farmers with minimal manual intervention. A solar powered IOT sensors will be an energy efficient option to smart gardening. With these sensors, the greenhouse state, plants and water consumption can be monitored via digital alerts from the system to the grower through a mobile apps and online web portal. Automatic irrigation is carried out in this intelligent system. An automated worm farm system is integrated to supply organic fertilizer for the garden. Worms can turn organic waste into fertilizer, so integrated worm farm can ensure a regular supply of organic fertilizer to the plants. A water system from a fish tank will add the advantage as the water source is very rich in nitrogen and other nutrients came from fish waste in pond water. This multi-function IOT garden is proposed for the indigenous community to give them the digital empowerment to adopt and use technology in their everyday life. This is a work in progress. Results have shown that 50% growth of kangkung plant is recorded in 7 days with IOT farming against traditional farming.

Cerebral Palsy is a common neurodevelopmental condition. The condition may present itself in many different kinds of classification. Cerebral Palsy is always showing many deficits such as mental retardation, speech, language and motor problems. This research was inspired from Elisya, a nine-year-old girl with Cerebral Palsy since born with an auditory and speech disorder including motor problem that affects her mobility. Her senses and brain do not fully coordinate and this creates a communication issue between Elisya and her parents. The aim of this research is to provide a mean for children with Cerebral Palsy who can’t speak to communicate significantly with their parents and carers without using any sign language. There are plenty of assistive tools in the market and this includes the Augmentative and Alternative Communication devices for people with speech disorders. However, there is no app found in Malay language and the content can’t be personalized. Make Me Speak is an Augmentative and Alternative Communication tool using mobile technology which is developed to help people with Cerebral Palsy to communicate with people around them. Make Me Speak is not just for Cerebral Palsy community but for anyone with speech disorder. It is developed in dual language – Malay and English with a personalized content. React Native mobile development platform is used to create the app. React Native helps in building cross platform mobile apps. Hence, it saves time and cost to build mobile apps on multiple platforms. Usability test was done on Elisya and it was found that she is able to manage the app and chose the right buttons to express her needs. This research is in line with the social innovation initiative for people with disabilities as described in the Eleventh Malaysia Plan (RMK-11).

This research aims to analyze the importance and relationships between the usability attributes for mobile application. The usability attributes were grouped into nine (9) factors such as efficiency, effectiveness, learnability, memorability, errors, satisfaction, cognitive workload, simplicity, and interruptibility. A total of 411 useable questionnaires form the basis of analysis. The results revealed that Errors (Mean = 3.82) was the most important usability attribute for mobile application and there was a significant correlation between satisfaction and errors, (r = .591, n = 411, p <.01). The numbers of navigational errors can potentially effects on user performance, user progress and user perception toward mobile applications. Many respondents also agreed that the higher satisfaction (Mean = 3.75), the more simple interface (Mean = 3.72), and the less cognitive workload attribute (Mean = 3.71) may enhance the level of usability of mobile application. Interestingly, satisfaction was found correlated with cognitive load (r = .553, n = 411, p <.01) and learnability was found correlated with memorability (r = .480, n = 411, p <.01). This study contributed in providing an insight into the importance and relationships between usability attributes which can be applied in usability measurement for mobile applications. � 2017 American Scientific Publishers All rights reserved.

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.

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. � 2014 IEEE.

Smart mobile phones are used in a variety of activities, including social networking, messaging, connectivity and context-sensitive applications. The ubiquities of handheld computer technology have been found to be very useful, especially in flood training applications. The aim of this paper is to propose a prototype for one stop center disaster training information through smart mobile phone application called 'MyDisasterTraining'. Smart mobile phones are used as the medium between the community and organizations in promoting the training provided to the public, as well as providing training services to the community about the importance of disaster training. 'MyDisasterTraining' application is a center database and contains the information about flood disaster training in the Malaysian context. It is a simple, user-friendly, and a low cost application which is a mobile application to be used by the third parties training providers, organizations or individuals. It aims to spread the awareness on the availability of disaster training to the society as well as to inculcate voluntarily workforce during the need of the disaster. The utilization and the roles of ICT are described in the context of disseminating the training information to the society, especially on the training of flood disaster. The features and benefits of the application are also described and explained in this paper.

Informer on Site is one of the prototype mobile applications for information about disaster complaints with site pictures and location placement using smartphones. The information is automatically delivered to the officer in charge for prompt response to the civil complaint by identifying the location and situation based on information initially provided by the community via the service. The Informer on Site service is focused on disaster cases such as floods, typhoons, haze and landslides. This application can help the authorities handle disasters more effectively and faster. The objective of this paper is to describe the features, benefits and the flow of the application process.

Once a set of security requirements are elicited, they need to be prioritized. Due to constraints such as development risk, cost, time to market, and security risk avoidance, it can be difficult to implement all security requirements that have been elicited for a system. Also, security requirements are often implemented in stages, and prioritization can help to determine which ones should be implemented first. Usually requirements are prioritized based on stockholders� preference with regards to the importance and easiest to implement. However, these approaches cannot be used with efficiency when dealing with security requirements because there are additional elements that are unique with security requirements. This paper proposes a Risk-based Security Requirements Prioritization (RiskSRP), a process that allows the prioritization of security requirements according to the Total Risk Impact (TI) of security threat(s). � 2017 American Scientific Publishers All rights reserved.

This study presents a framework for safety critical e-commerce application development based on an Extreme Programming methodology with inbuilt security across the development lifecycle to mitigate security lapses. This approach tightens security checks and balances at every stage of development process, minimizes any vulnerability that will manifest in production environment and avoids an unnecessary extension of the life cycle. � 2011 Asian Network for Scientific Information.