Designing a Framework for Network Security Protection

As the Internet continues to grow at a rapid pace as the primary medium for communications and commerce and as telecommunication networks and systems continue to expand their global reach, digital information has become the most popular and important information resource and our dependence upon the underlying cyber infrastructure has been increasing significantly. Unfortunately, as our dependency has grown, so has the threat to the cyber infrastructure from spammers, attackers and criminal enterprises. In this paper, we propose a new machine learning based network intrusion detection framework for cyber security. The detection process of the framework consists of two stages: model construction and intrusion detection. In the model construction stage, a semi-supervised machine learning algorithm is applied to a collected set of network audit data to generate a profile of normal network behavior and in the intrusion detection stage, input network events are analyzed and compared with the patterns gathered in the profile, and some of them are then flagged as anomalies should these events are sufficiently far from the expected normal behavior. The proposed framework is particularly applicable to the situations where there is only a small amount of labeled network training data available, which is very typical in real world network environments.

An Efficient and Optimized Multi Constrained Path Computation for Real Time Interactive Applications in Packet Switched Networks

Quality of Service (QoS) Routing aims to find path between source and destination satisfying the QoS requirements which efficiently using the network resources and underlying routing algorithm and to fmd low-cost paths that satisfy given QoS constraints. One of the key issues in providing end-to-end QoS guarantees in packet networks is determining feasible path that satisfies a number of QoS constraints. We present a Optimized Multi- Constrained Routing (OMCR) algorithm for the computation of constrained paths for QoS routing in computer networks. OMCR applies distance vector to construct a shortest path for each destination with reference to a given optimization metric, from which a set of feasible paths are derived at each node. OMCR is able to fmd feasible paths as well as optimize the utilization of network resources. OMCR operates with the hop-by-hop, connectionless routing model in IP Internet and does not create any loops while fmding the feasible paths. Nodes running OMCR not necessarily maintaining global view of network state such as topology, resource information and routing updates are sent only to neighboring nodes whereas its counterpart link-state routing method depend on complete network state for constrained path computation and that incurs excessive communication overhead.

CFD Analysis of Incompressible Turbulent Swirling Flow through Circle Grids Space Filling Plate

Circle grid space filling plate is a flow conditioner with a fractal pattern and used to eliminate turbulence originating from pipe fittings in experimental fluid flow applications. In this paper, steady state, incompressible, swirling turbulent flow through circle grid space filling plate has been studied. The solution and the analysis were carried out using finite volume CFD solver FLUENT 6.2. Three turbulence models were used in the numerical investigation and their results were compared with the pressure drop correlation of BS EN ISO 5167-2:2003. The turbulence models investigated here are the standard k-ε, realizable k-ε, and the Reynolds Stress Model (RSM). The results showed that the RSM model gave the best agreement with the ISO pressure drop correlation. The effects of circle grids space filling plate thickness and Reynolds number on the flow characteristics have been investigated as well.

Decision Tree-based Feature Ranking using Manhattan Hierarchical Cluster Criterion

Feature selection study is gaining importance due to its contribution to save classification cost in terms of time and computation load. In search of essential features, one of the methods to search the features is via the decision tree. Decision tree act as an intermediate feature space inducer in order to choose essential features. In decision tree-based feature selection, some studies used decision tree as a feature ranker with a direct threshold measure, while others remain the decision tree but utilized pruning condition that act as a threshold mechanism to choose features. This paper proposed threshold measure using Manhattan Hierarchical Cluster distance to be utilized in feature ranking in order to choose relevant features as part of the feature selection process. The result is promising, and this method can be improved in the future by including test cases of a higher number of attributes.

Sustainable Construction in Malaysia – Developers- Awareness

The creation of a sustainable future depends on the knowledge and involvement of the people, as well as an understanding of the consequences of individual actions. Construction industry has long been associated with the detrimental effects to our mother earth. In Malaysia, the government, professional bodies and private companies are beginning to take heed in the necessity to reduce this environmental problem without restraining the need for development. This paper focuses on the actions undertaken by the Malaysian government, non-government organizations and construction players in promoting sustainability in construction. To ensure that those concerted efforts are not only skin deep in its impact, a survey was conducted to investigate the awareness of the developers regarding this issue and whether those developers has absorb the concept of sustainable construction in their current practices. The survey revealed that although the developers are aware of the rising issues on sustainability, little efforts are generated from them in implementing it. More effort is necessary to boost this application and further stimulate actions and strategies towards a sustainable built environment.

Similarity Detection in Collaborative Development of Object-Oriented Formal Specifications

The complexity of today-s software systems makes collaborative development necessary to accomplish tasks. Frameworks are necessary to allow developers perform their tasks independently yet collaboratively. Similarity detection is one of the major issues to consider when developing such frameworks. It allows developers to mine existing repositories when developing their own views of a software artifact, and it is necessary for identifying the correspondences between the views to allow merging them and checking their consistency. Due to the importance of the requirements specification stage in software development, this paper proposes a framework for collaborative development of Object- Oriented formal specifications along with a similarity detection approach to support the creation, merging and consistency checking of specifications. The paper also explores the impact of using additional concepts on improving the matching results. Finally, the proposed approach is empirically evaluated.

Reduction of Search Space by Applying Controlled Genetic Operators for Weight Constrained Shortest Path Problem

The weight constrained shortest path problem (WCSPP) is one of most several known basic problems in combinatorial optimization. Because of its importance in many areas of applications such as computer science, engineering and operations research, many researchers have extensively studied the WCSPP. This paper mainly concentrates on the reduction of total search space for finding WCSP using some existing Genetic Algorithm (GA). For this purpose, some controlled schemes of genetic operators are adopted on list chromosome representation. This approach gives a near optimum solution with smaller elapsed generation than classical GA technique. From further analysis on the matter, a new generalized schema theorem is also developed from the philosophy of Holland-s theorem.

Using PFA in Feature Analysis and Selection for H.264 Adaptation

Classification of video sequences based on their contents is a vital process for adaptation techniques. It helps decide which adaptation technique best fits the resource reduction requested by the client. In this paper we used the principal feature analysis algorithm to select a reduced subset of video features. The main idea is to select only one feature from each class based on the similarities between the features within that class. Our results showed that using this feature reduction technique the source video features can be completely omitted from future classification of video sequences.

Machine Vision for the Inspection of Surgical Tasks: Applications to Robotic Surgery Systems

The use of machine vision to inspect the outcome of surgical tasks is investigated, with the aim of incorporating this approach in robotic surgery systems. Machine vision is a non-contact form of inspection i.e. no part of the vision system is in direct contact with the patient, and is therefore well suited for surgery where sterility is an important consideration,. As a proof-of-concept, three primary surgical tasks for a common neurosurgical procedure were inspected using machine vision. Experiments were performed on cadaveric pig heads to simulate the two possible outcomes i.e. satisfactory or unsatisfactory, for tasks involved in making a burr hole, namely incision, retraction, and drilling. We identify low level image features to distinguish the two outcomes, as well as report on results that validate our proposed approach. The potential of using machine vision in a surgical environment, and the challenges that must be addressed, are identified and discussed.

Ethnobotany and Distribution of Wild Edible Tubers in Pulau Redang and Nearby Islands of Terengganu, Malaysia

An ethnobotanical study was conducted to document local knowledge and potentials of wild edible tubers that has been reported and sighted and to investigate and record their distribution in Pulau Redang and nearby islands of Terengganu, Malaysia. Information was gathered from 42 villagers by using semi-structured questionnaire. These respondents were selected randomly and no appointment was made prior to the visits. For distribution, the locations of wild edible tubers were recorded by using the Global Positioning System (GPS). The wild edible tubers recorded were ubi gadung, ubi toyo, ubi kasu, ubi jaga, ubi seratus and ubi kertas. Dioscorea or commonly known as yam is reported to be one of the major food sources worldwide. The majority of villagers used Dioscorea hispida Dennst. or ubi gadung in many ways in their life such as for food, medicinal purposes and fish poison. The villagers have identified this ubi gadung by looking at the morphological characteristics; that include leaf shape, stem and the color of the tuber-s flesh.

Simulation Games in Business Process Management Education

Business process management (BPM) has become widely accepted within business community as a means for improving business performance. However, it is of the highest importance to incorporate BPM as part of the curriculum at the university level education in order to achieve the appropriate acceptance of the method. Goal of the paper is to determine the current state of education in business process management (BPM) at the Croatian universities and abroad. It investigates the applied forms of instruction and teaching methods and gives several proposals for BPM courses improvement. Since majority of undergraduate and postgraduate students have limited understanding of business processes and lack of any practical experience, there is a need for introducing new teaching approaches. Therefore, we offer some suggestions for further improvement, among which the introduction of simulation games environment in BPM education is strongly recommended.

Text-independent Speaker Identification Based on MAP Channel Compensation and Pitch-dependent Features

One major source of performance decline in speaker recognition system is channel mismatch between training and testing. This paper focuses on improving channel robustness of speaker recognition system in two aspects of channel compensation technique and channel robust features. The system is text-independent speaker identification system based on two-stage recognition. In the aspect of channel compensation technique, this paper applies MAP (Maximum A Posterior Probability) channel compensation technique, which was used in speech recognition, to speaker recognition system. In the aspect of channel robust features, this paper introduces pitch-dependent features and pitch-dependent speaker model for the second stage recognition. Based on the first stage recognition to testing speech using GMM (Gaussian Mixture Model), the system uses GMM scores to decide if it needs to be recognized again. If it needs to, the system selects a few speakers from all of the speakers who participate in the first stage recognition for the second stage recognition. For each selected speaker, the system obtains 3 pitch-dependent results from his pitch-dependent speaker model, and then uses ANN (Artificial Neural Network) to unite the 3 pitch-dependent results and 1 GMM score for getting a fused result. The system makes the second stage recognition based on these fused results. The experiments show that the correct rate of two-stage recognition system based on MAP channel compensation technique and pitch-dependent features is 41.7% better than the baseline system for closed-set test.

Italians- Social and Emotional Loneliness: The Results of Five Studies

Subjective loneliness describes people who feel a disagreeable or unacceptable lack of meaningful social relationships, both at the quantitative and qualitative level. The studies to be presented tested an Italian 18-items self-report loneliness measure, that included items adapted from scales previously developed, namely a short version of the UCLA (Russell, Peplau and Cutrona, 1980), and the 11-items Loneliness scale by De Jong-Gierveld & Kamphuis (JGLS; 1985). The studies aimed at testing the developed scale and at verifying whether loneliness is better conceptualized as a unidimensional (so-called 'general loneliness') or a bidimensional construct, namely comprising the distinct facets of social and emotional loneliness. The loneliness questionnaire included 2 singleitem criterion measures of sad mood, and social contact, and asked participants to supply information on a number of socio-demographic variables. Factorial analyses of responses obtained in two preliminary studies, with 59 and 143 Italian participants respectively, showed good factor loadings and subscale reliability and confirmed that perceived loneliness has clearly two components, a social and an emotional one, the latter measured by two subscales, a 7-item 'general' loneliness subscale derived from UCLA, and a 6–item 'emotional' scale included in the JGLS. Results further showed that type and amount of loneliness are related, negatively, to frequency of social contacts, and, positively, to sad mood. In a third study data were obtained from a nation-wide sample of 9.097 Italian subjects, 12 to about 70 year-olds, who filled the test on-line, on the Italian web site of a large-audience magazine, Focus. The results again confirmed the reliability of the component subscales, namely social, emotional, and 'general' loneliness, and showed that they were highly correlated with each other, especially the latter two. Loneliness scores were significantly predicted by sex, age, education level, sad mood and social contact, and, less so, by other variables – e.g., geographical area and profession. The scale validity was confirmed by the results of a fourth study, with elderly men and women (N 105) living at home or in residential care units. The three subscales were significantly related, among others, to depression, and to various measures of the extension of, and satisfaction with, social contacts with relatives and friends. Finally, a fifth study with 315 career-starters showed that social and emotional loneliness correlate with life satisfaction, and with measures of emotional intelligence. Altogether the results showed a good validity and reliability in the tested samples of the entire scale, and of its components.

An Effective Islanding Detection and Classification Method Using Neuro-Phase Space Technique

The purpose of planned islanding is to construct a power island during system disturbances which are commonly formed for maintenance purpose. However, in most of the cases island mode operation is not allowed. Therefore distributed generators (DGs) must sense the unplanned disconnection from the main grid. Passive technique is the most commonly used method for this purpose. However, it needs improvement in order to identify the islanding condition. In this paper an effective method for identification of islanding condition based on phase space and neural network techniques has been developed. The captured voltage waveforms at the coupling points of DGs are processed to extract the required features. For this purposed a method known as the phase space techniques is used. Based on extracted features, two neural network configuration namely radial basis function and probabilistic neural networks are trained to recognize the waveform class. According to the test result, the investigated technique can provide satisfactory identification of the islanding condition in the distribution system.

Review of a Real-Time Infectious Waste Management System Using QR Code

In the management of industrial waste, conversion from the use of paper invoices to electronic forms is currently under way in developed countries. Difficulties in such computerization include the lack of synchronization between the actual goods and the corresponding data managed by the server. Consequently, a system which utilizes the incorporation of a QR code in connection with the waste material has been developed. The code is read at each stage, from discharge until disposal, and progress at each stage can be easily reported. This system can be linked with Japanese public digital authentication service of waste, taking advantage of its good points, and can be used to submit reports to the regulatory authorities. Its usefulness was confirmed by a verification test, and put into actual practice.

Factorial Structure and Psychometric Validation of Ecotourism Experiential Value Construct: Insights from Taman Negara National Park, Malaysia

The purpose of this research is to disentangle and validate the underlying factorial-structure of Ecotourism Experiential Value (EEV) measurement scale and subsequently investigate its psychometric properties. The analysis was based on a sample of 225 eco-tourists, collected at the vicinity of Taman Negara National Park (TNNP) via interviewer-administered questionnaire. Exploratory factor analysis (EFA) was performed to determine the factorial structure of EEV. Subsequently, to confirm and validate the factorial structure and assess the psychometric properties of EEV, confirmatory factor analysis (CFA) was executed. In addition, to establish the nomological validity of EEV a structural model was developed to examine the effect of EEV on Total Eco-tourist Experience Quality (TEEQ). It is unveiled that EEV is a secondorder six-factorial structure construct and it scale has adequately met the psychometric criteria, thus could permit interpretation of results confidently. The findings have important implications for future research directions and management of ecotourism destination.

Degradation in Organic Light Emitting Diodes

The objective is to fabricate organic light emitting diode and to study its degradation process in atmosphere condition in which PFO as an emitting material and PEDOT:PSS as a hole injecting material were used on ITO substrate. Thus degradation process of the OLED was studied upon its current-voltage characteristic. By fabricating this OLED and obtaining blue light and analysis of current-voltage characteristic during the time after fabrication, it was observed that the current of the OLED was exponentially decreased. Current reduction during the initial hours of fabrication was outstanding and after few days its reduction rate was dropped significantly, while the diode was dying.

Classification System for a Collaborative Urban Retail Logistics

From an economic standpoint the current and future road traffic situation in urban areas is a cost factor. Traffic jams and congestion prolong journey times and tie up resources in trucks and personnel. Many discussions about imposing charges or tolls for cities in Europe in order to reduce traffic congestion are currently in progress. Both of these effects lead – directly or indirectly - to additional costs for the urban distribution systems in retail companies. One approach towards improving the efficiency of retail distribution systems, and thus towards avoiding negative environmental factors in urban areas, is horizontal collaboration for deliveries to retail outlets – Urban Retail Logistics. This paper presents a classification system to help reveal where cooperation between retail companies is possible and makes sense for deliveries to retail outlets in urban areas.

Communicating a Mega Sporting Event in a Social Network Environment

Arguments on a popular microblogging site were analysed by means of a methodological approach to business rhetoric focusing on the logos communication technique. The focus of the analysis was the 100 day countdown to the 2011 Rugby World Cup as advanced by the organisers. Big sporting events provide an attractive medium for sport event marketers in that they have become important strategic communication tools directed at sport consumers. Sport event marketing is understood in the sense of using a microblogging site as a communication tool whose purpose it is to disseminate a company-s marketing messages by involving the target audience in experiential activities. Sport creates a universal language in that it excites and increases the spread of information by word of mouth and other means. The findings highlight the limitations of a microblogging site in terms of marketing messages which can assist in better practices. This study can also serve as a heuristic tool for other researchers analysing sports marketing messages in social network environments.

Plant Location Selection by Using a Three-Step Methodology: Delphi-AHP-VIKOR

Nowadays, the plant location selection has a critical impact on the performance of numerous companies. In this paper, a methodology is presented to solve this problem. The three decision making methods, namely Delphi, AHP and improved VIKOR, are hybridized in order to make the best use of information available based on the decision makers or experts. In this respect, the aim of using Delphi is to select the most influential criteria by a few decision makers. The AHP is utilized to give weights of the selected criteria. Finally, the improved VIKOR method is applied to rank alternatives. At the end of paper, an application example demonstrates the applicability of the proposed methodology.