Proposal of a Model Supporting Decision-Making on Information Security Risk Treatment

Management is required to understand all information security risks within an organization, and to make decisions on which information security risks should be treated in what level by allocating how much amount of cost. However, such decision-making is not usually easy, because various measures for risk treatment must be selected with the suitable application levels. In addition, some measures may have objectives conflicting with each other. It also makes the selection difficult. Therefore, this paper provides a model which supports the selection of measures by applying multi-objective analysis to find an optimal solution. Additionally, a list of measures is also provided to make the selection easier and more effective without any leakage of measures.

Teacher Professionalisation and Career Commitment

Overall, the findings of the present study suggest that teachers have low to moderate levels of professionalisation, high level of career identity and moderate levels of career resilience, and career planning. From the T-tests and F-tests conducted, it was found that gender has a significant impact on career identity whereas age and marital status have significant impact on career planning and also on career identity. The results indicate that there is a higher possibility of male teachers to leave the teaching profession than the female teachers. The result of the T-test on career identity in relation to gender supports this deduction in which female teachers have significantly higher career identity than their male counterparts. Marital status was also found to have a significant impact on career identity.

Extent of Highway Capacity Loss Due to Rainfall

Traffic flow in adverse weather conditions have been investigated in this study for general traffic, week day and week end traffic. The empirical evidence is strong in support of the view that rainfall affects macroscopic traffic flow parameters. Data generated from a basic highway section along J5 in Johor Bahru, Malaysia was synchronized with 161 rain events over a period of three months. This revealed a 4.90%, 6.60% and 11.32% reduction in speed for light rain, moderate rain and heavy rain conditions respectively. The corresponding capacity reductions in the three rainfall regimes are 1.08% for light rain, 6.27% for moderate rain and 29.25% for heavy rain. In the week day traffic, speed drops of 8.1% and 16.05% were observed for light and heavy conditions. The moderate rain condition speed increased by 12.6%. The capacity drops for week day traffic are 4.40% for light rain, 9.77% for moderate rain and 45.90% for heavy rain. The weekend traffic indicated speed difference between the dry condition and the three rainy conditions as 6.70% for light rain, 8.90% for moderate rain and 13.10% for heavy rain. The capacity changes computed for the weekend traffic were 0.20% in light rain, 13.90% in moderate rain and 16.70% in heavy rain. No traffic instabilities were observed throughout the observation period and the capacities reported for each rain condition were below the norain condition capacity. Rainfall has tremendous impact on traffic flow and this may have implications for shock wave propagation.

Integrating Computational Intelligence Techniques and Assessment Agents in ELearning Environments

In this contribution an innovative platform is being presented that integrates intelligent agents and evolutionary computation techniques in legacy e-learning environments. It introduces the design and development of a scalable and interoperable integration platform supporting: I) various assessment agents for e-learning environments, II) a specific resource retrieval agent for the provision of additional information from Internet sources matching the needs and profile of the specific user and III) a genetic algorithm designed to extract efficient information (classifying rules) based on the students- answering input data. The agents are implemented in order to provide intelligent assessment services based on computational intelligence techniques such as Bayesian Networks and Genetic Algorithms. The proposed Genetic Algorithm (GA) is used in order to extract efficient information (classifying rules) based on the students- answering input data. The idea of using a GA in order to fulfil this difficult task came from the fact that GAs have been widely used in applications including classification of unknown data. The utilization of new and emerging technologies like web services allows integrating the provided services to any web based legacy e-learning environment.

A Decision Support Model for Bank Branch Location Selection

Location selection is one of the most important decision making process which requires to consider several criteria based on the mission and the strategy. This study-s object is to provide a decision support model in order to help the bank selecting the most appropriate location for a bank-s branch considering a case study in Turkey. The object of the bank is to select the most appropriate city for opening a branch among six alternatives in the South-Eastern of Turkey. The model in this study was consisted of five main criteria which are Demographic, Socio-Economic, Sectoral Employment, Banking and Trade Potential and twenty one subcriteria which represent the bank-s mission and strategy. Because of the multi-criteria structure of the problem and the fuzziness in the comparisons of the criteria, fuzzy AHP is used and for the ranking of the alternatives, TOPSIS method is used.

A Comparison of SVM-based Criteria in Evolutionary Method for Gene Selection and Classification of Microarray Data

An evolutionary method whose selection and recombination operations are based on generalization error-bounds of support vector machine (SVM) can select a subset of potentially informative genes for SVM classifier very efficiently [7]. In this paper, we will use the derivative of error-bound (first-order criteria) to select and recombine gene features in the evolutionary process, and compare the performance of the derivative of error-bound with the error-bound itself (zero-order) in the evolutionary process. We also investigate several error-bounds and their derivatives to compare the performance, and find the best criteria for gene selection and classification. We use 7 cancer-related human gene expression datasets to evaluate the performance of the zero-order and first-order criteria of error-bounds. Though both criteria have the same strategy in theoretically, experimental results demonstrate the best criterion for microarray gene expression data.

Different Multimedia Presentation Types and Students' Interpretation Achievement

The main purpose of the study was to determine whether students- interpretation achievement differed with the use of various multimedia presentation types. Four groups of students, text only (T), audio only (A), text and audio (TA), text and image (TI), were arranged and they were presented the same story via different types of multimedia presentations. Inference achievement was measured by a critical thinking inference test. Higher mean scores for the TA group compared to the other three groups were found. Also when compared pairwise, interpretation achievement of the TA group differed significantly from scores of the T and TI groups. These differences were interpreted with the increased cognitive load. Increased cognitive load for the TA group may have invited students to put more effort into comprehending the text, thus resulting in better test scores. Findings of the study can be seen as a sign of the importance of learning situations and learning outcomes in multimedia-supported learning environments and may have practical benefits for instructional designers.

Towards a New Era of Sustainability in the Automotive Industry: Strategic Human Resource Management and Green Technology Innovation

Although automotive industry has brought different beneficiaries to human life, it is being pointed out as one of the major cause of global air pollution which resulted in climate change, smog, green house gases (GHGs), and human diseases by many reasons. Since auto industry is one of the largest consumers of fossil fuels, the realization of green innovations is becoming a crucial choice to meet the challenges towards sustainable development. Recently, many auto manufacturers have embarked on green technology initiatives to gain a competitive advantage in the global market; however, innovative manufacturing systems and technologies can enhance operational performance only if the human resource management is in place to elicit the motivation of the employees and develop their organizational expertise. No organization can perform at peak levels unless each employee is committed to the company goals and works as an effective team member. Strategic human resource practices are the primary means by which firms can shape the skills, attitudes, and behavior of individuals to align with the business strategic objectives. This study investigates on the comprehensive approach of multiple advanced technology innovations and human resource management at Toyota Motor Corporation as the market leader of full hybrid technology in the automotive industry. Then, HRM framework of the company is described and three sets of human resource practices that support the innovation-oriented HR system, presented. Finally, a conceptual framework for innovativeness in green technology in automotive industry by applying a deliberate strategic HR management system and knowledge management with the intervening factors of organizational culture, knowledge application and knowledge sharing is proposed.

A Sequential Pattern Mining Method Based On Sequential Interestingness

Sequential mining methods efficiently discover all frequent sequential patterns included in sequential data. These methods use the support, which is the previous criterion that satisfies the Apriori property, to evaluate the frequency. However, the discovered patterns do not always correspond to the interests of analysts, because the patterns are common and the analysts cannot get new knowledge from the patterns. The paper proposes a new criterion, namely, the sequential interestingness, to discover sequential patterns that are more attractive for the analysts. The paper shows that the criterion satisfies the Apriori property and how the criterion is related to the support. Also, the paper proposes an efficient sequential mining method based on the proposed criterion. Lastly, the paper shows the effectiveness of the proposed method by applying the method to two kinds of sequential data.

Vision Based Hand Gesture Recognition

With the development of ubiquitous computing, current user interaction approaches with keyboard, mouse and pen are not sufficient. Due to the limitation of these devices the useable command set is also limited. Direct use of hands as an input device is an attractive method for providing natural Human Computer Interaction which has evolved from text-based interfaces through 2D graphical-based interfaces, multimedia-supported interfaces, to fully fledged multi-participant Virtual Environment (VE) systems. Imagine the human-computer interaction of the future: A 3Dapplication where you can move and rotate objects simply by moving and rotating your hand - all without touching any input device. In this paper a review of vision based hand gesture recognition is presented. The existing approaches are categorized into 3D model based approaches and appearance based approaches, highlighting their advantages and shortcomings and identifying the open issues.

Situation-based Knowledge Presentation for Mobile Workers

The work presented in this paper focus on Knowledge Management services enabling CSCW (Computer Supported Cooperative Work) applications to provide an appropriate adaptation to the user and the situation in which the user is working. In this paper, we explain how a knowledge management system can be designed to support users in different situations exploiting contextual data, users' preferences, and profiles of involved artifacts (e.g., documents, multimedia files, mockups...). The presented work roots in the experience we had in the MILK project and early steps made in the MAIS project.

Importance of Public Communication Campaigns and Art Activities in Social Education

Universities have an important role in social education in many aspects. In terms of creating awareness and convincing public about social issues, universities take a leading position for public. The best way to provide public support for social education is to develop public communication campaigns. The aim of this study is to present a public communication model which will be guided in social education practices. The study titled “Importance of public communication campaigns and art activities in Social Education “is based on the following topics: Effects of public communication campaigns on social education, Public relations techniques for education, communication strategies, Steps of public relations campaigns in social education, making persuasive messages for public communication campaigns, developing artistic messages and organizing art activities in social education. In addition to these topics, media planning for social education, forming a team as campaign managers, dialogues with opinion leaders in education and preparing creative communication models for social education will be taken into consideration. This study also aims to criticize social education Case studies in Turkey. At the same time, some communicative methods and principles will be given in the light of communication campaigns within the context of this notice.

Evaluation the Distribution of Implant Supported Prostheses between 2005-2009 Years

The aim of this retrospective study was to evaluate the parameters of dental implants such as patient gender, number of implant, failed implant before prosthetic restorations and failed implant after implantation and failed implant after prosthetic restorations. 135 male and 99 female patients, total 234 implant patients which have been treated with 450 implant between 2005- 2009 years in GATA Haydarpasa Training Hospital Dental Service. Twelve implants were failed before prosthetic restorations. Four implant were failed after fixed prosthetic restorations. Cumulative survival rate after prostheses were 97.56 % during 6 years period.

Computer Aided Detection on Mammography

A typical definition of the Computer Aided Diagnosis (CAD), found in literature, can be: A diagnosis made by a radiologist using the output of a computerized scheme for automated image analysis as a diagnostic aid. Often it is possible to find the expression Computer Aided Detection (CAD or CADe): this definition emphasizes the intent of CAD to support rather than substitute the human observer in the analysis of radiographic images. In this article we will illustrate the application of CAD systems and the aim of these definitions. Commercially available CAD systems use computerized algorithms for identifying suspicious regions of interest. In this paper are described the general CAD systems as an expert system constituted of the following components: segmentation / detection, feature extraction, and classification / decision making. As example, in this work is shown the realization of a Computer- Aided Detection system that is able to assist the radiologist in identifying types of mammary tumor lesions. Furthermore this prototype of station uses a GRID configuration to work on a large distributed database of digitized mammographic images.

Greening the Greyfields: Unlocking the Redevelopment Potential of the Middle Suburbs in Australian Cities

Pressures for urban redevelopment are intensifying in all large cities. A new logic for urban development is required – green urbanism – that provides a spatial framework for directing population and investment inwards to brownfields and greyfields precincts, rather than outwards to the greenfields. This represents both a major opportunity and a major challenge for city planners in pluralist liberal democracies. However, plans for more compact forms of urban redevelopment are stalling in the face of community resistance. A new paradigm and spatial planning platform is required that will support timely multi-level and multi-actor stakeholder engagement, resulting in the emergence of consensus plans for precinct-level urban regeneration capable of more rapid implementation. Using Melbourne, Australia as a case study, this paper addresses two of the urban intervention challenges – where and how – via the application of a 21st century planning tool ENVISION created for this purpose.

Bitrate Reduction Using FMO for Video Streaming over Packet Networks

Flexible macroblock ordering (FMO), adopted in the H.264 standard, allows to partition all macroblocks (MBs) in a frame into separate groups of MBs called Slice Groups (SGs). FMO can not only support error-resilience, but also control the size of video packets for different network types. However, it is well-known that the number of bits required for encoding the frame is increased by adopting FMO. In this paper, we propose a novel algorithm that can reduce the bitrate overhead caused by utilizing FMO. In the proposed algorithm, all MBs are grouped in SGs based on the similarity of the transform coefficients. Experimental results show that our algorithm can reduce the bitrate as compared with conventional FMO.

A Support System Applicable to Multiple APIs for Haptic VR Application Designers

This paper describes a proposed support system which enables applications designers to effectively create VR applications using multiple haptic APIs. When the VR designers create applications, it is often difficult to handle and understand many parameters and functions that have to be set in the application program using documentation manuals only. This complication may disrupt creative imagination and result in inefficient coding. So, we proposed the support application which improved the efficiency of VR applications development and provided the interactive components of confirmation of operations with haptic sense previously. In this paper, we describe improvements of our former proposed support application, which was applicable to multiple APIs and haptic devices, and evaluate the new application by having participants complete VR program. Results from a preliminary experiment suggest that our application facilitates creation of VR applications.

Model to Support Synchronous and Asynchronous in the Learning Process with An Adaptive Hypermedia System

In blended learning environments, the Internet can be combined with other technologies. The aim of this research was to design, introduce and validate a model to support synchronous and asynchronous activities by managing content domains in an Adaptive Hypermedia System (AHS). The application is based on information recovery techniques, clustering algorithms and adaptation rules to adjust the user's model to contents and objects of study. This system was applied to blended learning in higher education. The research strategy used was the case study method. Empirical studies were carried out on courses at two universities to validate the model. The results of this research show that the model had a positive effect on the learning process. The students indicated that the synchronous and asynchronous scenario is a good option, as it involves a combination of work with the lecturer and the AHS. In addition, they gave positive ratings to the system and stated that the contents were adapted to each user profile.

Vibration of Functionally Graded Cylindrical Shells Under Effect Clamped-Free Boundary Conditions Using Hamilton's Principle

In the present work, study of the vibration of thin cylindrical shells made of a functionally gradient material (FGM) composed of stainless steel and nickel is presented. Material properties are graded in the thickness direction of the shell according to volume fraction power law distribution. The objective is to study the natural frequencies, the influence of constituent volume fractions and the effects of boundary conditions on the natural frequencies of the FG cylindrical shell. The study is carried out using third order shear deformation shell theory. The analysis is carried out using Hamilton's principle. The governing equations of motion of FG cylindrical shells are derived based on shear deformation theory. Results are presented on the frequency characteristics, influence of constituent volume fractions and the effects of clamped-free boundary conditions

Information System Life Cycle: Applications in Construction and Manufacturing

In this paper, we present the information life cycle, and analyze the importance of managing the corporate application portfolio across this life cycle. The approach presented here does not correspond just to the extension of the traditional information system development life cycle. This approach is based in the generic life cycle employed in other contexts like manufacturing or marketing. In this paper it is proposed a model of an information system life cycle, supported in the assumption that a system has a limited life. But, this limited life may be extended. This model is also applied in several cases; being reported here two examples of the framework application in a construction enterprise, and in a manufacturing enterprise.