Earticle

The escalation of IBS (Intelligent Building System) by convergence technologies is currently in progress with the rapid growth of data communication technology and advanced modern construction system, and on this basis, new high-density urbanization is formed. The severe problem of the formation of high-density cities is leading to the phenomenon of spatial collapse by geographical deformation, global warming and destruction of the ecosystem by climate change. Notwithstanding the fact that high accuracies are shown in the past data in terms of information on precipitation, serious vulnerabilities are shown with respect to flood preparation on the subject of natural disasters by the anomaly climate, which tends to produce an exceedingly low level of accuracy, and consequently, adverse effects by which the loss of nations’ assets and human damage are caused came about. This thesis, to bring about improvement to the drawbacks addressed, suggests a design modeling of water level prediction in relation to regional flood by constructing an OLAP-based multidimensional cube with the use of historic regional precipitation and water level data. The historic precipitation and water level data by region design the prediction model of flood inundation by extracting the pattern of the water level information after topographical relations and intelligent buildings have been increased through the extraction of multidimensional table modeling and construct of the data warehouse for the analysis of the source data via pre-processing of documents.

Histogram equalization is an essential technique in Image Processing. It is a contrast adjustment process using image histogram. Contrast upgrade is an imperative zone in image processing for both human and PC vision. Different Methods are proposed and some extraordinary Image Histogram strategies are Adaptive Histogram Equalization system, Recursive mean square histogram adjustment, and Global Histogram balance. In this paper, impressive histogram equalization method by changing mega pixel value is implementing. We consider some of the pixel value between ranges and then calculate its cumulative frequency. After equally distribution intensity is mapped to get a new intensity value a new histogram value.

In constructing a leak monitoring system for active management of potential leaks in a water supply network, the level of performance as well as the cost required to maintain good economic feasibility have been calculated. The amount of water loss that can be reduced by applying the leak monitoring system, has been calculated to be the difference between the actual amount of loss currently being generated and the economic water loss (sum of economic background leakage, reported and unreported leakage). Based on analysis of the current status of domestic water supply networks and international scholarly research materials, the price must be kept under 10 million KRW (assuming 30 items are included in 1 set) for cases in which the distance between sensors is approximately 300m (latest technology applied) in large metropolitan areas, and under 3.4 million KRW for cases in which the distance between sensors is approximately 100m in order to secure economic feasibility and, subsequently, be applied in actual situations.

This research studied the cases of civil engineering-BIM applications to understand how much BIM is being applied throughout Korea’s civil engineering industry, and then analyzed the research related to the enhancement of interoperability to secure universal availability of BIM data models. To encourage BIM in civil engineering industry, a clear understanding and definition of the purpose and scope of use for BIM should come first. Based on this, cases of applying BIM for civil construction such as building BIM data(BIM models) should be collected. At the same time, studies on BIM standardization for general purposes, and establishing a BIM system and its manual should also be performed continuously.

Requirements need to be validated at the early phase of the software development to avoid errors such as inconsistency, incompleteness and incorrectness. Drawn from this argument, a requirements validation process needs to consider Consistency, Completeness and Correctness (“3 Cs”) for the production of a quality software specifications. This paper provides a review of requirements validation and consistency management based on the existing literature in order to identify the gaps in the existing knowledge on the process of software requirements specifications. This paper begins with a review of the definitions of the 3Cs,upon which the understanding of the 3Cs is derived. Next comprehensive review of related works on the identified consistency management techniques: traceability and analysis approaches are then presented. This is supported with a heat map representations of the related research on the types of contributions, techniques, specifications and semantics used in consistency management. Since semi-formal specifications were found as the most common representation of the requirements, the types of models used as semi-formal specifications to represent the requirements were also discussed. Overall, this paper identifies the various gaps existing within the process of validating and managing the consistency of requirements to avoid re-inventing the wheels in the diverse and comprehensive knowledge of requirements engineering.

The present study aims to develop an English-learning device for the hearing-impaired using UNITY 3D for smart phones. Despite the fact that a number of English learning tools are continually being developed in accordance with the improvement of digital devices, most learning tools are designed for those of normal hearing and thus it is challenging to employ them while teaching the hearing-impaired. For this reason, it is essential to develop learning tools for the hearing-impaired who usually rely on visual aids for their learning. Therefore, this study attempts to enhance the accuracy of learners’ pronunciation by visualizing the motion of articulators in different angles through the application of UNITY 3D for smart phones, which has a great advantage of being highly portable. Furthermore, it is expected that this application can ultimately lead to self-initiated learning by piquing the interest of the learners.

Software testing is a set of activities that typically consumes roughly 50% of the total time and cost of testers during the software development process. Developing an enhanced technique to test mobile application becomes a necessity considering the high demand of mobile applications, android specifically, hence the need for software quality assurance. Adapting software testing model would not only lessen the cost incurred in the process of mobile application development but also increase the reliability of the software under test. In this paper, we discuss mobile application testing and its challenges. The Reweb and Testweb frameworks are also discussed followed by an adaptation model from both frameworks to improve testing of android applications. Asides from adapting these web application testing frameworks, another major contribution of our approach is the refactoring the source code before generating test cases to reduce redundancy in the test case library thereby improving the generated test case. Keywords: Refactoring, Android Application, Software

Art therapy is a form of therapeutic practice that uses art in order to relax and cure the symptoms of depression. In this paper, researchers propose an artificial art therapy recommendation system based on an expert system to provide the customized art therapy for the individual patient. Facts and rules about the unique abstract art painting techniques of Jackson Pollock’s art therapy are collected to develop a knowledge base and an inference engine for the expert system. The proposed system analyzes the symptoms of a patient from the answers in the questionnaire and provides the most appropriate art therapy to the patient. With the proposed system, the customized art therapy program can be provided at an affordable cost without limitation of time and place.

In this paper, we propose the clustering-based ensemble management system which extracts new data patterns from the input streaming data by using clustering and generates new classification models only when a certain amount of data has been collected in a cluster. The clustering-based ensemble management system can reduce the number of the data labeling and keep the accuracy of the existing ensemble. The clustering-based ensemble management system collects similar patterned data from the input streaming data for building a cluster. The clustering-based ensemble management system performs the data labeling for the each cluster only when a certain amount of data has been collected in the cluster. The data labeling by experts goes on to generate the new classification model to be added to the ensemble. The clustering-based ensemble management system applies the K-NN technique to classification model units in order to keep the accuracy of the existing system while it uses a small amount of data. The efficiency of the clustering-based ensemble management system proposed in this paper is shown by the simulated results for benchmarks comparing with the existing ensemble techniques.

One of the most important activities in software maintenance is Regression testing. The re-execution of all test cases during the regression testing is costly. And even though several of the code based proposed techniques address procedural programs, so many of them can’t be use directly on object-oriented programs. This paper presents modification-revealing test case selection for regression testing of object-oriented software using dependence graph model analysis of the source code. The experimental evaluation of our proposed approach was done using nine programs. We measured the performances of our selection approach using precision and inclusiveness metrics. It was observed from the results that our approach increase the efficiency and effectiveness of regression testing in term of precision and inclusiveness. It was concluded that selection of modification-revealing test cases based on affected statements provides considerably better results for precision and inclusiveness compared to retest-all and random technique, and reducing the cost of regression testing.

Nowadays, the quality of web services represents the basic pillar in the development of web-based applications integrating web services. In this paper, we assume that the development and the use of web services are achieved through the meta-model called MAP. Hence, we propose a new strategic approach to address the quality of web services in a process-centered environment using the MAP meta-model. This approach extends the MAP meta-model by the QoS concerns and offers a navigational structure which supports the dynamic selection of the intention to be achieved and the appropriate strategy to be selected. Firstly, according to the actor's needs, the new approach allows to improve his/her decision and guide him/her to select the best strategies. Secondly, the realization of intentions accommodate with the current situation by selecting the appropriate QoS techniques.

Common Criteria (CC) is a global standard for the information technology security evaluation of IT products. IT products must obtain at least a certain Evaluation Assurance Level (EAL) to be supplied to governmental institutions. The general software development life cycle (SDLC) does not provide guidelines for the removal of the weaknesses in the software development process for CC certification, and software applications developed with security weaknesses that have not been removed can lead to fatal situations. At present, CC provides only security certification for the target of evaluation (TOE) and does not provide guidelines regarding the secure software development life cycle (SSDLC), which considers the weaknesses in the development process. If a TOE that has been specialized for CC is developed by SSDLC, both evaluators and developers can undertake CC certification from an objective standpoint. This paper presents an SSDLC that is appropriate for CC by discerning weaknesses, by referring to MS-SDL, McGraw’s TouchPoints, and OWASP CLASP based on the weaknesses provided by CWE (Common Weakness Enumeration). The findings of this study can be used as guidelines for the development process of weakness-free software applications by developers aiming for CC certification.

Technology from cloud computing firms could contribute to improving the capability of user firms. This study tries to identify the impact of technology spillover in cloud computing and we hope to give the managers of user firms the managerial implications.

Identifying the specific machining processes used to produce specific workpiece surfaces is very useful in materials inspection. Machine vision can be used to semi- or fully automate this identification process by firstly extracting features from captured workpiece images, followed by analysis using machine learning algorithms. This enables inspection to be performed more reliably with minimal human intervention. In this paper, three visual texture features are investigated to classify machined workpiece surfaces into the six machining process classes of Turning, Grinding, Horizontal Milling, Vertical Milling, Lapping, and Shaping. These are the multi-directional Gabor filtered images, intensity histogram and edge features statistics. Support Vector Machines (SVM) applying different kernel functions are investigated for best classifier performance. Results indicate that the Gabor-based SVM-linear kernel provides superior performance.

Wireless sensor networks (WSNs) generally consist of densely deployed sensor nodes that depend on batteries for energy. The WSN systems have several applications, from target tracking to environment monitoring. Recently, there has been an increased interest in the design of WSN protocols for mission-critical applications, such as military surveillance, health monitoring, and infrastructure security. These applications require capability of sending data with different real time requirements. However, due to strict resource constraints of the sensor nodes, WSNs pose critical challenges in network protocol design for the mission-critical applications. In this paper, we propose an epidemic-inspired node-scheduling scheme (ENS) with aim of delay guaranteeing. The ENS controls the state of the sensor node depending on the application’s specific requirement under dynamic network environments. Simulation results indicate that the ENS achieves globally optimal behavior with reliable delay guarantees.

Since the emphasis of utilizing ICT in education moves from ICT to Computing in many countries, curriculums adapt the Computational Thinking (CT) teaching as a basic courses not only for primary school but also to CS education. Even though the depth of CT teaching may be different, we may expect similar impact of CT teaching results to student problem solving skills. With this rationale, we opened designed CT based education program for freshman introductory of computer application course. Developed course consists of 10 class hours program and the effectiveness of designed programs have been tested, firstly for improving CT capabilities of learners in problem solving environment, and secondarily the cognitive load changes appeared in the problem solving process have been measured with direct brain wave measurement of EEG while solving problems. The test results showed that designed CT program affected to the improvement of problem solving skill, and also show the tendency of decrease in cognitive overload in the experimental group.

The present paper analyses the comparison of two stochastic models of a cable manufacturing plant subjected to inspection and scheduled maintenance. Here, two models are compared on the basis of MTSF, steady state availability and profit function using Laplace transforms and software package Code-Blocks 13.12. Model 1 is a single unit system with scheduled maintenance whereas Model 2 is a single unit system with inspection of repairable failure, reinstallation/reconditioning failure and replaceable failure. The graphs have been plotted to decide which model is better than the other model for a particular condition. Using regenerative point technique and semi-Markov processes, the complete system is analyzed.

In the healthcare literature, happiness has been neglected as an important research issue. However, it seems clear that happiness becomes more important in research agenda as societies grow older. It is well known that happiness is related with various kinds of factors. Therefore, managing happiness requires careful handling of a number of related factors in a very systematic and organized way. In this sense, this study proposes General Bayesian Network (GBN) approach in order to extract causal knowledge about happiness from the analysis of the related factors. By using Friends-and-Family dataset, we performed GBN-based scenario analyses to answer sophisticated questions about happiness. The empirical results showed that GBN proved to have huge potentials in handling well-ness problems in the field of health informatics.

Following recent abnormal patterns of climate, strong rainfall exceeding the recurrence interval of the pipeline is causing frequent flooding in urban areas. To reinforce its flood control capacity and deal with climate change, Seoul Metropolitan City has raised the sewer recurrence interval of the Basic Plan for Organizing Sewage to 10 years for branch pipelines and 30 years for trunk pipelines. To review storm sewer capacity following the raising of probable frequency, this study selected the redevelopment area of Godeok3 District, Seoul, as the subject area to collect data on the sewer and watershed status. Then, using the MOUSE model to analyze sewers, the study conducted a numerical simulation. Taking the flood level (18.2m) of Godeok Stream's designed frequency (30 years) as suggested by the Basic Plan for Organizing Five Streams including Banpo Stream as the benchmark, a numerical analysis was conducted using the probable rainfall of Seoul in a 10-year frequency (designed frequency for the sewer) and a 30-year frequency (adjusted frequency). The results showed that pipelines located at the outlet were influenced by downstream backwater to mostly show full-pipe condition. Especially in the 30-year frequency, the scope of full-pipe condition seemed larger. In principle, sewer capacity requires some margin. Even if flooding does not occur on the ground, sections showing full-pipe condition exceeding a certain in-pipe level should be considered for sewer extension or improvement. To secure margin for sewer sections where full-pipe condition occurred, this study suggests extending the sewer.