• KIPS Transactions on Software and Data Engineering
• /
• v.7 no.6
• /
• pp.221-228
• /
• 2018

With an increase in demand for the high added value of shipbuilding and marine industry based on the information and communications technology (ICT), software technology has become more important than ever in the industry. In this paper, we present the result of our preliminary investigation on the current software development environment in the shipbuilding and marine industry in order to develop reusable software component, which can enhance the competitiveness of software development. The investigation is performed based on the survey answers from 34 developers who are working in different shipbuilding and marine companies. The questionnaire is composed of items to gather the information of each company such as the number of employees and product domain, and actual software development environment such as operating system, programming languages, deployment format, obstacles for developing components, and the adoption of software development methods and tools. According to the results of the survey, the most important consideration to select their development platform was the number of available utilities and the technical supports, followed by performance, price and security problems. In addition, the requirements of various platforms supporting and the higher reliability, and the limitations of low development cost and manpower made it difficult for them to develop reusable software components. Finally, throughout the survey, we find out that only 15% of developers used software development processes and managed the quality to systematically develop their software products, therefore, shipbuilding and marine companies need more technical and institutional support to improve their ability to develop high qualified software.

• Journal of KIISE:Software and Applications
• /
• v.30 no.11
• /
• pp.1025-1036
• /
• 2003

In industry, it is a current trend that systems are developed by using Enterprise JavaBeans(EJB) technology for reducing the cost and the time. Thus, the architecture of EJB is getting more essential to enhance reusability, extensibility and portability of system. However little has been studied in the realm of the practical software architectures for EJB. The architecture has just bean studied in abstract level, but not in concrete level providing the method to substantiate it using the practical J2EE techniques. Just using the EJB technology doesn't guarantee the reusability of the artifacts because EJB specification provides the characteristics and architecture for only fine grained components as session and entity bean. In this paper, we propose the enterprise software architecture for the systems based on EJB and the concrete techniques for implementing that. Also, design patterns of modeling efficient enterprise architecture are represented. By analyzing both the strengths and the weaknesses of suggested design patterns, EJB design patterns which are suitable for each layer of enterprise architecture will be identified. Through the component which design patterns are applied, the architecture can support the optimized relationship between the components. Five techniques for designing components from fine grained to coarse grained based on EJB technology, and architecture design techniques including transaction and assembling techniques are proposed.

• KIPS Transactions on Software and Data Engineering
• /
• v.2 no.10
• /
• pp.651-660
• /
• 2013

Object oriented design brought up improvement of productivity and software quality by adopting some concepts such as inheritance and encapsulation. However, both the number of software's classes and object couplings are increasing as the software volume is becoming larger. The object coupling between classes is closely related with software complexity, and high complexity causes decreasing software quality. In order to solve the object coupling issue, IT-field researchers adopt a component based development and software quality metrics. The component based development requires explicit representation of dependencies between classes and the software quality metrics evaluates quality of software. As part of the research, we intend to gain a basic data that will be used on decomposing software. We focused on properties of the linkage between classes rather than previous studies evaluated and accumulated the qualities of individual classes. Our method exploits machine learning technique to analyze the properties of linkage and predict the strength of dependency between classes, as a new perspective on analyzing software property.

• Journal of Korean Society on Water Environment
• /
• v.35 no.3
• /
• pp.224-233
• /
• 2019

Nitrogen components in liquid manure can reduce safety and quality of environment harmfully. To minimize the environmental risks of manure, understanding fate of manure in environment is necessary. This study aimed at investigating applicability of a simplified Level III fugacity model for simulating $NH_3-N$ component to analyze environmental fate and transport of $NH_3-N$ in liquid manure and to provide basis for improving management of N in the liquid manure system and for minimizing the environmental impacts of N. The model simulation conducted for four environmental compartments (air, water, soil, and rice plants) during rice-cropping to trace $NH_3-N$ component and provided applicability of the Level III fugacity model in studying the environmental fate of $NH_3-N$ in manure. Most of $NH_3-N$ was found in water body and in rice plants depending upon the physicochemical properties and proper removal processes. For more precise model results, the model is needed to modify with the detailed removal processes in each compartment and to collect proper and accurate information for input parameters. Further study should be about simulations of various N-typed fertilizers to compare with the liquid manure based on a modified and relatively simplified Level III fugacity model.

• Journal of Intelligence and Information Systems
• /
• v.16 no.2
• /
• pp.33-54
• /
• 2010

The World Wide Web is transitioning from being a mere collection of documents that contain useful information toward providing a collection of services that perform useful tasks. The emerging Web service technology has been envisioned as the next technological wave and is expected to play an important role in this recent transformation of the Web. By providing interoperable interface standards for application-to-application communication, Web services can be combined with component based software development to promote application interaction both within and across enterprises. To make Web services for service-oriented computing operational, it is important that Web service repositories not only be well-structured but also provide efficient tools for developers to find reusable Web service components that meet their needs. As the potential of Web services for service-oriented computing is being widely recognized, the demand for effective Web service discovery mechanisms is concomitantly growing. A number of public Web service repositories have been proposed, but the Web service taxonomy generation has not been satisfactorily addressed. Unfortunately, most existing Web service taxonomies are either too rudimentary to be useful or too hard to be maintained. In this paper, we propose a Web service taxonomy generation framework that combines an artificial neural network based clustering techniques with descriptive label generating and leverages the semantics of the XML-based service specification in WSDL documents. We believe that this is one of the first attempts at applying data mining techniques in the Web service discovery domain. We have developed a prototype system based on the proposed framework using an unsupervised artificial neural network and empirically evaluated the proposed approach and tool using real Web service descriptions drawn from operational Web service repositories. We report on some preliminary results demonstrating the efficacy of the proposed approach.

• Journal of Institute of Control, Robotics and Systems
• /
• v.16 no.12
• /
• pp.1150-1158
• /
• 2010

In this study, the Polynomial-based Radial Basis Function Neural Networks is proposed as one of the recognition part of overall face recognition system that consists of two parts such as the preprocessing part and recognition part. The design methodology and procedure of the proposed pRBFNNs are presented to obtain the solution to high-dimensional pattern recognition problem. First, in preprocessing part, we use a CCD camera to obtain a picture frame in real-time. By using histogram equalization method, we can partially enhance the distorted image influenced by natural as well as artificial illumination. We use an AdaBoost algorithm proposed by Viola and Jones, which is exploited for the detection of facial image area between face and non-facial image area. As the feature extraction algorithm, PCA method is used. In this study, the PCA method, which is a feature extraction algorithm, is used to carry out the dimension reduction of facial image area formed by high-dimensional information. Secondly, we use pRBFNNs to identify the ID by recognizing unique pattern of each person. The proposed pRBFNNs architecture consists of three functional modules such as the condition part, the conclusion part, and the inference part as fuzzy rules formed in 'If-then' format. In the condition part of fuzzy rules, input space is partitioned with Fuzzy C-Means clustering. In the conclusion part of rules, the connection weight of pRBFNNs is represented as three kinds of polynomials such as constant, linear, and quadratic. Coefficients of connection weight identified with back-propagation using gradient descent method. The output of pRBFNNs model is obtained by fuzzy inference method in the inference part of fuzzy rules. The essential design parameters (including learning rate, momentum coefficient and fuzzification coefficient) of the networks are optimized by means of the Particle Swarm Optimization. The proposed pRBFNNs are applied to real-time face recognition system and then demonstrated from the viewpoint of output performance and recognition rate.

• Journal of the Korean Society of Marine Environment & Safety
• /
• v.29 no.2
• /
• pp.160-167
• /
• 2023

An INS is a composite navigation system providing "added value" so defined if work stations provide Multi-Function Displays(MFDs) integrating information and functions for navigational tasks. Even though the minimum requirements for an INS are defined by IMO performance standards, a generic list of the devices and functions that constitute an INS does not exist, so the configuration of the INS is different for each manufacturer, and guidelines based on users' perspectives are also insufficient. This study was conducted to enhance the usability of the INS by analyzing the information required by users according to the ship's operating status and tasks and effectively structuring it in the MFD of the INS. By analyzing INS-related international standards and manufacturers' component equipment lists, mandatory navigation information was selected and card sorting tests were conducted on ship operators with experience in using MFDs to group the information required for each INS task. The results of the study can serve as a basic guideline for manufacturers to structure information based on users' experience when designing products.

• Journal of the Korean Society for Railway
• /
• v.11 no.5
• /
• pp.441-448
• /
• 2008

Increasing urban sprawl and climate changes have been causing unexpected high-intensity rainfall events. Thus there are needs to enhance conventional disaster management system for comprehensive actions to secure safety. Therefore long-term and comprehensive flood management plans need to be well established. Recently torrential snowfall are occurring frequently, causing have snow traffic jams on the road. To secure safety and on-time operation of the Bi-modal tram system, well-structured disaster management system capable of analyzing the show pack melt/freezing due to unexpected snowfall are needed. To secure safety of the Bi-modal tram system due to torrential snow-fall, the snow melt simulation capability was investigated. The snow accumulation and snow melt were measured to validate the SWMM snow melt component. It showed that there was a good agreement between measured snow melt data and the simulated ones. Therefore, the Bi-modal tram disaster management system will be able to predict snow melt reasonably well to secure safety of the Bi-modal tram system during the winter. The Bi-modal tram disaster management system can be used to identify top priority area for know removal within the tram route in case of torrential snowfall to secure on-time operation of the tram. Also it can be used for detour route in the tram networks based on the disaster management system prediction.

• Journal of the Korean Society for information Management
• /
• v.41 no.1
• /
• pp.261-282
• /
• 2024

This study proposed and evaluated electroencephalography (EEG)-based and eye-tracking-based methods to determine relevance by utilizing users' implicit relevance feedback while navigating content in a digital library. For this, EEG/eye-tracking experiments were conducted on 32 participants using video, image, and text data. To assess the usefulness of the proposed methods, deep learning-based artificial intelligence (AI) techniques were used as a competitive benchmark. The evaluation results showed that EEG component-based methods (av_P600 and f_P3b components) demonstrated high classification accuracy in selecting relevant videos and images (faces/emotions). In contrast, AI-based methods, specifically object recognition and natural language processing, showed high classification accuracy for selecting images (objects) and texts (newspaper articles). Finally, guidelines for implementing a digital library interface based on EEG, eye-tracking, and artificial intelligence technologies have been proposed. Specifically, a system model based on implicit relevance feedback has been presented. Moreover, to enhance classification accuracy, methods suitable for each media type have been suggested, including EEG-based, eye-tracking-based, and AI-based approaches.

• Korean Journal of Remote Sensing
• /
• v.34 no.6_1
• /
• pp.1041-1053
• /
• 2018

In this study, a real-time storage level and capacity monitoring and forecasting system for Yongdam Dam watershed was developed using high resolution satellite image. The drought indices such as Standardized Precipitation Index (SPI) from satellite data were used for storage level monitoring in case of drought. Moreover, to predict storage volume we used a statistical method based on Principle Component Analysis (PCA) of Singular Spectrum Analysis (SSA). According to this study, correlation coefficient between storage level and SPI (3) was highly calculated with CC=0.78, and the monitoring and predictability of storage level was diagnosed using the drought index calculated from satellite data. As a result of analysis of principal component analysis by SSA, correlation between SPI (3) and each Reconstructed Components (RCs) data were highly correlated with CC=0.87 to 0.99. And also, the correlations of RC data with Normalized Water Surface Level (N-W.S.L.) were confirmed that has highly correlated with CC=0.83 to 0.97. In terms of high resolution satellite image we developed a water detection algorithm by applying an exponential method to monitor the change of storage level by using Multi-Spectral Instrument (MSI) sensor of Sentinel-2 satellite. The materials of satellite image for water surface area detection in Yongdam dam watershed was considered from 2016 to 2018, respectively. Based on this, we proposed the possibility of real-time drought monitoring system using high resolution water surface area detection by Sentinel-2 satellite image. The results of this study can be applied to estimate of the reservoir volume calculated from various satellite observations, which can be used for monitoring and estimating hydrological droughts in an unmeasured area.