• Journal of the Computational Structural Engineering Institute of Korea
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• v.21 no.6
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• pp.535-541
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• 2008

As the concurrent engineering concept has emerged along with the support of optimization techniques, lots of endeavors have been made to apply optimization techniques to actual design problems for a holistic decision. Even if the range of design problems which the optimization is applicable to has been extended, most of ship designs still remain in an iterative approach due to the difficulties of seamless integration of all related design activities. In this approach, an entire design problem is divided into many sub-problems and carried out by many different disciplines through complicated internal interactions. This paper focuses on preliminary ship design process. This paper proposes a process centric integrated framework as the first step to establish a workflow based design process management system. The framework consists of two parts; a schedule management part to support a manager to monitor current progress status and adjust current schedule, and a process management part to assist a design to effectively perform a series of design activities by following a predefined procedure. Overall system are decomposed into modules according to the target to be managed in each module. Appropriate interactions between the decomposed modules are designed to achieve a consistency of the entire system. Design process model is also designed on a thorough analysis of actual ship design practice. The proposed framework will be embodied using a commercial workflow package.

• The Journal of the Korea Contents Association
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• v.22 no.3
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• pp.500-512
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• 2022

Post-Occupancy Evaluation (POE), which is one of the construction environment evaluation methods, is a series of processes that ask about the functional requirements and satisfaction of an object from a life cycle perspective such as design/construction/residence. However, there are no POE research activities targeting large-scale units. On the other hand, large-scale third-phase new towns are being developed. Therefore, this study conducted a post-residence evaluation (POE) research activity in a large-scale unit (Multifunctional Administrative City). The procedure of this study is to conduct a literature survey on the current status and implications of the multi-functional administrative city area, and based on the research data, derive the Happy City evaluation index for the major issues and special issues of the Happy City. Afterwards, 450 questionnaires were conducted for the residents of Happy City, and POE analysis was performed on the derived data for each module. And based on the analysis results, implications such as problems and improvement points for the current status of the Happy City were derived. This can be used as a basis for the expansion of a large-scale new city into a self-sufficient city, and it can be used as a basic data for the development and improvement of a happy city that meets social needs in the future.

• Journal of Cadastre & Land InformatiX
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• v.53 no.1
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• pp.5-20
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• 2023

The government is operating a course evaluation-type qualification system for the purpose of overcoming the limitations of the test-type qualification system and cultivating talents with practical skills applicable to related industries. However, there is a part that does not match the purpose of the course evaluation qualification system by educating competency units in the field of surveying rather than the field of cadastral field in the education and training course of the course evaluation qualification. Therefore, this study closely analyzed the course evaluation qualification system in the cadastral field and suggested improvement plans accordingly. First, NCS in the cadastral field has not been supplemented or developed since its development in 2014, and there are many parts that do not conform to the current laws, so supplementary development is necessary. Second, It was proposed to improve the optional competency unit in the field of surveying to the NCS competency unit in the cadastral field. In addition, if the 12 competency units of the current NCS in the cadastral field are designated as essential competency units and education and training are operated, it will be possible to foster working-level talents with sufficient competency at the cadastral engineer level. However, for practical system operation and application, supplementation and development of NCS in the cadastral field, which is used for education and training of the course evaluation qualification system, must be preceded.

• Journal of Navigation and Port Research
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• v.42 no.6
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• pp.427-436
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• 2018

In this study, experimental and numerical analysis were performed on the survivability of a long pipe-type buoy structure in waves. The buoy structure is an articulated tower consisting of an upper structure, buoyancy module, and gravity anchor with long pipes forming the base frame. A series of experiment were performed in the ocean engineering basin of KRISO with the scaled model of 1/ 22 to evaluate the survivability of the buoy structure at West Sea in South Korea. Survival condition was considered as the wave of 50 year return period. Additional experiments were performed to investigate the effects of current and wave period. The factors considered for the evaluation of the buoy's survival were the pitch angle of the structure, anchor reaction force, and the number of submergence of the upper structure. Numerical simulations were carried out with the OrcaFlex, the commercial program for the mooring analysis, with the aim of performing mutual validation with the experimental results. Based on the evaluation, the behavior characteristics of the buoy structure were first examined according to the tidal conditions. The changes were investigated for the pitch angle and anchor reaction force at HAT and LAT conditions, and the results directly compared with those obtained from numerical simulation. Secondly, the response characteristics of the buoy structure were studied depending on the wave period and the presence of current velocity. Third, the number of submergence through video analysis was compared with the simulation results in relation to the submergence of the upper structure. Finally, the simulation results for structural responses which were not directly measured in the experiment were presented, and the structural safety discussed in the survival waves. Through a series of survivability evaluation studies, the behavior characteristics of the buoy structure were examined in survival waves. The vulnerability and utility of the buoy structure were investigated through the sensitivity studies of waves, current, and tides.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.97-117
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• 2020

Product evaluation criteria is an indicator describing attributes or values of products, which enable users or manufacturers measure and understand the products. When companies analyze their products or compare them with competitors, appropriate criteria must be selected for objective evaluation. The criteria should show the features of products that consumers considered when they purchased, used and evaluated the products. However, current evaluation criteria do not reflect different consumers' opinion from product to product. Previous studies tried to used online reviews from e-commerce sites that reflect consumer opinions to extract the features and topics of products and use them as evaluation criteria. However, there is still a limit that they produce irrelevant criteria to products due to extracted or improper words are not refined. To overcome this limitation, this research suggests LDA-k-NN model which extracts possible criteria words from online reviews by using LDA and refines them with k-nearest neighbor. Proposed approach starts with preparation phase, which is constructed with 6 steps. At first, it collects review data from e-commerce websites. Most e-commerce websites classify their selling items by high-level, middle-level, and low-level categories. Review data for preparation phase are gathered from each middle-level category and collapsed later, which is to present single high-level category. Next, nouns, adjectives, adverbs, and verbs are extracted from reviews by getting part of speech information using morpheme analysis module. After preprocessing, words per each topic from review are shown with LDA and only nouns in topic words are chosen as potential words for criteria. Then, words are tagged based on possibility of criteria for each middle-level category. Next, every tagged word is vectorized by pre-trained word embedding model. Finally, k-nearest neighbor case-based approach is used to classify each word with tags. After setting up preparation phase, criteria extraction phase is conducted with low-level categories. This phase starts with crawling reviews in the corresponding low-level category. Same preprocessing as preparation phase is conducted using morpheme analysis module and LDA. Possible criteria words are extracted by getting nouns from the data and vectorized by pre-trained word embedding model. Finally, evaluation criteria are extracted by refining possible criteria words using k-nearest neighbor approach and reference proportion of each word in the words set. To evaluate the performance of the proposed model, an experiment was conducted with review on '11st', one of the biggest e-commerce companies in Korea. Review data were from 'Electronics/Digital' section, one of high-level categories in 11st. For performance evaluation of suggested model, three other models were used for comparing with the suggested model; actual criteria of 11st, a model that extracts nouns by morpheme analysis module and refines them according to word frequency, and a model that extracts nouns from LDA topics and refines them by word frequency. The performance evaluation was set to predict evaluation criteria of 10 low-level categories with the suggested model and 3 models above. Criteria words extracted from each model were combined into a single words set and it was used for survey questionnaires. In the survey, respondents chose every item they consider as appropriate criteria for each category. Each model got its score when chosen words were extracted from that model. The suggested model had higher scores than other models in 8 out of 10 low-level categories. By conducting paired t-tests on scores of each model, we confirmed that the suggested model shows better performance in 26 tests out of 30. In addition, the suggested model was the best model in terms of accuracy. This research proposes evaluation criteria extracting method that combines topic extraction using LDA and refinement with k-nearest neighbor approach. This method overcomes the limits of previous dictionary-based models and frequency-based refinement models. This study can contribute to improve review analysis for deriving business insights in e-commerce market.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.25 no.2
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• pp.63-75
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• 2013

The Inner Port Phase 2 area of the Pyeongtaek-Dangjin Port is enclosed by a total of three permeable sea-walls, and the disposal site to the east of the Inner Port Phase 2 is also enclosed by two permeable sea-walls. The maximum tidal range measured in the Inner Port Phase 2 and in the disposal site in May 2010 is 4.70 and 2.32 m, respectively. It reaches up to 54 and 27%, respectively of 8.74 m measured simultaneously in the exterior. Regression formulas between the difference of hydraulic head and the rate of interior water volume change, are induced. A three-dimensional numerical hydrodynamic model for the Asan Bay is constructed incorporating a module to compute water discharge through the permeable sea-walls at each computation time step by employing the formulas. Hydrodynamics for the period from 13th to 27th May, 2010 is simulated by driving forces of real-time reconstructed tide with major five constituents($M_2$, $S_2$, $K_1$, $O_1$ and $N_2$) and freshwater discharges from Asan, Sapkyo, Namyang and Seokmoon Sea dikes. The skill scores of modeled mean high waters, mean sea levels and mean low waters are excellent to be 96 to 100% in the interior of permeable sea-walls. Compared with the results of simulation to obstruct the flow through the permeable sea-walls, the maximum current speed increases by 0.05 to 0.10 m/s along the main channel and by 0.1 to 0.2 m/s locally in the exterior of the Outer Sea-wall of Inner Port. The maximum bottom shear stress is also intensified by 0.1 to 0.4 $N/m^2$ in the main channel and by more than 0.4 $N/m^2$ locally around the arched Outer Sea-wall. The module developed to compute the flow through impermeable seawalls can be practically applied to simulate and predict the advection and dispersion of materials, the erosion or deposion of sediments, and the local scouring around coastal structures where large-scale permeable sea-walls are maintained.

• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.4
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• pp.126-138
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• 2017

Recently, the national interest in environment is increasing and for dealing with water environment-related issues swiftly and accurately, the demand to facilitate the analysis of water environment data using a GIS is growing. To meet such growing demands, a spatial network data-based stream network analysis map(Korean Reach File; KRF) supporting spatial analysis of water environment data was developed and is being provided. However, there is a difficulty in delineating catchment areas, which are the basis of supplying spatial data including relevant information frequently required by the users such as establishing remediation measures against water pollution accidents. Therefore, in this study, the development of a computer program was made. The development process included steps such as designing a delineation method, and developing an algorithm and modules. DEM(Digital Elevation Model) and FDR(Flow Direction) were used as the major data to automatically delineate catchment areas. The algorithm for the delineation of catchment areas was developed through three stages; catchment area grid extraction, boundary point extraction, and boundary line division. Also, an add-in catchment area delineation module, based on ArcGIS from ESRI, was developed in the consideration of productivity and utility of the program. Using the developed program, the catchment areas were delineated and they were compared to the catchment areas currently used by the government. The results showed that the catchment areas were delineated efficiently using the digital elevation data. Especially, in the regions with clear topographical slopes, they were delineated accurately and swiftly. Although in some regions with flat fields of paddles and downtowns or well-organized drainage facilities, the catchment areas were not segmented accurately, the program definitely reduce the processing time to delineate existing catchment areas. In the future, more efforts should be made to enhance current algorithm to facilitate the use of the higher precision of digital elevation data, and furthermore reducing the calculation time for processing large data volume.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.149-162
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• 2014

Course guidance is a mentoring process which is performed before students register for coming classes. The course guidance plays a very important role to students in checking degree audits of students and mentoring classes which will be taken in coming semester. Also, it is intimately involved with a graduation assessment or a completion of ABEEK certification. Currently, course guidance is manually performed by some advisers at most of universities in Korea because they have no electronic systems for the course guidance. By the lack of the systems, the advisers should analyze each degree audit of students and curriculum information of their own departments. This process often causes the human error during the course guidance process due to the complexity of the process. The electronic system thus is essential to avoid the human error for the course guidance. If the relation data model-based system is applied to the mentoring process, then the problems in manual way can be solved. However, the relational data model-based systems have some limitations. Curriculums of a department and certification systems can be changed depending on a new policy of a university or surrounding environments. If the curriculums and the systems are changed, a scheme of the existing system should be changed in accordance with the variations. It is also not sufficient to provide semantic search due to the difficulty of extracting semantic relationships between subjects. In this paper, we model a course mentoring ontology based on the analysis of a curriculum of computer science department, a structure of degree audit, and ABEEK certification. Ontology-based course guidance system is also proposed to overcome the limitation of the existing methods and to provide the effectiveness of course mentoring process for both of advisors and students. In the proposed system, all data of the system consists of ontology instances. To create ontology instances, ontology population module is developed by using JENA framework which is for building semantic web and linked data applications. In the ontology population module, the mapping rules to connect parts of degree audit to certain parts of course mentoring ontology are designed. All ontology instances are generated based on degree audits of students who participate in course mentoring test. The generated instances are saved to JENA TDB as a triple repository after an inference process using JENA inference engine. A user interface for course guidance is implemented by using Java and JENA framework. Once a advisor or a student input student's information such as student name and student number at an information request form in user interface, the proposed system provides mentoring results based on a degree audit of current student and rules to check scores for each part of a curriculum such as special cultural subject, major subject, and MSC subject containing math and basic science. Recall and precision are used to evaluate the performance of the proposed system. The recall is used to check that the proposed system retrieves all relevant subjects. The precision is used to check whether the retrieved subjects are relevant to the mentoring results. An officer of computer science department attends the verification on the results derived from the proposed system. Experimental results using real data of the participating students show that the proposed course guidance system based on course mentoring ontology provides correct course mentoring results to students at all times. Advisors can also reduce their time cost to analyze a degree audit of corresponding student and to calculate each score for the each part. As a result, the proposed system based on ontology techniques solves the difficulty of mentoring methods in manual way and the proposed system derive correct mentoring results as human conduct.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.93-107
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• 2014

In this paper, we report what we have observed with regard to user-perspective issue clustering based on multi-layered two-mode network analysis. This work is significant in the context of data collection by companies about customer needs. Most companies have failed to uncover such needs for products or services properly in terms of demographic data such as age, income levels, and purchase history. Because of excessive reliance on limited internal data, most recommendation systems do not provide decision makers with appropriate business information for current business circumstances. However, part of the problem is the increasing regulation of personal data gathering and privacy. This makes demographic or transaction data collection more difficult, and is a significant hurdle for traditional recommendation approaches because these systems demand a great deal of personal data or transaction logs. Our motivation for presenting this paper to academia is our strong belief, and evidence, that most customers' requirements for products can be effectively and efficiently analyzed from unstructured textual data such as Internet news text. In order to derive users' requirements from textual data obtained online, the proposed approach in this paper attempts to construct double two-mode networks, such as a user-news network and news-issue network, and to integrate these into one quasi-network as the input for issue clustering. One of the contributions of this research is the development of a methodology utilizing enormous amounts of unstructured textual data for user-oriented issue clustering by leveraging existing text mining and social network analysis. In order to build multi-layered two-mode networks of news logs, we need some tools such as text mining and topic analysis. We used not only SAS Enterprise Miner 12.1, which provides a text miner module and cluster module for textual data analysis, but also NetMiner 4 for network visualization and analysis. Our approach for user-perspective issue clustering is composed of six main phases: crawling, topic analysis, access pattern analysis, network merging, network conversion, and clustering. In the first phase, we collect visit logs for news sites by crawler. After gathering unstructured news article data, the topic analysis phase extracts issues from each news article in order to build an article-news network. For simplicity, 100 topics are extracted from 13,652 articles. In the third phase, a user-article network is constructed with access patterns derived from web transaction logs. The double two-mode networks are then merged into a quasi-network of user-issue. Finally, in the user-oriented issue-clustering phase, we classify issues through structural equivalence, and compare these with the clustering results from statistical tools and network analysis. An experiment with a large dataset was performed to build a multi-layer two-mode network. After that, we compared the results of issue clustering from SAS with that of network analysis. The experimental dataset was from a web site ranking site, and the biggest portal site in Korea. The sample dataset contains 150 million transaction logs and 13,652 news articles of 5,000 panels over one year. User-article and article-issue networks are constructed and merged into a user-issue quasi-network using Netminer. Our issue-clustering results applied the Partitioning Around Medoids (PAM) algorithm and Multidimensional Scaling (MDS), and are consistent with the results from SAS clustering. In spite of extensive efforts to provide user information with recommendation systems, most projects are successful only when companies have sufficient data about users and transactions. Our proposed methodology, user-perspective issue clustering, can provide practical support to decision-making in companies because it enhances user-related data from unstructured textual data. To overcome the problem of insufficient data from traditional approaches, our methodology infers customers' real interests by utilizing web transaction logs. In addition, we suggest topic analysis and issue clustering as a practical means of issue identification.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.7
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• pp.138-143
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• 2016

The designed and fabricated millimeter-wave security screening system receives radiation energy from an object and a human body. The imaging system consist of sixteen array antennas, sixteen four-stage LNAs, sixteen detectors, an infrared camera, a CCD camera, reflector, and a focusing lens. This system requires high sensitivity and wide bandwidth to detect the input thermal noise. The LNA module of the system has been measured to have 65.8 dB in average linear gain and 82 GHz~102 GHz in bandwidth to enhance the sensitivity for thermal noise, and to receive it over a wide bandwidth. The detector is used for direct current (DC) output translation of millimeter-wave signals with a zero bias Schottky diode. The lens and front-end of the millimeter-wave sensor are important in the system to detect the input thermal noise signal. The frequency range in the receiving sensitivity of the detectors was 350 to 400 mV/mW at 0 dBm (1 mW) input power. The developed W-band imaging system is effective for detecting and identifying concealed objects such as metal or plastic.