• Journal of the Korea Society for Simulation
• /
• v.28 no.2
• /
• pp.107-117
• /
• 2019

Because shipbuilding is single-product production with limited resources, production management technology is essential to manage the resources effectively and maximize the productivity of ship-process. Therefore, many shipbuilding companies are conducting research on ship production plan and process considering various constraints in the field by applying modeling and simulation. However, it is difficult to provide accurate production plan on sudden schedule and process changes, and to understand the interconnectivity between the processes that produce blocks in existing research. In addition, there are many differences between the production planning and field planning because detailed processes and quantity of blocks can not be considered. In this research, we propose the integrated process-based modeling method considering process-operation sequences, BOM(Bill of materials) and resource constraints of all the scheduled blocks in the indoor system. Through the integrated process-based model, it is easy for the user to grasp the assembly relationship, workspace and preliminary relationship of assembly process between the blocks in indoor system. Also, it is possible to obtain the overall production plan that maximizes resource efficiency without the separate simulation and resource modeling procedures because resource balancing that considers the amount of resource quantity shared in the indoor system is carried out.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2016.10a
• /
• pp.256-259
• /
• 2016

The growth of mobile devices in Internet of Things (IoT) leads to a number of intelligent buildings related IoT applications. For instance, home automation controlling system uses client system such web apps on smartphone or web service to access the home server by sending control commands. The home server receives the command, then controls for instance the light system. The gateway based RESTful technology responsible for handling clients' requests attests an internet latency in case a large number of clients' requests submit toward the gateway increases. In this paper, we propose the design tasks of the IoT gateway for handling concurrency events. In the procedure of designing tasks, concurrency is best understood by employing multiple levels of abstraction. The way that is eminently to accomplish concurrency is to build an object-oriented environment with support for messages passing between concurrent objects. We also investigate the performance of event-driven architecture for building IoT gateway using node.js on one side and communication protocol based message-oriented middleware known as XMPP to handle communications of intelligent building control devices connected to the gateway through a centralized hub. The Node.JS is 40% faster than the traditional web server side features thread-based approach. The use of Node.js server-side handles a large number of clients' requests, then therefore, reduces delay in performing predefined actions automatically in intelligent building IoT environment.

• The Korean Journal of Archival Studies
• /
• no.53
• /
• pp.45-77
• /
• 2017

This study intends to rehabilitate the memories of the social other which have been gradually forgotten in the social events overloaded with the undemocratic violence in South Korea today. This study explores a case of Yongsan Tragedy in 2009 among the most tragic events. It notes the autonomous ways in which activist artists would like to memorize the socio-historical events anew despite the emptiness of public records. In other words, this study considers the Yongsan case to be significant that a group of the public, artists, grassroots activists, religion men got together in solidarity so as to create the contested narratives countering dominant memories and thus to signify the records written by the civil society. Among others, activist artists had documented the unofficial counter-memories of socially alienated peoples in terms of planning a series of artistic events such as opening some gallery exhibitions and performance events, issuing a volume of work books, comics and photographies, online broadcasting, and directing some documentaries. Especially, this paper tends to note the documentation of on-site activist artists to record the counter-memories against social oblivion. By doing so, it finally suggests how we could document the Yongsan Tragedy both to search out the archival implications of today's art activism and to insert those artistic records into the commonly shared counter-memories in a more inclusive way.

• Database Research
• /
• v.34 no.3
• /
• pp.148-158
• /
• 2018

The optical character recognition (OCR) is a technique to extract and recognize texts from images. It is an important preprocessing step in data analysis since most actual text information is embedded in images. Many OCR engines have high recognition accuracy for images where texts are clearly separable from background, such as white background and black lettering. However, they have low recognition accuracy for images where texts are not easily separable from complex background. To improve this low accuracy problem with complex images, it is necessary to transform the input image to make texts more noticeable. In this paper, we propose a method to segment an input image into text lines to enable OCR engines to recognize each line more efficiently, and to determine the final output by comparing the recognition rates of CLAHE module and Two-step module which distinguish texts from background regions based on image processing techniques. Through thorough experiments comparing with well-known OCR engines, Tesseract and Abbyy, we show that our proposed method have the best recognition accuracy with complex background images.

• Journal of Korean Society of Neurocognitive Rehabilitation
• /
• v.10 no.2
• /
• pp.1-7
• /
• 2018

The study has compared normally developed children and children who were diagnosed as autism spectrum in goal management training them to observe the effect. The research was conducted to four normally developed children and four children who were diagnosed as autism spectrum, and all subjects were provided with identical goal management training. The children and the caregivers have selected desired objectives activity, and all three activities were followed by goal management training. Intervention periods were conducted ten times in total, two times a week for five weeks, and eight subjects in the two groups were trained one on one by the researcher. The training time was 40 minutes for every session. The descriptive statistics and frequency analysis were used as the statistical method, and the Mann-Whitney test, the nonparametric statistical analysis, was conducted to compare the difference between the two groups. Goal management training for two groups did not show a statistically significant difference in terms of the performance status of Canadian Occupational Performance Measure (p>.05). In the summary of Bruininks-Oseretsky Test of Motor Proficiency (2nd) which evaluates the motor skill, there was a statistically significant difference between the autism spectrum disorder group and normal group (p<.05). Additionally, the two groups showed a statistically significant difference in eye-hand coordination sub-test among Developmental Test of Visual Perception (2nd) which evaluates the visual perception performance (p<.05). The research has confirmed the applicability of goal management training to children with autism spectrum compared to the normally developed children, and it has confirmed the effectiveness of the training.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.41 no.3
• /
• pp.305-316
• /
• 2021

Construction accidents occur due to a number of reasons-worker carelessness, non-adoption of safety equipment, and failure to comply with safety rules are some examples. Because much construction work is done outdoors, weather conditions can also be a factor in accidents. Past construction accident data are useful for accident prevention, but since construction accident data are often in a text format consisting of natural language, extracting construction hazards from construction accident data can take a lot of time and that entails extra cost. Therefore, in this study, we extracted construction hazards from 2,026 domestic construction accident reports using text mining and performed a seasonal analysis of construction hazards through frequency analysis and centrality analysis. Of the 254 construction hazards defined by Korea's Ministry of Land, Infrastructure, and Transport, we extracted 51 risk factors from the construction accident data. The results showed that a significant hazard was "Formwork" in spring and autumn, "Scaffold" in summer, and "Crane" in winter. The proposed method would enable construction safety managers to prepare better safety measures against outdoor construction accidents according to weather, season, and climate.

• KIPS Transactions on Software and Data Engineering
• /
• v.11 no.3
• /
• pp.141-148
• /
• 2022

Recently, reinforcement learning combined with deep neural network technology has achieved remarkable success in various fields such as board games such as Go and chess, computer games such as Atari and StartCraft, and robot object manipulation tasks. However, such deep reinforcement learning describes states, actions, and policies in vector representation. Therefore, the existing deep reinforcement learning has some limitations in generality and interpretability of the learned policy, and it is difficult to effectively incorporate domain knowledge into policy learning. On the other hand, dNL-RRL, a new relational reinforcement learning framework proposed to solve these problems, uses a kind of vector representation for sensor input data and lower-level motion control as in the existing deep reinforcement learning. However, for states, actions, and learned policies, It uses a relational representation with logic predicates and rules. In this paper, we present dNL-RRL-based policy learning for transportation mobile robots in a manufacturing environment. In particular, this study proposes a effective method to utilize the prior domain knowledge of human experts to improve the efficiency of relational reinforcement learning. Through various experiments, we demonstrate the performance improvement of the relational reinforcement learning by using domain knowledge as proposed in this paper.

• Journal of the Korean Society of Marine Environment & Safety
• /
• v.28 no.1
• /
• pp.141-152
• /
• 2022

As interest increases related to the development of eco-friendly energy, the offshore wind turbine market is growing at an increasing rate every year. In line with this, the demand for an installation vessel with large scaled capacity is also increasing rapidly. The wind turbine installation vessel (WTIV) is a fixed penetration of the spudcan in the sea-bed to install the wind turbine. At this time, a review of the spudcan is an important issue regarding structural safety in the entire structure system. In the study, we analyzed the current procedure suggested by classification of societies and new procedures reflect the new loading scenarios based on reasonable operating conditions; which is also verified through FE-analysis. The current procedure shows that the maximum stress is less than the allowable criteria because it does not consider the effect of the sea-bed slope, the leg bending moment, and the spudcan shape. However, results of some load conditions as defined by the new procedure confirm that it is necessary to reinforce the structure to required levels under actual pre-load conditions. Therefore, the new procedure considers additional actual operating conditions and the possible problems were verified through detailed FE-analysis.

• Korean Journal of Construction Engineering and Management
• /
• v.23 no.4
• /
• pp.15-25
• /
• 2022

As the incidence and mortality of serious disasters in the construction industry are the highest, various efforts are being made in Korea to reduce them. Among them, risk assessment is used as data for disaster reduction measures and evaluation of risk factors at the construction stage. However, the existing risk assessment involves the subjectivity of the performer and is vulnerable to the domestic construction site. This study established a DB classification system for risk assessment with the aim of early identification and pre-removal of risks by quantitatively deriving risk factors using BIM in the risk assessment field and presents a methodology for risk assessment using BIM. Through this, prior removal of risks increases the safety of construction workers and reduces additional costs in the field of safety management. In addition, since it can be applied to new construction methods, it improves the understanding of project participants and becomes a tool for communication. This study proposes a framework for deriving quantitative risks based on BIM, and will be used as a base technology in the field of risk assessment using BIM in the future.

• Korean Association of Arts Management
• /
• no.53
• /
• pp.207-247
• /
• 2020

is a project for the senior generation with humanistic knowledge to become a mentor and communicate with them to present the wisdom and direction of life to the new generations of mentees based on various life experiences. has been expanding since 2015, starting with the pilot operation in 2014. In general, projects such as these are assessed to establish effectiveness indicators to verify effectiveness and to establish project management and development strategies. However, most of the evaluations have been conducted quantitatively and qualitatively based on the short-term duration of the project. Therefore, in the case of continuous projects such as , especially in the field of culture and arts where long-term effectiveness verification is required, the short-term evaluation is difficult to predict and judge the actual meaningful effects. In this regard, tried to examine the qualitative change of key participants in this project through the 2017 and 2018 image tracking survey. For this purpose, we adopted qualitative research methodology through interview video shooting, field shooting, and value coding as a research method suitable for the research subject. To analyze the results, first, the interview images were transcribed, keywords were extracted, value encoding works were matched with human psychological values, and the theoretical method was used to identify changes and to derive the meaning. In fact, despite the fact that the study conducted in this study was a follow-up survey, it remained a limitation that it analyzed the changed pattern in a rather short time of 2 years. However, this study systemized the specific methodology that researchers should conduct for follow-up and provided the flow of research at the present time when there is hardly a model for follow-up in the field of culture and arts education business in Korea as well as abroad. Significance can be derived from this point. In addition, it can be said that it has great significance in preparing the detailed system and case of comparative analysis methodology through value coding.