• Journal of Elementary Mathematics Education in Korea
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• v.9 no.2
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• pp.85-110
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• 2005

The purpose of this study is to examine the characteristics of visual representation used in problem solving process and examine the representation types the students used to successfully solve the problem and focus on systematizing the visual representation method using the condition students suggest in the problems. To achieve the goal of this study, following questions have been raised. (1) what characteristic does the representation the elementary school students used in the process of solving a math problem possess? (2) what types of representation did students use in order to successfully solve elementary math problem? 240 4th graders attending J Elementary School located in Seoul participated in this study. Qualitative methodology was used for data analysis, and the analysis suggested representation method the students use in problem solving process and then suggested the representation that can successfully solve five different problems. The results of the study as follow. First, the students are not familiar with representing with various methods in the problem solving process. Students tend to solve the problem using equations rather than drawing a diagram when they can not find a word that gives a hint to draw a diagram. The method students used to restate the problem was mostly rewriting the problem, and they could not utilize a table that is essential in solving the problem. Thus, various errors were found. Students did not simplify the complicated problem to find the pattern to solve the problem. Second, the image and strategy created as the problem was read and the affected greatly in solving the problem. The first image created as the problem was read made students to draw different diagram and make them choose different strategies. The study showed the importance of first image by most of the students who do not pass the trial and error step and use the strategy they chose first. Third, the students who successfully solved the problems do not solely depend on the equation but put them in the form which information are decoded. They do not write difficult equation that they can not solve, but put them into a simplified equation that know to solve the problem. On fraction problems, they draw a diagram to solve the problem without calculation, Fourth, the students who. successfully solved the problem drew clear diagram that can be understood with intuition. By representing visually, unnecessary information were omitted and used simple image were drawn using symbol or lines, and to clarify the relationship between the information, numeric explanation was added. In addition, they restricted use of complicated motion line and dividing line, proper noun in the word problems were not changed into abbreviation or symbols to clearly restate the problem. Adding additional information was useful source in solving the problem.

• Journal of Korea Port Economic Association
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• v.38 no.1
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• pp.129-142
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• 2022

In the past, interest in air pollution was concentrated on greenhouse gases, but in recent years, interest in fine dust has been increasing. The media and environmental organizations continue to emphasize air pollution caused by fine dust. The awareness of fine dust is increasing, and air pollution generated at ports is analyzed to be serious as a domestic factor excluding foreign inflows. Recognizing this, in order to reduce air pollution generated at ports, special laws on improving air quality, such as port areas, have been enacted in Korea, and attempts are being made to curb air pollution caused by ports. In this law, it is a policy that regulates air pollutants generated not only by ships but also throughout ports such as vehicles and unloading machines, and representative are ECA, VSR, and AMP. This study attempted to analyze the effects of these eco-friendly policies at Incheon Port. First of all, a study was conducted to calculate emissions assuming that there was no policy, analyze each policy, and finally calculate and compare actual emissions reflecting all policies. The methodology presented by the European Environmental Administration and the U.S. Environmental Protection Agency was used, and pollutants to be analyzed were analyzed for sulfur oxides (SO_X), carbon monoxide (CO), nitrogen oxides (NO_X), total floating substances (TSP), fine dust and ultrafine dust (PM₁₀, PM_2.5) and ammonia (NH₃). As a result of the analysis, it was analyzed that the actual emission reflecting all policies was about 4,097 tons/year, which had an emission reduction effect of about 760 tons/year compared to about 4,857 tons/year when the policy was not reflected. When the effects of each policy were analyzed individually, it was found that ECA 4,111 tons/year, VSR 4,854 tons/year, and AMP 4,843 tons of air pollutant emissions occurred The results of this study can be used as basic data and evidence for policy establishment related to the atmospheric environment at Incheon Port.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.4
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• pp.363-371
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• 2023

To construct a ship, blocks of various sizes must be moved and erected . In this process, lugs are used such that they match the block fastening method and various functions suitable for the characteristics of each shipyard facility. The sizes and shapes of the lugs vary depending on the weight and shape of the block structures. The structure is reinforced by welding the doubling pads to compensate for insufficient rigidity around the holes where the shackle is fastened. As for the method of designing lugs according to lifting loading conditions, a simple calculation based on the beam theory and structural analysis using numerical modeling are performed. In the case of the analytical method, a standardized evaluation method must be established because results may differ depending on the type of element and modeling method. The application of this ambiguous methodology may cause serious safety problems during the process of moving and turning-over blocks. In this study , the effects of various parameters are compared and analyzed through numerical structural analysis to determine the modeling conditions and evaluation method that can evaluate the actual structural response of the lug. The modeling technique that represents the plate part and weld bead around the lug hole provides the most realistic behavior results. The modeling results with the same conditions as those of the actual lug where only the weld bead is connected to the main body of the lug, showed a lower ulimated strength compared with the results obtained by applying the MPC load. The two-dimensional shell element is applied to reduce the modeling and analysis time, and a safety working load was verified to be predicted by reducing the thickness of the doubling pad by 85%. The results of the effects of various parameters reviewed in the study are expected to be used as good reference data for the lug design and safe working load prediction.

• Korean Journal of Construction Engineering and Management
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• v.24 no.6
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• pp.24-35
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• 2023

Recently, the Ministry of Land, Infrastructure and Transport presented the '6th Construction Technology Promotion Basic Plan' and 'Smart Construction Revitalization Plan (2022.7.20)'. Off-Site Construction (OSC), which involves construction and production of PC (Precast Concrete) and Modular, etc., has advantages in shortening the construction period, reducing costs, improving quality, reducing construction waste, and reducing safety accidents. However, the construction cost is high compared to the traditional RC construction method, which has hindered its utilization and spread. In this study, OSC utilization was improved. An economic analysis indicator and methodology that can support decision-making in the planning and design stages for multi-unit housing were proposed. The factors used in the economic analysis of OSC (based on the PC method) of apartment houses were reviewed. As for the indicators used in the cost and benefit section, 'Construction Period', 'Disaster Occurrence', 'Waste Generation', and 'Greenhouse gas Emission', which reflect the technical advantages of OSC, were derived. In addition, a scenario analysis was conducted based on actual apartment housing case data for the presented economic analysis indicators and benefit calculation standards. The level of benefit that offsets the difference between the existing RC construction method and the construction cost was reviewed. In future studies, it will be necessary to conduct additional case studies to apply the measurement criteria for detailed indicators and supplement the benefit indicators.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.1-21
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• 2020

With the rapid development of artificial intelligence technology, various techniques have been developed to extract meaningful information from unstructured text data which constitutes a large portion of big data. Over the past decades, text mining technologies have been utilized in various industries for practical applications. In the field of business intelligence, it has been employed to discover new market and/or technology opportunities and support rational decision making of business participants. The market information such as market size, market growth rate, and market share is essential for setting companies' business strategies. There has been a continuous demand in various fields for specific product level-market information. However, the information has been generally provided at industry level or broad categories based on classification standards, making it difficult to obtain specific and proper information. In this regard, we propose a new methodology that can estimate the market sizes of product groups at more detailed levels than that of previously offered. We applied Word2Vec algorithm, a neural network based semantic word embedding model, to enable automatic market size estimation from individual companies' product information in a bottom-up manner. The overall process is as follows: First, the data related to product information is collected, refined, and restructured into suitable form for applying Word2Vec model. Next, the preprocessed data is embedded into vector space by Word2Vec and then the product groups are derived by extracting similar products names based on cosine similarity calculation. Finally, the sales data on the extracted products is summated to estimate the market size of the product groups. As an experimental data, text data of product names from Statistics Korea's microdata (345,103 cases) were mapped in multidimensional vector space by Word2Vec training. We performed parameters optimization for training and then applied vector dimension of 300 and window size of 15 as optimized parameters for further experiments. We employed index words of Korean Standard Industry Classification (KSIC) as a product name dataset to more efficiently cluster product groups. The product names which are similar to KSIC indexes were extracted based on cosine similarity. The market size of extracted products as one product category was calculated from individual companies' sales data. The market sizes of 11,654 specific product lines were automatically estimated by the proposed model. For the performance verification, the results were compared with actual market size of some items. The Pearson's correlation coefficient was 0.513. Our approach has several advantages differing from the previous studies. First, text mining and machine learning techniques were applied for the first time on market size estimation, overcoming the limitations of traditional sampling based- or multiple assumption required-methods. In addition, the level of market category can be easily and efficiently adjusted according to the purpose of information use by changing cosine similarity threshold. Furthermore, it has a high potential of practical applications since it can resolve unmet needs for detailed market size information in public and private sectors. Specifically, it can be utilized in technology evaluation and technology commercialization support program conducted by governmental institutions, as well as business strategies consulting and market analysis report publishing by private firms. The limitation of our study is that the presented model needs to be improved in terms of accuracy and reliability. The semantic-based word embedding module can be advanced by giving a proper order in the preprocessed dataset or by combining another algorithm such as Jaccard similarity with Word2Vec. Also, the methods of product group clustering can be changed to other types of unsupervised machine learning algorithm. Our group is currently working on subsequent studies and we expect that it can further improve the performance of the conceptually proposed basic model in this study.