1. Company introduction It is a comprehensive energy service corporation that supplies city gas throughout Daejeon Metropolitan City and Gyeryong City since its establishment in 1985. ※ In October 2017, the name was changed from Chungnam Urban Gas Co., Ltd. to CNCITY Energy Co., Ltd.     2. Problem Background and Summary Local city gas suppliers, including CNCTITY Energy Co., Ltd., are selling gas supplied by Korea Gas Corporation after predicting the supply in advance a year ago. When signing a contract with Korea Gas Corp. and changing the contract, there is a problem that the supply must be accurately predicted at least two months ago. Precise demand forecasts are needed to improve the limits of different meter dates and long-term temperature forecasts for different generations. The goal is to establish a more accurate demand forecasting model by analyzing the effects of sudden variables such as climate change, recession, and population fluctuations on gas demand, along with verifying the adequacy of existing data analysis (linear recovery analysis).     3. Solving Process For mid- to long-term forecasting, we developed a gas usage prediction model two months later by utilizing LSTM, one of the methods of deep learning. After receiving data such as sales volume by generation/use and daily temperature-linked supply, it was confirmed that the results of the existing linear return analysis were significant.   4. Ripple effects and future plans Based on mathematical theories such as fourier series and ARIMA, the daily/monthly gas demand rate is similar to regression analysis, but it is expected to be efficient when supplemented. Various variables affecting demand will be added and used as a mathematical basis for the actual demand forecast and order quantity calculation by the requesting company.

1. Company introduction The Marine Police Agency is a central administrative agency in charge of operations such as security and rescue, maritime traffic safety management, maritime security, and marine environment conservation. The Equipment Management Division of the Equipment Engineering Bureau that requested the problem manages about 300 vessels owned by the Marine Police Agency and is in charge of repair work in the event of a failure.           2. Problem Background and Summary If a ship of the National Maritime Police Agency suddenly breaks down, we will carry out emergency repairs, but if the total annual cost of the current emergency repair costs is not predicted, the allocated budget and the actual cost will not match There are many cases. The goal is to create a mathematical model that analyzes the scale and trend of urgent repair costs using mathematical methods and predicts appropriate emergency repair costs. It is necessary to formulate a formula for predicting the scale of emergency repair costs based on an analysis of the correlation between some characteristics of ships (tonnage, usage, year, etc.) and emergency repair costs.   3. Solving Process By substituting the tonnage and the number of ships for each type of ship that will be operated in the following year, we derived an emergency repair prediction model that can predict the scale of emergency repair costs. The correlation between ship tonnage and emergency repair cost was analyzed by applying a linear regression analysis model, and it was confirmed that the coefficient of determination was 0.95 or more, which was very accurate. 4. Ripple effects and future plans A report of the troubleshooting results has been ted to the Marine Police Agency and the research is complete. In addition to 2018, by using the mathematical model that has been built, it is expected that the amount of emergency repair costs incurred each year will be continuously predicted, and that emergency repairs for ships can be carried out satisfactorily. "The coefficient of determination of the mathematical prediction model for emergency repairs has been derived and can be used as an objective basis for future budget planning for emergency repairs," said Jung-wook, Chief of Equipment Management, Marine Police Agency.

1. Company introduction ㈜ Good Learning Value Improvement Center is a startup that develops and operates "onestopsurvey.com", a corporate performance management consulting and web-based online survey creation and statistical analysis site.     2. Problem Background and Summary In developing the online statistical analysis site "onestopsurvey.com", the following problems exist due to the mathematical verification of statistical analysis and the lack of professional manpower. Sites are difficult to use by users with insufficient experience in statistics and questionnaire writing. So We want to implement various statistical solutions on the web to meet customer demand. The current site is slow in processing compared to other statistical solutions. Our goal is to provide a mathematical explanation that can be clearly understood by site users and to produce an analysis implementation method manual to facilitate the loading of new analysis methods. 3. Solving Process The theoretical part of statistical analysis used in various fields was provided. To implement statistical analyses, we provided a way to fill out a questionnaire and implement it in statistical software R. A series of processes were documented with the developer of Good Learning Value Improvement Center, from theoretical explanations to how to mount data on websites, to facilitate the installation of new analytical models.   4. Ripple effects and future plans The statistical analysis site was opened (July 2017) by improving the method of deriving the results of the existing statistical analysis. We are currently exploring joint research projects after the completion of phase I support. Based on the mathematical data analysis ability and industrial problem-solving ability shown by the joint research period research institute, the research service of the Korea Coast Guard was developed "Development of a Repair Model for Prediction of Emergency Repair Expenses of Marine Police Ship."  

1. Company introduction GOONIES Co., Ltd. is a manufacturer of electrical equipment established in 2014 and is actively engaged in business activities such as participating in the Dubai Information and Communication Shopping Fair after being selected as a best-practice company for each stage of the Creative Factory organized by the Small and Medium Business Administration in 2015. Smart palette, a digital tool for drawing pictures by connecting to a smartphone, is the main product   2. Problem Background and Summary We are going to proceed with the patent based on the idea of putting balls and bearings inside the touch pen needed to use smart palettes. To do this, a mathematical basis is needed to explain the size of the ball and bearing. A geometrical analysis describing the relationship between the ball and the proper radius of the bearing is required. Calculate the appropriate ball and bearing radius according to the shape and size of the touch pen, and try to find possible number of bearings.     3. Solving Process A comprehensive repair model explaining the characteristics of the touch pen was produced so that the proper value of the radius of the ball and bearing and the possible number of bearings could be calculated according to various circumstances. The principles of geometry (triangle ratio, equation of circle, Pythagorean theorem, etc.) were used to derive the relational consciousness among the necessary variables.   4. Ripple effects and future plans Based on the mathematical analysis described in this question, the process of registering this idea as a patent is currently underway. By creating a model that mathematically articulates the idea of placing balls and bearings inside a touch pen, the idea could also be extended to other tools (wheeled chairs, department store carts, etc.) that rotate 360 times. Lee Yoon-jae, CEO of KUNS, said, "We have obtained more detailed mathematical analysis than what is needed to register patents."  

1. Company introduction A state-run company set up independent of Korea Electric Power Corp., which produces 31.9 percent of the nation's electricity Major projects include nuclear power generation, hydroelectric power generation, radioactive waste management, new and renewable energy development such as wind power, nuclear power plant construction, and other overseas nuclear power construction projects. 2. Problem Background and Summary Minimize the change path when changing the position of the insert during planned preventive maintenance of the nuclear power plant. 3. Solving Process Linear Programing(TSP) Application Using Linear Planning Method. It is considered that 33 fuels currently mounted on the insert and 33 fuels mounted on the insert are present on a plane. In other words, use Linear Programming in a loop that passes through all 66 points once (group 1: 33 nuclear fuel currently installed in the insert, group 2: 33 fuel inserted in the insert). - Path connecting points in group 1 should always be associated with points in group 2. Similarly, Path connecting points in Group 2 should always be associated with points in Group 1. (From the fuel on which the inserts are mounted, the inserts to the fuel on which the inserts are not mounted, install them, and then return to the fuel on which the inserts are mounted.) - Find a loop that minimizes the sum of all pathways (this minimized loop minimizes the pathways of the fuel inserts). It provided the Korea Hydro & Nuclear Power Co. with a way to find a loop that meets the above conditions using a Solver from Linear Programming.