• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.15 no.2
• /
• pp.36-49
• /
• 2016

A subway system is one of the major transportation modes at a metropolitan area. When it meets the other lines, the metro station, so-called transferring station, is usually threatened by severe pedestrian congestion and safety issue of transit users including the transportation vulnerable. Although transportation planners forecast travel demand at the beginning, it is not easy to predict pedestrian flows precisely for a long term if land use plans have dramatically changed. Due to expensive costs, structural extension of metro stations is limited. Therefore, it requires efficient and technical improvements as meeting the demand of pedestrian and physical characteristics. In this study, the core mechanism of pedestrian movement-based simulation model was introduced and evacuation scenarios were analyzed with the developed model. As a result, the multiple optimal routes for unexpected events at the solid space of the multiple stories are easily searched through the simulator and in the case of Sadang Station, travel time can be reduced by 60% when the evacuation information and intuitive design are provided.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.32 no.3D
• /
• pp.213-222
• /
• 2012

After enforcing 2007 semi-public management system of intra-city bus, Busan city has tried to promote the bus utilization through bus service improvements. As an effort for this, we attempted to clarify the main factors affecting to bus service satisfaction targeting intra-city bus users. In this study, 20 subcategories of intra-city bus service were assorted into 6 factors: Basic Service, Safe Driving, Route Information, Comfort, Cleanliness and Facilities, then the preference for each detailed bus service were analyzed. And the effects for bus service satisfaction were shown under the various conditions according to the general characteristics of intra-city bus users (gender, age), behavioral traffic characteristics (frequency of use, boarding time) and transportation environments (temperature, rainfall). These results would be important basic data for decision-making in bus policy for climate change and establishment of operating plan for bus utilization.

• The Journal of Industrial Distribution & Business
• /
• v.5 no.2
• /
• pp.29-35
• /
• 2014

Purpose - The study aimed to evaluate the market opportunities and constraints confronting resource-poor pig farmers in South Africa. Research design, data, and methodology - Information was collected from 292 households in three municipalities through interviews with key informants. The data collected included socio-economic characteristics, major market channels, prices for different pig classes, average weight of the pigs on sale, number of pigs sold annually, and preferred meat quality attributes. Results - In Ngqushwa, 96% of respondents sold pigs as compared to Elundini (81%) and Ntabankulu (65%). Less resource-poor households and those with market-oriented production had large herdsizes (P < 0.05) when compared to more resource-poor farmers. The probability of selling pigs was high for the backyard production system and educated farmers. For all farmers, opportunities included high pork demand, good prices, employment creation, and a niche market for organically produced indigenous pork. Constraints include disease, feed shortages for large herds, distances to formal markets, lack of training, and drugs. Conclusions - Constraints outnumbered opportunities for the resource-poor pig farmers.

• Journal of Korean Society on Water Environment
• /
• v.25 no.5
• /
• pp.735-741
• /
• 2009

In order to support the basic information for planning and performing the environment management such as Total Maximum Daily Loads (TMDLs), it is highly recommended to understand the spatial distribution of water quality and runoff data in the unit watersheds. Therefore, in the present study, we applied Self-Organizing Map (SOM) to detect the characteristics of spatial distribution of Biological Oxygen Demand (BOD) concentration and runoff data which have been measured in the Yeongsan, Seomjin, and Tamjin River basins. For the purpose, the input dataset for SOM was constructed with the mean, standard deviation, skewness, and kurtosis values of the respective data measured from the stations of 22-subbasins in the rivers. The results showed that the $4{\times}4$ array structure of SOM was selected by the trial and error method and the best performance was revealed when it classified the stations into three clusters according to the basic statistics. The cluster-1 and 2 were classified primarily by the skewness and kurtosis of runoff data and the cluster-3 including the basic statistics of YB_B, YB_C, and YB_D stations was clearly decomposed by the mean value of BOD concentration showing the worst condition of water quality among the three clusters. Consequently, the methodology based on the SOM proposed in the present study can be considered that it is highly applicable to detect the spatial distribution of BOD concentration and runoff data and it can be used effectively for the further utilization using different water quality items as a data analysis tool.

• Journal of IKEEE
• /
• v.21 no.2
• /
• pp.105-114
• /
• 2017

This paper proposes a design method of an LCL-filter for grid-tied three-level inverter systems. The demand for three-phase PWM inverters in applications such as wind or solar power generation systems has been increase in recent years. To reduce harmonic components caused by switching operation, such inverters are connected to the grid via an LCL filter. Although there are research results for designing LCL-filter, the modulation method should be fully considered to make the filter perform desired cancellation ability with minimized size. This paper presents the design methodology for an LCL-filter that is optimized for SVM switching operations. The simulation and experimental results verify the validity of the LCL-filter designed with proposed method in this paper.

• Archives of design research
• /
• v.11 no.1
• /
• pp.245-258
• /
• 1998

Due to the information technology improvement and the changing life style, a home is getting a new role of workspace besides the main function as rest area for the family members. Therefore, a demand for the home workstation furniture is increasing nowadays. In this study, three types of workstation furniture id designed, that makes possible the effective works and reflects the characteristics of the house. 1. Panel-based system furniture : main concept is flexibility and expandability, and various units can be composed as desired. 2. Cabinet-type workstation : all functions needed for the home office work is concentrated in a piece of furniture. 3. Movable multi-purpose furniture : small-sized, mobile furniture that functions as a simple workstation or a side station. Home office has a great possibility as a work place for the future, and there is a continuous need for the furniture design with diverse form and function.

• Journal of Digital Convergence
• /
• v.15 no.2
• /
• pp.527-535
• /
• 2017

As interest increases in health promotion through sports, demand for public sports facilities is steadily growing. However, there is a lack of research on operation and management compared with the supply plan of public sports facility. In this context, the aim of this study is to address problems of management of public sports centers and suggest strategies for vitalizing the facilities through the big-data. The data are collected from web such as news, blog, and cafe for one year in 2015. From the big-data, We can find that the national sports centers and the open gyms showed similar users' behavior but showed different needs. Both facilities have been used as sports and leisure area and have a high percentage of visitors for other purposes such as walking, picnics, etc. However, while the national sports facilities which were used for more specialized programs, the open sports center were used as leisure space.

• International journal of advanced smart convergence
• /
• v.7 no.1
• /
• pp.42-47
• /
• 2018

Recently, as the demand for limited resources continues to rise and problems of resource depletion rise worldwide, the importance of renewable energy is gradually increasing. In order to solve these problems, various methods such as energy conservation and alternative energy development have been suggested, and biogas, which can utilize the gas produced from biomass as fuel, is also receiving attention as the next generation of innovative renewable energy. New and renewable energy using biogas is an energy production method that is expected to be possible in large scale because it can supply energy with high efficiency in compliance with energy supply method of recycling conventional resources. In order to more efficiently produce and manage these biogas, a biogas plant has emerged. In recent years, a large number of biogas plants have been installed and operated in various locations. Organic wastes corresponding to biogas production resources in a biogas plant exist in a wide variety of types, and each of the incoming raw materials is processed in different processes. Because such a process is required, the case where the biogas plant process is inefficiently operated is continuously occurring, and the economic cost consumed for the operation of the biogas production relative to the generated biogas production is further increased. In order to solve such problems, various attempts such as process analysis and feedback based on the feedstock have been continued but it is a passive method and very limited to operate a medium/large scale biogas plant. In this paper, we propose "CNN-based production yield prediction algorithm for increasing process efficiency of biogas plant" for efficient operation of biogas plant process. Based on CNN-based production yield forecasting, which is one of the deep-leaning technologies, it enables mechanical analysis of the process operation process and provides a solution for optimal process operation due to process-related accumulated data analyzed by the automated process.

• Journal of Information Technology Services
• /
• v.20 no.5
• /
• pp.89-104
• /
• 2021

Food delivery service combined with IT technology and HMR (Home Meal Replacement) are rapidly growing due to the COVID-19. Recently, the demand for salads along with HMR has increased among office workers in their 20s and 30s who are interested in health and beauty. Freshcode is a food startup with 6 years of experience that started selling salad products through O2O service. Freshcode applied for a patent for a service that collects orders from nearby areas and delivers them on the same day to a designated delivery address 'FCOSPOT' to save shipping costs. In March 2021, in recognition of the growth potential of the regular delivery service, Freshcode received an investment of 6 billion won in Series A. This study may have practical implications to early-stage startups and scale-up stage startups through a longitudinal case study on the growth of a single company. As for the research method, the lean startup methodology and lean canvas were used in the early stage of startup. In particular, the process of the build-measure and learn feedback-loop, which is the core of lean startup methodology, was applied to each major decision-making step. In the scale-up stage after 5 years, the business model canvas was used to schematize the growth as a food online O2O platform to verify continuous innovation. This case study has three main findings. First, the idea of 'FCOSPOT' was successfully implemented through the Lean Startup methodology. Second, Freshcode demonstrated the scalability of the differentiated business model of shared base delivery O2O. Third, a key factor of success was the digital integrated communication operation strategy that maximizes the experience for the created customers.

• International Journal of Computer Science & Network Security
• /
• v.21 no.12
• /
• pp.137-142
• /
• 2021

Distance learning universities provide online course content. The main methods of providing class contents are on-demand and live-streaming. This means that students are not restricted by time or space. The advantage is that students can take the course anytime and anywhere. Therefore, unlike commuting students, there is no commuting time to the campus, and there is no natural process required to take classes. However, despite this convenient situation, the attendance rate and graduation rate of distance learning universities tend to be lower than that of commuting universities. Although the course environment is not the only factor, students cannot obtain a bachelor's degree unless they fulfill the graduation requirements. In both commuter and distance learning universities, taking classes is an important factor in earning credits. There are fewer time and space constraints for distance learning students than for commuting students. It is also easy for distance learning students to take classes at their own timing. There should be more ease of learning than for students who commute to school with restrictions. However, it is easier to take a course at a commuter university that conducts face-to-face classes. I thought that the reason for this was that commuting to school was a part of the process of taking classes for commuting students. Commuting to school was thought to increase the willingness and motivation to take classes. Therefore, I thought that the inconvenient constraints might encourage students to take the course. In this research, I focused on the act of commuting to school by students. These situations are also applied to the distance learning environment. The students have physical time constraints. To achieve this goal, I will implement a course restriction method that aims to promote the willingness and attitude of students. Therefore, in this paper, I have implemented a virtual school system called "virtual go to school (VG2S)" that reflects the actual route to school.