• Journal of Construction Engineering and Project Management
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• v.4 no.2
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• pp.31-40
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• 2014

The management of vehicular supply of "perishable" construction material, such as concrete mixes, faces a series of uncertainties such as weather, daily traffic patterns and accidents. Presented in this paper is a logistics control model for managing a hauling fleet with interrelated processes at both ends and queue capacities. Discrete event simulation is used to model the complex interactions of production units and the randomness of the real world. Two alternative strategies for ready mix concrete delivery, with and without an off-site waiting queue, are studied to compare supply performance. Secondly, the paper discusses the effect of an agent-based GPS tracking system providing real-time travel data that lessens the uncertainty of trucking time. The results show that the combination of GPS information with off-site queuing reduces productivity loss and process wastes of concrete placement as well as the idleness of supply trucks when crew or pump experience an unexpected stoppage.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.16 no.4
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• pp.225-237
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• 2016

In conventional transportation problem (TP), all the parameters are always certain. But, many of the real life situations in industry or organization, the parameters (supply, demand and cost) of the TP are not precise which are imprecise in nature in different factors like the market condition, variations in rates of diesel, traffic jams, weather in hilly areas, capacity of men and machine, long power cut, labourer's over time work, unexpected failures in machine, seasonal changes and many more. To counter these problems, depending on the nature of the parameters, the TP is classified into two categories namely type-2 and type-4 fuzzy transportation problems (FTPs) under uncertain environment and formulates the problem and utilizes the trapezoidal fuzzy number (TrFN) to solve the TP. The existing ranking procedure of Liou and Wang (1992) is used to transform the type-2 and type-4 FTPs into a crisp one so that the conventional method may be applied to solve the TP. Moreover, the solution procedure differs from TP to type-2 and type-4 FTPs in allocation step only. Therefore a simple and efficient method denoted by PSK (P. Senthil Kumar) method is proposed to obtain an optimal solution in terms of TrFNs. From this fuzzy solution, the decision maker (DM) can decide the level of acceptance for the transportation cost or profit. Thus, the major applications of fuzzy set theory are widely used in areas such as inventory control, communication network, aggregate planning, employment scheduling, and personnel assignment and so on.

• The Journal of Fisheries Business Administration
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• v.42 no.1
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• pp.57-70
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• 2011

Fisheries are subject to unexpected weather condition. While some change of it may be positive for some fisheries, the current state suggests that the effects will be undesirable for many fisheries. The aim of this study is to assess the vulnerability to climate change in 11 regional fisheries of Korea using the framework of IPCC. The vulnerability assessment depends upon the interrelation of three key elements; exposure, sensitivity and adaptive capacity, which were derived from Analytical Hierarchy Process method in this study. These elements would contribute to comprehend relative importance at the regional characteristics of fisheries. We compared the vulnerability index of 11 regional fisheries so as to look for strategies and adaptation methods to the impacts of potential climate change. Jeoun-Nam, Kyeong-Nam, and Jeju are identified as the most vulnerable provinces to climate change on their fisheries because they have high level of sensitivity to predicted climate change and relatively low adaptive capacity. The relatively low vulnerability of Ulsan, Gyeonggi reflects high financial independence, well-equipped infrastructure, social capital in these regions. Understanding of vulnerability to climate change suggests future research directions. This paper will provide a guide to local policy makers and fisheries managers about vulnerability and adaptation planning to climate change.

• The Journal of Bigdata
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• v.4 no.2
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• pp.85-91
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• 2019

Since online shopping has become common, people can easily buy fashion goods anytime, anywhere. Therefore, consumers quickly respond to various environmental variables such as weather and sales prices. Thus, utilizing big data for efficient inventory management has become very important in the fashion industry. In this paper, the changes in sales volume of fashion goods due to changes in temperature is analyzed via the proposed big data analysis algorithm by utilizing actual big data from Korean fashion company 'B'. According to the analytic results, the proposed big data analysis algorithm found both expected and unexpected changes in sales volume depending on the characteristics of the fashion goods.

• Proceedings of the IEEK Conference
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• 2001.06a
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• pp.53-56
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• 2001

This paper has been developed a millimeter-wave radar to prevent car collision. This system needs to progress the problem as follows; (1) Increase of traffic accidents causing damage and injuries due to the increased number of motor vehicles and long distance driving, (2) Need for a device to help drivers who are in trouble due to bad weather conditions. (3) Need for a millimeter-wave radar as obstacles which need to be detected are small. This system is composited with some major technologies, Narrow beams to recognize obstacles or other objects, One-side circuit technology to prevent interference between electric waves, and Parts designed for radar products which are able to transmit millimeter - waves. The system has a various a application Field, Car distance auto-control system, prevent bump collision due to unexpected stoppage of the front car or careless driving, obstacle warning system, Car following system, and industrial and military purposes system. We have a looking forward to propose to develop field tests under various road conditions and hybrid car sensor by combining with other sensors

• Korean Journal of Environmental Agriculture
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• v.33 no.1
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• pp.52-56
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• 2014

BACKGROUND: It is known that impacts of climate change on damage occurrence by insect pests and diseases are increasing. The negative effects of climate change on production will threaten our food security. It is needed that on the basis of analysis of the impacts, proper strategies in response to climate change are developed. METHODS AND RESULTS: The objective of this paper is to estimate impacts of climate change on rice damage occurrence by insect pests and diseases, using the panal model which analyzes both cross-section data and time series data. The result of an analysis on impacts of climate change on rice damage occurrence by pest insect and disease showed that the damage occurrence by Rice leaf roller and Rice water weevil increased if temperature increased, and damage occurrence by Stripe, Sheath blight, and Leaf Blast increased if precipitation(or amount of sunshine) increased(or decreased). CONCLUSION: Adaptation strategies, supplying weather forecasting information by region, developing systematical strategies for prevention of damage occurrence by pest insect and disease, analyzing the factors of damage occurrence by unexpected pest insect and disease, enforcing international cooperation for prevention of damage occurrence are needed to minimize the impacts of damage occurrence on rice production.

• Journal of Korean Society of Forest Science
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• v.95 no.6
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• pp.778-783
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• 2006

Price prediction is essential to decisions of investment and shipment in oak mushroom cultivation. But predicting the prices of oak mushroom is very difficult because there are so many uncertain factors affecting the demand and the supply in the market. The Box-Jenkins methodology is one of strong tools in price prediction especially for the short-term using historical observations of time series. In this paper, the Box-Jenkins methodology is applied to find a model to forecast future oak mushroom prices. And out-of-sample test was conducted to check out the prediction accuracy. The result shows the high accuracy except for market disturbance period affected by unexpected weather change and reveals the usefulness of the model.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.51 no.7
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• pp.349-361
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• 2002

Occasionally, equipment in a distribution system fails due to damage from weather, vandalism, or other causes. Failures and unexpected events do not always occur as and where expected. Therefore, a good contingency plan, multi-zone or otherwise, provides flexibility by locating switches at various strategic locations so that parts of a feeder can be picked up in the event of line outages at various places. It is possible to create feeder system layout that achieve remarkable contingency support economics, even as their normal peak loading levels approach thermal capacity, by utilizing six, seven, or even nine switchable zones per feeder. But many switchable zones per feeder are of questionable practicality and effectiveness, because of the complexity and time required for the switching operation. In practice, a zonal scheme with between three and four zones will usually provide complete contingency backup for all feeders. Line switches have both capital and maintenance costs, the planning for multi-zonal schemes is considerably more difficult than or loop or single-zone systems, and the required switching operations required during contingencies take more time. But multi-zonal schemes are used because these costs come to far less than the cost of additional capacity required for loop or single-zone. In this paper, we present the optimal number of switchable zones per feeder in Kora distribution system.

• Journal of Environmental Science International
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• v.23 no.4
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• pp.585-594
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• 2014

This study Analyzed four of seven runoffs which had happened in 2012 in comparison with the runoffs shown in Kalesto data, using the fixed surface image velocimetry (FSIV) installed at Oedo stream, Jeju Island. As a result of identifying a runoff curve graph, it was analyzed that the flood runoffs calculated with two observation devices were almost equivalent. As the differences in peak flows were 10 $m^3/s$, 0.7 $m^3/s$ and 3 $m^3/s$, the very similar result values were calculated. Even though there were errors in RMSE(Root Mean Square Error) made by two observation devices according to the degree of the peak flow, the values of $R^2$ by flood event were 0.89, 0.87, 0.86 and 0.82, showing the result values almost close to 1. Therefore, there was a very high correlation in flood runoffs calculated with two observation devices. This research method was considered to be a very suitable method to measure unexpected flood runoffs which could happen in the island area such as Jeju island during bad weather.

• The Journal of Korea Robotics Society
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• v.14 no.2
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• pp.122-130
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• 2019

Collecting a rich but meaningful training data plays a key role in machine learning and deep learning researches for a self-driving vehicle. This paper introduces a detailed overview of existing open-source simulators which could be used for training self-driving vehicles. After reviewing the simulators, we propose a new effective approach to make a synthetic autonomous vehicle simulation platform suitable for learning and training artificial intelligence algorithms. Specially, we develop a synthetic simulator with various realistic situations and weather conditions which make the autonomous shuttle to learn more realistic situations and handle some unexpected events. The virtual environment is the mimics of the activity of a genuine shuttle vehicle on a physical world. Instead of doing the whole experiment of training in the real physical world, scenarios in 3D virtual worlds are made to calculate the parameters and training the model. From the simulator, the user can obtain data for the various situation and utilize it for the training purpose. Flexible options are available to choose sensors, monitor the output and implement any autonomous driving algorithm. Finally, we verify the effectiveness of the developed simulator by implementing an end-to-end CNN algorithm for training a self-driving shuttle.