• Journal of Korean Society for Geospatial Information Science
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• v.9 no.2 s.18
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• pp.29-36
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• 2001

The purpose of this paper is to describe the Disaster Management System Development of Enterprise GIS at the Kangwon Province in Korea. This project is included into 'the Kangwon Enterprise GIS 21 plan'. The Division of Disaster Management is in the middle of the 2-year project of the Disaster Management System development, appropriate for business performed at the Departments of Forestry, Culture, Environment, Tourism, etc. At the 1st phase of CIS implementation, for more than half a year we focused on the necessity of management of disasters. In the planning process, we needed long-term information on the whole area of Kangwon. In the assessment and response processes, we needed real-time data from Korean Meteorological Administration and other agencies. All the above information was carefully studied and referred to. ESRI's new GIS technologies solve the natural hazard/disaster problems. For example, hazardous materials routing often needs to be found the least expensive path through a roadway network. In the circumstances given, we can choose the departure point and destination of the vehicle, which carries the materials. It's also possible to minimize overall risk and costs of disaster problems by making a plan of people and possessions evacuation from the disaster area in short time limits. We can meet all the above goals using the latest ESRI's technologies.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.4
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• pp.153-163
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• 2017

This research is based on the previous research that personally preferred safe distance, rotating angle and speed are differentiated. Thus, we use machine learning model for recognizing maneuvering modes trained per personal or per similar driving pattern groups, and we evaluate automatic driving according to maneuvering modes. By utilizing driving knowledge, we subdivided 8 kinds of longitudinal modes and 4 kinds of lateral modes, and by combining the longitudinal and lateral modes, we build 21 kinds of maneuvering modes. we train the labeled data set per time stamp through RNN, LSTM and Bi-LSTM models by the trips of drivers, which are supervised deep learning models, and evaluate the maneuvering modes of automatic driving for the test data set. The evaluation dataset is aggregated of living trips of 3,000 populations by VTTI in USA for 3 years and we use 1500 trips of 22 people and training, validation and test dataset ratio is 80%, 10% and 10%, respectively. For recognizing longitudinal 8 kinds of maneuvering modes, RNN achieves better accuracy compared to LSTM, Bi-LSTM. However, Bi-LSTM improves the accuracy in recognizing 21 kinds of longitudinal and lateral maneuvering modes in comparison with RNN and LSTM as 1.54% and 0.47%, respectively.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.4 s.316
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• pp.42-47
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• 2007

To reduce the chattering errors of reed switch sensors in the automatic remote measurement of water meter a reed switch sensor was analyzed and improved. The operation of reed switch sensors can be described as a mechanical contact switch by approximation of permanent magnet piece to generate an electrical pulse. The reed switch sensors are used mostly in measurement application to detect the rotational or translational displacement. To apply for water flow measurement devices, the reed switch sensors should keep high reliability. They are applied for the electronic digital type of water flow meters. The reed switch sensor is just mounted simply on the conventional mechanical type flow meter. A small magnet is attached on a pointer of the water meter counter rotor. Inside the reed sensor two steel leaf springs make mechanical contact and apart repeatedly as rotation of flow meter counter. The counting electrical contact pulses can be converted as the water flow amount. The MCU sends the digital flow rate data to the server using the wireless communication network. But the digital data is occurred difference or won by chattering noise. The reed switch sensor contains chattering error by it self at the force equivalent position. The vibrations such as passing vehicle near to the switch sensor installed location causes chattering. In order to reduce chattering error, most system uses just software methods, for example using filter algorithm and also statistical calibration methods. The chattering errors were reduced by changing leaf spring structure using mechanical characteristics.

• Journal of the Korean Society for Railway
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• v.17 no.4
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• pp.251-259
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• 2014

The transition zone between an earthwork and a bridge effect to the vehicle's running stability because support stiffness of the roadbed is suddenly changed. The design criteria for the transition structure on ballast track were not particular in the past. However with the introduction of concrete track is introduced, it requires there is a higher performance level required because of maintenance and running stability. In this present paper, a transition structure reinforced with geosynthetics is suggested to improve the performance of existing bridge-earthwork transition structures. The suggested transition structure, in which there is reinforcing of the approach block using high-tension geosynthetics, has a structure similar to that of earth reinforced abutments. The utilized backfill materials are cement treated soil and gravel. These materials are used to reduce water intrusion into the approach block and to increase the recycling of surplus earth materials. An experiment was performed under the same conditions in order to allow a comparison of this new structure with the existing transition structure. Evaluation items are elastic displacement, cumulative settlement, and earth pressure. As for the results of the real-scale accelerated testing, the suggested transition structure has excellent performance for the reduction of earth pressure and settlement. Above all, it has high resistance the variation of the water content.

• Journal of Korean Society of Transportation
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• v.22 no.6
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• pp.89-99
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• 2004

The purpose of this study is to evaluate the value of information on Bus-Route concerning on the User's Individual value. The value of information is estimated with the price of time saving by using the information. The price of unit time for each user is applied to convert the saving time to the cost. To estimate the user's expense from origin to destination the previous model is modified. Bus-travel cost is estimated with variables such as bus-travel time, bus-interval, bus-fare, and the price of walking distance. In this study, to estimate in-vehicle time the bus-travel time model is developed based on the spatial characteristics distinguished by three types of circular-road in the network of Daegu Metropolitan area. For the case study, a set of the origin and destination is selected as Dalsu-gu District Office and East Daegu Train Station respectively. There are several bus-routes which can be used as direct or transferable bus-routes selected. The study showed that when the value of time for individual users is \1,738/hr, there is no benefit to using information of transferable bus-routes. It also showed that the more discount rates of bus fare is increased, the benefit to using information of transferable bus-routes is increased, and that the lower value of time is, the benefit to using information of transferable bus-routes is increased.

• Journal of Korean Society of Forest Science
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• v.89 no.5
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• pp.576-584
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• 2000

The term 'greenways' is a fairly new one. The term greenways refer to linear corridors which set aside pieces of nature. The objective of this study was to find out the feasibility of developing greenways in Taegu. Sample of 446 trail users were asked to describe their use patterns and as well as their perceptions of the benefits and problems associated with trails through on-site interviews conducted during the months of July and August of 1999. Trail users in Taegu were predominately male(61%) and over half of the respondents used private vehicle to access to the study areas as compared to 2% of respondents used bicycle. Trail users responded that health & fitness and open space preservation were the two most important benefits, and the provision of trail access to disabled persons was ranked last. As problems at study areas, lack of interpretive information was the biggest problem followed by lack of drinking water, poor trail marking/signs and not enough information. Most(94.1%) of the trail users surveyed indicated that they would support greenways development and 96.8% of respondent would use after greenways development. Willingness to pay for developing greenways was assessed with hypothetical scenario. Average willingness to pay in the survey was 10,200 won as a tax. The development/application of greenways in Taegu would work best when establish a network of trails with environmentally sensitive manner.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.2
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• pp.95-111
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• 2021

As the population decreases in an aging society, the average age of drivers increases. Accordingly, the elderly at high risk of being in an accident need autonomous-driving vehicles. In order to secure driving safety on the road, several technologies to respond to various obstacles are required in those vehicles. Among them, technology is required to recognize static obstacles, such as poor road conditions, as well as dynamic obstacles, such as vehicles, bicycles, and people, that may be encountered while driving. In this study, we propose a deep neural network algorithm capable of simultaneously detecting these two types of obstacle. For this algorithm, we used 1,418 road images and produced annotation data that marks seven categories of dynamic obstacles and labels images to indicate road damage. As a result of training, dynamic obstacles were detected with an average accuracy of 46.22%, and road surface damage was detected with a mean intersection over union of 74.71%. In addition, the average elapsed time required to process a single image is 89ms, and this algorithm is suitable for personal mobility vehicles that are slower than ordinary vehicles. In the future, it is expected that driving safety with personal mobility vehicles will be improved by utilizing technology that detects road obstacles.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.3
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• pp.95-105
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• 2019

In recent years, image processing techniques for detecting road surface damaged spot have been actively researched. Especially, it is mainly used to acquire images through a smart phone or a black box that can be mounted in a vehicle and recognize the road surface damaged region in the image using several algorithms. In addition, in conjunction with the GPS module, the exact damaged location can be obtained. The most important technology is image processing algorithm. Recently, algorithms based on artificial intelligence have been attracting attention as research topics. In this paper, we will also discuss artificial intelligence image processing algorithms. Among them, an object detection method based on an region-based convolution neural networks method is used. To improve the recognition performance of road surface damage objects, 600 road surface damaged images and 1500 general road driving images are added to the learning database. Also, supervised learning using background object recognition method is performed to reduce false alarm and missing rate in road surface damage detection. As a result, we introduce a new method that improves the recognition performance of the algorithm to 8.66% based on average value of mAP through the same test database.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.5
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• pp.1-18
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• 2019

A short-turn bus is a bus that is operated within a subsection of an existing bus line. Previous studies regarding short-turn buses decided optimal turn-back points for a single bus line rather than a bus network. Also, in-vehicle crowding which has a significant impact on transit convenience was rarely considered. Therefore, this study aimed to develop a methodology to set priorities for the introduction of short-turn buses of bus lines and sections, considering crowding. To achieve this objective, we calculated occupancies and crowding alleviation benefits of existing bus lines overlapping a new short-turn route based on transit card data, before and after the introduction of short-turn strategy. Also, operator and social costs caused by the introduction of short-turn buses were calculated. Those procedures were iterated over bus lines and sections to operate a short-turn service, and a section whose benefit-to-cost ratio (B/C) is the largest in a line was selected to operate a short-turn service in the line. After, priorities of bus lines to introduce short-turn services could be determined based on B/C values, and the optimum total fleet size could be determined when a short-turn strategy is applied in multiple lines.

• Journal of Digital Convergence
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• v.17 no.1
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• pp.239-247
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• 2019

An accurate prediction of emotion is a very important issue for the sake of patient-centered medical device development and emotion-related psychology fields. Although there have been many studies on emotion prediction, no studies have applied the heart rate variability and neuro-fuzzy approach to emotion prediction. We propose ANFEP(Adaptive Neuro Fuzzy System for Emotion Prediction) HRV. The ANFEP bases its core functions on an ANFIS(Adaptive Neuro-Fuzzy Inference System) which integrates neural networks with fuzzy systems as a vehicle for training predictive models. To prove the proposed model, 50 participants were invited to join the experiment and Heart rate variability was obtained and used to input the ANFEP model. The ANFEP model with STDRR and RMSSD as inputs and two membership functions per input variable showed the best results. The result out of applying the ANFEP to the HRV metrics proved to be significantly robust when compared with benchmarking methods like linear regression, support vector regression, neural network, and random forest. The results show that reliable prediction of emotion is possible with less input and it is necessary to develop a more accurate and reliable emotion recognition system.