• Journal of the Korean Society for Railway
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• v.19 no.6
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• pp.833-843
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• 2016

Recently, in the field of rail freight transportation, the number of trains dedicated for shippers has been increasing. These dedicated trains, which run on the basis of a contract with shippers, had been restricted to the transportation of containers, or so called block trains. Nowadays, such commodities have extended to cement, hard coal, etc. Most full freight cars are transported by dedicated trains. But, for empty car distribution, the efficiency still remains questionable because the distribution plan is manually developed by dispatchers. In this study, we investigated distribution models delineated in the KTOCS system which was developed by KORAIL as well as mathematical models considered in the state-of-the-art. The models are based on optimization models, especially the network flow model. Here we suggest a new optimization model with a framework of the column generation approach. The master problem can be formulated into a transportation problem with additional constraints. The master problem is improved by adding a new edge between the supply node and the demand node; this edge can be found using a simple shorted path in the time-space network. Finally, we applied our algorithm to the Korean freight train network and were able to find the total number of empty car kilometers decreased.

• Journal of Korean Society of Transportation
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• v.23 no.6 s.84
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• pp.115-125
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• 2005

The line planning problem is to determine the origin and destination stations of the lines with their frequencies so as to meet the OD demands. Since the advent of high speed trains, Korea railway is confronted with the urgent difficulty to reconstruct the line configuration with the frequencies of each line and each fleet type so the demands could be newly created as well as satisfied. Furthermore. the existing trains except the high speed trains suffer from a longer traveling time than before. Now, to reduce the passenger traveling time, the trains with the various halting patterns are run in the same line. Therefore, it is necessary to develop a new line planning model to consider the various halting patterns. Most of studies find the frequencies of each lines which meet the link traffic loads or minimum link frequencies. But these are based on the assumption of all stop patterns. Furthermore, it is not easy to include the actual constraints as like the minimum number of stops at a station, the maximum number of stops or a train, etc. We develop the line planning model considering not only the various halting patterns but also the actual constraints which is based on the multicommodity network flow model with the additional constraints.

• Journal of Cadastre & Land InformatiX
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• v.46 no.2
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• pp.297-312
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• 2016

The current government strives to train those supposed to drive the national economy, and bridge the gap between qualification and industrial sites through competency-based qualification systems, not the educational background. In this regards, the government is planning to adopt the course evaluation qualification system. The course evaluation qualification system, on a basis of the NCS, is a system to qualify certain people completing the education and training fulling a specific requirement for a national technical qualification in case they meet the internally and externally assessed criteria. This can be seen as an attempt to practically link between job training and qualifications. The NCS model and learning module in the cadastral field are already utilized as the training and eduction in the specialized school and colleges. However, the current national technical qualification system is considered as a main system because the course evaluation qualification system has not been introduced yet. This study analyzed the process of the course evaluation qualification system, and conducted a survey to solicit feedback on introduction of course evaluation qualification system, Besides, the NCS evaluation model is presented in order for the introduction of course evaluation qualification system in the cadastral fields.

• KIPS Transactions on Computer and Communication Systems
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• v.5 no.10
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• pp.293-302
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• 2016

Since the electricity is produced and consumed simultaneously, predicting the electric load and securing affordable electric power are necessary for reliable electric power supply. In particular, a university campus is one of the highest power consuming institutions and tends to have a wide variation of electric load depending on time and environment. For these reasons, an accurate electric load forecasting method that can predict power consumption in real-time is required for efficient power supply and management. Even though various influencing factors of power consumption have been discovered for the educational institutions by analyzing power consumption patterns and usage cases, further studies are required for the quantitative prediction of electric load. In this paper, we build an electric load forecasting model by implementing and evaluating various machine learning algorithms. To do that, we consider three building clusters in a campus and collect their power consumption every 15 minutes for more than one year. In the preprocessing, features are represented by considering periodic characteristic of the data and principal component analysis is performed for the features. In order to train the electric load forecasting model, we employ both artificial neural network and support vector machine. We evaluate the prediction performance of each forecasting model by 5-fold cross-validation and compare the prediction result to real electric load.

• Journal of Korean Society of Steel Construction
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• v.29 no.6
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• pp.487-495
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• 2017

Recently rapid-transit railway systems have been constructed in many developing countries due to its advantages in congestions and environmental problems. Railway bridges show many different aspects compared to road bridges and passenger comfort and traffic safety are one of them. In particular, deflection and acceleration due to repeated vibration characteristics have a structural weakness that can cause undesirable response. Especially steel railway bridges have been known to have weaknesses due to its relatively light weights compared to concrete bridges. The purpose of this study is to analyze the dynamic response of steel box girder bridges due to passing trains then propose the appropriate method to mitigate the level of vibration in terms of accelerations. Three steel railway bridges are tested and the numerical model to analyze the dynamic response of the bridge by passing train are developed. For the verification of the model, the natural frequency extracted using the acceleration data measured in the bridge is compared with the natural frequency of the numerical model. To mitigate the acceleration level of the bridge, parametric studies are performed to find the effectiveness of the method. Based on the analysis, the appropriate method is proposed for decreasing the acceleration of the bridge for passenger comfort and traffic safety.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.5
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• pp.335-342
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• 2015

In this study, data linking module called GeoSWMM was developed using a typical secondary flooding model SWMM in order to improve the accuracy of the input data of SWMM and to map hourly inundation estimation areas that were not represented in the conventional inundation map. GeoSWMM is a data linking module of GIS and SWMM, which can generate a SWMM project file directly from sewer network GIS data. Utilizing the GeoSWMM the project file of SWMM model was constructed in the study area, Seocho 2-dong, Seoul. The actual flooding has occurred September 21, 2010 and the actual rainfall data were used for flood simulation. As a result, the outflow started from 2 PM due to the lack of water flow capacity of the sewage system. Based on the results, hourly inundation estimation maps were produced and compared with flood train map in 2010. The comparison showed about 66% matching in the overlap of inundation areas. By utilizing GeoSWMM that was developed in this study, it is easy to build the sewer network data for SWMM. In addition, the creation of hourly inundation estimation map using SWMM will be much help to flood disaster prevention plan.

• Journal of the Korean Society of Marine Environment & Safety
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• v.23 no.5
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• pp.473-481
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• 2017

Seafarer sea survival training, such as basic safety refresher training and advanced safety refresher training, in accordance with the STCW Convention, is an indispensable program that can increase the crew survival rate during emergency situations at sea. It is important for crew members to carry out theoretical and practical training with various safety equipment in order to effectively train according to IMO model courses. Therefore, this study suggests the following measures to improve safety training facilities for seafarers by reviewing survival training requirements based on the IMO model course and comparing and analyzing related facilities based on operating cases from domestic and overseas training institutes. First, it is necessary to establish a training environment where seafarers can practice utilizing various, updated safety equipment such as marine evacuation equipment (slides, chutes, etc.). Second, it is necessary to construct an educational environment in which learners can directly or indirectly experience realistic emergency situations by installing marine environment simulation facilities with such equipment as a wave generator, rain fall device, wind generating device, etc. Third, it is also necessary to develop and expand customized training using virtual reality equipment in addition to experiential training, audiovisual training and simulation training.

• Structural Monitoring and Maintenance
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• v.2 no.1
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• pp.77-93
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• 2015

The idea of using measured dynamic characteristics for damage detection is attractive because it allows for a global evaluation of the structural health and condition. However, vibration-based damage detection for complex structures such as long-span cable-supported bridges still remains a challenge. As a suspension or cable-stayed bridge involves in general thousands of structural components, the conventional damage detection methods based on model updating and/or parameter identification might result in ill-conditioning and non-uniqueness in the solution of inverse problems. Alternatively, methods that utilize, to the utmost extent, information from forward problems and avoid direct solution to inverse problems would be more suitable for vibration-based damage detection of long-span cable-supported bridges. The auto-associative neural network (ANN) technique and the probabilistic neural network (PNN) technique, that both eschew inverse problems, have been proposed for identifying and locating damage in suspension and cable-stayed bridges. Without the help of a structural model, ANNs with appropriate configuration can be trained using only the measured modal frequencies from healthy structure under varying environmental conditions, and a new set of modal frequency data acquired from an unknown state of the structure is then fed into the trained ANNs for damage presence identification. With the help of a structural model, PNNs can be configured using the relative changes of modal frequencies before and after damage by assuming damage at different locations, and then the measured modal frequencies from the structure can be presented to locate the damage. However, such formulated ANNs and PNNs may still be incompetent to identify damage occurring at the deck members of a cable-supported bridge because of very low modal sensitivity to the damage. The present study endeavors to enhance the damage identification capability of ANNs and PNNs when being applied for identification of damage incurred at deck members. Effort is first made to construct combined modal parameters which are synthesized from measured modal frequencies and modal shape components to train ANNs for damage alarming. With the purpose of improving identification accuracy, effort is then made to configure PNNs for damage localization by adapting the smoothing parameter in the Bayesian classifier to different values for different pattern classes. The performance of the ANNs with their input being modal frequencies and the combined modal parameters respectively and the PNNs with constant and adaptive smoothing parameters respectively is evaluated through simulation studies of identifying damage inflicted on different deck members of the double-deck suspension Tsing Ma Bridge.

• Korean Journal of Social Welfare
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• v.57 no.1
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• pp.121-146
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• 2005

The purpose of this paper is to analyze the structure and characteristics of the utilization support systems(USS), which has been institutionalized to aid the use of social welfare services in Japan's social welfare systems recently. In order to conduct such purposes, this paper made the process as follows. Firstly, this paper examined the developmental processes of social welfare systems, and the back ground of institutionalization of USS in Japan. Secondly, this paper formulated at ideal dimension the analytic model which was to explain the structure and characteristics of the USS. To build this model, this paper used two factors which were the connective dependency to the welfare support systems and the feasible-satisfying alternative setting for user. Thirdly, this paper analyzed the characteristics of the user-driven support facilities which has already activated in social welfare systems in Japan. According to the result of analyzing such model, this paper explained that USS in Japan has possessed the structure and characteristics, such as to aid self actualization and human right of user, to compose the inner coalition organization with supply systems, to emphasize the employee to train care management's skill, and to keep up bounded openness to USS's participation. Therefore, oligopoly market is formulated owing to bounded openness in the field of USS and the role of social worker such as a care manager is emphasized on making care plan.

• Korean Journal of Acupuncture
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• v.21 no.1
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• pp.113-127
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• 2004

Objectives : The usage of acupuncture has gained popularity as an alternative method of treatment for certain chronic pain conditions. However, the efficacy of acupuncture in various diseases has not been fully established and the underlying mechanism is not clearly understood. In the present study, the effect of electroacupuncture (EA) applied to foot samli$(ST_{36})$ on the carrageenan-induced knee arthritic pain was examined. Methods : A common source of persistent pain in humans is the knee arthritis. Knee arthritis was induced by injection of 2 % carrageenan $50\;{\mu}l$ into the knee joint cavity. When rats developed pain behaviors, EA was applied for 30 min. under enflurane anesthesia with repeated train stimuli at the intensity of 10X of muscle twitch threshold. The weight bearing force of the hind limb was measured for an indicator of pain level after each manipulation. Results : The average weight borne by the hind limb during normal gait was 55% of total body weight, which was reduced to less than 10% after knee arthritis. EA improved the weight bearing of the arthritic hind limb significantly for the duration of 4 hr. EA applied to $ST_{36}$ point produced a significant improvement of stepping force of the arthritic foot lasting for at least 4 h. However, $GB_{31}$ point did not produce any significant increase of weight bearing force. The analgesic effect was specific to the acupuncture point since the analgesic effect on the knee arthritis model could not be mimicked by EA applied to a nearby point, $GB_{31}$. The relations between EA-induced analgesia and endogenous nitric oxide(NO) and inducible NO synthase(iNOS)/neuronal NOS was also examined. Results were turned out that both NO production and nNOS/iNOS protein expression which is increased by arthritis were suppressed by EA stimulation applied to $ST_{36}$ point. Conclusions : The data suggest 1) that EA produces a potent analgesic effect on the rat model of chronic knee arthritis pain in a point specific manner and 2) that EA-induced analgesia modulate endogenous NO through the suppression of nNOS/iNOS protein expression.