• KIPS Transactions on Software and Data Engineering
• /
• v.2 no.12
• /
• pp.889-898
• /
• 2013

Due to the popularization of high-performance capturing equipments and the emergence of powerful image-editing softwares, it is easy to make high-quality counterfeit money. However, the probability of detecting counterfeit money to the general public is extremely low and the detection device is expensive. In this paper, a counterfeit money detection algorithm using a general purpose scanner and computer system is proposed. First, the printing features of color printers are calculated using morphological operations and gray-level co-occurrence matrix. Then, these features are used to train a support vector machine classifier. This trained classifier is applied for identifying either original or counterfeit money. In the experiment, we measured the detection rate between the original and counterfeit money. Also, the printing source was identified. The proposed algorithm was compared with the algorithm using wiener filter to identify color printing source. The accuracy for identifying counterfeit money was 91.92%. The accuracy for identifying the printing source was over 94.5%. The results support that the proposed algorithm performs better than previous researches.

• Journal of Families and Better Life
• /
• v.19 no.4
• /
• pp.49-68
• /
• 2001

The purpose of this study was 1) to review communal housing in the UK, 2) to consider the policy implications for elderly communal housing in Korea. The research methods used were 1) literature review about communal housing and related policy in the UK 2) field survey in the UK 3) interpretative suggestion for the proper policy implication to develope communal housing for the elderly in Korea. Sheltered housing in the UK had been developed as communal housing for the elderly with special needs since the 1970s. The type of sheltered housing were category 1 and category 2. Very sheltered housing with more facilities and meal services was added in 1980s. Sheltered housing was evaluated as the most humanistic solution for older people in the UK in 1980s. Because of the policy of moving institutional care to community care, sheltered housing became less in demand because of more options for older people including being able to stay in their own home. So new completion of sheltered housing by registered social landlords reduced saliently. Sheltered housing already totalled over half million units in which 5% of all elderly over 65 still lived and a small quantity of private sector for sale schemes emerged in the 1990s. The reason why the residents moved to sheltered housing was for sociable, secure, and manageable living arrangements. In general the residents were satisfied with these characteristics but dissatisfied with the service charge and quality of meals, especially in category 2.5 schemes. The degree of utilisation of communal spaces and facilities depended on the wardens ability and enthusiasm. Evaluation of sheltered housing indicated several problems such as wardens duty as a \"good neighbour\" ; difficult-to-let problems with poor location or individual units of bedsittiing type with shared bathroom ; and the under use of communal spaces and facilities. Some ideas to solve these problems were suggested by researchers through expanding wardens duty as a professional, opening the scheme to the public, improving interior standards, and accepting non-elderly applicants who need support. Some researchers insisted continuing development of sheltered housing, but higher standards must be considered for the minority who want to live in communal living arrangement. Recently, enhanced sheltered housing with greater involvement of relatives and with tied up policy in registration and funding suggested as an alternative for residential care. In conclusion, the rights of choice for older people should be policy support for special needs housing. Elderly communal housing, especially a model similar to sheltered housing category 2 with at least 1 meal a day might be recommended for a Korean Model. For special needs housing development either for rent or for sale, participation of the public sector and long term and low interest financial support for the private sector must be developed in Korea. Providing a system for scheme managers to train and retrain must be encouraged. The professional ability of the scheme manager to plan and to deliver services might be the most important factor for the success of elderly communal housing projects in Korea. In addition the expansion of a public health care service, the development of leisure programs in Senior Citizens Centre, home helper both for the elderly in communal housing and the elderly in mainstream housing of the community as well. Providing of elderly communal housing through the modified general Construction Act rather than the present Elderly Welfare Act might be more helpful to encourage the access of general people in Korea. in Korea.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.38 no.11
• /
• pp.1309-1315
• /
• 2014

The switch for a maglev vehicle should be designed such that the vehicle safely changes its track without touching the guiderail. In particular, a medium-to-low-speed EMS -type maglev train relies heavily on a U-type electromagnet where it generates levitation force and guidance force simultaneously. Therefore, it is necessary to evaluate the safety of the vehicle whenever it passes the switch, as it lacks active control of the guidance force. Furthermore, when the vehicle passes a segmented switch, which is a group of curves made up of connected lines with a small radius of curvature, it may come into mechanical contact with the guiderail owing to the excessive lateral displacement of the electromagnet. The goal of this study is to analyze the influence of a segmented switch on the safety of major design-related variables for achieving improved running safety. We propose a three-dimensional multibody dynamics model composed of two cars with one body. Using the proposed model, we perform a simulation of the lateral air gap, which is one of the measurements of the running safety of the vehicle when it passes the switch. The analyzed design variables are the length between short span girder, the articulation angle, the length between two centers of a fixed girder at its ends, and the number of girders. On the basis of the effects of the considered design variables, we establish an optimized design of a switch with improved safety.

• The Journal of the Korea Contents Association
• /
• v.20 no.7
• /
• pp.674-682
• /
• 2020

Recently, the problem of air pollution has become a global concern due to industrialization and overcrowding. Air pollution can cause various adverse effects on human health, among which respiratory diseases such as asthma, which have been of interest in this study, can be directly affected. Previous studies have used clinical data to identify how air pollutant affect diseases such as asthma based on relatively small samples. This is high likely to result in inconsistent results for each collection samples, and has significant limitations in that research is difficult for anyone other than the medical profession. In this study, the main focus was on predicting the actual asthmatic occurrence, based on data on the atmospheric environment data released by the government and the frequency of asthma outbreaks. First of all, this study verified the significant effects of each air pollutant with a time lag on the outbreak of asthma through the time-lag Pearson Correlation Coefficient. Second, train data built on the basis of verification results are utilized in Deep Learning algorithms, and models optimized for predicting the asthmatic occurrence are designed. The average error rate of the model was about 11.86%, indicating superior performance compared to other machine learning-based algorithms. The proposed model can be used for efficiency in the national insurance system and health budget management, and can also provide efficiency in the deployment and supply of medical personnel in hospitals. And it can also contribute to the promotion of national health through early warning of the risk of outbreak by atmospheric environment for chronic asthma patients.

• Journal of the Institute of Electronics Engineers of Korea SC
• /
• v.48 no.2
• /
• pp.47-55
• /
• 2011

Hemorrhagic shock is a cause of one third of death resulting from injury in the world. Early diagnosis of hemorrhagic shock makes it possible for physician to treat successfully. The objective of this paper was to select an optimal classifier model using physiological signals from rats measured during hemorrhagic experiment. This data set was used to train and predict survival rate using artificial neural network (ANN) and support vector machine (SVM). To avoid over-fitting, we chose the best classifier according to performance measured by a 10-fold cross validation method. As a result, we selected ANN having three hidden nodes with one hidden layer and SVM with Gaussian kernel function as trained prediction model, and the ANN showed 88.9 % of sensitivity, 96.7 % of specificity, 92.0 % of accuracy and the SVM provided 97.8 % of sensitivity, 95.0 % of specificity, 96.7 % of accuracy. Therefore, SVM was better than ANN for survival prediction.

• Journal of the Korean Society for Railway
• /
• v.20 no.2
• /
• pp.234-240
• /
• 2017

In this study, the influences of rail surface roughness on dynamic wheel-rail forces currently employed in conventional lines were assessed by performing field measurements according to grinding of rail surface roughness. The influence of the grinding effect was evaluated using a previous empirical prediction model for dynamic wheel-rail forces; model includes first-order derivatives of QI (Quality Index) and vehicle velocity. The theoretical dynamic wheel-rail force determined using the previous prediction equation was analyzed using the QI, which decreased due to rail grinding as determined through field measurements. At a constant track support stiffness, an increase in the QI caused an increase in dynamic wheel-rail forces. Further, it can be inferred that the results of dynamic wheel-rail analysis obtained using the measured data, such as the variation of QI due to rail grinding, can be used to predict the peak dynamic forces. Therefore, it is obvious that the optimum amount of rail grinding can be determined by considering the QI, that was regarding an operation characteristics of the target track (vehicle velocity and wheel load).

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.16 no.4
• /
• pp.153-163
• /
• 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 Korean Society of Transportation
• /
• v.22 no.6
• /
• pp.89-99
• /
• 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.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.41 no.1
• /
• pp.75-83
• /
• 2021

Over-urbanization has contributed to the increase in traffic problems. This makes the need for effective road planning and design more important than ever. I have been able to learn how to build a new road, and how to use it. However, in spite of the importance of good road planning, there are no systematic standards or methods for calculating traffic volume on railroad routes. Therefore, in this study, to strengthen the competitiveness of railroads, the concept of line capacity is introduced to railroads, and a clear standard and method for calculating railroad line capacity are presented. Based on the results, the line capacity of main railway lines for domestic railways was calculated. By applying the method of calculating the line capacity presented in this study, the capacity of existing railway lines and newly expanded routes can be calculated. It is expected that our findings will be able to provide systematic standards that can be applied to yield a more effective investment and design planning stage; the findings will also help improve the efficiency of railroad operation.

• Smart Structures and Systems
• /
• v.29 no.1
• /
• pp.1-16
• /
• 2022

Despite recent breakthroughs in deep learning and computer vision fields, the pixel-wise identification of tiny objects in high-resolution images with complex disturbances remains challenging. This study proposes a modified U-net for tiny crack segmentation in real-world steel-box-girder bridges. The modified U-net adopts the common U-net framework and a novel Self-Attention-Self-Adaption (SASA) neuron as the fundamental computing element. The Self-Attention module applies softmax and gate operations to obtain the attention vector. It enables the neuron to focus on the most significant receptive fields when processing large-scale feature maps. The Self-Adaption module consists of a multiplayer perceptron subnet and achieves deeper feature extraction inside a single neuron. For data augmentation, a grid-based crack random elastic deformation (CRED) algorithm is designed to enrich the diversities and irregular shapes of distributed cracks. Grid-based uniform control nodes are first set on both input images and binary labels, random offsets are then employed on these control nodes, and bilinear interpolation is performed for the rest pixels. The proposed SASA neuron and CRED algorithm are simultaneously deployed to train the modified U-net. 200 raw images with a high resolution of 4928 × 3264 are collected, 160 for training and the rest 40 for the test. 512 × 512 patches are generated from the original images by a sliding window with an overlap of 256 as inputs. Results show that the average IoU between the recognized and ground-truth cracks reaches 0.409, which is 29.8% higher than the regular U-net. A five-fold cross-validation study is performed to verify that the proposed method is robust to different training and test images. Ablation experiments further demonstrate the effectiveness of the proposed SASA neuron and CRED algorithm. Promotions of the average IoU individually utilizing the SASA and CRED module add up to the final promotion of the full model, indicating that the SASA and CRED modules contribute to the different stages of model and data in the training process.