• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.14 no.3
• /
• pp.231-238
• /
• 2021

In addition to individual calls and group calls, the Trunked Radio System (TRS), which belongs to a group, can make calls simultaneously, and many users can use it within a limited time by adjusting the call time. Also, the LCX infrastructure network of the subway Most of the FM, firefighting radio, TRS of the National Police Agency and the terrestrial DMB service built in 2005 are commonly connected to the network for service and operation. In connection with the analysis, call reception sensitivity, handoff, interference with other signals, time delay, etc. were analyzed, and tests such as reception field strength for each output of the repeater and the success rate of the call terminal were conducted and the test results were analyzed. In addition, it will help TRS cell design and network construction by predicting equipment output capacity and service coverage based on test results.

• Journal of the Society of Disaster Information
• /
• v.18 no.3
• /
• pp.589-599
• /
• 2022

Purpose: The purpose of this study is to quantitatively identify the environmental contribution generated by urban rail users in the metropolitan area. Method: As for the analysis method, the mode choice and assignment of the traffic demand analysis were repeatedly performed on the assumption that each line was not opened for the metropolitan urban railway lines 1 to 9. After that, the environmental contribution according to changes in demand for the road was analyzed. Result: The total amount of carbon dioxide emissions and benefits were found to be the largest for subway line 1. However, when considering the number of stations and length, it was analyzed that the environmental contribution was the greatest in Metro Line 4. Conclusion: Measures to promote the use of public transportation are representative of environmental improvement policies, but there is a limit in that it is difficult for actual users/non-users to feel it. Therefore, it is judged that it is necessary to quantitatively present the effect in order to improve and spread awareness of the environment.

• Journal of the Korea Society of Computer and Information
• /
• v.28 no.7
• /
• pp.1-9
• /
• 2023

Currently, as the demand for stops in the urban increases resulting from an increase in the supply of express trains, the development of trains capable of operating both high-floor platforms in the urban and low-floor platforms in the suburbs is required. In this paper, we studied the design and fabrication of a controller for train doors that consists of low and high steps as a plug-in type door mechanism and thus can be used on low and high platforms. This DCU H/W was designed and implemented using 32 bit MCU to control 4 motors, 33 digital inputs and 16 digital outputs. In addition, based on the software life cycle of EN50128, 2 items of operation requirements and 12 items of control requirements were derived, and then they were designed and implemented as operation SW. The implemented SW was tested for each requirement. As a result, we performed tests on 13 items that could be tested in the mock-up out of 14 total requirement items and showed that the requirements were satisfied.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.18 no.4
• /
• pp.938-958
• /
• 2024

Unsupervised Video Object Segmentation (UVOS) is a highly challenging problem in computer vision as the annotation of the target object in the testing video is unknown at all. The main difficulty is to effectively handle the complicated and changeable motion state of the target object and the confusion of similar background objects in video sequence. In this paper, we propose a novel deep Dual-stream Co-enhanced Network (DC-Net) for UVOS via bidirectional motion cues refinement and multi-level feature aggregation, which can fully take advantage of motion cues and effectively integrate different level features to produce high-quality segmentation mask. DC-Net is a dual-stream architecture where the two streams are co-enhanced by each other. One is a motion stream with a Motion-cues Refine Module (MRM), which learns from bidirectional optical flow images and produces fine-grained and complete distinctive motion saliency map, and the other is an appearance stream with a Multi-level Feature Aggregation Module (MFAM) and a Context Attention Module (CAM) which are designed to integrate the different level features effectively. Specifically, the motion saliency map obtained by the motion stream is fused with each stage of the decoder in the appearance stream to improve the segmentation, and in turn the segmentation loss in the appearance stream feeds back into the motion stream to enhance the motion refinement. Experimental results on three datasets (Davis2016, VideoSD, SegTrack-v2) demonstrate that DC-Net has achieved comparable results with some state-of-the-art methods.

• Journal of Internet Computing and Services
• /
• v.21 no.6
• /
• pp.23-31
• /
• 2020

This study was carried out to generate various images of railroad surfaces with random defects as training data to be better at the detection of defects. Defects on the surface of railroads are caused by various factors such as friction between track binding devices and adjacent tracks and can cause accidents such as broken rails, so railroad maintenance for defects is necessary. Therefore, various researches on defect detection and inspection using image processing or machine learning on railway surface images have been conducted to automate railroad inspection and to reduce railroad maintenance costs. In general, the performance of the image processing analysis method and machine learning technology is affected by the quantity and quality of data. For this reason, some researches require specific devices or vehicles to acquire images of the track surface at regular intervals to obtain a database of various railway surface images. On the contrary, in this study, in order to reduce and improve the operating cost of image acquisition, we constructed the 'Defective Railroad Surface Regeneration Model' by applying the methods presented in the related studies of the Generative Adversarial Network (GAN). Thus, we aimed to detect defects on railroad surface even without a dedicated database. This constructed model is designed to learn to generate the railroad surface combining the different railroad surface textures and the original surface, considering the ground truth of the railroad defects. The generated images of the railroad surface were used as training data in defect detection network, which is based on Fully Convolutional Network (FCN). To validate its performance, we clustered and divided the railroad data into three subsets, one subset as original railroad texture images and the remaining two subsets as another railroad surface texture images. In the first experiment, we used only original texture images for training sets in the defect detection model. And in the second experiment, we trained the generated images that were generated by combining the original images with a few railroad textures of the other images. Each defect detection model was evaluated in terms of 'intersection of union(IoU)' and F1-score measures with ground truths. As a result, the scores increased by about 10~15% when the generated images were used, compared to the case that only the original images were used. This proves that it is possible to detect defects by using the existing data and a few different texture images, even for the railroad surface images in which dedicated training database is not constructed.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.14 no.3
• /
• pp.50-62
• /
• 2015

Recently, Subway Line No. 9, described as a 'hell-like' subway for its recorded load factor of max. 240% due to the opening of the 2nd phase extension section, has been causing problems of recurrent congestion in a subway station building. A recurrent congestion in the station building becomes a factor to offend rail users and to reduce the efficiency of railway management. This study aims to establish the methodology for effect evaluation of information provided to rail users, and conducts a gate metering case study considering the congested conditions at a platform among the methodologies for effect evaluation. The metering effect evaluation by load factor was conducted through selecting the micro simulation and pedestrian simulation tool grafting a gate metering. As a result, it was confirmed that, if gate metering is performed, the service level and pedestrian density of a platform by load factor would improve. In other words, if metering is conducted at a platform, it is possible to control the load factor in the waiting space of a platform. Therefore, it was judged through this study that it is possible to set up the index for effect evaluation of information provided to manage congestion of rail users, and establish the methodology for effect evaluation of information provided to rail users through a program.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.38 no.4
• /
• pp.601-610
• /
• 2018

Since the building construction works are repeated vertically in a limited space, there is not a great need for the location information of each activity in the schedule management. On the other hand, civil engineering works such as road and railway projects consist of a large number of earthworks, long bridges, and long tunnels. These types of work should be controlled in a horizontal space according to the linear axis of several tens of kilometers. In other words, since most of the activities are managed in the unit of distance from the start point to the end point, it is possible to improve the efficiency of the schedule management by linking the location information of the activity with the schedule data in the schedule management system. This study presents a methodology for creating a linear schedule chart specific to a project with horizontal work space and compares the convenience with the existing Gantt chart. In addition, the methodology of linking linear schedule chart to the 4D CAD system, which is a typical BIM technology in the construction phase, is presented to improve the usability of BIM. The practical applicability of the proposed methodology was verified statistically.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.40 no.3
• /
• pp.588-594
• /
• 2015

Although GPS technology for location positioning system has been widely used, it is difficult to be used in intelligent transport systems, due to the large positioning error and limited area for receiving radio signals. Thanks to the rapid development of LED technology, LED lights become popular in many applications. Especially, visible light communications (VLC) has raised a lot of interests because of the simultaneous functioning of LED illumination and communication. Recent studies on positioning system using VLC mainly focused on indoor environments and still difficult to satisfy positioning accuracy and simple implementation simultaneously. In this paper, we propose a positioning system based on VLC using the coordinate information of LEDs installed on the road infrastructure. Extracting the LED signal, obtained through VLC, from the easily accessible camera image, it is possible to estimate the position of the car on the road. Simulation results show that the proposed scheme can achieve a high positioning accuracy of 1 m when large number of pixels is utilized and the distance from the LED light is close.

• KIPS Transactions on Software and Data Engineering
• /
• v.8 no.5
• /
• pp.193-204
• /
• 2019

The explosion of data due to the improvement of sensor technology and computing performance has become the basis for analyzing the situation in the industrial fields, and various attempts to detect events based on such data are increasing recently. In particular, sound signals collected from sensors are used as important information to classify events in various application fields as an advantage of efficiently collecting field information at a relatively low cost. However, the performance of sound-event classification in the field cannot be guaranteed if noise can not be removed. That is, in order to implement a system that can be practically applied, robust performance should be guaranteed even in various noise conditions. In this study, we propose a system that can classify the sound event after generating the enhanced sound signal based on the deep learning algorithm. Especially, to remove noise from the sound signal itself, the enhanced sound data against the noise is generated using SEGAN applied to the GAN with a VAE technique. Then, an end-to-end based sound-event classification system is designed to classify the sound events using the enhanced sound signal as input data of CNN structure without a data conversion process. The performance of the proposed method was verified experimentally using sound data obtained from the industrial field, and the f1 score of 99.29% (railway industry) and 97.80% (livestock industry) was confirmed.

• Proceedings of the KSR Conference
• /
• 2011.05a
• /
• pp.1799-1810
• /
• 2011

Origin-Destination(OD) trip survey being used in travel demand forecasting has been obtained through totalizing process with direct sample survey techniques such as plate license survey, roadside interview, household travel survey, and cordon line counts. However, the OD survey has many discrepancies in sampling, totalizing process, and such discrepancies contains problems of difference between forecasted traffic volume and observed data. On the other hand, transit smart card data recently collected has credible resource of obtaining travel information for bus and metro. This paper presents parameter estimation of gravity model by using transit smart card data. Through the parameter estimation method, we estimated =0.57, ${\beta}$=0.14 of gravity model for bus, and ${\alpha}$=-0.21, ${\beta}$=0.05 for metro. The statistical test such as T-test, coefficient of correlation, Theil`s inequality coefficient showed no difference between observed volume and estimated volume. Elasticities of bus and metro derived in this paper are also reasonable.