• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.5 no.3
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• pp.226-233
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• 1993

Thermosyphons are simple devices that can passively transport thermal energy over relatively large distance with little temperature degradation. Especially, the thermosyphon system requires no costly energy input and is completely maintenance free. These attributes permit the use of low grade thermal energy for thermal control of structures including the stabilization of highway foundations. This paper presents the experimental results of the snow melting system in which thermosyphon was utilized to ransfer the earth energy to the pavement to remove snow and ice. The test facility, three earth heated and one unheated test panels, is designed to investigate the variables associated with removing snow and ice from pavement surfaces. The results of these test show that the earth heated panel surface temperature is higher $2{\sim}6^{\circ}C$ than unheated panel when the ambient air temperature is $-7^{\circ}C$. The thermal performance of this earth source thermosyphon system for road heating showed that there was no snow on the heated test panels when the snowfall was 5cm average for the region.

• Proceedings of the KAIS Fall Conference
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• 2010.05a
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• pp.400-403
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• 2010

도로상의 안개로 인한 시정감소는 교통사고를 유발하는 주된 원인이므로 전방의 운전자에게 도로의 시정거리를 미리 알려주어 안전운행을 유도하기 위한 안개경고시스템은 도로의 안전관리를 위해 매우 중요한 요소이다. 우리는 CCTV 카메라 영상에서 도로상에 통행중인 차량의 이동영역이 시정에 따라 달라진다는 점에 착안하여 이동영역을 추출하고 이를 이용하여 가시거리를 계산하는 시정 측정 장치를 개발하고 있으며, 주간, 야간 등 날씨의 변화에 덜 민감하면서도 효과적이고 정확한 이동영역의 추출은 시정측정을 위해 매우 중요하다. 본 논문에서는 이동영역의 추출을 위해 영상대비를 이용하여 자동으로 임계치를 결정하는 방법을 제안하며, 결정된 임계치를 적용시킴으로써 프레임간의 차영상으로 부터 잡음이 효과적으로 제거될 수 있음을 보인다. 또한, 차영상을 일정시간 누적시키는 방법을 통해 효과적으로 차량의 이동영역이 추출 되는 것을 보이기 위해 실제 고속도로에서 촬영된 CCTV 영상을 이용하여 실험한 결과를 제시한다.

• The KIPS Transactions:PartB
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• v.17B no.3
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• pp.207-214
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• 2010

A method of the region extraction and recognition of a traffic light and speed sign board in the real road environment is proposed. Traffic light was recognized by using brightness and color information based on HSI color model. Speed sign board was extracted by measuring red intensity from the HSI color information We improve the recognition rate by performing an incline compensation of the speed sign for directions clockwise and counterclockwise. The proposed algorithm shows a robust recognition rate in the image sequence which includes traffic light and speed sign board.

• International Journal of Computer Science & Network Security
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• v.22 no.7
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• pp.220-228
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• 2022

Image always carry useful information, detecting a text from scene images is imperative. The proposed work's purpose is to recognize scene text image, example boarding image kept on highways. Scene text detection on highways boarding's plays a vital role in road safety measures. At initial stage applying preprocessing techniques to the image is to sharpen and improve the features exist in the image. Likely, morphological operator were applied on images to remove the close gaps exists between objects. Here we proposed a two phase algorithm for extracting and recognizing text from scene images. In phase I text from scenery image is extracted by applying various image preprocessing techniques like blurring, erosion, tophat followed by applying thresholding, morphological gradient and by fixing kernel sizes, then canny edge detector is applied to detect the text contained in the scene images. In phase II text from scenery image recognized using MSER (Maximally Stable Extremal Region) and OCR; Proposed work aimed to detect the text contained in the scenery images from popular dataset repositories SVT, ICDAR 2003, MSRA-TD 500; these images were captured at various illumination and angles. Proposed algorithm produces higher accuracy in minimal execution time compared with state-of-the-art methodologies.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.8
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• pp.1996-2015
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• 2023

High-definition (HD) maps can provide precise road information that enables an autonomous driving system to effectively navigate a vehicle. Recent research has focused on leveraging semantic segmentation to achieve automatic annotation of HD maps. However, the existing methods suffer from low recognition accuracy in automatic driving scenarios, leading to inefficient annotation processes. In this paper, we propose a novel semantic segmentation method for automatic HD map annotation. Our approach introduces a new encoder, known as the convolutional transformer hybrid encoder, to enhance the model's feature extraction capabilities. Additionally, we propose a multi-level fusion module that enables the model to aggregate different levels of detail and semantic information. Furthermore, we present a novel decoupled boundary joint decoder to improve the model's ability to handle the boundary between categories. To evaluate our method, we conducted experiments using the Bird's Eye View point cloud images dataset and Cityscapes dataset. Comparative analysis against stateof-the-art methods demonstrates that our model achieves the highest performance. Specifically, our model achieves an mIoU of 56.26%, surpassing the results of SegFormer with an mIoU of 1.47%. This innovative promises to significantly enhance the efficiency of HD map automatic annotation.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.6
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• pp.786-792
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• 2010

This paper presents a real-time lane detection method which can accurately find the lane-mark boundaries in complex road environment. Unlike many existing methods that pay much attention on the post-processing stage to fit lane-mark position among a great deal of outliers, the proposed method aims at removing those outliers as much as possible at feature extraction stage, so that the searching space at post-processing stage can be greatly reduced. To achieve this goal, a grid-based morphology operation is firstly used to generate the regions of interest (ROI) dynamically, in which a directional edge-linking algorithm with directional edge-gap closing is proposed to link edge-pixels into edge-links which lie in the valid directions, these directional edge-links are then grouped into pairs by checking the valid lane-mark width at certain height of the image. Finally, lane-mark colors are checked inside edge-link pairs in the YUV color space, and lane-mark types are estimated employing a Bayesian probability model. Experimental results show that the proposed method is effective in identifying lane-mark edges among heavy clutter edges in complex road environment, and the whole algorithm can achieve an accuracy rate around 92% at an average speed of 10ms/frame at the image size of $320{\times}240$.

• Journal of Korean Tunnelling and Underground Space Association
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• v.12 no.3
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• pp.215-222
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• 2010

An experimental study was carried out on a reduced scale model tunnel to investigate the efficiency of disaster prevention at underground and ground ventilation equipments for the fire in road tunnels. Based on Froude modeling, the 1/50 scaled model tunnel (20 m long) was manufactured. The vertical shafts that are used in the analysis of efficiency of disaster prevention are the two models that had considered when the real tunnels are designed and the amounts of smoke exhaust are applied the miniature of the real tunnels' smoke exhaust, 560 and $280\;m^3/s$. As the result of analysis, it is the possible the emissions of the entire quantity of CO gas through the vertical shafts. In the ground ventilation equipments, the concentration of CO is discharged 2.23~2,73 ppm smaller than the underground ventilation equipments. And the temperature rise in the ground ventilation equipments is $0.53{\sim}0.94^{\circ}C$ lower than in the underground ventilation equipments because of a cooling effect of the surface of the tunnel wall. As a result of analysis of CO concentration and the temperature rise in the modeling ventilation equipment, the position of ground ventilation equipment is more effective than the underground ventilation equipment in disaster prevention measures.

• Journal of Korean Society of Forest Science
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• v.101 no.3
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• pp.365-373
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• 2012

This study purposed to extract and assess the accuracy of assessment for deforestation area in Wonju city using medium resolution satellite image. The total size of deforestation area during the last nine years (2000-2008) was about 467 ha, and it was occurred annually about 52 ha. The most frequent form of deforestation was settlements (72%). Ninety percent of the size of deforestation was less than 2 ha in size. In addition, 79 percent of deforestation area was found within 500 m from the road network and within 100 m of the Forest/Non-forest boundary. This study compared the deforestation based on the administrative information (GIS deforestationI) with the deforestation (RS deforestation) extracted from the satellite imagery by vegetation indices (NDVI, NBR, NDWI). Extraction accuracy, mean-standard deviation${\times}1.5$ applied 3 by 3 filtering, showed reliable accuracy 35.47% k-value 0.20. However, error could be occurred because of the difference of land-use change and land-cover change. The actual rate of land-cover change deforestation area was 32% on administrative information. The 7.52% of forest management activities area was misjudged as deforestation by RS deforestation. Finally, the comparison of land-cover change deforestation (GIS deforestationII) with the RS deforestation accuracy, as a result NDVI mean-standard deviation${\times}2$ applied 3 by 3 filtering, showed improved accuracy 61.23%, k-value 0.23.

• Journal of Korean Society of Forest Science
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• v.102 no.2
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• pp.229-238
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• 2013

This study was conducted to analyze on the operational cost of logging operations in the whole-tree logging operation system by tower-yarder and swing-yarder, and in the cut-to-length logging operation system by excavator with grapple in order to spread efficient logging operation technique and to establish the logging operation system. In the results of the analysis of operation cost, in case of the whole-tree logging operation system, the operation cost was 2,099 won/$m^3$ in felling by chain saw, 28,286 won/$m^3$ in yarding by tower-yarder, 18,265 won/$m^3$ in yarding by swing-yarder, 18,939 won/$m^3$ in bucking by excavator with grapple and chain saw, 20,484 won/$m^3$ in forwarding and accumulation by wheel type mini-forwarder, 12,701 won/$m^3$ in forwarding and accumulation by excavator with grapple and small forwarding vehicle. In case of the cut-to-length logging operation system, the operation cost was 10,160 won/$m^3$ in felling and bucking by chain saw, 7,567 won/$m^3$ in cut-to-length extraction by excavator with grapple, 6,982 won/$m^3$ in branches and leaves extraction by excavator with grapple, 3,040 won/$m^3$ in the operation road construction by excavator with grapple, 20,484 won/$m^3$ in forwarding and accumulation by wheel type mini-forwarder, 12,701 won/$m^3$ in forwarding and accumulation by excavator with grapple and small forwarding vehicle.

• Journal of Korean Society of Forest Science
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• v.101 no.3
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• pp.344-355
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• 2012

This study was conducted to analyze on the operational time and productivities of logging operations in whole-tree logging operation system by tower-yarder and swing-yarder, and in cut-to-length logging operation system by excavator with grapple in order to establish the efficient logging operation system and to spread logging operation technique. In the analysis of operational time, in case of whole-tree logging operation system, the felling time was 46.6 sec/cycle by chain saw, the yarding time was 480.6 sec/cycle by tower-yarder, the yarding time was 287.4 sec/cycle by swing-yarder and the bucking time was 155.14 sec/cycle by chain saw. In case of the cut-to-length logging operation system, the felling and bucking time was 225.65 sec/cycle by chain saw, the cut-to-length extraction time was 4,972 sec/cycle by excavator with grapple, the branches and leaves extraction time was 3,143 sec/cycle by excavator with grapple. The forwarding time was 4,688 sec/cycle by wheel type mini-forwarder, the forwarding time was 2,118 sec/cycle by excavator with grapple and small forwarding vehicle. In the analysis of operational productivities, in case of whole-tree logging operation system, the average felling performance was $57.89m^3/day$ by chain saw, the average yarding performance was $20.3m^3/day$ by tower-yarder, $31.55m^3/day$ by swing-yarder respectively, the average bucking performance was $20.3m^3/day$ by chain saw. In case of the cut-to-length logging operation system, the average felling and bucking performance was $11.96m^3/day$ by chain saw, the average cut-to-length extraction performance was $34.75m^3/day$ by excavator with grapple, the average branches and leaves extraction performance was $37.66m^3/day$ by excavator with grapple, the average length of operation road construction was 73.8 m/day by excavator with grapple. The average forwarding performance by wheel type mini-forwarder and the average forwarding performance by excavator with grapple and small forwarding vehicle was $15.73m^3/day$ and $65.03m^3/day$, respectively.