• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.11
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• pp.66-72
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• 2014

Histogram of oriented gradient (HOG) feature is widely used in vision-based pedestrian detection. The interpolation is the most important technique in HOG feature calculation to provide high detection rate. In interpolation technique of HOG feature calculation, two nearest orientation bins to gradient orientation for each pixel and the corresponding weights are required. In this paper, therefore, an efficient gradient orientation bin and weight calculation circuit for HOG feature is proposed. In the proposed circuit, pre-calculated values are defined in tables to avoid the operations of tangent function and division, and the size of tables is minimized by utilizing the characteristics of tangent function and weights for each gradient orientation. Pipeline architecture is adopted to the proposed circuit to accelerate the processing speed, and orientation bins and the corresponding weights for each pixel are calculated in two clock cycles by applying efficient coarse and fine search schemes. Since the proposed circuit calculates gradient orientation for each pixel with the interval of $1^{\circ}$ and determines both orientation bins and weights required in interpolation technique, it can be utilized in HOG feature calculation to support interpolation technique to provide high detection rate.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.6
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• pp.87-96
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• 2022

The traffic vulnerable, including elderly pedestrians, have a relatively low walking speed and slow cognitive response time due to reduced physical ability. Although a smart crossing system has been developed and operated to improve problem, it is difficult to operate a signal that reflects the appropriate walking speed for each pedestrian. In this study, a neural network model and a multiple regression model-based traversing speed estimation model were developed using image information collected in an area with a high percentage of traffic vulnerability. to support the provision of optimal walking signals according to real-time traffic weakness. actual traffic data collected from the urban traffic network of Paju-si, Gyeonggi-do were used. The performance of the model was evaluated through seven selected indicators, including correlation coefficient and mean absolute error. The multiple linear regression model had a correlation coefficient of 0.652 and 0.182; the neural network model had a correlation coefficient of 0.823 and 0.105. The neural network model showed higher predictive power.

• Journal of the Korean Institute of Landscape Architecture
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• v.47 no.6
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• pp.53-66
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• 2019

The purpose of this study was to suggest indicator-based selection and improvement plans for evaluating urban regeneration projects. First, we selected the indicators by conducting expert surveys and analysis of the responses received. Additionally, using the selected indicators, we analyzed the residents' opinions in Wongogae Village, where urban regeneration projects were in progress. Based on these, we suggested a plan to improve Wongogae Village. According to the study, we classified the urban regeneration evaluation indicators into 'Physical environment', 'Social environment' and 'Economic environment' according to their characteristics. We selected urban regeneration evaluation factors through the first expert survey and MCB analysis. As a result, we selected six factors for the 'Physical environment' category: 'Traffic and pedestrian environment', 'Residential (housing) environment', 'Safety and security environment', 'Greenspace', 'Landscape improvement' and 'Public space', In the 'Social environment' category, four factors were chosen: 'Resident participation', 'Community activation', 'Role of the local government and support centers' and 'Resident education' while for the 'Economic environment' category three factors were selected: 'Local economic revitalization', 'Creating an economy-based environment', 'Job creation'. Next, we conducted a second expert survey and carried out an AHP analysis using the selected evaluation factors to derive the overall weight for each. Among the evaluation factors for urban regeneration, the 'Residential (housing) environment' has the highest weighted value of 0.108, followed by 'Local economic revitalization' and 'Resident participation'. Lastly, the analysis of the residents' opinions of Wongogae Village using the urban regeneration evaluation factors, Parking environment', 'Maintenance of old houses and living environment', 'Environment for founding town and social enterprises', 'Improve commercial and business environment', 'Maintain and activate existing business' and 'Vitalizing small regional economies such as domestic handicrafts and side-job' had high overall importance, but low satisfaction, which means that it is necessary to improve the focus. Therefore, in order to improve the urban regeneration project in villages, it is necessary to improve the parking environment by expanding public parking lots, eliminate close houses, and idle lands, or open a school playground in the village for the residents. In addition, it is essential to encourage economic activities, such as fostering village enterprises and social enterprises in connection with cooperatives and allow for the selling of the products through resident activities, such as neighboring markets.