Housing vacancies have become a major issue in urban areas, there have been many efforts to address this issue at the national and local levels. The purpose of this paper is to investigate the factors contributing to housing vacancies in old town Incheon in South Korea. In particular, the research focuses on examining the effects of multiple levels of factors on housing vacancies in a comprehensive way; the three levels of factors were identified with a literature review including housing (Level 1), Neighborhood (Level 2), and Region (Level 3). A multi-level logistic regression model was used to examine the relationship between 13 factors in three spatial levels and housing vacancies. As a result, the factors in all three levels were able to explain housing vacancies including site area and shape, proximity to major roads (Level 1), ratio of houses in designated urban renewal area and slope (Level 2), and ratio of the elderly living alone, land price, changes in land price and ratio of new houses (Level 3). These results show that the combination of the physical inferiority of the housing site and the neighborhood environment and the economic and social vulnerability of the region is likely to increases the number of vacant houses. This study also suggested that a multi-dimensional policy strategy is needed to solve the problem of housing vacancies, and urban policies, such as supplying new housing or urban renewal area designation, should be carefully implemented in a way not to create housing vacancies.
Song, Jaein;Kang, Min Hee;Cho, Yun Ji;Hwang, Kee yeon
The Journal of The Korea Institute of Intelligent Transport Systems
/
v.19
no.6
/
pp.163-179
/
2020
With the expansion of platform-based taxi service, mobility and convenience of users are getting better. However, due to profitability problem, marginalized areas in the supply of the service are expected to appear. As such, this study analyzed spatial marginalization of taxi service caused by imbalance in supply and demand during the night-time when public transportation service is suspended. According to hot-spot analysis of taxi, outskirt of a city and residential areas showed high vacancy and greater number of drop-offs compared to the number of pick-ups. On the contrary, they were confirmed low in the center and sub-centers of a city. Centrality analysis also showed a similar pattern with hot-spot analysis. Due to this, drivers may refuse to pick up a customer bound for an area with lower out-degree centrality compared to in-degree centrality as it might be difficult for the drivers to pick up another customer after dropping off the current customer. Thus, customers may need to wait for a taxi for a longer time. For this reason, improvement in spatial marginalization caused by mismatch of supply and demand is required. Also, the outcome of this study is expected to be utilized as a basic data.
As deep learning-based object detection and recognition research have been developed recently, the scope of application to industry and real life is expanding. But deep learning-based systems in the construction system are still much less studied. Calculating materials in the construction system is still manual, so it is a reality that transactions of wrong volumn calculation are generated due to a lot of time required and difficulty in accurate accumulation. A fast and accurate automatic drawing recognition system is required to solve this problem. Therefore, we propose an AI-based automatic drawing recognition accumulation system that detects and recognizes steel materials in construction drawings. To accurately detect steel materials in construction drawings, we propose data augmentation techniques and spatial attention modules for improving small object detection performance based on YOLOv4. The detected steel material area is recognized by text, and the number of steel materials is integrated based on the predicted characters. Experimental results show that the proposed method increases the accuracy and precision by 1.8% and 16%, respectively, compared with the conventional YOLOv4. As for the proposed method, Precision performance was 0.938. The recall was 1. Average Precision AP0.5 was 99.4% and AP0.5:0.95 was 67%. Accuracy for character recognition obtained 99.9.% by configuring and learning a suitable dataset that contains fonts used in construction drawings compared to the 75.6% using the existing dataset. The average time required per image was 0.013 seconds in the detection, 0.65 seconds in character recognition, and 0.16 seconds in the accumulation, resulting in 0.84 seconds.
Purpose: This study analyzes accessibility of outdoor evacuation places for earthquake and the accessibility improvement effects when expanding the evacuation places in accessibility-deficient areas. In order to consider real-world evacuees, the accessibility analysis is based on service population not on resident population. Method: Location-allocation model as a GIS-based spatial optimization mode is used to analyze accessibility and vulnerable areas to evacuation places. Of location-allocation problem types, 'Maximize Coverage' method is chosen to allocate as many potential evacuees as possible to evacuation places. And impedence cutoffs or evacuation distances (times) are applied to three classes: 500m (7.5 minutes), 1,000m (15 minutes), and 1,500m (22.5 minutes). Case study area is Jung-gu areas, Seoul as a high-density downtown area. Result: Results show that accessibility-deficient areas and population to evacuation places are much more in service population than in resident population. Accessibility is significantly improved when increases when expanding the evacuation places in accessibility-deficient areas. Yet, accessibility-deficient areas are still remained since available lands are insufficient in the high-density downtown area. Conclusion: The study suggests that temporary evacuation facilities like outdoor evacuation places for earthquake need to consider real potential evacuees based not only on resident population but also on service population. Also, policy measures to provide emergency shelters need to more utilize spatial optimization tools like location-allocation model.
Among imaging and treatment devices for small animals, positron emission tomography(PET) causes a change in spatial resolution within a field of view. This is a phenomenon caused by using a small gantry and a thin and long scintillation pixel, and detectors that measure the interaction depth are being developed and researched to solve this problem. In this study, a detector that measures the interaction depth was designed using several scintillator blocks and light guides with different reflector patterns. The scintillator block composed of 4 × 4 arrays of 3 mm × 3 mm × 5 mm scintillation pixels formed four layers, and a light guide was inserted in each layer to configure the entire detector. In order to check whether the interaction depth was measured, a gamma ray interaction was generated at the center of all scintillation pixels to acquire data and then reconstructed into a flood image. The reflector patterns of the light guides inserted between the layers were all different, so the positions of the scintillation pixels for each layer were formed in different locations. It is considered that even spatial resolution can be achieved over all regions of the field of view if all positions of the scintillation pixels thus formed are separated and used for image reconstruction.
In preclinical positron emisson tomography(PET), spatial resolution degradation occurs outside the field of view(FOV). To solve this problem, a depth of interaction(DOI) detector was developed that measures the position where gamma rays and the scintillator interact. There are a method in which a scintillation pixel array is composed of multiple layers, a method in which photosensors are arranged at both ends of a single layer, a method in which a scintillation pixel array is constituted in several layers and a photosensor is arranged in each layer. In this study, a new type of DOI detector was designed by analyzing the characteristics of the previously developed detectors. In the two-layer detector, different sizes of scintillation pixels were used for each layer, and the array size was configured differently. When configured in this form, the positions of the scintillation pixels for each layer are arranged to be shifted from each other, so that they are imaged at different positions in a flood image. DETECT2000 simulation was performed to confirm the possibility of measuring the depth of interaction of the designed detector. A flood image was reconstructed from a light signal acquired by a gamma-ray event generated at the center of each scintillation pixel. As a result, it was confirmed that all scintillation pixels for each layer were separated from the reconstructed flood image and imaged to measure the interaction depth. When this detector is applied to preclinical PET, it is considered that excellent images can be obtained by improving spatial resolution.
Interests in clean fuels have been soaring because of environmental problems such as air pollution and global warming. Unlike fossil fuels, hydrogen obtains public attention as a eco-friendly energy source because it releases only water when burned. Various policy efforts have been made to establish a hydrogen based transportation network. The station that supplies hydrogen to hydrogen-powered trucks is essential for building the hydrogen based logistics system. Thus, determining the optimal location of refueling stations is an important topic in the network. Although previous studies have mostly applied optimization based methodologies, this paper adopts machine learning to review spatial attributes of candidate locations in selecting the optimal position of the refueling stations. Machine learning shows outstanding performance in various fields. However, it has not yet applied to an optimal location selection problem of hydrogen refueling stations. Therefore, several machine learning models are applied and compared in performance by setting variables relevant to the location of highway rest areas and random points on a highway. The results show that Random Forest model is superior in terms of F1-score. We believe that this work can be a starting point to utilize machine learning based methods as the preliminary review for the optimal sites of the stations before the optimization applies.
The medical information system is an effective medical diagnosis assistance system which offers an environment in which medial images and diagnosis information can be shared. However, this system can only stored and transmitted information without other functions. To resolve this problem and to enhance the efficiency of diagnostic activities, a medical image classification and retrieval system is necessary. The medical image classification and retrieval system can improve efficiency in a medical diagnosis by providing disease-related images and can be useful in various medical practices by checking diverse cases. However, it is difficult to understand the meanings contained in images because the existing image classification and retrieval system has handled superficial information only. Therefore, a medical image classification system which can classify medical images by analyzing the relation among the elements of the image as well as the superficial information has been required. In this paper, we propose the method for learning and classification of brain MRI, in which the superficial information as well as the spatial information extracted from images are used. The superficial information of images, which is color, shape, etc., is called low-level image information and the logical information of the image is called high-level image information. In extracting both low-level and high-level image information in this paper, the anatomical names and structure of the brain have been used. The low-level information is used to give an anatomical name in brain images and the high-level image information is extracted by analyzing the relation among the anatomical parts. Each information is used in learning and classification. In an experiment, the MRI of the brain including disease have been used.
When a scintillator block is constructed using fine scintillator pixels, the scintillator block located at the edge of the scintillator block results in overlapping images. To solve this problem, a light guide was inserted between the scintillator block and the photosensor, and images of all scintillation pixels were separated and acquired. However, loss of light may occur through the light guide, which eventually affects the quality of the image due to a decrease in energy resolution. Therefore, in this study, a detector was designed that can separate scintilltion pixels better by using a reflector on the side of the light guide and can secre excellent energy resolution by minimizing light loss. For comparative evaluation with previous studies, flood images were obtained through DETECT2000 capable of light simulation, and the degree of separation and light collection rate were evaluated. When a reflector was used on the side of the light guide, all materials showed excellent separation regardless of the material of the light guide, which showed better separation results than previous studies. In addition, the light collection rate was more that five times better when the reflector was applied than when it wa not. If this detector is applied to a small animal positron emission tomography, it will be possilbe to secre excellent image quality through excellent spatial resolution and energy resolution.
Sevaral problems of administrative area sysem in Korea have been brought up for a long time. Because its frame has remained since Chosun and Japanese colonial period in spite of changing local administrative environment in accordance with rapid industrialization and urbanization. Recent reform of city (Shi)- county (Gun) integration is derived from this argument. But problems which permeate deeply overall system cannot be solved by partial reorganization of Shi-Gun. They may be rationalized only through the reform of the whole system. The aims of this study are to analyze problems of administrative area system entirelr and to discuss the direction of its reform from that point of view. Major problems of administrative area system are summed up into the followings. Firstly, it is found that administrative hierarchies are too many levels. Contemporary administrative hierarchical structure is 4 levels: regional autonomous government (Tukpyolshi, Jik'halshi, Do), local autonomous government (Shi, Gun), two leveis of auxiliary administrative area (Up, Myun and Ri). These hierarchies were established in late period of Chosun which transportation was undeveloped and residential activity space was confined. But today developing transportion and expanding sphere of life don't need administrative hierarchical structurl with many levels. Besides developing administrative technology reduces administrative space by degrees. Many levels of contemporary administrative hierarchical structure are main factor of administrative inefficency, discording with settlement system. Second problem is that Tukpyolshi and Jik'halshi - cities under direct control of the central government as metropolitan area - underbounded cities. Underbounded city discomforts residential life and increases external elects of local pulic services. Especially this problem is Seoul, Pusan and Daegu. Third problem is that Do-areas are mostly two larger in integrating into single sphere of life. In fact each of them consistes of two or three sphere of life. Fourth Problem is metropolitan government system that central city is seperated from complementary area, i.e. Do. It brings about weakening the economic force of Do. Fifth problem is that several cities divided single sphere of life. It is main factor of finantial inefficency and facing difficult regional administration. Finally necessity of rural parish (Myun.) is diminished gradually with higher order center oriented activty of rural residents. First of all administrative area system should corresponds with substantial sphere of life in order to solve these problems. Followings are some key directions this study proposes on the reform of administrative area system from that standpoint. 1. Principles of reorgnization -- integration of central dty with complementary area. -- correspondence of administrative hierarchical structure with settlement system. -- correspondence of boundary of administrative area with sphere of life. 2. Reform strategy -- Jik'halshi is integrated with Do and is under the contol of Do. -- Small Seoul shi (city) which have special functions as captal is demarcated in Seoul tukpyolshi and 22 autonomous distrcts of Seoul tukpyolshi is integrated into 3-4 cities. -- Neighboring cities (Shies) in single sphere of life are intrgrated into single city (Shj). -- Myun and Ri are abolished in rural region and new unit of local administrative area on the basis of lowest order sphere of life into which 3-4 Ries are integrated replaces them.
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