This study explores potential capability of a machine learning approach for monitoring urban morphology based on an evident case study. The case study conveys year 2006 investigations on interpreting urban morphology of Boston Main Streets by applying a machine learning approach. From the lesson of the precedent study, in 2016, another field research and interview was conducted to compare changes in urban situation, data commons culture, and technology innovation during the decade. This paper describes open possibilities to advance urban monitoring for morphological changes. Most of all, a multi-participatory data platform enables managing urban data system in real time. Second, collaboration with machines with artificial intelligence can intervene the framework of the urban management system as well as transform it through new demands of innovative industries. Recently, urban regeneration became a dominant urban planning strategy in Korean, therefore, urban monitoring is on demand. It is timely important to correspond to in-situ problems based on empirical research.
Kim, Sang Hoon;Kim, Dong Sub;Kim, Jin-Baek;Ha, Bo-Keun;Lee, Duk Man;Song, Hi Sup;Kang, Si-Yong
Horticultural Science & Technology
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v.33
no.2
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pp.298-301
/
2015
A new Hibiscus syriacus variety, 'Dasom', was developed by radiation breeding using gamma ray exposure at the Korea Atomic Energy Research Institute (KAERI). Seeds of the original variety, 'Hongsun', were collected in 1993. These seeds were irradiated at 100 Gy dose and $M_1$ seeds were planted in a field of the KAERI in 1994. Lines with preferred flower color that were going to be used for street trees were initially selected in 1998. Analyses of characteristics were conducted from 2005 to 2010. The 5-year-old 'Dasom' plants were approximately 106 cm in height and averaged 19 branches, and thus were suitable for street trees. The flowers of 'Dasom' were semi-double type with medium red color and red eye spots. Petal length and width were about 4.0 cm and 3.3 cm, respectively. Flower diameter was slightly small, at about 5.8 cm, because of highly overlapping petals. The flowering period of 'Dasom' was about 105 days, which was 6 days shorter than that of the original variety, 'Hongsun'. However, the main charactersistics of 'Dasom' including leaf shape were similar to those of the original variety, 'Hongsun'.
Purpose: The purpose of this study was to research the display of optician's shop through questionnaire to suggest the direction for more effective display method. Methods: The study visited 50 optician's shops located in main area of Ulsan (university street, downtown and residential street), performed questionnaire and researched optician's display preference. Results: The displays preferred by opticians were as follows. They displayed contact lens in entrance of shop, displayed sunglasses in the wall rather than displayed them in the center of shop and displayed medium or low price products in the center so that consumers could access them conveniently. In addition, they prepared resting place for customer's convenience by locating it in entrance or inside of shop. Conclusions: It seems that effective display of optician's shop can attract consumer's mind and improve purchase, resulting in significant change of optician's shop sales. Therefore, it is necessary to perform the study to use systematic, discriminated display strategy so that shop image can be controlled consistently and continuously.
The Journal of The Korea Institute of Intelligent Transport Systems
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v.17
no.4
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pp.124-137
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2018
The main purpose of this study is to find the hotspots of crimes that occur frequently in the space and to derive the appropriate CCTV installation location. One of the characteristics of crime is clustered around past occurrence area, and these crimes are strongly correlated. It is also possible to find the cause of the clusters and the variables that affect the crime through the history of the crime. In addition to the traditional OLS model, spatial differential model including spatial autocorrelation and spatial error model were used to select the variables influencing the five major crime rate, the theft rate and the foreign resident rate. The variables affecting the Five major crimes were positive (+) sign for the welfare and the rate of the bar cluster rate, and negative (-) for the street density. The CCTV area occupies 46% of the hotspots based on the overlapping of the areas where the elderly people are crowded, the bar cluster, many multicultural families, and the areas with low density of street lamps. It turned out. Taking into account the current CCTV operation, the total number of new cases to cover the risk point was 89.
Purpose - This paper attempts to identify the problems and limitations of a market maintenance project conducted according to the 「Special Act for the Development of Traditional Markets and Shopping Street」 and to present a revised direction for the special law and lay the groundwork for market maintenance projects to be promoted smoothly. Research design, data, and methodology - The revised direction for the legislation and the proposal were written based on an investigation of the problems and the legal system, and proposed measures for market maintenance operation and system improvements to derive the improvements needed for market maintenance projects. Results - A market maintenance project has been conducted as a means to reinvigorate traditional markets that are economically depressed, and to revive the local economy. It was largely conducted in the form of reconstruction and redevelopment and represents the interests of landowners and merchants. Thus, it is most likely to contribute to the gradual disappearance of traditional markets. First, as part of a market maintenance project, many companies are building multipurpose buildings or high-rise residential buildings to increase profits. In these high-rise buildings, they can raise rents, which may not be affordable for some existing small businesses. To solve such problems, the large-scale store registration requirement needs to be relaxed or abolished once the market maintenance project is completed. If the large-scale store registration requirement is to be abolished, the term 'large retail store' should be changed in the 「Special Act for the Development of Traditional Markets and Shopping Street」. After registration, the Small and Medium Business Administration should train merchants, offer consultations, and support events, to the extent that the existing traditional market management modernization project permits, and further continue to manage and support its ongoing activities. However, unless large-scale store registration is abolished, adding an exception clause in the special law to relax large-scale store registration criteria, and permitting changes to building use is another option. At the end of a market maintenance project, empty stores should be purchased by the Small and Medium Business Administration, and local government, etc., at the actual construction cost, to utilize them as public rental shopping areas, which in turn may be re-utilized as a temporary market for another market maintenance project. The second problem in market maintenance projects is merchant-protection. Currently, the special law prescribes that a temporary market be created for merchants to conduct business during the rental period of a market maintenance project. Conclusions - In reality, a market maintenance project is conducted usually in big metropolitan cities with 500,000 residents or more. The main building type created under these projects is a multipurpose building. For this reason, it is very difficult to secure a location for a temporary market in the surrounding area of such a project. To solve this problem, this study suggests 'public rental shopping areas' as mentioned above.
The road sign is one of street furnitures functioning to guide directions for drivers. The road sign should be employed and designed to help drivers find their destinations easily and accurately. It is obvious that the road sign is one of the main components that enhance efficiency and safety of driving environments. The current way of guiding strategy at road signs in Korea is a system for mainly guiding 'points' although a new system guiding 'road names' and 'street numbers' with the introduction of new address system is now being introduced on urban areas. When the regional territory management offices and local governments try to employ current road sign systems, they are supposed to follow the sign regulations which contains standard project processes, selection methods of guiding points, character size and design, and location selection for each road sign. However, the current road sign regulations are very complex to understand and unclear for a person in charge to do tasks described above. Especially, selection process and criteria of guiding points are cumbersome and controversial. Furthermore, non sufficient ways of selecting guiding points considering road functions and geographic characteristics decrease the connectivity of guiding points. This study develops enhanced ways of increasing connectivity of successive guiding points through three case studies. Developed ways will help highway agencies and officials understand how to improve the connectivity of road signs.
In this study, landscape changes were examined by periods through the analysis of visual quantity on the landscape components of national road including the mountains, the sky, road pavements, street trees, paddy fields and dry fields, billboard, telegraph pole, building, structure, slope, guard fence, soundproof wall, and median strip etc. For this, subject national road in suburb arreas was selected to grasp its landscape characteristics, and divisional criteria of landscape type of the national road were suggested to look into the trend of landscape changes by periods. Findings of this study are as follows:1.Divisional criteria of landscape type of the national road include location and geometry, structure, land use, perspective, and surrounding buildings of the national road. 2.The highest visual quantity was found in road pavements by periods among landscape components of the national road. It was found that this result has a thread of connection with previous study emphasizing the importance of road geometry as one of landscape components, and road geometry shall be regarded as a visually significant component in analyzing and evaluating landscape of the national road. 3.Most distinguished factors of landscape changes of the national road by periods were median strip(F=33.296) and street tree(F=32.881), and then the sky(F=24.735) and mountain(F=23.477) showed similar level of statistically significant difference. However, statistically significance difference was not found in buildings and structures. 4.It was shown that natural elements decreased gradually but structural landscape made of artificial elements became the main in construction of the national road. This result implies that although the scenic and ecological soundness is recognized in construction of the national road, it is not out of the limitation of functionalities that is, access and mobility.
The old residences and shops in the backside blocks are affected by the traffic noises from the main road. The noise of the backside roads is affected by the following factors such as the height of the roadside buildings, the distance between the road and the backside streets, distance among adjacent roadside buildings, and the difference of the adjacent building heights. The both noise levels on the road and the backside street were measured simultaneously in 15 urban blocks of a city which can be categorized into two types of roadside building plans ; 1) one single building along the street, 2) buildings arranged on one axis beside the road. As the results, there is no significant noise reduction due to the width of the buildings in general. However, in the cases of buildings arranged on one axis beside the road, it was found that the average noise reduction was 12 dB(A) on the basis of the building height of 4 m. Also, it was analysed that for each 4 m increase in the building height, noise reduction occurred by 2 dB(A) beyond building height of 4 m. In general, it was proved that the noise of the back streets is mainly affected by the lowest height of the roadside buildings. It was found that noise is increased by 1 dB(A) for each 4 m increase of the height difference between adjacent buildings. Also, It was revealed that for each 0.5 m increase in the distance between roadside building, noise reduction decreased by 1 dB(A).
Joon-Woo Lee;Yu-Han Han;Jeong-Taek Lee;Jin-Hyuk Park;Geun-Han Kim
Korean Journal of Remote Sensing
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v.39
no.6_3
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pp.1721-1730
/
2023
As awareness of the problem of global warming emerges around the world, the role of carbon sinks in settlement is increasingly emphasized to achieve carbon neutrality in urban areas. In order to manage carbon sinks in settlement, it is necessary to identify the current status of carbon sinks. Identifying the status of carbon sinks requires a lot of manpower and time and a corresponding budget. Therefore, in this study, a map predicting the location of trees was created using already established tree location information and Sentinel-2 satellite images targeting Seoul. To this end, after constructing a tree presence/absence dataset, structured data was generated using 16 types of vegetation indices information constructed from satellite images. After learning this by applying the Extreme Gradient Boosting (XGBoost) model, a tree prediction map was created. Afterward, the correlation between independent and dependent variables was investigated in model learning using the Shapely value of Shapley Additive exPlanations(SHAP). A comparative analysis was performed between maps produced for local parts of Seoul and sub-categorized land cover maps. In the case of the tree prediction model produced in this study, it was confirmed that even hard-to-detect street trees around the main street were predicted as trees.
This research investigates training methods for large language models to accurately identify sentiments and comprehend information about increasing and decreasing fluctuations in the financial domain. The main goal is to identify suitable datasets that enable these models to effectively understand expressions related to financial increases and decreases. For this purpose, we selected sentences from Wall Street Journal that included relevant financial terms and sentences generated by GPT-3.5-turbo-1106 for post-training. We assessed the impact of these datasets on language model performance using Financial PhraseBank, a benchmark dataset for financial sentiment analysis. Our findings demonstrate that post-training FinBERT, a model specialized in finance, outperformed the similarly post-trained BERT, a general domain model. Moreover, post-training with actual financial news proved to be more effective than using generated sentences, though in scenarios requiring higher generalization, models trained on generated sentences performed better. This suggests that aligning the model's domain with the domain of the area intended for improvement and choosing the right dataset are crucial for enhancing a language model's understanding and sentiment prediction accuracy. These results offer a methodology for optimizing language model performance in financial sentiment analysis tasks and suggest future research directions for more nuanced language understanding and sentiment analysis in finance. This research provides valuable insights not only for the financial sector but also for language model training across various domains.
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