• Korean Journal of Construction Engineering and Management
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• v.16 no.1
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• pp.52-63
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• 2015

Business facilities among domestic architectures have rapidly been constructed along with domestic economic development. It is an important facility taking the second largest proportion next to apartment buildings among current 31 building types of fire department classification of 2012 year for urban architectures. The expected service life of business facilities is 15 years, but 70% of those in urban areas have surpassed the 15 year service life as of the present 2014. Thus, the demand for urgent rehabilitation of such facilities is constantly increasing due to the aging and performance deterioration of the facilities'main finishing materials. Especially, the business facilities are being used for the lease of company office or private office, and such problems as aging and performance deterioration of the facilities could cause less competitive edge for leasing and real estate value depreciation for the O&M (Operation & Management) agent and the owner, respectively. Therefore, an effective planned rehabilitation as a preventive measure according to the standardized repair rate by the number of years after the construction is in need in order to prevent the aging and performance deterioration of the facilities(La et al. 2001). Nonetheless, domestic repair/rehabilitation standards based on the repair rate are mainly limited to apartment buildings and pubic institutions, resulting in impractical application of such standards to business facilities. It has been investigated and analyzed that annual repair rate data for each finishing material are required for examination of the applicability of the repair rate standard for the purpose of establishment of a repair plan. Hence, this study aimed at developing a repair rate computation model for finishing materials of the facilities and verifying the appropriateness of the annual repair rate for each finishing material through a case study after collecting and analyzing the repair history data of six business facilities. The results of this study are expected to contribute to the planning and implementation of more efficient repair/rehabilitation budget by preventing the waste of unpredicted repair cost and opportunity cost for the sake of the business facilities' owners and O&M agents.

• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.113-129
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• 2015

Location branding is a very important income making activity, by giving special meanings to a specific location while producing identity and communal value which are based around the understanding of a place's location branding concept methodology. Many other areas, such as marketing, architecture, and city construction, exert an influence creating an impressive brand image. A place brand which shows great recognition to both native people of S. Korea and foreigners creates significant economic effects. There has been research on creating a strategically and detailed place brand image, and the representative research has been carried out by Anholt who surveyed two million people from 50 different countries. However, the investigation, including survey research, required a great deal of effort from the workforce and required significant expense. As a result, there is a need to make more affordable, objective and effective research methods. The purpose of this paper is to find a way to measure the intensity of the image of the brand objective and at a low cost through text mining purposes. The proposed method extracts the keyword and the factors constructing the location brand image from the related web documents. In this way, we can measure the brand image intensity of the specific location. The performance of the proposed methodology was verified through comparison with Anholt's 50 city image consistency index ranking around the world. Four methods are applied to the test. First, RNADOM method artificially ranks the cities included in the experiment. HUMAN method firstly makes a questionnaire and selects 9 volunteers who are well acquainted with brand management and at the same time cities to evaluate. Then they are requested to rank the cities and compared with the Anholt's evaluation results. TM method applies the proposed method to evaluate the cities with all evaluation criteria. TM-LEARN, which is the extended method of TM, selects significant evaluation items from the items in every criterion. Then the method evaluates the cities with all selected evaluation criteria. RMSE is used to as a metric to compare the evaluation results. Experimental results suggested by this paper's methodology are as follows: Firstly, compared to the evaluation method that targets ordinary people, this method appeared to be more accurate. Secondly, compared to the traditional survey method, the time and the cost are much less because in this research we used automated means. Thirdly, this proposed methodology is very timely because it can be evaluated from time to time. Fourthly, compared to Anholt's method which evaluated only for an already specified city, this proposed methodology is applicable to any location. Finally, this proposed methodology has a relatively high objectivity because our research was conducted based on open source data. As a result, our city image evaluation text mining approach has found validity in terms of accuracy, cost-effectiveness, timeliness, scalability, and reliability. The proposed method provides managers with clear guidelines regarding brand management in public and private sectors. As public sectors such as local officers, the proposed method could be used to formulate strategies and enhance the image of their places in an efficient manner. Rather than conducting heavy questionnaires, the local officers could monitor the current place image very shortly a priori, than may make decisions to go over the formal place image test only if the evaluation results from the proposed method are not ordinary no matter what the results indicate opportunity or threat to the place. Moreover, with co-using the morphological analysis, extracting meaningful facets of place brand from text, sentiment analysis and more with the proposed method, marketing strategy planners or civil engineering professionals may obtain deeper and more abundant insights for better place rand images. In the future, a prototype system will be implemented to show the feasibility of the idea proposed in this paper.

• Journal of Korean Society for Geospatial Information Science
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• v.22 no.4
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• pp.3-11
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• 2014

Recently, rapid urbanization has necessitated continuous updates in digital map to provide the latest and accurate information for users. However, conventional aerial photogrammetry has some restrictions on periodic updates of small areas due to high cost, and as-built drawing also brings some problems with maintaining quality. Alternatively, this paper proposes a scheme for efficient and accurate update of digital map using point cloud data acquired by Terrestrial Laser Scanner (TLS). Initially, from the whole point cloud data, the building sides are extracted and projected onto a 2D image to trace out the 2D building footprints. In order to register the footprint extractions on the digital map, 2D Affine model is used. For Affine parameter estimation, the centroids of each footprint groups are randomly chosen and matched by means of a modified RANSAC algorithm. Based on proposed algorithm, the experimental results showed that it is possible to renew digital map using building footprint extracted from TLS data.

• Journal of Korean Society of Transportation
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• v.27 no.2
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• pp.35-46
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• 2009

This paper presents an evaluation index for the supply levels of pedestrian facilities in residential area planning. The pedestrian facility supply levels reveal the quality of a residential area, and can be associated with the resident living standards and satisfaction, pedestrian safety levels, and the effectiveness of the construction cost. This research conducted multifaceted procedures for the index development, and these procedures start first by identifying dominant influencing factors on pedestrian travel demand by reviewing the final reports of site planning in more than eight already-completed residential development sites. Second, based on the Space Syntax model, which was initially developed in the UK by establishing statistical relationships among an integration index, population size (persons/day), and the total development area, this research formulated a set of pedestrian demand estimation models. Then these models were utilized in forming a pedestrian facility supply index by integrating the new models and their results with the available accepted practice in the residential planning sector. This was necessary because planners want to understand the total supply level of pedestrian facilities in a residential area during the initial design stage. Finally, to test the model validity in satisfying pedestrian satisfaction, the research included a resident satisfaction interview, and it was revealed that the evaluation index developed in this research could provide planners and engineers with more promising results. It is therefore anticipated that this research can be of service when designing pedestrian facilities in future residential area planning and design activities.

• Steel and Composite Structures
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• v.34 no.5
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• pp.743-767
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• 2020

Due to the impressive flexural performance, enhanced compressive strength and more constrained crack propagation, Fibre-reinforced concrete (FRC) have been widely employed in the construction application. Majority of experimental studies have focused on the seismic behavior of FRC columns. Based on the valid experimental data obtained from the previous studies, the current study has evaluated the seismic response and compressive strength of FRC rectangular columns while following hybrid metaheuristic techniques. Due to the non-linearity of seismic data, Adaptive neuro-fuzzy inference system (ANFIS) has been incorporated with metaheuristic algorithms. 317 different datasets from FRC column tests has been applied as one database in order to determine the most influential factor on the ultimate strengths of FRC rectangular columns subjected to the simulated seismic loading. ANFIS has been used with the incorporation of Particle Swarm Optimization (PSO) and Genetic algorithm (GA). For the analysis of the attained results, Extreme learning machine (ELM) as an authentic prediction method has been concurrently used. The variable selection procedure is to choose the most dominant parameters affecting the ultimate strengths of FRC rectangular columns subjected to simulated seismic loading. Accordingly, the results have shown that ANFIS-PSO has successfully predicted the seismic lateral load with R² = 0.857 and 0.902 for the test and train phase, respectively, nominated as the lateral load prediction estimator. On the other hand, in case of compressive strength prediction, ELM is to predict the compressive strength with R² = 0.657 and 0.862 for test and train phase, respectively. The results have shown that the seismic lateral force trend is more predictable than the compressive strength of FRC rectangular columns, in which the best results belong to the lateral force prediction. Compressive strength prediction has illustrated a significant deviation above 40 Mpa which could be related to the considerable non-linearity and possible empirical shortcomings. Finally, employing ANFIS-GA and ANFIS-PSO techniques to evaluate the seismic response of FRC are a promising reliable approach to be replaced for high cost and time-consuming experimental tests.

• Journal of Korean Society of Transportation
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• v.30 no.5
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• pp.71-82
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• 2012

Some previous studies adopted a method statistically based on the observed traffic volumes and travel times to estimate the parameters. Others tried to find an optimal set of parameters to minimize the gap between the observed and estimated traffic volumes using, for instance, a combined optimization model with a traffic assignment model. The latter is frequently used in a large-scale network that has a capability to find a set of optimal parameter values, but its appropriateness has never been demonstrated. Thus, we developed a methodology to estimate a set of parameter values of BPR(Bureau of Public Road) function using Harmony Search (HS) method. HS was developed in early 2000, and is a global search method proven to be superior to other global search methods (e.g. Genetic Algorithm or Tabu search). However, it has rarely been adopted in transportation research arena yet. The HS based transportation network calibration algorithm developed in this study is tested using a grid network, and its outcomes are compared to those from incremental method (Incre) and Golden Section (GS) method. It is found that the HS algorithm outperforms Incre and GS for copying the given observed link traffic counts, and it is also pointed out that the popular optimal network calibration techniques based on an objective function of traffic volume replication are lacking the capability to find appropriate free flow travel speed and ${\alpha}$ value.

• Journal of KIISE
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• v.43 no.10
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• pp.1085-1093
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• 2016

Community-based Question Answering system is a system which provides answers for each question from the documents uploaded on web communities. In order to enhance the capacity of question analysis, former methods have developed specific rules suitable for a target region or have applied machine learning to partial processes. However, these methods incur an excessive cost for expanding fields or lead to cases in which system is overfitted for a specific field. This paper proposes a multiple machine learning method which automates the overall process by adapting appropriate machine learning in each procedure for efficient processing of community-based Question Answering system. This system can be divided into question analysis part and answer selection part. The question analysis part consists of the question focus extractor, which analyzes the focused phrases in questions and uses conditional random fields, and the question type classifier, which classifies topics of questions and uses support vector machine. In the answer selection part, the we trains weights that are used by the similarity estimation models through an artificial neural network. Also these are a number of cases in which the results of morphological analysis are not reliable for the data uploaded on web communities. Therefore, we suggest a method that minimizes the impact of morphological analysis by using character features in the stage of question analysis. The proposed system outperforms the former system by showing a Mean Average Precision criteria of 0.765 and R-Precision criteria of 0.872.

• Spatial Information Research
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• v.5 no.2
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• pp.133-146
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• 1997

While occasional disasters have occurred recently in urban facilities such as bridges, buildings, subways, roads and others, the systematic safety management of urban facilities is greatly needed to prevent the disaster or to minimize the damages. This study proposes the way of setting-up and managing an building disaster information system so that this experience can be applied to other urban facilities to minimize trials and errors. With such a purpose, this study presents a building safety management information system and utilizes it for the building disasten information system. This study includes research agendas as follows : building maintenance and management infonnation system, setting-up and utilization the building safety management infonnation system, building disaster infonnation system using GIS. The results suggest that the building safety management infonnation system which can be related to the urban disaster infonnation system should be constructed in advance in order to utilize the building disaster infonnation system, and that, under this condition, it proved to be easily connected to the related database, especially GIS. And, to utilize such an infonnation system, the application programs such as safety evaluation program, cost estimation program and documents management program should be readily available. In addition, other functional programs related with maintenance and management should be designed and established. The schemes or devices for practical usage should be supplemented through a standardization and a pilot project in central government or Seoul Metropolitan Government level in order to set up and utilize the building safety management infonnation system, and the related laws or regulations should be prepared or amended to support the system.

• Journal of Digital Convergence
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• v.19 no.5
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• pp.145-152
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• 2021

In this study, we have examined the effect of open innovation of SMEs on innovation performance of firms. Most studies do not consider internal generation in relation to open innovation and innovation performance.We conducted empirical studies to overcome this problem. The research was carried out by collecting data collected from 512 SMEs and the 3SLS method was used to minimize the internal generation. As a result, open innovation investment and use of external ideas among SMEs' open innovation have positively influenced project success and technical performance. But, the introduction of technology and cooperation with the research organization did not affect the innovation performance, which is presumed to be due to the fact that the open innovation of SMEs is limited to relatively inexpensive activities. Therefore, in order to promote open innovation of SMEs, it is necessary to provide support for relatively high-cost activities and to improve the innovation performance of enterprises. In order to reduce the difficulties of open innovation activities, domestic universities and research institutes should support the construction of enterprise networks and actively support the utilization of technology to expand innovation performance.

• Magazine of the Korean Society of Agricultural Engineers
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• v.17 no.4
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• pp.3943-3955
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• 1975

The purposes of this study are to evaluate the utilization characteristics of electrical power consumption, to grasp the present trends in the use of electrical equipments, to estimate the demand factor and load factor being held, and to evaluate the efficiency of electical uses for the recently electrified farms cultivating paddy rice. For the purposes, 109 sample farms located in eleven villiages electrified in six different years from 1968 to 1973, were chosen at random and investigated on 35 items concerning to electrical uses and wiring systems. The survey was carried out in 1975, in the vinicity of Suweon city. The results are summarized as follows: i) The average annual power consumption on sample farms is considered to be low, being 242.9 Kwh. in 1974, and varied according to the different electrified year and size of cultivated land, respectively. It has significant positive correlation to the area of farm, too. ii) Between the number of year of electrical uses and the power consumption, there is very significant positive correlation, which could be expressed as Y=43.041+16.108 X, where X represents the number of years of electrical uses. The annual increment of power consumption is much greater at the beginning of the electrification than that at the later years, its average being approximately 20 percent. However, it is recommended that any estimation of long-term increments should be carefully investigated. iii) The monthly power consumption varies considerably throughout a year, in which the heaviest farm load occurs in November. Observing the seasonal variation of consumption, the winter-time is the heaviest season while the summer is the lowest. The result implies house lighting is chief contribution to the present electrical consumption on the farms. Comparing the variation of monthly consumption ratios between the sample farms and industries, the electrical uses on the farms are independant of the industrial uses, and further, the agricultural uses are of inverse pattern to the farms from the results that there is negative correlationship between them, iv) The number of electrical equipments used on the farms are occupied chiefly by lighting sources. Next to the lighting sources, household appliances of small quantity and some motors are used. The mean electrical quantity is about 1, 127.4 watt, which corresponds to about 37.6 per cent to the contracted quantity. The composition of quantity is chiefly occupied by the electrical motor of about 1.5 hp., single-phased. The number of the annual utilization hours of each equipment is tabulated in Table IV-5. In contradiction to the high utilization of lighting sources and small household appliances, the motor is poorly used for approximately 22 hours in a year. v) More than 55 per cent of farms want to purchase new electrical equipments such as small household appliances and electrical motors in their number. The impulse of purchasing such items is stimulated by the contacts to the mass media and their knowledge on such equipments. Consequently, the increase of electrical uses could be prompted by such trials as education and demonstration. vi) The demand and load factors on the farms vary considerably according to the greater variation of the power consumption, daily or monthly. The daily demand factor is 22.4 per cent and load factor 18.6 per cent, while the annual demand factor is 1.3 per cent and load factor 70 per cent approximately. Therefore, the low efficiency of construction cost requires re-evaluation of the present contracted quantity of 3 Kw. or increase of electrical uses. vii) The electrical energy on the farms devoted chiefly to lighten the farm residences does not contribute to the farm incomes. Consequently, the cost of electrical consumption presses considerably upon the farm economy. Therefore, there is great need to build up the electrical uses on the farms through the development of new works and techinques to utilize any electrical equipments on the production of farm products. Further more, such the development should be related to increase the actual income of the farm consumers.