• International Journal of Highway Engineering
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• v.17 no.2
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• pp.1-11
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• 2015

PURPOSES : This study set out to investigate the fundamental properties of alkali-activated concrete (AAC) using modified slag as the pavement maintenance material. METHODS: The material properties of modified slag based alkali-activated concrete (MSAAC) were analyzed and evaluated against those of alkali-activated slag concrete (AASC). Several mix formulations were considered, including one MSACC and four AASCs. The main variables considered in the study were slump, air content, compressive strength, rapid chloride permeability test, scaling resistance, freeze-thaw test, XRD, SEM, and EDS. RESULTS: MSAAC exhibits a compressive strength in excess of 21 MPa six hours after curing. Also, the charge passed of the MSACC was found to be less than 2000 coulombs after seven days and about 1000 coulombs after 28 days. The weight loss determined from a scaling test did not exceed $1kg/cm^2$ in the case of the MSACC, but that of the AASCs had already exceeded $1kg/cm^2$ at the 10th cycle. Based on the results of the freeze-thaw test, the relative dynamic modulus of every mix was found to be in excess of 90%. An energy dispersive spectroscopy(EDS) analysis found that the weight rate percentage of the calcium and aluminum in the MSAAC mix is twice that of the AASC mixes. CONCLUSIONS : It was found that the MSAAC mix exhibits significantly better performance than AASC mixes, based on various fundamental properties.

• Earthquakes and Structures
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• v.27 no.1
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• pp.17-29
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• 2024

The traditional double story isolated structure is a derivative of the base isolated and inter-story isolated structures, while the new double story isolated structure represents a novel variation derived from the traditional double story isolated structure. In order to investigate the seismic response of the new double story isolated structure, a comprehensive structural model was developed. Concurrently, models for the basic fixed, base isolated, inter-story isolated, and traditional double story isolated structures were also established for comparative analysis. The nonlinear dynamic time-history response of the new double story isolated structure under rare earthquake excitations was analyzed. The findings of the study reveal that, in comparison to the basic fixed structure, the new double story isolated structure exhibits superior performance across all evaluated aspects. Furthermore, when compared to the base isolated and inter-story isolated structures, the new double story isolated structure demonstrates significant reductions in inter-story shear force, top acceleration, and inter-frame displacement. The horizontal displacement of the new double story isolated structure is primarily localized within the two isolation layers, effectively dissipating the majority of input seismic energy. In contrast to the traditional double story isolated structure, the new design minimizes displacements within the inter-isolation layer situated in the central part of the frame, as well as mitigates the overturning forces acting on the lower frame column. Consequently, this design ensures the structural integrity of the core tube, thereby preventing potential collapse and structural damage.

• Journal of Convergence for Information Technology
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• v.9 no.1
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• pp.116-122
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• 2019

In recent years, small and medium-sized businesses are rapidly changing to an industrial structure where process/quality/energy data aggregates can be automatically or real-time to achieve global competitiveness. In particular, real-time information analysis produced in the production process of small businesses is evolving into a new process process that analyzes, predicts, prescribes and implements significant performance of small businesses. In this paper, we propose a platform-building model that can transform the automated production information system of small businesses into big data so that they can upgrade data that is generated by small businesses. The proposed model has the capability to support operational efficiency (consulting and training) and strategic decision making of small businesses by utilizing a variety of data on the basic information of products produced by small businesses for data collection by smart SMEs. In addition, the proposed model is characterized by close cooperation between small and medium-sized businesses with different regional characteristics and areas of information sharing and system linkage.

• Journal of the Korea institute for structural maintenance and inspection
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• v.17 no.1
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• pp.1-9
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• 2013

In this study of Eccentric Braced Frames have identified the following target eccentricity on the length of the inelastic behavior of the reaction by calculating the correction factor by comparing it to the value suggested by the earthquake provided material for the rational design aims to There are. As a variable-length V-braced frame analysis model stations were set up. Eccentricity faults in the model according to the length stiffness ratio, the maximum amount of energy dissipation were analyzed base shear and multi-layered model of the reaction from the eccentricity correction factor calculated on the length of the building standards proposed by KBC 2009 in response eccentricity correction factor calculated from The length varies. does not have the same response modification factor was confirmed.

• Journal of the Korea Institute of Building Construction
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• v.20 no.5
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• pp.417-423
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• 2020

In order to reduce cooling and heating, which is 40% of the energy consumption of buildings, it is important to improve the insulation of the skin. In order to improve the existing insulation, research is being conducted to apply a vacuum insulation panel(VIP) to buildings. However, VIP cannot be repaired, so we considered the metal vacuum insulation panel. Since the core of the metal vacuum pressure and have low thermal conductivity, foam concrete is adopted. However, preliminary experiments confirmed that the time to reach 0.001torr differs depending on the amount and nature of the bubbles. This effect is determined by the type of foaming agent and the density of the bubble slurry, the vacuum delivery time is determined to be the optimum foam concrete conditions are necessary. Therfore, this study aims to present basic data applicable to core materials by measuring vacuum delivery time and thermal conductivity change according to the foaming agent type and foam slurry density of foam large concrete which is core material of metal vacuum insulation panel. Experimental results and analysis show that compressive strength can be used regardless of the type of foam, In terms of thermal conductivity, it is stable to use vegetable foaming agents at 0.9g/㎤ or less. In terms of the vacuum delivery time, the foaming agent appeared similar regardless of the type of foaming agent, but it is considered suitable to use vegetable foaming agent based on compressive strength and thermal conductivity.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.5
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• pp.379-387
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• 2016

The goal of this research is to identify the planning techniques of high-rise housing estates applying a smart green city concept in order to understand the necessity of integrating 'planning & building' planning techniques and 'smart system' planning techniques and to analyze the current status of application. For the research, firstl, the definition of smart green city was established and high-rise housing estates planning was categorized according to a three space hierarchy, seven planning directions and 17 major features through literature review. Second, 28 'planning & building' planning techniques and 'smart system' planning techniques were derived through literature review and FGI analysis. Last, four cases in Multi-functional Administrative City were analyzed for the current status of application of planning techniques. In conclusion, planning techniques in 'Transportation Network', 'Environment-friendly layout planning of housing', 'Revitalization of green transportation', 'Utilization of new & renewable energy', 'Crime prevention and accident reduction', 'Use of high performance, and efficiency facility' main feature were identified as important planning techniques for Smart Green City and its implications were estimated.

• Journal of the Korea Institute of Building Construction
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• v.19 no.2
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• pp.175-184
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• 2019

This paper presents a modeling prototype that optimizes construction processes implementing information communication technology (ICT). Using "IAMB", each and every actual steps of the construction process may be defined visually and explicitly by elaborating ICT to improve productivity and management efficiency. It contributes to identify the features on what parts of construction task are covered by ICT, and the effects of ICT on process performance. After analyzing 10 real project cases, ICT application types are classified into four categories according to ICT type, job functions that ICT applied, and the project phase in which ICT used. As a reuslt, it was confirmed that the positive outcomes on the construction process were beneficial to mostly the general contractors and mainly obtained by automated information processing, external consignment and consistent information use. Negative effects, which were occurred by mainly manual manipulation and duplication of information handling, were accrued to general contractors minimally, but to subcontractors maximally. Expert focus group commends that several important issues should be considered when implementing ICT.

• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.37-51
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• 2015

Due to the development of internet technology and the rapid increase of internet data, various studies are actively conducted on how to use and analyze internet data for various purposes. In particular, in recent years, a number of studies have been performed on the applications of text mining techniques in order to overcome the limitations of the current application of structured data. Especially, there are various studies on sentimental analysis to score opinions based on the distribution of polarity such as positivity or negativity of vocabularies or sentences of the texts in documents. As a part of such studies, this study tries to predict ups and downs of stock prices of companies by performing sentimental analysis on news contexts of the particular companies in the Internet. A variety of news on companies is produced online by different economic agents, and it is diffused quickly and accessed easily in the Internet. So, based on inefficient market hypothesis, we can expect that news information of an individual company can be used to predict the fluctuations of stock prices of the company if we apply proper data analysis techniques. However, as the areas of corporate management activity are different, an analysis considering characteristics of each company is required in the analysis of text data based on machine-learning. In addition, since the news including positive or negative information on certain companies have various impacts on other companies or industry fields, an analysis for the prediction of the stock price of each company is necessary. Therefore, this study attempted to predict changes in the stock prices of the individual companies that applied a sentimental analysis of the online news data. Accordingly, this study chose top company in KOSPI 200 as the subjects of the analysis, and collected and analyzed online news data by each company produced for two years on a representative domestic search portal service, Naver. In addition, considering the differences in the meanings of vocabularies for each of the certain economic subjects, it aims to improve performance by building up a lexicon for each individual company and applying that to an analysis. As a result of the analysis, the accuracy of the prediction by each company are different, and the prediction accurate rate turned out to be 56% on average. Comparing the accuracy of the prediction of stock prices on industry sectors, 'energy/chemical', 'consumer goods for living' and 'consumer discretionary' showed a relatively higher accuracy of the prediction of stock prices than other industries, while it was found that the sectors such as 'information technology' and 'shipbuilding/transportation' industry had lower accuracy of prediction. The number of the representative companies in each industry collected was five each, so it is somewhat difficult to generalize, but it could be confirmed that there was a difference in the accuracy of the prediction of stock prices depending on industry sectors. In addition, at the individual company level, the companies such as 'Kangwon Land', 'KT & G' and 'SK Innovation' showed a relatively higher prediction accuracy as compared to other companies, while it showed that the companies such as 'Young Poong', 'LG', 'Samsung Life Insurance', and 'Doosan' had a low prediction accuracy of less than 50%. In this paper, we performed an analysis of the share price performance relative to the prediction of individual companies through the vocabulary of pre-built company to take advantage of the online news information. In this paper, we aim to improve performance of the stock prices prediction, applying online news information, through the stock price prediction of individual companies. Based on this, in the future, it will be possible to find ways to increase the stock price prediction accuracy by complementing the problem of unnecessary words that are added to the sentiment dictionary.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.2
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• pp.91-108
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• 2022

In most cases, optical images have been used as training data of DL (Deep Learning) models for object detection, recognition, identification, classification, semantic segmentation, and instance segmentation. However, properties of 3D objects in the real-world could not be fully explored with 2D images. One of the major sources of the 3D geospatial information is DSM (Digital Surface Model). In this matter, characteristic information derived from DSM would be effective to analyze 3D terrain features. Especially, man-made objects such as buildings having geometrically unique shape could be described by geometric elements that are obtained from 3D geospatial data. The background and motivation of this paper were drawn from concept of the intrinsic image that is involved in high-level visual information processing. This paper aims to extract buildings after classifying terrain features by training DL model with DSM-derived information including slope, aspect, and SRI (Shaded Relief Image). The experiments were carried out using DSM and label dataset provided by ISPRS (International Society for Photogrammetry and Remote Sensing) for CNN-based SegNet model. In particular, experiments focus on combining multi-source information to improve training performance and synergistic effect of the DL model. The results demonstrate that buildings were effectively classified and extracted by the proposed approach.

• KIPS Transactions on Computer and Communication Systems
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• v.1 no.3
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• pp.143-150
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• 2012

A simulation methodology and corresponding program based on it is to be discussed for analyzing the effects of the networking operation of existing DHC system in connection with CHP system on-site. The practical simulation for arbitrary areas with various building compositions is carried out for the analysis of operational features in both systems, and the various aspects of thermal energy grids with connecting operation are highlighted through the detailed assessment of predicted results. The intrinsic operational features of CHP prime movers, gas engine, gas turbine etc., are effectively implemented by realizing the performance data, i.e. actual operation efficiency in the full and part loads range. For the sake of simplicity, a simple mathematical correlation model is proposed for simulating various aspects of change effectively on the existing DHC system side due to the connecting operation, instead of performing cycle simulations separately. The empirical correlations are developed using the hourly based annual operation data for a branch of the Korean District Heating Corporation (KDHC) and are implicit in relation between main operation parameters such as fuel consumption by use, heat and power production. In the simulation, a variety of system configurations are able to be considered according to any combination of the probable CHP prime-movers, absorption or turbo type cooling chillers of every kind and capacity. From the analysis of the thermal network operation simulations, it is found that the newly proposed methodology of mathematical correlation for modelling of the existing DHC system functions effectively in reflecting the operational variations due to thermal energy grids with connecting operation. The effects of intrinsic features of CHP prime-movers, e.g. the different ratio of heat and power production, various combinations of different types of chillers (i.e. absorption and turbo types) on the overall system operation are discussed in detail with the consideration of operation schemes and corresponding simulation algorithms.