• Korean Journal of Construction Engineering and Management
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• v.24 no.3
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• pp.12-19
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• 2023

In the case of the construction industry, the relationship between process and cost should be appropriately distributed so that the finished product can be delivered at the minimum fee within the construction period. At that time, it should be considered the size of the bridge, the construction method, the environment and production capacity of the factory, and the transport distance. However, due to various reasons that occur during the construction period, problems such as construction delay, construction cost increase, and quality and reliability degradation occur. Therefore, a systematic and scientific construction technique and process management technology are needed to break away from the conventional method. The prefab(Pre-Fabrication) is a representative OSC (Off-Site Construction) method manufactured in a factory and constructed onsite. This study develops a resource and process plan optimization system for the process management of the Nodular girder, a prefab bridge girder. A simulation algorithm develops to automatically test various variables in the personnel equipment mobilization plan to derive the optimal value. And, the algorithm was applied to the Paju-Pocheon Expressway Construction (Section 3) Dohwa 4 Bridge under construction, and the results compare. Based on construction work standard product calculation, actual input manpower, equipment type, and quantity were applied to the Activity Card, and the amount of work by quantity counting, resource planning, and resource requirements was reflected. In the future, we plan to improve the accuracy of the program by applying forecasting techniques including various field data.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.6 no.5
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• pp.367-377
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• 2016

The purpose of the projects for strengthening the Service Business Competitiveness, which had been sponsored by the Ministry of Trade, Industry and Energy, and managed by the NIPA, is to support for combining the whole business process of the SMEs with the business model considering the scientific aspects of the services, to enhance the productivity of them and to add the values of their activities. 5 organizations are selected in 2014, and 4 in 2015 as leading organizations for these projects. This study analyzed the efficiency of these projects using DEA. Throughout the analysis of the prior researches, this study used the amount of government-sponsored money as the input variable, and the number of new customer business, the sales revenue, and the number of new employment as the output variables. And the result of this analysis showed that the decision making unit 12, 15, and 21 was efficient. And from this study, we found out two more performance indicators such as, the number of new employment and the amount of sales revenue, besides the number of new customer businesses.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.129-148
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• 2023

Bitcoin is a blockchain technology-based digital currency that has been recognized as a representative cryptocurrency and a financial investment asset. Due to its highly volatile nature, Bitcoin has gained a lot of attention from investors and the public. Based on this popularity, numerous studies have been conducted on price and trend prediction using machine learning and deep learning. This study employed LSTM (Long Short Term Memory) and CNN (Convolutional Neural Networks), which have shown potential for predictive performance in the finance domain, to enhance the classification accuracy in Bitcoin price trend prediction. XAI(eXplainable Artificial Intelligence) techniques were applied to the predictive model to enhance its explainability and interpretability by providing a comprehensive explanation of the model. In the empirical experiment, CNN was applied to technical indicators and Google trend data to build a Bitcoin price trend prediction model, and the CNN model using both technical indicators and Google trend data clearly outperformed the other models using neural networks, SVM, and LSTM. Then SHAP(Shapley Additive exPlanations) was applied to the predictive model to obtain explanations about the output values. Important prediction drivers in input variables were extracted through global interpretation, and the interpretation of the predictive model's decision process for each instance was suggested through local interpretation. The results show that our proposed research framework demonstrates both improved classification accuracy and explainability by using CNN, Google trend data, and SHAP.

• Journal of Service Research and Studies
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• v.11 no.2
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• pp.67-77
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• 2021

This study is a study on the methodology of establishing an innovation strategy centering on the customer experience, which is essential in order to transform the existing collection and preservation-centered mutual aid company service into a visitor-centered service. To this end, we conducted literature research on environmental changes in the funeral industry from the perspective of service science and the significance and value of customer experiences within them, good customer experiences and bad customer experiences from the perspective of customer experience management. A study was conducted to present and prove a specific model. The customer experience-oriented innovation strategy of the funeral industry means to search for various alternatives that can reach the target state from the present state, focusing on the customer, and select the most appropriate transformation plan among them. As an effect of application, it was found that it is a source of differentiation by generating positive emotions to customers, and that customer experience data is highly helpful in making important decisions for the actual resource input of the parent company. This innovation model was presented, and its value was firstly proved by analyzing the difference from the existing evaluation method. Finally, as a result of analyzing the causal relationship through regression analysis using the customer experience measurement procedure, customer experience diagnosis/evaluation, customer experience innovation strategy, and cooperative company's performance as variables, the relationship proved to be significant.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.1C
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• pp.1-8
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• 2008

Recently, there have been many construction projects on soft ground with growth of industry and economy. Therefore foundation piles of abutments and(or) buildings had been suffering from a lot of stability problems of inordinary displacement due to lateral flow of soft ground. Although many researches about lateral flow have been carried out, it is still difficult to assess the mechanism of lateral flow in soft ground quantitatively. And reasonable design method for judgement of lateral flow occurrence in soft ground is not established yet. In this study, six PNN (Probabilistic Neural Network) models were developed according to input variables and database compiled from Korea and Japan for the judgment of lateral flow occurrence. PNN models were compared with present empirical methods. It was found that the developed PNN models can give more precise and reliable judgment of lateral flow occurrence than empirical methods.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.5B
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• pp.485-493
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• 2008

The Artificial Neural Network (ANN) model was suggested for predicting probability of precipitation (PoP) using RDAPS NWP model, observation at AWS and upper-air sounding station. The prediction work was implemented for flood season and the data period is the July, August of 2001 and June of 2002. Neural network input variables (predictors) were composed of geopotential height 500/750/1000 hPa, atmospheric thickness 500-1000 hPa, X & Y-component of wind at 500 hPa, X & Y-component of wind at 750 hPa, wind speed at surface, temperature at 500/750 hPa/surface, mean sea level pressure, 3-hr accumulated precipitation, occurrence of observed precipitation, precipitation accumulated in 6 & 12 hrs previous to RDAPS run, precipitation occurrence in 6 & 12 hrs previous to RDAPS run, relative humidity measured 0 & 12 hrs before RDAPS run, precipitable water measured 0 & 12 hrs before RDAPS run, precipitable water difference in 12 hrs previous to RDAPS run. The suggested ANN has a 3-layer perceptron (multi layer perceptron; MLP) and back-propagation learning algorithm. The result shows that there were 6.8% increase in Hit rate (H), especially 99.2% and 148.1% increase in Threat Score (TS) and Probability of Detection (POD). It illustrates that the suggested ANN model can be a useful tool for predicting rainfall event prediction. The Kuipers Skill Score (KSS) was increased 92.8%, which the ANN model improves the rainfall occurrence prediction over RDAPS.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.5A
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• pp.673-683
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• 2008

This study improved the existing method of using the longitudinal strain and concept of influence line to develop Bridge Weigh-in-Motion system without axle detector using the dynamic strain of the bridge girders and concrete slab. This paper first describes the considered algorithms of extracting passing vehicle information from the dynamic strain signal measured at the bridge slab, girders, and cross beams. Two different analysis methods of 1) influence line method, and 2) neural network method are considered, and parameter study of measurement locations is also performed. Then the procedures and the results of field tests are described. The field tests are performed to acquire training sets and test sets for neural networks, and also to verify and compare performances of the considered algorithms. Finally, comparison between the results of different algorithms and discussions are followed. For a PSC I-girder bridge, vehicle weight can be calculated within a reasonable error range using the dynamic strain gauge installed on the girders. The passing lane and passing speed of the vehicle can be accurately estimated using the strain signal from the concrete slab. The passing speed and peak duration were added to the input variables to reflect the influence of the dynamic interaction between the bridge and vehicles, and impact of the distance between axles, respectively; thus improving the accuracy of the weight calculation.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.2A
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• pp.93-102
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• 2010

The numerical analysis and safety assessment by construction stages were considered the essential examination particular in order to solving the unstability of long-span bridges in the middle a construction. When estimating structural response characteristics by the construction stage analysis of long-span bridges, the influence of the near-field ground motion (NFGM) would be evaluated as a critical factor for the seismic design because it indicates clearly different aspects from the existing input earthquake motion data. Therefore, this study re-examined the response aspect of long-span bridges considering NFGM characteristics based on the response spectrum result, and advanced the presented numerical analysis program by the related research for conducting the construction stage analysis and reliability assessment of long-span bridges efficiently. The excellency of various construction schemes was assessed using the time history analysis result of critical member considering NFGM characteristics. For evaluating quantitative safety level, the reliability analysis was conducted considering the influence of external uncertainties included in random variables, and presented the safety index and failure probability of the critical construction stage by NFGM characteristics. In addition, the reliability result was examined the influence of internal uncertainties using monte carlo simulation (MCS), and assessed the distribution aspect of the essential analysis result. It is expected that this study will provide the basic information for the construction safety improvement when performing seismic design of long-span bridges considering NFGM characteristics.

• 지역과문화
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• v.6 no.2
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• pp.77-104
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• 2019

This study examines the efficiency of using local cultural resources in local governments. The study does so by DEA(Data Envelope Analysis) using data from the year 2017 for 17 local governments in Korea. In addition, this study tries to estimate environmental efficiency of local cultural resources. For this, the 'Total Efficiency' including the output variables related to the local cultural resource environment was analyzed. After than It compared the 'Total Efficiency' with the 'Utilization Efficiency', to estimate the 'Environmental Efficiency' of local cultural resources. The followings are results which are significant statistically. Firstly, it was evaluated that five of the 17 local governments utilized the local cultural resources efficiently. Secondly, it was result that the inefficiency of the other local governments was relatively influenced by the economies of scale than PTE(Pure Technical Efficiency). Thirdly, It has been confirmed that environmental aspects such as cultural properties and cultural infrastructure have a considerable impact on the increase or decrease of efficiency in local governments. The difference in the efficiency of local governments are influenced by the population density. In order to improve the efficiency in the future, it is necessary to adjust the appropriate level of input according to the local population estimate, which is a major consumer of the local cultural resource utilization. In addition, the local festivals and village festivals held by local governments should be checked to improve in quality by eliminating inefficiencies. Also, it should be considered of environmental factors together, when analyzing the efficiency of the local cultural resource in local governments.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.7
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• pp.857-862
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• 2023

In order for an autonomous ship to arrive near the pier and automatically berth without the help of a tugboat or pilot, it is necessary to recognize the pier and calculate the thruster output and output angle for berthing to the pier at a fixed berthing speed under given external force conditions. Therefore, in this study, the external force and moment acting on the ship while berthing were analyzed, and the thruster output calculation for automatic berthing was designed and the basic concept for the development of the automatic berthing program was designed. The wind pressure applied to the hull by the wind while the ship is berthing was calculated based on the wind pressure area and the wind direction angle and the turning moment to rotate the ship according to the transverse force of the ship was calculated. Considering the force acting on the ship and the turning moment during berthing, a theoretical formula was presented to calculate the thruster output and output angle for berthing parallel to the pier, and the turning due to other variables was controlled by the PID controller. In addition, the basic concept for program development was presented by analyzing the input elements necessary for the theoretical formula.