• Korean Security Journal
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• no.15
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• pp.147-171
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• 2008

This study examines the degrees of criminal investigators' job satisfaction and organizational commitment and investigates which factors determine the variations in them. In the first step of analysis, independent variables of criminal investigators' job satisfaction consist of work itself, achievement, responsibility, safety, stability, interpersonal relations, recognition, supervision, and opportunity of growth. In the second step, job satisfaction is a mediating variable and organizational commitment is a defendant variable. Organizational commitment is classified into three types - "affective", "continuance" and "normative". According to the structural equation model analysis, responsibility has a great influence on job satisfaction, and job satisfaction affects affective commitment and continuance commitment. This study suggests that job satisfaction should be increased to improve criminal investigators' organizational commitment. And responsibility is necessary for the improvement of job satisfaction. Despite the professional detective system operating in Korea since January 1, 2005, the level of criminal investigators' recognitions of safety, stability and opportunity of growth turn out to be low. Based on these findings, this study presents four ways to reform measures which are listed below. First, to improve a! n economical circumstance of criminal investigators, any expense associated with criminal investigation should be paid by organizations. Second, to improve safety of criminal investigators, it is necessary to develop and supply enough police equipments. Third, criminal investigators' working hours should be shorten. Fourth, to improve criminal investigators' responsibilities, criminal investigators should be allowed to conduct criminal investigation independently from the prosecution.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.5
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• pp.113-120
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• 2020

Safety accidents, called industrial accidents in construction work, are causing a lot of casualties, property damage and social controversy in the event of an accident, causing the construction to lose public confidence. The risk of safety accidents at construction sites may continue to increase as the construction of high-rise, large-scale, and multi-purpose complex buildings has increased in recent years. In particular, the most frequently constructed apartment construction among reinforced concrete buildings is designed and constructed with a wall-like structure with no beams for each floor, while the lower floors are made of lamen with columns and beams. As a result, the transfer beam or transfer slab to withstand the upper load is installed on the upper part of the Ramen structure, so the system Dongbari, which is installed as a temporary material during concrete laying construction, may collapse at any time during plowing and curing. The purpose of this study is to apply IT convergence technology to prevent the collapse of the system Dongbari during concrete installation, and to apply many of the variables that may occur during construction on a case-by-case basis to check the stability of the system Dongbari and to propose a model of the anti-conducting prediction system.

• Journal of the Korean Society of Safety
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• v.20 no.4 s.72
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• pp.171-179
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• 2005

It is essential to understand the role of wall lining materials when they are exposed to a fire from an ignition source. Full-scale test methods permit an assessment of the performance of a wall lining material. Fire growth models have been developed due to the costly expense associated with full-scale testing. The models require heat flux maps from the ignition burner flame as input data. Work to date was impeded by a lack of detailed spatial characterization of the heat flux maps due to the use of limited instrumentation. To increase the power of fire modeling, accurate and detailed heat flux maps from the ignition burner are essential. High level spatial resolution for surface temperature can be provided from an infrared camera. The objective of this study was to develop a heat flux mapping procedure for a room test burner flame to a wall configuration with surface temperature information taken from an infrared camera. A prototype experiment was performed using the ISO 9705 test burner to demonstrate the developed heat flux mapping procedure. The results of the experiment allow the heat flux and spatial resolutions of the method to be determined and compared to the methods currently available.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.127-146
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• 2017

Services using artificial intelligence have begun to emerge in daily life. Artificial intelligence is applied to products in consumer electronics and communications such as artificial intelligence refrigerators and speakers. In the financial sector, using Kensho's artificial intelligence technology, the process of the stock trading system in Goldman Sachs was improved. For example, two stock traders could handle the work of 600 stock traders and the analytical work for 15 people for 4weeks could be processed in 5 minutes. Especially, big data analysis through machine learning among artificial intelligence fields is actively applied throughout the financial industry. The stock market analysis and investment modeling through machine learning theory are also actively studied. The limits of linearity problem existing in financial time series studies are overcome by using machine learning theory such as artificial intelligence prediction model. The study of quantitative financial data based on the past stock market-related numerical data is widely performed using artificial intelligence to forecast future movements of stock price or indices. Various other studies have been conducted to predict the future direction of the market or the stock price of companies by learning based on a large amount of text data such as various news and comments related to the stock market. Investing on commodity asset, one of alternative assets, is usually used for enhancing the stability and safety of traditional stock and bond asset portfolio. There are relatively few researches on the investment model about commodity asset than mainstream assets like equity and bond. Recently machine learning techniques are widely applied on financial world, especially on stock and bond investment model and it makes better trading model on this field and makes the change on the whole financial area. In this study we made investment model using Support Vector Machine among the machine learning models. There are some researches on commodity asset focusing on the price prediction of the specific commodity but it is hard to find the researches about investment model of commodity as asset allocation using machine learning model. We propose a method of forecasting four major commodity indices, portfolio made of commodity futures, and individual commodity futures, using SVM model. The four major commodity indices are Goldman Sachs Commodity Index(GSCI), Dow Jones UBS Commodity Index(DJUI), Thomson Reuters/Core Commodity CRB Index(TRCI), and Rogers International Commodity Index(RI). We selected each two individual futures among three sectors as energy, agriculture, and metals that are actively traded on CME market and have enough liquidity. They are Crude Oil, Natural Gas, Corn, Wheat, Gold and Silver Futures. We made the equally weighted portfolio with six commodity futures for comparing with other commodity indices. We set the 19 macroeconomic indicators including stock market indices, exports & imports trade data, labor market data, and composite leading indicators as the input data of the model because commodity asset is very closely related with the macroeconomic activities. They are 14 US economic indicators, two Chinese economic indicators and two Korean economic indicators. Data period is from January 1990 to May 2017. We set the former 195 monthly data as training data and the latter 125 monthly data as test data. In this study, we verified that the performance of the equally weighted commodity futures portfolio rebalanced by the SVM model is better than that of other commodity indices. The prediction accuracy of the model for the commodity indices does not exceed 50% regardless of the SVM kernel function. On the other hand, the prediction accuracy of equally weighted commodity futures portfolio is 53%. The prediction accuracy of the individual commodity futures model is better than that of commodity indices model especially in agriculture and metal sectors. The individual commodity futures portfolio excluding the energy sector has outperformed the three sectors covered by individual commodity futures portfolio. In order to verify the validity of the model, it is judged that the analysis results should be similar despite variations in data period. So we also examined the odd numbered year data as training data and the even numbered year data as test data and we confirmed that the analysis results are similar. As a result, when we allocate commodity assets to traditional portfolio composed of stock, bond, and cash, we can get more effective investment performance not by investing commodity indices but by investing commodity futures. Especially we can get better performance by rebalanced commodity futures portfolio designed by SVM model.

• Asia pacific journal of information systems
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• v.19 no.3
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• pp.151-179
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• 2009

The purpose of this study is to make an empirical analysis on the factors affecting the intention for the continuous use of the BSC system, which has been recently spread in the public sector. Because the object of acceptance is the performance management system based on BSC (Balanced Scorecard) implemented in the form of information systems, this study proposes a research model by applying TAM (Technology Acceptance Model). Independent variables are factors affecting the acceptance of BSC system such as training, communication, IS support, CEO support and personal innovativeness, and we examine their effects on the dependent variable, namely, intention on continuous use via mediating variables: perceived usefulness and perceived ease of use. A questionnaire survey was conducted with public institutions(firms) that had introduced and were operating the BSC system; 264 valid questionnaires are adopted. Collected data are analyzed using SPSS 16.0 and AMOS 7.0. Results of reliability test show that all analyzed data are reliable. In validity test, one item regarding communication was excluded; 9 latent variables and 34 observed variables are used in the final analysis. Based on the results of the hypothesis test through path analysis using a structural equation model, 10 out of 16 hypotheses are accepted. Factors affecting perceived usefulness are training and IS(Information System) support. The analysis results indicate that perceived ease of use is mainly affected by IS support, CEO support, and personal innovativeness among the factors related to the acceptance of the BSC system. This suggests that, contrary to the expectation that the BSC system may be used without difficulty, the management's active support is required in order to attain expected improvement in productivity and work efficiency. This was also pointed out in case studies on the construction of the BSC system in public sectors. On the other hand, perceived ease of use is found to affect perceived usefulness. This supports the results of previous researches on TAM. Perceived ease of use and perceived usefulness are found to affect the attitude towards the use of the system. The intention on continuous use is affected more by perceived usefulness than by the attitude towards the use of system. This result supports the results of previous researches on TAM, showing that the BSC system is utilized substantially in worksites. This study is considered meaningful in that it was actually performed on users at public institutions(firms) that had introduced the BSC system and that it empirically tested hypotheses on the acceptance of the BSC system by applying TAM to the research model.

• Korean Journal of Social Welfare
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• v.57 no.4
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• pp.225-251
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• 2005

This study examines the changing paradigm of family welfare policy and tries to find an appropriate model for the delivery system of family welfare service. First, the study reviews the contexts of family policy in new paradigm, and traces the changing process of family welfare-related administration from the ministry of human and health to the ministry of family and gender equality. Second, the study examines the principles of the delivery system for family welfare service to pursue the advancement of family policy. In conclusion, it proposes an alternative model for the successful settlement into community of family welfare delivery system, and a desirable position and role of family support center. The principles of the delivery system of family welfare service is fundamentally to make family policy come realistic, such as strengthening family stability through the harmonic reconciliation of work and family, preventing any forms of families from social safety net, and securing happy lives. Comprehensiveness, continuity, effectiveness, and accessibility of the system are also needed. In particular, family support center, recently very controversial, could be better as a representative council of networking various kinds of community organizations in the fields of family welfare enhancement, rather than organization of direct service provision, such as family counselling, education and therapy. Finally, an alternative model of delivery system for family welfare service is presented.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.11 no.1
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• pp.9-16
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• 1991

The concept of damage is all-pervasive in structural engineering. It can be considered a state variable and defined to vary from 0(no damage) to 1(failure). Thus, the factor of safety against failure, the most important aspect of a structure, cannot be assessed without evaluating the damageability of a structure under load. It is the objective of the research reported herein to study the behavior of concrete under repeated load applications. Concrete is known to deteriorate under such loading, i.e., it suffers damage of increasing degree. Its response to future loading is a function of the amount of damage sustained during previous load exposures. The same can be said about reinforced concrete members and entire structures, but here we wish to consider only plain concrete and express some of its material properties as functions of the degree of sustained damage. The work described herein is based on the stipulation that the energy dissipation capacity of plain concrete is a material property and the damage accumulates in direct proportion to the degree to which the energy dissipation capacity is being exhausted, in some analogy to both high- and low-cycle failure behavior of materials.

• Steel and Composite Structures
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• v.24 no.2
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• pp.227-237
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• 2017

This paper presents optimization of a long-span portal steel frame under dynamic wind loads using a surrogate-assisted evolutionary algorithm. Long-span portal steel frames are often used in low-rise industrial and commercial buildings. The structure needs be able to resist the wind loads, and at the same time it should be as light as possible in order to be cost-effective. In this work, numerical model of a portal steel frame is constructed using structural analysis program (SAP2000), with the web-heights at five locations of I-sections of the columns and rafters as the decision variables. In order to evaluate the performance of a given design under dynamic wind loading, the equivalent static wind load (ESWL) is obtained from a database of wind pressures measured in wind tunnel tests. A modified formulation of the problem compared to the one available in the literature is also presented, considering additional design constraints for practicality. Evolutionary algorithms (EA) are often used to solve such non-linear, black-box problems, but when each design evaluation is computationally expensive (e.g., in this case a SAP2000 simulation), the time taken for optimization using EAs becomes untenable. To overcome this challenge, we employ a surrogate-assisted evolutionary algorithm (SAEA) to expedite the convergence towards the optimum design. The presented SAEA uses multiple spatially distributed surrogate models to approximate the simulations more accurately in lieu of commonly used single global surrogate models. Through rigorous numerical experiments, improvements in results and time savings obtained using SAEA over EA are demonstrated.

• Journal of Energy Engineering
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• v.11 no.3
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• pp.237-246
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• 2002

If the safety depressurization system of APR-1400, the Korean next generation reactor, is in operation, water, air and steam are successively discharging into a in-containment refueling water storage tank through spargers. Among the phenomena occurring during the discharging processes, the air bubble clouds produce a low-frequency and high-amplitude oscillatory loading, which may result in the most significant damages to the submerged structures if the oscillation frequency is the same or close to the natural frequency of the structures. The involved phenomena are so complicated that most of the prediction of frequency and pressure loads has been resorted to experimental work and computational approach has been precluded. This study deals with a numerical simulation on the behavior of air bubble clouds discharging into a water pool through a sparger, by using a commercial thermal hydraulic analysis code, FLUENT, version 4.5. Among the multiphase flow models, the VOF (Volume Of Fluid) model was selected to simulate the water, air and steam flows. A satisfactory result was obtained comparing the analysis results with the ABB-Atom test results which had been performed for the development of sparser.

• Journal of the Korean Society of Industry Convergence
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• v.20 no.5
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• pp.359-364
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• 2017

A machine such as bean crusher machine is subjected to different loads and vibration. Due to this vibration there will be certain deformations which affect the performance of the machine in adverse manner. This paper proposed a vibration analysis of bean crusher machine using ANSYS. The Finite Element Method (FEM) analysis is carried out to study the effect of vibration on the structure in order to ensure the safety. This work helps the machine developer make a better product at the early design stage with lower cost and faster development time. To do this, firstly, using Inventor, a CAD model is prepared. Secondly, the analysis is to be carried out using ANSYS 15. The modal analysis and random vibration analysis of the structure was conducted. The analysis shows that the proposed design was successfully shows the minimum deformation when the vibration was applied in normal condition.