• Journal of Practical Engineering Education
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• v.7 no.1
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• pp.57-66
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• 2015

While North-South cooperation (NSC) continues to play a considerably dominant role in international development cooperation efforts, there is growing criticisms across the world as to the role and effectiveness of the NSC to support the developing countries to meet their development needs. As such, South-South cooperation (SSC) has become a subject of discussion in recent years across the world in international development and has increasingly become popular as an effective aid modality. However, there is unavailability of sufficient empirical studies about the efficacy of the SSC in the context of Bangladesh. The present paper attempts to examine two KOICA's projects to facilitate HRD in ICT in Bangladesh taking into consideration of Korea as a southern country. The study revealed that Korea's bilateral development cooperation efforts have been effective so far to fulfill their objectives. The findings of the study put forward that SSC may work in the form of technical cooperation to support the developing countries, provided that technical cooperation is demand-driven, and that there is sufficient level of absorptive capacity and supportive policy as well on the part of developing partner country to utilize external skills and technology.

• Journal of Construction Engineering and Project Management
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• v.7 no.2
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• pp.19-33
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• 2017

Various forms of procurement are open to companies when constructing new owner-occupied properties. The selection of a form of procurement is an important decision-making problem for companies and their Corporate Real Estate Management (CREM) departments. With this in mind, a decision support tool has been developed to optimise the outcome and success of company's proposed real estate development projects and is presented in this paper. This model can also be used for current real estate portfolios to optimise returns in the long term. In pursuit of this objective and in order to provide an academic basis for this study, decision-relevant goals and parameters were initially identified from the referenced literature used in our research. These were subsequently evaluated in a case study of a corporate development project and identified as specific decision criteria from the perspective of the CREM. The investigation identified 15 criteria that are relevant to the corporate decision-making process in procuring and/or developing property. A model for supporting and resolving decision-making problems of this type was derived from decision theory. In this paper, a decision-making tool is presented that takes into account all the decision criteria from the CREM point of view for the first time. This model should therefore serve as an aid in implementing the decision-making process for the development of real estate projects in a more structured and transparent manner.

• International Journal of Naval Architecture and Ocean Engineering
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• v.8 no.2
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• pp.177-187
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• 2016

To evaluate the tractive performance of tracked trencher on seafloor surface, a new shear stress-displacement empirical model was proposed for saturated soft-plastic soil (SSP model). To validate the SSP model, a test platform, where track segment shear test can be performed in seafloor soil simulacrum (bentonite water mixture), was built. Series shear tests were carried out. Test results indicate that the SSP model can describe the mechanical behavior of track segment with good approximation in seafloor soil simulacrum. Through analyzing the main external forces applied to seafloor tracked trencher during the uniform linear trenching process, a drawbar pull prediction model was deduced with the SSP model. A tracked walking mechanism of the seafloor tracked trencher prototype was built, and verification tests were carried out. Test results indicate that this prediction model was feasible and effective; moreover, from another side, this conclusion also proved that the SSP model was effective.

• Nuclear Engineering and Technology
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• v.49 no.2
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• pp.426-433
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• 2017

This paper describes the development process, the innovative techniques used and insights gained from the latest integrated, full scope, multistate Level 2 PSA analysis conducted at the Leibstadt Nuclear Power Plant (KKL), Switzerland. KKL is a modern single-unit General Electric Boiling Water Reactor (BWR/6) with Mark III Containment, and a power output of $3600MW_{th}/1200MW_e$, the highest among the five operating reactors in Switzerland. A Level 2 Probabilistic Safety Assessment (PSA) analyses accident phenomena in nuclear power plants, identifies ways in which radioactive releases from plants can occur and estimates release pathways, magnitude and frequency. This paper attempts to give an overview of the advanced modeling techniques that have been developed and implemented for the recent KKL Level 2 PSA update, with the aim of systematizing the analysis and modeling processes, as well as complying with the relatively prescriptive Swiss requirements for PSA. The analysis provides significant insights into the absolute and relative importances of risk contributors and accident prevention and mitigation measures. Thanks to several newly developed techniques and an integrated approach, the KKL Level 2 PSA report exhibits a high degree of reviewability and maintainability, and transparently highlights the most important risk contributors to Large Early Release Frequency (LERF) with respect to initiating events, components, operator actions or seismic component failure probabilities (fragilities).

• Journal of Korean Society of Industrial and Systems Engineering
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• v.28 no.3
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• pp.133-141
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• 2005

The previous research has been mainly focused on individual technology of voice recognition, voice synthesis, translation, and bone transmission technical. Recently, commercial models have been produced using aforementioned technologies. In this research, a new automated translation support system concept has been proposed by combining established technology of bone transmission and wireless system. The proposed system has following three major components. First, the hybrid system consist of headset, bone transmission and other technologies will recognize user's voice. Second, computer recognized voice (using small server attached to the user) of the user will be converted into digital signal. Then it will be translated into other user's language by translation algorithm. Third, the translated language will be wirelessly transmitted to the other party. The transmitted signal will be converted into voice in the other party's computer using the hybrid system. This hybrid system will transmit the clear message regardless of the noise level in the environment or user's hearing ability. By using the network technology, communication between users can also be clearly transmitted despite the distance.

• Journal of the Korea Institute of Military Science and Technology
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• v.22 no.4
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• pp.509-516
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• 2019

It is well known that nitroglycerin(NG) may evaporate and migrate from the triple base propellant grains in storage. This physical process makes it double base environment to the CCC(combustible cartridge case) which is based on nitrocellulose(NC) without NG. Meanwhile, it is not appropriate to use diphenylamine(DPA) as a stabilizer for CCC in this double base environment because of incompatibility between DPA and NG. So we estimated the shelf life to study the effect of NG migration from propellant to CCC by following the procedures in the STANAG 4257. And we found out that CCC with ethylcentralite(ECL) has 7.5 years longer shelf life than with DPA, when NG migrates to CCC from triple base propellant grains.

• Journal of the Korea Society of Computer and Information
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• v.27 no.10
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• pp.59-66
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• 2022

This research conducted a study classifying gender of speakers by analyzing feature vectors extracted from the voice data. The study provides convenience in automatically recognizing gender of customers without manual classification process when they request any service via voice such as phone call. Furthermore, it is significant that this study can analyze frequently requested services for each gender after gender classification using a learning model and offer customized recommendation services according to the analysis. Based on the voice data of males and females excluding blank spaces, the study extracts feature vectors from each data using MFCC(Mel Frequency Cepstral Coefficient) and utilizes SVM(Support Vector Machine) models to conduct machine learning. As a result of gender classification of voice data using a learning model, the gender recognition rate was 94%.

• International Journal of Computer Science & Network Security
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• v.23 no.9
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• pp.37-46
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• 2023

The main aim of the article is to solve the problem of automating price monitoring using marketing forecasting methods and Excel functionality under martial law. The study used the method of algorithms, trend analysis, correlation and regression analysis, ANOVA, extrapolation, index method, etc. The importance of monitoring consumer price developments in market pricing at the macro and micro levels is proved. The introduction of a Dummy variable to account for the influence of martial law in market pricing is proposed, both in linear multiple regression modelling and in forecasting the components of the Consumer Price Index. Experimentally, the high reliability of forecasting based on a five-factor linear regression model with a Dummy variable was proved in comparison with a linear trend equation and a four-factor linear regression model. Pessimistic, realistic and optimistic scenarios were developed for forecasting the Consumer Price Index for the situation of the end of the Russian-Ukrainian war until the end of 2023 and separately until the end of 2024.

• International Journal of Advanced Culture Technology
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• v.12 no.2
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• pp.167-179
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• 2024

This study addresses the challenge of objectively evaluating the performance of early-stage startups amidst limited information and uncertainty. Focusing on companies selected by TIPS, a leading private sector-driven startup support policy in Korea, the research develops a new indicator to assess technological efficiency. By analyzing various input and output variables collected from Crunchbase and KIND (Korea Investor's Network for Disclosure System) databases, including technology use metrics, patents, and Crunchbase rankings, the study derives technological efficiency for TIPS-selected startups. A prediction model is then developed utilizing machine learning techniques such as Random Forest and boosting (XGBoost) to classify startups into efficiency percentiles (10th, 30th, and 50th). The results indicate that prediction accuracy improves with higher percentiles based on the technical efficiency index, providing valuable insights for evaluating and predicting startup performance in early markets characterized by information scarcity and uncertainty. Future research directions should focus on assessing growth potential and sustainability using the developed classification and prediction models, aiding investors in making data-driven investment decisions and contributing to the development of the early startup ecosystem.

• The Journal of Economics, Marketing and Management
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• v.6 no.1
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• pp.17-24
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• 2018

Purpose - Major countries in the world continue to grow up without employment by the economy opening, more investment in foreign countries and technical innovation. Nevertheless, SMEs have job creation continuously. As this result, support for SMEs that is the source of job creation has increased attention. However, previous research between SMEs and job-creating is limited to the job creation effect of comparing with large companies, and R&D investment effect including government support. Also, many research provides the different result of correlation with technology innovation and job creation. Therefore, previous research has insufficient to explain job creation by which in the technology commercialization stage and the job-specific workforce. Research design, data, and Methodology - This study investigated the impact of customized R&D support upon job creation by using questionnaires of SMEs R&D service of K-Institution from 2009 to 2013. In detail, we analyzed the relationship between the technology commercialization stage and the usefulness of customized R&D support. Also, we added the analyzed the relationship between the usefulness of customized R&D support and the job-specific workforce. Results - Research result, Job creation had a significant relation to the usefulness of customized R&D support in product design stage and mass production stage. Also, R&D worker and production worker correlated with the usefulness of customized R&D support. These results indicate the importance of hiring R&D workers and production workers at the higher technology readiness. Conclusions -Therefore, this study suggests some implications for the government's SMEs support policy and the solve employment problems such as youth unemployment.