The expansionary monetary policy was practiced after 2001 in Japan to treat the deflation spiral, and reduced only the nominal interest rates and domestic household demand. One of the most serious factors for this failure was the change of private sector's expectancy. This paper has studied the effect of Japanese monetary policy in 21c., with empirical research based on a renewed macroeconomic model and the VAR. The empirical analysis shows that the effect of monetary policy on the national income during 2001.01-2015.03 is weaker than that of 1985.01-1994.04. Money volume has a diminutive effect on the growth of GDP within a short term after 2001. The change in the expectations of the private sectors might have been the cause of ineffectiveness of the expansive monetary policy. Economic agents learned from the past Japanese financial crisis that an expansive monetary policy increased the inflation rate and caused the 'bubbles to burst' afterwards. The VAR analysis says that the effectiveness of monetary policy on the economic depression declined over the past 20 years and the expansion of money volume has no influence on exchange rate and net export. This means that the expansive monetary policy lost its effect on net export and national income steadily. Monetary policy makers have to recognize this fact, and to consider another anti-cycle political instrument, i.e. the fiscal policy with government debt.
Journal of the Korean Society of Marine Environment & Safety
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v.27
no.1
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pp.53-59
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2021
The marine transport industry generally applies new technologies later than other transport industries, such as airways and railways. Vessels require efficient operation, and their performance and lifespan depend on the level of maintenance and management. Many studies have shown that corrective maintenance (CM) and time-based maintenance (TBM) have restrictions with respect to enabling efficient maintenance of workload and cost to improve operational efficiency. Predictive maintenance (PdM) is an advanced technology that allows monitoring the condition and performance of a target machine to predict its time of failure and helps maintain the key machinery in optimal working conditions at all times. This study presents the development of a marine predictive maintenance (MPdM; maritime predictive maintenance) method based on applying PdM to the marine environment. The MPdM scheme is designed by considering the special environment of the marine transport industry and the extreme marine conditions. Further, results of the study elaborates upon the concept of MPdM and its necessity to advancing marine transportation in the future.
Purpose - Offshoring has emerged as one of the major trends in international trade and has become one of the strategies for achieving competitiveness in the global market. In spite of this, the expected gains of offshoring can be offset by hidden costs and risks, such as those associated with the COVID-19 pandemic, the trade war between the USA and China, and the ongoing trade dispute between Korea and Japan. To obviate such business failure and prevent critical business blunders, offshoring strategies that efficiently consider both risk elements and potential wealth creation are urgently need. The first purpose of this study is to contribute to the development of more advanced offshoring strategies to help host countries select the best locations to manage supply chain risks and create unique value. The second purpose is to specifically analyze the current status of Korea and provide Korean companies with implications to be considered when deciding whether to offshore or re-shore. Design/methodology - A Network DEA model was applied to measure the comparative location efficiency of national competencies for offshoring strategy from perspectives of wealth creation opportunities (profitability and marketability) and supply chain risk management. The location efficiencies are compared among a total 70 countries selected from the Global Competitiveness Index (GCI) and globally attractive locations outlined by Kearney (2017). For the secondary analysis of efficiency, a t-test examining the nature of competitive advantage and the level of sophistication in production processes was implemented in three divisions. We then analyzed differences in offshoring performance in terms of the identified national traits. Moreover, Tobit regression analysis is conducted to investigate the correlation between value-added business activities and each divisional efficiency, seeking to determine how each degree of value-added business activity influences the increase in offshoring productivity. Findings - Regarding overall location efficiency for offshoring performance, only the USA and Italy were identified as being efficient as host countries for offshoring, under circumstances of advanced development, such as productivity and risk management. Korea ranks 13th among 70 countries. The determinants of national competitiveness depend on national traits (the nature of competitive advantage and business sophistication). Countries with labor/resource advantages and labor-intensive industries are more competitive in terms of marketability than others. In contrast, countries with strong technology-intensive industries benefit offshoring companies, particularly in the technology sector, with the added advantage of supply chain risk management. As the perception of a value chain is broader in a country, it can achieve both production sophistication and competitive advantages such as marketability and SCRM. Originality/value - Existing studies focus on offshoring effectiveness from a company perspective. This paper contributes to comparing country efficiency in producing core competencies related to an offshoring strategy and also segments countries into three performance-based considerations associated with the global offshoring market. It also details Korea's position as an offshoring location according to national efficiency and competency.
Asia-Pacific Journal of Business Venturing and Entrepreneurship
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v.16
no.6
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pp.269-285
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2021
As the systematic management of knowledge within an organization is recognized as a core factor for the continuous growth of an organization, organizations are increasing their interest in knowledge management. Knowledge management requires the active sharing of knowledge by insiders of the organization, but there are cases of failure due to the lack of participation of leaders and employees of the organization. The purpose of this study is to suggest a mechanism by which the authentic leadership of leaders in small and medium-sized enterprises(SME), which are relatively lacking in knowledge production capacity, leads to intention to share knowledge of employees. In addition, the study confirms that reciprocal feedback and task interdependence moderate the relationship between antecedent factors and intention to share knowledge. In this study, a research model was derived based on precedent research, and 272 samples were obtained by conducting a questionnaire survey on employees of SME that introduced a knowledge management policy. And, the study verified the hypothesis by applying structural equation modeling based on AMOS 22.0. The results of the study proved that authentic leadership has a positive effect on the intention to share knowledge through organization identification and organization commitment, and confirmed that reciprocal feedback and work interdependence moderate the relationship between knowledge sharing intentions and antecedent factors. This study suggests the mechanism by which the authentic behavior of the leaders of SMEs affects the knowledge sharing behavior of employees, and suggests that work cooperation strengthens the influence of the mechanism.
Kim, Ji Eun;Kim, Min Ji;Choi, Sijung;Lee, Joo-Heon;Kim, Tae-Woong
Journal of Korea Water Resources Association
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v.55
no.8
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pp.589-601
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2022
Although drought is a natural phenomenon, its damage occurs in combination with regional physical and social factors. Especially, related to the supply and demand of various waters, drought causes great socio-economic damage. Even meteorological droughts occur with similar severity, its impact varies depending on the regional characteristics and water supply system. Therefore, this study assessed regional drought risk considering regional socio-economic factors and water supply system. Drought hazard was assessed by grading the joint drought management index (JDMI) which represents water shortage. Drought vulnerability was assessed by weighted averaging 10 socio-economic factors using Entropy, Principal Component Analysis (PCA), and Gaussian Mixture Model (GMM). Drought response capacity that represents regional water supply factors was assessed by employing Bayesian networks. Drought risk was determined by multiplying a cubic root of the hazard, vulnerability, and response capacity. For the drought hazard meaning the possibility of failure to supply water, Goesan-gun was the highest at 0.81. For the drought vulnerability, Daejeon was most vulnerable at 0.61. Considering the regional water supply system, Sejong had the lowest drought response capacity. Finally, the drought risk was the highest in Cheongju-si. This study identified the regional drought risk and vulnerable causes of drought, which is useful in preparing drought mitigation policy considering the regional characteristics in the future.
I intended to discuss the new phase of the publicness of museums in a digital environment with the Goole Arts & Culture Project. To this end, I critically examined the instrumental approaches and technological optimism in the application of digital technology to museums, and scrutinized the recent museological issues, particularly the revision or curtailment of the museum's publicness amid the spread of neoliberal policy, which have been omitted within those technological approaches. This is because the meaning of Google Art & Culture can be considered more effectively through an extended theoretical reconstruction. Based on these theoretical discussions, I critically reviewed how the "non-profit," an important concept that defines the publicness of museums, was adopted and utilized as an business strategy by Google. As a result, I wanted to reveal that the neoliberalization of museums, the failure of the government's public function, the crisis of museum's publicness, and Google's "non-profit" strategy have been closely related. Armed with advanced digital technology, the GAC project appropriated the publicness of museums as a useful profit-making model. As such, now the concept of publicness of museums is at a point of more controversial and radical transformation than ever before.
Maglev rail joints are vital components serving as connections between the adjacent F-type rail sections in maglev guideway. Damage to maglev rail joints such as bolt looseness may result in rough suspension gap fluctuation, failure of suspension control, and even sudden clash between the electromagnets and F-type rail. The condition monitoring of maglev rail joints is therefore highly desirable to maintain safe operation of maglev. In this connection, an online damage detection approach based on three-dimensional (3D) convolutional neural network (CNN) and time-frequency characterization is developed for simultaneous detection of multiple damage of maglev rail joints in this paper. The training and testing data used for condition evaluation of maglev rail joints consist of two months of acceleration recordings, which were acquired in-situ from different rail joints by an integrated online monitoring system during a maglev train running on a test line. Short-time Fourier transform (STFT) method is applied to transform the raw monitoring data into time-frequency spectrograms (TFS). Three CNN architectures, i.e., small-sized CNN (S-CNN), middle-sized CNN (M-CNN), and large-sized CNN (L-CNN), are configured for trial calculation and the M-CNN model with excellent prediction accuracy and high computational efficiency is finally optioned for multiple damage detection of maglev rail joints. Results show that the rail joints in three different conditions (bolt-looseness-caused rail step, misalignment-caused lateral dislocation, and normal condition) are successfully identified by the proposed approach, even when using data collected from rail joints from which no data were used in the CNN training. The capability of the proposed method is further examined by using the data collected after the loosed bolts have been replaced. In addition, by comparison with the results of CNN using frequency spectrum and traditional neural network using TFS, the proposed TFS-CNN framework is proven more accurate and robust for multiple damage detection of maglev rail joints.
Kim, Uiseok;Kim, Junghoon;Kim, Jiyoon;Min, Byungchan;Choi, Hangseok
Journal of the Korean GEO-environmental Society
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v.22
no.12
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pp.5-13
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2021
Expandable steel pipe piles have been developed to ensure stability and reduce construction costs during underground floor remodeling and extension work. Expandable steel pipe piles are more economical and stable than micropiles. Extensible steel pipe pile is a method of improving the performance of steel pipes by expanding steel pipes underground. In this paper, the changes in buckling strength according to the shape of steel pipes in an extended steel pipe pile were identified, a numerical analysis model was developed to determine the expended part effect of bumps due to steel pipe expansion, and the optimal steel pipe expansion was calculated through material tests. The larger the expansion diameter of the steel pipe and the greater the number of expanded part, the greater the buckling strength. Numerical results showed that the number of expanded part has a greater effect on buckling strength than the expansion rate. When the expansion rate is more than 1.2 times, it can be seen that as the number of expanded part increases, the effect of increasing buckling strength increases significantly. It was also noted that the expanded part effect of the bumps occur significantly when the extension angle is less than 45° and the expansion rate is 1.3 times higher. When the steel pipe is failure, the expanded rate is 20 to 32%, averaging 25.4%. Through the material test, it was analyzed that it is desirable to limit the maximum expansion rate for performing steel pipes to 16%.
The Journal of The Korea Institute of Intelligent Transport Systems
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v.21
no.5
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pp.171-182
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2022
The safe use of a structure requires it to be maintained in an undamaged state. Thus, a typical factor that determines the safety of a structure is a crack in it. In addition, cracks are caused by various reasons, damage the structure in various ways, and exist in different shapes. Making matters worse, if these cracks are unattended, the risk of structural failure increases and proceeds to a catastrophe. Hence, recently, methods of checking structural damage using deep learning and computer vision technology have been introduced. These methods usually have the premise that there should be a large amount of training image data. However, the amount of training image data is always insufficient. Particularly, this insufficiency negatively affects the performance of deep learning crack detection algorithms. Hence, in this study, a method of augmenting crack image data based on the image translation technique was developed. In particular, this method obtained the crack image data for training a deep learning neural network model by transforming a specific case of a asphalt crack image into a concrete crack image or vice versa . Eventually, this method expected that a robust crack detection algorithm could be developed by increasing the diversity of its training data.
Byeong A Yoo;Su Jin Kwon;Yu-Mi Im;Dong-Hee Kim;Eun Seok Choi;Bo Sang Kwon;Chun Soo Park;Tae-Jin Yun
Journal of Chest Surgery
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v.56
no.3
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pp.155-161
/
2023
Background: Surgical closure of an atrial septal defect (ASD) is infrequently indicated during infancy. We evaluated the clinical characteristics and outcomes of patients who underwent surgical ASD closure during infancy. Methods: A single-center retrospective review was performed for 39 patients (19 males) who underwent surgical ASD closure during infancy between 1993 and 2020. The median body weight percentile at the time of operation was 9.3. Results: During a median follow-up of 60.9 months, 4 late deaths occurred due to chronic respiratory failure. A preoperative history of bronchopulmonary dysplasia (BPD) was the only risk factor for late mortality identified in Cox regression (hazard ratio, 3.54; 95% confidence interval [CI], 1.75-163.04; p=0.015). The 5-year survival rate was significantly lower in patients with preoperative history of BPD (97.0% vs. 50.0%, p<0.001) and preoperative ventilatory support (97.1% vs. 40.4%, p<0.001). There were significant postoperative increases in left ventricular end-diastolic (p=0.017), end-systolic (p=0.014), and stroke volume (p=0.013) indices. A generalized estimated equation model showed significantly better postoperative improvement in body weight percentiles in patients with lower weight percentiles at the time of operation (<10th percentile, p=0.01) and larger indexed ASD diameter (≥45 mm/m2, p=0.025). Conclusion: Patients with ASD necessitating surgical closure during infancy are extremely small preoperatively and remain small even after surgical closure. However, postoperative somatic growth was more prominent in smaller patients with larger defects, which may be attributable to an increase in postoperative cardiac output due to changes in ventricular septal configuration. The benefits of ASD closure in patients with BPD are undetermined.
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