• Smart Structures and Systems
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• v.17 no.2
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• pp.167-194
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• 2016

This paper investigates the Synergetics based Damage Detection Method (SDDM) for frame structures by using surface-bonded PZT (Lead Zirconate Titanate) patches. After analyzing the mechanism of pattern recognition from Synergetics, the operating framework with cooperation-competition-update process of SDDM was proposed. First, the dynamic identification equation of structural conditions was established and the adjoint vector (AV) set of original vector (OV) set was obtained by Generalized Inverse Matrix (GIM).Then, the order parameter equation and its evolution process were deduced through the strict mathematics ratiocination. Moreover, in order to complete online structural condition update feature, the iterative update algorithm was presented. Subsequently, the pathway in which SDDM was realized through the modified Synergetic Neural Network (SNN) was introduced and its assessment indices were confirmed. Finally, the experimental platform with a two-story frame structure was set up. The performances of the proposed methodology were tested for damage identifications by loosening various screw nuts group scenarios. The experiments were conducted in different damage degrees, the disturbance environment and the noisy environment, respectively. The results show the feasibility of SDDM using piezoceramic sensors and actuators, and demonstrate a strong ability of anti-disturbance and anti-noise in frame structure applications. This proposed approach can be extended to the similar structures for damage identification.

• Journal of Korea Trade
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• v.26 no.3
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• pp.23-44
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• 2022

Purpose - Recent issues such as vessel enlargement, strengthening of environmental regulations, and port smartization are expected to increase costs and intensify competition in the port industry. In the new normal era, when external growth has reached its limit, the efficient operation of ports is becoming indispensable for achieving sustainable growth. This study aims to identify the determinants of inefficiency by examining the cost structure and efficiency of container terminals in Korea and furthermore propose the political implications to derive the maximization of efficiency. Design/methodology - This study estimates the cost function of container terminal operators and identifies the efficiency of container terminals using stochastic cost frontier (SCF) in the first stage. In the second step, the SCF results are compared with the data envelopment analysis (DEA). Last, this paper proposes efficiency determinants on container terminal operation to establish appropriate strategies. Out of the 29 container terminal operators in South Korea, 13 operators participated in the survey. The translog cost function was estimated utilizing a total of 116 observations collected over the 2007-2017 period. Findings - Empirical analysis shows that economies of scale exist in Korea's container ports, which provides a rationale for the government's policy to establish the global terminal operator by integrating small terminal operators to enhance competitiveness. In addition, as a result of the determinants analysis, container throughput, weight of direct employment costs, and labour cost share have positive effects on improving cost efficiency, while inefficiency increases as the length of quay increases. More specifically, cost efficiency improves as the proportion of direct employment costs to outsourcing service costs increases. Originality/value - This study contributes to analyzing the inefficiency factors of container terminals through efficiency analysis with respect to a cost function. In addition, this study proposes the practical and political implications, such as establishing a long-term manpower pool, the application of the hybrid liner terminal system, and the construction of a statistical data system, to improve the cost inefficiency of terminal operators.

• Publications of The Korean Astronomical Society
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• v.26 no.3
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• pp.89-101
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• 2011

The International Olympiad on Astronomy and Astrophysics (IOAA) initiated by the Thailand Astronomical Society in 2007 is an annual competition for high school students. One of its aim is to enhance the development of international exchange in the field of school education in astronomy and astrophysics. This paper first provides the overview of the IOAA in terms of key regulations based on its statutes, history and current status. Secondly, the published syllabus of the IOAA is used for content analysis according to subject areas regarding the exam questions of the IOAA in theoretical, observational and data analysis parts from 2007 to 2010. Also, a scientific inquiry framework is applied to the same questions for assessment based on scientific inquiry in the cognitive aspect with two sub-classes of scientific knowledge and scientific reasoning. Among a dozen astronomy subject areas listed on the syllabus, the theoretical part of the IOAA makes more frequent use of the Sun, the solar system, properties of stars, and concept of time. In content knowledge, a factor of scientific knowledge, the IOAA questions, especially in the theoretical part have a lesser degree in difficulty than the IAO (International Astronomy Olympiad) exam questions for the same period whose degree in difficulty is comparable to college level. With regard to scientific reasoning, the IOAA questions tend to involve convergent rather than divergent thinking. Lastly, in light of these findings, discussions are given on the outcome of Korean participation in the previous IOAAs and ways to help better in preparing Korean students for future astronomy Olympiads.

• Smart Structures and Systems
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• v.29 no.1
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• pp.251-266
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• 2022

Structural Health Monitoring (SHM) of critical infrastructure comprises a major pillar of maintenance management, shielding public safety and economic sustainability. Although SHM is usually associated with data-driven metrics and thresholds, expert judgement is essential, especially in cases where erroneous predictions can bear casualties or substantial economic loss. Considering that visual inspections are time consuming and potentially subjective, artificial-intelligence tools may be leveraged in order to minimize the inspection effort and provide objective outcomes. In this context, timely detection of sensor malfunctioning is crucial in preventing inaccurate assessment and false alarms. The present work introduces a sensor-fault detection and interpretation framework, based on the well-established support-vector machine scheme for anomaly detection, combined with a coalitional game-theory approach. The proposed framework is implemented in two datasets, provided along the 1st International Project Competition for Structural Health Monitoring (IPC-SHM 2020), comprising acceleration and cable-load measurements from two real cable-stayed bridges. The results demonstrate good predictive performance and highlight the potential for seamless adaption of the algorithm to intrinsically different data domains. For the first time, the term "decision trajectories", originating from the field of cognitive sciences, is introduced and applied in the context of SHM. This provides an intuitive and comprehensive illustration of the impact of individual features, along with an elaboration on feature dependencies that drive individual model predictions. Overall, the proposed framework provides an easy-to-train, application-agnostic and interpretable anomaly detector, which can be integrated into the preprocessing part of various SHM and condition-monitoring applications, offering a first screening of the sensor health prior to further analysis.

• Smart Structures and Systems
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• v.31 no.4
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• pp.365-381
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• 2023

The existing vision-based techniques for inspection and condition assessment of civil infrastructure are mostly manual and consequently time-consuming, expensive, subjective, and risky. As a viable alternative, researchers in the past resorted to deep learning-based autonomous damage detection algorithms for expedited post-disaster reconnaissance of structures. Although a number of automatic damage detection algorithms have been proposed, the scarcity of labeled training data remains a major concern. To address this issue, this study proposed a semi-supervised learning (SSL) framework based on consistency regularization and cross-supervision. Image data from post-earthquake reconnaissance, that contains cracks, spalling, and exposed rebars are used to evaluate the proposed solution. Experiments are carried out under different data partition protocols, and it is shown that the proposed SSL method can make use of unlabeled images to enhance the segmentation performance when limited amount of ground truth labels are provided. This study also proposes DeepLab-AASPP and modified versions of U-Net++ based on channel-wise attention mechanism to better segment the components and damage areas from images of reinforced concrete buildings. The channel-wise attention mechanism can effectively improve the performance of the network by dynamically scaling the feature maps so that the networks can focus on more informative feature maps in the concatenation layer. The proposed DeepLab-AASPP achieves the best performance on component segmentation and damage state segmentation tasks with mIoU scores of 0.9850 and 0.7032, respectively. For crack, spalling, and rebar segmentation tasks, modified U-Net++ obtains the best performance with Igou scores (excluding the background pixels) of 0.5449, 0.9375, and 0.5018, respectively. The proposed architectures win the second place in IC-SHM2021 competition in all five tasks of Project 2.

• Journal of Soil and Groundwater Environment
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• v.16 no.4
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• pp.23-30
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• 2011

Risk based pollution level of Pb and Cd in metal contaminated soils depending on physicochemical properties of soil in a target site was assessed using biotic ligand model. Heavy metal activity in soil solution defined as exposure activity (EA) was assumed to be toxic to Vibrio fischeri and soil organisms. Predicted effective activity (PEA) determined by biotic ligand model was compared to EA value to calculate risk quotient. Field contaminated soils (n = 10) were collected from a formes area and their risk based pollution levels were assessed in the present study using the calculated risk quotient. Concentrations of Pb determined by aqua regia were 295, 258, and 268 mg/kg in B, H and J points and concentrations of Cd were 4.73 and 6.36 mg/kg in G and I points, respectively. These points exceeded the current soil conservation standards. However, risk based pollution levels of the ten points were not able to be calculated because concentrations of Pb and Cd in soil solution were smaller than detection limits or one (i.e., non toxic). It was because heavy metal activity in soil solution was dominant toxicological form to organisms, not a total heavy metal concentration in soil. In addition, heavy metal toxicity was decreased by competition effect of major cations and formation of complex with dissolved organic carbon in soil solution. Therefore, it is essential to consider site-specific factors affecting bioavailability and toxicity for estimating reliable risk of Pb and Cd.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.251-259
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• 2006

The increase in international logistics market and various customer demands emphasize the importance of Multimodal Transportation, and that market is continuously keep growing. In order to ensure competitive superiority in a market of such infinite competition, service that can satisfy each individual customer by considering various customer characteristics, has become an issue. Thus, through the aspect of service, in order to improve customer satisfaction, growing factors of Multimodal Transportation Route on was studied in this research. For this research, first of all main service factors that affect the growth of Multimodal Transportation were seized by literature survey and positive research. The, by using these factors a methodology that enables individual customers to assess Multimodal Transportation Route was studied. Through this research, individual customers can acquire objective assessment data and Multimodal Transportation companies can seize what factors are considered as important by their customers.

• Safety and Health at Work
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• v.10 no.1
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• pp.95-102
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• 2019

Background: In a cluster-randomized trial, the Safety and Health Involvement For Truck drivers intervention produced statistically significant and medically meaningful weight loss at 6 months (-3.31 kg between-group difference). The current manuscript evaluates the relative impact of intervention components on study outcomes among participants in the intervention condition who reported for a post-intervention health assessment (n = 134) to encourage the adoption of effective tactics and inform future replications, tailoring, and enhancements. Methods: The Safety and Health Involvement For Truck drivers intervention was implemented in a Web-based computer and smartphone-accessible format and included a group weight loss competition and body weight and behavioral self-monitoring with feedback, computer-based training, and motivational interviewing. Indices were calculated to reflect engagement patterns for these components, and generalized linear models quantified predictive relationships between participation in intervention components and outcomes. Results: Participants who completed the full program-defined dose of the intervention had significantly greater weight loss than those who did not. Behavioral self-monitoring, computer-based training, and health coaching were significant predictors of dietary changes, whereas behavioral and body weight self-monitoring was the only significant predictor of changes in physical activity. Behavioral and body weight self-monitoring was the strongest predictor of weight loss. Conclusion: Web-based self-monitoring of body weight and health behaviors was a particularly impactful tactic in our mobile health intervention. Findings advance the science of behavior change in mobile health intervention delivery and inform the development of health programs for dispersed populations.

• The Journal of Industrial Distribution & Business
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• v.9 no.3
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• pp.57-68
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• 2018

Purpose - The purpose of this study is to classify that the quality factors for comparing the Visegrard Group with the Nordic Council have historical similarities against Germany and the Soviet Union. However, this is because in the integrated European market, the competitiveness possessed by the two groups of countries is invested in the priority order to grow. Research design, data, and methodology - The study was conducted on the research design, and the reason for trying to compare the competence of the automobile industry in the assessment of industrial capability is that the Visegrard Group focuses on automotive production and the Nordic Association focuses on the commercialization of the automobile(market). In this study, searching and quantifying indirect evidence was made through standards are more complementary in Europe since each country acts like the role of the European automotive industry for example, which is different from the realistic evaluation criteria, are more important than those of the United States(first in the world) or Germany(first in Europe). Results - The results of this study are as follows: In the global EV market U.S.(export: $ 2.62 billion /share: 36.7%), Germany($ 1.29 billion /18.1%), France($ 390 million /5.4%), United Kingdom($ 380 million /5.4%), and South Korea($ 320 million/ 4.4%). South Korea's share of the EV market is 4.4%, while TSI reaches at +0.9 which measures the comparative advantage of a specific commodity in the world trade market. There is great potential for evaluated as products processing in export competition. But, commercialization, standardization, and overall market expansion did not have a positive impact on global satisfaction. Conclusions - EVs put importance on various utilities. So this suggests that Korea's exports to the EU, including the Visegrard Group, should be more focused on marketability when illuminating with a sharing industrial system under the European Union. It is necessary to specialize in manufacturing and commercialization by country(region) to prepare sharing economy and blockchain in order to create a smart-sharing city linked on artificial intelligence, as the commercialization of electric vehicles, which will have a larger growth rate than that of manufacturing in the fourth revolutionary era.

• Journal of the Korea Institute of Building Construction
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• v.11 no.2
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• pp.108-115
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• 2011

This study investigates the construction management selection methods for fair competition within the construction management market by analyzing the current status of domestic construction management, the 2010 publication on the status of construction management, and the construction management evaluation criteria. Also, the 2009 publication of top CM service establishments, the average proportion of tender for 120 CM services from 2002 to 2010, and six assessment results which are open to the parties directly involved were statistically analyzed to review the adequacy of the evaluation criteria. This analysis shows that the evaluation criteria for the CM service impedes the development of the construction management industry and companies, since the criteria are decided by the service payment, and the technical skills assessed by technical proposals have no ties with contract prices. Therefore, this study proposes an improvement of the selection methods in accordance with the project characteristics and the technical requirements. However, more research is still needed to derive a detailed classification method of the technical requirement, the owner's evaluation criteria selection, and the preparation of an institutional foundation for the construction manager's post-evaluation.