• Journal of Information Technology and Architecture
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• v.10 no.1
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• pp.13-22
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• 2013

The Internet has motivated firms to participate in electronic commerce. With the development of electronic commerce, SMEs (small- and medium-sized enterprises) may be forced to use e-intermediaries in export marketing. This study aims at assessing e-intermediaries in various aspects. Empirical and theoretical studies are conducted to investigate determinants and effects of eintermediary use in export marketing. Based on resource-based view (RBV), the study develops a conceptual model that can address the question of which international competence and export performance are closely related to e-intermediary use by SMEs. Based on literature review and theoretical foundations, this study made four hypotheses. With AMOS, structural equation modeling (SEM) was used for testing four hypotheses. The empirical findings support all hypotheses. Last, this study suggests examining comprehensive internal and external factors in terms of e-intermediary use as an interesting topic for future research.

• Journal of the Korean Society of Marine Environment & Safety
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• v.7 no.3
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• pp.61-74
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• 2001

The prevention of marine accidents has been a major topic in marine society and various policies and countermeasures has been developed, applied to the industries. Formal Safety Assessment is a structured and systematic methodology, aimed at enhancing maritime safety, including protection of life, health, the marine environment and property, by using risk and cost-benefit assessments. In addition, it provides a means of being proactive, enabling potential hazards to be considered before a serious accident occurs. In this paper, we has been screening and ranking of hazards using fuzzy structural modeling method and quantitative risk assessment for the ship's collision in the last 10 years marine accidents.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.21 no.6
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• pp.615-632
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• 2008

The bridge health monitoring has become an important research topic in conjunction with damage assessment and safety evaluation of structures owing to the improvement of structural modeling techniques incorporating response measurements and the advancements in signal analysis and information processing capabilities. The bridge monitoring systems are generally composed of hardwares such as sensors, data acquisition equipment, data transmission systems, etc, and softwares such as signal processing, damage assessment, display and management, etc. In this paper, the research and development(R&D) activities on the information processing for structural health monitoring of bridges are reviewed. After a brief introduction to the process of bridge health monitoring, various information processing techniques including various signal processing and damage detection algorithms are introduced in detail. Several challenges addressing critical issues in the current bridge health monitoring system and future R&D activities are discussed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.5
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• pp.1252-1271
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• 2013

Automatic image annotation has become an increasingly important research topic owing to its key role in image retrieval. Simultaneously, it is highly challenging when facing to large-scale dataset with large variance. Practical approaches generally rely on similarity measures defined over images and multi-label prediction methods. More specifically, those approaches usually 1) leverage similarity measures predefined or learned by optimizing for ranking or annotation, which might be not adaptive enough to datasets; and 2) predict labels separately without taking the correlation of labels into account. In this paper, we propose a method for image annotation through collaborative similarity metric learning from dataset and modeling the label correlation of the dataset. The similarity metric is learned by simultaneously optimizing the 1) image ranking using structural SVM (SSVM), and 2) image annotation using correlated label propagation, with respect to the similarity metric. The learned similarity metric, fully exploiting the available information of datasets, would improve the two collaborative components, ranking and annotation, and sequentially the retrieval system itself. We evaluated the proposed method on Corel5k, Corel30k and EspGame databases. The results for annotation and retrieval show the competitive performance of the proposed method.

• Smart Structures and Systems
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• v.14 no.2
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• pp.85-104
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• 2014

Damage detection is a challenging, complex, and at the same time very important research topic in civil engineering. Identifying the location and severity of damage in a structure, as well as the global effects of local damage on the performance of the structure are fundamental elements of damage detection algorithms. Local damage detection is essential for structural health monitoring since local damages can propagate and become detrimental to the functionality of the entire structure. Existing studies present several methods which utilize sensor data, and track global changes in the structure. The challenging issue for these methods is to be sensitive enough in identifYing local damage. Autoregressive models with exogenous terms (ARX) are a popular class of modeling approaches which are the basis for a large group of local damage detection algorithms. This study presents an algorithm, called Influence-based Damage Detection Algorithm (IDDA), which is developed for identification of local damage based on regression of the vibration responses. The formulation of the algorithm and the post-processing statistical framework is presented and its performance is validated through implementation on an experimental beam-column connection which is instrumented by dense-clustered wired and wireless sensor networks. While implementing the algorithm, two different sensor networks with different sensing qualities are utilized and the results are compared. Based on the comparison of the results, the effect of sensor noise on the performance of the proposed algorithm is observed and discussed in this paper.

• Economic and Environmental Geology
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• v.54 no.3
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• pp.353-364
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• 2021

Since the mid-twentieth century, geology has gradually evolved as an interdisciplinary context in South Korea. The journal of Economic and Environmental Geology (EEG) has a long history of over 52 years and published interdisciplinary articles based on geology. In this study, we performed a literature review using topic modeling based on Latent Dirichlet Allocation (LDA), an unsupervised machine learning model, to identify geological topics, historical trends (classic topics and emerging topics), and association by analyzing titles, keywords, and abstracts of 2,571 publications in EEG during 1968-2020. The results showed that 8 topics ('petrology and geochemistry', 'hydrology and hydrogeology', 'economic geology', 'volcanology', 'soil contaminant and remediation', 'general and structural geology', 'geophysics and geophysical exploration', and 'clay mineral') were identified in the EEG. Before 1994, classic topics ('economic geology', 'volcanology', and 'general and structure geology') were dominant research trends. After 1994, emerging topics ('hydrology and hydrogeology', 'soil contaminant and remediation', 'clay mineral') have arisen, and its portion has gradually increased. The result of association analysis showed that EEG tends to be more comprehensive based on 'economic geology'. Our results provide understanding of how geological research topics branch out and merge with other fields using a useful literature review tool for geological research in South Korea.

• Journal of the Korean Society of Marine Environment & Safety
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• v.7 no.2
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• pp.39-48
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• 2001

In recent years, the marine traffic congestion has increased due to the expansion of vessel traffic volume in Korean coastal waterway. Heavy traffic could bring serious marine casualties which cause the loss of human lives, properties and marine pollution in coastal area. The prevention of marine accidents has been a major topic in marin society and various policies and countermeasures have been developed, applied to the industries. VTS(Vessel Traffic Services) is considered as one of effective method to promote marine safety but it needs relatively huge amount of budgets to build and also number of personnels for the operation. Thus prior to establishing the VTS. It should be surveyed the marine traffics, general conditions of waterway including geographical, meteorological characteristics and assessed to find the most reasonable area and places for the system. Therefore this paper aims to develop the method for this evaluation through the hierarchical evaluation structure model in connection with ISM(interpretive structural modeling) and AHP(analytic hierarchy process) methods. The model in this paper is applied to 4 coastal area in Korean waterway as candidates and found that the priority for the needs of VTS should be in order such as Yosu, Wando, Mokpo, Geoje coastal area.

• Journal of Distribution Science
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• v.13 no.11
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• pp.15-22
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• 2015

Purpose - This study aims to propose and validate a research model that describes the relationships between customer socialization, customer participation, and customer loyalty in the online service industry. Although customer loyalty is frequently discussed topic in marketing and strategy research, this study takes a novel approach in adopting customer socialization and participation as the antecedents to customer loyalty. Research design, data, and methodology - Based on adopting and modifying measurement items of the constructs from previous studies, this study develops survey regarding the constructs within the proposed research model. Among current registered members of Facebook and DaumKakao, 522 college students and other regular users are selected as the samples for conducting the survey. The collected data is analyzed by structural equation modeling method using SPSS and AMOS. Results Proposed hypotheses of the positive relationships - between customer socialization and customer participation, and between customer participation and customer loyalty are all supported. Conclusions - The results of this study suggest customer participation as an important precursor to customer loyalty in the online service industry. Also, customer socialization is validated as a new strategy to increase customer participation. These results validate the practical importance of communicating mission, purpose, value, and other customer socialization activities that firms undertake.

• The Journal of Information Systems
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• v.28 no.4
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• pp.105-129
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• 2019

Purpose Issues related to information security have been a crucial topic of interest to researchers and practitioners in the IT/IS field. This study develops a research model based on a Structure-Conduct-Outcome (SCO) framework for the social exchange relationship between employees and organizations regarding information security. Design/methodology/approach In applying an SCO framework to information security, structure and conduct are activities imposed on employees within an organizational context; outcomes are activities that protect information security from an employee. Data were collected from 438 employees working in manufacturing and service firms currently implementing an information security policy in South Korea. Structural equation modeling (SEM) with AMOS 22.0 is used to test the validation of the measurement model and the proposed casual relationships in the research model. Findings The results demonstrate support for the relationships between predicting variables in organization structure (security policy and physical security system) and the outcome variables in organization conduct (top management support, security education program, and security visibility). Results confirm that the three variables in organization conduct had a positive effect on individual outcome (security knowledge and compliance intention).

• Journal of Fisheries and Marine Sciences Education
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• v.28 no.3
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• pp.872-880
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• 2016

The purpose of this study is to find the research trends relating to flipped learning through keyword network analysis. For investigating this topic, final 100 papers (removed due to overlap in all 205 papers) were selected as subjects from the result of research databases such as RISS, DBPIA, and KISS. After keyword extraction, coding, and data cleaning, we made a 2-mode network with final 202 keywords. In order to find out the research trends, frequency analysis, social network structural property analysis based on co-keyword network modeling, and social network centrality analysis were used. Followings were the results of the research: (a) Achievement, writing, blended learning, teaching and learning model, learner centered education, cooperative leaning, and learning motivation, and self-regulated learning were found to be the most common keywords except flipped learning. (b) Density was .088, and geodesic distance was 3.150 based on keyword network type 2. (c) Teaching and learning model, blended learning, and satisfaction were centrally located and closed related to other keywords. Satisfaction, teaching and learning model blended learning, motivation, writing, communication, and achievement were playing an intermediary role among other keywords.