• Smart Structures and Systems
• /
• v.30 no.6
• /
• pp.687-701
• /
• 2022

Inevitable response loss under complex operational conditions significantly affects the integrity and quality of measured data, leading the structural health monitoring (SHM) ineffective. To remedy the impact of data loss, a common way is to transfer the recorded response of available measure point to where the data loss occurred by establishing the response mapping from measured data. However, the current research has yet addressed the structural condition changes afterward and response mapping learning from a small sample. So, this paper proposes a novel data driven structural response reconstruction method based on a sophisticated designed generating adversarial network (UAGAN). Advanced deep learning techniques including U-shaped dense blocks, self-attention and a customized loss function are specialized and embedded in UAGAN to improve the universal and representative features extraction and generalized responses mapping establishment. In numerical validation, UAGAN efficiently and accurately captures the distinguished features of structural response from only 40 training samples of the intact structure. Besides, the established response mapping is universal, which effectively reconstructs responses of the structure suffered up to 10% random stiffness reduction or structural damage. In the experimental validation, UAGAN is trained with ambient response and applied to reconstruct response measured under earthquake. The reconstruction losses of response in the time and frequency domains reached 16% and 17%, that is better than the previous research, demonstrating the leading performance of the sophisticated designed network. In addition, the identified modal parameters from reconstructed and the corresponding true responses are highly consistent indicates that the proposed UAGAN is very potential to be applied to practical civil engineering.

• Convergence Security Journal
• /
• v.23 no.5
• /
• pp.45-55
• /
• 2023

With the widespread use of digital devices, anonymous communication technologies such as the dark web and deep web are becoming increasingly popular for criminal activity. Because these technologies leave little local data on the device, they are difficult to track using conventional crime investigation techniques. The United States and the United Kingdom have enacted laws and developed systems to address this issue, but South Korea has not yet taken any significant steps. This paper proposes a new blockchain-based crime investigation method that uses physical memory data analysis to track the behavior of anonymous network users. The proposed method minimizes infringement of basic rights by only collecting physical memory data from the device of the suspected user and storing the tracking information on a blockchain, which is tamper-proof and transparent. The paper evaluates the effectiveness of the proposed method using a simulation environment and finds that it can track the behavior of dark website users with a residual rate of 77.2%.

• The Journal of the Convergence on Culture Technology
• /
• v.7 no.1
• /
• pp.539-544
• /
• 2021

The tactical data link is a military data network to improve the ability to recognize battlefield situations. The ROK military is promoting the tactical data link performance improvement programs. Tactical data link is essential to combine and integrate various platforms, sensor data, and command and control (C2) systems. Therefore, the research on related technical fields is required. However, the tactical data link has not disclosed detailed technical information due to the characteristics of military operation. In this paper, we propose a data-based automated analysis methodology using intellectual property information to understand the technology trend of tactical data link. In this paper, data related to intellectual property is automatically collected and pre-processed, and analyzed in terms of time series. In addition, the current status of each institution of patent technology information was generated, and the process of identifying key-researchers through network analysis was presented with providing results of our approach in this paper.

• Journal of Korean Institute of Industrial Engineers
• /
• v.43 no.1
• /
• pp.62-71
• /
• 2017

In order to attract foreign tourists, it is important to understand what factors on domestic tour spots are critically considered and how they are evaluated after visit. However, most of the researches on tour business have collected information from tourists through survey on a small number of tourists, which leads to inaccurate and biased conclusion. In this paper, we suggest a data-driven methodology to figure out tourists' satisfaction factors and estimate sentiment scores on them. To do so, we collected review comments data from popular web site. Latent dirichlet allocation is employed to extract key factors and elastic net is used to estimate sentiment scores. Then, an aggregated evaluation score is generated by combining the factors and the sentiment scores per topics. Our proposed method can be used to recommend travel schedules with themes and discover new spots.

• Journal of Korean Academy of Nursing Administration
• /
• v.8 no.3
• /
• pp.381-392
• /
• 2002

Purpose : The purpose of this study was to examine the degrees of turnover intention among Korean staff nurses(N=175) and to identify discriminating factors of their turnover intention. Method : The data were driven from a larger study and staff nurses who had worked more than 1 year as nurses were included in the analyses. The original data were collected from May 1999 to March 2000. Descriptive and discriminant analyses were utilized. Results : 87% of the participants reported turnover intention. Nurses were grouped into three group(GP)s depending on the frequencies of turnover intention: Never GP(N=23), Sometimes GP(N=107), Frequent GP(N=43). With three GPs, two functions were produced and only function 1 was significant that significantly discriminated Never and Frequent GPs. Additional discriminant analysis with only Never and Frequent GPs produced function classified 93% of the participants correctly into two GPs. Sub-dimensions of work satisfaction were significant discriminating factors. Nurses who are satisfied with doctor and nurse relationship, pay, and hospital administration tend to report no intention in turnover. Conclusion : Based on the findings of this study, possible managemental intervention for increasing interpersonal skills and assertiveness of nurses, inviting medical residents in ward team meeting, increasing incentives or baseline adjustment of annual income for registered nurses were suggested.

• The Journal of Asian Finance, Economics and Business
• /
• v.8 no.3
• /
• pp.237-249
• /
• 2021

Indonesia has successfully increased its ranking to 40th place in the 2019 Travel & Tourism Competitiveness Index. While tourism has become the country's second largest foreign exchange contributor, there is no existing competitive advantage model for Indonesian tourist destinations. The purpose and novelty of this study is to develop and formulate a competitive advantage model for Indonesia's tourism industry. The model will be based on the supply-side perception analysis of competitiveness indicators from Bali and five designated super-priority destinations in Indonesia. This model is expected to become a guideline for policymakers to design an effective and focused strategy. Data were obtained from in-depth interviews with, and questionnaires given to, 62 qualified industry players from the public and private sectors. This data-driven approach builds a relationship between competitiveness indicators and competitive advantages using a combination of importance-performance analysis and confirmatory factor analysis, thereby leveraging these advantages to generate a strategic model to compete in the international tourism industry. This would also be the first study to use this method in defining the competitive advantage of a destination. Using structural equation modeling, the study found that there are 54 indicators representing twelve dimensions of competitive advantages with good fit criteria.

• Transactions of the Korean hydrogen and new energy society
• /
• v.34 no.5
• /
• pp.478-489
• /
• 2023

In this study, fault diagnosis and detection methods developed to ensure the reliability of polymer electrolyte membrane (PEM) hydrogen electrolysis systems have been proposed. The proposed method consists of model development and data generation of the PEM hydrogen electrolysis system, and data-driven fault diagnosis learning model development. The developed fault diagnosis learning model describes how to detect and classify faults in the sensors and components of the system.

• The Journal of the Acoustical Society of Korea
• /
• v.23 no.2
• /
• pp.173-179
• /
• 2004

Due to the insufficiency of training data in large vocabulary continuous speech recognition, similar context dependent phones can be clustered by decision trees to share the data. When the decision trees are built and used to predict unseen triphones, a phonetic question set is required. The phonetic question set, which contains categories of the phones with similar co-articulation effects, is usually generated by phonetic or linguistic experts. This knowledge-based approach for generating phonetic question set, however, may reduce the homogeneity of the clusters. Moreover, the experts must adjust the question sets whenever the language or the PLU (phone-like unit) of a recognition system is changed. Therefore, we propose a data-driven method to automatically generate phonetic question set. Since the proposed method generates the phone categories using speech data distribution, it is not dependent on the language or the PLU, and may enhance the homogeneity of the clusters. In large vocabulary speech recognition experiments, the proposed algorithm has been found to reduce the error rate by 14.3%.

• Journal of the Korean Society of Marine Environment & Safety
• /
• v.21 no.4
• /
• pp.437-448
• /
• 2015

In this paper, smartphone based measuring device was developed by integration of several sonsors such as moving, temperature, pulsation, respiration and hearing and sever/client programs was developed for the data acquisition and communication between smartphone and server computer. Then, the concept of CSI(combined safety index) was proposed for the comprehensive diagnositcs of workers status. For the validation of the proposed concept, the real data was acquired by boarding at training ship of korea maritime and ocean university. The acquired data was analyzed with the stochastical method of regressionn, then the meaningful result was driven that could explain the relation between the risky situation and the measured chronical data.

• KIPS Transactions on Software and Data Engineering
• /
• v.8 no.7
• /
• pp.303-310
• /
• 2019

In the current mobile environment that is indispensable to our everyday lives, various forms of new business models are created including personalized services such as Google's "Google NOW" and Apple's "Siri". These services would not have been possible without technologies on the effective integration of various services and models. The requirements for effective integration of services include, 1) the efficient data sharing among multiple services, 2) the data-driven asynchronous execution of services, and 3) the simple extensible interaction method for the services. In this paper, we propose a mobile service architecture that utilizes the blackboard architecture to satisfy the aforementioned requirements to enable effective integration of various services, sharing and management of data between services, and asynchronous execution of services.