• Structural Monitoring and Maintenance
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• v.6 no.3
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• pp.237-254
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• 2019

This paper presents an improved time series based damage detection approach with experimental verifications for detection, localization, and quantification of damage in shear-type structures under varying mass effects using output-only vibration data. The proposed method can be very effective for automated monitoring of buildings to develop proactive maintenance strategies. In this method, Auto-Regressive Moving Average models with eXogenous inputs (ARMAX) are built to represent the dynamic relationship of different sensor clusters. The damage features are extracted based on the relative difference of the ARMAX model coefficients to identify the existence, location and severity of damage of stiffness and mass separately. The results from a laboratory-scale shear type structure show that different damage scenarios are revealed successfully using the approach. At the end of this paper, the methodology limitations are also discussed, especially when simultaneous occurrence of mass and stiffness damage at multiple locations.

• Nuclear Engineering and Technology
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• v.53 no.11
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• pp.3675-3684
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• 2021

Human reliability analysis (HRA) is a proactive approach to model and evaluate human systematic errors, and has been extensively applied in various complicated systems. Dependence assessment among human errors plays a key role in the HRA, which relies heavily on the knowledge and experience of experts in real-world cases. Moreover, there are ofthen different types of uncertainty when experts use linguistic labels to evaluate the dependencies between human failure events. In this context, this paper aims to develop a new method based on linguistic hesitant fuzzy sets and the technique for human error rate prediction (THERP) technique to manage the dependence in HRA. This method handles the linguistic assessments given by experts according to the linguistic hesitant fuzzy sets, determines the weights of influential factors by an extended best-worst method, and confirms the degree of dependence between successive actions based on the THERP method. Finally, the effectiveness and practicality of the presented linguistic hesitant fuzzy THERP method are demonstrated through an empirical healthcare dependence analysis.

• Journal of Korean Dental Science
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• v.15 no.2
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• pp.166-171
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• 2022

This case report describes a dynamic digital esthetic rehabilitation procedure that integrates a new three-dimensional augmented reality (3D-AR) technique to treat a patient with multiple missing anterior teeth. The prostheses were designed using computer-aided design (CAD) software and virtually trialed using static and dynamic visualization methods. In the static method, the prostheses were visualized by integrating the CAD model with a 3D face scan of the patient. For the dynamic method, the 3D-AR application was used for real-time tracking and projection of the CAD prostheses in the patient's mouth. Results of a quick survey on patient satisfaction with the two visualization methods showed that the patient felt more satisfied with the dynamic visualization method because it allowed him to observe the prostheses directly on his face and be more proactive in the treatment process.

• International journal of advanced smart convergence
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• v.13 no.3
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• pp.135-142
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• 2024

Recently, along with digital transformation, technologies such as cloud computing, big data, and artificial intelligence have been actively introduced. In a situation where these technological changes are progressing rapidly, it is often difficult to manage processes efficiently using existing simple workflow management methods. Companies providing current cloud services are adopting virtualization technologies, including virtual machines (VMs) and containers, in their distributed system infrastructure for automated application deployment. Accordingly, this paper proposes a process-based orchestration system for integrated execution of corporate process-oriented workloads by integrating the potential of big data and machine learning technologies. This system consists of four layers as components for performing workload processes. Additionally, a common information model is applied to the data to efficiently integrate and manage the various formats and uses of data generated during the process creation stage. Moreover, a standard metadata protocol is introduced to ensure smooth exchange between data. This proposed system utilizes various types of data storage to store process data, metadata, and analysis models. This enables flexible management and efficient processing of data.

• International conference on construction engineering and project management
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• 2024.07a
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• pp.145-151
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• 2024

Road sign support systems are not usually well managed because bridges and pavement have budget and maintenance priority while the sign boards and sign supports are considered as miscellaneous items. The authors of this paper suggested the implementation of simplified machine learning algorithms for asset risk management in highway sign support systems. By harnessing historical and real-time data, machine learning models can forecast potential vulnerabilities, enabling early intervention and proactive maintenance protocols. The raw data were collected from the Connecticut Department of Transportation (CTDOT) asset management database that includes asset ages, repair history, installation and repair costs, and other administrative information. While there are many advanced and complicated structural deterioration prediction models, a simple deterioration curve is assumed, and prediction model has been developed using machine learning algorithm to determine the risk assessment and prediction. The integration of simplified machine learning in asset risk management for highway sign support systems not only enables predictive maintenance but also optimizes resource allocation. This approach ensures that decision-makers are not inundated with excessive detailed information, making it particularly practical for industry application.

• Journal of Information Technology Services
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• v.12 no.1
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• pp.323-340
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• 2013

As the importance of collaboration becomes critical in today's open and complex business environment network, the issues and solutions on compatibility and reusability between different kinds of applications are being increasingly important as well in systems analysis and design. And therefore, service-centered SOA is receiving attention in such business environment as a strategic approach that makes possible for prompt action according to the needs of users and business process. Various implementation methodologies have been proposed for SOA, however, in practical aspects most of them have some problems since they fail to propose specific policies in definition and identification of services for the exact user requirements and business situations. To solve or alleviate those problems, this paper suggests a new service identification model based on hierarchical ontology, where three different ontologies such as business ontology, context ontology and service ontology are proposed to define the relationship and design the link between user requirements, business process, applications and services. Through a suggested methodology in this paper, it would be possible to provide proactive services that meets a variety of business environments and demands of user. Also, since the information can be modified adaptively and dynamically by hierarchical ontology, this study is expected to play a positive role in increasing the flexibility of systems and business environments.

• Journal of Information Technology Applications and Management
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• v.31 no.4
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• pp.149-162
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• 2024

This paper explored the characters in spin-off works that are becoming a hot topic not only in Korea but also in the world. I would like to find out whether there are changes in the character in the original and the character's character and behavior in the spin-off work, and if there are changes, for what reason the changes occur. The subjects of the study were "Puss in Boots" and "Minions," which released a number of spin-off works based on the original. As analysis tools, we used the five-step theory of need by Abraham H. Maslow and the behavioral model of Greimas. As a result, in the spin-off work, Minions and Puss have shifted away from the role of facilitator in the original and become subjective characters. According to Maslow's theory of needs, the analysis also confirmed that this appears as an action to satisfy the needs of belonging, love, respect, and self-realization beyond basic physiological and safety needs. This change allowed him to develop a more independent and proactive personality and behavior, and be at the center of the story. This is the result of reflecting the production team's intention and audience expectations to provide audiences with deeper characters and richer stories. is analyzed.

• Convergence Security Journal
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• v.17 no.3
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• pp.103-114
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• 2017

Terrorism is a serious problem in that it can infringe on a broad range of legal interests, from individual legal interests to national legal interests. And if these legal values are damaged, it is very unlikely that they will be restored to their original state. Therefore, it is necessary to recognize the importance of preventive activities as well as institutional improvement and alternative policies. The role of the criminal justice authority is of paramount importance in ensuring proactive action and procedural legitimacy. It would be meaningful to look at their perception about terrorism before specific procedures and legal approaches are taken. A Study is related terrorism awareness of police officers - focused on 'Comprehensive Emergency Management Model'. Four phases of Comprehensive Emergency Management Model: mitigation, preparedness, response, and recovery.

• Korean Journal of Construction Engineering and Management
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• v.10 no.3
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• pp.139-147
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• 2009

Accurate construction cost estimation in the initial stage of building project plays a key role for project success and for mitigation of disputes. Total construction cost(TCC) estimation of apartment projects in Vietnam has become more important because those projects increasingly rise in quantity with the urbanization and population growth. This paper presents the application of artificial neural networks(ANNs) in estimating TCC of apartment projects. Ninety-one questionnaires were collected to identify input variables. Fourteen data sets of completed apartment projects were obtained and processed for training and generalizing the neural network(NN). MATLAB software was used to train the NN. A program was constructed using Visual C++ in order to apply the neural network to realistic projects. The results suggest that this model is reasonable in predicting TCCs for apartment projects and reinforce the reliability of using neural networks to cost models. Although the proposed model is not validated in a rigorous way, the ANN-based model may be useful for both practitioners and researchers. It facilitates systematic predictions in early phases of construction projects. Practitioners are more proactive in estimating construction costs and making consistent decisions in initial phases of apartment projects. Researchers should benefit from exploring insights into its implementation in the real world. The findings are useful not only to researchers and practitioners in the Vietnam Construction Industry(VCI) but also to participants in other developing countries in South East Asia. Since Korea has emerged as the first largest foreign investor in Vietnam, the results of this study may be also useful to participants in Korea.

• Journal of Agricultural Extension & Community Development
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• v.19 no.3
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• pp.699-727
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• 2012

Conditions of farm crop switching are affected by several important external factors such as agricultural products import opening, policy support, and climate change. Farming environment is always changing; barriers to imports are becoming lower and lower because of FTA and others, and climate change affects a boundary line of cultivation. Those situations give farmers motivation to change crops in order to cope with them. In addition, crop switching has been done in response to the local government measures about purchase of local agricultural products according to the local food and the expansion of organic agricultural products in school meal. Even though the favorable environment toward crop switching has been created, there are not many researches or outcomes regarding crop switching. Only few studies focus on the list of decision-making in crop switching, and locally suitable crop selection is not treated. In order to utilize crop switching as a farm management strategy, the proper frame should be studied and practical researches on application possibility also need. Therefore, study on crop switching is in a timely, proactive manner because farms catch the chance of expansion of school meal by changing crops. This paper applies HERO model used for venture foundation process to crop switching process. Success factors of HERO model are comprised of Habitate, Entrepreneurship, Resource, and Opportunity, and these phased application factors are applied to crop switching process. By doing so, each phase success factor of crop switching can be uncovered. Three farm organizations supplying organic agricultural products to schools are studied in Gyeonggi province. As a result, the stabilization stage cannot be achieved because of the habitate conditions and social conditions with low risk bearing of crop switching and current school meal systems are the main problems to block the diversification of risks. In order to succeed in crop switching, constructing the habitate in local districts or in systems of school meal is more effective than supporting each farm.