• Nuclear Engineering and Technology
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• v.55 no.4
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• pp.1382-1399
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• 2023

Pressure relief valve (PRV) is one of the important control valves used in nuclear power plants, and its sealing performance is crucial to ensure the safety and function of the entire pressure system. For the sealing performance improving purpose, an explicit function that accounts for all design parameters and can accurately describe the relationship between the multi-design parameters and the seal performance is essential, which is also the challenge of the valve seal design and/or optimization work. On this basis, a surrogate model-based design optimization is carried out in this paper. To obtain the basic data required by the surrogate model, both the Finite Element Model (FEM) and the Computational Fluid Dynamics (CFD) based numerical models were successively established, and thereby both the contact stresses of valve static sealing and dynamic impact (between valve disk and nozzle) could be predicted. With these basic data, the polynomial chaos expansion (PCE) surrogate model which can not only be used for inputs-outputs relationship construction, but also produce the sensitivity of different design parameters were developed. Based on the PCE surrogate model, a new design scheme was obtained after optimization, in which the valve sealing stress is increased by 24.42% while keeping the maximum impact stress lower than 90% of the material allowable stress. The result confirms the ability and feasibility of the method proposed in this paper, and should also be suitable for performance design optimizations of control valves with similar structures.

• The Journal of Health Technology Assessment
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• v.1 no.1
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• pp.22-26
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• 2013

Objectives: Balancing benefits and risks through the drug life cycle has been discussed for many decades. The objective of this study was to review the processes and tools currently proposed for benefit-risk assessment of medicinal drugs. It aimed to establish scientific and efficient drug safety management system based on the synthetic analysis of benefit-risk evidence. Methods: We conducted a review of exiting literatures published by regulatory agencies or initiatives. Not only quantitative methodologies but also qualitative method were compared to understand their key characteristics for the benefit and risk assessment of drugs. Results: Recently, benefit-risk assessments have more structured approaches to decision making as part of regulatory science. Regulatory agencies such as European Medicines Agency, FDA have prepared plans to apply benefit-risk assessment to regulatory decision making. Also many initiatives such as IMI (Innovative Medicine Initiative) have conducted research and published reports about benefit-risk assessment. For benefit-risk assessment, four kinds of methods are necessary. Frameworks such as BRAT (Benefit Risk Action Team) framework, PrOACT-URL provide guidance for the whole process of decision-making. Metrics are measurements of risk benefit. The estimation techniques are methods to synthesis and combine evidences from various sources. The utility survey techniques are necessary to explicit preferences of various outcome from stakeholders. Conclusion: There is the lack of widely accepted, validated model for benefit-risk assessment. Nor there is an agreement among academia, industry, and government on methods for the quantitative valuation. It is also limited by available evidence and underlying assumptions. Nevertheless, benefit-risk assessment is fundamental to improve transparency, consistency and predictability for decision making through the structured systematic approaches.

• Pediatric Gastroenterology, Hepatology & Nutrition
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• v.27 no.5
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• pp.267-273
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• 2024

Helicobacter pylori infection is often acquired in early childhood. While most infected children remain asymptomatic, H. pylori can cause chronic gastritis, gastric ulceration, and, in the long term, gastric cancer. This article aimed to review different diagnostic and treatment options and discuss the challenges associated with applying the current guidelines in the real world. Relevant articles published from 2015 to August 2023 in the English language in PubMed and Medline electronic databases were extracted using subject headings and keywords of interest to the topic. References of interest in the selected articles were also considered. Invasive and noninvasive diagnostic tests have advantages but also disadvantages and limitations according to the clinical setting and age of the child. Guidelines recommend not performing diagnostic testing in children with long-lasting or recurrent abdominal complaints or cases of a family history of severe disease caused by H. pylori. However, parents regularly consult with the explicit demand to test for H. pylori because of them or a close family member experiencing severe gastric disease caused by H. pylori. In some situations, it may be challenging for the healthcare professional to stick to evidence-based guidelines and not consider "patient-centered care," with the risk of putting a trustful relationship in danger. Physicians may find it challenging not to perform diagnostic tests for H. pylori and prescribe eradication treatment in specific clinical settings when maintaining a trusting patientphysician relationship by applying this "patient-centered care" method when evidence-based guidelines recommend differently.

• Journal of Smart Tourism
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• v.4 no.2
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• pp.5-14
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• 2024

This study explores the transformative potential of machine learning (ML) and ML-driven data analytics in the hospitality industry. It provides a comprehensive overview of this emerging method, from explaining ML's origins to introducing the evolution of ML-driven data analytics in the hospitality industry. The present study emphasizes the shift embodied in ML, moving from explicit programming towards a self-learning, adaptive approach refined over time through big data. Meanwhile, social media analytics has progressed from simplistic metrics deriving nuanced qualitative insights into consumer behavior as an industry-specific example. Additionally, this study explores innovative applications of these innovative technologies in the hospitality sector, whether in demand forecasting, personalized marketing, predictive maintenance, etc. The study also emphasizes the integration of ML and social media analytics, discussing the implications like enhanced customer personalization, real-time decision-making capabilities, optimized marketing campaigns, and improved fraud detection. In conclusion, ML-driven hospitality data analytics have become indispensable in the strategic and operation machinery of contemporary hospitality businesses. It projects these technologies' continued significance in propelling data-centric advancements across the industry.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.11
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• pp.53-62
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• 1994

This paper presents a new approach of analyzing errors resulting from nonideal general-purpose lighting environment when the Photometric Stereo Method (PSM) is applied to estimate the surface-orientation of a three-dimensional object. The approach introduces the explicit modeling of the lighting environment including a circular-disk type irradiance object plane and the direct simulation of the error distribution with the model. The light source is modeled as a point source that has a certain amount of beam angle, and the luminance distribution on the irradiance plane is modeled as a Gaussian function with different deviation values. A simulation algorithm is devised to estimate the light source orientation computing the average luminance intensities obtained from the irradiance object planes positioned in three different orientations. The effect of the nonideal lighting model is directly reflected in such simulation, because of the analogy between the PSM and the proposed algorithm. With an instrumental tool designed to provide arbitrary orientations of the object plane at the origin of the coordinate system, experiment can be performed in a systematic way for the error analysis and compensation. Simulations are performed to find out the error distribution by widely varying the light model and the orientation set of the object plane. The simulation results are compared with those of the experiment performed in the same way as the simulation. It is confirmed from the experiment that a fair amount of errors is due to the erroneous effect of the general-purpose lighting environment.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2009.04a
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• pp.108-108
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• 2009

The main object of this research is to minimize the shock effects which frequently result in fatal damage in wind met mast on impact of barge. The collision between wind met mast and barge is generally a complex problem and it is often not practical to perform rigorous finite element analyses to include all effects and sequences during the collision. LS-dyna generally purpose explicit finite element code, which is a product of ANSYS software, is used to model and analyze the non-linear response of the met mast due to barge collision. A significant part of the collision energy is dissipated as strain energy and except for global deformation modes, the contribution from elastic straining can normally be neglected. On applying impact force of a barge to wind met mast, the maximum acceleration, internal energy and plastic strain were calculated for each load cases using the finite element method and then compare it, varying to the velocity of barge, with one varying to the thickness of rubber fender conditions. Hence, we restrict the present research mainly to the wind met mast and also parametric study has been carried out with various velocities of barge, thickness of wind met mast, thickness and Mooney-Rivlin coefficient of rubber fender with experimental data. The equation of motion of the wind met mast is derived under the assumption that it was ignored vertical movement effect of barge on sea water. Such an analyzing method which was developed so far, make it possible to determine the proper size and material properties of rubber fender and the optimal moving conditions of barge, and finally, application method can be suggested in designing process of rubber fender considering barge impact.

• The KIPS Transactions:PartC
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• v.17C no.1
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• pp.15-26
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• 2010

Social Networks such as 'Facebook' and 'Myspace' are regarded as useful tools for people to share interests and maintain or expand relationships with other people. However, they pose the risk that personal information can be exposed to other people without explicit permission from the information owner. Therefore, we need a solution for this problem. Although existing social network sites allow users to specify the exposing range or users who can access their personal information, this cannot be a practical solution because the information can still be revealed to third parties through the permitted users albeit unintentionally. Usually, people allow the access of unknown person to personal data in online social networks and this implies the possibility of information leakage. We could use an access control method based on trust value, but this has the limitation that it cannot reflect the quantitative risk of information leakage. As a solution to this problem, this paper proposes an access control method based on a synthesized metric from trust and risk factors. Our various experiments show that the risk of information leakage can play an important role in the access control of online social networks.

• Journal of Korean Society of Forest Science
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• v.100 no.3
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• pp.455-465
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• 2011

In order to assess and mitigate climate change, the role of forest biomass as carbon sink has to be understood spatially and quantitatively. Since existing forest statistics can not provide spatial information about forest resources, it is needed to predict spatial distribution of forest biomass under an alternative scheme. This study focuses on developing an upscaling method that expands forest variables from plot to landscape scale to estimate spatially explicit aboveground biomass(AGB). For this, forest stand variables were extracted from National Forest Inventory(NFI) data and used to develop AGB regression models by tree species. Dominant/codominant height and crown density were used as explanatory variables of AGB regression models. Spatial distribution of AGB could be estimated using AGB models, forest type map and the stand height map that was developed by forest type map and height regression models. Finally, it was estimated that total amount of forest AGB in Danyang was 6,606,324 ton. This estimate was within standard error of AGB statistics calculated by sample-based estimator, which was 6,518,178 ton. This AGB upscaling method can provide the means that can easily estimate biomass in large area. But because forest type map used as base map was produced using categorical data, this method has limits to improve a precision of AGB map.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.2
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• pp.244-251
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• 2007

Intention reading technique is essential to provide personalized services toward more convenient and human-friendly services in complex ubiquitous environment such as a smart home. If a system has knowledge about an user's intention of his/her behavioral pattern, the system can provide mote qualified and satisfactory services automatically in advance to the user's explicit command. In this sense, learning capability is considered as a key function for the intention reading technique in view of knowledge discovery. In this paper, ore introduce a personalized media control method for a possible application iii a smart home. Note that data pattern such as human behavior contains lots of inconsistent data due to limitation of feature extraction and insufficiently available features, where separable data groups are intermingled with inseparable data groups. To deal with such a data pattern, we introduce an effective engineering approach with the combination of fuzzy logic and probabilistic reasoning. The proposed learning system, which is based on IFCS (Iterative Fuzzy Clustering with Supervision) algorithm, extract probabilistic fuzzy rules effectively from the given numerical training data pattern. Furthermore, an extended architectural design methodology of the learning system incorporating with the IFCS algorithm are introduced. Finally, experimental results of the media contents recommendation system are given to show the effectiveness of the proposed system.

• Journal of KIISE:Software and Applications
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• v.37 no.4
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• pp.282-296
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• 2010

OWL is an ontology language for the Semantic Web, and suited to modelling the knowledge of a specific domain in the real-world. Ontology also can infer new implicit knowledge from the explicit knowledge. However, the modeled knowledge cannot be complete as the whole of the common-sense of the human cannot be represented totally. Ontology do not concern handling nonmonotonic reasoning to detect incomplete modeling such as the integrity constraints and exceptions. A default rule can handle the exception about a specific class in ontology. Integrity constraint can be clear that restrictions on class define which and how many relationships the instances of that class must hold. In this paper, we propose a practical reasoning system for open and closed-world reasoning that supports a novel hybrid integration of ontology based on open world assumption (OWA) and non-monotonic rule based on closed-world assumption (CWA). The system utilizes a method to solve the problem which occurs when dealing with the incomplete knowledge under the OWA. The method uses the answer set programming (ASP) to find a solution. ASP is a logic-program, which can be seen as the computational embodiment of non-monotonic reasoning, and enables a query based on CWA to knowledge base (KB) of description logic. Our system not only finds practical cases from examples by the Protege, which require non-monotonic reasoning, but also estimates novel reasoning results for the cases based on KB which realizes a transparent integration of rules and ontologies supported by some well-known projects.