• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.6
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• pp.735-746
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• 1999

We design the robust and inherently fault tolerant decetralized$$H^infty$$ filter for the multisensor state estimation problem when there are insufficient priori informations on the statistical properties of external disturbances. For developing the proposed algorithm, an alternative form of suboptimal$$H^infty$$ filter equations are formulated by applying an alternative form of Kalman filter equations to the indefinite inner product space state model of suboptimal$$H^infty$$ filtering problems. The decentralized$$H^infty$$ filter that consists of local and central fusion filters can be designed effciently using the proposed alternative$$H^infty$$ filiter gain equations. The proposed decentralized$$H^infty$$ filter is robust against un-known external disturbances since it bounds the maximum energy gain from the external disturbances to the estimation errors under the prescribed level$$r^2$$ in both local and central fusion filters and is also fault tolerant due to its inherent redundancy. In addition, the central fusion equations between the global and local data can reduce the unnecessary calculation burden effectively. Computer simulations are made to ceritfy the robustness and fault tolerance of the proposed algorithm.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.3
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• pp.537-547
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• 2001

The paper proposes the fuzzy logic global approximate optimization strategies in optimal sizing of automotive A-pillar trim with rib structures for occupant head protection. Two different strategies referred to as evolutionary fuzzy modeling (EFM) and neuro-fuzzy modeling (NFM) are implemented in the context of global approximate optimization. EFM and NFM are based on soft computing paradigms utilizing fuzzy systems, neural networks and evolutionary computing techniques. Such approximation methods may have their promising characteristics in a case where the inherent nonlinearity in analysis model should be accommodated over the entire design space and the training data is not sufficiently provided. The objective of structural design is to determine the dimensions of rib in A-pillar, minimizing the equivalent head injury criterion HIC(d). The paper describes the head-form modeling and head impact simulation using LS-DYNA3D, and the approximation procedures including fuzzy rule generation, membership function selection and inference process for EFM and NFM, and subsequently presents their generalization capabilities in terms of number of fuzzy rules and training data.

• Korean Journal of Adult Nursing
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• v.15 no.4
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• pp.650-659
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• 2003

Purpose: The purpose of this study was to identify predictors of depression and quality of life among older adults with osteoarthritis. The predictors included in the model were the client's characteristics(age, pain, disease duration, ADLs), personal resources(hardiness, self-care agency and family support), and depression. Method: 150 subjects who were older than 65 years and had diagnosis of osteoarthritis participated in the study. To answer the research questions, descriptive analysis, Pearson correlation, and hierarchical multiple regression were utilized using SPSS WIN program. Result: Older adults who were younger and had lower levels of pain and dependency on ADLs, and higher levels of self care agency and hardiness reported lower levels of depression($R^2=0.517$). Older adults who had lower levels of depression, pain, and dependency on ADLs, higher levels of family support and hardiness, and who are younger reported higher levels of quality of life($R^2=0.084$). Conclusion: Based on the findings of this study, development of nursing intervention program including pain reduction, enhancing ADL abilities and personal resources (hardiness, family support) can be suggested. Further study is needed to increase the ability of generalization of the study findings to the broader population.

• Journal of Korean Society on Water Environment
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• v.32 no.6
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• pp.511-519
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• 2016

National Institute of Environmental Research (NIER) has developed the Korean Reach File (KRF) for scientific and systematic analysis of variables related to water quality, pollutant sources and aquatic ecosystems in consideration of steam reach networks. The KRF provides a new framework for data production, storage, management and analysis for water related variables in relation to spatial characteristics, connections, and topologies of stream reaches. However, the current version of KRF (ver.2) has limited applicability because its nodes include not only the stream points based on topological characteristics but also those based on water quality monitoring stations, which may undermine its generality. In this study, a new version of KRF (ver.3) was designed and established to overcome the weak point of version 2. The version 3 is a generalization of the old KRF graphic data and it integrates the attribute data while separating it from the graphic data to minimize additional work that is needed for data association and search. We tested the KRF (ver.3) on actual cases and convenience and adaptability for each application was verified. Further research should focus on developing a database link model and real-world applications that are targeted to process event data.

• Korean Journal of Clinical Pharmacy
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• v.30 no.3
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• pp.169-176
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• 2020

Background: Most meta-analyses of risk factors for severe or critical outcomes in patients with COVID-19 only included studies conducted in China and this causes difficulties in generalization. Therefore, this study aimed to systematically evaluate the risk factors in patients with COVID-19 from various countries. Methods: PubMed, Embase, and Web of Science were searched for studies published on the mortality risk in patients with COVID-19 from January 1 to May 7, 2020. Pooled estimates were calculated as odds ratio (OR) with 95% confidence interval (CI) using the random-effects model. Results: We analyzed data from seven studies involving 26,542 patients in total in this systematic review and meta-analysis. Among the patients, 2,337 deaths were recorded (8.8%). Elderly patients and males showed significantly higher mortality rates than young patients and females; the OR values were 3.6 (95% CI 2.5-5.1) and 1.2 (95% CI 1.0-1.3), respectively. Among comorbidities, hypertension (OR 2.3, 95% CI 1.1-4.6), diabetes (OR 2.2, 95% CI 1.2-3.9), cardiovascular disease (OR 3.1, 95% CI 1.5-6.3), chronic obstructive pulmonary disease (OR 4.4, 95% CI 1.7-11.5), and chronic kidney disease (OR 4.2, 95% CI 2.0-8.6) were significantly associated with increased mortalities. Conclusion: This meta-analysis, involving a huge global sample, employed a systematic method for synthesizing quantitative results of studies on the risk factors for mortality in patients with COVID-19. It is helpful for clinicians to identify patients with poor prognosis and improve the allocation of health resources to patients who need them most.

• Journal of Korean Library and Information Science Society
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• v.35 no.1
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• pp.187-213
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• 2004

Nowadays changes of financial environment are internalization, generalization and autonomous system. The most importance in a struggle for existence is to secure a customer. The purpose of this study is to analyze whether information on financial service accounts have fully offered over internet, which information consumers needed in buying financial service accounts and whether consumer have satisfied with offered information Through this, to enhance the efficiency of financial information offered to consumer over internet and to explore the consumer demanding information model by finding the problems of offering financial information. The specific purpose of this study me following; 1. to investigate the actual situation which consumers behaviour of information providing and choosing about financial accounts items on internet. 2. to analyze the relationship between the level of consumer information need about financial information and rotated variables. 3. to analyze the relationship between the level of consumer information satisfaction about financial information over internet and related variables. 4. to analyze the new information financial service and contents. 5. to analyze the informatic information and financial service accounts.

• Journal of Biosystems Engineering
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• v.17 no.1
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• pp.65-78
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• 1992

When using a computer vision system for a measurement, the geometrically distorted input image usually restricts the site and size of the measuring window. A geometrically distorted image caused by the image sensing and processing hardware degrades the accuracy of the visual measurement and prohibits the arbitrary selection of the measuring scope. Therefore, an image calibration is inevitable to improve the measuring accuracy. A calibration process is usually done via four steps such as measurement, modeling, parameter estimation, and compensation. In this paper, the efficient error calibration technique of a geometrically distorted input image was developed using a neural network. After calibrating a unit pixel, the distorted image was compensated by training CMLAN(Cerebellar Model Linear Associator Network) without modeling the behavior of any system element. The input/output training pairs for the network was obtained by processing the image of the devised sampled pattern. The generalization property of the network successfully compensates the distortion errors of the untrained arbitrary pixel points on the image space. The error convergence of the trained network with respect to the network control parameters were also presented. The compensated image through the network was then post processed using a simple DDA(Digital Differential Analyzer) to avoid the pixel disconnectivity. The compensation effect was verified using known sized geometric primitives. A way to extract directly a real scaled geometric quantity of the object from the 8-directional chain coding was also devised and coded. Since the developed calibration algorithm does not require any knowledge of modeling system elements and estimating parameters, it can be applied simply to any image processing system. Furthermore, it efficiently enhances the measurement accuracy and allows the arbitrary sizing and locating of the measuring window. The applied and developed algorithms were coded as a menu driven way using MS-C language Ver. 6.0, PC VISION PLUS library functions, and VGA graphic functions.

• Journal of Elementary Mathematics Education in Korea
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• v.14 no.3
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• pp.745-768
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• 2010

The purpose of this study at gifted students' solving ability of the given study task by using all knowledge and tools which encompass mathematical contents and curriculums, and developing the teaching learning materials of gifted students in accordance with their level which tan enhance their mathematical thinking ability and develop creative idea. With these considerations in mind, this paper sought for the standard and procedures of teaching learning materials development according to the levels for the education of the mathematically gifted students. presented the procedure model of material development, produced teaching learning methods according to levels in the task of figurate number, and developed prototypes and examples of teaching learning materials for the mathematically gifted students. Based on the prototype of teaching learning materials for the gifted students in mathematics in accordance with their level, this research developed the materials for students and materials for teachers, and performed the modification and complement of material through the field application and verification. It confirmed various solving processes and mathematical thinking levels by analyzing the figurate number tasks. This result will contribute to solving the study task by using all knowledge and tools of mathematical contents and curriculums that encompass various mathematically gifted students, and provide the direction of the learning contents and teaching learning materials which can promote the development of mathematically gifted students.

• Culinary science and hospitality research
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• v.23 no.4
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• pp.193-202
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• 2017

This study conducted a survey on 414 industrial organization food service workers in the Kyungnam area to find out the effect relationship of the job characteristics of organization food service workers and its effects on job commitment and job satisfaction by recognizing the need for job application through the job characteristic model, which was the beginning of the intrinsic motivation theory for the job of organization food service workers. To accomplish the purpose of this study, the method to analyze the survey was undertaken by using the SPSS 23.0 and Amos 21.0 statistic package program via a data coding process for collected data processing. We can confirm from the analysis results that there is a statistically significant causal relationship in all factors, except task identity, which is a sub factor of job characteristic. This result reaffirms the results of previous research by showing that the worker must be allowed to ensure completion of the entire job when performing the job as the job itself is not one part of the processes. Decision-making autonomy must be given in the work process when the worker performs their job in order to raise job satisfaction and furthermore to increase job commitment. The limitation of this study is that there are limits that making generalization as the study was conducted on industrial organization food service workers in the Kyungnam area as extracted samples.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.3
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• pp.215-222
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• 2001

Neural network based models of semiconductor manufacturing processes have been shown to offer advantages in both accuracy and generalization over traditional methods. However, model development is often complicated by the fact that back-propagation neural networks contain several adjustable parameters whose optimal values unknown during training. These include learning rate, momentum, training tolerance, and the number of hidden layer neurOnS. This paper presents an investigation of the use of genetic algorithms (GAs) to determine the optimal neural network parameters for the modeling of plasma-enhanced chemical vapor deposition (PECVD) of silicon dioxide films. To find an optimal parameter set for the neural network PECVD models, a performance index was defined and used in the GA objective function. This index was designed to account for network prediction error as well as training error, with a higher emphasis on reducing prediction error. The results of the genetic search were compared with the results of a similar search using the simplex algorithm.