• Physical Therapy Korea
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• v.15 no.2
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• pp.44-53
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• 2008

The purpose of this preliminary study was to develop a measurement for assessing risk factors for falling in community-dwelling elderly persons. Rasch analysis and principal component analysis were performed to examine whether items on the Activities-Specific Balance Confidence (ABC), assessing self-efficacy, and items on the Berg Balance Scale (BBS), assessing balance function, contribute jointly to a unidimensional construct in the elderly. A total of 35 elderly persons (4 men, 31 women) participated. In this study, each item of ABC (16 items) and BBS (14 items) was scored on a 5-point ordinal rating scale from 0 to 4. The initial Rasch and principal component analysis indicated that 3 of the ABC items and 2 of the BBS items were misfit for this study. These 5 items were excluded from further study. After combining ABC and BBS, Rasch and principal component analyses were examined and finally 23 items selected; 12 items from ABC, 11 items from BBS. The 23 combined ABC-BBC items were arranged in order of difficulty. The hardest item was 'walk outside on icy sidewalks' and the easiest item was 'pivot transfer'. Although structural calibration of each 5 rating scale categories was not ordered, the other three essential criteria of Linacre's optimal rating scale were satisfied. Overall, the ABC-BBS showed sound item psychometric properties. Each of the 5 rating scale categories appeared to distinctly identify subjects at different ability levels. The findings of this study support that the new ABC-BBS scale measure balance function and self-efficacy. It will be a clinically useful assessment of risk factors for falling in the elderly. However, the number of subjects was too small to generalize our results. Further study is needed to develop a new assessment considering more risk factors of falling in elderly.

• Structural Engineering and Mechanics
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• v.72 no.6
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• pp.689-712
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• 2019

Time-series models like AR-ARX and ARMAX, provide a robust way to capture the dynamic properties of structures, and their residuals can be effectively used as features for damage detection. Even though several research papers discuss the implementation of AR-ARX and ARMAX models for damage diagnosis, they are basically been exploited so far for detecting the time instant of damage and also the spatial location of the damage. However, the inverse problem associated with damage quantification i.e. extent of damage using time series models is not been reported in the literature. In this paper, an approach to detect the extent of damage by combining the ARMAX model by formulating the inverse problem as a multi-constrained optimization problem and solving using a newly developed hybrid adaptive differential search with dynamic interaction is presented. The proposed variant of the differential search technique employs small multiple populations which perform the search independently and exchange the information with the dynamic neighborhood. The adaptive features and local search ability features are built into the algorithm in order to improve the convergence characteristics and also the overall performance of the technique. The multi-constrained optimization formulations of the inverse problem, associated with damage quantification using time series models, attempted here for the first time, can considerably improve the robustness of the search process. Numerical simulation studies have been carried out by considering three numerical examples to demonstrate the effectiveness of the proposed technique in robustly identifying the extent of the damage. Issues related to modeling errors and also measurement noise are also addressed in this paper.

• Journal of the Society of Naval Architects of Korea
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• v.50 no.5
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• pp.355-363
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• 2013

Panel methods are essential tools for analyzing a fluid-flow problem around complex three dimensional bodies, but they lack ability to solve viscous effects. On the other hand, CFD methods are considered as powerful tools for analyzing fluid-flow characteristics including viscosity. However, they also have short falls, requiring more computing time and showing different results depending on the selection of turbulence models and grid systems. In this paper a hybrid scheme combining a panel method and a CFD method is suggested. The scheme adopts a panel method for far-field solution where viscous effects are negligible and a CFD method for the solution of RANS equations in near-field where viscous effects are relatively strong. The intermediate region between the far-field and near-field is introduced where the calculated field point velocities by the panel method are given as boundary velocities for the CFD method. To verify the scheme, calculated results, by a panel method, a CFD method and the hybrid scheme, for a two dimensional foil section are compared. The suggested hybrid scheme gives reasonable results, while computation time and memory can be dramatically reduced. By using the hybrid scheme efforts can be concentrated for the local flow near the leading and trailing edges, by providing more dense grid system, where detailed flow characteristics are required.

• Smart Structures and Systems
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• v.25 no.1
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• pp.111-122
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• 2020

Researchers up to date have introduced several Structural Health Monitoring (SHM) techniques with varying advantages and drawbacks for each. Satellite positioning systems (GPS, GLONASS and GALILEO) based techniques proved to be promising, especially for high natural period structures. Particularly, the GPS has proved sufficient performance and reasonable accuracy in tracking real time dynamic displacements of flexible structures independent of atmospheric conditions, temperature variations and visibility of the monitored object. Tall structures are particularly sensitive to oscillations produced by different sources of dynamic actions; such as typhoons. Wind forces induce in the structure both longitudinal and perpendicular displacements with respect to the wind direction, resulting in torsional effects, which are usually more complex to be detected. To efficiently track the horizontal rotations of the in-plane sections of such flexible structures, two main issues have to be considered: a suitable sensor topology (i.e., location, installation, and combination of sensors), and the methodology used to process the data recorded by sensors. This paper reports the contributions of the measurements recorded from dual frequency GPS receivers and uni-axial accelerometers in a full-scale experimental campaign. The Canton tower in Guangzhou-China is the case study of this research, which is instrumented with a long-term structural health monitoring system deploying both accelerometers and GPS receivers. The elaboration of combining the obtained rather long records provided by these two types of sensors in detecting the torsional behavior of the tower under ambient vibration condition and during strong wind events is discussed in this paper. Results confirmed the reliability of GPS receivers in obtaining the dynamic characteristics of the system, and its ability to capture the torsional response of the tower when used alone or when they are combined with accelerometers integrated data.

• Journal of KIISE:Software and Applications
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• v.29 no.1_2
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• pp.1-9
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• 2002

Evolutionary artificial neural networks (EANNs) are towards the near optimal ANN using the global search of evolutionary instead of trial-and-error process. However, many real-world problems are too hard to be solved by only one ANN. Recently there has been plenty of interest on combining ANNs in the last generation to improve the performance and reliability. This paper proposes a new approach of constructing multiple ANNs which complement each other by speciation. Also, we develop a multiple ANN to combine the results in abstract, rank, and measurement levels. The experimental results on Australian credit approval data from UCI benchmark data set have shown that combining of the speciated EANNs have better recognition ability than EANNs which are not speciated, and the average error rate of 0.105 proves the superiority of the proposed EANNs.

• Smart Structures and Systems
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• v.23 no.2
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• pp.107-122
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• 2019

As one of the most important parameters in structural health monitoring, structural frequency has many advantages, such as convenient to be measured, high precision, and insensitive to noise. In addition, frequency-change-ratio based method had been validated to have the ability to identify the damage occurrence and location. However, building a precise enough finite elemental model (FEM) for the test structure is still a huge challenge for this frequency-change-ratio based damage detection technique. In order to overcome this disadvantage and extend the application for frequencies in structural health monitoring area, a novel method was developed in this paper by combining the cross-model cross-mode (CMCM) model updating algorithm with the frequency-change-ratio based method. At first, assuming the physical parameters, including the element mass and stiffness, of the test structure had been known with a certain value, then an initial to-be-updated model with these assumed parameters was constructed according to the typical mass and stiffness distribution characteristic of shear buildings. After that, this to-be-updated model was updated using CMCM algorithm by combining with the measured frequencies of the actual structure when no damage was introduced. Thus, this updated model was regarded as a representation of the FEM model of actual structure, because their modal information were almost the same. Finally, based on this updated model, the frequency-change-ratio based method can be further proceed to realize the damage detection and localization. In order to verify the effectiveness of the developed method, a four-level shear building was numerically simulated and two actual shear structures, including a three-level shear model and an eight-story frame, were experimentally test in laboratory, and all the test results demonstrate that the developed method can identify the structural damage occurrence and location effectively, even only very limited modal frequencies of the test structure were provided.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.2
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• pp.201-210
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• 2023

Deep learning-based face verificattion model show high performance and are used in many fields, but there is a possibility the user's face image may be leaked in the process of inputting the face image to the model. Althoughde-identification technology exists as a method for minimizing the exposure of face features, there is a problemin that verification performance decreases when the existing technology is applied. In this paper, after combining the face features of other person, a de-identified face image is created through StyleGAN. In addition, we propose a method of optimizingthe combining ratio of features according to the face verification model using HopSkipJumpAttack. We visualize the images generated by the proposed method to check the de-identification performance, and evaluate the ability to maintain the performance of the face verification model through experiments. That is, face verification can be performed using the de-identified image generated through the proposed method, and leakage of face personal information can be prevented.

• Korean Journal of Poultry Science
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• v.7 no.1
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• pp.31-42
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• 1980

In order to identify the best superior cross combination of breeder stocks for broiler production, combining ability test and analyses of phenotypic performances for parent stocks were examined on records of 1,440 broiler chicken which were produced from 4 parental strains and 3 maternal strains at Hanhyup Poultry Breeding Farm from September 28, 1978 to January 5, 1979. The results obtained were as follows; 1. There was not found heterosis effect in viability but it seems to be desirable to select Hubbard strain in paternal line to improve viability. 2. As the paternal and maternal lines, selection of Ross strain showed the best paternal and maternal performance and the best general combining ability in body weight at 8 weeks of age is expected to be able to improve body weight of it s crossbred And the most superior cross combinations based on the specific combining ability and performance of rack crossbred were identified as Hubbard x Ross ana Ross x Hypeco crossbreds. 3. The best paternal and maternal lines on the smallest feed consumption for 8 weeks were Hubbard and Ross strains, and Hypeco strain, respectively. Especially Hubbard x Hypeco cross combination was proved as the smallest feed consumption compared with other cross combinations. 4. In feed requirement per Kg body weight increase, Hubbard strain for paternal line, Hypeco strain for naternal line, and cross combinations of Hubbard x Hypeco, Hubbard x Ross and Ross x Hypeco were certified as the most superiors. 5. Also superior cross combinations of Hubbard x Hypeco and Hubbard x Ross earned the most profit per bird through economic analysis. According to results as shown above, this experiment seems to be able to reach a such conclusion that production of superior cross combinations Hubbard x Ross, Hubbard x Hypeco and Ross x Hypeco through selection of Ross and Hubbard strains to paternal line and Hypeco and Ross strains for maternal line may become to considerable improvement for important economic characters of broiler; viability, body weight, feed consumption and feed requirement.

• Korean journal of applied entomology
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• v.17 no.4 s.37
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• pp.193-199
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• 1978

Five parents and their 10 $F_1$ crosses of maize (Zea mays L.) were tested by means of diallel analysis for the inheritance of peroxidase activity following Puccinia sorghi rust infection. Peroxidase activity was measured at day zero and at 2 days and 8 days after inoculation. Peroxidase activity was increased significantly by P. sorghi infection in all 15 genotypes after 8 days, but not after 2 days. Highly significant differences in peroxidase activity were detected among the 15 genotypes. The highly genera] resistant inbred, CM105, and its hybrids showed exceptionally high peroxidase activity in both healthy and infected plants. However, another highly resistant inbred, Oh545, showed exceptionally low peroxidase activity. Significant general combining ability (GCA) and specific combining ability (SCA) means quares were detected for peroxidase activity independent of disease. GCA mean spuares, however, were consistently a major contiribution to the inheritance of peroxidase activity in the infected plants whereas SCA men square contributions were minor. Rust resistant maize plants controlling mongenic dominant $Rp_1^d$gene showed stronger peroxidase reroxidase responses than their susceptible counterparts in the gel electrophoresis and densiometric tracings. The increased peroxidase activity occurred in both major leaf peroxidases, $Px_3\;and\; Px_7$.

• Korean Journal of Weed Science
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• v.10 no.3
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• pp.179-185
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• 1990

Five parents which showed differential response to thiobencarb and their $F_1$ hybrids were treated with thiobencarb (S-[(4-chlorophenyl) methyl]diethylcarbamothioate) at 2 and 4 kg ai/ha in order to investigate the inheritance of rice (Oryza sativa L.) to the herbicide. In the analysis of diallel crosses for tolerance of rice cultivars to the herbicide, highly significant GCA (general combining ability) and SCA (specific combining ability) effects were observed at both herbicide rates using the parameters of plant height and dry weight ; the GCA effect being greater than the SCA effect. The additive effects appeared to be more prevalent than dominance effects, and partial dominance was recognized in relation to herbicide tolerance in the different rice cultivars. Higher heritabilities in the narrow and broad senses were observed at 4 kg ai/ha. The heritabilities in the narrow sense for plant height and dry weight were 0.726 and 0. 743, respectively. IR9660-50-3-1 which showed the highest GCA effects seemed to possess more dominant genes related to herbicide tolerance than the other rice cultivars tested.