• 대한조현병학회지
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• 제17권1호
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• pp.36-42
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• 2014

Objectives : The dysfunctional neural networks underlying self-evaluation in schizophrenia are overlapped with the neural structures involved in emotion regulation. The purpose of this study was to investigate the influence of anhedonia on the self-evaluation attitude of patients with schizophrenia. Methods : Twenty healthy controls and twenty patients with schizophrenia performed a self-evaluation task, presenting a pair of the face (self, familiar other, and unfamiliar other) and word (negative, neutral, and positive noun) at the same time. Participants were asked to evaluate relevance between the pairs by pressing a corresponding button. Relevance rating scores were compared between the groups and were correlated with the severity of physical and social anhedonia. Results : Patients evaluated the condition of a self face with a negative word and a familiar face with a negative word to be more relevant than healthy controls. In the patient group, the scores of relevance rating in the condition of an unfamiliar other face with a negative word were positively correlated with the anhedonia scale scores (physical : r=0.486, p=0.030 ; social : r=0.499, p=0.025). There was no correlation between the self-evaluation attitude and the severity of anhedonia. Conclusion : Patients with schizophrenia evaluate themselves badly in only negative circumstances, and anhedonia is not related to self-evaluation, but rather other-evaluation.

• Smart Structures and Systems
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• 제16권2호
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• pp.295-328
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• 2015

In recent years the monitoring of structural behavior through acquisition of vibrational data has become common practice. In addition, recent advances in sensor development have made the collection of diverse dynamic information feasible. Other than the commonly collected acceleration information, Global Position System (GPS) receivers and non-contact, optical techniques have also allowed for the synchronous collection of highly accurate displacement data. The fusion of this heterogeneous information is crucial for the successful monitoring and control of structural systems especially when aiming at real-time estimation. This task is not a straightforward one as measurements are inevitably corrupted with some percentage of noise, often leading to imprecise estimation. Quite commonly, the presence of noise in acceleration signals results in drifting estimates of displacement states, as a result of numerical integration. In this study, a new approach based on a time domain identification method, namely the Unscented Kalman Filter (UKF), is proposed for correcting the "drift effect" in displacement or rotation estimates in an online manner, i.e., on the fly as data is attained. The method relies on the introduction of artificial white noise (WN) observations into the filter equations, which is shown to achieve an online correction of the drift issue, thus yielding highly accurate motion data. The proposed approach is demonstrated for two cases; firstly, the illustrative example of a single degree of freedom linear oscillator is examined, where availability of acceleration measurements is exclusively assumed. Secondly, a field inspired implementation is presented for the torsional identification of a tall tower structure, where acceleration measurements are obtained at a high sampling rate and non-collocated GPS displacement measurements are assumed available at a lower sampling rate. A multi-rate Kalman Filter is incorporated into the analysis in order to successfully fuse data sampled at different rates.

• 한국시뮬레이션학회논문지
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• 제27권3호
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• pp.53-63
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• 2018

미래 전장 환경이 복잡하고 다양화됨에 따라 조직에 적절한 구조 및 편성을 작성하는 것도 간단하지 않은 일이 되었다. 이에 본 연구에서는 육군의 미래 제대별 참모부 편성을 시스템 다이내믹스를 활용하여 검증하는 방법론을 제시한다. 참모부 구조 및 편성 검증을 위한 SD 활용 절차는 입력 DB값 산출, 인과지도 작성 및 모델 구축, 모의 및 분석 순으로 진행된다. 시스템 다이내믹스를 활용한 모의분석의 취약점은 입력 값에 따라 결과가 달라질 수 있고 모의인원의 관점에 따라 분석이 달라질 수 있다는 것이다. 본 연구에서는 이에 대한 보완책으로 연구 분석, 설문 등을 병행하여 종합분석에 포함하는 방법을 적용하였다. 본 연구의 의의는 군조직의 구조 및 편성을 검증하기 위한 과학적인 방법으로 조직편성의 적절성을 정량화하여 판단할 수 있는 전투실험 방법을 제시함으로써 그 활용 가치가 크다고 판단된다.

• 한국해양공학회지
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• 제29권1호
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• pp.45-55
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• 2015

Because of the high stress concentration near the toe of a welded joint, the calculation of local stress using the finite element method which is relevant to the fatigue strength of the weld toe crack, is a challenging task. This is mainly caused by the sensitivity of finite element analysis, which usually occurs near the area of a dramatically changing stress field. This paper presents a novel numerical method through which a less mesh-sensitive local stress calculation can be achieved based on the 3D solid finite element, strictly sticking to the original definition of hot spot stress. In order to achieve the goal, a traction stress, defined at 0.5t and 1.5t away from the weld toe, was calculated using either a force-equivalent or work-equivalent approach, both of which are based on the internal nodal forces on the imaginary cut planes. In the force-equivalent approach, the traction stress on the imaginary cut plane was calculated using the simple force and moment equilibrium, whereas the equivalence of the work done by both the nodal forces and linearized traction stress was employed in the work-equivalent approach. In order to confirm the validity of the proposed method, five typical welded joints widely used in ships and offshore structures were analyzed using five different solid element types and four different mesh sizes. Finally, the performance of the proposed method was compared with that of the traditionally used surface stress extrapolation method. It turned out that the sensitivity of the hot spot stress for the analyzed typical welded joints obtained from the proposed method outperformed the traditional extrapolation method by far.

• Journal of Advanced Research in Ocean Engineering
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• 제1권2호
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• pp.106-114
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• 2015

In the fabrication of offshore oil and gas facilities, the significance of dimension control is growing continuously. But, it is difficult to determine the deformation of the structure during fabrication by simple lab tests due to the large size and the complicated shape. Strain-boundary method (a kind of shrinkage method) based on the shell element was proposed to predict the welding distortion of a structure effectively. Modeling of weld geometry in shell element is still a difficult task. In this paper, a concept of imaginary temperature pair is introduced to handle the effect of geometric factors such as groove shape, plate thickness and pass number, etc. Single pass imaginary temperature pair formula is derived from the relation between the groove area and the FE mesh size. By considering the contribution of each weld layer to the whole weldment, multi-pass imaginary temperature is also derived. Since the temperature difference represents the distortion increment, cumulative distortion curve can be drawn by integrating the temperature difference. This curve will be a useful solution when engineers meet some problems occurred in the shipyard. A typical example is shown about utilization of this curve. Several verifications are conducted to examine the validity of the proposed methodology. The applicability of the model is also demonstrated by applying it to the fabrication process of the heavy ship block. It is expected that the imaginary temperature model can effectively solve the modeling problem in shell element. It is also expected that the cumulative distortion curve derived from the imaginary temperature can offer useful qualitative information about angular distortion without FE analysis.

• Smart Structures and Systems
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• 제15권5호
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• pp.1373-1392
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• 2015

Placing sensors at appropriate locations is an important task in the design of an efficient structural health monitoring (SHM) system for a large-scale civil structure. In this paper, a hybrid optimization algorithm called virus monkey algorithm (VMA) based on the virus theory of evolution is proposed to seek the optimal placement of sensors. Firstly, the dual-structure coding method is adopted instead of binary coding method to code the solution. Then, the VMA is designed to incorporate two populations, a monkey population and a virus population, enabling the horizontal propagation between the monkey and virus individuals and the vertical inheritance of monkey's position information from the previous to following position. Correspondingly, the monkey population in this paper is divided into the superior and inferior monkey populations, and the virus population is divided into the serious and slight virus populations. The serious virus is used to infect the inferior monkey to make it escape from the local optima, while the slight virus is adopted to infect the superior monkey to let it find a better result in the nearby area. This kind of novel virus infection operator enables the coevolution of monkey and virus populations. Finally, the effectiveness of the proposed VMA is demonstrated by designing the sensor network of the Canton Tower, the tallest TV Tower in China. Results show that innovations in the VMA proposed in this paper can improve the convergence of algorithm compared with the original monkey algorithm (MA).

• 대한의용생체공학회:의공학회지
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• 제34권2호
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• pp.55-62
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• 2013

Wrist joints consist of irregularly shaped carpal bones and other complicated structures. Thus, evaluating the motion of a wrist joint is a challenging task. In this study, we used an infrared camera to perform a kinematic analysis of a dart-throwing motion. We measured the difference between the movement of a normal wrist and constrained wrist (wrist with a wrist glove) in the dart-throwing motion with thirty six healthy participants. We measured the ulna flexion - radial extension motion using the attached passive marker and analyzed it using Polygon software and SPSS. The pitch and yaw motions with a glove was bigger than the ones without a glove by 20 and 15 degrees, respectively. On the other hand, the roll motion without a glove was bigger than the one with a glove by 7 degree. Wilcoxon signed rank test (p<0.05) confirmed that there are significant differences between the motion with and without a glove. It was found that the magnitude of the pitch and yaw motion with a constrained wrist joint toward radial extension in dart-throwing motion is smaller than the one with a normal wrist joint. However, a normal wrist joint showed a bigger movement in the roll direction.

• 지능정보연구
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• 제4권1호
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• pp.133-147
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• 1998

Recently, many researchers have been involved in finding deterministic equations which can accurately predict future event, based on chaotic theory, or fractal theory. The theory says that some events which seem very random but internally deterministic can be accurately predicted by fractal equations. In contrast to the conventional methods, such as AR model, MA, model, or ARIMA model, the fractal equation attempts to discover a deterministic order inherent in time series data set. In discovering deterministic order, researchers have found that neural networks are much more effective than the conventional statistical models. Even though prediction accuracy of the network can be different depending on the topological structure and modification of the algorithms, many researchers asserted that the neural network systems outperforms other systems, because of non-linear behaviour of the network models, mechanisms of massive parallel processing, generalization capability based on adaptive learning. However, recent survey shows that prediction accuracy of the forecasting models can be determined by the model structure and data structures. In the experiments based on actual economic data sets, it was found that the prediction accuracy of the neural network model is similar to the performance level of the conventional forecasting model. Especially, for the data set which is deterministically chaotic, the AR model, a conventional statistical model, was not significantly different from the MLP model, a neural network model. This result shows that the forecasting model. This result shows that the forecasting model a, pp.opriate to a prediction task should be selected based on characteristics of the time series data set. Analysis of the characteristics of the data set was performed by fractal analysis, measurement of Hurst index, and measurement of Lyapunov exponents. As a conclusion, a significant difference was not found in forecasting future events for the time series data which is deterministically chaotic, between a conventional forecasting model and a typical neural network model.

• 산업공학
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• 제24권1호
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• pp.1-7
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• 2011

The purpose of this research was to develop an integrated interface for the usability test of systems or products in the design process. It is capable of automatically creating GOMS models which can predict human task performances. It can generate GOMS models to be interacted with the prototype interfaces. It can also effectively manage various design information and various usability test results to be implemented into the new product and/or system design. Thus we can perform usability test for products or system prototypes more effectively and also reduce time and effort required for this test. For usability tests, we established an integrated interface based on GOMS model by the LabVIEW program. We constructed the system that the linkage to GOMS model is available. Using this integrated interface, the menu structure of mobile phone can be constructed easily. User can design a depth and a breath that he want. The size of button and the label of the button is changable. The path to the goal can be defined by the user. Using a designed menu structure, the experiment could be performed. The results of GOMS model and the actual time are presented. Besides, values of operators of GOMS model can be defined as the value that user wants. Using the integrated interface that we developed, the optimal menu structure deducted. The menu structure that user wants can be established easily. The optimal layout and button size can be decided by comparison of numerous menu structures. User can choose the method of usability test among GOMS model and empirical data. Using this integrated interface, the time and costs can be saved and the optimal menu structure can be found easily.

• Steel and Composite Structures
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• 제45권2호
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• pp.205-218
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• 2022

Proper calculation of splitting tensile strength (STS) of concrete has been a crucial task, due to the wide use of concrete in the construction sector. Following many recent studies that have proposed various predictive models for this aim, this study suggests and tests the functionality of three hybrid models in predicting the STS from the characteristics of the mixture components including cement compressive strength, cement tensile strength, curing age, the maximum size of the crushed stone, stone powder content, sand fine modulus, water to binder ratio, and the ratio of sand. A multi-layer perceptron (MLP) neural network incorporates invasive weed optimization (IWO), cuttlefish optimization algorithm (CFOA), and electrostatic discharge algorithm (ESDA) which are among the newest optimization techniques. A dataset from the earlier literature is used for exploring and extrapolating the STS behavior. The results acquired from several accuracy criteria demonstrated a nice learning capability for all three hybrid models viz. IWO-MLP, CFOA-MLP, and ESDA-MLP. Also in the prediction phase, the prediction products were in a promising agreement (above 88%) with experimental results. However, a comparative look revealed the ESDA-MLP as the most accurate predictor. Considering mean absolute percentage error (MAPE) index, the error of ESDA-MLP was 9.05%, while the corresponding value for IWO-MLP and CFOA-MLP was 9.17 and 13.97%, respectively. Since the combination of MLP and ESDA can be an effective tool for optimizing the concrete mixture toward a desirable STS, the last part of this study is dedicated to extracting a predictive formula from this model.