• 비파괴검사학회지
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• 제31권5호
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• pp.494-499
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• 2011

인체 근골격 시스템에 대한 다물체 동역학 모델을 이용한 동작중의 인체 내부의 생체역학 분석 및 평가 기술에 대하여 기술하였다. 의료영상과 사체실험 결과를 기본으로 하는 인체 다물체 동역학 모델과 3차원 동작분석 시스템을 이용한 인체 동작분석기술을 이용하여 생체내 발생하는 관절기구학, 관절모멘트 관절접촉력 및 근력을 예측하는 기술을 보행과 팔굽혀펴기 두 동작에 적용하였다. 본 연구에서 개발한 인체 다물체 동역학 모델링 기술과 3차원 동작분석기술은 다양한 동작을 수행하는 생체의 분석 및 평가 기술로 활용성이 높을 것으로 생각한다.

• Geomechanics and Engineering
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• 제31권1호
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• pp.113-127
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• 2022

The undrained shear strength of soil is considered one of the engineering parameters of utmost significance in geotechnical design methods. In-situ experiments like cone penetration tests (CPT) have been used in the last several years to estimate the undrained shear strength depending on the characteristics of the soil. Nevertheless, the majority of these techniques rely on correlation presumptions, which may lead to uneven accuracy. This research's general aim is to extend a new united soft computing model, which is a combination of random forest (RF) with grasshopper optimization algorithm (GOA) to the pile set-up parameters' better approximation from CPT, based on two different types of data as inputs. Data type 1 contains pile parameters, and data type 2 consists of soil properties. The contribution of this article is that hybrid GOA - RF for the first time, was suggested to forecast the pile set-up parameter from CPT. In order to do this, CPT data and related bore log data were gathered from 70 various locations across Louisiana. With an R² greater than 0.9098, which denotes the permissible relationship between measured and anticipated values, the results demonstrated that both models perform well in forecasting the set-up parameter. It is comprehensible that, in the training and testing step, the model with data type 2 has finer capability than the model using data type 1, with R² and RMSE are 0.9272 and 0.0305 for the training step and 0.9182 and 0.0415 for the testing step. All in all, the models' results depict that the A parameter could be forecasted with adequate precision from the CPT data with the usage of hybrid GOA - RF models. However, the RF model with soil features as input parameters results in a finer commentary of pile set-up parameters.

• 한국도로학회논문집
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• 제16권3호
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• pp.35-41
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• 2014

PURPOSES : The dynamic modulus for a specimen can be determined by using either the non-destructed or destructed testing method. The Impact Resonance Testing (IRT) is the one of the non-destructed testing methods. The MTS has proved the source credibility and has the disadvantages which indicate the expensive equipment to operate and need a lot of manpower to manufacture the specimens because of the low repeatability with an experiment. To overcome these shortcomings from MTS, the objective of this paper is to compare the dynamic modulus obtained from IRT with MTS result and prove the source credibility. METHODS : The dynamic modulus obtained from IRT could be determined by using the Resonance Frequency (RF) from the Frequency Response Function (FRF) that derived from the Fourier Transform based on the Frequency Analysis of the Digital Signal Processing (DSP)(S. O. Oyadigi; 1985). The RF values are verified from the Coherence Function (CF). To estimate the error, the Root Mean Squared Error (RMSE) method could be used. RESULTS : The dynamic modulus data obtained from IRT have the maximum error of 8%, and RMSE of 2,000MPa compared to the dynamic modulus measured by the Dynamic Modulus Testing (DMT) of MTS testing machine. CONCLUSIONS : The IRT testing method needs the prediction model of the dynamic modulus for a Linear Visco-Elastic (LVE) specimen to improve the suitability.

• 한국정보전자통신기술학회논문지
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• 제9권5호
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• pp.496-502
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• 2016

본 논문에서는 소프트웨어 제품을 개발하여 테스팅을 하는 시행에서 소프트웨어 운용자들이 소프트웨어 검사 도구에 적용할 수 있는 학습기법에 근거한 NHPP 소프트웨어 모형에 대하여 비교 연구 하였다. 수명분포는 Makeham 분포를 이용하고 유한고장 NHPP모형을 적용하였다. 소프트웨어 오류 탐색 방법은 미리 인지하지 못하지만 자동적으로 발견되는 에러에 영향을 주는 영향요인과 사전경험에 기초하여 에러를 관찰하기 위하여 테스팅 운용자가 미리 설정해놓은 요인인 학습효과의 영향에 대한 문제를 비교 분석하였다. 그 결과 학습요인이 자동 에러 탐색요인보다 큰 경우가 일반적으로 효율적인 모형으로 나타났다. 본 논문의 신뢰특성분석에서는 소프트웨어고장시간을 적용하고 모수추정 방법은 최우추정법을 적용하고 추세분석을 통하여 자료의 신뢰성을 확보한 이후에 평균제곱오차와 $R^2$ (결정계수)를 적용하여 효율적인 모형을 선택 비교 분석하였다. 이 연구를 통하여 소프트웨어 운영자들은 다양한 학습효과를 고려함으로서 소프트웨어 고장추세에 대한 기본지식을 파악하는데 하나의 지침으로 사용가능함을 보여주고 있다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권2호
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• pp.726-741
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• 2022

The purpose of this study is to provide instructive theoretical models for art (music) education institutions especially when unpredictable risks, such as pandemics, occur again. Based on the customer behavior theory of the business-to-business-to-customer (B2B2C) platform, and in combination with the technology acceptance model (TAM) and expectation confirmation model (ECM), this study proposes an online education model from the perspective of art education. The framework is based on the three decision-making processes of the customer, and includes the product owner, content owner, and customer area. This paper highlights the factors that influence customers in making decisions when art education institutions are product owners. Regression analysis was introduced to study the factors influencing the expectation confirmation, and the overall fitting testing and six hypotheses testing of 385 effective samples were performed using the structural equation modeling (SEM). The results show that the course-design and after-service positively influenced the expectation confirmation, and the domain image positively influenced the continuance behavior. Negative emotions skipped the mediator (expectation confirmation) and directly exerted a significant negative impact on customers' willingness to continue system usage (continuance behavior). In addition, expectation confirmation positively influenced continuance behavior. The paths of detailed items comprising course-design, after-service, and negative emotion were also analyzed and discussed. In this path analysis, ordinary art learners did not believe that AI partners can play a very good auxiliary role. The findings contribute to the scope of information systems acting as an art education platform academically, and provide effective and theoretical support for the actual operation of art education institutions.

• Geomechanics and Engineering
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• 제36권4호
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• pp.381-390
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• 2024

The introduction of bio-based materials has been recommended in the geotechnical engineering field to reduce environmental pollutants such as heavy metals and greenhouse gases. However, bio-treated soil methods face limitations in field application due to short research periods and insufficient verification of engineering performance, especially when compared to conventional materials like cement. Therefore, this study aimed to develop a machine learning model for predicting the unconfined compressive strength, a representative soil property, of biopolymer-based soil treatment (BPST). Four machine learning algorithms were compared to determine a suitable model, including linear regression (LR), support vector regression (SVR), random forest (RF), and neural network (NN). Except for LR, the SVR, RF, and NN algorithms exhibited high predictive performance with an R² value of 0.98 or higher. The permutation feature importance technique was used to identify the main factors affecting the strength enhancement of BPST. The results indicated that the unconfined compressive strength of BPST is affected by mean particle size, followed by biopolymer content and water content. With a reliable prediction model, the proposed model can present guidelines prior to laboratory testing and field application, thereby saving a significant amount of time and money.

• International Journal of Internet, Broadcasting and Communication
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• 제15권2호
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• pp.261-267
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• 2023

A common approach to the problem of predicting student test scores is based on the student's previous educational history. In this study, high school transcripts of about two thousand candidates, who took the High-school Student Assessment (HSA) were collected. The data were estimated through building a regression model - Random Forest and optimizing the model's parameters based on Genetic Algorithm (GA) to predict the HSA scores. The RMSE (Root Mean Square Error) measure of the predictive models was used to evaluate the model's performance.

• 비파괴검사학회지
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• 제31권3호
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• pp.246-259
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• 2011

This study presents a structural health monitoring (SHM) method for bolted connections by using multi-channel wireless impedance sensor nodes and multiple PZT-interfaces. To achieve the objective, the following approaches are implemented. Firstly, a PZT-interface is designed to monitor bolt loosening in bolted connection based on variation of electro-mechanical(EM) impedance signatures. Secondly, a wireless impedance sensor node is designed for autonomous, cost-efficient and multi-channel monitoring. For the sensor platform, Imote2 is selected on the basis of its high operating speed, low power requirement and large storage memory. Finally, the performance of the wireless sensor node and the PZT-interfaces is experimentally evaluated for a bolt-connection model Damage monitoring method using root mean square deviation(RMSD) index of EM impedance signatures is utilized to estimate the strength of the bolted joint.

• 비파괴검사학회지
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• 제25권3호
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• pp.178-188
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• 2005

This paper introduces a structural damage identification method to identify 4he multiple directional damages generated within a cylindrical shell by using the measured frequency response function (FRF). The equations of motion for a damaged cylindrical shell are derived. by using a theory of continuum damage mechanics in which a small material volume containing a directional damage is represented by the effective orthotropic elastic stiffness. In contrast with most existing vibration-based structural damage identification methods which require the modal Parameters measured in both intact and damaged states, the present method requires only the FRF-data measured at damaged state. Numerically simulated damage identification tests are conducted to verify the feasibility of the Proposed structural damage identification method.

• 대한간호
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• 제30권4호
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• pp.61-68
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• 1991

This study was conducted to testing the criterion - related validity of a mental health assessment tool which developed based on a korean culture. Criteria scale for this tool were MMPI and CMI(M - R). The study subject were 100 male and female aged 20 or more with quota sampling. The data was collected from August 16. to August 26. 1989. The data obtained from 85 subjects were analysed using S.P.S.S.(Stastistical Package for the Social Science). As a result, there are no significant correlation between Mental Health Assessment Tool and MMPI and CMI except Mf(Masculinity-Feminity) Subscale of MMPI. This result means the MMPI and CMI was not related to tool which developed based on medical model from etic perspectives, although the tool which had been developed in America Modified to Korean situation. So I dare to say that only the absence of mental illness does not means mental health and the diagnosis of mental illness is not the only criteria of a mental health.