• Journal of Software Assessment and Valuation
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• v.16 no.2
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• pp.53-62
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• 2020

In the end-user domain of an IoT environment, there are more and more intelligent M2M devices that provide resources to create and share application services. Therefore, it can be very useful to manage trust by transferring the role of the existing centralized service provider to end users in a P2P environment. However, in a decentralized M2M computing environment where end users independently provide or consume services, mutual trust building is the most important factor. This is because malicious users trying to build malfunctioning services can cause security problems in M2M computing environments such as IoT. In this paper, we provide an integrated analysis and approach for trust evaluation of M2M application services, and an optimized trust evaluation model that can guarantee reliability among users of the M2M community.

• Computers and Concrete
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• v.30 no.5
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• pp.339-355
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• 2022

The high cost of ultra-high-performance engineered cementitious composite (UHP-ECC) is currently a crucial issue, especially in terms of the polyethylene (PE) fibers use. In this paper, cheap calcium carbonate whiskers (CW) were evaluated on the feasibility of hybrid with PE fibers. Diverse combinations of PE fibers and CW were employed to investigate the multi-scale enhancement on the UHP-ECC performance. A probabilistic-based UHP-ECC tensile strain reliability analysis approach was utilized, which was in general agreement with the experimental results. Furthermore, a multi-dimensional integrated representation was conducted for the comprehensive assessment of UHP-ECC. Results illustrated that CW improved the compressive strength and energy dissipation capacity of UHP-ECC owing to the microscopic strengthening mechanism. CW and PE fiber further promoted the saturated cracking of composite by multi-scale crack arresting effect. In particular, PE1.75-CW0.5 specimen possessed the best overall performance. The ultimate cracking width of PE1.75-CW0.5 group had 98 ㎛, which was 46.18% lower compared to PE2-CW0 group, the 28d compressive strength were slightly improved, the tensile strain capacity was comparable to that of PE2-CW0 group. The results above demonstrated that combinations of PE fiber and CW could significantly enhance the comprehensive performance of UHP-ECC, which was beneficial for large-scale engineering applications.

• Structural Monitoring and Maintenance
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• v.11 no.3
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• pp.173-185
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• 2024

Currently, the electro-hydraulic servo loading control system manufactured by MTS, OpenFresco hybrid test interface software and OpenSees finite element software are widely used in structure laboratories to carry out hybrid test, but there is no relevant public information about full structure pseudo-dynamic test based on the above software and hardware. In order to study the feasibility of using the above software and hardware to carry out full structure pseudo-dynamic test, the full structure pseudo-dynamic virtual experiments of a single degree of freedom (SDOF) structure and a two degrees of freedom (2DOFs) structure are carried out based on the MTS 793 Demo Mode, and the results are respectively compared with the finite element analysis method. The results show that the finite element analysis results and full structure pseudo-dynamic virtual experiment results are highly consistent, which verifies the feasibility of carrying out the full structure pseudo-dynamic test based on the above software and hardware. Then, a three story steel frame full structure pseudo-dynamic test is conducted, and the smooth implementation of full structure pseudo-dynamic test of the three story steel frame further verifies the reliability of thistesting method. The implementation method of carrying out the full structure pseudo-dynamic tests are introduced in detail, which can provide some reference for relevant research.

• Proceedings of the Korean Geotechical Society Conference
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• 2007.09a
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• pp.623-634
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• 2007

The aim of this research is development and verification of resistivity seismic dilatometer (RSDMT) system. The resistivity module for obtaining resistivity-depth plot and seismic module for obtaining wave velocity-depth plot are attached to the conventional flat dilatometer testing equipment. To enhance reliability and repeatability of seismic part in RSDMT, automatic testing system including automatic surface source, PC based data acquisition system and operating program were developed. To obtain real resistivity value of soil, geometric factor for the array of electrodes in RSDMT was derived empirically. The verification studies for the developed RSDMT system were performed at the southeast side of Korea where soil improvement work is planned. SPT, CPT, geophysical subsurface imaging techniques and some laboratory tests were performed for the comparisons. As one penetration of RSDMT, various soil parameters could be obtained. The results of field test showed good repeatability and reliability in every part. From these studies, developed RSDMT system was checked and the effectiveness of this system was verified in light of proper evaluation of geotechnical characteristics of soft soil.

• Journal of the Korean Geotechnical Society
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• v.28 no.12
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• pp.111-122
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• 2012

Resistivity seismic dilatometer (RSDMT) system is introduced. The resistivity module for obtaining resistivity-depth plot and seismic module for obtaining wave velocity-depth plot are attached to the conventional flat dilatometer testing equipment. To enhance the reliability and repeatability of seismic part in RSDMT, automatic testing system including automatic surface source, PC based data acquisition system and operating program was constructed. To obtain real resistivity value of soil, geometric factor for the array of electrodes in RSDMT was derived empirically. The verification studies for the developed RSDMT system were performed with SPT, CPTu, bender element test and DC resistivity survey. Through one penetration of RSDMT, various soil parameters were obtained and the reliability and repeatability of developed RSDMT system could be checked.

• Geomechanics and Engineering
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• v.31 no.2
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• pp.129-147
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• 2022

The properties of soil are naturally highly variable and thus, to ensure proper safety and reliability, we need to test a large number of samples across the length and depth. In pile foundations, conducting field tests are highly expensive and the traditional empirical relations too have been proven to be poor in performance. The study proposes a state-of-art Particle Swarm Optimization (PSO) hybridized Artificial Neural Network (ANN), Extreme Learning Machine (ELM) and Adaptive Neuro Fuzzy Inference System (ANFIS); and comparative analysis of metaheuristic models (ANN-PSO, ELM-PSO, ANFIS-PSO) for prediction of bearing capacity of pile foundation trained and tested on dataset of nearly 300 dynamic pile tests from the literature. A novel ensemble model of three hybrid models is constructed to combine and enhance the predictions of the individual models effectively. The authenticity of the dataset is confirmed using descriptive statistics, correlation matrix and sensitivity analysis. Ram weight and diameter of pile are found to be most influential input parameter. The comparative analysis reveals that ANFIS-PSO is the best performing model in testing phase (R² = 0.85, RMSE = 0.01) while ELM-PSO performs best in training phase (R² = 0.88, RMSE = 0.08); while the ensemble provided overall best performance based on the rank score. The performance of ANN-PSO is least satisfactory compared to the other two models. The findings were confirmed using Taylor diagram, error matrix and uncertainty analysis. Based on the results ELM-PSO and ANFIS-PSO is proposed to be used for the prediction of bearing capacity of piles and ensemble learning method of joining the outputs of individual models should be encouraged. The study possesses the potential to assist geotechnical engineers in the design phase of civil engineering projects.

• Journal of agriculture & life science
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• v.46 no.2
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• pp.9-17
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• 2012

In this study, in addition to the green tea - wood fiber hybrid composite boards of previous researches, to make effective use of saw dust of domestic cypress tree with functionalities and application as interior materials, eco-friendly hybrid composite boards were manufactured from wood fiber, green tea and saw dust of cypress tree. We investigated the effect of the component ratio of saw dust and green tea on dynamic MOE (modulus of elasticity). Dynamic MOE was within 1.41~1.65 GPa, and showed the highest value in wood fiber : green tea : saw dust = 50 : 40 : 10 of the component ratio, and had the lowest value in 50 : 30 : 20 of component ratio. These values were 1.4~1.6 times higher than static bending MOE of wood fiber - saw dust - green tea hybrid composite boards, and were 2.0~2.9 times lower than those of green tea - wood fiber hybrid composite boards reported in the previous researches. From the results of correlation regression analyses between dynamic MOE and static strength performances, a very high correlation coefficients were obtained, therefore it was found that static bending strength performances can be estimated with a high reliability from dynamic MOE.

• Journal of Korean Society of Transportation
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• v.30 no.1
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• pp.19-30
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• 2012

The majority of daily travel demands concentrate at particular time-periods, which causes the difficulties in the travel demand analysis and the corresponding benefit estimation. Thus, it is necessary to consider time-specific traffic characteristics to yield more reliable results. Traditionally, na$\ddot{i}$ve, heuristic, and statistical approaches have been applied to address the peak-hour ratio. In this study, a hybrid clustering model which is one of the statistical methods is applied to calculate the peak-hour ratio and its duration. The 2009 national 24-hour traffic data provided by the Korea institute of Construction Technology are used. The analysis is conducted dividing vehicle types into passenger cars and trucks. For the verification for the usefulness of the methodology, the toll collection system data by the Korea Express Corporation are collected. The result of the research shows lower errors during the off-peak hours and night times and increasing error ratios as the travel distance increases. Since the method proposed can reduce the arbitrariness of analysts and can accommodate the statistical significance test, the model could be considered as a more robust and stable methodology. It is hoped that the result of this paper could contribute to the enhancement of the reliability for the travel demand analysis.

• Magazine of the Korean Society of Agricultural Engineers
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• v.22 no.3
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• pp.75-87
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• 1980

Most hydro]ogic phenomena are the complex and organic products of multiple causations like climatic and hydro-geological factors. A certain significant correlation on the run-off in river basin would be expected and foreseen in advance, and the effect of each these causual and associated factors (independant variables; present-month rainfall, previous-month run-off, evapotranspiration and relative humidity etc.) upon present-month run-off(dependent variable) may be determined by multiple regression analysis. Functions between independant and dependant variables should be treated repeatedly until satisfactory and optimal combination of independant variables can be obtained. Reliability of the estimated function should be tested according to the result of statistical criterion such as analysis of variance, coefficient of determination and significance-test of regression coefficients before first estimated multiple regression model in historical sequence is determined. But some error between observed and estimated run-off is still there. The error arises because the model used is an inadequate description of the system and because the data constituting the record represent only a sample from a population of monthly discharge observation, so that estimates of model parameter will be subject to sampling errors. Since this error which is a deviation from multiple regression plane cannot be explained by first estimated multiple regression equation, it can be considered as a random error governed by law of chance in nature. This unexplained variance by multiple regression equation can be solved by stochastic approach, that is, random error can be stochastically simulated by multiplying random normal variate to standard error of estimate. Finally hybrid model on estimation of monthly run-off in nonhistorical sequence can be determined by combining the determistic component of multiple regression equation and the stochastic component of random errors. Monthly run-off in Naju station in Yong-San river basin is estimated by multiple regression model and hybrid model. And some comparisons between observed and estimated run-off and between multiple regression model and already-existing estimation methods such as Gajiyama formula, tank model and Thomas-Fiering model are done. The results are as follows. (1) The optimal function to estimate monthly run-off in historical sequence is multiple linear regression equation in overall-month unit, that is; Qn=0.788Pn+0.130Qn-1-0.273En-0.1 About 85% of total variance of monthly runoff can be explained by multiple linear regression equation and its coefficient of determination (R2) is 0.843. This means we can estimate monthly runoff in historical sequence highly significantly with short data of observation by above mentioned equation. (2) The optimal function to estimate monthly runoff in nonhistorical sequence is hybrid model combined with multiple linear regression equation in overall-month unit and stochastic component, that is; Qn=0. 788Pn+0. l30Qn-1-0. 273En-0. 10+Sy.t The rest 15% of unexplained variance of monthly runoff can be explained by addition of stochastic process and a bit more reliable results of statistical characteristics of monthly runoff in non-historical sequence are derived. This estimated monthly runoff in non-historical sequence shows up the extraordinary value (maximum, minimum value) which is not appeared in the observed runoff as a random component. (3) "Frequency best fit coefficient" (R2f) of multiple linear regression equation is 0.847 which is the same value as Gaijyama's one. This implies that multiple linear regression equation and Gajiyama formula are theoretically rather reasonable functions.

• Korea Science and Art Forum
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• v.37 no.2
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• pp.35-46
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• 2019

The purpose of this study was to develop a hybrid model forecasting the optimal number of employees for the hotel MICE and investigate indicators' reliability and validity empirically. The dominant approach of manpower planning has long been conducted based on heuristic experience in the field of Hotel and MICE. There is little research on the manpower planning and forecasting in the hotel and MICE studies. However, it is significantly important to ensure how many the optimal number of employees are calculated to meet the goals of the company as well as the expectation of their customers. A focus group interview was used to collect data through a series of surveys. A total of 289 samples were collected to test validity of finalized indicators for forecasting the optimal number of employees for the Hotel MICE. The study developed 15 quantitative indicators and 19 qualitative indicators to forecasting the optimal number of employees for the Hotel MICE, based on three types of groups such as 'service-oriented', 'stability-oriented', and 'profitability-oriented' hotel company The study revealed the econometrics formula for the practical application for this field.