Prediction of workability of concrete using design of experiments for mixtures

I-Cheng Yeh 사단법인 한국계산역학회 2008 Computers and Concrete, An International Journal Vol.5 No.1

In this study, the effects and the interactions of water content, SP-binder ratio, and waterbinder ratio on the workability performance of concrete were investigated. The experiments were designed based on flatted simplex-centroid experiment design modified from standard simplex-centroid one. The data gotten from the design was used to build the concrete slump model using neural networks. Research reported in this paper shows that a small number of slump experiments can be performed and meaningful data obtained with the experiment design. Such data would be suitable for building slump model using neural networks. The trained network can be satisfactorily used for exploring the effects of the components and their interactions on the workability of concrete. It has found that a high water content and a high SP/b ratio is essential for high workability, but achieving this by increasing these parameters will not in itself guarantee high workability. The w/b played a very important role in producing workability and had rather profound effects; however, the medium value about 0.4 is the best w/b to reach high slump without too much effort on trying to find the appropriate water content and SP/b.

Modeling slump of concrete with fly ash and superplasticizer

I-Cheng Yeh 사단법인 한국계산역학회 2008 Computers and Concrete, An International Journal Vol.5 No.6

The effects of fly ash and superplasticizer (SP) on workability of concrete are quite difficult to predict because they are dependent on other concrete ingredients. Because of high complexity of the relations between workability and concrete compositions, conventional regression analysis could be not sufficient to build an accurate model. In this study, a workability model has been built using artificial neural networks (ANN). In this model, the workability is a function of the content of all concrete ingredients, including cement, fly ash, blast furnace slag, water, superplasticizer, coarse aggregate, and fine aggregate. The effects of water/binder ratio (w/b), fly ash-binder ratio (fa/b), superplasticizer-binder ratio (SP/b), and water content on slump were explored by the trained ANN. This study led to the following conclusions: (1) ANN can build a more accurate workability model than polynomial regression. (2) Although the water content and SP/b were kept constant, a change in w/b and fa/b had a distinct effect on the workability properties. (3) An increasing content of fly ash decreased the workability, while raised the slump upper limit that can be obtained.

Heart Rate Variability Biofeedback Increased Autonomic Activation and Improved Symptoms of Depression and Insomnia among Patients with Major Depression Disorder

I-Mei Lin,Sheng-Yu Fan,Cheng-Fang Yen,Yi-Chun Yeh,Tze‐Chun Tang,Mei-Feng Huang,Tai-Ling Liu,Peng-Wei Wang,Huang-Chi Lin,Hsin-Yi Tsai,Yu-Che Tsai 대한정신약물학회 2019 CLINICAL PSYCHOPHARMACOLOGY AND NEUROSCIENCE Vol.17 No.2

Objective: Autonomic imbalance is considered a psychopathological mechanism underlying major depressive disorder (MDD). Heart rate variability (HRV) is an index for autonomic activation. Poor sleep quality is common among patients with MDD. HRV biofeedback (BF) has been used for regulating autonomic balance among patients with physical illness and mental disorders. The purpose of present study was to examine the effects of HRV-BF on depressive symptoms, sleep quality, pre-sleep arousal, and HRV indices, in patients with MDD and insomnia. Methods: In this case-controlled study, patients with MDD and Pittsburgh Sleep Quality Index (PSQI) score higher than 6 were recruited. The HRV-BF group received weekly 60-minute protocol for 6 weeks, and the control group who have matched the age and sex received medical care only. All participants were assessed on Beck Depression Inventory-II, Back Anxiety Inventory, PSQI, and Pre-Sleep Arousal Scale. Breathing rates and electrocardiography were also performed under resting state at pre-testing, and post-testing conditions and for the HRV-BF group, also at 1-month follow-up. Results: In the HRV-BF group, symptoms of depression and anxiety, sleep quality, and pre-sleep arousal were significantly improved, and increased HRV indices, compared with the control group. Moreover, in the HRV-BF group, significantly improved symptoms of depression and anxiety, decreased breathing rates, and increased HRV indices were detected at post-testing and at 1-month follow-up, compared with pre-testing values. Conclusion: This study confirmed that HRV-BF is a useful psychosocial intervention for improving autonomic balance, baroreflex, and symptoms of depression and insomnia in MDD patients.

Optimal design of plane frame structures using artificial neural networks and ratio variables

Chin-Sheng Kao,I-Cheng Yeh 국제구조공학회 2014 Structural Engineering and Mechanics, An Int'l Jou Vol.52 No.4

There have been many packages that can be employed to analyze plane frames. However, because most structural analysis packages suffer from closeness of system, it is very difficult to integrate it with an optimization package. To overcome the difficulty, we proposed a possible alternative, DAMDO, which integrate Design, Analysis, Modeling, Definition, and Optimization phases into an integrative environment. The DAMDO methodology employs neural networks to integrate structural analysis package and optimization package so as not to need directly to integrate these two packages. The key problem of the DAMDO approach is how to generate a set of reasonable random designs in the first phase. According to the characteristics of optimized plane frames, we proposed the ratio variable approach to generate them. The empirical results show that the ratio variable approach can greatly improve the accuracy of the neural networks, and the plane frame optimization problems can be solved by the DAMDO methodology.

Modeling strength of high-performance concrete using genetic operation trees with pruning techniques

Chien-Hua Peng,I-Cheng Yeh,Li-Chuan Lien 사단법인 한국계산역학회 2009 Computers and Concrete, An International Journal Vol.6 No.3

Regression analysis (RA) can establish an explicit formula to predict the strength of High-Performance Concrete (HPC); however, the accuracy of the formula is poor. Back-Propagation Networks (BPNs) can establish a highly accurate model to predict the strength of HPC, but cannot generate an explicit formula. Genetic Operation Trees (GOTs) can establish an explicit formula to predict the strength of HPC that achieves a level of accuracy in between the two aforementioned approaches. Although GOT can produce an explicit formula but the formula is often too complicated so that unable to explain the substantial meaning of the formula. This study developed a Backward Pruning Technique (BPT) to simplify the complexity of GOT formula by replacing each variable of the tip node of operation tree with the median of the variable in the training dataset belonging to the node, and then pruning the node with the most accurate test dataset. Such pruning reduces formula complexity while maintaining the accuracy. 404 experimental datasets were used to compare accuracy and complexity of three model building techniques, RA, BPN and GOT. Results show that the pruned GOT can generate simple and accurate formula for predicting the strength of HPC.

Optimal design of plane frame structures using artificial neural networks and ratio variables

Kao, Chin-Sheng,Yeh, I-Cheng Techno-Press 2014 Structural Engineering and Mechanics, An Int'l Jou Vol.52 No.4

There have been many packages that can be employed to analyze plane frames. However, because most structural analysis packages suffer from closeness of system, it is very difficult to integrate it with an optimization package. To overcome the difficulty, we proposed a possible alternative, DAMDO, which integrate Design, Analysis, Modeling, Definition, and Optimization phases into an integrative environment. The DAMDO methodology employs neural networks to integrate structural analysis package and optimization package so as not to need directly to integrate these two packages. The key problem of the DAMDO approach is how to generate a set of reasonable random designs in the first phase. According to the characteristics of optimized plane frames, we proposed the ratio variable approach to generate them. The empirical results show that the ratio variable approach can greatly improve the accuracy of the neural networks, and the plane frame optimization problems can be solved by the DAMDO methodology.

Optimal design of reinforced concrete plane frames using artificial neural networks

Chin-Sheng Kao,I-Cheng Yeh 사단법인 한국계산역학회 2014 Computers and Concrete, An International Journal Vol.14 No.4

To solve structural optimization problems, it is necessary to integrate a structural analysis package and an optimization package. There have been many packages that can be employed to analyze reinforced concrete plane frames. However, because most structural analysis packages suffer from closeness of systems, it is very difficult to integrate them with optimization packages. To overcome the difficulty, we proposed a possible alternative, DAMDO, which integrates Design, Analysis, Modeling, Definition, and Optimization phases into an integration environment as follows. (1) Design: first generate many possible structural design alternatives. Each design alternative consists of many design variables X. (2) Analysis: employ the structural analysis software to analyze all structural design alternatives to obtain their internal forces and displacements. They are the response variables Y. (3) Modeling: employ artificial neural networks to build the models Y=f(X) to obtain the relationship functions between the design variables X and the response variables Y. (4) Definition: employ the design variables X and the response variables Y to define the objective function and constraint functions. (5) Optimization: employ the optimization software to solve the optimization problem consisting of the objective function and the constraint functions to produce the optimum design variables. The RC frame optimization problem was examined to evaluate the DAMDO approach, and the empirical results showed that it can be solved by the approach.

An approach to evaluate groundwater recharge from streamflow and groundwater records

Wen-Jui Kung,Hsin-Fu Yeh,Hung-I Lin,Wei-Ping Chen,Cheng-Haw Lee 한국지질과학협의회 2013 Geosciences Journal Vol.17 No.3

To assess groundwater recharge, this study provided a composite method combining the recession-curve-displacement method and water-table fluctuation method. First, the initial recharge reference value was determined using the water-table fluctuation method. The corresponding groundwater discharge was then determined from the recharge reference value using the recession-curve-displacement method. Furthermore, the recession segment of the match between groundwater discharge and streamflow was computed. The recharge reference value was repeatedly adjusted to achieve a good fit with the recession segment for groundwater discharge and streamflow, thereby attaining the final groundwater recharge using the proposed method. Finally, the groundwater recharge of the Lanyang Creek basin in Taiwan was estimated as a case study. A comparison of recession-curve-displacement method and proposed composite method are presented. Estimation results show that the number of recharge events, recharge timing of these events, groundwater recharge events that satisfy recession theory, and range of transmissivity can be obtained using the proposed composite method. Comparison results demonstrate that the number of groundwater recharge events obtained with the composite method was greater than that acquired with the recession-curve-displacement method. However, the annual recharge and seasonal recharge obtained with the recession-curve-displacement method and composite method were close.

Scaling up the in-hospital hepatitis C virus care cascade in Taiwan

( Chung-feng Huang ),( Pey-fang Wu ),( Ming-lun Yeh ),( Ching-i Huang ),( Po-cheng Liang ),( Cheng-ting Hsu ),( Po-yao Hsu ),( Hung-yin Liu ),( Ying-chou Huang ),( Zu-yau Lin ),( Shinn-cherng Chen ),( 대한간학회 2021 Clinical and Molecular Hepatology(대한간학회지) Vol.27 No.1

Background/Aims: Obstacles exist in facilitating hepatitis C virus (HCV) care cascade. To increase timely and accurate diagnosis, disease awareness and accessibility, in-hospital HCV reflex testing followed by automatic appointments and a late call-back strategy (R.N.A. model) was applied. We aimed to compare the HCV treatment rate of patients treated with this strategy compared to those without. Methods: One hundred and twenty-five anti-HCV seropositive patients who adopted the R.N.A. model in 2020 and another 1,396 controls treated in 2019 were enrolled to compare the gaps in accurate HCV RNA diagnosis to final treatment allocation. Results: The HCV RNA testing rate was significantly higher in patients who received reflex testing than in those without reflex testing (100% vs. 84.8%, P<0.001). When patients were stratified according to the referring outpatient department, a significant improvement in the HCV RNA testing rate was particularly noted in patients from non-hepatology departments (100% vs. 23.3%, P<0.001). The treatment rate in HCV RNA seropositive patients was 83% (83/100) after the adoption of the R.N.A. model, among whom 96.1% and 73.9% of patients were from the hepatology and non-hepatology departments, respectively. Compared to subjects without R.N.A. model application, a significant improvement in the treatment rate was observed for patients from non-hepatology departments (73.9% vs. 27.8%, P=0.001). The application of the R.N.A. model significantly increased the in-hospital HCV treatment uptake from 6.4% to 73.9% for patients from non-hepatology departments (P<0.001). Conclusions: The care cascade increased the treatment uptake and set up a model for enhancing in-hospital HCV elimination. (Clin Mol Hepatol 2021;27:136-143)

The Different Expression of Gene Profiles on Hepatocellular Carcinoma Cells with Different Intracellular Hepatitis C Viral Load

( Chia-yen Dai ),( Shu-chi Wang ),( Meng-hsuan Hsieh ),( Cheng-fu Yang ),( Ching-i Huang ),( Chung-feng Huang ),( Ming-lun Yeh ),( Jee-fu Huang ),( Wang-long Chung ),( Ming-lung Yu ) 대한간학회 2017 춘·추계 학술대회 (KASL) Vol.2017 No.1

Aims: The different hepatitis C virus (HCV) replication has been reported among individual hepatocytes in chronic HCV infection by identifying hepatocytes with different HCV RNA levels. We have previously established a fluorescence-activated cell sorting (FACS) protocol to study the effects of different intracellular viral loads in HCV-infected cells. The present study aimed to further study the gene expression on different hepatocellular carcinoma (HCC) cells with different HCV viral load. Methods: The JFH1-EYFP viral florescence intensity was used to sort the high and low viral load cells after 5 days infection in vitro which has been shown in our previous study that infected cells efficiently and accurately discriminated between high- and low-viral load cell populations. The next generation sequence-RNA sequence was used to clarify the mRNA and miRNA gene network between HCV-high and HCV-low infected cells of the HCC cell line. Venn diagram summarizing the probe sets that were differentially expressingbetween the Huh7.5.1 versus each differential viral load cell population and miRDB and miRTar databases were used to predict HVL and LVL/S2 unique miRNA target genes. Results: By analyzing the NGS dataset and miRNA microarray dataset, of the significant transcripts, three miRNA were unique for the LVL/S2 cells and nine miRNA unique for the HVL. Twenty-three miRNA were common for all 3 viral load groups. We verified them by q-PCR and data confirmed the array data expression level. We found that high viral loads were associated with cell inflammation- and cell death-associated pathway; and the low viral loads were associated many stress response- and cell adhesion molecular (CAMs)-related genes. Conclusions: With the established cell sorting protocol, we have demonstrated that different gene network between HCV-high and HCV-low infected cells in JFH1-EYFP infectious cells exists. Our results may provide a boarder gene regulation map between high and low viral load cell populations.