KSCE Journal of Civil and Environmental Engineering Research
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v.13
no.3
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pp.185-192
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1993
A numerical model has been used for the prediction of wave agitations in a harbor which are induced by the intrusion and transformation of incident waves. Based on linear wave theory a mild-slope equation has been used. A partial absorbing boundary condition has been used on solid boundary. Functional has been derived following Chen and Mei(l974)'s technique based on Hybrid Element Method which uses finite discretisation in the inner region and analytical solution of Helmholtz equation in the outer region. Final simultaneous equation has been solved using the Gaussian Elimination Method. Helmholtz natural period and second peak period of seiche in Donghae Harbor coincide very well with the results from numerical calculation. Computed amplification factors show good agreement, especially when the reflection coefficient on solid boundary is 0.99, with those of measurements.
Wang, Shu;Ma, Yi Jia;Li, Yong Shi;Ge, Xu Sheng;Lu, Chang;Cai, Chun Bo;Yang, Yang;Zhao, Yan;Liang, Guo Ming;Guo, Xiao Hong;Cao, Guo Qing;Li, Bu Gao;Gao, Peng Fei
Animal Bioscience
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v.35
no.7
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pp.975-988
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2022
Objective: In this study, we aimed to identify long non-coding RNAs (lncRNAs) that play important roles in starvation stress, analyze their functions, and discover potential molecular targets to alleviate starvation stress to provide a theoretical reference for subsequent in-depth research. Methods: We generated a piglet starvation stress animal model. Nine Yorkshire weaned piglets were randomly divided into a long-term starvation stress group (starved for 72 h), short-term starvation stress group (starved for 48 h), and the control group. LncRNA libraries were constructed using high-throughput sequencing of piglet ileums. Results: We obtained 11,792 lncRNAs, among which, 2,500 lncRNAs were novel. In total, 509 differentially expressed (DE)lncRNAs were identified in this study. Target genes of DElncRNAs were predicted via cis and trans interactions, and functional and pathway analyses were performed. Gene ontology functions and Kyoto encyclopedia of genes and genomes analysis revealed that lncRNA-targeted genes mainly participated in metabolic pathways, cellular processes, immune system processes, digestive systems, and transport activities. To reveal the mechanism underlying starvation stress, the interaction network between lncRNAs and their targets was constructed based on 26 DElncRNAs and 72 DEmRNAs. We performed an interaction network analysis of 121 DElncRNA-DEmRNA pairs with a Pearson correlation coefficient greater than 0.99. Conclusion: We found that MSTRG.19894.13, MSTRG.16726.3, and MSTRG.12176.1 might play important roles in starvation stress. This study not only generated a library of enriched lncRNAs in piglets, but its outcomes also provide a strong foundation to screen key lncRNAs involved in starvation stress and a reference for subsequent in-depth research.
Journal of Institute of Control, Robotics and Systems
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v.16
no.12
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pp.1150-1158
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2010
In this study, the Polynomial-based Radial Basis Function Neural Networks is proposed as one of the recognition part of overall face recognition system that consists of two parts such as the preprocessing part and recognition part. The design methodology and procedure of the proposed pRBFNNs are presented to obtain the solution to high-dimensional pattern recognition problem. First, in preprocessing part, we use a CCD camera to obtain a picture frame in real-time. By using histogram equalization method, we can partially enhance the distorted image influenced by natural as well as artificial illumination. We use an AdaBoost algorithm proposed by Viola and Jones, which is exploited for the detection of facial image area between face and non-facial image area. As the feature extraction algorithm, PCA method is used. In this study, the PCA method, which is a feature extraction algorithm, is used to carry out the dimension reduction of facial image area formed by high-dimensional information. Secondly, we use pRBFNNs to identify the ID by recognizing unique pattern of each person. The proposed pRBFNNs architecture consists of three functional modules such as the condition part, the conclusion part, and the inference part as fuzzy rules formed in 'If-then' format. In the condition part of fuzzy rules, input space is partitioned with Fuzzy C-Means clustering. In the conclusion part of rules, the connection weight of pRBFNNs is represented as three kinds of polynomials such as constant, linear, and quadratic. Coefficients of connection weight identified with back-propagation using gradient descent method. The output of pRBFNNs model is obtained by fuzzy inference method in the inference part of fuzzy rules. The essential design parameters (including learning rate, momentum coefficient and fuzzification coefficient) of the networks are optimized by means of the Particle Swarm Optimization. The proposed pRBFNNs are applied to real-time face recognition system and then demonstrated from the viewpoint of output performance and recognition rate.
The new and renewable energy today has a great interest in all countries around the world. In special it has need more limit of the fossil fuel that needs of low carbon emission among the social necessary conditions. Recently, the high-rise building demand the structural safety, the economic feasibility and the functional design. The high-rise building spends enormous energy and it satisfied the design in solving energy requirements. The requirements of energy for the building depends on the partly form wind energy due to the cladding of the building that came from the surroundings of the high-rise building. In this study of the wind energy, the cladding of the building was assessed a tentative study. The wind energy obtains from several small wind powers that came from the building or the surrounding of the building. In making a cladding the wind energy forms with wind pressure by means of energy transformation methods. The assessment for the building cladding was surrounded of wind speed and wind pressure that was carried out as a result of numerical simulation of wind environment and wind pressure which is coefficient around the high-rise building with the computational fluid dynamics. In case of the obtained wind energy from the pressure of the building cladding was estimated by the simulation of CFD of the building. The wind energy at this case was calculated by energy transform methods: the wind pressure coefficients were obtained from the simulated model for wind environment using CFD as follow. The concept for the factor of $E_f$ was suggested in this study. $$C_p=\frac{P_{surface}}{0.5{\rho}V^{2ref}}$$$$E_c=C_p{\cdot}E_f$$ Where $C_p$ is wind pressure coefficient from CFD, $E_f$ means energy transformation parameter from the principle of the conservation of energy and $E_c$ means energy from the building cladding. The other wind energy that is $E_p$ was assessed by wind power on the building or building surroundings. In this case the small wind power system was carried out for wind energy on the place with the building and it was simulated by computational fluid dynamics. Therefore the total wind energy in the building was calculated as the follows. $$E=E_c+E_p$$ The energy transformation, which is $E_f$ will need more research and estimation for various wind situation of the building. It is necessary for the assessment to make a comparative study about the wind tunnel test or full scale test.
Journal of the Korean Institute of Intelligent Systems
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v.21
no.6
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pp.749-754
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2011
In this study, we propose the design of optimized pRBFNNs-based face recognition system using two-dimensional Image and ASM algorithm. usually the existing 2 dimensional face recognition methods have the effects of the scale change of the image, position variation or the backgrounds of an image. In this paper, the face region information obtained from the detected face region is used for the compensation of these defects. In this paper, we use a CCD camera to obtain a picture frame directly. By using histogram equalization method, we can partially enhance the distorted image influenced by natural as well as artificial illumination. AdaBoost algorithm is used for the detection of face image between face and non-face image area. We can butt up personal profile by extracting the both face contour and shape using ASM(Active Shape Model) and then reduce dimension of image data using PCA. The proposed pRBFNNs consists of three functional modules such as the condition part, the conclusion part, and the inference part. In the condition part of fuzzy rules, input space is partitioned with Fuzzy C-Means clustering. In the conclusion part of rules, the connection weight of RBFNNs is represented as three kinds of polynomials such as constant, linear, and quadratic. The essential design parameters (including learning rate, momentum coefficient and fuzzification coefficient) of the networks are optimized by means of Differential Evolution. The proposed pRBFNNs are applied to real-time face image database and then demonstrated from viewpoint of the output performance and recognition rate.
Perfluorinated compounds(PFCs), an emerging environmental pollutant, are environmentally persistent and bioaccumulative organic compounds that possess a toxic impact on human health and ecosystems. PFCs are distributed widely in environment media including groundwater, surface water, soil and sediment. PFCs in contaminated solid can potentially leach into groundwater. Therefore, understanding PFCs partitioning between the aqueous phase and solid phase is important for the determination of their fate and transport in the environment. In this study, the sorption equilibrium batch and kinetic experiment of PFCs were carried out to estimated the sorption coefficient(Kd) and the fraction between aqueous-solid phase partition, respectively. Sorption branches of the PFDA(Perfluoro-n-decanoic acid), PFNA(Perfluoro-n-nonanoic acid), PFOA(Perfluoro-n-octanoic acid), PFOS(Perfluoro-1-octane sulfonic acid) and PFHxS(Perfluoro-1-hexane sulfonic acid) isotherms were nearly linear, and the estimated Kd was as follow: PFDA(1.50) > PFOS(1.49) > PFNA(0.81) > PFHxS(0.45) > PFOA(0.39). The sorption kinetics of PFDA, PFNA, PFOA, PFOS and PFHxS onto soil were described by a biexponential adsorption model, suggesting that a fast transport into the surface layer of soil, followed by two-step diffusion transport into the internal water and/or organic matter of soil. Shorter times(<20hr) were required to achieve equilibrium and fraction for adsorption on solid(F1, F2) increased with perfluorinated carbon chain length and sulfonate compounds in this study. Overall, our results suggested that not only the perfluorocarbon chain length, but also the terminal functional groups are important contributors to electrostatic and hydrophobic interactions between PFCs and soils, and organic matter in soils significantly affects adsorption maximum capacity than kinetic rate.
This paper empirically examines factors that potentially influence the success of a Web-based semantic search engine. A research model has been proposed that shows the impact of quality-related factors upon the effectiveness of a semantic search engine, based on DeLone and McLean's(2003) information systems success model. An empirical study has been conducted to test hypotheses formulated around the research model, and statistical methods were applied to analyze gathered data and draw conclusions. Implications for academics and practitioners are offered based on the findings of the study. The proposed model includes three quality dimensions of a Web-based semantic search engine-namely, information quality, system quality and service quality. These three dimensions each have measures designed to collectively assess the respective dimension. The model is intended to examine the relationship between measures of these quality dimensions and measures of two dependent constructs, including individuals' net benefit and user satisfaction. Individuals' net benefit was measured by the extent to which the user's information needs were adequately met, whereas user satisfaction was measured by a combination of the perceived satisfaction with search results and the perceived satisfaction with the overall system. A total of 23 hypotheses have been formulated around the model, and a questionnaire survey has been conducted using a functional semantic search website created by KT and Hakia, so as to collect data to validate the model. Copies of a questionnaire form were handed out in person to 160 research associates and employees working in the area of designing and developing semantic search engines. Those who received the form, 148 respondents returned valid responses. The survey form asked respondents to use the given website to answer questions concerning the system. The results of the empirical study have indicated that, of the three quality dimensions, information quality was found to have the strongest association with the effectiveness of a Web-based semantic search engine. This finding is consistent with the observation in the literature that the aspects of the information quality should serve as a basis for evaluating the search outcomes from a semantic search engine. Measures under the information quality dimension that have a positive effect on informational gratification and user satisfaction were found to be recall and currency. Under the system quality dimension, response time and interactivity, were positively related to informational gratification. On the other hand, only one measure under the service quality dimension, reliability was found to have a positive relationship with user satisfaction. The results were based on the seven hypotheses that have been accepted. One may wonder why 15 out of the 23 hypotheses have been rejected and question the theoretical soundness of the model. However, the correlations between independent variables and dependent variables came out to be fairly high. This suggests that the structural equation model yielded results inconsistent with those of coefficient analysis, because the structural equation model intends to examine the relationship among independent variables as well as the relationship between independent variables and dependent variables. The findings offer some useful implications for owners of a semantic search engine, as far as the design and maintenance of the website is concerned. First, the system should be designed to respond to the user's query as fast as possible. Also it should be designed to support the search process by recommending, revising, and choosing a search query, so as to maximize users' interactions with the system. Second, the system should present search results with maximum recall and currency to effectively meet the users' expectations. Third, it should be capable of providing online services in a reliable and trustworthy manner. Finally, effective increase in user satisfaction requires the improvement of quality factors associated with a semantic search engine, which would in turn help increase the informational gratification for users. The proposed model can serve as a useful framework for measuring the success of a Web-based semantic search engine. Applying the search engine success framework to the measurement of search engine effectiveness has the potential to provide an outline of what areas of a semantic search engine needs improvement, in order to better meet information needs of users. Further research will be needed to make this idea a reality.
This paper is based on the design and analysis computing model of oxygen saturation with the pulse oximeter using the integral ratio of pulsating components. In our proposed algorithm. we modeled the transmitted optical signal in fingertip or earlobe to DC component $A_{dc}$ pulsating component $A_a\;Sinwt$, noise component $A_{noise}$ and etc.. To separate the pulsating components and DC components efficiently, we defined the signal average to DC components. Also we presented the way to eliminate the noise using integral ratio. To acquire a linearity of correlation graph for pulsating components ratios and non invasive oxygen saturation. we intensively observed on the oxygen saturations in the range of 75-100% in consideration of the error range of simulator. Also, for real time processing we experimented on changing the period of area calculating cycle from 1 to 6. The functional evaluation of the algorithm is compared with the method using the amplitude ratio of pulsating components frequently seen with pulse oximeter. The result was that our algorithm with 4 cycles of area calculating cycle which considered to be best fit by 1% to the existing method. Moreover r , the decision coefficient showing the correlation of regression graph with real data, proved better result of 0.985 than 0.970.
This study presents development of the ANN simulator for well placement of infill drilling in gas fields. The input data of the ANN simulator includes the production time, well location, all inter well distances, boundary inter well distance, infill well position, productivity potential, functional links, reservoir pressure. The output data includes the bottomhole pressure in addition to the production rate. Thus, it is possible to calculate the productivity and bottomhole pressure during production period simultaneously, and it is expected that this model could replace conventional simulators. Training for the 20 well placement scenarios was conducted. As a result, it was found that accuracy of ANN simulator was high as the coefficient of correlation for production rate was 0.99 and the bottomhole pressure 0.98 respectively. From the resultes, the validity of the ANN simulator has been verified. The term, which could produce Maximum Daily Quantity (MDQ) at the gas field and the productivity according to the well location was analyzed. As a result, the MDQ could be maintained for a short time in scenario C-1, which has the three infill wells nearby aquifer boundary, and a long time in scenario A-1. In conclusion, it was found that scenario A maintained the MDQ up to 21% more than those of scenarios B and C which include parameters that might affect the productivity. Thus, the production rate can be maximized by selecting the location of production wells in comprehensive consideration of parameters that may affect the productivity. Also, because the developed ANN simulator could calculate both production rate and bottomhole pressure, respectively, it could be used as the forward simulator in a various inverse model.
The increasing use of cardioplegic solution for the reduction of ischemic tissue injury requires that all cardiplegic solution be carefully assessed for any protective or damaging properties. This study describes functional, enzymatic and structural assessment of the efficiency of three cardioplegic solutions (Young & GIK, Bretschneider, and $K^{+}$ Albumin solution) in a Modified Isolated Rat Heart Model of cardiopulmonary bypass and ischemic arrest. Isolated rat heart were subjected to a 2-minute period of coronary infusion with a cold cardioplegic or a noncardioplegic solution immediately before and also at the midpoint of a 60-minute period of hypothermic ($10{\pm}1$. C) ischemic cardiac arrest. The results of this study were as follow: 1. Spontaneous heart beat after ischemic arrest occured 16 seconds later after Langendorff reperfusion in the Young & GIK group (n=6), and 40 second later in the Bretschneider group (n=6) and 6 minute later in the $K^{+}$ Albumin group (n=6), and 16 minute later in the control group (non-cardioplegia). A good recovery state of spontaneous heart beat was shown in the Young & GIK and Bretschneider groups. 2. The percentage of recorveries of heart function at 30 minute after postischemic working heart perfusion were : heart rate $91.6{\pm}3.1$% (P<0.01)m oeaj airtuc oressyre $83{\pm}3$% (P<0.01), coronary flow $70{\pm}8$% (P<0.05) and aortic flow flow rate $39{\pm}9.3$% (P<0.05) in the Young & GIK group. This percentage of recoveries of the Young & GIK group was significantly greater than the control group. In the Bretschneider group, the percentage of recoveries were : heart rate $87.8{\pm}7.5$%(P<0.05), peak aortic pressure $71{\pm}2.3$% (P<0.05) and aortic flow rate $33.2{\pm}6.6$%(P<0.05). hte percentage of recoveries were significantly greater than in the control group. In the $K^{+}$ Albumin group, recoveries of heart function were poor. 3. Total CPK leakage was $131.2{\pm}12.75$IU/30 min/gm. dry weight in the control group, $50.65{\pm}12.75$IU in the Young & GIK gruop, $69.40{\pm}32.21$Iu in Bretschneider group, and $103.65{\pm}15.47$IU in the $K^{+}$ Albumin group during the 30 minute postischemic Langendorff reperfusion. Total CPK leakage was significantly less (P<0.001) in the Young & GIK group, than in the control group. 4. Direct correlatin between percentage recovery of aortic flow rate and total amount of CPK leakage from Myocardium was noticed.(Correlation Coefficient r = 0.76, P<0.001). 5. Mild perivascular edema was the only finding of light microscopic study of myocardium after 60 minute ischemic arrest with cold cardioplegic solutions and hypothermla.
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