Search results for: Fang Ye Yixuan Kang

Authors: Hyun Ah Yoon, Ji Yeon Kang, Hee Sun Kim, Yeong Soo Shin

Abstract:

Reinforced concrete (RC) shear wall system of residential buildings is popular in South Korea. RC walls are subjected to axial forces in common and the effect of axial forces on the strength loss of the fire damaged walls has not been investigated. This paper aims at investigating temperature distribution on fire damaged concrete walls having different axial loads. In the experiments, a variable of specimens is axial force ratio. RC walls are fabricated with 150mm of wall thicknesses, 750mm of lengths and 1,300mm of heights having concrete strength of 24MPa. After curing, specimens are heated on one surface with ISO-834 standard time-temperature curve for 2 hours and temperature distributions during the test are measured using thermocouples inside the walls. The experimental results show that the temperature of the RC walls exposed to fire increases as axial force ratio increases. To verify the experiments, finite element (FE) models are generated for coupled temperature-structure analyses. The analytical results of thermal behaviors are in good agreement with the experimental results. The predicted displacement of the walls decreases when the axial force increases. 

Keywords: Axial force ratio, coupled analysis, fire, reinforced concrete wall, temperature distribution.

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Authors: Zhou Xiong, Kang Shao Bo, Yang Bo

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To date, high-performance structural steel has been widely used for columns in construction practices due to its significant advantages over conventional steel. However, the same design approach with conventional steel columns is still adopted in the design of high-performance steel columns. As a result, its superior properties cannot be fully considered in design. This paper conducts a test and finite element analysis on the overall stability behaviour of welded Q460GJ steel box columns. In the test, four steel columns with different slenderness and width-to-thickness ratio were compressed under an axial compression testing machine. And finite element models were established in which material nonlinearity and residual stress distributions of test columns were included. Then, comparisons were made between test results and finite element result, it showed that finite element analysis results are agree well with the test result. It means that the test and finite element model are reliable. Then, we compared the test result with the design value calculated by current code, the result showed that Q460GJ steel box columns have the higher overall buckling capacity than the design value. It is necessary to update the design curves for Q460GJ steel columns so that the overall stability capacity of Q460GJ box columns can be designed appropriately.

Keywords: Axial compression, Finite element analysis, Overall stability, Q460GJ steel, Welded box columns.

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Authors: Shih-Bin Wang, Ping Yuan, Syu-Fang Liu, Ming-Jun Kuo

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By the application of an improved back-propagation neural network (BPNN), a model of current densities for a solid oxide fuel cell (SOFC) with 10 layers is established in this study. To build the learning data of BPNN, Taguchi orthogonal array is applied to arrange the conditions of operating parameters, which totally 7 factors act as the inputs of BPNN. Also, the average current densities achieved by numerical method acts as the outputs of BPNN. Comparing with the direct solution, the learning errors for all learning data are smaller than 0.117%, and the predicting errors for 27 forecasting cases are less than 0.231%. The results show that the presented model effectively builds a mathematical algorithm to predict performance of a SOFC stack immediately in real time. Also, the calculating algorithms are applied to proceed with the optimization of the average current density for a SOFC stack. The operating performance window of a SOFC stack is found to be between 41137.11 and 53907.89. Furthermore, an inverse predicting model of operating parameters of a SOFC stack is developed here by the calculating algorithms of the improved BPNN, which is proved to effectively predict operating parameters to achieve a desired performance output of a SOFC stack.

Keywords: a SOFC stack, BPNN, inverse predicting model of operating parameters, optimization of the average current density

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Authors: Yi-Zhong Weng, Chien-Kang Huang, Yu-Feng Huang, Chi-Yuan Yu, Darby Tien-Hao Chang

Abstract:

Search for a tertiary substructure that geometrically matches the 3D pattern of the binding site of a well-studied protein provides a solution to predict protein functions. In our previous work, a web server has been built to predict protein-ligand binding sites based on automatically extracted templates. However, a drawback of such templates is that the web server was prone to resulting in many false positive matches. In this study, we present a sequence-order constraint to reduce the false positive matches of using automatically extracted templates to predict protein-ligand binding sites. The binding site predictor comprises i) an automatically constructed template library and ii) a local structure alignment algorithm for querying the library. The sequence-order constraint is employed to identify the inconsistency between the local regions of the query protein and the templates. Experimental results reveal that the sequence-order constraint can largely reduce the false positive matches and is effective for template-based binding site prediction.

Keywords: Protein structure, binding site, functional prediction

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Authors: Jing Fang, Yao Cui, Mingming Wang, Shengli She, Jianping Yuan

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Wearable robotics is a potential solution in aiding gait rehabilitation of lower limbs dyskinesia patients, such as knee osteoarthritis or stroke afflicted patients. Many wearable robots have been developed in the form of rigid exoskeletons, but their bulk devices, high cost and control complexity hinder their popularity in the field of gait rehabilitation. Thus, the development of a portable, compliant and low-cost wearable robot for gait rehabilitation is necessary. Inspired by Chinese traditional folding fans and balloon inflators, the authors present an inflatable, foldable and variable stiffness knee exosuit (IFVSKE) in this paper. The pneumatic actuator of IFVSKE was fabricated in the shape of folding fans by using thermoplastic polyurethane (TPU) fabric materials. The geometric and mechanical properties of IFVSKE were characterized with experimental methods. To assist the knee joint smartly, an intelligent control profile for IFVSKE was proposed based on the concept of full-cycle energy management of the biomechanical energy during human movement. The biomechanical energy of knee joints in a walking gait cycle of patients could be collected and released to assist the joint motion just by adjusting the inner pressure of IFVSKE. Finally, a healthy subject was involved to walk with and without the IFVSKE to evaluate the assisting effects.

Keywords: Biomechanical energy management, gait rehabilitation, knee exosuit, wearable robotics.

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Authors: Jing Jia, Shanqing Huang, Fang Liu, Qiang Ren, Gui Li, Mengyun Cheng, Chufeng Jin, Yican Wu

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Medical image registration is the key technology in image guided radiation therapy (IGRT) systems. On the basis of the previous work on our IGRT prototype with a biorthogonal x-ray imaging system, we described a method focused on the 2D/2D rigid-body registration using multiresolution pyramid based mutual information in this paper. Three key steps were involved in the method ： firstly, four 2D images were obtained including two x-ray projection images and two digital reconstructed radiographies（DRRs ） as the input for the registration ； Secondly, each pair of the corresponding x-ray image and DRR image were matched using multiresolution pyramid based mutual information under the ITK registration framework ； Thirdly, we got the final couch offset through a coordinate transformation by calculating the translations acquired from the two pairs of the images. A simulation example of a parotid gland tumor case and a clinical example of an anthropomorphic head phantom were employed in the verification tests. In addition, the influence of different CT slice thickness were tested. The simulation results showed that the positioning errors were 0.068±0.070, 0.072±0.098, 0.154±0.176mm along three axes which were lateral, longitudinal and vertical. The clinical test indicated that the positioning errors of the planned isocenter were 0.066, 0.07, 2.06mm on average with a CT slice thickness of 2.5mm. It can be concluded that our method with its verified accuracy and robustness can be effectively used in IGRT systems for patient setup.

Keywords: 2D/2D registration, image guided radiation therapy, multi resolution pyramid, mutual information.

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Authors: Mi Ok Kang

Abstract:

This study examined the influences of including LGBTQ-related content in a multicultural teacher education course on the development of prospective teachers’ social justice identities. Appling a content analysis to 53 reflection texts written by participating prospective teachers in response to the relevant course content, this study deduced the stages of social justice identity development (naïve, acceptance, resistance, redefinition, and internalization) that participants reached during the course. The analysis demonstrated that the participants reached various stages in the social identity development model and none of the participants remained at the naïve stage during/after class. The majority (53%) of the participants reached the internalization stage during the coursework and became conscious about the heterosexual privileges they have had and aware of possible impacts of such privilege on their future LGBTQ students. Also the participants had begun to develop pedagogic action plans and devised applicable teaching strategies for their future students based on the new understanding of heteronormativity. We expect this study will benefit teacher educators and educational administrators who want to address LGBTQ-related issues in their multicultural education programs and/or revisit the goals, directions, and implications of their approach.

Keywords: LGBTQ, heteronormativity, social justice identity, teacher education, multicultural education, content analysis.

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Authors: Hui Zhang, Ye Tian, Fang Ye, Ziming Guo

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Communication signal modulation recognition technology is one of the key technologies in the field of modern information warfare. At present, communication signal automatic modulation recognition methods are mainly divided into two major categories. One is the maximum likelihood hypothesis testing method based on decision theory, the other is a statistical pattern recognition method based on feature extraction. Now, the most commonly used is a statistical pattern recognition method, which includes feature extraction and classifier design. With the increasingly complex electromagnetic environment of communications, how to effectively extract the features of various signals at low signal-to-noise ratio (SNR) is a hot topic for scholars in various countries. To solve this problem, this paper proposes a feature extraction algorithm for the communication signal based on the improved Holder cloud feature. And the extreme learning machine (ELM) is used which aims at the problem of the real-time in the modern warfare to classify the extracted features. The algorithm extracts the digital features of the improved cloud model without deterministic information in a low SNR environment, and uses the improved cloud model to obtain more stable Holder cloud features and the performance of the algorithm is improved. This algorithm addresses the problem that a simple feature extraction algorithm based on Holder coefficient feature is difficult to recognize at low SNR, and it also has a better recognition accuracy. The results of simulations show that the approach in this paper still has a good classification result at low SNR, even when the SNR is -15dB, the recognition accuracy still reaches 76%.

Keywords: Communication signal, feature extraction, holder coefficient, improved cloud model.

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Authors: Baydaa H. Maula, Ling Zhang, Tang Liang, Gao Xia, Xu Peng-Ju, Zhang Yong-Qiang, Kang Jie, Su Lei

Abstract:

Firstly, this study briefly presents the current situation that there exists a vast gap between current Chinese and Japanese seismic design specification for bridge pile foundation in liquefiable and liquefaction-induced lateral spreading ground; The Chinese and Japanese seismic design method and technical detail for bridge pile foundation in liquefying and lateral spreading ground are described and compared systematically and comprehensively, the methods of determining coefficient of subgrade reaction and its reduction factor as well as the computing mode of the applied force on pile foundation due to liquefaction-induced lateral spreading soil in Japanese design specification are especially introduced. Subsequently, the comparison indicates that the content of Chinese seismic design specification for bridge pile foundation in liquefiable and liquefaction-induced lateral spreading ground, just presenting some qualitative items, is too general and lacks systematicness and maneuverability. Finally, some defects of seismic design specification in China are summarized, so the improvement and revision of specification in the field turns out to be imperative for China, some key problems of current Chinese specifications are generalized and the corresponding improvement suggestions are proposed.

Keywords: liquefying soil, laterally spreading ground, seismic design specification for bridge pile foundation.

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Authors: Kang-Gyu Park, Sun-Jong Park, Hong Jae Yim, Hyo-Gyung Kwak

Abstract:

This paper attempts to evaluate the effect of fire damage on concrete by using nonlinear resonance vibration method, one of the nonlinear nondestructive method. Concrete exhibits not only nonlinear stress-strain relation but also hysteresis and discrete memory effect which are contained in consolidated materials. Hysteretic materials typically show the linear resonance frequency shift. Also, the shift of resonance frequency is changed according to the degree of micro damage. The degree of the shift can be obtained through nonlinear resonance vibration method. Five exposure scenarios were considered in order to make different internal micro damage. Also, the effect of post-fire-curing on fire-damaged concrete was taken into account to conform the change in internal damage. Hysteretic nonlinearity parameter was obtained by amplitudedependent resonance frequency shift after specific curing periods. In addition, splitting tensile strength was measured on each sample to characterize the variation of residual strength. Then, a correlation between the hysteretic nonlinearity parameter and residual strength was proposed from each test result.

Keywords: Fire damaged concrete, nonlinear resonance vibration method, nonlinearity parameter, post-fire-curing, splitting tensile strength.

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Authors: Kyekyung Kim, Sangseung Kang, Suyoung Chi, Jaehong Kim

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In recent years, IT convergence technology has been developed to get creative solution by combining robotics or sports science technology. Object detection and recognition have mainly applied to sports science field that has processed by recognizing face and by tracking human body. But object detection and recognition using vision sensor is challenge task in real world because of illumination. In this paper, object detection and recognition using vision sensor applied to sports simulator has been introduced. Face recognition has been processed to identify user and to update automatically a person athletic recording. Human body has tracked to offer a most accurate way of riding horse simulator. Combined image processing has been processed to reduce illumination adverse affect because illumination has caused low performance in detection and recognition in real world application filed. Face has recognized using standard face graph and human body has tracked using pose model, which has composed of feature nodes generated diverse face and pose images. Face recognition using Gabor wavelet and pose recognition using pose graph is robust to real application. We have simulated using ETRI database, which has constructed on horse riding simulator.

Keywords: Horse riding simulator, Object detection, Object recognition, User identification, Pose recognition.

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Authors: Chi-Fang Huang, Yun-Shiow Chen, Yun-Kung Chung

Abstract:

In the past decade, artificial neural networks (ANNs) have been regarded as an instrument for problem-solving and decision-making; indeed, they have already done with a substantial efficiency and effectiveness improvement in industries and businesses. In this paper, the Back-Propagation neural Networks (BPNs) will be modulated to demonstrate the performance of the collaborative forecasting (CF) function of a Collaborative Planning, Forecasting and Replenishment (CPFR®) system. CPFR functions the balance between the sufficient product supply and the necessary customer demand in a Supply and Demand Chain (SDC). Several classical standard BPN will be grouped, collaborated and exploited for the easy implementation of the proposed modular ANN framework based on the topology of a SDC. Each individual BPN is applied as a modular tool to perform the task of forecasting SKUs (Stock-Keeping Units) levels that are managed and supervised at a POS (point of sale), a wholesaler, and a manufacturer in an SDC. The proposed modular BPN-based CF system will be exemplified and experimentally verified using lots of datasets of the simulated SDC. The experimental results showed that a complex CF problem can be divided into a group of simpler sub-problems based on the single independent trading partners distributed over SDC, and its SKU forecasting accuracy was satisfied when the system forecasted values compared to the original simulated SDC data. The primary task of implementing an autonomous CF involves the study of supervised ANN learning methodology which aims at making “knowledgeable" decision for the best SKU sales plan and stocks management.

Keywords: CPFR, artificial neural networks, global logistics, supply and demand chain.

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Authors: Yoon- Ho Shin, Jin-Seung Choi, Dong-Won Kang, Jeong-Woo Seo, Joo-Hack Lee, Ju-Young Kim, Dae-Hyeok Kim, Seung-Tae Yang, Gye-Rae Tack

Abstract:

It is difficult to study the effect of various variables on cycle fitting through actual experiment. To overcome such difficulty, the forward dynamics of a musculoskeletal model was applied to cycle fitting in this study. The measured EMG data weres compared with the muscle activities of the musculoskeletal model through forward dynamics. EMG data were measured from five cyclists who do not have musculoskeletal diseases during three minutes pedaling with a constant load (150 W) and cadence (90 RPM). The muscles used for the analysis were the Vastus Lateralis (VL), Tibialis Anterior (TA), Bicep Femoris (BF), and Gastrocnemius Medial (GM). Person’s correlation coefficients of the muscle activity patterns, the peak timing of the maximum muscle activities, and the total muscle activities were calculated and compared. BIKE3D model of AnyBody (Anybodytech, Denmark) was used for the musculoskeletal model simulation. The comparisons of the actual experiments with the simulation results showed significant correlations in the muscle activity patterns (VL: 0.789, TA: 0.503, BF: 0.468, GM: 0.670). The peak timings of the maximum muscle activities were distributed at particular phases. The total muscle activities were compared with the normalized muscle activities, and the comparison showed about 10% difference in the VL (+10%), TA (+9.7%), and BF (+10%), excluding the GM (+29.4%). Thus, it can be concluded that muscle activities of model & experiment showed similar results. The results of this study indicated that it was possible to apply the simulation of further improved musculoskeletal model to cycle fitting.

Keywords: Cycle fitting, EMG, Musculoskeletal modeling, Simulation.

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Authors: Yamini Raju, Parminder S. Kang, Adam Moroz, Ross Clement, Ashley Hopwell, Alistair Duffy

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Accurate forecasting of fresh produce demand is one the challenges faced by Small Medium Enterprise (SME) wholesalers. This paper is an attempt to understand the cause for the high level of variability such as weather, holidays etc., in demand of SME wholesalers. Therefore, understanding the significance of unidentified factors may improve the forecasting accuracy. This paper presents the current literature on the factors used to predict demand and the existing forecasting techniques of short shelf life products. It then investigates a variety of internal and external possible factors, some of which is not used by other researchers in the demand prediction process. The results presented in this paper are further analysed using a number of techniques to minimize noise in the data. For the analysis past sales data (January 2009 to May 2014) from a UK based SME wholesaler is used and the results presented are limited to product ‘Milk’ focused on café’s in derby. The correlation analysis is done to check the dependencies of variability factor on the actual demand. Further PCA analysis is done to understand the significance of factors identified using correlation. The PCA results suggest that the cloud cover, weather summary and temperature are the most significant factors that can be used in forecasting the demand. The correlation of the above three factors increased relative to monthly and becomes more stable compared to the weekly and daily demand.

Keywords: Demand Forecasting, Deteriorating Products, Food Wholesalers, Principal Component Analysis and Variability Factors.

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Authors: Dongwan Kang, Joohyung Oh, Chaetae Im

Abstract:

Advancement of communication technologies and smart devices in the recent times is leading to changes into the integrated wired and wireless communication environments. Since early days, businesses had started introducing environments for mobile device application to their operations in order to improve productivity (efficiency) and the closed corporate environment gradually shifted to an open structure. Recently, individual user's interest in working environment using mobile devices has increased and a new corporate working environment under the concept of BYOD is drawing attention. BYOD (bring your own device) is a concept where individuals bring in and use their own devices in business activities. Through BYOD, businesses can anticipate improved productivity (efficiency) and also a reduction in the cost of purchasing devices. However, as a result of security threats caused by frequent loss and theft of personal devices and corporate data leaks due to low security, companies are reluctant about adopting BYOD system. In addition, without considerations to diverse devices and connection environments, there are limitations in detecting abnormal behaviors, such as information leaks, using the existing network-based security equipment. This study suggests a method to detect abnormal behaviors according to individual behavioral patterns, rather than the existing signature-based malicious behavior detection, and discusses applications of this method in BYOD environment.

Keywords: BYOD, Security, Anomaly Behavior Detection.

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Authors: Mei-Fang Wu, Shu-Li Wang, Feng-Tsung Cheng

Abstract:

Highly developed technology and highly competitive global market highlight the important role of competitive advantages and operation performances in sustainable company operation. Activity-Based Costing (ABC) provides accurate operation cost and operation performance information. Rich literatures provide relevant research with cases study on Activity-Based Costing application, but the research on cause relationship between key success factors and its specific outcome, such as profitability or share market are few. These relationships provide the ways to handle the key success factors to achieve the specific outcomes for ensuring to promote the competitive advantages and operation performances. The main purposes of this research are exploring the key success paths by Key Success Paths approach which will lead the ways to apply Activity-Base Costing. The Key Success Paths is the innovative method which is exploring the cause relationships and explaining what are the effects of key success factors to specific outcomes of Activity-Based Costing implementation. The cause relationships between key success factors and successful specific outcomes are Key Success Paths (KSPs). KSPs are the guidelines to lead the cost management strategies to achieve the goals of competitive advantages and operation performances. The research findings indicate that good management system design may affect the well outcomes of Activity-Based Costing application and achieve to outstanding competitive advantage, operating performance and profitability as well by KSPs exploration.

Keywords: Activity-Based Costing, Key success factors, Key success paths approach, Key success paths, Key failure paths.

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Authors: Fang Yao, Minglei Chen

Abstract:

City shrinkage is one of the thorny problems that many European cities have to face with nowadays. It is mainly expressed as the decrease of population in these cities. Eastern Germany is one of the pioneers of European shrinking cities with long shrinking history. The paper selects one representative shrinking city Halle (Saale) in eastern Germany as research objective, collecting and investigating nearly 20 years (1993-2010) municipal data after the reunification of Germany. These data based on five dimensions, which are demographic, economic, social, spatial and environmental and total 16 eligible variables. Factor Analysis is used to deal with these variables in order to assess the most important factors affecting shrinking Halle. The results show that there are three main factors determine the shrinkage of Halle, respectively named “demographical and economical factor”, “social stability factor”, and “city vitality factor”. The three factors act at different time period of Halle’s shrinkage: from 1993 to 1997 the demographical and economical factor played an important role; from 1997 to 2004 the social stability factor is significant to city shrinkage; since 2005 city vitality factor determines the shrinkage of Halle. In recent years, the shrinkage in Halle mitigates that shows the sign of growing population. Thus the city Halle should focus on attaching more importance on the city vitality factor to prevent the city from shrinkage. Meanwhile, the city should possess a positive perspective to shift the growth-oriented development to tap the potential of shrinking cities. This method is expected to apply to further research and other shrinking cities

Keywords: Demography, Factor analysis, Halle, Shrinking cities.

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Authors: Woo-tai Jung, Jong-sup Park, Jae-yoon Kang, Moon-seoung Keum

Abstract:

CFRP (Carbon Fiber Reinforced Polymer) is mainly used as reinforcing material for degraded structures owing to its advantages including its non-corrodibility, high strength and lightweight properties. Recently, dedicated studies focused not only on its simple bonding but also on its tensioning. The tension necessary for prestressing requires the anchoring of multi-CFRP tendons with high capacity and the surface treatment of the CFRP tendons may also constitute an important issue according to the type of anchor. The wedge type, swage type or bonded type anchor can be used to anchor the CFRP tendon. The bonded type anchor presents the disadvantage to lengthen the length of the anchor due to the low bond strength of the CFRP tendon without surface treatment. This study intends to overcome this drawback through the application of a method enlarging the bond area at the end of the CFRP tendon. This method enlarges the bond area by splitting the end of the CFRP tendon along its length and can be applied when CFRP is produced by pultrusion. The application of this method shows that the mono-CFRP tendon and 3-multi CFRP tendon secured the anchor performance corresponding to the tensile performance of the CFRP tendon and that the 7-multi tendon secured anchor performance corresponding to 90% of the tensile strength due to the occurrence of buckling in the steel tube anchorage. 

Keywords: Carbon fiber reinforced polymer (CFRP), Tendon, Anchor, Tensile property, Bond strength.

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Authors: Chongya Song, Kang Yen, Alexander Pons, Jin Liu

Abstract:

In the field of machine learning, the ensemble has been employed as a common methodology to improve the performance upon multiple base classifiers. However, the true predictions are often canceled out by the false ones during consensus due to a phenomenon called “curse of correlation” which is represented as the strong interferences among the predictions produced by the base classifiers. In addition, the existing practices are still not able to effectively mitigate the problem of imbalanced classification. Based on the analysis on our experiment results, we conclude that the two problems are caused by some inherent deficiencies in the approach of consensus. Therefore, we create an enhanced ensemble algorithm which adopts a designed rank-based chain-mode consensus to overcome the two problems. In order to evaluate the proposed ensemble algorithm, we employ a well-known benchmark data set NSL-KDD (the improved version of dataset KDDCup99 produced by University of New Brunswick) to make comparisons between the proposed and 8 common ensemble algorithms. Particularly, each compared ensemble classifier uses the same 22 base classifiers, so that the differences in terms of the improvements toward the accuracy and reliability upon the base classifiers can be truly revealed. As a result, the proposed rank-based chain-mode consensus is proved to be a more effective ensemble solution than the traditional consensus approach, which outperforms the 8 ensemble algorithms by 20% on almost all compared metrices which include accuracy, precision, recall, F1-score and area under receiver operating characteristic curve.

Keywords: Consensus, curse of correlation, imbalanced classification, rank-based chain-mode ensemble.

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Authors: Yazan M. Alatrash, Han-ok Kang, Hyun-gi Yoon, Shen Zhang, Juhyeon Yoon

Abstract:

Flow coastdown phenomena are very important to secure nuclear fuel integrity during loss of off-site power accidents. In this study, primary coolant flow coastdown phenomena are investigated for the Jordan Research and Training Reactor (JRTR) using a simulation software package, Modular Modeling System (MMS). Two MMS models are built. The first one is a simple model to investigate the characteristics of the primary coolant pump only. The second one is a model for a simulation of the Primary Coolant System (PCS) loop, in which all the detailed design data of the JRTR PCS system are modeled, including the geometrical arrangement data. The same design data for a PCS pump are used for both models. Coastdown curves obtained from the two models are compared to study the PCS loop coolant inertia effect on a flow coastdown. Results showed that the loop coolant inertia effect is found to be small in the JRTR PCS loop, i.e., about one second increases in a coastdown half time required to halve the coolant flow rate. The effects of different flywheel inertia on the flow coastdown are also investigated. It is demonstrated that the coastdown half time increases with the flywheel inertia linearly. The designed coastdown half time is proved to be well above the design requirement for the fuel integrity.

Keywords: Flow Coastdown, Loop Coolant Inertia, Modeling, Research Reactor.

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Authors: Wanhyun Cho, Soonja Kang, Sangkyoon Kim, Soonyoung Park

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In this paper, we propose the variational EM inference algorithm for the multi-class Gaussian process classification model that can be used in the field of human behavior recognition. This algorithm can drive simultaneously both a posterior distribution of a latent function and estimators of hyper-parameters in a Gaussian process classification model with multiclass. Our algorithm is based on the Laplace approximation (LA) technique and variational EM framework. This is performed in two steps: called expectation and maximization steps. First, in the expectation step, using the Bayesian formula and LA technique, we derive approximately the posterior distribution of the latent function indicating the possibility that each observation belongs to a certain class in the Gaussian process classification model. Second, in the maximization step, using a derived posterior distribution of latent function, we compute the maximum likelihood estimator for hyper-parameters of a covariance matrix necessary to define prior distribution for latent function. These two steps iteratively repeat until a convergence condition satisfies. Moreover, we apply the proposed algorithm with human action classification problem using a public database, namely, the KTH human action data set. Experimental results reveal that the proposed algorithm shows good performance on this data set.

Keywords: Bayesian rule, Gaussian process classification model with multiclass, Gaussian process prior, human action classification, laplace approximation, variational EM algorithm.

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Authors: Hai-Ying Liu, Yi-Hao Chen, Shu-Yin Pang, Feng-Hua Wang, Xiao-Fang Peng, Li-Yuan Yang, Zheng-Rong Chen, Yi Chen, Bing Zhu

Abstract:

Objective: Biliary atresia (BA) is characterized by progressive liver fibrosis. Epithelial-mesenchymal transition (EMT) has been implicated as a key mechanism in the pathogenesis of organ fibrosis. MiR-200a has been shown to repress EMT. We aim to explore the role of miR-200a in the fibrogenesis of BA. Methods: We obtained the plasma samples and liver samples from patients with BA or controls to examine the role of miR-200a. Histological liver fibrosis was assessed using the Ishak fibrosis scores. Reverse transcription quantitative polymerase chain reaction (RT-qPCR) was performed to detect the expression of miR-200a in plasma. We also evaluated the expression of miR-200a in liver tissues using tyramide signal amplification fluorescence in situ hybridization (TSA-FISH). The expression of EMT related proteins zinc finger E-box-binding homeobox 1 (ZEB1), E-cadherin and α-smooth muscle actin (α-SMA) in the liver sections were detected by immunohistochemical staining. Results: We found that the expression of miR-200a was both elevated in the plasma and liver tissues from BA patients compared with the controls. The hepatic expression of ZEB1 and α-SMA were markedly increased in the liver sections from BA patients compared to the controls, whereas E-cadherin was downregulated in the BA group. Simultaneously, we noted that the hepatic expression of miR-200a, E-cadherin and α-SMA were upregulated with the progression of liver fibrosis in the BA group, while ZEB1 was downregulated with the progression of liver fibrosis in BA patients. Conclusion: These findings suggest EMT has a critical effect on the fibrotic process of BA, and the interaction between miR-200a and ZEB1 may regulate EMT and eventually influence liver fibrogenesis of BA.

Keywords: Biliary atresia, liver fibrosis, MicroRNA, epithelial-mesenchymal transition, zinc finger e-box-binding homeobox 1.

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Authors: Eun Mi Ryu, Ah Young An, Ji Yeon Kang, Yeong Soo Shin, Hee Sun Kim

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When high strength reinforced concrete is exposed to high temperature due to a fire, deteriorations occur such as loss in strength and elastic modulus, cracking and spalling of the concrete. Therefore, it is important to understand risk of structural safety in building structures by studying structural behaviors and rehabilitation of fire damaged high strength concrete structures. This paper aims at investigating rehabilitation effect on fire damaged high strength concrete beams using experimental and analytical methods. In the experiments, flexural specimens with high strength concrete are exposed to high temperatures according to ISO 834 standard time temperature curve. From four-point loading test, results show that maximum loads of the rehabilitated beams are similar to or higher than those of the non-fire damaged RC beam. In addition, structural analyses are performed using ABAQUS 6.10-3 with same conditions as experiments to provide accurate predictions on structural and mechanical behaviors of rehabilitated RC beams. The parameters are the fire cover thickness and strengths of repairing mortar. Analytical results show good rehabilitation effects, when the results predicted from the rehabilitated models are compared to structural behaviors of the non-damaged RC beams. In this study, fire damaged high strength concrete beams are rehabilitated using polymeric cement mortar. The predictions from the finite element (FE) models show good agreements with the experimental results and the modeling approaches can be used to investigate applicability of various rehabilitation methods for further study.

Keywords: Fire, High strength concrete, Rehabilitation, Reinforced concrete beam.

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Authors: Won Yeol Choi, Sangmo Kang

Abstract:

The propulsion of a bacterial flagellum in a viscous fluid has attracted many interests in the field of biological hydrodynamics, but remains yet fully understood and thus still a challenging problem. In this study, therefore, we have numerically investigated the flow around a steadily rotating micro-sized spring to further understand such bacterial flagellum propulsion. Note that a bacterium gains thrust (propulsive force) by rotating the flagellum connected to the body through a bio motor to move forward. For the investigation, we convert the spring model from the micro scale to the macro scale using a similitude law (scale law) and perform simulations on the converted macro-scale model using a commercial software package, CFX v13 (ANSYS). To scrutinize the propulsion characteristics of the flagellum through the simulations, we make parameter studies by changing some flow parameters, such as the pitch, helical radius and rotational speed of the spring and the Reynolds number (or fluid viscosity), expected to affect the thrust force experienced by the rotating spring. Results show that the propulsion characteristics depend strongly on the parameters mentioned above. It is observed that the forward thrust increases in a linear fashion with either of the rotational speed or the fluid viscosity. In addition, the thrust is directly proportional to square of the helical radius and but the thrust force is increased and then decreased based on the peak value to the pitch. Finally, we also present the appropriate flow and pressure fields visualized to support the observations.

Keywords: Fluid viscosity, hydrodynamics, similitude, propulsive force.

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Authors: Jeong-Woo Seo, Jin-Seung Choi, Dong-Won Kang, Jae-Hyuk Bae, Gye-Rae Tack

Abstract:

To achieve accurate and precise results of finite element analysis (FEA) of bones, it is important to represent the load/boundary conditions as identical as possible to the human body such as the bone properties, the type and force of the muscles, the contact force of the joints, and the location of the muscle attachment. In this study, the difference in the Von-Mises stress and the total deformation was compared by classifying them into Case 1, which shows the actual anatomical form of the muscle attached to the femur when the same muscle force was applied, and Case 2, which gives a simplified representation of the attached location. An inverse dynamical musculoskeletal model was simulated using data from an actual walking experiment to complement the accuracy of the muscular force, the input value of FEA. The FEA method using the results of the muscular force that were calculated through the simulation showed that the maximum Von-Mises stress and the maximum total deformation in Case 2 were underestimated by 8.42% and 6.29%, respectively, compared to Case 1. The torsion energy and bending moment at each location of the femur occurred via the stress ingredient. Due to the geometrical/morphological feature of the femur of having a long bone shape when the stress distribution is wide, as shown in Case 1, a greater Von-Mises stress and total deformation are expected from the sum of the stress ingredients. More accurate results can be achieved only when the muscular strength and the attachment location in the FEA of the bones and the attachment form are the same as those in the actual anatomical condition under the various moving conditions of the human body.

Keywords: Musculoskeletal modeling, Finite element analysis, Von-Mises stress, Deformation, Muscle attachment.

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Authors: Chao-Linag Hsieh, Zheng-Wei Ye, Chen-Kang Huang, Yeun-Chung Lee, Chih-Hong Sun, Tzai-Hung Wen, Jehn-Yih Juang, Joe-Air Jiang

Abstract:

Air pollution and climate warming become more and more intensified in many areas, especially in urban areas. Environmental parameters are critical information to air pollution and weather monitoring. Thus, it is necessary to develop a suitable air pollution and weather monitoring system for urban areas. In this study, a vehicle monitoring system (VMS) based on the IoT technique is developed. Cars are selected as the research tool because it can reach a greater number of streets to collect data. The VMS can monitor different environmental parameters, including ambient temperature and humidity, and air quality parameters, including PM2.5, NO₂, CO, and O₃. The VMS can provide other information, including GPS signals and the vibration information through driving a car on the street. Different sensor modules are used to measure the parameters and collect the measured data and transmit them to a cloud server through the LoRa protocol. A user interface is used to show the sensing data storing at the cloud server. To examine the performance of the system, a researcher drove a Nissan x-trail 1998 to the area close to the Da’an District office in Taipei to collect monitoring data. The collected data are instantly shown on the user interface. The four kinds of information are provided by the interface: GPS positions, weather parameters, vehicle information, and air quality information. With the VMS, users can obtain the information regarding air quality and weather conditions when they drive their car to an urban area. Also, government agencies can make decisions on traffic planning based on the information provided by the proposed VMS.

Keywords: Vehicle, monitoring system, LoRa, smart city.

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Authors: Joo-Hack Lee, Jin-Seung Choi, Dong-Won Kang, Jeong-Woo Seo, Ju-Young Kim, Dae-Hyeok Kim, Seung-Tae Yang, Gye-Rae Tack

Abstract:

For cycling, the analysis of the pedal force is one of the important factors in the study of exercise ability assessment and overuse injuries. In past studies, a two-axis measurement sensor was used at the sagittal plane to measure the force only in the anterior, posterior, and vertical directions and to analyze the loss of force and the injury on the frontal plane due to the forces in the right and left directions. In this study, which is a basic study on diverse analyses of the pedal force that consider the forces on the sagittal plane and the frontal plane, a three-axis pedal force measurement sensor was developed to measure the anterior-posterior (Fx), medio-lateral (Fz), and vertical (Fy) forces. The sensor was fabricated with a size and shape similar to those of the general flat pedal, and had a 550g weight that allowed smooth pedaling. Its measurement range was ±1000 N for Fx and Fz and ±2000 N for Fy, and its non-linearity, hysteresis, and repeatability were approximately 0.5%. The data were sampled at 1000 Hz using a signal collector. To use the developed sensor, the pedaling efficiency (index of efficiency, IE) and the range of left and right (medio-lateral, ML) forces were measured with two seat heights (low and high). The results of the measurement showed that the IE was higher and the force range in the ML direction was lower with the high position than with the low position. The developed measurement sensor and its application results will be useful in understanding and explaining the complicated pedaling technique, and will enable diverse kinematic analyses of the pedal force on the sagittal plane and the frontal plane.

Keywords: Cycling, Index of effectiveness, Pedal force.

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Authors: H. Zarei, M. H. Fazel Zarandi, M. Karbasian

Abstract:

A Decision Support System/Expert System for stock portfolio selection presented where at first step, both technical and fundamental data used to estimate technical and fundamental return and risk (1st phase); Then, the estimated values are aggregated with the investor preferences (2nd phase) to produce convenient stock portfolio. In the 1st phase, there are two expert systems, each of which is responsible for technical or fundamental estimation. In the technical expert system, for each stock, twenty seven candidates are identified and with using rough sets-based clustering method (RC) the effective variables have been selected. Next, for each stock two fuzzy rulebases are developed with fuzzy C-Mean method and Takai-Sugeno- Kang (TSK) approach; one for return estimation and the other for risk. Thereafter, the parameters of the rule-bases are tuned with backpropagation method. In parallel, for fundamental expert systems, fuzzy rule-bases have been identified in the form of “IF-THEN" rules through brainstorming with the stock market experts and the input data have been derived from financial statements; as a result two fuzzy rule-bases have been generated for all the stocks, one for return and the other for risk. In the 2nd phase, user preferences represented by four criteria and are obtained by questionnaire. Using an expert system, four estimated values of return and risk have been aggregated with the respective values of user preference. At last, a fuzzy rule base having four rules, treats these values and produce a ranking score for each stock which will lead to a satisfactory portfolio for the user. The stocks of six manufacturing companies and the period of 2003-2006 selected for data gathering.

Keywords: Stock Portfolio Selection, Fuzzy Rule-Base ExpertSystems, Financial Decision Support Systems, Technical Analysis, Fundamental Analysis.

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Authors: Chengfeng Fang, Mohamed Ali Sadakkathulla, Abdul Sheikh

Abstract:

Ultra-high-performance fiber reinforced concrete (UHPFRC) is a specially formulated cement-based composite characterized with an ultra-high compressive strength (f_c^’ = 240 MPa) and a low water-cement ratio (W/B= 0.2). With such material characteristics, UHPFRC is favored for the design and constructions of structures required high structural performance and slender geometries. Unlike conventional concrete, the structural performance of members manufactured with UHPFRC has not yet been fully studied, particularly, for UHPFRC columns with high slenderness. In this study, the behaviors of slender UHPFRC columns under concentric or eccentric load will be investigated both experimentally and numerically. Four slender UHPFRC columns were tested under eccentric loads with eccentricities, of 0 mm, 35 mm, 50 mm, and 85 mm, respectively, and one UHPFRC beam was tested under four-point bending. Finite element (FE) analysis was conducted with concrete damage plasticity (CDP) modulus to simulating the load-middle height or middle span deflection relationships and damage patterns of all UHPFRC members. Simulated results were compared against the experimental results and observation to gain the confidence of FE model, and this model was further extended to conduct parametric studies, which aim to investigate the effects of slenderness regarding failure modes and load-moment interaction relationships. Experimental results showed that the load bearing capacities of the slender columns reduced with an increase in eccentricity. Comparisons between load-middle height and middle span deflection relationships as well as damage patterns of all UHPFRC members obtained both experimentally and numerically demonstrated high accuracy of the FE simulations. Based on the available FE model, the following parametric study indicated that a further increase in the slenderness of column resulted in significant decreases in the load-bearing capacities, ductility index, and flexural bending capacities.

Keywords: Eccentric loads, ductility index, RC column, slenderness, UHPFRC.

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Authors: Yeo Kyeong Lee, Hae Won Min, Ji Yeon Kang, Hee Sun Kim, Yeong Soo Shin

Abstract:

In recent years, fire accidents have been steadily increased and the amount of property damage caused by the accidents has gradually raised. Damaging building structure, fire incidents bring about not only such property damage but also strength degradation and member deformation. As a result, the building structure undermines its structural ability. Examining the degradation and the deformation is very important because reusing the building is more economical than reconstruction. Therefore, engineers need to investigate the strength degradation and member deformation well, and make sure that they apply right rehabilitation methods. This study aims at evaluating deformation characteristics of fire damaged and rehabilitated normal strength concrete beams through both experiments and finite element analyses. For the experiments, control beams, fire damaged beams and rehabilitated beams are tested to examine deformation characteristics. Ten test beam specimens with compressive strength of 21MPa are fabricated and main test variables are selected as cover thickness of 40mm and 50mm and fire exposure time of 1 hour or 2 hours. After heating, fire damaged beams are air-recurred for 2 months and rehabilitated beams are repaired with polymeric cement mortar after being removed the fire damaged concrete cover. All beam specimens are tested under four points loading. FE analyses are executed to investigate the effects of main parameters applied to experimental study. Test results show that both maximum load and stiffness of the rehabilitated beams are higher than those of the fire damaged beams. In addition, predicted structural behaviors from the analyses also show good rehabilitation effect and the predicted load-deflection curves are similar to the experimental results. For the further, the proposed analytical method can be used to predict deformation characteristics of fire damaged and rehabilitated concrete beams without suffering from time and cost consuming of experimental process.

Keywords: Fire, Normal strength concrete, Rehabilitation, Reinforced concrete beam.

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