Search results for: Ming L. Wang

Authors: Shu-Yu Chung, Ying-Fang Wang, Shih-Min Wang

Abstract:

To conduct long-term exposure assessments are important for workers exposed to chemicals with chronic effects. However, it usually encounters with several constrains, including cost, workers' willingness, and interference to work practice, etc., leading to inadequate long-term exposure data in the real world. In this study, an integrated approach was developed for conducting long-term exposure assessment for welding workers in a shipbuilding factory. A laboratory study was conducted to yield the fume generation rates under various operating conditions. The results and the measured environmental conditions were applied to the near field/far field (NF/FF) model for predicting long term fume exposures via the Monte Carlo simulation. Then, the predicted long-term concentrations were used to determine the prior distribution in Bayesian decision analysis (BDA). Finally, the resultant posterior distributions were used to assess the long-term exposure and serve as basis for initiating control strategies for shipbuilding workers. Results show that the NF/FF model was a suitable for predicting the exposures of metal contents containing in welding fume. The resultant posterior distributions could effectively assess the long-term exposures of shipbuilding welders. Welders' long-term Fe, Mn and Pb exposures were found with high possibilities to exceed the action level indicating preventive measures should be taken for reducing welders' exposures immediately. Though the resultant posterior distribution can only be regarded as the best solution based on the currently available predicting and monitoring data, the proposed integrated approach can be regarded as a possible solution for conducting long term exposure assessment in the field.

Keywords: Bayesian decision analysis, exposure assessment, near field and far field model, shipbuilding industry, welding fume

Procedia PDF Downloads 142

Authors: Yan Wang, Guowei Chen, Gang Wang

Abstract:

Soil microbial diversity is one of the important parameters to assess the soil fertility and soil health, even stability of the ecosystem. In this paper, we aim to reveal the soil microbial difference in rhizosphere and root zone, even to pick the special biomarkers influenced by the long term tillage practices, which included four treatments of no-tillage, ridge tillage, continuous cropping with corn and crop rotation with corn and soybean. Here, high-throughput sequencing was performed to investigate the difference of bacteria in rhizosphere and root zone. The results showed a very significant difference of species richness between rhizosphere and root zone soil at the same crop rotation system (p < 0.01), and also significant difference of species richness was found between continuous cropping with corn and corn-soybean rotation treatment in the rhizosphere statement, no-tillage and ridge tillage in root zone soils. Implied by further beta diversity analysis, both tillage methods and crop rotation systems influence the soil microbial diversity and community structure in varying degree. The composition and community structure of microbes in rhizosphere and root zone soils were clustered distinctly by the beta diversity (p < 0.05). Linear discriminant analysis coupled with effect size (LEfSe) analysis of total taxa in rhizosphere picked more than 100 bacterial taxa, which were significantly more abundant than that in root zone soils, whereas the number of biomarkers was lower between the continuous cropping with corn and crop rotation treatment, the same pattern was found at no-tillage and ridge tillage treatment. Bacterial communities were greatly influenced by main environmental factors in large scale, which is the result of biological adaptation and acclimation, hence it is beneficial for optimizing agricultural practices.

Keywords: tillage methods, biomarker, biodiversity, rhizosphere

Procedia PDF Downloads 166

Authors: Xiaochun Huang, Xuejun Zhao, Yun Zou, Feiyu Yang, Wenbin Liu, Nan Deng, Ming Zhang, Nengbin Cai

Abstract:

A simple device termed infrared radiation (IR) was developed for rapid visualization of sweat fingerprints deposit on paper with blue light (450 nm, 11 W). In this approach, IR serves as the pretreatment device before the sweat fingerprints was illuminated by blue light. An annular blue light source was adopted for visualizing latent sweat fingerprints. Sample fingerprints were examined under various conditions after deposition, and experimental results indicate that the recovery rate of the latent sweat fingerprints is in the range of 50%-100% without chemical treatments. A mechanism for the observed visibility is proposed based on transportation and re-impregnation of fluorescer in paper at the region of water. And further exploratory experimental results gave the full support to the visible mechanism. Therefore, such a method as IR-pretreated in detecting latent fingerprints may be better for examination in the case where biological information of samples is needed for consequent testing.

Keywords: forensic science, visualization, infrared radiation, blue light, latent sweat fingerprints, detection

Procedia PDF Downloads 497

Authors: Ming Su, Ziqiang Mu

Abstract:

This paper proposes a synthesis method for nonuniform linear antenna arrays that combine Gaussian process regression (GPR) and genetic algorithm (GA). In this method, the GPR model can be used to calculate the array radiation pattern in the presence of mutual coupling effects, and then the GA is used to optimize the excitations and locations of the elements so as to generate the desired radiation pattern. In this paper, taking a 9-element nonuniform linear array as an example and the desired radiation pattern corresponding to a Chebyshev distribution as the optimization objective, optimize the excitations and locations of the elements. Finally, the optimization results are verified by electromagnetic simulation software CST, which shows that the method is effective.

Keywords: nonuniform linear antenna arrays, GPR, GA, mutual coupling effects, active element pattern

Procedia PDF Downloads 110

Authors: Lin Wenli, Fu Linchun, Zhang Yi, Wu Ming

Abstract:

To meet the demands of long-life and high-intelligence for satellites, the electrical power system should be provided with self-health condition evaluation capability. Any over-stress events in operations should be recorded. Based on Linear stresses accumulation damage theory, accumulative damage analysis was performed on thermal-mechanical-electrical united stresses for three components including the solar array, the batteries and the power conditioning unit. Then an overall health percentage evaluation model for satellite electrical power system was built. To obtain the accurate quantity for system health percentage, an automatic feedback closed-loop correction method for all coefficients in the evaluation model was present. The evaluation outputs could be referred as taking earlier fault-forecast and interventions for Ground Control Center or Satellites self.

Keywords: satellite electrical power system, health percentage, linear stresses accumulation damage, evaluation model

Procedia PDF Downloads 412

Authors: Fuad Noman, Sh-Hussain Salleh, Chee-Ming Ting, Hadri Hussain, Syed Rasul

Abstract:

In this paper, a data-driven dictionary approach is proposed for the automatic detection and classification of cardiovascular abnormalities. Electrocardiography (ECG) signal is represented by the trained complete dictionaries that contain prototypes or atoms to avoid the limitations of pre-defined dictionaries. The data-driven trained dictionaries simply take the ECG signal as input rather than extracting features to study the set of parameters that yield the most descriptive dictionary. The approach inherently learns the complicated morphological changes in ECG waveform, which is then used to improve the classification. The classification performance was evaluated with ECG data under two different preprocessing environments. In the first category, QT-database is baseline drift corrected with notch filter and it filters the 60 Hz power line noise. In the second category, the data are further filtered using fast moving average smoother. The experimental results on QT database confirm that our proposed algorithm shows a classification accuracy of 92%.

Keywords: electrocardiogram, dictionary learning, sparse coding, classification

Procedia PDF Downloads 386

Authors: Guo-Ming Sung, Ramavath Naga Raju Naik

Abstract:

This paper presents a low power, high speed, sense-amplifier based flip-flop (SAFF). The flip-flop’s power con-sumption and delay are greatly reduced by employing a new conditionally precharge sense-amplifier stage and a single-ended latch stage. Glitch-free and contention-free latch operation is achieved by using a conditional cut-off strategy. The design uses fewer transistors, has a lower clock load, and has a simple structure, all of which contribute to a near-zero setup time. When compared to previous flip-flop structures proposed for similar input/output conditions, this design’s performance and overall PDP have improved. The post layout simulation of the circuit uses 2.91µW of power and has a delay of 65.82 ps. Overall, the power-delay product has seen some enhancements. Cadence Virtuoso Designing tool with CMOS 90nm technology are used for all designs.

Keywords: high-speed, low-power, flip-flop, sense-amplifier

Procedia PDF Downloads 163

Authors: Mengying Wang, Dongjing Liu, Holger Schwender, Ping Wang, Hongping Zhu, Tao Wu, Terri H Beaty

Abstract:

Background: Maternal smoking is a recognized risk factor for nonsyndromic cleft lip with or without cleft palate (NSCL/P). It has been reported that the effect of maternal smoking on oral clefts is mediated through genes that influence nicotine dependence. The polymorphisms of cholinergic receptor nicotinic alpha (CHRNA) and beta (CHRNB) subunits genes have previously shown strong associations with nicotine dependence. Here, we attempted to investigate whether the above genes are associated with clefting risk through testing for potential gene-gene (G×G) and gene-environment (G×E) interaction. Methods: We selected 120 markers in 14 genes associated with nicotine dependence to conduct transmission disequilibrium tests among 806 Chinese NSCL/P case-parent trios ascertained in an international consortium which conducted a genome-wide association study (GWAS) of oral clefts. We applied Cordell’s method using “TRIO” package in R to explore G×G as well as G×E interaction involving environmental tobacco smoke (ETS) based on conditional logistic regression model. Results: while no SNP showed significant association with NSCL/P after Bonferroni correction, we found signals for G×G interaction between 10 pairs of SNPs in CHRNA3, CHRNA5, and CHRNB4 (p<10-8), among which the most significant interaction was found between RS3743077 (CHRNA3) and RS11636753 (CHRNB4, p<8.2×10-12). Linkage disequilibrium (LD) analysis revealed only low level of LD between these markers. However, there were no significant results for G×ETS interaction. Conclusion: This study fails to detect association between nicotine dependence genes and NSCL/P, but illustrates the importance of taking into account potential G×G interaction for genetic association analysis in NSCL/P. This study also suggests nicotine dependence genes should be considered as important candidate genes for NSCL/P in future studies.

Keywords: Gene-Gene Interaction, Maternal Smoking, Nicotine Dependence, Non-Syndromic Cleft Lip with or without Cleft Palate

Procedia PDF Downloads 338

Authors: Jer-Yuh Liu, Je-Chiuan Ye, Jin-Ming Hwang

Abstract:

Protein kinase C alpha (PKCα) is a key signaling molecule in human cancer development. As a therapeutic strategy, targeting PKCα is difficult because the molecule is ubiquitously expressed in non-malignant cells. PKCα is regulated by the cooperative interaction of the transcription factors myeloid zinc finger 1 (MZF-1) and Ets-like protein-1 (Elk-1) in human cancer cells. By conducting tissue array analysis, herein, we determined the protein expression of MZF-1/Elk-1/PKCα in various cancers. The data show that the expression of MZF-1/Elk-1 is correlated with that of PKCα in hepatocellular carcinoma (HCC), but not in bladder and lung cancers. In addition, the PKCα down-regulation by shRNA Elk-1 was only observed in the HCC SK-Hep-1 cells. Blocking the interaction between MZF-1 and Elk-1 through the transfection of their binding domain MZF-160–72 decreased PKCα expression. This step ultimately depressed the epithelial-mesenchymal transition potential of the HCC cells. These findings could be used to develop an alternative therapeutic strategy for patients with the PKCα-derived HCC.

Keywords: protein kinase C alpha, myeloid zinc finger 1, ets-like protein-1, hepatocellular carcinoma

Procedia PDF Downloads 227

Authors: Jason Ting Jing Cheng, Lee Foo Wei, Yew Ming Kun, Mo Kim Hung, Yip Chun Chieh

Abstract:

This research delves into the structural characteristics of distinct construction material, rubberized lightweight foam concrete (RLFC) wall panels, which have been developed as a sustainable alternative for the construction industry. These panels are engineered with a RLFC core, possessing a density of 1150 kg/m3, which is specifically formulated to bear structural loads. The core is enveloped with high-strength fiber cement boards, selected for their superior load-bearing capabilities, and enhanced flexural strength when compared to conventional concrete. A thin bed adhesive, known as TPS, is employed to create a robust bond between the RLFC core and the fiber cement cladding. This study underscores the potential of RLFC wall panels as a viable and eco-friendly option for modern building construction, offering a combination of structural efficiency and environmental benefits.

Keywords: structural performance, rubberized concrete wall panel, fiber cement board, insulation performance

Procedia PDF Downloads 63

Authors: Zhaojun Wang, Zongdi Sun, Yongjie Chen, Manman Chen, Linghui Wang

Abstract:

This paper uses the analytic hierarchy process to study the execution effect of the minimum purchase price of grain in different regions and various grain crops. Firstly, for different regions, five indicators including grain yield, grain sown area, gross agricultural production, grain consumption price index, and disposable income of rural residents were selected to construct an evaluation index system. We collect data of six provinces including Hebei Province, Heilongjiang Province and Shandong Province from 2006 to 2017. Then, the judgment matrix is constructed, and the hierarchical single ordering and consistency test are carried out to determine the scoring standard for the minimum purchase price of grain. The ranking of the execution effect from high to low is: Heilongjiang Province, Shandong Province, Hebei Province, Guizhou Province, Shaanxi Province, and Guangdong Province. Secondly, taking Shandong Province as an example, we collect the relevant data of sown area and yield of cereals, beans, potatoes and other crops from 2006 to 2017. The weight of area and yield index is determined by expert scoring method. And the average sown area and yield of cereals, beans and potatoes in 2006-2017 were calculated, respectively. On this basis, according to the sum of products of weights and mean values, the execution effects of different grain crops are determined. It turns out that among the cereals, the minimum purchase price had the best execution effect on paddy, followed by wheat and finally maize. Moreover, among major categories of crops, cereals perform best, followed by beans and finally potatoes. Lastly, countermeasures are proposed for different regions, various categories of crops, and different crops of the same category.

Keywords: analytic hierarchy process, grain yield, grain sown area, minimum grain purchase price

Procedia PDF Downloads 140

Authors: Fuyuan Ma, Yuhan Wang, Junhe Zhang, Ying Wang

Abstract:

Identifying the sources of information dissemination is a pivotal task in the study of collective behaviors in networks, enabling us to discern and intercept the critical pathways through which information propagates from its origins. This allows for the control of the information’s dissemination impact in its early stages. Numerous methods for source detection rely on pre-existing, underlying propagation models as prior knowledge. Current models that eschew prior knowledge attempt to harness label propagation algorithms to model the statistical characteristics of propagation states or employ Graph Neural Networks (GNNs) for deep reverse modeling of the diffusion process. These approaches are either deficient in modeling the propagation patterns of information or are constrained by the over-smoothing problem inherent in GNNs, which limits the stacking of sufficient model depth to excavate global propagation patterns. Consequently, we introduce the ODESI model. Initially, the model employs a label propagation algorithm to delineate the distribution density of infected states within a graph structure and extends the representation of infected states from integers to state vectors, which serve as the initial states of nodes. Subsequently, the model constructs a deep architecture based on GNNs-coupled Ordinary Differential Equations (ODEs) to model the global propagation patterns of continuous propagation processes. Addressing the challenges associated with solving ODEs on graphs, we approximate the analytical solutions to reduce computational costs. Finally, we conduct simulation experiments on two real-world social network datasets, and the results affirm the efficacy of our proposed ODESI model in source identification tasks.

Keywords: source identification, ordinary differential equations, label propagation, complex networks

Procedia PDF Downloads 22

Authors: Ming-Jen Huang, Chun-Fang Huang, Chiching Wei

Abstract:

With the recent advance of the deep neural network, we observe new applications of NLP (natural language processing) and CV (computer vision) powered by deep neural networks for processing business documents. However, creating a real-world document processing system needs to integrate several NLP and CV tasks, rather than treating them separately. There is a need to have a unified approach for processing documents containing textual and graphical elements with rich formats, diverse layout arrangement, and distinct semantics. In this paper, a framework that fulfills this unified approach is presented. The framework includes a representation model definition for holding the information generated by various tasks and specifications defining the coordination between these tasks. The framework is a blueprint for building a system that can process documents with rich formats, styles, and multiple types of elements. The flexible and lightweight design of the framework can help build a system for diverse business scenarios, such as contract monitoring and reviewing.

Keywords: document processing, framework, formal definition, machine learning

Procedia PDF Downloads 219

Authors: Lie-Sian Yap, Ming-Chien Yang

Abstract:

This study demonstrated a novel injectable hydrogel scaffold composing of Pluronic F127, carboxymethyl hexanoyl chitosan (CA) and glutaraldehyde (GA) for encapsulating human fetal osteoblastic cells (hFOB) 1.19. The hydrogel was prepared by mixing F127 and GA in CA solution at 4°C. The mechanical properties and cytotoxicity of this hydrogel were determined through rheological measurements and MTT assay, respectively. After encapsulation process, the hFOB 1.19 cells morphology was examined using fluorescent and confocal imaging. The results indicated that the Tgel of this system was around 30°C, where sol-gel transformation occurred within 90s and F127/CA/GA gel was able to remain intact in the medium for more than 1 month. In vitro cell culture assay revealed that F127/CA/GA hydrogels were non-cytotoxic. Encapsulated hFOB 1.19 cells not only showed the spherical shape and formed colonies, but also reduced their size. Moreover, the hFOB 1.19 cells showed that cells remain alive after the encapsulation process. Based on these results, these F127/CA/GA hydrogels can be used to encapsulate cells for tissue engineering applications.

Keywords: carboxymethyl hexanoyl chitosan, cell encapsulation, hFOB 1.19, Pluronic F127

Procedia PDF Downloads 244

Authors: Xiaoqin Wang, Li Yin

Abstract:

Background and purpose: In many practices, one estimates causal effects arising from a complex stochastic process, where a sequence of treatments are assigned to influence a certain outcome of interest, and there exist time-dependent covariates between treatments. When covariates are plentiful and/or continuous, statistical modeling is needed to reduce the huge dimensionality of the problem and allow for the estimation of causal effects. Recently, Wang and Yin (Annals of statistics, 2020) derived a new general formula, which expresses these causal effects in terms of the point effects of treatments in single-point causal inference. As a result, it is possible to conduct the modeling via point effects. The purpose of the work is to study the modeling of these causal effects via point effects. Challenges and solutions: The time-dependent covariates often have influences from earlier treatments as well as on subsequent treatments. Consequently, the standard parameters – i.e., the mean of the outcome given all treatments and covariates-- are essentially all different (null paradox). Furthermore, the dimension of the parameters is huge (curse of dimensionality). Therefore, it can be difficult to conduct the modeling in terms of standard parameters. Instead of standard parameters, we have use point effects of treatments to develop likelihood-based parametric approach to the modeling of these causal effects and are able to model the causal effects of a sequence of treatments by modeling a small number of point effects of individual treatment Achievements: We are able to conduct the modeling of the causal effects from a sequence of treatments in the familiar framework of single-point causal inference. The simulation shows that our method achieves not only an unbiased estimate for the causal effect but also the nominal level of type I error and a low level of type II error for the hypothesis testing. We have applied this method to a longitudinal study of COVID-19 mortality among Scandinavian countries and found that the Swedish approach performed far worse than the other countries' approach for COVID-19 mortality and the poor performance was largely due to its early measure during the initial period of the pandemic.

Keywords: causal effect, point effect, statistical modelling, sequential causal inference

Procedia PDF Downloads 206

Authors: Shaohua Li, Aihua Zhang, Kelly Zatopek, Saba Parvez, Andrew F. Gardner, Ivan R. Corrêa Jr., Christopher J. Noren, Ming-Qun Xu

Abstract:

Covalent immobilization of enzymes on solid supports is an alternative approach to biocatalysis with the added benefits of simple enzyme removal, improved stability, and adaptability to automation and high-throughput applications. Nevertheless, immobilized enzymes generally suffer from reduced activities compared to their soluble counterparts. One major factor leading to activity loss is the intrinsic hydrophobic property of the supporting material surface, which could result in the conformational change/confinement of enzymes. We report a strategy of utilizing flexible poly (ethylene oxide) (PEO) moieties as to improve the surface hydrophilicity of solid supports used for enzyme immobilization. DNA modifying enzymes were covalently conjugated to PEO-coated magnetic-beads. Kinetics studies proved that the activities of the covalently-immobilized DNA modifying enzymes were greatly enhanced by the PEO modification on the bead surface.

Keywords: immobilized enzymes, biocatalysis, poly(ethylene oxide), surface modification

Procedia PDF Downloads 309

Authors: Y. H. Wu, Ji-Yuan Lin, Yu-Ming Liou

Abstract:

This study aims to set up the landslide susceptibility map of County Route 89 at Ren-Ai Township in Nantou County using the Instability Index Method and Logistic regression. Seven susceptibility factors including Slope Angle, Aspect, Elevation, Distance to fold, Distance to River, Distance to Road and Accumulated Rainfall were obtained by GIS based on the Typhoon Toraji landslide area identified by Industrial Technology Research Institute in 2001. To calculate the landslide percentage of each factor and acquire the weight and grade the grid by means of Instability Index Method. In this study, landslide susceptibility can be classified into four grades: high, medium high, medium low and low, in order to determine the advantages and disadvantages of the two models. The precision of this model is verified by classification error matrix and SRC curve. These results suggest that the logistic regression model is a preferred method than instability index in the assessment of landslide susceptibility. It is suitable for the landslide prediction and precaution in this area in the future.

Keywords: instability index method, logistic regression, landslide susceptibility, SRC curve

Procedia PDF Downloads 292

Authors: Yu-Lin Shen, Ming-Kuen Chang

Abstract:

In addition to a considerable amount of machinery and equipment, intricacies of the transmission pipeline exist in Petrochemical plants. Long term corrosion may lead to pipeline thinning and rupture, causing serious safety concerns. With the advances in non-destructive testing technology, more rapid and long-range ultrasonic detection techniques are often used for pipeline inspection, EMAT without coupling to detect, it is a non-contact ultrasonic, suitable for detecting elevated temperature or roughened e surface of line. In this study, we prepared artificial defects in pipeline for Electromagnetic Acoustic Transducer Testing (EMAT) to survey the relationship between the defect location, sizing and the EMAT signal. It was found that the signal amplitude of EMAT exhibited greater signal attenuation with larger defect depth and length.. In addition, with bigger flat hole diameter, greater amplitude attenuation was obtained. In summary, signal amplitude attenuation of EMAT was affected by the defect depth, defect length and the hole diameter and size.

Keywords: EMAT, artificial defect, NDT, ultrasonic testing

Procedia PDF Downloads 333

Authors: Hong-Ming Chen

Abstract:

This work considers the resolution of the Hull and White interest rate model with the jump process. A deterministic process is adopted to model the random behavior of interest rate variation as deterministic perturbations, which is depending on the time t. The Brownian motion and jumps uncertainty are denoted as the integral functions piecewise constant function w(t) and point function θ(t). It shows that the interest rate function and the yield function of the Hull and White interest rate model with jump process can be obtained by solving a nonlinear semi-infinite programming problem. A relaxed cutting plane algorithm is then proposed for solving the resulting optimization problem. The method is calibrated for the U.S. treasury securities at 3-month data and is used to analyze several effects on interest rate prices, including interest rate variability, and the negative correlation between stock returns and interest rates. The numerical results illustrate that our approach essentially generates the yield functions with minimal fitting errors and small oscillation.

Keywords: optimization, interest rate model, jump process, deterministic

Procedia PDF Downloads 161

Authors: Jefunnie Matahum, Yu-Chi Kuo, Chao-Ming Su, Tzong-Rong Ger

Abstract:

Magnetic cell labeling is of great importance in various applications in biomedical fields such as cell separation and cell sorting. Since analytical methods for quantification of cell uptake of magnetic nanoparticles (MNPs) are already well established, image analysis on single cell level still needs more characterization. This study reports an alternative non-destructive quantification methods of single-cell uptake of positively charged MNPs. Magnetophoresis experiments were performed to calculate the number of MNPs in a single cell. Mobility of magnetic cells and the area of intracellular MNP stained by Prussian blue were quantified by image processing software. ICP-MS experiments were also performed to confirm the internalization of MNPs to cells. Initial results showed that the magnetic cells incubated at 100 µg and 50 µg MNPs/mL concentration move at 18.3 and 16.7 µm/sec, respectively. There is also an increasing trend in the number and area of intracellular MNP with increasing concentration. These results could be useful in assessing the nanoparticle uptake in a single cell level.

Keywords: magnetic nanoparticles, single cell, magnetophoresis, image analysis

Procedia PDF Downloads 333

Authors: Wang Xiaoqing, Fang Youyuan, Zheng Yanxing, Gu Tianyang, Zong Jianjian, Tong Jinrong

Abstract:

Compared with traditional distributed environment, the net-centric environment brings on more demanding challenges for information sharing with the characteristics of ultra-large scale and strong distribution, dynamic, autonomy, heterogeneity, redundancy. This paper realizes an information sharing model and a series of core services, through which provides an open, flexible and scalable information sharing platform.

Keywords: net-centric environment, information sharing, metadata registry and catalog, cross-domain data access control

Procedia PDF Downloads 571

Authors: Yaxuan Wang

Abstract:

It has long been a mystery that why the Mongolian possessive suffix, which is constrained by Condition A of binding theory, has the ability to probe a potential antecedent outside of its binding domain. This squib argues that binding theory alone is not sufficient to explain the linguistic facts and proposes an analysis adopting the Agree operation. The current analysis correctly predicts all the possible and impossible structures, with an additional hypothesis that Mongolian possessive suffixes serve as an antecedent for PROs in adjunct. The findings thus provide insights into how Agree operates in Mongolian language.

Keywords: syntax, Mongolian, agreement, possessive particles

Procedia PDF Downloads 101

Authors: Long Long Chen, Xinwei Liao, Shanfa Tang, Shaojing Jiang, Ruijia Tang, Rui Wang, Shu Yun Feng, Si Yao Wang

Abstract:

Unconventional oil reservoirs have the characteristics of strong heterogeneity and poor injectability, and traditional chemical flooding technology is not effective in such reservoirs; polymer flooding in the production of heavy oil reservoirs is difficult to handle produced fluid and easy to block oil wells, etc. Therefore, a viscoelastic fluid flooding system with good adaptability, low interfacial tension, plugging, and diverting capabilities was studied. The viscosity, viscoelasticity, surface/interfacial activity, wettability, emulsification, and oil displacement performance of the anionic Gemini surfactant flooding system were studied, and the adaptability of the system to the reservoir environment was evaluated. The oil displacement effect of the system in low-permeability and high-permeability (heavy oil) reservoirs was investigated, and the mechanism of the system to enhance water flooding recovery was discussed. The results show that the system has temperature resistance and viscosity increasing performance (65℃, 4.12mPa•s), shear resistance and viscoelasticity; at a lower concentration (0.5%), the oil-water interfacial tension can be reduced to ultra-low (10-3mN/m); has good emulsifying ability for heavy oil, and is easy to break demulsification (4.5min); has good adaptability to reservoirs with high salinity (30000mg/L). Oil flooding experiments show that this system can increase the water flooding recovery rate of low-permeability homogeneous and heterogeneous cores by 13% and 15%, respectively, and can increase the water-flooding recovery rate of high-permeability heavy oil reservoirs by 40%. The anionic Gemini surfactant flooding system studied in this paper is a viscoelastic fluid, has good emulsifying and oil washing ability, can effectively improve sweep efficiency, reduce injection pressure, and has broad application in unconventional reservoirs to enhance oil recovery prospect.

Keywords: oil displacement system, recovery factor, rheology, interfacial activity, environmental adaptability

Procedia PDF Downloads 125

Authors: Yu Zhao, Min Zhang, Yuanqian Wang, Qiuyu Yu

Abstract:

The prediction of aesthetics of apparel is helpful for the development of a new type of apparel. This study is to build the quantitative relationship between the aesthetics and its design parameters. In particular, women’s pants have been preliminarily studied. This aforementioned relationship has been carried out by statistical analysis. The contributions of this study include the development of a more personalized apparel design mechanism and the provision of some empirical knowledge for the development of other products in the aspect of aesthetics.

Keywords: aesthetics, crease line, cropped straight leg pants, knee width

Procedia PDF Downloads 186

Authors: Ji-Yuan Lin, Yu-Ming Liou, Yi-Ting Chen, Chen-Syuan Lin

Abstract:

Soil water index obtained by tank model is now commonly used in soil and sand disaster alarm system in Japan. Comparing with the rainfall trigging index in Taiwan, the tank model is easy to predict the slope water content on large-scale landslide. Therefore, this study aims to estimate the threshold value of large-scale landslide using the soil water index Sixteen typhoons and heavy rainfall events, were selected to establish the, to relationship between landslide event and soil water index. Finally, the proposed threshold values for landslides on country road No.89 are suggested in this study. The study results show that 95% landslide cases occurred in soil water index more than 125mm, and 30% of the more serious slope failure occurred in the soil water index is greater than 250mm. Beside, this study speculates when soil water index more than 250mm and the difference value between second tank and third tank less than -25mm, it leads to large-scale landslide more probably.

Keywords: soil water index, tank model, landslide, threshold values

Procedia PDF Downloads 387

Authors: Shu-Min Tsao, Chung-Ming Lo, Shao-Chun Chen

Abstract:

Most diabetes patients tend to suffer from its complication of retina diseases. Therefore, early detection and early treatment are important. In clinical examinations, using color fundus image was the most convenient and available examination method. According to the exudates appeared in the retinal image, the status of retina can be confirmed. However, the routine screening of diabetic retinopathy by color fundus images would bring time-consuming tasks to physicians. This study thus proposed a computer-aided exudate diagnosis for the screening of diabetic retinopathy. After removing vessels and optic disc in the retinal image, six quantitative features including region number, region area, and gray-scale values etc… were extracted from the remaining regions for classification. As results, all six features were evaluated to be statistically significant (p-value < 0.001). The accuracy of classifying the retinal images into normal and diabetic retinopathy achieved 82%. Based on this system, the clinical workload could be reduced. The examination procedure may also be improved to be more efficient.

Keywords: computer-aided diagnosis, diabetic retinopathy, exudate, image processing

Procedia PDF Downloads 274

Authors: Yu-Lin Shen, Ming-Kuen Chang

Abstract:

In addition to a considerable amount of machinery and equipment, intricacies of the transmission pipeline exist in Petrochemical plants. Long term corrosion may lead to pipeline thinning and rupture, causing serious safety concerns. With the advances in non-destructive testing technology, more rapid and long-range ultrasonic detection techniques are often used for pipeline inspection, EMAT without coupling to detect, it is a non-contact ultrasonic, suitable for detecting elevated temperature or roughened e surface of line. In this study, we prepared artificial defects in pipeline for Electromagnetic Acoustic Transducer testing (EMAT) to survey the relationship between the defect location, sizing and the EMAT signal. It was found that the signal amplitude of EMAT exhibited greater signal attenuation with larger defect depth and length. In addition, with bigger flat hole diameter, greater amplitude attenuation was obtained. In summary, signal amplitude attenuation of EMAT was affected by the defect depth, defect length and the hole diameter and size.

Keywords: EMAT, artificial defect, NDT, ultrasonic testing

Procedia PDF Downloads 350

Authors: Xiao-Li Liu, Ling-Yun Zhao, Xing-Jie Liang, Hai-Ming Fan

Abstract:

Owing to their unique properties, magnetic nanoparticles have been used as diagnostic and therapeutic agents for biomedical applications. Highly monodispersed magnetic nanoparticles with controlled particle size and surface coating have been successfully synthesized as a model system to investigate the effect of surface coating on the T2 relaxivity and specific absorption rate (SAR) under an alternating magnetic field, respectively. Amongst, by using mPEG-g-PEI to solubilize oleic-acid capped 6 nm magnetic nanoparticles, the T2 relaxivity could be significantly increased by up to 4-fold as compared to PEG coated nanoparticles. Moreover, it largely enhances the cell uptake with a T2 relaxivity of 92.6 mM-1s-1 for in vitro cell MRI. As for hyperthermia agent, SAR value increase with the decreased thickness of PEG surface coating. By elaborate optimization of surface coating and particle size, a significant increase of SAR (up to 74%) could be achieved with a minimal variation on the saturation magnetization (<5%). The 19 nm magnetic nanoparticles with 2000 Da PEG exhibited the highest SAR of 930 W•g-1 among the samples, which can be maintained in various simulated physiological conditions. This systematic work provides a general strategy for the optimization of surface coating of magnetic core for high performance MRI contrast agent and hyperthermia agent.

Keywords: magnetic nanoparticles, magnetic hyperthermia, magnetic resonance imaging, surface modification

Procedia PDF Downloads 510

Authors: Ming-Yue Zhai

Abstract:

Due to the multipath and pulse noise nature, power line communications(PLC) channel can be modelled as a memory one with the finite states Markov model(FSMC). As the most important parameter modelling a Markov channel,the memory order in an FSMC is not solved in PLC systems yet. In the paper, the mutual information is used as a measure of the dependence between the different symbols, treated as the received SNA or amplitude of the current channel symbol or that of previous symbols. The joint distribution probabilities of the envelopes in PLC systems are computed based on the multi-path channel model, which is commonly used in PLC. we confirm that given the information of the symbol immediately preceding the current one, any other previous symbol is independent of the current one in PLC systems, which means the PLC channels is a Markov chain with the first-order. The field test is also performed to model the received OFDM signals with the help of AR model. The results show that the first-order AR model is enough to model the fading channel in PLC systems, which means the amount of uncertainty remaining in the current symbol should be negligible, given the information corresponding to the immediately preceding one.

Keywords: power line communication, channel model, markovian, information theory, first-order

Procedia PDF Downloads 414

Authors: Sujing Wang, Song Wang, Jian Zhang, Qiang Xu

Abstract:

Flaring emissions during abnormal operating conditions such as plant start-ups, shut-downs, and upsets in chemical process industries (CPI) are usually significant. Flare minimization can help to save raw material and energy for CPI plants, and to improve local environmental sustainability. In this paper, a systematic methodology based on plant-wide dynamic simulation is presented for CPI plant flare minimizations under abnormal operating conditions. Since off-specification emission sources are inevitable during abnormal operating conditions, to significantly reduce flaring emission in a CPI plant, they must be either recycled to the upstream process for online reuse, or stored somewhere temporarily for future reprocessing, when the CPI plant manufacturing returns to stable operation. Thus, the off-spec products could be reused instead of being flared. This can be achieved through the identification of viable design and operational strategies during normal and abnormal operations through plant-wide dynamic scheduling, simulation, and optimization. The proposed study includes three stages of simulation works: (i) developing and validating a steady-state model of a CPI plant; (ii) transiting the obtained steady-state plant model to the dynamic modeling environment; and refining and validating the plant dynamic model; and (iii) developing flare minimization strategies for abnormal operating conditions of a CPI plant via a validated plant-wide dynamic model. This cost-effective methodology has two main merits: (i) employing large-scale dynamic modeling and simulations for industrial flare minimization, which involves various unit models for modeling hundreds of CPI plant facilities; (ii) dealing with critical abnormal operating conditions of CPI plants such as plant start-up and shut-down. Two virtual case studies on flare minimizations for start-up operation (over 50% of emission savings) and shut-down operation (over 70% of emission savings) of an ethylene plant have been employed to demonstrate the efficacy of the proposed study.

Keywords: flare minimization, large-scale modeling and simulation, plant shut-down, plant start-up

Procedia PDF Downloads 322