Search results for: Jian Guo Zhou
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 397

Search results for: Jian Guo Zhou

367 Effects of the SNPS on rs855791 and rs3811647 on the Levels of SF and sTFR in the Group of 8-14

Authors: Piao Wei, Sun Jing, Huang Jian, Wang Lijuan, Tang Yanbin, Li Jin, Huo Junsheng

Abstract:

Objective: To investigate effects on the levels of SF and sTfR by the SNPs of rs855791on TMPRSS6 and rs3811647 on TF in adolescent. Methods: DNA was extracted from venous blood which were drawn from 50 subjects, and then the two SNPs of each sample were identified by Sequenom MassArray. T test and chi-square test were selected to identify the relationship between the levels of SF and sTfR in each allele carriers, and then the effects of each SNP on the levels of SF and sTfR would be assessed. Results: The level of SF of A allele carriers on rs855791 (54±28.2 ng/ml) was higher than GG carriers (33.1±20.2 ng/ml) (P<0.05), and the discrimination of the level of sTfR between each allele carrier was not observed (P>0.05); the discriminations of the different levels of SF and sTfR among each SNP on rs3811647 were not observed (P>0.05). Conclusions: The level of SF may be affected by the SNP of rs855791on TMPRSS6, and the effect of rs3811647 on TF may be weakened by the former one.

Keywords: SNP, SF, sTfR, adolescent

Procedia PDF Downloads 540
366 Prediction of Coronary Artery Stenosis Severity Based on Machine Learning Algorithms

Authors: Yu-Jia Jian, Emily Chia-Yu Su, Hui-Ling Hsu, Jian-Jhih Chen

Abstract:

Coronary artery is the major supplier of myocardial blood flow. When fat and cholesterol are deposit in the coronary arterial wall, narrowing and stenosis of the artery occurs, which may lead to myocardial ischemia and eventually infarction. According to the World Health Organization (WHO), estimated 740 million people have died of coronary heart disease in 2015. According to Statistics from Ministry of Health and Welfare in Taiwan, heart disease (except for hypertensive diseases) ranked the second among the top 10 causes of death from 2013 to 2016, and it still shows a growing trend. According to American Heart Association (AHA), the risk factors for coronary heart disease including: age (> 65 years), sex (men to women with 2:1 ratio), obesity, diabetes, hypertension, hyperlipidemia, smoking, family history, lack of exercise and more. We have collected a dataset of 421 patients from a hospital located in northern Taiwan who received coronary computed tomography (CT) angiography. There were 300 males (71.26%) and 121 females (28.74%), with age ranging from 24 to 92 years, and a mean age of 56.3 years. Prior to coronary CT angiography, basic data of the patients, including age, gender, obesity index (BMI), diastolic blood pressure, systolic blood pressure, diabetes, hypertension, hyperlipidemia, smoking, family history of coronary heart disease and exercise habits, were collected and used as input variables. The output variable of the prediction module is the degree of coronary artery stenosis. The output variable of the prediction module is the narrow constriction of the coronary artery. In this study, the dataset was randomly divided into 80% as training set and 20% as test set. Four machine learning algorithms, including logistic regression, stepwise regression, neural network and decision tree, were incorporated to generate prediction results. We used area under curve (AUC) / accuracy (Acc.) to compare the four models, the best model is neural network, followed by stepwise logistic regression, decision tree, and logistic regression, with 0.68 / 79 %, 0.68 / 74%, 0.65 / 78%, and 0.65 / 74%, respectively. Sensitivity of neural network was 27.3%, specificity was 90.8%, stepwise Logistic regression sensitivity was 18.2%, specificity was 92.3%, decision tree sensitivity was 13.6%, specificity was 100%, logistic regression sensitivity was 27.3%, specificity 89.2%. From the result of this study, we hope to improve the accuracy by improving the module parameters or other methods in the future and we hope to solve the problem of low sensitivity by adjusting the imbalanced proportion of positive and negative data.

Keywords: decision support, computed tomography, coronary artery, machine learning

Procedia PDF Downloads 205
365 Rural Landscape Design-Method Researching Based on the Population Diversification

Authors: Zhou Ziyi, Chen Qiuxiao, Wu Shuang

Abstract:

Population diversification is very common in villages located in the developed coastal areas of China. Based on the analyses of the characteristics of the traditional rural society and its landscape, also in consideration of the diversified landscape demand due to the population diversification of the village, with the dual ideas of heritage and innovation, the ideas and methods of rural landscape design were explored by taking Duxuao Village in Zhejiang Province of China as an example.

Keywords: rural landscape, population diversification, landscape design, architecture

Procedia PDF Downloads 582
364 Characteristics of Different Solar PV Modules under Partial Shading

Authors: Hla Hla Khaing, Yit Jian Liang, Nant Nyein Moe Htay, Jiang Fan

Abstract:

Partial shadowing is one of the problems that are always faced in terrestrial applications of solar photovoltaic (PV). The effects of partial shadow on the energy yield of conventional mono-crystalline and multi-crystalline PV modules have been researched for a long time. With deployment of new thin-film solar PV modules in the market, it is important to understand the performance of new PV modules operating under the partial shadow in the tropical zone. This paper addresses the impacts of different partial shadowing on the operating characteristics of four different types of solar PV modules that include multi-crystalline, amorphous thin-film, CdTe thin-film and CIGS thin-film PV modules.

Keywords: partial shade, CdTe, CIGS, multi-crystalline (mc-Si), amorphous silicon (a-Si), bypass diode

Procedia PDF Downloads 417
363 Grid Tied Photovoltaic Power on School Roof

Authors: Yeong-cheng Wang, Jin-Yinn Wang, Ming-Shan Lin, Jian-Li Dong

Abstract:

To universalize the adoption of sustainable energy, the R.O.C. government encourages public buildings to introduce the PV power station on the building roof, whereas most old buildings did not include the considerations of photovoltaic (PV) power facilities in the design phase. Several factors affect the PV electricity output, the temperature is the key one, different PV technologies have different temperature coefficients. Other factors like PV panel azimuth, panel inclination from the horizontal plane, and row to row distance of PV arrays, mix up at the beginning of system design. The goal of this work is to maximize the annual energy output of a roof mount PV system. Tables to simplify the design work are developed; the results can be used for engineering project quote directly.

Keywords: optimal inclination, array azimuth, annual output

Procedia PDF Downloads 645
362 Microjetting from a Grooved Metal Surface under Decaying Shocks

Authors: Jian-Li Shao

Abstract:

Using Molecular Dynamic (MD) simulations, we simulated the microjet from the metal surface under decaying shock loading. The microjetting processes under release melting conditions are presented in detail, and some properties on the microjet mass and velocity are revealed. The phased increase of microjet mass with shock pressure is found. For all cases, the ratio of the maximal jetting velocity to the surface velocity approximately keeps a constant for liquid state. In addition, the temperature of the microjet can be always above the melting point. When introducing slow decaying profiles, the microjet mass begins to increase with the decay rate, which is dominated by the deformation of the bubble during pull-back. When the decay rate becomes fast enough, the microspall occurs as expected, meanwhile, the microjet appears to reduce because of the shock energy reduction.

Keywords: microjetting, shock, metal, molecular dynamics

Procedia PDF Downloads 167
361 Method of Visual Prosthesis Design Based on Biologically Inspired Design

Authors: Shen Jian, Hu Jie, Zhu Guo Niu, Peng Ying Hong

Abstract:

There are two issues exited in the traditional visual prosthesis: lacking systematic method and the low level of humanization. To tackcle those obstacles, a visual prosthesis design method based on biologically inspired design is proposed. Firstly, a constrained FBS knowledge cell model is applied to construct the functional model of visual prosthesis in biological field. Then the clustering results of engineering domain are ob-tained with the use of the cross-domain knowledge cell clustering algorithm. Finally, a prototype system is designed to support the bio-logically inspired design where the conflict is digested by TRIZ and other tools, and the validity of the method is verified by the solution scheme

Keywords: knowledge-based engineering, visual prosthesis, biologically inspired design, biomedical engineering

Procedia PDF Downloads 162
360 Microstructures of Si Surfaces Fabricated by Electrochemical Anodic Oxidation with Agarose Stamps

Authors: Hang Zhou, Limin Zhu

Abstract:

This paper investigates the fabrication of microstructures on Si surfaces by using electrochemical anodic oxidation with agarose stamps. The fabricating process is based on a selective anodic oxidation reaction that occurs in the contact area between a stamp and a Si substrate. The stamp which is soaked in electrolyte previously acts as a current flow channel. After forming the oxide patterns as an etching mask, a KOH aqueous is used for the wet etching of Si. A complicated microstructure array of 1 cm2 was fabricated by the method with high accuracy.

Keywords: microstructures, anodic oxidation, silicon, agarose stamps

Procedia PDF Downloads 274
359 Model Averaging for Poisson Regression

Authors: Zhou Jianhong

Abstract:

Model averaging is a desirable approach to deal with model uncertainty, which, however, has rarely been explored for Poisson regression. In this paper, we propose a model averaging procedure based on an unbiased estimator of the expected Kullback-Leibler distance for the Poisson regression. Simulation study shows that the proposed model average estimator outperforms some other commonly used model selection and model average estimators in some situations. Our proposed methods are further applied to a real data example and the advantage of this method is demonstrated again.

Keywords: model averaging, poission regression, Kullback-Leibler distance, statistics

Procedia PDF Downloads 491
358 Asymptotic Expansion of the Korteweg-de Vries-Burgers Equation

Authors: Jian-Jun Shu

Abstract:

It is common knowledge that many physical problems (such as non-linear shallow-water waves and wave motion in plasmas) can be described by the Korteweg-de Vries (KdV) equation, which possesses certain special solutions, known as solitary waves or solitons. As a marriage of the KdV equation and the classical Burgers (KdVB) equation, the Korteweg-de Vries-Burgers (KdVB) equation is a mathematical model of waves on shallow water surfaces in the presence of viscous dissipation. Asymptotic analysis is a method of describing limiting behavior and is a key tool for exploring the differential equations which arise in the mathematical modeling of real-world phenomena. By using variable transformations, the asymptotic expansion of the KdVB equation is presented in this paper. The asymptotic expansion may provide a good gauge on the validation of the corresponding numerical scheme.

Keywords: asymptotic expansion, differential equation, Korteweg-de Vries-Burgers (KdVB) equation, soliton

Procedia PDF Downloads 224
357 The Preparation of High Surface Area Ni/MgAl2O4 Catalysts for Syngas Methanation

Authors: Jingyu Zhou, Hongfang Ma, Haitao Zhang, Weiyong Ying

Abstract:

High surface area MgAl2O4 supported Nickel catalysts with PVA loadings varying from 0% to 15% were prepared by precipitation and impregnation method. The catalysts were characterized by low temperature N2 adsorption/desorption, X-ray diffraction and H2 temperature programmed reduction. Compared with Ni/γ-Al2O3 catalyst, Ni/MgAl2O4 catalysts exhibited higher activity and selectivity in high temperature. Among the catalysts, Ni/MgAl2O4-5P with 5 wt% PVA showed the best performance, and achieved 95% CO conversion and 96% CH4 selectivity at 600°C, 2.0 MPa, and a WHSV of 12,000 mL·g⁻¹.h⁻¹. It also maintained good stability in 50h life test.

Keywords: methanation, MgAl2O4 support, PVA, high surface area

Procedia PDF Downloads 301
356 Study on Roll Marks of Stainless Steel in Rolling Mill

Authors: Cai-Wan Chang-Jian, Han-Ting Tsai

Abstract:

In the processing industry of metal forming, rolling is the most used method of processing. In a cold rolling factory of stainless steel, there occurs a product defect on temper rolling process within cold rolling. It is called 'roll marks', which is a phenomenon of undesirable flatness problem. In this research, we performed a series of experimental measurements on the roll marks, and we used optical sensors to measure it and compared the vibration frequency of roll marks with the vibration frequency of key components in the skin pass mill. We found there is less correlation between the above mentioned data. Finally, we took measurement on the motor driver in rolling mill. We found that the undulation frequency of motor could match with the frequency of roll marks, and then we have confirmed that the motor’s undulation caused roll marks.

Keywords: roll mark, plane strain, rolling mill, stainless steel

Procedia PDF Downloads 433
355 Method of Cluster Based Cross-Domain Knowledge Acquisition for Biologically Inspired Design

Authors: Shen Jian, Hu Jie, Ma Jin, Peng Ying Hong, Fang Yi, Liu Wen Hai

Abstract:

Biologically inspired design inspires inventions and new technologies in the field of engineering by mimicking functions, principles, and structures in the biological domain. To deal with the obstacles of cross-domain knowledge acquisition in the existing biologically inspired design process, functional semantic clustering based on functional feature semantic correlation and environmental constraint clustering composition based on environmental characteristic constraining adaptability are proposed. A knowledge cell clustering algorithm and the corresponding prototype system is developed. Finally, the effectiveness of the method is verified by the visual prosthetic device design.

Keywords: knowledge clustering, knowledge acquisition, knowledge based engineering, knowledge cell, biologically inspired design

Procedia PDF Downloads 406
354 Solar Light-Driving Photoconversion of CO₂ Into Renewable Hydrocarbon Fuels

Authors: Yong Zhou, Congping Wu, Zhigang Zou

Abstract:

With the rapid societal development, energy demand has increased exponentially and is mainly based on traditional and nonrenewable energy resources, such as petroleum, fossil fuels, and coal. The combustion of carbon-containing fuels releases a large amount of CO₂, causing the greenhouse effect that contribute to climate change. Photocatalytic CO₂ reduction into solar fuels is a promising approach to simultaneously alleviate current energy and environmental issues. In this study, we report the synthesis of a series of atomically ultrathin 2D structures, which contain an ultrahigh fraction of surface atoms, benefitting for efficiency and selectivity regulation of the target products toward CO₂ photoconversion.

Keywords: Photocatalysis, CO₂, Solar fuels, Nanostructure

Procedia PDF Downloads 34
353 Fat-Tail Test of Regulatory DNA Sequences

Authors: Jian-Jun Shu

Abstract:

The statistical properties of CRMs are explored by estimating similar-word set occurrence distribution. It is observed that CRMs tend to have a fat-tail distribution for similar-word set occurrence. Thus, the fat-tail test with two fatness coefficients is proposed to distinguish CRMs from non-CRMs, especially from exons. For the first fatness coefficient, the separation accuracy between CRMs and exons is increased as compared with the existing content-based CRM prediction method – fluffy-tail test. For the second fatness coefficient, the computing time is reduced as compared with fluffy-tail test, making it very suitable for long sequences and large data-base analysis in the post-genome time. Moreover, these indexes may be used to predict the CRMs which have not yet been observed experimentally. This can serve as a valuable filtering process for experiment.

Keywords: statistical approach, transcription factor binding sites, cis-regulatory modules, DNA sequences

Procedia PDF Downloads 267
352 A Method of the Semantic on Image Auto-Annotation

Authors: Lin Huo, Xianwei Liu, Jingxiong Zhou

Abstract:

Recently, due to the existence of semantic gap between image visual features and human concepts, the semantic of image auto-annotation has become an important topic. Firstly, by extract low-level visual features of the image, and the corresponding Hash method, mapping the feature into the corresponding Hash coding, eventually, transformed that into a group of binary string and store it, image auto-annotation by search is a popular method, we can use it to design and implement a method of image semantic auto-annotation. Finally, Through the test based on the Corel image set, and the results show that, this method is effective.

Keywords: image auto-annotation, color correlograms, Hash code, image retrieval

Procedia PDF Downloads 464
351 Cars Redistribution Optimization Problem in the Free-Float Car-Sharing

Authors: Amine Ait-Ouahmed, Didier Josselin, Fen Zhou

Abstract:

Free-Float car-sharing is an one-way car-sharing service where cars are available anytime and anywhere in the streets such that no dedicated stations are needed. This means that after driving a car you can park it anywhere. This car-sharing system creates an imbalance car distribution in the cites which can be regulated by staff agents through the redistribution of cars. In this paper, we aim to solve the car-reservation and agents traveling problem so that the number of successful cars’ reservations could be maximized. Beside, we also tend to minimize the distance traveled by agents for cars redistribution. To this end, we present a mixed integer linear programming formulation for the car-sharing problem.

Keywords: one-way car-sharing, vehicle redistribution, car reservation, linear programming

Procedia PDF Downloads 319
350 Trace Network: A Probabilistic Relevant Pattern Recognition Approach to Attribution Trace Analysis

Authors: Jian Xu, Xiaochun Yun, Yongzheng Zhang, Yafei Sang, Zhenyu Cheng

Abstract:

Network attack prevention is a critical research area of information security. Network attack would be oppressed if attribution techniques are capable to trace back to the attackers after the hacking event. Therefore attributing these attacks to a particular identification becomes one of the important tasks when analysts attempt to differentiate and profile the attacker behind a piece of attack trace. To assist analysts in expose attackers behind the scenes, this paper researches on the connections between attribution traces and proposes probabilistic relevance based attribution patterns. This method facilitates the evaluation of the plausibility relevance between different traceable identifications. Furthermore, through analyzing the connections among traces, it could confirm the existence probability of a certain organization as well as discover its affinitive partners by the means of drawing relevance matrix from attribution traces.

Keywords: attribution trace, probabilistic relevance, network attack, attacker identification

Procedia PDF Downloads 334
349 A Semiparametric Approach to Estimate the Mode of Continuous Multivariate Data

Authors: Tiee-Jian Wu, Chih-Yuan Hsu

Abstract:

Mode estimation is an important task, because it has applications to data from a wide variety of sources. We propose a semi-parametric approach to estimate the mode of an unknown continuous multivariate density function. Our approach is based on a weighted average of a parametric density estimate using the Box-Cox transform and a non-parametric kernel density estimate. Our semi-parametric mode estimate improves both the parametric- and non-parametric- mode estimates. Specifically, our mode estimate solves the non-consistency problem of parametric mode estimates (at large sample sizes) and reduces the variability of non-parametric mode estimates (at small sample sizes). The performance of our method at practical sample sizes is demonstrated by simulation examples and two real examples from the fields of climatology and image recognition.

Keywords: Box-Cox transform, density estimation, mode seeking, semiparametric method

Procedia PDF Downloads 256
348 The Gap of Green Consumption Behavior: Driving from Attitude to Behavior

Authors: Yu Du, Jian-Guo Wang

Abstract:

Green consumption is a key link to develop the ecological economy, and consumers are vital to carry out green consumption. With environmental awareness gradually being aroused, consumers often fail to turn their positive attitude into actual green consumption behavior. According to behavior reasoning theory, reasons for adoption have a direct (positive) influence on consumers’ attitude while reasons against adoption have a direct (negative) influence on consumers’ adoption intentions, the incongruous coexistence of which leads to the attitude-behavior gap of green consumption. Based on behavior reasoning theory, this research integrates reasons for adoption and reasons against adoption into a proposed model, in which reasons both for and against green consumption mediate the relationship between consumer’ values, attitudes, and behavioral intentions. It not only extends the conventional theory of reasoned action but also provides a reference for the government and enterprises to design the repairing strategy of green consumption attitude-behavior gap.

Keywords: green product, attitude-behavior gap, behavior reasoning theory, green consumption, SEM

Procedia PDF Downloads 417
347 The Acquisition of Case in Biological Domain Based on Text Mining

Authors: Shen Jian, Hu Jie, Qi Jin, Liu Wei Jie, Chen Ji Yi, Peng Ying Hong

Abstract:

In order to settle the problem of acquiring case in biological related to design problems, a biometrics instance acquisition method based on text mining is presented. Through the construction of corpus text vector space and knowledge mining, the feature selection, similarity measure and case retrieval method of text in the field of biology are studied. First, we establish a vector space model of the corpus in the biological field and complete the preprocessing steps. Then, the corpus is retrieved by using the vector space model combined with the functional keywords to obtain the biological domain examples related to the design problems. Finally, we verify the validity of this method by taking the example of text.

Keywords: text mining, vector space model, feature selection, biologically inspired design

Procedia PDF Downloads 230
346 Evaluation of Turbulence Modelling of Gas-Liquid Two-Phase Flow in a Venturi

Authors: Mengke Zhan, Cheng-Gang Xie, Jian-Jun Shu

Abstract:

A venturi flowmeter is a common device used in multiphase flow rate measurement in the upstream oil and gas industry. Having a robust computational model for multiphase flow in a venturi is desirable for understanding the gas-liquid and fluid-pipe interactions and predicting pressure and phase distributions under various flow conditions. A steady Eulerian-Eulerian framework is used to simulate upward gas-liquid flow in a vertical venturi. The simulation results are compared with experimental measurements of venturi differential pressure and chord-averaged gas holdup in the venturi throat section. The choice of turbulence model is nontrivial in the multiphase flow modelling in a venturi. The performance cross-comparison of the k-ϵ model, Reynolds stress model (RSM) and shear-stress transport (SST) k-ω turbulence model is made in the study. In terms of accuracy and computational cost, the SST k-ω turbulence model is observed to be the most efficient.

Keywords: computational fluid dynamics (CFD), gas-liquid flow, turbulence modelling, venturi

Procedia PDF Downloads 147
345 SiC Particulate-Reinforced SiC Composites Fabricated by PIP Method Using Highly Concentrated SiC Slurry

Authors: Jian Gu, Sea-Hoon Lee, Jun-Seop Kim

Abstract:

SiC particulate-reinforced SiC ceramic composites (SiCp/SiC) were successfully fabricated using polymer impregnation and pyrolysis (PIP) method. The effects of green density, infiltrated method, pyrolytic temperature, and heating rate on the densification behavior of the composites were investigated. SiCp/SiC particulate reinforced composites with high relative density up to 88.06% were fabricated after 4 PIP cycles using SiC pellets with high green density. The pellets were prepared by drying 62-70 vol.% aqueous SiC slurries, and the maximum relative density of the pellets was 75.5%. The hardness of the as-fabricated SiCp/SiCs was 21.05 GPa after 4 PIP cycles, which value increased to 23.99 GPa after a heat treatment at 2000℃. Excellent mechanical properties, thermal stability, and short processing time render the SiCp/SiC composite as a challenging candidate for the high-temperature application.

Keywords: high green density, mechanical property, polymer impregnation and pyrolysis, structural application

Procedia PDF Downloads 114
344 Statistical Analysis of Cables in Long-Span Cable-Stayed Bridges

Authors: Ceshi Sun, Yueyu Zhao, Yaobing Zhao, Zhiqiang Wang, Jian Peng, Pengxin Guo

Abstract:

With the rapid development of transportation, there are more than 100 cable-stayed bridges with main span larger than 300 m in China. In order to ascertain the statistical relationships among the design parameters of stay cables and their distribution characteristics, 1500 cables were selected from 25 practical long-span cable-stayed bridges. A new relationship between the first order frequency and the length of cable was found by conducting the curve fitting. Then, based on this relationship other interesting relationships were deduced. Several probability density functions (PDFs) were used to investigate the distributions of the parameters of first order frequency, stress level and the Irvine parameter. It was found that these parameters obey the Lognormal distribution, the Weibull distribution and the generalized Pareto distribution, respectively. Scatter diagrams of the three parameters were plotted and their 95% confidence intervals were also investigated.

Keywords: cable, cable-stayed bridge, long-span, statistical analysis

Procedia PDF Downloads 599
343 Effect of the Support Shape on Fischer-Tropsch Cobalt Catalyst Performance

Authors: Jian Huang, Weixin Qian, Hongfang Ma, Haitao Zhang, Weiyong Ying

Abstract:

Cobalt catalysts were supported on extruded silica carrier and different-type (SiO2, γ-Al2O3) commercial supports with different shapes and sizes to produce heavy hydrocarbons for Fischer-Tropsch synthesis. The catalysts were characterized by N2 physisorption and H2-TPR. The catalytic performance of the catalysts was tested in a fixed bed reactor. The results of Fischer-Tropsch synthesis performance showed that the cobalt catalyst supported on spherical silica supports displayed a higher activity and a higher selectivity to C5+ products, due to the fact that the active components were only distributed in the surface layer of spherical carrier, and the influence of gas diffusion restriction on catalytic performance was weakened. Therefore, it can be concluded that the eggshell cobalt catalyst was superior to precious metals modified catalysts in the synthesis of heavy hydrocarbons.

Keywords: fischer-tropsch synthesis, cobalt catalyst, support shape, heavy hydrocarbons

Procedia PDF Downloads 255
342 Reliable Soup: Reliable-Driven Model Weight Fusion on Ultrasound Imaging Classification

Authors: Shuge Lei, Haonan Hu, Dasheng Sun, Huabin Zhang, Kehong Yuan, Jian Dai, Yan Tong

Abstract:

It remains challenging to measure reliability from classification results from different machine learning models. This paper proposes a reliable soup optimization algorithm based on the model weight fusion algorithm Model Soup, aiming to improve reliability by using dual-channel reliability as the objective function to fuse a series of weights in the breast ultrasound classification models. Experimental results on breast ultrasound clinical datasets demonstrate that reliable soup significantly enhances the reliability of breast ultrasound image classification tasks. The effectiveness of the proposed approach was verified via multicenter trials. The results from five centers indicate that the reliability optimization algorithm can enhance the reliability of the breast ultrasound image classification model and exhibit low multicenter correlation.

Keywords: breast ultrasound image classification, feature attribution, reliability assessment, reliability optimization

Procedia PDF Downloads 53
341 The Catalytic Properties of PtSn/Al2O3 for Acetic Acid Hydrogenation

Authors: Mingchuan Zhou, Haitao Zhang, Hongfang Ma, Weiyong Ying

Abstract:

Alumina supported platinum and tin catalysts with different loadings of Pt and Sn were prepared and characterized by low temperature N2 adsorption/desorption, H2-temperature programed reduction and CO pulse chemisorption. Pt and Sn below 1% loading were suitable for acetic acid hydrogenation. The best performance over 0.75Pt1Sn/Al2O3 can reach 87.55% conversion of acetic acid and 47.39% selectivity of ethanol. The operating conditions of acetic acid hydrogenation over 1Pt1Sn/Al2O3 were investigated. High reaction temperature can enhance the conversion of acetic acid, but it decreased total selectivity of ethanol and acetyl acetate. High pressure and low weight hourly space velocity were beneficial to both conversion of acetic acid and selectivity to ethanol.

Keywords: acetic acid, hydrogenation, operating condition, PtSn

Procedia PDF Downloads 328
340 Face Tracking and Recognition Using Deep Learning Approach

Authors: Degale Desta, Cheng Jian

Abstract:

The most important factor in identifying a person is their face. Even identical twins have their own distinct faces. As a result, identification and face recognition are needed to tell one person from another. A face recognition system is a verification tool used to establish a person's identity using biometrics. Nowadays, face recognition is a common technique used in a variety of applications, including home security systems, criminal identification, and phone unlock systems. This system is more secure because it only requires a facial image instead of other dependencies like a key or card. Face detection and face identification are the two phases that typically make up a human recognition system.The idea behind designing and creating a face recognition system using deep learning with Azure ML Python's OpenCV is explained in this paper. Face recognition is a task that can be accomplished using deep learning, and given the accuracy of this method, it appears to be a suitable approach. To show how accurate the suggested face recognition system is, experimental results are given in 98.46% accuracy using Fast-RCNN Performance of algorithms under different training conditions.

Keywords: deep learning, face recognition, identification, fast-RCNN

Procedia PDF Downloads 100
339 Understanding the Performance and Loss Mechanisms in Ag Alloy CZTS Solar Cells: Photocurrent Generation, Charge Separation, and Carrier Transport

Authors: Kang Jian Xian, Huda Abdullah, Md. Akhtaruzzaman, Iskandar Yahya, Mohd Hafiz Dzarfan Othman, Brian Yulianto

Abstract:

The CZTS absorber layer doped with a silver (Ag) is one of the candidates that suggest improving the efficiency of thin films. Silver element functions to reduce antisite defects, increase grain size and create the plasmonic effect. In this work, an experimental study has been done to investigate the electrical and physical properties of CZTS, ACZTS, and AZTS. Ag replaces the Cu in (Cu1-xAgx)2ZnSnS4 (ACZTS) is up to x ≤1. ACZTS thin-films solar cells have been deposited by sol–the gel spin coating method. There are a total of 19 samples done with 11 significant percentages (0%, 10%, 20%… 100%) to show the whole phenomena of efficiency rate and nine specific percentages to find out the best concentration rate for Ag-doped. The obtained results can be helpful for better understanding ACZTS layers.

Keywords: CZTS, ACZTS, AZTS, silver, antisite, efficiency, thin-film solar cell

Procedia PDF Downloads 61
338 DSPIC30F6010A Control for 12/8 Switched Reluctance Motor

Authors: Yang Zhou, Chen Hao, Ma Xiaoping

Abstract:

This paper briefly mentions the micro controller unit, and then goes into details about the exact regulations for SRM. Firstly, it proposes the main driving state control for motor and the importance of the motor position sensor. For different speed, the controller will choice various styles such as voltage chopper control, angle position control and current chopper control for which owns its advantages and disadvantages. Combining the strengths of the three discrepant methods, the main control chip will intelligently select the best performing control depending on the load and speed demand. Then the exact flow diagram is showed in paper. At last, an experimental platform is established to verify the correctness of the proposed theory.

Keywords: switched reluctance motor, dspic microcontroller, current chopper

Procedia PDF Downloads 399