Search results for: Zhu Jian Bing

Authors: Jian Zheng, Yoshiyasu Takahashi, Yuichi Kobayashi, Tatsuhiro Sato

Abstract:

In the study, we present a conceptual framework for developing a scheduling system that can generate self-explanatory and easy-understanding schedules. To this end, a user interface is conceived to help planners record factors that are considered crucial in scheduling, as well as internal and external sources relating to such factors. A hybrid approach combining machine learning and constraint programming is developed to generate schedules and the corresponding factors, and accordingly display them on the user interface. Effects of the proposed system on scheduling are discussed, and it is expected that scheduling efficiency and system understandability will be improved, compared with previous scheduling systems.

Keywords: constraint programming, factors considered in scheduling, machine learning, scheduling system

Procedia PDF Downloads 324

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

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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

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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 229

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

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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

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

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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 677

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

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Authors: Delele Worku Ayele, Bing-Joe Hwang

Abstract:

A method that does not employ hot injection techniques has been developed for the size-tunable synthesis of high-quality CdSe quantum dots (QDs) with a zinc blende structure. In this environmentally benign synthetic route, which uses relatively less toxic precursors, solvents, and capping ligands, CdSe QDs that absorb visible light are obtained. The size of the as-prepared CdSe QDs and, thus, their optical properties can be manipulated by changing the microwave reaction conditions. The QDs are characterized by XRD, TEM, UV-vis, FTIR, time-resolved fluorescence spectroscopy, and fluorescence spectrophotometry. In this approach, the reaction is conducted in open air and at a much lower temperature than in hot injection techniques. The use of microwaves in this process allows for a highly reproducible and effective synthesis protocol that is fully adaptable for mass production and can be easily employed to synthesize a variety of semiconductor QDs with the desired properties. The possible application of the as-prepared CdSe QDs has been also assessed using deposition on TiO2 films.

Keywords: average life time, CdSe QDs, microwave (MW), mass production oleic acid, Na2SeSO3

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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 192

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 249

Authors: Delele Worku Ayele, Bing-Joe Hwang

Abstract:

A method that does not employ hot injection techniques has been developed for the size-tunable synthesis of high-quality CdSe quantum dots (QDs) with a zinc blende structure. In this environmentally benign synthetic route, which uses relatively less toxic precursors, solvents, and capping ligands, CdSe QDs that absorb visible light are obtained. The size of the as-prepared CdSe QDs and, thus, their optical properties can be manipulated by changing the microwave reaction conditions. The QDs are characterized by XRD, TEM, UV-vis, FTIR, time-resolved fluorescence spectroscopy, and fluorescence spectrophotometry. In this approach, the reaction is conducted in open air and at a much lower temperature than in hot injection techniques. The use of microwaves in this process allows for a highly reproducible and effective synthesis protocol that is fully adaptable for mass production and can be easily employed to synthesize a variety of semiconductor QDs with the desired properties. The possible application of the as-prepared CdSe QDs has been also assessed using deposition on TiO2 films.

Keywords: CdSe QDs, Na2SeSO3, microwave (MW), oleic acid, mass production, average life time

Procedia PDF Downloads 709

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

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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

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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

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Authors: Bing Song, Kexi Han, Xuewei Lv

Abstract:

Titania slag is a high quality raw material containing titanium in the subsequent process of titanium pigment. The effects of cooling approaches of granulating, water cooling, and air cooling on chemical, phases, and acidolysis of Panzhihua titania slag were investigated. Compared to the original slag which was prepared by the conventional processing route, the results show that the titania slag undergoes oxidation of Ti³⁺during different cooling ways. The Ti₂O₃ content is 17.50% in the original slag, but it is 16.55% and 16.84% in water cooled and air-cooled slag, respectively. Especially, the Ti₂O₃ content in granulated slag is decreased about 27.6%. The content of Fe₂O₃ in granulated slag is approximately 2.86% also obviously higher than water (<0.5%) or air-cooled slag (<0.5%). Rutile in cooled titania slag was formed because of the oxidation of Ti³⁺. The rutile phase without a noticeable change in water cooled and air-cooled slag after the titania slag was cooled, but increased significantly in the granulated slag. The rate of sulfuric acid acidolysis of cooled slag is less than the original slag. The rate of acidolysis is 90.61% and 92.46% to the water-cooled slag and air-cooled slag, respectively. However, the rate of acidolysis of the granulated slag is less than that of industry slag about 20%, only 74.72%.

Keywords: cooling approaches, titania slag, granulating, sulfuric acid acidolysis

Procedia PDF Downloads 238

Authors: Gebregziabher Brhane Berhe, Bing Joe Hwange, Wei-Nien Su

Abstract:

For a high-voltage cell, severe capacity fading is usually observed when the commercially carbonate-based electrolyte is employed due to the oxidative decomposition of solvents. To mitigate this capacity fading, an advanced electrolyte of fluoroethylene carbonate, ethyl methyl carbonate (EMC), and 1,1,2,2-Tetrafluoroetyle-2,2,3,3-tetrafluoropropyl ether (TTE) (in vol. ratio of 3:2:5) is dissolved with oxidative stability. A high-voltage lithium-ion battery was designed by coupling sulfured carbon anode from polyacrylonitrile (S-C(PAN)) and LiN0.5Mn1.5 O4 (LNMO) cathode. The discharged capacity of the cell made with modified electrolyte reaches 688 mAhg-1S a rate of 2 C, while only 19 mAhg-1S for the control electrolyte. The adopted electrolyte can effectively stabilize the sulfurized carbon anode and LNMO cathode surfaces, as the X-ray photoelectron spectroscopy (XPS) results confirmed. The developed robust high-voltage lithium-ion battery enjoys wider oxidative stability, high rate capability, and good cyclic performance, which can be attributed to the partially fluorinated electrolyte formulations with balanced viscosity and conductivity.

Keywords: high voltage, LNMO, fluorinated electrolyte, lithium-ion batteries

Procedia PDF Downloads 66

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 366

Authors: Bing-Wen Chen, Alvin W. Y. Su, Yu-Lin Wang

Abstract:

Electromyography (EMG) is one of the important indicators during exercise, as it is closely related to the level of muscle activations. This work quantifies the muscle conditions of the lower limbs in a constant workload exercise. Surface EMG signals of the vastus laterals (VL), vastus medialis (VM), rectus femoris (RF), gastrocnemius medianus (GM), gastrocnemius lateral (GL) and Soleus (SOL) were recorded from fourteen healthy males. The EMG signals were segmented in two phases: activation segment (AS) and relaxation segment (RS). Period entropy (PE), peak count (PC), zero crossing (ZC), wave length (WL), mean power frequency (MPF), median frequency (MDF) and root mean square (RMS) are calculated to provide the quantitative information of the measured EMG segments. The outcomes reveal that the PE, PC, ZC and RMS have significantly changed (p<.001); WL presents moderately changed (p<.01); MPF and MDF show no changed (p>.05) during exercise. The results also suggest that the RS is also preferred for performance evaluation, while the results of the extracted features in AS are usually affected directly by the amplitudes. It is further found that the VL exhibits the most significant changes within six muscles during pedaling exercise. The proposed work could be applied to quantify the stamina analysis and to predict the instant muscle status in athletes.

Keywords: electromyographic feature extraction, muscle status, pedaling exercise, relaxation segment

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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 285

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

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Authors: Gebregziabher Brhane Berhe, Wei-Nien Su, Bing Joe Hwang

Abstract:

A new lithium-ion battery is configured by coupling sulfurized carbon anode and high voltage LiNi₀.₅Mn₁.₅O₄ (LNMO) cathode. The anode is derived from sulfurized polyacrylonitrile (S-C(PAN)). Severe capacity fading usually becomes unavoidable due to the oxidative decomposition of solvents, primarily when a conventional carbonate electrolyte with 1 M lithium hexafluorophosphate (LiPF6) is employed. Fluoroethylene carbonate (FEC), ethyl methyl carbonate (EMC), and 1, 1, 2, 2-Tetrafluoroethyl-2, 2, 3, 3-tetrafluoropropyl ether (TTE) are formulated as the best electrolyte (3:2:5 in vol. ratio) for this new high-voltage lithium-ion battery to mitigate this capacity fading and improve the adaptability of the S-C(PAN) and LNMO. The discharge capacity of a full cell made with 1 M lithium hexafluorophosphate (LiPF6) in FEC/EMC/TTE (3:2:5) electrolyte reaches 688 mAh g⁻¹ at a rate of 2 C, while 19 mAh g⁻¹ for the control electrolyte. X-ray photoelectron spectroscopy (XPS) results confirm that the fluorinated electrolyte effectively stabilizes both surfaces of S-C(PAN) and LNMO in the full cell. Compared to the control electrolyte, the developed electrolyte enhances the cyclic stability and rate capability of both half cells (Li//S-C(PAN and Li//LiNi₀.₅Mn₁.₅O₄) and S-C(PAN)//LiNi₀.₅Mn₁.₅O₄ full cells.

Keywords: fluorinated electrolyte, high voltage, lithium-ion battery, polyacrylonitrile

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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 262

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

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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

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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

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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

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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

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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

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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

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Authors: Muhammad Fathurridho

Abstract:

Grammar as a rule used by every language to be understood by everyone is always related to syntax and morphology. Arabic grammar is different with another languages’ grammars. It has more rules and difficulties. This paper aims to investigate and describe the English grammatical errors of machine translation systems in translating Arabic sentences, including declarative, exclamation, imperative, and interrogative sentences, specifically in year 2018 which can be supported with artificial intelligence’s role. The Arabic sample sentences which are divided into two; verbal and nominal sentence of several Arabic published texts will be examined as the source language samples. The translated sentences done by several popular online machine translation systems, including Google Translate, Microsoft Bing, Babylon, Facebook, Hellotalk, Worldlingo, Yandex Translate, and Tradukka Translate are the material objects of this research. Descriptive method that will be taken to finish this research will show the grammatical errors of English target language, and classify them. The conclusion of this paper has showed that the grammatical errors of machine translation results are varied and generally classified into morphological, syntactical, and semantic errors in all type of Arabic words (Noun, Verb, and Particle), and it will be one of the evaluations for machine translation’s providers to correct them in order to improve their understandable results.

Keywords: Arabic, Arabic-English translation, machine translation, grammatical errors

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Authors: Wei Fang, Jian Jun Gu, Di Xue

Abstract:

Objective: To analyze the employee compensation status of secondary public hospitals of Pudong New Area in Shanghai in order to provide information for compensation reform of public hospitals in Shanghai and as well as in China. Methods: We surveyed all 15 secondary public hospitals of Pudong New Area in Shanghai to collect hospital annual compensation data for their employees and to investigate their suggestions for compensation reform in public hospitals in China. We also collected related annual compensation data of employees in Shanghai and of physicians in the USA from Shanghai statistical Yearbook 2013 and from Bureau of Labor Statistics, U.S. Department of Labor. Results: The average annual compensation for the employees in secondary public hospitals of Pudong New Area in Shanghai in 2012 was 2.65 times of that for overall employees in Shanghai. The physician’s compensation in these public hospitals was relatively lower than that in the USA. Conclusion: The physicians’ compensation in the secondary public hospitals of Pudong New Area in Shanghai should be increased rationally and new compensation reform in public hospitals in Shanghai should be carefully designed.

Keywords: human resource, compensation, public hospital, Shanghai

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