A Study of EM Algorithm as an Imputation Method: A Model-Based Simulation Study with Application to a Synthetic Compositional Data

Compositional data, such as relative information, is a crucial aspect of machine learning and other related fields. It is typically recorded as closed data or sums to a constant, like 100%. The statistical linear model is the most used technique for identifying hidden relationships between underlying random variables of interest. However, data quality is a significant challenge in machine learning, especially when missing data is present. The linear regression model is a commonly used statistical modeling technique used in various applications to find relationships between variables of interest. When estimating linear regression parameters which are useful for things like future prediction and partial effects analysis of independent variables, maximum likelihood estimation (MLE) is the method of choice. However, many datasets contain missing observations, which can lead to costly and time-consuming data recovery. To address this issue, the expectation-maximization (EM) algorithm has been suggested as a solution for situations including missing data. The EM algorithm repeatedly finds the best estimates of parameters in statistical models that depend on variables or data that have not been observed. This is called maximum likelihood or maximum a posteriori (MAP). Using the present estimate as input, the expectation (E) step constructs a log-likelihood function. Finding the parameters that maximize the anticipated log-likelihood, as determined in the E step, is the job of the maximization (M) phase. This study looked at how well the EM algorithm worked on a made-up compositional dataset with missing observations. It used both the robust least square version and ordinary least square regression techniques. The efficacy of the EM algorithm was compared with two alternative imputation techniques, k-Nearest Neighbor (k-NN) and mean imputation (), in terms of Aitchison distances and covariance.

Exploration on Teaching Reform of Synthetic Biology Course Based on the New Engineering Concept

Synthetic biology is a new frontier of life science,which aims to design,transform and even synthesize organisms with engineering design concept.Doing a good job in the teaching of"synthetic biology"is of great significance to the cultivation and reserve of biotechnology professionals in China,and also has an important impact on students' employment competitiveness.Under the background of"new engineering",the course reform of"synthetic biology"was carried out in terms of the construction of teaching staff,teaching methods,students' participation and the innovation of course content,and specific reform suggestions were put forward,hoping to effectively promote the sustainable development of"synthetic biology"and effectively improve the quality of education.

2D MXenes as Co-catalysts in Photocatalysis:Synthetic Methods

Since their seminal discovery in 2011,two-dimensional(2D)transition metal carbides/nitrides known as MXenes,that constitute a large family of 2D materials,have been targeted toward various applications due to their outstanding electronic properties.MXenes functioning as co-catalyst in combination with certain photocatalysts have been applied in photocatalytic systems to enhance photogenerated charge separation,suppress rapid charge recombination,and convert solar energy into chemical energy or use it in the degradation of organic compounds.The photocatalytic performance greatly depends on the composition and morphology of the photocatalyst,which,in turn,are determined by the method of preparation used.Here,we review the four different synthesis methods(mechanical mixing,self-assembly,in situ decoration,and oxidation)reported for MXenes in view of their application as co-catalyst in photocatalysis.In addition,the working mechanism for MXenes application in photocatalysis is discussed and an outlook for future research is also provided.

Theory and Method of Mineral Resource Prediction Based on Synthetic Information

Metallogenic prognosis of synthetic information uses the geological body and the mineral resource body as a statistical unit to interpret synthetically the information of geology, geophysics, geochemistry and remote sensing from the evolution of geology and puts all the information into one entire system by drawing up digitalized interpretation maps of the synthetic information. On such basis, different grades and types of mineral resource prospecting models and predictive models of synthetic information can be established. Hence, a new integrated prediction system will be formed of metallogenic prognosis (qualitative prediction), mineral resources statistic prediction (determining targets) and mineral resources prediction (determining resources amount).

Fuzzy Synthetic Evaluation Model for Smart Washing Machine

Generally fuzzy control system (FCS) is worked in washing machine. For the fuzzy set theory, membership functions are the building blocks. In a fuzzy set, fuzziness is determined by its membership functions. The shapes of membership functions are important, because it has an effect on fuzzy inference system. The shapes of membership functions can be triangular, trapezoidal and gaussian. The most widely used triangular membership function is used in this paper, because it can capture the short time period. In washing machine, open loop control system is found. This paper applies a fuzzy synthetic evaluation method (FSEM) for washing cloth in washing machine as FSEM can handle the multiple criteria with the help of evaluation matrix generated from membership function and weight matrix generated by Analytical Hierarchy Process (AHP). The purpose of this research is to minimize the wash time. By applying FSEM, we get a wash time which is less than that wash time got from applying the Mamdani approach in FCS. An example is given for illustration. For more reduction of wash time, statistical averaging method is also used. To reduce the wash time, statistical averaging method can be used in Mamdani approach also.

Application of simple array method in one-way traffic synthetic asessment

One-Way Traffic synthetic assessing can not only determine the assessment method, but can also provide an opportunity for further study of road systems. Comparing three Road Traffic Planning methods, which are Value Analysis method, Simple Array method and Step Analysis method, this paper concludes that Simple Array method has one prominent merit, avoiding the complicated relationship of various factors and simplifying the complex problem. Therefore Simple Array method is firstly presented in this paper to be the assessing measure to assess the One-Way Traffic Planning project. Although this assessing method cannot wholly give way to man’s will, through consistently testing on qualitative factors and with the decision-making results of a multi-program, this method is still an effective method. Using an example of Harbin One-Way Traffic planning, with seven assessing indexes including economic benefit index, Simple Array method is applied to synthetically assessing the program. This fully reflects the general function of One-Way Traffic planning program and objectively evaluates the program. It also proves that, as the method of One-Way Traffic synthetic assessing, Simple Array method is rational and practical.

Analysis and Application of the Synthetic Relative Measuring Method in On-Line Monitoring for Capacitive Equipment in Power Systems

On-line measurement for dielectric loss angle can effectively monitor the insulation condition of capacitive equipment in power systems. Synthetic relative measuring methods not only markedly overcome the shortcomings of traditional absolute measuring methods but also greatly improve the accuracy of dielectric loss angle measurement. However, synthetic relative measuring methods based on two or three pieces of capacitive equipment do not have the characteristic of generality. In this paper, a principle of synthetic relative measuring method is presented. The example of application for synthetic relative methods based on three and four pieces of capacitive equipment running in the same phase is taken to present the failure judgment matrices for N pieces of equipment. According to these matrices, the fault condition of N pieces of capacitive equipment can be watched, which is more general. Then some problems needing to be concerned along with two diagnostic methods used in diagnostic system are introduced. Finally, two programmable flow charts for the two methods are given and corresponding examples demonstrate their feasibility in practice.

Assessment of Effects of Green Construction by Analytic Hierarchy Process and Fuzzy Synthetic Judgment Method

The index system, code system, and weights of indexes are established to assess the effects of green construction. The index system consists of index level, factor level and sub-factor level. The analytic hierarchy process is used to determine the weights of indexes, and the consistency test indicate that the weight assignment is reasonable. Using fuzzy synthetic judgment method, the assessment model is built, which includes factor set, weight set and conclusion set. An example is given to demonstrate the assessment procedures.

Method of Monitoring Three-dimensional Mining Surface Deformation Based on InSAR

In order to solve the problems of small monitoring range,long time and high cost of existing sedimentation observation methods,based on two-view sentinel No.1 radar images of Guqiao mining area in Huainan City from November 4,2017 to November 28,2017,surface change information was obtained in combination with D-InSAR,and the three-dimensional surface deformation was monitored by two-pass method and single line of sight D-InSAR method.The results show that during the research period of 24 d,the maximum deformation of the mining area reached 71 mm,and the southern subsidence was the most obvious,which was in line with the mining subsidence law.The maximum displacement from the north to the south was about 250 mm,while the maximum displacement from the east to the west was about 80 mm,and the maximum subsidence in the center was 110 mm.It is concluded that D-InSAR technique has a good effect on the inversion of the mining subsidence,and this method is suitable for three-dimensional surface monitoring in areas with similar geological conditions.The monitoring results have certain reference value.

NEW SYNTHETIC METHOD OF 4,4'-OXYBIS(BENZOIC ACID)AND ITS APPLICATION IN POLYESTER

4,4'-Oxybis(benzoic acid)(Ⅰ)is an important monomer for making synthetic resin,heat resistant film and liquid crystal fiber,etc.It has been synthesized either by the oxidation of 4,4'-dimethyl diphenyl ether,or by the electrophilic substitution of diphenyl ether,these substituents introduced into the benzene ring can be further transformed into carboxylic groups.Diphenyl ethers are usually prepared from phenols and halobenzenes through Ullmann resction.Due to the high reaction temerature(usually above 200℃),long time heating and the formation of isomers,it is difficult to obtain pure products in high yields.

A NOVEL SYNTHETIC METHOD AND STRUCTURE OF TETRAKIS(BENZOATE)BIS(TRIPHENYLPHOSPHINE OXIDE)DICOPPER(II).OXIDATIVE ADDITION OF DIBENZOYL ON METALLIC COPPER

Dibenzoyl peroxide undergoes oxidative addition on metallic copper with triphenylphosphine in a mixed solvent(acetone,dichloromethane and trichloromethane),and affords the binuclear copper complex (Cu(C_6H_5COO)_2(OPPh_3))_2.Crystals are monoclinic,space group A_2/a,with cell parameters,a=24.337(3),b=10.566(1),c=21.579(2),β= 93.18(1)°, V=5540(1)~3,Z=4,R=0.042,and Rw=0.044 for 5872 observed reflections. Each copper ion is coordinated by four bridging benzoato ligands and one triphenylphosphine oxide group to form binuclear complexes.

An Advanced Simple Method for Generating Synthetic Average Instant Hourly Solar Energy

The main objective of this study is to generate accurate synthetic hourly solar radiation data by using an easily accessible open source data.In this regard,a new approach is proposed for estimation of synthetic hourly global solar radiation during the day by utilizing only annual solar energy data.First time in literature,a model has been developed for prediction hourly and daily solar radiation based on annual solar energy parameter in this study.Parameters of the model were generated and tested for Turkey and one of them was presented as a case study within this paper.Long term measured hourly horizontal solar irradiance data from a network of Turkish meteorological stations was used to calibrate the model function.The predictions are compared with the solar data available in literature for Turkey.The advanced simple new model is utilized in open source computer program and has the potential to be adapted to other countries.

A Mo LC+Mo M-based G^0 distribution parameter estimation method with application to synthetic aperture radar target detection

The accuracy of background clutter model is a key factor which determines the performance of a constant false alarm rate(CFAR) target detection method. G0 distribution is one of the optimal statistic models in the synthetic aperture radar(SAR) image background clutter modeling and can accurately model various complex background clutters in the SAR images. But the application of the distribution is greatly limited by its disadvantages that the parameter estimation is complex and the local detection threshold is difficult to be obtained. In order to solve the above-mentioned problems, an synthetic aperture radar CFAR target detection method using the logarithmic cumulant(Mo LC) + method of moment(Mo M)-based G0 distribution clutter model is proposed. In the method, G0 distribution is used for modeling the background clutters, a new Mo LC+Mo M-based parameter estimation method coupled with a fast iterative algorithm is used for estimating the parameters of G0 distribution and an exquisite dichotomy method is used for obtaining the local detection threshold of CFAR detection, which greatly improves the computational efficiency, detection performance and environmental adaptability of CFAR detection. Experimental results show that the proposed SAR CFAR target detection method has good target detection performance in various complex background clutter environments.

The Application of Synthetic Fuzzy Assessing Method in Measurement and Control System of Plating Solution Evaporator

The synthetic fuzzy assessing method is usually applied to sensory evaluation. The method has simple and reliable virtue, and it is consistent with objective evaluation results. Using this method, system status of plating solution evaporator is evaluated, and the result is applied to compensate a fuzzy controller. Experimental results have shown the correctness and the validity of the proposed approach.

Study on the Method of Short-Term Synthetic Earthquake Prediction in the North China Region

Based on the extraction and calculation of the short-term seismic precursory information magnitude from the 114 major precursory observations in the North China region, and together with consideration of factors such as geological structure, seismicity, crustal thickness, and in particular, the current geodynamics of the region, the authors studied the time-space evolution characteristics of the short-term earthquake precursory information magnitude and its relationship with earthquakes and proposed the index and method for the short-term synthetic prediction of earthquakes with M S≥5.0 in the North China region. The inspection through R-value shows that the method is effective to a certain extent for earthquake prediction.

A synthetic aperture radar sea surface distribution estimation by n-order Bézier curve and its application in ship detection

To dates,most ship detection approaches for single-pol synthetic aperture radar（SAR） imagery try to ensure a constant false-alarm rate（CFAR）.A high performance ship detector relies on two key components：an accurate estimation to a sea surface distribution and a fine designed CFAR algorithm.First,a novel nonparametric sea surface distribution estimation method is developed based on n-order Bézier curve.To estimate the sea surface distribution using n-order Bézier curve,an explicit analytical solution is derived based on a least square optimization,and the optimal selection also is presented to two essential parameters,the order n of Bézier curve and the number m of sample points.Next,to validate the ship detection performance of the estimated sea surface distribution,the estimated sea surface distribution by n-order Bézier curve is combined with a cell averaging CFAR（CA-CFAR）.To eliminate the possible interfering ship targets in background window,an improved automatic censoring method is applied.Comprehensive experiments prove that in terms of sea surface estimation performance,the proposed method is as good as a traditional nonparametric Parzen window kernel method,and in most cases,outperforms two widely used parametric methods,K and G0 models.In terms of computation speed,a major advantage of the proposed estimation method is the time consuming only depended on the number m of sample points while independent of imagery size,which makes it can achieve a significant speed improvement to the Parzen window kernel method,and in some cases,it is even faster than two parametric methods.In terms of ship detection performance,the experiments show that the ship detector which constructed by the proposed sea surface distribution model and the given CA-CFAR algorithm has wide adaptability to different SAR sensors,resolutions and sea surface homogeneities and obtains a leading performance on the test dataset.

Influence of air pressure on the performance of plasma synthetic jet actuator

Plasma synthetic jet actuator（PSJA） has a wide application prospect in the high-speed flow control field for its high jet velocity.In this paper,the influence of the air pressure on the performance of a two-electrode PSJA is investigated by the schlieren method in a large range from 7 k Pa to 100 k Pa.The energy consumed by the PSJA is roughly the same for all the pressure levels.Traces of the precursor shock wave velocity and the jet front velocity vary a lot for different pressures.The precursor shock wave velocity first decreases gradually and then remains at 345 m/s as the air pressure increases.The peak jet front velocity always appears at the first appearance of a jet,and it decreases gradually with the increase of the air pressure.A maximum precursor shock wave velocity of 520 m/s and a maximum jet front velocity of 440 m/s are observed at the pressure of 7 k Pa.The averaged jet velocity in one period ranges from 44 m/s to 54 m/s for all air pressures,and it drops with the rising of the air pressure.High velocities of the precursor shock wave and the jet front indicate that this type of PSJA can still be used to influence the high-speed flow field at 7 k Pa.

An accelerated nonlocal means algorithm for synthetic aperture radar ocean image despeckling

Synthetic aperture radar(SAR)images play an increasingly important role in ocean environmental monitoring and research.However,SAR images are inherently corrupted by speckle noise.SAR ocean images have some unique characteristics.The signatures of ocean phenomena in SAR images mainly exhibit as stripe or plaque shaped features.These features typically have a high degree of self-similarity or redundancy.The nonlocal means(NLM)method can measure the structural similarity between different image patches and take advantage of redundant information in images.Considering that the NLM algorithm is computationally intensive and timeconsuming,an accelerated NLM algorithm for SAR ocean image despeckling is proposed in this paper.A method is used to discriminate between texture and flat pixels in SAR images.Large similarity and search windows are used on texture pixels,whereas small similarity and search windows are used on flat pixels.Furthermore,the improved NLM algorithm is accelerated by a graphic processing unit(GPU)based on the compute unified device architecture(CUDA)parallel computation framework.The computational efficiency is improved by approximately 200 times.

Application of Cationic Waterborne Polyurethane as Impregnation Material for Microfiber Synthetic Leather Base

A cationic waterborne polyurethane(CWPU) was synthesized and utilized as impregnation material for manufacturing microfiber synthetic leather base,in an attempt to decrease environmental pollution associated with organic solvents and improve simulation degree relative to genuine leather.The alkali resistance of the CWPU and four manufacture methods were investigated.Meanwhile,the dyeing properties of the microfiber synthetic leather base were studied.It was found that the CWPU displayed enough alkali resistance to endure the alkali deweighting process for microfiber synthetic leather base manufacture.In terms of bending length,bending rigidity,compression elasticity ratio and specific compression elasticity ratio of the resulting base,coagulating the impregnated CWPU with sodium hydroxide before steam treatment was the optimal method.The extent of fiber splitting and the handle of the base from this method were both similar to conventional base filled with solvent-based polyurethane(SPU).The dyeing properties of the microfiber synthetic leather base filled with CWPU were also found superior to the one filled with either anionic waterborne polyurethane(AWPU) or SPU.

Fuzzy synthetic evaluation on layoff mechanism for human resource

According to the modern theory of human resource management, the condition of buyout mainly depends on two variables of an employee: his interior value of product and exterior work reward. There exist shortages in evaluating the value of the employees in an enterprise. Consequently, a lot of employees might be laid off. Hence, this paper puts forward a two-stage method for decision-making to carry out a selective plan of buyout, based on the fuzzy synthetic evaluation involing many factors impacting on human resource. Moreover, a positive analysis is also given.