Customized Optimization for Vehicle Acoustic Statistical Energy Analysis

Statistical Energy Analysis(SEA) is one of the conventional tools for predicting vehicle high-frequency acoustic responses.This study proposes a new method that can provide customized optimization solutions to meet NVH targets based on the specific needs of different project teams during the initial project stages.This approach innovatively integrates dynamic optimization,Radial Basis Function(RBF),and Fuzzy Design Variables Genetic Algorithm(FDVGA) into the optimization process of Statistical Energy Analysis(SEA),and also takes vehicle sheet metal into account in the optimization of sound packages.In the implementation process,a correlation model is established through Python scripts to link material density with acoustic parameters,weight,and cost.By combining Optimus and VaOne software,an optimization design workflow is constructed and the optimization design process is successfully executed.Under various constraints related to acoustic performance,weight and cost,a globally optimal design is achieved.This technology has been effectively applied in the field of Battery Electric Vehicle(BEV).

Improved statistical fluctuation analysis for two decoy-states phase-matching quantum key distribution

Phase-matching quantum key distribution is a promising scheme for remote quantum key distribution,breaking through the traditional linear key-rate bound.In practical applications,finite data size can cause significant system performance to deteriorate when data size is below 1010.In this work,an improved statistical fluctuation analysis method is applied for the first time to two decoy-states phase-matching quantum key distribution,offering a new insight and potential solutions for improving the key generation rate and the maximum transmission distance while maintaining security.Moreover,we also compare the influence of the proposed improved statistical fluctuation analysis method on system performance with those of the Gaussian approximation and Chernoff-Hoeffding boundary methods on system performance.The simulation results show that the proposed scheme significantly improves the key generation rate and maximum transmission distance in comparison with the Chernoff-Hoeffding approach,and approach the results obtained when the Gaussian approximation is employed.At the same time,the proposed scheme retains the same security level as the Chernoff-Hoeffding method,and is even more secure than the Gaussian approximation.

Statistical analysis on the influence of mechanical parameters in the vibration of pylons

We present a statistical investigation of the degree of influence that assumptions made in relation to the mechanical parameters of a pylon have on its ground-induced vibrations.The study is set up by using as a key kinematic variable the displacement at the top of a reference,a stand-alone pylon with a uniform cross-section and fixity at its base.Next,statistics are produced using a dimensionless displacement ratio defined between the‘parental’and the‘subsidiary’cases,the latter defined for the pylon(a)resting on compliant soil,(b)having an attached top mass,and(c)being non-uniform with height.Furthermore,two materials are examined,namely,steel and reinforced concrete(R/C).More specifically,this displacement ratio is independent of the excitation and plays the role of a transfer function between the base and the top of the pylon.Both horizontal and vertical motions are considered,and the equations of motion are solved in the frequency domain.The ensuing statistical analysis is conducted for the following parameter combinations:(a)pylon founded on soft,intermediate,and stiff soil;(b)low,intermediate,and high-mass ratios of the attached mass to the pylon′s mass;(c)a constant and quadratic degree of pylon tapering with height.Spearman correlation coefficients are calculated for all the above combinations to arrive at statistical results that establish validity bounds and quantify the degree of influence of each assumption on the pylon′s response.

Effect of Jianpi Bushen formula for colon cancer patients who underwent adjuvant chemotherapy:Statistical analysis plan for a multicenter trial

Background:Patients with colon cancer who receive chemotherapy usually experience various gastrointestinal adverse reactions,including nausea,vomiting,and diarrhea,which make it challenging for them to adhere to treatment.As an effective traditional Chinese medicine,the Jianpi Bushen formula has been widely used to alleviate the side effects of chemotherapy.Objective:To evaluate the efficacy and safety of Jianpi Bushen formulae for patients who undergo chemotherapy.This statistical analysis plan(SAP)is intended to enhance the transparency and research quality of our randomized controlled trial.Methods:Our study is a multicenter,double-blind,randomized controlled clinical trial.This trial aimed to compare the completion rate of chemotherapy in colon cancer patients who are using and not using Jianpi Bushen formula.To attenuate possible selection bias in the final report,we declared the overall trial design,outcome measures,subgroup analyses,and safety measures.Also,we described the data management and statistical analysis methods in detail.Conclusion:The SAP provides more detailed information than the trial protocol for data management and statistical analysis methods.Further post-hoc analyses can be performed by referring to the SAP,and possible selection bias can be attenuated.

Statistical Analysis and Countermeasures for Specimen Rejection in the Emergency Department

The rejected specimens from the Emergency Department of the Center of Clinical Laboratory from January 1,2022 to January 1,2023 were analyzed to reduce the specimen rejection rates and to improve the quality of inspection.The results showed that there were 1488 samples of rejected specimens and the non-conforming rate was 0.58%.The departments involved were mainly the Emergency Department,the Hematology Department,the Cardiology Department,the Intensive Care Department,and the Brain Surgery Department.Among the reasons for rejection,blood hemolysis accounted for 43.15%,blood coagulation accounted for 26.61%,and the rate of insufficient specimens was 17.14%.Among them,the sample rejection rate for arterial blood gas analysis was the highest,which accounted for 1.74%;followed by specimens for coagulation test,which was 1.18%.These results indicate the main reason for producing rejected specimens is mainly due to not following the standard operating procedure.Specimen rejection can largely be avoided if the standards for specimen collection are strictly followed.

3D Modeling and Determination of Factors Responsible for Zinc-Lead Mineralization in the Mehdiabad Deposit,Central Iran,based on Statistical Analysis of Geochemical Data

Although the Mehdiabad zinc-lead deposit is one of the most well-known deposits in the central Iran structural zone,the genesis of the deposit remains controversial.The host rock of the ore is a dolomitic limestone of the Lower Cretaceous Taft Formation.In the two main orebodies of the deposit,which includes the Black Hill and East Ridge ore zones,the oxide and sulfide ores are observed at the surface and at depth,respectively.The elements Zn,Fe,Mn and Mg are more abundant in the East Ridge ore zone(in both sulfide and oxide ores),with Ba,Pb,Ag and Cu being more abundant in the Black Hill oxide ore.Based on the distribution of elements and their correlation with each other in these ore zones,the elements are divided into three general groups,that of terrigenous elements,chemically-deposited elements and oreforming(hydrothermally deposited)elements,a division that is supported by the results of factor analyses.The spatial distribution of elements is jointly affected by contact with host rocks,the boundary of oxide-sulfide ores and fault zones.The main factors governing the distribution of elements are the mechanical transfer of detrital sediments,chemical sedimentation,transfer by hydrothermal fluids,oxidation and surface dissolution,all of which affected the spatial distribution of elements.The ore-forming elements are mostly affected by hydrothermal fluids and oxidation.This study not only provides additional information about the genesis of the Mehdiabad deposit,but also could assist in the exploitation of ore and further exploration purposes.The results of this study can aid in the exploration and exploitation of the Mehdiabad deposit and similar deposits in the region.

Comparison of Several Statistical Analysis Models for Genotypic Stability of Saccharum officinarum

[Objective] The study aimed to compare several statistical analysis models for estimating the sugarcane （Saccharum spp.） genotypic stability. [Method] The data of sugarcane regional trials in Guangdong, in 2009 was analyzed by three models respectively： Finlay and Wilkinson model： the additive main effects and multiplicative interaction （AMMI） model and linear regression-principal components analysis （LR- PCA） model, so as to compare the models. [Result] The Finlay and Wilkinson model was easier, but the analysis of the other two models was more comprehensive, and there was a bit difference between the additive main effects and multiplicative inter- action （AMMI） model and linear regression-principal components analysis （LR-PCA） model. [Conclusion] In practice, while the proper statistical method was usually con- sidered according to the different data, it should be also considered that the same data should be analyzed with different statistical methods in order to get a more reasonable result by comparison.

Integration between Genomic and Computational Statistical Surveys for the Screening of SNP Genetic Variants in Inflammatory Bowel Disease (IBD) Pediatric Patients*

Inflammatory bowel diseases (IBD) are complex multifactorial disorders that include Crohn’s disease (CD) and ulcerative colitis (UC). Considering that IBD is a genetic and multifactorial disease, we screened for the distribution dynamism of IBD pathogenic genetic variants (single nucleotide polymorphisms;SNPs) and risk factors in four (4) IBD pediatric patients, by integrating both clinical exome sequencing and computational statistical approaches, aiming to categorize IBD patients in CD and UC phenotype. To this end, we first aligned genomic read sequences of these IBD patients to hg19 human genome by using bowtie 2 package. Next, we performed genetic variant calling analysis in terms of single nucleotide polymorphism (SNP) for genes covered by at least 20 read genomic sequences. Finally, we checked for biological and genomic functions of genes exhibiting statistically significant genetic variant (SNPs) by introducing Fitcon genomic parameter. Findings showed Fitcon parameter as normalizing IBD patient’s population variability, as well as inducing a relative good clustering between IBD patients in terms of CD and UC phenotypes. Genomic analysis revealed a random distribution of risk factors and as well pathogenic SNPs genetic variants in the four IBD patient’s genome, claiming to be involved in: i) Metabolic disorders, ii) Autoimmune deficiencies;iii) Crohn’s disease pathways. Integration of genomic and computational statistical analysis supported a relative genetic variability regarding IBD patient population by processing IBD pathogenic SNP genetic variants as opposite to IBD risk factor variants. Interestingly, findings clearly allowed categorizing IBD patients in CD and UC phenotypes by applying Fitcon parameter in selecting IBD pathogenic genetic variants. Considering as a whole, the study suggested the efficiency of integrating clinical exome sequencing and computational statistical tools as a right approach in discriminating IBD phenotypes as well as improving inflammatory bowel disease (IBD) molecular diagnostic process.

Statistical and causes analysis of storm surges along Tianjin coast during the past 20 years

Based on tidal data statistical analysis for 20 years of Tanggu Marine Environmental Monitoring Station from 1991 to 2010, we concluded that an average of nearly 10 days of 100 cm above water increase took place at Tianjin coast every year. The maximum high tide and average tide of Tianjin coast occurred in summer and autumn, and the maximum water increase also occurred in summer and autumn. Days with water increase more than 100 cm mostly occurred in spring, autumn and winter. Then we summarized the causes of coastal storm surge disaster in Tianjin based on astronomical tide factors, meteorological factors, sea level rise, land subsidence, and geographic factors, et al. Finally, we proposed storm surge disaster prevention measures.

Statistical Approach to Basketball Players’Skill Level

In basketball, each player’s skill level is the key to a team’s success or failure, the skill level is affected by many personal and environmental factors. A physics-informed AI statistics has become extremely important. In this article, a complex non-linear process is considered by taking into account the average points per game of each player, playing time, shooting percentage, and others. This physics-informed statistics is to construct a multiple linear regression model with physics-informed neural networks. Based on the official data provided by the American Basketball League, and combined with specific methods of R program analysis, the regression model affecting the player’s average points per game is verified, and the key factors affecting the player’s average points per game are finally elucidated. The paper provides a novel window for coaches to make meaningful in-game adjustments to team members.

The Application of SPSS in Statistical Analysis Project-A Study of the Inheritance of Chinese Traditional Shadow Play in Schools

Chinese traditional shadow play has been selected into the List of Intangible Cultural Heritage in 2011.Yet,reflecting abundant national cultural values,such traditional art form is degenerating and fading out from people’s sight.As the earliest statistical analysis software,Statistical Package for the Social Science(SPSS)is comprehensive in analyzing and managing statistical data.This study explores the application of SPSS in minimizing the workload of researchers while raising the validity of data in supporting the analysis of the survey data which reflected the inheritance and development of Chinese traditional shadow play in schools.

Simulation on a Car Interior Aerodynamic Noise Control Based on Statistical Energy Analysis

How to simulate interior aerodynamic noise accurately is an important question of a car interior noise reduction. The unsteady aerodynamic pressure on body surfaces is proved to be the key effect factor of car interior aerodynamic noise control in high frequency on high speed. In this paper, a detail statistical energy analysis （SEA） model is built. And the vibra-acoustic power inputs are loaded on the model for the valid result of car interior noise analysis. The model is the solid foundation for further optimization on car interior noise control. After the most sensitive subsystems for the power contribution to car interior noise are pointed by SEA comprehensive analysis, the sound pressure level of car interior aerodynamic noise can be reduced by improving their sound and damping characteristics. The further vehicle testing results show that it is available to improve the interior acoustic performance by using detailed SEA model, which comprised by more than 80 subsystems, with the unsteady aerodynamic pressure calculation on body surfaces and the materials improvement of sound/damping properties. It is able to acquire more than 2 dB reduction on the central frequency in the spectrum over 800 Hz. The proposed optimization method can be looked as a reference of car interior aerodynamic noise control by the detail SEA model integrated unsteady computational fluid dynamics （CFD） and sensitivity analysis of acoustic contribution.

STATISTICAL ANALYSIS AND NUMERICAL SIMULATION OF POYANG LAKE'S INFLUENCE ON TROPICAL CYCLONES

Based on the Tropical Cyclone(TC briefly thereafter)Yearbook 1980-2009,this paper first analyzes the number and intensity change of the TCs which passed directly over or by the side of Poyang Lake(the distance of TC center is less than 1°longitude or 1°latitude from the Lake)among all the landfalling TCs in China during the past 30 years.Two cases are examined in detail in this paper.One is severe typhoon Rananim with a speed of 3.26 m/s and a change of 1 hPa in intensity when it was passing the Lake.The other is super typhoon Saomai with a faster moving speed of 6.50 m/s and a larger change in intensity of 6 hPa.Through numerical simulation experiments,this paper analyzes how the change of underlying surface from water to land contributes to the differences in intensity,speed and mesoscale convection of the two TCs when they passed the Lake.Results show that the moisture and dynamic condition above the Lake were favorable for the maintenance of the intensity when Rananim was passing through Poyang Lake,despite the moisture supply from the ocean was cut off.As a result,there was strong convection around the lake which led to a rainfall spinning counter-clockwise as it was affected by the TC movement.However,little impact was seen in the Saomai case.These results indicate that for the TCs coming ashore on Poyang Lake with a slow speed,the large water body is conducive to the sustaining of the intensity and strengthening of the convection around the TC center and the subsequent heavy rainfall.On the contrary,a fast-moving TC is less likely to be influenced by the underlying surface in terms of intensity and speed.

Application of Integration of Spatial Statistical Analysis with GIS to Regional Economic Analysis

This paper summarizes a few spatial statistical analysis methods for to measuring spatial autocorrelation and spatial association, discusses the criteria for the identification of spatial association by the use of global Moran Coefficient, Local Moran and Local Geary. Furthermore, a user-friendly statistical module, combining spatial statistical analysis methods with GIS visual techniques, is developed in Arcview using Avenue. An example is also given to show the usefulness of this module in identifying and quantifying the underlying spatial association patterns between economic units.

Statistical Analysis on Field Efficacy Trial of Pesticide Using Visual Basic

[Objective] To introduce a convenient and easy way for the statistical anal- ysis on field efficacy trials of pesticide by using Visual Basic. [Method] The calcula- tion procedure of using Visual Basic to conduct statistical analysis on the field efficacy of pesticides was introduced, and an example was used to illustrate the usage and skill of the program. [Result] The procedure could quickly and accurately con- duct statistical analysis on the field efficacy of pesticide by only inputting initial data of the test, and it could compare the significance of differences between various fac- tors. Its calculated results were consistent with the results of the specialized statisti- cal software DPS. [Conclusion] It is a quick and simple method with high accuracy and reliability, which can greatly improve the efficiency of pesticide formulation opti- mization.

Multivariate Statistical Process Monitoring of an Industrial Polypropylene Catalyzer Reactor with Component Analysis and Kernel Density Estimation

Abstract Data-driven tools, such as principal component analysis （PCA） and independent component analysis （ICA） have been applied to different benchmarks as process monitoring methods. The difference between the two methods is that the components of PCA are still dependent while ICA has no orthogonality constraint and its latentvariables are independent. Process monitoring with PCA often supposes that process data or principal components is Gaussian distribution. However, this kind of constraint cannot be satisfied by several practical processes. To ex-tend the use of PCA, a nonparametric method is added to PCA to overcome the difficulty, and kernel density estimation （KDE） is rather a good choice. Though ICA is based on non-Gaussian distribution intormation, .KDE can help in the close monitoring of the data. Methods, such as PCA, ICA, PCA.with .KDE（KPCA）, and ICA with KDE,（KICA）, are demonstrated and. compared by applying them to a practical industnal Spheripol craft polypropylene catalyzer reactor instead of a laboratory emulator.

Application of Statistical Tools for Data Analysis and Interpretation in Rice Plant Pathology

There has been a significant advancement in the application of statistical tools in plant pathology during the past four decades. These tools include multivariate analysis of disease dynamics involving principal component analysis, cluster analysis, factor analysis, pattern analysis, discriminant analysis, multivariate analysis of variance, correspondence analysis, canonical correlation analysis, redundancy analysis, genetic diversity analysis, and stability analysis, which involve in joint regression, additive main effects and multiplicative interactions, and genotype-by-environment interaction biplot analysis. The advanced statistical tools, such as non-parametric analysis of disease association, meta-analysis, Bayesian analysis, and decision theory, take an important place in analysis of disease dynamics. Disease forecasting methods by simulation models for plant diseases have a great potentiality in practical disease control strategies. Common mathematical tools such as monomolecular, exponential, logistic, Gompertz and linked differential equations take an important place in growth curve analysis of disease epidemics. The highly informative means of displaying a range of numerical data through construction of box and whisker plots has been suggested. The probable applications of recent advanced tools of linear and non-linear mixed models like the linear mixed model, generalized linear model, and generalized linear mixed models have been presented. The most recent technologies such as micro-array analysis, though cost effective, provide estimates of gene expressions for thousands of genes simultaneously and need attention by the molecular biologists. Some of these advanced tools can be well applied in different branches of rice research, including crop improvement, crop production, crop protection, social sciences as well as agricultural engineering. The rice research scientists should take advantage of these new opportunities adequately in adoption of the new highly potential advanced technologies while planning experimental designs, data collection, analysis and interpretation of their research data sets.

Construction of Inorganic Elemental Fingerprint and Multivariate Statistical Analysis of Marine Traditional Chinese Medicine Meretricis concha from Rushan Bay

Meretricis concha is a kind of marine traditional Chinese medicine(TCM), and has been commonly used for the treatment of asthma and scald burns. In order to investigate the relationship between the inorganic elemental fingerprint and the geographical origin identification of Meretricis concha, the elemental contents of M. concha from five sampling points in Rushan Bay have been determined by means of inductively coupled plasma optical emission spectrometry(ICP-OES). Based on the contents of 14 inorganic elements(Al, As, Cd, Co, Cr, Cu, Fe, Hg, Mn, Mo, Ni, Pb, Se, and Zn), the inorganic elemental fingerprint which well reflects the elemental characteristics was constructed. All the data from the five sampling points were discriminated with accuracy through hierarchical cluster analysis(HCA) and principle component analysis(PCA), indicating that a four-factor model which could explain approximately 80% of the detection data was established, and the elements Al, As, Cd, Cu, Ni and Pb could be viewed as the characteristic elements. This investigation suggests that the inorganic elemental fingerprint combined with multivariate statistical analysis is a promising method for verifying the geographical origin of M. concha, and this strategy should be valuable for the authenticity discrimination of some marine TCM.

Statistical Analysis and Prediction of the Concentration of Harmful Algae in Bohai Bay

Based on the data of phytoplankton concentration and environmental factors in Bohai Bay from May to September in 2003. the relationship between environmental factors and phytoplankton biomass was analyzed. By analysis of variance, the weather condition was found to have no direct relation with phytoplankton biomass. Correlation coefficients showed that temperature, pH value,the concentrations of silicate and nitrate exhibited linear relationship with phytoplankton biomass.With principal component analysis, pollution types which affected the abundance of phytoplankton included point sources such as municipal and industrial effluents, agricultural runoff and earth＇s surface water. Using multivariate stepwise regression method and taking the correlation analysis results into consideration, a multi-step regression equation was developed to predict the concentration of phytoplankton in September 2003. Combined results show that temperature, pH value, the concentrations of silicate and nitrate are the critical ecological factors affecting the phytoplankton biomass in Bohai Bay.

Identification of distant co-evolving residues in antigen 85C from Mycobacterium tuberculosis using statistical coupling analysis of the esterase family proteins

A fundamental goal in cellular signaling is to understand allosteric communication, the process by which sig-nals originating at one site in a protein propagate reliably to affect distant functional sites. The general principles of protein structure that underlie this process remain unknown. Statistical coupling analysis （SCA） is a statistical technique that uses evolutionary data of a protein family to measure correlation between distant functional sites and suggests allosteric communication. In proteins, very distant and small interactions between collections of amino acids provide the communication which can be important for signaling process. In this paper, we present the SCA of protein alignment of the esterase family （pfam ID： PF00756） containing the sequence of antigen 85C secreted by Mycobacterium tuberculosis to identify a subset of interacting residues. Clustering analysis of the pairwise correlation highlighted seven important residue positions in the esterase family alignments. These resi-dues were then mapped on the crystal structure of antigen 85C （PDB ID： 1DQZ）. The mapping revealed corre-lation between 3 distant residues （Asp38, Leu123 and Met125） and suggests allosteric communication between them. This information can be used for a new drug against this fatal disease.