Does N ratio affect survival in D1 and D2 lymph node dissection for gastric cancer?

AIM:To identify whether there could have been changes in survival if lymph node ratio (N ratio) had been used.METHODS:We assessed 334 gastric adenocarcinoma cases retrospectively between 2001 and 2009.Two hundred and sixteen patients out of 334 were included in the study.Patients were grouped according to disection1 (D1) or dissection 2 (D2) dissection.We compared the estimated survival and actual survival determined by Pathologic nodes (pN) class and N ratio,and SPSS 15.0 software was used for statistical analysis.RESULTS:Ninety-six (44.4%) patients underwent D1 dissection and 120 (55.6%) had D2 dissection.When groups were evaluated,23 (24.0%) patients in D1 and 21 (17.5%) in D2 had stage migration (P=0.001).When both D1 and D2 groups were evaluated for number of pathological lymph nodes,despite the fact that there was no difference in N ratio between D1 and D2 groups,a statistically significant difference was found between them with regard to pN1 and pN2 groups (P=0.047,P=0.044 respectively).In D1,pN0 had the longest survival while pN3 had the shortest.In D2,pN0 had the longest survival whereas pN3 had the shortest survival.CONCLUSION:N ratio is an accurate staging system for defining prognosis and treatment plan,thus decreasing methodological errors in gastric cancer staging.

Forecasting Financial Distress of Chinese High-tech Manufacturing Companies Based on a Hybrid Model of GA-SVM

Owing to the radical changing of Chinese economy, it is essential to build an effective financial distress prediction model. In this paper, we present a genetic algorithm （GA） approach for optimizing parameters of support vector machine （SVM）. We validate the proposed model on datasets of Chinese high-tech manufacturing industry. Experimental results reveal that the proposed GAo SVM model can compare to and even outperform other exiting classifiers. Compared to grid-search algorithm, the proposed GA-based takes less time to optimize SVM parameter without degrading the prediction accuracy of SVM.

Study on the Calibration Function of Local Earthquake Magnitude in the Gansu Region

To calculate the deviations between single station magnitudes and average ones by the magnitude residual statistical method,the paper selects 13086 seismic events recorded by the Gansu broadband digital seismic network from January 2009 to December 2012. The frequency distribution and quantitative statistics of the deviations of earthquake magnitude are analyzed. The MLcalibration function is modified and a uniform local magnitude system characteristic of the Gansu region,is obtained.

Computation of Average Run Length for Residual-Based T^2 Control Chart for Multivariate Autocorrelated Processes

The expression of residual is obtained according to its dynamic response to mean shift, then the distribu- tion of T2 statistic applied to the residual is derived, thus the probability of the 7a statistic lying outside the control limit is calculated. The above-mentioned results are substituted into the infinite definition expression of the average run length （ARL）, and then the final finite ARL expression is obtained. An example is used to demonstrate the procedures of the proposed method. In the comparative study, eight autocorrelated processes and four different mean shifts are performed, and the ARL values of the proposed method are compared with those obtained by simulation method with 50 000 replications. The accuracy of the proposed method can be illustrated through the comparative results.

The Analysis on Chinese Women＇s Olympic Gold Medal Special Features and Influence Factors

This paper mainly by using the method of literature, mathematical statistics, the Beijing Olympic gold medal to our country distribution of statistical analysis, aiming at improving the Chinese competitive sports scores, strengthening our country provides the reference for the development of the Olympic Games and countermeasures, make our country to create more outstanding achievemenL and soon become physical power.

Modelling of Wage and Income Distributions Using the Method of L-Moments

Commonly used statistical procedure to describe the observed statistical sets is to use their conventional moments or cumulants. When choosing an appropriate parametric distribution for the data set is typically that parameters of a parametric distribution are estimated using the moment method of creating a system of equations in which the sample conventional moments lay in the equality of the corresponding moments of the theoretical distribution. However, the moment method of parameter estimation is not always convenient, especially for small samples. An alternative approach is based on the use of other characteristics, which the author calls L-moments. L-moments are analogous to conventional moments, but they are based on linear combinations of order statistics, i.e., L-statistics. Using L-moments is theoretically preferable to the conventional moments and consists in the fact that L-moments characterize a wider range of distribution. When estimating from sample L-moments, L-moments are more robust to the presence of outliers in the data. Experience also shows that, compared to conventional moments, L-moments are less prone to bias of estimation. Parameter estimates obtained using L-moments are mainly in the case of small samples often even more accurate than estimates of parameters made by maximum likelihood method. Using the method of L-moments in the case of small data sets from the meteorology is primarily known in statistical literature. This paper deals with the use of L-moments in the case for large data sets of income distribution （individual data） and wage distribution （data are ordered to form of interval frequency distribution of extreme open intervals）. This paper also presents a comparison of the accuracy of the method of L-moments with an accuracy of other methods of point estimation of parameters of parametric probability distribution in the case of large data sets of individual data and data ordered to form of interval frequency distribution.

Calendar Effects in AAPL Value-at-Risk

This study investigates calendar anomalies： day-of-the-week effect and seasonal effect in the Value-at-Risk （VaR） analysis of stock returns for AAPL during the period of 1995 through 2015. The statistical properties are examined and a comprehensive set of diagnostic checks are made on the two decades of AAPL daily stock returns. Combing the Extreme Value Approach together with a statistical analysis, it is learnt that the lowest VaR occurs on Fridays and Mondays typically. Moreover, high Q4 and Q3 VaR are observed during the test period. These results are valuable for anyone who needs evaluation and forecasts of the risk situation in AAPL. Moreover, this methodology, which is applicable to any other stocks or portfolios, is more realistic and comprehensive than the standard normal distribution based VaR model that is commonly used.

LO-RAY-LIGH@ Diffraction Gratings in UV-VIS Spectroscopy

It has been more than half a century since the release of the first Shimadzu UV-VIS （UV-visible） spectrophotometer QB-50 in 1952, and during this time more than 160,000 UV-VIS spectrometers have been produced and installed in a wide variety of different applications. A lot of technical innovations have been implemented to improve the performance and significantly reduce the stray light levels. The latest innovation during development of sophisticated spectrophotometers is based on a new holographic exposure method and optimized etching process which has made it possible to produce both high-efficient and exceptionally low stray light gratings. These LO-RAY-LIGH~ gratings have guaranteed values of stray light at the intermediate position between zero-order and first-order lights. The values are measured by Shimadzu＇s laser stray-light-measuring system. The latest development in the series of UV-VIS spectrophotometers is the UV-2700 which is a true double beam double monochromator system in a compact design for high-precision spectral analysis of a wide range of samples including organic and inorganic compounds, biological samples, optical materials and photovoltaics. The high performance optical system is designed with ＂LO-RAY-LIGH＂ diffraction gratings, featuring highest efficiency and exceptionally low stray light. The spectrophotometer operates in the wavelength range from 185 nm to 900 nm and allows highly sophisticated applications such as direct measurement of high density samples up to 8 absorbance units without dilution.

Improving Auditors＇ Going Concern Judgment by Applying Statistical Failure Models as an Analytical Procedure

The main goal of this research is to enhance the auditor＇s judgment ability in going concern opinion by applying bankruptcy prediction models as an analytical procedure. Data for this research have been collected through questionnaires. The statistical population consists of auditors who are members of Iranian Association of Certified Public Accountants （IACPA）. The research results reflect that： （1） Auditors do not use statistical techniques for assessing going concern as an analytical procedure; （2） Auditors do not use these techniques as a tool to decrease the bias of judgments in assessing the going concern assumption; （3） Auditors do not use statistical techniques to assess audit risk in the planning stage; （4） Auditors do not use statistical techniques to assess audit risk in the final stage. Furthermore this research shows that auditors believe that the ＂standard concerning usage of analytical procedures needs more clarification＂ and ＂statistical bankruptcy predication models can help auditors in the planning stage＂. The other goal of this research is to show different auditor＇s judgments in assessing the going concern opinion with and without applying the bankruptcy prediction models as an analytical procedure. The result shows that the judgment of auditors toward the going concern assumption has improved by using statistical bankruptcy predication models.

An Analysis of Annual Household Income From the Survey of Consumer Finances

This paper presents a brief analysis of the frequency and cumulative distributions of Americans＇ annual household income. In addition, a thorough discussion of the correlations between average income and some key demographic variables are included. The data come from the 2004 Survey of Consumer Finances. Utilizing the Survey a new, extraordinarily close, power law, relationship between current annual household income and accumulated financial assets is demonstrated. Another startling result is that the dependence of mean annual income on portfolio composition has nearly perfect power law dependence too. As money has scale, and power laws do not, this makes no sense.

An estimation of the penetration rate of rotary drills using the Specific Rock Mass Drillability index

The main purpose of the present study was to provide a practical, convenient drillability prediction model based on rock mass characteristics, geological sampling from blast holes, and drill operational factors. Empirical equations that predict drill penetration rate have been developed using statistical analyses of data from the Sarcheshmeh Copper Mine. Seven parameters of the rock or rock mass, including uniaxial compressive strength （UCS） of the rock, Schmidt hammer hardness value, quartz content, fragment size （dso）, alteration, and joint dip, are included in the model along with two operational parameters of the rotary drill, bit rotational speed and thrust. These parameters were used to predict values of the newly developed Specific Rock Mass Drillability （SRMD） index. Comparing measured SRMD values to those pre- dicted by the multi-parameter linear, or nonlinear, regression models showed good agreement. The cor- relation coefficients were 0.82 and 0.81. resoectively.

An Empirical Study of Applying English Films and TV Programs to English-Listening Teaching

This is a study of the feasibility and effects of teaching listening with films and TV programs. The research is a part of the English Learning Program directed by ZHANG Zhen, which is sponsored by Academic Affairs Office of Leshan Normal University. The researcher of the program sought for theretical bases from Krashen＇s Input Hypothesis, the Motivation Theory, the Context Theory, and the Communicative Language Teaching Theory. Then the author introduced a pilot study conducted by utilizing films or TV programs to teach listening from September 2010 till now. The statistic results from the experiment suggest that there is indeed some correlations between teaching listening with films or TV programs and a learner＇s listening comprehension in general in language achievement tests at certain stages. The scores of the students from the experimental group are improved after two years of teaching with the new methods. Analyses and discussions have been done based on a questionnaire and an interview. The results showed that both the teachers and the students had positive attitudes towards teaching listening with films or TV programs. Most of them view this method as an effective way in ELT （English language teaching）, because it provides more opportunities for contextual practice, lower their anxiety; it can also help to motivate them, stimulate their active participation and increase their activities as well. Therefore, this method can be used to cultivate students＇ communicative competence. Consequently, we can draw the conclusion that this method has some advantages over teaching listening with the pre-taped materials in New College English. It may play an important role in ELT, especially in listening teaching. Based on the statistic analyses and the survey, some activities and techniques are provided for the teacher on how to teach listening with films or TV programs. The roles that an English teacher plays in this method are illustrated at the end of the thesis.

The Impact of Enterprise Resource Planning （ERP） System on the Cost and Price of Auditing Auditor＇s Perspective

Technology plays a key role in today＇s business environment. Many companies greatly rely on computers and software to provide accurate information to effectively manage their business processes. It is becoming increasingly necessary for all businesses to incorporate information technology solutions to operate successfully. One way for many corporations to adopt information technology （IT） on a large scale is by installing enterprise resource planning （ERP） systems to accomplish their business transactions and data-processing needs. ERP systems are software packages that enable the integration of business processes throughout an organization. This study aims to determine the effect of the ERP system on the cost of auditing period compared with traditional computerized （non-ERP） systems. According to cost analysis, the study also points out the changes in audit price. The methodology used in this research is survey-based data collection. The questionnaires are sent to auditors who are working with companies with ERP systems. The answers are processed and analyzed using Statistical Package for Social Sciences （SPSS） 20. The data are performed using the statistical test to determine the effect of ERP usage on the cost of auditing process and pricing policy of auditors. The findings of this study are： （1） Companies with ERP systems are reducing their auditing costs; and （2） Auditing companies are not implying a low rate of price to their customers using ERP.

The Research of Education Technology Based on the SPSS Statistical Software

Through a questionnaire survey of primary and secondary school teachers and Normal Students to carry out a statistical analysis of the data based on SPSS 17.0 statistical analysis software. So we draw primary and secondary school teachers and normal students to arrive at the current status quo of educational technology ability and analyzes the strengths and weaknesses of the ability of its parts. Finally, we proposed new initiatives and methods of education and technical ability training.

Strategies and Principles of Distributed Machine Learning on Big Data

The rise of big data has led to new demands for machine learning （ML） systems to learn complex mod- els, with millions to billions of parameters, that promise adequate capacity to digest massive datasets and offer powerful predictive analytics （such as high-dimensional latent features, intermediate repre- sentations, and decision functions） thereupon. In order to run ML algorithms at such scales, on a distrib- uted cluster with tens to thousands of machines, it is often the case that significant engineering efforts are required-and one might fairly ask whether such engineering truly falls within the domain of ML research. Taking the view that ＂big＂ ML systems can benefit greatly from ML-rooted statistical and algo- rithmic insights-and that ML researchers should therefore not shy away from such systems design-we discuss a series of principles and strategies distilled from our recent efforts on industrial-scale ML solu- tions. These principles and strategies span a continuum from application, to engineering, and to theo- retical research and development of big ML systems and architectures, with the goal of understanding how to make them efficient, generally applicable, and supported with convergence and scaling guaran- tees. They concern four key questions that traditionally receive little attention in ML research： How can an ML program be distributed over a cluster？ How can ML computation be bridged with inter-machine communication？ How can such communication be performed？ What should be communicated between machines？ By exposing underlying statistical and algorithmic characteristics unique to ML programs but not typically seen in traditional computer programs, and by dissecting successful cases to reveal how we have harnessed these principles to design and develop both high-performance distributed ML software as well as general-purpose ML frameworks, we present opportunities for ML researchers and practitioners to further shape and enlarge the area that lies between ML and systems..

Throughput-efficient wireless system and blind detection via improved particle filtering

This paper introduces throughput-efficient wireless system based on an extension to binary phasemodulations,named extended binary phase shift keying(EBPSK),and the corresponding analysis ofpower spectra,especially the extension to channel capacity are given.Importantly,a novel sequential es-timation and detection approach for this EBPSK system is proposed.The basic idea is to design a proba-bilistic approximation method for the computation of the maximum a posterior distribution via particle fil-tering method(PF).Subsequently,a new important function in PF is presented,so that the performanceof the detector has a great improvement.Finally,computer simulation illustrates that EBPSK system hasvery high transmission rate,and also the good performance of the proposed PF detector is demonstrated.

Related factors and regional differences in energy consumption in China

This article used the Cluster analysis of statistical method to separate China＇s 30 provinces and municipalities into three categories according to their energy consumption discrepancies and characteristics from 1985 to 2007. The categories were high, moderate and low energy consumption areas and they had significant differences in energy consumption. Based on this classification, the authors analyzed the influencing factors of energy consumption in the three areas by means of panel data econometric model. The results showed that the influencing factors were obviously different. In order to support national goal of energy conservation and emission reduction, the energy measures and policies should be distinctly taken.

The Effect of a Proposed Training Program Based on the Reflective Model on the Teachers＇ Reading Practices in Mafraq

This study aimed at investigating the effect of a proposed EFL （English as a Foreign Language） training program on the teachers＇ reading practices in Mafraq. This program was developed by the researcher according to the ninth-grade EFL teachers＇ needs. The participants of the study were 20 ninth-grade females EFL teachers who represented the experimental and control groups （10 teachers in each group）. They were randomly chosen from 10 schools in the Northwestern Badia Directorate of Education. To achieve the purposes of the study, the researcher designed a needs analysis questionnaire, a training program, a pre and post observation checklist, and a pre and post received knowledge test for teachers. Proper statistical analysis was used to analyze the results of the research questions. The results of the study showed that teachers were in need to be trained on 20 reading comprehension practices to be able to teach reading comprehension effectively. Besides, there were statistically significant differences at the level of （a = 0.05） between the means scores of the ninth-grade teachers＇ performance of the control and experimental groups on the post observation checklist and on the post received knowledge test in favor of the experimental group due to the training program.

Minimal Sufficiency in Rare Populations

It is well understood that for conventional survey designs the set of unordered distinct units in a sample is a minimally sufficient statistic. This means that for inferential statistic of the sample, the value of the sampled units rather than the sample design is important. Sampling rare populations presents distinct challenges. Examples of rare populations are in biology with rare and endangered animals where there are only a few remaining individuals, or in social science, with the low incidence of people from an unusually high （or low） income group. Sampling rare populations tends to result in the case that many of the sample units do not contain information on the characteristic of interest （e.g., the rare animal, or people from the unusual income group）. For finite rare populations the set of unordered distinct rare-units in a sample is a minimally sufficient statistic. In an example case study of a rare buttercup, the properties of the minimal sufficient estimator are explored. We compare the efficiency of the estimator for the population total based on the minimally sufficient statistic, with the standard estimator for a range of sample sizes. The variance of the minimally sufficient estimator was always smaller than the variance of the sufficient estimator. For rare populations where non-rare units can be distinguished from rare units because they have the same fixed value, the minimal sufficient statistic is the rare units, if any, in the sample.