Amount Of Trimming Research Articles

Research on the Performance of an End-to-End Intelligent Receiver with Reduced Transmitter Data

A large amount of data transmission is one of the challenges faced by communication systems. In this paper, we revisit the intelligent receiver consisting of a neural network, and we find that the intelligent receiver can reduce the data at the transmitting end while improving the decoding accuracy. Specifically, we first construct a smart receiver model, and then design two ways to reduce the data at the transmitter side, namely, end-of-transmitter data trimming and equal-interval data trimming, to investigate the decoding performance of the receiver under the different trimming methods. The simulation results show that the receiver still has an accurate decoding performance with a small amount of trimming at the end of the transmitter data, while the decoding performance of the smart receiver is better than that of the conventional receiver with complete data when the data is trimmed at equal intervals. Moreover, the receiver with equally-spaced data cropping has a lower BER when the data at the transmitter side is reduced by the same data length. This paper provides a new solution to reduce the amount of data at the transmitter side.

Lesions found at foot trimming of dairy goats: Baseline data for comparing lesions and locomotion scoring

Data on the foot lesions of housed dairy goats, especially those that are not lame, is sparse. In this study, visits were made to four farms for whole herd locomotion scoring after milking and to observe routine foot trimming. During trimming, the amount of trimming required for each hoof was recorded, alongside the presence of lesions. The process was repeated at the next routine foot trim on three of the four farms (on Farm 1 whole herd locomotion scoring after milking was not feasible). Across both visits, 3445 locomotion scores were recorded, alongside 3850 trimming and lesion records. There were large differences between farms and visits in the proportion of lame goats (6.7 to 25.5%) and in the proportion of goats which needed a substantial trim of all four feet (15.1–33.1%). Hoof lesions were observed in 65.5% of trimmed goats. We defined lesions by their site and presence of separation and/or granuloma, with white line separation being the most commonly recorded lesion (41.5% of goats). On all visits on the three farms which were locomotion scored, the number of goats recorded as lame was lower than the number observed with white line lesions, but the relative proportion ranged from 17% to 95.4%. Separations were much more common than granulomas, as granulomas were usually accompanied by separation. Toe lesions were much more likely to be associated with granulomas than white line lesions, with 91.5% of toe separations having granulomas but only 10.6% of white line separations. This study provides useful baseline data for comparing lesions and locomotion scoring between goat herds but also identifies areas where we need more data and more consensus.

A Hybrid Incremental Nonlinear Dynamic Inversion Control for Improving Flying Qualities of Asymmetric Store Configuration Aircraft

Highly maneuverability fighter aircrafts are equipped with various weapons for successful air-to-air and air-to-ground missions. The aircraft has abrupt transient response due to ejection force generated when store of one wing is launched and the movement of lateral center-of-gravity (YCG) changing by the mass distribution of both wings after launched. Under maintaining 1 g level flight with manual trim system in the asymmetric store configuration, the aircraft causes unexpected roll motion for the pure longitudinal maneuver because the change of AoA and airspeed changes the amount of trim for level flight of the aircraft. For this reason, the pilot should continuously use the roll control stick input to maintain level flight. This characteristic increases the pilot’s workload and adversely affects the flying qualities of the aircraft, which is a major cause of deteriorating mission efficiency for combat maneuver. In this paper, we propose a hybrid control that combines model- and sensor-based Incremental Nonlinear Dynamic Inversion (INDI) control based mathematical model of the supersonic advanced trainer to minimize the transient response of the aircraft when the store is launched and to effectively reduce the unexpected roll motion that occurs for the pure longitudinal maneuvering in the asymmetric store configuration. As a result of the frequency- and time-domain evaluation, the proposed control method can effectively reduce the transient response for store launch and minimize unexpected roll motion for the pure longitudinal maneuver. Therefore, this control method can effectively improve flying qualities and mission efficiency by reducing the pilot’s workload in the operation of the asymmetric store configuration.

Trimmed extreme value estimators for censored heavy-tailed data

We consider estimation of the extreme value index and extreme quantiles for heavy–tailed data that are right-censored. We study a general procedure of removing low importance observations in tail estimators. This trimming procedure is applied to the state-of-the-art estimators for randomly right-censored tail estimators. Through an averaging procedure over the amount of trimming we derive new kernel type estimators. Extensive simulation suggests that one of the new considered kernels leads to a highly competitive estimator against virtually any other available alternative in this framework. Moreover we propose an adaptive selection method for the amount of top data used in estimation based on the trimming procedure minimizing the asymptotic mean squared error. We also provide an illustration of this approach to simulated as well as to real-world MTPL insurance data.

Prediction of the Effect of Impeller Trimming on the Hydraulic Performance of Low Specific-Speed Centrifugal Pumps

The effect of trimming of radial impellers on the hydraulic performance of low specific-speed centrifugal pumps is studied. Prediction methods from literature, together with a new prediction method that is based on the simplified description of the flow field in the impeller, are used to quantify the effect of trimming on the hydraulic performance. The predictions by these methods are compared to measured effects of trimming on the hydraulic performance for an extensive set of pumps for flow rates in the range of 80% to 110% of the best efficiency point. Of the considered methods, the new prediction method is more accurate (even for a large impeller trim of 12%) than the considered methods from literature. The new method generally overestimates the reduction in the pump head after trimming, and hence results less often in impeller trims that are too large when the method is used to determine the amount of trimming that is necessary in order to attain a specified head.

Exploratory Analysis and Modeling of Stock Returns

In this article, novel joint semiparametric spline-based modeling of conditional mean and volatility of financial time series is proposed and evaluated on daily stock return data. The modeling includes functions of lagged response variables and time as predictors. The latter can be viewed as a proxy for omitted economic variables contributing to the underlying dynamics. The conditional mean model is additive. The conditional volatility model is multiplicative and linearized with a logarithmic transformation. In addition, a cube-root power transformation is employed to symmetrize the lagged response variables. Using cubic splines, the model can be written as a multiple linear regression, thereby allowing predictions to be obtained in a simple manner. As outliers are often present in financial data, reliable estimation of the model parameters is achieved by trimmed least-square (TLS) estimation for which a reasonable amount of trimming is suggested. To obtain a parsimonious specification of the model, a new model selection criterion corresponding to TLS is derived. Moreover, the (three-parameter) generalized gamma distribution is identified as suitable for the absolute multiplicative errors and shown to work well for predictions and also for the calculation of quantiles, which is important to determine the value at risk. All model choices are motivated by a detailed analysis of IBM, HP, and SAP daily returns. The prediction performance is compared to the classical generalized autoregressive conditional heteroskedasticity (GARCH) and asymmetric power GARCH (APGARCH) models as well as to a nonstationary time-trend volatility model. The results suggest that the proposed model may possess a high predictive power for future conditional volatility. Supplementary materials for this article are available online.

Механизм и причины образования глубоких поверхностных дефектов на слябах при непрерывной разливке нержавеющих сталей, легированных титаном

The paper considers the structure of metal losses in melting stainless steel with titanium and casting the steel in curved-type continuous casting machine. A hypothesis on the mechanism of surface defect formation on continously cast slabs is described and recommendations to decrease the amount of trimming of defects are given. In other authors’ works it was supposed that this defect is caused by rippled surface like in ingot casting of stainless steel by uphill teeming; by sinking into liquid metal of raw slag-metal shells formed by interaction of dissolved titanium with oxygen and chamotte refractory lining of tundish; that there is relation between surface defects and the quality of slag mix for continuous casting machine mould and the character of distribution of metal streams in the mould. Arguments to criticize the versions that decreasing the amount of dissolved nitrogen is the key factor in obtaining better slab surface quality are also presented. Effect of dissolved nitrogen and titanium on trimming level of continuously cast slabs is shown, the ways to decrease this defect are proposed and the factors affecting its appearance are described.

The NS Matrix System

ABSTRACT Unlike amalgam, the difficulty of condensing composite presents us with the challenge, recreating a tight interproximal contact. May be more importantly, trimming composite that has been extruded beyond the preparation margin around an interproximal box is difficult, frustrating and unpredictable. So in a quest to minimize the amount of trimming we need to do with high-speed instrumentation after the composite is cured. Recreating the natural tooth shape and sealing the walls begins with the matrix. A matrix system must do the following three things: Recreate the natural tooth shape and interproximal contact Seal the proximal and gingival walls of the prep Overcome the thickness of the band. On the market today are both plastic and metal matrix bands. They are available in a variety of thicknesses and delivery systems that include sectional matrix bands, circumferential systems and bands that require a holder. Here, we present the NS matrix system which is a highly effective and economical matrix system that can be used for a variety of clinical applications, including posterior and anterior restorations. How to cite this article Sharma NS, Shrivastav SS, Hazarey PV, Kamble RH, Sharma PN. The NS Matrix System. World J Dent 2013;4(1):4-5.

Robust and Efficient Adaptive Estimation of Binary-Choice Regression Models

The binary-choice regression models, such as probit and logit, are used to describe the effect of explanatory variables on a binary response variable. Typically estimated by the maximum likelihood method, estimates are very sensitive to deviations from a model, such as heteroscedasticity and data contamination. At the same time, the traditional robust (high-breakdown point) methods, such as the maximum trimmed likelihood, are not applicable because, by trimming observations, they induce nonidentification of parameter estimates. To provide a robust estimation method for binary-choice regression, we consider a maximum symmetrically trimmed likelihood estimator (MSTLE) and design a parameter-free adaptive procedure for choosing the amount of trimming. The proposed adaptive MSTLE preserves the robust properties of the original MSTLE, significantly improves the finite-sample behavior of MSTLE, and also ensures the asymptotic equivalence of the MSTLE and maximum likelihood estimator under no contamination. The results concerning the trimming identification, robust properties, and asymptotic distribution of the proposed method are accompanied by simulation experiments and an application documenting the finite-sample behavior of some existing and the proposed methods.

Modified repeated median filters

We discuss moving window techniques for fast extraction of a signal composed of monotonic trends and abrupt shifts from a noisy time series with irrelevant spikes. Running medians remove spikes and preserve shifts, but they deteriorate in trend periods. Modified trimmed mean filters use a robust scale estimate such as the median absolute deviation about the median (MAD) to select an adaptive amount of trimming. Application of robust regression, particularly of the repeated median, has been suggested for improving upon the median in trend periods. We combine these ideas and construct modified filters based on the repeated median offering better shift preservation. All these filters are compared w.r.t. fundamental analytical properties and in basic data situations. An algorithm for the update of the MAD running in time O(log n) for window width n is presented as well.

Comparing the "typical score" across independent groups based on different criteria for trimming

Nonnormality and variance heterogeneity affect the validity of the traditional tests for treatment group equality (e.g. ANOVA F-test and t-test), particularly when group sizes are unequal. Adopting trimmed means instead of the usual least squares estimator has been shown to be mostly affective in combating the deleterious effects of nonnormality. There are, however, practical concerns regarding trimmed means, such as the predetermined amount of symmetric trimming that is typically used. Wilcox and Keselman proposed the Modified One- Step M-estimator (MOM) which empirically determines the amount of trimming. Othman et al. found that when this estimator is used with Schrader and Hettmansperger's H statistic, rates of Type I error were well controlled even though data were nonnormal in form. In this paper, we modified the criterion for choosing the sample values for MOM by replacing the default scale estimator, MADn, with two robust scale estimators, Sn and Tn , suggested by Rousseeuw and Croux (1993). To study the robustness of the modified methods, conditions that are known to negatively affect rates of Type I error were manipulated. As well, a bootstrap method was used to generate a better approximate sampling distribution since the null distribution of MOM-H is intractable. These modified methods resulted in better Type I error control especially when data were extremely skewed.

TR-MUSIC—A robust frequency estimation method in impulsive noise

Sinusoidal frequency estimation has been studied for many years. The MUSIC method represents a class of super-resolution methods based on subspace decomposition. However, the MUSIC method has poor performance in impulsive noise environments due to the prevalence of outliers and very large noise variance. A more robust method called trimmed correlation based-MUSIC (TR-MUSIC) method is proposed in this paper. Through a trimming operation, outliers in the samples participating in the correlation calculation are discarded, yielding a correlation sequence that is closer to the true underlying correlation. The amount of trimming is determined by the Mahalanobis distance in which robust estimates of location and scale are utilized to compensate for outlier effects. Frequency estimation results from the eigendecomposition of the trimmed correlation matrix. In the simulations, we take α -stable noise ( α > 1 ) as an example of impulsive noise. The proposed method is very robust and performs better than the conventional MUSIC and other robust methods. Furthermore, it can be applied to real signals as well as complex signals.

Carcase characteristics of emus (Dromaius novaehollandiae)

1. Six emus (Dromaius novaehollandiae) were slaughtered at 13 months of age in order to determine carcase, by-product and muscle yields. 2. Emus had a lower percentage of hot carcase weight (52%) and total fat (28%) to body weight but a higher lean meat to carcase weight (69%) than ostriches or rheas. 3. The amount of trimming of connective tissue from muscles of the lower leg (Gastrocnemius, Fibularis longus) has an influence (P <0.05) on the yields from these muscles.

Microbial Decontamination of Beef and Sheep Carcasses by Steam, Hot Water Spray Washes, and a Steam-Vacuum Sanitizer

Three separate studies were conducted to determine the effectiveness of various temperature water spray washes (Wt), wash and steam combinations (WtS), and vacuum and wash combinations (VWt) for reducing fecal bacteria on sheep and beef carcasses. Wt of 15.6, 54.4, and 82.2°C were administered to sheep carcasses contaminated with feces, using a hand-held spray nozzle. Initial carcass bacterial populations of approximately 2.5, 4, and 6 log CFU/cm2 were subjected to all wash combinations. W82.2 and W82.2S reduced 6 log CFU/cm2 bacterial populations as much as 4.0 log cycles. When carcasses were subjected to WtS and W82.2, the initial contamination levels (4 and 6 log CFU/cm2) had little effect on final bacterial levels (2.7 to 3.3 log CFU/cm2). However, uninoculated carcasses with initial bacterial populations of 2.5 log CFU/cm2 experienced a 1.5-log-cycle reduction when subjected to WtS and W82.2. It is possible that hydration of a carcass before and during interventions affords some protection to bacteria. The next study used a commercial carcass washer to apply a hot water (72°C), low pressure (20 psi) wash in combination with a high pressure (125 psi), warm water (30°C) wash (W72/30). Reductions on beef of 2.7, 3.3, and 3.4 log cycles for aerobic plate count (APC), coliforms, and E. coli populations, respectively, were observed. When a commercial steam-vacuum was used in conjunction with W72/30, reductions of 3.1, 4.2, and 4.3 log cycles for APC, coliforms, and E. coli populations, respectively, were achieved. Implementation of these interventions could reduce the amount of trimming needed on carcass-processing lines and would increase the microbial safety of beef carcasses.

Simulation Results on Solutions to the Multivariate Behrens-Fisher Problem Via Trimmed Means

A well-known result is that slight departures from normality towards a heavy-tailed distribution can substantially lower the power of methods for comparing means because heavy-tailed distributions inflate the standard error of the mean. One approach to this problem is to replace means with trimmed means. Trimmed means have standard errors that are less affected by heavy-tailed distributions, there are practical situations where they can have substantially higher power and the power remains relatively high when sampling from normal distributions, provided that the amount of trimming is not too high. This paper uses simulations to investigate the small sample characteristics of several solutions to the two-sample multivariate Behrens-Fisher problem based on trimmed means. Extant results when dealing with means are limited to normal distributions, so another goal is to report results on how three methods for means are affected by non-normality.

Trimmed slope estimates for simple linear regression

Abstract For the simple linear regression model, the trimmed slope estimate introduced here is a direct extension of the concept of a trimmed mean. To calculate a trimmed mean, order the observations, disregard unusually high and low ones, and take an average of the remaining observations. Specifying which observations are unusual is the discriminating factor among several types of trimmed means. Similar to the mean, the least squares estimate of the slope may be thought of as a weighted average of slopes calculated from pairs of observations. To calculate a trimmed slope estimate, order the pairwise slopes, disregard unusually high and low ones, and take a weighted average of the remaining slopes. In this paper we discuss various methods of specifying the unusual slopes to be trimmed. We also allow a broad class of weights to be used in the averaging. In some situations which admit outliers in the data, from a robustness viewpoint certain choices of weights are useful even without trimming pairwise slopes. Trimmed slope estimates enjoy advantages similar to those of trimmed means. They are easy to interpret and explain. Since they are linear combinations of the pairwise slopes, computation of the estimates is straightforward. Further, the data analyst can control the amount of trimming through an explicit parameter. It turns out that the large sample properties are also similar. In this paper the consistency, asymptotic normality and influence functions of the trimmed slope estimators are investigated.

Adaptive Robust Procedures: A Partial Review and Some Suggestions for Future Applications and Theory

Abstract After providing some background for the need to consider estimates other than those resulting from normal theory, there is a brief review of some nonadaptive robust estimators. We introduce adaptive estimators using those of Tukey and McLaughlin, Jaeckel, Johns, Birnbaum and Miké, Takeuchi, Hàjek, van Eeden, and Beran. Adaptive estimators based on preliminary testing and Stein-like procedures are then considered, and recommendations are made on how to select the amount of trimming. Various proposals for estimating regression coefficients are also considered. Adaptive distrubution-free tests look very promising for improving the power of nonparametric tests, and some of these techniques can be used effectively in data analysis. Asymmetric trimmed means, adapted to the particular sample, can easily be used with data and provide good descriptive statistics having an approximate error structure. Finally, it is conjectured that estimators based on “cliff-hangers” might be extremely effective if there are sharp changes in the height of the underlying density function.

Thermal Processing of Tantalum Nitride Resistors

A study of the thermal oxidation of tantalum nitride (Ta-N) thin films has led to the development of a thermal processing technique by which these metal films can be made to exhibit superior resistor characteristics. The thermal process simply involves heating the Ta-N film resistors in air at some temperature between 450° and 700°C. Radiant heating has been found to be most convenient for this purpose. While the resistor is maintained at the elevated temperature, its resistance is monitored. When the resistor reaches the desired value, the heat source is quickly removed. Resistors can be easily trimmed to O.B%, and by exercising some care, 0.1% and less may be attained. In comparison with the usual "anodic" processing of Ta-N resistors, the thermal technique holds promise of greater economy in manufacture by reducing the number of process steps and by increasing the resistor yield. The latter benefit derives from the fact that the electrical behavior of thermally oxidized Ta-N resistors shows a marked insensitivity to certain deposition parameters which are normally controlled with some care. Accelerated tests of resistors made by this method are being carried out at various load levels and under high humidity conditions. Resistance changes as low as 0.1% per thousand hours have been recorded for nominal 1/2 watt resistors operating at 1 watt. Processing parameters such as substrate material, nitrogen doping level, trim rate, and amount of trim have been investigated. Although continued evaluation will be required before thermal processing is fully qualified, it is already clear that it will be of considerable importance to the Ta-N discrete and integrated resistor technology.