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Label distribution learning (LDL) is a framework to solve label ambiguity. To improve the performance of LDL, some existing algorithms exploit global and local label correlations. In reality, local correlations are more reasonable than global ones because few correlations can be globally adapted to all samples. The existing algorithms exploiting local correlations assume that the smaller the Euclidean distance between samples, the more likely the samples are to share the same label correlations. Specifically, they all use K-means to divide samples into several clusters, and then mine local correlations in each cluster based on this assumption. However, this assumption is incorrect in some cases and may lead to inappropriate clustering results and biased correlations. In this paper, we propose a novel LDL algorithm which mines local label correlations in self-regulating clusters independent of sample distance. In particular, we introduce clustering with learnable parameters into the model to realize that the clustering can be optimized jointly with the objective function instead of depending on the distance between samples. In this way, our proposed algorithm can mine more accurate local label correlations in these more appropriate clusters. Experimental results on 15 real-world datasets demonstrate the effectiveness of the proposed algorithm.

The use of data mining and machine learning is common on the advent of artificial intelligence in the field of modern agriculture. The use of clustering algorithm is to classify each data point into a specific group. The soil test report dataset was preprocessed and feed on Rapid Miner and used X-means and K-means clustering algorithms to discover knowledge. The result clusters of locations and chemical characters’ pH, P, K and N were very good in frequency distribution of samples. The analysis and performance of each centroid are far more acceptable due to p-values are less than 0.05. Average sample distance from each centroid is also in acceptable values. For future endeavors, more experiments on clustering the chemical characteristics on each type of crops, soil type, and soil test request date submission from the dataset.

To define and control the parameters which impact headspace solid-phase microextraction (HS-SPME), it is important to reach the highest level of reproducibility. The present study aims to assess, for the first time, the effect of fiber-sample distance during HS-SPME in pre-equilibrium conditions. Analyses were primarily performed on mixtures of standard volatiles compounds (alkanes, alcohols, organic acids) designed in our lab and then on various food matrices (wine, chicken, cheese, tea), repeating already published experiments. Extractions were performed varying fiber penetration depths (10-60 mm) at different times (10-60 min) and temperatures of extraction (30-80 °C). The study revealed that variation of the distance between the fiber and the sample into the vial clearly impacts the results obtained during HS-SPME when conditions are such that no equilibrium is reached in HS. For example, in wine analysis, the percentage of octanoic acid at 80 °C was higher at 40 mm (7.5 ± 0.2%) than that at 20 mm (4.4 ± 0.3%). Moreover, regardless of the extraction temperature, the lower the time of extraction, the stronger the dependence on the fiber-sample distance. Indeed, at 60 °C, the obtained response factors for octadecane at 20 and 40 mm of fiber penetration were 21.8 and 44.5, respectively, after 10 min of extraction, 54.1 and 71.0 after 30 min, and 79.4 and 82.4 after 60 min of extraction. The analyses have been here corroborated by a theoretical model based on the diffusion equation. Therefore, to improve the method robustness during HS-SPME studies, we suggest specifying the fiber penetration depth or the fiber-sample distance with the other parameters of extraction.

A novel IBAF system (altered conventional biological aerated filter (BAF) for intermittent aeration) was used to treat BDD anodes electrochemical oxidation gasification wastewater effluent, after which 454 pyrosequencing was applied to investigate the bacterial community of IBAF and demonstrate the relationship between dissolved oxygen (DO) and the bacterial community. The results showed that the concentration of COD, NH4+-N and NO3−-N reached 55.08, 7.64 and 7.76 mg/L, respectively, in IBAF effluent because of changes in the DO concentration at 30 days after system start-up. The bacterial community results revealed that the 40 cm sample had the highest bacterial diversity. The bacterial species were approximate in total samples at phylum and family level, but the relative abundance was significantly different because of change in DO concentration. In addition, sample distance analysis indicated that the similarity of different samples was related to the DO concentration at different heights.

A novel particle tracking framework is introduced in this paper that utilizes null-collisions to sample distance to collision in Monte Carlo particle transport problems. The sampling process is des...

The distance between the showerhead and the sample surface (GAP) is one of the main growth parameters of the commonly used research reactor, Close Coupled Showerhead. We examine its influence on the growth rate of GaN layers deposited under various conditions (growth temperature, carrier gas, V/III ratio and growth pressure). Regardless of other growth parameters, increasing the GAP value leads to a reduction in the growth rate.

Batch effect is a frequent challenge in deep sequencing data analysis that can lead to misleading conclusions. We present scBatch, a numerical algorithm that conducts batch effect correction on the count matrix of RNA sequencing (RNA-seq) data. Different from traditional methods, scBatch starts with establishing an ideal correction of the sample distance matrix that effectively reflect the underlying biological subgroups, without considering the actual correction of the raw count matrix itself. It then seeks an optimal linear transformation of the count matrix to approximate the established sample pattern. The benefit of such an approach is the final result is not restricted by assumptions on the mechanism of the batch effect. As a result, the method yields good clustering and gene differential expression (DE) results. We compared the new method, scBatch, with leading batch effect removal methods ComBat and mnnCorrect on simulated data, real bulk RNA-seq data, and real single-cell RNA-seq data. The comparisons demonstrated that scBatch achieved better sample clustering and DE gene detection results.

With the rapid development of mobile Internet, the network has become an important medium for people to exchange information. The research on text classification has practical significance. Using the Hadoop platform to parallelize the KNN classification algorithm can quickly and accurately classify the text, but when calculating the similarity or distance of the sample points, the KNN algorithm will increase with the increase of the sample data, which will lead to the algorithm time. Increased complexity and reduced classification accuracy. Therefore, Parallel Processing of Improved KNN text classification algorithm based on Hadoop platform is proposed. The CLARA clustering algorithm is used to cut out the samples with low similarity in the dataset, and the calculation of sample distance in the dataset is reduced. Then design the parallel KNN MapReduce program to classify the network public opinion data. The experimental results show that the improved parallel KNN algorithm improves the accuracy and time of text classification.

Peripheral edema is of ten assessed by medical prof essionals to gain insights about development of many patient conditions. Currently, doctors assess edema by pushing on the swollen area of a patient. The difficulty with this method is the inconsistency assessment results between different physicians due to the subjective nature of the practice. The proposed solution uses AERO (or Air Edema RepOrting), a mobile, handheld device consisting of a high-speed camera with a macro lens, LED light, and compressed air to create edema indentation and capture images of the skin /tissue response. A MATLAB program analyzes these images and determines the correct level of edema. AERO was tested with a LifeformOR pitting edema trainer (four pieces of skin sample that represent the four edema levels). Various system configurations, such as the air pressure, camera to sample distance, and air incidence angle, were examined and optimal parameters were identified. Results demonstrated that AERO was able to distinguish the four levels of edema sample pads. This solution can potentially provide a quantified, standard evaluation of peripheral edema for both home and health care environments.

16 Introduction 16 Materials and Methods 18 Results 20 Discussion 21 Acknowledgement 23 References Cited 23 Appendix 32 THE INFLUENCE OF STATURE AND STATUS ON INTER-OBSERVER SAMPLING VARIATION IN COUNTS OF ADULT CORN ROOTWORMS 38 Abstract 38 Introduction 38 Materials and Methods 40 Results 41

Lateral-force microscopy is a powerful tool to study the frictional properties of two-dimensional materials. However, few works distinctly reveal the correlation between the tip radius with the tip&ndash, sample distance and the frictional properties of the two-dimensional (2D) materials. We performed molecular-dynamics simulations to study the atomic-scale friction of a typical two-dimensional single-layer molybdenum disulfide (SLMoS2). The effects of tip radius and tip&ndash, sample distance on the frictional properties were analyzed and discussed. The frictional force&ndash, sliding-distance curves show typical stick&ndash, slip behaviors, and the periodicity can be used to characterize the lattice constants of SLMoS2. Sub-nanoscale stick-slip movements occur in one-lattice sliding periods along with only the armchair (AC) direction and only when the tip radius is smaller than 3 &Aring, with 1.47 &Aring, tip-sample distance. At the same tip&ndash, sample distance, a smaller tip can provide a more detailed characterization and higher-precision frictional properties of SLMoS2. A larger tip is capable of providing comparative frictional properties of SLMoS2 at a proper vertical tip&ndash, sample distance, compared with the small tip.

In this work a 23 factorial design was carried out aiming the multivariate optimization of Instrumental Neutron Activation Analysis (INAA) for mass fraction determination of Co, Cr, Fe, Rb, Sc, Se and Zn in biological samples and Co, Cr, Fe, Sc and Zn in geological samples. The factors investigated in this study were sample decay time, sample distance to detector and sample measurement time. The optimal condition for each method was outlined according to the main effect and interactions results. It was observed that sample decay time is the most important factor for the INAA optimization in the different methods.

The transmission of 1 MeV proton microbeam passing between two parallel flat plates was investigated. Three different materials were used in our experiments. As insulators we used Polytetrafluoroethylene and borosilicate glass plates and glass with gold layer on the surface as conductor. The surface of the plates was parallel to the beam axis and one of the plates was moved towards the beam. The energy distribution and the deflection of the transmitted beam were measured as the function of the sample distance relative to the beam. We found systematic differences between the behaviour of the metallic and insulator samples. The proton microbeam suffered significant deflection towards the sample surface due to the image acceleration when using conductor material. In case of the glass and Polytetrafluoroethylene plates the beam was deflected into the opposite direction, and the incident protons did not suffer significant energy loss, which is the consequence of the guiding effect.

Optimization of testing parameters are the prerequisite for laser induced breakdown spectroscopy (LIBS) further data analysis, which can offer important reference value for the soil detection in the field. This work investigated the influence of the main testing parameters laser energy (LE), delay time (DT), and lens to sample distance (LTSD) of LIBS system. Based on the spectral characteristic of main elements in soils, the testing parameters of LIBS for soil detection were obtained and verified. The optimization analysis of three testing parameters LE (50–160 mJ), DT (0.5–4.5 μs), and LTSD (94–102 mm) were conducted by response surface methodology (RSM). Central composite design (CCD) in RSM was introduced to carry out experimental runs. The combined signal-background-ratio (SBR) of characteristic spectral lines from main elements (Si, Fe, Mg, Ca, Al, Na, K, etc.) in soil were defined as the objective function (named YSBR). The interaction influences among three independent variables (LE, DT, and LTSD) on soil plasma characteristics were explored and the optimized testing parameters of LIBS were summarized. Results revealed as follows: the factor LE showed a remarkable linear effect to YSBR, and factors DT and LTSD exhibited opposite results. The interactive items of three factors displayed a non-significant relationship. Meanwhile, the quadratic items of LE2, DT2 and LTSD2 offered significant surface relationships. Through the RSM analysis, the optimized testing parameters for LIBS soil detection were LE: 103.09 mJ; DT: 2.92 μs; LTSD: 97.69 mm; and a peak value YSBR of 198.60. After that, the LIBS data of 21 representative soil samples were collected under the optimized LIBS testing parameters. Partial least squares regression (PLSR) was introduced to predict the main elemental contents. Results indicated that PLSR models offered promising outputs for predicting the contents of Al, Ca, Fe, K, Mg, and Na in the sampled soil, which revealed that the testing parameters of LIBS optimized by RSM were available. This work provided a theoretical basis for the accurate LIBS data analysis and regarded as a technical support for the field soil LIBS testing parameters selection.

In order to improve the speed of multi-class support vector machine, based on One-versus-One SVM, the method of combining hierarchical classification is proposed which can reduce the number of classifiers during training and testing, and use the inter-class separation degree, the intra-class sample distance, and the intra-class sample distance standard deviation as the classification measures to divide the subset of binary classification and then form the binary tree structure. Finally, the 1-v-1 training is performed on the subclasses respectively. Experiments show that compared with the traditional 1-v-1 SVM, this method can effectively shorten the time required for classification and reduce the influence of error accumulation of H-SVMs.

Currently, single factor experiments are used in most of the traditional materials preparation without considering the interaction of the various process factors. Plackett-Burman (PB) design and central composite design (CCD) were applied to optimize eight factors for the silica (SiOx) films deposited by RF magnetron sputtering. The results show that the three key factors, RF power density, work pressure and target sample distance are significant to prepare (SiOx) films using PB design, in which the deposition rate is regarded as the target response. By CCD design and response surface analysis, the optimal deposition conditions are 3.72W/cm2, work pressure 0.7Pa, target substrate distance 6cm, and deposition rate is 3.5nm/min.

Today's automotive college students will shape the future of the automobile industry. The success of college-level automotive programs has long been dependent on the students' ability to participate in hands-on classroom based interactions. In this article, distance learning and how it can be used to teach automotive management skills, as well as why it is important for students to learn from places such as home or work, are discussed. Distance learning, an increasingly popular trend of content delivery, requires teachers to take on multiple roles. In addition to responding to individual students, facilitators moderate discussions and manage the flow of content through activities and assessments. To help understand how distance learning might be used to teach automotive management skills, and to provide an opportunity for automotive students to learn these vital skills in non-traditional settings, a sample distance education course for the automotive department at Farmingdale State College has been developed. The project has taken into account many areas of related research in cognitive learning patterns of college students with regard to distance education and traditional automotive skill building courses.

The effect of conveyor speed, test sample size, antenna to sample distance, antenna polarization and ideal tag location in relation to the coupling capabilities of ultra-high frequency radio frequency identification on optimal reader antenna placement were studied. The influence of each individual factor and its interaction was determined using the general linear model analysis of variance. In decreasing order of significance of the variables tested were sample type (F = 4174.40, p < 0.0005), smaller samples preferred for coupling; distance (F = 863.83, p < 0.0005), where distance between sample and antenna should be kept to a minimum; inlay design (F = 167.82, p < 0.0005), where AD-612 preformed best due to its large antenna area; and reader antenna polarization (F = 149.64, p < 0.0005), where circular polarization preformed better yet comparative advantage decreased with distance. A reader antenna offset of 95 mm, while not significant, (F = 1.73, p = 0.188) tended to decrease coupling capabilities of the system despite increasing the zone of influence. Ideal tag location on sample was found to be on the right, back and front face with y-orientation proving superior than either x or z. A 190-mm centre–to-centre reader antenna offset resulted in a decrease in the average tag detection rate from 62 to 49% highlighting the importance of optimal reader antenna placement which needs to be confirmed if a similar result is to be obtained when a large number of tags are interrogated simultaneously. Copyright © 2010 John Wiley & Sons, Ltd.

Pulsed UV-light is a novel technology that can be used for effective inactivation of pathogens. In this study, efficacy of pulsed UV-light (100 to 1100 nm) was investigated for the inactivation of Staphylococcus aureus (ATCC 25923) in milk and milk foam, due to its pathogenic effect in milk and milk products. Static cell suspensions of 12, 30, or 48 mL in milk were treated under pulsed UV-light for 30, 105, or 180 s at various distances (8, 10.5, and 13 cm for milk, and 5, 8, and 11 cm for milk foam). Reductions varied from 0.16 to 8.55 log10 CFU/mL, demonstrating the ability of pulsed UV-light to inactivate S. aureus. Complete inactivation was obtained at: (1) 8 cm sample distance from the quartz window of the UV-light source, 30 mL sample volume, and 180 s time combination; and (2) 10.5 cm sample distance, 12 mL sample volume, and 180 s treatment time combination. Reductions up to 6.61 ±0.11 log10 CFU/g were obtained in milk foam for various treatment conditions. It was noted that there was a significant increase in the milk temperature (up to 90°C in some cases) during pulsed UV-light treatment, which might have also provided synergistic effect on microbial inactivation.

The ( 3 × 3 ) to (3 × 3) phase transition in Sn/Ge(1 1 1)-( 3 × 3 )R30° and Sn/Si(1 1 1)-( 3 × 3 )R30° systems was investigated for the first time using a non-contact atomic force microscope (NC-AFM). Observations show the occurrence of the phase transition with small (3 × 3) domains on the Sn/Ge(1 1 1) surface at low temperatures of 78 and 6 K. However, no evidence was found to support the presence of the phase transition for the Sn/Si(1 1 1) system, even when the temperature was lowered to 6 K. The (3 × 3) domains present two patterns, one hexagonal and the other honeycomb, depending on the tip to sample distance.

Tip–sample interactions are at the origin of atomic resolution in non-contact atomic force microscopy (NC-AFM) but also make it difficult to understand the meaning of atomic features observed as NC-AFM images. (110) surfaces of III–V semiconductors such as GaAs or InP have relaxed (1 × 1) surfaces with both anions and cations of different dangling bond states. Since these atoms are located at the surface where an atom attached to the tip apex can reach to interact with them and show significant relaxation via tip–sample interaction, NC-AFM images of the surface are expected to strongly depend upon the atomic species or the electronic state of the topmost atom at the tip apex. We have taken a number of NC-AFM images of GaAs(110) surfaces with a Si tip by means of room-temperature ultra-high vacuum NC-AFM and categorized them into two types of image which have different tip–sample distance dependencies. In comparison with a theoretical prediction of tip–surface interaction on the GaAs(110) surface, we have found that one of these images is due to a Si atom attached to the apex which reveals the tip–sample interaction with As and Ga surface atoms as individual peaks in the NC-AFM image.

A single-passage, bimodal magnetic force microscopy technique optimized for scanning samples with arbitrary topography is discussed. A double phase-locked loop (PLL) system is used to mechanically excite a high quality factor cantilever under vacuum conditions on its first mode and via an oscillatory tip-sample potential on its second mode. The obtained second mode oscillation amplitude is then used as a proxy for the tip-sample distance, and for the control thereof. With appropriate $z$-feedback parameters two data sets reflecting the magnetic tip-sample interaction and the sample topography are simultaneously obtained., Comment: 4 Pages, 4 Figures

This paper details a method of surveying the travel behaviour and values of households within inner, middle and outer urban zones. This survey of 400 households in two North Queensland (Australia) cities provides details of 3500 urban trips, travel modes and choices linked to household location. Stratified sampling based on distance from the Central Business District shows pronounced methodological advantages. This simple and effective method shows that outer urban dwellers used about three times the amount of fuel as their more central counterparts, placing them at the vanguard of unsustainable urban travel, a great challenge for policy, developers and city planners.

The shear force damping between a tapered near-field probe and a well-cleaned glass sample depends on the humidity. A slow decay region, up to few hundred A, appeared in the onset of the damping curves as the humidity increased. This humidity-dependent interaction force is of viscous type and ∼0.1 nN. The frictional coefficient increases faster than the estimation from Newton’s law of viscosity as the probe and sample distance decreases. This is attributed to the enhancement of viscosity in thin water layer.

The effects of plate and air temperature and plate distance were studied on a plate type far infrared radiation (FIR) drier on drying rate and quality (TBA) of dehydrated shrimp. Experimental design and regression equations were derived by response surface methodology. Effect of plate distance on drying rate was not significant. Drying rate increased monotonically with increasing plate and air temperatures. The maximum TBA value occurred at plate temperature 286°C, air temperature 81°C, and plate to sample distance of 7.9cm. Both high plate with low air temperatures and low plate with high air temperatures resulted in optimum drying rate and quality. The low air temperatures are recommended for energy saving consideration.

We present a local density estimator based on first-order statistics. To estimate the density at a point, x, the original sample is divided into subsets and the average minimum sample distance to x over all such subsets is used to define the density estimate at x. The tuning parameter is thus the number of subsets instead of the typical bandwidth of kernel or histogram-based density estimators. The proposed method is similar to nearest-neighbor density estimators but it provides smoother estimates. We derive the asymptotic distribution of this minimum sample distance statistic to study globally optimal values for the number and size of the subsets. Simulations are used to illustrate and compare the convergence properties of the estimator. The results show that the method provides good estimates of a wide variety of densities without changes of the tuning parameter, and that it offers competitive convergence performance., United States. Department of Energy. Applied Mathematical Sciences Program (Award DE-FG02-08ER2585), United States. Department of Energy. Applied Mathematical Sciences Program (Award de-sc0009297)

A technique to make the detection efficiency in XRF systems less dependent on source-to-sample distance is presented. It is shown that this dependence can be made more constant within a large range of distances if a properly calculated annular mask is used. Experimental results (for Ca, Ti, V and Zr), in good agreement with the calculated ones, are presented and show that constant efficiency values within ±5% can be obtained when the sample distance varies from 3 to 12 mm. However, peak absolute efficiencies are then reduced by a factor of about five.

A method of optical distance control for an aperture-SNOM has been developed, which is especially useful for investigations at the liquid/air interface. The method is based on modulations in the transmitted light, which appear when the tip is moved toward the sample. This effect is due to interference. By tracking an extremum of the transmitted light intensity, the distance regulation is not affected by local differences in the transmission of the sample. When taking an image, during the backward scan the distance control keeps the distance between tip and sample constant. During the forward scan the feedback is switched off and the tip is further moved toward the sample, to bring it into the near-field region. Since the feedback is not active at all times, the proposed method is suitable only for flat samples. Images of a solid test specimen, obtained by applying optical distance control are presented in this communication.