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Sample records for ground cottonseed kernels

  1. Mapping of quantitative trait loci for oil content in cottonseed kernel.

    Science.gov (United States)

    Alfred, Quampah; Liu, Hai Ying; Xu, Hai Ming; Li, Jin Rong; Wu, Jian Guo; Zhu, Shui Jin; Shi, Chun Hai

    2012-01-01

    Oil content in cottonseed is a major quality trait which when improved through breeding could enhance the competitiveness of cottonseed oil among other vegetable oils. Cottonseed oil content is a quantitative trait controlled by genes in the tetraploid embryo and tetraploid maternal plant genomes, and the knowledge of quantitative trait loci (QTLs) and the genetic effects related to oil content in both genomes could facilitate the improvement in its quality and quantity. However, till date, QTL mapping and genetic analysis related to this trait in cotton have only been conducted in the tetraploid embryo genome. In the current experiment, an IF(2) population of cottonseed kernels from the random crossing of 188 intraspecific recombinant inbred lines which were derived from the hybrid of two parents, HS46 and MARCABUCAG8US-1-88, were used to simultaneously locate QTLs for oil content in the embryo and maternal plant genomes. The four QTLs found to be associated with oil content in cottonseed were: qOC-18-1 on chromosome 18; qOC-LG-11 on linkage group 11; qOC-18-2 on chromosome 18; and qOC-22 on chromosome 22. At a high selection threshold of 0.05, there was strong evidence linking the QTLs above the oil content in cottonseed. Embryo additive and dominant effects from the tetraploid embryo genome, as well as maternal additive effects from the tetraploid maternal plant genome were found to be significant contributors to genetic variation in cottonseed oil content.

  2. Mapping of quantitative trait loci for oil content in cottonseed kernel

    Indian Academy of Sciences (India)

    Quampah Alfred; Hai Ying Liu; Hai Ming Xu; Jin Rong Li; Jian Guo Wu; Shui Jin Zhu; Chun Hai Shi

    2012-12-01

    Oil content in cottonseed is a major quality trait which when improved through breeding could enhance the competitiveness of cottonseed oil among other vegetable oils. Cottonseed oil content is a quantitative trait controlled by genes in the tetraploid embryo and tetraploid maternal plant genomes, and the knowledge of quantitative trait loci (QTLs) and the genetic effects related to oil content in both genomes could facilitate the improvement in its quality and quantity. However, till date, QTL mapping and genetic analysis related to this trait in cotton have only been conducted in the tetraploid embryo genome. In the current experiment, an IF2 population of cottonseed kernels from the random crossing of 188 intraspecific recombinant inbred lines which were derived from the hybrid of two parents, HS46 and MARCABUCAG8US-1-88, were used to simultaneously locate QTLs for oil content in the embryo and maternal plant genomes. The four QTLs found to be associated with oil content in cottonseed were: qOC-18-1 on chromosome 18; qOC-LG-11 on linkage group 11; qOC-18-2 on chromosome 18; and qOC-22 on chromosome 22. At a high selection threshold of 0.05, there was strong evidence linking the QTLs above the oil content in cottonseed. Embryo additive and dominant effects from the tetraploid embryo genome, as well as maternal additive effects from the tetraploid maternal plant genome were found to be significant contributors to genetic variation in cottonseed oil content.

  3. The Palomar Kernel Phase Experiment: Testing Kernel Phase Interferometry for Ground-based Astronomical Observations

    CERN Document Server

    Pope, Benjamin; Hinkley, Sasha; Ireland, Michael J; Greenbaum, Alexandra; Latyshev, Alexey; Monnier, John D; Martinache, Frantz

    2015-01-01

    At present, the principal limitation on the resolution and contrast of astronomical imaging instruments comes from aberrations in the optical path, which may be imposed by the Earth's turbulent atmosphere or by variations in the alignment and shape of the telescope optics. These errors can be corrected physically, with active and adaptive optics, and in post-processing of the resulting image. A recently-developed adaptive optics post-processing technique, called kernel phase interferometry, uses linear combinations of phases that are self-calibrating with respect to small errors, with the goal of constructing observables that are robust against the residual optical aberrations in otherwise well-corrected imaging systems. Here we present a direct comparison between kernel phase and the more established competing techniques, aperture masking interferometry, point spread function (PSF) fitting and bispectral analysis. We resolve the alpha Ophiuchi binary system near periastron, using the Palomar 200-Inch Telesco...

  4. Multiple Kernel Learning for Explosive Hazard Detection in Forward-Looking Ground-Penetrating Radar

    Science.gov (United States)

    2012-04-01

    34Feature analysis for the NIITEK ground penetrating radar using order weighted averaging operators for landmine detection", Proc. SPIE 5415, 953-962...This paper proposes an effective anomaly detection algorithm for forward-looking ground - penetrating radar (FLGPR). The challenges in detecting...TERMS explosive hazards detection, ground - penetrating radar , false alarm rejection, multiple kernel learning, feature-level fusion Timothy C. Havens

  5. Multiple kernel learning for explosive hazard detection in forward-looking ground-penetrating radar

    Science.gov (United States)

    Havens, Timothy C.; Stone, Kevin; Anderson, Derek T.; Keller, James M.; Ho, K. C.; Ton, Tuan T.; Wong, David C.; Soumekh, Mehrdad

    2012-06-01

    This paper proposes an effective anomaly detection algorithm for forward-looking ground-penetrating radar (FLGPR). The challenges in detecting explosive hazards with FLGPR are that there are multiple types of targets buried at different depths in a highly-cluttered environment. A wide array of target and clutter signatures exist, which makes classifier design difficult. Recent work in this application has focused on fusing the classifier results from multiple frequency subband images. Each sub-band classifier is trained on suites of image features, such as histogram of oriented gradients (HOG) and local binary patterns (LBP). This prior work fused the sub-band classifiers by, first, choosing the top-ranked feature at each frequency sub-band in the training data and then accumulating the sub-band results in a confidence map. We extend this idea by employing multiple kernel learning (MKL) for feature-level fusion. MKL fuses multiple sources of information and/or kernels by learning the weights of a convex combination of kernel matrices. With this method, we are able to utilize an entire suite of features for anomaly detection, not just the top-ranked feature. Using FLGPR data collected at a US Army test site, we show that classifiers trained using MKL show better explosive hazard detection capabilities than single-kernel methods.

  6. Replacing cottonseed meal with ground Prosopis juliflora pods; effect on intake, weight gain and carcass parameters of Afar sheep fed pasture hay basal diet.

    Science.gov (United States)

    Yasin, Mohammed; Animut, Getachew

    2014-08-01

    The experiment was conducted to determine the supplementary feeding value of ground Prosopis juliflora pod (Pjp) and cottonseed meal (CSM) and their mixtures on feed intake, body weight gain and carcass parameters of Afar sheep fed a basal diet of pasture hay. Twenty-five yearling fat-tailed Afar rams with mean initial live weight 17.24 ± 1.76 kg (mean ± SD) were used in a randomized complete block design. Animals were blocked on their initial body weight. The experiment was conducted for 12 weeks and carcass evaluation followed. Treatments were hay alone ad libitum (T 1) or with 300 g CSM (T 2), 300 g Pjp (T 5), 2:1 ratio (T 3) and 1:2 ratio of CSM : Pjp (T 4). The CP contents of the hay, CSM and Pjp were 10.5, 44.5 and 16.7 %, respectively. Hay DM intake was higher (P < 0.05) for non-supplemented and total DM intake was lower in non-supplemented. Average daily weight gain (ADG) was lower (P < 0.05) for T 1 compared to all supplemented treatments except T 5. Hot carcass weight and rib-eye muscle area also followed the same trend like that of ADG. Compared with feeding hay alone, supplementing with CSM or a mixture of CSM and Pjp appeared to be a better feeding strategy, biologically, for yearling Afar rams.

  7. 7 CFR 319.8-6 - Cottonseed cake and cottonseed meal.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 5 2010-01-01 2010-01-01 false Cottonseed cake and cottonseed meal. 319.8-6 Section... of Importation and Entry of Cotton and Covers § 319.8-6 Cottonseed cake and cottonseed meal. Entry of cottonseed cake and cottonseed meal will be authorized through any port at which the services of an...

  8. Final report on the safety assessment of Hydrogenated Cottonseed Oil, Cottonseed (Gossypium) Oil, Cottonseed Acid, Cottonseed Glyceride, and Hydrogenated Cottonseed Glyceride.

    Science.gov (United States)

    2001-01-01

    Hydrogenated Cottonseed Oil, Cottonseed (Gossypium) Oil, Cottonseed Acid, Cottonseed Glyceride, and Hydrogenated Cottonseed Glyceride are cosmetic ingredients derived from Cottonseed Oil and used as skin-conditioning agents and surfactants. Nonoils known to be toxic that may be found in cottonseed oils include gossypol, aflatoxin, and cyclopropenoid fatty acids (CPFA). Toxic heavy metal and/or polychlorinated biphenyl (PCB) or other pesticide contamination is also possible. Cottonseed Oil was nontoxic in acute oral toxicity studies in rats. In a short-term study, rabbits that had been fed 2% Cottonseed Oil for 7 weeks had significantly lower blood chemistry parameters (compared to wheat bran controls) and significantly more stored hepatic vitamin A (compared to rabbits fed other fats). Cottonseed Oil controls used as vehicles in two parenteral studies produced negative results. Hydrogenated Cottonseed Oil tested in formulation did not produce dermal or ocular irritation in rabbits. An oral-dose reproductive study tested up to 30% Cottonseed Oil (with 1% CPFAs) and reported no adverse effects on sexual maturity and reproductive performance of the F0 generation; changes were noted in the F1 generation but reproductive capacity was not altered. Parenteral-dose reproductive studies reported no adverse effects. Cottonseed Oil was not mutagenic. Cottonseed Oil did not induce aberrant crypt foci when given orally to mice, but in other studies, it increased the incidence of spontaneous mammary tumors in rats and mice. Mice fed 20% Hydrogenated Cottonseed Oil during induction and promotion of photocarcinogenesis had significantly lower tumor incidence compared to mice fed 20% sunflower oil. Hydrogenated Cottonseed Oil in formulation (up to approximately 21%) was neither an irritant nor sensitizer in clinical studies. Limited clinical data indicated that Cottonseed Oil does not contain allergic protein. Based on the available data, it was concluded that these ingredients may

  9. Cottonseed and cotton plant biomass

    Science.gov (United States)

    The cotton plant generates several marketable products as a result of the ginning process. The product that garners the most attention in regards to value and research efforts, is lint with cottonseed being secondary. In addition to lint and cottonseed, the plant material itself has a value that...

  10. Nitrogen fertility and irrigation effects on cottonseed composition

    Science.gov (United States)

    Cottonseed products have become a valuable secondary revenue source for cotton (Gossypium hirsutum L.) producers, but how production practices impact cottonseed composition is not clear. This research evaluated how cottonseed composition was altered by varying irrigation and nitrogen fertilization ...

  11. Gossypol Toxicity from Cottonseed Products

    Directory of Open Access Journals (Sweden)

    Ivana Cristina N. Gadelha

    2014-01-01

    Full Text Available Gossypol is a phenolic compound produced by pigment glands in cotton stems, leaves, seeds, and flower buds (Gossypium spp.. Cottonseed meal is a by-product of cotton that is used for animal feeding because it is rich in oil and proteins. However, gossypol toxicity limits cottonseed use in animal feed. High concentrations of free gossypol may be responsible for acute clinical signs of gossypol poisoning which include respiratory distress, impaired body weight gain, anorexia, weakness, apathy, and death after several days. However, the most common toxic effects is the impairment of male and female reproduction. Another important toxic effect of gossypol is its interference with immune function, reducing an animal’s resistance to infections and impairing the efficiency of vaccines. Preventive procedures to limit gossypol toxicity involve treatment of the cottonseed product to reduce the concentration of free gossypol with the most common treatment being exposure to heat. However, free gossypol can be released from the bound form during digestion. Agronomic selection has produced cotton varieties devoid of glands producing gossypol, but these varieties are not normally grown because they are less productive and are more vulnerable to attacks by insects.

  12. An improved device to measure cottonseed strength

    Science.gov (United States)

    During processing, seeds of cotton cultivars with fragile seeds often break and produce seed coat fragments that can cause processing problems at textile mills. A cottonseed shear tester, previously developed to measure cottonseed strength, was modified with enhancements to the drive system to provi...

  13. Feeding behavior of crossbred steers fed diets containing babassu mesocarp meal and corn in kernels or ground

    Directory of Open Access Journals (Sweden)

    Aline Evangelista Machado Santana

    2014-05-01

    Full Text Available The objective of the present study was to evaluate the effect of the use of babassu mesocarp meal (BMM and corn in different physical forms on the feeding behavior of crossbred young bulls of a dairy breed. Twenty-four crossbred (Nellore vs. Holstein steers (307.35 kg were fed four experimental diets containing two levels of inclusion of the babassu mesocarp meal (0 and 412.4 g/kg and corn in two physical forms (kernels or ground for 98 days. Data was collected on three days during the finishing phase, with observations every five minutes, for 24 hours. When the activities performed by the animals were evaluated as a function of the period of the day, the physical form of the corn showed interaction with the BMM inclusion level on the time spent feeding and on other activities. When the activities were evaluated over the day, the defecation frequency was affected and decreased as BMM was included. The feeding time was longer at the moments that followed feed supply, whereas the time used for other activities increased during the morning period, regardless of the diet utilized. Rumination and idle times were affected by the period of the day and remained high during the night and morning periods. There was increase in feeding time and dry matter rumination efficiencies and neutral detergent fiber as BMM was added to the diet. The number of rumination chews per bolus, however, decreased as BMB was included. Inclusion of babassu mesocarp meal increases the animal feeding time but the physical form of corn does not change its feeding behavior.

  14. Cogeneration of biodiesel and nontoxic cottonseed meal from cottonseed processed by two-phase solvent extraction

    Energy Technology Data Exchange (ETDEWEB)

    Qian, Junfeng [Jiangsu Provincial Key Laboratory of Fine Petrochemical Engineering, Jiangsu Polytechnic University, Changzhou 213016 (China); College of Chemistry and Chemical Engineering, Nanjing University of Technology, Nanjing 210009 (China); Yun, Zhi; Shi, Haixian [College of Chemistry and Chemical Engineering, Nanjing University of Technology, Nanjing 210009 (China)

    2010-12-15

    In the present work, the preparation of biodiesel from cottonseed oil produced by two-phase solvent extraction (TSE) was studied. The experimental results of TSE process of cottonseed showed that the optimal extraction conditions were 30 g samples, 240 mL extraction solvent mixture and methanol/petroleum ether volume ratio 60:40, extraction temperature 30 C, extraction time 30 min. Under the extraction conditions, the extraction rate of cottonseed oil could achieve 98.3%, the free fatty acid (FFA) and water contents of cottonseed oil were reduced to 0.20% and 0.037%, respectively, which met the requirement of alkali-catalyzed transesterification. The free gossypol (FG) content in cottonseed meal produced from two-phase solvent extraction could reduce to 0.014% which was far below the FAO standard. And the nontoxic cottonseed meal could be used as animal protein feed resources. After the TSE process of cottonseed, the investigations were carried out on transesterification of methanol with oil-petroleum ether solution coming from TSE process in the presence of sodium hydroxide (CaO) as the solid base catalyst. The influences of weight ratio of petroleum ether to cottonseed oil, reaction temperature, molar ratio of methanol to oil, alkali catalyst amount and reaction time on cottonseed oil conversion were respectively investigated by mono-factor experiments. The conversion of cottonseed oil into fatty acid methyl ester (FAME) could achieve 98.6% with 3:1 petroleum ether/oil weight ratio, 65 C reaction temperature, 9:1 methanol/oil mole ratio, 4% (catalyst/oil weight ratio, w/w) solid base catalyst amount and 3 h reaction time. The properties of FAME product prepared from cottonseed oil produced by two-phase solvent extraction met the ASTM specifications for biodiesel. (author)

  15. Cogeneration of biodiesel and nontoxic cottonseed meal from cottonseed processed by two-phase solvent extraction

    Energy Technology Data Exchange (ETDEWEB)

    Qian Junfeng, E-mail: qianjunfeng80@126.co [Jiangsu Provincial Key Laboratory of Fine Petrochemical Engineering, Jiangsu Polytechnic University, Changzhou 213016 (China) and College of Chemistry and Chemical Engineering, Nanjing University of Technology, Nanjing 210009 (China); Yun Zhi; Shi Haixian [College of Chemistry and Chemical Engineering, Nanjing University of Technology, Nanjing 210009 (China)

    2010-12-15

    In the present work, the preparation of biodiesel from cottonseed oil produced by two-phase solvent extraction (TSE) was studied. The experimental results of TSE process of cottonseed showed that the optimal extraction conditions were 30 g samples, 240 mL extraction solvent mixture and methanol/petroleum ether volume ratio 60:40, extraction temperature 30 deg. C, extraction time 30 min. Under the extraction conditions, the extraction rate of cottonseed oil could achieve 98.3%, the free fatty acid (FFA) and water contents of cottonseed oil were reduced to 0.20% and 0.037%, respectively, which met the requirement of alkali-catalyzed transesterification. The free gossypol (FG) content in cottonseed meal produced from two-phase solvent extraction could reduce to 0.014% which was far below the FAO standard. And the nontoxic cottonseed meal could be used as animal protein feed resources. After the TSE process of cottonseed, the investigations were carried out on transesterification of methanol with oil-petroleum ether solution coming from TSE process in the presence of sodium hydroxide (CaO) as the solid base catalyst. The influences of weight ratio of petroleum ether to cottonseed oil, reaction temperature, molar ratio of methanol to oil, alkali catalyst amount and reaction time on cottonseed oil conversion were respectively investigated by mono-factor experiments. The conversion of cottonseed oil into fatty acid methyl ester (FAME) could achieve 98.6% with 3:1 petroleum ether/oil weight ratio, 65 deg. C reaction temperature, 9:1 methanol/oil mole ratio, 4% (catalyst/oil weight ratio, w/w) solid base catalyst amount and 3 h reaction time. The properties of FAME product prepared from cottonseed oil produced by two-phase solvent extraction met the ASTM specifications for biodiesel.

  16. Comparison of the quality of cottonseed oil and cottonseed meal extracted by two solvents%两种溶剂萃取棉籽油和棉籽粕的质量比较

    Institute of Scientific and Technical Information of China (English)

    马传国; 程亚芳; 董学工; 王向坡; 仝莹莹

    2011-01-01

    The cottonseed oil and meal were obtained from the cottonseed kernel by extraction with n -hexane and isopropanol respectively. The physicochemical properties of cottonseed oil were determined, and the result showed that there were some differences in physicochemical properties between the cottonseed oil extracted by two solvents. The protein content and functional properties of the cottonseed meal were analyzed, and the crude protein content and water soluble protein content of cottonseed meal extracted by n -hexane were lower than that by isopropanol. The oil absorption,foam stability of the cottonseed meal extracted by n - hexane were' less than that by isopropanol, while the water absorption, emulsifying ' capacity, emulsion stability and foaming capacity of the former's were higher than that of the latter's. The free gossypol( FGP) content in cottonseed oil extracted by the isopropanol was higher than that by n - hexane. The FGP content of cottonseed meal extracted by isopropanol met the national standard of the limited safe use,and it was not necessary to add the detoxification process when used as the feedstuff.%利用正己烷和异丙醇作溶剂,分别萃取棉籽仁得到棉籽油和棉籽粕.对棉籽油的理化指标进行测定,结果表明两种不同溶剂萃取得到的棉籽油在理化指标上存在一定的差异.分析所得棉籽粕的蛋白含量和功能特性,结果表明正己烷萃取的棉籽粕中粗蛋白含量和水溶性蛋白含量均低于异丙醇萃取的棉籽粕;正己烷萃取的棉籽粕吸油性、泡沫稳定性小于异丙醇萃取的棉籽粕,但是吸水性、乳化性、乳化稳定性和起泡性却高于异丙醇萃取的棉籽粕.分析游离棉酚含量时,发现异丙醇萃取的棉籽油中游离棉酚(FGP)含量高于正己烷萃取的棉籽油.用异丙醇萃取的棉籽粕中FGP含量在国家标准规定的安全使用限量范围内,用作饲料时不需再增加脱毒工艺.

  17. Cottonseed oil in diets for growing broilers

    Directory of Open Access Journals (Sweden)

    Vânia de Sousa Lima Aguiar

    2016-05-01

    Full Text Available ABSTRACT The objective of this study was to evaluate the effect of three levels of crude cottonseed oil on performance, organ weights, and blood parameters of growing broilers. Carcass and cut yields after 33 and 42 days of age and the economic viability of the diets were also evaluated. Male broilers of the Ross line were distributed in a completely randomized design, in a 4 × 2 factorial arrangement (0, 2, 4, and 6% inclusion of cottonseed oil, with and without ferrous sulfate with five replicates. In the period from 22 to 33 days, quadratic and increasing linear effects were observed on feed intake and weight gain, respectively. Feed conversion during the same period was better with the addition of ferrous sulfate. The addition of ferrous sulfate caused a reduction in heart weight. From 22 to 42 days, carcass and cuts yield, organ weight, and intestine length were not influenced by the levels of oil or by the addition of ferrous sulfate. Supplementation with iron salts provided a lower red blood cell count and increased mean cell volume. Balanced diets formulated with up to 6% of crude cottonseed oil for broilers from 22-33 and 22-42 days of age do not affect their performance or the weight of their organs. Supplementation with ferrous sulfate improved feed conversion up to 33 days. Diets formulated with 4% cottonseed oil supplemented with ferrous sulfate are economically viable in the period from 22 to 42 days.

  18. [Determination of protein and gossypol content in cotton kernel powder with near infrared reflectance spectroscopy].

    Science.gov (United States)

    Qin, Li; Shen, Xiao-Jia; Chen, Jin-Hong; Zhu, Shui-Jin

    2010-03-01

    Near-infrared reflectance spectroscopy (NIRS) was used as a rapid and nondestructive method to determine the protein content and gossypol content in cotton kernel powder samples, using 49 upland cotton (Gossypium hirsutum L.) germplasms and 188 recombinant inbred lines (RILs). The cottonseed samples harvested from the upland cotton germplasms and RILs grown in different cotton growing regions in different years were analyzed chemically for protein and gossypol contents, as well as scanned in the reflectance mode of a scanning monochromator. Using ISI software for scanning and data analysis, protein and gossypol calibration equations were obtained with a standard normal variate + detrending scatter correction and a 2, 4, 4, 1 math treatment and modified partial least square (MPLS) as the regression method. The protein content calibration results revealed that the multiple correlation coefficients (RSQ) and statistic 1--variance ratio (1-VR) for the determination of protein content in cottonseed kernels were 0.933 and 0.929, respectively, and its standard error of calibration (SEC) and standard error of cross validation (SECV) were 0.623 and 0.638, respectively. As the calibration equations were judged by the calibration RSQ (or 1-VR) and SEC (or SECV), the results indicated that NIRS is comparable to chemical methods in both accuracy and prediction and is reliable in the determination of protein content in cottonseed kernels. However, the RSQ, SEC, 1-VR and SECV for gossypol content determination of NIRS were 0.836, 0.811, 0.074 and 0.079, respectively. Although it was weaker than that of protein content, the NIRS method is still good enough for the determination and prediction of the gossypol content in cottonseed kernels. Therefore, NIRS models were successfully developed for protein content and gossypol content analysis of cotton kernel powder sample in the present study and they could be introduced into the cotton germplasm evaluation and breeding program for

  19. Soy and cottonseed protein blends as wood adhesives

    Science.gov (United States)

    As an environmentally friendlier alternative to adhesives from petroleum feedstock, soy proteins are currently being formulated as wood adhesives. Cottonseed proteins have also been found to provide good adhesive properties. In at least some cases, cottonseed proteins appear to form greater shear ...

  20. Hydrogenated cottonseed oil as raw material for biobased materials

    Science.gov (United States)

    There has been a lot of recent interest in using vegetable oils as biodegradable and renewable raw materials for the syntheses of various biobased materials. Although most of the attention has been paid to soybean oil thus far, cottonseed oil is a viable alternative. An advantage of cottonseed oil...

  1. Urea modified cottonseed protein adhesive for wood composite products

    Science.gov (United States)

    Cottonseed protein has the potential to be used as renewable and environmentally friendly adhesives in wood products industry. However, the industry application was limited by its low mechanical properties, low water resistance and viscosity. In this work, urea modified cottonseed protein adhesive w...

  2. Fractionation of cottonseed flour for improving its adhesive properties

    Science.gov (United States)

    As early as the 1950's, cottonseed flour (i. e. meal) was tested for use as wood adhesives. Recently, renewed interest exists in the use of plant proteins as wood adhesives, as these materials are renewable and biodegradable. In this research, we separated cottonseed flour into several fractions wit...

  3. Extraction and Characterization of Cottonseed (Gossypium Oil

    Directory of Open Access Journals (Sweden)

    Efomah Andrew Ndudi

    2012-10-01

    Full Text Available This study investigated the extraction and characterization of cottonseed oil using solvent extraction method. Normal hexane was used as solvent in the extraction process. The AOAC method of Analysis was employed in the determination of the chemical, physical and proximate compositions of the oil. The chemical properties of the oil determined include the saponification value, free fatty acid, iodine value, peroxide value and acid value. The physical properties of the oil determined are viscosity, specific gravity, refractive index, color, odor, taste and pH. The values obtained are Saponification value (189mgKOH/g, free fatty acid (5.75mgKOH/g, iodine value (94.7gI/100g, peroxide value (9.25mEq/kg and acid value (11.50mgKOH/g. The proximate compositions obtained are Carbohydrate (57.06%, lipid/fat (13.30%, crude fiber (0.5%, ash (1.5%, moisture content (7.21%, and crude protein (15.40%. The oil yield was 15.05%. From the results obtained it can be seen that cottonseed oil has great potential for use as domestic and industrial oil.

  4. Investigation of modified cottonseed protein adhesives for wood composites

    Science.gov (United States)

    Several modified cottonseed protein isolates were studied and compared to corresponding soy protein isolates for their adhesive properties when bonded to wood composites. Modifications included treatments with alkali, guanidine hydrochloride, sodium dodecyl sulfate (SDS), and urea. Wood composites...

  5. Performance of lactating dairy cows fed whole cottonseed coated with gelatinized cornstarch.

    Science.gov (United States)

    Bernard, J K

    1999-06-01

    The handling characteristics of whole cottonseed are improved by coating with gelatinized cornstarch, but limited information is available on the effects of feeding the coated cottonseed to lactating dairy cows. Thirty-six lactating Jersey cows were used in a crossover design trial with 4-wk experimental periods to evaluate the influence of coating whole cottonseed with 2.5% gelatinized cornstarch on dry matter intake, milk yield, and composition. Cows were fed diets containing 10.2% alfalfa-orchardgrass hay, 45.2% corn silage, 15.0% coated or uncoated whole cottonseed, and 29.6% concentrate for ad libitum consumption. Coating whole cottonseed with gelatinized cornstarch tended to reduce dry matter intake, which averaged 16.2 and 15.9 kg/d for uncoated and coated cottonseed, respectively. Milk yield and composition were similar for uncoated and coated cottonseed. The yield of energy-corrected milk per unit of dry matter consumed was greater with coated cottonseed. Cows fed coated cottonseed gained body weight, but cows fed uncoated cottonseed lost weight. Concentrations of plasma urea were similar among treatments; however, NEFA concentrations were lower for cows fed coated whole cottonseed. Results of this trial indicate that coating whole cottonseed with 2.5% gelatinized cornstarch does not alter its feeding value for lactating dairy cows.

  6. Fermentation of cottonseed and other feedstuffs in cattle rumen fluid.

    Science.gov (United States)

    Schneider, Ian C; Ames, Michael L; Rasmussen, Mark A; Reilly, Peter J

    2002-04-10

    Bovine rumen fluid was fermented anaerobically over 48 h with cottonseed, corn, alfalfa, or a mixture of these substrates in anaerobic mineral buffer. Samples taken at different incubation times were derivatized with n-butanol and subjected to gas chromatography and mass spectroscopy. No unusual fermentation end-products from the cottonseed substrate were detected. Cottonseed supported rumen fermentation at levels comparable to those of the other substrates. Major components were usually found in the decreasing order of acetate, propionate, butyrate, and valerate, although acetate and propionate concentrations decreased late in the alfalfa and mixed-feed fermentations, eventually allowing butyrate concentrations to exceed those of propionate. As expected, lactate was produced in high concentrations when corn was fermented. The minor components 2-methylpropionate, 2- and 3-methylbutyrate, phenylacetate, phenylpropionate, and caproate also accumulated, with their relative concentrations varying with the substrate. Succinate was produced in substantial amounts only when corn and alfalfa were fermented; it did not accumulate when cottonseed was the substrate. Samples containing cottonseed were derivatized and subjected to reversed-phase high-performance liquid chromatography, revealing that gossypol concentrations did not change during fermentation.

  7. Kinetics and thermodynamics of cottonseed oil extraction

    Energy Technology Data Exchange (ETDEWEB)

    Saxena, D. K.; Sharma, S. K.

    2011-07-01

    Petroleum derived n-hexane is commercially used in solvent extraction plants due to its higher extraction efficiency in spite of the fact that it is graded as highly toxic and hazardous. The present study is based on the use of both a much safer and non toxic solvent ethanol and n-hexane for the extraction of oil from cottonseed. The extraction data were obtained by varying temperature, solvent-solid ratio and particle size, to compare the extraction efficiency of both ethanol and n-hexane. The data show that nearly the same amount of extraction is possible at a higher solvent-solid ratio for both the solvents. This study has established that the kinetics of oil extraction follows a second order reaction mechanism. The thermodynamic analysis of the data shows that both .{delta}H degree centigrade and {delta}G degree centigrade are positive, and {delta}G degree centigrade is negative indicating that the extraction process is endothermic, irreversible, and spontaneous. (Author) 41 refs.

  8. Statement on the presence of free gossypol in whole cottonseed

    DEFF Research Database (Denmark)

    Petersen, Annette

    The European Commission asked EFSA to assess information provided by the Spanish Ministry of Agriculture, Food and Environment, on the toxicity of free gossypol in relation to the use of whole cotton seed in feed for ruminants, in particular dairy cows, and, if necessary, to update the previous...... opinion of the EFSA Panel on Contaminants in the Food Chain (CONTAM) on gossypol as an undesirable substance in animal feed. Gossypol is a polyphenolic compound that exists in a racemic mixture of (+)-gossypol and (-)-gossypol isomers. It occurs in free or (protein-) bound forms in cottonseeds. The most...... commonly used cottonseeds in feed are from Upland and Pima varieties. The Pima variety is considered more toxic due to a higher content of the (-)-gossypol isomer. Upland whole cottonseeds (WCS) are fed with no further processing (after delinting); Pima varieties normally undergo further processing...

  9. Effect of Bt-cottonseed meal feeding on performance, fermentation ...

    African Journals Online (AJOL)

    MKTripati

    2014-01-15

    Jan 15, 2014 ... Effect of the Bt- or conventional cottonseed meal was assessed as well as the performance, ... Using advanced molecular ... procedure of 100 ml glass syringe was used for in-vitro ... temperature conditions of gas measurement in our laboratory. After the 24 h ...... Feeding standards for Australian livestock.

  10. 21 CFR 173.322 - Chemicals used in delinting cottonseed.

    Science.gov (United States)

    2010-04-01

    ... by condensation of coconut oil fatty acids and dietha-nolamine, CAS Reg. No. 068603-42-9 May be used... (CONTINUED) FOOD FOR HUMAN CONSUMPTION (CONTINUED) SECONDARY DIRECT FOOD ADDITIVES PERMITTED IN FOOD FOR HUMAN CONSUMPTION Specific Usage Additives § 173.322 Chemicals used in delinting cottonseed....

  11. Hydrogenation of cottonseed oil with nickel, palladium and platinum catalysts

    Science.gov (United States)

    A number of commercial catalysts have been used to study hydrogenation of cottonseed oil, with the goal of minimizing trans fatty acid (TFA) content. Despite the different temperatures used, catalyst levels, and reaction times, the data from each catalyst type fall on the same curve when the TFA le...

  12. Subsampling Realised Kernels

    DEFF Research Database (Denmark)

    Barndorff-Nielsen, Ole Eiler; Hansen, Peter Reinhard; Lunde, Asger

    2011-01-01

    In a recent paper we have introduced the class of realised kernel estimators of the increments of quadratic variation in the presence of noise. We showed that this estimator is consistent and derived its limit distribution under various assumptions on the kernel weights. In this paper we extend our...... analysis, looking at the class of subsampled realised kernels and we derive the limit theory for this class of estimators. We find that subsampling is highly advantageous for estimators based on discontinuous kernels, such as the truncated kernel. For kinked kernels, such as the Bartlett kernel, we show...... that subsampling is impotent, in the sense that subsampling has no effect on the asymptotic distribution. Perhaps surprisingly, for the efficient smooth kernels, such as the Parzen kernel, we show that subsampling is harmful as it increases the asymptotic variance. We also study the performance of subsampled...

  13. Kinetics and thermodynamics of cottonseed oil extraction

    Directory of Open Access Journals (Sweden)

    Saxena, Devesh K.

    2011-06-01

    Full Text Available Petroleum derived n-hexane is commercially used in solvent extraction plants due to its higher extraction efficiency in spite of the fact that it is graded as highly toxic and hazardous. The present study is based on the use of both a much safer and non toxic solvent ethanol and n-hexane for the extraction of oil from cottonseed. The extraction data were obtained by varying temperature, solvent-solid ratio and particle size, to compare the extraction efficiency of both ethanol and n-hexane. The data show that nearly the same amount of extraction is possible at a higher solvent-solid ratio for both the solvents. This study has established that the kinetics of oil extraction follows a second order reaction mechanism. The thermodynamic analysis of the data shows that both ΔHº and ΔSº are positive, and ΔGº is negative indicating that the extraction process is endothermic, irreversible, and spontaneous.

    El n-hexano derivado del petróleo es comercialmente usado en plantas de extracción con disolventes debido a su mayor eficiencia de extracción, a pesar de que está calificado como altamente tóxico y peligroso. El presente estudio está basado en el uso de etanol, disolvente mucho más seguros y no tóxico, y n-hexano en la extracción de aceite de algodón. Los datos de extracción fueron obtenidos variando la temperatura, la proporción sólido-disolvente y el tamaño de partícula, para comparar la eficiencia de extracción del etanol y del hexano. Los datos muestran que casi la misma cantidad de extracción es posible para ambos disolventes a la proporción más alta de sólido-disolvente. Este estudio es capaz de establecer que las cinéticas de extracción de aceite siguen un mecanismo de reacción de segundo orden. El análisis termodinámico de los datos mostró que ΔHº and ΔSº son positivas, y ΔGº es negativa, indicando que el proceso de extracción es endotérmico, irreversible y espontáneo.

  14. Robust Kernel (Cross-) Covariance Operators in Reproducing Kernel Hilbert Space toward Kernel Methods

    OpenAIRE

    Alam, Md. Ashad; Fukumizu, Kenji; Wang, Yu-Ping

    2016-01-01

    To the best of our knowledge, there are no general well-founded robust methods for statistical unsupervised learning. Most of the unsupervised methods explicitly or implicitly depend on the kernel covariance operator (kernel CO) or kernel cross-covariance operator (kernel CCO). They are sensitive to contaminated data, even when using bounded positive definite kernels. First, we propose robust kernel covariance operator (robust kernel CO) and robust kernel crosscovariance operator (robust kern...

  15. Nonextensive Entropic Kernels

    Science.gov (United States)

    2008-08-01

    Berg et al., 1984] has been used in a machine learning context by Cuturi and Vert [2005]. Definition 26 Let (X ,+) be a semigroup .2 A function ϕ : X...R is called pd (in the semigroup sense) if k : X × X → R, defined as k(x, y) = ϕ(x + y), is a pd kernel. Likewise, ϕ is called nd if k is a nd...kernel. Accordingly, these are called semigroup kernels. 7.3 Jensen-Shannon and Tsallis kernels The basic result that allows deriving pd kernels based on

  16. Bimetal Adsorption by Cottonseed Carbon: Equlibrium and Kinetic Studies

    Directory of Open Access Journals (Sweden)

    K. Srinivasan

    2009-01-01

    Full Text Available The simultaneous adsorption of Pb(II and Hg(II on cottonseed carbon (CSC was employed for the removal of these metals from wastewater. The influence of various factors such as agitation time, pH and carbon dosage on the adsorption capacity has been studied. Langmuir and Freundlich equation could be used to interpret adsorption data. Sorption kinetics has indicated that reversible first order kinetics model could be applied with film diffusion as the controlling mechanism.

  17. Reduced terpene levels in cottonseed add food to fiber.

    Science.gov (United States)

    Townsend, Belinda J; Llewellyn, Danny J

    2007-06-01

    Using RNA interference (RNAi) technology, the levels of a toxic phytoprotectant have recently been reduced specifically in the seeds of cotton to generate a novel dual-purpose crop. By engineering an endogenous terpene pathway, there is now the exciting potential for an added-value, genetically modified crop with the cash value of the fiber supported by the improved nutritional value and expanded food and feed use for the cottonseed, which is normally a low-value by-product.

  18. Approximate kernel competitive learning.

    Science.gov (United States)

    Wu, Jian-Sheng; Zheng, Wei-Shi; Lai, Jian-Huang

    2015-03-01

    Kernel competitive learning has been successfully used to achieve robust clustering. However, kernel competitive learning (KCL) is not scalable for large scale data processing, because (1) it has to calculate and store the full kernel matrix that is too large to be calculated and kept in the memory and (2) it cannot be computed in parallel. In this paper we develop a framework of approximate kernel competitive learning for processing large scale dataset. The proposed framework consists of two parts. First, it derives an approximate kernel competitive learning (AKCL), which learns kernel competitive learning in a subspace via sampling. We provide solid theoretical analysis on why the proposed approximation modelling would work for kernel competitive learning, and furthermore, we show that the computational complexity of AKCL is largely reduced. Second, we propose a pseudo-parallelled approximate kernel competitive learning (PAKCL) based on a set-based kernel competitive learning strategy, which overcomes the obstacle of using parallel programming in kernel competitive learning and significantly accelerates the approximate kernel competitive learning for large scale clustering. The empirical evaluation on publicly available datasets shows that the proposed AKCL and PAKCL can perform comparably as KCL, with a large reduction on computational cost. Also, the proposed methods achieve more effective clustering performance in terms of clustering precision against related approximate clustering approaches.

  19. Use of additives to enhance the properties of cottonseed protein as wood adhesives

    Science.gov (United States)

    Soy protein is currently being used commercially as a “green” wood adhesive. Previous work in this laboratory has shown that cottonseed protein isolate, tested on maple wood veneer, produced higher adhesive strength and hot water resistance relative to soy protein. In the present study, cottonseed...

  20. Sequential fractionation of cottonseed meal to improve its wood adhesive properties

    Science.gov (United States)

    To find a more environment-friendly and cost effective means to prepare cottonseed protein-based wood adhesives, cottonseed flours (i.e., defatted meals) were separated into several fractions. Flours from both glanded and glandless cotton varieties were used. The flour was extracted first with wat...

  1. Oven-drying reduces ruminal starch degradation in maize kernels

    NARCIS (Netherlands)

    Ali, M.; Cone, J.W.; Hendriks, W.H.; Struik, P.C.

    2014-01-01

    The degradation of starch largely determines the feeding value of maize (Zea mays L.) for dairy cows. Normally, maize kernels are dried and ground before chemical analysis and determining degradation characteristics, whereas cows eat and digest fresh material. Drying the moist maize kernels (consist

  2. Oven-drying reduces ruminal starch degradation in maize kernels

    NARCIS (Netherlands)

    Ali, M.; Cone, J.W.; Hendriks, W.H.; Struik, P.C.

    2014-01-01

    The degradation of starch largely determines the feeding value of maize (Zea mays L.) for dairy cows. Normally, maize kernels are dried and ground before chemical analysis and determining degradation characteristics, whereas cows eat and digest fresh material. Drying the moist maize kernels

  3. Optimized Kernel Entropy Components.

    Science.gov (United States)

    Izquierdo-Verdiguier, Emma; Laparra, Valero; Jenssen, Robert; Gomez-Chova, Luis; Camps-Valls, Gustau

    2016-02-25

    This brief addresses two main issues of the standard kernel entropy component analysis (KECA) algorithm: the optimization of the kernel decomposition and the optimization of the Gaussian kernel parameter. KECA roughly reduces to a sorting of the importance of kernel eigenvectors by entropy instead of variance, as in the kernel principal components analysis. In this brief, we propose an extension of the KECA method, named optimized KECA (OKECA), that directly extracts the optimal features retaining most of the data entropy by means of compacting the information in very few features (often in just one or two). The proposed method produces features which have higher expressive power. In particular, it is based on the independent component analysis framework, and introduces an extra rotation to the eigen decomposition, which is optimized via gradient-ascent search. This maximum entropy preservation suggests that OKECA features are more efficient than KECA features for density estimation. In addition, a critical issue in both the methods is the selection of the kernel parameter, since it critically affects the resulting performance. Here, we analyze the most common kernel length-scale selection criteria. The results of both the methods are illustrated in different synthetic and real problems. Results show that OKECA returns projections with more expressive power than KECA, the most successful rule for estimating the kernel parameter is based on maximum likelihood, and OKECA is more robust to the selection of the length-scale parameter in kernel density estimation.

  4. Some analytical characters of cottonseed varieties grown in Turkey

    Directory of Open Access Journals (Sweden)

    Nergiz, Cevdet

    1997-12-01

    Full Text Available Sixteen cottonseed varieties grown in Turkey were analysed. The average oil content in varieties ranged from 309.7g Kg-1 to 379.5g Kg-1 whereas the range in values of gossypol content for glanded varieties was 7.4-12.8g Kg-1. One glandless variety contained gossypol as 0.2g Kg-1. The samples contained 337.2- 466.5g Kg-1 protein. Fatty acid composition of the oils obtained from cottonseed varieties were also determined. Generally total gossypol content of cottonseed varieties were below the limits established by the some nations for human food or animal feed.

    Se han analizado dieciséis variedades de semillas de algodón cultivadas en Turquía. El contenido medio de aceite en las distintas variedades osciló entre 309,7g Kg-1 y 379,5g Kg-1 mientras que el contenido en gosipol para variedades con glándulas fue desde 7,4 a 12,8g Kg-1. Una variedad sin glándula tuvo un valor en gosipol de 0, Kg-1. El valor en proteínas de las muestras osciló entre 337,2 y 466,5g Kg-1. También se determinó la composición en ácidos grasos de los aceites obtenidos de las distintas variedades de semilla de algodón. Por lo general el contenido total en gosipol en las distintas variedades fue inferior a los límites establecidos por algunas naciones para su consumo humano o para alimentación animal.

  5. Regularization in kernel learning

    CERN Document Server

    Mendelson, Shahar; 10.1214/09-AOS728

    2010-01-01

    Under mild assumptions on the kernel, we obtain the best known error rates in a regularized learning scenario taking place in the corresponding reproducing kernel Hilbert space (RKHS). The main novelty in the analysis is a proof that one can use a regularization term that grows significantly slower than the standard quadratic growth in the RKHS norm.

  6. Iterative software kernels

    Energy Technology Data Exchange (ETDEWEB)

    Duff, I.

    1994-12-31

    This workshop focuses on kernels for iterative software packages. Specifically, the three speakers discuss various aspects of sparse BLAS kernels. Their topics are: `Current status of user lever sparse BLAS`; Current status of the sparse BLAS toolkit`; and `Adding matrix-matrix and matrix-matrix-matrix multiply to the sparse BLAS toolkit`.

  7. Kernel Affine Projection Algorithms

    Directory of Open Access Journals (Sweden)

    José C. Príncipe

    2008-05-01

    Full Text Available The combination of the famed kernel trick and affine projection algorithms (APAs yields powerful nonlinear extensions, named collectively here, KAPA. This paper is a follow-up study of the recently introduced kernel least-mean-square algorithm (KLMS. KAPA inherits the simplicity and online nature of KLMS while reducing its gradient noise, boosting performance. More interestingly, it provides a unifying model for several neural network techniques, including kernel least-mean-square algorithms, kernel adaline, sliding-window kernel recursive-least squares (KRLS, and regularization networks. Therefore, many insights can be gained into the basic relations among them and the tradeoff between computation complexity and performance. Several simulations illustrate its wide applicability.

  8. Kernel Affine Projection Algorithms

    Science.gov (United States)

    Liu, Weifeng; Príncipe, José C.

    2008-12-01

    The combination of the famed kernel trick and affine projection algorithms (APAs) yields powerful nonlinear extensions, named collectively here, KAPA. This paper is a follow-up study of the recently introduced kernel least-mean-square algorithm (KLMS). KAPA inherits the simplicity and online nature of KLMS while reducing its gradient noise, boosting performance. More interestingly, it provides a unifying model for several neural network techniques, including kernel least-mean-square algorithms, kernel adaline, sliding-window kernel recursive-least squares (KRLS), and regularization networks. Therefore, many insights can be gained into the basic relations among them and the tradeoff between computation complexity and performance. Several simulations illustrate its wide applicability.

  9. Design and Implementation of the Connectionless Network Protocol (CLNP) as Loadable Kernel Modules in Linux Kernel 2.6

    CERN Document Server

    Sugiarto, Bunga; Rizal, Arra'di Nur; Galinium, Maulahikmah; Atmadiputra, Pradana; Rubianto, Melvin; Fahmi, Husni; Sampurno, Tri; Kisworo, Marsudi

    2012-01-01

    In this paper, we present an implementation of CLNP ground-to-ground packet processing for ATN in Linux kernel version 2.6. We present the big picture of CLNP packet processing, the details of input, routing, and output processing functions, and the implementation of each function based on ISO 8473-1. The functions implemented in this work are PDU header decomposition, header format analysis, header error detection, error reporting, reassembly, source routing, congestion notification, forwarding, composition, segmentation, and transmit to device functions. Each function is initially implemented and tested as a separated loadable kernel module. These modules are successfully loaded into Linux kernel 2.6.

  10. Synthesis of vegetable oil based polyol with cottonseed oil and sorbitol derived from natural source

    Institute of Scientific and Technical Information of China (English)

    Lian Kun Jia; Li Xiang Gong; Wen Jiao Ji; Cheng You Kan

    2011-01-01

    In order to prepare the polyol with all bio-based components as raw materials, cottonseed oil was first epoxidized by peroxyformic acid generated in situ from hydrogen peroxide and formic acid, and the cottonseed oil based polyols with variable hydroxyl value were then prepared by the ring-opening of epoxidized cottonseed oil with sorbitol, which is a multi-functional hydroxyl compound derived from a natural source. The chemical structure of the products was characterized with FTIR analysis, and the residual epoxy oxygen content and hydroxyl value of the polyol versus the ring-opening time were investigated.

  11. Kernels in circulant digraphs

    Directory of Open Access Journals (Sweden)

    R. Lakshmi

    2014-06-01

    Full Text Available A kernel $J$ of a digraph $D$ is an independent set of vertices of $D$ such that for every vertex $w,in,V(D,setminus,J$ there exists an arc from $w$ to a vertex in $J.$ In this paper, among other results, a characterization of $2$-regular circulant digraph having a kernel is obtained. This characterization is a partial solution to the following problem: Characterize circulant digraphs which have kernels; it appeared in the book {it Digraphs - theory, algorithms and applications}, Second Edition, Springer-Verlag, 2009, by J. Bang-Jensen and G. Gutin.

  12. Kernels for structured data

    CERN Document Server

    Gärtner, Thomas

    2009-01-01

    This book provides a unique treatment of an important area of machine learning and answers the question of how kernel methods can be applied to structured data. Kernel methods are a class of state-of-the-art learning algorithms that exhibit excellent learning results in several application domains. Originally, kernel methods were developed with data in mind that can easily be embedded in a Euclidean vector space. Much real-world data does not have this property but is inherently structured. An example of such data, often consulted in the book, is the (2D) graph structure of molecules formed by

  13. Locally linear approximation for Kernel methods : the Railway Kernel

    OpenAIRE

    Muñoz, Alberto; González, Javier

    2008-01-01

    In this paper we present a new kernel, the Railway Kernel, that works properly for general (nonlinear) classification problems, with the interesting property that acts locally as a linear kernel. In this way, we avoid potential problems due to the use of a general purpose kernel, like the RBF kernel, as the high dimension of the induced feature space. As a consequence, following our methodology the number of support vectors is much lower and, therefore, the generalization capability of the pr...

  14. Linux Kernel in a Nutshell

    CERN Document Server

    Kroah-Hartman, Greg

    2009-01-01

    Linux Kernel in a Nutshell covers the entire range of kernel tasks, starting with downloading the source and making sure that the kernel is in sync with the versions of the tools you need. In addition to configuration and installation steps, the book offers reference material and discussions of related topics such as control of kernel options at runtime.

  15. Data-variant kernel analysis

    CERN Document Server

    Motai, Yuichi

    2015-01-01

    Describes and discusses the variants of kernel analysis methods for data types that have been intensely studied in recent years This book covers kernel analysis topics ranging from the fundamental theory of kernel functions to its applications. The book surveys the current status, popular trends, and developments in kernel analysis studies. The author discusses multiple kernel learning algorithms and how to choose the appropriate kernels during the learning phase. Data-Variant Kernel Analysis is a new pattern analysis framework for different types of data configurations. The chapters include

  16. Mixture Density Mercer Kernels

    Data.gov (United States)

    National Aeronautics and Space Administration — We present a method of generating Mercer Kernels from an ensemble of probabilistic mixture models, where each mixture model is generated from a Bayesian mixture...

  17. Remarks on kernel Bayes' rule

    OpenAIRE

    Johno, Hisashi; Nakamoto, Kazunori; Saigo, Tatsuhiko

    2015-01-01

    Kernel Bayes' rule has been proposed as a nonparametric kernel-based method to realize Bayesian inference in reproducing kernel Hilbert spaces. However, we demonstrate both theoretically and experimentally that the prediction result by kernel Bayes' rule is in some cases unnatural. We consider that this phenomenon is in part due to the fact that the assumptions in kernel Bayes' rule do not hold in general.

  18. Linearized Kernel Dictionary Learning

    Science.gov (United States)

    Golts, Alona; Elad, Michael

    2016-06-01

    In this paper we present a new approach of incorporating kernels into dictionary learning. The kernel K-SVD algorithm (KKSVD), which has been introduced recently, shows an improvement in classification performance, with relation to its linear counterpart K-SVD. However, this algorithm requires the storage and handling of a very large kernel matrix, which leads to high computational cost, while also limiting its use to setups with small number of training examples. We address these problems by combining two ideas: first we approximate the kernel matrix using a cleverly sampled subset of its columns using the Nystr\\"{o}m method; secondly, as we wish to avoid using this matrix altogether, we decompose it by SVD to form new "virtual samples," on which any linear dictionary learning can be employed. Our method, termed "Linearized Kernel Dictionary Learning" (LKDL) can be seamlessly applied as a pre-processing stage on top of any efficient off-the-shelf dictionary learning scheme, effectively "kernelizing" it. We demonstrate the effectiveness of our method on several tasks of both supervised and unsupervised classification and show the efficiency of the proposed scheme, its easy integration and performance boosting properties.

  19. A method to refine crude cottonseed oil using non-toxic polyamine-based cationic polymers☆

    Institute of Scientific and Technical Information of China (English)

    Hailin Lin; Tom C Wedegaertner; Xiaoyun Mao; Xudong Jing; Aicardo Roa-Espinosa

    2015-01-01

    The traditional method to refine crude cottonseed oil is time-consuming and expensive. This study evaluates the effectiveness of coagulation–flocculation–sedimentation process using quaternary polyamine-based polymers in refining crude cottonseed oil. Flocculated by four commercial polyamine-based cationic polymers (SL2700, SL3000, SL4500 and SL5000) with varied molecular weight (MW) and charge density (CD) and followed by co-agulation with sodium hydroxide, crude cottonseed oil can be effectively purified. Free fatty acids, gossypol, pig-ments and trace elements are all effectively and sufficiently removed by the four polymers in a MW-and CD-dependent manner. Our results suggest that the use of polyamine-based cationic polymers may offer an effective and feasible alternative to the traditional method for crude cottonseed oil refining.

  20. Effects of feeding crude glycerin on performance and ruminal kinetics of lactating Holstein cows fed corn silage- or cottonseed hull-based, low-fiber diets.

    Science.gov (United States)

    Shin, J H; Wang, D; Kim, S C; Adesogan, A T; Staples, C R

    2012-07-01

    The objective was to determine whether crude glycerin could partially replace concentrate ingredients in corn silage- or cottonseed hull-based diets formulated to support minimal milk fat production without reducing milk production. Multiparous, lactating Holstein cows (n=24; 116 ± 13d in milk) were assigned to dietary treatments arranged in a 2 × 3 factorial design; namely, 2 dietary roughage sources (cottonseed hulls or corn silage) and 3 dietary concentrations of glycerin [0, 5, or 10% on a dry matter (DM) basis]. Four different cows received each dietary treatment in each of 3 periods such that each diet was evaluated using 12 cows. Crude glycerin, produced using soybean oil, contained 12% water, 5% oil, 6.8% sodium chloride, and 0.4% methanol. Glycerin partially replaced ground corn, corn gluten feed, and citrus pulp. Diets of minimum fiber concentrations were fed to lactating dairy cows and resulted in low concentrations of milk fat (averaging 3.12% for cows fed diets without glycerin). The effects of glycerin on cow performance and ruminal measurements were the same for both dietary roughage sources with the exception of feed efficiency. Replacing concentrate with crude glycerin at 5% of dietary DM increased DM intake without increasing milk yield. Concentration and yield of milk fat were reduced when glycerin was fed at 10% of dietary DM. This was accompanied by a 30% reduction in apparent total-tract digestion of dietary neutral detergent fiber. Crude glycerin affected the microbial population in the rumen as evidenced by increased molar proportions of propionic, butyric, and valeric acids and decreased molar proportions of acetic acid. Efficiency of N utilization was improved as evidenced by lower concentrations of blood urea nitrogen and ruminal ammonia-N. Cows fed cottonseed hull-based diets consumed 5.3 kg/d more DM but produced only 1.7 kg/d more milk, resulting in reduced efficiency. Increased production of ruminal microbial protein, molar

  1. Polymeric efficiency in remove impurities during cottonseed biodiesel production

    Science.gov (United States)

    Lin, H. L.; Liang, Y. H.; Yan, J.; Lin, H. D.; Espinosa, A. R.

    2016-07-01

    This paper describes a new process for developing biodiesel by polymer from crude cottonseed oil. The study was conducted to examine the effectiveness of the alkali transesterification-flocculation-sedimentation process on fast glycerol and other impurities in the separation from biodiesel by using quaternary polyamine-based cationic polymers SL2700 and polyacylamide cationic polymer SAL1100. The settling velocity of glycerol and other impurities in biodiesel was investigated through settling test experiments; the quality of the biodiesel was investigated by evaluating the viscosity and density. The results revealed that SL2700, SAL1100 and their combination dramatically improved the settling velocity of glycerol and other impurities materials than traditional method. SL 2700 with molecular weight of 0.2 million Da and charge density of 50% then plus SAL1100 with molecular weight of 11 million Da and charge density of 10% induced observable particle aggregation with the best settling performance.

  2. GOSSYPOL CONTENTS IN COTTONSEED CAKES COLLECTED FROM DIFFERENT DISTRICTS OF THE PUNJAB PROVINCE OF PAKISTAN

    Directory of Open Access Journals (Sweden)

    I. A. Zahid, L. A. Lodhil, Z. I. Qureshil, N. Ahmadl, N.U. Rehmanl and M. S. Akhtar2

    2003-07-01

    Full Text Available In the present study, gossypol contents of cottonseed cakes (CSC, prepared from different varieties of cotton grown in the Punjab province of Pakistan, were determined. For this purpose, cottonseed cake samples were collected from 14 districts of the Punjab including Bahawalnagar, Bahawalpur, Dera Ghazi Khan, Faisalabad, Jhang, Kasur, Khanewal, Lahore, Multan, Okara, Sahiwal, Sargodha, Toba Tek Singh and Vehari. These samples were analyzed for the free and the total gossypol contents applying American Oil Chemist Society Official Methods, Ba 7-58 and Ba 8-78, respectively. The results showed that the free and the total gossypol contents of cottonseed cakes averaged 0.28 ± 0.02 and 1.44 ± 0.04 per cent, respectively. The highest values of the free and the total gossypol contents, 0.36 ± 0.02 and 1.59 ± 0.03 per cent respectively, were recorded in cottonseed cake samples collected from Vehari district, while the lowest values, 0.21 ± 0.01 and 1.29 ± 0.01 per cent respectively, were found in those collected from Lahore district. Analysis of variance revealed significant differences (P<0.05 in the free and the total gossypol contents of cottonseed cakes among districts. It was concluded that the free and the total gossypol contents of cottonseed cakes available in different parts of the province differed significantly (P<0.05

  3. Formation of polymerization compounds during thermal oxidation of cottonseed oil, partially hydrogenated cottonseed oil and their blends

    Directory of Open Access Journals (Sweden)

    Barrera-Arellano, D. Laboratório de Óleos e Gorduras, Departa

    2006-09-01

    Full Text Available Samples of cottonseed oil, partially hydrogenated cottonseed oil and their blends, with iodine values between 60 and 110, tocopherol-stripped or not by aluminium oxide treatment, were submitted to thermal oxidation, at 180 °C, for 10 hours. Samples were collected at 0, 2, 5, 8 and 10 hours, for the determination of dimers and polymers (degradation compounds and of tocopherols. The influence of the degree of hydrogenation on the formation of dimers and polymers and the role of originally present tocopherols in the protection of fats and oils against thermal degradation was verified. The degradation curves for tocopherols showed a fast destruction rate for the tocopherols present in cottonseed fats and oil (α and γ-tocopherols, with residual levels close to zero after 10 hours under thermal oxidation conditions. Nevertheless, samples with their natural tocopherols presented a slower rate of thermal degradation. The unsaturation degree was apparently more important in the protection against thermal degradation than the content of tocopherolsMuestras de aceite de algodón, aceite de algodón parcialmente hidrogenado y sus mezclas, con índices de yodo de 60 a 110, tratadas o no con óxido de aluminio, fueron sometidas a termoxidación, a 180 °C, durante 10 horas. Se retiraron muestras en los tiempos 0, 2, 5, 8 y 10 horas, para determinación de dímeros y polímeros (compuestos de degradación y de tocoferoles. Se verificó la influencia del grado de hidrogenación sobre la formación de dímeros y polímeros, y también el papel de los tocoferoles originalmente presentes en el aceite y en las grasas, en la protección contra la degradación térmica. Las curvas de degradación de los tocoferoles mostraron una destrucción bastante rápida de los tocoferoles presentes en el aceite y en las grasas de algodón (α y γ-tocoferoles, con niveles residuales próximos a cero después de 10 horas de termoxidación. Aún así, muestras con sus

  4. Contingent kernel density estimation.

    Directory of Open Access Journals (Sweden)

    Scott Fortmann-Roe

    Full Text Available Kernel density estimation is a widely used method for estimating a distribution based on a sample of points drawn from that distribution. Generally, in practice some form of error contaminates the sample of observed points. Such error can be the result of imprecise measurements or observation bias. Often this error is negligible and may be disregarded in analysis. In cases where the error is non-negligible, estimation methods should be adjusted to reduce resulting bias. Several modifications of kernel density estimation have been developed to address specific forms of errors. One form of error that has not yet been addressed is the case where observations are nominally placed at the centers of areas from which the points are assumed to have been drawn, where these areas are of varying sizes. In this scenario, the bias arises because the size of the error can vary among points and some subset of points can be known to have smaller error than another subset or the form of the error may change among points. This paper proposes a "contingent kernel density estimation" technique to address this form of error. This new technique adjusts the standard kernel on a point-by-point basis in an adaptive response to changing structure and magnitude of error. In this paper, equations for our contingent kernel technique are derived, the technique is validated using numerical simulations, and an example using the geographic locations of social networking users is worked to demonstrate the utility of the method.

  5. Multidimensional kernel estimation

    CERN Document Server

    Milosevic, Vukasin

    2015-01-01

    Kernel estimation is one of the non-parametric methods used for estimation of probability density function. Its first ROOT implementation, as part of RooFit package, has one major issue, its evaluation time is extremely slow making in almost unusable. The goal of this project was to create a new class (TKNDTree) which will follow the original idea of kernel estimation, greatly improve the evaluation time (using the TKTree class for storing the data and creating different user-controlled modes of evaluation) and add the interpolation option, for 2D case, with the help of the new Delaunnay2D class.

  6. for palm kernel oil extraction

    African Journals Online (AJOL)

    user

    OEE), ... designed (CRD) experimental approach with 4 factor levels and 2 replications was used to determine the effect of kernel .... palm kernels in either a continuous or batch mode ... are fed through the hopper; the screw conveys, crushes,.

  7. Evaluation of ultra-low Gossypol cottonseed and regular glandless cottonseed meals as dietary protein and lipid sources for Litopenaeus Vannamei reared under zero-exchange conditions

    Science.gov (United States)

    Our previous studies showed that glandless cottonseed meal (GCSM), produced from naturally occurring mutant plants, can replace 67-100% of fishmeal in shrimp diets without any negative effects on the growth and survival of shrimp. However, glandless cotton plants, completely lacking protective goss...

  8. Comparison of adhesive properties of water- and phosphate-buffer-washed cottonseed meals with cottonseed protein isolate on maple and poplar veneers

    Science.gov (United States)

    Water- and phosphate buffer (35 mM Na2HPO4/NaH2PO4, pH 7.5)-washed cottonseed meals (abbreviated as WCM and BCM, respectively) could be low-cost and environmentally friendly protein-based adhesives as their preparation does not involve corrosive alkali and acid solutions that are needed for cottonse...

  9. Kernel bundle EPDiff

    DEFF Research Database (Denmark)

    Sommer, Stefan Horst; Lauze, Francois Bernard; Nielsen, Mads

    2011-01-01

    In the LDDMM framework, optimal warps for image registration are found as end-points of critical paths for an energy functional, and the EPDiff equations describe the evolution along such paths. The Large Deformation Diffeomorphic Kernel Bundle Mapping (LDDKBM) extension of LDDMM allows scale space...

  10. Multivariate realised kernels

    DEFF Research Database (Denmark)

    Barndorff-Nielsen, Ole Eiler; Hansen, Peter Reinhard; Lunde, Asger

    2011-01-01

    We propose a multivariate realised kernel to estimate the ex-post covariation of log-prices. We show this new consistent estimator is guaranteed to be positive semi-definite and is robust to measurement error of certain types and can also handle non-synchronous trading. It is the first estimator...

  11. Adaptive metric kernel regression

    DEFF Research Database (Denmark)

    Goutte, Cyril; Larsen, Jan

    2000-01-01

    regression by minimising a cross-validation estimate of the generalisation error. This allows to automatically adjust the importance of different dimensions. The improvement in terms of modelling performance is illustrated on a variable selection task where the adaptive metric kernel clearly outperforms...

  12. Adaptive Metric Kernel Regression

    DEFF Research Database (Denmark)

    Goutte, Cyril; Larsen, Jan

    1998-01-01

    by minimising a cross-validation estimate of the generalisation error. This allows one to automatically adjust the importance of different dimensions. The improvement in terms of modelling performance is illustrated on a variable selection task where the adaptive metric kernel clearly outperforms the standard...

  13. Experimental investigation on fuel properties of biodiesel prepared from cottonseed oil

    Science.gov (United States)

    Payl, Ashish Naha; Mashud, Mohammad

    2017-06-01

    In recent time's world's energy demands are satisfied by coal, natural gas as well as petroleum though the prices of these are escalating. If this continues, global recession is unavoidable and diminution of world reserve accelerates undoubtedly. Recently, Biodiesel is found to be more sustainable, non-toxic and energy efficient alternative which is also biodegradable. The use of biofuels in compression ignition engines is now a contemplation attention in place of petrochemicals. In view of this, cottonseed oil is quite a favorable candidate as an alternative fuel. The present study covers the various aspects of biodiesels fuel prepared from cottonseed oil. In this work Biodiesel was prepared from cottonseed oil through transesterification process with methanol, using sodium hydroxide as catalyst. The fuel properties of cottonseed oil methyl esters, kinematic viscosity, flash point, density, calorific value, boiling point etc. were evaluated and discussed in the light of Conventional Diesel Fuel. The properties of biodiesel produced from cotton seed oil are quite close to that of diesel except from flash point. And so the methyl esters of cottonseed oil can be used in existing diesel engines without any modifications.

  14. Simultaneous quantification of oil and protein in cottonseed by low-field time-domain nuclear magnetic resonance

    Science.gov (United States)

    Modification of cottonseed quality traits is likely to be achieved through a combination of genetic modification, manipulation of nutrient allocation and selective breeding. Oil and protein stores comprise the majority of mass of cottonseed embryos. A more comprehensive understanding of the relation...

  15. Viscosity kernel of molecular fluids

    DEFF Research Database (Denmark)

    Puscasu, Ruslan; Todd, Billy; Daivis, Peter

    2010-01-01

    , temperature, and chain length dependencies of the reciprocal and real-space viscosity kernels are presented. We find that the density has a major effect on the shape of the kernel. The temperature range and chain lengths considered here have by contrast less impact on the overall normalized shape. Functional...... forms that fit the wave-vector-dependent kernel data over a large density and wave-vector range have also been tested. Finally, a structural normalization of the kernels in physical space is considered. Overall, the real-space viscosity kernel has a width of roughly 3–6 atomic diameters, which means...

  16. Multiple Kernel Point Set Registration.

    Science.gov (United States)

    Nguyen, Thanh Minh; Wu, Q M Jonathan

    2016-06-01

    The finite Gaussian mixture model with kernel correlation is a flexible tool that has recently received attention for point set registration. While there are many algorithms for point set registration presented in the literature, an important issue arising from these studies concerns the mapping of data with nonlinear relationships and the ability to select a suitable kernel. Kernel selection is crucial for effective point set registration. We focus here on multiple kernel point set registration. We make several contributions in this paper. First, each observation is modeled using the Student's t-distribution, which is heavily tailed and more robust than the Gaussian distribution. Second, by automatically adjusting the kernel weights, the proposed method allows us to prune the ineffective kernels. This makes the choice of kernels less crucial. After parameter learning, the kernel saliencies of the irrelevant kernels go to zero. Thus, the choice of kernels is less crucial and it is easy to include other kinds of kernels. Finally, we show empirically that our model outperforms state-of-the-art methods recently proposed in the literature.

  17. Effects of gossypol from cottonseed cake on the blood profile in sheep.

    Science.gov (United States)

    Câmara, Antônio Carlos Lopes; do Vale, André Menezes; Mattoso, Cláudio Roberto Scabelo; Melo, Marília Martins; Soto-Blanco, Benito

    2016-06-01

    Cottonseed cake contains gossypol, a potentially toxic compound that, when consumed by sheep, can affect reproduction, the immune system, and the liver. Changes in hematologic and serum biochemical parameters were monitored for 63 days in 12 Santa Inês ewes, six of which received ration containing 400 g kg(-1) of cottonseed cake. Blood samples were collected at the start of the experiment and weekly thereafter for hematologic assessment and determination of serum urea, creatinine, total protein, and albumin concentrations and for measurement of alanine aminotransferase, aspartate aminotransferase, alkaline phosphatase, and γ-glutamyl transferase activities. No clinical signs of toxicity were observed. Evaluation of the erythron showed that sheep consuming cottonseed cake had an increased packed cell volume (p cake by sheep for 63 days may induce changes in the erythron but no consistent changes in serum biochemical parameters, indicating no damage to the liver or kidneys.

  18. Studies on colour fixation of the oil of mature, immature and damaged cottonseed

    Directory of Open Access Journals (Sweden)

    Helmy, H. E.

    1994-06-01

    Full Text Available Oil was extracted from mature, inmature and damaged cottonseed with the acetone-hexane-water azeotrope (53:44:3 by volume. Mature cottonseed oil (M, 10% immature cottonseed oil in mature cottonseed oil (MIM and 10% damaged cottonseed oil in mature cottonseed oil (MD were subjected to some treatments e.g. refining and bleaching or the addition of sodium silicate before refining and bleaching or before colour fixation. The treated oils were spectrophotometrically studied.
    The presence of 10% oil from immature or damaged cottonseed in oil from mature cottonseed produced an increase in the colour and absorption spectra of most samples, resulting in an oil that could not be refined and bleached satisfactorily. Sodium silicate proved to be an effective treatment before refining and colour fixation of the oils. The study revealed gossypol pigments, carotenoids and chlorophylls present in different M, MIM and MD samples.

    Se extrajo aceite de semilla de algodón madura, Inmadura y dañada con el azeotropo, acetona-hexano-agua (53:44:3 v/v/v. Se sometieron a diversos tratamientos tales como refinación y decoloración, silicato sódico antes de la refinación y decoloración o antes de la fijación de color, a aceite de semilla de algodón madura (M, 10% de aceite de semilla de algodón inmadura en aceite de semilla de algodón madura (MIM y 10% de aceite de semilla de algodón dañada en aceite de semilla de algodón.
    madura (MD. Los aceites tratados se estudiaron espectrofotométricamente. La presencia de un 10% de aceite de semilla de algodón inmadura o dañada con aceite de semilla de algodón madura produjo un incremento en el color y en el espectro de absorción de la mayoría de las muestras, así ocurrió en un aceite que no pudo ser refinado y decolorado satisfactoriamente. El tratamiento con silicato sódico resultó efectivo antes de la refinación y fijación del color de los aceites. El estudio reveló la presencia de

  19. Assessment of the process of cottonseed oil bleaching in hexane

    Directory of Open Access Journals (Sweden)

    Megahed, Ola A.

    2002-12-01

    Full Text Available This work has been initiated to assess the feasibility of bleaching cottonseed oil in miscella as a processing step next to alkali refining in miscella. Alkali refining of cottonseed oil in miscella has several advantages over conventional refining technologies with respect to oil quality, oil losses and process cost. Therefore, the process efficiency of the bleaching of cottonseed oil in presence of hexane (at a volumetric ratio of 1:1, has been studied and compared to that without solvent. The process efficiency has been evaluated according to the decolourization capacity, the oil losses on spent earth, the filtration rate of the oil from the clay and the acidity of the bleached oil as well as its peroxide content. The bleaching in presence of hexane was carried out at 25ºC whereas that by conventional bleaching at 110ºC. Different clay loads were used in each of the two bleaching techniques and the colour indices of the oils before and after bleaching determined in each case. The results were used to predict Freundlich adsorption equations for the oil pigments in both cases. These equations were then used to predict the colour of the oils obtained by bleaching of refined oils of different grades. The results have shown that oil decolourization is more efficient in presence of solvent when the starting oil is of an acceptable grade and the reverse is true for low grade oils. Also, the possibility of oil oxidation during bleaching is less in presence of solvent. Moreover, the bleaching in miscella has proved two other additional advantages over conventional bleaching. The filtration of oil from clay is much faster in miscella bleaching and the oil losses on spent earth is lower. This will be reflected on the overall process economy.Este trabajo ha sido iniciado para evaluar la viabilidad de la decoloración del aceite de semilla de algodón en miscela como un paso de procesado próximo a la refinación alcalina en miscela. La refinaci

  20. Testing Monotonicity of Pricing Kernels

    OpenAIRE

    Timofeev, Roman

    2007-01-01

    In this master thesis a mechanism to test mononicity of empirical pricing kernels (EPK) is presented. By testing monotonicity of pricing kernel we can determine whether utility function is concave or not. Strictly decreasing pricing kernel corresponds to concave utility function while non-decreasing EPK means that utility function contains some non-concave regions. Risk averse behavior is usually described by concave utility function and considered to be a cornerstone of classical behavioral ...

  1. Effects of fuzzless cottonseed phenotype on cottonseed nutrient composition in near isogenic cotton (Gossypium hirsutum L. mutant lines under well-watered and water stress conditions

    Directory of Open Access Journals (Sweden)

    Nacer eBellaloui

    2013-12-01

    Full Text Available There is no information available on the effect of fuzzless seed trait on cottonseed nutrient composition (minerals, N, S, protein, and oil under drought stress. The objective of this research was to investigate the effect of the fuzzless seed trait on cottonseed nutrients using four sets of near-isogenic lines (NILs. Each set consists of two lines that share the same genetic background, but differ in seed fuzziness (fuzzy, F; fuzzless, N. The near isogenic lines will enable us to compare the effect of the trait without confounding the genotypic background effects. We hypothesized that since the fuzzless trait involved in fiber initiation development, and was reported to be involved in biochemical, molecular, and genetic processes, this trait may also alter cottonseed nutrient composition. Results showed that NIL sets accumulated different levels of minerals in seeds and leaves, and the fuzzless trait (NF in most of the lines altered seed and leaf mineral accumulations when compared with fuzzy lines (FN or the control line. For example, K, P, Mg, Cu, and Na concentrations in seeds were higher in MD N and STV N than in their equivalent MD F and STV F lines. Leaf concentrations of Ca, K, Mg, S, B, Cu, and Fe in MD N lines were higher than MD F line. Lower levels of nutrients in seeds and leaves were observed under water stress conditions, especially Ca, Mg, N, and B in seeds. Generally and with few exceptions, seed protein was higher in fuzzy lines that in fuzzless lines; however, seed oil was higher in fuzzless lines than in fuzzy lines. Our research demonstrated that fuzzless trait altered the composition and level of nutrients in seed and leaves in well watered and water stressed plants. Differences in protein and oil between fuzzy and fuzzless seeds may indicate alteration in nitrogen and carbon fixation and metabolism. The differential accumulation of seed nutrients in this germplasm could be used by cotton breeders to select for higher

  2. 7 CFR 51.1415 - Inedible kernels.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 2 2010-01-01 2010-01-01 false Inedible kernels. 51.1415 Section 51.1415 Agriculture... Standards for Grades of Pecans in the Shell 1 Definitions § 51.1415 Inedible kernels. Inedible kernels means that the kernel or pieces of kernels are rancid, moldy, decayed, injured by insects or...

  3. 7 CFR 981.8 - Inedible kernel.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 8 2010-01-01 2010-01-01 false Inedible kernel. 981.8 Section 981.8 Agriculture... Regulating Handling Definitions § 981.8 Inedible kernel. Inedible kernel means a kernel, piece, or particle of almond kernel with any defect scored as serious damage, or damage due to mold, gum, shrivel,...

  4. 7 CFR 981.7 - Edible kernel.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 8 2010-01-01 2010-01-01 false Edible kernel. 981.7 Section 981.7 Agriculture... Regulating Handling Definitions § 981.7 Edible kernel. Edible kernel means a kernel, piece, or particle of almond kernel that is not inedible....

  5. 7 CFR 981.408 - Inedible kernel.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 8 2010-01-01 2010-01-01 false Inedible kernel. 981.408 Section 981.408 Agriculture... Administrative Rules and Regulations § 981.408 Inedible kernel. Pursuant to § 981.8, the definition of inedible kernel is modified to mean a kernel, piece, or particle of almond kernel with any defect scored...

  6. Clustering via Kernel Decomposition

    DEFF Research Database (Denmark)

    Have, Anna Szynkowiak; Girolami, Mark A.; Larsen, Jan

    2006-01-01

    Methods for spectral clustering have been proposed recently which rely on the eigenvalue decomposition of an affinity matrix. In this work it is proposed that the affinity matrix is created based on the elements of a non-parametric density estimator. This matrix is then decomposed to obtain...... posterior probabilities of class membership using an appropriate form of nonnegative matrix factorization. The troublesome selection of hyperparameters such as kernel width and number of clusters can be obtained using standard cross-validation methods as is demonstrated on a number of diverse data sets....

  7. 21 CFR 73.140 - Toasted partially defatted cooked cottonseed flour.

    Science.gov (United States)

    2010-04-01

    ... color additive mixtures for coloring foods. (b) Specifications. Toasted partially defatted cooked... compound and therefore may not exceed a maximum natural background level of 0.2 part per million total... defatted cooked cottonseed flour may be safely used for coloring foods generally, in amounts...

  8. The induction of lycopene in germinating cottonseed with 2-(4-Methylphenoxy)Triethylamine (MPTA)

    Science.gov (United States)

    Cottonseed (Gossypium hirsutum Acala cultivar) were imbibed in H2O for 6 hr and seed coats removed. The seeds were imbibed for an additional 3 hr in H2O or 7.2x10**-4M 2-(4-methylphenoxy) triethylamine (MPTA) and germinated in the dark for 72 hr. The carotenoids were extracted and analyzed by HPLC...

  9. Biodiesel and biohydrogen production from cotton-seed cake in biorefinery concept

    NARCIS (Netherlands)

    Panagiotopoulos, I.A.; Pasias, S.; Bakker, R.R.C.; Vrije, de G.J.; Papayannakos, N.; Claassen, P.A.M.; Koukios, E.G.

    2013-01-01

    Biodiesel production from cotton-seed cake (CSC) and the pretreatment of the remaining biomass for dark fermentative hydrogen production was investigated. The direct conversion to biodiesel with alkali free fatty acids neutralization pretreatment and alkali transesterification resulted in a biodiese

  10. Effect of heat treatment of whole cottonseed on in vitro, in situ and in ...

    African Journals Online (AJOL)

    'n fraksionele rumenuiwloeitempo van. 0.08/h, vanaf 54.2Vo tot 29.57a verlaag, terwyl die in siln-verdwyning van vet vanaf 47.87o .... containing 3Wo whole cottonseed t(i) control; (ii) heat treated ... design according to ..... North Carolina Agric.

  11. 21 CFR 172.894 - Modified cottonseed products intended for human consumption.

    Science.gov (United States)

    2010-04-01

    ... consumption. 172.894 Section 172.894 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) FOOD FOR HUMAN CONSUMPTION (CONTINUED) FOOD ADDITIVES PERMITTED FOR DIRECT ADDITION TO FOOD FOR HUMAN CONSUMPTION Multipurpose Additives § 172.894 Modified cottonseed products...

  12. Capillary electrophoresis to quantitate gossypol enantiomers in cottonseed and flower petals

    Science.gov (United States)

    Gossypol occurs as a mixture of enantiomers in cotton plant tissues including seed and flower petals. The (-)-enantiomer is less toxic to non-ruminant animals. Efforts to breed cottonseed with a low percentage of (-)-gossypol requires the determination of the (+)- to (-)-gossypol ratio in seed and...

  13. Comparison of soybean and cottonseed oils upon hydrogenation with nickel, palladium and platinum catalysts

    Science.gov (United States)

    There is current interest in reducing the trans fatty acids (TFA) in hydrogenated vegetable oils because consumption of foods high in TFA has been linked to increased serum cholesterol content. In this work, hydrogenation was carried out on soybean oil and cottonseed oil at two pressures (2 and 5 b...

  14. The influence of cooking process on the microwave-assisted extraction of cottonseed oil.

    Science.gov (United States)

    Taghvaei, Mostafa; Jafari, Seid Mahdi; Nowrouzieh, Shahram; Alishah, Omran

    2015-02-01

    Cooking process is one of the most energy and time consuming steps in the edible oil extraction factories. The main goal of this study was cottonseed oil extraction by microwave radiation and elimination of any heat treatment of cottonseeds before extraction. The effect of cooking process on the physicochemical properties of extracted oil from two varieties of cottonseed (Pak and Sahel) was evaluated by free fatty acid content, melting point, smoke point and refractive index. Our results didn't show any significant differences between cooked and uncooked samples (P > 0.05) regarding physicochemical characteristics. From GC analysis of extracted oils, it was found there is no significant difference in fatty acid composition of cooked, uncooked and control (conventional extraction) samples. The thermal stability (Rancimat) analysis of oil samples showed the cooking process could cause a slight increase in the stability of oils for both varieties (about 40 min). The cooking process also increased total extracted phenolic compounds and considerably decreased total gossypol content of the cottonseed oil; but the extraction efficiency didn't change considerably after elimination of the cooking process. It can be concluded that microwave rays can destroy the structure of oil cells during process and facilitate the oil extraction without any heat treatment before extraction.

  15. Adhesive properties of water washed cottonseed meal on poplar, douglas fir, walnut, and white oak

    Science.gov (United States)

    The interest in natural product-based wood adhesives has been steadily increasing due to the environmental and sustainable concerns of petroleum-based adhesives. In this work, we reported our research on utilization of water washed cottonseed meal (WCM) as wood adhesives. The adhesive strength and w...

  16. Adhesive properties of water washed cottonseed meal on four types of wood

    Science.gov (United States)

    The interest in natural product-based wood adhesives has been steadily increasing due to the environmental and sustainable concerns of petroleum-based adhesives. In this work, we reported our research on the utilization of water washed cottonseed meal (WCM) as wood adhesives. The adhesive strength a...

  17. Adhesive performance of washed cottonseed meal at high solid contents and low temperatures

    Science.gov (United States)

    Water-washed cottonseed meal (WCSM) has been shown as a promising biobased wood adhesive. Recently, we prepared WSCM in a pilot scale for promoting its industrial application. In this work, we tested the adhesive strength and viscosity of the adhesive preparation with high solid contents (up to 30%...

  18. Rheological behavior, chemical and physical characterization of soybean and cottonseed methyl esters submitted to thermal oxidation process

    Energy Technology Data Exchange (ETDEWEB)

    Silva, Adriano Sant' ana; Silva, Flavio Luiz Honorato da; Lima, Ezenildo Emanuel de; Carvalho, Maria Wilma N.C. [Universidade Federal de Campina Grande (CCT/UFCG), PB (Brazil). Centro de Ciencia e Tecnologia; Dantas, Hemeval Jales; Farias, Paulo de Almeida [Universidade Federal de Campina Grande (CTRN/UFCG), PB (Brazil). Centro de Tecnologia e Recursos Naturais

    2008-07-01

    In this study the effect of antioxidant terc-butylhydroxyanisol (BHA) on the oxidative stability of soybean and cottonseed methyl esters subjected to thermal degradation at 100 deg C was studied. Soybean and cottonseed methyl esters specific mass, dynamic viscosity and rheological behavior were evaluated. According to results, antioxidant degraded samples specific mass and dynamic viscosity did not showed alterations, remaining statistically equal. Soybean and cottonseed methyl esters showed a Newtonian rheological behavior and degraded samples without adding BHA showed rheological behavior alterations. (author)

  19. Rheological behavior, chemical and physical characterization of soybean and cottonseed methyl esters submitted to thermal oxidation process

    Energy Technology Data Exchange (ETDEWEB)

    Silva, Adriano Sant' ana; Silva, Flavio Luiz Honorato da; Lima, Ezenildo Emanuel de; Carvalho, Maria Wilma N.C. [Universidade Federal de Campina Grande (CCT/UFCG), PB (Brazil). Centro de Ciencia e Tecnologia; Dantas, Hemeval Jales; Farias, Paulo de Almeida [Universidade Federal de Campina Grande (CTRN/UFCG), PB (Brazil). Centro de Tecnologia e Recursos Naturais

    2008-07-01

    In this study the effect of antioxidant terc-butylhydroxyanisol (BHA) on the oxidative stability of soybean and cottonseed methyl esters subjected to thermal degradation at 100 deg C was studied. Soybean and cottonseed methyl esters specific mass, dynamic viscosity and rheological behavior were evaluated. According to results, antioxidant degraded samples specific mass and dynamic viscosity did not showed alterations, remaining statistically equal. Soybean and cottonseed methyl esters showed a Newtonian rheological behavior and degraded samples without adding BHA showed rheological behavior alterations. (author)

  20. Use of hazelnut kernel oil methyl ester and its blends as alternative fuels in diesel engines

    Energy Technology Data Exchange (ETDEWEB)

    Guemues, M.; Atmaca, M. [Marmara Univ., Istanbul (Turkey). Mechanical Department

    2008-09-30

    Interest in vegetable oil as an alternative to diesel fuel in diesel engines has increased during the last few decades because reserves of petroleum fuel and its derivatives are diminishing rapidly, and because they have harmful effects on the environment. Numerous vegetable oil esters have been tried as alternatives to diesel fuel. Many researchers have reported that with the use of vegetable oil ester as a fuel in diesel engiens there is a decrease in harmful exhaust emissions and engine performance that is the equivalent of diesel fuel. Several studies have found that biodiesel emits far less of the most regulated pollutants than standard diesel fuel. Decreasing carbon dioxide (CO{sub 2}) emissions by using biodiesel contributes to reducing the greenhouse effect. Furthermore, diminishing carbon monoxide (CO), hydrocarbons (HC), nitrogen oxides (NO{sub x}), and smoke density improves air quality. Essential oils that have been tested in diesel engines are soybean, sunflower, corn, safflower, cottonseed, and rapeseed, which are categorized as edible oils; however, some edible oils, such as neat hazelnut kernel oil, have not been comprehensively tested as alternative fuel in diesel engines. In this study, hazelnut (Corylus avellana L.) kernel oil was evaluated as an alternative fuel in diesel engines. Firstly, the optimum transesteri.cation reaction conditions for hazelnut kernel oil, with respect to reaction temperature, volumetric ratio of reactants, and catalyst, were investigated. Secondly, an experimental investigation was carried out to examine performance and emissions of a direct injection diesel engine running on hazelnut kernel oil methyl ester and its blends with diesel fuel. Results showed that hazelnut kernel oil methyl ester and its blends with diesel fuel are generally comparable to diesel fuel, according to engine performance and emissions.

  1. Absolute Orientation Based on Distance Kernel Functions

    Directory of Open Access Journals (Sweden)

    Yanbiao Sun

    2016-03-01

    Full Text Available The classical absolute orientation method is capable of transforming tie points (TPs from a local coordinate system to a global (geodetic coordinate system. The method is based only on a unique set of similarity transformation parameters estimated by minimizing the total difference between all ground control points (GCPs and the fitted points. Nevertheless, it often yields a transformation with poor accuracy, especially in large-scale study cases. To address this problem, this study proposes a novel absolute orientation method based on distance kernel functions, in which various sets of similarity transformation parameters instead of only one set are calculated. When estimating the similarity transformation parameters for TPs using the iterative solution of a non-linear least squares problem, we assigned larger weighting matrices for the GCPs for which the distances from the point are short. The weighting matrices can be evaluated using the distance kernel function as a function of the distances between the GCPs and the TPs. Furthermore, we used the exponential function and the Gaussian function to describe distance kernel functions in this study. To validate and verify the proposed method, six synthetic and two real datasets were tested. The accuracy was significantly improved by the proposed method when compared to the classical method, although a higher computational complexity is experienced.

  2. Kernel Phase and Kernel Amplitude in Fizeau Imaging

    CERN Document Server

    Pope, Benjamin J S

    2016-01-01

    Kernel phase interferometry is an approach to high angular resolution imaging which enhances the performance of speckle imaging with adaptive optics. Kernel phases are self-calibrating observables that generalize the idea of closure phases from non-redundant arrays to telescopes with arbitrarily shaped pupils, by considering a matrix-based approximation to the diffraction problem. In this paper I discuss the recent history of kernel phase, in particular in the matrix-based study of sparse arrays, and propose an analogous generalization of the closure amplitude to kernel amplitudes. This new approach can self-calibrate throughput and scintillation errors in optical imaging, which extends the power of kernel phase-like methods to symmetric targets where amplitude and not phase calibration can be a significant limitation, and will enable further developments in high angular resolution astronomy.

  3. Global Polynomial Kernel Hazard Estimation

    DEFF Research Database (Denmark)

    Hiabu, Munir; Miranda, Maria Dolores Martínez; Nielsen, Jens Perch;

    2015-01-01

    This paper introduces a new bias reducing method for kernel hazard estimation. The method is called global polynomial adjustment (GPA). It is a global correction which is applicable to any kernel hazard estimator. The estimator works well from a theoretical point of view as it asymptotically...

  4. Global Polynomial Kernel Hazard Estimation

    DEFF Research Database (Denmark)

    Hiabu, Munir; Miranda, Maria Dolores Martínez; Nielsen, Jens Perch

    2015-01-01

    This paper introduces a new bias reducing method for kernel hazard estimation. The method is called global polynomial adjustment (GPA). It is a global correction which is applicable to any kernel hazard estimator. The estimator works well from a theoretical point of view as it asymptotically redu...

  5. Graph kernels between point clouds

    CERN Document Server

    Bach, Francis

    2007-01-01

    Point clouds are sets of points in two or three dimensions. Most kernel methods for learning on sets of points have not yet dealt with the specific geometrical invariances and practical constraints associated with point clouds in computer vision and graphics. In this paper, we present extensions of graph kernels for point clouds, which allow to use kernel methods for such ob jects as shapes, line drawings, or any three-dimensional point clouds. In order to design rich and numerically efficient kernels with as few free parameters as possible, we use kernels between covariance matrices and their factorizations on graphical models. We derive polynomial time dynamic programming recursions and present applications to recognition of handwritten digits and Chinese characters from few training examples.

  6. Kernel Generalized Noise Clustering Algorithm

    Institute of Scientific and Technical Information of China (English)

    WU Xiao-hong; ZHOU Jian-jiang

    2007-01-01

    To deal with the nonlinear separable problem, the generalized noise clustering (GNC) algorithm is extended to a kernel generalized noise clustering (KGNC) model. Different from the fuzzy c-means (FCM) model and the GNC model which are based on Euclidean distance, the presented model is based on kernel-induced distance by using kernel method. By kernel method the input data are nonlinearly and implicitly mapped into a high-dimensional feature space, where the nonlinear pattern appears linear and the GNC algorithm is performed. It is unnecessary to calculate in high-dimensional feature space because the kernel function can do itjust in input space. The effectiveness of the proposed algorithm is verified by experiments on three data sets. It is concluded that the KGNC algorithm has better clustering accuracy than FCM and GNC in clustering data sets containing noisy data.

  7. Robotic intelligence kernel

    Science.gov (United States)

    Bruemmer, David J.

    2009-11-17

    A robot platform includes perceptors, locomotors, and a system controller. The system controller executes a robot intelligence kernel (RIK) that includes a multi-level architecture and a dynamic autonomy structure. The multi-level architecture includes a robot behavior level for defining robot behaviors, that incorporate robot attributes and a cognitive level for defining conduct modules that blend an adaptive interaction between predefined decision functions and the robot behaviors. The dynamic autonomy structure is configured for modifying a transaction capacity between an operator intervention and a robot initiative and may include multiple levels with at least a teleoperation mode configured to maximize the operator intervention and minimize the robot initiative and an autonomous mode configured to minimize the operator intervention and maximize the robot initiative. Within the RIK at least the cognitive level includes the dynamic autonomy structure.

  8. Flexible kernel memory.

    Science.gov (United States)

    Nowicki, Dimitri; Siegelmann, Hava

    2010-06-11

    This paper introduces a new model of associative memory, capable of both binary and continuous-valued inputs. Based on kernel theory, the memory model is on one hand a generalization of Radial Basis Function networks and, on the other, is in feature space, analogous to a Hopfield network. Attractors can be added, deleted, and updated on-line simply, without harming existing memories, and the number of attractors is independent of input dimension. Input vectors do not have to adhere to a fixed or bounded dimensionality; they can increase and decrease it without relearning previous memories. A memory consolidation process enables the network to generalize concepts and form clusters of input data, which outperforms many unsupervised clustering techniques; this process is demonstrated on handwritten digits from MNIST. Another process, reminiscent of memory reconsolidation is introduced, in which existing memories are refreshed and tuned with new inputs; this process is demonstrated on series of morphed faces.

  9. Flexible kernel memory.

    Directory of Open Access Journals (Sweden)

    Dimitri Nowicki

    Full Text Available This paper introduces a new model of associative memory, capable of both binary and continuous-valued inputs. Based on kernel theory, the memory model is on one hand a generalization of Radial Basis Function networks and, on the other, is in feature space, analogous to a Hopfield network. Attractors can be added, deleted, and updated on-line simply, without harming existing memories, and the number of attractors is independent of input dimension. Input vectors do not have to adhere to a fixed or bounded dimensionality; they can increase and decrease it without relearning previous memories. A memory consolidation process enables the network to generalize concepts and form clusters of input data, which outperforms many unsupervised clustering techniques; this process is demonstrated on handwritten digits from MNIST. Another process, reminiscent of memory reconsolidation is introduced, in which existing memories are refreshed and tuned with new inputs; this process is demonstrated on series of morphed faces.

  10. Mixture Density Mercer Kernels: A Method to Learn Kernels

    Data.gov (United States)

    National Aeronautics and Space Administration — This paper presents a method of generating Mercer Kernels from an ensemble of probabilistic mixture models, where each mixture model is generated from a Bayesian...

  11. Feed intake, milk production and composition of crossbred cows fed with insect-protected Bollgard II® cottonseed containing Cry1Ac and Cry2Ab proteins.

    Science.gov (United States)

    Singhal, K K; Tyagi, A K; Rajput, Y S; Singh, M; Kaur, H; Perez, T; Hartnell, G F

    2011-09-01

    Twenty crossbred lactating multiparous cows were used in a 28-day study to compare dry matter intake (DMI), milk yield, milk composition and Bacillus thuringiensis (Bt) protein concentrations in plasma when fed diets containing Bollgard II(®) cottonseed (BGII) or a control non-genetically modified isogenic cottonseed (CON). Bollgard II cottonseed contains the Cry1Ac and Cry2Ab insecticidal proteins that protect cotton plants from feeding damage caused by certain lepidopteran insects. Cows were assigned randomly to the BGII or CON treatments after a 2-week adjustment period. Cows consumed a concentrate containing 40% crushed cottonseed according to milk yield and green maize forage ad libitum. All cows received the same diet but with different crushed cottonseed sources. Cottonseed was included to provide approximately 2.9 kg per cow daily (dry matter basis). The ingredient composition of the concentrate was 40% crushed cottonseed, 15% groundnut cake, 20% corn, 22% wheat bran, 1% salt and 2% mineral mixture. Milk and blood plasma were analyzed for Cry1Ac and Cry2Ab proteins. DMI, BW, milk yield and milk components did not differ between cows on the BGII and CON treatments. Although milk yield and milk fat percentage were not affected by treatment, 4% fat-corrected milk (FCM) production and FCM/kg DMI for cows on the BGII treatment (14.0 kg/cow per day, 1.12 kg/kg) were significantly improved compared with cows on the CON treatment (12.1 kg/cow per day, 0.97 kg/kg). Gossypol contents in BGII cottonseed and conventional cottonseed were similar. Cry1Ac and Cry2Ab2 proteins in Bollgard II cottonseed were 5.53 and 150.8 μg/g, respectively, and were not detected in the milk or plasma samples. The findings suggested that Bollgard II cottonseed can replace conventional cottonseed in dairy cattle diets with no adverse effects on performance and milk composition.

  12. 7 CFR 981.9 - Kernel weight.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 8 2010-01-01 2010-01-01 false Kernel weight. 981.9 Section 981.9 Agriculture Regulations of the Department of Agriculture (Continued) AGRICULTURAL MARKETING SERVICE (Marketing Agreements... Regulating Handling Definitions § 981.9 Kernel weight. Kernel weight means the weight of kernels,...

  13. (Pre)kernel catchers for cooperative games

    NARCIS (Netherlands)

    Chang, Chih; Driessen, Theo

    1995-01-01

    The paper provides a new (pre)kernel catcher in that the relevant set always contains the (pre)kernel. This new (pre)kernel catcher gives rise to a better lower bound ɛ*** such that the kernel is included in strong ɛ-cores for all real numbers ɛ not smaller than the relevant bound ɛ***.

  14. 7 CFR 51.2295 - Half kernel.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 2 2010-01-01 2010-01-01 false Half kernel. 51.2295 Section 51.2295 Agriculture... Standards for Shelled English Walnuts (Juglans Regia) Definitions § 51.2295 Half kernel. Half kernel means the separated half of a kernel with not more than one-eighth broken off....

  15. A kernel version of spatial factor analysis

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg

    2009-01-01

    . Schölkopf et al. introduce kernel PCA. Shawe-Taylor and Cristianini is an excellent reference for kernel methods in general. Bishop and Press et al. describe kernel methods among many other subjects. Nielsen and Canty use kernel PCA to detect change in univariate airborne digital camera images. The kernel...... version of PCA handles nonlinearities by implicitly transforming data into high (even infinite) dimensional feature space via the kernel function and then performing a linear analysis in that space. In this paper we shall apply kernel versions of PCA, maximum autocorrelation factor (MAF) analysis...

  16. Kernel model-based diagnosis

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    The methods for computing the kemel consistency-based diagnoses and the kernel abductive diagnoses are only suited for the situation where part of the fault behavioral modes of the components are known. The characterization of the kernel model-based diagnosis based on the general causal theory is proposed, which can break through the limitation of the above methods when all behavioral modes of each component are known. Using this method, when observation subsets deduced logically are respectively assigned to the empty or the whole observation set, the kernel consistency-based diagnoses and the kernel abductive diagnoses can deal with all situations. The direct relationship between this diagnostic procedure and the prime implicants/implicates is proved, thus linking theoretical result with implementation.

  17. An alkali catalyzed trans-esterification of rice bran, cottonseed and waste cooking oil

    Directory of Open Access Journals (Sweden)

    Akhtar Faheem H.

    2014-01-01

    Full Text Available In this research work, biodiesel production by trans-esterification of three raw materials including virgin and used edible oil and non edible oil has been presented. A two step method following acidic and alkali catalyst was used for non edible oil due to the unsuitability of using the straight alkaline-catalyzed trans-esterification of high FFA present in rice bran oil. The acid value after processing for rice bran, cottonseed and waste cooking oil was found to be 0.95, 0.12 and 0.87 respectively. The influence of three variables on percentage yield i.e., methanol to oil molar ratio, reaction temperature and reaction time were studied at this stage. Cottonseed oil, waste cooking oil and rice bran oil showed a maximum yield of 91.7%, 84.1% and 87.1% under optimum conditions. Fuel properties of the three biodiesel satisfied standard biodiesel fuel results.

  18. [Immobilized lipase-catalyzed synthesis of biodiesel from crude cottonseed oil].

    Science.gov (United States)

    Liu, Weitao; Zhou, Liya; Jiang, Yanjun; Gao, Jing

    2009-12-01

    We investigated the transesterification of crude cottonseed oil with methyl acetate to biodiesel, by using Lipozyme TL IM and Novozym 435 as catalysts. Results showed that the biodiesel yield significantly increased with the addition of methanol into the reaction system, and the highest biodiesel yield of 91.83% was achieved with the optimum conditions as follows: n-hexane as solvent, molar ratio of methyl acetate to oil 9:1, 3% methanol based on the oil mass to inhibit the creation of acetic acid, 10% Lipozyme TL IM and 5% Novozym 435 as catalyst based on the oil mass, reaction temperature 55 degrees C and reaction time 8 h. Additionally, we explored the kinetics of lipase-catalyzed crude cottonseed oil to biodiesel, and proposed a kinetic model.

  19. Cottonseed oil for biodiesel production; Oleo de algodao para a producao de biodiesel

    Energy Technology Data Exchange (ETDEWEB)

    Pighinelli, Anna L.M.T.; Park, Kil J. [Universidade Estadual de Campinas (UNICAMP), SP (Brazil)], E-mail: annalets@feagri.unicamp.br; Ferrari, Roseli A.; Miguel, Ana M.R.O. [Instituto de Tecnologia de Alimentos (ITAL), Campinas, SP (Brazil)], Emails: roseliferrari@ital.sp.gov.br, anarauen@ital.sp.gov.br, kil@feagri.unicamp.br

    2009-07-01

    Crude cottonseed oil is an alternative for biodiesel production, mostly in Mato Grosso State, where its production is the biggest of Brazil. Even being an acid oil, esterification reaction, followed by transesterification, could make possible the biodiesel production. In this study, crude cottonseed oil obtained from expelled process was reacted to evaluate molar ration and catalyst concentration effects in biodiesel yield. Molar ratio varied from 3 to 15 moles of ethanol to 1 mol of oil, and catalyst, from 1 to 5% by oil mass. Statistic analysis showed that none of studied variables was significant, for the values range. Biodiesel yield had a maximum of 88%, for molar ratio of 4.7 and 4.42% of catalyst concentration. A combination of oil with high free fatty acid content and ethanol as alcohol, affected the separation between esters and glycerol. (author)

  20. Notes on the gamma kernel

    DEFF Research Database (Denmark)

    Barndorff-Nielsen, Ole E.

    The density function of the gamma distribution is used as shift kernel in Brownian semistationary processes modelling the timewise behaviour of the velocity in turbulent regimes. This report presents exact and asymptotic properties of the second order structure function under such a model......, and relates these to results of von Karmann and Horwath. But first it is shown that the gamma kernel is interpretable as a Green’s function....

  1. Kernel Rootkits Implement and Detection

    Institute of Scientific and Technical Information of China (English)

    LI Xianghe; ZHANG Liancheng; LI Shuo

    2006-01-01

    Rootkits, which unnoticeably reside in your computer, stealthily carry on remote control and software eavesdropping, are a great threat to network and computer security. It' time to acquaint ourselves with their implement and detection. This article pays more attention to kernel rootkits, because they are more difficult to compose and to be identified than useland rootkits. The latest technologies used to write and detect kernel rootkits, along with their advantages and disadvantages, are present in this article.

  2. CHEMICAL STABILITY OF COTTONSEED AND GROUNDNUT OIL USED FOR FRYING BHAJIAS AND ITS SENSORY QUALITIES

    Directory of Open Access Journals (Sweden)

    Ashima Gupta

    2014-12-01

    Full Text Available Deep fried snacks, which evolved as snacks between meals include bhajia, samosa, etc are very popular in India and commercially exploited on a wide scale.Cottonseed and Groundnut oil frequently used in Gujarat for cooking purpose studied for its intermittent frying stability. Indian fried snack popularly known as ‘Bhajia’ fried for 5 min at an interval of 1 h; 5 times a day for 5 consecutive days and studied for its various sensory attributes using 9-point hedonic scale. Standard AOCS and AOAC methods were used to determine the quality of oil. Peroxide and p-anisidine values of both oils increased significantly p<0.001 during the 25 h of intermittent frying. Iodine value of cottonseed oil did not decrease throughout the intermittent frying period. Polar components increased 257.5% in cottonseed oil (CSO and 142.9% in groundnut oil (GNO.The saturated and monounsaturated fatty acid content increased significantly with the increase in frying hours.No significant change was seen in linoleic/palmitic acid ratio of both the oils during bhajias frying. The sensory qualities of bhajia fried at different intervals did not change significantly for various attributes namely flavor, taste, crispness, greasiness, odor, color, appearance and overall acceptability.

  3. Modified oleic cottonseeds show altered content, composition and tissue-specific distribution of triacylglycerol molecular species.

    Science.gov (United States)

    Horn, Patrick J; Sturtevant, Drew; Chapman, Kent D

    2014-01-01

    Targeted increases in monounsaturated (oleic acid) fatty acid content of refined cottonseed oil could support improved human nutrition and cardiovascular health. Genetic modifications of cottonseed fatty acid composition have been accomplished using several different molecular strategies. Modification of oleic acid content in cottonseed embryos using a dominant-negative protein approach, while successful in effecting change in the desired fatty acid composition, resulted in reduced oil content and seed viability. Here these changes in fatty acid composition were associated with changes in dominant molecular species of triacylglycerols (TAGs) and their spatial distributions within embryo tissues. A combination of mass spectrometry (MS)-based lipidomics approaches, including MS imaging of seed cryo-sections, revealed that cotton embryos expressing a non-functional allele of a Brassica napus delta-12 desaturase showed altered accumulation of TAG species, especially within cotyledonary tissues. While lipid analysis of seed extracts could demonstrate detailed quantitative changes in TAG species in transgenics, the spatial contribution of metabolite compartmentation could only be visualized by MS imaging. Our results suggest tissue-specific differences in TAG biosynthetic pathways within cotton embryos, and indicate the importance of considering the location of metabolites in tissues in addition to their identification and quantification when developing a detailed view of cellular metabolism.

  4. Trials to improve the colour of colour fixed cottonseed oil using sodium oleate and sodium stearate in the absence and presence of azeotropic extract of cottonseed meal

    Directory of Open Access Journals (Sweden)

    Yousef, Elham A. A.

    1998-04-01

    Full Text Available The effectiveness of two additives, namely, laboratory prepared sodium oleate and sodium stearate to improve the colour of colour fixed cottonseed oil was studied. Also the presence of the azeotropic extract of cottonseed meal together with 5% Na oleate or 10%Na stearate was taken In consideration. Improvement in the colour index of most treated refined and bleached oil samples is observed. This is confirmed with the reduction of gossypol contents of the refined and bleached treated oil samples compared with the untreated oil sample.

    Se estudió la eficacia de dos aditivos, a saber, oleato sódico y estearato sódico preparados en laboratorio para mejorar el color del aceite de semilla de algodón con color fijado. También se tuvo en consideración la presencia de extracto azeotrópico de harina de semilla de algodón junto con oleato sódico al 50% o estearato sódico al 10%. Se observó la mejora en el índice de color de la mayoría de las muestras de aceite decolorado y refinado tratado. Esto está confirmado con la reducción de los contenidos en gosipol de las muestras de aceites refinados y decolorados tratados comparado con la muestra de aceite no tratado.

  5. Kernel versions of some orthogonal transformations

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg

    Kernel versions of orthogonal transformations such as principal components are based on a dual formulation also termed Q-mode analysis in which the data enter into the analysis via inner products in the Gram matrix only. In the kernel version the inner products of the original data are replaced...... by inner products between nonlinear mappings into higher dimensional feature space. Via kernel substitution also known as the kernel trick these inner products between the mappings are in turn replaced by a kernel function and all quantities needed in the analysis are expressed in terms of this kernel...... function. This means that we need not know the nonlinear mappings explicitly. Kernel principal component analysis (PCA) and kernel minimum noise fraction (MNF) analyses handle nonlinearities by implicitly transforming data into high (even infinite) dimensional feature space via the kernel function...

  6. An Approximate Approach to Automatic Kernel Selection.

    Science.gov (United States)

    Ding, Lizhong; Liao, Shizhong

    2016-02-02

    Kernel selection is a fundamental problem of kernel-based learning algorithms. In this paper, we propose an approximate approach to automatic kernel selection for regression from the perspective of kernel matrix approximation. We first introduce multilevel circulant matrices into automatic kernel selection, and develop two approximate kernel selection algorithms by exploiting the computational virtues of multilevel circulant matrices. The complexity of the proposed algorithms is quasi-linear in the number of data points. Then, we prove an approximation error bound to measure the effect of the approximation in kernel matrices by multilevel circulant matrices on the hypothesis and further show that the approximate hypothesis produced with multilevel circulant matrices converges to the accurate hypothesis produced with kernel matrices. Experimental evaluations on benchmark datasets demonstrate the effectiveness of approximate kernel selection.

  7. Model Selection in Kernel Ridge Regression

    DEFF Research Database (Denmark)

    Exterkate, Peter

    Kernel ridge regression is gaining popularity as a data-rich nonlinear forecasting tool, which is applicable in many different contexts. This paper investigates the influence of the choice of kernel and the setting of tuning parameters on forecast accuracy. We review several popular kernels......, including polynomial kernels, the Gaussian kernel, and the Sinc kernel. We interpret the latter two kernels in terms of their smoothing properties, and we relate the tuning parameters associated to all these kernels to smoothness measures of the prediction function and to the signal-to-noise ratio. Based...... on these interpretations, we provide guidelines for selecting the tuning parameters from small grids using cross-validation. A Monte Carlo study confirms the practical usefulness of these rules of thumb. Finally, the flexible and smooth functional forms provided by the Gaussian and Sinc kernels makes them widely...

  8. Integral equations with contrasting kernels

    Directory of Open Access Journals (Sweden)

    Theodore Burton

    2008-01-01

    Full Text Available In this paper we study integral equations of the form $x(t=a(t-\\int^t_0 C(t,sx(sds$ with sharply contrasting kernels typified by $C^*(t,s=\\ln (e+(t-s$ and $D^*(t,s=[1+(t-s]^{-1}$. The kernel assigns a weight to $x(s$ and these kernels have exactly opposite effects of weighting. Each type is well represented in the literature. Our first project is to show that for $a\\in L^2[0,\\infty$, then solutions are largely indistinguishable regardless of which kernel is used. This is a surprise and it leads us to study the essential differences. In fact, those differences become large as the magnitude of $a(t$ increases. The form of the kernel alone projects necessary conditions concerning the magnitude of $a(t$ which could result in bounded solutions. Thus, the next project is to determine how close we can come to proving that the necessary conditions are also sufficient. The third project is to show that solutions will be bounded for given conditions on $C$ regardless of whether $a$ is chosen large or small; this is important in real-world problems since we would like to have $a(t$ as the sum of a bounded, but badly behaved function, and a large well behaved function.

  9. Model selection for Gaussian kernel PCA denoising

    DEFF Research Database (Denmark)

    Jørgensen, Kasper Winther; Hansen, Lars Kai

    2012-01-01

    We propose kernel Parallel Analysis (kPA) for automatic kernel scale and model order selection in Gaussian kernel PCA. Parallel Analysis [1] is based on a permutation test for covariance and has previously been applied for model order selection in linear PCA, we here augment the procedure to also...... tune the Gaussian kernel scale of radial basis function based kernel PCA.We evaluate kPA for denoising of simulated data and the US Postal data set of handwritten digits. We find that kPA outperforms other heuristics to choose the model order and kernel scale in terms of signal-to-noise ratio (SNR...

  10. Kernel learning algorithms for face recognition

    CERN Document Server

    Li, Jun-Bao; Pan, Jeng-Shyang

    2013-01-01

    Kernel Learning Algorithms for Face Recognition covers the framework of kernel based face recognition. This book discusses the advanced kernel learning algorithms and its application on face recognition. This book also focuses on the theoretical deviation, the system framework and experiments involving kernel based face recognition. Included within are algorithms of kernel based face recognition, and also the feasibility of the kernel based face recognition method. This book provides researchers in pattern recognition and machine learning area with advanced face recognition methods and its new

  11. Cottonseed protein, oil, and mineral status in near-isogenic cotton (Gossypium hirsutum) lines expressing fuzzy/linted and fuzzless/linted seed phenotypes

    Science.gov (United States)

    Cotton is an important crop in the world and is a major source of oil for human consumption and cotton meal for livestock. Cottonseed composition constituents (protein, oil, and minerals) determine the quality of seeds. Therefore, maintaining optimum levels of cottonseed constituents is critical. Ph...

  12. Semi-Supervised Kernel PCA

    DEFF Research Database (Denmark)

    Walder, Christian; Henao, Ricardo; Mørup, Morten

    We present three generalisations of Kernel Principal Components Analysis (KPCA) which incorporate knowledge of the class labels of a subset of the data points. The first, MV-KPCA, penalises within class variances similar to Fisher discriminant analysis. The second, LSKPCA is a hybrid of least...... squares regression and kernel PCA. The final LR-KPCA is an iteratively reweighted version of the previous which achieves a sigmoid loss function on the labeled points. We provide a theoretical risk bound as well as illustrative experiments on real and toy data sets....

  13. Congruence Kernels of Orthoimplication Algebras

    Directory of Open Access Journals (Sweden)

    I. Chajda

    2007-10-01

    Full Text Available Abstracting from certain properties of the implication operation in Boolean algebras leads to so-called orthoimplication algebras. These are in a natural one-to-one correspondence with families of compatible orthomodular lattices. It is proved that congruence kernels of orthoimplication algebras are in a natural one-to-one correspondence with families of compatible p-filters on the corresponding orthomodular lattices. Finally, it is proved that the lattice of all congruence kernels of an orthoimplication algebra is relatively pseudocomplemented and a simple description of the relative pseudocomplement is given.

  14. Model selection in kernel ridge regression

    DEFF Research Database (Denmark)

    Exterkate, Peter

    2013-01-01

    Kernel ridge regression is a technique to perform ridge regression with a potentially infinite number of nonlinear transformations of the independent variables as regressors. This method is gaining popularity as a data-rich nonlinear forecasting tool, which is applicable in many different contexts....... The influence of the choice of kernel and the setting of tuning parameters on forecast accuracy is investigated. Several popular kernels are reviewed, including polynomial kernels, the Gaussian kernel, and the Sinc kernel. The latter two kernels are interpreted in terms of their smoothing properties......, and the tuning parameters associated to all these kernels are related to smoothness measures of the prediction function and to the signal-to-noise ratio. Based on these interpretations, guidelines are provided for selecting the tuning parameters from small grids using cross-validation. A Monte Carlo study...

  15. Bergman kernel on generalized exceptional Hua domain

    Institute of Scientific and Technical Information of China (English)

    YIN; weipng(殷慰萍); ZHAO; zhengang(赵振刚)

    2002-01-01

    We have computed the Bergman kernel functions explicitly for two types of generalized exceptional Hua domains, and also studied the asymptotic behavior of the Bergman kernel function of exceptional Hua domain near boundary points, based on Appell's multivariable hypergeometric function.

  16. Comparison of full-fat corn germ, whole cottonseed, and tallow as fat sources for lactating dairy cattle.

    Science.gov (United States)

    Miller, W F; Shirley, J E; Titgemeyer, E C; Brouk, M J

    2009-07-01

    Twenty-four multiparous Holstein cows (124 +/- 39 d in milk; 682 +/- 72 kg of body weight) were used in 6 simultaneous 4 x 4 Latin squares to evaluate full-fat corn germ as a fat source for lactating dairy cows. Experimental diets were a control (containing 28% ground corn, 23% alfalfa hay, 19% wet corn gluten feed, and 10% corn silage, dry matter basis), and 3 diets with either whole cottonseed (WCS), tallow (TAL), or full-fat corn germ (FFCG) added to provide 1.6% supplemental fat. Cows were fed twice daily for ad libitum intake. Dry matter intake, milk yield, and energy-corrected milk did not differ among diets. Efficiency of milk production (energy-corrected milk/dry matter intake) was greater for cows fed WCS than for cows fed the control, TAL, or FFCG. Milk fat percentage from cows fed FFCG was less than that of cows fed WCS or the control, but was similar to that of cows fed TAL. Milk protein percentage was less for cows fed FFCG than for those fed the control. Total saturated fatty acids were less in milk from cows fed fat sources, and cows fed WCS and TAL had greater saturated fatty acids in milk than did cows fed FFCG. Unsaturated fatty acids were greater in milk from cows fed FFCG than in milk from cows fed the control, WCS, or TAL. The cis-9, trans-11 conjugated linoleic acid content was greater in milk from cows fed WCS, TAL, and FFCG than from cows fed the control, and it was greater in milk from cows fed FFCG than in milk from cows fed WCS or TAL. These results indicate that FFCG can be used effectively as a fat source in diets for lactating dairy cattle.

  17. QTL mapping based on different genetic systems for essential amino acid contents in cottonseeds in different environments.

    Directory of Open Access Journals (Sweden)

    Haiying Liu

    Full Text Available Cottonseeds are rich in various essential amino acids. However, the inheritance of them at molecular level are still not defined across various genetic systems. In the present study, using a newly developed mapping model that can analyze the embryo and maternal main effects as well as QTL × environment interaction effects on quantitative quality trait loci (QTLs in cottonseeds, a study on QTL located in the tetraploid embryo and tetraploid maternal plant genomes for essential amino acid contents in cottonseeds under different environments was carried out, using the immortal F2 (IF2 populations from a set of 188 recombinant inbred lines derived from an intraspecific hybrid cross of two upland cotton germplasms HS46 and MARKCBUCAG8US-1-88 as experimental materials. The results showed a total of 35 QTLs associated with these quality traits in cottonseeds. Nineteen QTLs were subsequently mapped on chromosome 5, 6 and 8 in sub-A genome and chromosome 15, 18, 22 and 23 in sub-D genome. Eighteen QTLs were also found having QTL × environment (QE interaction effects. The genetic main effects from QTLs located on chromosomes in the embryo and maternal plant genomes and their QE effects in different environments were all important for these essential amino acids in cottonseeds. The results suggested that the influence of environmental factors on the expression of some QTLs located in different genetic systems should be considered when improving for these amino acids. This study can serve as the foundation for the improvement of these essential amino acids in cottonseeds.

  18. Methane emission of Santa Inês sheep fed cottonseed by-products containing different levels of gossypol.

    Science.gov (United States)

    Lima, Paulo de Mello Tavares; Oliveira, Pedro Batelli; Campeche, Aline; Moreira, Guilherme Dias; Paim, Tiago do Prado; McManus, Concepta; Abdalla, Adibe Luiz; Dantas, Angela Maria Morais; de Souza, Jurandir Rodrigues; Louvandini, Helder

    2014-01-01

    The aim of this study was to evaluate the methane (CH4) emission of Santa Inês sheep fed cottonseed by-products, verifying if the gossypol content of these feedstuffs affects CH4 emission. Twelve late-lactating Santa Inês sheep (44.8 ± 7.5 kg body weight (BW)) were allocated in metabolic cages for an experimental period of 19 days, 14 days for adaptation and 5 days for measuring CH4 emission and dry matter intake (DMI). The animals were divided into four treatments, established in accordance with the cottonseed by-product used in concentrate formulation: Control (CON - no cottonseed by-product), Whole cottonseed (WCS), Cottonseed cake (CSC), and Cottonseed meal (CSM). The free gossypol level of the concentrates were 0, 1,276, 350, and 190 ppm for CON, WCS, CSC, and CSM, respectively. Also, the animals received Cynodon dactylon cv. Coast Cross hay, water, and mineral salt ad libitum. The ether extract content of the diets was balanced between treatments by including soybean oil in concentrates. The technique used to measure the CH4 emission was the sulfur hexafluoride (SF6) tracer technique, and the gas samples collected were quantified by analysis in gas chromatography system. The CH4 emission was evaluated considering the daily emission (g CH4/day); DMI (g CH4/kg DMI); and BW (g CH4/kg BW). No statistical difference was found (P > 0.05) between treatments for DMI and CH4 parameters. In the regression analysis, no significant relation (P > 0.05) between gossypol content and CH4 emission was observed. These results suggest that gossypol does not affect rumen methanogenesis.

  19. A kernel version of multivariate alteration detection

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg; Vestergaard, Jacob Schack

    2013-01-01

    Based on the established methods kernel canonical correlation analysis and multivariate alteration detection we introduce a kernel version of multivariate alteration detection. A case study with SPOT HRV data shows that the kMAD variates focus on extreme change observations.......Based on the established methods kernel canonical correlation analysis and multivariate alteration detection we introduce a kernel version of multivariate alteration detection. A case study with SPOT HRV data shows that the kMAD variates focus on extreme change observations....

  20. Random Feature Maps for Dot Product Kernels

    OpenAIRE

    Kar, Purushottam; Karnick, Harish

    2012-01-01

    Approximating non-linear kernels using feature maps has gained a lot of interest in recent years due to applications in reducing training and testing times of SVM classifiers and other kernel based learning algorithms. We extend this line of work and present low distortion embeddings for dot product kernels into linear Euclidean spaces. We base our results on a classical result in harmonic analysis characterizing all dot product kernels and use it to define randomized feature maps into explic...

  1. ks: Kernel Density Estimation and Kernel Discriminant Analysis for Multivariate Data in R

    Directory of Open Access Journals (Sweden)

    Tarn Duong

    2007-09-01

    Full Text Available Kernel smoothing is one of the most widely used non-parametric data smoothing techniques. We introduce a new R package ks for multivariate kernel smoothing. Currently it contains functionality for kernel density estimation and kernel discriminant analysis. It is a comprehensive package for bandwidth matrix selection, implementing a wide range of data-driven diagonal and unconstrained bandwidth selectors.

  2. On the Diamond Bessel Heat Kernel

    Directory of Open Access Journals (Sweden)

    Wanchak Satsanit

    2011-01-01

    Full Text Available We study the heat equation in n dimensional by Diamond Bessel operator. We find the solution by method of convolution and Fourier transform in distribution theory and also obtain an interesting kernel related to the spectrum and the kernel which is called Bessel heat kernel.

  3. Local Observed-Score Kernel Equating

    Science.gov (United States)

    Wiberg, Marie; van der Linden, Wim J.; von Davier, Alina A.

    2014-01-01

    Three local observed-score kernel equating methods that integrate methods from the local equating and kernel equating frameworks are proposed. The new methods were compared with their earlier counterparts with respect to such measures as bias--as defined by Lord's criterion of equity--and percent relative error. The local kernel item response…

  4. Computations of Bergman Kernels on Hua Domains

    Institute of Scientific and Technical Information of China (English)

    殷慰萍; 王安; 赵振刚; 赵晓霞; 管冰辛

    2001-01-01

    @@The Bergman kernel function plays an important ro1e in several complex variables.There exists the Bergman kernel function on any bounded domain in Cn. But we can get the Bergman kernel functions in explicit formulas for a few types of domains only,for example:the bounded homogeneous domains and the egg domain in some cases.

  5. Veto-Consensus Multiple Kernel Learning

    NARCIS (Netherlands)

    Y. Zhou; N. Hu; C.J. Spanos

    2016-01-01

    We propose Veto-Consensus Multiple Kernel Learning (VCMKL), a novel way of combining multiple kernels such that one class of samples is described by the logical intersection (consensus) of base kernelized decision rules, whereas the other classes by the union (veto) of their complements. The propose

  6. Levels of high energy cottonseed meal in multiple supplements for grazing cattle: performance and economic evaluation

    Directory of Open Access Journals (Sweden)

    Joanis Tilemahos Zervoudakis

    2015-10-01

    Full Text Available The objective was to evaluate the substitution levels of protein from soybean meal by high energy cottonseed (CS meal in multiple supplements for beef cattle grazing in the dry season on the average daily gain (ADG and economic viability. Twenty Nellore steers with initial body weight of 351.25±35.38 kg and average initial age of 24±0.8 months were used, divided into four paddocks of Brachiaria brizantha cv. Marandu with 1.6 ha each incompletely randomized design with four animals and five supplements to assess the following supplements: 0CS, 25CS and 50CS corresponding to the level of 0,25 and 50% high energy cottonseed meal to replace the meal soybean, provided the amount of 2 kg/animal/day, which were compared to mineral mixture (MM. The supplement 25CS provided higher (P<0.0001 ADG (0.75kg/animal/day-1 compared to supplement 50CS (0.60kg/animal/day-1. The ADG of animals supplemented with 0CS (0.53kg/animal/day-1 did not differ (P<0.0001 of the ADG of the bulls receiving supplementation with 25CS (0.75k /animal/day-1 and 50CS (0,60kg / animal / day-1. The 25CS supplement showed a higher economic return on invested capital in the period. The use of cottonseed meal high energy level of 25% replacement of soybean meal in multiple supplements provided greater weight gain of cattle and improved economic viability. 

  7. Accelerating the Original Profile Kernel.

    Directory of Open Access Journals (Sweden)

    Tobias Hamp

    Full Text Available One of the most accurate multi-class protein classification systems continues to be the profile-based SVM kernel introduced by the Leslie group. Unfortunately, its CPU requirements render it too slow for practical applications of large-scale classification tasks. Here, we introduce several software improvements that enable significant acceleration. Using various non-redundant data sets, we demonstrate that our new implementation reaches a maximal speed-up as high as 14-fold for calculating the same kernel matrix. Some predictions are over 200 times faster and render the kernel as possibly the top contender in a low ratio of speed/performance. Additionally, we explain how to parallelize various computations and provide an integrative program that reduces creating a production-quality classifier to a single program call. The new implementation is available as a Debian package under a free academic license and does not depend on commercial software. For non-Debian based distributions, the source package ships with a traditional Makefile-based installer. Download and installation instructions can be found at https://rostlab.org/owiki/index.php/Fast_Profile_Kernel. Bugs and other issues may be reported at https://rostlab.org/bugzilla3/enter_bug.cgi?product=fastprofkernel.

  8. Adaptive wiener image restoration kernel

    Science.gov (United States)

    Yuan, Ding

    2007-06-05

    A method and device for restoration of electro-optical image data using an adaptive Wiener filter begins with constructing imaging system Optical Transfer Function, and the Fourier Transformations of the noise and the image. A spatial representation of the imaged object is restored by spatial convolution of the image using a Wiener restoration kernel.

  9. An Extreme Learning Machine Based on the Mixed Kernel Function of Triangular Kernel and Generalized Hermite Dirichlet Kernel

    Directory of Open Access Journals (Sweden)

    Senyue Zhang

    2016-01-01

    Full Text Available According to the characteristics that the kernel function of extreme learning machine (ELM and its performance have a strong correlation, a novel extreme learning machine based on a generalized triangle Hermitian kernel function was proposed in this paper. First, the generalized triangle Hermitian kernel function was constructed by using the product of triangular kernel and generalized Hermite Dirichlet kernel, and the proposed kernel function was proved as a valid kernel function of extreme learning machine. Then, the learning methodology of the extreme learning machine based on the proposed kernel function was presented. The biggest advantage of the proposed kernel is its kernel parameter values only chosen in the natural numbers, which thus can greatly shorten the computational time of parameter optimization and retain more of its sample data structure information. Experiments were performed on a number of binary classification, multiclassification, and regression datasets from the UCI benchmark repository. The experiment results demonstrated that the robustness and generalization performance of the proposed method are outperformed compared to other extreme learning machines with different kernels. Furthermore, the learning speed of proposed method is faster than support vector machine (SVM methods.

  10. Random Feature Maps for Dot Product Kernels

    CERN Document Server

    Kar, Purushottam

    2012-01-01

    Approximating non-linear kernels using feature maps has gained a lot of interest in recent years due to applications in reducing training and testing times of SVM classifiers and other kernel based learning algorithms. We extend this line of work and present low distortion embeddings for dot product kernels into linear Euclidean spaces. We base our results on a classical result in harmonic analysis characterizing all dot product kernels and use it to define randomized feature maps into explicit low dimensional Euclidean spaces in which the native dot product provides an approximation to the dot product kernel with high confidence.

  11. Testing Infrastructure for Operating System Kernel Development

    DEFF Research Database (Denmark)

    Walter, Maxwell; Karlsson, Sven

    2014-01-01

    Testing is an important part of system development, and to test effectively we require knowledge of the internal state of the system under test. Testing an operating system kernel is a challenge as it is the operating system that typically provides access to this internal state information. Multi......-core kernels pose an even greater challenge due to concurrency and their shared kernel state. In this paper, we present a testing framework that addresses these challenges by running the operating system in a virtual machine, and using virtual machine introspection to both communicate with the kernel...... and obtain information about the system. We have also developed an in-kernel testing API that we can use to develop a suite of unit tests in the kernel. We are using our framework for for the development of our own multi-core research kernel....

  12. Speech Enhancement Using Kernel and Normalized Kernel Affine Projection Algorithm

    Directory of Open Access Journals (Sweden)

    Bolimera Ravi

    2013-08-01

    Full Text Available The goal of this paper is to investigate the speech signal enhancement using Kernel Affine ProjectionAlgorithm (KAPA and Normalized KAPA. The removal of background noise is very important in manyapplications like speech recognition, telephone conversations, hearing aids, forensic, etc. Kernel adaptivefilters shown good performance for removal of noise. If the evaluation of background noise is more slowlythan the speech, i.e., noise signal is more stationary than the speech, we can easily estimate the noiseduring the pauses in speech. Otherwise it is more difficult to estimate the noise which results indegradation of speech. In order to improve the quality and intelligibility of speech, unlike time andfrequency domains, we can process the signal in new domain like Reproducing Kernel Hilbert Space(RKHS for high dimensional to yield more powerful nonlinear extensions. For experiments, we have usedthe database of noisy speech corpus (NOIZEUS. From the results, we observed the removal noise in RKHShas great performance in signal to noise ratio values in comparison with conventional adaptive filters.

  13. Performance and emission analysis of cottonseed oil methyl ester in a diesel engine

    Energy Technology Data Exchange (ETDEWEB)

    Aydin, Hueseyin [Department of Automotive, Faculty of Technical Education, Batman University, Batman 72060 (Turkey); Bayindir, Hasan [Department of Mechanical Engineering, Faculty of Engineering and Architecture, Dicle University, Diyarbakir, 21280 (Turkey)

    2010-03-15

    In this study, performance and emissions of cottonseed oil methyl ester in a diesel engine was experimentally investigated. For the study, cottonseed oil methyl ester (CSOME) was added to diesel fuel, numbered D2, by volume of 5%(B5), 20%(B20), 50%(B50) and 75%(B75) as well as pure CSOME (B100). Fuels were tested in a single cylinder, direct injection, air cooled diesel engine. The effects of CSOME-diesel blends on engine performance and exhaust emissions were examined at various engine speeds and full loaded engine. The effect of B5, B20, B50, B75, B100 and D2 on the engine power, engine torque, bsfc's and exhaust gasses temperature were clarified by the performance tests. The influences of blends on CO, NO{sub x}, SO{sub 2} and smoke opacity were investigated by emission tests. The experimental results showed that the use of the lower blends (B5) slightly increases the engine torque at medium and higher speeds in compression ignition engines. However, there were no significant differences in performance values of B5, B20 and diesel fuel. Also with the increase of the biodiesel in blends, the exhaust emissions were reduced. The experimental results showed that the lower contents of CSOME in the blends can partially be substituted for the diesel fuel without any modifications in diesel engines. (author)

  14. Removal of Neutral Red from aqueous solution by adsorption on spent cottonseed hull substrate

    Energy Technology Data Exchange (ETDEWEB)

    Zhou Qi [School of Resources and Environmental Engineering, Wuhan University of Technology, Luoshi Road 122, Wuhan, Hubei 430070 (China); Gong Wenqi, E-mail: gongwenqi@yahoo.com.cn [School of Resources and Environmental Engineering, Wuhan University of Technology, Luoshi Road 122, Wuhan, Hubei 430070 (China); Xie Chuanxin [SINOPEC Research Institute of Safety Engineering, Qingdao 266071 (China); Yang Dongjiang [Environmental Futures Centre and Griffith School of Environment, Gold Coast Campus, Griffith University, QLD 4222 (Australia); Ling Xiaoqing; Yuan Xiao; Chen Shaohua [School of Resources and Environmental Engineering, Wuhan University of Technology, Luoshi Road 122, Wuhan, Hubei 430070 (China); Liu Xiaofang [School of Chemical Engineering, Wuhan University of Technology, Wuhan 430070 (China)

    2011-01-15

    Cottonseed hull, a low-cost widely available agricultural waste in China, after used as substrate for the white rot fungus Pleurotus ostreatus cultivation, was tested for the removal of Neutral Red (NR), a cationic dye, from aqueous solution. A batch adsorption study was carried out with varied solution pH, adsorbent dosage, reaction time and initial NR concentration. The results show that the kinetics of dye removal by the spent cottonseed hull substrate (SCHS) is prompt in the first 5 min and the adsorption equilibrium can be attained after 240 min. The biosorption kinetics and equilibrium follow typical pseudo-second-order and Langmuir adsorption models. Thermodynamic parameters of {Delta}G{sup o}, {Delta}H{sup o} and {Delta}S{sup o} show that the adsorption is a spontaneous and endothermic process. Fourier transform infrared (FTIR) spectroscopy was used for the characterization of possible dye-biosorbent interaction. This study provides a facile method to produce low-cost biosorbent for the purification of dye contaminated water.

  15. Adjuvant activity of peanut, cottonseed and rice oils on cellular and humoral response

    Directory of Open Access Journals (Sweden)

    Erika Freitas

    2013-04-01

    Full Text Available The potentiality of the usage of vegetable oils such as soybean, corn, olive, sesame, murici seed, rapeseed, linseed, rice and cashew nuts as adjuvant of the humoral and cellular immune response has been recently shown. In the present work, besides of evaluating the adjuvant action of peanut, cottonseed and rice oils on humoral and cellular immune responses against ovalbumin (OVA we also evaluated the protective immune response induced by Leishmania antigens. The peanut oil significantly increased the synthesis of anti-ovalbumin antibodies in the primary response, but it did not favor cellular response. Concerning mice immunized with L. amazonensis antigens emulsified with peanut oil exacerbated skin lesions and lymph node parasite load what suggests stimulation of the Th2 immune response and down regulation of Th1 response. The cottonseed oil was shown to have adjuvant effect to the humoral response, stimulating a secondary response and also favored the delayed-type hypersensitivity (DTH response to OVA. The rice oil stimulated a strong DTH reaction to OVA and enhanced the synthesis of antibodies after the third dose. Mice immunized with L. amazonensis antigens emulsified with rice oil or cotton seed oil were protected from developing skin lesions and lymph node parasite load. These results emphasize the interest and importance of the vegetable oils as tools in different procedures of immunization and their differential role in relation to the other adjuvant under usage.

  16. Is the enhancement produced by priming in cottonseeds maintained during storage?

    Directory of Open Access Journals (Sweden)

    María Eugenia Toselli

    2014-12-01

    Full Text Available The objective of this study was to evaluate: a whether the effects of hydropriming and osmopriming in manitol on cottonseed germination are maintained during their storage; b whether the behavior of the treated seeds -in storage- depends on the type of priming substrate used; c whether seeds from different harvest years [age] have a similar response. The effects of 16 h of hydropriming and 41 h in mannitol were tested at 18 and 25 ºC on the velocity of germination, standard germination and the vigor in cottonseeds from the 2007 and 2008 harvests, and within 0, 6 and 12 months of postpriming storage. The enhancement produced by the priming treatments used remained at least for 6 months in the case of hydropriming and 12 months for osmopriming in mannitol. The latter was more effective in increasing velocity of germination and the vigor index (CWVI. Priming enhanced the behavior in both seed lots but was more effective on the younger seeds.

  17. QTL mapping with different genetic systems for nine non-essential amino acids of cottonseeds.

    Science.gov (United States)

    Liu, Haiying; Quampah, Alfred; Chen, Jinhong; Li, Jinrong; Huang, Zhuangrong; He, Qiuling; Shi, Chunhai; Zhu, Shuijin

    2017-03-18

    Amino acid is an important nutrient resource for both human and animals. Using a set of 188 RILs population derived from an elite hybrid cross of upland cotton cultivars 'HS46' × 'MARCABUCAG8US-1-88' and their immortal F2 (IF2) with reciprocal backcrosses BC1F1 and BC2F1 (BC) populations in two environments, the QTLs located on the embryo genome and maternal plant genome for nine amino acids of cottonseed were studied across environments. The QTL Network-CL-2.0-seed software was used to analyze the QTLs and their genetic effects for nine amino acids. A total of 56 QTLs for nine amino acids were detected in both populations, with many having over 5% of phenotypic variation. Ten of the total QTLs could be simultaneously found in the IF2 and BC populations. For most QTLs, the genetic effects from embryo genome were more important than those from maternal plant genome for the performance of nine amino acids. Significant embryo additive main effects and maternal additive main effect with their environment interaction effects from many QTLs were also found in present experiment. Some QTLs with larger phenotypic variation were important for improving the amino-acid contents in cottonseeds.

  18. Effect of different relative humidities on the oil extracted from stored cottonseed

    Directory of Open Access Journals (Sweden)

    Helmy, H. E.

    1996-10-01

    Full Text Available Effect of different relative humidities (room, 10%, 46% and 97% R. H. on the oil extracted from cottonseed stored for one year was studied. The oil extracted from recent non-stored cottonseed was used as a control. Moisture content and oil content in the seed and acid value, peroxide value and percentage gossypol in the oil were determined. The results obtained for the oil extracted from the seed stored under (room, 10% and 46% R. H. showed a slight difference with the results obtained for the oil extracted from the non-stored conttonseed, while the results of the oil extracted from the seed stored under 97% R. H. showed a considerable difference. Fatty acids composition and unsaturated: saturated fatty acids ratio (U:S were also evaluated in previous oils. Unsaturated fatty acids were decreased by storage. Accordingly U:S was also decreased. Effect of relative humidity during storage of the cottonseeds on refining and bleaching of the oil was also investigated. The oil of the cottonseed stored under (room, 10% and 46% R. H. was satisfactorily refined and bleached, givining oils with good colour. While the oil of the cottonseed stored under 97% R. H. could not be satisfactorily refined and bleached. The oil was very dark in colour and did not response to refining and bleaching.

    Se ha estudiado el efecto de diferentes humedades relativas (ambiente, 10%, 46% y 97% en aceites extraídos de semilla de algodón almacenada durante un año. Se utilizó como control el aceite extraído de semilla de algodón reciente no almacenada. Se determinó la riqueza grasa y humedad en la semilla y el índice de acidez, índice de peróxidos y el porcentaje de gosipol en el aceite. Los resultados obtenidos para el aceite extraído a partir de la semilla almacenada bajo las condiciones de humedades relativas (ambiente, 10% y 46% mostraron una ligera diferencia con los resultados obtenidos para el aceite extraído a partir de semilla de algodón no almacenada

  19. Ultra-low gossypol cottonseed: gene-silencing opens up a vast, but underutilized protein resource for human nutrition

    Science.gov (United States)

    Cotton, grown mainly for its fiber, is a major crop in several developing and developed countries across the globe. In 2012, 48.8 million metric tons (MMT) of cottonseed was produced worldwide as a by-product of the 25.9 MMT of cotton lint production (FAO Production Statistics). This amount of cot...

  20. Morphological influence of cellulose nanoparticles (CNs) from cottonseed hulls on rheological properties of polyvinyl alcohol/CN suspensions

    Science.gov (United States)

    This work aims to extract and characterize fibrous, rod-like and spherical cellulose nanoparticles (CNs) from cottonseed hull and to investigate the structure-morphology-rheology relationships. The rheological behavior of poly(vinyl alcohol) (PVA)/CNs suspensions was also examined to guide the solve...

  1. Application of tung oil to improve adhesion strength and water resistance of cottonseed meal and protein adhesives on maple veneer

    Science.gov (United States)

    Cottonseed meal-based products show promise in serving as environment-friendly wood adhesives. However, their practical utilization is currently limited due to low durability and water resistant properties. In this research, we tested the improvement of adhesion strength and water resistance of cott...

  2. Inclusion of sorghum, millet and cottonseed meal in broiler diets: a meta-analysis of effects on performance.

    Science.gov (United States)

    Batonon-Alavo, D I; Umar Faruk, M; Lescoat, P; Weber, G M; Bastianelli, D

    2015-07-01

    A meta-analysis was conducted (i) to evaluate broiler response to partial or total substitution of corn by sorghum and millet and (ii) to determine the effect of soybean meal replacement by cottonseed meal in broiler diet. The database included 190 treatments from 29 experiments published from 1990 to 2013. Bird responses to an experimental diet were calculated relative to the control (Experimental-Control), and were submitted to mixed-effect models. Results showed that diets containing millet led to similar performance as the corn-based ones for all parameters, whereas sorghum-based diets decreased growth performance. No major effect of the level of substitution was observed with millet or cottonseed meal. No effect of the level of substitution of sorghum on feed intake was found; however, growth performance decreased when the level of substitution of corn by sorghum increased. Cottonseed meal was substituted to soybean meal up to 40% and found to increase feed intake while reducing growth performance. Young birds were not more sensitive to these ingredients than older birds since there was no negative effect of these ingredients on performance in the starter phase. Results obtained for sorghum pointed out the necessity to find technological improvements that will increase the utilization of these feedstuffs in broiler diet. An additional work is scheduled to validate these statistical results in vivo and to evaluate the interactions induced with the simultaneous inclusions of sorghum, millet and cottonseed meal in broiler feeding.

  3. Effects of pH and storage time on the adhesive and rheological properties of cottonseed meal-based products

    Science.gov (United States)

    Adhesive bonding is a key factor for efficiently utilizing timber and other lignocellulosic resources. To increase the basic knowledge of cottonseed meal-based adhesives and optimize the operational parameters for practical applications, in this study, we investigated the effects of pH and storage t...

  4. Non-destructive quantification of oil and protein in cottonseed by time-domain nuclear magnetic resonance

    Science.gov (United States)

    Modification of cotton seed quality traits is likely to be achieved through a combination of genetic modification, nutrient allocation, and selective breeding. Oil and protein stores comprise the majority of mass of cottonseed embryos. A more comprehensive understanding of the relationship between f...

  5. kLog: A Language for Logical and Relational Learning with Kernels

    CERN Document Server

    Frasconi, Paolo; De Raedt, Luc; De Grave, Kurt

    2012-01-01

    kLog is a logical and relational language for kernel-based learning. It allows users to specify logical and relational learning problems at a high level in a declarative way. It builds on simple but powerful concepts: learning from interpretations, entity/relationship data modeling, logic programming and deductive databases (Prolog and Datalog), and graph kernels. kLog is a statistical relational learning system but unlike other statistical relational learning models, it does not represent a probability distribution directly. It is rather a kernel-based approach to learning that employs features derived from a grounded entity/relationship diagram. These features are derived using a novel technique called graphicalization: first, relational representations are transformed into graph based representations; subsequently, graph kernels are employed for defining feature spaces. kLog can use numerical and symbolic data, background knowledge in the form of Prolog or Datalog programs (as in inductive logic programmin...

  6. Nonlinear Deep Kernel Learning for Image Annotation.

    Science.gov (United States)

    Jiu, Mingyuan; Sahbi, Hichem

    2017-02-08

    Multiple kernel learning (MKL) is a widely used technique for kernel design. Its principle consists in learning, for a given support vector classifier, the most suitable convex (or sparse) linear combination of standard elementary kernels. However, these combinations are shallow and often powerless to capture the actual similarity between highly semantic data, especially for challenging classification tasks such as image annotation. In this paper, we redefine multiple kernels using deep multi-layer networks. In this new contribution, a deep multiple kernel is recursively defined as a multi-layered combination of nonlinear activation functions, each one involves a combination of several elementary or intermediate kernels, and results into a positive semi-definite deep kernel. We propose four different frameworks in order to learn the weights of these networks: supervised, unsupervised, kernel-based semisupervised and Laplacian-based semi-supervised. When plugged into support vector machines (SVMs), the resulting deep kernel networks show clear gain, compared to several shallow kernels for the task of image annotation. Extensive experiments and analysis on the challenging ImageCLEF photo annotation benchmark, the COREL5k database and the Banana dataset validate the effectiveness of the proposed method.

  7. Substitution of soybean meal for cottonseed meal in multiple supplements for grazing beef heifers in the dry season

    Directory of Open Access Journals (Sweden)

    Román Maza Ortega

    2016-02-01

    Full Text Available The objective of this study was to evaluate the effect of substituting soybean meal for cottonseed meal in multiple supplements on the nutritional characteristics and performance of beef heifers in their postweaning phase on Brachiaria decumbens pastures during the dry season. Twenty-four Nellore beef heifers (average initial age and weight of 8 mo and 210±6 kg, respectively were used. The design was completely randomized, with four treatments and six replicates. Supplements contained approximately 30% crude protein (CP and a progressive substitution of soybean meal for cottonseed meal (0, 50 and 100%. The control animals received only a mineral mixture ad libitum, and those on the other treatments received supplementation at 1.0 kg/animal/day. No differences were found in ADG between supplemented and control animals (P>0.10. Supplementation increased crude protein (CP intake only (P<0.10. The level of substitution of soybean meal for cottonseed meal did not affect (P>0.10 the intake of supplemented animals. Supplementation elevated the apparent digestibility coefficients (P<0.10 of OM, CP, NFC and TDN, but not EE or NDFap (P>0.10. A positive linear effect (P<0.10 of the level of substitution of soybean meal for cottonseed cake was observed on the digestibility of OM, NFC and TDN. Supplementation and the level of substitution had an effect (P<0.10 on the serum urea nitrogen and urine urea nitrogen contents. Supplementation or substitution level had no effect on the flow of microbial nitrogen to the intestine (MICN or efficiency of microbial protein synthesis (EMPS (P>0.10. Substitution caused a decreasing linear effect (P<0.10 on microbial nitrogen/nitrogen intake ratio (MICNR. In conclusion, substitution of soybean meal for cottonseed meal in multiple supplements during the dry season does not impair the productive performance of beef heifers.

  8. Simultaneous inclusion of sorghum and cottonseed meal or millet in broiler diets: effects on performance and nutrient digestibility.

    Science.gov (United States)

    Batonon-Alavo, D I; Bastianelli, D; Lescoat, P; Weber, G M; Umar Faruk, M

    2016-07-01

    Two experiments were conducted to investigate the use of sorghum, cottonseed meal and millet in broiler diets and their interaction when they are used simultaneously. In Experiment 1, a corn-soybean meal control diet was compared with eight experimental treatments based on low tannin sorghum (S30, S45 and S60), cottonseed meal (CM15, CM40) or both ingredients included in the same diet (S30/CM40, S45/CM25 and S60CM15). Results showed that BW gain was not affected by the inclusion of sorghum or cottonseed meal. However, feed intake tended to be affected by the cereal type with the highest values with sorghum-based diets. Feed conversion ratio increased (Pdiets compared with the control diet, whereas a combination of cottonseed meal and sorghum in the same diet did not affect the feed conversion ratio. Significant differences (Pdiets having lower protein and energy digestibility compared with corn-based diets. In Experiment 2, a control diet was compared with six diets in which corn was substituted at 60%, 80% or 100% by either sorghum or millet and other three diets with simultaneous inclusion of these two ingredients (S30/M30, S40/M40, S50/M50). Single or combined inclusion of sorghum and millet resulted in similar feed intake and growth performance as the control diet. Apparent ileal digestibility of protein and energy was higher with millet-based diets (Pdiets tended to decrease linearly with the increasing level of substitution. Sorghum-based diets resulted in lower total tract digestibility of fat compared with millet and sorghum/millet-based diets (Pdiet and millet-based diets compared with the sorghum-based treatments. Results of the two experiments suggest that broiler growth performance was not affected by the dietary level of sorghum, millet or cottonseed meal. Nutrient digestion can, however, be affected by these feed ingredients.

  9. Reduction of Aflatoxins in Apricot Kernels by Electronic and Manual Color Sorting

    Directory of Open Access Journals (Sweden)

    Rosanna Zivoli

    2016-01-01

    Full Text Available The efficacy of color sorting on reducing aflatoxin levels in shelled apricot kernels was assessed. Naturally-contaminated kernels were submitted to an electronic optical sorter or blanched, peeled, and manually sorted to visually identify and sort discolored kernels (dark and spotted from healthy ones. The samples obtained from the two sorting approaches were ground, homogenized, and analysed by HPLC-FLD for their aflatoxin content. A mass balance approach was used to measure the distribution of aflatoxins in the collected fractions. Aflatoxin B1 and B2 were identified and quantitated in all collected fractions at levels ranging from 1.7 to 22,451.5 µg/kg of AFB1 + AFB2, whereas AFG1 and AFG2 were not detected. Excellent results were obtained by manual sorting of peeled kernels since the removal of discolored kernels (2.6%–19.9% of total peeled kernels removed 97.3%–99.5% of total aflatoxins. The combination of peeling and visual/manual separation of discolored kernels is a feasible strategy to remove 97%–99% of aflatoxins accumulated in naturally-contaminated samples. Electronic optical sorter gave highly variable results since the amount of AFB1 + AFB2 measured in rejected fractions (15%–18% of total kernels ranged from 13% to 59% of total aflatoxins. An improved immunoaffinity-based HPLC-FLD method having low limits of detection for the four aflatoxins (0.01–0.05 µg/kg was developed and used to monitor the occurrence of aflatoxins in 47 commercial products containing apricot kernels and/or almonds commercialized in Italy. Low aflatoxin levels were found in 38% of the tested samples and ranged from 0.06 to 1.50 μg/kg for AFB1 and from 0.06 to 1.79 μg/kg for total aflatoxins.

  10. Reduction of Aflatoxins in Apricot Kernels by Electronic and Manual Color Sorting.

    Science.gov (United States)

    Zivoli, Rosanna; Gambacorta, Lucia; Piemontese, Luca; Solfrizzo, Michele

    2016-01-19

    The efficacy of color sorting on reducing aflatoxin levels in shelled apricot kernels was assessed. Naturally-contaminated kernels were submitted to an electronic optical sorter or blanched, peeled, and manually sorted to visually identify and sort discolored kernels (dark and spotted) from healthy ones. The samples obtained from the two sorting approaches were ground, homogenized, and analysed by HPLC-FLD for their aflatoxin content. A mass balance approach was used to measure the distribution of aflatoxins in the collected fractions. Aflatoxin B₁ and B₂ were identified and quantitated in all collected fractions at levels ranging from 1.7 to 22,451.5 µg/kg of AFB₁ + AFB₂, whereas AFG₁ and AFG₂ were not detected. Excellent results were obtained by manual sorting of peeled kernels since the removal of discolored kernels (2.6%-19.9% of total peeled kernels) removed 97.3%-99.5% of total aflatoxins. The combination of peeling and visual/manual separation of discolored kernels is a feasible strategy to remove 97%-99% of aflatoxins accumulated in naturally-contaminated samples. Electronic optical sorter gave highly variable results since the amount of AFB₁ + AFB₂ measured in rejected fractions (15%-18% of total kernels) ranged from 13% to 59% of total aflatoxins. An improved immunoaffinity-based HPLC-FLD method having low limits of detection for the four aflatoxins (0.01-0.05 µg/kg) was developed and used to monitor the occurrence of aflatoxins in 47 commercial products containing apricot kernels and/or almonds commercialized in Italy. Low aflatoxin levels were found in 38% of the tested samples and ranged from 0.06 to 1.50 μg/kg for AFB₁ and from 0.06 to 1.79 μg/kg for total aflatoxins.

  11. Nonlinear projection trick in kernel methods: an alternative to the kernel trick.

    Science.gov (United States)

    Kwak, Nojun

    2013-12-01

    In kernel methods such as kernel principal component analysis (PCA) and support vector machines, the so called kernel trick is used to avoid direct calculations in a high (virtually infinite) dimensional kernel space. In this brief, based on the fact that the effective dimensionality of a kernel space is less than the number of training samples, we propose an alternative to the kernel trick that explicitly maps the input data into a reduced dimensional kernel space. This is easily obtained by the eigenvalue decomposition of the kernel matrix. The proposed method is named as the nonlinear projection trick in contrast to the kernel trick. With this technique, the applicability of the kernel methods is widened to arbitrary algorithms that do not use the dot product. The equivalence between the kernel trick and the nonlinear projection trick is shown for several conventional kernel methods. In addition, we extend PCA-L1, which uses L1-norm instead of L2-norm (or dot product), into a kernel version and show the effectiveness of the proposed approach.

  12. Theory of reproducing kernels and applications

    CERN Document Server

    Saitoh, Saburou

    2016-01-01

    This book provides a large extension of the general theory of reproducing kernels published by N. Aronszajn in 1950, with many concrete applications. In Chapter 1, many concrete reproducing kernels are first introduced with detailed information. Chapter 2 presents a general and global theory of reproducing kernels with basic applications in a self-contained way. Many fundamental operations among reproducing kernel Hilbert spaces are dealt with. Chapter 2 is the heart of this book. Chapter 3 is devoted to the Tikhonov regularization using the theory of reproducing kernels with applications to numerical and practical solutions of bounded linear operator equations. In Chapter 4, the numerical real inversion formulas of the Laplace transform are presented by applying the Tikhonov regularization, where the reproducing kernels play a key role in the results. Chapter 5 deals with ordinary differential equations; Chapter 6 includes many concrete results for various fundamental partial differential equations. In Chapt...

  13. Filters, reproducing kernel, and adaptive meshfree method

    Science.gov (United States)

    You, Y.; Chen, J.-S.; Lu, H.

    Reproducing kernel, with its intrinsic feature of moving averaging, can be utilized as a low-pass filter with scale decomposition capability. The discrete convolution of two nth order reproducing kernels with arbitrary support size in each kernel results in a filtered reproducing kernel function that has the same reproducing order. This property is utilized to separate the numerical solution into an unfiltered lower order portion and a filtered higher order portion. As such, the corresponding high-pass filter of this reproducing kernel filter can be used to identify the locations of high gradient, and consequently serves as an operator for error indication in meshfree analysis. In conjunction with the naturally conforming property of the reproducing kernel approximation, a meshfree adaptivity method is also proposed.

  14. Effect of some degossypolisation treatments of cottonseed meal on its functional properties

    Directory of Open Access Journals (Sweden)

    Mohamed, S. S.

    1993-10-01

    Full Text Available The presence of gossypol is a limiting factor in the use of cottonseed meal for animal feed and human foods. Gossypol in the free form has been found to be toxic to monogastric animals and the Protein Advisor Group of U.N. has limited its content in cottonseed protein products to 0,06%. In the present paper the effect of some degossypolisation techniques on the functional properties of cottonseed meals has been studied. Best results were obtained with the acetic acid method as it improved the nitrogen solubility and available lysine, reduced the free gossypol to 0,03% and enhanced the water absorption capacity, wettability and flowability. The protein product resulting from this treatment can be incorporated into bakery and instant products. The azeotrope: ammonium treatment produced similar effects. Ethanolamine treatment is recommended for the preparation of protein products for instant foods.

    La presencia de gosipol es un factor limitante en el uso de harina de semilla de algodón para la alimentación animal y humana. El gosipol, en forma libre, ha sido encontrado tóxico para animales monogástricos, y el Grupo Asesor en Proteína de Naciones Unidas ha limitado su contenido en productos proteínicos de semilla de algodón al 0,06%. En el presente trabajo se ha estudiado el efecto de algunas técnicas de desgosiposilación sobre las propiedades funcionales de harinas de semillas de algodón. Los mejores resultados se obtuvieron con el método del ácido acético ya que mejoró la solubilidad de nitrógeno y lisina disponible, redujo el gosipol libre al 0,03% y aumentó la capacidad de absorción de agua, humectabilidad y fluidez. El producto proteínico resultante de este tratamiento puede ser incorporado en productos alimenticios instantáneos y horneados. El tratamiento azeótropo: amonio produjo efectos similares. El tratamiento con etanolamina está recomendado para la preparación de productos proteínicos para alimentos instantáneos.

  15. Treatments of free fatty acids to prevent or decrease colour fixation in cottonseed oil

    Directory of Open Access Journals (Sweden)

    Helmy, H. E.

    1994-12-01

    Full Text Available Some treatments have been investigated to prevent or remove colour fixation of cottonseed oil containing high level of free fatty acids without using excess of sodium hydroxide in the refining step. The treatments included use of sodium carbonate and ethanolamine before and after subjecting a crude cottonseed oil containing excess of free fatty acid to a colour fixation treatment.
    The results revealed that the carbonate/ethanolamine treatment improved the oil colour by decreasing the free fatty acids and gossypol in the oil, without using any excess of sodium hydroxide.
    Carrying out the carbonate/ethanolamine treatment on cottonseed oil with high levels of free fatty acid before colour fixation takes place is more recommended than carrying out the same treatment on the same oil after it has been fixed.

    Se han investigado algunos tratamientos para prevenir o eliminar la fijación del color de aceite de semilla de algodón que contienen alto nivel de ácidos grasos libres, sin utilizar un exceso de hidróxido sódico en la etapa de refinación.
    Los tratamientos incluyeron el uso de carbonato sódico y etanolamina antes y después, sometiendo un aceite crudo de semilla de algodón que contiene exceso de ácidos grasos libres a tratamiento de fijación del color.
    Los resultados mostraron que el tratamiento carbonato/etanolamina mejoró el color del aceite por disminución de los ácidos grasos libres y gosipol en el aceite, sin utilizar un exceso de hidróxido sódico.
    Llevar a cabo el tratamiento con carbonato/etanolamina sobre aceite de semilla de algodón con niveles altos de ácidos grasos libres antes que tenga lugar la fijación del color es más recomendable que llevar a cabo el mismo tratamiento sobre el mismo aceite después de que se haya fijado.

  16. Kernel principal component analysis for change detection

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg; Morton, J.C.

    2008-01-01

    region acquired at two different time points. If change over time does not dominate the scene, the projection of the original two bands onto the second eigenvector will show change over time. In this paper a kernel version of PCA is used to carry out the analysis. Unlike ordinary PCA, kernel PCA...... with a Gaussian kernel successfully finds the change observations in a case where nonlinearities are introduced artificially....

  17. Tame Kernels of Pure Cubic Fields

    Institute of Scientific and Technical Information of China (English)

    Xiao Yun CHENG

    2012-01-01

    In this paper,we study the p-rank of the tame kernels of pure cubic fields.In particular,we prove that for a fixed positive integer m,there exist infinitely many pure cubic fields whose 3-rank of the tame kernel equal to m.As an application,we determine the 3-rank of their tame kernels for some special pure cubic fields.

  18. Kernel Factor Analysis Algorithm with Varimax

    Institute of Scientific and Technical Information of China (English)

    Xia Guoen; Jin Weidong; Zhang Gexiang

    2006-01-01

    Kernal factor analysis (KFA) with varimax was proposed by using Mercer kernel function which can map the data in the original space to a high-dimensional feature space, and was compared with the kernel principle component analysis (KPCA). The results show that the best error rate in handwritten digit recognition by kernel factor analysis with varimax (4.2%) was superior to KPCA (4.4%). The KFA with varimax could more accurately image handwritten digit recognition.

  19. Convergence of barycentric coordinates to barycentric kernels

    KAUST Repository

    Kosinka, Jiří

    2016-02-12

    We investigate the close correspondence between barycentric coordinates and barycentric kernels from the point of view of the limit process when finer and finer polygons converge to a smooth convex domain. We show that any barycentric kernel is the limit of a set of barycentric coordinates and prove that the convergence rate is quadratic. Our convergence analysis extends naturally to barycentric interpolants and mappings induced by barycentric coordinates and kernels. We verify our theoretical convergence results numerically on several examples.

  20. Efficient classification for additive kernel SVMs.

    Science.gov (United States)

    Maji, Subhransu; Berg, Alexander C; Malik, Jitendra

    2013-01-01

    We show that a class of nonlinear kernel SVMs admits approximate classifiers with runtime and memory complexity that is independent of the number of support vectors. This class of kernels, which we refer to as additive kernels, includes widely used kernels for histogram-based image comparison like intersection and chi-squared kernels. Additive kernel SVMs can offer significant improvements in accuracy over linear SVMs on a wide variety of tasks while having the same runtime, making them practical for large-scale recognition or real-time detection tasks. We present experiments on a variety of datasets, including the INRIA person, Daimler-Chrysler pedestrians, UIUC Cars, Caltech-101, MNIST, and USPS digits, to demonstrate the effectiveness of our method for efficient evaluation of SVMs with additive kernels. Since its introduction, our method has become integral to various state-of-the-art systems for PASCAL VOC object detection/image classification, ImageNet Challenge, TRECVID, etc. The techniques we propose can also be applied to settings where evaluation of weighted additive kernels is required, which include kernelized versions of PCA, LDA, regression, k-means, as well as speeding up the inner loop of SVM classifier training algorithms.

  1. Molecular hydrodynamics from memory kernels

    CERN Document Server

    Lesnicki, Dominika; Carof, Antoine; Rotenberg, Benjamin

    2016-01-01

    The memory kernel for a tagged particle in a fluid, computed from molecular dynamics simulations, decays algebraically as $t^{-3/2}$. We show how the hydrodynamic Basset-Boussinesq force naturally emerges from this long-time tail and generalize the concept of hydrodynamic added mass. This mass term is negative in the present case of a molecular solute, at odds with incompressible hydrodynamics predictions. We finally discuss the various contributions to the friction, the associated time scales and the cross-over between the molecular and hydrodynamic regimes upon increasing the solute radius.

  2. Hilbertian kernels and spline functions

    CERN Document Server

    Atteia, M

    1992-01-01

    In this monograph, which is an extensive study of Hilbertian approximation, the emphasis is placed on spline functions theory. The origin of the book was an effort to show that spline theory parallels Hilbertian Kernel theory, not only for splines derived from minimization of a quadratic functional but more generally for splines considered as piecewise functions type. Being as far as possible self-contained, the book may be used as a reference, with information about developments in linear approximation, convex optimization, mechanics and partial differential equations.

  3. Biocatalytic production of biodiesel from cottonseed oil: Standardization of process parameters and comparison of fuel characteristics

    Energy Technology Data Exchange (ETDEWEB)

    Chattopadhyay, Soham; Karemore, Ankush; Das, Sancharini; Sen, Ramkrishna [Department of Biotechnology, Indian Institute of Technology Kharagpur, West Bengal 721302 (India); Deysarkar, Asoke [PfP Technology LLC., 14227 Fern, Houston, TX 77079 (United States)

    2011-04-15

    The enzymatic production of biodiesel by transesterification of cottonseed oil was studied using low cost crude pancreatic lipase as catalyst in a batch system. The effects of the critical process parameters including water percentage, methanol:oil ratio, enzyme concentration, buffer pH and reaction temperature were determined. Maximum conversion of 75-80% was achieved after 4 h at 37 C, pH 7.0 and with 1:15 M ratio of oil to methanol, 0.5% (wt of oil) enzyme and water concentration of 5% (wt of oil). Various organic solvents were tested among which a partially polar solvent (t-butanol) was found to be suitable for the reaction. The major fuel characteristics like specific gravity, kinematic viscosity, flash point and calorific value of the 20:80 blends (B20) of the fatty acid methyl esters with petroleum diesel conformed very closely to those of American Society for Testing Materials (ASTM) standards. (author)

  4. Effect of cottonseed oilcake inclusion on ostrich growth performance and meat chemical composition.

    Science.gov (United States)

    Dalle Zotte, A; Brand, T S; Hoffman, L C; Schoon, K; Cullere, M; Swart, R

    2013-02-01

    This study investigated the effect of replacing dietary soybean oilcake meal with increasing levels of cottonseed oilcake meal (CSOCM) on the growth performance and meat (Iliofibularis muscle) chemical composition of ostriches in order to decrease total feed costs. A total of 105 ostriches were divided into five feeding groups according to the CSOCM inclusion level in the whole diet: Control (0% CSOCM), 3%, 6%, 9% and 12% CSOCM (of the whole diet), and fed with experimental diets from 6 to 13 months of age. As a result of feeding CSOCM, the final live weight and the average daily gain significantly increased in the 12% CSOCM group. The proximate composition, cholesterol content, mineral and fatty acid profile of the meat remained unaffected. Thus CSOCM may be used as an alternative protein source to the more expensive soybean oilcake meal in ostrich nutrition.

  5. Pretreatment of cottonseed flakes with proteases and an amylase for higher oil yields

    Directory of Open Access Journals (Sweden)

    Hassanein, Minar M.

    2007-09-01

    Full Text Available The effect of enzymatic pretreatment of cottonseed flakes on oil extractability was studied. The enzymes investigated included bacterial protease (Bp, papain (Pa, savinase (S, termamyl (T, pectinase (Pe and cellulase (C. The variables studied during the enzymatic hydrolysis experiments were: enzyme concentration, moisture: cottonseed flakes ratio, and time of hydrolysis. Enzymatic hydrolysis experiments were first carried out with a single enzyme, then with enzyme mixtures formulated according to the results of single enzyme treatments. Results were evaluated based on the relative increase in oil extractability, and some oil characteristics in comparison with untreated cottonseed flakes (control. Pretreatment with enzyme mixtures resulted in a relative increase in oil extractability that was higher than single enzyme pretreatment and the control. Statistical analysis showed a significant difference (at 5% level between the control and all enzymatically treated oils as well as among different enzymatically treated oils. The relative increase in oil extractability due to pretreatment with enzyme mixtures were in the following order: S: Pe: Bp>S: P>S: C: Pe>S: Bp>S:T>S: C >S: Pa with values 44.9%, 38.9%, 37.1%, 34.9%, 30.1%, 28.9%, respectively. Enzymatic pretreatment of cottonseed flakes resulted in oils with fatty acid composition, acid value, iodine value and peroxide values that were generally comparable to the control.En este trabajo se estudió el efecto del pretratamiento con enzimas sobre la extractabilidad del aceite en hojuelas de semilla de algodón. Las enzimas que se investigaron fueron proteasa bacteriana (Bp, papaína (Pa, savinasa (S, temamil (T, pectinasa (Pe y celulasa (C. Las variables estudiadas durante los experimentos de hidrólisis enzimática fueron: concentración de la enzima, ratio humedad:cantidad de hojuelas y tiempo de hidrólisis. Estos experimentos se realizaron primeramente con una sola enzima y posteriormente con

  6. Fractionation of commercial hexane and use of its fractions as extracting solvent of cottonseed oil

    Directory of Open Access Journals (Sweden)

    Megahed, Ola A.

    2001-04-01

    Full Text Available The problem of producing off-graded cottonseed oil using locally produced commercial hexane as extracting solvent has explored this research. It was aimed in this work to investigate whether this problem can be solved by controlling the boiling range of the extracting solvent. Four different hexane fractions of different boiling ranges were prepared from commercial hexane. The boiling range of commercial hexane was 62-68ºC while the boiling ranges of the four fractions were 62- 64, 64-65, 65-66 and 66-68ºC. Commercial hexane and the prepared four hexane fractions were then used to extract cottonseed oil from a fixed seed sample. The five crude oil samples were then refined and bleached and their colours were measured. The results have shown that the heaviest hexane fraction ( b.r 66-68ºC produced the lightest coloured oils. The colour index of the bleached oil using this heavy cut was 190 compared to 350 using the original commercial hexane. However, the production of a commercial hexane cut having a narrow boiling range will be costly. Therefore, this research has been extended to investigate the suitability of a heavy petroleum cut which has a boiling range as wide as that of commercial hexane to extract cottonseed oil. The boiling range of this cut was 66-72ºC. The obtained results proved that the extraction of cottonseed oil using that heavy petroleum fraction produces much lighter oil than the use of conventional hexane solvent.En esta investigación se ha examinado el problema de producir aceite de semilla de algodón sin-clasificar usando hexano comercial producido localmente como disolvente. El objetivo de este trabajo fue investigar si este problema puede ser solucionado controlando el rango de ebullición del disolvente extractante. Cuatro fracciones diferentes de hexano de diversos rangos de ebullición fueron preparadas del hexano comercial. El rango al que ebullía el hexano comercial era 62-68ºC mientras que los

  7. Bees wax and its unsaponifiables as natural preservative for butter and cottonseed oils

    Directory of Open Access Journals (Sweden)

    Farag, R. S.

    1993-06-01

    Full Text Available Simple model systems consisting of butter oil or refined cottonseed oil mixed with melted bees wax and its unsaponifiables were designated to study their hydrolytic and oxidative rancidity during storage. Whole bees wax at 0,5 and 1% levels possessed significant pro-hydrolytic activity whilst its unsaponifiables at 0,25 and 0,5% exhibited antihydrolytic effect on butter oil. The addition of whole bees wax at 0,5 and 1 % caused no effect on peroxide and thiobarbituric acid values of butter oil. However, bees wax unsaponifiables significantly reduced both peroxide and thiobarbituric acid values of stored butter oil. Bees wax unsaponifiables added to refined cottonseed oil had no effect on the acid value, whilst whole bees wax possessed significant prohydrolytic activity. The data for peroxide and thiobarbituric acid values of refined cottonseed oil demonstrated that both whole bees wax and its unsaponifiables had approximately the same antioxidant efficacy. The effectiveness of the added materials on the secondary oxidation products of refined cottonseed oil can be ranked according to its inhibition activity as follows: BHT (200 ppm > bees wax (1% > bees wax (0,5% > bees wax unsaponifiables (0,5% > bees wax unsaponifiables (0,25% > control.

    aceites de semilla de algodón Sistemas modelo simples consistentes en aceite de mantequilla o aceite de semilla de algodón refinado mezclado con cera de abeja derretida y su insaponificable fueron diseñados para estudiar su rancidez oxidativa e hidrolítica durante el almacenamiento. La cera de abeja íntegra a niveles del 0,5 y 1% tuvo una actividad pro-hidrolítica significativa, mientras que su insaponificable al 0,25 y 0,5% exhibió efecto antihidrolítico sobre el aceite de mantequilla. La adición de cera de abeja íntegra al 0,5 y 1% no causó efecto sobre el índice de peróxido y ácido tiobarbitúrico del aceite de mantequilla. Sin embargo, el insaponificable de cera de abeja redujo

  8. Integrated Management Strategies Increase Cottonseed, Oil and Protein Production: The Key Role of Carbohydrate Metabolism

    Science.gov (United States)

    Yang, Hongkun; Zhang, Xinyue; Chen, Binglin; Meng, Yali; Wang, Youhua; Zhao, Wenqing; Zhou, Zhiguo

    2017-01-01

    Cottonseed, oil, and protein, as the by-products of cotton production, have the potential to provide commodities to meet the increasing demand of renewable bio-fuels and ruminant feed. An increase in crop yield per unit area requires high-yielding cultivar management with an economic nitrogen (N) rate, an optimal N application schedule, high-yielding plant populations and strong seedlings. Whether the integration of these agronomic practices into a coherent management system can increase the productivity of cotton fiber, embryo oil and protein requires experimental elucidation. In this 2-year study, conventional management practices (CM) were used as a control, and two integrated management strategies (IMS1 and IMS2) were considered at two soil fertility levels (high soil fertility and low soil fertility) to analyze the metabolic and biochemical traits of cotton embryos. The results illustrate that the cottonseed, oil, and protein yields for IMS1 and IMS2 were significantly higher than those under CM at both soil fertility levels and the fiber yield increased as well. The IMS regulated the maternal photo thermal environment by delaying the flowering date, resulting in increases in the seed weight. In developing cotton embryos, the IMS increased the embryo weight accumulation rate and biomass partitioning into oil and protein, which were associated with high activities of H+-ATPase, H+-PPase, sucrose synthase (SuSy), and cell wall invertase (C-INV) and low activities of sucrose phosphate synthase (SPS) and vacuole invertase (V-INV). Increased hexoses (D-fructose, D-glucose) content contributed to the oil and protein contents. These results suggest that increased sucrose/H+ symport, sucrose hydrolysis, hexoses synthesis, and cumulative photo-thermal product (PTP), especially in the early stage of embryo growth, play a dominant role in the high productivity of cotton oil and protein. PMID:28194156

  9. The Induction of Lycopene in Germinating Cottonseed with 2-(4-Methylphenoxy Triethylamine (MPTA

    Directory of Open Access Journals (Sweden)

    Lorraine S. Puckhaber

    2011-01-01

    Full Text Available Problem statement: Increasing carotenoids content in foods was currently of great interest. The present paper reports strong stimulatory effect of MPTA on the carotenogenesis in cotton, which was used as a model. Approach: Cotton seedlings were treated with MPTA vs. water and germinated in the dark. The levels of carotenoids were determined by HPLC and the expression levels of the key genes were determined by real-time PCR. Results: In the water treated dark germinating control cotton seedlings only low levels of lutein and β-carotene were detected. Treatment of dark germinating seedlings with substituted triethylamine MPTA resulted in an 88% reduction of lutein and a 100% reduction of β-carotene and nearly 18 fold increases in the total carotenoid production with the increase mainly due to the formation of lycopene and its precursors. Treatment of the germinating cottonseed with MPTA and antibiotics such as actinomycin-D, α-amanitin, cordycepin or cycloheximide reduced the stimulatory effect of MPTA. This indicates that increased biosynthesis of carotenes with MPTA was dependent on gene expression, polyadenylation of the gene transcripts and translation of the mRNA on 80S ribosomes. In addition, the relative transcript levels of phytoene synthase, psy1 and psy2 in the MPTA germinating seedlings increased 6.5 and 2.2 fold, respectively, compared to the transcript levels in the H2O controls. The relative levels of lyc-β and lyc-ε transcripts in the MPTA treated seed increased 3.7 and 3.6 fold, respectively, compared to the H2O controls. Conclusion: These results support the conclusion that the accumulation of lycopene and lycopene precursors in the MPTA treated germinating cottonseed was dependent on the partial blockage of LYC-β and LYC-ε and the induced expression and translation of the psy genes leading to an increased carotenogenesis.

  10. Supplementation with Cashew Nut and Cottonseed Meal to Modify Fatty Acid Content in Lamb Meat.

    Science.gov (United States)

    Pereira, Elzania S; Mizubuti, Ivone Y; Oliveira, Ronaldo L; Pinto, Andréa P; Ribeiro, Edson L A; Gadelha, Carla R F; Campos, Ana C N; Pereira, Marília F; Carneiro, Maria S S; Arruda, Paulo C; Silva, Luciano P

    2016-09-01

    This study evaluates the effect of cashew nut meal (CNM), whole cottonseed (WCS), and calcium salts of long-chain fatty acids (Ca-LCFA) on the fatty acid profiles of meat from hair lambs. Thirty-five 60-d-old, male, noncastrated Santa Ines lambs with an initial average body weight of 13.00 ± 1.80 kg were used in a randomized complete-block design with 7 blocks and 5 treatments. The experimental treatments consisted of a control diet (CON) without supplemental lipids and 4 test diets with different lipid supplements that were selected according to the degree of protection from ruminal hydrogenation and their polyunsaturated fatty acid richness. The tests diets included the following modifications: supplementation with WCS, supplementation with CNM, supplementation with both cottonseed and CNM (CSCNM), and supplementation with Ca-LCFA. The C18:1n9c content was highest in the meat of the animals fed the CNM diet (42.00%). The meat from lambs fed the WCS and Ca-LCFA diets had higher C18:0 contents (25.23 and 22.80%, respectively). The C16:1 content was higher in the meat from the animals fed the CNM and CON diets (1.54 and 1.49%, respectively). C18:2c9t11 concentration was higher in the meat from the animals fed the Ca-LCFA and CNM diets. The estimated enzyme activity of Δ9-desaturase C18 was highest in the muscles of the lambs fed the CON, CNM, and CSCNM diets. The use of cashew nuts in the diet resulted in an increase in the C18:2c9t11 content of the lamb meat, which improved the nutritional characteristics of the fat.

  11. A robust, high-throughput method for computing maize ear, cob, and kernel attributes automatically from images.

    Science.gov (United States)

    Miller, Nathan D; Haase, Nicholas J; Lee, Jonghyun; Kaeppler, Shawn M; de Leon, Natalia; Spalding, Edgar P

    2017-01-01

    Grain yield of the maize plant depends on the sizes, shapes, and numbers of ears and the kernels they bear. An automated pipeline that can measure these components of yield from easily-obtained digital images is needed to advance our understanding of this globally important crop. Here we present three custom algorithms designed to compute such yield components automatically from digital images acquired by a low-cost platform. One algorithm determines the average space each kernel occupies along the cob axis using a sliding-window Fourier transform analysis of image intensity features. A second counts individual kernels removed from ears, including those in clusters. A third measures each kernel's major and minor axis after a Bayesian analysis of contour points identifies the kernel tip. Dimensionless ear and kernel shape traits that may interrelate yield components are measured by principal components analysis of contour point sets. Increased objectivity and speed compared to typical manual methods are achieved without loss of accuracy as evidenced by high correlations with ground truth measurements and simulated data. Millimeter-scale differences among ear, cob, and kernel traits that ranged more than 2.5-fold across a diverse group of inbred maize lines were resolved. This system for measuring maize ear, cob, and kernel attributes is being used by multiple research groups as an automated Web service running on community high-throughput computing and distributed data storage infrastructure. Users may create their own workflow using the source code that is staged for download on a public repository.

  12. The Production of Biodiesel from Cottonseed Oil Using Rhizopus oryzae Whole Cell Biocatalysts

    Science.gov (United States)

    Athalye, Sneha Kishor

    Biodiesel is an environmentally friendly alternative to fossil fuels which have become increasingly expensive in recent times. An alternate approach to alkaline biodiesel production is needed as catalyst miscibility with the glycerol by-product, generation of large amounts of waste water, and saponification of the feedstock are major disadvantages associated with the process. Lipases are water soluble enzymes which act as catalysts in many lipid based reactions. Reuse of lipases can significantly reduce cost of enzymatic biodiesel production; however retention of lipolytic activity still remains a challenge. Use of microbial cells immobilized on various surfaces like sponge, foam and plastics as biocatalysts instead of extracted enzyme could help overcome this problem. A novel, rigid biomass support with high surface area made from recyclable polyethylene (Bioblok(TM)) was used in this study. Several fungal and bacterial species have been reported to possess appreciable levels of lipase activity. The biomass production and immobilization as well as lipase activity of three different species; Candida rugosa (ATCC #38772), Aspergillus oryzae (ATCC #58299), and Rhizopus oryzae (ATTC #34612) were tested. C. rugosa did not attach well to the support particles while A.oryzae had lower biomass accumulation of 6.1 g (dry cell wt)/L compared to 11.8 g (dry cell wt)/L for R.oryzae. Hence Rhizopus oryzae, fungal specie with cell surface bound lipase was selected for the current study. The study investigated the influence of media composition and growth time of the R.oryzae whole cell biocatalysts, immobilized on the BSPs, for FAME production from cottonseed oil. R.oryzae BSPs grown in basal media supplemented with 1% (w/v) of glucose or oil or both for 48 h, 72 h or 90 h were used in a 36 h transesterification reaction with cottonseed oil and methanol. BSPs grown in both glucose and oil supplemented medium for 72 h had the highest conversion of 22.4% (wt/wt) and a biomass

  13. Differentiable Kernels in Generalized Matrix Learning Vector Quantization

    NARCIS (Netherlands)

    Kästner, M.; Nebel, D.; Riedel, M.; Biehl, M.; Villmann, T.

    2013-01-01

    In the present paper we investigate the application of differentiable kernel for generalized matrix learning vector quantization as an alternative kernel-based classifier, which additionally provides classification dependent data visualization. We show that the concept of differentiable kernels allo

  14. Kernel current source density method.

    Science.gov (United States)

    Potworowski, Jan; Jakuczun, Wit; Lȩski, Szymon; Wójcik, Daniel

    2012-02-01

    Local field potentials (LFP), the low-frequency part of extracellular electrical recordings, are a measure of the neural activity reflecting dendritic processing of synaptic inputs to neuronal populations. To localize synaptic dynamics, it is convenient, whenever possible, to estimate the density of transmembrane current sources (CSD) generating the LFP. In this work, we propose a new framework, the kernel current source density method (kCSD), for nonparametric estimation of CSD from LFP recorded from arbitrarily distributed electrodes using kernel methods. We test specific implementations of this framework on model data measured with one-, two-, and three-dimensional multielectrode setups. We compare these methods with the traditional approach through numerical approximation of the Laplacian and with the recently developed inverse current source density methods (iCSD). We show that iCSD is a special case of kCSD. The proposed method opens up new experimental possibilities for CSD analysis from existing or new recordings on arbitrarily distributed electrodes (not necessarily on a grid), which can be obtained in extracellular recordings of single unit activity with multiple electrodes.

  15. Filtering algorithms using shiftable kernels

    CERN Document Server

    Chaudhury, Kunal Narayan

    2011-01-01

    It was recently demonstrated in [4][arxiv:1105.4204] that the non-linear bilateral filter \\cite{Tomasi} can be efficiently implemented using an O(1) or constant-time algorithm. At the heart of this algorithm was the idea of approximating the Gaussian range kernel of the bilateral filter using trigonometric functions. In this letter, we explain how the idea in [4] can be extended to few other linear and non-linear filters [18,21,2]. While some of these filters have received a lot of attention in recent years, they are known to be computationally intensive. To extend the idea in \\cite{Chaudhury2011}, we identify a central property of trigonometric functions, called shiftability, that allows us to exploit the redundancy inherent in the filtering operations. In particular, using shiftable kernels, we show how certain complex filtering can be reduced to simply that of computing the moving sum of a stack of images. Each image in the stack is obtained through an elementary pointwise transform of the input image. Thi...

  16. Kernel parameter dependence in spatial factor analysis

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg

    2010-01-01

    feature space via the kernel function and then performing a linear analysis in that space. In this paper we shall apply a kernel version of maximum autocorrelation factor (MAF) [7, 8] analysis to irregularly sampled stream sediment geochemistry data from South Greenland and illustrate the dependence...

  17. Improving the Bandwidth Selection in Kernel Equating

    Science.gov (United States)

    Andersson, Björn; von Davier, Alina A.

    2014-01-01

    We investigate the current bandwidth selection methods in kernel equating and propose a method based on Silverman's rule of thumb for selecting the bandwidth parameters. In kernel equating, the bandwidth parameters have previously been obtained by minimizing a penalty function. This minimization process has been criticized by practitioners…

  18. Ranking Support Vector Machine with Kernel Approximation.

    Science.gov (United States)

    Chen, Kai; Li, Rongchun; Dou, Yong; Liang, Zhengfa; Lv, Qi

    2017-01-01

    Learning to rank algorithm has become important in recent years due to its successful application in information retrieval, recommender system, and computational biology, and so forth. Ranking support vector machine (RankSVM) is one of the state-of-art ranking models and has been favorably used. Nonlinear RankSVM (RankSVM with nonlinear kernels) can give higher accuracy than linear RankSVM (RankSVM with a linear kernel) for complex nonlinear ranking problem. However, the learning methods for nonlinear RankSVM are still time-consuming because of the calculation of kernel matrix. In this paper, we propose a fast ranking algorithm based on kernel approximation to avoid computing the kernel matrix. We explore two types of kernel approximation methods, namely, the Nyström method and random Fourier features. Primal truncated Newton method is used to optimize the pairwise L2-loss (squared Hinge-loss) objective function of the ranking model after the nonlinear kernel approximation. Experimental results demonstrate that our proposed method gets a much faster training speed than kernel RankSVM and achieves comparable or better performance over state-of-the-art ranking algorithms.

  19. Generalized Derivative Based Kernelized Learning Vector Quantization

    NARCIS (Netherlands)

    Schleif, Frank-Michael; Villmann, Thomas; Hammer, Barbara; Schneider, Petra; Biehl, Michael; Fyfe, Colin; Tino, Peter; Charles, Darryl; Garcia-Osoro, Cesar; Yin, Hujun

    2010-01-01

    We derive a novel derivative based version of kernelized Generalized Learning Vector Quantization (KGLVQ) as an effective, easy to interpret, prototype based and kernelized classifier. It is called D-KGLVQ and we provide generalization error bounds, experimental results on real world data, showing t

  20. PALM KERNEL SHELL AS AGGREGATE FOR LIGHT

    African Journals Online (AJOL)

    of cement, sand, gravel andpalm kernel shells respectively gave the highest compressive strength of ... Keywords: Aggregate, Cement, Concrete, Sand, Palm Kernel Shell. ... delivered to the jOb Slte in a plastic ... structures, breakwaters, piers and docks .... related to cement content at a .... sheet and the summary is shown.

  1. Panel data specifications in nonparametric kernel regression

    DEFF Research Database (Denmark)

    Czekaj, Tomasz Gerard; Henningsen, Arne

    parametric panel data estimators to analyse the production technology of Polish crop farms. The results of our nonparametric kernel regressions generally differ from the estimates of the parametric models but they only slightly depend on the choice of the kernel functions. Based on economic reasoning, we...

  2. Seismic Hazard Analysis Using the Adaptive Kernel Density Estimation Technique for Chennai City

    Science.gov (United States)

    Ramanna, C. K.; Dodagoudar, G. R.

    2012-01-01

    Conventional method of probabilistic seismic hazard analysis (PSHA) using the Cornell-McGuire approach requires identification of homogeneous source zones as the first step. This criterion brings along many issues and, hence, several alternative methods to hazard estimation have come up in the last few years. Methods such as zoneless or zone-free methods, modelling of earth's crust using numerical methods with finite element analysis, have been proposed. Delineating a homogeneous source zone in regions of distributed seismicity and/or diffused seismicity is rather a difficult task. In this study, the zone-free method using the adaptive kernel technique to hazard estimation is explored for regions having distributed and diffused seismicity. Chennai city is in such a region with low to moderate seismicity so it has been used as a case study. The adaptive kernel technique is statistically superior to the fixed kernel technique primarily because the bandwidth of the kernel is varied spatially depending on the clustering or sparseness of the epicentres. Although the fixed kernel technique has proven to work well in general density estimation cases, it fails to perform in the case of multimodal and long tail distributions. In such situations, the adaptive kernel technique serves the purpose and is more relevant in earthquake engineering as the activity rate probability density surface is multimodal in nature. The peak ground acceleration (PGA) obtained from all the three approaches (i.e., the Cornell-McGuire approach, fixed kernel and adaptive kernel techniques) for 10% probability of exceedance in 50 years is around 0.087 g. The uniform hazard spectra (UHS) are also provided for different structural periods.

  3. Kernel Model Applied in Kernel Direct Discriminant Analysis for the Recognition of Face with Nonlinear Variations

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    A kernel-based discriminant analysis method called kernel direct discriminant analysis is employed, which combines the merit of direct linear discriminant analysis with that of kernel trick. In order to demonstrate its better robustness to the complex and nonlinear variations of real face images, such as illumination, facial expression, scale and pose variations, experiments are carried out on the Olivetti Research Laboratory, Yale and self-built face databases. The results indicate that in contrast to kernel principal component analysis and kernel linear discriminant analysis, the method can achieve lower (7%) error rate using only a very small set of features. Furthermore, a new corrected kernel model is proposed to improve the recognition performance. Experimental results confirm its superiority (1% in terms of recognition rate) to other polynomial kernel models.

  4. Parameter-Free Spectral Kernel Learning

    CERN Document Server

    Mao, Qi

    2012-01-01

    Due to the growing ubiquity of unlabeled data, learning with unlabeled data is attracting increasing attention in machine learning. In this paper, we propose a novel semi-supervised kernel learning method which can seamlessly combine manifold structure of unlabeled data and Regularized Least-Squares (RLS) to learn a new kernel. Interestingly, the new kernel matrix can be obtained analytically with the use of spectral decomposition of graph Laplacian matrix. Hence, the proposed algorithm does not require any numerical optimization solvers. Moreover, by maximizing kernel target alignment on labeled data, we can also learn model parameters automatically with a closed-form solution. For a given graph Laplacian matrix, our proposed method does not need to tune any model parameter including the tradeoff parameter in RLS and the balance parameter for unlabeled data. Extensive experiments on ten benchmark datasets show that our proposed two-stage parameter-free spectral kernel learning algorithm can obtain comparable...

  5. Determination of trace nickel in hydrogenated cottonseed oil by electrothermal atomic absorption spectrometry after microwave-assisted digestion.

    Science.gov (United States)

    Zhang, Gai

    2012-01-01

    Microwave digestion of hydrogenated cottonseed oil prior to trace nickel determination by electrothermal atomic absorption spectrometry (ETAAS) is proposed here for the first time. Currently, the methods outlined in U.S. Pharmacopeia 28 (USP28) or British Pharmacopeia (BP2003) are recommended as the official methods for analyzing nickel in hydrogenated cottonseed oil. With these methods the samples may be pre-treated by a silica or a platinum crucible. However, the samples were easily tarnished during sample pretreatment when using a silica crucible. In contrast, when using a platinum crucible, hydrogenated cottonseed oil acting as a reducing material may react with the platinum and destroy the crucible. The proposed microwave-assisted digestion avoided tarnishing of sample in the process of sample pretreatment and also reduced the cycle of analysis. The programs of microwave digestion and the parameters of ETAAS were optimized. The accuracy of the proposed method was investigated by analyzing real samples. The results were compared with the ones by pressurized-PTFE-bomb acid digestion and ones obtained by the U.S. Pharmacopeia 28 (USP28) method. The new method involves a relatively rapid matrix destruction technique compared with other present methods for the quantification of metals in oil.

  6. Heat-kernel approach for scattering

    CERN Document Server

    Li, Wen-Du

    2015-01-01

    An approach for solving scattering problems, based on two quantum field theory methods, the heat kernel method and the scattering spectral method, is constructed. This approach has a special advantage: it is not only one single approach; it is indeed a set of approaches for solving scattering problems. Concretely, we build a bridge between a scattering problem and the heat kernel method, so that each method of calculating heat kernels can be converted into a method of solving a scattering problem. As applications, we construct two approaches for solving scattering problems based on two heat-kernel expansions: the Seeley-DeWitt expansion and the covariant perturbation theory. In order to apply the heat kernel method to scattering problems, we also calculate two off-diagonal heat-kernel expansions in the frames of the Seeley-DeWitt expansion and the covariant perturbation theory, respectively. Moreover, as an alternative application of the relation between heat kernels and partial-wave phase shifts presented in...

  7. Ideal regularization for learning kernels from labels.

    Science.gov (United States)

    Pan, Binbin; Lai, Jianhuang; Shen, Lixin

    2014-08-01

    In this paper, we propose a new form of regularization that is able to utilize the label information of a data set for learning kernels. The proposed regularization, referred to as ideal regularization, is a linear function of the kernel matrix to be learned. The ideal regularization allows us to develop efficient algorithms to exploit labels. Three applications of the ideal regularization are considered. Firstly, we use the ideal regularization to incorporate the labels into a standard kernel, making the resulting kernel more appropriate for learning tasks. Next, we employ the ideal regularization to learn a data-dependent kernel matrix from an initial kernel matrix (which contains prior similarity information, geometric structures, and labels of the data). Finally, we incorporate the ideal regularization to some state-of-the-art kernel learning problems. With this regularization, these learning problems can be formulated as simpler ones which permit more efficient solvers. Empirical results show that the ideal regularization exploits the labels effectively and efficiently.

  8. Kernel score statistic for dependent data.

    Science.gov (United States)

    Malzahn, Dörthe; Friedrichs, Stefanie; Rosenberger, Albert; Bickeböller, Heike

    2014-01-01

    The kernel score statistic is a global covariance component test over a set of genetic markers. It provides a flexible modeling framework and does not collapse marker information. We generalize the kernel score statistic to allow for familial dependencies and to adjust for random confounder effects. With this extension, we adjust our analysis of real and simulated baseline systolic blood pressure for polygenic familial background. We find that the kernel score test gains appreciably in power through the use of sequencing compared to tag-single-nucleotide polymorphisms for very rare single nucleotide polymorphisms with <1% minor allele frequency.

  9. Kernel-based Maximum Entropy Clustering

    Institute of Scientific and Technical Information of China (English)

    JIANG Wei; QU Jiao; LI Benxi

    2007-01-01

    With the development of Support Vector Machine (SVM),the "kernel method" has been studied in a general way.In this paper,we present a novel Kernel-based Maximum Entropy Clustering algorithm (KMEC).By using mercer kernel functions,the proposed algorithm is firstly map the data from their original space to high dimensional space where the data are expected to be more separable,then perform MEC clustering in the feature space.The experimental results show that the proposed method has better performance in the non-hyperspherical and complex data structure.

  10. Kernel adaptive filtering a comprehensive introduction

    CERN Document Server

    Liu, Weifeng; Haykin, Simon

    2010-01-01

    Online learning from a signal processing perspective There is increased interest in kernel learning algorithms in neural networks and a growing need for nonlinear adaptive algorithms in advanced signal processing, communications, and controls. Kernel Adaptive Filtering is the first book to present a comprehensive, unifying introduction to online learning algorithms in reproducing kernel Hilbert spaces. Based on research being conducted in the Computational Neuro-Engineering Laboratory at the University of Florida and in the Cognitive Systems Laboratory at McMaster University, O

  11. Multiple Operator-valued Kernel Learning

    CERN Document Server

    Kadri, Hachem; Bach, Francis; Preux, Philippe

    2012-01-01

    This paper addresses the problem of learning a finite linear combination of operator-valued kernels. We study this problem in the case of kernel ridge regression for functional responses with a lr-norm constraint on the combination coefficients. We propose a multiple operator-valued kernel learning algorithm based on solving a system of linear operator equations by using a block coordinate descent procedure. We experimentally validate our approach on a functional regression task in the context of finger movement prediction in Brain-Computer Interface (BCI).

  12. Polynomial Kernelizations for $\\MINF_1$ and $\\MNP$

    CERN Document Server

    Kratsch, Stefan

    2009-01-01

    The relation of constant-factor approximability to fixed-parameter tractability and kernelization is a long-standing open question. We prove that two large classes of constant-factor approximable problems, namely $\\MINF_1$ and $\\MNP$, including the well-known subclass $\\MSNP$, admit polynomial kernelizations for their natural decision versions. This extends results of Cai and Chen (JCSS 1997), stating that the standard parameterizations of problems in $\\MSNP$ and $\\MINF_1$ are fixed-parameter tractable, and complements recent research on problems that do not admit polynomial kernelizations (Bodlaender et al. ICALP 2008).

  13. Approximating W projection as a separable kernel

    OpenAIRE

    Merry, Bruce

    2015-01-01

    W projection is a commonly-used approach to allow interferometric imaging to be accelerated by Fast Fourier Transforms (FFTs), but it can require a huge amount of storage for convolution kernels. The kernels are not separable, but we show that they can be closely approximated by separable kernels. The error scales with the fourth power of the field of view, and so is small enough to be ignored at mid to high frequencies. We also show that hybrid imaging algorithms combining W projection with ...

  14. Approximating W projection as a separable kernel

    Science.gov (United States)

    Merry, Bruce

    2016-02-01

    W projection is a commonly used approach to allow interferometric imaging to be accelerated by fast Fourier transforms, but it can require a huge amount of storage for convolution kernels. The kernels are not separable, but we show that they can be closely approximated by separable kernels. The error scales with the fourth power of the field of view, and so is small enough to be ignored at mid- to high frequencies. We also show that hybrid imaging algorithms combining W projection with either faceting, snapshotting, or W stacking allow the error to be made arbitrarily small, making the approximation suitable even for high-resolution wide-field instruments.

  15. Extension of Wirtinger's Calculus in Reproducing Kernel Hilbert Spaces and the Complex Kernel LMS

    CERN Document Server

    Bouboulis, Pantelis

    2010-01-01

    Over the last decade, kernel methods for nonlinear processing have successfully been used in the machine learning community. The primary mathematical tool employed in these methods is the notion of the Reproducing Kernel Hilbert Space. However, so far, the emphasis has been on batch techniques. It is only recently, that online techniques have been considered in the context of adaptive signal processing tasks. Moreover, these efforts have only been focussed on and real valued data sequences. To the best of our knowledge, no kernel-based strategy has been developed, so far, that is able to deal with complex valued signals. In this paper, we present a general framework to attack the problem of adaptive filtering of complex signals, using either real reproducing kernels, taking advantage of a technique called \\textit{complexification} of real RKHSs, or complex reproducing kernels, highlighting the use of the complex gaussian kernel. In order to derive gradients of operators that need to be defined on the associat...

  16. Kernel map compression for speeding the execution of kernel-based methods.

    Science.gov (United States)

    Arif, Omar; Vela, Patricio A

    2011-06-01

    The use of Mercer kernel methods in statistical learning theory provides for strong learning capabilities, as seen in kernel principal component analysis and support vector machines. Unfortunately, after learning, the computational complexity of execution through a kernel is of the order of the size of the training set, which is quite large for many applications. This paper proposes a two-step procedure for arriving at a compact and computationally efficient execution procedure. After learning in the kernel space, the proposed extension exploits the universal approximation capabilities of generalized radial basis function neural networks to efficiently approximate and replace the projections onto the empirical kernel map used during execution. Sample applications demonstrate significant compression of the kernel representation with graceful performance loss.

  17. The Linux kernel as flexible product-line architecture

    NARCIS (Netherlands)

    Jonge, M. de

    2002-01-01

    The Linux kernel source tree is huge ($>$ 125 MB) and inflexible (because it is difficult to add new kernel components). We propose to make this architecture more flexible by assembling kernel source trees dynamically from individual kernel components. Users then, can select what component they real

  18. 7 CFR 51.2296 - Three-fourths half kernel.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 2 2010-01-01 2010-01-01 false Three-fourths half kernel. 51.2296 Section 51.2296 Agriculture Regulations of the Department of Agriculture AGRICULTURAL MARKETING SERVICE (Standards...-fourths half kernel. Three-fourths half kernel means a portion of a half of a kernel which has more...

  19. 7 CFR 981.401 - Adjusted kernel weight.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 8 2010-01-01 2010-01-01 false Adjusted kernel weight. 981.401 Section 981.401... Administrative Rules and Regulations § 981.401 Adjusted kernel weight. (a) Definition. Adjusted kernel weight... kernels in excess of five percent; less shells, if applicable; less processing loss of one percent...

  20. 7 CFR 51.1441 - Half-kernel.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 2 2010-01-01 2010-01-01 false Half-kernel. 51.1441 Section 51.1441 Agriculture... Standards for Grades of Shelled Pecans Definitions § 51.1441 Half-kernel. Half-kernel means one of the separated halves of an entire pecan kernel with not more than one-eighth of its original volume...

  1. 7 CFR 51.1403 - Kernel color classification.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 2 2010-01-01 2010-01-01 false Kernel color classification. 51.1403 Section 51.1403... STANDARDS) United States Standards for Grades of Pecans in the Shell 1 Kernel Color Classification § 51.1403 Kernel color classification. (a) The skin color of pecan kernels may be described in terms of the...

  2. NLO corrections to the Kernel of the BKP-equations

    Energy Technology Data Exchange (ETDEWEB)

    Bartels, J. [Hamburg Univ. (Germany). 2. Inst. fuer Theoretische Physik; Fadin, V.S. [Budker Institute of Nuclear Physics, Novosibirsk (Russian Federation); Novosibirskij Gosudarstvennyj Univ., Novosibirsk (Russian Federation); Lipatov, L.N. [Hamburg Univ. (Germany). 2. Inst. fuer Theoretische Physik; Petersburg Nuclear Physics Institute, Gatchina, St. Petersburg (Russian Federation); Vacca, G.P. [INFN, Sezione di Bologna (Italy)

    2012-10-02

    We present results for the NLO kernel of the BKP equations for composite states of three reggeized gluons in the Odderon channel, both in QCD and in N=4 SYM. The NLO kernel consists of the NLO BFKL kernel in the color octet representation and the connected 3{yields}3 kernel, computed in the tree approximation.

  3. Relative n-widths of periodic convolution classes with NCVD-kernel and B-kernel

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    In this paper,we consider the relative n-widths of two kinds of periodic convolution classes,Kp(K) and Bp(G),whose convolution kernels are NCVD-kernel K and B-kernel G. The asymptotic estimations of Kn(Kp(K),Kp(K))q and Kn(Bp(G),Bp(G))q are obtained for p=1 and ∞,1≤ q≤∞.

  4. Reproducing Kernel for D2(Ω, ρ) and Metric Induced by Reproducing Kernel

    Institute of Scientific and Technical Information of China (English)

    ZHAO Zhen Gang

    2009-01-01

    An important property of the reproducing kernel of D2(Ω, ρ) is obtained and the reproducing kernels for D2(Ω, ρ) are calculated when Ω = Bn × Bn and ρ are some special functions. A reproducing kernel is used to construct a semi-positive definite matrix and a distance function defined on Ω×Ω. An inequality is obtained about the distance function and the pseudodistance induced by the matrix.

  5. GROWTH PERFORMANCE AND FEED CONVERSION RATIO (FCR OF HYBRID FINGERLINGS (CATLA CATLA X LABEO ROHITA FED ON COTTONSEED MEAL, SUNFLOWER MEAL AND BONE MEAL

    Directory of Open Access Journals (Sweden)

    T. SAHZADI, M. SALIM, UM-E-KALSOOM AND K. SHAHZAD

    2006-10-01

    Full Text Available An experiment was conducted in six glass aquaria to study the growth performance and feed conversion ratio (FCR of hybrid fingerlings (Catla catla x Labeo rohita fed on sunflower meal, cottonseed meal and bone meal. Two replicates for each ingredient were followed. The feed was supplied at the rate of 4% of wet body weight of fingerlings twice a day. The hybrid (Catla catla x Labeo rohita fingerlings gained highest body weight (1.62 ± 0.0 g on sunflower meal, followed by cottonseed meal (1.61 ± 0.01 g and bone meal (1.52 ± 0.0 g. The total length obtained by hybrid fish was 6.35 ± 0.05 cm on sunflower meal, 6.12 ± 0.05 cm on cottonseed meal and 5.85 ± 0.05 cm on bone meal. The overall mean values of FCR were lower (better on sunflower meal (1.78 ± 0.05, followed by cottonseed meal (2.17 ± 0.01 and bone meal (2.46 ± 0.01. Thus, The sunflower meal and cottonseed meal, on the basis of growth performance and better FCR, can be included in the feed formulation for hybrid fingerlings.

  6. Losses and nutritional value of elephant grass silage with inclusion levels of cottonseed meal - doi: 10.4025/actascianimsci.v35i2.13736

    Directory of Open Access Journals (Sweden)

    Mauro Pereira de Figueiredo

    2013-03-01

    Full Text Available The experiment was conducted to evaluate losses and nutritive value of elephant grass silage containing increasing levels of cottonseed meal. The experimental design was completely randomized, with five treatments: 0, 7, 14, 21 and 28% inclusion of cottonseed meal, and four replications. The material was chopped and packed in PVC silos and stored for 80 days. The pH and dry matter (DM, crude protein, lignin and ether extract of the silages increased linearly with the addition of cottonseed meal, while the levels of acid detergent insoluble nitrogen, neutral detergent fiber, acid detergent fiber, cellulose and hemicellulose decreased linearly. The addition of 28% cottonseed meal reduced the in situ disappearance of DM (48h to values lower than those of silage without additives. The concentration of ammonia nitrogen and the losses from gases and effluent were reduced. The inclusion of 28% cottonseed meal in elephant grass silage containing 18.4% DM improved the fermentation characteristics of silage more efficiently by reducing the moisture content and effluent losses, starting at the 7% level of inclusion.

  7. Effects of cottonseed hull levels in the diet and ageing time on visual and sensory meat acceptability from young bulls finished in feedlot.

    Science.gov (United States)

    Eiras, C E; Guerrero, A; Valero, M V; Pardo, J A; Ornaghi, M G; Rivaroli, D C; Sañudo, C; Prado, I N

    2017-03-01

    Cottonseed hulls are co-product of agribusiness that can be used in beef cattle rations, decreasing the cost of feed. The aim of this study was to evaluate the effects of different cottonseed hull levels, display and ageing times on visual and sensorial meat acceptability. Longissimus thoracis muscle from 30 crossbred young bulls finished on three high-grain diets (210, 270 or 330 g/kg of cottonseed hulls on dry matter, respectively) were visually evaluated during 10 days of display by 37 appraisers. Tenderness, flavour and overall acceptability from the three diets and three ageing times (1, 7 and 14 days) were evaluated by 120 consumers. On the visual study, time of display (P⩽0.001) was a more significant factor than diet. Cottonseed hull level had no effect on sensorial analyses, with tenderness acceptability improving with ageing time (P⩽0.001). Results indicate the possibility of using the three studied levels of cottonseed without damaging consumer meat acceptability.

  8. Discriminant Kernel Assignment for Image Coding.

    Science.gov (United States)

    Deng, Yue; Zhao, Yanyu; Ren, Zhiquan; Kong, Youyong; Bao, Feng; Dai, Qionghai

    2017-06-01

    This paper proposes discriminant kernel assignment (DKA) in the bag-of-features framework for image representation. DKA slightly modifies existing kernel assignment to learn width-variant Gaussian kernel functions to perform discriminant local feature assignment. When directly applying gradient-descent method to solve DKA, the optimization may contain multiple time-consuming reassignment implementations in iterations. Accordingly, we introduce a more practical way to locally linearize the DKA objective and the difficult task is cast as a sequence of easier ones. Since DKA only focuses on the feature assignment part, it seamlessly collaborates with other discriminative learning approaches, e.g., discriminant dictionary learning or multiple kernel learning, for even better performances. Experimental evaluations on multiple benchmark datasets verify that DKA outperforms other image assignment approaches and exhibits significant efficiency in feature coding.

  9. Multiple Kernel Spectral Regression for Dimensionality Reduction

    Directory of Open Access Journals (Sweden)

    Bing Liu

    2013-01-01

    Full Text Available Traditional manifold learning algorithms, such as locally linear embedding, Isomap, and Laplacian eigenmap, only provide the embedding results of the training samples. To solve the out-of-sample extension problem, spectral regression (SR solves the problem of learning an embedding function by establishing a regression framework, which can avoid eigen-decomposition of dense matrices. Motivated by the effectiveness of SR, we incorporate multiple kernel learning (MKL into SR for dimensionality reduction. The proposed approach (termed MKL-SR seeks an embedding function in the Reproducing Kernel Hilbert Space (RKHS induced by the multiple base kernels. An MKL-SR algorithm is proposed to improve the performance of kernel-based SR (KSR further. Furthermore, the proposed MKL-SR algorithm can be performed in the supervised, unsupervised, and semi-supervised situation. Experimental results on supervised classification and semi-supervised classification demonstrate the effectiveness and efficiency of our algorithm.

  10. Quantum kernel applications in medicinal chemistry.

    Science.gov (United States)

    Huang, Lulu; Massa, Lou

    2012-07-01

    Progress in the quantum mechanics of biological molecules is being driven by computational advances. The notion of quantum kernels can be introduced to simplify the formalism of quantum mechanics, making it especially suitable for parallel computation of very large biological molecules. The essential idea is to mathematically break large biological molecules into smaller kernels that are calculationally tractable, and then to represent the full molecule by a summation over the kernels. The accuracy of the kernel energy method (KEM) is shown by systematic application to a great variety of molecular types found in biology. These include peptides, proteins, DNA and RNA. Examples are given that explore the KEM across a variety of chemical models, and to the outer limits of energy accuracy and molecular size. KEM represents an advance in quantum biology applicable to problems in medicine and drug design.

  11. Kernel method-based fuzzy clustering algorithm

    Institute of Scientific and Technical Information of China (English)

    Wu Zhongdong; Gao Xinbo; Xie Weixin; Yu Jianping

    2005-01-01

    The fuzzy C-means clustering algorithm(FCM) to the fuzzy kernel C-means clustering algorithm(FKCM) to effectively perform cluster analysis on the diversiform structures are extended, such as non-hyperspherical data, data with noise, data with mixture of heterogeneous cluster prototypes, asymmetric data, etc. Based on the Mercer kernel, FKCM clustering algorithm is derived from FCM algorithm united with kernel method. The results of experiments with the synthetic and real data show that the FKCM clustering algorithm is universality and can effectively unsupervised analyze datasets with variform structures in contrast to FCM algorithm. It is can be imagined that kernel-based clustering algorithm is one of important research direction of fuzzy clustering analysis.

  12. Kernel representations for behaviors over finite rings

    NARCIS (Netherlands)

    Kuijper, M.; Pinto, R.; Polderman, J.W.; Yamamoto, Y.

    2006-01-01

    In this paper we consider dynamical systems finite rings. The rings that we study are the integers modulo a power of a given prime. We study the theory of representations for such systems, in particular kernel representations.

  13. Ensemble Approach to Building Mercer Kernels

    Data.gov (United States)

    National Aeronautics and Space Administration — This paper presents a new methodology for automatic knowledge driven data mining based on the theory of Mercer Kernels, which are highly nonlinear symmetric positive...

  14. Convolution kernels for multi-wavelength imaging

    National Research Council Canada - National Science Library

    Boucaud, Alexandre; Bocchio, Marco; Abergel, Alain; Orieux, François; Dole, Hervé; Hadj-Youcef, Mohamed Amine

    2016-01-01

    .... Given the knowledge of the PSF in each band, a straightforward way of processing images is to homogenise them all to a target PSF using convolution kernels, so that they appear as if they had been...

  15. Difference image analysis: Automatic kernel design using information criteria

    CERN Document Server

    Bramich, D M; Alsubai, K A; Bachelet, E; Mislis, D; Parley, N

    2015-01-01

    We present a selection of methods for automatically constructing an optimal kernel model for difference image analysis which require very few external parameters to control the kernel design. Each method consists of two components; namely, a kernel design algorithm to generate a set of candidate kernel models, and a model selection criterion to select the simplest kernel model from the candidate models that provides a sufficiently good fit to the target image. We restricted our attention to the case of solving for a spatially-invariant convolution kernel composed of delta basis functions, and we considered 19 different kernel solution methods including six employing kernel regularisation. We tested these kernel solution methods by performing a comprehensive set of image simulations and investigating how their performance in terms of model error, fit quality, and photometric accuracy depends on the properties of the reference and target images. We find that the irregular kernel design algorithm employing unreg...

  16. Preparing UO2 kernels by gelcasting

    Institute of Scientific and Technical Information of China (English)

    GUO Wenli; LIANG Tongxiang; ZHAO Xingyu; HAO Shaochang; LI Chengliang

    2009-01-01

    A process named gel-casting has been developed for the production of dense UO2 kernels for the high-ten-temperature gas-cooled reactor. Compared with the sol-gel process, the green microspheres can be got by dispersing the U3O8 slurry in gelcasting process, which means that gelcasting is a more facilitative process with less waste in fabricating UO2 kernels. The heat treatment.

  17. The Bergman kernel functions on Hua domains

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    We get the Bergman kernel functions in explicit formulas on four types of Hua domain.There are two key steps: First, we give the holomorphic automorphism groups of four types of Hua domain; second, we introduce the concept of semi-Reinhardt domain and give their complete orthonormal systems. Based on these two aspects we obtain the Bergman kernel function in explicit formulas on Hua domains.

  18. Fractal Weyl law for Linux Kernel Architecture

    CERN Document Server

    Ermann, L; Shepelyansky, D L

    2010-01-01

    We study the properties of spectrum and eigenstates of the Google matrix of a directed network formed by the procedure calls in the Linux Kernel. Our results obtained for various versions of the Linux Kernel show that the spectrum is characterized by the fractal Weyl law established recently for systems of quantum chaotic scattering and the Perron-Frobenius operators of dynamical maps. The fractal Weyl exponent is found to be $\

  19. Varying kernel density estimation on ℝ+

    Science.gov (United States)

    Mnatsakanov, Robert; Sarkisian, Khachatur

    2015-01-01

    In this article a new nonparametric density estimator based on the sequence of asymmetric kernels is proposed. This method is natural when estimating an unknown density function of a positive random variable. The rates of Mean Squared Error, Mean Integrated Squared Error, and the L1-consistency are investigated. Simulation studies are conducted to compare a new estimator and its modified version with traditional kernel density construction. PMID:26740729

  20. Lipase catalyzed interesterification of rice bran oil with hydrogenated cottonseed oil to produce trans free fat.

    Science.gov (United States)

    Neeharika, T S V R; Rallabandi, Ramya; Ragini, Y; Kaki, Shiva Shanker; Rani, K N Prasanna; Prasad, R B N

    2015-08-01

    Lipase catalyzed interesterification of rice bran oil (RBO) with hydrogenated cottonseed oil (HCSO) was carried out for producing a low trans free fat. The interesterification reaction was performed by varying parameters such as weight proportions of RBO and HCSO, reaction temperatures, time period and lipase concentration. Both non specific and specific lipases namely Novozym 435 and Lipozyme TL IM were employed for this study. Based on the data generated, the optimum reaction conditions were found to be: weight proportion of RBO and HCSO, 80:20; lipase concentration, 5 % (w/w) of substrates; reaction temperature, 60 °C; reaction time, 4 h for Lipozyme TL IM and 5 h for Novozym 435. The degree of interesterification, calculated based on the results of solid fat characteristics was used for comparing the catalytic activity of Novozym 435 and Lipozyme TL IM. It was observed that the degree of interesterification (DI) reached a near 100 % at the 4th hour for reaction employing Lipozyme TL IM with a rate constant of 0.191 h(-1) while Novozym 435 catalyzed reaction reached a near 100 % degree of interesterification at the 5th hour with a rate constant of 0.187 h(-1), suggesting that Lipozyme TL IM has a faster catalytic activity.

  1. Adaptively Learning the Crowd Kernel

    CERN Document Server

    Tamuz, Omer; Belongie, Serge; Shamir, Ohad; Kalai, Adam Tauman

    2011-01-01

    We introduce an algorithm that, given n objects, learns a similarity matrix over all n^2 pairs, from crowdsourced data alone. The algorithm samples responses to adaptively chosen triplet-based relative-similarity queries. Each query has the form "is object 'a' more similar to 'b' or to 'c'?" and is chosen to be maximally informative given the preceding responses. The output is an embedding of the objects into Euclidean space (like MDS); we refer to this as the "crowd kernel." The runtime (empirically observed to be linear) and cost (about $0.15 per object) of the algorithm are small enough to permit its application to databases of thousands of objects. The distance matrix provided by the algorithm allows for the development of an intuitive and powerful sequential, interactive search algorithm which we demonstrate for a variety of visual stimuli. We present quantitative results that demonstrate the benefit in cost and time of our approach compared to a nonadaptive approach. We also show the ability of our appr...

  2. Evaluating the Gradient of the Thin Wire Kernel

    Science.gov (United States)

    Wilton, Donald R.; Champagne, Nathan J.

    2008-01-01

    Recently, a formulation for evaluating the thin wire kernel was developed that employed a change of variable to smooth the kernel integrand, canceling the singularity in the integrand. Hence, the typical expansion of the wire kernel in a series for use in the potential integrals is avoided. The new expression for the kernel is exact and may be used directly to determine the gradient of the wire kernel, which consists of components that are parallel and radial to the wire axis.

  3. On the Inclusion Relation of Reproducing Kernel Hilbert Spaces

    OpenAIRE

    Zhang, Haizhang; Zhao, Liang

    2011-01-01

    To help understand various reproducing kernels used in applied sciences, we investigate the inclusion relation of two reproducing kernel Hilbert spaces. Characterizations in terms of feature maps of the corresponding reproducing kernels are established. A full table of inclusion relations among widely-used translation invariant kernels is given. Concrete examples for Hilbert-Schmidt kernels are presented as well. We also discuss the preservation of such a relation under various operations of ...

  4. Kernel abortion in maize : I. Carbohydrate concentration patterns and Acid invertase activity of maize kernels induced to abort in vitro.

    Science.gov (United States)

    Hanft, J M; Jones, R J

    1986-06-01

    Kernels cultured in vitro were induced to abort by high temperature (35 degrees C) and by culturing six kernels/cob piece. Aborting kernels failed to enter a linear phase of dry mass accumulation and had a final mass that was less than 6% of nonaborting field-grown kernels. Kernels induced to abort by high temperature failed to synthesize starch in the endosperm and had elevated sucrose concentrations and low fructose and glucose concentrations in the pedicel during early growth compared to nonaborting kernels. Kernels induced to abort by high temperature also had much lower pedicel soluble acid invertase activities than did nonaborting kernels. These results suggest that high temperature during the lag phase of kernel growth may impair the process of sucrose unloading in the pedicel by indirectly inhibiting soluble acid invertase activity and prevent starch synthesis in the endosperm. Kernels induced to abort by culturing six kernels/cob piece had reduced pedicel fructose, glucose, and sucrose concentrations compared to kernels from field-grown ears. These aborting kernels also had a lower pedicel soluble acid invertase activity compared to nonaborting kernels from the same cob piece and from field-grown ears. The low invertase activity in pedicel tissue of the aborting kernels was probably caused by a lack of substrate (sucrose) for the invertase to cleave due to the intense competition for available assimilates. In contrast to kernels cultured at 35 degrees C, aborting kernels from cob pieces containing all six kernels accumulated starch in a linear fashion. These results indicate that kernels cultured six/cob piece abort because of an inadequate supply of sugar and are similar to apical kernels from field-grown ears that often abort prior to the onset of linear growth.

  5. Cottonseed protein, oil, and mineral status in near-isogenic Gossypium hirsutum cotton lines expressing fuzzy/linted and fuzzless/linted seed phenotypes under field conditions.

    Science.gov (United States)

    Bellaloui, Nacer; Stetina, Salliana R; Turley, Rickie B

    2015-01-01

    Cotton is an important crop in the world and is a major source of oil for human consumption and cotton meal for livestock. Cottonseed nutrition (seed composition: protein, oil, and minerals) determines the quality of seeds. Therefore, maintaining optimum levels of cottonseed nutrition is critical. Physiological and genetic mechanisms controlling the levels of these constituents in cottonseed are still largely unknown. Our previous research conducted under greenhouse conditions showed that seed and leaf nutrition differed between fuzzless and fuzzy seed isolines. Therefore, the objective of this research was to investigate the seed fuzz phenotype (trait) effects on seed protein, oil, N, C, S, and minerals in five sets of near-isogenic mutant cotton lines for seed fuzz in a 2-year experiment under field condition to evaluate the stability of the effect of the trait on seed nutrition. The isolines (genotypes) in each set differ for the seed fuzz trait (fuzzless/linted seed line, N lines, and fuzzy/linted seed line, F lines). Results showed that seed protein was higher in the fuzzy genotype in all sets, but seed oil was higher in fuzzless genotype in all sets. The concentrations of seed Ca and C were higher in all fuzzless genotypes, but N, S, B, Fe, and Zn were higher in most of the fuzzy genotypes. Generally, minerals were higher in leaves of F lines, suggesting the translocation of minerals from leaves to seeds was limited. The research demonstrated that fiber development could be involved in cottonseed composition. This may be due to the involvement of fiber development in carbon and nitrogen metabolism, and the mobility of nutrients from leaves (source) to seed (sink). This information is beneficial to breeders to consider fuzzless cottonseed for potential protein and oil use and select for higher oil or higher protein content, and to physiologists to further understand the mobility of minerals to increase the quality of cottonseed nutrition for food and feed.

  6. Cottonseed protein, oil, and mineral status in near-isogenic Gossypium hirsutum cotton lines expressing fuzzy/linted and fuzzless/linted seed phenotypes under field conditions

    Directory of Open Access Journals (Sweden)

    Nacer eBellaloui

    2015-03-01

    Full Text Available Cotton is an important crop in the world and is a major source of oil for human consumption and cotton meal for livestock. Cottonseed nutrition (seed composition: protein, oil, and minerals determine the quality of seeds. Therefore, maintaining optimum levels of cottonseed nutrition is critical. Physiological and genetic mechanisms controlling the levels of these constituents in cottonseed are still largely unknown. Our previous research conducted under greenhouse conditions showed that seed and leaf nutrition differed between fuzzless and fuzzy seed isolines. Therefore, the objective of this research was to investigate the seed fuzz phenotype (trait effects on seed protein, oil, N, C, S, and minerals in five sets of near-isogenic mutant cotton lines for seed fuzz in a two-year experiment under field condition to evaluate the stability of the effect of the trait on seed nutrition. The isolines (genotypes in each set differ for the seed fuzz trait (fuzzless/linted seed line, N lines, and fuzzy/linted seed line, F lines. Results showed that seed protein was higher in the fuzzy genotype in all sets, but seed oil was higher in fuzzless genotype in all sets. The concentrations of seed Ca and C were higher in all fuzzless genotypes, but N, S, B, Fe, and Zn were higher in most of the fuzzy genotypes. Generally, minerals were higher in leaves of F lines, suggesting the translocation of minerals from leaves to seeds was limited. The research demonstrated that fiber development could be involved in cottonseed composition. This may be due to the involvement of fiber development in carbon and nitrogen metabolism, and the mobility of nutrients from leaves (source to seed (sink. This information is beneficial to breeders to consider fuzzless cottonseed for potential protein and oil use and select for higher oil or higher protein content, and to physiologists to further understand the mobility of minerals to increase the quality of cottonseed nutrition for

  7. Single pass kernel -means clustering method

    Indian Academy of Sciences (India)

    T Hitendra Sarma; P Viswanath; B Eswara Reddy

    2013-06-01

    In unsupervised classification, kernel -means clustering method has been shown to perform better than conventional -means clustering method in identifying non-isotropic clusters in a data set. The space and time requirements of this method are $O(n^2)$, where is the data set size. Because of this quadratic time complexity, the kernel -means method is not applicable to work with large data sets. The paper proposes a simple and faster version of the kernel -means clustering method, called single pass kernel k-means clustering method. The proposed method works as follows. First, a random sample $\\mathcal{S}$ is selected from the data set $\\mathcal{D}$. A partition $\\Pi_{\\mathcal{S}}$ is obtained by applying the conventional kernel -means method on the random sample $\\mathcal{S}$. The novelty of the paper is, for each cluster in $\\Pi_{\\mathcal{S}}$, the exact cluster center in the input space is obtained using the gradient descent approach. Finally, each unsampled pattern is assigned to its closest exact cluster center to get a partition of the entire data set. The proposed method needs to scan the data set only once and it is much faster than the conventional kernel -means method. The time complexity of this method is $O(s^2+t+nk)$ where is the size of the random sample $\\mathcal{S}$, is the number of clusters required, and is the time taken by the gradient descent method (to find exact cluster centers). The space complexity of the method is $O(s^2)$. The proposed method can be easily implemented and is suitable for large data sets, like those in data mining applications. Experimental results show that, with a small loss of quality, the proposed method can significantly reduce the time taken than the conventional kernel -means clustering method. The proposed method is also compared with other recent similar methods.

  8. Kernel-Based Reconstruction of Graph Signals

    Science.gov (United States)

    Romero, Daniel; Ma, Meng; Giannakis, Georgios B.

    2017-02-01

    A number of applications in engineering, social sciences, physics, and biology involve inference over networks. In this context, graph signals are widely encountered as descriptors of vertex attributes or features in graph-structured data. Estimating such signals in all vertices given noisy observations of their values on a subset of vertices has been extensively analyzed in the literature of signal processing on graphs (SPoG). This paper advocates kernel regression as a framework generalizing popular SPoG modeling and reconstruction and expanding their capabilities. Formulating signal reconstruction as a regression task on reproducing kernel Hilbert spaces of graph signals permeates benefits from statistical learning, offers fresh insights, and allows for estimators to leverage richer forms of prior information than existing alternatives. A number of SPoG notions such as bandlimitedness, graph filters, and the graph Fourier transform are naturally accommodated in the kernel framework. Additionally, this paper capitalizes on the so-called representer theorem to devise simpler versions of existing Thikhonov regularized estimators, and offers a novel probabilistic interpretation of kernel methods on graphs based on graphical models. Motivated by the challenges of selecting the bandwidth parameter in SPoG estimators or the kernel map in kernel-based methods, the present paper further proposes two multi-kernel approaches with complementary strengths. Whereas the first enables estimation of the unknown bandwidth of bandlimited signals, the second allows for efficient graph filter selection. Numerical tests with synthetic as well as real data demonstrate the merits of the proposed methods relative to state-of-the-art alternatives.

  9. A new Mercer sigmoid kernel for clinical data classification.

    Science.gov (United States)

    Carrington, André M; Fieguth, Paul W; Chen, Helen H

    2014-01-01

    In classification with Support Vector Machines, only Mercer kernels, i.e. valid kernels, such as the Gaussian RBF kernel, are widely accepted and thus suitable for clinical data. Practitioners would also like to use the sigmoid kernel, a non-Mercer kernel, but its range of validity is difficult to determine, and even within range its validity is in dispute. Despite these shortcomings the sigmoid kernel is used by some, and two kernels in the literature attempt to emulate and improve upon it. We propose the first Mercer sigmoid kernel, that is therefore trustworthy for the classification of clinical data. We show the similarity between the Mercer sigmoid kernel and the sigmoid kernel and, in the process, identify a normalization technique that improves the classification accuracy of the latter. The Mercer sigmoid kernel achieves the best mean accuracy on three clinical data sets, detecting melanoma in skin lesions better than the most popular kernels; while with non-clinical data sets it has no significant difference in median accuracy as compared with the Gaussian RBF kernel. It consistently classifies some points correctly that the Gaussian RBF kernel does not and vice versa.

  10. THE EFFECT OF COTTONSEED AND SOYBEAN SUPPLEMENTATION ON CLA ISOMERS AND OTHER UNSATURATED FATTY ACIDS COMPOSITION IN SHEEP MILK

    Directory of Open Access Journals (Sweden)

    Marmaryan G. Y.

    2013-11-01

    Full Text Available The objective of the present study was to investigate the supplementation effect of different treatments of whole cottonseed and full fat soybean on the diet of dairy ewes and the milk fatty acid profile and conjugated linoleic acid (CLA content. The results indicate for both diets it is most suitable to use the second treatment in order to increase the level of cis- 9,trans-11 CLA isomer in milk. In the level of trans-10,cis-12 and cis-9, cis-11 no changes were observed in neither of the diets.

  11. GPR Surveying in the kernel area of Grove Mountains, Antarctica

    Institute of Scientific and Technical Information of China (English)

    WANG Zemin; TAN Zhi; AI Songtao; LIU Haiyan; CHE Guowei

    2014-01-01

    The Grove Mountains, located between the Zhongshan Station and Dome A, are a very important area in inland Antarctic research. China has organized ifve investigations of the Grove Mountains, encompassing the geological structure, ancient climate, meteorites, ice-movement monitoring, basic mapping, meteorological observations, and other multi-disciplinary observational studies. During the 26th Chinese National Antarctic Research Expedition in 2010, the Grove Mountains investigation team applied specialized ground-penetrating radar (GPR) to survey subglacial topography in the eastern kernel area of the Grove Mountains. In this paper, we processed GPS and GPR data gathered in the ifeld and drew, for the ifrst time, two subglacial topographic maps of the Grove Mountains kernel area using professional graphics software. The preliminary results reveal the mystery of the nunatak landform of this area, give an exploratory sense of the real bedrock landforms, and indicate a possible sedimentary basin under the Pliocene epoch fossil ice in the Grove Mountains area. Additionally, it has been proven from cross-sectional analysis between Mount Harding and the Zakharoff ridge that the box-valley shape between two nunataks has already matured.

  12. Pattern Classification of Signals Using Fisher Kernels

    Directory of Open Access Journals (Sweden)

    Yashodhan Athavale

    2012-01-01

    Full Text Available The intention of this study is to gauge the performance of Fisher kernels for dimension simplification and classification of time-series signals. Our research work has indicated that Fisher kernels have shown substantial improvement in signal classification by enabling clearer pattern visualization in three-dimensional space. In this paper, we will exhibit the performance of Fisher kernels for two domains: financial and biomedical. The financial domain study involves identifying the possibility of collapse or survival of a company trading in the stock market. For assessing the fate of each company, we have collected financial time-series composed of weekly closing stock prices in a common time frame, using Thomson Datastream software. The biomedical domain study involves knee signals collected using the vibration arthrometry technique. This study uses the severity of cartilage degeneration for classifying normal and abnormal knee joints. In both studies, we apply Fisher Kernels incorporated with a Gaussian mixture model (GMM for dimension transformation into feature space, which is created as a three-dimensional plot for visualization and for further classification using support vector machines. From our experiments we observe that Fisher Kernel usage fits really well for both kinds of signals, with low classification error rates.

  13. Analog forecasting with dynamics-adapted kernels

    Science.gov (United States)

    Zhao, Zhizhen; Giannakis, Dimitrios

    2016-09-01

    Analog forecasting is a nonparametric technique introduced by Lorenz in 1969 which predicts the evolution of states of a dynamical system (or observables defined on the states) by following the evolution of the sample in a historical record of observations which most closely resembles the current initial data. Here, we introduce a suite of forecasting methods which improve traditional analog forecasting by combining ideas from kernel methods developed in harmonic analysis and machine learning and state-space reconstruction for dynamical systems. A key ingredient of our approach is to replace single-analog forecasting with weighted ensembles of analogs constructed using local similarity kernels. The kernels used here employ a number of dynamics-dependent features designed to improve forecast skill, including Takens’ delay-coordinate maps (to recover information in the initial data lost through partial observations) and a directional dependence on the dynamical vector field generating the data. Mathematically, our approach is closely related to kernel methods for out-of-sample extension of functions, and we discuss alternative strategies based on the Nyström method and the multiscale Laplacian pyramids technique. We illustrate these techniques in applications to forecasting in a low-order deterministic model for atmospheric dynamics with chaotic metastability, and interannual-scale forecasting in the North Pacific sector of a comprehensive climate model. We find that forecasts based on kernel-weighted ensembles have significantly higher skill than the conventional approach following a single analog.

  14. Effects of Cottonseed Meal on Hematological, Biochemical and Behavioral Alterations in Male Japanese Quail (Coturnix japonica

    Directory of Open Access Journals (Sweden)

    M. Moazam Jalees, M. Zargham Khan*, M. Kashif Saleemi and Ahrar Khan

    2011-06-01

    Full Text Available The present study was carried out to find toxico-pathological effects of cottonseed meal (CSM in male Japanese quail (Coturnix japonica. Male birds (n=48 were equally divided into four groups (A to D. Three isonitric and isocaloric experimental feeds were formulated by replacing soybean meal with three levels of CSM i.e., 13, 27 and 41%. The respective feed was offered to the birds ad libitum for the duration of experiment (42 days. Clinical signs, behavioral alterations, feed consumption, body weight, absolute and relative organ weight, hematological and biochemical parameters along with gross and histopathological lesions were studied. In group B and C, birds were temporarily depressed but later on became active. In group D, birds remained dull and depressed and 66.7% mortality was recorded. Body weight, absolute and relative organ weight was non-significantly different in treatment groups compared with control. Feed intake at week 1 was significantly low in group D while during remaining experiment; it differed non-significantly in all the treatment groups compared with control. Testicular volume at day 21 was significantly (P<0.05 low in group D. Significantly low serum total proteins and albumin in groups B and C and hematocrit values in all the groups and hemoglobin concentration in group D were recorded at day 42 of experiment. It was concluded that CSM 13% level did not have any deleterious effect on the feed conversion and body weight but the reproductive performance of the male Japanese quail was affected.

  15. The effect of feed intake containing whole cottonseed on blood parameters of Nellore bulls

    Directory of Open Access Journals (Sweden)

    V.S. Gomes

    Full Text Available ABSTRACT The aim of this study was to evaluate the effect of diets containing whole cottonseed (WC on blood biochemical parameters of bulls. Thirty bulls with 30±6 months and 382.7±28.4kg were kept in feedlot (85 days and fed the following WC levels: 0, 2.22, 4.44, 6.66, 8.88 and 11.11%. In comparing biochemical indicators from the beginning to the end of the experiment, the control group (CG and those fed diets containing 2.22, 8.88 and 11.11% of WC had an increase (P<0.05 in serum Ca concentrations (8.34±0.65−9.56±0.92mEqL-1. In relation to Fe (202.79±69.04−300.04±79.88µg/dL, the CG and those treated with 6.66% WC showed an increase (P<0.05 in serum concentrations. As to the Mg (1.92±0.18−2.40±0.27mEqL-1, groups treated with diet containing 2.22, 4.44 and 6.66% of WC had higher (p<0.05 concentrations at the end of the study. Regarding blood lipids, groups with diets containing 2.22; 4.44; 6.66 and 8.88% of WC increased (p<0.05, respectively, in concentrations of HDL, TG, VLDL and COL. The group that received 11.11% of WC increased (P<0.05 in the concentrations of COL and HDL. It can be concluded that diets containing WC, caused no alterations in the concentrations of blood parameters analyzed in this study, with the exception of Mg.

  16. Object classification and detection with context kernel descriptors

    DEFF Research Database (Denmark)

    Pan, Hong; Olsen, Søren Ingvor; Zhu, Yaping

    2014-01-01

    Context information is important in object representation. By embedding context cue of image attributes into kernel descriptors, we propose a set of novel kernel descriptors called Context Kernel Descriptors (CKD) for object classification and detection. The motivation of CKD is to use spatial...... consistency of image attributes or features defined within a neighboring region to improve the robustness of descriptor matching in kernel space. For feature selection, Kernel Entropy Component Analysis (KECA) is exploited to learn a subset of discriminative CKD. Different from Kernel Principal Component...

  17. OS X and iOS Kernel Programming

    CERN Document Server

    Halvorsen, Ole Henry

    2011-01-01

    OS X and iOS Kernel Programming combines essential operating system and kernel architecture knowledge with a highly practical approach that will help you write effective kernel-level code. You'll learn fundamental concepts such as memory management and thread synchronization, as well as the I/O Kit framework. You'll also learn how to write your own kernel-level extensions, such as device drivers for USB and Thunderbolt devices, including networking, storage and audio drivers. OS X and iOS Kernel Programming provides an incisive and complete introduction to the XNU kernel, which runs iPhones, i

  18. The scalar field kernel in cosmological spaces

    Energy Technology Data Exchange (ETDEWEB)

    Koksma, Jurjen F; Prokopec, Tomislav [Institute for Theoretical Physics (ITP) and Spinoza Institute, Utrecht University, Postbus 80195, 3508 TD Utrecht (Netherlands); Rigopoulos, Gerasimos I [Helsinki Institute of Physics, University of Helsinki, PO Box 64, FIN-00014 (Finland)], E-mail: J.F.Koksma@phys.uu.nl, E-mail: T.Prokopec@phys.uu.nl, E-mail: gerasimos.rigopoulos@helsinki.fi

    2008-06-21

    We construct the quantum-mechanical evolution operator in the functional Schroedinger picture-the kernel-for a scalar field in spatially homogeneous FLRW spacetimes when the field is (a) free and (b) coupled to a spacetime-dependent source term. The essential element in the construction is the causal propagator, linked to the commutator of two Heisenberg picture scalar fields. We show that the kernels can be expressed solely in terms of the causal propagator and derivatives of the causal propagator. Furthermore, we show that our kernel reveals the standard light cone structure in FLRW spacetimes. We finally apply the result to Minkowski spacetime, to de Sitter spacetime and calculate the forward time evolution of the vacuum in a general FLRW spacetime.

  19. Robust Visual Tracking via Fuzzy Kernel Representation

    Directory of Open Access Journals (Sweden)

    Zhiqiang Wen

    2013-05-01

    Full Text Available A robust visual kernel tracking approach is presented for solving the problem of existing background pixels in object model. At first, after definition of fuzzy set on image is given, a fuzzy factor is embedded into object model to form the fuzzy kernel representation. Secondly, a fuzzy membership functions are generated by center-surround approach and log likelihood ratio of feature distributions. Thirdly, details about fuzzy kernel tracking algorithm is provided. After that, methods of parameter selection and performance evaluation for tracking algorithm are proposed. At last, a mass of experimental results are done to show our method can reduce the influence of the incomplete representation of object model via integrating both color features and background features.

  20. Fractal Weyl law for Linux Kernel architecture

    Science.gov (United States)

    Ermann, L.; Chepelianskii, A. D.; Shepelyansky, D. L.

    2011-01-01

    We study the properties of spectrum and eigenstates of the Google matrix of a directed network formed by the procedure calls in the Linux Kernel. Our results obtained for various versions of the Linux Kernel show that the spectrum is characterized by the fractal Weyl law established recently for systems of quantum chaotic scattering and the Perron-Frobenius operators of dynamical maps. The fractal Weyl exponent is found to be ν ≈ 0.65 that corresponds to the fractal dimension of the network d ≈ 1.3. An independent computation of the fractal dimension by the cluster growing method, generalized for directed networks, gives a close value d ≈ 1.4. The eigenmodes of the Google matrix of Linux Kernel are localized on certain principal nodes. We argue that the fractal Weyl law should be generic for directed networks with the fractal dimension d < 2.

  1. Optoacoustic inversion via Volterra kernel reconstruction

    CERN Document Server

    Melchert, O; Roth, B

    2016-01-01

    In this letter we address the numeric inversion of optoacoustic signals to initial stress profiles. Therefore we put under scrutiny the optoacoustic kernel reconstruction problem in the paraxial approximation of the underlying wave-equation. We apply a Fourier-series expansion of the optoacoustic Volterra kernel and obtain the respective expansion coefficients for a given "apparative" setup by performing a gauge procedure using synthetic input data. The resulting effective kernel is subsequently used to solve the optoacoustic source reconstruction problem for general signals. We verify the validity of the proposed inversion protocol for synthetic signals and explore the feasibility of our approach to also account for the diffraction transformation of signals beyond the paraxial approximation.

  2. Tile-Compressed FITS Kernel for IRAF

    Science.gov (United States)

    Seaman, R.

    2011-07-01

    The Flexible Image Transport System (FITS) is a ubiquitously supported standard of the astronomical community. Similarly, the Image Reduction and Analysis Facility (IRAF), developed by the National Optical Astronomy Observatory, is a widely used astronomical data reduction package. IRAF supplies compatibility with FITS format data through numerous tools and interfaces. The most integrated of these is IRAF's FITS image kernel that provides access to FITS from any IRAF task that uses the basic IMIO interface. The original FITS kernel is a complex interface of purpose-built procedures that presents growing maintenance issues and lacks recent FITS innovations. A new FITS kernel is being developed at NOAO that is layered on the CFITSIO library from the NASA Goddard Space Flight Center. The simplified interface will minimize maintenance headaches as well as add important new features such as support for the FITS tile-compressed (fpack) format.

  3. Improvement of efficiency of oil extraction from wild apricot kernels by using enzymes.

    Science.gov (United States)

    Bisht, Tejpal Singh; Sharma, Satish Kumar; Sati, Ramesh Chandra; Rao, Virendra Kumar; Yadav, Vijay Kumar; Dixit, Anil Kumar; Sharma, Ashok Kumar; Chopra, Chandra Shekhar

    2015-03-01

    An experiment was conducted to evaluate and standardize the protocol for enhancing recovery of oil and quality from cold pressed wild apricot kernels by using various enzymes. Wild apricot kernels were ground into powder in a grinder. Different lots of 3 kg powdered kernel were prepared and treated with different concentrations of enzyme solutions viz. Pectazyme (Pectinase), Mashzyme (Cellulase) and Pectazyme + Mashzyme. Kernel powder mixed with enzyme solutions were kept for 2 h at 50(±2) °C temperature for enzymatic treatment before its use for oil extraction through oil expeller. Results indicate that use of enzymes resulted in enhancement of oil recovery by 9.00-14.22 %. Maximum oil recovery was observed at 0.3-0.4 % enzyme concentration for both the enzymes individually, as well as in combination. All the three enzymatic treatments resulted in increasing oil yield. However, with 0.3 % (Pectazyme + Mashzyme) combination, maximum oil recovery of 47.33 % could be observed against were 33.11 % in control. The oil content left (wasted) in the cake and residue were reduced from 11.67 and 11.60 % to 7.31 and 2.72 % respectively, thus showing a high increase in efficiency of oil recovery from wild apricot kernels. Quality characteristics indicate that the oil quality was not adversely affected by enzymatic treatment. It was concluded treatment of powdered wild apricot kernels with 0.3 % (Pectazyme + Mashzyme) combination was highly effective in increasing oil recovery by 14.22 % without adversely affecting the quality and thus may be commercially used by the industry for reducing wastage of highly precious oil in the cake.

  4. A kernel-based approach for biomedical named entity recognition.

    Science.gov (United States)

    Patra, Rakesh; Saha, Sujan Kumar

    2013-01-01

    Support vector machine (SVM) is one of the popular machine learning techniques used in various text processing tasks including named entity recognition (NER). The performance of the SVM classifier largely depends on the appropriateness of the kernel function. In the last few years a number of task-specific kernel functions have been proposed and used in various text processing tasks, for example, string kernel, graph kernel, tree kernel and so on. So far very few efforts have been devoted to the development of NER task specific kernel. In the literature we found that the tree kernel has been used in NER task only for entity boundary detection or reannotation. The conventional tree kernel is unable to execute the complete NER task on its own. In this paper we have proposed a kernel function, motivated by the tree kernel, which is able to perform the complete NER task. To examine the effectiveness of the proposed kernel, we have applied the kernel function on the openly available JNLPBA 2004 data. Our kernel executes the complete NER task and achieves reasonable accuracy.

  5. Full Waveform Inversion Using Waveform Sensitivity Kernels

    Science.gov (United States)

    Schumacher, Florian; Friederich, Wolfgang

    2013-04-01

    We present a full waveform inversion concept for applications ranging from seismological to enineering contexts, in which the steps of forward simulation, computation of sensitivity kernels, and the actual inversion are kept separate of each other. We derive waveform sensitivity kernels from Born scattering theory, which for unit material perturbations are identical to the Born integrand for the considered path between source and receiver. The evaluation of such a kernel requires the calculation of Green functions and their strains for single forces at the receiver position, as well as displacement fields and strains originating at the seismic source. We compute these quantities in the frequency domain using the 3D spectral element code SPECFEM3D (Tromp, Komatitsch and Liu, 2008) and the 1D semi-analytical code GEMINI (Friederich and Dalkolmo, 1995) in both, Cartesian and spherical framework. We developed and implemented the modularized software package ASKI (Analysis of Sensitivity and Kernel Inversion) to compute waveform sensitivity kernels from wavefields generated by any of the above methods (support for more methods is planned), where some examples will be shown. As the kernels can be computed independently from any data values, this approach allows to do a sensitivity and resolution analysis first without inverting any data. In the context of active seismic experiments, this property may be used to investigate optimal acquisition geometry and expectable resolution before actually collecting any data, assuming the background model is known sufficiently well. The actual inversion step then, can be repeated at relatively low costs with different (sub)sets of data, adding different smoothing conditions. Using the sensitivity kernels, we expect the waveform inversion to have better convergence properties compared with strategies that use gradients of a misfit function. Also the propagation of the forward wavefield and the backward propagation from the receiver

  6. Inverse of the String Theory KLT Kernel

    CERN Document Server

    Mizera, Sebastian

    2016-01-01

    The field theory Kawai-Lewellen-Tye (KLT) kernel, which relates scattering amplitudes of gravitons and gluons, turns out to be the inverse of a matrix whose components are bi-adjoint scalar partial amplitudes. In this note we propose an analogous construction for the string theory KLT kernel. We present simple diagrammatic rules for the computation of the $\\alpha'$-corrected bi-adjoint scalar amplitudes that are exact in $\\alpha'$. We find compact expressions in terms of graphs, where the standard Feynman propagators $1/p^2$ are replaced by either $1/\\sin (\\pi \\alpha' p^2)$ or $1/\\tan (\\pi \\alpha' p^2)$, which is determined by a recursive procedure.

  7. Reduced multiple empirical kernel learning machine.

    Science.gov (United States)

    Wang, Zhe; Lu, MingZhe; Gao, Daqi

    2015-02-01

    Multiple kernel learning (MKL) is demonstrated to be flexible and effective in depicting heterogeneous data sources since MKL can introduce multiple kernels rather than a single fixed kernel into applications. However, MKL would get a high time and space complexity in contrast to single kernel learning, which is not expected in real-world applications. Meanwhile, it is known that the kernel mapping ways of MKL generally have two forms including implicit kernel mapping and empirical kernel mapping (EKM), where the latter is less attracted. In this paper, we focus on the MKL with the EKM, and propose a reduced multiple empirical kernel learning machine named RMEKLM for short. To the best of our knowledge, it is the first to reduce both time and space complexity of the MKL with EKM. Different from the existing MKL, the proposed RMEKLM adopts the Gauss Elimination technique to extract a set of feature vectors, which is validated that doing so does not lose much information of the original feature space. Then RMEKLM adopts the extracted feature vectors to span a reduced orthonormal subspace of the feature space, which is visualized in terms of the geometry structure. It can be demonstrated that the spanned subspace is isomorphic to the original feature space, which means that the dot product of two vectors in the original feature space is equal to that of the two corresponding vectors in the generated orthonormal subspace. More importantly, the proposed RMEKLM brings a simpler computation and meanwhile needs a less storage space, especially in the processing of testing. Finally, the experimental results show that RMEKLM owns a much efficient and effective performance in terms of both complexity and classification. The contributions of this paper can be given as follows: (1) by mapping the input space into an orthonormal subspace, the geometry of the generated subspace is visualized; (2) this paper first reduces both the time and space complexity of the EKM-based MKL; (3

  8. Volatile compound formation during argan kernel roasting.

    Science.gov (United States)

    El Monfalouti, Hanae; Charrouf, Zoubida; Giordano, Manuela; Guillaume, Dominique; Kartah, Badreddine; Harhar, Hicham; Gharby, Saïd; Denhez, Clément; Zeppa, Giuseppe

    2013-01-01

    Virgin edible argan oil is prepared by cold-pressing argan kernels previously roasted at 110 degrees C for up to 25 minutes. The concentration of 40 volatile compounds in virgin edible argan oil was determined as a function of argan kernel roasting time. Most of the volatile compounds begin to be formed after 15 to 25 minutes of roasting. This suggests that a strictly controlled roasting time should allow the modulation of argan oil taste and thus satisfy different types of consumers. This could be of major importance considering the present booming use of edible argan oil.

  9. Learning Rates for -Regularized Kernel Classifiers

    Directory of Open Access Journals (Sweden)

    Hongzhi Tong

    2013-01-01

    Full Text Available We consider a family of classification algorithms generated from a regularization kernel scheme associated with -regularizer and convex loss function. Our main purpose is to provide an explicit convergence rate for the excess misclassification error of the produced classifiers. The error decomposition includes approximation error, hypothesis error, and sample error. We apply some novel techniques to estimate the hypothesis error and sample error. Learning rates are eventually derived under some assumptions on the kernel, the input space, the marginal distribution, and the approximation error.

  10. Face Recognition Using Kernel Discriminant Analysis

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    Linear Discrimiant Analysis (LDA) has demonstrated their success in face recognition. But LDA is difficult to handle the high nonlinear problems, such as changes of large viewpoint and illumination in face recognition. In order to overcome these problems, we investigate Kernel Discriminant Analysis (KDA) for face recognition. This approach adopts the kernel functions to replace the dot products of nonlinear mapping in the high dimensional feature space, and then the nonlinear problem can be solved in the input space conveniently without explicit mapping. Two face databases are used to test KDA approach. The results show that our approach outperforms the conventional PCA(Eigenface) and LDA(Fisherface) approaches.

  11. 棉籽分离蛋白的功能特性研究%Functional property of cottonseed protein isolate

    Institute of Scientific and Technical Information of China (English)

    赵小龙; 刘大川

    2015-01-01

    In order to explore the application possibility of cottonseed protein isolate in food industry,the impacts of pH,temperature and mass fraction of protein solution on the functional properties of cottonseed protein isolate including solubility,water holding capacity,oil absorption,foamability,emulsifying property etc were studied. The results showed that the solubility of cottonseed protein isolate was the lowest and NSI(nitrogen soluble index)was only 2. 11% at pH 4-5;when pH was higher than 5,its solubility in-creased gradually;when pH was above 11,cottonseed protein isolate was almost completely dissolved and the NSI reached 93 . 8%. The water holding capacity of cottonseed protein isolate basically unchanged at pH 4-6,when pH was higher than 6,its water holding capacity improved markedly. When pH was 7,the foamability and emulsifying property of cottonseed protein isolate increased with the increase of mass frac-tion of protein solution,while its foam stability and emulsion stability were less affected. Its oil absorption decreased with temperature rising. The denaturation temperature of cottonseed protein isolate determined by differential scanning calorimetry was 95. 18℃,higher than that of soybean protein isolate (88. 64℃), and its denaturation enthalpy was 137. 6 J/g,lower than that of soybean protein isolate(178. 7 J/g). The gel strength of the gel from cottonseed protein isolate determined by physical tester was larger than that from soybean protein isolate under the same condition.%为了探讨棉籽分离蛋白在食品工业中应用的可能性,研究了pH、温度、蛋白质溶液质量分数对棉籽分离蛋白的溶解性、持水性、吸油性、起泡性及乳化性等功能特性的影响。结果表明,在pH 4~5之间时,棉籽分离蛋白溶解性最低,氮溶指数(NSI)仅为2.11%。当pH大于5,棉籽分离蛋白溶解性逐渐增加,在pH达到11之后,棉籽分离蛋白几乎全部溶解,氮溶指数为93.8%。在pH 4~6之间时,棉

  12. Effect of Cottonseed Meal Fermented with Yeast on the Lipid-related Gene Expression in Broiler Chickens

    Directory of Open Access Journals (Sweden)

    CX Nie

    2015-12-01

    Full Text Available ABSTRACT Fermented cottonseed meal (FCSM is widely used in poultry diets in China. This study was conducted to investigate the effect of FCSM on lipid-related gene expression in broilers. Initially, 180 broiler chickens (21-days-old, equal number of males and females were randomly divided into three groups, with six pens per group and 10 birds per pen. The chickens in the control group were fed a diet containing unfermented cottonseed meal, and those in the treatment groups were fed with diets including either CSM fermented by Candida tropicalis (Ct group or CSM fermented by Candida tropicalis plus Saccharomyces cerevisae (Ct-Sc group until 64 days old. The results revealed that, compared with the control group (p0.05. Likewise, the expressions of peroxisome proliferator-activated receptor gamma (PPAR-g and LPL in the abdominal fat were not altered by the FCSM-supplemented diets (p>0.05. The results in this study indicate that CSM fermented by Candida tropicalis and Saccharomyces cerevisiaeeffectively regulated the genes involved in fatty acid b-oxidation and triglyceride hydrolysis in male broiler chickens. Furthermore, the effects of the FCSM-supplemented diets were significantly different between bird sexes and between yeast strains used in the fermentation process.

  13. Regularization techniques for PSF-matching kernels - I. Choice of kernel basis

    Science.gov (United States)

    Becker, A. C.; Homrighausen, D.; Connolly, A. J.; Genovese, C. R.; Owen, R.; Bickerton, S. J.; Lupton, R. H.

    2012-09-01

    We review current methods for building point spread function (PSF)-matching kernels for the purposes of image subtraction or co-addition. Such methods use a linear decomposition of the kernel on a series of basis functions. The correct choice of these basis functions is fundamental to the efficiency and effectiveness of the matching - the chosen bases should represent the underlying signal using a reasonably small number of shapes, and/or have a minimum number of user-adjustable tuning parameters. We examine methods whose bases comprise multiple Gauss-Hermite polynomials, as well as a form-free basis composed of delta-functions. Kernels derived from delta-functions are unsurprisingly shown to be more expressive; they are able to take more general shapes and perform better in situations where sum-of-Gaussian methods are known to fail. However, due to its many degrees of freedom (the maximum number allowed by the kernel size) this basis tends to overfit the problem and yields noisy kernels having large variance. We introduce a new technique to regularize these delta-function kernel solutions, which bridges the gap between the generality of delta-function kernels and the compactness of sum-of-Gaussian kernels. Through this regularization we are able to create general kernel solutions that represent the intrinsic shape of the PSF-matching kernel with only one degree of freedom, the strength of the regularization λ. The role of λ is effectively to exchange variance in the resulting difference image with variance in the kernel itself. We examine considerations in choosing the value of λ, including statistical risk estimators and the ability of the solution to predict solutions for adjacent areas. Both of these suggest moderate strengths of λ between 0.1 and 1.0, although this optimization is likely data set dependent. This model allows for flexible representations of the convolution kernel that have significant predictive ability and will prove useful in implementing

  14. Kernel methods and minimum contrast estimators for empirical deconvolution

    CERN Document Server

    Delaigle, Aurore

    2010-01-01

    We survey classical kernel methods for providing nonparametric solutions to problems involving measurement error. In particular we outline kernel-based methodology in this setting, and discuss its basic properties. Then we point to close connections that exist between kernel methods and much newer approaches based on minimum contrast techniques. The connections are through use of the sinc kernel for kernel-based inference. This `infinite order' kernel is not often used explicitly for kernel-based deconvolution, although it has received attention in more conventional problems where measurement error is not an issue. We show that in a comparison between kernel methods for density deconvolution, and their counterparts based on minimum contrast, the two approaches give identical results on a grid which becomes increasingly fine as the bandwidth decreases. In consequence, the main numerical differences between these two techniques are arguably the result of different approaches to choosing smoothing parameters.

  15. Kernel methods in orthogonalization of multi- and hypervariate data

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg

    2009-01-01

    A kernel version of maximum autocorrelation factor (MAF) analysis is described very briefly and applied to change detection in remotely sensed hyperspectral image (HyMap) data. The kernel version is based on a dual formulation also termed Q-mode analysis in which the data enter into the analysis...... via inner products in the Gram matrix only. In the kernel version the inner products are replaced by inner products between nonlinear mappings into higher dimensional feature space of the original data. Via kernel substitution also known as the kernel trick these inner products between the mappings...... are in turn replaced by a kernel function and all quantities needed in the analysis are expressed in terms of this kernel function. This means that we need not know the nonlinear mappings explicitly. Kernel PCA and MAF analysis handle nonlinearities by implicitly transforming data into high (even infinite...

  16. Variable kernel density estimation in high-dimensional feature spaces

    CSIR Research Space (South Africa)

    Van der Walt, Christiaan M

    2017-02-01

    Full Text Available Estimating the joint probability density function of a dataset is a central task in many machine learning applications. In this work we address the fundamental problem of kernel bandwidth estimation for variable kernel density estimation in high...

  17. HEAT KERNEL AND HARDY'S THEOREM FOR JACOBI TRANSFORM

    Institute of Scientific and Technical Information of China (English)

    T. KAWAZOE; LIU JIANMING(刘建明)

    2003-01-01

    In this paper, the authors obtain sharp upper and lower bounds for the heat kernel associatedwith Jacobi transform, and get some analogues of Hardy's Theorem for Jacobi transform byusing the sharp estimate of the heat kernel.

  18. Analysis of maize ( Zea mays ) kernel density and volume using microcomputed tomography and single-kernel near-infrared spectroscopy.

    Science.gov (United States)

    Gustin, Jeffery L; Jackson, Sean; Williams, Chekeria; Patel, Anokhee; Armstrong, Paul; Peter, Gary F; Settles, A Mark

    2013-11-20

    Maize kernel density affects milling quality of the grain. Kernel density of bulk samples can be predicted by near-infrared reflectance (NIR) spectroscopy, but no accurate method to measure individual kernel density has been reported. This study demonstrates that individual kernel density and volume are accurately measured using X-ray microcomputed tomography (μCT). Kernel density was significantly correlated with kernel volume, air space within the kernel, and protein content. Embryo density and volume did not influence overall kernel density. Partial least-squares (PLS) regression of μCT traits with single-kernel NIR spectra gave stable predictive models for kernel density (R(2) = 0.78, SEP = 0.034 g/cm(3)) and volume (R(2) = 0.86, SEP = 2.88 cm(3)). Density and volume predictions were accurate for data collected over 10 months based on kernel weights calculated from predicted density and volume (R(2) = 0.83, SEP = 24.78 mg). Kernel density was significantly correlated with bulk test weight (r = 0.80), suggesting that selection of dense kernels can translate to improved agronomic performance.

  19. Full replacement of menhaden fish meal protein by low-gossypol cottonseed flour protein in the diet of juvenile black sea bass Centropristis striata

    Science.gov (United States)

    Eight iso-nitrogeneous (46% crude protein) and iso-lipidic (14% crude lipid) diets were formulated and prepared to replace menhaden fish meal (FM) protein (59.5% CP) by low-gossypol glandless meal (GCSM) protein (50.4% CP), solvent-extracted cottonseed meal (SCSM) protein (53.8% protein) and high go...

  20. Kernel Partial Least Squares for Nonlinear Regression and Discrimination

    Science.gov (United States)

    Rosipal, Roman; Clancy, Daniel (Technical Monitor)

    2002-01-01

    This paper summarizes recent results on applying the method of partial least squares (PLS) in a reproducing kernel Hilbert space (RKHS). A previously proposed kernel PLS regression model was proven to be competitive with other regularized regression methods in RKHS. The family of nonlinear kernel-based PLS models is extended by considering the kernel PLS method for discrimination. Theoretical and experimental results on a two-class discrimination problem indicate usefulness of the method.

  1. Mitigation of artifacts in rtm with migration kernel decomposition

    KAUST Repository

    Zhan, Ge

    2012-01-01

    The migration kernel for reverse-time migration (RTM) can be decomposed into four component kernels using Born scattering and migration theory. Each component kernel has a unique physical interpretation and can be interpreted differently. In this paper, we present a generalized diffraction-stack migration approach for reducing RTM artifacts via decomposition of migration kernel. The decomposition leads to an improved understanding of migration artifacts and, therefore, presents us with opportunities for improving the quality of RTM images.

  2. Sparse Event Modeling with Hierarchical Bayesian Kernel Methods

    Science.gov (United States)

    2016-01-05

    the kernel function which depends on the application and the model user. This research uses the most popular kernel function, the radial basis...an important role in the nation’s economy. Unfortunately, the system’s reliability is declining due to the aging components of the network [Grier...kernel function. Gaussian Bayesian kernel models became very popular recently and were extended and applied to a number of classification problems. An

  3. An Extended Ockham Algebra with Endomorphism Kernel Property

    Institute of Scientific and Technical Information of China (English)

    Jie FANG

    2007-01-01

    An algebraic structure (∮) is said to have the endomorphism kernel property if every congruence on (∮) , other than the universal congruence, is the kernel of an endomorphism on (∮) .Inthis paper, we consider the EKP (that is, endomorphism kernel property) for an extended Ockham algebra (∮) . In particular, we describe the structure of the finite symmetric extended de Morgan algebras having EKP.

  4. End-use quality of soft kernel durum wheat

    Science.gov (United States)

    Kernel texture is a major determinant of end-use quality of wheat. Durum wheat has very hard kernels. We developed soft kernel durum wheat via Ph1b-mediated homoeologous recombination. The Hardness locus was transferred from Chinese Spring to Svevo durum wheat via back-crossing. ‘Soft Svevo’ had SKC...

  5. 7 CFR 981.61 - Redetermination of kernel weight.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 8 2010-01-01 2010-01-01 false Redetermination of kernel weight. 981.61 Section 981... GROWN IN CALIFORNIA Order Regulating Handling Volume Regulation § 981.61 Redetermination of kernel weight. The Board, on the basis of reports by handlers, shall redetermine the kernel weight of...

  6. Multiple spectral kernel learning and a gaussian complexity computation.

    Science.gov (United States)

    Reyhani, Nima

    2013-07-01

    Multiple kernel learning (MKL) partially solves the kernel selection problem in support vector machines and similar classifiers by minimizing the empirical risk over a subset of the linear combination of given kernel matrices. For large sample sets, the size of the kernel matrices becomes a numerical issue. In many cases, the kernel matrix is of low-efficient rank. However, the low-rank property is not efficiently utilized in MKL algorithms. Here, we suggest multiple spectral kernel learning that efficiently uses the low-rank property by finding a kernel matrix from a set of Gram matrices of a few eigenvectors from all given kernel matrices, called a spectral kernel set. We provide a new bound for the gaussian complexity of the proposed kernel set, which depends on both the geometry of the kernel set and the number of Gram matrices. This characterization of the complexity implies that in an MKL setting, adding more kernels may not monotonically increase the complexity, while previous bounds show otherwise.

  7. A Fast and Simple Graph Kernel for RDF

    NARCIS (Netherlands)

    de Vries, G.K.D.; de Rooij, S.

    2013-01-01

    In this paper we study a graph kernel for RDF based on constructing a tree for each instance and counting the number of paths in that tree. In our experiments this kernel shows comparable classification performance to the previously introduced intersection subtree kernel, but is significantly faster

  8. 7 CFR 981.60 - Determination of kernel weight.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 8 2010-01-01 2010-01-01 false Determination of kernel weight. 981.60 Section 981.60... Regulating Handling Volume Regulation § 981.60 Determination of kernel weight. (a) Almonds for which settlement is made on kernel weight. All lots of almonds, whether shelled or unshelled, for which...

  9. 21 CFR 176.350 - Tamarind seed kernel powder.

    Science.gov (United States)

    2010-04-01

    ... 21 Food and Drugs 3 2010-04-01 2009-04-01 true Tamarind seed kernel powder. 176.350 Section 176... Substances for Use Only as Components of Paper and Paperboard § 176.350 Tamarind seed kernel powder. Tamarind seed kernel powder may be safely used as a component of articles intended for use in...

  10. Heat kernel analysis for Bessel operators on symmetric cones

    DEFF Research Database (Denmark)

    Möllers, Jan

    2014-01-01

    . The heat kernel is explicitly given in terms of a multivariable $I$-Bessel function on $Ω$. Its corresponding heat kernel transform defines a continuous linear operator between $L^p$-spaces. The unitary image of the $L^2$-space under the heat kernel transform is characterized as a weighted Bergmann space...

  11. Stable Kernel Representations as Nonlinear Left Coprime Factorizations

    NARCIS (Netherlands)

    Paice, A.D.B.; Schaft, A.J. van der

    1994-01-01

    A representation of nonlinear systems based on the idea of representing the input-output pairs of the system as elements of the kernel of a stable operator has been recently introduced. This has been denoted the kernel representation of the system. In this paper it is demonstrated that the kernel

  12. Kernel Temporal Differences for Neural Decoding

    Directory of Open Access Journals (Sweden)

    Jihye Bae

    2015-01-01

    Full Text Available We study the feasibility and capability of the kernel temporal difference (KTD(λ algorithm for neural decoding. KTD(λ is an online, kernel-based learning algorithm, which has been introduced to estimate value functions in reinforcement learning. This algorithm combines kernel-based representations with the temporal difference approach to learning. One of our key observations is that by using strictly positive definite kernels, algorithm’s convergence can be guaranteed for policy evaluation. The algorithm’s nonlinear functional approximation capabilities are shown in both simulations of policy evaluation and neural decoding problems (policy improvement. KTD can handle high-dimensional neural states containing spatial-temporal information at a reasonable computational complexity allowing real-time applications. When the algorithm seeks a proper mapping between a monkey’s neural states and desired positions of a computer cursor or a robot arm, in both open-loop and closed-loop experiments, it can effectively learn the neural state to action mapping. Finally, a visualization of the coadaptation process between the decoder and the subject shows the algorithm’s capabilities in reinforcement learning brain machine interfaces.

  13. Bergman kernel and complex singularity exponent

    Institute of Scientific and Technical Information of China (English)

    LEE; HanJin

    2009-01-01

    We give a precise estimate of the Bergman kernel for the model domain defined by Ω F={(z,w) ∈ C n+1:Im w |F (z)| 2 > 0},where F=(f 1,...,f m) is a holomorphic map from C n to C m,in terms of the complex singularity exponent of F.

  14. Kernel based subspace projection of hyperspectral images

    DEFF Research Database (Denmark)

    Larsen, Rasmus; Nielsen, Allan Aasbjerg; Arngren, Morten

    In hyperspectral image analysis an exploratory approach to analyse the image data is to conduct subspace projections. As linear projections often fail to capture the underlying structure of the data, we present kernel based subspace projections of PCA and Maximum Autocorrelation Factors (MAF...

  15. Analytic properties of the Virasoro modular kernel

    CERN Document Server

    Nemkov, Nikita

    2016-01-01

    On the space of generic conformal blocks the modular transformation of the underlying surface is realized as a linear integral transformation. We show that the analytic properties of conformal block implied by Zamolodchikov's formula are shared by the kernel of the modular transformation and illustrate this by explicit computation in the case of the one-point toric conformal block.

  16. A Cubic Kernel for Feedback Vertex Set

    NARCIS (Netherlands)

    Bodlaender, H.L.

    2006-01-01

    The FEEDBACK VERTEX SET problem on unweighted, undirected graphs is considered. Improving upon a result by Burrage et al. [7], we show that this problem has a kernel with O(κ3) vertices, i.e., there is a polynomial time algorithm, that given a graph G and an integer κ, finds a graph G' and integer

  17. Analytic properties of the Virasoro modular kernel

    Energy Technology Data Exchange (ETDEWEB)

    Nemkov, Nikita [Moscow Institute of Physics and Technology (MIPT), Dolgoprudny (Russian Federation); Institute for Theoretical and Experimental Physics (ITEP), Moscow (Russian Federation); National University of Science and Technology MISIS, The Laboratory of Superconducting metamaterials, Moscow (Russian Federation)

    2017-06-15

    On the space of generic conformal blocks the modular transformation of the underlying surface is realized as a linear integral transformation. We show that the analytic properties of conformal block implied by Zamolodchikov's formula are shared by the kernel of the modular transformation and illustrate this by explicit computation in the case of the one-point toric conformal block. (orig.)

  18. Hyperbolic L2-modules with Reproducing Kernels

    Institute of Scientific and Technical Information of China (English)

    David EELPODE; Frank SOMMEN

    2006-01-01

    Abstract In this paper, the Dirac operator on the Klein model for the hyperbolic space is considered. A function space containing L2-functions on the sphere Sm-1 in (R)m, which are boundary values of solutions for this operator, is defined, and it is proved that this gives rise to a Hilbert module with a reproducing kernel.

  19. Protein Structure Prediction Using String Kernels

    Science.gov (United States)

    2006-03-03

    Prediction using String Kernels 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 5e. TASK NUMBER...consists of 4352 sequences from SCOP version 1.53 extracted from the Astral database, grouped into families and superfamilies. The dataset is processed

  20. Bergman kernel and complex singularity exponent

    Institute of Scientific and Technical Information of China (English)

    CHEN BoYong; LEE HanJin

    2009-01-01

    We give a precise estimate of the Bergman kernel for the model domain defined by Ω_F = {(z,w) ∈ C~(n+1) : Imw - |F(z)|~2 > 0},where F = (f_1,... ,f_m) is a holomorphic map from C~n to C~m,in terms of the complex singularity exponent of F.

  1. Symbol recognition with kernel density matching.

    Science.gov (United States)

    Zhang, Wan; Wenyin, Liu; Zhang, Kun

    2006-12-01

    We propose a novel approach to similarity assessment for graphic symbols. Symbols are represented as 2D kernel densities and their similarity is measured by the Kullback-Leibler divergence. Symbol orientation is found by gradient-based angle searching or independent component analysis. Experimental results show the outstanding performance of this approach in various situations.

  2. Developing Linux kernel space device driver

    Institute of Scientific and Technical Information of China (English)

    Zheng Wei; Wang Qinruo; Wu Naiyou

    2003-01-01

    This thesis introduces how to develop kernel level device drivers on Linux platform in detail. On the basis of comparing proc file system with dev file system, we choose PCI devices and USB devices as instances to introduce the method of writing device drivers for character devices by using these two file systems.

  3. Heat Kernel Renormalization on Manifolds with Boundary

    OpenAIRE

    Albert, Benjamin I.

    2016-01-01

    In the monograph Renormalization and Effective Field Theory, Costello gave an inductive position space renormalization procedure for constructing an effective field theory that is based on heat kernel regularization of the propagator. In this paper, we extend Costello's renormalization procedure to a class of manifolds with boundary. In addition, we reorganize the presentation of the preexisting material, filling in details and strengthening the results.

  4. Convolution kernels for multi-wavelength imaging

    Science.gov (United States)

    Boucaud, A.; Bocchio, M.; Abergel, A.; Orieux, F.; Dole, H.; Hadj-Youcef, M. A.

    2016-12-01

    Astrophysical images issued from different instruments and/or spectral bands often require to be processed together, either for fitting or comparison purposes. However each image is affected by an instrumental response, also known as point-spread function (PSF), that depends on the characteristics of the instrument as well as the wavelength and the observing strategy. Given the knowledge of the PSF in each band, a straightforward way of processing images is to homogenise them all to a target PSF using convolution kernels, so that they appear as if they had been acquired by the same instrument. We propose an algorithm that generates such PSF-matching kernels, based on Wiener filtering with a tunable regularisation parameter. This method ensures all anisotropic features in the PSFs to be taken into account. We compare our method to existing procedures using measured Herschel/PACS and SPIRE PSFs and simulated JWST/MIRI PSFs. Significant gains up to two orders of magnitude are obtained with respect to the use of kernels computed assuming Gaussian or circularised PSFs. A software to compute these kernels is available at https://github.com/aboucaud/pypher

  5. Covariant derivative expansion of the heat kernel

    Energy Technology Data Exchange (ETDEWEB)

    Salcedo, L.L. [Universidad de Granada, Departamento de Fisica Moderna, Granada (Spain)

    2004-11-01

    Using the technique of labeled operators, compact explicit expressions are given for all traced heat kernel coefficients containing zero, two, four and six covariant derivatives, and for diagonal coefficients with zero, two and four derivatives. The results apply to boundaryless flat space-times and arbitrary non-Abelian scalar and gauge background fields. (orig.)

  6. A Kernel Approach to Multi-Task Learning with Task-Specific Kernels

    Institute of Scientific and Technical Information of China (English)

    Wei Wu; Hang Li; Yun-Hua Hu; Rong Jin

    2012-01-01

    Several kernel-based methods for multi-task learning have been proposed,which leverage relations among tasks as regularization to enhance the overall learning accuracies.These methods assume that the tasks share the same kernel,which could limit their applications because in practice different tasks may need different kernels.The main challenge of introducing multiple kernels into multiple tasks is that models from different reproducing kernel Hilbert spaces (RKHSs) are not comparable,making it difficult to exploit relations among tasks.This paper addresses the challenge by formalizing the problem in the square integrable space (SIS).Specially,it proposes a kernel-based method which makes use of a regularization term defined in SIS to represent task relations.We prove a new representer theorem for the proposed approach in SIS.We further derive a practical method for solving the learning problem and conduct consistency analysis of the method.We discuss the relationship between our method and an existing method.We also give an SVM (support vector machine)-based implementation of our method for multi-label classification.Experiments on an artificial example and two real-world datasets show that the proposed method performs better than the existing method.

  7. Kernel based orthogonalization for change detection in hyperspectral images

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg

    Kernel versions of principal component analysis (PCA) and minimum noise fraction (MNF) analysis are applied to change detection in hyperspectral image (HyMap) data. The kernel versions are based on so-called Q-mode analysis in which the data enter into the analysis via inner products in the Gram...... the kernel function and then performing a linear analysis in that space. An example shows the successful application of (kernel PCA and) kernel MNF analysis to change detection in HyMap data covering a small agricultural area near Lake Waging-Taching, Bavaria, in Southern Germany. In the change detection...

  8. Geodesic exponential kernels: When Curvature and Linearity Conflict

    DEFF Research Database (Denmark)

    Feragen, Aase; Lauze, François; Hauberg, Søren

    2015-01-01

    We consider kernel methods on general geodesic metric spaces and provide both negative and positive results. First we show that the common Gaussian kernel can only be generalized to a positive definite kernel on a geodesic metric space if the space is flat. As a result, for data on a Riemannian...... Laplacian kernel can be generalized while retaining positive definiteness. This implies that geodesic Laplacian kernels can be generalized to some curved spaces, including spheres and hyperbolic spaces. Our theoretical results are verified empirically....

  9. The pre-image problem in kernel methods.

    Science.gov (United States)

    Kwok, James Tin-yau; Tsang, Ivor Wai-hung

    2004-11-01

    In this paper, we address the problem of finding the pre-image of a feature vector in the feature space induced by a kernel. This is of central importance in some kernel applications, such as on using kernel principal component analysis (PCA) for image denoising. Unlike the traditional method which relies on nonlinear optimization, our proposed method directly finds the location of the pre-image based on distance constraints in the feature space. It is noniterative, involves only linear algebra and does not suffer from numerical instability or local minimum problems. Evaluations on performing kernel PCA and kernel clustering on the USPS data set show much improved performance.

  10. Generalization Performance of Regularized Ranking With Multiscale Kernels.

    Science.gov (United States)

    Zhou, Yicong; Chen, Hong; Lan, Rushi; Pan, Zhibin

    2016-05-01

    The regularized kernel method for the ranking problem has attracted increasing attentions in machine learning. The previous regularized ranking algorithms are usually based on reproducing kernel Hilbert spaces with a single kernel. In this paper, we go beyond this framework by investigating the generalization performance of the regularized ranking with multiscale kernels. A novel ranking algorithm with multiscale kernels is proposed and its representer theorem is proved. We establish the upper bound of the generalization error in terms of the complexity of hypothesis spaces. It shows that the multiscale ranking algorithm can achieve satisfactory learning rates under mild conditions. Experiments demonstrate the effectiveness of the proposed method for drug discovery and recommendation tasks.

  11. Flavour changes due to effect of different packaging materials on storing of cottonseed oil, hydrogenated oil and margarine.

    Directory of Open Access Journals (Sweden)

    El-Shattory, Y.

    1997-04-01

    Full Text Available Bleached cottonseed oil, partially hydrogenated palm oil and margarine were packed in metal cans and white plastic bottles and stored for seven months at room temperature on side bench. Assessment of the stability of the oils towards flavour deterioration was reported. The deterioration of flavour developed from bleached cottonseed oil, partially hydrogenated palm oil and margarine was observed due to increase amount of aldehydes and ketones which play an important role in deterioration of the oils. From the results we found metal can offered suitable and better protection against deterioration than plastic package for cottonseed oil, partially hydrogenated palm oil. While plastic container was better for storing margarine and this is due to the presence of water and salt in margarine where they compose about 16% and 2% respectively.

    Aceite de semilla de algodón decolorado, aceite de palma parcialmente hidrogenado y margarina fueron envasados en latas metálicas y botellas de plástico blancas y almacenados durante siete meses a temperatura ambiente en estantes. Se relacionó la evaluación de la estabilidad de los aceites con la deterioración del flavor. La deterioración del flavor producida en aceite de semilla de algodón decolorado, aceite de palma parcialmente hidrogenado y margarina fue observada debido al aumento en la cantidad de aldehídos y cotonas que juegan un importante papel en la deterioración de los aceites. A partir de los resultados obtenidos se encontró que las latas metálicas ofrecieron una adecuada y mejor protección frente a la deterioración que los envases de plásticos para aceite de semilla de algodón y aceite de palma parcialmente hidrogenado. Por otra parte, los recipientes de plástico fueron mejores para el almacenamiento de margarina y esto es debido a la presencia de agua y sales en ella en una proporción del 16% y 2% respectivamente.

  12. Kernel Methods for Machine Learning with Life Science Applications

    DEFF Research Database (Denmark)

    Abrahamsen, Trine Julie

    Kernel methods refer to a family of widely used nonlinear algorithms for machine learning tasks like classification, regression, and feature extraction. By exploiting the so-called kernel trick straightforward extensions of classical linear algorithms are enabled as long as the data only appear...... models to kernel learning, and means for restoring the generalizability in both kernel Principal Component Analysis and the Support Vector Machine are proposed. Viability is proved on a wide range of benchmark machine learning data sets....... as innerproducts in the model formulation. This dissertation presents research on improving the performance of standard kernel methods like kernel Principal Component Analysis and the Support Vector Machine. Moreover, the goal of the thesis has been two-fold. The first part focuses on the use of kernel Principal...

  13. Efficient $\\chi ^{2}$ Kernel Linearization via Random Feature Maps.

    Science.gov (United States)

    Yuan, Xiao-Tong; Wang, Zhenzhen; Deng, Jiankang; Liu, Qingshan

    2016-11-01

    Explicit feature mapping is an appealing way to linearize additive kernels, such as χ(2) kernel for training large-scale support vector machines (SVMs). Although accurate in approximation, feature mapping could pose computational challenges in high-dimensional settings as it expands the original features to a higher dimensional space. To handle this issue in the context of χ(2) kernel SVMs learning, we introduce a simple yet efficient method to approximately linearize χ(2) kernel through random feature maps. The main idea is to use sparse random projection to reduce the dimensionality of feature maps while preserving their approximation capability to the original kernel. We provide approximation error bound for the proposed method. Furthermore, we extend our method to χ(2) multiple kernel SVMs learning. Extensive experiments on large-scale image classification tasks confirm that the proposed approach is able to significantly speed up the training process of the χ(2) kernel SVMs at almost no cost of testing accuracy.

  14. Multiple Kernel Learning in Fisher Discriminant Analysis for Face Recognition

    Directory of Open Access Journals (Sweden)

    Xiao-Zhang Liu

    2013-02-01

    Full Text Available Recent applications and developments based on support vector machines (SVMs have shown that using multiple kernels instead of a single one can enhance classifier performance. However, there are few reports on performance of the kernel‐based Fisher discriminant analysis (kernel‐based FDA method with multiple kernels. This paper proposes a multiple kernel construction method for kernel‐based FDA. The constructed kernel is a linear combination of several base kernels with a constraint on their weights. By maximizing the margin maximization criterion (MMC, we present an iterative scheme for weight optimization. The experiments on the FERET and CMU PIE face databases show that, our multiple kernel Fisher discriminant analysis (MKFD achieves high recognition performance, compared with single‐kernel‐based FDA. The experiments also show that the constructed kernel relaxes parameter selection for kernel‐based FDA to some extent.

  15. 棉粕的营养组成及其在畜禽生产中的应用%Nutritional Composition of Cottonseed Meal and Its Application in Poultry and Animal Production

    Institute of Scientific and Technical Information of China (English)

    刘少娟; 陈家顺; 姚康; 印遇龙

    2016-01-01

    Cottonseed meal, the light red and yellow granular articles, is obtained from cottonseed by processing technics of press and extraction. The crude protein content of cottonseed meal is second only to soybean meal and reaches above 40%. Accordingly, cottonseed meal is one of the good resources of plant protein and is widely applied in livestock breeding industry as feedstuff. However, there are a series of anti-nutritional factors in cottonseed meal, including free gossypol, tannin, phytic acid, cyclopropane fatty acid, etc. These anti-nutritional factors show toxic effect to animals, which constricts the application of cottonseed meal in animals production. With the goal of providing references for the rational application of cottonseed meal in animal production, we reviewed the nutritional composition of cottonseed meal and its application in poultry and animal production.%棉粕是棉籽经过压榨、浸出等工艺得到的一种微红色或黄色的颗粒状物品,其粗蛋白的含量可达40%以上,仅次于豆粕,是优良的植物蛋白源之一。因此,常被人们当做饲料原料应用于养殖业中。但因棉粕中含有很多抗营养因子,如游离棉酚、单宁、植酸、环丙烯脂肪酸等,会对动物产生一定的毒害作用,使得棉粕在动物中的利用受到限制。对棉粕的营养组成及其在畜禽生产中的应用进行了综述,以期为棉粕在畜禽生产中的合理利用提供参考。

  16. A Novel Framework for Learning Geometry-Aware Kernels.

    Science.gov (United States)

    Pan, Binbin; Chen, Wen-Sheng; Xu, Chen; Chen, Bo

    2016-05-01

    The data from real world usually have nonlinear geometric structure, which are often assumed to lie on or close to a low-dimensional manifold in a high-dimensional space. How to detect this nonlinear geometric structure of the data is important for the learning algorithms. Recently, there has been a surge of interest in utilizing kernels to exploit the manifold structure of the data. Such kernels are called geometry-aware kernels and are widely used in the machine learning algorithms. The performance of these algorithms critically relies on the choice of the geometry-aware kernels. Intuitively, a good geometry-aware kernel should utilize additional information other than the geometric information. In many applications, it is required to compute the out-of-sample data directly. However, most of the geometry-aware kernel methods are restricted to the available data given beforehand, with no straightforward extension for out-of-sample data. In this paper, we propose a framework for more general geometry-aware kernel learning. The proposed framework integrates multiple sources of information and enables us to develop flexible and effective kernel matrices. Then, we theoretically show how the learned kernel matrices are extended to the corresponding kernel functions, in which the out-of-sample data can be computed directly. Under our framework, a novel family of geometry-aware kernels is developed. Especially, some existing geometry-aware kernels can be viewed as instances of our framework. The performance of the kernels is evaluated on dimensionality reduction, classification, and clustering tasks. The empirical results show that our kernels significantly improve the performance.

  17. Effects of feeding extruded full-fat cottonseed pellets in place of tallow as a fat source for finishing heifers on feedlot performance, carcass characteristics, sensory traits, display color, and fatty acid profiles.

    Science.gov (United States)

    Stelzleni, A M; Froetschel, M A; Pringle, T D

    2013-09-01

    The objective of this study was to examine the effects of supplemental feeding of full-fat extruded cottonseed pellets (FFECS) compared with tallow on carcass characteristics, sensory traits, retail display color, and fatty acid profiles, especially CLA isomers in finishing heifers. Twenty-one Angus heifers (450 ± 5 kg) were assigned randomly to 1 of 3 experimental diets: 1) 100% supplemental fat from tallow at 4.1% of ration DM (TAL), 2) a 50:50 ratio of supplemental fat from a combination of tallow at 2.1% and FFECS at 12.8% of ration DM (TAL/ECS), and 3) 100% supplemental fat from FFECS at 25.6% ration DM (ECS). All rations were formulated to contain 7.5% fat on a DM basis. Heifers were individually fed, ad libitum, for 82 d, and BW, G:F, DMI, ADG, and body composition via ultrasound were collected at 3 to 4 wk intervals. After 82 d on feed heifers were slaughtered under federal inspection, and carcass characteristics were measured (at 24 h). The LM was removed for retail display color (1, 3, 6, 10 d), Warner-Bratzler shear force (1, 3, 7, 14, 21 d postmortem aging), sensory analysis (1, 7, 14, 21 d postmortem aging), and fatty acid profile analysis. Subcutaneous fat, including all layers, was removed from the LM for fatty acid profile analysis, and ground beef patties (80:20) were produced with lean from the brisket and fat from the plate for retail color analysis (1, 2, 4, 7 d). Supplemental fat source did not influence feedlot performance for any of the traits measured (P > 0.12) or any carcass traits related to yield, quality, or LM color at the 12th- to 13th-rib interface (P > 0.15). Supplemental fat source did not affect Warner-Bratzler shear force or any sensory traits (P > 0.20), but LM steaks became more tender as postmortem aging time increased up to 14 d (P tallow increased linoleic acid (C18:2(n-6)) in both intramuscular and subcutaneous fat (P 0.90). Full-fat extruded cottonseed pellets are interchangeable with tallow in heifer finishing diets

  18. Kernel Density Estimation, Kernel Methods, and Fast Learning in Large Data Sets.

    Science.gov (United States)

    Wang, Shitong; Wang, Jun; Chung, Fu-lai

    2014-01-01

    Kernel methods such as the standard support vector machine and support vector regression trainings take O(N(3)) time and O(N(2)) space complexities in their naïve implementations, where N is the training set size. It is thus computationally infeasible in applying them to large data sets, and a replacement of the naive method for finding the quadratic programming (QP) solutions is highly desirable. By observing that many kernel methods can be linked up with kernel density estimate (KDE) which can be efficiently implemented by some approximation techniques, a new learning method called fast KDE (FastKDE) is proposed to scale up kernel methods. It is based on establishing a connection between KDE and the QP problems formulated for kernel methods using an entropy-based integrated-squared-error criterion. As a result, FastKDE approximation methods can be applied to solve these QP problems. In this paper, the latest advance in fast data reduction via KDE is exploited. With just a simple sampling strategy, the resulted FastKDE method can be used to scale up various kernel methods with a theoretical guarantee that their performance does not degrade a lot. It has a time complexity of O(m(3)) where m is the number of the data points sampled from the training set. Experiments on different benchmarking data sets demonstrate that the proposed method has comparable performance with the state-of-art method and it is effective for a wide range of kernel methods to achieve fast learning in large data sets.

  19. Kernel Smoothing Methods for Non-Poissonian Seismic Hazard Analysis

    Science.gov (United States)

    Woo, Gordon

    2017-04-01

    For almost fifty years, the mainstay of probabilistic seismic hazard analysis has been the methodology developed by Cornell, which assumes that earthquake occurrence is a Poisson process, and that the spatial distribution of epicentres can be represented by a set of polygonal source zones, within which seismicity is uniform. Based on Vere-Jones' use of kernel smoothing methods for earthquake forecasting, these methods were adapted in 1994 by the author for application to probabilistic seismic hazard analysis. There is no need for ambiguous boundaries of polygonal source zones, nor for the hypothesis of time independence of earthquake sequences. In Europe, there are many regions where seismotectonic zones are not well delineated, and where there is a dynamic stress interaction between events, so that they cannot be described as independent. From the Amatrice earthquake of 24 August, 2016, the subsequent damaging earthquakes in Central Italy over months were not independent events. Removing foreshocks and aftershocks is not only an ill-defined task, it has a material effect on seismic hazard computation. Because of the spatial dispersion of epicentres, and the clustering of magnitudes for the largest events in a sequence, which might all be around magnitude 6, the specific event causing the highest ground motion can vary from one site location to another. Where significant active faults have been clearly identified geologically, they should be modelled as individual seismic sources. The remaining background seismicity should be modelled as non-Poissonian using statistical kernel smoothing methods. This approach was first applied for seismic hazard analysis at a UK nuclear power plant two decades ago, and should be included within logic-trees for future probabilistic seismic hazard at critical installations within Europe. In this paper, various salient European applications are given.

  20. First discovery of acetone extract from cottonseed oil sludge as a novel antiviral agent against plant viruses.

    Directory of Open Access Journals (Sweden)

    Lei Zhao

    Full Text Available A novel acetone extract from cottonseed oil sludge was firstly discovered against plant viruses including Tobacco mosaic virus (TMV, Rice stripe virus (RSV and Southern rice black streaked dwarf virus (SRBSDV. Gossypol and β-sitosterol separated from the acetone extract were tested for their effects on anti-TMV and analysed by nuclear magnetic resonance (NMR assay. In vivo and field trials in different geographic distributions and different host varieties declared that this extract mixture was more efficient than the commercial agent Ningnanmycin with a broad spectrum of anti-plant-viruses activity. No phytotoxic activity was observed in the treated plants and environmental toxicology showed that this new acetone extract was environmentally friendly, indicating that this acetone extract has potential application in the control of plant virus in the future.

  1. First discovery of acetone extract from cottonseed oil sludge as a novel antiviral agent against plant viruses.

    Science.gov (United States)

    Zhao, Lei; Feng, Chaohong; Hou, Caiting; Hu, Lingyun; Wang, Qiaochun; Wu, Yunfeng

    2015-01-01

    A novel acetone extract from cottonseed oil sludge was firstly discovered against plant viruses including Tobacco mosaic virus (TMV), Rice stripe virus (RSV) and Southern rice black streaked dwarf virus (SRBSDV). Gossypol and β-sitosterol separated from the acetone extract were tested for their effects on anti-TMV and analysed by nuclear magnetic resonance (NMR) assay. In vivo and field trials in different geographic distributions and different host varieties declared that this extract mixture was more efficient than the commercial agent Ningnanmycin with a broad spectrum of anti-plant-viruses activity. No phytotoxic activity was observed in the treated plants and environmental toxicology showed that this new acetone extract was environmentally friendly, indicating that this acetone extract has potential application in the control of plant virus in the future.

  2. Wilson Dslash Kernel From Lattice QCD Optimization

    Energy Technology Data Exchange (ETDEWEB)

    Joo, Balint [Jefferson Lab, Newport News, VA; Smelyanskiy, Mikhail [Parallel Computing Lab, Intel Corporation, California, USA; Kalamkar, Dhiraj D. [Parallel Computing Lab, Intel Corporation, India; Vaidyanathan, Karthikeyan [Parallel Computing Lab, Intel Corporation, India

    2015-07-01

    Lattice Quantum Chromodynamics (LQCD) is a numerical technique used for calculations in Theoretical Nuclear and High Energy Physics. LQCD is traditionally one of the first applications ported to many new high performance computing architectures and indeed LQCD practitioners have been known to design and build custom LQCD computers. Lattice QCD kernels are frequently used as benchmarks (e.g. 168.wupwise in the SPEC suite) and are generally well understood, and as such are ideal to illustrate several optimization techniques. In this chapter we will detail our work in optimizing the Wilson-Dslash kernels for Intel Xeon Phi, however, as we will show the technique gives excellent performance on regular Xeon Architecture as well.

  3. Learning Potential Energy Landscapes using Graph Kernels

    CERN Document Server

    Ferré, G; Barros, K

    2016-01-01

    Recent machine learning methods make it possible to model potential energy of atomic configurations with chemical-level accuracy (as calculated from ab-initio calculations) and at speeds suitable for molecular dynamics simulation. Best performance is achieved when the known physical constraints are encoded in the machine learning models. For example, the atomic energy is invariant under global translations and rotations; it is also invariant to permutations of same-species atoms. Although simple to state, these symmetries are complicated to encode into machine learning algorithms. In this paper, we present a machine learning approach based on graph theory that naturally incorporates translation, rotation, and permutation symmetries. Specifically, we use a random walk graph kernel to measure the similarity of two adjacency matrices, each of which represents a local atomic environment. We show on a standard benchmark that our Graph Approximated Energy (GRAPE) method is competitive with state of the art kernel m...

  4. Viability Kernel for Ecosystem Management Models

    CERN Document Server

    Anaya, Eladio Ocana; Oliveros--Ramos, Ricardo; Tam, Jorge

    2009-01-01

    We consider sustainable management issues formulated within the framework of control theory. The problem is one of controlling a discrete--time dynamical system (e.g. population model) in the presence of state and control constraints, representing conflicting economic and ecological issues for instance. The viability kernel is known to play a basic role for the analysis of such problems and the design of viable control feedbacks, but its computation is not an easy task in general. We study the viability of nonlinear generic ecosystem models under preservation and production constraints. Under simple conditions on the growth rates at the boundary constraints, we provide an explicit description of the viability kernel. A numerical illustration is given for the hake--anchovy couple in the Peruvian upwelling ecosystem.

  5. A kernel version of spatial factor analysis

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg

    2009-01-01

    of PCA and related techniques. An interesting dilemma in reduction of dimensionality of data is the desire to obtain simplicity for better understanding, visualization and interpretation of the data on the one hand, and the desire to retain sufficient detail for adequate representation on the other hand......Based on work by Pearson in 1901, Hotelling in 1933 introduced principal component analysis (PCA). PCA is often used for general feature generation and linear orthogonalization or compression by dimensionality reduction of correlated multivariate data, see Jolliffe for a comprehensive description...... version of PCA handles nonlinearities by implicitly transforming data into high (even infinite) dimensional feature space via the kernel function and then performing a linear analysis in that space. In this paper we shall apply kernel versions of PCA, maximum autocorrelation factor (MAF) analysis...

  6. Quark-hadron duality: pinched kernel approch

    CERN Document Server

    Dominguez, C A; Schilcher, K; Spiesberger, H

    2016-01-01

    Hadronic spectral functions measured by the ALEPH collaboration in the vector and axial-vector channels are used to study potential quark-hadron duality violations (DV). This is done entirely in the framework of pinched kernel finite energy sum rules (FESR), i.e. in a model independent fashion. The kinematical range of the ALEPH data is effectively extended up to $s = 10\\; {\\mbox{GeV}^2}$ by using an appropriate kernel, and assuming that in this region the spectral functions are given by perturbative QCD. Support for this assumption is obtained by using $e^+ e^-$ annihilation data in the vector channel. Results in both channels show a good saturation of the pinched FESR, without further need of explicit models of DV.

  7. Analog Forecasting with Dynamics-Adapted Kernels

    CERN Document Server

    Zhao, Zhizhen

    2014-01-01

    Analog forecasting is a non-parametric technique introduced by Lorenz in 1969 which predicts the evolution of states of a dynamical system (or observables defined on the states) by following the evolution of the sample in a historical record of observations which most closely resembles the current initial data. Here, we introduce a suite of forecasting methods which improve traditional analog forecasting by combining ideas from state-space reconstruction for dynamical systems and kernel methods developed in harmonic analysis and machine learning. The first improvement is to augment the dimension of the initial data using Takens' delay-coordinate maps to recover information in the initial data lost through partial observations. Then, instead of using Euclidean distances between the states, weighted ensembles of analogs are constructed according to similarity kernels in delay-coordinate space, featuring an explicit dependence on the dynamical vector field generating the data. The eigenvalues and eigenfunctions ...

  8. Preparation and properties of cottonseed protein/polyurethane composite%棉籽蛋白/聚氨酯复合材料的制备与性能

    Institute of Scientific and Technical Information of China (English)

    王长松; 陈磊

    2012-01-01

    为了开发棉籽蛋白在材料领域的应用,利用含肽键的棉籽蛋白与含酰胺基的聚氨酯预聚物共混改性反应制备复合材料,来改善棉籽蛋白的力学性能和耐水性,以保持其生物降解性.利用反应挤出技术,将棉籽分离蛋白与聚氨酯预聚物共混挤出,采用热压工艺,制备了聚氨酯预聚物交联的可降解棉籽蛋白复合材料.结果表明,该材料的加工性、力学性能和耐水性优良.随着聚氨酯组分的增加,材料的断裂伸长率增加,耐水性提高,其中,聚氨酯预聚物质量分数为50%的复合材料,其拉伸强度、断裂伸长率和耐水性分别达到7 MPa、150%和20%,是优良的可降解韧性复合材料.%In order to promote the application of cottonseed protein in material field,the blending modification reaction between cottonseed protein containing peptide bonds and polyurethane prepolymer containing amide groups was used for preparing the composites to improve the mechanical properties and water resistance of cottonseed protein and thus maintain the biodegradability of cottonseed protein.The reaction extrusion technology was applied to perform the blending extrusion of isolated cottonseed protein and polyurethane prepolymer.The degradable cottonseed protein composites with cross-linking of polyurethane prepolymer were prepared with hot extrusion technology.The results show that the workability,mechanical properties and water resistance of the prepared composites are excellent.With increasing the content of polyurethane prepolymer,the fracture elongation and water resistance of the composites get enhanced.The tensile strength,fracture elongation and water resistance of the composite with 50% of polyurethane prepolymer reach 7 MPa,150% and 20%,respectively.It is obvious that the prepared material is an excellent degradable ductile composite.

  9. Searching and Indexing Genomic Databases via Kernelization

    Directory of Open Access Journals (Sweden)

    Travis eGagie

    2015-02-01

    Full Text Available The rapid advance of DNA sequencing technologies has yielded databases of thousands of genomes. To search and index these databases effectively, it is important that we take advantage of the similarity between those genomes. Several authors have recently suggested searching or indexing only one reference genome and the parts of the other genomes where they differ. In this paper we survey the twenty-year history of this idea and discuss its relation to kernelization in parameterized complexity.

  10. Kernel based subspace projection of hyperspectral images

    DEFF Research Database (Denmark)

    Larsen, Rasmus; Nielsen, Allan Aasbjerg; Arngren, Morten

    In hyperspectral image analysis an exploratory approach to analyse the image data is to conduct subspace projections. As linear projections often fail to capture the underlying structure of the data, we present kernel based subspace projections of PCA and Maximum Autocorrelation Factors (MAF). Th......). The MAF projection exploits the fact that interesting phenomena in images typically exhibit spatial autocorrelation. The analysis is based on nearinfrared hyperspectral images of maize grains demonstrating the superiority of the kernelbased MAF method....

  11. Hyperspectral Small Target Detection by Combining Kernel PCA with Linear Mixture Model

    Institute of Scientific and Technical Information of China (English)

    GUYanfeng; ZHANGYe

    2005-01-01

    In this paper, a kernel-based invariant detection method is proposed for small target detection of hyperspectral images. The method combines Kernel principal component analysis (KPCA) with Iinear mixture model (LMM) together. The LMM is used to describe each pixel in the hyperspectral images as a mixture of target,background and noise. The KPCA is used to build back-ground subspace. Finally, a generalized likelihood ratio test is used to detect whether each pixel in hyperspectral image includes target. The numerical experiments are performed on hyperspectral data with 126 bands collected by Airborne visible/infrared imaging spectrometer (AVIRIS).The experimental results show the effectiveness of the proposed method and prove that this method can commendably overcome spectral variability and sparsity of target in the hyperspectral target detection, and it has great ability to separate target from background.

  12. Wheat kernel dimensions: how do they contribute to kernel weight at an individual QTL level?

    Indian Academy of Sciences (India)

    Fa Cui; Anming Ding; Jun Li; Chunhua Zhao; Xingfeng Li; Deshun Feng; Xiuqin Wang; Lin Wang; Jurong Gao; Honggang Wang

    2011-12-01

    Kernel dimensions (KD) contribute greatly to thousand-kernel weight (TKW) in wheat. In the present study, quantitative trait loci (QTL) for TKW, kernel length (KL), kernel width (KW) and kernel diameter ratio (KDR) were detected by both conditional and unconditional QTL mapping methods. Two related F8:9 recombinant inbred line (RIL) populations, comprising 485 and 229 lines, respectively, were used in this study, and the trait phenotypes were evaluated in four environments. Unconditional QTL mapping analysis detected 77 additive QTL for four traits in two populations. Of these, 24 QTL were verified in at least three trials, and five of them were major QTL, thus being of great value for marker assisted selection in breeding programmes. Conditional QTL mapping analysis, compared with unconditional QTL mapping analysis, resulted in reduction in the number of QTL for TKW due to the elimination of TKW variations caused by its conditional traits; based on which we first dissected genetic control system involved in the synthetic process between TKW and KD at an individual QTL level. Results indicated that, at the QTL level, KW had the strongest influence on TKW, followed by KL, and KDR had the lowest level contribution to TKW. In addition, the present study proved that it is not all-inclusive to determine genetic relationships of a pairwise QTL for two related/causal traits based on whether they were co-located. Thus, conditional QTL mapping method should be used to evaluate possible genetic relationships of two related/causal traits.

  13. Physicochemical Properties of Palm Kernel Oil

    Directory of Open Access Journals (Sweden)

    Amira P. Olaniyi

    2014-09-01

    Full Text Available Physicochemical analyses were carried out on palm kernel oil (Adin and the following results were obtained: Saponification value; 280.5±56.1 mgKOH/g, acid value; 2.7±0.3 mg KOH/g, Free Fatty Acid (FFA; 1.35±0.15 KOH/g, ester value; 277.8±56.4 mgKOH/g, peroxide value; 14.3±0.8 mEq/kg; iodine value; 15.86±4.02 mgKOH/g, Specific Gravity (S.G value; 0.904, refractive index; 1.412 and inorganic materials; 1.05%. Its odour and colour were heavy burnt smell and burnt brown, respectively. These values were compared with those obtained for groundnut and coconut oils. It was found that the physico-chemical properties of palm kernel oil are comparable to those of groundnut and coconut oils except for the peroxide value (i.e., 14.3±0.8 mEq which was not detectable in groundnut and coconut oils. Also the odour of both groundnut and coconut oils were pleasant while that of the palm kernel oil was not as pleasant (i.e., heavy burnt smell.

  14. Convolution kernels for multi-wavelength imaging

    CERN Document Server

    Boucaud, Alexandre; Abergel, Alain; Orieux, François; Dole, Hervé; Hadj-Youcef, Mohamed Amine

    2016-01-01

    Astrophysical images issued from different instruments and/or spectral bands often require to be processed together, either for fitting or comparison purposes. However each image is affected by an instrumental response, also known as PSF, that depends on the characteristics of the instrument as well as the wavelength and the observing strategy. Given the knowledge of the PSF in each band, a straightforward way of processing images is to homogenise them all to a target PSF using convolution kernels, so that they appear as if they had been acquired by the same instrument. We propose an algorithm that generates such PSF-matching kernels, based on Wiener filtering with a tunable regularisation parameter. This method ensures all anisotropic features in the PSFs to be taken into account. We compare our method to existing procedures using measured Herschel/PACS and SPIRE PSFs and simulated JWST/MIRI PSFs. Significant gains up to two orders of magnitude are obtained with respect to the use of kernels computed assumin...

  15. A Fast Reduced Kernel Extreme Learning Machine.

    Science.gov (United States)

    Deng, Wan-Yu; Ong, Yew-Soon; Zheng, Qing-Hua

    2016-04-01

    In this paper, we present a fast and accurate kernel-based supervised algorithm referred to as the Reduced Kernel Extreme Learning Machine (RKELM). In contrast to the work on Support Vector Machine (SVM) or Least Square SVM (LS-SVM), which identifies the support vectors or weight vectors iteratively, the proposed RKELM randomly selects a subset of the available data samples as support vectors (or mapping samples). By avoiding the iterative steps of SVM, significant cost savings in the training process can be readily attained, especially on Big datasets. RKELM is established based on the rigorous proof of universal learning involving reduced kernel-based SLFN. In particular, we prove that RKELM can approximate any nonlinear functions accurately under the condition of support vectors sufficiency. Experimental results on a wide variety of real world small instance size and large instance size applications in the context of binary classification, multi-class problem and regression are then reported to show that RKELM can perform at competitive level of generalized performance as the SVM/LS-SVM at only a fraction of the computational effort incurred.

  16. Kernel methods for phenotyping complex plant architecture.

    Science.gov (United States)

    Kawamura, Koji; Hibrand-Saint Oyant, Laurence; Foucher, Fabrice; Thouroude, Tatiana; Loustau, Sébastien

    2014-02-07

    The Quantitative Trait Loci (QTL) mapping of plant architecture is a critical step for understanding the genetic determinism of plant architecture. Previous studies adopted simple measurements, such as plant-height, stem-diameter and branching-intensity for QTL mapping of plant architecture. Many of these quantitative traits were generally correlated to each other, which give rise to statistical problem in the detection of QTL. We aim to test the applicability of kernel methods to phenotyping inflorescence architecture and its QTL mapping. We first test Kernel Principal Component Analysis (KPCA) and Support Vector Machines (SVM) over an artificial dataset of simulated inflorescences with different types of flower distribution, which is coded as a sequence of flower-number per node along a shoot. The ability of discriminating the different inflorescence types by SVM and KPCA is illustrated. We then apply the KPCA representation to the real dataset of rose inflorescence shoots (n=1460) obtained from a 98 F1 hybrid mapping population. We find kernel principal components with high heritability (>0.7), and the QTL analysis identifies a new QTL, which was not detected by a trait-by-trait analysis of simple architectural measurements. The main tools developed in this paper could be use to tackle the general problem of QTL mapping of complex (sequences, 3D structure, graphs) phenotypic traits.

  17. Laguerre Kernels –Based SVM for Image Classification

    Directory of Open Access Journals (Sweden)

    Ashraf Afifi

    2014-01-01

    Full Text Available Support vector machines (SVMs have been promising methods for classification and regression analysis because of their solid mathematical foundations which convey several salient properties that other methods hardly provide. However the performance of SVMs is very sensitive to how the kernel function is selected, the challenge is to choose the kernel function for accurate data classification. In this paper, we introduce a set of new kernel functions derived from the generalized Laguerre polynomials. The proposed kernels could improve the classification accuracy of SVMs for both linear and nonlinear data sets. The proposed kernel functions satisfy Mercer’s condition and orthogonally properties which are important and useful in some applications when the support vector number is needed as in feature selection. The performance of the generalized Laguerre kernels is evaluated in comparison with the existing kernels. It was found that the choice of the kernel function, and the values of the parameters for that kernel are critical for a given amount of data. The proposed kernels give good classification accuracy in nearly all the data sets, especially those of high dimensions.

  18. Identification of Fusarium damaged wheat kernels using image analysis

    Directory of Open Access Journals (Sweden)

    Ondřej Jirsa

    2011-01-01

    Full Text Available Visual evaluation of kernels damaged by Fusarium spp. pathogens is labour intensive and due to a subjective approach, it can lead to inconsistencies. Digital imaging technology combined with appropriate statistical methods can provide much faster and more accurate evaluation of the visually scabby kernels proportion. The aim of the present study was to develop a discrimination model to identify wheat kernels infected by Fusarium spp. using digital image analysis and statistical methods. Winter wheat kernels from field experiments were evaluated visually as healthy or damaged. Deoxynivalenol (DON content was determined in individual kernels using an ELISA method. Images of individual kernels were produced using a digital camera on dark background. Colour and shape descriptors were obtained by image analysis from the area representing the kernel. Healthy and damaged kernels differed significantly in DON content and kernel weight. Various combinations of individual shape and colour descriptors were examined during the development of the model using linear discriminant analysis. In addition to basic descriptors of the RGB colour model (red, green, blue, very good classification was also obtained using hue from the HSL colour model (hue, saturation, luminance. The accuracy of classification using the developed discrimination model based on RGBH descriptors was 85 %. The shape descriptors themselves were not specific enough to distinguish individual kernels.

  19. Implementing Kernel Methods Incrementally by Incremental Nonlinear Projection Trick.

    Science.gov (United States)

    Kwak, Nojun

    2016-05-20

    Recently, the nonlinear projection trick (NPT) was introduced enabling direct computation of coordinates of samples in a reproducing kernel Hilbert space. With NPT, any machine learning algorithm can be extended to a kernel version without relying on the so called kernel trick. However, NPT is inherently difficult to be implemented incrementally because an ever increasing kernel matrix should be treated as additional training samples are introduced. In this paper, an incremental version of the NPT (INPT) is proposed based on the observation that the centerization step in NPT is unnecessary. Because the proposed INPT does not change the coordinates of the old data, the coordinates obtained by INPT can directly be used in any incremental methods to implement a kernel version of the incremental methods. The effectiveness of the INPT is shown by applying it to implement incremental versions of kernel methods such as, kernel singular value decomposition, kernel principal component analysis, and kernel discriminant analysis which are utilized for problems of kernel matrix reconstruction, letter classification, and face image retrieval, respectively.

  20. Image quality of mixed convolution kernel in thoracic computed tomography.

    Science.gov (United States)

    Neubauer, Jakob; Spira, Eva Maria; Strube, Juliane; Langer, Mathias; Voss, Christian; Kotter, Elmar

    2016-11-01

    The mixed convolution kernel alters his properties geographically according to the depicted organ structure, especially for the lung. Therefore, we compared the image quality of the mixed convolution kernel to standard soft and hard kernel reconstructions for different organ structures in thoracic computed tomography (CT) images.Our Ethics Committee approved this prospective study. In total, 31 patients who underwent contrast-enhanced thoracic CT studies were included after informed consent. Axial reconstructions were performed with hard, soft, and mixed convolution kernel. Three independent and blinded observers rated the image quality according to the European Guidelines for Quality Criteria of Thoracic CT for 13 organ structures. The observers rated the depiction of the structures in all reconstructions on a 5-point Likert scale. Statistical analysis was performed with the Friedman Test and post hoc analysis with the Wilcoxon rank-sum test.Compared to the soft convolution kernel, the mixed convolution kernel was rated with a higher image quality for lung parenchyma, segmental bronchi, and the border between the pleura and the thoracic wall (P kernel, the mixed convolution kernel was rated with a higher image quality for aorta, anterior mediastinal structures, paratracheal soft tissue, hilar lymph nodes, esophagus, pleuromediastinal border, large and medium sized pulmonary vessels and abdomen (P kernel cannot fully substitute the standard CT reconstructions. Hard and soft convolution kernel reconstructions still seem to be mandatory for thoracic CT.

  1. MULTI-VIEW FACE DETECTION BASED ON KERNEL PRINCIPAL COMPONENT ANALYSIS AND KERNEL SUPPORT VECTOR TECHNIQUES

    Directory of Open Access Journals (Sweden)

    Muzhir Shaban Al-Ani

    2011-05-01

    Full Text Available Detecting faces across multiple views is more challenging than in a frontal view. To address this problem,an efficient approach is presented in this paper using a kernel machine based approach for learning suchnonlinear mappings to provide effective view-based representation for multi-view face detection. In thispaper Kernel Principal Component Analysis (KPCA is used to project data into the view-subspaces thencomputed as view-based features. Multi-view face detection is performed by classifying each input imageinto face or non-face class, by using a two class Kernel Support Vector Classifier (KSVC. Experimentalresults demonstrate successful face detection over a wide range of facial variation in color, illuminationconditions, position, scale, orientation, 3D pose, and expression in images from several photo collections.

  2. Comparing Alternative Kernels for the Kernel Method of Test Equating: Gaussian, Logistic, and Uniform Kernels. Research Report. ETS RR-08-12

    Science.gov (United States)

    Lee, Yi-Hsuan; von Davier, Alina A.

    2008-01-01

    The kernel equating method (von Davier, Holland, & Thayer, 2004) is based on a flexible family of equipercentile-like equating functions that use a Gaussian kernel to continuize the discrete score distributions. While the classical equipercentile, or percentile-rank, equating method carries out the continuization step by linear interpolation,…

  3. Kernels for Vector-Valued Functions: a Review

    CERN Document Server

    Alvarez, Mauricio A; Lawrence, Neil D

    2011-01-01

    Kernel methods are among the most popular techniques in machine learning. From a frequentist/discriminative perspective they play a central role in regularization theory as they provide a natural choice for the hypotheses space and the regularization functional through the notion of reproducing kernel Hilbert spaces. From a Bayesian/generative perspective they are the key in the context of Gaussian processes, where the kernel function is also known as the covariance function. Traditionally, kernel methods have been used in supervised learning problem with scalar outputs and indeed there has been a considerable amount of work devoted to designing and learning kernels. More recently there has been an increasing interest in methods that deal with multiple outputs, motivated partly by frameworks like multitask learning. In this paper, we review different methods to design or learn valid kernel functions for multiple outputs, paying particular attention to the connection between probabilistic and functional method...

  4. FRACTIONAL INTEGRALS WITH VARIABLE KERNELS ON HARDY SPACES

    Institute of Scientific and Technical Information of China (English)

    ZhangPu; DingYong

    2003-01-01

    The fractional integral operators with variable kernels are discussed.It is proved that if the kernel satisfies the Dini-condition,then the fractional integral operators with variable kernels are bounded from Hp(Rn) into Lq(Rn) when 0

  5. Approximating and learning by Lipschitz kernel on the sphere

    Institute of Scientific and Technical Information of China (English)

    CAO Fei-long; WANG Chang-miao

    2014-01-01

    This paper investigates some approximation properties and learning rates of Lips-chitz kernel on the sphere. A perfect convergence rate on the shifts of Lipschitz kernel on the sphere, which is faster than O(n-1/2), is obtained, where n is the number of parameters needed in the approximation. By means of the approximation, a learning rate of regularized least square algorithm with the Lipschitz kernel on the sphere is also deduced.

  6. Kernel based visual tracking with scale invariant features

    Institute of Scientific and Technical Information of China (English)

    Risheng Han; Zhongliang Jing; Yuanxiang Li

    2008-01-01

    The kernel based tracking has two disadvantages:the tracking window size cannot be adjusted efficiently,and the kernel based color distribution may not have enough ability to discriminate object from clutter background.FDr boosting up the feature's discriminating ability,both scale invariant features and kernel based color distribution features are used as descriptors of tracked object.The proposed algorithm can keep tracking object of varying scales even when the surrounding background is similar to the object's appearance.

  7. Classification of maize kernels using NIR hyperspectral imaging

    DEFF Research Database (Denmark)

    Williams, Paul; Kucheryavskiy, Sergey V.

    2016-01-01

    NIR hyperspectral imaging was evaluated to classify maize kernels of three hardness categories: hard, medium and soft. Two approaches, pixel-wise and object-wise, were investigated to group kernels according to hardness. The pixel-wise classification assigned a class to every pixel from individual...... and specificity of 0.95 and 0.93). Both feature extraction methods can be recommended for classification of maize kernels on production scale....

  8. Effect of Carbohydrate Source and Cottonseed Meal Level in the Concentrate on Feed Intake, Nutrient Digestibility, Rumen Fermentation and Microbial Protein Synthesis in Swamp Buffaloes

    Directory of Open Access Journals (Sweden)

    M. Wanapat

    2013-07-01

    Full Text Available The objective of this study was to investigate the effect of carbohydrate source and cottonseed meal level in the concentrate on feed intake, nutrient digestibility, rumen fermentation and microbial protein synthesis in swamp buffaloes. Four, 4-yr old rumen fistulated swamp buffaloes were randomly assigned to receive four dietary treatments according to a 2×2 factorial arrangement in a 4×4 Latin square design. Factor A was carbohydrate source; cassava chip (CC and CC+rice bran at a ratio 3:1 (CR3:1, and factor B was level of cottonseed meal (CM; 109 g CP/kg (LCM and 328 g CP/kg (HCM in isonitrogenous diets (490 g CP/kg. Buffaloes received urea-treated rice straw ad libitum and supplemented with 5 g concentrate/kg BW. It was found that carbohydrate source did not affect feed intake, nutrient intake, digested nutrients, nutrient digestibility, ammonia nitrogen concentration, fungi and bacterial populations, or microbial protein synthesis (p>0.05. Ruminal pH at 6 h after feeding and the population of protozoa at 4 h after feeding were higher when buffalo were fed with CC than in the CR3:1 treatment (p0.05. Based on this experiment, concentrate with a low level of cottonseed meal could be fed with cassava chips as an energy source in swamp buffalo receiving rice straw.

  9. Parameter optimization in the regularized kernel minimum noise fraction transformation

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg; Vestergaard, Jacob Schack

    2012-01-01

    Based on the original, linear minimum noise fraction (MNF) transformation and kernel principal component analysis, a kernel version of the MNF transformation was recently introduced. Inspired by we here give a simple method for finding optimal parameters in a regularized version of kernel MNF...... analysis. We consider the model signal-to-noise ratio (SNR) as a function of the kernel parameters and the regularization parameter. In 2-4 steps of increasingly refined grid searches we find the parameters that maximize the model SNR. An example based on data from the DLR 3K camera system is given....

  10. Reproducing wavelet kernel method in nonlinear system identification

    Institute of Scientific and Technical Information of China (English)

    WEN Xiang-jun; XU Xiao-ming; CAI Yun-ze

    2008-01-01

    By combining the wavelet decomposition with kernel method, a practical approach of universal multi-scale wavelet kernels constructed in reproducing kernel Hilbert space (RKHS) is discussed, and an identifica-tion scheme using wavelet support vector machines ( WSVM ) estimator is proposed for nonlinear dynamic sys-tems. The good approximating properties of wavelet kernel function enhance the generalization ability of the pro-posed method, and the comparison of some numerical experimental results between the novel approach and some existing methods is encouraging.

  11. Influence of wheat kernel physical properties on the pulverizing process.

    Science.gov (United States)

    Dziki, Dariusz; Cacak-Pietrzak, Grażyna; Miś, Antoni; Jończyk, Krzysztof; Gawlik-Dziki, Urszula

    2014-10-01

    The physical properties of wheat kernel were determined and related to pulverizing performance by correlation analysis. Nineteen samples of wheat cultivars about similar level of protein content (11.2-12.8 % w.b.) and obtained from organic farming system were used for analysis. The kernel (moisture content 10 % w.b.) was pulverized by using the laboratory hammer mill equipped with round holes 1.0 mm screen. The specific grinding energy ranged from 120 kJkg(-1) to 159 kJkg(-1). On the basis of data obtained many of significant correlations (p kernel physical properties and pulverizing process of wheat kernel, especially wheat kernel hardness index (obtained on the basis of Single Kernel Characterization System) and vitreousness significantly and positively correlated with the grinding energy indices and the mass fraction of coarse particles (> 0.5 mm). Among the kernel mechanical properties determined on the basis of uniaxial compression test only the rapture force was correlated with the impact grinding results. The results showed also positive and significant relationships between kernel ash content and grinding energy requirements. On the basis of wheat physical properties the multiple linear regression was proposed for predicting the average particle size of pulverized kernel.

  12. A Kernel-based Account of Bibliometric Measures

    Science.gov (United States)

    Ito, Takahiko; Shimbo, Masashi; Kudo, Taku; Matsumoto, Yuji

    The application of kernel methods to citation analysis is explored. We show that a family of kernels on graphs provides a unified perspective on the three bibliometric measures that have been discussed independently: relatedness between documents, global importance of individual documents, and importance of documents relative to one or more (root) documents (relative importance). The framework provided by the kernels establishes relative importance as an intermediate between relatedness and global importance, in which the degree of `relativity,' or the bias between relatedness and importance, is naturally controlled by a parameter characterizing individual kernels in the family.

  13. Isolation of bacterial endophytes from germinated maize kernels.

    Science.gov (United States)

    Rijavec, Tomaz; Lapanje, Ales; Dermastia, Marina; Rupnik, Maja

    2007-06-01

    The germination of surface-sterilized maize kernels under aseptic conditions proved to be a suitable method for isolation of kernel-associated bacterial endophytes. Bacterial strains identified by partial 16S rRNA gene sequencing as Pantoea sp., Microbacterium sp., Frigoribacterium sp., Bacillus sp., Paenibacillus sp., and Sphingomonas sp. were isolated from kernels of 4 different maize cultivars. Genus Pantoea was associated with a specific maize cultivar. The kernels of this cultivar were often overgrown with the fungus Lecanicillium aphanocladii; however, those exhibiting Pantoea growth were never colonized with it. Furthermore, the isolated bacterium strain inhibited fungal growth in vitro.

  14. WAVELET KERNEL SUPPORT VECTOR MACHINES FOR SPARSE APPROXIMATION

    Institute of Scientific and Technical Information of China (English)

    Tong Yubing; Yang Dongkai; Zhang Qishan

    2006-01-01

    Wavelet, a powerful tool for signal processing, can be used to approximate the target function. For enhancing the sparse property of wavelet approximation, a new algorithm was proposed by using wavelet kernel Support Vector Machines (SVM), which can converge to minimum error with better sparsity. Here, wavelet functions would be firstly used to construct the admitted kernel for SVM according to Mercy theory; then new SVM with this kernel can be used to approximate the target funciton with better sparsity than wavelet approxiamtion itself. The results obtained by our simulation experiment show the feasibility and validity of wavelet kernel support vector machines.

  15. Convolution kernel design and efficient algorithm for sampling density correction.

    Science.gov (United States)

    Johnson, Kenneth O; Pipe, James G

    2009-02-01

    Sampling density compensation is an important step in non-cartesian image reconstruction. One of the common techniques to determine weights that compensate for differences in sampling density involves a convolution. A new convolution kernel is designed for sampling density attempting to minimize the error in a fully reconstructed image. The resulting weights obtained using this new kernel are compared with various previous methods, showing a reduction in reconstruction error. A computationally efficient algorithm is also presented that facilitates the calculation of the convolution of finite kernels. Both the kernel and the algorithm are extended to 3D. Copyright 2009 Wiley-Liss, Inc.

  16. 42 Variability Bugs in the Linux Kernel

    DEFF Research Database (Denmark)

    Abal, Iago; Brabrand, Claus; Wasowski, Andrzej

    2014-01-01

    Feature-sensitive verification pursues effective analysis of the exponentially many variants of a program family. However, researchers lack examples of concrete bugs induced by variability, occurring in real large-scale systems. Such a collection of bugs is a requirement for goal-oriented research......, serving to evaluate tool implementations of feature-sensitive analyses by testing them on real bugs. We present a qualitative study of 42 variability bugs collected from bug-fixing commits to the Linux kernel repository. We analyze each of the bugs, and record the results in a database. In addition, we...

  17. 40 Variability Bugs in the Linux Kernel

    DEFF Research Database (Denmark)

    Abal Rivas, Iago; Brabrand, Claus; Wasowski, Andrzej

    2014-01-01

    is a requirement for goal-oriented research, serving to evaluate tool implementations of feature-sensitive analyses by testing them on real bugs. We present a qualitative study of 40 variability bugs collected from bug-fixing commits to the Linux kernel repository. We investigate each of the 40 bugs, recording......Feature-sensitive verification is a recent field that pursues the effective analysis of the exponential number of variants of a program family. Today researchers lack examples of concrete bugs induced by variability, and occurring in real large-scale software. Such a collection of bugs...

  18. Application of RBAC Model in System Kernel

    Directory of Open Access Journals (Sweden)

    Guan Keqing

    2012-11-01

    Full Text Available In the process of development of some technologies about Ubiquitous computing, the application of embedded intelligent devices is booming. Meanwhile, information security will face more serious threats than before. To improve the security of information terminal’s operation system, this paper analyzed the threats to system’s information security which comes from the abnormal operation by processes, and applied RBAC model into the safety management mechanism of operation system’s kernel. We built an access control model of system’s process, and proposed an implement framework. And the methods of implementation of the model for operation systems were illustrated.

  19. SVM multiuser detection based on heuristic kernel

    Institute of Scientific and Technical Information of China (English)

    Yang Tao; Hu Bo

    2007-01-01

    A support vector machine (SVM) based multiuser detection (MUD) scheme in code-division multiple-access (CDMA) system is proposed. In this scheme, the equivalent support vector (SV) is obtained through a kernel sparsity approximation algorithm, which avoids the conventional costly quadratic programming (QP) procedure in SVM. Besides, the coefficient of the SV is attained through the solution to a generalized eigenproblem. Simulation results show that the proposed scheme has almost the same bit error rate (BER) as the standard SVM and is better than minimum mean square error (MMSE) scheme. Meanwhile, it has a low computation complexity.

  20. Characterization of Flour from Avocado Seed Kernel

    OpenAIRE

    Macey A. Mahawan; Ma. Francia N. Tenorio; Jaycel A. Gomez; Rosenda A. Bronce

    2015-01-01

    The study focused on the Characterization of Flour from Avocado Seed Kernel. Based on the findings of the study the percentages of crude protein, crude fiber, crude fat, total carbohydrates, ash and moisture were 7.75, 4.91, 0.71, 74.65, 2.83 and 14.05 respectively. On the other hand the falling number was 495 seconds while gluten was below the detection limit of the method used. Moreover, the sensory evaluation in terms of color, texture and aroma in 0% proportion of Avocado seed flour was m...

  1. Fixed kernel regression for voltammogram feature extraction

    Science.gov (United States)

    Acevedo Rodriguez, F. J.; López-Sastre, R. J.; Gil-Jiménez, P.; Ruiz-Reyes, N.; Maldonado Bascón, S.

    2009-12-01

    Cyclic voltammetry is an electroanalytical technique for obtaining information about substances under analysis without the need for complex flow systems. However, classifying the information in voltammograms obtained using this technique is difficult. In this paper, we propose the use of fixed kernel regression as a method for extracting features from these voltammograms, reducing the information to a few coefficients. The proposed approach has been applied to a wine classification problem with accuracy rates of over 98%. Although the method is described here for extracting voltammogram information, it can be used for other types of signals.

  2. Kernel based subspace projection of near infrared hyperspectral images of maize kernels

    DEFF Research Database (Denmark)

    Larsen, Rasmus; Arngren, Morten; Hansen, Per Waaben;

    2009-01-01

    In this paper we present an exploratory analysis of hyper- spectral 900-1700 nm images of maize kernels. The imaging device is a line scanning hyper spectral camera using a broadband NIR illumi- nation. In order to explore the hyperspectral data we compare a series of subspace projection methods...

  3. Kernel based subspace projection of near infrared hyperspectral images of maize kernels

    DEFF Research Database (Denmark)

    Larsen, Rasmus; Arngren, Morten; Hansen, Per Waaben

    2009-01-01

    In this paper we present an exploratory analysis of hyper- spectral 900-1700 nm images of maize kernels. The imaging device is a line scanning hyper spectral camera using a broadband NIR illumi- nation. In order to explore the hyperspectral data we compare a series of subspace projection methods...

  4. Cottonseed: protein, oil yields, and oil properties as influenced by potassium fertilization and foliar application of zinc and phosphorus

    Directory of Open Access Journals (Sweden)

    Alkassas, Abou-El-Ela R.

    2007-03-01

    Full Text Available In maximizing the quantity and quality of a crop’s nutritional value in terms of fatty acids and protein, it is necessary to identify the constraints which may affect it and to devise methods of overcoming them through the use of inputs or changes in management practices. Field experiments were conducted during two successive seasons at the Agricultural Research Center, Giza, Egypt, on the cotton cultivar “Giza 86” (Gossypium barbadense L. to study the effects of potassium fertilization (at 0.0 and 47.4 kg of K ha–1 and foliar application of zinc (at 0.0 and 57.6 g of Zn ha–1, two times, 70 and 85 days after planting, “during square initiation and boll setting stage” and phosphorus (at 0.0, 576, 1152 and 1728 g of P ha–1, two times, 80 and 95 days after planting on cottonseed. The application of potassium along with spraying plants with zinc and phosphorus caused  an increase in cottonseed yield ha–1, seed index, seed oil content, oil and protein yields ha–1, seed oil unsaponifiable matter and total unsaturated fatty acids (oleic and linoleic. However, those treatments resulted in a decrease in oil acid value, saponification value and total saturated fatty acids. The highest P concentration of 1728 g ha–1 gave the best values of cottonseed yield/ha, seed index, and seed oil and protein yields/ha and oil saponifiable matter.Para maximizar la cantidad y calidad del valor nutricional de una semilla en términos de ácidos grasos y proteínas es necesario identificar los factores que los afectan y proponer métodos que favorezcan los resultados deseados a través de cambios o mejoras en las prácticas utilizadas. Los experimentos se llevaron a cabo en dos campañas sucesivas en el Agricultural Research Center, Giza, Egipto, en el cultivo “Giza 86” (Gossypium barbadense L. para estudiar los efectos de la fertilización con potasio (a 0.0 y 47.7 kg por ha y las aplicaciones foliares de zinc (a 0.0 y 57.6 g por ha, dos veces

  5. Kernel learning at the first level of inference.

    Science.gov (United States)

    Cawley, Gavin C; Talbot, Nicola L C

    2014-05-01

    Kernel learning methods, whether Bayesian or frequentist, typically involve multiple levels of inference, with the coefficients of the kernel expansion being determined at the first level and the kernel and regularisation parameters carefully tuned at the second level, a process known as model selection. Model selection for kernel machines is commonly performed via optimisation of a suitable model selection criterion, often based on cross-validation or theoretical performance bounds. However, if there are a large number of kernel parameters, as for instance in the case of automatic relevance determination (ARD), there is a substantial risk of over-fitting the model selection criterion, resulting in poor generalisation performance. In this paper we investigate the possibility of learning the kernel, for the Least-Squares Support Vector Machine (LS-SVM) classifier, at the first level of inference, i.e. parameter optimisation. The kernel parameters and the coefficients of the kernel expansion are jointly optimised at the first level of inference, minimising a training criterion with an additional regularisation term acting on the kernel parameters. The key advantage of this approach is that the values of only two regularisation parameters need be determined in model selection, substantially alleviating the problem of over-fitting the model selection criterion. The benefits of this approach are demonstrated using a suite of synthetic and real-world binary classification benchmark problems, where kernel learning at the first level of inference is shown to be statistically superior to the conventional approach, improves on our previous work (Cawley and Talbot, 2007) and is competitive with Multiple Kernel Learning approaches, but with reduced computational expense.

  6. Automatic detection of aflatoxin contaminated corn kernels using dual-band imagery

    Science.gov (United States)

    Ononye, Ambrose E.; Yao, Haibo; Hruska, Zuzana; Kincaid, Russell; Brown, Robert L.; Cleveland, Thomas E.

    2009-05-01

    Aflatoxin is a mycotoxin predominantly produced by Aspergillus flavus and Aspergillus parasitiucus fungi that grow naturally in corn, peanuts and in a wide variety of other grain products. Corn, like other grains is used as food for human and feed for animal consumption. It is known that aflatoxin is carcinogenic; therefore, ingestion of corn infected with the toxin can lead to very serious health problems such as liver damage if the level of the contamination is high. The US Food and Drug Administration (FDA) has strict guidelines for permissible levels in the grain products for both humans and animals. The conventional approach used to determine these contamination levels is one of the destructive and invasive methods that require corn kernels to be ground and then chemically analyzed. Unfortunately, each of the analytical methods can take several hours depending on the quantity, to yield a result. The development of high spectral and spatial resolution imaging sensors has created an opportunity for hyperspectral image analysis to be employed for aflatoxin detection. However, this brings about a high dimensionality problem as a setback. In this paper, we propose a technique that automatically detects aflatoxin contaminated corn kernels by using dual-band imagery. The method exploits the fluorescence emission spectra from corn kernels captured under 365 nm ultra-violet light excitation. Our approach could lead to a non-destructive and non-invasive way of quantifying the levels of aflatoxin contamination. The preliminary results shown here, demonstrate the potential of our technique for aflatoxin detection.

  7. STUDIES ON CONTINUOUS GRINDING PROCESS FOR DRIED WATER CHESTNUT KERNEL

    Directory of Open Access Journals (Sweden)

    S.K. GARG

    2010-06-01

    Full Text Available Grinding is a unit operation to break big solid material into smaller pieces. As far as process of grinding is concerned, power consumption, specific energy consumption and particle size distribution and mill capacity are main considerations from engineering point of view. The experiments were conducted to study the effect of speed of mill, sieve size, feed rate and time of grinding on power consumption and average particle diameter of water chestnut in continuous grinding process. Power consumption was measured for a constant feed rate of 1 and 2 kg/h at different speed of the mill varied from 800 to 1200 rpm for the sieve openings of 0.5 mm, 1.0 mm and 2.0 mm. For all the sieve sizes and feed rates, it was observed that as the speed of the mill increases, there is an increase in power consumption and found significantly low for higher sieve size and lower feed rate. The size distribution of the water chestnut kernel for different speeds and sieve sizes at constant feed rate were obtained by sieve analysis. The milling speed has no significant effect on particle size distribution of ground product and mass fraction was minimum at lower feed rate and higher sieve size. Harris model was found best suitable to describe the size distribution in continuous grinding process. Fineness modulus decreases with increase of milling speed for experimental sieve size and feed rate.

  8. Probabilistic seismic hazard assessment of Italy using kernel estimation methods

    Science.gov (United States)

    Zuccolo, Elisa; Corigliano, Mirko; Lai, Carlo G.

    2013-07-01

    A representation of seismic hazard is proposed for Italy based on the zone-free approach developed by Woo (BSSA 86(2):353-362, 1996a), which is based on a kernel estimation method governed by concepts of fractal geometry and self-organized seismicity, not requiring the definition of seismogenic zoning. The purpose is to assess the influence of seismogenic zoning on the results obtained for the probabilistic seismic hazard analysis (PSHA) of Italy using the standard Cornell's method. The hazard has been estimated for outcropping rock site conditions in terms of maps and uniform hazard spectra for a selected site, with 10 % probability of exceedance in 50 years. Both spectral acceleration and spectral displacement have been considered as ground motion parameters. Differences in the results of PSHA between the two methods are compared and discussed. The analysis shows that, in areas such as Italy, characterized by a reliable earthquake catalog and in which faults are generally not easily identifiable, a zone-free approach can be considered a valuable tool to address epistemic uncertainty within a logic tree framework.

  9. Molecular hardness and softness, local hardness and softness, hardness and softness kernels, and relations among these quantities

    Science.gov (United States)

    Berkowitz, Max; Parr, Robert G.

    1988-02-01

    Hardness and softness kernels η(r,r') and s(r,r') are defined for the ground state of an atomic or molecular electronic system, and the previously defined local hardness and softness η(r) and s(r) and global hardness and softness η and S are obtained from them. The physical meaning of s(r), as a charge capacitance, is discussed (following Huheey and Politzer), and two alternative ``hardness'' indices are identified and briefly discussed.

  10. Generalized Langevin equation with tempered memory kernel

    Science.gov (United States)

    Liemert, André; Sandev, Trifce; Kantz, Holger

    2017-01-01

    We study a generalized Langevin equation for a free particle in presence of a truncated power-law and Mittag-Leffler memory kernel. It is shown that in presence of truncation, the particle from subdiffusive behavior in the short time limit, turns to normal diffusion in the long time limit. The case of harmonic oscillator is considered as well, and the relaxation functions and the normalized displacement correlation function are represented in an exact form. By considering external time-dependent periodic force we obtain resonant behavior even in case of a free particle due to the influence of the environment on the particle movement. Additionally, the double-peak phenomenon in the imaginary part of the complex susceptibility is observed. It is obtained that the truncation parameter has a huge influence on the behavior of these quantities, and it is shown how the truncation parameter changes the critical frequencies. The normalized displacement correlation function for a fractional generalized Langevin equation is investigated as well. All the results are exact and given in terms of the three parameter Mittag-Leffler function and the Prabhakar generalized integral operator, which in the kernel contains a three parameter Mittag-Leffler function. Such kind of truncated Langevin equation motion can be of high relevance for the description of lateral diffusion of lipids and proteins in cell membranes.

  11. Pareto-path multitask multiple kernel learning.

    Science.gov (United States)

    Li, Cong; Georgiopoulos, Michael; Anagnostopoulos, Georgios C

    2015-01-01

    A traditional and intuitively appealing Multitask Multiple Kernel Learning (MT-MKL) method is to optimize the sum (thus, the average) of objective functions with (partially) shared kernel function, which allows information sharing among the tasks. We point out that the obtained solution corresponds to a single point on the Pareto Front (PF) of a multiobjective optimization problem, which considers the concurrent optimization of all task objectives involved in the Multitask Learning (MTL) problem. Motivated by this last observation and arguing that the former approach is heuristic, we propose a novel support vector machine MT-MKL framework that considers an implicitly defined set of conic combinations of task objectives. We show that solving our framework produces solutions along a path on the aforementioned PF and that it subsumes the optimization of the average of objective functions as a special case. Using the algorithms we derived, we demonstrate through a series of experimental results that the framework is capable of achieving a better classification performance, when compared with other similar MTL approaches.

  12. The Kernel Estimation in Biosystems Engineering

    Directory of Open Access Journals (Sweden)

    Esperanza Ayuga Téllez

    2008-04-01

    Full Text Available In many fields of biosystems engineering, it is common to find works in which statistical information is analysed that violates the basic hypotheses necessary for the conventional forecasting methods. For those situations, it is necessary to find alternative methods that allow the statistical analysis considering those infringements. Non-parametric function estimation includes methods that fit a target function locally, using data from a small neighbourhood of the point. Weak assumptions, such as continuity and differentiability of the target function, are rather used than "a priori" assumption of the global target function shape (e.g., linear or quadratic. In this paper a few basic rules of decision are enunciated, for the application of the non-parametric estimation method. These statistical rules set up the first step to build an interface usermethod for the consistent application of kernel estimation for not expert users. To reach this aim, univariate and multivariate estimation methods and density function were analysed, as well as regression estimators. In some cases the models to be applied in different situations, based on simulations, were defined. Different biosystems engineering applications of the kernel estimation are also analysed in this review.

  13. Scientific Computing Kernels on the Cell Processor

    Energy Technology Data Exchange (ETDEWEB)

    Williams, Samuel W.; Shalf, John; Oliker, Leonid; Kamil, Shoaib; Husbands, Parry; Yelick, Katherine

    2007-04-04

    The slowing pace of commodity microprocessor performance improvements combined with ever-increasing chip power demands has become of utmost concern to computational scientists. As a result, the high performance computing community is examining alternative architectures that address the limitations of modern cache-based designs. In this work, we examine the potential of using the recently-released STI Cell processor as a building block for future high-end computing systems. Our work contains several novel contributions. First, we introduce a performance model for Cell and apply it to several key scientific computing kernels: dense matrix multiply, sparse matrix vector multiply, stencil computations, and 1D/2D FFTs. The difficulty of programming Cell, which requires assembly level intrinsics for the best performance, makes this model useful as an initial step in algorithm design and evaluation. Next, we validate the accuracy of our model by comparing results against published hardware results, as well as our own implementations on a 3.2GHz Cell blade. Additionally, we compare Cell performance to benchmarks run on leading superscalar (AMD Opteron), VLIW (Intel Itanium2), and vector (Cray X1E) architectures. Our work also explores several different mappings of the kernels and demonstrates a simple and effective programming model for Cell's unique architecture. Finally, we propose modest microarchitectural modifications that could significantly increase the efficiency of double-precision calculations. Overall results demonstrate the tremendous potential of the Cell architecture for scientific computations in terms of both raw performance and power efficiency.

  14. Scheduler Activations on BSD: Sharing Thread Management Between Kernel and Application

    OpenAIRE

    Small, Christopher A.; Seltzer, Margo I.

    1995-01-01

    There are two commonly used thread models: kernel level threads and user level threads. Kernel level threads suffer from the cost of frequent user-kernel domain crossings and fixed kernel scheduling priorities. User level threads are not integrated with the kernel, blocking all threads whenever one thread is blocked. The Scheduler Activations model, proposed by Anderson et al. [ANDE91], combines kernel CPU al location decisions with application control over thread scheduling. This paper discu...

  15. A multi-scale kernel bundle for LDDMM

    DEFF Research Database (Denmark)

    Sommer, Stefan Horst; Nielsen, Mads; Lauze, Francois Bernard

    2011-01-01

    The Large Deformation Diffeomorphic Metric Mapping framework constitutes a widely used and mathematically well-founded setup for registration in medical imaging. At its heart lies the notion of the regularization kernel, and the choice of kernel greatly affects the results of registrations...

  16. THE COLLOCATION METHODS FOR SINGULAR INTEGRAL EQUATIONS WITH CAUCHY KERNELS

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    This paper applies the singular integral operators,singular quadrature operators and discretization matrices associated withsingular integral equations with Cauchy kernels, which are established in [1],to give a unified framework for various collocation methods of numericalsolutions of singular integral equations with Cauchy kernels. Under theframework, the coincidence of the direct quadrature method and the indirectquadrature method is very simple and obvious.

  17. Extracting Feature Model Changes from the Linux Kernel Using FMDiff

    NARCIS (Netherlands)

    Dintzner, N.J.R.; Van Deursen, A.; Pinzger, M.

    2014-01-01

    The Linux kernel feature model has been studied as an example of large scale evolving feature model and yet details of its evolution are not known. We present here a classification of feature changes occurring on the Linux kernel feature model, as well as a tool, FMDiff, designed to automatically ex

  18. KERNEL IDEALS AND CONGRUENCES ON MS-ALGEBRAS

    Institute of Scientific and Technical Information of China (English)

    Luo Congwen; Zeng Yanlu

    2006-01-01

    In this article, the authors describe the largest congruence induced by a kernel ideal of an MS-algebra and characterize those MS-algebras on which all the congruences are in a one-to-one correspondence with the kernel ideals.

  19. Integral Transform Methods: A Critical Review of Various Kernels

    Science.gov (United States)

    Orlandini, Giuseppina; Turro, Francesco

    2017-03-01

    Some general remarks about integral transform approaches to response functions are made. Their advantage for calculating cross sections at energies in the continuum is stressed. In particular we discuss the class of kernels that allow calculations of the transform by matrix diagonalization. A particular set of such kernels, namely the wavelets, is tested in a model study.

  20. Resolvent kernel for the Kohn Laplacian on Heisenberg groups

    Directory of Open Access Journals (Sweden)

    Neur Eddine Askour

    2002-07-01

    Full Text Available We present a formula that relates the Kohn Laplacian on Heisenberg groups and the magnetic Laplacian. Then we obtain the resolvent kernel for the Kohn Laplacian and find its spectral density. We conclude by obtaining the Green kernel for fractional powers of the Kohn Laplacian.

  1. Integrating the Gradient of the Thin Wire Kernel

    Science.gov (United States)

    Champagne, Nathan J.; Wilton, Donald R.

    2008-01-01

    A formulation for integrating the gradient of the thin wire kernel is presented. This approach employs a new expression for the gradient of the thin wire kernel derived from a recent technique for numerically evaluating the exact thin wire kernel. This approach should provide essentially arbitrary accuracy and may be used with higher-order elements and basis functions using the procedure described in [4].When the source and observation points are close, the potential integrals over wire segments involving the wire kernel are split into parts to handle the singular behavior of the integrand [1]. The singularity characteristics of the gradient of the wire kernel are different than those of the wire kernel, and the axial and radial components have different singularities. The characteristics of the gradient of the wire kernel are discussed in [2]. To evaluate the near electric and magnetic fields of a wire, the integration of the gradient of the wire kernel needs to be calculated over the source wire. Since the vector bases for current have constant direction on linear wire segments, these integrals reduce to integrals of the form

  2. ON APPROXIMATION BY SPHERICAL REPRODUCING KERNEL HILBERT SPACES

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    The spherical approximation between two nested reproducing kernels Hilbert spaces generated from different smooth kernels is investigated. It is shown that the functions of a space can be approximated by that of the subspace with better smoothness. Furthermore, the upper bound of approximation error is given.

  3. End-use quality of soft kernel durum wheat

    Science.gov (United States)

    Kernel texture is a major determinant of end-use quality of wheat. Durum wheat is known for its very hard texture, which influences how it is milled and for what products it is well suited. We developed soft kernel durum wheat lines via Ph1b-mediated homoeologous recombination with Dr. Leonard Joppa...

  4. Optimal Bandwidth Selection in Observed-Score Kernel Equating

    Science.gov (United States)

    Häggström, Jenny; Wiberg, Marie

    2014-01-01

    The selection of bandwidth in kernel equating is important because it has a direct impact on the equated test scores. The aim of this article is to examine the use of double smoothing when selecting bandwidths in kernel equating and to compare double smoothing with the commonly used penalty method. This comparison was made using both an equivalent…

  5. Comparison of Kernel Equating and Item Response Theory Equating Methods

    Science.gov (United States)

    Meng, Yu

    2012-01-01

    The kernel method of test equating is a unified approach to test equating with some advantages over traditional equating methods. Therefore, it is important to evaluate in a comprehensive way the usefulness and appropriateness of the Kernel equating (KE) method, as well as its advantages and disadvantages compared with several popular item…

  6. Integral transform methods: a critical review of various kernels

    CERN Document Server

    Orlandini, Giuseppina

    2016-01-01

    Some general remarks about integral transform approaches to response functions are made. Their advantage for calculating cross sections at energies in the continuum is stressed. In particular we discuss the class of kernels that allow calculations of the transform by matrix diagonalization. A particular set of such kernels, namely the wavelets, is tested in a model study.

  7. Indigenous Methods in Preserving Bush Mango Kernels in Cameroon

    Directory of Open Access Journals (Sweden)

    Zac Tchoundjeu

    2005-01-01

    Full Text Available Traditional practices for preserving Irvingia wombolu and Irvingia gabonensis (bush mango kernels were assessed in a survey covering twelve villages (Dongo, Bouno, Gribi [East], Elig-Nkouma, Nkom I, Ngoumou [Centre], Bidjap, Nko’ovos, Ondodo [South], Besong-Abang, Ossing and Kembong [Southwest], in the humid lowland forest zone of Cameroon. All the interviewed households that own trees of species were found to preserve kernels in periods of abundance, excluding Elig-Nkouma (87.5%. Eighty nine and 85% did so in periods of scarcity for I. wombolu and I. gabonensis respectively. Seventeen and twenty-nine kernel preservation practices were recorded for I. wombolu and I. gabonensis respectively. Most were based on continuous heating of the kernels or kernel by-products (cakes. The most commonly involved keeping the sun-dried kernels in a plastic bag on a bamboo rack hung above the fireplace in the kitchen. A 78% of interviews households reported preserving I. wombolu kernels for less than one year while 22% preserved it for more than one year with 1.9% for two years, the normal length of the off-season period for trees in the wild. Cakes wrapped with leaves and kept on a bamboo rack hung over the fireplace were reported by households in the East and South provinces to store Irvingia gabonensis longer (more than one year. Further studies on the utilization of heat for preserving and canning bush mango kernels are recommended.

  8. THE HEAT KERNEL ON THE CAYLEY HEISENBERG GROUP

    Institute of Scientific and Technical Information of China (English)

    Luan Jingwen; Zhu Fuliu

    2005-01-01

    The authors obtain an explicit expression of the heat kernel for the Cayley Heisenberg group of order n by using the stochastic integral method of Gaveau. Apart from the standard Heisenberg group and the quaternionic Heisenberg group, this is the only nilpotent Lie group on which an explicit formula for the heat kernel has been obtained.

  9. Open Problem: Kernel methods on manifolds and metric spaces

    DEFF Research Database (Denmark)

    Feragen, Aasa; Hauberg, Søren

    2016-01-01

    Radial kernels are well-suited for machine learning over general geodesic metric spaces, where pairwise distances are often the only computable quantity available. We have recently shown that geodesic exponential kernels are only positive definite for all bandwidths when the input space has strong...

  10. Efficient Kernel-based 2DPCA for Smile Stages Recognition

    Directory of Open Access Journals (Sweden)

    Fitri Damayanti

    2012-03-01

    Full Text Available Recently, an approach called two-dimensional principal component analysis (2DPCA has been proposed for smile stages representation and recognition. The essence of 2DPCA is that it computes the eigenvectors of the so-called image covariance matrix without matrix-to-vector conversion so the size of the image covariance matrix are much smaller, easier to evaluate covariance matrix, computation cost is reduced and the performance is also improved than traditional PCA. In an effort to improve and perfect the performance of smile stages recognition, in this paper, we propose efficient Kernel based 2DPCA concepts. The Kernelization of 2DPCA can be benefit to develop the nonlinear structures in the input data. This paper discusses comparison of standard Kernel based 2DPCA and efficient Kernel based 2DPCA for smile stages recognition. The results of experiments show that Kernel based 2DPCA achieve better performance in comparison with the other approaches. While the use of efficient Kernel based 2DPCA can speed up the training procedure of standard Kernel based 2DPCA thus the algorithm can achieve much more computational efficiency and remarkably save the memory consuming compared to the standard Kernel based 2DPCA.

  11. Kernel maximum autocorrelation factor and minimum noise fraction transformations

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg

    2010-01-01

    ) dimensional feature space via the kernel function and then performing a linear analysis in that space. Three examples show the very successful application of kernel MAF/MNF analysis to 1) change detection in DLR 3K camera data recorded 0.7 seconds apart over a busy motorway, 2) change detection...

  12. Lp-boundedness of flag kernels on homogeneous groups

    CERN Document Server

    Glowacki, Pawel

    2010-01-01

    We prove that the flag kernel singular integral operators of Nagel-Ricci-Stein on a homogeneous group are bounded on the Lp spaces. The gradation associated with the kernels is the natural gradation of the underlying Lie algebra. Our main tools are the Littlewood-Paley theory and a symbolic calculus combined in the spirit of Duoandikoetxea and Rubio de Francia.

  13. Extracting Feature Model Changes from the Linux Kernel Using FMDiff

    NARCIS (Netherlands)

    Dintzner, N.J.R.; Van Deursen, A.; Pinzger, M.

    2014-01-01

    The Linux kernel feature model has been studied as an example of large scale evolving feature model and yet details of its evolution are not known. We present here a classification of feature changes occurring on the Linux kernel feature model, as well as a tool, FMDiff, designed to automatically

  14. Gaussian kernel operators on white noise functional spaces

    Institute of Scientific and Technical Information of China (English)

    骆顺龙; 严加安

    2000-01-01

    The Gaussian kernel operators on white noise functional spaces, including second quantization, Fourier-Mehler transform, scaling, renormalization, etc. are studied by means of symbol calculus, and characterized by the intertwining relations with annihilation and creation operators. The infinitesimal generators of the Gaussian kernel operators are second order white noise operators of which the number operator and the Gross Laplacian are particular examples.

  15. Evolutionary optimization of kernel weights improves protein complex comembership prediction.

    Science.gov (United States)

    Hulsman, Marc; Reinders, Marcel J T; de Ridder, Dick

    2009-01-01

    In recent years, more and more high-throughput data sources useful for protein complex prediction have become available (e.g., gene sequence, mRNA expression, and interactions). The integration of these different data sources can be challenging. Recently, it has been recognized that kernel-based classifiers are well suited for this task. However, the different kernels (data sources) are often combined using equal weights. Although several methods have been developed to optimize kernel weights, no large-scale example of an improvement in classifier performance has been shown yet. In this work, we employ an evolutionary algorithm to determine weights for a larger set of kernels by optimizing a criterion based on the area under the ROC curve. We show that setting the right kernel weights can indeed improve performance. We compare this to the existing kernel weight optimization methods (i.e., (regularized) optimization of the SVM criterion or aligning the kernel with an ideal kernel) and find that these do not result in a significant performance improvement and can even cause a decrease in performance. Results also show that an expert approach of assigning high weights to features with high individual performance is not necessarily the best strategy.

  16. Visualization of nonlinear kernel models in neuroimaging by sensitivity maps

    DEFF Research Database (Denmark)

    Rasmussen, Peter Mondrup; Madsen, Kristoffer Hougaard; Lund, Torben Ellegaard

    2011-01-01

    There is significant current interest in decoding mental states from neuroimages. In this context kernel methods, e.g., support vector machines (SVM) are frequently adopted to learn statistical relations between patterns of brain activation and experimental conditions. In this paper we focus......, and conclude that the sensitivity map is a versatile and computationally efficient tool for visualization of nonlinear kernel models in neuroimaging....

  17. Digestibility of the cottonseed meal with or without addition of protease and phytase enzymes in swine diet - doi: 10.4025/actascianimsci.v34i3.12360

    Directory of Open Access Journals (Sweden)

    Maria do Carmo Mouhaupt Marques Ludke

    2012-05-01

    Full Text Available This study evaluated the digestibility of cottonseed meal with or without addition of enzymes (phytase and protease for growing pigs. It was used 18 barrows, housed in metabolism cages, distributed in a completely randomized design, standardizing body weight (bw with average of 25.8 ± 3.6 kg, with three treatments and six repetitions. The treatments consisted of a reference diet based on corn and soybean meal, the second treatment with replacement of 30% of the reference diet by cottonseed meal without enzymes, and the third with 30% of the reference diet replaced by cottonseed meal with added enzymes. Was determined the digestible protein, digestible energy, digestibility of dry matter, energy and protein. It was also registered the balance of nitrogen and phosphorus. The use of cottonseed meal with the addition of enzymes in diets for growing pigs has no effect on the digestibility of dry matter, gross energy and crude protein, but improved the absorption of phosphorus, consequently reducing its excretion in the feces. There was no improvement in nitrogen balance in the diets containing cottonseed meal with enzymes.

  18. Grounded theory.

    Science.gov (United States)

    Harris, Tina

    2015-04-29

    Grounded theory is a popular research approach in health care and the social sciences. This article provides a description of grounded theory methodology and its key components, using examples from published studies to demonstrate practical application. It aims to demystify grounded theory for novice nurse researchers, by explaining what it is, when to use it, why they would want to use it and how to use it. It should enable nurse researchers to decide if grounded theory is an appropriate approach for their research, and to determine the quality of any grounded theory research they read.

  19. Higher Order Kernels and Locally Affine LDDMM Registration

    CERN Document Server

    Sommer, Stefan; Darkner, Sune; Pennec, Xavier

    2011-01-01

    To achieve sparse description that allows intuitive analysis, we aim to represent deformation with a basis containing interpretable elements, and we wish to use elements that have the description capacity to represent the deformation compactly. We accomplish this by introducing higher order kernels in the LDDMM registration framework. The kernels allow local description of affine transformations and subsequent compact description of non-translational movement and of the entire non-rigid deformation. This is obtained with a representation that contains directly interpretable information from both mathematical and modeling perspectives. We develop the mathematical construction behind the higher order kernels, we show the implications for sparse image registration and deformation description, and we provide examples of how the capacity of the kernels enables registration with a very low number of parameters. The capacity and interpretability of the kernels lead to natural modeling of articulated movement, and th...

  20. Hypothesis testing using pairwise distances and associated kernels

    CERN Document Server

    Sejdinovic, Dino; Sriperumbudur, Bharath; Fukumizu, Kenji

    2012-01-01

    We provide a unifying framework linking two classes of statistics used in two-sample and independence testing: on the one hand, the energy distances and distance covariances from the statistics literature; on the other, distances between embeddings of distributions to reproducing kernel Hilbert spaces (RKHS), as established in machine learning. The equivalence holds when energy distances are computed with semimetrics of negative type, in which case a kernel may be defined such that the RKHS distance between distributions corresponds exactly to the energy distance. We determine the class of probability distributions for which kernels induced by semimetrics are characteristic (that is, for which embeddings of the distributions to an RKHS are injective). Finally, we investigate the performance of this family of kernels in two-sample and independence tests: we show in particular that the energy distance most commonly employed in statistics is just one member of a parametric family of kernels, and that other choic...

  1. An iterative modified kernel based on training data

    Institute of Scientific and Technical Information of China (English)

    Zhi-xiang ZHOU; Feng-qing HAN

    2009-01-01

    To improve performance of a support vector regression, a new method for a modified kernel function is proposed. In this method, information of all samples is included in the kernel function with conformal mapping. Thus the kernel function is data-dependent. With a random initial parameter, the kernel function is modified re-peatedly until a satisfactory result is achieved. Compared with the conventional model, the improved approach does not need to select parameters of the kernel function. Sim-ulation is carried out for the one-dimension continuous function and a case of strong earthquakes. The results show that the improved approach has better learning ability and forecasting precision than the traditional model. With the increase of the iteration number, the figure of merit decreases and converges. The speed of convergence depends on the parameters used in the algorithm.

  2. Nonlinear Statistical Process Monitoring and Fault Detection Using Kernel ICA

    Institute of Scientific and Technical Information of China (English)

    ZHANG Xi; YAN Wei-wu; ZHAO Xu; SHAO Hui-he

    2007-01-01

    A novel nonlinear process monitoring and fault detection method based on kernel independent component analysis (ICA) is proposed. The kernel ICA method is a two-phase algorithm: whitened kernel principal component (KPCA) plus ICA. KPCA spheres data and makes the data structure become as linearly separable as possible by virtue of an implicit nonlinear mapping determined by kernel. ICA seeks the projection directions in the KPCA whitened space, making the distribution of the projected data as non-gaussian as possible. The application to the fluid catalytic cracking unit (FCCU) simulated process indicates that the proposed process monitoring method based on kernel ICA can effectively capture the nonlinear relationship in process variables. Its performance significantly outperforms monitoring method based on ICA or KPCA.

  3. Anatomically-aided PET reconstruction using the kernel method

    Science.gov (United States)

    Hutchcroft, Will; Wang, Guobao; Chen, Kevin T.; Catana, Ciprian; Qi, Jinyi

    2016-09-01

    This paper extends the kernel method that was proposed previously for dynamic PET reconstruction, to incorporate anatomical side information into the PET reconstruction model. In contrast to existing methods that incorporate anatomical information using a penalized likelihood framework, the proposed method incorporates this information in the simpler maximum likelihood (ML) formulation and is amenable to ordered subsets. The new method also does not require any segmentation of the anatomical image to obtain edge information. We compare the kernel method with the Bowsher method for anatomically-aided PET image reconstruction through a simulated data set. Computer simulations demonstrate that the kernel method offers advantages over the Bowsher method in region of interest quantification. Additionally the kernel method is applied to a 3D patient data set. The kernel method results in reduced noise at a matched contrast level compared with the conventional ML expectation maximization algorithm.

  4. OSKI: A Library of Automatically Tuned Sparse Matrix Kernels

    Energy Technology Data Exchange (ETDEWEB)

    Vuduc, R; Demmel, J W; Yelick, K A

    2005-07-19

    The Optimized Sparse Kernel Interface (OSKI) is a collection of low-level primitives that provide automatically tuned computational kernels on sparse matrices, for use by solver libraries and applications. These kernels include sparse matrix-vector multiply and sparse triangular solve, among others. The primary aim of this interface is to hide the complex decision-making process needed to tune the performance of a kernel implementation for a particular user's sparse matrix and machine, while also exposing the steps and potentially non-trivial costs of tuning at run-time. This paper provides an overview of OSKI, which is based on our research on automatically tuned sparse kernels for modern cache-based superscalar machines.

  5. OSKI: A library of automatically tuned sparse matrix kernels

    Science.gov (United States)

    Vuduc, Richard; Demmel, James W.; Yelick, Katherine A.

    2005-01-01

    The Optimized Sparse Kernel Interface (OSKI) is a collection of low-level primitives that provide automatically tuned computational kernels on sparse matrices, for use by solver libraries and applications. These kernels include sparse matrix-vector multiply and sparse triangular solve, among others. The primary aim of this interface is to hide the complex decisionmaking process needed to tune the performance of a kernel implementation for a particular user's sparse matrix and machine, while also exposing the steps and potentially non-trivial costs of tuning at run-time. This paper provides an overview of OSKI, which is based on our research on automatically tuned sparse kernels for modern cache-based superscalar machines.

  6. CRKSPH - A Conservative Reproducing Kernel Smoothed Particle Hydrodynamics Scheme

    CERN Document Server

    Frontiere, Nicholas; Owen, J Michael

    2016-01-01

    We present a formulation of smoothed particle hydrodynamics (SPH) that employs a first-order consistent reproducing kernel function, exactly interpolating linear fields with particle tracers. Previous formulations using reproducing kernel (RK) interpolation have had difficulties maintaining conservation of momentum due to the fact the RK kernels are not, in general, spatially symmetric. Here, we utilize a reformulation of the fluid equations such that mass, momentum, and energy are all manifestly conserved without any assumption about kernel symmetries. Additionally, by exploiting the increased accuracy of the RK method's gradient, we formulate a simple limiter for the artificial viscosity that reduces the excess diffusion normally incurred by the ordinary SPH artificial viscosity. Collectively, we call our suite of modifications to the traditional SPH scheme Conservative Reproducing Kernel SPH, or CRKSPH. CRKSPH retains the benefits of traditional SPH methods (such as preserving Galilean invariance and manif...

  7. A novel extended kernel recursive least squares algorithm.

    Science.gov (United States)

    Zhu, Pingping; Chen, Badong; Príncipe, José C

    2012-08-01

    In this paper, a novel extended kernel recursive least squares algorithm is proposed combining the kernel recursive least squares algorithm and the Kalman filter or its extensions to estimate or predict signals. Unlike the extended kernel recursive least squares (Ex-KRLS) algorithm proposed by Liu, the state model of our algorithm is still constructed in the original state space and the hidden state is estimated using the Kalman filter. The measurement model used in hidden state estimation is learned by the kernel recursive least squares algorithm (KRLS) in reproducing kernel Hilbert space (RKHS). The novel algorithm has more flexible state and noise models. We apply this algorithm to vehicle tracking and the nonlinear Rayleigh fading channel tracking, and compare the tracking performances with other existing algorithms.

  8. Virtual screening with support vector machines and structure kernels

    CERN Document Server

    Mahé, Pierre

    2007-01-01

    Support vector machines and kernel methods have recently gained considerable attention in chemoinformatics. They offer generally good performance for problems of supervised classification or regression, and provide a flexible and computationally efficient framework to include relevant information and prior knowledge about the data and problems to be handled. In particular, with kernel methods molecules do not need to be represented and stored explicitly as vectors or fingerprints, but only to be compared to each other through a comparison function technically called a kernel. While classical kernels can be used to compare vector or fingerprint representations of molecules, completely new kernels were developed in the recent years to directly compare the 2D or 3D structures of molecules, without the need for an explicit vectorization step through the extraction of molecular descriptors. While still in their infancy, these approaches have already demonstrated their relevance on several toxicity prediction and s...

  9. 3-D waveform tomography sensitivity kernels for anisotropic media

    KAUST Repository

    Djebbi, R.

    2014-01-01

    The complications in anisotropic multi-parameter inversion lie in the trade-off between the different anisotropy parameters. We compute the tomographic waveform sensitivity kernels for a VTI acoustic medium perturbation as a tool to investigate this ambiguity between the different parameters. We use dynamic ray tracing to efficiently handle the expensive computational cost for 3-D anisotropic models. Ray tracing provides also the ray direction information necessary for conditioning the sensitivity kernels to handle anisotropy. The NMO velocity and η parameter kernels showed a maximum sensitivity for diving waves which results in a relevant choice of those parameters in wave equation tomography. The δ parameter kernel showed zero sensitivity; therefore it can serve as a secondary parameter to fit the amplitude in the acoustic anisotropic inversion. Considering the limited penetration depth of diving waves, migration velocity analysis based kernels are introduced to fix the depth ambiguity with reflections and compute sensitivity maps in the deeper parts of the model.

  10. Genomic Prediction of Genotype × Environment Interaction Kernel Regression Models.

    Science.gov (United States)

    Cuevas, Jaime; Crossa, José; Soberanis, Víctor; Pérez-Elizalde, Sergio; Pérez-Rodríguez, Paulino; Campos, Gustavo de Los; Montesinos-López, O A; Burgueño, Juan

    2016-11-01

    In genomic selection (GS), genotype × environment interaction (G × E) can be modeled by a marker × environment interaction (M × E). The G × E may be modeled through a linear kernel or a nonlinear (Gaussian) kernel. In this study, we propose using two nonlinear Gaussian kernels: the reproducing kernel Hilbert space with kernel averaging (RKHS KA) and the Gaussian kernel with the bandwidth estimated through an empirical Bayesian method (RKHS EB). We performed single-environment analyses and extended to account for G × E interaction (GBLUP-G × E, RKHS KA-G × E and RKHS EB-G × E) in wheat ( L.) and maize ( L.) data sets. For single-environment analyses of wheat and maize data sets, RKHS EB and RKHS KA had higher prediction accuracy than GBLUP for all environments. For the wheat data, the RKHS KA-G × E and RKHS EB-G × E models did show up to 60 to 68% superiority over the corresponding single environment for pairs of environments with positive correlations. For the wheat data set, the models with Gaussian kernels had accuracies up to 17% higher than that of GBLUP-G × E. For the maize data set, the prediction accuracy of RKHS EB-G × E and RKHS KA-G × E was, on average, 5 to 6% higher than that of GBLUP-G × E. The superiority of the Gaussian kernel models over the linear kernel is due to more flexible kernels that accounts for small, more complex marker main effects and marker-specific interaction effects.

  11. Fuel properties and precipitate formation at low temperature in soy-, cottonseed-, and poultry fat-based biodiesel blends

    Energy Technology Data Exchange (ETDEWEB)

    Haiying Tang; Steven O. Salley; K.Y. Simon Ng [Wayne State University, Detroit, MI (United States). Department of Chemical Engineering and Materials Science

    2008-10-15

    The formation of precipitates in biodiesel blends may have serious implications for diesel engine fuel delivery systems. Precipitates were observed in Soybean oil (SBO-), cottonseed oil (CSO-), and poultry fat (PF-) based biodiesel blends after storage at 4{sup o}C. CSO- and PF-based biodiesel had a lower mass of precipitates observed than the SBO-based. Moreover, different rates of precipitate formation were observed for the B20 versus the B100. These suggested that the formation of precipitate during cold temperature storage was dependent on the feedstock and blend concentration. The solvency effects of biodiesel blends were more pronounced at low temperature than at room temperature leading to a higher amount of precipitates formed. Fourier transform infrared (FTIR) spectra, and gas chromatography-flame ionization detector (GC-FID) chromatograms indicated that steryl glucosides are the major cause of precipitate formation in SBO-based biodiesel; while for PF-based biodiesel, the precipitates are due to mono-glycerides. However, the precipitates from CSO-based biodiesel are due to both steryl glucosides and mono-glycerides. 45 refs., 11 figs., 2 tabs.

  12. Continuous production of biodiesel from cottonseed oil and methanol using a column reactor packed with calcined sodium silicate base catalyst☆

    Institute of Scientific and Technical Information of China (English)

    Xia Gui; Sichen Chen; Zhi Yun

    2016-01-01

    Sodium silicate and that calcined at 400 °C for 2 h were used to catalyze the transesterification of cottonseed oil with methanol. Calcined sodium silicate (CSS) catalyst exhibited much higher catalytic activity and stability. A maximum biodiesel yield of 98.9%was achieved at methanol/oil mole ratio of 12:1, reaction temperature 65 °C, reaction time 3.0 h, and CSS/oil mass ratio of 2 wt%. After 7 consecutive reactions without any treatment, biodiesel yield reduced to 82.5%. Considering technological and economic feasibility, CSS base catalyst supported onθrings was prepared for continuous transesterification. The maximum yield was 99.1%under optimum conditions (reaction temperature 55 °C, methanol velocity 1 ml·min−1, oil velocity 3 ml·min−1, and 5 tower sec-tions). These results indicate that this new continuous biodiesel production process and apparatus present a great potential for industrial application in biodiesel.

  13. The response of meat ducks from 15 to 35 d of age to gossypol from cottonseed meal.

    Science.gov (United States)

    Zeng, Q F; Bai, P; Wang, J P; Ding, X M; Luo, Y H; Bai, S P; Xuan, Y; Su, Z W; Lin, S Q; Zhao, L J; Zhang, K Y

    2015-06-01

    The objective of this study was to investigate the responses of meat ducks of 15 to 35 d of age to free gossypol (FG) from cottonseed meal (CSM) and to establish the maximum limits of dietary FG concentration based on growth performance, blood parameters, and tissue residues of gossypol. Nine hundred 15-d-old ducks were randomly allocated to 5 treatments with 10 cages/treatment and 18 ducks/cage on the basis of BW. Five isonitrogenous and isocaloric experimental diets were formulated on a digestible amino acid basis to produce diets in which 0% (without FG), 25% (36 mg FG/kg), 50% (75 mg FG/kg), 75% (111 mg FG/kg), and 100% (153 mg FG/kg) of protein from soybean meal were replaced by that from CSM. Increasing dietary FG content, BW, and ADG decreased (linearly, PDucks fed 36 mg FG/kg (5.83% CSM of diet) diet had a normal histological structure of liver, and muscle (breast and leg) had no residue of gossypol. The maximum limit of dietary FG concentration was estimated to range from a low of 36 mg/kg to maximize serum globulin concentration to a high of 124 mg/kg to minimize feed intake for 22 to 28 d on the basis of a quadratic broken-line model.

  14. Biodiesel synthesis from cottonseed oil using homogeneous alkali catalyst and using heterogeneous multi walled carbon nanotubes: Characterization and blending studies

    Directory of Open Access Journals (Sweden)

    A. Arun Shankar

    2017-03-01

    Full Text Available The trans-esterification of cottonseed oil using strong alkali catalyst and using multi walled carbon nano tubes as catalyst to produce biodiesel was studied. The interaction effects of various factors such as temperature, amount of alkali used, alcohol to oil ratio and reaction time on yield of biodiesel were studied. The maximum yield of 95% biodiesel was obtained. The biodiesel produced was characterized using FT-IR spectral analysis and GC–MS analysis to ascertain the various functional groups and compounds available in it. The properties of biodiesel using homogeneous alkali catalyst and heterogeneous multi walled carbon nanotubes such as calorific value (36.18 MJ/kg, 33.78 MJ/kg, flash point (160 °C, 156 °C and other properties such as viscosity, cloud point, pour point and density were found to determine the quality of biodiesel produced. The studies were done by blending the biodiesel produced with diesel and properties of blended samples were estimated to ascertain the use of blended samples in internal combustion engines.

  15. Heat kernel method and its applications

    CERN Document Server

    Avramidi, Ivan G

    2015-01-01

    The heart of the book is the development of a short-time asymptotic expansion for the heat kernel. This is explained in detail and explicit examples of some advanced calculations are given. In addition some advanced methods and extensions, including path integrals, jump diffusion and others are presented. The book consists of four parts: Analysis, Geometry, Perturbations and Applications. The first part shortly reviews of some background material and gives an introduction to PDEs. The second part is devoted to a short introduction to various aspects of differential geometry that will be needed later. The third part and heart of the book presents a systematic development of effective methods for various approximation schemes for parabolic differential equations. The last part is devoted to applications in financial mathematics, in particular, stochastic differential equations. Although this book is intended for advanced undergraduate or beginning graduate students in, it should also provide a useful reference ...

  16. Image Processing Variations with Analytic Kernels

    CERN Document Server

    Garnett, John B; Vese, Luminita A

    2012-01-01

    Let $f\\in L^1(\\R^d)$ be real. The Rudin-Osher-Fatemi model is to minimize $\\|u\\|_{\\dot{BV}}+\\lambda\\|f-u\\|_{L^2}^2$, in which one thinks of $f$ as a given image, $\\lambda > 0$ as a "tuning parameter", $u$ as an optimal "cartoon" approximation to $f$, and $f-u$ as "noise" or "texture". Here we study variations of the R-O-F model having the form $\\inf_u\\{\\|u\\|_{\\dot{BV}}+\\lambda \\|K*(f-u)\\|_{L^p}^q\\}$ where $K$ is a real analytic kernel such as a Gaussian. For these functionals we characterize the minimizers $u$ and establish several of their properties, including especially their smoothness properties. In particular we prove that on any open set on which $u \\in W^{1,1}$ and $\

  17. The Dynamical Kernel Scheduler - Part 1

    CERN Document Server

    Adelmann, Andreas; Suter, Andreas

    2015-01-01

    Emerging processor architectures such as GPUs and Intel MICs provide a huge performance potential for high performance computing. However developing software using these hardware accelerators introduces additional challenges for the developer such as exposing additional parallelism, dealing with different hardware designs and using multiple development frameworks in order to use devices from different vendors. The Dynamic Kernel Scheduler (DKS) is being developed in order to provide a software layer between host application and different hardware accelerators. DKS handles the communication between the host and device, schedules task execution, and provides a library of built-in algorithms. Algorithms available in the DKS library will be written in CUDA, OpenCL and OpenMP. Depending on the available hardware, the DKS can select the appropriate implementation of the algorithm. The first DKS version was created using CUDA for the Nvidia GPUs and OpenMP for Intel MIC. DKS was further integrated in OPAL (Object-or...

  18. Online Learning of Noisy Data with Kernels

    CERN Document Server

    Cesa-Bianchi, Nicolò; Shamir, Ohad

    2010-01-01

    We study online learning when individual instances are corrupted by random noise. We assume the noise distribution is unknown, and may change over time with no restriction other than having zero mean and bounded variance. Our technique relies on a family of unbiased estimators for non-linear functions, which may be of independent interest. We show that a variant of online gradient descent can learn functions in any dot-product (e.g., polynomial) or Gaussian kernel space with any analytic convex loss function. Our variant uses randomized estimates that need to query a random number of noisy copies of each instance, where with high probability this number is upper bounded by a constant. Allowing such multiple queries cannot be avoided: Indeed, we show that online learning is in general impossible when only one noisy copy of each instance can be accessed.

  19. Index-free Heat Kernel Coefficients

    CERN Document Server

    De van Ven, A E M

    1998-01-01

    Using index-free notation, we present the diagonal values of the first five heat kernel coefficients associated with a general Laplace-type operator on a compact Riemannian space without boundary. The fifth coefficient appears here for the first time. For a flat space with a gauge connection, the sixth coefficient is given too. Also provided are the leading terms for any coefficient, both in ascending and descending powers of the Yang-Mills and Riemann curvatures, to the same order as required for the fourth coefficient. These results are obtained by directly solving the relevant recursion relations, working in Fock-Schwinger gauge and Riemann normal coordinates. Our procedure is thus noncovariant, but we show that for any coefficient the `gauged' respectively `curved' version is found from the corresponding `non-gauged' respectively `flat' coefficient by making some simple covariant substitutions. These substitutions being understood, the coefficients retain their `flat' form and size. In this sense the fift...

  20. Kernel density estimation using graphical processing unit

    Science.gov (United States)

    Sunarko, Su'ud, Zaki

    2015-09-01

    Kernel density estimation for particles distributed over a 2-dimensional space is calculated using a single graphical processing unit (GTX 660Ti GPU) and CUDA-C language. Parallel calculations are done for particles having bivariate normal distribution and by assigning calculations for equally-spaced node points to each scalar processor in the GPU. The number of particles, blocks and threads are varied to identify favorable configuration. Comparisons are obtained by performing the same calculation using 1, 2 and 4 processors on a 3.0 GHz CPU using MPICH 2.0 routines. Speedups attained with the GPU are in the range of 88 to 349 times compared the multiprocessor CPU. Blocks of 128 threads are found to be the optimum configuration for this case.

  1. Learning RoboCup-Keepaway with Kernels

    CERN Document Server

    Jung, Tobias

    2012-01-01

    We apply kernel-based methods to solve the difficult reinforcement learning problem of 3vs2 keepaway in RoboCup simulated soccer. Key challenges in keepaway are the high-dimensionality of the state space (rendering conventional discretization-based function approximation like tilecoding infeasible), the stochasticity due to noise and multiple learning agents needing to cooperate (meaning that the exact dynamics of the environment are unknown) and real-time learning (meaning that an efficient online implementation is required). We employ the general framework of approximate policy iteration with least-squares-based policy evaluation. As underlying function approximator we consider the family of regularization networks with subset of regressors approximation. The core of our proposed solution is an efficient recursive implementation with automatic supervised selection of relevant basis functions. Simulation results indicate that the behavior learned through our approach clearly outperforms the best results obta...

  2. Heat kernel measures on random surfaces

    CERN Document Server

    Klevtsov, Semyon

    2015-01-01

    The heat kernel on the symmetric space of positive definite Hermitian matrices is used to endow the spaces of Bergman metrics of degree k on a Riemann surface M with a family of probability measures depending on a choice of the background metric. Under a certain matrix-metric correspondence, each positive definite Hermitian matrix corresponds to a Kahler metric on M. The one and two point functions of the random metric are calculated in a variety of limits as k and t tend to infinity. In the limit when the time t goes to infinity the fluctuations of the random metric around the background metric are the same as the fluctuations of random zeros of holomorphic sections. This is due to the fact that the random zeros form the boundary of the space of Bergman metrics.

  3. Pattern Programmable Kernel Filter for Bot Detection

    Directory of Open Access Journals (Sweden)

    Kritika Govind

    2012-05-01

    Full Text Available Bots earn their unique name as they perform a wide variety of automated task. These tasks include stealing sensitive\tuser\tinformation. Detection of bots using solutions such as behavioral\tcorrelation of\tflow\trecords,\tgroup activity\tin DNS traffic, observing\tthe periodic repeatability in\tcommunication, etc., lead to monitoring\tthe network traffic\tand\tthen\tclassifying them as Bot or normal traffic.\tOther solutions for\tBot detection\tinclude kernel level key stroke verification, system call initialization,\tIP black listing, etc. In the first\ttwo solutions\tthere is no assurance\tthat\tthe\tpacket carrying user information is prevented from being sent to the attacker and the latter suffers from the problem of\tIP spoofing. This motivated\tus to think\tof a solution that would\tfilter\tout\tthe malicious\tpackets\tbefore being\tput onto\tthe network. To come out with such a\tsolution,\ta real time\tbot\tattack\twas\tgenerated with SpyEye Exploit kit and traffic\tcharacteristics were analyzed. The analysis revealed the existence\tof a unique repeated communication\tbetween\tthe Zombie machine\tand\tthe botmaster. This motivated us to propose, a Pattern\tProgrammable Kernel\tFilter (PPKF\tfor filtering out the malicious\tpackets generated by bots.\tPPKF was developed\tusing the\twindows\tfiltering platform (WFP filter engine.\tPPKF was programmed to\tfilter\tout\tthe\tpackets\twith\tunique pattern which were observed\tfrom\tthe\tbot\tattack experiments. Further\tPPKF was found\tto completely suppress the\tflow\tof packets having the programmed uniqueness in them thus preventing the functioning of bots in terms of user information being sent to the Botmaster.

  4. Associative morphological memories based on variations of the kernel and dual kernel methods.

    Science.gov (United States)

    Sussner, Peter

    2003-01-01

    Morphological associative memories (MAMs) belong to the class of morphological neural networks. The recording scheme used in the original MAM models is similar to the correlation recording recipe. Recording is achieved by means of a maximum (MXY model) or minimum (WXY model) of outer products. Notable features of autoassociative morphological memories (AMMs) include optimal absolute storage capacity and one-step convergence. Heteroassociative morphological memories (HMMs) do not have these properties and are not very well understood. The fixed points of AMMs can be characterized exactly in terms of the original patterns. Unfortunately, AMM fixed points include a large number of spurious memories. In this paper, we combine the MXX model and variations of the kernel method to produce new autoassociative and heteroassociative memories. We also introduce a dual kernel method. A new, dual model is given by a combination of the WXX model and a variation of the dual kernel method. The new MAM models exhibit better error correction capabilities than MXX and WXX and a reduced number of spurious memories which can be easily described in terms of the fundamental memories.

  5. Grounded cognition.

    Science.gov (United States)

    Barsalou, Lawrence W

    2008-01-01

    Grounded cognition rejects traditional views that cognition is computation on amodal symbols in a modular system, independent of the brain's modal systems for perception, action, and introspection. Instead, grounded cognition proposes that modal simulations, bodily states, and situated action underlie cognition. Accumulating behavioral and neural evidence supporting this view is reviewed from research on perception, memory, knowledge, language, thought, social cognition, and development. Theories of grounded cognition are also reviewed, as are origins of the area and common misperceptions of it. Theoretical, empirical, and methodological issues are raised whose future treatment is likely to affect the growth and impact of grounded cognition.

  6. Classification of maize kernels using NIR hyperspectral imaging.

    Science.gov (United States)

    Williams, Paul J; Kucheryavskiy, Sergey

    2016-10-15

    NIR hyperspectral imaging was evaluated to classify maize kernels of three hardness categories: hard, medium and soft. Two approaches, pixel-wise and object-wise, were investigated to group kernels according to hardness. The pixel-wise classification assigned a class to every pixel from individual kernels and did not give acceptable results because of high misclassification. However by using a predefined threshold and classifying entire kernels based on the number of correctly predicted pixels, improved results were achieved (sensitivity and specificity of 0.75 and 0.97). Object-wise classification was performed using two methods for feature extraction - score histograms and mean spectra. The model based on score histograms performed better for hard kernel classification (sensitivity and specificity of 0.93 and 0.97), while that of mean spectra gave better results for medium kernels (sensitivity and specificity of 0.95 and 0.93). Both feature extraction methods can be recommended for classification of maize kernels on production scale.

  7. Gaussian kernel width optimization for sparse Bayesian learning.

    Science.gov (United States)

    Mohsenzadeh, Yalda; Sheikhzadeh, Hamid

    2015-04-01

    Sparse kernel methods have been widely used in regression and classification applications. The performance and the sparsity of these methods are dependent on the appropriate choice of the corresponding kernel functions and their parameters. Typically, the kernel parameters are selected using a cross-validation approach. In this paper, a learning method that is an extension of the relevance vector machine (RVM) is presented. The proposed method can find the optimal values of the kernel parameters during the training procedure. This algorithm uses an expectation-maximization approach for updating kernel parameters as well as other model parameters; therefore, the speed of convergence and computational complexity of the proposed method are the same as the standard RVM. To control the convergence of this fully parameterized model, the optimization with respect to the kernel parameters is performed using a constraint on these parameters. The proposed method is compared with the typical RVM and other competing methods to analyze the performance. The experimental results on the commonly used synthetic data, as well as benchmark data sets, demonstrate the effectiveness of the proposed method in reducing the performance dependency on the initial choice of the kernel parameters.

  8. Training Lp norm multiple kernel learning in the primal.

    Science.gov (United States)

    Liang, Zhizheng; Xia, Shixiong; Zhou, Yong; Zhang, Lei

    2013-10-01

    Some multiple kernel learning (MKL) models are usually solved by utilizing the alternating optimization method where one alternately solves SVMs in the dual and updates kernel weights. Since the dual and primal optimization can achieve the same aim, it is valuable in exploring how to perform Lp norm MKL in the primal. In this paper, we propose an Lp norm multiple kernel learning algorithm in the primal where we resort to the alternating optimization method: one cycle for solving SVMs in the primal by using the preconditioned conjugate gradient method and other cycle for learning the kernel weights. It is interesting to note that the kernel weights in our method can obtain analytical solutions. Most importantly, the proposed method is well suited for the manifold regularization framework in the primal since solving LapSVMs in the primal is much more effective than solving LapSVMs in the dual. In addition, we also carry out theoretical analysis for multiple kernel learning in the primal in terms of the empirical Rademacher complexity. It is found that optimizing the empirical Rademacher complexity may obtain a type of kernel weights. The experiments on some datasets are carried out to demonstrate the feasibility and effectiveness of the proposed method.

  9. Spectrum-based kernel length estimation for Gaussian process classification.

    Science.gov (United States)

    Wang, Liang; Li, Chuan

    2014-06-01

    Recent studies have shown that Gaussian process (GP) classification, a discriminative supervised learning approach, has achieved competitive performance in real applications compared with most state-of-the-art supervised learning methods. However, the problem of automatic model selection in GP classification, involving the kernel function form and the corresponding parameter values (which are unknown in advance), remains a challenge. To make GP classification a more practical tool, this paper presents a novel spectrum analysis-based approach for model selection by refining the GP kernel function to match the given input data. Specifically, we target the problem of GP kernel length scale estimation. Spectrums are first calculated analytically from the kernel function itself using the autocorrelation theorem as well as being estimated numerically from the training data themselves. Then, the kernel length scale is automatically estimated by equating the two spectrum values, i.e., the kernel function spectrum equals to the estimated training data spectrum. Compared with the classical Bayesian method for kernel length scale estimation via maximizing the marginal likelihood (which is time consuming and could suffer from multiple local optima), extensive experimental results on various data sets show that our proposed method is both efficient and accurate.

  10. Relaxation and diffusion models with non-singular kernels

    Science.gov (United States)

    Sun, HongGuang; Hao, Xiaoxiao; Zhang, Yong; Baleanu, Dumitru

    2017-02-01

    Anomalous relaxation and diffusion processes have been widely quantified by fractional derivative models, where the definition of the fractional-order derivative remains a historical debate due to its limitation in describing different kinds of non-exponential decays (e.g. stretched exponential decay). Meanwhile, many efforts by mathematicians and engineers have been made to overcome the singularity of power function kernel in its definition. This study first explores physical properties of relaxation and diffusion models where the temporal derivative was defined recently using an exponential kernel. Analytical analysis shows that the Caputo type derivative model with an exponential kernel cannot characterize non-exponential dynamics well-documented in anomalous relaxation and diffusion. A legitimate extension of the previous derivative is then proposed by replacing the exponential kernel with a stretched exponential kernel. Numerical tests show that the Caputo type derivative model with the stretched exponential kernel can describe a much wider range of anomalous diffusion than the exponential kernel, implying the potential applicability of the new derivative in quantifying real-world, anomalous relaxation and diffusion processes.

  11. Per-Sample Multiple Kernel Approach for Visual Concept Learning

    Directory of Open Access Journals (Sweden)

    Tian Yonghong

    2010-01-01

    Full Text Available Abstract Learning visual concepts from images is an important yet challenging problem in computer vision and multimedia research areas. Multiple kernel learning (MKL methods have shown great advantages in visual concept learning. As a visual concept often exhibits great appearance variance, a canonical MKL approach may not generate satisfactory results when a uniform kernel combination is applied over the input space. In this paper, we propose a per-sample multiple kernel learning (PS-MKL approach to take into account intraclass diversity for improving discrimination. PS-MKL determines sample-wise kernel weights according to kernel functions and training samples. Kernel weights as well as kernel-based classifiers are jointly learned. For efficient learning, PS-MKL employs a sample selection strategy. Extensive experiments are carried out over three benchmarking datasets of different characteristics including Caltech101, WikipediaMM, and Pascal VOC'07. PS-MKL has achieved encouraging performance, comparable to the state of the art, which has outperformed a canonical MKL.

  12. Widely Linear Complex-Valued Kernel Methods for Regression

    Science.gov (United States)

    Boloix-Tortosa, Rafael; Murillo-Fuentes, Juan Jose; Santos, Irene; Perez-Cruz, Fernando

    2017-10-01

    Usually, complex-valued RKHS are presented as an straightforward application of the real-valued case. In this paper we prove that this procedure yields a limited solution for regression. We show that another kernel, here denoted as pseudo kernel, is needed to learn any function in complex-valued fields. Accordingly, we derive a novel RKHS to include it, the widely RKHS (WRKHS). When the pseudo-kernel cancels, WRKHS reduces to complex-valued RKHS of previous approaches. We address the kernel and pseudo-kernel design, paying attention to the kernel and the pseudo-kernel being complex-valued. In the experiments included we report remarkable improvements in simple scenarios where real a imaginary parts have different similitude relations for given inputs or cases where real and imaginary parts are correlated. In the context of these novel results we revisit the problem of non-linear channel equalization, to show that the WRKHS helps to design more efficient solutions.

  13. Localized Multiple Kernel Learning Via Sample-Wise Alternating Optimization.

    Science.gov (United States)

    Han, Yina; Yang, Kunde; Ma, Yuanliang; Liu, Guizhong

    2014-01-01

    Our objective is to train support vector machines (SVM)-based localized multiple kernel learning (LMKL), using the alternating optimization between the standard SVM solvers with the local combination of base kernels and the sample-specific kernel weights. The advantage of alternating optimization developed from the state-of-the-art MKL is the SVM-tied overall complexity and the simultaneous optimization on both the kernel weights and the classifier. Unfortunately, in LMKL, the sample-specific character makes the updating of kernel weights a difficult quadratic nonconvex problem. In this paper, starting from a new primal-dual equivalence, the canonical objective on which state-of-the-art methods are based is first decomposed into an ensemble of objectives corresponding to each sample, namely, sample-wise objectives. Then, the associated sample-wise alternating optimization method is conducted, in which the localized kernel weights can be independently obtained by solving their exclusive sample-wise objectives, either linear programming (for l1-norm) or with closed-form solutions (for lp-norm). At test time, the learnt kernel weights for the training data are deployed based on the nearest-neighbor rule. Hence, to guarantee their generality among the test part, we introduce the neighborhood information and incorporate it into the empirical loss when deriving the sample-wise objectives. Extensive experiments on four benchmark machine learning datasets and two real-world computer vision datasets demonstrate the effectiveness and efficiency of the proposed algorithm.

  14. Per-Sample Multiple Kernel Approach for Visual Concept Learning

    Directory of Open Access Journals (Sweden)

    Ling-Yu Duan

    2010-01-01

    Full Text Available Learning visual concepts from images is an important yet challenging problem in computer vision and multimedia research areas. Multiple kernel learning (MKL methods have shown great advantages in visual concept learning. As a visual concept often exhibits great appearance variance, a canonical MKL approach may not generate satisfactory results when a uniform kernel combination is applied over the input space. In this paper, we propose a per-sample multiple kernel learning (PS-MKL approach to take into account intraclass diversity for improving discrimination. PS-MKL determines sample-wise kernel weights according to kernel functions and training samples. Kernel weights as well as kernel-based classifiers are jointly learned. For efficient learning, PS-MKL employs a sample selection strategy. Extensive experiments are carried out over three benchmarking datasets of different characteristics including Caltech101, WikipediaMM, and Pascal VOC'07. PS-MKL has achieved encouraging performance, comparable to the state of the art, which has outperformed a canonical MKL.

  15. Inverse Integral Kernel for Diffusion in a Harmonic Potential

    Science.gov (United States)

    Kosugi, Taichi

    2014-05-01

    The inverse integral kernel for diffusion in a harmonic potential of an overdamped Brownian particle is derived in the present study. It is numerically demonstrated that a sufficiently large number of polynomials for the calculation of the inverse integral kernel are needed for the accurate reproduction of a probability distribution function at past. The inverse integral kernel derived can be used around each of the minima of a generic potential, provided that the lifetimes of the population in the neighboring higher wells are much longer than the negative time lapse.

  16. Non-Rigid Object Tracking by Anisotropic Kernel Mean Shift

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    Mean shift, an iterative procedure that shifts each data point to the average of data points in its neighborhood, has been applied to object tracker. However, the traditional mean shift tracker by isotropic kernel often loses the object with the changing object structure in video sequences, especially when the object structure varies fast. This paper proposes a non-rigid object tracker by anisotropic kernel mean shift in which the shape, scale, and orientation of the kernels adapt to the changing object structure. The experimental results show that the new tracker is self-adaptive and approximately twice faster than the traditional tracker, which ensures the robustness and real time of tracking.

  17. Bergman kernel function on Hua construction of the fourth type

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    This paper introduces the Hua construction and presents the holomorphic automorphism group of the Hua construction of the fourth type. Utilizing the Bergman kernel function, under the condition of holomorphic automorphism and the standard complete orthonormal system of the semi-Reinhardt domain, the infinite series form of the Bergman kernel function is derived. By applying the properties of polynomial and Γ functions, various identification relations of the aforementioned form are developed and the explicit formula of the Bergman kernel function for the Hua construction of the fourth type is obtained, which suggest that many of the previously-reported results are only the special cases of our findings.

  18. The Bergman kernel function of some Reinhardt domains (Ⅱ)

    Institute of Scientific and Technical Information of China (English)

    龚昇; 郑学安

    2000-01-01

    The boundary behavior of the Bergman kernel function of a kind of Reinhardt domain is studied. Upper and lower bounds for the Bergman kernel function are found at the diagonal points ( Z, Z) Let Q be the Reinhardt domainwhere is the Standard Euclidean norm in and let K( Z, W) be the Bergman kernel function of Ω. Then there exist two positive constants m and M, and a function F such thatholds for every Z∈Ω . Hereand is the defining function of Ω The constants m and M depend only on Ω = This result extends some previous known results.

  19. Explicit signal to noise ratio in reproducing kernel Hilbert spaces

    DEFF Research Database (Denmark)

    Gomez-Chova, Luis; Nielsen, Allan Aasbjerg; Camps-Valls, Gustavo

    2011-01-01

    This paper introduces a nonlinear feature extraction method based on kernels for remote sensing data analysis. The proposed approach is based on the minimum noise fraction (MNF) transform, which maximizes the signal variance while also minimizing the estimated noise variance. We here propose...... an alternative kernel MNF (KMNF) in which the noise is explicitly estimated in the reproducing kernel Hilbert space. This enables KMNF dealing with non-linear relations between the noise and the signal features jointly. Results show that the proposed KMNF provides the most noise-free features when confronted...

  20. The Bergman Kernels on Generalized Exceptional Hua Domains

    Institute of Scientific and Technical Information of China (English)

    殷慰萍; 赵振刚

    2001-01-01

    @@Yin Weiping introduce four types of Hua domain which are built on four types of Cartan domain and the Bergman kernels on these four types of Hua domain can be computed in explicit formulas[1]. In this paper, two types of domains defined by (10), (11) (see below) are introduced which are built on two exceptional Cartan domains. And We compute Bergman Kernels explicitly for these two domains. We also study the asymptotic behavior of the Bergman kernel function near boundary points, drawing on Appell's multivariable hypergeometric function.

  1. Flour quality and kernel hardness connection in winter wheat

    Directory of Open Access Journals (Sweden)

    Szabó B. P.

    2016-12-01

    Full Text Available Kernel hardness is controlled by friabilin protein and it depends on the relation between protein matrix and starch granules. Friabilin is present in high concentration in soft grain varieties and in low concentration in hard grain varieties. The high gluten, hard wheat our generally contains about 12.0–13.0% crude protein under Mid-European conditions. The relationship between wheat protein content and kernel texture is usually positive and kernel texture influences the power consumption during milling. Hard-textured wheat grains require more grinding energy than soft-textured grains.

  2. Linear and kernel methods for multi- and hypervariate change detection

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg; Canty, Morton J.

    2010-01-01

    code exists which allows for fast data exploration and experimentation with smaller datasets. Computationally demanding kernelization of test data with training data and kernel image projections have been programmed to run on massively parallel CUDA-enabled graphics processors, when available, giving...... the primal eigenvectors. IDL (Interactive Data Language) implementations of IR-MAD, automatic radiometric normalization and kernel PCA/MAF/MNF transformations have been written which function as transparent and fully integrated extensions of the ENVI remote sensing image analysis environment. Also, Matlab...

  3. FUZZY PRINCIPAL COMPONENT ANALYSIS AND ITS KERNEL BASED MODEL

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    Principal Component Analysis (PCA) is one of the most important feature extraction methods, and Kernel Principal Component Analysis (KPCA) is a nonlinear extension of PCA based on kernel methods. In real world, each input data may not be fully assigned to one class and it may partially belong to other classes. Based on the theory of fuzzy sets, this paper presents Fuzzy Principal Component Analysis (FPCA) and its nonlinear extension model, i.e., Kernel-based Fuzzy Principal Component Analysis (KFPCA). The experimental results indicate that the proposed algorithms have good performances.

  4. Mercer Kernel Based Fuzzy Clustering Self-Adaptive Algorithm

    Institute of Scientific and Technical Information of China (English)

    李侃; 刘玉树

    2004-01-01

    A novel mercer kernel based fuzzy clustering self-adaptive algorithm is presented. The mercer kernel method is introduced to the fuzzy c-means clustering. It may map implicitly the input data into the high-dimensional feature space through the nonlinear transformation. Among other fuzzy c-means and its variants, the number of clusters is first determined. A self-adaptive algorithm is proposed. The number of clusters, which is not given in advance, can be gotten automatically by a validity measure function. Finally, experiments are given to show better performance with the method of kernel based fuzzy c-means self-adaptive algorithm.

  5. Composition Formulas of Bessel-Struve Kernel Function

    Directory of Open Access Journals (Sweden)

    K. S. Nisar

    2016-01-01

    Full Text Available The object of this paper is to study and develop the generalized fractional calculus operators involving Appell’s function F3(· due to Marichev-Saigo-Maeda. Here, we establish the generalized fractional calculus formulas involving Bessel-Struve kernel function Sαλz,  λ,z∈C to obtain the results in terms of generalized Wright functions. The representations of Bessel-Struve kernel function in terms of exponential function and its relation with Bessel and Struve function are also discussed. The pathway integral representations of Bessel-Struve kernel function are also given in this study.

  6. Capturing Option Anomalies with a Variance-Dependent Pricing Kernel

    DEFF Research Database (Denmark)

    Christoffersen, Peter; Heston, Steven; Jacobs, Kris

    2013-01-01

    We develop a GARCH option model with a new pricing kernel allowing for a variance premium. While the pricing kernel is monotonic in the stock return and in variance, its projection onto the stock return is nonmonotonic. A negative variance premium makes it U shaped. We present new semiparametric...... evidence to confirm this U-shaped relationship between the risk-neutral and physical probability densities. The new pricing kernel substantially improves our ability to reconcile the time-series properties of stock returns with the cross-section of option prices. It provides a unified explanation...

  7. Preparation of cottonseed protein concentrate by enzymolysis and alcohol extraction%酶解醇洗法制备棉籽浓缩蛋白

    Institute of Scientific and Technical Information of China (English)

    潘晶; 陈思思; 张晖; 郭晓娜

    2011-01-01

    The pre-pressed cottonseed meal as material was firstly hydrolyzed by pentosan compound enzyme and glucoamylase, and then washed by ethanol to preparate protein concentrate. The result illustrated as that:Under the condition of adding glucoamylase 1 600 U/g, pentosan enzyme 0. 60 fbg/g, solvent/solid ratio of 1:10, temperature 50℃, the cottonseed meal was hydrolyzed for 140 min, and then washed by 70% (v/v) ethanol at 60℃ dipped for 2 times(once for 45 min), with solvent/solid ratio of 1 :7. The protein content of cottonseed protein concentrate prepared was 64 %, and the yield of protein was 78 %.%以预榨浸提棉籽粕为原料,先选用戊聚糖复合酶、糖化酶等植物水解酶对棉籽粕进行作用,再进一步用乙醇溶液浸洗制备棉籽浓缩蛋白.结果表明:在添加糖化酶1600 U/g、戊聚糖复合酶0.60 fbg/g、料液比1 ∶ 10和温度50℃条件下酶作用140 min后,再以料液比1∶7、体积分数70%乙醇溶液和温度60℃条件下醇洗2次,每次45 min,得到产品浓缩蛋白的蛋白质质量分数为64%,蛋白质收率为78%.

  8. Rare variant testing across methods and thresholds using the multi-kernel sequence kernel association test (MK-SKAT).

    Science.gov (United States)

    Urrutia, Eugene; Lee, Seunggeun; Maity, Arnab; Zhao, Ni; Shen, Judong; Li, Yun; Wu, Michael C

    Analysis of rare genetic variants has focused on region-based analysis wherein a subset of the variants within a genomic region is tested for association with a complex trait. Two important practical challenges have emerged. First, it is difficult to choose which test to use. Second, it is unclear which group of variants within a region should be tested. Both depend on the unknown true state of nature. Therefore, we develop the Multi-Kernel SKAT (MK-SKAT) which tests across a range of rare variant tests and groupings. Specifically, we demonstrate that several popular rare variant tests are special cases of the sequence kernel association test which compares pair-wise similarity in trait value to similarity in the rare variant genotypes between subjects as measured through a kernel function. Choosing a particular test is equivalent to choosing a kernel. Similarly, choosing which group of variants to test also reduces to choosing a kernel. Thus, MK-SKAT uses perturbation to test across a range of kernels. Simulations and real data analyses show that our framework controls type I error while maintaining high power across settings: MK-SKAT loses power when compared to the kernel for a particular scenario but has much greater power than poor choices.

  9. Type of cottonseed and level of gossypol in diets of lactating dairy cows: plasma gossypol, health, and reproductive performance.

    Science.gov (United States)

    Santos, J E P; Villasenor, M; Robinson, P H; DePeters, E J; Holmberg, C A

    2003-03-01

    Objectives were to determine effects of altering gossypol intake by feeding whole linted Upland (WUP) or a 1:2 blend of WUP and cracked Pima (BUPCP) cottonseed on plasma gossypol (PG) concentrations, reproduction, and health of Holstein cows. Cows, 813, on three dairy farms were assigned to one of two diets starting at 13 +/- 11 d in milk for a 170-d experiment. Diets contained 717 and 951 mg of free gossypol/kg of dry matter from WUP and BUPCP, respectively. Concentrations of PG, as well as the proportion of total gossypol (TG) as the minus isomer were higher for cows fed BUPCP vs cows fed WUP. Conception rate at the first postpartum artificial insemination did not differ between treatments. However, cows consuming the higher gossypol diet had reduced subsequent conception rates and a lower pregnancy rate. Incidence of abortions increased in the higher gossypol diet, and cows that aborted or remained open had higher PG concentrations. Increasing PG concentrations resulted in reduced conception rates and extended days open. The probability of conception after the first artificial insemination declined at a decreasing rate as the plasma TG increased. Incidence of health disorders were unaffected by gossypol intake and PG concentrations. Similarly, gossypol intake and PG concentrations had no effect on culling or mortality. Six cows died in each diet, and none had postmortem signs compatible with gossypol toxicity. Consumption of a high gossypol diet for 170 d had no effect on health of lactating dairy cows, but it increased PG concentrations and impaired reproductive performance.

  10. Consumption of a Diet Rich in Cottonseed Oil (CSO Lowers Total and LDL Cholesterol in Normo-Cholesterolemic Subjects

    Directory of Open Access Journals (Sweden)

    Kathleen E. Davis

    2012-06-01

    Full Text Available Animal data indicates that dietary cottonseed oil (CSO may lower cholesterol; however, the effects of a CSO-rich diet have not been evaluated in humans. Thirty-eight healthy adults (aged 18–40; 12 males, 26 females consumed a CSO rich diet (95 g CSO daily for one week. Anthropometric measurements were obtained, and blood was drawn pre- and post-intervention. Serum lipids (total cholesterol (TC, high density lipoprotein (HDL, low density lipoprotein (LDL, triglyceride (TG, and free fatty acids (FFA were assayed. There was no change in weight or waist circumference among participants. There was no change in HDL (Pre: 1.27 ± 0.4 mmol/L; Post: 1.21 ± 0.3 mmol/L or TG (Pre: 0.91 ± 0.6 mmol/L; Post: 1.06 ± 1.0 mmol/L. Total cholesterol and LDL were reduced (TC Pre: 4.39 ± 0.9 mmol/L; Post: 4.16 ± 0.8 mmol/L; LDL Pre: 2.70 ± 0.8 mmol/L; Post: 2.47 ± 0.6 mmol/L. When data were grouped by sex, total cholesterol was reduced in female participants (Pre: 4.34 ± 0.9 mmol/L; Post: 4.09 ± 0.8 mmol/L. Consumption of a high fat, CSO-rich diet for one week reduced total cholesterol in female participants without reducing HDL.

  11. Effects of cottonseed meal supplementation time on ruminal fermentation and forage intake by Holstein steers fed fescue hay.

    Science.gov (United States)

    Judkins, M B; Krysl, L J; Barton, R K; Holcombe, D W; Gunter, S A; Broesder, J T

    1991-09-01

    Four ruminally cannulated Holstein steers (average BW 303 kg) were used in a 4 x 4 Latin square design digestion trial to study the influence of daily cottonseed meal (CSM; 1.6 g of CP/kg of BW) supplementation time on forage intake and ruminal fluid kinetics and fermentation. Steers were housed individually in tie stalls and were fed chopped fescue hay on an ad libitum basis at 0600 and 1400. Treatments were 1) control, grass hay only (CON) and grass hay and CSM fed once daily at 2) 0600 (EAM) 3) 1000 (MAM), or 4) 1400 (PM). Ruminal NH3 N concentrations reflected a time of supplementation x sampling time interaction (P less than .05); CON steers had the lowest (P less than .05) ruminal NH3 N concentrations at all times other than at 0600, 1000, 1200, and 2400, when they did not differ (P greater than .05) from at least one of the supplemented groups. Forage intake, ratio of bacterial purine:N, rate of DM and NDF disappearance, and ruminal fluid kinetics were not influenced (P greater than .05) by supplementation time. Total ruminal VFA differed (P less than .05) between CON and supplemented steers, as well as among supplemented steers (linear and quadratic effects P less than .05). Acetate, propionate, and valerate proportions were influenced (P less than .05) by a sampling time X supplementation time interaction. Under the conditions of this study, greater peak ammonia concentrations with morning supplementation than with afternoon supplementation did not stimulate ruminal fermentation or rate of NDF disappearance.

  12. Bioconversion of palm kernel meal for aquaculture: Experiences ...

    African Journals Online (AJOL)

    SERVER

    2008-04-17

    Apr 17, 2008 ... countries where so much agro-industry by-products exist such as palm kernel meal, .... as basic ingredients for margarine production, confectionery, animal ..... Sciences, Universiti Sains Malaysia, Penang 11800, Malaysia.

  13. Linear and kernel methods for multivariate change detection

    DEFF Research Database (Denmark)

    Canty, Morton J.; Nielsen, Allan Aasbjerg

    2012-01-01

    ), as well as maximum autocorrelation factor (MAF) and minimum noise fraction (MNF) analyses of IR-MAD images, both linear and kernel-based (nonlinear), may further enhance change signals relative to no-change background. IDL (Interactive Data Language) implementations of IR-MAD, automatic radiometric...... normalization, and kernel PCA/MAF/MNF transformations are presented that function as transparent and fully integrated extensions of the ENVI remote sensing image analysis environment. The train/test approach to kernel PCA is evaluated against a Hebbian learning procedure. Matlab code is also available...... that allows fast data exploration and experimentation with smaller datasets. New, multiresolution versions of IR-MAD that accelerate convergence and that further reduce no-change background noise are introduced. Computationally expensive matrix diagonalization and kernel image projections are programmed...

  14. OSCILLATORY SINGULAR INTEGRALS WITH VARIABLE ROUGH KERNEL, Ⅱ

    Institute of Scientific and Technical Information of China (English)

    Tang Lin; Yang Dachun

    2003-01-01

    Let n≥2. In this paper, the author establishes the L2(Rn)-boundedness of some oscillatory singular inte-grals with variable rough kernels by means of some estimates on hypergeometric functions and confluent hy-pergeometric funtions.

  15. A Security Kernel Architecture Based Trusted Computing Platform

    Institute of Scientific and Technical Information of China (English)

    CHEN You-lei; SHEN Chang-xiang

    2005-01-01

    A security kernel architecture built on trusted computing platform in the light of thinking about trusted computing is presented. According to this architecture, a new security module TCB (Trusted Computing Base) is added to the operation system kernel and two operation interface modes are provided for the sake of self-protection. The security kernel is divided into two parts and trusted mechanism is separated from security functionality. The TCB module implements the trusted mechanism such as measurement and attestation,while the other components of security kernel provide security functionality based on these mechanisms. This architecture takes full advantage of functions provided by trusted platform and clearly defines the security perimeter of TCB so as to assure self-security from architectural vision. We also present function description of TCB and discuss the strengths and limitations comparing with other related researches.

  16. A Thermodynamic Model for Argon Plasma Kernel Formation

    Directory of Open Access Journals (Sweden)

    James Keck

    2010-11-01

    Full Text Available Plasma kernel formation of argon is studied experimentally and theoretically. The experiments have been performed in a constant volume cylindrical vessel located in a shadowgraph system. The experiments have been done in constant pressure. The energy of plasma is supplied by an ignition system through two electrodes located in the vessel. The experiments have been done with two different spark energies to study the effect of input energy on kernel growth and its properties. A thermodynamic model employing mass and energy balance was developed to predict the experimental data. The agreement between experiments and model prediction is very good. The effect of various parameters such as initial temperature, initial radius of the kernel, and the radiation energy loss have been investigated and it has been concluded that initial condition is very important on formation and expansion of the kernel.

  17. Kernel based eigenvalue-decomposition methods for analysing ham

    DEFF Research Database (Denmark)

    Christiansen, Asger Nyman; Nielsen, Allan Aasbjerg; Møller, Flemming

    2010-01-01

    conditions and finding useful additives to hinder the color to change rapidly. To be able to prove which methods of storing and additives work, Danisco wants to monitor the development of the color of meat in a slice of ham as a function of time, environment and ingredients. We have chosen to use multi...... methods, such as PCA, MAF or MNF. We therefore investigated the applicability of kernel based versions of these transformation. This meant implementing the kernel based methods and developing new theory, since kernel based MAF and MNF is not described in the literature yet. The traditional methods only...... have two factors that are useful for segmentation and none of them can be used to segment the two types of meat. The kernel based methods have a lot of useful factors and they are able to capture the subtle differences in the images. This is illustrated in Figure 1. You can see a comparison of the most...

  18. Palmprint Recognition by Applying Wavelet-Based Kernel PCA

    Institute of Scientific and Technical Information of China (English)

    Murat Ekinci; Murat Aykut

    2008-01-01

    This paper presents a wavelet-based kernel Principal Component Analysis (PCA) method by integrating the Daubechies wavelet representation of palm images and the kernel PCA method for palmprint recognition. Kernel PCA is a technique for nonlinear dimension reduction of data with an underlying nonlinear spatial structure. The intensity values of the palmprint image are first normalized by using mean and standard deviation. The palmprint is then transformed into the wavelet domain to decompose palm images and the lowest resolution subband coefficients are chosen for palm representation.The kernel PCA method is then applied to extract non-linear features from the subband coefficients. Finally, similarity measurement is accomplished by using weighted Euclidean linear distance-based nearest neighbor classifier. Experimental results on PolyU Palmprint Databases demonstrate that the proposed approach achieves highly competitive performance with respect to the published palmprint recognition approaches.

  19. Screening of the kernels of Pentadesma butyracea from various ...

    African Journals Online (AJOL)

    Gwla10

    The plant producing type 1 kernels (with medium length, low width and high thickness) and ... Recent works on the biological activities of P. butyracea showed that the ... collection sites belong to various agroecological zones of Benin. Thus ...

  20. 438 Adaptive Kernel in Meshsize Boosting Algorithm in KDE (Pp ...

    African Journals Online (AJOL)

    FIRST LADY

    2011-01-18

    Jan 18, 2011 ... classifier is boosted by suitably re-weighting the data. This weight ... Methods. Algorithm on Boosting Kernel Density Estimates and Bias Reduction ... Gaussian (since all distributions tend to be normal as n, the sample size,.

  1. Removal of Lead from Aqueous Solution by Palm Kernel Fibre

    African Journals Online (AJOL)

    NJD

    E. Augustine Ofomaja,a* I. Emmanuel Unuabonaha and N. Abiola Oladojab ... The sorption of lead on palm kernel fibre, an agricultural waste product, has been studied. ... present a cheap and cost-effective alternative for lead removal.

  2. Estimates of Oseen kernels in weighted $L^{p}$ spaces

    OpenAIRE

    KRAČMAR, Stanislav; Novotný, Antonín; Pokorný, Milan

    2001-01-01

    We study convolutions with Oseen kernels (weakly singular and singular) in both two- and three-dimensional space. We give a detailed weighted $L^{p}$ theory for $ p\\in(1;\\infty$ ] for anisotropic weights.

  3. INTEGRAL COLLISION KERNEL FOR THE GROWTH OF AEROSOL PARTICLES

    Institute of Scientific and Technical Information of China (English)

    Hongyong Xie

    2005-01-01

    Integral collision kernel is elucidated using experimental results for titania, silica and alumina nanoparticles synthesized by FCVD process, and titania submicron particles synthesized in a tube furnace reactor. The integral collision kernel was obtained from a particle number balance equation by the integration of collision rates from the kinetic theory of dilute gases for the free-molecule regime, from the Smoluchowski theory for the continuum regime, and by a semi-empirical interpolation for the transition regime between the two limiting regimes. Comparisons have been made on particle size and the integral collision kernel, showing that the predicted integral collision kernel agreed well with the experimental results in Knudsen number range from about 1.5 to 20.

  4. Analysis of Kernel Approach in Fuzzy-Based Image Classifications

    Directory of Open Access Journals (Sweden)

    Mragank Singhal

    2013-03-01

    Full Text Available This paper presents a framework of kernel approach in the field of fuzzy based image classification in remote sensing. The goal of image classification is to separate images according to their visual content into two or more disjoint classes. Fuzzy logic is relatively young theory. Major advantage of this theory is that it allows the natural description, in linguistic terms, of problems that should be solved rather than in terms of relationships between precise numerical values. This paper describes how remote sensing data with uncertainty are handled with fuzzy based classification using Kernel approach for land use/land cover maps generation. The introduction to fuzzification using Kernel approach provides the basis for the development of more robust approaches to the remote sensing classification problem. The kernel explicitly defines a similarity measure between two samples and implicitly represents the mapping of the input space to the feature space.

  5. Effect of mixing scanner types and reconstruction kernels on the characterization of lung parenchymal pathologies: emphysema, interstitial pulmonary fibrosis and normal non-smokers

    Science.gov (United States)

    Xu, Ye; van Beek, Edwin J.; McLennan, Geoffrey; Guo, Junfeng; Sonka, Milan; Hoffman, Eric

    2006-03-01

    In this study we utilize our texture characterization software (3-D AMFM) to characterize interstitial lung diseases (including emphysema) based on MDCT generated volumetric data using 3-dimensional texture features. We have sought to test whether the scanner and reconstruction filter (kernel) type affect the classification of lung diseases using the 3-D AMFM. We collected MDCT images in three subject groups: emphysema (n=9), interstitial pulmonary fibrosis (IPF) (n=10), and normal non-smokers (n=9). In each group, images were scanned either on a Siemens Sensation 16 or 64-slice scanner, (B50f or B30 recon. kernel) or a Philips 4-slice scanner (B recon. kernel). A total of 1516 volumes of interest (VOIs; 21x21 pixels in plane) were marked by two chest imaging experts using the Iowa Pulmonary Analysis Software Suite (PASS). We calculated 24 volumetric features. Bayesian methods were used for classification. Images from different scanners/kernels were combined in all possible combinations to test how robust the tissue classification was relative to the differences in image characteristics. We used 10-fold cross validation for testing the result. Sensitivity, specificity and accuracy were calculated. One-way Analysis of Variances (ANOVA) was used to compare the classification result between the various combinations of scanner and reconstruction kernel types. This study yielded a sensitivity of 94%, 91%, 97%, and 93% for emphysema, ground-glass, honeycombing, and normal non-smoker patterns respectively using a mixture of all three subject groups. The specificity for these characterizations was 97%, 99%, 99%, and 98%, respectively. The F test result of ANOVA shows there is no significant difference (p <0.05) between different combinations of data with respect to scanner and convolution kernel type. Since different MDCT and reconstruction kernel types did not show significant differences in regards to the classification result, this study suggests that the 3-D AMFM can

  6. KERNEL FEATURE CROSS-CORRELATION FOR UNSUPERVISED QUANTIFICATION OF DAMAGE FROM WINDTHROW IN FORESTS

    Directory of Open Access Journals (Sweden)

    F. Pirotti

    2016-06-01

    Full Text Available In this study estimation of tree damage from a windthrow event using feature detection on RGB high resolution imagery is assessed. An accurate quantitative assessment of the damage in terms of volume is important and can be done by ground sampling, which is notably expensive and time-consuming, or by manual interpretation and analyses of aerial images. This latter manual method also requires an expert operator investing time to manually detect damaged trees and apply relation functions between measures and volume which are also error-prone. In the proposed method RGB images with 0.2 m ground sample distance are analysed using an adaptive template matching method. Ten images corresponding to ten separate study areas are tested. A 13x13 pixels kernel with a simplified linear-feature representation of a cylinder is applied at different rotation angles (from 0° to 170° at 10° steps. The higher values of the normalized cross-correlation (NCC of all angles are recorded for each pixel for each image. Several features are tested: percentiles (75, 80, 85, 90, 95, 99, max and sum and number of pixels with NCC above 0.55. Three regression methods are tested, multiple regression (mr, support vector machines (svm with linear kernel and random forests. The first two methods gave the best results. The ground-truth was acquired by ground sampling, and total volumes of damaged trees are estimated for each of the 10 areas. Damaged volumes in the ten areas range from ~1.8 x102 m3 to ~1.2x104 m3. Regression results show that smv regression method over the sum gives an R-squared of 0.92, a mean of absolute errors (MAE of 255 m3 and a relative absolute error (RAE of 34% using leave-one-out cross validation from the 10 observations. These initial results are encouraging and support further investigations on more finely tuned kernel template metrics to define an unsupervised image analysis process to automatically assess forest damage from windthrow.

  7. Kernel Feature Cross-Correlation for Unsupervised Quantification of Damage from Windthrow in Forests

    Science.gov (United States)

    Pirotti, F.; Travaglini, D.; Giannetti, F.; Kutchartt, E.; Bottalico, F.; Chirici, G.

    2016-06-01

    In this study estimation of tree damage from a windthrow event using feature detection on RGB high resolution imagery is assessed. An accurate quantitative assessment of the damage in terms of volume is important and can be done by ground sampling, which is notably expensive and time-consuming, or by manual interpretation and analyses of aerial images. This latter manual method also requires an expert operator investing time to manually detect damaged trees and apply relation functions between measures and volume which are also error-prone. In the proposed method RGB images with 0.2 m ground sample distance are analysed using an adaptive template matching method. Ten images corresponding to ten separate study areas are tested. A 13x13 pixels kernel with a simplified linear-feature representation of a cylinder is applied at different rotation angles (from 0° to 170° at 10° steps). The higher values of the normalized cross-correlation (NCC) of all angles are recorded for each pixel for each image. Several features are tested: percentiles (75, 80, 85, 90, 95, 99, max) and sum and number of pixels with NCC above 0.55. Three regression methods are tested, multiple regression (mr), support vector machines (svm) with linear kernel and random forests. The first two methods gave the best results. The ground-truth was acquired by ground sampling, and total volumes of damaged trees are estimated for each of the 10 areas. Damaged volumes in the ten areas range from ~1.8 x102 m3 to ~1.2x104 m3. Regression results show that smv regression method over the sum gives an R-squared of 0.92, a mean of absolute errors (MAE) of 255 m3 and a relative absolute error (RAE) of 34% using leave-one-out cross validation from the 10 observations. These initial results are encouraging and support further investigations on more finely tuned kernel template metrics to define an unsupervised image analysis process to automatically assess forest damage from windthrow.

  8. Digital Communications Channel Equalisation Using the Kernel Adaline.

    OpenAIRE

    Mitchinson, B.; Harrison, R F

    2000-01-01

    For transmission of digital signals over a linear channel with additive white gaussian noise, it has been shown that the optimal symbol decision equaliser is non-linear. The Kernel Adaline algorithm, a non-linear generalisation of Widrow's and Hoff's Adaline, has been shown to be capable of learning arbitrary non-linear decision boundaries, whilst retaining the desirable convergence properties of the linear Adaline. This work investigates the use of the Kernel Adaline as equaliser for such ch...

  9. Music Emotion Detection Using Hierarchical Sparse Kernel Machines

    OpenAIRE

    Yu-Hao Chin; Chang-Hong Lin; Ernestasia Siahaan; Jia-Ching Wang

    2014-01-01

    For music emotion detection, this paper presents a music emotion verification system based on hierarchical sparse kernel machines. With the proposed system, we intend to verify if a music clip possesses happiness emotion or not. There are two levels in the hierarchical sparse kernel machines. In the first level, a set of acoustical features are extracted, and principle component analysis (PCA) is implemented to reduce the dimension. The acoustical features are utilized to generate the first-l...

  10. Reconstructing Concept Lattices Usingnth-Order Context Kernels

    Institute of Scientific and Technical Information of China (English)

    SHEN Xiajiong; XU Bin; LIU Zongtian

    2006-01-01

    To be different from traditional algorithms for concept lattice constructing, a method based on nth-order context kernel is suggested in this paper.The context kernels support generating small lattices for sub-contexts split by a given context.The final concept lattice is reconstructed by combining these small lattices.All relevant algorithms are implemented in a system IsoFCA.Test shows that the method yields concept lattices in lower time complexity than Godin algorithm in practical case.

  11. Nonlinear stochastic system identification of skin using volterra kernels.

    Science.gov (United States)

    Chen, Yi; Hunter, Ian W

    2013-04-01

    Volterra kernel stochastic system identification is a technique that can be used to capture and model nonlinear dynamics in biological systems, including the nonlinear properties of skin during indentation. A high bandwidth and high stroke Lorentz force linear actuator system was developed and used to test the mechanical properties of bulk skin and underlying tissue in vivo using a non-white input force and measuring an output position. These short tests (5 s) were conducted in an indentation configuration normal to the skin surface and in an extension configuration tangent to the skin surface. Volterra kernel solution methods were used including a fast least squares procedure and an orthogonalization solution method. The practical modifications, such as frequency domain filtering, necessary for working with low-pass filtered inputs are also described. A simple linear stochastic system identification technique had a variance accounted for (VAF) of less than 75%. Representations using the first and second Volterra kernels had a much higher VAF (90-97%) as well as a lower Akaike information criteria (AICc) indicating that the Volterra kernel models were more efficient. The experimental second Volterra kernel matches well with results from a dynamic-parameter nonlinearity model with fixed mass as a function of depth as well as stiffness and damping that increase with depth into the skin. A study with 16 subjects showed that the kernel peak values have mean coefficients of variation (CV) that ranged from 3 to 8% and showed that the kernel principal components were correlated with location on the body, subject mass, body mass index (BMI), and gender. These fast and robust methods for Volterra kernel stochastic system identification can be applied to the characterization of biological tissues, diagnosis of skin diseases, and determination of consumer product efficacy.

  12. Bergman kernel and metric on non-smooth pseudoconvex domains

    Institute of Scientific and Technical Information of China (English)

    陈伯勇; 张锦豪

    1999-01-01

    A stability theorem of the Bergman kernel and completeness of the Bergman metric have been proved on a type of non-smooth pseudoconvex domains defined in the following way: D={z∈U|r(z)<0} where U is a neighbourhood of (?) and r is a continuous plurisubharmonic function on U. A continuity principle of the Bergman Kernel for pseudoconvex domains with Lipschitz boundary is also given, which answers a problem of Boas.

  13. A compact kernel for the calculus of inductive constructions

    Indian Academy of Sciences (India)

    A Asperti; W Ricciotti; C Sacerdoti Coen; E Tassi

    2009-02-01

    The paper describes the new kernel for the Calculus of Inductive Constructions (CIC) implemented inside the Matita Interactive Theorem Prover. The design of the new kernel has been completely revisited since the first release, resulting in a remarkably compact implementation of about 2300 lines of OCaml code. The work is meant for people interested in implementation aspects of Interactive Provers, and is not self contained. In particular, it requires good acquaintance with Type Theory and functional programming languages.

  14. Kernel approximation for solving few-body integral equations

    Science.gov (United States)

    Christie, I.; Eyre, D.

    1986-06-01

    This paper investigates an approximate method for solving integral equations that arise in few-body problems. The method is to replace the kernel by a degenerate kernel defined on a finite dimensional subspace of piecewise Lagrange polynomials. Numerical accuracy of the method is tested by solving the two-body Lippmann-Schwinger equation with non-separable potentials, and the three-body Amado-Lovelace equation with separable two-body potentials.

  15. GPU Acceleration of Image Convolution using Spatially-varying Kernel

    OpenAIRE

    Hartung, Steven; Shukla, Hemant; Miller, J. Patrick; Pennypacker, Carlton

    2012-01-01

    Image subtraction in astronomy is a tool for transient object discovery such as asteroids, extra-solar planets and supernovae. To match point spread functions (PSFs) between images of the same field taken at different times a convolution technique is used. Particularly suitable for large-scale images is a computationally intensive spatially-varying kernel. The underlying algorithm is inherently massively parallel due to unique kernel generation at every pixel location. The spatially-varying k...

  16. X-Y separable pyramid steerable scalable kernels

    OpenAIRE

    Shy, Douglas; Perona, Pietro

    1994-01-01

    A new method for generating X-Y separable, steerable, scalable approximations of filter kernels is proposed which is based on a generalization of the singular value decomposition (SVD) to three dimensions. This “pseudo-SVD” improves upon a previous scheme due to Perona (1992) in that it reduces convolution time and storage requirements. An adaptation of the pseudo-SVD is proposed to generate steerable and scalable kernels which are suitable for use with a Laplacian pyramid. The properties of ...

  17. ON APPROXIMATION BY REPRODUCING KERNEL SPACES IN WEIGHTED Lp SPACES

    Institute of Scientific and Technical Information of China (English)

    Baohuai SHENG

    2007-01-01

    In this paper, we investigate the order of approximation by reproducing kernel spaces on (-1, 1) in weighted Lp spaces. We first restate the translation network from the view of reproducing kernel spaces and then construct a sequence of approximating operators with the help of Jacobi orthogonal polynomials, with which we establish a kind of Jackson inequality to describe the error estimate.Finally, The results are used to discuss an approximation problem arising from learning theory.

  18. The Dynamic Kernel Scheduler-Part 1

    Science.gov (United States)

    Adelmann, Andreas; Locans, Uldis; Suter, Andreas

    2016-10-01

    Emerging processor architectures such as GPUs and Intel MICs provide a huge performance potential for high performance computing. However developing software that uses these hardware accelerators introduces additional challenges for the developer. These challenges may include exposing increased parallelism, handling different hardware designs, and using multiple development frameworks in order to utilise devices from different vendors. The Dynamic Kernel Scheduler (DKS) is being developed in order to provide a software layer between the host application and different hardware accelerators. DKS handles the communication between the host and the device, schedules task execution, and provides a library of built-in algorithms. Algorithms available in the DKS library will be written in CUDA, OpenCL, and OpenMP. Depending on the available hardware, the DKS can select the appropriate implementation of the algorithm. The first DKS version was created using CUDA for the Nvidia GPUs and OpenMP for Intel MIC. DKS was further integrated into OPAL (Object-oriented Parallel Accelerator Library) in order to speed up a parallel FFT based Poisson solver and Monte Carlo simulations for particle-matter interaction used for proton therapy degrader modelling. DKS was also used together with Minuit2 for parameter fitting, where χ2 and max-log-likelihood functions were offloaded to the hardware accelerator. The concepts of the DKS, first results, and plans for the future will be shown in this paper.

  19. Characterization of Flour from Avocado Seed Kernel

    Directory of Open Access Journals (Sweden)

    Macey A. Mahawan

    2015-11-01

    Full Text Available The study focused on the Characterization of Flour from Avocado Seed Kernel. Based on the findings of the study the percentages of crude protein, crude fiber, crude fat, total carbohydrates, ash and moisture were 7.75, 4.91, 0.71, 74.65, 2.83 and 14.05 respectively. On the other hand the falling number was 495 seconds while gluten was below the detection limit of the method used. Moreover, the sensory evaluation in terms of color, texture and aroma in 0% proportion of Avocado seed flour was moderate like and slight like for 25% and 50% proportions of Avocado seed flour. On the otherhand, the taste of the biscuits prepared with 0% Avocado seed flour was moderate like, in 25% proportion of Avocado seed flour were slight like and in 50% proportion was neither liked nor disliked. The overall acceptability results for 0% proportion of Avocado seed flour was moderate like and slight like for 25% and 50% proportions of Avocado seed flour. Furthermore, the computed p values for the comparison of the level of acceptability in terms of color, texture, aroma, taste and overall acceptability of biscuits using 0%, 25%, and 50% avocado seed flour were lower than 0.05. Thus the null hypothesis is rejected.

  20. The spectrum of kernel random matrices

    CERN Document Server

    Karoui, Noureddine El

    2010-01-01

    We place ourselves in the setting of high-dimensional statistical inference where the number of variables $p$ in a dataset of interest is of the same order of magnitude as the number of observations $n$. We consider the spectrum of certain kernel random matrices, in particular $n\\times n$ matrices whose $(i,j)$th entry is $f(X_i'X_j/p)$ or $f(\\Vert X_i-X_j\\Vert^2/p)$ where $p$ is the dimension of the data, and $X_i$ are independent data vectors. Here $f$ is assumed to be a locally smooth function. The study is motivated by questions arising in statistics and computer science where these matrices are used to perform, among other things, nonlinear versions of principal component analysis. Surprisingly, we show that in high-dimensions, and for the models we analyze, the problem becomes essentially linear--which is at odds with heuristics sometimes used to justify the usage of these methods. The analysis also highlights certain peculiarities of models widely studied in random matrix theory and raises some questio...

  1. Local Kernel for Brains Classification in Schizophrenia

    Science.gov (United States)

    Castellani, U.; Rossato, E.; Murino, V.; Bellani, M.; Rambaldelli, G.; Tansella, M.; Brambilla, P.

    In this paper a novel framework for brain classification is proposed in the context of mental health research. A learning by example method is introduced by combining local measurements with non linear Support Vector Machine. Instead of considering a voxel-by-voxel comparison between patients and controls, we focus on landmark points which are characterized by local region descriptors, namely Scale Invariance Feature Transform (SIFT). Then, matching is obtained by introducing the local kernel for which the samples are represented by unordered set of features. Moreover, a new weighting approach is proposed to take into account the discriminative relevance of the detected groups of features. Experiments have been performed including a set of 54 patients with schizophrenia and 54 normal controls on which region of interest (ROI) have been manually traced by experts. Preliminary results on Dorso-lateral PreFrontal Cortex (DLPFC) region are promising since up to 75% of successful classification rate has been obtained with this technique and the performance has improved up to 85% when the subjects have been stratified by sex.

  2. An Ensemble Approach to Building Mercer Kernels with Prior Information

    Science.gov (United States)

    Srivastava, Ashok N.; Schumann, Johann; Fischer, Bernd

    2005-01-01

    This paper presents a new methodology for automatic knowledge driven data mining based on the theory of Mercer Kernels, which are highly nonlinear symmetric positive definite mappings from the original image space to a very high, possibly dimensional feature space. we describe a new method called Mixture Density Mercer Kernels to learn kernel function directly from data, rather than using pre-defined kernels. These data adaptive kernels can encode prior knowledge in the kernel using a Bayesian formulation, thus allowing for physical information to be encoded in the model. Specifically, we demonstrate the use of the algorithm in situations with extremely small samples of data. We compare the results with existing algorithms on data from the Sloan Digital Sky Survey (SDSS) and demonstrate the method's superior performance against standard methods. The code for these experiments has been generated with the AUTOBAYES tool, which automatically generates efficient and documented C/C++ code from abstract statistical model specifications. The core of the system is a schema library which contains templates for learning and knowledge discovery algorithms like different versions of EM, or numeric optimization methods like conjugate gradient methods. The template instantiation is supported by symbolic-algebraic computations, which allows AUTOBAYES to find closed-form solutions and, where possible, to integrate them into the code.

  3. Kernel-Based Nonlinear Discriminant Analysis for Face Recognition

    Institute of Scientific and Technical Information of China (English)

    LIU QingShan (刘青山); HUANG Rui (黄锐); LU HanQing (卢汉清); MA SongDe (马颂德)

    2003-01-01

    Linear subspace analysis methods have been successfully applied to extract features for face recognition. But they are inadequate to represent the complex and nonlinear variations of real face images, such as illumination, facial expression and pose variations, because of their linear properties. In this paper, a nonlinear subspace analysis method, Kernel-based Nonlinear Discriminant Analysis (KNDA), is presented for face recognition, which combines the nonlinear kernel trick with the linear subspace analysis method - Fisher Linear Discriminant Analysis (FLDA).First, the kernel trick is used to project the input data into an implicit feature space, then FLDA is performed in this feature space. Thus nonlinear discriminant features of the input data are yielded. In addition, in order to reduce the computational complexity, a geometry-based feature vectors selection scheme is adopted. Another similar nonlinear subspace analysis is Kernel-based Principal Component Analysis (KPCA), which combines the kernel trick with linear Principal Component Analysis (PCA). Experiments are performed with the polynomial kernel, and KNDA is compared with KPCA and FLDA. Extensive experimental results show that KNDA can give a higher recognition rate than KPCA and FLDA.

  4. Nonlinear Forecasting With Many Predictors Using Kernel Ridge Regression

    DEFF Research Database (Denmark)

    Exterkate, Peter; Groenen, Patrick J.F.; Heij, Christiaan

    This paper puts forward kernel ridge regression as an approach for forecasting with many predictors that are related nonlinearly to the target variable. In kernel ridge regression, the observed predictor variables are mapped nonlinearly into a high-dimensional space, where estimation of the predi......This paper puts forward kernel ridge regression as an approach for forecasting with many predictors that are related nonlinearly to the target variable. In kernel ridge regression, the observed predictor variables are mapped nonlinearly into a high-dimensional space, where estimation...... of the predictive regression model is based on a shrinkage estimator to avoid overfitting. We extend the kernel ridge regression methodology to enable its use for economic time-series forecasting, by including lags of the dependent variable or other individual variables as predictors, as typically desired...... in macroeconomic and financial applications. Monte Carlo simulations as well as an empirical application to various key measures of real economic activity confirm that kernel ridge regression can produce more accurate forecasts than traditional linear and nonlinear methods for dealing with many predictors based...

  5. Searching for efficient Markov chain Monte Carlo proposal kernels.

    Science.gov (United States)

    Yang, Ziheng; Rodríguez, Carlos E

    2013-11-26

    Markov chain Monte Carlo (MCMC) or the Metropolis-Hastings algorithm is a simulation algorithm that has made modern Bayesian statistical inference possible. Nevertheless, the efficiency of different Metropolis-Hastings proposal kernels has rarely been studied except for the Gaussian proposal. Here we propose a unique class of Bactrian kernels, which avoid proposing values that are very close to the current value, and compare their efficiency with a number of proposals for simulating different target distributions, with efficiency measured by the asymptotic variance of a parameter estimate. The uniform kernel is found to be more efficient than the Gaussian kernel, whereas the Bactrian kernel is even better. When optimal scales are used for both, the Bactrian kernel is at least 50% more efficient than the Gaussian. Implementation in a Bayesian program for molecular clock dating confirms the general applicability of our results to generic MCMC algorithms. Our results refute a previous claim that all proposals had nearly identical performance and will prompt further research into efficient MCMC proposals.

  6. Multiple Crop Classification Using Various Support Vector Machine Kernel Functions

    Directory of Open Access Journals (Sweden)

    Rupali R. Surase

    2015-01-01

    Full Text Available This study was carried out with techniques of Remote Sensing (RS based crop discrimination and area estimation with single date approach. Several kernel functions are employed and compared in this study for mapping the input space with including linear, sigmoid, and polynomial and Radial Basis Function (RBF. The present study highlights the advantages of Remote Sensing (RS and Geographic Information System (GIS techniques for analyzing the land use/land cover mapping for Aurangabad region of Maharashtra, India. Single date, cloud free IRS-Resourcesat-1 LISS-III data was used for further classification on training set for supervised classification. ENVI 4.4 is used for image analysis and interpretation. The experimental tests show that system is achieved 94.82% using SVM with kernel functions including Polynomial kernel function compared with Radial Basis Function, Sigmoid and linear kernel. The Overall Accuracy (OA to up to 5.17% in comparison to using sigmoid kernel function, and up to 3.45% in comparison to a 3rd degree polynomial kernel function and RBF with 200 as a penalty parameter.

  7. Sparse kernel learning with LASSO and Bayesian inference algorithm.

    Science.gov (United States)

    Gao, Junbin; Kwan, Paul W; Shi, Daming

    2010-03-01

    Kernelized LASSO (Least Absolute Selection and Shrinkage Operator) has been investigated in two separate recent papers [Gao, J., Antolovich, M., & Kwan, P. H. (2008). L1 LASSO and its Bayesian inference. In W. Wobcke, & M. Zhang (Eds.), Lecture notes in computer science: Vol. 5360 (pp. 318-324); Wang, G., Yeung, D. Y., & Lochovsky, F. (2007). The kernel path in kernelized LASSO. In International conference on artificial intelligence and statistics (pp. 580-587). San Juan, Puerto Rico: MIT Press]. This paper is concerned with learning kernels under the LASSO formulation via adopting a generative Bayesian learning and inference approach. A new robust learning algorithm is proposed which produces a sparse kernel model with the capability of learning regularized parameters and kernel hyperparameters. A comparison with state-of-the-art methods for constructing sparse regression models such as the relevance vector machine (RVM) and the local regularization assisted orthogonal least squares regression (LROLS) is given. The new algorithm is also demonstrated to possess considerable computational advantages. Copyright 2009 Elsevier Ltd. All rights reserved.

  8. Silage quality of Piata palisadegrass with palm kernel cake

    Directory of Open Access Journals (Sweden)

    Rângelis de Sousa Figueredo

    2014-02-01

    Full Text Available This study was developed to evaluate silage quality of Piata palisadegrass with palm kernel cake (Elaeis guineensis Jacq.. The experiment was carried out at the Federal Institute of Goiás State, Campus Rio Verde, in a completely randomized design with four treatments and five repetitions. The treatments consisted of Piata palisadegrass ensiled with palm kernel in the levels of 0, 5, 10 and 15% on a natural basis of the Piata palisadegrass. The material was minced, mixed, packed into experimental silos and opened after 60 days of fermentation. The palm kernel cake is an agro-industrial by-product that can enrich the silage, increasing its nutritional value.The addition of palm kernel cake improved the fermentative and bromatological parameters of the silage, increasing the dry matter, crude protein, ether extract, and total digestible nutrients, with a reduction in the fiber fraction, values of pH, ammonia nitrogen, and titratable acidity. The use of palm kernel cake in Piata palisadegrass silage increase the fractions A, B1, B2 and in vitro dry matter digestibility, and decrease the fractions B3 and C. For achieving the best quality silage it is recommended the addition of 15% palm kernel cake.

  9. Kernels by Monochromatic Paths and Color-Perfect Digraphs

    Directory of Open Access Journals (Sweden)

    Galeana-Śanchez Hortensia

    2016-05-01

    Full Text Available For a digraph D, V (D and A(D will denote the sets of vertices and arcs of D respectively. In an arc-colored digraph, a subset K of V(D is said to be kernel by monochromatic paths (mp-kernel if (1 for any two different vertices x, y in N there is no monochromatic directed path between them (N is mp-independent and (2 for each vertex u in V (D \\ N there exists v ∈ N such that there is a monochromatic directed path from u to v in D (N is mp-absorbent. If every arc in D has a different color, then a kernel by monochromatic paths is said to be a kernel. Two associated digraphs to an arc-colored digraph are the closure and the color-class digraph CC(D. In this paper we will approach an mp-kernel via the closure of induced subdigraphs of D which have the property of having few colors in their arcs with respect to D. We will introduce the concept of color-perfect digraph and we are going to prove that if D is an arc-colored digraph such that D is a quasi color-perfect digraph and CC(D is not strong, then D has an mp-kernel. Previous interesting results are generalized, as for example Richardson′s Theorem.

  10. Representative sets and irrelevant vertices: New tools for kernelization

    CERN Document Server

    Kratsch, Stefan

    2011-01-01

    Recent work of the present authors provided a polynomial kernel for Odd Cycle Transversal by introducing matroid-based tools into kernelization. In the current work we further establish the usefulness of matroid theory to kernelization by showing applications of a result on representative sets due to Lov\\'asz (Combinatorial Surveys 1977) and Marx (TCS 2009). We give two types of applications: 1. Direct applications of the representative objects idea. In this direction, we give a polynomial kernel for Almost 2-SAT by reducing the problem to a cut problem with pairs of vertices as sinks, and subsequently reducing the set of pairs to a representative subset of bounded size. This implies polynomial kernels for several other problems, including Vertex Cover parameterized by the size of the LP gap, and the RHorn-Backdoor Deletion Set problem from practical SAT solving. We also get a polynomial kernel for Multiway Cut with deletable terminals, by producing a representative set of vertices, of bounded size, which is ...

  11. Kernel CMAC: an Efficient Neural Network for Classification and Regression

    Directory of Open Access Journals (Sweden)

    Gábor Horváth

    2006-01-01

    Full Text Available Kernel methods in learning machines have been developed in the last decade asnew techniques for solving classification and regression problems. Kernel methods havemany advantageous properties regarding their learning and generalization capabilities,but for getting the solution usually the computationally complex quadratic programming isrequired. To reduce computational complexity a lot of different versions have beendeveloped. These versions apply different kernel functions, utilize the training data indifferent ways or apply different criterion functions. This paper deals with a special kernelnetwork, which is based on the CMAC neural network. Cerebellar Model ArticulationController (CMAC has some attractive features: fast learning capability and thepossibility of efficient digital hardware implementation. Besides these attractive featuresthe modelling and generalization capabilities of a CMAC may be rather limited. The papershows that kernel CMAC – an extended version of the classical CMAC networkimplemented in a kernel form – improves that properties of the classical versionsignificantly. Both the modelling and the generalization capabilities are improved while thelimited computational complexity is maintained. The paper shows the architecture of thisnetwork and presents the relation between the classical CMAC and the kernel networks.The operation of the proposed architecture is illustrated using some common benchmarkproblems.

  12. Ground Wars

    DEFF Research Database (Denmark)

    Nielsen, Rasmus Kleis

    Political campaigns today are won or lost in the so-called ground war--the strategic deployment of teams of staffers, volunteers, and paid part-timers who work the phones and canvass block by block, house by house, voter by voter. Ground Wars provides an in-depth ethnographic portrait of two...... infrastructures that utilize large databases with detailed individual-level information for targeting voters, and armies of dedicated volunteers and paid part-timers. Nielsen challenges the notion that political communication in America must be tightly scripted, controlled, and conducted by a select coterie...... of professionals. Yet he also quashes the romantic idea that canvassing is a purer form of grassroots politics. In today's political ground wars, Nielsen demonstrates, even the most ordinary-seeming volunteer knocking at your door is backed up by high-tech targeting technologies and party expertise. Ground Wars...

  13. Out-of-Sample Extensions for Non-Parametric Kernel Methods.

    Science.gov (United States)

    Pan, Binbin; Chen, Wen-Sheng; Chen, Bo; Xu, Chen; Lai, Jianhuang

    2017-02-01

    Choosing suitable kernels plays an important role in the performance of kernel methods. Recently, a number of studies were devoted to developing nonparametric kernels. Without assuming any parametric form of the target kernel, nonparametric kernel learning offers a flexible scheme to utilize the information of the data, which may potentially characterize the data similarity better. The kernel methods using nonparametric kernels are referred to as nonparametric kernel methods. However, many nonparametric kernel methods are restricted to transductive learning, where the prediction function is defined only over the data points given beforehand. They have no straightforward extension for the out-of-sample data points, and thus cannot be applied to inductive learning. In this paper, we show how to make the nonparametric kernel methods applicable to inductive learning. The key problem of out-of-sample extension is how to extend the nonparametric kernel matrix to the corresponding kernel function. A regression approach in the hyper reproducing kernel Hilbert space is proposed to solve this problem. Empirical results indicate that the out-of-sample performance is comparable to the in-sample performance in most cases. Experiments on face recognition demonstrate the superiority of our nonparametric kernel method over the state-of-the-art parametric kernel methods.

  14. D-Lactic acid production by Sporolactobacillus inulinus YBS1-5 with simultaneous utilization of cottonseed meal and corncob residue.

    Science.gov (United States)

    Bai, Zhongzhong; Gao, Zhen; Sun, Junfei; Wu, Bin; He, Bingfang

    2016-05-01

    d-Lactic acid, is an important organic acid produced from agro-industrial wastes by Sporolactobacillus inulinus YBS1-5 was investigated to reduce the raw material cost of fermentation. The YBS1-5 strain could produce d-lactic acid by using cottonseed meal as the sole nitrogen source. For efficient utilization, the cottonseed meal was enzymatically hydrolyzed and simultaneously utilized during d-lactic acid fermentation. Corncob residues are rich in cellulose and can be enzymatically hydrolyzed without pretreatment. The hydrolysate of this lignocellulosic waste could be utilized by strain YBS1-5 as a carbon source for d-lactic acid production. Under optimal conditions, a high d-lactic acid concentration (107.2g/L) was obtained in 7-L fed-batch fermenter, with an average productivity of 1.19g/L/h and a yield of 0.85g/g glucose. The optical purity of d-lactic acid in the broth was 99.2%. This study presented a new approach for low-cost production of d-lactic acid for an industrial application.

  15. Investigation of electron beam irradiation effects on anti-nutritional factors, chemical composition and digestion kinetics of whole cottonseed, soybean and canola seeds

    Energy Technology Data Exchange (ETDEWEB)

    Ebrahimi-Mahmoudabad, S.R., E-mail: ebrahimiyazd@yahoo.com [Department of Animal Science, Faculty of Agriculture, Shahr-e-Qods Branch, Islamic Azad University, P.O. Box 37515-374, Shahr-e-Qods (Iran, Islamic Republic of); Taghinejad-Roudbaneh, M. [Department of Animal Science, Faculty of Agriculture, Tabriz Branch, Islamic Azad University, P.O. Box 51589, Tabriz (Iran, Islamic Republic of)

    2011-12-15

    This study was completed to determine effects of electron beam (EB) irradiation at doses of 15, 30 and 45 kGy on anti-nutritional factors, ruminal degradation and in vitro crude protein (CP) digestibility of whole cottonseed (WCS), soybean (SB) and canola seeds (CS). EB-irradiation eliminated completely (P<0.001) phytic acid of WCS, SB and CS at a dose of 30 kGy. EB-irradiation decreased linearly (P<0.001) the total glucosinolate content of CS. Trypsin inhibitor activity of 15, 30 and 45 kGy EB-irradiated SB was decreased by 19, 73 and 88%, respectively. Free gossypol content of WCS was reduced linearly (P<0.001) by irradiation. EB-irradiation increased linearly (P<0.001) CP digestibility of feeds. In conclusion, EB-irradiation was an effective processing method for improving the nutritive value of WCS, SB and CS. - Highlights: > Effects of electron beam (EB) irradiation on nutritive value of some oilseeds were evaluated. > EB-irradiation eliminated completely phytic acid of seeds at a dose of 30 kGy. > EB-irradiation decreased trypsin inhibitor activity of soybean. > Free gossypol content of whole cottonseed was reduced linearly by EB-irradiation. > EB-irradiation increased escape protein and crude protein digestibility of seeds.

  16. Gabor-based kernel PCA with fractional power polynomial models for face recognition.

    Science.gov (United States)

    Liu, Chengjun

    2004-05-01

    This paper presents a novel Gabor-based kernel Principal Component Analysis (PCA) method by integrating the Gabor wavelet representation of face images and the kernel PCA method for face recognition. Gabor wavelets first derive desirable facial features characterized by spatial frequency, spatial locality, and orientation selectivity to cope with the variations due to illumination and facial expression changes. The kernel PCA method is then extended to include fractional power polynomial models for enhanced face recognition performance. A fractional power polynomial, however, does not necessarily define a kernel function, as it might not define a positive semidefinite Gram matrix. Note that the sigmoid kernels, one of the three classes of widely used kernel functions (polynomial kernels, Gaussian kernels, and sigmoid kernels), do not actually define a positive semidefinite Gram matrix either. Nevertheless, the sigmoid kernels have been successfully used in practice, such as in building support vector machines. In order to derive real kernel PCA features, we apply only those kernel PCA eigenvectors that are associated with positive eigenvalues. The feasibility of the Gabor-based kernel PCA method with fractional power polynomial models has been successfully tested on both frontal and pose-angled face recognition, using two data sets from the FERET database and the CMU PIE database, respectively. The FERET data set contains 600 frontal face images of 200 subjects, while the PIE data set consists of 680 images across five poses (left and right profiles, left and right half profiles, and frontal view) with two different facial expressions (neutral and smiling) of 68 subjects. The effectiveness of the Gabor-based kernel PCA method with fractional power polynomial models is shown in terms of both absolute performance indices and comparative performance against the PCA method, the kernel PCA method with polynomial kernels, the kernel PCA method with fractional power

  17. 固态发酵对棉籽粕脱毒效果的影响%Effect of Solid-state Fermentation on Virus-free of Cottonseed Meal

    Institute of Scientific and Technical Information of China (English)

    刘志勤; 彭博

    2011-01-01

    [Objective] The study aimed to optimize the conditions for the biological virus-free of cottonseed meal and decrease the free gossypol content in the cottonseed meal. [ Method] The solid state fermentation was performed by Aspergillus oryzae 3042 to degrade the free gossypol in the cottonseed meal. The effects of the inoculum size .fermentation temperature, solid-liquid ratio and fermentation time on the virus-free of cottonseed meal were studied and the optimum conditions for the biological virus-free of the cottonseed meal were confirmed through the single factor test and orthogonal test. [Result] The range analysis showed that the effects of 4 factors on the free gossypol content in the fermented cottonseed meal were in order of solid-liquid ratio > fermentation temperature > inoculum size > fermentation time. The orthogonal test showed that the optimal conditions for biological virus-free of of cottonseed meal were as follows:A oryzae 3042 inoculum size of 5% , cottonseed meal with addition of 0.5% urea and 1% sucrose, solid-liquid ratio of l:0. 8, fermentation temperature of 35 ℃ and time of 48 h. Under the conditions, the content of free gossypol reduced to 117 mg/kg and the ratio of degradation reached 78. 13% ; the crud protein content in the fermented cottonseed meal reached 40.16% ,being 12.87% higher than the one before the fermentation. [ Conclusion] The study offered the scientific basis for the production of the cottonseed meal feed that could meet the feeding standard.%[目的]优化棉籽粕微生物脱毒条件,降低棉籽粕中的游离棉酚含量.[方法]利用米曲霉3042固态发酵降解棉籽粕中的游离棉酚,通过单因素试验和正交试验,研究接菌量、发酵温度、料水比和发酵时间对棉籽粕脱毒的影响,确定棉籽粕微生物脱毒的最优脱毒条件.[结果]极差分析表明,影响发酵棉籽粕游离棉酚含量的4个因素主次顺序依次为料水比>发酵温度>接菌量>

  18. Local coding based matching kernel method for image classification.

    Directory of Open Access Journals (Sweden)

    Yan Song

    Full Text Available This paper mainly focuses on how to effectively and efficiently measure visual similarity for local feature based representation. Among existing methods, metrics based on Bag of Visual Word (BoV techniques are efficient and conceptually simple, at the expense of effectiveness. By contrast, kernel based metrics are more effective, but at the cost of greater computational complexity and increased storage requirements. We show that a unified visual matching framework can be developed to encompass both BoV and kernel based metrics, in which local kernel plays an important role between feature pairs or between features and their reconstruction. Generally, local kernels are defined using Euclidean distance or its derivatives, based either explicitly or implicitly on an assumption of Gaussian noise. However, local features such as SIFT and HoG often follow a heavy-tailed distribution which tends to undermine the motivation behind Euclidean metrics. Motivated by recent advances in feature coding techniques, a novel efficient local coding based matching kernel (LCMK method is proposed. This exploits the manifold structures in Hilbert space derived from local kernels. The proposed method combines advantages of both BoV and kernel based metrics, and achieves a linear computational complexity. This enables efficient and scalable visual matching to be performed on large scale image sets. To evaluate the effectiveness of the proposed LCMK method, we conduct extensive experiments with widely used benchmark datasets, including 15-Scenes, Caltech101/256, PASCAL VOC 2007 and 2011 datasets. Experimental results confirm the effectiveness of the relatively efficient LCMK method.

  19. Effect of Water Hyacinth (Eichhornia Crassipes) Silage on Intake and Nutrient Digestibility in Cattle Fed Rice Straw and Cottonseed Cake

    Science.gov (United States)

    Tham, Ho Thanh; Udén, Peter

    2013-01-01

    Four crossbred Sindhi heifers with an average body weight (BW) of 135 kg and a mean age of 17 months were used to investigate the effect of feeding different combinations of rice straw and ensiled water hyacinth (EWH) supplemented with a source of protein in the form of cottonseed cake (CSC) on intake and digestibility. Four treatments consisting of graded levels of EWH were arranged in a 4×4 Latin square. The levels of EWH were set at: 0 (EWH0), 15 (EWH15), 30 (EWH30), and 45% (EWH45) of an expected total dietary dry matter (DM) intake of 30 g total DM per kg BW per day. Rice straw was offered ad libitum, while CSC was given at a fixed level of 5 g DM/kg body weight (BW). Voluntary intake and digestibility were measured consecutively in the 4 experimental periods which each lasted 28 days. The crude protein (CP) content of EWH, rice straw and CSC were 174, 53 and 370 g/kg DM, respectively. Rice straw had the highest neutral detergent fibre (NDFom) content (666 g/kg DM), followed by EWH (503 g/kg DM) and the lowest content was 418 g/kg DM in the CSC. The actual EWH contents in the consumed diets were 0, 17, 32 and 52% for EWH0, EWH15, EWH30 and EWH45, respectively. Rice straw intake decreased with level of EWH offered from 3049 for EWH0 to 1014 g/day for EWH45. Crude protein intake was 16, 25 and 33% higher (p<0.001) in EWH15, EWH30 and EWH45 treatments, respectively, as compared to EWH0. Digestibility of organic matter (OM), CP, NDFom and acid detergent fibre (ADFom) increased with increasing level of EWH offered. The highest OM digestibility (72.2%) was found for treatment EWH45 and the lowest (47.4%) for treatment EWH0. In spite of similar dietary CP contents, CP digestibility increased by 21 (EWH15), 31 (EWH30) and 40% (EWH45) with increasing level of EWH in comparison with treatment EWH0. It is concluded that increasing level of EWH in cattle diets considerably improved CP intake and digestibility of nutrients. PMID:25049834

  20. Continuity properties of the semi-group and its integral kernel in non-relativistic QED

    Science.gov (United States)

    Matte, Oliver

    2016-07-01

    Employing recent results on stochastic differential equations associated with the standard model of non-relativistic quantum electrodynamics by B. Güneysu, J. S. Møller, and the present author, we study the continuity of the corresponding semi-group between weighted vector-valued Lp-spaces, continuity properties of elements in the range of the semi-group, and the pointwise continuity of an operator-valued semi-group kernel. We further discuss the continuous dependence of the semi-group and its integral kernel on model parameters. All these results are obtained for Kato decomposable electrostatic potentials and the actual assumptions on the model are general enough to cover the Nelson model as well. As a corollary, we obtain some new pointwise exponential decay and continuity results on elements of low-energetic spectral subspaces of atoms or molecules that also take spin into account. In a simpler situation where spin is neglected, we explain how to verify the joint continuity of positive ground state eigenvectors with respect to spatial coordinates and model parameters. There are no smallness assumptions imposed on any model parameter.