WorldWideScience

Sample records for ground cottonseed kernels

  1. Complex use of cottonseed kernels

    Energy Technology Data Exchange (ETDEWEB)

    Glushenkova, A I

    1977-01-01

    A review with 41 references is made on the manufacture of oil, protein, and other products from cottonseed, the effects of gossypol on protein yield and quality and technology of gossypol removal. A process eliminating thermal treatment of the kernels and permitting the production of oil, proteins, phytin, gossypol, sugar, sterols, phosphatides, tocopherols, and residual shells and baggase is described.

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

    Indian Academy of Sciences (India)

    (next to fiber) which serves as raw material for oil extraction or animal feed production ... systems that control the performance of these traits could facilitate the application of this information for cottonseed improvement that will help ensure ...

  3. Products from cottonseed

    Energy Technology Data Exchange (ETDEWEB)

    Glushenkova,

    1977-01-01

    A review with 41 references is made on the manufacture of oil, protein, and other products from cottonseed, the effects of gossypol on protein yield and quality and technology of gossypol removal. A process eliminating thermal treatment of the kernels and permitting the production of oil, proteins, phytin, gossypol, sugar, sterols, phosphatides, tocopherols, and residual shells and bagasse is described.

  4. 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.

  5. [Utilization of gossypol-free cottonseed and its by-products as human food].

    Science.gov (United States)

    Cornu, A; Delpeuch, F; Favier, J C

    1977-01-01

    Trials have principally turned on a glandless cottonseed flour, with 56 p. 100 of proteins. It is possible to blend it with millet or sorghum flour, and so to prepare the main meals of the local cooking. Trial of acceptability and long-dated consumption have shown that this flour is rather well appreciated especially in sauces. The growth of young children has been better thanks to the consumption of a cottonseed flour pap during six months. Trials to manufacture biscuits and noodles have been attempted. Kernels of cottonseed with 32 p. 100 of proteins and 33 p. 100 of lipids have been consumed with success. Four tons of kernels have been sold at the same price as sorghum in the area where the glandless cotton plant is under cultivation.

  6. 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.

  7. Interlaboratory study of DNA extraction from multiple ground samples, multiplex real-time PCR, and multiplex qualitative PCR for individual kernel detection system of genetically modified maize.

    Science.gov (United States)

    Akiyama, Hiroshi; Sakata, Kozue; Makiyma, Daiki; Nakamura, Kosuke; Teshima, Reiko; Nakashima, Akie; Ogawa, Asako; Yamagishi, Toru; Futo, Satoshi; Oguchi, Taichi; Mano, Junichi; Kitta, Kazumi

    2011-01-01

    In many countries, the labeling of grains, feed, and foodstuff is mandatory if the genetically modified (GM) organism content exceeds a certain level of approved GM varieties. We previously developed an individual kernel detection system consisting of grinding individual kernels, DNA extraction from the individually ground kernels, GM detection using multiplex real-time PCR, and GM event detection using multiplex qualitative PCR to analyze the precise commingling level and varieties of GM maize in real sample grains. We performed the interlaboratory study of the DNA extraction with multiple ground samples, multiplex real-time PCR detection, and multiplex qualitative PCR detection to evaluate its applicability, practicality, and ruggedness for the individual kernel detection system of GM maize. DNA extraction with multiple ground samples, multiplex real-time PCR, and multiplex qualitative PCR were evaluated by five laboratories in Japan, and all results from these laboratories were consistent with the expected results in terms of the commingling level and event analysis. Thus, the DNA extraction with multiple ground samples, multiplex real-time PCR, and multiplex qualitative PCR for the individual kernel detection system is applicable and practicable in a laboratory to regulate the commingling level of GM maize grain for GM samples, including stacked GM maize.

  8. Irrigation & Planting Date Effects on Cottonseed Composition

    Science.gov (United States)

    As bans on the use of trans-fats in restaurant cooking proliferate across the US, the restaurant industry is increasingly turning to cottonseed oil because of its desirable cooking qualities. Cottonseed meal is also increasingly being utilized as a feed supplement for dairy cattle. Therefore it’s ...

  9. 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.

  10. 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)

  11. Cottonseed oil and yield assessment via economic heterosis and ...

    African Journals Online (AJOL)

    user

    2010-11-01

    Nov 1, 2010 ... ISSN 1684–5315 ©2010 Academic Journals. Full Length ... Key words: Hybrid vigor, inbreeding depression, cottonseed traits, cottonseed oil, Gossypium hirsutum. ... in yield and superior performance than well-adapted.

  12. 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.

  13. Feeding of whole cottonseed on performance, carcass ...

    African Journals Online (AJOL)

    The present study was conducted to determine the effect of including different levels of whole cottonseed (WCS) in the finishing diet of lambs on their dry matter intake (DMI), live weight gain, feed conversion ratio (FCR, kg feed/kg gain), carcass characteristics and small intestinal morphology. Twenty Zandi male lambs (29.8 ...

  14. Extraction and Characterization of Cottonseed (Gossypium) Oil

    OpenAIRE

    Efomah Andrew Ndudi; Orhevba Bosede Adelola

    2012-01-01

    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 viscos...

  15. Angiotensin I-converting enzyme inhibitor derived from cottonseed ...

    African Journals Online (AJOL)

    Six proteolytic enzymes, including alcalase, flavourzyme, trypsin, neutrase, papain and pepsin, were employed to hydrolyze cottonseed protein to produce the hydrolysates of Angiotensin I-converting enzyme (ACE) inhibitory activity. The result indicated that the cottonseed protein hydrolysate (CPH) produced by papain had ...

  16. Characterization of cottonseed protein isolate as a paper additive

    Science.gov (United States)

    There is current interest in using agro-based biopolymers in industrial applications. Because cottonseed protein is abundantly available, it would be useful to explore its feasibility as a polymeric additive and possible substitute for petroleum-based materials. In this work we studied cottonseed ...

  17. Evaluation of biodiesel obtained from cottonseed oil

    Energy Technology Data Exchange (ETDEWEB)

    Rashid, Umer [Department of Chemistry and Biochemistry, University of Agriculture, Faisalabad-38040 (Pakistan); Department of Industrial Chemistry, Government College University, Faisalabad-38000 (Pakistan); Anwar, Farooq [Department of Chemistry and Biochemistry, University of Agriculture, Faisalabad-38040 (Pakistan); Knothe, Gerhard [United States Department of Agriculture, Agricultural Research Service, National Center for Agricultural Utilization Research, Peoria, IL 61604 (United States)

    2009-09-15

    Esters from vegetable oils have attracted a great deal of interest as substitutes for petrodiesel to reduce dependence on imported petroleum and provide a fuel with more benign environmental properties. In this work biodiesel was prepared from cottonseed oil by transesterification with methanol, using sodium hydroxide, potassium hydroxide, sodium methoxide and potassium methoxide as catalysts. A series of experiments were conducted in order to evaluate the effects of reaction variables such as methanol/oil molar ratio (3:1-15:1), catalyst concentration (0.25-1.50%), temperature (25-65 C), and stirring intensity (180-600 rpm) to achieve the maximum yield and quality. The optimized variables of 6:1 methanol/oil molar ratio (mol/mol), 0.75% sodium methoxide concentration (wt.%), 65 C reaction temperature, 600 rpm agitation speed and 90 min reaction time offered the maximum methyl ester yield (96.9%). The obtained fatty acid methyl esters (FAME) were analyzed by gas chromatography (GC) and {sup 1}H NMR spectroscopy. The fuel properties of cottonseed oil methyl esters (COME), cetane number, kinematic viscosity, oxidative stability, lubricity, cloud point, pour point, cold filter plugging point, flash point, ash content, sulfur content, acid value, copper strip corrosion value, density, higher heating value, methanol content, free and bound glycerol were determined and are discussed in the light of biodiesel standards such as ASTM D6751 and EN 14214. (author)

  18. 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...... 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...... (grinding or cracking). It is claimed that WCS have a greater retention time in the rumen, which results in an increased detoxifying activity, compared to a shorter ruminal retention time, in the case of cracked cottonseed or cottonseed meal products. Increased erythrocyte fragility has been observed...

  19. Surface characterization of cottonseed meal products by SEM, SEM-EDS, XRD and XPS analysis

    Science.gov (United States)

    The utilization of cottonseed meal as a valuable industrial feedstock needs to be exploited. We have recently produced water-washed cottonseed meal, total cottonseed protein, sequentially extracted water- and alkali-soluble proteins, and two residues after the total and sequential protein extraction...

  20. Chemical Composition of Defatted Cottonseed and Soy Meal Products

    Science.gov (United States)

    He, Zhongqi; Zhang, Hailin; Olk, Dan C.

    2015-01-01

    Chemical composition is critical information for product quality and exploration of new use. Hence defatted cottonseed meals from both glanded (with gossypol) and glandless (without gossypol) cotton seeds were separated into water soluble and insoluble fractions, or water soluble, alkali soluble as well as total protein isolates. The contents of gossypol, total protein and amino acids, fiber and carbohydrates, and selected macro and trace elements in these products were determined and compared with each other and with those of soy meal products. Data reported in this work improved our understanding on the chemical composition of different cottonseed meal products that is helpful for more economical utilization of these products. These data would also provide a basic reference for product standards and quality control when the production of the cottonseed meal products comes to pilot and industrial scales. PMID:26079931

  1. Carbaryl residues in cottonseed products in the Philippines

    International Nuclear Information System (INIS)

    Pablo, F.E.

    1981-01-01

    Residues of carbaryl in cottonseed products were determined by spectrophotometry. Carbaryl residues in oil and cake were 0.83 and 0.04 mg/kg respectively. Parallel experiments with 14 C-carbaryl gave comparable results. 14 C-carbaryl residues in oil and cake were 0.42 and 0.15 mg/kg respectively. (author)

  2. 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.

  3. Kernel based orthogonalization for change detection in hyperspectral images

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg

    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 MNF analyses handle nonlinearities by implicitly transforming data into high (even infinite) dimensional feature space via...... analysis all 126 spectral bands of the HyMap are included. Changes on the ground are most likely due to harvest having taken place between the two acquisitions and solar effects (both solar elevation and azimuth have changed). Both types of kernel analysis emphasize change and unlike kernel PCA, kernel MNF...

  4. Preparation and utilization of water washed cottonseed meal as wood adhesives

    Science.gov (United States)

    Cotton fiber and cottonseed are the two major products of cotton crop. The ratio of fiber and cotton is 100/150. Cotton fiber represents 85- 90% of cotton's total economic value. Thus, enhanced utilization of cottonseed products as industrial raw materials would greatly benefit cotton growers and pr...

  5. 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...

  6. 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. Copyright © 2014 Elsevier Ltd. All rights reserved.

  7. 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.

  8. Modification of Wastewater Treatment Technology at Cottonseed Oil Plant

    Directory of Open Access Journals (Sweden)

    Alshabab Mary Shick

    2016-01-01

    Full Text Available Wastewaters from cottonseed oil producing plant in Syria were studied in laboratory experiments. Aim of the study was to suggest modification of wastewater treatment technology in order to increase its efficiency. Concentration of pollutants in wastewaters was controlled by measurement of COD. According to the results of experiments it was suggested to decrease significantly (8-20 times dosages of reagents (acidifier, coagulant, flocculant in several actual stages of treatment (acidification, separation, coagulation and sedimentation and add stage of dispersed air flotation before coagulation treatment. The modified wastewater treatment technology would reduce COD to the values allowed for irrigation waters by Syrian National Standard.

  9. 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

  10. Optimized Kernel Entropy Components.

    Science.gov (United States)

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

    2017-06-01

    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.

  11. 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...... 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...

  12. 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`.

  13. 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

  14. Effectiveness of neutral detergent fiber in whole cottonseed and dried distillers grains compared with alfalfa haylage.

    Science.gov (United States)

    Clark, P W; Armentano, L E

    1993-09-01

    Sixteen Holstein cows in midlactation were used in a 4 x 4 Latin square design to determine the effect of replacing alfalfa NDF with NDF from whole, linted cottonseed or dried distillers grains. Low and high fiber control diets (13 and 19% of dietary DM from alfalfa haylage NDF, respectively) were compared with diets designed to contain 13% of DM from alfalfa haylage NDF plus 6% of DM from either cottonseed NDF or distillers grains NDF. Dry matter intake, milk yield, and milk protein yield were lower from the high fiber control diet. Milk fat percentage was lower for the low fiber control diet. The cottonseed diet was equal to the high fiber control diet in stimulating rumination. Rumen acetate to propionate ratio was higher for the high fiber control and cottonseed diets. Replacing alfalfa with either of these high fiber by-product feeds increased feed intake and yields of milk fat and protein. The effectiveness of the NDF in distillers grains and cottonseed was not significantly different from that of alfalfa NDF for maintaining milk fat yield. Whole cottonseed and dried distillers grains appear to be good sources of effective fiber for maintaining milk fat test when they are substituted for alfalfa haylage fiber in lactating cow rations.

  15. 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

  16. Classification With Truncated Distance Kernel.

    Science.gov (United States)

    Huang, Xiaolin; Suykens, Johan A K; Wang, Shuning; Hornegger, Joachim; Maier, Andreas

    2018-05-01

    This brief proposes a truncated distance (TL1) kernel, which results in a classifier that is nonlinear in the global region but is linear in each subregion. With this kernel, the subregion structure can be trained using all the training data and local linear classifiers can be established simultaneously. The TL1 kernel has good adaptiveness to nonlinearity and is suitable for problems which require different nonlinearities in different areas. Though the TL1 kernel is not positive semidefinite, some classical kernel learning methods are still applicable which means that the TL1 kernel can be directly used in standard toolboxes by replacing the kernel evaluation. In numerical experiments, the TL1 kernel with a pregiven parameter achieves similar or better performance than the radial basis function kernel with the parameter tuned by cross validation, implying the TL1 kernel a promising nonlinear kernel for classification tasks.

  17. 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

  18. Effects of Particle Size on the Morphology and Water- and Thermo-Resistance of Washed Cottonseed Meal-Based Wood Adhesives

    Directory of Open Access Journals (Sweden)

    Zhongqi He

    2017-12-01

    Full Text Available Water washing of cottonseed meal is more cost-efficient and environmentally friendly than protein isolation by means of alkaline extraction and acidic precipitation. Thus, water-washed cottonseed meal (WCSM is more promising as biobased wood adhesives. In this work, we examined the effects of the particle size on the morphology and adhesive performance of WCSM. Pilot-scale produced and dried WCSM was treated by three grinding methods: (1 ground by a hammer mill and passed through a 0.5-mm screen, (2 further ground by a cyclone mill and passed through a 0.5-mm screen, or (3 further ground by a ball mill and passed through a 0.18-mm screen. Micro-morphological examination revealed two types of particles. The filament-like particles were mainly fibrous materials from residual linters. Chunk-like particles were more like aggregates or accumulations of small particles, with proteins as the major component. Further grinding of the 0.5-mm Hammer product with the Cyclone and Ball mill led to more fine (smaller particles in the WCSM products. The impact of further grinding on the dry and soaked adhesive strengths was minimal. However, the decrease of the hot and wet strengths of WCSM products by the additional grinding was significant (p ≤ 0.05. Data presented in this work is useful in developing the industrial standards of WCSM products used in wood bonding.

  19. 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 capab...

  20. 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

  1. 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...

  2. Physicochemical and functional properties of protein isolate obtained from cottonseed meal.

    Science.gov (United States)

    Ma, Mengting; Ren, Yanjing; Xie, Wei; Zhou, Dayun; Tang, Shurong; Kuang, Meng; Wang, Yanqin; Du, Shuang-Kui

    2018-02-01

    To investigate the effect of preparation methods of cottonseed meals on protein properties, the physicochemical and functional properties of proteins isolated from hot-pressed solvent extraction cottonseed meal (HCM), cold-pressed solvent extraction cottonseed meal (CCM) and subcritical fluid extraction cottonseed meal (SCM) were investigated. Cottonseed proteins had two major bands (at about 45 and 50kD), two X-ray diffraction peaks (8.5° and 19.5°) and one endothermic peak (94.31°C-97.72°C). Proteins of HCM showed relatively more β-sheet (38.3%-40.5%), and less β-turn (22.2%-25.8%) and α-helix (15.8%-19.5%), indicating the presence of highly denatured protein molecules. Proteins of CCM and SCM exhibited high water/oil absorption capacity, emulsifying abilities, surface hydrophobicity and fluorescence intensity, suggesting that the proteins have potential as functional ingredients in the food industry. Copyright © 2017 Elsevier Ltd. All rights reserved.

  3. 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.

  4. 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...

  5. Effects of particle size on the morphology and waterand thermo-resistance of washed cottonseed meal-based wood adhesives

    Science.gov (United States)

    Water wash of cottonseed meal is more cost-efficient and environment-friendly than the protein isolation which involves alkaline extraction and acidic precipitation. Thus, water-washed cottonseed meal (WCSM) is more promising as biobased wood adhesives. In this work, we examined the effects of the p...

  6. Production of furfural and ethyl alcohol from cottonseed hulls

    Energy Technology Data Exchange (ETDEWEB)

    Bobovnikov, B M; Tsirlin, Yu A; Chepigo, S V; Shpuntova, M E

    1957-01-01

    Cottonseed hulls (8.3 tons per digester) and H/sub 2/SO/sub 4/ solution at temperature of 100/sup 0/ were added to the digester simultaneously. The final H/sub 2/SO/sub 4/ concentration of the charge was approximately 0.7%. The pentosans were hydrolyzed at 133/sup 0/ and 2 atmosphere for 6 hours and 15 minutes, then the temperature was raised to 179/sup 0/ at the top and to 150/sup 0/ at the bottom of the digester for 5 hours and 30 minutes. The hydrolytic products of pentosan were separated, neutralized, and transferred to a dehydration tank. The hexosans were then hydrolyzed at 179 to 187/sup 0/. Dry hulls gave 19.4% of pentose reducing sugars, of which 81.4% were fermented. One ton of dry hulls gave 74 to 79 l. of ethanol. The optimum condition for dehydration was at 165 to 175/sup 0/ for no longer than 4 to 4.5 hours. 2-Furaldehyde was produced in the following steps: the pentosan hydrolyzate was dehydrated with steam, the vapor-furaldehyde mixture was then reheated and finally distilled in a continuous column. The yield of furaldehyde was 36 to 37% of incoming pentoses (7% of dry hulls).

  7. 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 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.

  8. Realized kernels in practice

    DEFF Research Database (Denmark)

    Barndorff-Nielsen, Ole Eiler; Hansen, P. Reinhard; Lunde, Asger

    2009-01-01

    and find a remarkable level of agreement. We identify some features of the high-frequency data, which are challenging for realized kernels. They are when there are local trends in the data, over periods of around 10 minutes, where the prices and quotes are driven up or down. These can be associated......Realized kernels use high-frequency data to estimate daily volatility of individual stock prices. They can be applied to either trade or quote data. Here we provide the details of how we suggest implementing them in practice. We compare the estimates based on trade and quote data for the same stock...

  9. Adaptive metric kernel regression

    DEFF Research Database (Denmark)

    Goutte, Cyril; Larsen, Jan

    2000-01-01

    Kernel smoothing is a widely used non-parametric pattern recognition technique. By nature, it suffers from the curse of dimensionality and is usually difficult to apply to high input dimensions. In this contribution, we propose an algorithm that adapts the input metric used in multivariate...... 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...

  10. Adaptive Metric Kernel Regression

    DEFF Research Database (Denmark)

    Goutte, Cyril; Larsen, Jan

    1998-01-01

    Kernel smoothing is a widely used nonparametric pattern recognition technique. By nature, it suffers from the curse of dimensionality and is usually difficult to apply to high input dimensions. In this paper, we propose an algorithm that adapts the input metric used in multivariate regression...... 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...

  11. Kernel methods for deep learning

    OpenAIRE

    Cho, Youngmin

    2012-01-01

    We introduce a new family of positive-definite kernels that mimic the computation in large neural networks. We derive the different members of this family by considering neural networks with different activation functions. Using these kernels as building blocks, we also show how to construct other positive-definite kernels by operations such as composition, multiplication, and averaging. We explore the use of these kernels in standard models of supervised learning, such as support vector mach...

  12. Multivariate realised kernels

    DEFF Research Database (Denmark)

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

    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 noise of certain types and can also handle non-synchronous trading. It is the first estimator...

  13. 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...

  14. Kernel structures for Clouds

    Science.gov (United States)

    Spafford, Eugene H.; Mckendry, Martin S.

    1986-01-01

    An overview of the internal structure of the Clouds kernel was presented. An indication of how these structures will interact in the prototype Clouds implementation is given. Many specific details have yet to be determined and await experimentation with an actual working system.

  15. Coupling individual kernel-filling processes with source-sink interactions into GREENLAB-Maize.

    Science.gov (United States)

    Ma, Yuntao; Chen, Youjia; Zhu, Jinyu; Meng, Lei; Guo, Yan; Li, Baoguo; Hoogenboom, Gerrit

    2018-02-13

    Failure to account for the variation of kernel growth in a cereal crop simulation model may cause serious deviations in the estimates of crop yield. The goal of this research was to revise the GREENLAB-Maize model to incorporate source- and sink-limited allocation approaches to simulate the dry matter accumulation of individual kernels of an ear (GREENLAB-Maize-Kernel). The model used potential individual kernel growth rates to characterize the individual potential sink demand. The remobilization of non-structural carbohydrates from reserve organs to kernels was also incorporated. Two years of field experiments were conducted to determine the model parameter values and to evaluate the model using two maize hybrids with different plant densities and pollination treatments. Detailed observations were made on the dimensions and dry weights of individual kernels and other above-ground plant organs throughout the seasons. Three basic traits characterizing an individual kernel were compared on simulated and measured individual kernels: (1) final kernel size; (2) kernel growth rate; and (3) duration of kernel filling. Simulations of individual kernel growth closely corresponded to experimental data. The model was able to reproduce the observed dry weight of plant organs well. Then, the source-sink dynamics and the remobilization of carbohydrates for kernel growth were quantified to show that remobilization processes accompanied source-sink dynamics during the kernel-filling process. We conclude that the model may be used to explore options for optimizing plant kernel yield by matching maize management to the environment, taking into account responses at the level of individual kernels. © The Author(s) 2018. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  16. 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...

  17. Two approaches in preparation for cogeneration alpha-tocopherol and biodiesel from cottonseed

    Energy Technology Data Exchange (ETDEWEB)

    Zhu, Q.-L.; Zang, L.-Y.; Zhang, L.; Yun, Z. [Nanjing University of Technology (China)

    2012-02-15

    Vitamin E is a group of lipid soluble antioxidants that is widely used in the food, cosmetic and medical industries. It is comprised of four tocopherols and four tocotrienols, i.e. alpha, beta, gamma and delta, which are characterized by a chromanol ring structure with a distinct substitution pattern of methyl groups. This paper presents two approaches in preparation for co-generation of alpha-tocopherol and biodiesel from cottonseed. The approaches are a two-step process and a direct alkaline trans-esterification process. Using single factor experiments and an orthogonal design method, the effects of certain factors on the alpha-tocopherol recovery and conversion of cottonseed oil to biodiesel in both processes was systematically studied. In the two-step process, biodiesel and alpha-tocopherol were produced using a two-phase solvent combined with base-catalyzed trans-esterification. It was observed that 95.5% cottonseed oil was converted to biodiesel. In the direct-alkaline trans-esterification process, 98.3% cottonseed oil was converted to biodiesel.

  18. Non-destructive measurements of cottonseed nutritional trait diversity in the US National Cotton Germplasm Collection

    Science.gov (United States)

    Recent studies have suggested that cottonseed (Gossypium spp.) has the potential to contribute to the effort against world hunger, particularly by providing a high-quality protein source. This report analyzed the diversity in protein content and other seed quality factors in the U.S. National Cotton...

  19. 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...

  20. 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...

  1. 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...

  2. 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)

  3. Variable Kernel Density Estimation

    OpenAIRE

    Terrell, George R.; Scott, David W.

    1992-01-01

    We investigate some of the possibilities for improvement of univariate and multivariate kernel density estimates by varying the window over the domain of estimation, pointwise and globally. Two general approaches are to vary the window width by the point of estimation and by point of the sample observation. The first possibility is shown to be of little efficacy in one variable. In particular, nearest-neighbor estimators in all versions perform poorly in one and two dimensions, but begin to b...

  4. Steerability of Hermite Kernel

    Czech Academy of Sciences Publication Activity Database

    Yang, Bo; Flusser, Jan; Suk, Tomáš

    2013-01-01

    Roč. 27, č. 4 (2013), 1354006-1-1354006-25 ISSN 0218-0014 R&D Projects: GA ČR GAP103/11/1552 Institutional support: RVO:67985556 Keywords : Hermite polynomials * Hermite kernel * steerability * adaptive filtering Subject RIV: JD - Computer Applications, Robotics Impact factor: 0.558, year: 2013 http://library.utia.cas.cz/separaty/2013/ZOI/yang-0394387. pdf

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

    OpenAIRE

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

    2016-01-01

    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 distributi...

  6. Kernel Machine SNP-set Testing under Multiple Candidate Kernels

    Science.gov (United States)

    Wu, Michael C.; Maity, Arnab; Lee, Seunggeun; Simmons, Elizabeth M.; Harmon, Quaker E.; Lin, Xinyi; Engel, Stephanie M.; Molldrem, Jeffrey J.; Armistead, Paul M.

    2013-01-01

    Joint testing for the cumulative effect of multiple single nucleotide polymorphisms grouped on the basis of prior biological knowledge has become a popular and powerful strategy for the analysis of large scale genetic association studies. The kernel machine (KM) testing framework is a useful approach that has been proposed for testing associations between multiple genetic variants and many different types of complex traits by comparing pairwise similarity in phenotype between subjects to pairwise similarity in genotype, with similarity in genotype defined via a kernel function. An advantage of the KM framework is its flexibility: choosing different kernel functions allows for different assumptions concerning the underlying model and can allow for improved power. In practice, it is difficult to know which kernel to use a priori since this depends on the unknown underlying trait architecture and selecting the kernel which gives the lowest p-value can lead to inflated type I error. Therefore, we propose practical strategies for KM testing when multiple candidate kernels are present based on constructing composite kernels and based on efficient perturbation procedures. We demonstrate through simulations and real data applications that the procedures protect the type I error rate and can lead to substantially improved power over poor choices of kernels and only modest differences in power versus using the best candidate kernel. PMID:23471868

  7. Gaseous emissions from burning diesel, crude and prime bleachable summer yellow cottonseed oil in a burner for drying seedcotton

    International Nuclear Information System (INIS)

    Holt, G.A.; Hooker, J.D.

    2004-01-01

    Cottonseed oil has been used as a fuel source either as a blend with diesel in varying proportions or undiluted (100 %) in numerous studies evaluating its potential use in internal combustion engines. However, limited research is available on the use of cottonseed oil as a fuel source in a multi-fueled burner similar to those used by cottonseed oil mills and cotton gins in their drying operations. The purpose of this study was to evaluate emissions from five fuel oil treatments while firing a multi-fueled burner in a setup similar to those used for drying operations of both cottonseed oil mills and cotton gins. For each treatment, gaseous emissions were measured while firing the burner at three fuel flow rates. The five fuel oil treatments evaluated were: (1) No.2 diesel at 28.3 deg C, (2) prime bleachable summer yellow (PBSY) cottonseed oil at 28.3 deg C (PBSY-28), (3) crude cottonseed oil at 28.3 deg C (Crude-28), (4) PBSY at 60 deg C (PBSY-60), and (5) crude at 60 deg C (Crude-60). Results indicate that PBSY treatments had the lowest overall emissions of all treatments. The other treatments varied in emission rates based on treatment and fuel flow rate. Preheating the oil to 60 deg C resulted in higher NO x emissions but displayed varying results in regards to CO. The CO emissions for the crude treatments were relatively unaffected by the 60 deg C preheat temperature whereas the preheated PBSY treatments demonstrated lower CO emissions. Overall, both cottonseed oils performed well in the multi-fueled burner and displayed a promising potential as an alternative fuel source for cottonseed oil mills and cotton gins in their drying operations. (Author)

  8. Identification of candidate genes from the SAD gene family in cotton for determination of cottonseed oil composition.

    Science.gov (United States)

    Shang, Xiaoguang; Cheng, Chaoze; Ding, Jian; Guo, Wangzhen

    2017-02-01

    Cotton is an economically important crop grown for natural fiber and seed oil production. Cottonseed oil ranks third after soybean oil and colza oil in terms of edible oilseed tonnage worldwide. The fatty acid composition of cottonseed oil determines its industrial application and nutritional values. However, little progress has been made in understanding cottonseed oil biogenesis. Stearoyl-acyl carrier protein desaturase (SAD), the only known enzyme to convert saturated fatty acids into unsaturated fatty acids in plants, plays key roles in determining the fatty acid composition of cottonseed oil. In this study, we identified 9, 9, 18 and 19 SAD genes in the genomes of four sequenced cotton species: diploid Gossypium raimondii (D 5 ), G. arboreum (A 2 ), tetraploid G. hirsutum acc. TM-1 (AD 1 ) and G. barbadense cv. Xinhai21 (AD 2 ), respectively. Bioinformatic and phylogenetic analyses revealed that cotton SADs can be classified into two classes. Expression patterns showed developmental and spatial regulation of SADs in cotton. GhSAD2 and GhSAD4 were preferentially expressed in developing ovules 20-35 days post-anthesis, and significantly different expression patterns were found between high-oil and low-oil cotton cultivars, implying these two genes could be involved in cottonseed oil biogenesis. Association analysis further confirmed that GhSAD4-At expression was closely related to the oleic acid (O) content, linoleic acid (L) content and O/L value in cottonseed, implying GhSAD4 plays an important role in cottonseed oil composition. This study brings new perspectives for integrated genome-wide identification of SADs in cotton and provides references for the genetic improvement of cottonseed oil.

  9. The definition of kernel Oz

    OpenAIRE

    Smolka, Gert

    1994-01-01

    Oz is a concurrent language providing for functional, object-oriented, and constraint programming. This paper defines Kernel Oz, a semantically complete sublanguage of Oz. It was an important design requirement that Oz be definable by reduction to a lean kernel language. The definition of Kernel Oz introduces three essential abstractions: the Oz universe, the Oz calculus, and the actor model. The Oz universe is a first-order structure defining the values and constraints Oz computes with. The ...

  10. 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. [41 FR 26852, June 30, 1976] ...

  11. 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 as...

  12. 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, or...

  13. 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...... which has these three properties which are all essential for empirical work in this area. We derive the large sample asymptotics of this estimator and assess its accuracy using a Monte Carlo study. We implement the estimator on some US equity data, comparing our results to previous work which has used...

  14. 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....

  15. 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...

  16. 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)

  17. Biodiesel production from crude cottonseed oil: an optimization process using response surface methodology

    Energy Technology Data Exchange (ETDEWEB)

    Fan, Xiaohu; Wang, Xi; Chen, Feng

    2011-07-01

    As the depletion of fossil resources continues, the demand for environmentally friendly sources of energy as biodiesel is increasing. Biodiesel is the resulting fatty acid methyl ester (FAME) from an esterification reaction. The use of cottonseed oil to produce biodiesel has been investigated in recent years, but it is difficult to find the optimal conditions of this process since multiple factors are involved. The aim of this study was to optimize the transesterification of cottonseed oil with methanol to produce biodiesel. A response surface methodology (RSM), an experimental method to seek optimal conditions for a multivariable system and reverse phase HPLC was used to analyze the conversion of triglyceride into biodiesel. RSM was successfully applied and the optimal condition was found with a 97% yield.

  18. 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.

  19. 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.

  20. Robotic intelligence kernel

    Science.gov (United States)

    Bruemmer, David J [Idaho Falls, ID

    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.

  1. 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.

  2. 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...

  3. 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, including...

  4. 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. ...

  5. 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...

  6. kernel oil by lipolytic organisms

    African Journals Online (AJOL)

    USER

    2010-08-02

    Aug 2, 2010 ... Rancidity of extracted cashew oil was observed with cashew kernel stored at 70, 80 and 90% .... method of American Oil Chemist Society AOCS (1978) using glacial ..... changes occur and volatile products are formed that are.

  7. Multivariate and semiparametric kernel regression

    OpenAIRE

    Härdle, Wolfgang; Müller, Marlene

    1997-01-01

    The paper gives an introduction to theory and application of multivariate and semiparametric kernel smoothing. Multivariate nonparametric density estimation is an often used pilot tool for examining the structure of data. Regression smoothing helps in investigating the association between covariates and responses. We concentrate on kernel smoothing using local polynomial fitting which includes the Nadaraya-Watson estimator. Some theory on the asymptotic behavior and bandwidth selection is pro...

  8. 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....

  9. 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 (Pdigestibility (%) of protein and energy with the cottonseed meal and sorghum/cottonseed meal-based diets 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 (Pdigestibility of protein in sorghum and millet-based diets 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 (Pdigestibility of starch were obtained with the control diet 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.

  10. Influence Function and Robust Variant of Kernel Canonical Correlation Analysis

    OpenAIRE

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

    2017-01-01

    Many unsupervised kernel methods rely on the estimation of the kernel covariance operator (kernel CO) or kernel cross-covariance operator (kernel CCO). Both kernel CO and kernel CCO are sensitive to contaminated data, even when bounded positive definite kernels are used. To the best of our knowledge, there are few well-founded robust kernel methods for statistical unsupervised learning. In addition, while the influence function (IF) of an estimator can characterize its robustness, asymptotic ...

  11. 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. 

  12. 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...

  13. 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.

  14. 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...

  15. 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.

  16. 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

  17. 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...

  18. RTOS kernel in portable electrocardiograph

    Science.gov (United States)

    Centeno, C. A.; Voos, J. A.; Riva, G. G.; Zerbini, C.; Gonzalez, E. A.

    2011-12-01

    This paper presents the use of a Real Time Operating System (RTOS) on a portable electrocardiograph based on a microcontroller platform. All medical device digital functions are performed by the microcontroller. The electrocardiograph CPU is based on the 18F4550 microcontroller, in which an uCOS-II RTOS can be embedded. The decision associated with the kernel use is based on its benefits, the license for educational use and its intrinsic time control and peripherals management. The feasibility of its use on the electrocardiograph is evaluated based on the minimum memory requirements due to the kernel structure. The kernel's own tools were used for time estimation and evaluation of resources used by each process. After this feasibility analysis, the migration from cyclic code to a structure based on separate processes or tasks able to synchronize events is used; resulting in an electrocardiograph running on one Central Processing Unit (CPU) based on RTOS.

  19. RTOS kernel in portable electrocardiograph

    International Nuclear Information System (INIS)

    Centeno, C A; Voos, J A; Riva, G G; Zerbini, C; Gonzalez, E A

    2011-01-01

    This paper presents the use of a Real Time Operating System (RTOS) on a portable electrocardiograph based on a microcontroller platform. All medical device digital functions are performed by the microcontroller. The electrocardiograph CPU is based on the 18F4550 microcontroller, in which an uCOS-II RTOS can be embedded. The decision associated with the kernel use is based on its benefits, the license for educational use and its intrinsic time control and peripherals management. The feasibility of its use on the electrocardiograph is evaluated based on the minimum memory requirements due to the kernel structure. The kernel's own tools were used for time estimation and evaluation of resources used by each process. After this feasibility analysis, the migration from cyclic code to a structure based on separate processes or tasks able to synchronize events is used; resulting in an electrocardiograph running on one Central Processing Unit (CPU) based on RTOS.

  20. 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....

  1. 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.

  2. Ambient Temperature Flotation of Sedimentary Phosphate Ore Using Cottonseed Oil as a Collector

    Directory of Open Access Journals (Sweden)

    Yaoyang Ruan

    2017-04-01

    Full Text Available The mid-low grade sedimentary phosphate ore, abundant in silicate and carbonate gangue minerals, exhibits a poor processability. It is conventionally enriched using high temperature flotation to remove silicate gangues with fatty acid as a collector. Cottonseed oil has been proved to be an efficient collector for achieving ambient temperature flotation of the sedimentary phosphate ore used in this study. Flotation kinetics was investigated to ascertain the excellent collecting performance of cottonseed oil, as compared with oleic acid, and the phosphate flotation fitted well with the first-order flotation model. Based on the analysis of flotation reagent effect on the direct flotation process using the response surface methodology (RSM, a closed circuit of direct-reverse flotation for stepwise removing silicate and carbonate gangues from the sedimentary phosphate ore was established. Consequently, a required high quality of phosphate concentrate containing 30.16% P2O5 was obtained, with a recovery of 90.90%. Scanning electron microscopy (SEM and X-ray diffraction analysis (XRD of the flotation products confirmed that the majority of silicate and carbonate gangues were effectively removed from the concentrate products.

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

    International Nuclear Information System (INIS)

    Zhou Qi; Gong Wenqi; Xie Chuanxin; Yang Dongjiang; Ling Xiaoqing; Yuan Xiao; Chen Shaohua; Liu Xiaofang

    2011-01-01

    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 ΔG o , ΔH o and ΔS 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.

  4. 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...

  5. 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.

  6. 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...

  7. 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...

  8. Desempenho e espermatogênese de alevinos de tilápia alimentados com farelo ou farinha de semente de algodão Performance and spermatogenesis of nile tilapia fingerlings fed with cottonseed meal or cottonseed flour

    Directory of Open Access Journals (Sweden)

    Ana Lúcia Salaro

    1999-03-01

    Full Text Available Este trabalho avaliou o efeito do farelo e da farinha de semente de algodão no ganho de peso e na atividade testicular de alevinos de tilápia-do-nilo (Oreochromis niloticus. Cento e cinqüenta alevinos com peso médio inicial de 1,26 g foram mantidos em aquários de 45 L, com renovação contínua d'água, e alimentados por 120 dias com dietas isoprotéicas (28% PB e isocalóricas (4.030 kcal EB/kg de ração contendo 0%, 2%, 4% e 6% de semente de algodão descorticada e moída, e 24% de farelo de algodão. Foi observado que os níveis avaliados interferem na atividade testicular, diminuindo a espermatogênese, embora não tenham comprometido de forma significativa o ganho de peso dos alevinos.This experiment evaluated the effect of cottonseed meal or cottonseed flour on growth and testis activity of Nile tilapia fingerlings (Oreochromis niloticus. One hundred and fifty fingerlings with mean initial weight of 1.26 g were maintained in 45 L aquaria with continuous water supply. Fish were fed in isoproteic (28% CP and isoenergetic (4,030 kcal CE/kg of ration diets during 120 days. The experimental diets comprised a control diet, without cottonseed flour or meal, and diets containing 2%, 4% and 6% of cottonseed flour and 24% cottonseed meal. The results indicated that the use of seed flour or meal should be limited since at the tested levels they interferred with testis activity although they had not adversely affected the weight gain of fingerlings.

  9. 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...

  10. Multiple Kernel Learning with Data Augmentation

    Science.gov (United States)

    2016-11-22

    JMLR: Workshop and Conference Proceedings 63:49–64, 2016 ACML 2016 Multiple Kernel Learning with Data Augmentation Khanh Nguyen nkhanh@deakin.edu.au...University, Australia Editors: Robert J. Durrant and Kee-Eung Kim Abstract The motivations of multiple kernel learning (MKL) approach are to increase... kernel expres- siveness capacity and to avoid the expensive grid search over a wide spectrum of kernels . A large amount of work has been proposed to

  11. 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....

  12. A novel adaptive kernel method with kernel centers determined by a support vector regression approach

    NARCIS (Netherlands)

    Sun, L.G.; De Visser, C.C.; Chu, Q.P.; Mulder, J.A.

    2012-01-01

    The optimality of the kernel number and kernel centers plays a significant role in determining the approximation power of nearly all kernel methods. However, the process of choosing optimal kernels is always formulated as a global optimization task, which is hard to accomplish. Recently, an

  13. 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.

  14. Kernel regression with functional response

    OpenAIRE

    Ferraty, Frédéric; Laksaci, Ali; Tadj, Amel; Vieu, Philippe

    2011-01-01

    We consider kernel regression estimate when both the response variable and the explanatory one are functional. The rates of uniform almost complete convergence are stated as function of the small ball probability of the predictor and as function of the entropy of the set on which uniformity is obtained.

  15. GRIM : Leveraging GPUs for Kernel integrity monitoring

    NARCIS (Netherlands)

    Koromilas, Lazaros; Vasiliadis, Giorgos; Athanasopoulos, Ilias; Ioannidis, Sotiris

    2016-01-01

    Kernel rootkits can exploit an operating system and enable future accessibility and control, despite all recent advances in software protection. A promising defense mechanism against rootkits is Kernel Integrity Monitor (KIM) systems, which inspect the kernel text and data to discover any malicious

  16. Paramecium: An Extensible Object-Based Kernel

    NARCIS (Netherlands)

    van Doorn, L.; Homburg, P.; Tanenbaum, A.S.

    1995-01-01

    In this paper we describe the design of an extensible kernel, called Paramecium. This kernel uses an object-based software architecture which together with instance naming, late binding and explicit overrides enables easy reconfiguration. Determining which components reside in the kernel protection

  17. 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…

  18. Veto-Consensus Multiple Kernel Learning

    NARCIS (Netherlands)

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

    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

  19. 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.

  20. Viscozyme L pretreatment on palm kernels improved the aroma of palm kernel oil after kernel roasting.

    Science.gov (United States)

    Zhang, Wencan; Leong, Siew Mun; Zhao, Feifei; Zhao, Fangju; Yang, Tiankui; Liu, Shaoquan

    2018-05-01

    With an interest to enhance the aroma of palm kernel oil (PKO), Viscozyme L, an enzyme complex containing a wide range of carbohydrases, was applied to alter the carbohydrates in palm kernels (PK) to modulate the formation of volatiles upon kernel roasting. After Viscozyme treatment, the content of simple sugars and free amino acids in PK increased by 4.4-fold and 4.5-fold, respectively. After kernel roasting and oil extraction, significantly more 2,5-dimethylfuran, 2-[(methylthio)methyl]-furan, 1-(2-furanyl)-ethanone, 1-(2-furyl)-2-propanone, 5-methyl-2-furancarboxaldehyde and 2-acetyl-5-methylfuran but less 2-furanmethanol and 2-furanmethanol acetate were found in treated PKO; the correlation between their formation and simple sugar profile was estimated by using partial least square regression (PLS1). Obvious differences in pyrroles and Strecker aldehydes were also found between the control and treated PKOs. Principal component analysis (PCA) clearly discriminated the treated PKOs from that of control PKOs on the basis of all volatile compounds. Such changes in volatiles translated into distinct sensory attributes, whereby treated PKO was more caramelic and burnt after aqueous extraction and more nutty, roasty, caramelic and smoky after solvent extraction. Copyright © 2018 Elsevier Ltd. All rights reserved.

  1. Wigner functions defined with Laplace transform kernels.

    Science.gov (United States)

    Oh, Se Baek; Petruccelli, Jonathan C; Tian, Lei; Barbastathis, George

    2011-10-24

    We propose a new Wigner-type phase-space function using Laplace transform kernels--Laplace kernel Wigner function. Whereas momentum variables are real in the traditional Wigner function, the Laplace kernel Wigner function may have complex momentum variables. Due to the property of the Laplace transform, a broader range of signals can be represented in complex phase-space. We show that the Laplace kernel Wigner function exhibits similar properties in the marginals as the traditional Wigner function. As an example, we use the Laplace kernel Wigner function to analyze evanescent waves supported by surface plasmon polariton. © 2011 Optical Society of America

  2. 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.

  3. Credit scoring analysis using kernel discriminant

    Science.gov (United States)

    Widiharih, T.; Mukid, M. A.; Mustafid

    2018-05-01

    Credit scoring model is an important tool for reducing the risk of wrong decisions when granting credit facilities to applicants. This paper investigate the performance of kernel discriminant model in assessing customer credit risk. Kernel discriminant analysis is a non- parametric method which means that it does not require any assumptions about the probability distribution of the input. The main ingredient is a kernel that allows an efficient computation of Fisher discriminant. We use several kernel such as normal, epanechnikov, biweight, and triweight. The models accuracy was compared each other using data from a financial institution in Indonesia. The results show that kernel discriminant can be an alternative method that can be used to determine who is eligible for a credit loan. In the data we use, it shows that a normal kernel is relevant to be selected for credit scoring using kernel discriminant model. Sensitivity and specificity reach to 0.5556 and 0.5488 respectively.

  4. 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....

  5. Kernel parameter dependence in spatial factor analysis

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg

    2010-01-01

    kernel PCA. Shawe-Taylor and Cristianini [4] is an excellent reference for kernel methods in general. Bishop [5] and Press et al. [6] describe kernel methods among many other subjects. 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 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...... of the kernel width. The 2,097 samples each covering on average 5 km2 are analyzed chemically for the content of 41 elements....

  6. Residues in cottonseed oil and cake resulting from the combined application of DDT and dimethoate

    International Nuclear Information System (INIS)

    El Zorgani, G.A.; Ahmed, M.M.

    1981-01-01

    Cotton plants were treated with a combination of DDT and dimethoate under conditions of local agricultural practice to study the fate and magnitude of both chemicals in the cottonseed and related products. GLC and nuclear (using 14 C-DDT) techniques were used. DDT residues in the crude oil averaged 0.115 mg/kg; mainly as p,p'-DDT while residues in the cake were not detected. Dimethoate and dimethoxon in the crude oil were 0.13 and 0.01 mg/kg respectively. The cake contained 0.14 mg/kg dimethoate and 0.01 mg/kg dimethoxon. By simulating commercial oil processing in the laboratory using 14 C-DDT fortified oil samples it was found that alkali treatment and bleaching removed only 7% of the total residue, while deodorization effected removal of 40-50% of the residue. (author)

  7. 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

  8. Whole linted cottonseed meal (Gossypium hirsutum L. protein and fiber degradability in the rumen

    Directory of Open Access Journals (Sweden)

    Deborah Clea Ruy

    1996-12-01

    3 x 3 change-over design to evaluate the following treatments: A = 0% WLC; B = 6.6% WLC; and C = 15.0% WLC. Sorghum silage contributed with 70% in all three treatments. DM degradability at 48h incubation time was statistically different (p < 0.05 (A = 54.4%; B = 54.2% and C = 58.7%, as well as PB degradability at 12h (A = 40.3%; B = 47.7% and C = 53.1% and ADF degradability at 48h (A = 40.3%; B = 41.2% and C = 45.6%. Ruminal volume, turn overtime and ruminal pH weren’t affected by the experimental diets. Substitution of WLC for cottonseed meal up to 15% diet increased degradability of DM, CP and ADF of WLC.

  9. 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

  10. Validation of Born Traveltime Kernels

    Science.gov (United States)

    Baig, A. M.; Dahlen, F. A.; Hung, S.

    2001-12-01

    Most inversions for Earth structure using seismic traveltimes rely on linear ray theory to translate observed traveltime anomalies into seismic velocity anomalies distributed throughout the mantle. However, ray theory is not an appropriate tool to use when velocity anomalies have scale lengths less than the width of the Fresnel zone. In the presence of these structures, we need to turn to a scattering theory in order to adequately describe all of the features observed in the waveform. By coupling the Born approximation to ray theory, the first order dependence of heterogeneity on the cross-correlated traveltimes (described by the Fréchet derivative or, more colourfully, the banana-doughnut kernel) may be determined. To determine for what range of parameters these banana-doughnut kernels outperform linear ray theory, we generate several random media specified by their statistical properties, namely the RMS slowness perturbation and the scale length of the heterogeneity. Acoustic waves are numerically generated from a point source using a 3-D pseudo-spectral wave propagation code. These waves are then recorded at a variety of propagation distances from the source introducing a third parameter to the problem: the number of wavelengths traversed by the wave. When all of the heterogeneity has scale lengths larger than the width of the Fresnel zone, ray theory does as good a job at predicting the cross-correlated traveltime as the banana-doughnut kernels do. Below this limit, wavefront healing becomes a significant effect and ray theory ceases to be effective even though the kernels remain relatively accurate provided the heterogeneity is weak. The study of wave propagation in random media is of a more general interest and we will also show our measurements of the velocity shift and the variance of traveltime compare to various theoretical predictions in a given regime.

  11. 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

  12. RKRD: Runtime Kernel Rootkit Detection

    Science.gov (United States)

    Grover, Satyajit; Khosravi, Hormuzd; Kolar, Divya; Moffat, Samuel; Kounavis, Michael E.

    In this paper we address the problem of protecting computer systems against stealth malware. The problem is important because the number of known types of stealth malware increases exponentially. Existing approaches have some advantages for ensuring system integrity but sophisticated techniques utilized by stealthy malware can thwart them. We propose Runtime Kernel Rootkit Detection (RKRD), a hardware-based, event-driven, secure and inclusionary approach to kernel integrity that addresses some of the limitations of the state of the art. Our solution is based on the principles of using virtualization hardware for isolation, verifying signatures coming from trusted code as opposed to malware for scalability and performing system checks driven by events. Our RKRD implementation is guided by our goals of strong isolation, no modifications to target guest OS kernels, easy deployment, minimal infra-structure impact, and minimal performance overhead. We developed a system prototype and conducted a number of experiments which show that the per-formance impact of our solution is negligible.

  13. Kernel Bayesian ART and ARTMAP.

    Science.gov (United States)

    Masuyama, Naoki; Loo, Chu Kiong; Dawood, Farhan

    2018-02-01

    Adaptive Resonance Theory (ART) is one of the successful approaches to resolving "the plasticity-stability dilemma" in neural networks, and its supervised learning model called ARTMAP is a powerful tool for classification. Among several improvements, such as Fuzzy or Gaussian based models, the state of art model is Bayesian based one, while solving the drawbacks of others. However, it is known that the Bayesian approach for the high dimensional and a large number of data requires high computational cost, and the covariance matrix in likelihood becomes unstable. This paper introduces Kernel Bayesian ART (KBA) and ARTMAP (KBAM) by integrating Kernel Bayes' Rule (KBR) and Correntropy Induced Metric (CIM) to Bayesian ART (BA) and ARTMAP (BAM), respectively, while maintaining the properties of BA and BAM. The kernel frameworks in KBA and KBAM are able to avoid the curse of dimensionality. In addition, the covariance-free Bayesian computation by KBR provides the efficient and stable computational capability to KBA and KBAM. Furthermore, Correntropy-based similarity measurement allows improving the noise reduction ability even in the high dimensional space. The simulation experiments show that KBA performs an outstanding self-organizing capability than BA, and KBAM provides the superior classification ability than BAM, respectively. Copyright © 2017 Elsevier Ltd. All rights reserved.

  14. 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.

  15. 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...

  16. Bioavailability of iron in cottonseed meal, ferric sulfate, and two ferrous sulfate by-products of the galvanizing industry.

    Science.gov (United States)

    Boling, S D; Edwards, H M; Emmert, J L; Biehl, R R; Baker, D H

    1998-09-01

    Iron depletion-repletion assays were carried out with young chicks to establish Fe bioavailability values for Fe2(SO4)3.7H2O (22.7% Fe), Fe-ZnSO4.H2O (20.2% Fe, 13.0% Zn), Zn-FeSO4.H2O (20.2% Zn, 14.2% Fe), and cottonseed meal (200 mg Fe/kg). Standard hemoglobin response curves were established using feed-grade FeSO4.H2O (28.8% Fe) or reagent-grade FeSO4.7H2O (20.1% Fe) as standards such that relative bioavailability (RBV) could be assessed for the experimental sources of Fe. Weight gain, hemoglobin, and hematocrit responded linearly (P 0.10) from the standard. However, evaluation of all criteria of response (hemoglobin, hematocrit, weight gain) suggested that neither Fe-ZnSO4.H2O nor Zn-FeSO4.H2O had different Fe RBV values than FeSO4.H2O. Standard-curve calculations were used for assessment of Fe RBV in Fe2(SO4)3.7H2O and cottonseed meal, as only a single level of Fe addition was studied for each of these products. Iron RBV in Fe2(SO4)3.7H2O was estimated to be 37%, whereas Fe RBV in cottonseed meal was found to be 56%. Both of these values were lower (P galvanizing industry, are excellent sources of bioavailable Fe, whereas ferric sulfate and cottonseed meal are relatively poor sources of usable Fe.

  17. 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.

  18. Convergence of barycentric coordinates to barycentric kernels

    KAUST Repository

    Kosinka, Jiří ; Barton, Michael

    2016-01-01

    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.

  19. 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....

  20. Partial Deconvolution with Inaccurate Blur Kernel.

    Science.gov (United States)

    Ren, Dongwei; Zuo, Wangmeng; Zhang, David; Xu, Jun; Zhang, Lei

    2017-10-17

    Most non-blind deconvolution methods are developed under the error-free kernel assumption, and are not robust to inaccurate blur kernel. Unfortunately, despite the great progress in blind deconvolution, estimation error remains inevitable during blur kernel estimation. Consequently, severe artifacts such as ringing effects and distortions are likely to be introduced in the non-blind deconvolution stage. In this paper, we tackle this issue by suggesting: (i) a partial map in the Fourier domain for modeling kernel estimation error, and (ii) a partial deconvolution model for robust deblurring with inaccurate blur kernel. The partial map is constructed by detecting the reliable Fourier entries of estimated blur kernel. And partial deconvolution is applied to wavelet-based and learning-based models to suppress the adverse effect of kernel estimation error. Furthermore, an E-M algorithm is developed for estimating the partial map and recovering the latent sharp image alternatively. Experimental results show that our partial deconvolution model is effective in relieving artifacts caused by inaccurate blur kernel, and can achieve favorable deblurring quality on synthetic and real blurry images.Most non-blind deconvolution methods are developed under the error-free kernel assumption, and are not robust to inaccurate blur kernel. Unfortunately, despite the great progress in blind deconvolution, estimation error remains inevitable during blur kernel estimation. Consequently, severe artifacts such as ringing effects and distortions are likely to be introduced in the non-blind deconvolution stage. In this paper, we tackle this issue by suggesting: (i) a partial map in the Fourier domain for modeling kernel estimation error, and (ii) a partial deconvolution model for robust deblurring with inaccurate blur kernel. The partial map is constructed by detecting the reliable Fourier entries of estimated blur kernel. And partial deconvolution is applied to wavelet-based and learning

  1. Process for producing metal oxide kernels and kernels so obtained

    International Nuclear Information System (INIS)

    Lelievre, Bernard; Feugier, Andre.

    1974-01-01

    The process desbribed is for producing fissile or fertile metal oxide kernels used in the fabrication of fuels for high temperature nuclear reactors. This process consists in adding to an aqueous solution of at least one metallic salt, particularly actinide nitrates, at least one chemical compound capable of releasing ammonia, in dispersing drop by drop the solution thus obtained into a hot organic phase to gel the drops and transform them into solid particles. These particles are then washed, dried and treated to turn them into oxide kernels. The organic phase used for the gel reaction is formed of a mixture composed of two organic liquids, one acting as solvent and the other being a product capable of extracting the anions from the metallic salt of the drop at the time of gelling. Preferably an amine is used as product capable of extracting the anions. Additionally, an alcohol that causes a part dehydration of the drops can be employed as solvent, thus helping to increase the resistance of the particles [fr

  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. Dense Medium Machine Processing Method for Palm Kernel/ Shell ...

    African Journals Online (AJOL)

    ADOWIE PERE

    Cracked palm kernel is a mixture of kernels, broken shells, dusts and other impurities. In ... machine processing method using dense medium, a separator, a shell collector and a kernel .... efficiency, ease of maintenance and uniformity of.

  4. Mitigation of artifacts in rtm with migration kernel decomposition

    KAUST Repository

    Zhan, Ge; Schuster, Gerard T.

    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

  5. How does the dietary cottonseed hull affect the carcass characteristics and meat quality of young bulls finished in a high-concentrate diet?

    Directory of Open Access Journals (Sweden)

    Carlos Emanuel Eiras

    2016-08-01

    Full Text Available This study evaluated the effects of diets composed by cottonseed hull and meat aging on carcass characteristics and meat quality from young bulls fed on a high-concentrate system. Thirty crossbred bulls were assigned in a complete randomized experimental factorial design with three diets (CH21: cottonseed hull 210 g kg-1on a DM basis, CH27: cottonseed hull 270 g kg-1on a DM basis and CH33: cottonseed hull 330 g kg-1on a DM basis and different aging times (24 hours and 3, 7 and 14 days. Meat from CH27 diets presented smaller LM moisture content (p < 0.05. Total lipids were smaller in CH33 diet (p <0.05. At 24 hours, CH21 diet presented smaller LM cooking loss than other diets. The increasing aging time reduced the shear force (p < 0.001 on the LM. Meat from CH27 diet presented the highest luminosity (p < 0.05 and yellowness values (p < 0.001. Three or seven aging days presented smaller values of LM luminosity. Likewise, the increasing aging time presented greater (p < 0.05 yellowness within the LM. Lipid oxidation was lower from CH21 diet (p < 0.001. The fatty acid composition on LM was similar among diets. The use of cottonseed hull could be useful strategies to improve the meat quality and lean beef production.

  6. 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.

  7. 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.

  8. Ranking Support Vector Machine with Kernel Approximation

    Directory of Open Access Journals (Sweden)

    Kai Chen

    2017-01-01

    Full Text Available 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.

  9. 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.

  10. Sentiment classification with interpolated information diffusion kernels

    NARCIS (Netherlands)

    Raaijmakers, S.

    2007-01-01

    Information diffusion kernels - similarity metrics in non-Euclidean information spaces - have been found to produce state of the art results for document classification. In this paper, we present a novel approach to global sentiment classification using these kernels. We carry out a large array of

  11. Evolution kernel for the Dirac field

    International Nuclear Information System (INIS)

    Baaquie, B.E.

    1982-06-01

    The evolution kernel for the free Dirac field is calculated using the Wilson lattice fermions. We discuss the difficulties due to which this calculation has not been previously performed in the continuum theory. The continuum limit is taken, and the complete energy eigenfunctions as well as the propagator are then evaluated in a new manner using the kernel. (author)

  12. 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...

  13. 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…

  14. Kernel Korner : The Linux keyboard driver

    NARCIS (Netherlands)

    Brouwer, A.E.

    1995-01-01

    Our Kernel Korner series continues with an article describing the Linux keyboard driver. This article is not for "Kernel Hackers" only--in fact, it will be most useful to those who wish to use their own keyboard to its fullest potential, and those who want to write programs to take advantage of the

  15. Metabolic network prediction through pairwise rational kernels.

    Science.gov (United States)

    Roche-Lima, Abiel; Domaratzki, Michael; Fristensky, Brian

    2014-09-26

    Metabolic networks are represented by the set of metabolic pathways. Metabolic pathways are a series of biochemical reactions, in which the product (output) from one reaction serves as the substrate (input) to another reaction. Many pathways remain incompletely characterized. One of the major challenges of computational biology is to obtain better models of metabolic pathways. Existing models are dependent on the annotation of the genes. This propagates error accumulation when the pathways are predicted by incorrectly annotated genes. Pairwise classification methods are supervised learning methods used to classify new pair of entities. Some of these classification methods, e.g., Pairwise Support Vector Machines (SVMs), use pairwise kernels. Pairwise kernels describe similarity measures between two pairs of entities. Using pairwise kernels to handle sequence data requires long processing times and large storage. Rational kernels are kernels based on weighted finite-state transducers that represent similarity measures between sequences or automata. They have been effectively used in problems that handle large amount of sequence information such as protein essentiality, natural language processing and machine translations. We create a new family of pairwise kernels using weighted finite-state transducers (called Pairwise Rational Kernel (PRK)) to predict metabolic pathways from a variety of biological data. PRKs take advantage of the simpler representations and faster algorithms of transducers. Because raw sequence data can be used, the predictor model avoids the errors introduced by incorrect gene annotations. We then developed several experiments with PRKs and Pairwise SVM to validate our methods using the metabolic network of Saccharomyces cerevisiae. As a result, when PRKs are used, our method executes faster in comparison with other pairwise kernels. Also, when we use PRKs combined with other simple kernels that include evolutionary information, the accuracy

  16. Replacing soybean meal for cottonseed meal on performance of lactating dairy cows.

    Science.gov (United States)

    Imaizumi, Hugo; De Souza, Jonas; Batistel, Fernanda; Santos, Flávio Augusto Portela

    2016-01-01

    Cottonseed meal (CSM) is an alternative source of protein, and previous studies have been shown that it can replace soybean meal (SBM) without decrease animal performance. However, Brazilian CSM has a different chemical composition compared with the usual CSM reported in the literature. The objective of this experiment was to evaluate the effects of replacing SBM for Brazilian CSM on performance and energy balance of mid-lactating dairy cows. Forty-two Holstein cows were used in a replicate 3 × 3 Latin square design. Increasing contents of CSM (0, 15, and 30% of dry matter (DM)) were fed in diets to replace SBM. Milk yield and feed efficiency were linearly reduced with the replacement of CSM for SBM (P = 0.001). Milk fat content tended to increase quadratically (P = 0.07) with CSM addition. Replacing SBM for CSM affected milk protein content quadratically (P = 0.05). Milk urea nitrogen and plasma urea nitrogen (PUN) tended to respond quadratically (P = 0.06 and 0.10) when CSM replaced SBM to the diets. Variation in body weight (BW) also responded quadratically as CSM replaced SBM (P = 0.05). Altogether, the findings suggest better performance when cows receive SBM diet compared with the Brazilian CSM diet.

  17. Use of Sunflower Meal as a Substitute for Cottonseed Meal in Rations of Growing Lambs

    International Nuclear Information System (INIS)

    Saleh, S.A.; EI-Fouly, H.A.

    2008-01-01

    Eighteen growing male lambs with an average of 3 months old were randomly divided into three equal groups. Animals of each group were kept in separate shaded pen and fed one of the three tested rations as follows: 1st group fed ration one (RI): (CFM) concentrate feed mixture contained 30% cottonseed meal (CSM) + 0.00 sunflower meal (SFM). 2nd group fed ration two (RII): CFM contained 15% CSM + 15% SFM. 3rd group fed ration three (RIll): CFM contained 00.0% CSM + 30% SFM. Wheat straw was offered to the 3 experiment groups ad libitum. Lambs were weighed at the beginning of the experimental period then at two weeks intervals. At the end of the experimental period, four animals from each group were used to evaluate the nutrients digestibility and nutritive value of the experimental rations. Blood samples were taken each three weeks before feeding animals. The present study showed that lambs fed RII and RIll had significantly higher CP and EE digestibility values compared to those fed RI. % Nitrogen balance was currently higher for RIll than RI and RII. No significant differences among the tested blood serum parameters for the experimental lambs except for total protein, AST, triglycerides and cholesterol values. Average daily weight gain (ADG) and feed efficiency were better for RII and RIll than RI

  18. Bayesian Kernel Mixtures for Counts.

    Science.gov (United States)

    Canale, Antonio; Dunson, David B

    2011-12-01

    Although Bayesian nonparametric mixture models for continuous data are well developed, there is a limited literature on related approaches for count data. A common strategy is to use a mixture of Poissons, which unfortunately is quite restrictive in not accounting for distributions having variance less than the mean. Other approaches include mixing multinomials, which requires finite support, and using a Dirichlet process prior with a Poisson base measure, which does not allow smooth deviations from the Poisson. As a broad class of alternative models, we propose to use nonparametric mixtures of rounded continuous kernels. An efficient Gibbs sampler is developed for posterior computation, and a simulation study is performed to assess performance. Focusing on the rounded Gaussian case, we generalize the modeling framework to account for multivariate count data, joint modeling with continuous and categorical variables, and other complications. The methods are illustrated through applications to a developmental toxicity study and marketing data. This article has supplementary material online.

  19. Putting Priors in Mixture Density Mercer Kernels

    Science.gov (United States)

    Srivastava, Ashok N.; Schumann, Johann; Fischer, Bernd

    2004-01-01

    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 infinite dimensional feature space. We describe a new method called Mixture Density Mercer Kernels to learn kernel function directly from data, rather than using predefined kernels. These data adaptive kernels can en- code prior knowledge in the kernel using a Bayesian formulation, thus allowing for physical information to be encoded in the model. We compare the results with existing algorithms on data from the Sloan Digital Sky Survey (SDSS). 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 template 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. The results show that the Mixture Density Mercer-Kernel described here outperforms tree-based classification in distinguishing high-redshift galaxies from low- redshift galaxies by approximately 16% on test data, bagged trees by approximately 7%, and bagged trees built on a much larger sample of data by approximately 2%.

  20. Anisotropic hydrodynamics with a scalar collisional kernel

    Science.gov (United States)

    Almaalol, Dekrayat; Strickland, Michael

    2018-04-01

    Prior studies of nonequilibrium dynamics using anisotropic hydrodynamics have used the relativistic Anderson-Witting scattering kernel or some variant thereof. In this paper, we make the first study of the impact of using a more realistic scattering kernel. For this purpose, we consider a conformal system undergoing transversally homogenous and boost-invariant Bjorken expansion and take the collisional kernel to be given by the leading order 2 ↔2 scattering kernel in scalar λ ϕ4 . We consider both classical and quantum statistics to assess the impact of Bose enhancement on the dynamics. We also determine the anisotropic nonequilibrium attractor of a system subject to this collisional kernel. We find that, when the near-equilibrium relaxation-times in the Anderson-Witting and scalar collisional kernels are matched, the scalar kernel results in a higher degree of momentum-space anisotropy during the system's evolution, given the same initial conditions. Additionally, we find that taking into account Bose enhancement further increases the dynamically generated momentum-space anisotropy.

  1. 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

  2. Carcass characteristics and meat quality of Santa Inês lambs fed with sunflower cake replacing cottonseed meal

    Directory of Open Access Journals (Sweden)

    Francisco Fernandes Júnior

    2014-02-01

    Full Text Available The objective of this study was to evaluate carcass characteristics and meat quality of lambs fed sunflower cake to replace the protein of cottonseed meal. The experiment was conducted at the sheep sector at the Farm School, State University of Londrina. Thirty Santa Inês lambs, intact males, with age and weight at the beginning of the experiment of 80 days and 21.45 ± 2.16 kg, respectively, were used. It was used a completely randomized experimental design. The animals were divided into 5 treatments, with 6 replicates per treatment, according to the amount of protein of cottonseed meal replaced by protein of the sunflower cake (0, 20, 40, 60 and 80% of replacement. Carcasses were evaluated and the Longissimus dorsi was removed for analyzes of shear force, color, pH, marbling, water loss by pressure, sensory analysis, chemical analyses and lipid oxidation. Hot and cold carcass yields showed quadratic distributions, where the best values were found for treatments with low inclusion of sunflower cake. Carcass measurements, as well as cut yields were not affected by the content of sunflower cake. Regarding the parameters of lamb meat, only water losses during cooking and shear force were affected, being quadratic and linear, respectively. The meat was more tender in animals fed higher amounts of sunflower cake. The tasters of the sensory panel did not identify differences between treatments, and classified the meat with moderate odor intensity, good tenderness, low to moderate juiciness and medium acceptability. The replacement of cottonseed meal protein by sunflower cake protein in the levels used, did not affect the majority of the carcass characteristics and the meat quality.

  3. Evaluation and comparison of gamma- and electron beam irradiation effects on total and free gossypol of cottonseed meal

    International Nuclear Information System (INIS)

    Shawrang, P.; Mansouri, M.H.; Sadeghi, A.A.; Ziaie, F.

    2011-01-01

    Impact of gamma- and electron beam irradiation on total and free gossypol content of cottonseed meal was assessed by exposing them to doses of 10, 15, 20, 25 and 30 kGy. Gamma rays and electron beam showed the same effects with significant dose-dependent decrease in total and free gossypol content. Based on these results, ionizing irradiation at doses of 25 kGy and above could completely remove free gossypol and bring down total gossypol content to permissible level in poultry feed.

  4. COMPARATIVE EFFICIENCY OF SUNFLOWER MEAL AND COTTONSEED CAKES IN THE FEED OF CROSSBRED CALVES FOR MEAT PRODUCTION

    OpenAIRE

    M. A. JABBAR, M. I. ANJUM1, S. REHMAN2 AND W. SHAHZAD2

    2006-01-01

    Thirty crossbred (Sahiwal x Friesian) male calves of 9-10 months age and weighing 70 to 90 kg, were used in completely randomized design to investigate the possibility of replacing cottonseed cakes (CSC) with sunflower meal (SFM), partially or completely, in rations for fattening of crossbred calves for meat production. Three concentrate rations viz. A, B and C were formulated. Ration A containing CSC was fed to the calves of group A, ration B containing SFM was fed to calves of group B and...

  5. Higher-Order Hybrid Gaussian Kernel in Meshsize Boosting Algorithm

    African Journals Online (AJOL)

    In this paper, we shall use higher-order hybrid Gaussian kernel in a meshsize boosting algorithm in kernel density estimation. Bias reduction is guaranteed in this scheme like other existing schemes but uses the higher-order hybrid Gaussian kernel instead of the regular fixed kernels. A numerical verification of this scheme ...

  6. 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.

  7. Adaptive Kernel in Meshsize Boosting Algorithm in KDE ...

    African Journals Online (AJOL)

    This paper proposes the use of adaptive kernel in a meshsize boosting algorithm in kernel density estimation. The algorithm is a bias reduction scheme like other existing schemes but uses adaptive kernel instead of the regular fixed kernels. An empirical study for this scheme is conducted and the findings are comparatively ...

  8. Adaptive Kernel In The Bootstrap Boosting Algorithm In KDE ...

    African Journals Online (AJOL)

    This paper proposes the use of adaptive kernel in a bootstrap boosting algorithm in kernel density estimation. The algorithm is a bias reduction scheme like other existing schemes but uses adaptive kernel instead of the regular fixed kernels. An empirical study for this scheme is conducted and the findings are comparatively ...

  9. Kernel maximum autocorrelation factor and minimum noise fraction transformations

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg

    2010-01-01

    in hyperspectral HyMap scanner data covering a small agricultural area, and 3) maize kernel inspection. In the cases shown, the kernel MAF/MNF transformation performs better than its linear counterpart as well as linear and kernel PCA. The leading kernel MAF/MNF variates seem to possess the ability to adapt...

  10. 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 missing...

  11. 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 than...

  12. 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 for...

  13. 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 color...

  14. The Linux kernel as flexible product-line architecture

    NARCIS (Netherlands)

    M. de Jonge (Merijn)

    2002-01-01

    textabstractThe 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

  15. Effect of feeding cottonseed meal on some hematological and serum biochemical parameters in broiler birds

    Directory of Open Access Journals (Sweden)

    G. Thirumalaisamy

    2016-07-01

    Full Text Available Aim: The study was undertaken to find out the effect of feeding cottonseed meal (CSM on performance of hematological and serum biochemical parameters in broiler birds. Materials and Methods: A 6-week biological trial was carried out with 432-day-old Cobb 400 broiler chicks distributed to nine experimental diets with six replicates, each containing eight chicks. The experimental diets were formulated based on total amino acids (BTAA or based on digestible amino acids (BDAA with or without iron supplementation with two levels of CSM (2% and 4% and control diet based on maize – soybean. The whole blood was subjected to hematological studies. The serum samples were analyzed for protein fractions and lipid profiles. Results: The packed cell volume (PCV value, red blood cell (RBC numbers, and hemoglobin (Hb were lower in iron unsupplemented CSM BTAA or BDAA diets than the control (33.86-35.54 vs. 36.41%, 2.78-2.87 vs. 2.98 × 106/μl, and 10.30-10.70 vs. 10.88%. Supplementation of iron in CSM diets improved the PCV, RBC numbers, and Hb, and the values were comparable to the control. White blood cell numbers, mean corpuscular volume, mean corpuscular Hb (MCH, and MCH concentration values were comparable to the control. The erythrocyte osmotic fragility (EOF was poor in birds fed diets containing up to 4% CSM BTAA or CSM BDAA without iron supplementation (32.02-32.57 vs. 28.77%. Supplementation of iron improved the EOF. The serum cholesterol level did not change with or without iron supplementation. Conclusion: This study suggested that feeding of CSM BTAA or BDAA up to 4% level voiding iron supplementation lowers the hematological parameters, whereas supplementation of iron did not alter serum protein fractions and cholesterol profile; however, it had lowered some hematological parameters, which was rectified by iron supplementation.

  16. Digital signal processing with kernel methods

    CERN Document Server

    Rojo-Alvarez, José Luis; Muñoz-Marí, Jordi; Camps-Valls, Gustavo

    2018-01-01

    A realistic and comprehensive review of joint approaches to machine learning and signal processing algorithms, with application to communications, multimedia, and biomedical engineering systems Digital Signal Processing with Kernel Methods reviews the milestones in the mixing of classical digital signal processing models and advanced kernel machines statistical learning tools. It explains the fundamental concepts from both fields of machine learning and signal processing so that readers can quickly get up to speed in order to begin developing the concepts and application software in their own research. Digital Signal Processing with Kernel Methods provides a comprehensive overview of kernel methods in signal processing, without restriction to any application field. It also offers example applications and detailed benchmarking experiments with real and synthetic datasets throughout. Readers can find further worked examples with Matlab source code on a website developed by the authors. * Presents the necess...

  17. Parsimonious Wavelet Kernel Extreme Learning Machine

    Directory of Open Access Journals (Sweden)

    Wang Qin

    2015-11-01

    Full Text Available In this study, a parsimonious scheme for wavelet kernel extreme learning machine (named PWKELM was introduced by combining wavelet theory and a parsimonious algorithm into kernel extreme learning machine (KELM. In the wavelet analysis, bases that were localized in time and frequency to represent various signals effectively were used. Wavelet kernel extreme learning machine (WELM maximized its capability to capture the essential features in “frequency-rich” signals. The proposed parsimonious algorithm also incorporated significant wavelet kernel functions via iteration in virtue of Householder matrix, thus producing a sparse solution that eased the computational burden and improved numerical stability. The experimental results achieved from the synthetic dataset and a gas furnace instance demonstrated that the proposed PWKELM is efficient and feasible in terms of improving generalization accuracy and real time performance.

  18. 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...

  19. LAI inversion algorithm based on directional reflectance kernels.

    Science.gov (United States)

    Tang, S; Chen, J M; Zhu, Q; Li, X; Chen, M; Sun, R; Zhou, Y; Deng, F; Xie, D

    2007-11-01

    Leaf area index (LAI) is an important ecological and environmental parameter. A new LAI algorithm is developed using the principles of ground LAI measurements based on canopy gap fraction. First, the relationship between LAI and gap fraction at various zenith angles is derived from the definition of LAI. Then, the directional gap fraction is acquired from a remote sensing bidirectional reflectance distribution function (BRDF) product. This acquisition is obtained by using a kernel driven model and a large-scale directional gap fraction algorithm. The algorithm has been applied to estimate a LAI distribution in China in mid-July 2002. The ground data acquired from two field experiments in Changbai Mountain and Qilian Mountain were used to validate the algorithm. To resolve the scale discrepancy between high resolution ground observations and low resolution remote sensing data, two TM images with a resolution approaching the size of ground plots were used to relate the coarse resolution LAI map to ground measurements. First, an empirical relationship between the measured LAI and a vegetation index was established. Next, a high resolution LAI map was generated using the relationship. The LAI value of a low resolution pixel was calculated from the area-weighted sum of high resolution LAIs composing the low resolution pixel. The results of this comparison showed that the inversion algorithm has an accuracy of 82%. Factors that may influence the accuracy are also discussed in this paper.

  20. Control Transfer in Operating System Kernels

    Science.gov (United States)

    1994-05-13

    microkernel system that runs less code in the kernel address space. To realize the performance benefit of allocating stacks in unmapped kseg0 memory, the...review how I modified the Mach 3.0 kernel to use continuations. Because of Mach’s message-passing microkernel structure, interprocess communication was...critical control transfer paths, deeply- nested call chains are undesirable in any case because of the function call overhead. 4.1.3 Microkernel Operating

  1. Uranium kernel formation via internal gelation

    International Nuclear Information System (INIS)

    Hunt, R.D.; Collins, J.L.

    2004-01-01

    In the 1970s and 1980s, U.S. Department of Energy (DOE) conducted numerous studies on the fabrication of nuclear fuel particles using the internal gelation process. These amorphous kernels were prone to flaking or breaking when gases tried to escape from the kernels during calcination and sintering. These earlier kernels would not meet today's proposed specifications for reactor fuel. In the interim, the internal gelation process has been used to create hydrous metal oxide microspheres for the treatment of nuclear waste. With the renewed interest in advanced nuclear fuel by the DOE, the lessons learned from the nuclear waste studies were recently applied to the fabrication of uranium kernels, which will become tri-isotropic (TRISO) fuel particles. These process improvements included equipment modifications, small changes to the feed formulations, and a new temperature profile for the calcination and sintering. The modifications to the laboratory-scale equipment and its operation as well as small changes to the feed composition increased the product yield from 60% to 80%-99%. The new kernels were substantially less glassy, and no evidence of flaking was found. Finally, key process parameters were identified, and their effects on the uranium microspheres and kernels are discussed. (orig.)

  2. Quantum tomography, phase-space observables and generalized Markov kernels

    International Nuclear Information System (INIS)

    Pellonpaeae, Juha-Pekka

    2009-01-01

    We construct a generalized Markov kernel which transforms the observable associated with the homodyne tomography into a covariant phase-space observable with a regular kernel state. Illustrative examples are given in the cases of a 'Schroedinger cat' kernel state and the Cahill-Glauber s-parametrized distributions. Also we consider an example of a kernel state when the generalized Markov kernel cannot be constructed.

  3. Penetuan Bilangan Iodin pada Hydrogenated Palm Kernel Oil (HPKO) dan Refined Bleached Deodorized Palm Kernel Oil (RBDPKO)

    OpenAIRE

    Sitompul, Monica Angelina

    2015-01-01

    Have been conducted Determination of Iodin Value by method titration to some Hydrogenated Palm Kernel Oil (HPKO) and Refined Bleached Deodorized Palm Kernel Oil (RBDPKO). The result of analysis obtained the Iodin Value in Hydrogenated Palm Kernel Oil (A) = 0,16 gr I2/100gr, Hydrogenated Palm Kernel Oil (B) = 0,20 gr I2/100gr, Hydrogenated Palm Kernel Oil (C) = 0,24 gr I2/100gr. And in Refined Bleached Deodorized Palm Kernel Oil (A) = 17,51 gr I2/100gr, Refined Bleached Deodorized Palm Kernel ...

  4. Detoxification Treatments of Free Gossypol in Cottonseed Meal by Microbial Treatment of Mixed Cultures and Biochemical Evaluation on Rabbits

    International Nuclear Information System (INIS)

    Atia, A.I.; Abdel- Rahim, G.A.

    2009-01-01

    Detoxification of ti-ee gossypol (FG) in cottonseed meal (CSM) by Saccharomyces cerevisiae and Aspergillus niger, as a mixed culture, was carried out in solid state fermentation (SSF). Experiments were adopted to optimize the fermentation conditions. Maximum detoxification efficiency (90.2%) occurred after 48 h of incubation at 30 degree C in a 250 ml conical flask containing 15 g of CSM supplemented with 1 % (w/w) (NH 4 ) 2 SO 4 at the optimal conditions including the initial moisture content 55% (w/w) and inoculum level at 5% (v/w). The detoxification of FG was a growth-associated process, which was highly correlated with the dry matter weight loss. Moreover, high activities of hydrolytic enzymes were also produced in solid state fermentation, which enhanced the nutritive value of the detoxified cottonseed powder. A total number of 48 white New Zealand male rabbits were used to biologically examine the feeding of treated (detoxified) CSM without any adverse effects. Hematological and biochemical relevant parameters of white New Zealand male rabbits as affected by feeding treated meal were in the normal physiological range without no obvious change. No significant changes in liver and kidney functions of the rabbits weight gain, feed conversion and efficiency did not significantly change among experimental groups. The study showed that the feeding of the detoxified CSM by S. cerevisiae and A. niger as a mixed culture in this research without any adverse effects on rabbits

  5. 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...

  6. Exact Heat Kernel on a Hypersphere and Its Applications in Kernel SVM

    Directory of Open Access Journals (Sweden)

    Chenchao Zhao

    2018-01-01

    Full Text Available Many contemporary statistical learning methods assume a Euclidean feature space. This paper presents a method for defining similarity based on hyperspherical geometry and shows that it often improves the performance of support vector machine compared to other competing similarity measures. Specifically, the idea of using heat diffusion on a hypersphere to measure similarity has been previously proposed and tested by Lafferty and Lebanon [1], demonstrating promising results based on a heuristic heat kernel obtained from the zeroth order parametrix expansion; however, how well this heuristic kernel agrees with the exact hyperspherical heat kernel remains unknown. This paper presents a higher order parametrix expansion of the heat kernel on a unit hypersphere and discusses several problems associated with this expansion method. We then compare the heuristic kernel with an exact form of the heat kernel expressed in terms of a uniformly and absolutely convergent series in high-dimensional angular momentum eigenmodes. Being a natural measure of similarity between sample points dwelling on a hypersphere, the exact kernel often shows superior performance in kernel SVM classifications applied to text mining, tumor somatic mutation imputation, and stock market analysis.

  7. Nonhydrogenated cottonseed oil can be used as a deep fat frying medium to reduce trans-fatty acid content in french fries.

    Science.gov (United States)

    Daniel, Darla R; Thompson, Leslie D; Shriver, Brent J; Wu, Chih-Kang; Hoover, Linda C

    2005-12-01

    The purpose of this research study was to evaluate the fatty acid profile, in particular trans-fatty acids, of french fries fried in nonhydrogenated cottonseed oil as compared with french fries fried in partially hydrogenated canola oil and french fries fried in partially hydrogenated soybean oil. Cottonseed oil, partially hydrogenated canola oil, and partially hydrogenated soybean oil were subjected to a temperature of 177 degrees C for 8 hours per day, and six batches of french fries were fried per day for 5 consecutive days. French fries were weighed before frying, cooked for 5 minutes, allowed to drain, and reweighed. Oil was not replenished and was filtered once per day. Both the oil and the french fries were evaluated to determine fatty acid profiles, trans-fatty acids, and crude fat. A randomized block design with split plot was used to analyze the data collected. Least-squares difference was used as the means separation test. No significant differences were found between fries prepared in the three oil types for crude fat. Fatty acid profiles for the french fries remained stable. The french fries prepared in cottonseed oil were significantly lower in trans-fatty acids. The combined total of the trans-fatty acid content and saturated fatty acid content were lower in french fries prepared in cottonseed oil. Because deep fat frying remains a popular cooking technique, health professionals should educate the public and the food service industry on the benefits of using nonhydrogenated cottonseed oil as an alternative to the commonly used hydrogenated oils.

  8. Aflatoxin contamination of developing corn kernels.

    Science.gov (United States)

    Amer, M A

    2005-01-01

    Preharvest of corn and its contamination with aflatoxin is a serious problem. Some environmental and cultural factors responsible for infection and subsequent aflatoxin production were investigated in this study. Stage of growth and location of kernels on corn ears were found to be one of the important factors in the process of kernel infection with A. flavus & A. parasiticus. The results showed positive correlation between the stage of growth and kernel infection. Treatment of corn with aflatoxin reduced germination, protein and total nitrogen contents. Total and reducing soluble sugar was increase in corn kernels as response to infection. Sucrose and protein content were reduced in case of both pathogens. Shoot system length, seeding fresh weigh and seedling dry weigh was also affected. Both pathogens induced reduction of starch content. Healthy corn seedlings treated with aflatoxin solution were badly affected. Their leaves became yellow then, turned brown with further incubation. Moreover, their total chlorophyll and protein contents showed pronounced decrease. On the other hand, total phenolic compounds were increased. Histopathological studies indicated that A. flavus & A. parasiticus could colonize corn silks and invade developing kernels. Germination of A. flavus spores was occurred and hyphae spread rapidly across the silk, producing extensive growth and lateral branching. Conidiophores and conidia had formed in and on the corn silk. Temperature and relative humidity greatly influenced the growth of A. flavus & A. parasiticus and aflatoxin production.

  9. 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.

  10. 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

  11. The Classification of Diabetes Mellitus Using Kernel k-means

    Science.gov (United States)

    Alamsyah, M.; Nafisah, Z.; Prayitno, E.; Afida, A. M.; Imah, E. M.

    2018-01-01

    Diabetes Mellitus is a metabolic disorder which is characterized by chronicle hypertensive glucose. Automatics detection of diabetes mellitus is still challenging. This study detected diabetes mellitus by using kernel k-Means algorithm. Kernel k-means is an algorithm which was developed from k-means algorithm. Kernel k-means used kernel learning that is able to handle non linear separable data; where it differs with a common k-means. The performance of kernel k-means in detecting diabetes mellitus is also compared with SOM algorithms. The experiment result shows that kernel k-means has good performance and a way much better than SOM.

  12. 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...

  13. 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.

  14. Protein Subcellular Localization with Gaussian Kernel Discriminant Analysis and Its Kernel Parameter Selection.

    Science.gov (United States)

    Wang, Shunfang; Nie, Bing; Yue, Kun; Fei, Yu; Li, Wenjia; Xu, Dongshu

    2017-12-15

    Kernel discriminant analysis (KDA) is a dimension reduction and classification algorithm based on nonlinear kernel trick, which can be novelly used to treat high-dimensional and complex biological data before undergoing classification processes such as protein subcellular localization. Kernel parameters make a great impact on the performance of the KDA model. Specifically, for KDA with the popular Gaussian kernel, to select the scale parameter is still a challenging problem. Thus, this paper introduces the KDA method and proposes a new method for Gaussian kernel parameter selection depending on the fact that the differences between reconstruction errors of edge normal samples and those of interior normal samples should be maximized for certain suitable kernel parameters. Experiments with various standard data sets of protein subcellular localization show that the overall accuracy of protein classification prediction with KDA is much higher than that without KDA. Meanwhile, the kernel parameter of KDA has a great impact on the efficiency, and the proposed method can produce an optimum parameter, which makes the new algorithm not only perform as effectively as the traditional ones, but also reduce the computational time and thus improve efficiency.

  15. Kernel abortion in maize. II. Distribution of 14C among kernel carboydrates

    International Nuclear Information System (INIS)

    Hanft, J.M.; Jones, R.J.

    1986-01-01

    This study was designed to compare the uptake and distribution of 14 C among fructose, glucose, sucrose, and starch in the cob, pedicel, and endosperm tissues of maize (Zea mays L.) kernels induced to abort by high temperature with those that develop normally. Kernels cultured in vitro at 309 and 35 0 C were transferred to [ 14 C]sucrose media 10 days after pollination. Kernels cultured at 35 0 C aborted prior to the onset of linear dry matter accumulation. Significant uptake into the cob, pedicel, and endosperm of radioactivity associated with the soluble and starch fractions of the tissues was detected after 24 hours in culture on atlageled media. After 8 days in culture on [ 14 C]sucrose media, 48 and 40% of the radioactivity associated with the cob carbohydrates was found in the reducing sugars at 30 and 35 0 C, respectively. Of the total carbohydrates, a higher percentage of label was associated with sucrose and lower percentage with fructose and glucose in pedicel tissue of kernels cultured at 35 0 C compared to kernels cultured at 30 0 C. These results indicate that sucrose was not cleaved to fructose and glucose as rapidly during the unloading process in the pedicel of kernels induced to abort by high temperature. Kernels cultured at 35 0 C had a much lower proportion of label associated with endosperm starch (29%) than did kernels cultured at 30 0 C (89%). Kernels cultured at 35 0 C had a correspondingly higher proportion of 14 C in endosperm fructose, glucose, and sucrose

  16. Fluidization calculation on nuclear fuel kernel coating

    International Nuclear Information System (INIS)

    Sukarsono; Wardaya; Indra-Suryawan

    1996-01-01

    The fluidization of nuclear fuel kernel coating was calculated. The bottom of the reactor was in the from of cone on top of the cone there was a cylinder, the diameter of the cylinder for fluidization was 2 cm and at the upper part of the cylinder was 3 cm. Fluidization took place in the cone and the first cylinder. The maximum and the minimum velocity of the gas of varied kernel diameter, the porosity and bed height of varied stream gas velocity were calculated. The calculation was done by basic program

  17. 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

  18. Comparative Analysis of Kernel Methods for Statistical Shape Learning

    National Research Council Canada - National Science Library

    Rathi, Yogesh; Dambreville, Samuel; Tannenbaum, Allen

    2006-01-01

    .... In this work, we perform a comparative analysis of shape learning techniques such as linear PCA, kernel PCA, locally linear embedding and propose a new method, kernelized locally linear embedding...

  19. 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...

  20. Influence of differently processed mango seed kernel meal on ...

    African Journals Online (AJOL)

    Influence of differently processed mango seed kernel meal on performance response of west African ... and TD( consisted spear grass and parboiled mango seed kernel meal with concentrate diet in a ratio of 35:30:35). ... HOW TO USE AJOL.

  1. On methods to increase the security of the Linux kernel

    International Nuclear Information System (INIS)

    Matvejchikov, I.V.

    2014-01-01

    Methods to increase the security of the Linux kernel for the implementation of imposed protection tools have been examined. The methods of incorporation into various subsystems of the kernel on the x86 architecture have been described [ru

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

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg; Canty, Morton J.

    2010-01-01

    . Principal component analysis (PCA) as well as maximum autocorrelation factor (MAF) and minimum noise fraction (MNF) analyses of IR-MAD images, both linear and kernel-based (which are nonlinear), may further enhance change signals relative to no-change background. The kernel versions 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 the kernel function. This means that we need not know the nonlinear mappings explicitly. Kernel principal component...

  3. 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...

  4. 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.

  5. Effects of fermented cottonseed meal on the growth performance, gastrointestinal microflora population and small intestinal morphology in broiler chickens.

    Science.gov (United States)

    Jazi, V; Boldaji, F; Dastar, B; Hashemi, S R; Ashayerizadeh, A

    2017-08-01

    1. This experiment was conducted to evaluate the effects of replacing dietary cottonseed meal (CSM) or fermented cottonseed meal (FCSM) for soya bean meal (SBM) on growth performance, carcass characteristics, gastrointestinal microbial populations, and intestinal morphology of broiler chickens. 2. CSM was fermented with Bacillus subtilis, Aspergillus niger and A. oryzae for 7 d. A total of 300 one-d-old male Ross 308 broiler chickens were used in a 42-d experiment in which the birds were randomly allotted to one of 5 dietary treatments (containing 0%, 10% and 20% CSM or FCSM) in a completely randomised design. Birds were reared on litter floor and had free access to feed and water during the experiment. 3. Results indicated that the fermentation process significantly reduced crude fibre and free gossypol, while it increased crude protein content and lactic acid bacteria (LAB) count in CSM. 4. The use of FCSM instead of CSM significantly improved growth performance of broilers. The abdominal fat yield in treatments containing FCSM was significantly lower than in the other treatments. The increase in the population of LAB in the crop and decrease in the population of coliforms in the ileum of birds fed on diets containing FCSM were more significant than in other birds. Villi in the duodenum and jejunum of the birds fed on diets containing FCSM were significantly higher than for the other experimental groups. 5. The positive effects of diets containing FCSM on growth performance and intestinal health of broiler chickens showed that this processed source of protein can serve as an appropriate alternative for SBM in diets for broiler chickens.

  6. 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.

  7. Sparse Event Modeling with Hierarchical Bayesian Kernel Methods

    Science.gov (United States)

    2016-01-05

    SECURITY CLASSIFICATION OF: The research objective of this proposal was to develop a predictive Bayesian kernel approach to model count data based on...several predictive variables. Such an approach, which we refer to as the Poisson Bayesian kernel model, is able to model the rate of occurrence of... kernel methods made use of: (i) the Bayesian property of improving predictive accuracy as data are dynamically obtained, and (ii) the kernel function

  8. Relationship between attenuation coefficients and dose-spread kernels

    International Nuclear Information System (INIS)

    Boyer, A.L.

    1988-01-01

    Dose-spread kernels can be used to calculate the dose distribution in a photon beam by convolving the kernel with the primary fluence distribution. The theoretical relationships between various types and components of dose-spread kernels relative to photon attenuation coefficients are explored. These relations can be valuable as checks on the conservation of energy by dose-spread kernels calculated by analytic or Monte Carlo methods

  9. Fabrication of Uranium Oxycarbide Kernels for HTR Fuel

    International Nuclear Information System (INIS)

    Barnes, Charles; Richardson, Clay; Nagley, Scott; Hunn, John; Shaber, Eric

    2010-01-01

    Babcock and Wilcox (B and W) has been producing high quality uranium oxycarbide (UCO) kernels for Advanced Gas Reactor (AGR) fuel tests at the Idaho National Laboratory. In 2005, 350-(micro)m, 19.7% 235U-enriched UCO kernels were produced for the AGR-1 test fuel. Following coating of these kernels and forming the coated-particles into compacts, this fuel was irradiated in the Advanced Test Reactor (ATR) from December 2006 until November 2009. B and W produced 425-(micro)m, 14% enriched UCO kernels in 2008, and these kernels were used to produce fuel for the AGR-2 experiment that was inserted in ATR in 2010. B and W also produced 500-(micro)m, 9.6% enriched UO2 kernels for the AGR-2 experiments. Kernels of the same size and enrichment as AGR-1 were also produced for the AGR-3/4 experiment. In addition to fabricating enriched UCO and UO2 kernels, B and W has produced more than 100 kg of natural uranium UCO kernels which are being used in coating development tests. Successive lots of kernels have demonstrated consistent high quality and also allowed for fabrication process improvements. Improvements in kernel forming were made subsequent to AGR-1 kernel production. Following fabrication of AGR-2 kernels, incremental increases in sintering furnace charge size have been demonstrated. Recently small scale sintering tests using a small development furnace equipped with a residual gas analyzer (RGA) has increased understanding of how kernel sintering parameters affect sintered kernel properties. The steps taken to increase throughput and process knowledge have reduced kernel production costs. Studies have been performed of additional modifications toward the goal of increasing capacity of the current fabrication line to use for production of first core fuel for the Next Generation Nuclear Plant (NGNP) and providing a basis for the design of a full scale fuel fabrication facility.

  10. Consistent Estimation of Pricing Kernels from Noisy Price Data

    OpenAIRE

    Vladislav Kargin

    2003-01-01

    If pricing kernels are assumed non-negative then the inverse problem of finding the pricing kernel is well-posed. The constrained least squares method provides a consistent estimate of the pricing kernel. When the data are limited, a new method is suggested: relaxed maximization of the relative entropy. This estimator is also consistent. Keywords: $\\epsilon$-entropy, non-parametric estimation, pricing kernel, inverse problems.

  11. Quantum logic in dagger kernel categories

    NARCIS (Netherlands)

    Heunen, C.; Jacobs, B.P.F.

    2009-01-01

    This paper investigates quantum logic from the perspective of categorical logic, and starts from minimal assumptions, namely the existence of involutions/daggers and kernels. The resulting structures turn out to (1) encompass many examples of interest, such as categories of relations, partial

  12. Quantum logic in dagger kernel categories

    NARCIS (Netherlands)

    Heunen, C.; Jacobs, B.P.F.; Coecke, B.; Panangaden, P.; Selinger, P.

    2011-01-01

    This paper investigates quantum logic from the perspective of categorical logic, and starts from minimal assumptions, namely the existence of involutions/daggers and kernels. The resulting structures turn out to (1) encompass many examples of interest, such as categories of relations, partial

  13. 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.

  14. Flexible Scheduling in Multimedia Kernels: An Overview

    NARCIS (Netherlands)

    Jansen, P.G.; Scholten, Johan; Laan, Rene; Chow, W.S.

    1999-01-01

    Current Hard Real-Time (HRT) kernels have their timely behaviour guaranteed on the cost of a rather restrictive use of the available resources. This makes current HRT scheduling techniques inadequate for use in a multimedia environment where we can make a considerable profit by a better and more

  15. Reproducing kernel Hilbert spaces of Gaussian priors

    NARCIS (Netherlands)

    Vaart, van der A.W.; Zanten, van J.H.; Clarke, B.; Ghosal, S.

    2008-01-01

    We review definitions and properties of reproducing kernel Hilbert spaces attached to Gaussian variables and processes, with a view to applications in nonparametric Bayesian statistics using Gaussian priors. The rate of contraction of posterior distributions based on Gaussian priors can be described

  16. A synthesis of empirical plant dispersal kernels

    Czech Academy of Sciences Publication Activity Database

    Bullock, J. M.; González, L. M.; Tamme, R.; Götzenberger, Lars; White, S. M.; Pärtel, M.; Hooftman, D. A. P.

    2017-01-01

    Roč. 105, č. 1 (2017), s. 6-19 ISSN 0022-0477 Institutional support: RVO:67985939 Keywords : dispersal kernel * dispersal mode * probability density function Subject RIV: EH - Ecology, Behaviour OBOR OECD: Ecology Impact factor: 5.813, year: 2016

  17. Analytic continuation of weighted Bergman kernels

    Czech Academy of Sciences Publication Activity Database

    Engliš, Miroslav

    2010-01-01

    Roč. 94, č. 6 (2010), s. 622-650 ISSN 0021-7824 R&D Projects: GA AV ČR IAA100190802 Keywords : Bergman kernel * analytic continuation * Toeplitz operator Subject RIV: BA - General Mathematics Impact factor: 1.450, year: 2010 http://www.sciencedirect.com/science/article/pii/S0021782410000942

  18. On convergence of kernel learning estimators

    NARCIS (Netherlands)

    Norkin, V.I.; Keyzer, M.A.

    2009-01-01

    The paper studies convex stochastic optimization problems in a reproducing kernel Hilbert space (RKHS). The objective (risk) functional depends on functions from this RKHS and takes the form of a mathematical expectation (integral) of a nonnegative integrand (loss function) over a probability

  19. 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.)

  20. 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...

  1. Kernel Temporal Differences for Neural Decoding

    Science.gov (United States)

    Bae, Jihye; Sanchez Giraldo, Luis G.; Pohlmeyer, Eric A.; Francis, Joseph T.; Sanchez, Justin C.; Príncipe, José C.

    2015-01-01

    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. PMID:25866504

  2. Scattering kernels and cross sections working group

    International Nuclear Information System (INIS)

    Russell, G.; MacFarlane, B.; Brun, T.

    1998-01-01

    Topics addressed by this working group are: (1) immediate needs of the cold-moderator community and how to fill them; (2) synthetic scattering kernels; (3) very simple synthetic scattering functions; (4) measurements of interest; and (5) general issues. Brief summaries are given for each of these topics

  3. Enhanced gluten properties in soft kernel durum wheat

    Science.gov (United States)

    Soft kernel durum wheat is a relatively recent development (Morris et al. 2011 Crop Sci. 51:114). The soft kernel trait exerts profound effects on kernel texture, flour milling including break flour yield, milling energy, and starch damage, and dough water absorption (DWA). With the caveat of reduce...

  4. Predictive Model Equations for Palm Kernel (Elaeis guneensis J ...

    African Journals Online (AJOL)

    Estimated error of ± 0.18 and ± 0.2 are envisaged while applying the models for predicting palm kernel and sesame oil colours respectively. Keywords: Palm kernel, Sesame, Palm kernel, Oil Colour, Process Parameters, Model. Journal of Applied Science, Engineering and Technology Vol. 6 (1) 2006 pp. 34-38 ...

  5. 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

  6. 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 settlement...

  7. 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 producing...

  8. 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...

  9. 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...

  10. 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

  11. 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 almonds...

  12. Single pass kernel k-means clustering method

    Indian Academy of Sciences (India)

    paper proposes a simple and faster version of the kernel k-means clustering ... It has been considered as an important tool ... On the other hand, kernel-based clustering methods, like kernel k-means clus- ..... able at the UCI machine learning repository (Murphy 1994). ... All the data sets have only numeric valued features.

  13. Scuba: scalable kernel-based gene prioritization.

    Science.gov (United States)

    Zampieri, Guido; Tran, Dinh Van; Donini, Michele; Navarin, Nicolò; Aiolli, Fabio; Sperduti, Alessandro; Valle, Giorgio

    2018-01-25

    The uncovering of genes linked to human diseases is a pressing challenge in molecular biology and precision medicine. This task is often hindered by the large number of candidate genes and by the heterogeneity of the available information. Computational methods for the prioritization of candidate genes can help to cope with these problems. In particular, kernel-based methods are a powerful resource for the integration of heterogeneous biological knowledge, however, their practical implementation is often precluded by their limited scalability. We propose Scuba, a scalable kernel-based method for gene prioritization. It implements a novel multiple kernel learning approach, based on a semi-supervised perspective and on the optimization of the margin distribution. Scuba is optimized to cope with strongly unbalanced settings where known disease genes are few and large scale predictions are required. Importantly, it is able to efficiently deal both with a large amount of candidate genes and with an arbitrary number of data sources. As a direct consequence of scalability, Scuba integrates also a new efficient strategy to select optimal kernel parameters for each data source. We performed cross-validation experiments and simulated a realistic usage setting, showing that Scuba outperforms a wide range of state-of-the-art methods. Scuba achieves state-of-the-art performance and has enhanced scalability compared to existing kernel-based approaches for genomic data. This method can be useful to prioritize candidate genes, particularly when their number is large or when input data is highly heterogeneous. The code is freely available at https://github.com/gzampieri/Scuba .

  14. A laser optical method for detecting corn kernel defects

    Energy Technology Data Exchange (ETDEWEB)

    Gunasekaran, S.; Paulsen, M. R.; Shove, G. C.

    1984-01-01

    An opto-electronic instrument was developed to examine individual corn kernels and detect various kernel defects according to reflectance differences. A low power helium-neon (He-Ne) laser (632.8 nm, red light) was used as the light source in the instrument. Reflectance from good and defective parts of corn kernel surfaces differed by approximately 40%. Broken, chipped, and starch-cracked kernels were detected with nearly 100% accuracy; while surface-split kernels were detected with about 80% accuracy. (author)

  15. 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.

  16. Windows Vista Kernel-Mode: Functions, Security Enhancements and Flaws

    Directory of Open Access Journals (Sweden)

    Mohammed D. ABDULMALIK

    2008-06-01

    Full Text Available Microsoft has made substantial enhancements to the kernel of the Microsoft Windows Vista operating system. Kernel improvements are significant because the kernel provides low-level operating system functions, including thread scheduling, interrupt and exception dispatching, multiprocessor synchronization, and a set of routines and basic objects.This paper describes some of the kernel security enhancements for 64-bit edition of Windows Vista. We also point out some weakness areas (flaws that can be attacked by malicious leading to compromising the kernel.

  17. Difference between standard and quasi-conformal BFKL kernels

    International Nuclear Information System (INIS)

    Fadin, V.S.; Fiore, R.; Papa, A.

    2012-01-01

    As it was recently shown, the colour singlet BFKL kernel, taken in Möbius representation in the space of impact parameters, can be written in quasi-conformal shape, which is unbelievably simple compared with the conventional form of the BFKL kernel in momentum space. It was also proved that the total kernel is completely defined by its Möbius representation. In this paper we calculated the difference between standard and quasi-conformal BFKL kernels in momentum space and discovered that it is rather simple. Therefore we come to the conclusion that the simplicity of the quasi-conformal kernel is caused mainly by using the impact parameter space.

  18. Comparison of electron beam and gamma ray irradiations effects on ruminal crude protein and amino acid degradation kinetics, and in vitro digestibility of cottonseed meal

    International Nuclear Information System (INIS)

    Ghanbari, F.; Ghoorchi, T.; Shawrang, P.; Mansouri, H.; Torbati-Nejad, N.M.

    2012-01-01

    This study was conducted to compare effects of electron beam (EB) and gamma ray (GR) treatments at doses of 25, 50 and 75 kGy on ruminal degradation kinetics of crude protein (CP), amino acid (AA), and in vitro digestibility of cottonseed meal (CSM). Ionizing radiations of EB and GR had significant effects (P 0.05). Irradiation processing caused decrement in AA degradation after 16 h of ruminal incubation (P<0.05). EB irradiation was more effective than GR irradiation in lessening the ruminal degradability of AA (P<0.05). EB and GR treatments at a dose of 75 kGy increased in vitro digestibility of CSM numerically. This study showed that EB could cause CP and AA bypass rumen as well as GR. Therefore, ionizing irradiation processing can be used as an efficient method in improving nutritional value of CSM. - Highlights: ► Irradiation was effective on reducing ruminal degradability of cottonseed meal. ► Ionizing radiations, especially electron beam, lessened ruminal degradability of amino acid substantially. ► Irradiation processing could be used as a safe and efficient method in improving nutritional value of cottonseed meal.

  19. 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.

  20. Analytic scattering kernels for neutron thermalization studies

    International Nuclear Information System (INIS)

    Sears, V.F.

    1990-01-01

    Current plans call for the inclusion of a liquid hydrogen or deuterium cold source in the NRU replacement vessel. This report is part of an ongoing study of neutron thermalization in such a cold source. Here, we develop a simple analytical model for the scattering kernel of monatomic and diatomic liquids. We also present the results of extensive numerical calculations based on this model for liquid hydrogen, liquid deuterium, and mixtures of the two. These calculations demonstrate the dependence of the scattering kernel on the incident and scattered-neutron energies, the behavior near rotational thresholds, the dependence on the centre-of-mass pair correlations, the dependence on the ortho concentration, and the dependence on the deuterium concentration in H 2 /D 2 mixtures. The total scattering cross sections are also calculated and compared with available experimental results

  1. Quantized kernel least mean square algorithm.

    Science.gov (United States)

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

    2012-01-01

    In this paper, we propose a quantization approach, as an alternative of sparsification, to curb the growth of the radial basis function structure in kernel adaptive filtering. The basic idea behind this method is to quantize and hence compress the input (or feature) space. Different from sparsification, the new approach uses the "redundant" data to update the coefficient of the closest center. In particular, a quantized kernel least mean square (QKLMS) algorithm is developed, which is based on a simple online vector quantization method. The analytical study of the mean square convergence has been carried out. The energy conservation relation for QKLMS is established, and on this basis we arrive at a sufficient condition for mean square convergence, and a lower and upper bound on the theoretical value of the steady-state excess mean square error. Static function estimation and short-term chaotic time-series prediction examples are presented to demonstrate the excellent performance.

  2. Kernel-based tests for joint independence

    DEFF Research Database (Denmark)

    Pfister, Niklas; Bühlmann, Peter; Schölkopf, Bernhard

    2018-01-01

    if the $d$ variables are jointly independent, as long as the kernel is characteristic. Based on an empirical estimate of dHSIC, we define three different non-parametric hypothesis tests: a permutation test, a bootstrap test and a test based on a Gamma approximation. We prove that the permutation test......We investigate the problem of testing whether $d$ random variables, which may or may not be continuous, are jointly (or mutually) independent. Our method builds on ideas of the two variable Hilbert-Schmidt independence criterion (HSIC) but allows for an arbitrary number of variables. We embed...... the $d$-dimensional joint distribution and the product of the marginals into a reproducing kernel Hilbert space and define the $d$-variable Hilbert-Schmidt independence criterion (dHSIC) as the squared distance between the embeddings. In the population case, the value of dHSIC is zero if and only...

  3. 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.

  4. A Kernel for Protein Secondary Structure Prediction

    OpenAIRE

    Guermeur , Yann; Lifchitz , Alain; Vert , Régis

    2004-01-01

    http://mitpress.mit.edu/catalog/item/default.asp?ttype=2&tid=10338&mode=toc; International audience; Multi-class support vector machines have already proved efficient in protein secondary structure prediction as ensemble methods, to combine the outputs of sets of classifiers based on different principles. In this chapter, their implementation as basic prediction methods, processing the primary structure or the profile of multiple alignments, is investigated. A kernel devoted to the task is in...

  5. Scalar contribution to the BFKL kernel

    International Nuclear Information System (INIS)

    Gerasimov, R. E.; Fadin, V. S.

    2010-01-01

    The contribution of scalar particles to the kernel of the Balitsky-Fadin-Kuraev-Lipatov (BFKL) equation is calculated. A great cancellation between the virtual and real parts of this contribution, analogous to the cancellation in the quark contribution in QCD, is observed. The reason of this cancellation is discovered. This reason has a common nature for particles with any spin. Understanding of this reason permits to obtain the total contribution without the complicated calculations, which are necessary for finding separate pieces.

  6. Weighted Bergman Kernels for Logarithmic Weights

    Czech Academy of Sciences Publication Activity Database

    Engliš, Miroslav

    2010-01-01

    Roč. 6, č. 3 (2010), s. 781-813 ISSN 1558-8599 R&D Projects: GA AV ČR IAA100190802 Keywords : Bergman kernel * Toeplitz operator * logarithmic weight * pseudodifferential operator Subject RIV: BA - General Mathematics Impact factor: 0.462, year: 2010 http://www.intlpress.com/site/pub/pages/journals/items/pamq/content/vols/0006/0003/a008/

  7. Heat kernels and zeta functions on fractals

    International Nuclear Information System (INIS)

    Dunne, Gerald V

    2012-01-01

    On fractals, spectral functions such as heat kernels and zeta functions exhibit novel features, very different from their behaviour on regular smooth manifolds, and these can have important physical consequences for both classical and quantum physics in systems having fractal properties. This article is part of a special issue of Journal of Physics A: Mathematical and Theoretical in honour of Stuart Dowker's 75th birthday devoted to ‘Applications of zeta functions and other spectral functions in mathematics and physics’. (paper)

  8. Exploiting graph kernels for high performance biomedical relation extraction.

    Science.gov (United States)

    Panyam, Nagesh C; Verspoor, Karin; Cohn, Trevor; Ramamohanarao, Kotagiri

    2018-01-30

    Relation extraction from biomedical publications is an important task in the area of semantic mining of text. Kernel methods for supervised relation extraction are often preferred over manual feature engineering methods, when classifying highly ordered structures such as trees and graphs obtained from syntactic parsing of a sentence. Tree kernels such as the Subset Tree Kernel and Partial Tree Kernel have been shown to be effective for classifying constituency parse trees and basic dependency parse graphs of a sentence. Graph kernels such as the All Path Graph kernel (APG) and Approximate Subgraph Matching (ASM) kernel have been shown to be suitable for classifying general graphs with cycles, such as the enhanced dependency parse graph of a sentence. In this work, we present a high performance Chemical-Induced Disease (CID) relation extraction system. We present a comparative study of kernel methods for the CID task and also extend our study to the Protein-Protein Interaction (PPI) extraction task, an important biomedical relation extraction task. We discuss novel modifications to the ASM kernel to boost its performance and a method to apply graph kernels for extracting relations expressed in multiple sentences. Our system for CID relation extraction attains an F-score of 60%, without using external knowledge sources or task specific heuristic or rules. In comparison, the state of the art Chemical-Disease Relation Extraction system achieves an F-score of 56% using an ensemble of multiple machine learning methods, which is then boosted to 61% with a rule based system employing task specific post processing rules. For the CID task, graph kernels outperform tree kernels substantially, and the best performance is obtained with APG kernel that attains an F-score of 60%, followed by the ASM kernel at 57%. The performance difference between the ASM and APG kernels for CID sentence level relation extraction is not significant. In our evaluation of ASM for the PPI task, ASM

  9. 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.

  10. 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.

  11. 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 ......- tor transform outperform the linear methods as well as kernel principal components in producing interesting projections of the data.......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...... including principal component analysis and maximum autocorrelation factor analysis. The latter utilizes the fact that interesting phenomena in images exhibit spatial autocorrelation. However, linear projections often fail to grasp the underlying variability on the data. Therefore we propose to use so...

  12. 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.

  13. LZW-Kernel: fast kernel utilizing variable length code blocks from LZW compressors for protein sequence classification.

    Science.gov (United States)

    Filatov, Gleb; Bauwens, Bruno; Kertész-Farkas, Attila

    2018-05-07

    Bioinformatics studies often rely on similarity measures between sequence pairs, which often pose a bottleneck in large-scale sequence analysis. Here, we present a new convolutional kernel function for protein sequences called the LZW-Kernel. It is based on code words identified with the Lempel-Ziv-Welch (LZW) universal text compressor. The LZW-Kernel is an alignment-free method, it is always symmetric, is positive, always provides 1.0 for self-similarity and it can directly be used with Support Vector Machines (SVMs) in classification problems, contrary to normalized compression distance (NCD), which often violates the distance metric properties in practice and requires further techniques to be used with SVMs. The LZW-Kernel is a one-pass algorithm, which makes it particularly plausible for big data applications. Our experimental studies on remote protein homology detection and protein classification tasks reveal that the LZW-Kernel closely approaches the performance of the Local Alignment Kernel (LAK) and the SVM-pairwise method combined with Smith-Waterman (SW) scoring at a fraction of the time. Moreover, the LZW-Kernel outperforms the SVM-pairwise method when combined with BLAST scores, which indicates that the LZW code words might be a better basis for similarity measures than local alignment approximations found with BLAST. In addition, the LZW-Kernel outperforms n-gram based mismatch kernels, hidden Markov model based SAM and Fisher kernel, and protein family based PSI-BLAST, among others. Further advantages include the LZW-Kernel's reliance on a simple idea, its ease of implementation, and its high speed, three times faster than BLAST and several magnitudes faster than SW or LAK in our tests. LZW-Kernel is implemented as a standalone C code and is a free open-source program distributed under GPLv3 license and can be downloaded from https://github.com/kfattila/LZW-Kernel. akerteszfarkas@hse.ru. Supplementary data are available at Bioinformatics Online.

  14. Kernel based eigenvalue-decomposition methods for analysing ham

    DEFF Research Database (Denmark)

    Christiansen, Asger Nyman; Nielsen, Allan Aasbjerg; Møller, Flemming

    2010-01-01

    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...... useful factor of PCA and kernel based PCA respectively in Figure 2. The factor of the kernel based PCA turned out to be able to segment the two types of meat and in general that factor is much more distinct, compared to the traditional factor. After the orthogonal transformation a simple thresholding...

  15. 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....

  16. Ideal gas scattering kernel for energy dependent cross-sections

    International Nuclear Information System (INIS)

    Rothenstein, W.; Dagan, R.

    1998-01-01

    A third, and final, paper on the calculation of the joint kernel for neutron scattering by an ideal gas in thermal agitation is presented, when the scattering cross-section is energy dependent. The kernel is a function of the neutron energy after scattering, and of the cosine of the scattering angle, as in the case of the ideal gas kernel for a constant bound atom scattering cross-section. The final expression is suitable for numerical calculations

  17. 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. © The Author 2015. Published by Oxford University Press on behalf of Poultry Science Association.

  18. 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.

  19. Embedded real-time operating system micro kernel design

    Science.gov (United States)

    Cheng, Xiao-hui; Li, Ming-qiang; Wang, Xin-zheng

    2005-12-01

    Embedded systems usually require a real-time character. Base on an 8051 microcontroller, an embedded real-time operating system micro kernel is proposed consisting of six parts, including a critical section process, task scheduling, interruption handle, semaphore and message mailbox communication, clock managent and memory managent. Distributed CPU and other resources are among tasks rationally according to the importance and urgency. The design proposed here provides the position, definition, function and principle of micro kernel. The kernel runs on the platform of an ATMEL AT89C51 microcontroller. Simulation results prove that the designed micro kernel is stable and reliable and has quick response while operating in an application system.

  20. An SVM model with hybrid kernels for hydrological time series

    Science.gov (United States)

    Wang, C.; Wang, H.; Zhao, X.; Xie, Q.

    2017-12-01

    Support Vector Machine (SVM) models have been widely applied to the forecast of climate/weather and its impact on other environmental variables such as hydrologic response to climate/weather. When using SVM, the choice of the kernel function plays the key role. Conventional SVM models mostly use one single type of kernel function, e.g., radial basis kernel function. Provided that there are several featured kernel functions available, each having its own advantages and drawbacks, a combination of these kernel functions may give more flexibility and robustness to SVM approach, making it suitable for a wide range of application scenarios. This paper presents such a linear combination of radial basis kernel and polynomial kernel for the forecast of monthly flowrate in two gaging stations using SVM approach. The results indicate significant improvement in the accuracy of predicted series compared to the approach with either individual kernel function, thus demonstrating the feasibility and advantages of such hybrid kernel approach for SVM applications.

  1. 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.

  2. Dose point kernels for beta-emitting radioisotopes

    International Nuclear Information System (INIS)

    Prestwich, W.V.; Chan, L.B.; Kwok, C.S.; Wilson, B.

    1986-01-01

    Knowledge of the dose point kernel corresponding to a specific radionuclide is required to calculate the spatial dose distribution produced in a homogeneous medium by a distributed source. Dose point kernels for commonly used radionuclides have been calculated previously using as a basis monoenergetic dose point kernels derived by numerical integration of a model transport equation. The treatment neglects fluctuations in energy deposition, an effect which has been later incorporated in dose point kernels calculated using Monte Carlo methods. This work describes new calculations of dose point kernels using the Monte Carlo results as a basis. An analytic representation of the monoenergetic dose point kernels has been developed. This provides a convenient method both for calculating the dose point kernel associated with a given beta spectrum and for incorporating the effect of internal conversion. An algebraic expression for allowed beta spectra has been accomplished through an extension of the Bethe-Bacher approximation, and tested against the exact expression. Simplified expression for first-forbidden shape factors have also been developed. A comparison of the calculated dose point kernel for 32 P with experimental data indicates good agreement with a significant improvement over the earlier results in this respect. An analytic representation of the dose point kernel associated with the spectrum of a single beta group has been formulated. 9 references, 16 figures, 3 tables

  3. Hadamard Kernel SVM with applications for breast cancer outcome predictions.

    Science.gov (United States)

    Jiang, Hao; Ching, Wai-Ki; Cheung, Wai-Shun; Hou, Wenpin; Yin, Hong

    2017-12-21

    Breast cancer is one of the leading causes of deaths for women. It is of great necessity to develop effective methods for breast cancer detection and diagnosis. Recent studies have focused on gene-based signatures for outcome predictions. Kernel SVM for its discriminative power in dealing with small sample pattern recognition problems has attracted a lot attention. But how to select or construct an appropriate kernel for a specified problem still needs further investigation. Here we propose a novel kernel (Hadamard Kernel) in conjunction with Support Vector Machines (SVMs) to address the problem of breast cancer outcome prediction using gene expression data. Hadamard Kernel outperform the classical kernels and correlation kernel in terms of Area under the ROC Curve (AUC) values where a number of real-world data sets are adopted to test the performance of different methods. Hadamard Kernel SVM is effective for breast cancer predictions, either in terms of prognosis or diagnosis. It may benefit patients by guiding therapeutic options. Apart from that, it would be a valuable addition to the current SVM kernel families. We hope it will contribute to the wider biology and related communities.

  4. 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....

  5. Analysis of Advanced Fuel Kernel Technology

    International Nuclear Information System (INIS)

    Oh, Seung Chul; Jeong, Kyung Chai; Kim, Yeon Ku; Kim, Young Min; Kim, Woong Ki; Lee, Young Woo; Cho, Moon Sung

    2010-03-01

    The reference fuel for prismatic reactor concepts is based on use of an LEU UCO TRISO fissile particle. This fuel form was selected in the early 1980s for large high-temperature gas-cooled reactor (HTGR) concepts using LEU, and the selection was reconfirmed for modular designs in the mid-1980s. Limited existing irradiation data on LEU UCO TRISO fuel indicate the need for a substantial improvement in performance with regard to in-pile gaseous fission product release. Existing accident testing data on LEU UCO TRISO fuel are extremely limited, but it is generally expected that performance would be similar to that of LEU UO 2 TRISO fuel if performance under irradiation were successfully improved. Initial HTGR fuel technology was based on carbide fuel forms. In the early 1980s, as HTGR technology was transitioning from high-enriched uranium (HEU) fuel to LEU fuel. An initial effort focused on LEU prismatic design for large HTGRs resulted in the selection of UCO kernels for the fissile particles and thorium oxide (ThO 2 ) for the fertile particles. The primary reason for selection of the UCO kernel over UO 2 was reduced CO pressure, allowing higher burnup for equivalent coating thicknesses and reduced potential for kernel migration, an important failure mechanism in earlier fuels. A subsequent assessment in the mid-1980s considering modular HTGR concepts again reached agreement on UCO for the fissile particle for a prismatic design. In the early 1990s, plant cost-reduction studies led to a decision to change the fertile material from thorium to natural uranium, primarily because of a lower long-term decay heat level for the natural uranium fissile particles. Ongoing economic optimization in combination with anticipated capabilities of the UCO particles resulted in peak fissile particle burnup projection of 26% FIMA in steam cycle and gas turbine concepts

  6. Learning Rotation for Kernel Correlation Filter

    KAUST Repository

    Hamdi, Abdullah

    2017-08-11

    Kernel Correlation Filters have shown a very promising scheme for visual tracking in terms of speed and accuracy on several benchmarks. However it suffers from problems that affect its performance like occlusion, rotation and scale change. This paper tries to tackle the problem of rotation by reformulating the optimization problem for learning the correlation filter. This modification (RKCF) includes learning rotation filter that utilizes circulant structure of HOG feature to guesstimate rotation from one frame to another and enhance the detection of KCF. Hence it gains boost in overall accuracy in many of OBT50 detest videos with minimal additional computation.

  7. Research of Performance Linux Kernel File Systems

    Directory of Open Access Journals (Sweden)

    Andrey Vladimirovich Ostroukh

    2015-10-01

    Full Text Available The article describes the most common Linux Kernel File Systems. The research was carried out on a personal computer, the characteristics of which are written in the article. The study was performed on a typical workstation running GNU/Linux with below characteristics. On a personal computer for measuring the file performance, has been installed the necessary software. Based on the results, conclusions and proposed recommendations for use of file systems. Identified and recommended by the best ways to store data.

  8. Fixed kernel regression for voltammogram feature extraction

    International Nuclear Information System (INIS)

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

    2009-01-01

    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

  9. Reciprocity relation for multichannel coupling kernels

    International Nuclear Information System (INIS)

    Cotanch, S.R.; Satchler, G.R.

    1981-01-01

    Assuming time-reversal invariance of the many-body Hamiltonian, it is proven that the kernels in a general coupled-channels formulation are symmetric, to within a specified spin-dependent phase, under the interchange of channel labels and coordinates. The theorem is valid for both Hermitian and suitably chosen non-Hermitian Hamiltonians which contain complex effective interactions. While of direct practical consequence for nuclear rearrangement reactions, the reciprocity relation is also appropriate for other areas of physics which involve coupled-channels analysis

  10. Wheat kernel dimensions: how do they contribute to kernel weight at ...

    Indian Academy of Sciences (India)

    2011-12-02

    Dec 2, 2011 ... yield components, is greatly influenced by kernel dimensions. (KD), such as ..... six linkage gaps, and it covered 3010.70 cM of the whole genome with an ...... Ersoz E. et al. 2009 The Genetic architecture of maize flowering.

  11. Kernel Multivariate Analysis Framework for Supervised Subspace Learning: A Tutorial on Linear and Kernel Multivariate Methods

    DEFF Research Database (Denmark)

    Arenas-Garcia, J.; Petersen, K.; Camps-Valls, G.

    2013-01-01

    correlation analysis (CCA), and orthonormalized PLS (OPLS), as well as their nonlinear extensions derived by means of the theory of reproducing kernel Hilbert spaces (RKHSs). We also review their connections to other methods for classification and statistical dependence estimation and introduce some recent...

  12. Linked-cluster formulation of electron-hole interaction kernel in real-space representation without using unoccupied states.

    Science.gov (United States)

    Bayne, Michael G; Scher, Jeremy A; Ellis, Benjamin H; Chakraborty, Arindam

    2018-05-21

    Electron-hole or quasiparticle representation plays a central role in describing electronic excitations in many-electron systems. For charge-neutral excitation, the electron-hole interaction kernel is the quantity of interest for calculating important excitation properties such as optical gap, optical spectra, electron-hole recombination and electron-hole binding energies. The electron-hole interaction kernel can be formally derived from the density-density correlation function using both Green's function and TDDFT formalism. The accurate determination of the electron-hole interaction kernel remains a significant challenge for precise calculations of optical properties in the GW+BSE formalism. From the TDDFT perspective, the electron-hole interaction kernel has been viewed as a path to systematic development of frequency-dependent exchange-correlation functionals. Traditional approaches, such as MBPT formalism, use unoccupied states (which are defined with respect to Fermi vacuum) to construct the electron-hole interaction kernel. However, the inclusion of unoccupied states has long been recognized as the leading computational bottleneck that limits the application of this approach for larger finite systems. In this work, an alternative derivation that avoids using unoccupied states to construct the electron-hole interaction kernel is presented. The central idea of this approach is to use explicitly correlated geminal functions for treating electron-electron correlation for both ground and excited state wave functions. Using this ansatz, it is derived using both diagrammatic and algebraic techniques that the electron-hole interaction kernel can be expressed only in terms of linked closed-loop diagrams. It is proved that the cancellation of unlinked diagrams is a consequence of linked-cluster theorem in real-space representation. The electron-hole interaction kernel derived in this work was used to calculate excitation energies in many-electron systems and results

  13. 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. Copyright © 2014 Elsevier Ltd. All rights reserved.

  14. 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.

  15. Consistent Valuation across Curves Using Pricing Kernels

    Directory of Open Access Journals (Sweden)

    Andrea Macrina

    2018-03-01

    Full Text Available The general problem of asset pricing when the discount rate differs from the rate at which an asset’s cash flows accrue is considered. A pricing kernel framework is used to model an economy that is segmented into distinct markets, each identified by a yield curve having its own market, credit and liquidity risk characteristics. The proposed framework precludes arbitrage within each market, while the definition of a curve-conversion factor process links all markets in a consistent arbitrage-free manner. A pricing formula is then derived, referred to as the across-curve pricing formula, which enables consistent valuation and hedging of financial instruments across curves (and markets. As a natural application, a consistent multi-curve framework is formulated for emerging and developed inter-bank swap markets, which highlights an important dual feature of the curve-conversion factor process. Given this multi-curve framework, existing multi-curve approaches based on HJM and rational pricing kernel models are recovered, reviewed and generalised and single-curve models extended. In another application, inflation-linked, currency-based and fixed-income hybrid securities are shown to be consistently valued using the across-curve valuation method.

  16. Aligning Biomolecular Networks Using Modular Graph Kernels

    Science.gov (United States)

    Towfic, Fadi; Greenlee, M. Heather West; Honavar, Vasant

    Comparative analysis of biomolecular networks constructed using measurements from different conditions, tissues, and organisms offer a powerful approach to understanding the structure, function, dynamics, and evolution of complex biological systems. We explore a class of algorithms for aligning large biomolecular networks by breaking down such networks into subgraphs and computing the alignment of the networks based on the alignment of their subgraphs. The resulting subnetworks are compared using graph kernels as scoring functions. We provide implementations of the resulting algorithms as part of BiNA, an open source biomolecular network alignment toolkit. Our experiments using Drosophila melanogaster, Saccharomyces cerevisiae, Mus musculus and Homo sapiens protein-protein interaction networks extracted from the DIP repository of protein-protein interaction data demonstrate that the performance of the proposed algorithms (as measured by % GO term enrichment of subnetworks identified by the alignment) is competitive with some of the state-of-the-art algorithms for pair-wise alignment of large protein-protein interaction networks. Our results also show that the inter-species similarity scores computed based on graph kernels can be used to cluster the species into a species tree that is consistent with the known phylogenetic relationships among the species.

  17. 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.

  18. Formal truncations of connected kernel equations

    International Nuclear Information System (INIS)

    Dixon, R.M.

    1977-01-01

    The Connected Kernel Equations (CKE) of Alt, Grassberger and Sandhas (AGS); Kouri, Levin and Tobocman (KLT); and Bencze, Redish and Sloan (BRS) are compared against reaction theory criteria after formal channel space and/or operator truncations have been introduced. The Channel Coupling Class concept is used to study the structure of these CKE's. The related wave function formalism of Sandhas, of L'Huillier, Redish and Tandy and of Kouri, Krueger and Levin are also presented. New N-body connected kernel equations which are generalizations of the Lovelace three-body equations are derived. A method for systematically constructing fewer body models from the N-body BRS and generalized Lovelace (GL) equations is developed. The formally truncated AGS, BRS, KLT and GL equations are analyzed by employing the criteria of reciprocity and two-cluster unitarity. Reciprocity considerations suggest that formal truncations of BRS, KLT and GL equations can lead to reciprocity-violating results. This study suggests that atomic problems should employ three-cluster connected truncations and that the two-cluster connected truncations should be a useful starting point for nuclear systems

  19. 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.

  20. Delimiting areas of endemism through kernel interpolation.

    Science.gov (United States)

    Oliveira, Ubirajara; Brescovit, Antonio D; Santos, Adalberto J

    2015-01-01

    We propose a new approach for identification of areas of endemism, the Geographical Interpolation of Endemism (GIE), based on kernel spatial interpolation. This method differs from others in being independent of grid cells. This new approach is based on estimating the overlap between the distribution of species through a kernel interpolation of centroids of species distribution and areas of influence defined from the distance between the centroid and the farthest point of occurrence of each species. We used this method to delimit areas of endemism of spiders from Brazil. To assess the effectiveness of GIE, we analyzed the same data using Parsimony Analysis of Endemism and NDM and compared the areas identified through each method. The analyses using GIE identified 101 areas of endemism of spiders in Brazil GIE demonstrated to be effective in identifying areas of endemism in multiple scales, with fuzzy edges and supported by more synendemic species than in the other methods. The areas of endemism identified with GIE were generally congruent with those identified for other taxonomic groups, suggesting that common processes can be responsible for the origin and maintenance of these biogeographic units.

  1. Delimiting areas of endemism through kernel interpolation.

    Directory of Open Access Journals (Sweden)

    Ubirajara Oliveira

    Full Text Available We propose a new approach for identification of areas of endemism, the Geographical Interpolation of Endemism (GIE, based on kernel spatial interpolation. This method differs from others in being independent of grid cells. This new approach is based on estimating the overlap between the distribution of species through a kernel interpolation of centroids of species distribution and areas of influence defined from the distance between the centroid and the farthest point of occurrence of each species. We used this method to delimit areas of endemism of spiders from Brazil. To assess the effectiveness of GIE, we analyzed the same data using Parsimony Analysis of Endemism and NDM and compared the areas identified through each method. The analyses using GIE identified 101 areas of endemism of spiders in Brazil GIE demonstrated to be effective in identifying areas of endemism in multiple scales, with fuzzy edges and supported by more synendemic species than in the other methods. The areas of endemism identified with GIE were generally congruent with those identified for other taxonomic groups, suggesting that common processes can be responsible for the origin and maintenance of these biogeographic units.

  2. Evaluating and interpreting the chemical relevance of the linear response kernel for atoms II: open shell.

    Science.gov (United States)

    Boisdenghien, Zino; Fias, Stijn; Van Alsenoy, Christian; De Proft, Frank; Geerlings, Paul

    2014-07-28

    Most of the work done on the linear response kernel χ(r,r') has focussed on its atom-atom condensed form χAB. Our previous work [Boisdenghien et al., J. Chem. Theory Comput., 2013, 9, 1007] was the first effort to truly focus on the non-condensed form of this function for closed (sub)shell atoms in a systematic fashion. In this work, we extend our method to the open shell case. To simplify the plotting of our results, we average our results to a symmetrical quantity χ(r,r'). This allows us to plot the linear response kernel for all elements up to and including argon and to investigate the periodicity throughout the first three rows in the periodic table and in the different representations of χ(r,r'). Within the context of Spin Polarized Conceptual Density Functional Theory, the first two-dimensional plots of spin polarized linear response functions are presented and commented on for some selected cases on the basis of the atomic ground state electronic configurations. Using the relation between the linear response kernel and the polarizability we compare the values of the polarizability tensor calculated using our method to high-level values.

  3. Kernel method for air quality modelling. II. Comparison with analytic solutions

    Energy Technology Data Exchange (ETDEWEB)

    Lorimer, G S; Ross, D G

    1986-01-01

    The performance of Lorimer's (1986) kernel method for solving the advection-diffusion equation is tested for instantaneous and continuous emissions into a variety of model atmospheres. Analytical solutions are available for comparison in each case. The results indicate that a modest minicomputer is quite adequate for obtaining satisfactory precision even for the most trying test performed here, which involves a diffusivity tensor and wind speed which are nonlinear functions of the height above ground. Simulations of the same cases by the particle-in-cell technique are found to provide substantially lower accuracy even when use is made of greater computer resources.

  4. Proteomic comparison by iTRAQ combined with mass spectrometry of egg white proteins in laying hens (Gallus gallus) fed with soybean meal and cottonseed meal

    Science.gov (United States)

    He, Tao; Zhang, Haijun; Wang, Jing; Wu, Shugeng; Yue, Hongyuan; Qi, Guanghai

    2017-01-01

    Cottonseed meal (CSM) is commonly used in hens’ diets to replace soybean meal (SBM). However, the molecular consequences of this substitution remains unclear. To investigate the impact of this substitution at the molecular level, iTRAQ combined with biochemical analysis was performed in Hy-Line W-36 hens supplemented with a mixed diet of CSM and SBM. Egg weight, albumen height, and Haugh unit were significantly reduced in the CSM100 group (100% crude protein of SBM replaced by CSM) compared with the SBM group (Phen diet. PMID:28813468

  5. 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

  6. Replacement Value of Palm Kernel Meal for Maize on Carcass ...

    African Journals Online (AJOL)

    This study was conducted to evaluate the effect of replacing maize with palm kernel meal on nutrient composition, fatty acid profile and sensory qualities of the meat of turkeys fed the dietary treatments. Six dietary treatments were formulated using palm kernel meal to replace maize at 0, 20, 40, 60, 80 and 100 percent.

  7. Effect of Palm Kernel Cake Replacement and Enzyme ...

    African Journals Online (AJOL)

    A feeding trial which lasted for twelve weeks was conducted to study the performance of finisher pigs fed five different levels of palm kernel cake replacement for maize (0%, 40%, 40%, 60%, 60%) in a maize-palm kernel cake based ration with or without enzyme supplementation. It was a completely randomized design ...

  8. Capturing option anomalies with a variance-dependent pricing kernel

    NARCIS (Netherlands)

    Christoffersen, P.; Heston, S.; Jacobs, K.

    2013-01-01

    We develop a GARCH option model with a variance premium by combining the Heston-Nandi (2000) dynamic with a new pricing kernel that nests Rubinstein (1976) and Brennan (1979). While the pricing kernel is monotonic in the stock return and in variance, its projection onto the stock return is

  9. 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...

  10. Commutators of Integral Operators with Variable Kernels on Hardy ...

    Indian Academy of Sciences (India)

    Home; Journals; Proceedings – Mathematical Sciences; Volume 115; Issue 4. Commutators of Integral Operators with Variable Kernels on Hardy Spaces. Pu Zhang Kai Zhao. Volume 115 Issue 4 November 2005 pp 399-410 ... Keywords. Singular and fractional integrals; variable kernel; commutator; Hardy space.

  11. Discrete non-parametric kernel estimation for global sensitivity analysis

    International Nuclear Information System (INIS)

    Senga Kiessé, Tristan; Ventura, Anne

    2016-01-01

    This work investigates the discrete kernel approach for evaluating the contribution of the variance of discrete input variables to the variance of model output, via analysis of variance (ANOVA) decomposition. Until recently only the continuous kernel approach has been applied as a metamodeling approach within sensitivity analysis framework, for both discrete and continuous input variables. Now the discrete kernel estimation is known to be suitable for smoothing discrete functions. We present a discrete non-parametric kernel estimator of ANOVA decomposition of a given model. An estimator of sensitivity indices is also presented with its asymtotic convergence rate. Some simulations on a test function analysis and a real case study from agricultural have shown that the discrete kernel approach outperforms the continuous kernel one for evaluating the contribution of moderate or most influential discrete parameters to the model output. - Highlights: • We study a discrete kernel estimation for sensitivity analysis of a model. • A discrete kernel estimator of ANOVA decomposition of the model is presented. • Sensitivity indices are calculated for discrete input parameters. • An estimator of sensitivity indices is also presented with its convergence rate. • An application is realized for improving the reliability of environmental models.

  12. Kernel Function Tuning for Single-Layer Neural Networks

    Czech Academy of Sciences Publication Activity Database

    Vidnerová, Petra; Neruda, Roman

    -, accepted 28.11. 2017 (2018) ISSN 2278-0149 R&D Projects: GA ČR GA15-18108S Institutional support: RVO:67985807 Keywords : single-layer neural networks * kernel methods * kernel function * optimisation Subject RIV: IN - Informatics, Computer Science http://www.ijmerr.com/

  13. Geodesic exponential kernels: When Curvature and Linearity Conflict

    DEFF Research Database (Denmark)

    Feragen, Aase; Lauze, François; Hauberg, Søren

    2015-01-01

    manifold, the geodesic Gaussian kernel is only positive definite if the Riemannian manifold is Euclidean. This implies that any attempt to design geodesic Gaussian kernels on curved Riemannian manifolds is futile. However, we show that for spaces with conditionally negative definite distances the geodesic...

  14. Denoising by semi-supervised kernel PCA preimaging

    DEFF Research Database (Denmark)

    Hansen, Toke Jansen; Abrahamsen, Trine Julie; Hansen, Lars Kai

    2014-01-01

    Kernel Principal Component Analysis (PCA) has proven a powerful tool for nonlinear feature extraction, and is often applied as a pre-processing step for classification algorithms. In denoising applications Kernel PCA provides the basis for dimensionality reduction, prior to the so-called pre-imag...

  15. Design and construction of palm kernel cracking and separation ...

    African Journals Online (AJOL)

    Design and construction of palm kernel cracking and separation machines. ... Username, Password, Remember me, or Register. DOWNLOAD FULL TEXT Open Access DOWNLOAD FULL TEXT Subscription or Fee Access. Design and construction of palm kernel cracking and separation machines. JO Nordiana, K ...

  16. 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 a...

  17. Genetic relationship between plant growth, shoot and kernel sizes in ...

    African Journals Online (AJOL)

    Maize (Zea mays L.) ear vascular tissue transports nutrients that contribute to grain yield. To assess kernel heritabilities that govern ear development and plant growth, field studies were conducted to determine the combining abilities of parents that differed for kernel-size, grain-filling rates and shoot-size. Thirty two hybrids ...

  18. A relationship between Gel'fand-Levitan and Marchenko kernels

    International Nuclear Information System (INIS)

    Kirst, T.; Von Geramb, H.V.; Amos, K.A.

    1989-01-01

    An integral equation which relates the output kernels of the Gel'fand-Levitan and Marchenko inverse scattering equations is specified. Structural details of this integral equation are studied when the S-matrix is a rational function, and the output kernels are separable in terms of Bessel, Hankel and Jost solutions. 4 refs

  19. Boundary singularity of Poisson and harmonic Bergman kernels

    Czech Academy of Sciences Publication Activity Database

    Engliš, Miroslav

    2015-01-01

    Roč. 429, č. 1 (2015), s. 233-272 ISSN 0022-247X R&D Projects: GA AV ČR IAA100190802 Institutional support: RVO:67985840 Keywords : harmonic Bergman kernel * Poisson kernel * pseudodifferential boundary operators Subject RIV: BA - General Mathematics Impact factor: 1.014, year: 2015 http://www.sciencedirect.com/science/article/pii/S0022247X15003170

  20. Real time kernel performance monitoring with SystemTap

    CERN Multimedia

    CERN. Geneva

    2018-01-01

    SystemTap is a dynamic method of monitoring and tracing the operation of a running Linux kernel. In this talk I will present a few practical use cases where SystemTap allowed me to turn otherwise complex userland monitoring tasks in simple kernel probes.

  1. 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.

  2. Reproducing Kernels and Coherent States on Julia Sets

    Energy Technology Data Exchange (ETDEWEB)

    Thirulogasanthar, K., E-mail: santhar@cs.concordia.ca; Krzyzak, A. [Concordia University, Department of Computer Science and Software Engineering (Canada)], E-mail: krzyzak@cs.concordia.ca; Honnouvo, G. [Concordia University, Department of Mathematics and Statistics (Canada)], E-mail: g_honnouvo@yahoo.fr

    2007-11-15

    We construct classes of coherent states on domains arising from dynamical systems. An orthonormal family of vectors associated to the generating transformation of a Julia set is found as a family of square integrable vectors, and, thereby, reproducing kernels and reproducing kernel Hilbert spaces are associated to Julia sets. We also present analogous results on domains arising from iterated function systems.

  3. Reproducing Kernels and Coherent States on Julia Sets

    International Nuclear Information System (INIS)

    Thirulogasanthar, K.; Krzyzak, A.; Honnouvo, G.

    2007-01-01

    We construct classes of coherent states on domains arising from dynamical systems. An orthonormal family of vectors associated to the generating transformation of a Julia set is found as a family of square integrable vectors, and, thereby, reproducing kernels and reproducing kernel Hilbert spaces are associated to Julia sets. We also present analogous results on domains arising from iterated function systems

  4. 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...

  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. An analysis of 1-D smoothed particle hydrodynamics kernels

    International Nuclear Information System (INIS)

    Fulk, D.A.; Quinn, D.W.

    1996-01-01

    In this paper, the smoothed particle hydrodynamics (SPH) kernel is analyzed, resulting in measures of merit for one-dimensional SPH. Various methods of obtaining an objective measure of the quality and accuracy of the SPH kernel are addressed. Since the kernel is the key element in the SPH methodology, this should be of primary concern to any user of SPH. The results of this work are two measures of merit, one for smooth data and one near shocks. The measure of merit for smooth data is shown to be quite accurate and a useful delineator of better and poorer kernels. The measure of merit for non-smooth data is not quite as accurate, but results indicate the kernel is much less important for these types of problems. In addition to the theory, 20 kernels are analyzed using the measure of merit demonstrating the general usefulness of the measure of merit and the individual kernels. In general, it was decided that bell-shaped kernels perform better than other shapes. 12 refs., 16 figs., 7 tabs

  7. 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…

  8. Computing an element in the lexicographic kernel of a game

    NARCIS (Netherlands)

    Faigle, U.; Kern, Walter; Kuipers, Jeroen

    The lexicographic kernel of a game lexicographically maximizes the surplusses $s_{ij}$ (rather than the excesses as would the nucleolus). We show that an element in the lexicographic kernel can be computed efficiently, provided we can efficiently compute the surplusses $s_{ij}(x)$ corresponding to a

  9. Computing an element in the lexicographic kernel of a game

    NARCIS (Netherlands)

    Faigle, U.; Kern, Walter; Kuipers, J.

    2002-01-01

    The lexicographic kernel of a game lexicographically maximizes the surplusses $s_{ij}$ (rather than the excesses as would the nucleolus). We show that an element in the lexicographic kernel can be computed efficiently, provided we can efficiently compute the surplusses $s_{ij}(x)$ corresponding to a

  10. Pure endmember extraction using robust kernel archetypoid analysis for hyperspectral imagery

    Science.gov (United States)

    Sun, Weiwei; Yang, Gang; Wu, Ke; Li, Weiyue; Zhang, Dianfa

    2017-09-01

    A robust kernel archetypoid analysis (RKADA) method is proposed to extract pure endmembers from hyperspectral imagery (HSI). The RKADA assumes that each pixel is a sparse linear mixture of all endmembers and each endmember corresponds to a real pixel in the image scene. First, it improves the re8gular archetypal analysis with a new binary sparse constraint, and the adoption of the kernel function constructs the principal convex hull in an infinite Hilbert space and enlarges the divergences between pairwise pixels. Second, the RKADA transfers the pure endmember extraction problem into an optimization problem by minimizing residual errors with the Huber loss function. The Huber loss function reduces the effects from big noises and outliers in the convergence procedure of RKADA and enhances the robustness of the optimization function. Third, the random kernel sinks for fast kernel matrix approximation and the two-stage algorithm for optimizing initial pure endmembers are utilized to improve its computational efficiency in realistic implementations of RKADA, respectively. The optimization equation of RKADA is solved by using the block coordinate descend scheme and the desired pure endmembers are finally obtained. Six state-of-the-art pure endmember extraction methods are employed to make comparisons with the RKADA on both synthetic and real Cuprite HSI datasets, including three geometrical algorithms vertex component analysis (VCA), alternative volume maximization (AVMAX) and orthogonal subspace projection (OSP), and three matrix factorization algorithms the preconditioning for successive projection algorithm (PreSPA), hierarchical clustering based on rank-two nonnegative matrix factorization (H2NMF) and self-dictionary multiple measurement vector (SDMMV). Experimental results show that the RKADA outperforms all the six methods in terms of spectral angle distance (SAD) and root-mean-square-error (RMSE). Moreover, the RKADA has short computational times in offline

  11. 3-D waveform tomography sensitivity kernels for anisotropic media

    KAUST Repository

    Djebbi, Ramzi

    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.

  12. Anatomically-aided PET reconstruction using the kernel method.

    Science.gov (United States)

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

    2016-09-21

    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.

  13. 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...... linear properties. This negative result hints that radial kernel are perhaps not suitable over geodesic metric spaces after all. Here, however, we present evidence that large intervals of bandwidths exist where geodesic exponential kernels have high probability of being positive definite over finite...... datasets, while still having significant predictive power. From this we formulate conjectures on the probability of a positive definite kernel matrix for a finite random sample, depending on the geometry of the data space and the spread of the sample....

  14. Compactly Supported Basis Functions as Support Vector Kernels for Classification.

    Science.gov (United States)

    Wittek, Peter; Tan, Chew Lim

    2011-10-01

    Wavelet kernels have been introduced for both support vector regression and classification. Most of these wavelet kernels do not use the inner product of the embedding space, but use wavelets in a similar fashion to radial basis function kernels. Wavelet analysis is typically carried out on data with a temporal or spatial relation between consecutive data points. We argue that it is possible to order the features of a general data set so that consecutive features are statistically related to each other, thus enabling us to interpret the vector representation of an object as a series of equally or randomly spaced observations of a hypothetical continuous signal. By approximating the signal with compactly supported basis functions and employing the inner product of the embedding L2 space, we gain a new family of wavelet kernels. Empirical results show a clear advantage in favor of these kernels.

  15. The influence of irradiation treatment on gossypol and protein digestibility of decorticated cottonseed meal for Broiler chicks

    International Nuclear Information System (INIS)

    Farag, M.D.H.

    2000-01-01

    The Effect of gamma irradiation (5-20 kGy) on the chemical composition, soluble protein, available lysine, gossypol, in-vitro and in vivo digestibility of decorticated cottonseed meal (CSM) and the performance of broilers fed processed CSM were investigated. Radiation treatment of CSM at dose levels of 5, 10, 15 and 20 kGy did not affect moisture, crude protein, ether extract, crude fiber, ash and NFW content. However, the treatment reduced soluble protein by 4.18, 7.82, 10.91, 13.46%, respectively. Fluorodinitrobenzene-available lysine concentration reduced by 4.48, 8.12, 17.65 and 21.29% respectively. The concentrations of total gossypol decreased by 7.97, 15.78, 19.92 and 25.39% and free gossypol by 3.74, 7.85, 18.43 and 28.01%, respectively. The digestibility of CSM protein was increased by 5.3, 9.0, 16.6 and 17.2%, for in-vitro digestibility and by 4.8, 7.3, 9.4 and 12.9% for in-vivo due to treatment with 5,10, 15 and 20 kGy, respectively. From 7 to 42 days, arbor acres broilers were freely given iso energetic and iso nitrogenous : corn-soy control diet or diets containing 300 g kg -1 raw or irradiated CSM at 4, 15 or 20 kGy. Intake of raw CSM affected growth, feed intake and feed conversion as compared with birds receiving the control diet

  16. Science and technology of kernels and TRISO coated particle sorting

    International Nuclear Information System (INIS)

    Nothnagel, G.

    2006-09-01

    The ~1mm diameter TRISO coated particles, which form the elemental units of PBMR nuclear fuel, has to be close to spherical in order to best survive damage during sphere pressing. Spherical silicon carbide layers further provide the strongest miniature pressure vessels for fission product retention. To make sure that the final product contains particles of acceptable shape, 100% of kernels and coated particles have to be sorted on a surface-ground sorting table. Broken particles, twins, irregular (odd) shapes and extreme ellipsoids have to be separated from the final kernel and coated particle batches. Proper sorting of particles is an extremely important step in quality fuel production as the final failure fraction depends sensitively on the quality of sorting. After sorting a statistically significant sample of the sorted product is analysed for sphericity, which is defined as the ratio of maximum to minimum diameter, as part of a standard QC test to ensure conformance to German specifications. In addition a burn-leach test is done on coated particles (before pressing) and fuel spheres (after pressing) to ensure adherence to failure specifications. Because of the extreme importance of particle sorting for assurance of fuel quality it is essential to have an in-depth understanding of the capabilities and limitations of particle sorting. In this report a systematic scientific rationale is developed, from fundamental principles, to provide a basis for understanding the relationship between product quality and sorting parameters. The principles and concepts, developed in this report, will be of importance when future sorting tables (or equivalents) are to be designed. A number of new concepts and methodologies are developed to assist with equivalence validation of any two sorting tables. This is aimed in particular towards quantitative assessment of equivalence between current QC tables (closely based on the original NUKEM parameters, except for the driving mechanism

  17. Improved modeling of clinical data with kernel methods.

    Science.gov (United States)

    Daemen, Anneleen; Timmerman, Dirk; Van den Bosch, Thierry; Bottomley, Cecilia; Kirk, Emma; Van Holsbeke, Caroline; Valentin, Lil; Bourne, Tom; De Moor, Bart

    2012-02-01

    Despite the rise of high-throughput technologies, clinical data such as age, gender and medical history guide clinical management for most diseases and examinations. To improve clinical management, available patient information should be fully exploited. This requires appropriate modeling of relevant parameters. When kernel methods are used, traditional kernel functions such as the linear kernel are often applied to the set of clinical parameters. These kernel functions, however, have their disadvantages due to the specific characteristics of clinical data, being a mix of variable types with each variable its own range. We propose a new kernel function specifically adapted to the characteristics of clinical data. The clinical kernel function provides a better representation of patients' similarity by equalizing the influence of all variables and taking into account the range r of the variables. Moreover, it is robust with respect to changes in r. Incorporated in a least squares support vector machine, the new kernel function results in significantly improved diagnosis, prognosis and prediction of therapy response. This is illustrated on four clinical data sets within gynecology, with an average increase in test area under the ROC curve (AUC) of 0.023, 0.021, 0.122 and 0.019, respectively. Moreover, when combining clinical parameters and expression data in three case studies on breast cancer, results improved overall with use of the new kernel function and when considering both data types in a weighted fashion, with a larger weight assigned to the clinical parameters. The increase in AUC with respect to a standard kernel function and/or unweighted data combination was maximum 0.127, 0.042 and 0.118 for the three case studies. For clinical data consisting of variables of different types, the proposed kernel function--which takes into account the type and range of each variable--has shown to be a better alternative for linear and non-linear classification problems

  18. A method for manufacturing kernels of metallic oxides and the thus obtained kernels

    International Nuclear Information System (INIS)

    Lelievre Bernard; Feugier, Andre.

    1973-01-01

    A method is described for manufacturing fissile or fertile metal oxide kernels, consisting in adding at least a chemical compound capable of releasing ammonia to an aqueous solution of actinide nitrates dispersing the thus obtained solution dropwise in a hot organic phase so as to gelify the drops and transform them into solid particles, washing drying and treating said particles so as to transform them into oxide kernels. Such a method is characterized in that the organic phase used in the gel-forming reactions comprises a mixture of two organic liquids, one of which acts as a solvent, whereas the other is a product capable of extracting the metal-salt anions from the drops while the gel forming reaction is taking place. This can be applied to the so-called high temperature nuclear reactors [fr

  19. Learning molecular energies using localized graph kernels

    Science.gov (United States)

    Ferré, Grégoire; Haut, Terry; Barros, Kipton

    2017-03-01

    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. This Graph Approximated Energy (GRAPE) approach is flexible and admits many possible extensions. We benchmark a simple version of GRAPE by predicting atomization energies on a standard dataset of organic molecules.

  20. 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.

  1. Application of multivariate chemometric techniques for simultaneous determination of five parameters of cottonseed oil by single bounce attenuated total reflectance Fourier transform infrared spectroscopy.

    Science.gov (United States)

    Talpur, M Younis; Kara, Huseyin; Sherazi, S T H; Ayyildiz, H Filiz; Topkafa, Mustafa; Arslan, Fatma Nur; Naz, Saba; Durmaz, Fatih; Sirajuddin

    2014-11-01

    Single bounce attenuated total reflectance (SB-ATR) Fourier transform infrared (FTIR) spectroscopy in conjunction with chemometrics was used for accurate determination of free fatty acid (FFA), peroxide value (PV), iodine value (IV), conjugated diene (CD) and conjugated triene (CT) of cottonseed oil (CSO) during potato chips frying. Partial least square (PLS), stepwise multiple linear regression (SMLR), principal component regression (PCR) and simple Beer׳s law (SBL) were applied to develop the calibrations for simultaneous evaluation of five stated parameters of cottonseed oil (CSO) during frying of French frozen potato chips at 170°C. Good regression coefficients (R(2)) were achieved for FFA, PV, IV, CD and CT with value of >0.992 by PLS, SMLR, PCR, and SBL. Root mean square error of prediction (RMSEP) was found to be less than 1.95% for all determinations. Result of the study indicated that SB-ATR FTIR in combination with multivariate chemometrics could be used for accurate and simultaneous determination of different parameters during the frying process without using any toxic organic solvent. Copyright © 2014 Elsevier B.V. All rights reserved.

  2. Investigation of electron beam irradiation effects on anti-nutritional factors, chemical composition and digestion kinetics of whole cottonseed, soybean and canola seeds

    International Nuclear Information System (INIS)

    Ebrahimi-Mahmoudabad, S.R.; Taghinejad-Roudbaneh, M.

    2011-01-01

    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.

  3. 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.

  4. Stochastic subset selection for learning with kernel machines.

    Science.gov (United States)

    Rhinelander, Jason; Liu, Xiaoping P

    2012-06-01

    Kernel machines have gained much popularity in applications of machine learning. Support vector machines (SVMs) are a subset of kernel machines and generalize well for classification, regression, and anomaly detection tasks. The training procedure for traditional SVMs involves solving a quadratic programming (QP) problem. The QP problem scales super linearly in computational effort with the number of training samples and is often used for the offline batch processing of data. Kernel machines operate by retaining a subset of observed data during training. The data vectors contained within this subset are referred to as support vectors (SVs). The work presented in this paper introduces a subset selection method for the use of kernel machines in online, changing environments. Our algorithm works by using a stochastic indexing technique when selecting a subset of SVs when computing the kernel expansion. The work described here is novel because it separates the selection of kernel basis functions from the training algorithm used. The subset selection algorithm presented here can be used in conjunction with any online training technique. It is important for online kernel machines to be computationally efficient due to the real-time requirements of online environments. Our algorithm is an important contribution because it scales linearly with the number of training samples and is compatible with current training techniques. Our algorithm outperforms standard techniques in terms of computational efficiency and provides increased recognition accuracy in our experiments. We provide results from experiments using both simulated and real-world data sets to verify our algorithm.

  5. Multiple kernel boosting framework based on information measure for classification

    International Nuclear Information System (INIS)

    Qi, Chengming; Wang, Yuping; Tian, Wenjie; Wang, Qun

    2016-01-01

    The performance of kernel-based method, such as support vector machine (SVM), is greatly affected by the choice of kernel function. Multiple kernel learning (MKL) is a promising family of machine learning algorithms and has attracted many attentions in recent years. MKL combines multiple sub-kernels to seek better results compared to single kernel learning. In order to improve the efficiency of SVM and MKL, in this paper, the Kullback–Leibler kernel function is derived to develop SVM. The proposed method employs an improved ensemble learning framework, named KLMKB, which applies Adaboost to learning multiple kernel-based classifier. In the experiment for hyperspectral remote sensing image classification, we employ feature selected through Optional Index Factor (OIF) to classify the satellite image. We extensively examine the performance of our approach in comparison to some relevant and state-of-the-art algorithms on a number of benchmark classification data sets and hyperspectral remote sensing image data set. Experimental results show that our method has a stable behavior and a noticeable accuracy for different data set.

  6. 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.

  7. 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.

  8. 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.

  9. Deep Restricted Kernel Machines Using Conjugate Feature Duality.

    Science.gov (United States)

    Suykens, Johan A K

    2017-08-01

    The aim of this letter is to propose a theory of deep restricted kernel machines offering new foundations for deep learning with kernel machines. From the viewpoint of deep learning, it is partially related to restricted Boltzmann machines, which are characterized by visible and hidden units in a bipartite graph without hidden-to-hidden connections and deep learning extensions as deep belief networks and deep Boltzmann machines. From the viewpoint of kernel machines, it includes least squares support vector machines for classification and regression, kernel principal component analysis (PCA), matrix singular value decomposition, and Parzen-type models. A key element is to first characterize these kernel machines in terms of so-called conjugate feature duality, yielding a representation with visible and hidden units. It is shown how this is related to the energy form in restricted Boltzmann machines, with continuous variables in a nonprobabilistic setting. In this new framework of so-called restricted kernel machine (RKM) representations, the dual variables correspond to hidden features. Deep RKM are obtained by coupling the RKMs. The method is illustrated for deep RKM, consisting of three levels with a least squares support vector machine regression level and two kernel PCA levels. In its primal form also deep feedforward neural networks can be trained within this framework.

  10. 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. Copyright © 2013 Elsevier Ltd. All rights reserved.

  11. Gradient-based adaptation of general gaussian kernels.

    Science.gov (United States)

    Glasmachers, Tobias; Igel, Christian

    2005-10-01

    Gradient-based optimizing of gaussian kernel functions is considered. The gradient for the adaptation of scaling and rotation of the input space is computed to achieve invariance against linear transformations. This is done by using the exponential map as a parameterization of the kernel parameter manifold. By restricting the optimization to a constant trace subspace, the kernel size can be controlled. This is, for example, useful to prevent overfitting when minimizing radius-margin generalization performance measures. The concepts are demonstrated by training hard margin support vector machines on toy data.

  12. On weights which admit the reproducing kernel of Bergman type

    Directory of Open Access Journals (Sweden)

    Zbigniew Pasternak-Winiarski

    1992-01-01

    Full Text Available In this paper we consider (1 the weights of integration for which the reproducing kernel of the Bergman type can be defined, i.e., the admissible weights, and (2 the kernels defined by such weights. It is verified that the weighted Bergman kernel has the analogous properties as the classical one. We prove several sufficient conditions and necessary and sufficient conditions for a weight to be an admissible weight. We give also an example of a weight which is not of this class. As a positive example we consider the weight μ(z=(Imz2 defined on the unit disk in ℂ.

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

    DEFF Research Database (Denmark)

    Rasmussen, Peter Mondrup; Hansen, Lars Kai; Madsen, Kristoffer Hougaard

    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...... on visualization of such nonlinear kernel models. Specifically, we investigate the sensitivity map as a technique for generation of global summary maps of kernel classification methods. We illustrate the performance of the sensitivity map on functional magnetic resonance (fMRI) data based on visual stimuli. We...

  14. 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.

  15. Deep kernel learning method for SAR image target recognition

    Science.gov (United States)

    Chen, Xiuyuan; Peng, Xiyuan; Duan, Ran; Li, Junbao

    2017-10-01

    With the development of deep learning, research on image target recognition has made great progress in recent years. Remote sensing detection urgently requires target recognition for military, geographic, and other scientific research. This paper aims to solve the synthetic aperture radar image target recognition problem by combining deep and kernel learning. The model, which has a multilayer multiple kernel structure, is optimized layer by layer with the parameters of Support Vector Machine and a gradient descent algorithm. This new deep kernel learning method improves accuracy and achieves competitive recognition results compared with other learning methods.

  16. 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...

  17. Examining Potential Boundary Bias Effects in Kernel Smoothing on Equating: An Introduction for the Adaptive and Epanechnikov Kernels.

    Science.gov (United States)

    Cid, Jaime A; von Davier, Alina A

    2015-05-01

    Test equating is a method of making the test scores from different test forms of the same assessment comparable. In the equating process, an important step involves continuizing the discrete score distributions. In traditional observed-score equating, this step is achieved using linear interpolation (or an unscaled uniform kernel). In the kernel equating (KE) process, this continuization process involves Gaussian kernel smoothing. It has been suggested that the choice of bandwidth in kernel smoothing controls the trade-off between variance and bias. In the literature on estimating density functions using kernels, it has also been suggested that the weight of the kernel depends on the sample size, and therefore, the resulting continuous distribution exhibits bias at the endpoints, where the samples are usually smaller. The purpose of this article is (a) to explore the potential effects of atypical scores (spikes) at the extreme ends (high and low) on the KE method in distributions with different degrees of asymmetry using the randomly equivalent groups equating design (Study I), and (b) to introduce the Epanechnikov and adaptive kernels as potential alternative approaches to reducing boundary bias in smoothing (Study II). The beta-binomial model is used to simulate observed scores reflecting a range of different skewed shapes.

  18. 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.

  19. Efficient Online Subspace Learning With an Indefinite Kernel for Visual Tracking and Recognition

    NARCIS (Netherlands)

    Liwicki, Stephan; Zafeiriou, Stefanos; Tzimiropoulos, Georgios; Pantic, Maja

    2012-01-01

    We propose an exact framework for online learning with a family of indefinite (not positive) kernels. As we study the case of nonpositive kernels, we first show how to extend kernel principal component analysis (KPCA) from a reproducing kernel Hilbert space to Krein space. We then formulate an

  20. COMPARATIVE EFFICIENCY OF SUNFLOWER MEAL AND COTTONSEED CAKES IN THE FEED OF CROSSBRED CALVES FOR MEAT PRODUCTION

    Directory of Open Access Journals (Sweden)

    M. A. JABBAR, M. I. ANJUM1, S. REHMAN2 AND W. SHAHZAD2

    2006-07-01

    Full Text Available Thirty crossbred (Sahiwal x Friesian male calves of 9-10 months age and weighing 70 to 90 kg, were used in completely randomized design to investigate the possibility of replacing cottonseed cakes (CSC with sunflower meal (SFM, partially or completely, in rations for fattening of crossbred calves for meat production. Three concentrate rations viz. A, B and C were formulated. Ration A containing CSC was fed to the calves of group A, ration B containing SFM was fed to calves of group B and ration C containing both CSC + SFM was fed to calves of group C. The feed intake of calves belonging to group C was the highest (5.7 ± 2.3 kg followed by group B (5.5 ± 1.3 kg and group A (5.2 ± 2.0 kg. Average daily body weight gain was 0.73 ± 0.1, 0.72 ± 0.2 and 0.71 ± 0.1 kg for groups A, B and C, respectively. Calves fed SFM gained numerically less than the calves fed CSC but higher than SFM+ CSC. Feed conversion ratio was 7.1 ± 0.4, 7.7 ± 0.7 and 8.0 ± 0.6, for calves of groups A, B and C, respectively. Dressing percentage averaged 51.5 ± 1.3, 52.1 ± 1.2 and 52.3 ± 0.8 for the respective rations. However, the differences in feed intake, daily weight gain, feed conversion ratio and dressing percentages among calves of three groups were non significant. Considering the cost of feed and average growth, the cost of per kg body weight gain was 38, 30 and 37 rupees for the groups A, B and C, respectively. The lowest cost was observed in SFM based ration (B that was about 19% less than ration containing CSC. Results indicated that for fattening of crossbred calves the use of SFM is as efficient as CSC but more economical and can successfully replace CSC in fattening rations.

  1. Calculation of the thermal neutron scattering kernel using the synthetic model. Pt. 2. Zero-order energy transfer kernel

    International Nuclear Information System (INIS)

    Drozdowicz, K.

    1995-01-01

    A comprehensive unified description of the application of Granada's Synthetic Model to the slow-neutron scattering by the molecular systems is continued. Detailed formulae for the zero-order energy transfer kernel are presented basing on the general formalism of the model. An explicit analytical formula for the total scattering cross section as a function of the incident neutron energy is also obtained. Expressions of the free gas model for the zero-order scattering kernel and for total scattering kernel are considered as a sub-case of the Synthetic Model. (author). 10 refs

  2. A kernel adaptive algorithm for quaternion-valued inputs.

    Science.gov (United States)

    Paul, Thomas K; Ogunfunmi, Tokunbo

    2015-10-01

    The use of quaternion data can provide benefit in applications like robotics and image recognition, and particularly for performing transforms in 3-D space. Here, we describe a kernel adaptive algorithm for quaternions. A least mean square (LMS)-based method was used, resulting in the derivation of the quaternion kernel LMS (Quat-KLMS) algorithm. Deriving this algorithm required describing the idea of a quaternion reproducing kernel Hilbert space (RKHS), as well as kernel functions suitable with quaternions. A modified HR calculus for Hilbert spaces was used to find the gradient of cost functions defined on a quaternion RKHS. In addition, the use of widely linear (or augmented) filtering is proposed to improve performance. The benefit of the Quat-KLMS and widely linear forms in learning nonlinear transformations of quaternion data are illustrated with simulations.

  3. Bioconversion of palm kernel meal for aquaculture: Experiences ...

    African Journals Online (AJOL)

    SERVER

    2008-04-17

    Apr 17, 2008 ... es as well as food supplies have existed traditionally with coastal regions of Liberia and ..... Contamination of palm kernel meal with Aspergillus ... Sciences, Universiti Sains Malaysia, Penang 11800, Malaysia. Aquacult. Res.

  4. The effect of apricot kernel flour incorporation on the ...

    African Journals Online (AJOL)

    STORAGESEVER

    2009-01-05

    Jan 5, 2009 ... 2Department of Food Engineering, Erciyes University 38039, Kayseri, Turkey. Accepted 27 ... Key words: Noodle; apricot kernel, flour, cooking, sensory properties. ... their simple preparation requirement, desirable sensory.

  5. 3-D waveform tomography sensitivity kernels for anisotropic media

    KAUST Repository

    Djebbi, Ramzi; Alkhalifah, Tariq Ali

    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

  6. Kernel-based noise filtering of neutron detector signals

    International Nuclear Information System (INIS)

    Park, Moon Ghu; Shin, Ho Cheol; Lee, Eun Ki

    2007-01-01

    This paper describes recently developed techniques for effective filtering of neutron detector signal noise. In this paper, three kinds of noise filters are proposed and their performance is demonstrated for the estimation of reactivity. The tested filters are based on the unilateral kernel filter, unilateral kernel filter with adaptive bandwidth and bilateral filter to show their effectiveness in edge preservation. Filtering performance is compared with conventional low-pass and wavelet filters. The bilateral filter shows a remarkable improvement compared with unilateral kernel and wavelet filters. The effectiveness and simplicity of the unilateral kernel filter with adaptive bandwidth is also demonstrated by applying it to the reactivity measurement performed during reactor start-up physics tests

  7. 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...

  8. Resummed memory kernels in generalized system-bath master equations

    International Nuclear Information System (INIS)

    Mavros, Michael G.; Van Voorhis, Troy

    2014-01-01

    Generalized master equations provide a concise formalism for studying reduced population dynamics. Usually, these master equations require a perturbative expansion of the memory kernels governing the dynamics; in order to prevent divergences, these expansions must be resummed. Resummation techniques of perturbation series are ubiquitous in physics, but they have not been readily studied for the time-dependent memory kernels used in generalized master equations. In this paper, we present a comparison of different resummation techniques for such memory kernels up to fourth order. We study specifically the spin-boson Hamiltonian as a model system bath Hamiltonian, treating the diabatic coupling between the two states as a perturbation. A novel derivation of the fourth-order memory kernel for the spin-boson problem is presented; then, the second- and fourth-order kernels are evaluated numerically for a variety of spin-boson parameter regimes. We find that resumming the kernels through fourth order using a Padé approximant results in divergent populations in the strong electronic coupling regime due to a singularity introduced by the nature of the resummation, and thus recommend a non-divergent exponential resummation (the “Landau-Zener resummation” of previous work). The inclusion of fourth-order effects in a Landau-Zener-resummed kernel is shown to improve both the dephasing rate and the obedience of detailed balance over simpler prescriptions like the non-interacting blip approximation, showing a relatively quick convergence on the exact answer. The results suggest that including higher-order contributions to the memory kernel of a generalized master equation and performing an appropriate resummation can provide a numerically-exact solution to system-bath dynamics for a general spectral density, opening the way to a new class of methods for treating system-bath dynamics

  9. On Improving Convergence Rates for Nonnegative Kernel Density Estimators

    OpenAIRE

    Terrell, George R.; Scott, David W.

    1980-01-01

    To improve the rate of decrease of integrated mean square error for nonparametric kernel density estimators beyond $0(n^{-\\frac{4}{5}}),$ we must relax the constraint that the density estimate be a bonafide density function, that is, be nonnegative and integrate to one. All current methods for kernel (and orthogonal series) estimators relax the nonnegativity constraint. In this paper we show how to achieve similar improvement by relaxing the integral constraint only. This is important in appl...

  10. Improved Variable Window Kernel Estimates of Probability Densities

    OpenAIRE

    Hall, Peter; Hu, Tien Chung; Marron, J. S.

    1995-01-01

    Variable window width kernel density estimators, with the width varying proportionally to the square root of the density, have been thought to have superior asymptotic properties. The rate of convergence has been claimed to be as good as those typical for higher-order kernels, which makes the variable width estimators more attractive because no adjustment is needed to handle the negativity usually entailed by the latter. However, in a recent paper, Terrell and Scott show that these results ca...

  11. Graphical analyses of connected-kernel scattering equations

    International Nuclear Information System (INIS)

    Picklesimer, A.

    1982-10-01

    Simple graphical techniques are employed to obtain a new (simultaneous) derivation of a large class of connected-kernel scattering equations. This class includes the Rosenberg, Bencze-Redish-Sloan, and connected-kernel multiple scattering equations as well as a host of generalizations of these and other equations. The graphical method also leads to a new, simplified form for some members of the class and elucidates the general structural features of the entire class

  12. MULTITASKER, Multitasking Kernel for C and FORTRAN Under UNIX

    International Nuclear Information System (INIS)

    Brooks, E.D. III

    1988-01-01

    1 - Description of program or function: MULTITASKER implements a multitasking kernel for the C and FORTRAN programming languages that runs under UNIX. The kernel provides a multitasking environment which serves two purposes. The first is to provide an efficient portable environment for the development, debugging, and execution of production multiprocessor programs. The second is to provide a means of evaluating the performance of a multitasking program on model multiprocessor hardware. The performance evaluation features require no changes in the application program source and are implemented as a set of compile- and run-time options in the kernel. 2 - Method of solution: The FORTRAN interface to the kernel is identical in function to the CRI multitasking package provided for the Cray XMP. This provides a migration path to high speed (but small N) multiprocessors once the application has been coded and debugged. With use of the UNIX m4 macro preprocessor, source compatibility can be achieved between the UNIX code development system and the target Cray multiprocessor. The kernel also provides a means of evaluating a program's performance on model multiprocessors. Execution traces may be obtained which allow the user to determine kernel overhead, memory conflicts between various tasks, and the average concurrency being exploited. The kernel may also be made to switch tasks every cpu instruction with a random execution ordering. This allows the user to look for unprotected critical regions in the program. These features, implemented as a set of compile- and run-time options, cause extra execution overhead which is not present in the standard production version of the kernel

  13. The Flux OSKit: A Substrate for Kernel and Language Research

    Science.gov (United States)

    1997-10-01

    unclassified Standard Form 298 (Rev. 8-98) Prescribed by ANSI Std Z39-18 tions. Our own microkernel -based OS, Fluke [17], puts almost all of the OSKit to use...kernels distance the language from the hardware; even microkernels and other extensible kernels enforce some default policy which often conflicts with a...be particu- larly useful in these research projects. 6.1.1 The Fluke OS In 1996 we developed an entirely new microkernel - based system called Fluke

  14. Salus: Kernel Support for Secure Process Compartments

    Directory of Open Access Journals (Sweden)

    Raoul Strackx

    2015-01-01

    Full Text Available Consumer devices are increasingly being used to perform security and privacy critical tasks. The software used to perform these tasks is often vulnerable to attacks, due to bugs in the application itself or in included software libraries. Recent work proposes the isolation of security-sensitive parts of applications into protected modules, each of which can be accessed only through a predefined public interface. But most parts of an application can be considered security-sensitive at some level, and an attacker who is able to gain inapplication level access may be able to abuse services from protected modules. We propose Salus, a Linux kernel modification that provides a novel approach for partitioning processes into isolated compartments sharing the same address space. Salus significantly reduces the impact of insecure interfaces and vulnerable compartments by enabling compartments (1 to restrict the system calls they are allowed to perform, (2 to authenticate their callers and callees and (3 to enforce that they can only be accessed via unforgeable references. We describe the design of Salus, report on a prototype implementation and evaluate it in terms of security and performance. We show that Salus provides a significant security improvement with a low performance overhead, without relying on any non-standard hardware support.

  15. 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.

  16. KERNEL MAD ALGORITHM FOR RELATIVE RADIOMETRIC NORMALIZATION

    Directory of Open Access Journals (Sweden)

    Y. Bai

    2016-06-01

    Full Text Available The multivariate alteration detection (MAD algorithm is commonly used in relative radiometric normalization. This algorithm is based on linear canonical correlation analysis (CCA which can analyze only linear relationships among bands. Therefore, we first introduce a new version of MAD in this study based on the established method known as kernel canonical correlation analysis (KCCA. The proposed method effectively extracts the non-linear and complex relationships among variables. We then conduct relative radiometric normalization experiments on both the linear CCA and KCCA version of the MAD algorithm with the use of Landsat-8 data of Beijing, China, and Gaofen-1(GF-1 data derived from South China. Finally, we analyze the difference between the two methods. Results show that the KCCA-based MAD can be satisfactorily applied to relative radiometric normalization, this algorithm can well describe the nonlinear relationship between multi-temporal images. This work is the first attempt to apply a KCCA-based MAD algorithm to relative radiometric normalization.

  17. 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

  18. 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.

  19. A new discrete dipole kernel for quantitative susceptibility mapping.

    Science.gov (United States)

    Milovic, Carlos; Acosta-Cabronero, Julio; Pinto, José Miguel; Mattern, Hendrik; Andia, Marcelo; Uribe, Sergio; Tejos, Cristian

    2018-09-01

    Most approaches for quantitative susceptibility mapping (QSM) are based on a forward model approximation that employs a continuous Fourier transform operator to solve a differential equation system. Such formulation, however, is prone to high-frequency aliasing. The aim of this study was to reduce such errors using an alternative dipole kernel formulation based on the discrete Fourier transform and discrete operators. The impact of such an approach on forward model calculation and susceptibility inversion was evaluated in contrast to the continuous formulation both with synthetic phantoms and in vivo MRI data. The discrete kernel demonstrated systematically better fits to analytic field solutions, and showed less over-oscillations and aliasing artifacts while preserving low- and medium-frequency responses relative to those obtained with the continuous kernel. In the context of QSM estimation, the use of the proposed discrete kernel resulted in error reduction and increased sharpness. This proof-of-concept study demonstrated that discretizing the dipole kernel is advantageous for QSM. The impact on small or narrow structures such as the venous vasculature might by particularly relevant to high-resolution QSM applications with ultra-high field MRI - a topic for future investigations. The proposed dipole kernel has a straightforward implementation to existing QSM routines. Copyright © 2018 Elsevier Inc. All rights reserved.

  20. Exploration of Shorea robusta (Sal seeds, kernels and its oil

    Directory of Open Access Journals (Sweden)

    Shashi Kumar C.

    2016-12-01

    Full Text Available Physical, mechanical, and chemical properties of Shorea robusta seed with wing, seed without wing, and kernel were investigated in the present work. The physico-chemical composition of sal oil was also analyzed. The physico-mechanical properties and proximate composition of seed with wing, seed without wing, and kernel at three moisture contents of 9.50% (w.b, 9.54% (w.b, and 12.14% (w.b, respectively, were studied. The results show that the moisture content of the kernel was highest as compared to seed with wing and seed without wing. The sphericity of the kernel was closer to that of a sphere as compared to seed with wing and seed without wing. The hardness of the seed with wing (32.32, N/mm and seed without wing (42.49, N/mm was lower than the kernels (72.14, N/mm. The proximate composition such as moisture, protein, carbohydrates, oil, crude fiber, and ash content were also determined. The kernel (30.20%, w/w contains higher oil percentage as compared to seed with wing and seed without wing. The scientific data from this work are important for designing of equipment and processes for post-harvest value addition of sal seeds.

  1. Omnibus risk assessment via accelerated failure time kernel machine modeling.

    Science.gov (United States)

    Sinnott, Jennifer A; Cai, Tianxi

    2013-12-01

    Integrating genomic information with traditional clinical risk factors to improve the prediction of disease outcomes could profoundly change the practice of medicine. However, the large number of potential markers and possible complexity of the relationship between markers and disease make it difficult to construct accurate risk prediction models. Standard approaches for identifying important markers often rely on marginal associations or linearity assumptions and may not capture non-linear or interactive effects. In recent years, much work has been done to group genes into pathways and networks. Integrating such biological knowledge into statistical learning could potentially improve model interpretability and reliability. One effective approach is to employ a kernel machine (KM) framework, which can capture nonlinear effects if nonlinear kernels are used (Scholkopf and Smola, 2002; Liu et al., 2007, 2008). For survival outcomes, KM regression modeling and testing procedures have been derived under a proportional hazards (PH) assumption (Li and Luan, 2003; Cai, Tonini, and Lin, 2011). In this article, we derive testing and prediction methods for KM regression under the accelerated failure time (AFT) model, a useful alternative to the PH model. We approximate the null distribution of our test statistic using resampling procedures. When multiple kernels are of potential interest, it may be unclear in advance which kernel to use for testing and estimation. We propose a robust Omnibus Test that combines information across kernels, and an approach for selecting the best kernel for estimation. The methods are illustrated with an application in breast cancer. © 2013, The International Biometric Society.

  2. Ideal Gas Resonance Scattering Kernel Routine for the NJOY Code

    International Nuclear Information System (INIS)

    Rothenstein, W.

    1999-01-01

    In a recent publication an expression for the temperature-dependent double-differential ideal gas scattering kernel is derived for the case of scattering cross sections that are energy dependent. Some tabulations and graphical representations of the characteristics of these kernels are presented in Ref. 2. They demonstrate the increased probability that neutron scattering by a heavy nuclide near one of its pronounced resonances will bring the neutron energy nearer to the resonance peak. This enhances upscattering, when a neutron with energy just below that of the resonance peak collides with such a nuclide. A routine for using the new kernel has now been introduced into the NJOY code. Here, its principal features are described, followed by comparisons between scattering data obtained by the new kernel, and the standard ideal gas kernel, when such comparisons are meaningful (i.e., for constant values of the scattering cross section a 0 K). The new ideal gas kernel for variable σ s 0 (E) at 0 K leads to the correct Doppler-broadened σ s T (E) at temperature T

  3. Proteome analysis of the almond kernel (Prunus dulcis).

    Science.gov (United States)

    Li, Shugang; Geng, Fang; Wang, Ping; Lu, Jiankang; Ma, Meihu

    2016-08-01

    Almond (Prunus dulcis) is a popular tree nut worldwide and offers many benefits to human health. However, the importance of almond kernel proteins in the nutrition and function in human health requires further evaluation. The present study presents a systematic evaluation of the proteins in the almond kernel using proteomic analysis. The nutrient and amino acid content in almond kernels from Xinjiang is similar to that of American varieties; however, Xinjiang varieties have a higher protein content. Two-dimensional electrophoresis analysis demonstrated a wide distribution of molecular weights and isoelectric points of almond kernel proteins. A total of 434 proteins were identified by LC-MS/MS, and most were proteins that were experimentally confirmed for the first time. Gene ontology (GO) analysis of the 434 proteins indicated that proteins involved in primary biological processes including metabolic processes (67.5%), cellular processes (54.1%), and single-organism processes (43.4%), the main molecular function of almond kernel proteins are in catalytic activity (48.0%), binding (45.4%) and structural molecule activity (11.9%), and proteins are primarily distributed in cell (59.9%), organelle (44.9%), and membrane (22.8%). Almond kernel is a source of a wide variety of proteins. This study provides important information contributing to the screening and identification of almond proteins, the understanding of almond protein function, and the development of almond protein products. © 2015 Society of Chemical Industry. © 2015 Society of Chemical Industry.

  4. Evaluating the Application of Tissue-Specific Dose Kernels Instead of Water Dose Kernels in Internal Dosimetry : A Monte Carlo Study

    NARCIS (Netherlands)

    Moghadam, Maryam Khazaee; Asl, Alireza Kamali; Geramifar, Parham; Zaidi, Habib

    2016-01-01

    Purpose: The aim of this work is to evaluate the application of tissue-specific dose kernels instead of water dose kernels to improve the accuracy of patient-specific dosimetry by taking tissue heterogeneities into consideration. Materials and Methods: Tissue-specific dose point kernels (DPKs) and

  5. Scientific opinion on the acute health risks related to the presence of cyanogenic glycosides in raw apricot kernels and products derived from raw apricot kernels

    DEFF Research Database (Denmark)

    Petersen, Annette

    of kernels promoted (10 and 60 kernels/day for the general population and cancer patients, respectively), exposures exceeded the ARfD 17–413 and 3–71 times in toddlers and adults, respectively. The estimated maximum quantity of apricot kernels (or raw apricot material) that can be consumed without exceeding...

  6. Effect of diets containing whole cottonseed on the quality of sheep semen - doi: 10.4025/actascianimsci.v34i3.12963

    Directory of Open Access Journals (Sweden)

    Adriana Trindade Soares

    2012-05-01

    Full Text Available This study evaluated the semen quality of Santa Ines sheep fed diets containing different levels of whole cottonseed (WCS. Twenty sheep were distributed into four groups that were given diets with 0; 20; 30; 40% of WCS. For this study the semen was collected by electroejaculation, and a monthly andrological examination was performed during nine months. The analyzed variables were: scrotal circumference (SC, appearance and color of the ejaculate, progressive motility (PM, vigor, mass movement (MM, total sperm concentration (spzX109, sperm morphology (SM and blood hematocrit. The SC had no difference among diets, with mean 31.83 cm. The animals fed diets with WCS, presented mean intake of 9.16 mg gossypol kg BW, and were prone to present greenish semen, and appearance ranging from thin creamy to watery. The PM decreased linearly (p

  7. Investigation of electron beam irradiation effects on anti-nutritional factors, chemical composition and digestion kinetics of whole cottonseed, soybean and canola seeds

    Science.gov (United States)

    Ebrahimi-Mahmoudabad, S. R.; Taghinejad-Roudbaneh, M.

    2011-12-01

    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 ( Pcontent 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.

  8. 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.

  9. Protein fold recognition using geometric kernel data fusion.

    Science.gov (United States)

    Zakeri, Pooya; Jeuris, Ben; Vandebril, Raf; Moreau, Yves

    2014-07-01

    Various approaches based on features extracted from protein sequences and often machine learning methods have been used in the prediction of protein folds. Finding an efficient technique for integrating these different protein features has received increasing attention. In particular, kernel methods are an interesting class of techniques for integrating heterogeneous data. Various methods have been proposed to fuse multiple kernels. Most techniques for multiple kernel learning focus on learning a convex linear combination of base kernels. In addition to the limitation of linear combinations, working with such approaches could cause a loss of potentially useful information. We design several techniques to combine kernel matrices by taking more involved, geometry inspired means of these matrices instead of convex linear combinations. We consider various sequence-based protein features including information extracted directly from position-specific scoring matrices and local sequence alignment. We evaluate our methods for classification on the SCOP PDB-40D benchmark dataset for protein fold recognition. The best overall accuracy on the protein fold recognition test set obtained by our methods is ∼ 86.7%. This is an improvement over the results of the best existing approach. Moreover, our computational model has been developed by incorporating the functional domain composition of proteins through a hybridization model. It is observed that by using our proposed hybridization model, the protein fold recognition accuracy is further improved to 89.30%. Furthermore, we investigate the performance of our approach on the protein remote homology detection problem by fusing multiple string kernels. The MATLAB code used for our proposed geometric kernel fusion frameworks are publicly available at http://people.cs.kuleuven.be/∼raf.vandebril/homepage/software/geomean.php?menu=5/. © The Author 2014. Published by Oxford University Press.

  10. Generalized synthetic kernel approximation for elastic moderation of fast neutrons

    International Nuclear Information System (INIS)

    Yamamoto, Koji; Sekiya, Tamotsu; Yamamura, Yasunori.

    1975-01-01

    A method of synthetic kernel approximation is examined in some detail with a view to simplifying the treatment of the elastic moderation of fast neutrons. A sequence of unified kernel (fsub(N)) is introduced, which is then divided into two subsequences (Wsub(n)) and (Gsub(n)) according to whether N is odd (Wsub(n)=fsub(2n-1), n=1,2, ...) or even (Gsub(n)=fsub(2n), n=0,1, ...). The W 1 and G 1 kernels correspond to the usual Wigner and GG kernels, respectively, and the Wsub(n) and Gsub(n) kernels for n>=2 represent generalizations thereof. It is shown that the Wsub(n) kernel solution with a relatively small n (>=2) is superior on the whole to the Gsub(n) kernel solution for the same index n, while both converge to the exact values with increasing n. To evaluate the collision density numerically and rapidly, a simple recurrence formula is derived. In the asymptotic region (except near resonances), this recurrence formula allows calculation with a relatively coarse mesh width whenever hsub(a)<=0.05 at least. For calculations in the transient lethargy region, a mesh width of order epsilon/10 is small enough to evaluate the approximate collision density psisub(N) with an accuracy comparable to that obtained analytically. It is shown that, with the present method, an order of approximation of about n=7 should yield a practically correct solution diviating not more than 1% in collision density. (auth.)

  11. Unsupervised multiple kernel learning for heterogeneous data integration.

    Science.gov (United States)

    Mariette, Jérôme; Villa-Vialaneix, Nathalie

    2018-03-15

    Recent high-throughput sequencing advances have expanded the breadth of available omics datasets and the integrated analysis of multiple datasets obtained on the same samples has allowed to gain important insights in a wide range of applications. However, the integration of various sources of information remains a challenge for systems biology since produced datasets are often of heterogeneous types, with the need of developing generic methods to take their different specificities into account. We propose a multiple kernel framework that allows to integrate multiple datasets of various types into a single exploratory analysis. Several solutions are provided to learn either a consensus meta-kernel or a meta-kernel that preserves the original topology of the datasets. We applied our framework to analyse two public multi-omics datasets. First, the multiple metagenomic datasets, collected during the TARA Oceans expedition, was explored to demonstrate that our method is able to retrieve previous findings in a single kernel PCA as well as to provide a new image of the sample structures when a larger number of datasets are included in the analysis. To perform this analysis, a generic procedure is also proposed to improve the interpretability of the kernel PCA in regards with the original data. Second, the multi-omics breast cancer datasets, provided by The Cancer Genome Atlas, is analysed using a kernel Self-Organizing Maps with both single and multi-omics strategies. The comparison of these two approaches demonstrates the benefit of our integration method to improve the representation of the studied biological system. Proposed methods are available in the R package mixKernel, released on CRAN. It is fully compatible with the mixOmics package and a tutorial describing the approach can be found on mixOmics web site http://mixomics.org/mixkernel/. jerome.mariette@inra.fr or nathalie.villa-vialaneix@inra.fr. Supplementary data are available at Bioinformatics online.

  12. Germinação de sementes de algodoeiro deslintadas por diferentes métodos Germination of cottonseed delinted by different methods

    Directory of Open Access Journals (Sweden)

    Jocely A. Maeda

    1977-01-01

    Full Text Available Sementes de algodão do cultivar IAC 13-1 foram deslintadas por quatro diferentes métodos, a saber: mecanicamente, por ácido sulfúrico, por gás clorídrico e por flambagem. Após seleção em mesa de gravidade, cada porção relativa a um determinado método de deslintamento foi dividida em duas, sendo uma delas tratada com fungicída PCNB 75%, nas dosagens recomendadas pelos fabricantes. Após o teste inicial de germinação, as sementes foram armazenadas em ambiente de laboratório e novos testes de germinação foram feitos aos 3, 6 e 12 meses. Em todos os períodos de armazenamento as porcentagens de germinação das sementes deslintadas por ácido sulfúrico e gás clorídrico foram superiores às das sementes deslintadas mecanicamente ou por flambagem que, por sua vez, foram iguais entre si ou com a flambagem ocupando posição intermediária. Em todos os períodos as porcentagens de germinação das sementes tratadas com fungicida foram superiores às das sementes sem esse tratamento.The laboratory germination of mechanical-delinted, acid-delinted, gas-delinted, and flame-delinted cottonseed of the IAC 13-1 variety, treated and not treated with a fungicide, was evaluated during a storage period of 12 montns. In all the storage periods, acid-delinted and gas-delinted cottonseed provided higher germination percentages than those delinted by machine or by flame. In all the storage periods, fungicide-treated seeds of each type produced higher germination percentages than did untreated seed.

  13. Collision kernels in the eikonal approximation for Lennard-Jones interaction potential

    International Nuclear Information System (INIS)

    Zielinska, S.

    1985-03-01

    The velocity changing collisions are conveniently described by collisional kernels. These kernels depend on an interaction potential and there is a necessity for evaluating them for realistic interatomic potentials. Using the collision kernels, we are able to investigate the redistribution of atomic population's caused by the laser light and velocity changing collisions. In this paper we present the method of evaluating the collision kernels in the eikonal approximation. We discuss the influence of the potential parameters Rsub(o)sup(i), epsilonsub(o)sup(i) on kernel width for a given atomic state. It turns out that unlike the collision kernel for the hard sphere model of scattering the Lennard-Jones kernel is not so sensitive to changes of Rsub(o)sup(i) as the previous one. Contrary to the general tendency of approximating collisional kernels by the Gaussian curve, kernels for the Lennard-Jones potential do not exhibit such a behaviour. (author)

  14. Triacylglycerol composition, physico-chemical characteristics and oxidative stability of interesterified canola oil and fully hydrogenated cottonseed oil blends.

    Science.gov (United States)

    Imran, Muhammad; Nadeem, Muhammad

    2015-10-29

    Partial hydrogenation process is used worldwide to produce shortening, baking, and pastry margarines for food applications. However, demand for such products is decreased during last decade due to their possible links to consumer health and disease. This has raised the need to replace hydrogenation with alternative acceptable interesterification process which has advantage in context of modifying the physico-chemical properties of edible fat-based products. Therefore, the main mandate of research was the development of functional fat through chemical interesterification of canola oil (CaO) and fully hydrogenated cottonseed oil (FHCSO) mixtures. Blends were prepared in the proportions of 75:25 (T1), 50:50 (T2) and 25:75 (T3) of CaO:FHCSO (w/w). Interesterification was performed using sodium methoxide (0.2 %) as catalyst at 120 °C, under reduced pressure and constant agitation for 60 minutes. The non-interesterified and interesterified CaO:FHCSO blends were evaluated for triacylglycerol (TAG) composition, physico-chemical characteristics, oxidative stability and consumer acceptability at 0, 30 and 60 days of storage interval. The oleic acid (58.3 ± 0.6 %) was predominantly present in CaO while the contents of stearic acid (72 ± 0.8 %) were significantly higher in FHCSO. Maximum trisaturated (S3) contents (63.9 ± 0.5 %) were found in T3 while monounsaturated (S2U), diunsaturated (U2S) and triunsaturated (U3) contents were quite low in T2 and T3 before interesterification. A marked reduction in S3 and U3 contents with concomitant increase in S2U and U2S contents was observed for all CaO:FHCSO blends on interesterification. During storage, the changes in S3, S2U and U2S contents were not found significant (p ≥ 0.05). However, maximum decrease 13 %, 7.5 and 5.6 % in U3 contents for T1, T2 and T3 was noted after 60-days of interesterification, respectively. The Lovibond color R, melting point, refractive index, specific gravity, peroxide and free

  15. Bivariate discrete beta Kernel graduation of mortality data.

    Science.gov (United States)

    Mazza, Angelo; Punzo, Antonio

    2015-07-01

    Various parametric/nonparametric techniques have been proposed in literature to graduate mortality data as a function of age. Nonparametric approaches, as for example kernel smoothing regression, are often preferred because they do not assume any particular mortality law. Among the existing kernel smoothing approaches, the recently proposed (univariate) discrete beta kernel smoother has been shown to provide some benefits. Bivariate graduation, over age and calendar years or durations, is common practice in demography and actuarial sciences. In this paper, we generalize the discrete beta kernel smoother to the bivariate case, and we introduce an adaptive bandwidth variant that may provide additional benefits when data on exposures to the risk of death are available; furthermore, we outline a cross-validation procedure for bandwidths selection. Using simulations studies, we compare the bivariate approach proposed here with its corresponding univariate formulation and with two popular nonparametric bivariate graduation techniques, based on Epanechnikov kernels and on P-splines. To make simulations realistic, a bivariate dataset, based on probabilities of dying recorded for the US males, is used. Simulations have confirmed the gain in performance of the new bivariate approach with respect to both the univariate and the bivariate competitors.

  16. Structured Kernel Dictionary Learning with Correlation Constraint for Object Recognition.

    Science.gov (United States)

    Wang, Zhengjue; Wang, Yinghua; Liu, Hongwei; Zhang, Hao

    2017-06-21

    In this paper, we propose a new discriminative non-linear dictionary learning approach, called correlation constrained structured kernel KSVD, for object recognition. The objective function for dictionary learning contains a reconstructive term and a discriminative term. In the reconstructive term, signals are implicitly non-linearly mapped into a space, where a structured kernel dictionary, each sub-dictionary of which lies in the span of the mapped signals from the corresponding class, is established. In the discriminative term, by analyzing the classification mechanism, the correlation constraint is proposed in kernel form, constraining the correlations between different discriminative codes, and restricting the coefficient vectors to be transformed into a feature space, where the features are highly correlated inner-class and nearly independent between-classes. The objective function is optimized by the proposed structured kernel KSVD. During the classification stage, the specific form of the discriminative feature is needless to be known, while the inner product of the discriminative feature with kernel matrix embedded is available, and is suitable for a linear SVM classifier. Experimental results demonstrate that the proposed approach outperforms many state-of-the-art dictionary learning approaches for face, scene and synthetic aperture radar (SAR) vehicle target recognition.

  17. Mixed kernel function support vector regression for global sensitivity analysis

    Science.gov (United States)

    Cheng, Kai; Lu, Zhenzhou; Wei, Yuhao; Shi, Yan; Zhou, Yicheng

    2017-11-01

    Global sensitivity analysis (GSA) plays an important role in exploring the respective effects of input variables on an assigned output response. Amongst the wide sensitivity analyses in literature, the Sobol indices have attracted much attention since they can provide accurate information for most models. In this paper, a mixed kernel function (MKF) based support vector regression (SVR) model is employed to evaluate the Sobol indices at low computational cost. By the proposed derivation, the estimation of the Sobol indices can be obtained by post-processing the coefficients of the SVR meta-model. The MKF is constituted by the orthogonal polynomials kernel function and Gaussian radial basis kernel function, thus the MKF possesses both the global characteristic advantage of the polynomials kernel function and the local characteristic advantage of the Gaussian radial basis kernel function. The proposed approach is suitable for high-dimensional and non-linear problems. Performance of the proposed approach is validated by various analytical functions and compared with the popular polynomial chaos expansion (PCE). Results demonstrate that the proposed approach is an efficient method for global sensitivity analysis.

  18. On flame kernel formation and propagation in premixed gases

    Energy Technology Data Exchange (ETDEWEB)

    Eisazadeh-Far, Kian; Metghalchi, Hameed [Northeastern University, Mechanical and Industrial Engineering Department, Boston, MA 02115 (United States); Parsinejad, Farzan [Chevron Oronite Company LLC, Richmond, CA 94801 (United States); Keck, James C. [Massachusetts Institute of Technology, Cambridge, MA 02139 (United States)

    2010-12-15

    Flame kernel formation and propagation in premixed gases have been studied experimentally and theoretically. The experiments have been carried out at constant pressure and temperature in a constant volume vessel located in a high speed shadowgraph system. The formation and propagation of the hot plasma kernel has been simulated for inert gas mixtures using a thermodynamic model. The effects of various parameters including the discharge energy, radiation losses, initial temperature and initial volume of the plasma have been studied in detail. The experiments have been extended to flame kernel formation and propagation of methane/air mixtures. The effect of energy terms including spark energy, chemical energy and energy losses on flame kernel formation and propagation have been investigated. The inputs for this model are the initial conditions of the mixture and experimental data for flame radii. It is concluded that these are the most important parameters effecting plasma kernel growth. The results of laminar burning speeds have been compared with previously published results and are in good agreement. (author)

  19. Insights from Classifying Visual Concepts with Multiple Kernel Learning

    Science.gov (United States)

    Binder, Alexander; Nakajima, Shinichi; Kloft, Marius; Müller, Christina; Samek, Wojciech; Brefeld, Ulf; Müller, Klaus-Robert; Kawanabe, Motoaki

    2012-01-01

    Combining information from various image features has become a standard technique in concept recognition tasks. However, the optimal way of fusing the resulting kernel functions is usually unknown in practical applications. Multiple kernel learning (MKL) techniques allow to determine an optimal linear combination of such similarity matrices. Classical approaches to MKL promote sparse mixtures. Unfortunately, 1-norm regularized MKL variants are often observed to be outperformed by an unweighted sum kernel. The main contributions of this paper are the following: we apply a recently developed non-sparse MKL variant to state-of-the-art concept recognition tasks from the application domain of computer vision. We provide insights on benefits and limits of non-sparse MKL and compare it against its direct competitors, the sum-kernel SVM and sparse MKL. We report empirical results for the PASCAL VOC 2009 Classification and ImageCLEF2010 Photo Annotation challenge data sets. Data sets (kernel matrices) as well as further information are available at http://doc.ml.tu-berlin.de/image_mkl/(Accessed 2012 Jun 25). PMID:22936970

  20. Semi-supervised learning for ordinal Kernel Discriminant Analysis.

    Science.gov (United States)

    Pérez-Ortiz, M; Gutiérrez, P A; Carbonero-Ruz, M; Hervás-Martínez, C

    2016-12-01

    Ordinal classification considers those classification problems where the labels of the variable to predict follow a given order. Naturally, labelled data is scarce or difficult to obtain in this type of problems because, in many cases, ordinal labels are given by a user or expert (e.g. in recommendation systems). Firstly, this paper develops a new strategy for ordinal classification where both labelled and unlabelled data are used in the model construction step (a scheme which is referred to as semi-supervised learning). More specifically, the ordinal version of kernel discriminant learning is extended for this setting considering the neighbourhood information of unlabelled data, which is proposed to be computed in the feature space induced by the kernel function. Secondly, a new method for semi-supervised kernel learning is devised in the context of ordinal classification, which is combined with our developed classification strategy to optimise the kernel parameters. The experiments conducted compare 6 different approaches for semi-supervised learning in the context of ordinal classification in a battery of 30 datasets, showing (1) the good synergy of the ordinal version of discriminant analysis and the use of unlabelled data and (2) the advantage of computing distances in the feature space induced by the kernel function. Copyright © 2016 Elsevier Ltd. All rights reserved.

  1. Kernel Methods for Mining Instance Data in Ontologies

    Science.gov (United States)

    Bloehdorn, Stephan; Sure, York

    The amount of ontologies and meta data available on the Web is constantly growing. The successful application of machine learning techniques for learning of ontologies from textual data, i.e. mining for the Semantic Web, contributes to this trend. However, no principal approaches exist so far for mining from the Semantic Web. We investigate how machine learning algorithms can be made amenable for directly taking advantage of the rich knowledge expressed in ontologies and associated instance data. Kernel methods have been successfully employed in various learning tasks and provide a clean framework for interfacing between non-vectorial data and machine learning algorithms. In this spirit, we express the problem of mining instances in ontologies as the problem of defining valid corresponding kernels. We present a principled framework for designing such kernels by means of decomposing the kernel computation into specialized kernels for selected characteristics of an ontology which can be flexibly assembled and tuned. Initial experiments on real world Semantic Web data enjoy promising results and show the usefulness of our approach.

  2. Synthesis, characterization of spinels NiFe_2O_4 e CoFe_2O_4 and evaluation of performance in the trans esterification and esterification of cottonseed oil

    International Nuclear Information System (INIS)

    Dantas, J.; Silva, A.S.A.; Costa, A.C.F.M.; Freitas, N.L.

    2012-01-01

    The present study aimed synthesizes by combustion reaction and characterization of the spinel CoFe_2O_4 and NiFe_2O_4, and evaluation in the esterification and transesterification reaction of cottonseed oil for biodiesel. The samples were characterized by XRD, nitrogen adsorption/desorption (BET), SEM and transesterification e esterification reaction of the cottonseed oil for biodiesel. The results show that the synthesis was effective in achievement the CoFe_2O_4 and NiFe_2O_4 with surface area 23.75 and 18.18 m"2g"1. The results for esterification indicated that CoFe_2O_4 conversion 16.8 and 38.6%, however for transesterification reaction was observed that NiFe_2O_4 conversion 8.6 and 16.8% for ethanol and methanol, respectively. (author)

  3. Semisupervised kernel marginal Fisher analysis for face recognition.

    Science.gov (United States)

    Wang, Ziqiang; Sun, Xia; Sun, Lijun; Huang, Yuchun

    2013-01-01

    Dimensionality reduction is a key problem in face recognition due to the high-dimensionality of face image. To effectively cope with this problem, a novel dimensionality reduction algorithm called semisupervised kernel marginal Fisher analysis (SKMFA) for face recognition is proposed in this paper. SKMFA can make use of both labelled and unlabeled samples to learn the projection matrix for nonlinear dimensionality reduction. Meanwhile, it can successfully avoid the singularity problem by not calculating the matrix inverse. In addition, in order to make the nonlinear structure captured by the data-dependent kernel consistent with the intrinsic manifold structure, a manifold adaptive nonparameter kernel is incorporated into the learning process of SKMFA. Experimental results on three face image databases demonstrate the effectiveness of our proposed algorithm.

  4. 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...... for the implied volatility puzzle, the overreaction of long-term options to changes in short-term variance, and the fat tails of the risk-neutral return distribution relative to the physical distribution....

  5. Heat Kernel Asymptotics of Zaremba Boundary Value Problem

    Energy Technology Data Exchange (ETDEWEB)

    Avramidi, Ivan G. [Department of Mathematics, New Mexico Institute of Mining and Technology (United States)], E-mail: iavramid@nmt.edu

    2004-03-15

    The Zaremba boundary-value problem is a boundary value problem for Laplace-type second-order partial differential operators acting on smooth sections of a vector bundle over a smooth compact Riemannian manifold with smooth boundary but with discontinuous boundary conditions, which include Dirichlet boundary conditions on one part of the boundary and Neumann boundary conditions on another part of the boundary. We study the heat kernel asymptotics of Zaremba boundary value problem. The construction of the asymptotic solution of the heat equation is described in detail and the heat kernel is computed explicitly in the leading approximation. Some of the first nontrivial coefficients of the heat kernel asymptotic expansion are computed explicitly.

  6. Weighted Feature Gaussian Kernel SVM for Emotion Recognition.

    Science.gov (United States)

    Wei, Wei; Jia, Qingxuan

    2016-01-01

    Emotion recognition with weighted feature based on facial expression is a challenging research topic and has attracted great attention in the past few years. This paper presents a novel method, utilizing subregion recognition rate to weight kernel function. First, we divide the facial expression image into some uniform subregions and calculate corresponding recognition rate and weight. Then, we get a weighted feature Gaussian kernel function and construct a classifier based on Support Vector Machine (SVM). At last, the experimental results suggest that the approach based on weighted feature Gaussian kernel function has good performance on the correct rate in emotion recognition. The experiments on the extended Cohn-Kanade (CK+) dataset show that our method has achieved encouraging recognition results compared to the state-of-the-art methods.

  7. Rational kernels for Arabic Root Extraction and Text Classification

    Directory of Open Access Journals (Sweden)

    Attia Nehar

    2016-04-01

    Full Text Available In this paper, we address the problems of Arabic Text Classification and root extraction using transducers and rational kernels. We introduce a new root extraction approach on the basis of the use of Arabic patterns (Pattern Based Stemmer. Transducers are used to model these patterns and root extraction is done without relying on any dictionary. Using transducers for extracting roots, documents are transformed into finite state transducers. This document representation allows us to use and explore rational kernels as a framework for Arabic Text Classification. Root extraction experiments are conducted on three word collections and yield 75.6% of accuracy. Classification experiments are done on the Saudi Press Agency dataset and N-gram kernels are tested with different values of N. Accuracy and F1 report 90.79% and 62.93% respectively. These results show that our approach, when compared with other approaches, is promising specially in terms of accuracy and F1.

  8. A multi-label learning based kernel automatic recommendation method for support vector machine.

    Science.gov (United States)

    Zhang, Xueying; Song, Qinbao

    2015-01-01

    Choosing an appropriate kernel is very important and critical when classifying a new problem with Support Vector Machine. So far, more attention has been paid on constructing new kernels and choosing suitable parameter values for a specific kernel function, but less on kernel selection. Furthermore, most of current kernel selection methods focus on seeking a best kernel with the highest classification accuracy via cross-validation, they are time consuming and ignore the differences among the number of support vectors and the CPU time of SVM with different kernels. Considering the tradeoff between classification success ratio and CPU time, there may be multiple kernel functions performing equally well on the same classification problem. Aiming to automatically select those appropriate kernel functions for a given data set, we propose a multi-label learning based kernel recommendation method built on the data characteristics. For each data set, the meta-knowledge data base is first created by extracting the feature vector of data characteristics and identifying the corresponding applicable kernel set. Then the kernel recommendation model is constructed on the generated meta-knowledge data base with the multi-label classification method. Finally, the appropriate kernel functions are recommended to a new data set by the recommendation model according to the characteristics of the new data set. Extensive experiments over 132 UCI benchmark data sets, with five different types of data set characteristics, eleven typical kernels (Linear, Polynomial, Radial Basis Function, Sigmoidal function, Laplace, Multiquadric, Rational Quadratic, Spherical, Spline, Wave and Circular), and five multi-label classification methods demonstrate that, compared with the existing kernel selection methods and the most widely used RBF kernel function, SVM with the kernel function recommended by our proposed method achieved the highest classification performance.

  9. Broken rice kernels and the kinetics of rice hydration and texture during cooking.

    Science.gov (United States)

    Saleh, Mohammed; Meullenet, Jean-Francois

    2013-05-01

    During rice milling and processing, broken kernels are inevitably present, although to date it has been unclear as to how the presence of broken kernels affects rice hydration and cooked rice texture. Therefore, this work intended to study the effect of broken kernels in a rice sample on rice hydration and texture during cooking. Two medium-grain and two long-grain rice cultivars were harvested, dried and milled, and the broken kernels were separated from unbroken kernels. Broken rice kernels were subsequently combined with unbroken rice kernels forming treatments of 0, 40, 150, 350 or 1000 g kg(-1) broken kernels ratio. Rice samples were then cooked and the moisture content of the cooked rice, the moisture uptake rate, and rice hardness and stickiness were measured. As the amount of broken rice kernels increased, rice sample texture became increasingly softer (P hardness was negatively correlated to the percentage of broken kernels in rice samples. Differences in the proportions of broken rice in a milled rice sample play a major role in determining the texture properties of cooked rice. Variations in the moisture migration kinetics between broken and unbroken kernels caused faster hydration of the cores of broken rice kernels, with greater starch leach-out during cooking affecting the texture of the cooked rice. The texture of cooked rice can be controlled, to some extent, by varying the proportion of broken kernels in milled rice. © 2012 Society of Chemical Industry.

  10. Measurement of Weight of Kernels in a Simulated Cylindrical Fuel Compact for HTGR

    International Nuclear Information System (INIS)

    Kim, Woong Ki; Lee, Young Woo; Kim, Young Min; Kim, Yeon Ku; Eom, Sung Ho; Jeong, Kyung Chai; Cho, Moon Sung; Cho, Hyo Jin; Kim, Joo Hee

    2011-01-01

    The TRISO-coated fuel particle for the high temperature gas-cooled reactor (HTGR) is composed of a nuclear fuel kernel and outer coating layers. The coated particles are mixed with graphite matrix to make HTGR fuel element. The weight of fuel kernels in an element is generally measured by the chemical analysis or a gamma-ray spectrometer. Although it is accurate to measure the weight of kernels by the chemical analysis, the samples used in the analysis cannot be put again in the fabrication process. Furthermore, radioactive wastes are generated during the inspection procedure. The gamma-ray spectrometer requires an elaborate reference sample to reduce measurement errors induced from the different geometric shape of test sample from that of reference sample. X-ray computed tomography (CT) is an alternative to measure the weight of kernels in a compact nondestructively. In this study, X-ray CT is applied to measure the weight of kernels in a cylindrical compact containing simulated TRISO-coated particles with ZrO 2 kernels. The volume of kernels as well as the number of kernels in the simulated compact is measured from the 3-D density information. The weight of kernels was calculated from the volume of kernels or the number of kernels. Also, the weight of kernels was measured by extracting the kernels from a compact to review the result of the X-ray CT application

  11. Valor nutricional do farelo de algodão para alor a tilápia do nilo (Oreochromis niloticus = Nutritional value of cottonseed meal for Nile tilapia (Oreochromis niloticus

    Directory of Open Access Journals (Sweden)

    Geisa Karine Kleemann

    2009-01-01

    Full Text Available Determinou-se a composição química dos farelos de algodão 28,0; 38,0 e 46,0% de proteína bruta e os coeficientes de digestibilidade aparente (CDA pela tilápia do Nilo da matéria seca, proteína, aminoácidos, energia, lipídeo e minerais. Os CDA foram determinados, usando-se dieta-referência purificada, contendo 0,1% do indicador óxido de crômio-III. As rações-teste continham 60,0% da dieta-referência e 40,0% dos alimentos em estudo. Os resultados mostraram diferença (p Cottonseed meals (CSM with different protein levels (35, 39 and 40% were evaluated to determine their chemical composition and measure apparent digestibility coefficients (ADC of dry matter, protein, amino acids, energy, lipid and minerals for Nile tilapia. Apparent digestibility coefficients were determined using a reference purified diet containing 0.1% of chromic oxide indicator, and test diets contained 60% of reference diet and 40% of test ingredients. Results showed that apparent digestibility coefficients of cottonseed meals were different (p < 0.05. The apparent digestibility coefficients were: dry matter, 53.45-54.32%; crude protein, 71.56-74.81%; energy, 53.80-58.60%; lipid, 85.37- 89.11%; phosphorus, 33.75-34.50%; calcium, 41.21-43.75%; iron, 62.02-79.85%; zinc, 0- 67.41%; copper, 13.37-14.27%; essential amino acids, 71.39-79.17%; and non-essentialamino acids, 77.08-82.58%. The ADC of protein did not reflect the majority of amino acids ADC showing variation in individual digestibility of amino acids and among cottonseed meals. Cottonseed meal can be used as protein succedaneum in Nile tilapia diets.

  12. Theoretical developments for interpreting kernel spectral clustering from alternative viewpoints

    Directory of Open Access Journals (Sweden)

    Diego Peluffo-Ordóñez

    2017-08-01

    Full Text Available To perform an exploration process over complex structured data within unsupervised settings, the so-called kernel spectral clustering (KSC is one of the most recommended and appealing approaches, given its versatility and elegant formulation. In this work, we explore the relationship between (KSC and other well-known approaches, namely normalized cut clustering and kernel k-means. To do so, we first deduce a generic KSC model from a primal-dual formulation based on least-squares support-vector machines (LS-SVM. For experiments, KSC as well as other consider methods are assessed on image segmentation tasks to prove their usability.

  13. Modelling microwave heating of discrete samples of oil palm kernels

    International Nuclear Information System (INIS)

    Law, M.C.; Liew, E.L.; Chang, S.L.; Chan, Y.S.; Leo, C.P.

    2016-01-01

    Highlights: • Microwave (MW) drying of oil palm kernels is experimentally determined and modelled. • MW heating of discrete samples of oil palm kernels (OPKs) is simulated. • OPK heating is due to contact effect, MW interference and heat transfer mechanisms. • Electric field vectors circulate within OPKs sample. • Loosely-packed arrangement improves temperature uniformity of OPKs. - Abstract: Recently, microwave (MW) pre-treatment of fresh palm fruits has showed to be environmentally friendly compared to the existing oil palm milling process as it eliminates the condensate production of palm oil mill effluent (POME) in the sterilization process. Moreover, MW-treated oil palm fruits (OPF) also possess better oil quality. In this work, the MW drying kinetic of the oil palm kernels (OPK) was determined experimentally. Microwave heating/drying of oil palm kernels was modelled and validated. The simulation results show that temperature of an OPK is not the same over the entire surface due to constructive and destructive interferences of MW irradiance. The volume-averaged temperature of an OPK is higher than its surface temperature by 3–7 °C, depending on the MW input power. This implies that point measurement of temperature reading is inadequate to determine the temperature history of the OPK during the microwave heating process. The simulation results also show that arrangement of OPKs in a MW cavity affects the kernel temperature profile. The heating of OPKs were identified to be affected by factors such as local electric field intensity due to MW absorption, refraction, interference, the contact effect between kernels and also heat transfer mechanisms. The thermal gradient patterns of OPKs change as the heating continues. The cracking of OPKs is expected to occur first in the core of the kernel and then it propagates to the kernel surface. The model indicates that drying of OPKs is a much slower process compared to its MW heating. The model is useful

  14. Graphical analyses of connected-kernel scattering equations

    International Nuclear Information System (INIS)

    Picklesimer, A.

    1983-01-01

    Simple graphical techniques are employed to obtain a new (simultaneous) derivation of a large class of connected-kernel scattering equations. This class includes the Rosenberg, Bencze-Redish-Sloan, and connected-kernel multiple scattering equations as well as a host of generalizations of these and other equations. The basic result is the application of graphical methods to the derivation of interaction-set equations. This yields a new, simplified form for some members of the class and elucidates the general structural features of the entire class

  15. Reproducing Kernel Method for Solving Nonlinear Differential-Difference Equations

    Directory of Open Access Journals (Sweden)

    Reza Mokhtari

    2012-01-01

    Full Text Available On the basis of reproducing kernel Hilbert spaces theory, an iterative algorithm for solving some nonlinear differential-difference equations (NDDEs is presented. The analytical solution is shown in a series form in a reproducing kernel space, and the approximate solution , is constructed by truncating the series to terms. The convergence of , to the analytical solution is also proved. Results obtained by the proposed method imply that it can be considered as a simple and accurate method for solving such differential-difference problems.

  16. Kernel and divergence techniques in high energy physics separations

    Science.gov (United States)

    Bouř, Petr; Kůs, Václav; Franc, Jiří

    2017-10-01

    Binary decision trees under the Bayesian decision technique are used for supervised classification of high-dimensional data. We present a great potential of adaptive kernel density estimation as the nested separation method of the supervised binary divergence decision tree. Also, we provide a proof of alternative computing approach for kernel estimates utilizing Fourier transform. Further, we apply our method to Monte Carlo data set from the particle accelerator Tevatron at DØ experiment in Fermilab and provide final top-antitop signal separation results. We have achieved up to 82 % AUC while using the restricted feature selection entering the signal separation procedure.

  17. Rebootless Linux Kernel Patching with Ksplice Uptrack at BNL

    International Nuclear Information System (INIS)

    Hollowell, Christopher; Pryor, James; Smith, Jason

    2012-01-01

    Ksplice/Oracle Uptrack is a software tool and update subscription service which allows system administrators to apply security and bug fix patches to the Linux kernel running on servers/workstations without rebooting them. The RHIC/ATLAS Computing Facility (RACF) at Brookhaven National Laboratory (BNL) has deployed Uptrack on nearly 2,000 hosts running Scientific Linux and Red Hat Enterprise Linux. The use of this software has minimized downtime, and increased our security posture. In this paper, we provide an overview of Ksplice's rebootless kernel patch creation/insertion mechanism, and our experiences with Uptrack.

  18. Employment of kernel methods on wind turbine power performance assessment

    DEFF Research Database (Denmark)

    Skrimpas, Georgios Alexandros; Sweeney, Christian Walsted; Marhadi, Kun S.

    2015-01-01

    A power performance assessment technique is developed for the detection of power production discrepancies in wind turbines. The method employs a widely used nonparametric pattern recognition technique, the kernel methods. The evaluation is based on the trending of an extracted feature from...... the kernel matrix, called similarity index, which is introduced by the authors for the first time. The operation of the turbine and consequently the computation of the similarity indexes is classified into five power bins offering better resolution and thus more consistent root cause analysis. The accurate...

  19. Sparse kernel orthonormalized PLS for feature extraction in large datasets

    DEFF Research Database (Denmark)

    Arenas-García, Jerónimo; Petersen, Kaare Brandt; Hansen, Lars Kai

    2006-01-01

    In this paper we are presenting a novel multivariate analysis method for large scale problems. Our scheme is based on a novel kernel orthonormalized partial least squares (PLS) variant for feature extraction, imposing sparsity constrains in the solution to improve scalability. The algorithm...... is tested on a benchmark of UCI data sets, and on the analysis of integrated short-time music features for genre prediction. The upshot is that the method has strong expressive power even with rather few features, is clearly outperforming the ordinary kernel PLS, and therefore is an appealing method...

  20. Ground water

    International Nuclear Information System (INIS)

    Osmond, J.K.; Cowart, J.B.

    1982-01-01

    The subject is discussed under the headings: background and theory (introduction; fractionation in the hydrosphere; mobility factors; radioisotope evolution and aquifer classification; aquifer disequilibria and geochemical fronts); case studies (introduction; (a) conservative, and (b) non-conservative, behaviour); ground water dating applications (general requirements; radon and helium; radium isotopes; uranium isotopes). (U.K.)

  1. Ground water

    International Nuclear Information System (INIS)

    Osmond, J.K.; Cowart, J.B.

    1992-01-01

    The great variations in concentrations and activity ratios of 234 U/ 238 U in ground waters and the features causing elemental and isotopic mobility in the hydrosphere are discussed. Fractionation processes and their application to hydrology and other environmental problems such as earthquake, groundwater and aquifer dating are described. (UK)

  2. Supervised Kernel Optimized Locality Preserving Projection with Its Application to Face Recognition and Palm Biometrics

    Directory of Open Access Journals (Sweden)

    Chuang Lin

    2015-01-01

    Full Text Available Kernel Locality Preserving Projection (KLPP algorithm can effectively preserve the neighborhood structure of the database using the kernel trick. We have known that supervised KLPP (SKLPP can preserve within-class geometric structures by using label information. However, the conventional SKLPP algorithm endures the kernel selection which has significant impact on the performances of SKLPP. In order to overcome this limitation, a method named supervised kernel optimized LPP (SKOLPP is proposed in this paper, which can maximize the class separability in kernel learning. The proposed method maps the data from the original space to a higher dimensional kernel space using a data-dependent kernel. The adaptive parameters of the data-dependent kernel are automatically calculated through optimizing an objective function. Consequently, the nonlinear features extracted by SKOLPP have larger discriminative ability compared with SKLPP and are more adaptive to the input data. Experimental results on ORL, Yale, AR, and Palmprint databases showed the effectiveness of the proposed method.

  3. Comparative histological and transcriptional analysis of maize kernels infected with Aspergillus flavus and Fusarium verticillioides

    Science.gov (United States)

    Aspergillus flavus and Fusarium verticillioides infect maize kernels and contaminate them with the mycotoxins aflatoxin and fumonisin, respectively. Combined histological examination of fungal colonization and transcriptional changes in maize kernels at 4, 12, 24, 48, and 72 hours post inoculation (...

  4. Parameter Selection Method for Support Vector Regression Based on Adaptive Fusion of the Mixed Kernel Function

    Directory of Open Access Journals (Sweden)

    Hailun Wang

    2017-01-01

    Full Text Available Support vector regression algorithm is widely used in fault diagnosis of rolling bearing. A new model parameter selection method for support vector regression based on adaptive fusion of the mixed kernel function is proposed in this paper. We choose the mixed kernel function as the kernel function of support vector regression. The mixed kernel function of the fusion coefficients, kernel function parameters, and regression parameters are combined together as the parameters of the state vector. Thus, the model selection problem is transformed into a nonlinear system state estimation problem. We use a 5th-degree cubature Kalman filter to estimate the parameters. In this way, we realize the adaptive selection of mixed kernel function weighted coefficients and the kernel parameters, the regression parameters. Compared with a single kernel function, unscented Kalman filter (UKF support vector regression algorithms, and genetic algorithms, the decision regression function obtained by the proposed method has better generalization ability and higher prediction accuracy.

  5. The heating of UO_2 kernels in argon gas medium on the physical properties of sintered UO_2 kernels

    International Nuclear Information System (INIS)

    Damunir; Sri Rinanti Susilowati; Ariyani Kusuma Dewi

    2015-01-01

    The heating of UO_2 kernels in argon gas medium on the physical properties of sinter UO_2 kernels was conducted. The heated of the UO_2 kernels was conducted in a sinter reactor of a bed type. The sample used was the UO_2 kernels resulted from the reduction results at 800 °C temperature for 3 hours that had the density of 8.13 g/cm"3; porosity of 0.26; O/U ratio of 2.05; diameter of 1146 μm and sphericity of 1.05. The sample was put into a sinter reactor, then it was vacuumed by flowing the argon gas at 180 mmHg pressure to drain the air from the reactor. After that, the cooling water and argon gas were continuously flowed with the pressure of 5 mPa with 1.5 liter/minutes velocity. The reactor temperature was increased and variated at 1200-1500 °C temperature and for 1-4 hours. The sinters UO_2 kernels resulted from the study were analyzed in term of their physical properties including the density, porosity, diameter, sphericity, and specific surface area. The density was analyzed using pycnometer with CCl_4 solution. The porosity was determined using Haynes equation. The diameters and sphericity were showed using the Dino-lite microscope. The specific surface area was determined using surface area meter Nova-1000. The obtained products showed the the heating of UO_2 kernel in argon gas medium were influenced on the physical properties of sinters UO_2 kernel. The condition of best relatively at 1400 °C temperature and 2 hours time. The product resulted from the study was relatively at its best when heating was conducted at 1400 °C temperature and 2 hours time, produced sinters UO_2 kernel with density of 10.14 gr/ml; porosity of 7 %; diameters of 893 μm; sphericity of 1.07 and specific surface area of 4.68 m"2/g with solidify shrinkage of 22 %. (author)

  6. Biasing anisotropic scattering kernels for deep-penetration Monte Carlo calculations

    International Nuclear Information System (INIS)

    Carter, L.L.; Hendricks, J.S.

    1983-01-01

    The exponential transform is often used to improve the efficiency of deep-penetration Monte Carlo calculations. This technique is usually implemented by biasing the distance-to-collision kernel of the transport equation, but leaving the scattering kernel unchanged. Dwivedi obtained significant improvements in efficiency by biasing an isotropic scattering kernel as well as the distance-to-collision kernel. This idea is extended to anisotropic scattering, particularly the highly forward Klein-Nishina scattering of gamma rays

  7. The dipole form of the gluon part of the BFKL kernel

    International Nuclear Information System (INIS)

    Fadin, V.S.; Fiore, R.; Grabovsky, A.V.; Papa, A.

    2007-01-01

    The dipole form of the gluon part of the color singlet BFKL kernel in the next-to-leading order (NLO) is obtained in the coordinate representation by direct transfer from the momentum representation, where the kernel was calculated before. With this paper the transformation of the NLO BFKL kernel to the dipole form, started a few months ago with the quark part of the kernel, is completed

  8. Multivariable Christoffel-Darboux Kernels and Characteristic Polynomials of Random Hermitian Matrices

    Directory of Open Access Journals (Sweden)

    Hjalmar Rosengren

    2006-12-01

    Full Text Available We study multivariable Christoffel-Darboux kernels, which may be viewed as reproducing kernels for antisymmetric orthogonal polynomials, and also as correlation functions for products of characteristic polynomials of random Hermitian matrices. Using their interpretation as reproducing kernels, we obtain simple proofs of Pfaffian and determinant formulas, as well as Schur polynomial expansions, for such kernels. In subsequent work, these results are applied in combinatorics (enumeration of marked shifted tableaux and number theory (representation of integers as sums of squares.

  9. Ground Pollution Science

    International Nuclear Information System (INIS)

    Oh, Jong Min; Bae, Jae Geun

    1997-08-01

    This book deals with ground pollution science and soil science, classification of soil and fundamentals, ground pollution and human, ground pollution and organic matter, ground pollution and city environment, environmental problems of the earth and ground pollution, soil pollution and development of geological features of the ground, ground pollution and landfill of waste, case of measurement of ground pollution.

  10. Flexible Scheduling by Deadline Inheritance in Soft Real Time Kernels

    NARCIS (Netherlands)

    Jansen, P.G.; Wygerink, Emiel

    1996-01-01

    Current Hard Real Time (HRT) kernels have their timely behaviour guaranteed on the cost of a rather restrictive use of the available resources. This makes HRT scheduling techniques inadequate for use in Soft Real Time (SRT) environment where we can make a considerable profit by a better and more

  11. MARMER, a flexible point-kernel shielding code

    International Nuclear Information System (INIS)

    Kloosterman, J.L.; Hoogenboom, J.E.

    1990-01-01

    A point-kernel shielding code entitled MARMER is described. It has several options with respect to geometry input, source description and detector point description which extend the flexibility and usefulness of the code, and which are especially useful in spent fuel shielding. MARMER has been validated using the TN12 spent fuel shipping cask benchmark. (author)

  12. MARMER, a flexible point-kernel shielding code

    Energy Technology Data Exchange (ETDEWEB)

    Kloosterman, J.L.; Hoogenboom, J.E. (Interuniversitair Reactor Inst., Delft (Netherlands))

    1990-01-01

    A point-kernel shielding code entitled MARMER is described. It has several options with respect to geometry input, source description and detector point description which extend the flexibility and usefulness of the code, and which are especially useful in spent fuel shielding. MARMER has been validated using the TN12 spent fuel shipping cask benchmark. (author).

  13. Mycological deterioration of stored palm kernels recovered from oil ...

    African Journals Online (AJOL)

    Palm kernels obtained from Pioneer Oil Mill Ltd. were stored for eight (8) weeks and examined for their microbiological quality and proximate composition. Seven (7) different fungal species were isolated by serial dilution plate technique. The fungal species included Aspergillus flavus Link; A nidulans Eidem; A niger ...

  14. Metabolite identification through multiple kernel learning on fragmentation trees.

    Science.gov (United States)

    Shen, Huibin; Dührkop, Kai; Böcker, Sebastian; Rousu, Juho

    2014-06-15

    Metabolite identification from tandem mass spectrometric data is a key task in metabolomics. Various computational methods have been proposed for the identification of metabolites from tandem mass spectra. Fragmentation tree methods explore the space of possible ways in which the metabolite can fragment, and base the metabolite identification on scoring of these fragmentation trees. Machine learning methods have been used to map mass spectra to molecular fingerprints; predicted fingerprints, in turn, can be used to score candidate molecular structures. Here, we combine fragmentation tree computations with kernel-based machine learning to predict molecular fingerprints and identify molecular structures. We introduce a family of kernels capturing the similarity of fragmentation trees, and combine these kernels using recently proposed multiple kernel learning approaches. Experiments on two large reference datasets show that the new methods significantly improve molecular fingerprint prediction accuracy. These improvements result in better metabolite identification, doubling the number of metabolites ranked at the top position of the candidates list. © The Author 2014. Published by Oxford University Press.

  15. Notes on a storage manager for the Clouds kernel

    Science.gov (United States)

    Pitts, David V.; Spafford, Eugene H.

    1986-01-01

    The Clouds project is research directed towards producing a reliable distributed computing system. The initial goal is to produce a kernel which provides a reliable environment with which a distributed operating system can be built. The Clouds kernal consists of a set of replicated subkernels, each of which runs on a machine in the Clouds system. Each subkernel is responsible for the management of resources on its machine; the subkernal components communicate to provide the cooperation necessary to meld the various machines into one kernel. The implementation of a kernel-level storage manager that supports reliability is documented. The storage manager is a part of each subkernel and maintains the secondary storage residing at each machine in the distributed system. In addition to providing the usual data transfer services, the storage manager ensures that data being stored survives machine and system crashes, and that the secondary storage of a failed machine is recovered (made consistent) automatically when the machine is restarted. Since the storage manager is part of the Clouds kernel, efficiency of operation is also a concern.

  16. On Convergence of Kernel Density Estimates in Particle Filtering

    Czech Academy of Sciences Publication Activity Database

    Coufal, David

    2016-01-01

    Roč. 52, č. 5 (2016), s. 735-756 ISSN 0023-5954 Grant - others:GA ČR(CZ) GA16-03708S; SVV(CZ) 260334/2016 Institutional support: RVO:67985807 Keywords : Fourier analysis * kernel methods * particle filter Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.379, year: 2016

  17. Screening of the kernels of Pentadesma butyracea from various ...

    African Journals Online (AJOL)

    Gwla10

    Joseph D. Hounhouigan. 2. 1Laboratoire de .... laboratory. Kernels were washed and dried at 45°C for 72 h before analysis. ... generated values allow calculating the various shape ... (LLYOD Instruments, USA) fit with a 0.42 cm thick blade with a triangular ... vacuum. Extraction was run in triplicate on germ, albumen and.

  18. Some engineering properties of shelled and kernel tea ( Camellia ...

    African Journals Online (AJOL)

    Some engineering properties (size dimensions, sphericity, volume, bulk and true densities, friction coefficient, colour characteristics and mechanical behaviour as rupture ... The static coefficients of friction of shelled and kernel tea seeds for the large and small sizes higher values for rubber than the other friction surfaces.

  19. PERI - auto-tuning memory-intensive kernels for multicore

    International Nuclear Information System (INIS)

    Williams, S; Carter, J; Oliker, L; Shalf, J; Yelick, K; Bailey, D; Datta, K

    2008-01-01

    We present an auto-tuning approach to optimize application performance on emerging multicore architectures. The methodology extends the idea of search-based performance optimizations, popular in linear algebra and FFT libraries, to application-specific computational kernels. Our work applies this strategy to sparse matrix vector multiplication (SpMV), the explicit heat equation PDE on a regular grid (Stencil), and a lattice Boltzmann application (LBMHD). We explore one of the broadest sets of multicore architectures in the high-performance computing literature, including the Intel Xeon Clovertown, AMD Opteron Barcelona, Sun Victoria Falls, and the Sony-Toshiba-IBM (STI) Cell. Rather than hand-tuning each kernel for each system, we develop a code generator for each kernel that allows us identify a highly optimized version for each platform, while amortizing the human programming effort. Results show that our auto-tuned kernel applications often achieve a better than 4x improvement compared with the original code. Additionally, we analyze a Roofline performance model for each platform to reveal hardware bottlenecks and software challenges for future multicore systems and applications

  20. Deep sequencing of RNA from ancient maize kernels

    DEFF Research Database (Denmark)

    Fordyce, Sarah Louise; Avila Arcos, Maria del Carmen; Rasmussen, Morten

    2013-01-01

    The characterization of biomolecules from ancient samples can shed otherwise unobtainable insights into the past. Despite the fundamental role of transcriptomal change in evolution, the potential of ancient RNA remains unexploited - perhaps due to dogma associated with the fragility of RNA. We hy...... maize kernels. The results suggest that ancient seed transcriptomics may offer a powerful new tool with which to study plant domestication....

  1. Effect of Coconut ( cocus Nucifera ) and Palm Kernel ( eleasis ...

    African Journals Online (AJOL)

    Effect of Coconut ( cocus Nucifera ) and Palm Kernel ( eleasis Guinensis ) Oil Supplmented Diets on Serum Lipid Profile of Albino Wistar Rats. ... were fed normal rat pellet. At the end of the feeding period, animals were anaesthetized under chloroform vapor, dissected and blood obtained via cardiac puncture into tubes.

  2. Calculation of Volterra kernels for solutions of nonlinear differential equations

    NARCIS (Netherlands)

    van Hemmen, JL; Kistler, WM; Thomas, EGF

    2000-01-01

    We consider vector-valued autonomous differential equations of the form x' = f(x) + phi with analytic f and investigate the nonanticipative solution operator phi bar right arrow A(phi) in terms of its Volterra series. We show that Volterra kernels of order > 1 occurring in the series expansion of

  3. Moderate deviations principles for the kernel estimator of ...

    African Journals Online (AJOL)

    Abstract. The aim of this paper is to provide pointwise and uniform moderate deviations principles for the kernel estimator of a nonrandom regression function. Moreover, we give an application of these moderate deviations principles to the construction of condence regions for the regression function. Resume. L'objectif de ...

  4. Hollow microspheres with a tungsten carbide kernel for PEMFC application.

    Science.gov (United States)

    d'Arbigny, Julien Bernard; Taillades, Gilles; Marrony, Mathieu; Jones, Deborah J; Rozière, Jacques

    2011-07-28

    Tungsten carbide microspheres comprising an outer shell and a compact kernel prepared by a simple hydrothermal method exhibit very high surface area promoting a high dispersion of platinum nanoparticles, and an exceptionally high electrochemically active surface area (EAS) stability compared to the usual Pt/C electrocatalysts used for PEMFC application.

  5. Fractional quantum integral operator with general kernels and applications

    Science.gov (United States)

    Babakhani, Azizollah; Neamaty, Abdolali; Yadollahzadeh, Milad; Agahi, Hamzeh

    In this paper, we first introduce the concept of fractional quantum integral with general kernels, which generalizes several types of fractional integrals known from the literature. Then we give more general versions of some integral inequalities for this operator, thus generalizing some previous results obtained by many researchers.2,8,25,29,30,36

  6. Optimizing Multiple Kernel Learning for the Classification of UAV Data

    Directory of Open Access Journals (Sweden)

    Caroline M. Gevaert

    2016-12-01

    Full Text Available Unmanned Aerial Vehicles (UAVs are capable of providing high-quality orthoimagery and 3D information in the form of point clouds at a relatively low cost. Their increasing popularity stresses the necessity of understanding which algorithms are especially suited for processing the data obtained from UAVs. The features that are extracted from the point cloud and imagery have different statistical characteristics and can be considered as heterogeneous, which motivates the use of Multiple Kernel Learning (MKL for classification problems. In this paper, we illustrate the utility of applying MKL for the classification of heterogeneous features obtained from UAV data through a case study of an informal settlement in Kigali, Rwanda. Results indicate that MKL can achieve a classification accuracy of 90.6%, a 5.2% increase over a standard single-kernel Support Vector Machine (SVM. A comparison of seven MKL methods indicates that linearly-weighted kernel combinations based on simple heuristics are competitive with respect to computationally-complex, non-linear kernel combination methods. We further underline the importance of utilizing appropriate feature grouping strategies for MKL, which has not been directly addressed in the literature, and we propose a novel, automated feature grouping method that achieves a high classification accuracy for various MKL methods.

  7. Corruption clubs: empirical evidence from kernel density estimates

    NARCIS (Netherlands)

    Herzfeld, T.; Weiss, Ch.

    2007-01-01

    A common finding of many analytical models is the existence of multiple equilibria of corruption. Countries characterized by the same economic, social and cultural background do not necessarily experience the same levels of corruption. In this article, we use Kernel Density Estimation techniques to

  8. A compact kernel for the calculus of inductive constructions

    Indian Academy of Sciences (India)

    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 ...

  9. Finite Gaussian Mixture Approximations to Analytically Intractable Density Kernels

    DEFF Research Database (Denmark)

    Khorunzhina, Natalia; Richard, Jean-Francois

    The objective of the paper is that of constructing finite Gaussian mixture approximations to analytically intractable density kernels. The proposed method is adaptive in that terms are added one at the time and the mixture is fully re-optimized at each step using a distance measure that approxima...

  10. Disinfection studies of Nahar (Mesua ferrea) seed kernel oil using ...

    African Journals Online (AJOL)

    GREGORY

    2011-12-16

    Dec 16, 2011 ... with a k value of -0.040. Key words: Nahar (Mesua ferrea) seed kernel oil, extraction, gum Arabic, disinfection, kinetics. INTRODUCTION. Disinfection plays a key role in the reclamation and reuse of wastewater for eliminating infectious diseases, this, in part, augments domestic water supply and decreases ...

  11. Improved Interpolation Kernels for Super-resolution Algorithms

    DEFF Research Database (Denmark)

    Rasti, Pejman; Orlova, Olga; Tamberg, Gert

    2016-01-01

    Super resolution (SR) algorithms are widely used in forensics investigations to enhance the resolution of images captured by surveillance cameras. Such algorithms usually use a common interpolation algorithm to generate an initial guess for the desired high resolution (HR) image. This initial guess...... when their original interpolation kernel is replaced by the ones introduced in this work....

  12. Briquetting of Palm Kernel Shell | Ugwu | Journal of Applied ...

    African Journals Online (AJOL)

    In several developing countries, briquettes from agricultural residues contribute significantly to the energy mix especially for small scale and household requirements. In this work, briquettes were produced from Palm kernel shell. This was achieved by carbonising the shell to get the charcoal followed by the pulverization of ...

  13. Controller synthesis for L2 behaviors using rational kernel representations

    NARCIS (Netherlands)

    Mutsaers, M.E.C.; Weiland, S.

    2008-01-01

    This paper considers the controller synthesis problem for the class of linear time-invariant L2 behaviors. We introduce classes of LTI L2 systems whose behavior can be represented as the kernel of a rational operator. Given a plant and a controlled system in this class, an algorithm is developed

  14. Recent sea level change analysed with kernel EOF

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg; Andersen, Ole Baltazar; Knudsen, Per

    2009-01-01

    -2008. Preliminary analysis shows some interesting features related to climate change and particularly the pulsing of the El Niño/Southern Oscillation. Large scale ocean events associated with the El Niño/Southern Oscillation related signals are conveniently concentrated in the first SSH kernel EOF modes....

  15. Polynomial kernels for deletion to classes of acyclic digraphs

    NARCIS (Netherlands)

    Mnich, Matthias; van Leeuwen, E.J.

    2017-01-01

    We consider the problem to find a set X of vertices (or arcs) with |X| ≤ k in a given digraph G such that D = G − X is an acyclic digraph. In its generality, this is Directed Feedback Vertex Set (or Directed Feedback Arc Set); the existence of a polynomial kernel for these problems is a notorious

  16. Nutritional evaluation of fermented palm kernel cake using red tilapia

    African Journals Online (AJOL)

    The use of palm kernel cake (PKC) and other plant residues in fish feeding especially under extensive aquaculture have been in practice for a long time. On the other hand, the use of microbial-based feedstuff is increasing. In this study, the performance of red tilapia raised on Trichoderma longibrachiatum fermented PKC ...

  17. Preparation and characterization of active carbon using palm kernel ...

    African Journals Online (AJOL)

    Activated carbons were prepared from Palm kernel shells. Carbonization temperature was 6000C, at a residence time of 5 min for each process. Chemical activation was done by heating a mixture of carbonized material and the activating agents at a temperature of 700C to form a paste, followed by subsequent cooling and ...

  18. Matrix kernels for MEG and EEG source localization and imaging

    International Nuclear Information System (INIS)

    Mosher, J.C.; Lewis, P.S.; Leahy, R.M.

    1994-01-01

    The most widely used model for electroencephalography (EEG) and magnetoencephalography (MEG) assumes a quasi-static approximation of Maxwell's equations and a piecewise homogeneous conductor model. Both models contain an incremental field element that linearly relates an incremental source element (current dipole) to the field or voltage at a distant point. The explicit form of the field element is dependent on the head modeling assumptions and sensor configuration. Proper characterization of this incremental element is crucial to the inverse problem. The field element can be partitioned into the product of a vector dependent on sensor characteristics and a matrix kernel dependent only on head modeling assumptions. We present here the matrix kernels for the general boundary element model (BEM) and for MEG spherical models. We show how these kernels are easily interchanged in a linear algebraic framework that includes sensor specifics such as orientation and gradiometer configuration. We then describe how this kernel is easily applied to ''gain'' or ''transfer'' matrices used in multiple dipole and source imaging models

  19. PERI - Auto-tuning Memory Intensive Kernels for Multicore

    Energy Technology Data Exchange (ETDEWEB)

    Bailey, David H; Williams, Samuel; Datta, Kaushik; Carter, Jonathan; Oliker, Leonid; Shalf, John; Yelick, Katherine; Bailey, David H

    2008-06-24

    We present an auto-tuning approach to optimize application performance on emerging multicore architectures. The methodology extends the idea of search-based performance optimizations, popular in linear algebra and FFT libraries, to application-specific computational kernels. Our work applies this strategy to Sparse Matrix Vector Multiplication (SpMV), the explicit heat equation PDE on a regular grid (Stencil), and a lattice Boltzmann application (LBMHD). We explore one of the broadest sets of multicore architectures in the HPC literature, including the Intel Xeon Clovertown, AMD Opteron Barcelona, Sun Victoria Falls, and the Sony-Toshiba-IBM (STI) Cell. Rather than hand-tuning each kernel for each system, we develop a code generator for each kernel that allows us to identify a highly optimized version for each platform, while amortizing the human programming effort. Results show that our auto-tuned kernel applications often achieve a better than 4X improvement compared with the original code. Additionally, we analyze a Roofline performance model for each platform to reveal hardware bottlenecks and software challenges for future multicore systems and applications.

  20. An Adaptive Genetic Association Test Using Double Kernel Machines.

    Science.gov (United States)

    Zhan, Xiang; Epstein, Michael P; Ghosh, Debashis

    2015-10-01

    Recently, gene set-based approaches have become very popular in gene expression profiling studies for assessing how genetic variants are related to disease outcomes. Since most genes are not differentially expressed, existing pathway tests considering all genes within a pathway suffer from considerable noise and power loss. Moreover, for a differentially expressed pathway, it is of interest to select important genes that drive the effect of the pathway. In this article, we propose an adaptive association test using double kernel machines (DKM), which can both select important genes within the pathway as well as test for the overall genetic pathway effect. This DKM procedure first uses the garrote kernel machines (GKM) test for the purposes of subset selection and then the least squares kernel machine (LSKM) test for testing the effect of the subset of genes. An appealing feature of the kernel machine framework is that it can provide a flexible and unified method for multi-dimensional modeling of the genetic pathway effect allowing for both parametric and nonparametric components. This DKM approach is illustrated with application to simulated data as well as to data from a neuroimaging genetics study.

  1. Evaluating Equating Results: Percent Relative Error for Chained Kernel Equating

    Science.gov (United States)

    Jiang, Yanlin; von Davier, Alina A.; Chen, Haiwen

    2012-01-01

    This article presents a method for evaluating equating results. Within the kernel equating framework, the percent relative error (PRE) for chained equipercentile equating was computed under the nonequivalent groups with anchor test (NEAT) design. The method was applied to two data sets to obtain the PRE, which can be used to measure equating…

  2. Structured Kernel Subspace Learning for Autonomous Robot Navigation.

    Science.gov (United States)

    Kim, Eunwoo; Choi, Sungjoon; Oh, Songhwai

    2018-02-14

    This paper considers two important problems for autonomous robot navigation in a dynamic environment, where the goal is to predict pedestrian motion and control a robot with the prediction for safe navigation. While there are several methods for predicting the motion of a pedestrian and controlling a robot to avoid incoming pedestrians, it is still difficult to safely navigate in a dynamic environment due to challenges, such as the varying quality and complexity of training data with unwanted noises. This paper addresses these challenges simultaneously by proposing a robust kernel subspace learning algorithm based on the recent advances in nuclear-norm and l 1 -norm minimization. We model the motion of a pedestrian and the robot controller using Gaussian processes. The proposed method efficiently approximates a kernel matrix used in Gaussian process regression by learning low-rank structured matrix (with symmetric positive semi-definiteness) to find an orthogonal basis, which eliminates the effects of erroneous and inconsistent data. Based on structured kernel subspace learning, we propose a robust motion model and motion controller for safe navigation in dynamic environments. We evaluate the proposed robust kernel learning in various tasks, including regression, motion prediction, and motion control problems, and demonstrate that the proposed learning-based systems are robust against outliers and outperform existing regression and navigation methods.

  3. Bayesian Frequency Domain Identification of LTI Systems with OBFs kernels

    NARCIS (Netherlands)

    Darwish, M.A.H.; Lataire, J.P.G.; Tóth, R.

    2017-01-01

    Regularised Frequency Response Function (FRF) estimation based on Gaussian process regression formulated directly in the frequency-domain has been introduced recently The underlying approach largely depends on the utilised kernel function, which encodes the relevant prior knowledge on the system

  4. Single pass kernel k-means clustering method

    Indian Academy of Sciences (India)

    In unsupervised classification, kernel -means clustering method has been shown to perform better than conventional -means clustering method in ... 518501, India; Department of Computer Science and Engineering, Jawaharlal Nehru Technological University, Anantapur College of Engineering, Anantapur 515002, India ...

  5. Szegö Kernels and Asymptotic Expansions for Legendre Polynomials

    Directory of Open Access Journals (Sweden)

    Roberto Paoletti

    2017-01-01

    Full Text Available We present a geometric approach to the asymptotics of the Legendre polynomials Pk,n+1, based on the Szegö kernel of the Fermat quadric hypersurface, leading to complete asymptotic expansions holding on expanding subintervals of [-1,1].

  6. Magnetic resonance imaging of single rice kernels during cooking

    NARCIS (Netherlands)

    Mohoric, A.; Vergeldt, F.J.; Gerkema, E.; Jager, de P.A.; Duynhoven, van J.P.M.; Dalen, van G.; As, van H.

    2004-01-01

    The RARE imaging method was used to monitor the cooking of single rice kernels in real time and with high spatial resolution in three dimensions. The imaging sequence is optimized for rapid acquisition of signals with short relaxation times using centered out RARE. Short scan time and high spatial

  7. Optimizing memory-bound SYMV kernel on GPU hardware accelerators

    KAUST Repository

    Abdelfattah, Ahmad; Dongarra, Jack; Keyes, David E.; Ltaief, Hatem

    2013-01-01

    and increasing bandwidth, our preliminary asymptotic results show 3.5x and 2.5x fold speedups over the similar CUBLAS 4.0 kernel, and 7-8% and 30% fold improvement over the Matrix Algebra on GPU and Multicore Architectures (MAGMA) library in single and double

  8. 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 on v...

  9. Effects of de-oiled palm kernel cake based fertilizers on sole maize ...

    African Journals Online (AJOL)

    A study was conducted to determine the effect of de-oiled palm kernel cake based fertilizer formulations on the yield of sole maize and cassava crops. Two de-oiled palm kernel cake based fertilizer formulations A and B were compounded from different proportions of de-oiled palm kernel cake, urea, muriate of potash and ...

  10. System identification via sparse multiple kernel-based regularization using sequential convex optimization techniques

    DEFF Research Database (Denmark)

    Chen, Tianshi; Andersen, Martin Skovgaard; Ljung, Lennart

    2014-01-01

    Model estimation and structure detection with short data records are two issues that receive increasing interests in System Identification. In this paper, a multiple kernel-based regularization method is proposed to handle those issues. Multiple kernels are conic combinations of fixed kernels...

  11. Differential metabolome analysis of field-grown maize kernels in response to drought stress

    Science.gov (United States)

    Drought stress constrains maize kernel development and can exacerbate aflatoxin contamination. In order to identify drought responsive metabolites and explore pathways involved in kernel responses, a metabolomics analysis was conducted on kernels from a drought tolerant line, Lo964, and a sensitive ...

  12. Using the Intel Math Kernel Library on Peregrine | High-Performance

    Science.gov (United States)

    Computing | NREL the Intel Math Kernel Library on Peregrine Using the Intel Math Kernel Library on Peregrine Learn how to use the Intel Math Kernel Library (MKL) with Peregrine system software. MKL architectures. Core math functions in MKL include BLAS, LAPACK, ScaLAPACK, sparse solvers, fast Fourier

  13. Kernel based pattern analysis methods using eigen-decompositions for reading Icelandic sagas

    DEFF Research Database (Denmark)

    Christiansen, Asger Nyman; Carstensen, Jens Michael

    We want to test the applicability of kernel based eigen-decomposition methods, compared to the traditional eigen-decomposition methods. We have implemented and tested three kernel based methods methods, namely PCA, MAF and MNF, all using a Gaussian kernel. We tested the methods on a multispectral...... image of a page in the book 'hauksbok', which contains Icelandic sagas....

  14. Interaction between UO2 kernel and pyrocarbon coating in irradiated and unirradiated HTR fuel particles

    International Nuclear Information System (INIS)

    Drago, A.; Klersy, R.; Simoni, O.; Schrader, K.H.

    1975-08-01

    Experimental observations on unidirectional UO 2 kernel migration in TRISO type coated particle fuels are reported. An analysis of the experimental results on the basis of data and models from the literature is reported. The stoichiometric composition of the kernel is considered the main parameter that, associated with a temperature gradient, controls the unidirectional kernel migration

  15. Occurrence of 'super soft' wheat kernel texture in hexaploid and tetraploid wheats

    Science.gov (United States)

    Wheat kernel texture is a key trait that governs milling performance, flour starch damage, flour particle size, flour hydration properties, and baking quality. Kernel texture is commonly measured using the Perten Single Kernel Characterization System (SKCS). The SKCS returns texture values (Hardness...

  16. Genome-wide Association Analysis of Kernel Weight in Hard Winter Wheat

    Science.gov (United States)

    Wheat kernel weight is an important and heritable component of wheat grain yield and a key predictor of flour extraction. Genome-wide association analysis was conducted to identify genomic regions associated with kernel weight and kernel weight environmental response in 8 trials of 299 hard winter ...

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

    Science.gov (United States)

    2012-04-01

    Kevin Stone, Derek T. Anderson, James M. Keller, Dominic K.C. Ho, Tuan T. Ton, David C. Wong , Mehrdad Soumekh University of Missouri - Columbia...James M. Kellera, K.C. Hoa, Tuan T. Tone, David C. Wong\\ and Mehrdad Soumekhd aDept. ofElectrical and Computer Engineering, University of Missouri...2] Cremer , F., Schavemaker, J.G., de Jong, W., and Schutte, K., "Comparison of vehicle-mounted forward-looking polarimetric infrared and downward

  18. Gaussian interaction profile kernels for predicting drug-target interaction.

    Science.gov (United States)

    van Laarhoven, Twan; Nabuurs, Sander B; Marchiori, Elena

    2011-11-01

    The in silico prediction of potential interactions between drugs and target proteins is of core importance for the identification of new drugs or novel targets for existing drugs. However, only a tiny portion of all drug-target pairs in current datasets are experimentally validated interactions. This motivates the need for developing computational methods that predict true interaction pairs with high accuracy. We show that a simple machine learning method that uses the drug-target network as the only source of information is capable of predicting true interaction pairs with high accuracy. Specifically, we introduce interaction profiles of drugs (and of targets) in a network, which are binary vectors specifying the presence or absence of interaction with every target (drug) in that network. We define a kernel on these profiles, called the Gaussian Interaction Profile (GIP) kernel, and use a simple classifier, (kernel) Regularized Least Squares (RLS), for prediction drug-target interactions. We test comparatively the effectiveness of RLS with the GIP kernel on four drug-target interaction networks used in previous studies. The proposed algorithm achieves area under the precision-recall curve (AUPR) up to 92.7, significantly improving over results of state-of-the-art methods. Moreover, we show that using also kernels based on chemical and genomic information further increases accuracy, with a neat improvement on small datasets. These results substantiate the relevance of the network topology (in the form of interaction profiles) as source of information for predicting drug-target interactions. Software and Supplementary Material are available at http://cs.ru.nl/~tvanlaarhoven/drugtarget2011/. tvanlaarhoven@cs.ru.nl; elenam@cs.ru.nl. Supplementary data are available at Bioinformatics online.

  19. A kernel for open source drug discovery in tropical diseases.

    Science.gov (United States)

    Ortí, Leticia; Carbajo, Rodrigo J; Pieper, Ursula; Eswar, Narayanan; Maurer, Stephen M; Rai, Arti K; Taylor, Ginger; Todd, Matthew H; Pineda-Lucena, Antonio; Sali, Andrej; Marti-Renom, Marc A

    2009-01-01

    Conventional patent-based drug development incentives work badly for the developing world, where commercial markets are usually small to non-existent. For this reason, the past decade has seen extensive experimentation with alternative R&D institutions ranging from private-public partnerships to development prizes. Despite extensive discussion, however, one of the most promising avenues-open source drug discovery-has remained elusive. We argue that the stumbling block has been the absence of a critical mass of preexisting work that volunteers can improve through a series of granular contributions. Historically, open source software collaborations have almost never succeeded without such "kernels". HERE, WE USE A COMPUTATIONAL PIPELINE FOR: (i) comparative structure modeling of target proteins, (ii) predicting the localization of ligand binding sites on their surfaces, and (iii) assessing the similarity of the predicted ligands to known drugs. Our kernel currently contains 143 and 297 protein targets from ten pathogen genomes that are predicted to bind a known drug or a molecule similar to a known drug, respectively. The kernel provides a source of potential drug targets and drug candidates around which an online open source community can nucleate. Using NMR spectroscopy, we have experimentally tested our predictions for two of these targets, confirming one and invalidating the other. The TDI kernel, which is being offered under the Creative Commons attribution share-alike license for free and unrestricted use, can be accessed on the World Wide Web at http://www.tropicaldisease.org. We hope that the kernel will facilitate collaborative efforts towards the discovery of new drugs against parasites that cause tropical diseases.

  20. Adaptive kernel regression for freehand 3D ultrasound reconstruction

    Science.gov (United States)

    Alshalalfah, Abdel-Latif; Daoud, Mohammad I.; Al-Najar, Mahasen

    2017-03-01

    Freehand three-dimensional (3D) ultrasound imaging enables low-cost and flexible 3D scanning of arbitrary-shaped organs, where the operator can freely move a two-dimensional (2D) ultrasound probe to acquire a sequence of tracked cross-sectional images of the anatomy. Often, the acquired 2D ultrasound images are irregularly and sparsely distributed in the 3D space. Several 3D reconstruction algorithms have been proposed to synthesize 3D ultrasound volumes based on the acquired 2D images. A challenging task during the reconstruction process is to preserve the texture patterns in the synthesized volume and ensure that all gaps in the volume are correctly filled. This paper presents an adaptive kernel regression algorithm that can effectively reconstruct high-quality freehand 3D ultrasound volumes. The algorithm employs a kernel regression model that enables nonparametric interpolation of the voxel gray-level values. The kernel size of the regression model is adaptively adjusted based on the characteristics of the voxel that is being interpolated. In particular, when the algorithm is employed to interpolate a voxel located in a region with dense ultrasound data samples, the size of the kernel is reduced to preserve the texture patterns. On the other hand, the size of the kernel is increased in areas that include large gaps to enable effective gap filling. The performance of the proposed algorithm was compared with seven previous interpolation approaches by synthesizing freehand 3D ultrasound volumes of a benign breast tumor. The experimental results show that the proposed algorithm outperforms the other interpolation approaches.

  1. Nutrient digestibility and milk production responses to increasing levels of palmitic acid supplementation vary in cows receiving diets with or without whole cottonseed.

    Science.gov (United States)

    Rico, J E; de Souza, J; Allen, M S; Lock, A L

    2017-01-01

    Our study evaluated the dose-dependent effects of a palmitic acid-enriched supplement in basal diets with or without the inclusion of whole cottonseed on nutrient digestibility and production responses of dairy cows. Sixteen Holstein cows (149 ± 56 days in milk) were used in a split plot Latin square design experiment. Cows were blocked by 3.5% fat-corrected milk (FCM) and allocated to a main plot receiving either a basal diet with soyhulls (SH, = 8) or a basal diet with whole cottonseed (CS, = 8) that was fed throughout the experiment. A palmitic acid-enriched supplement (PA 88.5% C16:0) was fed at 0, 0.75, 1.50, or 2.25% of ration DM in a replicated 4 × 4 Latin Square design within each basal diet group. Periods were 14 d with the final 4 d used for data collection. PA dose increased milk fat content linearly, and cubically affected yields of milk fat and 3.5% FCM. The PA dose did not affect milk protein and lactose contents, BW, and BCS, but tended to increase yields of milk, milk protein, and milk lactose. Also, PA dose reduced DMI and 16-carbon fatty acid digestibility quadratically, and increased 18-carbon fatty acid digestibility quadratically. There were no effects of basal diet on the yield of milk or milk components, but DMI tended to decrease in CS compared with SH, increasing feed efficiency (3.5% FCM/DMI). Compared with SH, CS diets increased yield of preformed milk fatty acids and 16-carbon fatty acid digestibility, and tended to decrease 18-carbon fatty acid digestibility. We observed basal diet × PA dose interactions for yields of milk and milk protein and for 16-carbon and total fatty acid digestibility, as well as tendency for yields of milk fat and 3.5% FCM. Also, there was a tendency for an interaction between basal diet and PA dose for NDF digestibility, which increased more for CS with increasing PA than for SH. PA dose linearly decreased digestibility of total fatty acids in SH diets but did not affect it in CS diets Results demonstrate

  2. Unified heat kernel regression for diffusion, kernel smoothing and wavelets on manifolds and its application to mandible growth modeling in CT images.

    Science.gov (United States)

    Chung, Moo K; Qiu, Anqi; Seo, Seongho; Vorperian, Houri K

    2015-05-01

    We present a novel kernel regression framework for smoothing scalar surface data using the Laplace-Beltrami eigenfunctions. Starting with the heat kernel constructed from the eigenfunctions, we formulate a new bivariate kernel regression framework as a weighted eigenfunction expansion with the heat kernel as the weights. The new kernel method is mathematically equivalent to isotropic heat diffusion, kernel smoothing and recently popular diffusion wavelets. The numerical implementation is validated on a unit sphere using spherical harmonics. As an illustration, the method is applied to characterize the localized growth pattern of mandible surfaces obtained in CT images between ages 0 and 20 by regressing the length of displacement vectors with respect to a surface template. Copyright © 2015 Elsevier B.V. All rights reserved.

  3. Communication grounding facility

    International Nuclear Information System (INIS)

    Lee, Gye Seong

    1998-06-01

    It is about communication grounding facility, which is made up twelve chapters. It includes general grounding with purpose, materials thermal insulating material, construction of grounding, super strength grounding method, grounding facility with grounding way and building of insulating, switched grounding with No. 1A and LCR, grounding facility of transmission line, wireless facility grounding, grounding facility in wireless base station, grounding of power facility, grounding low-tenton interior power wire, communication facility of railroad, install of arrester in apartment and house, install of arrester on introduction and earth conductivity and measurement with introduction and grounding resistance.

  4. Effect of dietary cottonseed meal on growth performance, physiological response, and gossypol accumulation in pre-adult grass carp, Ctenopharyngodon idellus

    Science.gov (United States)

    Liu, Haokun; Yan, Quangen; Han, Dong; Jin, Junyan; Zhu, Xiaoming; Yang, Yunxia; Xie, Shouqi

    2016-09-01

    Cottonseed meal (CM) was used at up to 36.95% content in the diet (replacing 60% of dietary fish meal protein) without any negative eff ects on growth performance of pre-adult grass carp (initial body weight, 761 g) under outdoor conditions. A culture trial was conducted in net cages installed in a large concrete pond. Seven isonitrogenous and isoenergetic diets containing a gradient of CM concentrations (0, 12.2%, 24.4%, 36.6%, 48.8%, 54.8%, and 61.0%) as replacement for dietary fish meal protein (0, 20%, 40%, 60%, 80%, 90%, and 100%) were formulated. Dietary non-resistant starch (from maize) was inverse to dietary CM. Growth performance and feed utilization of fish fed the diets containing CM replacing 0-40% fishmeal protein were not aff ected after the 6-week feeding trial. Accumulation of hepatopancreatic total gossypol in the hepatopancreas was significantly correlated with free gossypol content in the diets (HTG=88.6+1.5×DFG, R 2=0.89, Preplacement). Increasing dietary CM content increased serum alanine aminotransferase levels but decreased serum alkaline phosphatase, cholesterol, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, triglycerides, and albumin ( P<0.05).

  5. Pure and Al-doped ZnO obtained by the modified Pechini method applied in ethanolic transesterification of cottonseed oil

    Energy Technology Data Exchange (ETDEWEB)

    Pereira, M.F.; Silva-Neta, A.R.; Farias, A.F.F.; Souza, A.G.; Fonseca, M.G.; Pontes, L.F.B.L.; Santos, I.M.G., E-mail: ieda.garcia@pq.cnpq.br [Universidade Federal da Paraiba (LACOM/UFPB), Joao Pessoa, PB (Brazil). Dept. de Quimica

    2017-01-15

    Pure zinc oxide (ZnO) and 5% Al-doped ZnO (ZNAL) were synthesized using the modified Pechini method and characterized by X-ray diffraction (XRD), X-ray fluorescence (XRF), Raman spectroscopy, infrared spectroscopy and UV-visible spectroscopy. XRF confirmed the theoretical stoichiometry, while XRD and Raman spectroscopy indicated that Al{sup 3+} was incorporated into the ZnO wurtzite lattice with no secondary phases, leading to a decrease in the band gap value and to a meaningful increase of the Lewis basic sites. Pure and doped ZnO were used as catalysts in the ethylic transesterification of cottonseed oil using a factorial design to determine the best synthesis conditions. Oil conversion into biodiesel was evaluated by viscosity measurements and {sup 1}H NMR spectroscopy. The results analyzed by factorial design indicated that the catalyst type and temperature were the determinant factors in the conversion indices. The highest basicity of the ZNAL lead to a significant increase of the catalytic potential, reaching a reduction of the oil viscosity next to 71% at 130 °C and greater than 85% at 200 °C. (author)

  6. 'Grounded' Politics

    DEFF Research Database (Denmark)

    Schmidt, Garbi

    2012-01-01

    play within one particular neighbourhood: Nørrebro in the Danish capital, Copenhagen. The article introduces the concept of grounded politics to analyse how groups of Muslim immigrants in Nørrebro use the space, relationships and history of the neighbourhood for identity political statements....... The article further describes how national political debates over the Muslim presence in Denmark affect identity political manifestations within Nørrebro. By using Duncan Bell’s concept of mythscape (Bell, 2003), the article shows how some political actors idealize Nørrebro’s past to contest the present...... ethnic and religious diversity of the neighbourhood and, further, to frame what they see as the deterioration of genuine Danish identity....

  7. Deriving albedo maps for HAPEX-Sahel from ASAS data using kernel-driven BRDF models

    Directory of Open Access Journals (Sweden)

    P. Lewis

    1999-01-01

    Full Text Available This paper describes the application and testing of a method for deriving spatial estimates of albedo from multi-angle remote sensing data. Linear kernel-driven models of surface bi-directional reflectance have been inverted against high spatial resolution multi-angular, multi- spectral airborne data of the principal cover types within the HAPEX-Sahel study site in Niger, West Africa. The airborne data are obtained from the NASA Airborne Solid-state Imaging Spectrometer (ASAS instrument, flown in Niger in September and October 1992. The maps of model parameters produced are used to estimate integrated reflectance properties related to spectral albedo. Broadband albedo has been estimated from this by weighting the spectral albedo for each pixel within the map as a function of the appropriate spectral solar irradiance and proportion of direct and diffuse illumination. Partial validation of the results was performed by comparing ASAS reflectance and derived directional-hemispherical reflectance with simulations of a millet canopy made with a complex geometric canopy reflectance model, the Botanical Plant Modelling System (BPMS. Both were found to agree well in magnitude. Broadband albedo values derived from the ASAS data were compared with ground-based (point sample albedo measurements and found to agree extremely well. These results indicate that the linear kernel-driven modelling approach, which is to be used operationally to produce global 16 day, 1 km albedo maps from forthcoming NASA Earth Observing System spaceborne data, is both sound and practical for the estimation of angle-integrated spectral reflectance quantities related to albedo. Results for broadband albedo are dependent on spectral sampling and on obtaining the correct spectral weigthings.

  8. Analysis of Drude model using fractional derivatives without singular kernels

    Directory of Open Access Journals (Sweden)

    Jiménez Leonardo Martínez

    2017-11-01

    Full Text Available We report study exploring the fractional Drude model in the time domain, using fractional derivatives without singular kernels, Caputo-Fabrizio (CF, and fractional derivatives with a stretched Mittag-Leffler function. It is shown that the velocity and current density of electrons moving through a metal depend on both the time and the fractional order 0 < γ ≤ 1. Due to non-singular fractional kernels, it is possible to consider complete memory effects in the model, which appear neither in the ordinary model, nor in the fractional Drude model with Caputo fractional derivative. A comparison is also made between these two representations of the fractional derivatives, resulting a considered difference when γ < 0.8.

  9. Development of Cold Neutron Scattering Kernels for Advanced Moderators

    International Nuclear Information System (INIS)

    Granada, J. R.; Cantargi, F.

    2010-01-01

    The development of scattering kernels for a number of molecular systems was performed, including a set of hydrogeneous methylated aromatics such as toluene, mesitylene, and mixtures of those. In order to partially validate those new libraries, we compared predicted total cross sections with experimental data obtained in our laboratory. In addition, we have introduced a new model to describe the interaction of slow neutrons with solid methane in phase II (stable phase below T = 20.4 K, atmospheric pressure). Very recently, a new scattering kernel to describe the interaction of slow neutrons with solid Deuterium was also developed. The main dynamical characteristics of that system are contained in the formalism, the elastic processes involving coherent and incoherent contributions are fully described, as well as the spin-correlation effects.

  10. Integral equations with difference kernels on finite intervals

    CERN Document Server

    Sakhnovich, Lev A

    2015-01-01

    This book focuses on solving integral equations with difference kernels on finite intervals. The corresponding problem on the semiaxis was previously solved by N. Wiener–E. Hopf and by M.G. Krein. The problem on finite intervals, though significantly more difficult, may be solved using our method of operator identities. This method is also actively employed in inverse spectral problems, operator factorization and nonlinear integral equations. Applications of the obtained results to optimal synthesis, light scattering, diffraction, and hydrodynamics problems are discussed in this book, which also describes how the theory of operators with difference kernels is applied to stable processes and used to solve the famous M. Kac problems on stable processes. In this second edition these results are extensively generalized and include the case of all Levy processes. We present the convolution expression for the well-known Ito formula of the generator operator, a convolution expression that has proven to be fruitful...

  11. Fault Localization for Synchrophasor Data using Kernel Principal Component Analysis

    Directory of Open Access Journals (Sweden)

    CHEN, R.

    2017-11-01

    Full Text Available In this paper, based on Kernel Principal Component Analysis (KPCA of Phasor Measurement Units (PMU data, a nonlinear method is proposed for fault location in complex power systems. Resorting to the scaling factor, the derivative for a polynomial kernel is obtained. Then, the contribution of each variable to the T2 statistic is derived to determine whether a bus is the fault component. Compared to the previous Principal Component Analysis (PCA based methods, the novel version can combat the characteristic of strong nonlinearity, and provide the precise identification of fault location. Computer simulations are conducted to demonstrate the improved performance in recognizing the fault component and evaluating its propagation across the system based on the proposed method.

  12. Analysis of Linux kernel as a complex network

    International Nuclear Information System (INIS)

    Gao, Yichao; Zheng, Zheng; Qin, Fangyun

    2014-01-01

    Operating system (OS) acts as an intermediary between software and hardware in computer-based systems. In this paper, we analyze the core of the typical Linux OS, Linux kernel, as a complex network to investigate its underlying design principles. It is found that the Linux Kernel Network (LKN) is a directed network and its out-degree follows an exponential distribution while the in-degree follows a power-law distribution. The correlation between topology and functions is also explored, by which we find that LKN is a highly modularized network with 12 key communities. Moreover, we investigate the robustness of LKN under random failures and intentional attacks. The result shows that the failure of the large in-degree nodes providing basic services will do more damage on the whole system. Our work may shed some light on the design of complex software systems

  13. Soft Sensing of Key State Variables in Fermentation Process Based on Relevance Vector Machine with Hybrid Kernel Function

    Directory of Open Access Journals (Sweden)

    Xianglin ZHU

    2014-06-01

    Full Text Available To resolve the online detection difficulty of some important state variables in fermentation process with traditional instruments, a soft sensing modeling method based on relevance vector machine (RVM with a hybrid kernel function is presented. Based on the characteristic analysis of two commonly-used kernel functions, that is, local Gaussian kernel function and global polynomial kernel function, a hybrid kernel function combing merits of Gaussian kernel function and polynomial kernel function is constructed. To design optimal parameters of this kernel function, the particle swarm optimization (PSO algorithm is applied. The proposed modeling method is used to predict the value of cell concentration in the Lysine fermentation process. Simulation results show that the presented hybrid-kernel RVM model has a better accuracy and performance than the single kernel RVM model.

  14. Some physical and mechanical properties of palm kernel shell (PKS ...

    African Journals Online (AJOL)

    In this study, some of the mechanical and physical properties of palm kernel shells (PKS) were evaluated. These are moisture content, 7.8325 ± 0.6672%; true density, 1.254 ± 5.292 x 10-3 g/cm3; bulk density, 1.1248g/cm3; mean rupture force along width, and thickness were 3174.52 ± 270.70N and 2806.94 ± 498.45N for ...

  15. Near infrared face recognition using Zernike moments and Hermite kernels

    Czech Academy of Sciences Publication Activity Database

    Farokhi, Sajad; Sheikh, U.U.; Flusser, Jan; Yang, Bo

    2015-01-01

    Roč. 316, č. 1 (2015), s. 234-245 ISSN 0020-0255 R&D Projects: GA ČR(CZ) GA13-29225S Keywords : face recognition * Zernike moments * Hermite kernel * Decision fusion * Near infrared Subject RIV: JD - Computer Applications, Robotics Impact factor: 3.364, year: 2015 http://library.utia.cas.cz/separaty/2015/ZOI/flusser-0444205.pdf

  16. Contextual Weisfeiler-Lehman Graph Kernel For Malware Detection

    OpenAIRE

    Narayanan, Annamalai; Meng, Guozhu; Yang, Liu; Liu, Jinliang; Chen, Lihui

    2016-01-01

    In this paper, we propose a novel graph kernel specifically to address a challenging problem in the field of cyber-security, namely, malware detection. Previous research has revealed the following: (1) Graph representations of programs are ideally suited for malware detection as they are robust against several attacks, (2) Besides capturing topological neighbourhoods (i.e., structural information) from these graphs it is important to capture the context under which the neighbourhoods are reac...

  17. Microscopic description of the collisions between nuclei. [Generator coordinate kernels

    Energy Technology Data Exchange (ETDEWEB)

    Canto, L F; Brink, D M [Oxford Univ. (UK). Dept. of Theoretical Physics

    1977-03-21

    The equivalence of the generator coordinate method and the resonating group method is used in the derivation of two new methods to describe the scattering of spin-zero fragments. Both these methods use generator coordinate kernels, but avoid the problem of calculating the generator coordinate weight function in the asymptotic region. The scattering of two ..cap alpha..-particles is studied as an illustration.

  18. Benchmarking NWP Kernels on Multi- and Many-core Processors

    Science.gov (United States)

    Michalakes, J.; Vachharajani, M.

    2008-12-01

    Increased computing power for weather, climate, and atmospheric science has provided direct benefits for defense, agriculture, the economy, the environment, and public welfare and convenience. Today, very large clusters with many thousands of processors are allowing scientists to move forward with simulations of unprecedented size. But time-critical applications such as real-time forecasting or climate prediction need strong scaling: faster nodes and processors, not more of them. Moreover, the need for good cost- performance has never been greater, both in terms of performance per watt and per dollar. For these reasons, the new generations of multi- and many-core processors being mass produced for commercial IT and "graphical computing" (video games) are being scrutinized for their ability to exploit the abundant fine- grain parallelism in atmospheric models. We present results of our work to date identifying key computational kernels within the dynamics and physics of a large community NWP model, the Weather Research and Forecast (WRF) model. We benchmark and optimize these kernels on several different multi- and many-core processors. The goals are to (1) characterize and model performance of the kernels in terms of computational intensity, data parallelism, memory bandwidth pressure, memory footprint, etc. (2) enumerate and classify effective strategies for coding and optimizing for these new processors, (3) assess difficulties and opportunities for tool or higher-level language support, and (4) establish a continuing set of kernel benchmarks that can be used to measure and compare effectiveness of current and future designs of multi- and many-core processors for weather and climate applications.

  19. Engineering a static verification tool for GPU kernels

    OpenAIRE

    Bardsley, E; Betts, A; Chong, N; Collingbourne, P; Deligiannis, P; Donaldson, AF; Ketema, J; Liew, D; Qadeer, S

    2014-01-01

    We report on practical experiences over the last 2.5 years related to the engineering of GPUVerify, a static verification tool for OpenCL and CUDA GPU kernels, plotting the progress of GPUVerify from a prototype to a fully functional and relatively efficient analysis tool. Our hope is that this experience report will serve the verification community by helping to inform future tooling efforts. ? 2014 Springer International Publishing.

  20. Adaptive Learning in Cartesian Product of Reproducing Kernel Hilbert Spaces

    OpenAIRE

    Yukawa, Masahiro

    2014-01-01

    We propose a novel adaptive learning algorithm based on iterative orthogonal projections in the Cartesian product of multiple reproducing kernel Hilbert spaces (RKHSs). The task is estimating/tracking nonlinear functions which are supposed to contain multiple components such as (i) linear and nonlinear components, (ii) high- and low- frequency components etc. In this case, the use of multiple RKHSs permits a compact representation of multicomponent functions. The proposed algorithm is where t...

  1. Wilson and Domainwall Kernels on Oakforest-PACS

    Science.gov (United States)

    Kanamori, Issaku; Matsufuru, Hideo

    2018-03-01

    We report the performance of Wilson and Domainwall Kernels on a new Intel Xeon Phi Knights Landing based machine named Oakforest-PACS, which is co-hosted by University of Tokyo and Tsukuba University and is currently fastest in Japan. This machine uses Intel Omni-Path for the internode network. We compare performance with several types of implementation including that makes use of the Grid library. The code is incorporated with the code set Bridge++.

  2. Learning with Generalization Capability by Kernel Methods of Bounded Complexity

    Czech Academy of Sciences Publication Activity Database

    Kůrková, Věra; Sanguineti, M.

    2005-01-01

    Roč. 21, č. 3 (2005), s. 350-367 ISSN 0885-064X R&D Projects: GA AV ČR 1ET100300419 Institutional research plan: CEZ:AV0Z10300504 Keywords : supervised learning * generalization * model complexity * kernel methods * minimization of regularized empirical errors * upper bounds on rates of approximate optimization Subject RIV: BA - General Mathematics Impact factor: 1.186, year: 2005

  3. The heat kernel as the pagerank of a graph

    Science.gov (United States)

    Chung, Fan

    2007-01-01

    The concept of pagerank was first started as a way for determining the ranking of Web pages by Web search engines. Based on relations in interconnected networks, pagerank has become a major tool for addressing fundamental problems arising in general graphs, especially for large information networks with hundreds of thousands of nodes. A notable notion of pagerank, introduced by Brin and Page and denoted by PageRank, is based on random walks as a geometric sum. In this paper, we consider a notion of pagerank that is based on the (discrete) heat kernel and can be expressed as an exponential sum of random walks. The heat kernel satisfies the heat equation and can be used to analyze many useful properties of random walks in a graph. A local Cheeger inequality is established, which implies that, by focusing on cuts determined by linear orderings of vertices using the heat kernel pageranks, the resulting partition is within a quadratic factor of the optimum. This is true, even if we restrict the volume of the small part separated by the cut to be close to some specified target value. This leads to a graph partitioning algorithm for which the running time is proportional to the size of the targeted volume (instead of the size of the whole graph).

  4. Optimal Bandwidth Selection for Kernel Density Functionals Estimation

    Directory of Open Access Journals (Sweden)

    Su Chen

    2015-01-01

    Full Text Available The choice of bandwidth is crucial to the kernel density estimation (KDE and kernel based regression. Various bandwidth selection methods for KDE and local least square regression have been developed in the past decade. It has been known that scale and location parameters are proportional to density functionals ∫γ(xf2(xdx with appropriate choice of γ(x and furthermore equality of scale and location tests can be transformed to comparisons of the density functionals among populations. ∫γ(xf2(xdx can be estimated nonparametrically via kernel density functionals estimation (KDFE. However, the optimal bandwidth selection for KDFE of ∫γ(xf2(xdx has not been examined. We propose a method to select the optimal bandwidth for the KDFE. The idea underlying this method is to search for the optimal bandwidth by minimizing the mean square error (MSE of the KDFE. Two main practical bandwidth selection techniques for the KDFE of ∫γ(xf2(xdx are provided: Normal scale bandwidth selection (namely, “Rule of Thumb” and direct plug-in bandwidth selection. Simulation studies display that our proposed bandwidth selection methods are superior to existing density estimation bandwidth selection methods in estimating density functionals.

  5. Optimizing memory-bound SYMV kernel on GPU hardware accelerators

    KAUST Repository

    Abdelfattah, Ahmad

    2013-01-01

    Hardware accelerators are becoming ubiquitous high performance scientific computing. They are capable of delivering an unprecedented level of concurrent execution contexts. High-level programming language extensions (e.g., CUDA), profiling tools (e.g., PAPI-CUDA, CUDA Profiler) are paramount to improve productivity, while effectively exploiting the underlying hardware. We present an optimized numerical kernel for computing the symmetric matrix-vector product on nVidia Fermi GPUs. Due to its inherent memory-bound nature, this kernel is very critical in the tridiagonalization of a symmetric dense matrix, which is a preprocessing step to calculate the eigenpairs. Using a novel design to address the irregular memory accesses by hiding latency and increasing bandwidth, our preliminary asymptotic results show 3.5x and 2.5x fold speedups over the similar CUBLAS 4.0 kernel, and 7-8% and 30% fold improvement over the Matrix Algebra on GPU and Multicore Architectures (MAGMA) library in single and double precision arithmetics, respectively. © 2013 Springer-Verlag.

  6. Aveiro method in reproducing kernel Hilbert spaces under complete dictionary

    Science.gov (United States)

    Mai, Weixiong; Qian, Tao

    2017-12-01

    Aveiro Method is a sparse representation method in reproducing kernel Hilbert spaces (RKHS) that gives orthogonal projections in linear combinations of reproducing kernels over uniqueness sets. It, however, suffers from determination of uniqueness sets in the underlying RKHS. In fact, in general spaces, uniqueness sets are not easy to be identified, let alone the convergence speed aspect with Aveiro Method. To avoid those difficulties we propose an anew Aveiro Method based on a dictionary and the matching pursuit idea. What we do, in fact, are more: The new Aveiro method will be in relation to the recently proposed, the so called Pre-Orthogonal Greedy Algorithm (P-OGA) involving completion of a given dictionary. The new method is called Aveiro Method Under Complete Dictionary (AMUCD). The complete dictionary consists of all directional derivatives of the underlying reproducing kernels. We show that, under the boundary vanishing condition, bring available for the classical Hardy and Paley-Wiener spaces, the complete dictionary enables an efficient expansion of any given element in the Hilbert space. The proposed method reveals new and advanced aspects in both the Aveiro Method and the greedy algorithm.

  7. Analyzing kernel matrices for the identification of differentially expressed genes.

    Directory of Open Access Journals (Sweden)

    Xiao-Lei Xia

    Full Text Available One of the most important applications of microarray data is the class prediction of biological samples. For this purpose, statistical tests have often been applied to identify the differentially expressed genes (DEGs, followed by the employment of the state-of-the-art learning machines including the Support Vector Machines (SVM in particular. The SVM is a typical sample-based classifier whose performance comes down to how discriminant samples are. However, DEGs identified by statistical tests are not guaranteed to result in a training dataset composed of discriminant samples. To tackle this problem, a novel gene ranking method namely the Kernel Matrix Gene Selection (KMGS is proposed. The rationale of the method, which roots in the fundamental ideas of the SVM algorithm, is described. The notion of ''the separability of a sample'' which is estimated by performing [Formula: see text]-like statistics on each column of the kernel matrix, is first introduced. The separability of a classification problem is then measured, from which the significance of a specific gene is deduced. Also described is a method of Kernel Matrix Sequential Forward Selection (KMSFS which shares the KMGS method's essential ideas but proceeds in a greedy manner. On three public microarray datasets, our proposed algorithms achieved noticeably competitive performance in terms of the B.632+ error rate.

  8. A kernel plus method for quantifying wind turbine performance upgrades

    KAUST Repository

    Lee, Giwhyun

    2014-04-21

    Power curves are commonly estimated using the binning method recommended by the International Electrotechnical Commission, which primarily incorporates wind speed information. When such power curves are used to quantify a turbine\\'s upgrade, the results may not be accurate because many other environmental factors in addition to wind speed, such as temperature, air pressure, turbulence intensity, wind shear and humidity, all potentially affect the turbine\\'s power output. Wind industry practitioners are aware of the need to filter out effects from environmental conditions. Toward that objective, we developed a kernel plus method that allows incorporation of multivariate environmental factors in a power curve model, thereby controlling the effects from environmental factors while comparing power outputs. We demonstrate that the kernel plus method can serve as a useful tool for quantifying a turbine\\'s upgrade because it is sensitive to small and moderate changes caused by certain turbine upgrades. Although we demonstrate the utility of the kernel plus method in this specific application, the resulting method is a general, multivariate model that can connect other physical factors, as long as their measurements are available, with a turbine\\'s power output, which may allow us to explore new physical properties associated with wind turbine performance. © 2014 John Wiley & Sons, Ltd.

  9. KNBD: A Remote Kernel Block Server for Linux

    Science.gov (United States)

    Becker, Jeff

    1999-01-01

    I am developing a prototype of a Linux remote disk block server whose purpose is to serve as a lower level component of a parallel file system. Parallel file systems are an important component of high performance supercomputers and clusters. Although supercomputer vendors such as SGI and IBM have their own custom solutions, there has been a void and hence a demand for such a system on Beowulf-type PC Clusters. Recently, the Parallel Virtual File System (PVFS) project at Clemson University has begun to address this need (1). Although their system provides much of the functionality of (and indeed was inspired by) the equivalent file systems in the commercial supercomputer market, their system is all in user-space. Migrating their 10 services to the kernel could provide a performance boost, by obviating the need for expensive system calls. Thanks to Pavel Machek, the Linux kernel has provided the network block device (2) with kernels 2.1.101 and later. You can configure this block device to redirect reads and writes to a remote machine's disk. This can be used as a building block for constructing a striped file system across several nodes.

  10. The depression of a graph and k-kernels

    Directory of Open Access Journals (Sweden)

    Schurch Mark

    2014-05-01

    Full Text Available An edge ordering of a graph G is an injection f : E(G → R, the set of real numbers. A path in G for which the edge ordering f increases along its edge sequence is called an f-ascent ; an f-ascent is maximal if it is not contained in a longer f-ascent. The depression of G is the smallest integer k such that any edge ordering f has a maximal f-ascent of length at most k. A k-kernel of a graph G is a set of vertices U ⊆ V (G such that for any edge ordering f of G there exists a maximal f-ascent of length at most k which neither starts nor ends in U. Identifying a k-kernel of a graph G enables one to construct an infinite family of graphs from G which have depression at most k. We discuss various results related to the concept of k-kernels, including an improved upper bound for the depression of trees.

  11. Multiple Kernel Learning for adaptive graph regularized nonnegative matrix factorization

    KAUST Repository

    Wang, Jim Jing-Yan; AbdulJabbar, Mustafa Abdulmajeed

    2012-01-01

    Nonnegative Matrix Factorization (NMF) has been continuously evolving in several areas like pattern recognition and information retrieval methods. It factorizes a matrix into a product of 2 low-rank non-negative matrices that will define parts-based, and linear representation of non-negative data. Recently, Graph regularized NMF (GrNMF) is proposed to find a compact representation, which uncovers the hidden semantics and simultaneously respects the intrinsic geometric structure. In GNMF, an affinity graph is constructed from the original data space to encode the geometrical information. In this paper, we propose a novel idea which engages a Multiple Kernel Learning approach into refining the graph structure that reflects the factorization of the matrix and the new data space. The GrNMF is improved by utilizing the graph refined by the kernel learning, and then a novel kernel learning method is introduced under the GrNMF framework. Our approach shows encouraging results of the proposed algorithm in comparison to the state-of-the-art clustering algorithms like NMF, GrNMF, SVD etc.

  12. Fast metabolite identification with Input Output Kernel Regression

    Science.gov (United States)

    Brouard, Céline; Shen, Huibin; Dührkop, Kai; d'Alché-Buc, Florence; Böcker, Sebastian; Rousu, Juho

    2016-01-01

    Motivation: An important problematic of metabolomics is to identify metabolites using tandem mass spectrometry data. Machine learning methods have been proposed recently to solve this problem by predicting molecular fingerprint vectors and matching these fingerprints against existing molecular structure databases. In this work we propose to address the metabolite identification problem using a structured output prediction approach. This type of approach is not limited to vector output space and can handle structured output space such as the molecule space. Results: We use the Input Output Kernel Regression method to learn the mapping between tandem mass spectra and molecular structures. The principle of this method is to encode the similarities in the input (spectra) space and the similarities in the output (molecule) space using two kernel functions. This method approximates the spectra-molecule mapping in two phases. The first phase corresponds to a regression problem from the input space to the feature space associated to the output kernel. The second phase is a preimage problem, consisting in mapping back the predicted output feature vectors to the molecule space. We show that our approach achieves state-of-the-art accuracy in metabolite identification. Moreover, our method has the advantage of decreasing the running times for the training step and the test step by several orders of magnitude over the preceding methods. Availability and implementation: Contact: celine.brouard@aalto.fi Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27307628

  13. Mode of inheritance and combining abilities for kernel row number, kernel number per row and grain yield in maize (Zea mays L.)

    NARCIS (Netherlands)

    Bocanski, J.; Sreckov, Z.; Nastasic, A.; Ivanovic, M.; Djalovic, I.; Vukosavljev, M.

    2010-01-01

    Bocanski J., Z. Sreckov, A. Nastasic, M. Ivanovic, I.Djalovic and M. Vukosavljev (2010): Mode of inheritance and combining abilities for kernel row number, kernel number per row and grain yield in maize (Zea mays L.) - Genetika, Vol 42, No. 1, 169- 176. Utilization of heterosis requires the study of

  14. Influence of Kernel Age on Fumonisin B1 Production in Maize by Fusarium moniliforme

    Science.gov (United States)

    Warfield, Colleen Y.; Gilchrist, David G.

    1999-01-01

    Production of fumonisins by Fusarium moniliforme on naturally infected maize ears is an important food safety concern due to the toxic nature of this class of mycotoxins. Assessing the potential risk of fumonisin production in developing maize ears prior to harvest requires an understanding of the regulation of toxin biosynthesis during kernel maturation. We investigated the developmental-stage-dependent relationship between maize kernels and fumonisin B1 production by using kernels collected at the blister (R2), milk (R3), dough (R4), and dent (R5) stages following inoculation in culture at their respective field moisture contents with F. moniliforme. Highly significant differences (P ≤ 0.001) in fumonisin B1 production were found among kernels at the different developmental stages. The highest levels of fumonisin B1 were produced on the dent stage kernels, and the lowest levels were produced on the blister stage kernels. The differences in fumonisin B1 production among kernels at the different developmental stages remained significant (P ≤ 0.001) when the moisture contents of the kernels were adjusted to the same level prior to inoculation. We concluded that toxin production is affected by substrate composition as well as by moisture content. Our study also demonstrated that fumonisin B1 biosynthesis on maize kernels is influenced by factors which vary with the developmental age of the tissue. The risk of fumonisin contamination may begin early in maize ear development and increases as the kernels reach physiological maturity. PMID:10388675

  15. Combined multi-kernel head computed tomography images optimized for depicting both brain parenchyma and bone.

    Science.gov (United States)

    Takagi, Satoshi; Nagase, Hiroyuki; Hayashi, Tatsuya; Kita, Tamotsu; Hayashi, Katsumi; Sanada, Shigeru; Koike, Masayuki

    2014-01-01

    The hybrid convolution kernel technique for computed tomography (CT) is known to enable the depiction of an image set using different window settings. Our purpose was to decrease the number of artifacts in the hybrid convolution kernel technique for head CT and to determine whether our improved combined multi-kernel head CT images enabled diagnosis as a substitute for both brain (low-pass kernel-reconstructed) and bone (high-pass kernel-reconstructed) images. Forty-four patients with nondisplaced skull fractures were included. Our improved multi-kernel images were generated so that pixels of >100 Hounsfield unit in both brain and bone images were composed of CT values of bone images and other pixels were composed of CT values of brain images. Three radiologists compared the improved multi-kernel images with bone images. The improved multi-kernel images and brain images were identically displayed on the brain window settings. All three radiologists agreed that the improved multi-kernel images on the bone window settings were sufficient for diagnosing skull fractures in all patients. This improved multi-kernel technique has a simple algorithm and is practical for clinical use. Thus, simplified head CT examinations and fewer images that need to be stored can be expected.

  16. Multineuron spike train analysis with R-convolution linear combination kernel.

    Science.gov (United States)

    Tezuka, Taro

    2018-06-01

    A spike train kernel provides an effective way of decoding information represented by a spike train. Some spike train kernels have been extended to multineuron spike trains, which are simultaneously recorded spike trains obtained from multiple neurons. However, most of these multineuron extensions were carried out in a kernel-specific manner. In this paper, a general framework is proposed for extending any single-neuron spike train kernel to multineuron spike trains, based on the R-convolution kernel. Special subclasses of the proposed R-convolution linear combination kernel are explored. These subclasses have a smaller number of parameters and make optimization tractable when the size of data is limited. The proposed kernel was evaluated using Gaussian process regression for multineuron spike trains recorded from an animal brain. It was compared with the sum kernel and the population Spikernel, which are existing ways of decoding multineuron spike trains using kernels. The results showed that the proposed approach performs better than these kernels and also other commonly used neural decoding methods. Copyright © 2018 Elsevier Ltd. All rights reserved.

  17. Caroço de algodão em dietas à base de palma forrageira para vacas leiteiras: síntese de proteína microbiana Whole cottonseed in forage cactus based diets: synthesis of microbial protein

    Directory of Open Access Journals (Sweden)

    Airon Aparecido Silva de Melo

    2007-08-01

    Full Text Available Objetivou-se avaliar o efeito da inclusão de caroço de algodão em substituição parcial à silagem de sorgo e ao farelo de soja em dietas à base de palma forrageira sobre a produção de proteína microbiana, a eficiência de síntese de proteína microbiana e as concentrações de uréia na urina e de uréia e N-uréia no plasma e no leite de vacas holandesas em lactação. Foram utilizados cinco animais aos 50 dias de lactação, distribuídos em quadrado latino 5 × 5. Os tratamentos consistiram de cinco níveis (0,0; 6,25; 12,50; 18,75 e 25,00% de inclusão de caroço de algodão na MS da dieta. A inclusão de caroço de algodão na dieta não influenciou a síntese de nitrogênio ou proteína microbiana, cujos valores médios foram 295,08 e 1.844,27 g/dia, respectivamente. As eficiências de síntese de nitrogênio e proteína microbiana diminuíram linearmente, em proporções de 0,30 e 1,43 g para cada 1% de caroço de algodão na dieta, respectivamente. Os níveis de uréia na urina e de uréia e N-uréia no plasma e no leite não foram afetados pela inclusão de caroço de algodão na dieta. Portanto, em dietas à base de palma forrageira, a inclusão de caroço de algodão em níveis de até 25% da MS não interfere na síntese de proteína microbiana e nas concentrações de uréia.The objective of this trial was to investigate the effects of partial replacement of sorghum silage and soybean meal with whole cottonseed on microbial protein synthesis and efficiency and nitrogen metabolism in lactating Holstein cows receiving forage cactus based diets. Five animals were randomly assigned to a 5 × 5 Latin square design and were fed diets containing (% of DM: 0.0, 6.25, 12.50, 18.75, and 25.00% of whole cottonseed. Inclusion of whole cottonseed in the diet did not affect microbial nitrogen and microbial protein synthesis, which averaged 295.08 and 1844.27 g/day, respectively. Microbial protein synthesis and microbial nitrogen

  18. Differential evolution algorithm-based kernel parameter selection for Fukunaga-Koontz Transform subspaces construction

    Science.gov (United States)

    Binol, Hamidullah; Bal, Abdullah; Cukur, Huseyin

    2015-10-01

    The performance of the kernel based techniques depends on the selection of kernel parameters. That's why; suitable parameter selection is an important problem for many kernel based techniques. This article presents a novel technique to learn the kernel parameters in kernel Fukunaga-Koontz Transform based (KFKT) classifier. The proposed approach determines the appropriate values of kernel parameters through optimizing an objective function constructed based on discrimination ability of KFKT. For this purpose we have utilized differential evolution algorithm (DEA). The new technique overcomes some disadvantages such as high time consumption existing in the traditional cross-validation method, and it can be utilized in any type of data. The experiments for target detection applications on the hyperspectral images verify the effectiveness of the proposed method.

  19. Conservação de sementes de algodoeiro deslintadas por diferentes métodos Preservation of cottonseeds delinted by different methods

    Directory of Open Access Journals (Sweden)

    Francisco S. O. Rodrigues Filho

    1979-01-01

    Full Text Available Estudaram-se os efeitos de quatro métodos de deslintamento na germinação e longevidade de sementes de algodoeiro do cultivar IAC 13-1, tratadas e não tratadas com o fungicida PCNB 75% e armazenadas em condições não controladas de armazém na região de Campinas (SP, por um período total de 21 meses. As sementes deslintadas por gás clorídrico e tratadas com fungicida mantiveram germinação acima de 80% até aos 15 meses de armazenamento. Aos 21 meses, as sementes que apresentaram germinação acima de 60% foram aquelas deslintadas por gás clorídrico ou ácido sulfúrico e tratadas com fungicida. Tais sementes apresentaram germinação mais alta e se conservaram melhor do que aquelas deslintadas a fogo ou mecanicamente. Independente do método de deslintamento. o tratamento com fungicida foi benéfico à germinação das sementes.Effects of four delinting methods on the germination and longevity of cottonseeds of the cultivar IAC 13-1, treated and non-treated with the fungicide PCNB 75% were studied. The seeds were stored in uncontrolled conditions at Campinas, State of São Paulo for a period of 21 months. Seeds delinted by gas and treated with fungicide maintained germination rates higher than 80 %, up to 15 months storage. At the end of the storage period, the seeds that presented germination higher than 60% were those delinted by gas or acid and treated with fungicide. Seeds delinted by gas or acid presented higher germination percentages and stored longer than those delinted by mechanical means or by flame. Aside the delinting method, the fungicide treatment was beneficial to the germination of the seeds.

  20. Evaluation of energy digestibility and prediction of digestible and metabolizable energy from chemical composition of different cottonseed meal sources fed to growing pigs.

    Science.gov (United States)

    Li, J T; Li, D F; Zang, J J; Yang, W J; Zhang, W J; Zhang, L Y

    2012-10-01

    The present experiment was conducted to determine the digestible energy (DE), metabolizable energy (ME) content, and the apparent total tract digestibility (ATTD) of energy in growing pigs fed diets containing one of ten cottonseed meals (CSM) collected from different provinces of China and to develop in vitro prediction equations for DE and ME content from chemical composition of the CSM samples. Twelve growing barrows with an initial body weight of 35.2±1.7 kg were allotted to two 6×6 Latin square designs, with six barrows and six periods and six diets for each. A corn-dehulled soybean meal diet was used as the basal diet, and the other ten diets were formulated with corn, dehulled soybean meal and 19.20% CSM. The DE, ME and ATTD of gross energy among different CSM sources varied largely and ranged from 1,856 to 2,730 kcal/kg dry matter (DM), 1,778 to 2,534 kcal/kg DM, and 42.08 to 60.47%, respectively. Several chemical parameters were identified to predict the DE and ME values of CSM, and the accuracy of prediction models were also tested. The best fit equations were: DE, kcal/kg DM = 670.14+31.12 CP+659.15 EE with R(2) = 0.82, RSD = 172.02, penergy varied substantially among different CSM sources, and that some prediction equations can be applied to predict DE and ME in CSM with an acceptable accuracy.