WorldWideScience

Sample records for rice kernels recovered

  1. 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.

  2. 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

  3. 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 ...

  4. X-ray photoelectron spectroscopic analysis of rice kernels and flours: Measurement of surface chemical composition.

    Science.gov (United States)

    Nawaz, Malik A; Gaiani, Claire; Fukai, Shu; Bhandari, Bhesh

    2016-12-01

    The objectives of this study were to evaluate the ability of X-ray photoelectron spectroscopy (XPS) to differentiate rice macromolecules and to calculate the surface composition of rice kernels and flours. The uncooked kernels and flours surface composition of the two selected rice varieties, Thadokkham-11 (TDK11) and Doongara (DG) demonstrated an over-expression of lipids and proteins and an under-expression of starch compared to the bulk composition. The results of the study showed that XPS was able to differentiate rice polysaccharides (mainly starch), proteins and lipids in uncooked rice kernels and flours. Nevertheless, it was unable to distinguish components in cooked rice samples possibly due to complex interactions between gelatinized starch, denatured proteins and lipids. High resolution imaging methods (Scanning Electron Microscopy and Confocal Laser Scanning Microscopy) were employed to obtain complementary information about the properties and location of starch, proteins and lipids in rice kernels and flours. Copyright © 2016. Published by Elsevier Ltd.

  5. IDENTIFICATION AND MAPPING OF A GENE FOR RICE SLENDER KERNEL USING Oryza glumaepatula INTROGRESSION LINES

    Directory of Open Access Journals (Sweden)

    Sobrizal Sobrizal

    2016-10-01

    Full Text Available World demand for superior rice grain quality tends to increase. One of the  criteria of appearance quality of rice grain is grain shape. Rice consumers  exhibit wide preferences for grain shape, but most Indonesian rice consumers prefer long and slender grain. The objectives of this study were to identify and map a gene for rice slender kernel trait using Oryza  glumaepatula introgression lines with O. sativa cv. Taichung 65 genetic background. A segregation analysis of BC4F2 population derived from backcrosses of a donor parent O. glumaepatula into a recurrent parent Taichung 65 showed that the slender kernel was controlled by a single recessive gene. This new identified gene was designated as sk1 (slender kernel 1. Moreover, based on the RFLP analyses using 14 RFLP markers located on chromosomes 2, 8, 9, and 10 in which the O. glumaepatula chromosomal segments were retained in BC4F2 population, the sk1 was located between RFLP markers C679 and C560 on the long arm of chromosome 2, with map distances of 2.8 and 1.5 cM, respectively. The wild rice O. glumaepatula carried a recessive allele for slender kernel. This allele may be useful in breeding of rice with slender kernel types. In addition, the development of plant materials and RFLP map associated with slender kernel in this study is the preliminary works in the effort to isolate this important grain shape gene.

  6. Effect of Neem Seed Kernel Extracts in the Management of Rice ...

    African Journals Online (AJOL)

    user

    conducted to determine the comparative efficacy of neem seed kernel ... sustainable production of rice and are generally not affordable to African peasant farmers. ... system where the use of natural enemies are being emphasized as a major ...

  7. The Conserved and Unique Genetic Architecture of Kernel Size and Weight in Maize and Rice.

    Science.gov (United States)

    Liu, Jie; Huang, Juan; Guo, Huan; Lan, Liu; Wang, Hongze; Xu, Yuancheng; Yang, Xiaohong; Li, Wenqiang; Tong, Hao; Xiao, Yingjie; Pan, Qingchun; Qiao, Feng; Raihan, Mohammad Sharif; Liu, Haijun; Zhang, Xuehai; Yang, Ning; Wang, Xiaqing; Deng, Min; Jin, Minliang; Zhao, Lijun; Luo, Xin; Zhou, Yang; Li, Xiang; Zhan, Wei; Liu, Nannan; Wang, Hong; Chen, Gengshen; Li, Qing; Yan, Jianbing

    2017-10-01

    Maize ( Zea mays ) is a major staple crop. Maize kernel size and weight are important contributors to its yield. Here, we measured kernel length, kernel width, kernel thickness, hundred kernel weight, and kernel test weight in 10 recombinant inbred line populations and dissected their genetic architecture using three statistical models. In total, 729 quantitative trait loci (QTLs) were identified, many of which were identified in all three models, including 22 major QTLs that each can explain more than 10% of phenotypic variation. To provide candidate genes for these QTLs, we identified 30 maize genes that are orthologs of 18 rice ( Oryza sativa ) genes reported to affect rice seed size or weight. Interestingly, 24 of these 30 genes are located in the identified QTLs or within 1 Mb of the significant single-nucleotide polymorphisms. We further confirmed the effects of five genes on maize kernel size/weight in an independent association mapping panel with 540 lines by candidate gene association analysis. Lastly, the function of ZmINCW1 , a homolog of rice GRAIN INCOMPLETE FILLING1 that affects seed size and weight, was characterized in detail. ZmINCW1 is close to QTL peaks for kernel size/weight (less than 1 Mb) and contains significant single-nucleotide polymorphisms affecting kernel size/weight in the association panel. Overexpression of this gene can rescue the reduced weight of the Arabidopsis ( Arabidopsis thaliana ) homozygous mutant line in the AtcwINV2 gene (Arabidopsis ortholog of ZmINCW1 ). These results indicate that the molecular mechanisms affecting seed development are conserved in maize, rice, and possibly Arabidopsis. © 2017 American Society of Plant Biologists. All Rights Reserved.

  8. Production and characterization of biodiesel using palm kernel oil; fresh and recovered from spent bleaching earth

    Directory of Open Access Journals (Sweden)

    Abiodun Aladetuyi

    2014-12-01

    Full Text Available Palm kernel oil (PKO was recovered from spent bleaching earth with a yield of 16 %, using n-hexane while the fresh oil was extracted from palm kernel with n-hexane and a yield of 40.23% was obtained. These oils were trans-esterified with methanol under the same reaction conditions: 100 oC, 2 h reaction time, and oil-methanol ratio of 5:1 (w/v. The cocoa pod ash (CPA was compared with potassium hydroxide (KOH as catalyst. The percentage yields of biodiesel obtained from PKO catalysed by CPA and KOH were 94 and 90%, respectively. While the yields achieved using the recovered oil catalysed by CPA and KOH were measured at 86 and 81.20 %. The physico-chemical properties of the biodiesel produced showed that the flash point, viscosity, density, ash content, percentage carbon content, specific gravity and the acid value fell within American Society for Testing and Materials (ASTM specifications for biodiesel. The findings of this study suggest that agricultural residues such as CPA used in this study could be explored as alternatives for KOH catalyst for biodiesel production.

  9. Novel QTLs affecting rice kernel fissure resistance discovered in the cultivar ‘Saber’ augment those from ‘Cybonnet’

    Science.gov (United States)

    Kernel fissures in rice (Oryza sativa L.) caused by pre- or post-harvest stresses are the leading cause of breakage among milled rice. Such breakage causes economic losses for producers, millers, and marketers. Five QTLs for kernel fissure resistance (FR) were identified among a set of 275 RILs de...

  10. Bioconversions of Palm Kernel Cake and Rice Bran Mixtures by Trichoderma viride Toward Nutritional Contents

    OpenAIRE

    Yana Sukaryana; Umi Atmomarsono; Vitus D. Yunianto; Ejeng Supriyatna

    2010-01-01

    The objective of the research is to examine the mixtures of palm kernel cake and rice bran of fermented by Trichoderma viride. Completely randomized design in factorial pattern 4 x 4 was used in this experiment. factor I is the doses of inoculums; D1 = 0%, D2 =  0,1% , D3 =  0,2%, D4 =  0,3%, and  complement factor II is mixtures of palm kernel cake and rice bran : T1=20:80% ; T2=40:60% ; T3=60:40% ; T4=80:20%. The treatment each of three replicate. Fermentation was conduc...

  11. Bioconversions of Palm Kernel Cake and Rice Bran Mixtures by Trichoderma viride Toward Nutritional Contents

    Directory of Open Access Journals (Sweden)

    Yana Sukaryana

    2010-12-01

    Full Text Available The objective of the research is to examine the mixtures of palm kernel cake and rice bran of fermented by Trichoderma viride. Completely randomized design in factorial pattern 4 x 4 was used in this experiment. factor I is the doses of inoculums; D1 = 0%, D2 =  0,1% , D3 =  0,2%, D4 =  0,3%, and  complement factor II is mixtures of palm kernel cake and rice bran : T1=20:80% ; T2=40:60% ; T3=60:40% ; T4=80:20%. The treatment each of three replicate. Fermentation was conducted at temperature 28 oC as long as 9 days. Determining the best of the mixtures be based on the crude protein increased and the crude fibre decreased. The results showed that the combination of product mix is the best fermentation inoculums doses 0.3% in mixture of palm kernel cake and rice bran ; 80%: 20%, which produces dry matter of 88,12%, crude protein 17.34%, ether extract 5,35%, crude fibre 23.67%, and ash 6.43%. When compared with a mixture of palm kernel cake and rice bran; 80%: 20% without of fermentation is crude protein increase 29.58% and crude fibre decreased 22.53%.

  12. Classification of Broken Rice Kernels using 12D Features

    Directory of Open Access Journals (Sweden)

    SUNDER ALI KHOWAJA

    2016-07-01

    Full Text Available Integrating the technological aspect for assessment of rice quality is very much needed for the Asian markets where rice is one of the major exports. Methods based on image analysis has been proposed for automated quality assessment by taking into account some of the textural features. These features are good at classifying when rice grains are scanned in controlled environment but it is not suitable for practical implementation. Rice grains are placed randomly on the scanner which neither maintains the uniformity in intensity regions nor the placement strategy is kept ideal thus resulting in false classification of grains. The aim of this research is to propose a method for extracting set of features which can overcome the said issues. This paper uses morphological features along-with gray level and Hough transform based features to overcome the false classification in the existing methods. RBF (Radial Basis function is used as a classification mechanism to classify between complete grains and broken grains. Furthermore the broken grains are classified into two classes? i.e. acceptable grains and non-acceptable grains. This research also uses image enhancement technique prior to the feature extraction and classification process based on top-hat transformation. The proposed method has been simulated in MATLAB to visually analyze and validate the results.

  13. The effect of rice kernel microstructure on cooking behaviour: A combined µ-CT and MRI study

    NARCIS (Netherlands)

    Mohoric, A.; Vergeldt, F.J.; Gerkema, E.; Dalen, van G.; Doel, van den L.R.; Vliet, van L.J.; As, van H.; Duynhoven, van J.P.M.

    2009-01-01

    In order to establish the underlying structure-dependent principles of instant cooking rice, a detailed investigation was carried out on rice kernels that were processed in eight different manners. Milling, parboiling, wet-processing and extrusion were applied, with and without a subsequent puffing

  14. A Non-Local, Energy-Optimized Kernel: Recovering Second-Order Exchange and Beyond in Extended Systems

    Science.gov (United States)

    Bates, Jefferson; Laricchia, Savio; Ruzsinszky, Adrienn

    The Random Phase Approximation (RPA) is quickly becoming a standard method beyond semi-local Density Functional Theory that naturally incorporates weak interactions and eliminates self-interaction error. RPA is not perfect, however, and suffers from self-correlation error as well as an incorrect description of short-ranged correlation typically leading to underbinding. To improve upon RPA we introduce a short-ranged, exchange-like kernel that is one-electron self-correlation free for one and two electron systems in the high-density limit. By tuning the one free parameter in our model to recover an exact limit of the homogeneous electron gas correlation energy we obtain a non-local, energy-optimized kernel that reduces the errors of RPA for both homogeneous and inhomogeneous solids. To reduce the computational cost of the standard kernel-corrected RPA, we also implement RPA renormalized perturbation theory for extended systems, and demonstrate its capability to describe the dominant correlation effects with a low-order expansion in both metallic and non-metallic systems. Furthermore we stress that for norm-conserving implementations the accuracy of RPA and beyond RPA structural properties compared to experiment is inherently limited by the choice of pseudopotential. Current affiliation: King's College London.

  15. A Unified and Comprehensible View of Parametric and Kernel Methods for Genomic Prediction with Application to Rice.

    Science.gov (United States)

    Jacquin, Laval; Cao, Tuong-Vi; Ahmadi, Nourollah

    2016-01-01

    One objective of this study was to provide readers with a clear and unified understanding of parametric statistical and kernel methods, used for genomic prediction, and to compare some of these in the context of rice breeding for quantitative traits. Furthermore, another objective was to provide a simple and user-friendly R package, named KRMM, which allows users to perform RKHS regression with several kernels. After introducing the concept of regularized empirical risk minimization, the connections between well-known parametric and kernel methods such as Ridge regression [i.e., genomic best linear unbiased predictor (GBLUP)] and reproducing kernel Hilbert space (RKHS) regression were reviewed. Ridge regression was then reformulated so as to show and emphasize the advantage of the kernel "trick" concept, exploited by kernel methods in the context of epistatic genetic architectures, over parametric frameworks used by conventional methods. Some parametric and kernel methods; least absolute shrinkage and selection operator (LASSO), GBLUP, support vector machine regression (SVR) and RKHS regression were thereupon compared for their genomic predictive ability in the context of rice breeding using three real data sets. Among the compared methods, RKHS regression and SVR were often the most accurate methods for prediction followed by GBLUP and LASSO. An R function which allows users to perform RR-BLUP of marker effects, GBLUP and RKHS regression, with a Gaussian, Laplacian, polynomial or ANOVA kernel, in a reasonable computation time has been developed. Moreover, a modified version of this function, which allows users to tune kernels for RKHS regression, has also been developed and parallelized for HPC Linux clusters. The corresponding KRMM package and all scripts have been made publicly available.

  16. The production of corn kernel miso based on rice-koji fermented by Aspergillus oryzae and Rhizopus oligosporus

    Directory of Open Access Journals (Sweden)

    Diah Ratnaningrum

    2018-04-01

    Full Text Available The suitability of corn kernel as raw material to produce miso fermented by rice-koji containing Aspergillus oryzae and Rhizopus oligosporus has been investigated. The optimization was conducted on two important factors in miso production namely mold composition in rice-koji and salt concentration. The mold composition was prepared by inoculating the spores of 2% A. oryzae, 2% R. oligosporus, and 2% the mixture of both in a ratio of 1:1, 2:1, and 1:2 (v/v into different rice media. The mold composition was optimized to produce rice-koji with high α-amylase and protease activity. Different NaCl concentrations of 10%, 15%, and 20% were subjected to optimization process and added to each mixture after five days of fermentation. The salt concentration was also optimized to produce corn kernel miso with high glucose and high dissolved protein concentration. The result showed that rice-koji containing A. oryzae and R. oligosporus in the ratio of 1:1 had the highest α-amylase and protease activity of 0.42 U/mL and 0.45 U/mL respectively. In addition, the presence of 10% NaCl in corn kernel miso fermented by A. oryzae and R. oligosporus in the ratio of 1:1 exhibited the highest glucose and dissolved protein concentration of 0.64 mg/mL and 8.80 mg/mL respectively. The optimized corn kernel miso by A. oryzae and R. oligosporus in the ratio of 1:1 with 10% NaCl was subjected to nutrient content analysis and compared to the result before the corn kernel was fermented. The nutrient content analysis showed nutrient enhancement after corn kernel was fermented and transformed into a miso. Glucose, dissolved protein, and fat content increased 6.74, 1.34, 7.63 times respectively. This study concludes corn kernel could be utilized to produce a novel corn kernel miso for dietary diversification and for improving nutritional and health status.

  17. Fine mapping and introgressing qFIS1-2, a major QTL for kernel fissure resistance in rice (Oryza sativa L.)

    Science.gov (United States)

    Rice (Oryza sativa L.) kernel fissuring increases breakage during milling and decreases the value of processed rice. This study employed molecular gene tagging methods to fine-map a fissure resistance (FR) locus in ‘Cybonnet’, a semidwarf tropical japonica cultivar, as well as transfer this trait to...

  18. A unified and comprehensible view of parametric and kernel methods for genomic prediction with application to rice

    Directory of Open Access Journals (Sweden)

    Laval Jacquin

    2016-08-01

    Full Text Available One objective of this study was to provide readers with a clear and unified understanding ofparametric statistical and kernel methods, used for genomic prediction, and to compare some ofthese in the context of rice breeding for quantitative traits. Furthermore, another objective wasto provide a simple and user-friendly R package, named KRMM, which allows users to performRKHS regression with several kernels. After introducing the concept of regularized empiricalrisk minimization, the connections between well-known parametric and kernel methods suchas Ridge regression (i.e. genomic best linear unbiased predictor (GBLUP and reproducingkernel Hilbert space (RKHS regression were reviewed. Ridge regression was then reformulatedso as to show and emphasize the advantage of the kernel trick concept, exploited by kernelmethods in the context of epistatic genetic architectures, over parametric frameworks used byconventional methods. Some parametric and kernel methods; least absolute shrinkage andselection operator (LASSO, GBLUP, support vector machine regression (SVR and RKHSregression were thereupon compared for their genomic predictive ability in the context of ricebreeding using three real data sets. Among the compared methods, RKHS regression and SVRwere often the most accurate methods for prediction followed by GBLUP and LASSO. An Rfunction which allows users to perform RR-BLUP of marker effects, GBLUP and RKHS regression,with a Gaussian, Laplacian, polynomial or ANOVA kernel, in a reasonable computation time hasbeen developed. Moreover, a modified version of this function, which allows users to tune kernelsfor RKHS regression, has also been developed and parallelized for HPC Linux clusters. The corresponding KRMM package and all scripts have been made publicly available.

  19. The Influence of Palm Kernel Cake and Rice Bran Fermentation Product Mixture to the Broiler Carcass Quality

    OpenAIRE

    Priabudiman, Yadi; Sukaryana, Yana

    2011-01-01

    The purpose of this research was to study the effect of the use of palm kernel cake (PKC) and rice bran (RB) fermentation products mixture to the percentage of broiler carcass weight pieces. Research using completely randomized design (CRD) with treatments of the fermentation product usage rate of   0% (P0), 10% (P1), 20% (P2), 30%&nbs...

  20. Nutritional value of high fiber co-products from the copra, palm kernel, and rice industries in diets fed to pigs.

    Science.gov (United States)

    Stein, Hans Henrik; Casas, Gloria Amparo; Abelilla, Jerubella Jerusalem; Liu, Yanhong; Sulabo, Rommel Casilda

    2015-01-01

    High fiber co-products from the copra and palm kernel industries are by-products of the production of coconut oil and palm kernel oil. The co-products include copra meal, copra expellers, palm kernel meal, and palm kernel expellers. All 4 ingredients are very high in fiber and the energy value is relatively low when fed to pigs. The protein concentration is between 14 and 22 % and the protein has a low biological value and a very high Arg:Lys ratio. Digestibility of most amino acids is less than in soybean meal but close to that in corn. However, the digestibility of Lys is sometimes low due to Maillard reactions that are initiated due to overheating during drying. Copra and palm kernel ingredients contain 0.5 to 0.6 % P. Most of the P in palm kernel meal and palm kernel expellers is bound to phytate, but in copra products less than one third of the P is bound to phytate. The digestibility of P is, therefore, greater in copra meal and copra expellers than in palm kernel ingredients. Inclusion of copra meal should be less than 15 % in diets fed to weanling pigs and less than 25 % in diets for growing-finishing pigs. Palm kernel meal may be included by 15 % in diets for weanling pigs and 25 % in diets for growing and finishing pigs. Rice bran contains the pericarp and aleurone layers of brown rice that is removed before polished rice is produced. Rice bran contains approximately 25 % neutral detergent fiber and 25 to 30 % starch. Rice bran has a greater concentration of P than most other plant ingredients, but 75 to 90 % of the P is bound in phytate. Inclusion of microbial phytase in the diets is, therefore, necessary if rice bran is used. Rice bran may contain 15 to 24 % fat, but it may also have been defatted in which case the fat concentration is less than 5 %. Concentrations of digestible energy (DE) and metabolizable energy (ME) are slightly less in full fat rice bran than in corn, but defatted rice bran contains less than 75 % of the DE and ME in

  1. Effect of Neem Seed Kernel Extracts in the Management of Rice ...

    African Journals Online (AJOL)

    user

    Rice plant is an ideal host for a large number of insect pests in ... For farmers and researchers alike reducing the numbers of these pests is therefore a priority. In the ..... Development of a rational control system against insect ... Integration of some biopesticides and trichogramma chilonis for the sustainable management of.

  2. Distribution of Phenolic Compounds and Antioxidative Activities of Rice Kernel and Their Relationships with Agronomic Practice

    Science.gov (United States)

    Kesarwani, Amit; Chiang, Po-Yuan; Chen, Shih-Shiung

    2014-01-01

    The phenolic and antioxidant activity of ethanolic extract of two Japonica rice cultivars, Taikeng no. 16 (medium and slender grain) and Kaohsiung no. 139 (short and round grain), grown under organic and conventional farming were examined. Analyses shows that Kaohsiung no. 139 contains the highest amount of secondary metabolites and continuous farming can increase its production. Results also suggest that phenolic content under different agronomic practices, has not shown significant differences but organically grown rice has proven to be better in higher accumulation of other secondary metabolites (2,2-diphenyl-1-picrylhydrazyl (DPPH), flavonoid content, and ferrous chelating capacity). In nutshell, genetic traits and environment have significant effect on phenolic compounds and the least variation reported under agronomic practices. PMID:25506072

  3. Distribution of Phenolic Compounds and Antioxidative Activities of Rice Kernel and Their Relationships with Agronomic Practice

    Directory of Open Access Journals (Sweden)

    Amit Kesarwani

    2014-01-01

    Full Text Available The phenolic and antioxidant activity of ethanolic extract of two Japonica rice cultivars, Taikeng no. 16 (medium and slender grain and Kaohsiung no. 139 (short and round grain, grown under organic and conventional farming were examined. Analyses shows that Kaohsiung no. 139 contains the highest amount of secondary metabolites and continuous farming can increase its production. Results also suggest that phenolic content under different agronomic practices, has not shown significant differences but organically grown rice has proven to be better in higher accumulation of other secondary metabolites (2,2-diphenyl-1-picrylhydrazyl (DPPH, flavonoid content, and ferrous chelating capacity. In nutshell, genetic traits and environment have significant effect on phenolic compounds and the least variation reported under agronomic practices.

  4. The influence of Palm Kernel Cake and Rice Bran Fermentation Product Mixture to the Broiler Carcass Quality

    Directory of Open Access Journals (Sweden)

    Yadi Priabudiman

    2011-07-01

    Full Text Available The purpose of this research was to study the effect of the use of palm kernel cake (PKC and rice bran (RB fermentation products mixture to the percentage of broiler carcass weight pieces. Research using completely randomized design (CRD with treatments of the fermentation product usage rate of   0% (P0, 10% (P1, 20% (P2, 30% (P3 and 40% (P4 of the total ration of 4replications.  Variables measured were percentage of carcass weight ratio cut    pieces  of carcass weight (carcass front, rear carcass, breast meat, wings, back, and thigh with carcass weight multiplied by 100%. The results showed that the percentage of carcass weight piece front and rear carcass was shown at P3.

  5. HS-SPME-GC-MS/MS Method for the Rapid and Sensitive Quantitation of 2-Acetyl-1-pyrroline in Single Rice Kernels.

    Science.gov (United States)

    Hopfer, Helene; Jodari, Farman; Negre-Zakharov, Florence; Wylie, Phillip L; Ebeler, Susan E

    2016-05-25

    Demand for aromatic rice varieties (e.g., Basmati) is increasing in the US. Aromatic varieties typically have elevated levels of the aroma compound 2-acetyl-1-pyrroline (2AP). Due to its very low aroma threshold, analysis of 2AP provides a useful screening tool for rice breeders. Methods for 2AP analysis in rice should quantitate 2AP at or below sensory threshold level, avoid artifactual 2AP generation, and be able to analyze single rice kernels in cases where only small sample quantities are available (e.g., breeding trials). We combined headspace solid phase microextraction with gas chromatography tandem mass spectrometry (HS-SPME-GC-MS/MS) for analysis of 2AP, using an extraction temperature of 40 °C and a stable isotopologue as internal standard. 2AP calibrations were linear between the concentrations of 53 and 5380 pg/g, with detection limits below the sensory threshold of 2AP. Forty-eight aromatic and nonaromatic, milled rice samples from three harvest years were screened with the method for their 2AP content, and overall reproducibility, observed for all samples, ranged from 5% for experimental aromatic lines to 33% for nonaromatic lines.

  6. Obtaining unique large kernel rice using chemical mutagenesis in tissue culture

    International Nuclear Information System (INIS)

    Alyoshin, N.E.; Avakyan, E.R.; Alyoshin, E.P.

    2001-01-01

    Full text: Lines with improved characters have been received by chemical mutagenesis in rice tissue culture. The japonica rice (Oryza sativa L.) varieties 'Krasnodarskii 424', 'Dubovskii 129', 'Slavyanetz', 'Liman', 'Lomello', 'VNIIR 2471' were used for mutation induction. Nnitrozo-N-methylurea (MNH) has been used as a mutagen. Two approaches were applied: 1. Development mutants by mutagenic treatment of seeds 2. Development regenerants from somatic tissue culture. In the first case, dry seeds with removed covering glumes have been treated with a solution of NMH (exposure 24 hours, tested concentrations 0.05%; 0.1%; 0.2%). After treatment seeds have been rinsed and planted into the soil in vessels. The effect of mutagen was very much genotype dependant. The highest frequency of mutants were observed in the following concentrations of MNH: for variety VNIIR 2471 - 0.05-0.1%, for variety Slavyanetz - 0.1%; for Lomello - 0.2%; for Linman - 0.05% and 0.2%. The mutant N 95, which has been selected from variety Liman after treatment with 0.2% concentration of mutagen, had the following improved characters: vegetation period 103 days (110 days for the parent variety); plant height 93.2 cm (98.2 cm - parent variety); length of the main panicle 17.2 cm; 1000 grain mass 44.9 g (39.2 g - parent variety). Mutant line N 101 selected from the same variety Liman after treatment with 0.05% concentration of mutagen mutated also in many characters: vegetation period 103 days; plant height 106 cm; 1000 grain mass was 47.0 g. In the second experiment, a somatic callus of the 2nd passage from varieties Kransnodarskii 424, Dubovskii 129, Slavyanetz, Liman were treated with the solution of mutagen NMH (concentration: 0.05%; 0.1%; 0.2% + 0.1% PABA by 40 minutes at Certomat shaking machine (100 rev./min). The treated callus has been cultivated at MS regeneration media (4 mg 2.4 D + 20 mg /l of sucrose) and MS intermediate media (non-hormonal + PABA) to obtain regenerants. Plant

  7. Small kernel 1 encodes a pentatricopeptide repeat protein required for mitochondrial nad7 transcript editing and seed development in maize (Zea mays) and rice (Oryza sativa).

    Science.gov (United States)

    Li, Xiao-Jie; Zhang, Ya-Feng; Hou, Mingming; Sun, Feng; Shen, Yun; Xiu, Zhi-Hui; Wang, Xiaomin; Chen, Zong-Liang; Sun, Samuel S M; Small, Ian; Tan, Bao-Cai

    2014-09-01

    RNA editing modifies cytidines (C) to uridines (U) at specific sites in the transcripts of mitochondria and plastids, altering the amino acid specified by the DNA sequence. Here we report the identification of a critical editing factor of mitochondrial nad7 transcript via molecular characterization of a small kernel 1 (smk1) mutant in Zea mays (maize). Mutations in Smk1 arrest both the embryo and endosperm development. Cloning of Smk1 indicates that it encodes an E-subclass pentatricopeptide repeat (PPR) protein that is targeted to mitochondria. Loss of SMK1 function abolishes the C → U editing at the nad7-836 site, leading to the retention of a proline codon that is edited to encode leucine in the wild type. The smk1 mutant showed dramatically reduced complex-I assembly and NADH dehydrogenase activity, and abnormal biogenesis of the mitochondria. Analysis of the ortholog in Oryza sativa (rice) reveals that rice SMK1 has a conserved function in C → U editing of the mitochondrial nad7-836 site. T-DNA knock-out mutants showed abnormal embryo and endosperm development, resulting in embryo or seedling lethality. The leucine at NAD7-279 is highly conserved from bacteria to flowering plants, and analysis of genome sequences from many plants revealed a molecular coevolution between the requirement for C → U editing at this site and the existence of an SMK1 homolog. These results demonstrate that Smk1 encodes a PPR-E protein that is required for nad7-836 editing, and this editing is critical to NAD7 function in complex-I assembly in mitochondria, and hence to embryo and endosperm development in maize and rice. © 2014 The Authors The Plant Journal © 2014 John Wiley & Sons Ltd.

  8. Physical, chemical and microbiological properties of mixed hydrogenated palm kernel oil and cold-pressed rice bran oil as ingredients in non-dairy creamer

    Directory of Open Access Journals (Sweden)

    Kunakorn Katsri

    2014-02-01

    Full Text Available The physical, chemical and microbiological properties of hydrogenated palm kernel oil (PKO and cold-pressed rice bran oil (RBOas ingredients in the production of liquid and powdered non-dairy creamer (coffee whitener were studied. The mixing ratios between hydrogenated PKO and cold-pressed RBO were statistically designed as of 100:0, 90:10,80:20, 70:30, 60:40, 50:50, 40:60, 30:70, 20:80, 10:90 and 0:100.The color, absorbanceand viscosity of the mixtures were investigated. As the ratio of cold-pressed RBO increased, the color became darker (L*of 93.06 to 86.25 and the absorbance significantly increased, while the viscosity of the mixtures of 20:80, 10:90 and 0:100 (54 cp. were the highest amongst the ratios tested.The hydrogenated PKO and cold-pressed RBO mixtures were further chemically tested for fatty acids, -oryzanol, -tocopherol, trans-fat contents andantioxidant activity. There were 10 fatty acids present in hydrogenated PKO with saturated fatty acid being the most predominant. Comparatively, there were only 5 fatty acids found in cold-pressed RBO with monounsaturated fatty acid being the major fatty acid. -Oryzanol and -tocopherol contents were higher with increasingcold-pressed RBO from 0-100% (0 to 1,155.00 mg/100g oil and 0.09 to 30.82 mg/100g oil, respectively. Antioxidant activity was increased with increasing cold-pressed RBO from 0-100% (9.26 to 94.24%.The pure hydrogenated PKO contained higher trans-fat content than that of the 90:10 and 80:20 mixtures (2.73, 1.93 and 1.85mg/100g oil,respectively while other samples had no trans-fat. No microorganisms were present in any of the samples.Therefore, substitution of hydrogenated PKO by cold-pressed RBO from 30-100% would offer more nutritional values and better chemical and physical properties of non-dairy creamer.

  9. Genetic manipulation of the γ-aminobutyric acid (GABA) shunt in rice: overexpression of truncated glutamate decarboxylase (GAD2) and knockdown of γ-aminobutyric acid transaminase (GABA-T) lead to sustained and high levels of GABA accumulation in rice kernels.

    Science.gov (United States)

    Shimajiri, Yasuka; Oonishi, Takayuki; Ozaki, Kae; Kainou, Kumiko; Akama, Kazuhito

    2013-06-01

    Gamma-aminobutyric acid (GABA) is a non-protein amino acid commonly present in all organisms. Because cellular levels of GABA in plants are mainly regulated by synthesis (glutamate decarboxylase, GAD) and catabolism (GABA-transaminase, GABA-T), we attempted seed-specific manipulation of the GABA shunt to achieve stable GABA accumulation in rice. A truncated GAD2 sequence, one of five GAD genes, controlled by the glutelin (GluB-1) or rice embryo globulin promoters (REG) and GABA-T-based trigger sequences in RNA interference (RNAi) cassettes controlled by one of these promoters as well, was introduced into rice (cv. Koshihikari) to establish stable transgenic lines under herbicide selection using pyriminobac. T₁ and T₂ generations of rice lines displayed high GABA concentrations (2-100 mg/100 g grain). In analyses of two selected lines from the T₃ generation, there was a strong correlation between GABA level and the expression of truncated GAD2, whereas the inhibitory effect of GABA-T expression was relatively weak. In these two lines both with two T-DNA copies, their starch, amylose, and protein levels were slightly lower than non-transformed cv. Koshihikari. Free amino acid analysis of mature kernels of these lines demonstrated elevated levels of GABA (75-350 mg/100 g polished rice) and also high levels of several amino acids, such as Ala, Ser, and Val. Because these lines of seeds could sustain their GABA content after harvest (up to 6 months), the strategy in this study could lead to the accumulation GABA and for these to be sustained in the edible parts. © 2013 Society for Experimental Biology, Association of Applied Biologists and John Wiley & Sons Ltd.

  10. 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

  11. 7 CFR 868.301 - Definition of milled rice.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 7 2010-01-01 2010-01-01 false Definition of milled rice. 868.301 Section 868.301... FOR CERTAIN AGRICULTURAL COMMODITIES United States Standards for Milled Rice Terms Defined § 868.301 Definition of milled rice. Whole or broken kernels of rice (Oryza sativa L.) from which the hulls and at...

  12. 7 CFR 868.201 - Definition of rough rice.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 7 2010-01-01 2010-01-01 false Definition of rough rice. 868.201 Section 868.201... FOR CERTAIN AGRICULTURAL COMMODITIES United States Standards for Rough Rice Terms Defined § 868.201 Definition of rough rice. Rice (Oryza sativa L.) which consists of 50 percent or more of paddy kernels (see...

  13. 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...

  14. 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.

  15. 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.

  16. 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...

  17. 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`.

  18. 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.

  19. 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.

  20. 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

  1. 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...

  2. 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

  3. Design and Analysis of Salmonid Tagging Studies in the Columbia Basin, Volume XIII; Appraisal of System-Wide Survival Estimation of Snake River Yearling Chinook Salmon Released in 1997 and 1988, Using PIT-Tags Recovered from Caspian Tern and Double-Crested Cormorant Breeding Colonies on Rice Island, 1997-1998 Technical Report.

    Energy Technology Data Exchange (ETDEWEB)

    Skalski, John R.; Perez-Comas, Jose A. (University of Washington, School of Fisheries, Seattle, WA)

    2000-05-01

    PIT-tags recovered from tern and cormorant breeding colonies at Rice Island and observations from the interrogation systems at John Day and Bonneville Dams were incorporated into survival analyses. Whether the estimates for the upper reaches of the system, between Lower Granite and McNary Dams were as expected (with weighted averages S{sub LGR-LGS} = 0.996, S{sub LGS-LMN} = 0.837, and S{sub LMN-McN} = 0.941), those for the lower reaches, between John Day and Bonneville Dams, appeared positively biased with survival estimates typically greater than 1. Their weighted averages were S{sub McN-JDA} = 0.707 and S{sub JDA-BON} = 1.792 for 1997 releases. For the 1998 releases, they were S{sub McN-JDA} = 0.795 and S{sub JDA-BON} = 1.312. If the estimates for the lower reaches were biased, the estimates for the whole project would also be biased (S{sub LGR-BON} = 0.819). We determined that bias could have arisen if the terns and cormorants of Rice Island fished for salmon yearlings in waters of the BON-Rice reach at low rates (M{sub BON-Rice} {le} 0.2), and the rates of tag-deposition and tag-detection were low (R{sub D} x R{sub R} {le} 0.4). Moreover, unknown levels of uncensored post-detection mortality and scavenging of previously dead salmon yearlings may have also added to the bias.

  4. Autoradiographic study on moisture distribution in pearl-barley and in rice grain

    International Nuclear Information System (INIS)

    Sakharov, Eh.V.; Koz'mina, E.P.; Troitskaya, E.Ya

    1975-01-01

    The dependence of some structural details of the pearl-barley and rice endosperm on the internal moisture distribution is found. The general scheme of the study is shown. The curves of the local moisture distribution in the pearly-barley and rice kernel are plotted according to the radiography data. Moisture distribution over the whole section of the rice kernel is relatively constant at 85 deg C after ten minutes of moisture. Whereas moisture of pearl-barley kernel is only approaching the center of kernel by the time the moisture content increases to 1.5-2%. The slow moisture transfer in the pearl-barley kernel makes the cooking period three times longer as that of the rice

  5. Development of three allele-specific co-Dominant PCR markers suitable for marker-assisted selection of amylose class and paste viscosity of rice

    Science.gov (United States)

    Most rice is consumed as whole kernel cooked rice, and the consumer preferences for cooked rice texture and other sensory properties differ among regions of the world. Rice is also used as an ingredient in a multitude of foods by food-processing companies across the globe. These sensory and function...

  6. 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...

  7. 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...

  8. 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...

  9. 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...

  10. 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...

  11. 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...

  12. 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.

  13. 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...

  14. 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...

  15. 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

  16. Morphological and starch structural characteristics of the Japonica rice mutant variety Seolgaeng for dry-milled flour

    Science.gov (United States)

    Producing fine, good quality rice flour is more difficult than wheat flour because the rice grain is harder. In this study, we analyzed the relationship between the morphology and starch of kernels from genetically different rice varieties that can be used to make dry-milled flour. The non-glutinous...

  17. 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

  18. Rice microstructure

    Science.gov (United States)

    An understanding of plant structure is desirable to obtain a clear idea of the overall impact of a crop. A mature rice plant consists of leafy components (left in the field post-harvest) and paddy rice (collected). The rice plant is supported by a hollow stem (culm) with leaf sheaths attached to nod...

  19. 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 ...

  20. Recycling rice husks for high-capacity lithium battery anodes.

    Science.gov (United States)

    Jung, Dae Soo; Ryou, Myung-Hyun; Sung, Yong Joo; Park, Seung Bin; Choi, Jang Wook

    2013-07-23

    The rice husk is the outer covering of a rice kernel and protects the inner ingredients from external attack by insects and bacteria. To perform this function while ventilating air and moisture, rice plants have developed unique nanoporous silica layers in their husks through years of natural evolution. Despite the massive amount of annual production near 10(8) tons worldwide, so far rice husks have been recycled only for low-value agricultural items. In an effort to recycle rice husks for high-value applications, we convert the silica to silicon and use it for high-capacity lithium battery anodes. Taking advantage of the interconnected nanoporous structure naturally existing in rice husks, the converted silicon exhibits excellent electrochemical performance as a lithium battery anode, suggesting that rice husks can be a massive resource for use in high-capacity lithium battery negative electrodes.

  1. 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] ...

  2. 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...

  3. 7 CFR 981.8 - Inedible kernel.

    Science.gov (United States)

    2010-01-01

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

  4. 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...

  5. 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....

  6. PROCESS OF RECOVERING URANIUM

    Science.gov (United States)

    Carter, J.M.; Larson, C.E.

    1958-10-01

    A process is presented for recovering uranium values from calutron deposits. The process consists in treating such deposits to produce an oxidlzed acidic solution containing uranium together with the following imparities: Cu, Fe, Cr, Ni, Mn, Zn. The uranium is recovered from such an impurity-bearing solution by adjusting the pH of the solution to the range 1.5 to 3.0 and then treating the solution with hydrogen peroxide. This results in the precipitation of uranium peroxide which is substantially free of the metal impurities in the solution. The peroxide precipitate is then separated from the solution, washed, and calcined to produce uranium trioxide.

  7. 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...

  8. 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.

  9. Effect of Xanthan, Mono-di-Glyceride and Cultivar on Physical and Sensory Properties of Canned Rice During Storage

    Directory of Open Access Journals (Sweden)

    A. Nasirpour

    2014-08-01

    Full Text Available Ready-to-eat or canned products have an important place in urban life style. Rice is consumed by half of world population. Problems related to production of canned rice are the coherences of rice kernel, retrogradation of rice starch and physico-chemical changes of rice during storage. Main factors affecting physico-chemical properties of canned rice are rice cultivar, amylose and amylopectin content of kernels, precooking conditions, kernel composition and added stabilizers. In this study, effect of three cultivars, Basmati and two local cultivars, Tarom Mazandaran and Tarom Hashemi, also two types of stabilizers, Xanthan, Mono-di-glyceride, on sensory and physical properties of canned rice were studied. Type and level of stabilizers, cultivars and time had significant effect on texture of cooked rice. Initially during storage, Basmati had the highest firmness and Tarom Mazandaran and Tarom Hashemi had lower firmness. The results of texture analysis indicated that both stabilizers reduced firmness of cooked rice during storage. Adding xhanthan as stabilizer had higher effect on reducing of cooked rice firmness comparing to mono-di-glyceride. Result of color analysis showed that Basmati cultivar was most yellowish and Tarom Mazandaran indicated maximum lightness. Sensory analysis of samples indicated that Basmati had the best score on texture, appearance and acceptability and Tarom Hashemi had the best score on taste and flavor. Type of stabilizer had significant effect on taste and flavor of cooked rice.

  10. Genetic Architecture of Grain Chalk in Rice and Interactions with a Low Phytic Acid Locus

    Science.gov (United States)

    Grain quality characteristics have a major impact on the value of the harvested rice crop. In addition to grain dimensions which determine rice grain market classes, translucent milled kernels are also important for assuring the highest grain quality and crop value. Over the last several years, ther...

  11. Effect of soaking and phytase treatment on phytic acid, calcium, iron and zinc in rice fractions

    NARCIS (Netherlands)

    Liang, J.; Han, B.Z.; Nout, M.J.R.; Hamer, R.J.

    2009-01-01

    With the aim to maximise phytic acid removal and minimise losses of dry matter and minerals (Ca, Fe, Zn) in rice, three products (whole kernels and flour milled from white and brown rice; and bran, all from the same batch of variety Kenjian 90-31) were soaked in demineralized water at 10 °C (SDW),

  12. 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.

  13. Sodium aerosol recovering device

    International Nuclear Information System (INIS)

    Fujimori, Koji; Ueda, Mitsuo; Tanaka, Kazuhisa.

    1997-01-01

    A main body of a recovering device is disposed in a sodium cooled reactor or a sodium cooled test device. Air containing sodium aerosol is sucked into the main body of the recovering device by a recycling fan and introduced to a multi-staged metal mesh filter portion. The air about against each of the metal mesh filters, and the sodium aerosol in the air is collected. The air having a reduced sodium aerosol concentration circulates passing through a recycling fan and pipelines to form a circulation air streams. Sodium aerosol deposited on each of the metal mesh filters is scraped off periodically by a scraper driving device to prevent clogging of each of the metal filters. (I.N.)

  14. 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...

  15. Use of oil palm kernel meal as a supplement material for abalone mushroom (Pleurotus cystidiosus O.K. Miller cultivation

    Directory of Open Access Journals (Sweden)

    Petcharat, V. and

    2004-09-01

    Full Text Available The objective of this study was to determine the optimum rate of oil palm kernel meal, for an abalone mushroom (Pleurotus cystidiosus cultivation. Different concentrations of oil palm kernel meal (5- 20% were added to pararubber sawdust and used to grow the abalone mushroom in plastic bags. Growth rate of the mycelia, number of days from watering to harvesting and yield were compared to those on 94% sawdust + 5% rice bran + 1% Ca(OH2. The results showed that 10% oil palm kernel meal was the optimum concentration for abalone mushroom cultivation. Yield on 950 g/bag of 89% sawdust + 10% oil palm kernel meal + 1% Ca(OH2 was 202.12 g/bag (B.E. = 60.79% during 120 days of havesting time. Addition of higher concentration of oil palm kernel meal (15-20% did not increase yield of the basidiocarps.

  16. 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...

  17. 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. ...

  18. 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...

  19. 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.

  20. 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...

  1. 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....

  2. Recovering valuable liquid hydrocarbons

    Energy Technology Data Exchange (ETDEWEB)

    Pier, M

    1931-06-11

    A process for recovering valuable liquid hydrocarbons from coking coal, mineral coal, or oil shale through treatment with hydrogen under pressure at elevated temperature is described. Catalysts and grinding oil may be used in the process if necessary. The process provides for deashing the coal prior to hydrogenation and for preventing the coking and swelling of the deashed material. During the treatment with hydrogen, the coal is either mixed with coal low in bituminous material, such as lean coal or active coal, as a diluent or the bituminous constituents which cause the coking and swelling are removed by extraction with solvents. (BLM)

  3. In vitro gastric digestion of cooked white and brown rice using a dynamic rat stomach model.

    Science.gov (United States)

    Wu, Peng; Deng, Renpan; Wu, Xuee; Wang, Yong; Dong, Zhizhong; Dhital, Sushil; Chen, Xiao Dong

    2017-12-15

    The changes in physical, rheological and enzyme-digestive behaviours of cooked white and brown rice, with similar amylose content, were investigated using a dynamic in vitro rat stomach (DIVRS) model and a static soaking method. The brown rice had a higher resistance on disintegration and lower gastric emptying rate with 53% of the brown rice particles retained in the stomach at the end compared to 32% for the white rice. Furthermore, the release rate of maltose from the starch hydrolysis was higher in the white rice throughout the digestion suggesting the lower glycemic potency of the brown rice. These differences could be contributed from the rigid bran layer in the brown rice which would inhibit the moisture absorption into rice kernels, limit textural degradation, and generate higher gastric digesta viscosity leading to lower mixing and mass transfer efficiency. This study suggests that the structural difference could affect physiochemical properties during gastric digestion. Copyright © 2017 Elsevier Ltd. All rights reserved.

  4. 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 ...

  5. 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.

  6. Uranium oxide recovering method

    International Nuclear Information System (INIS)

    Ota, Kazuaki; Takazawa, Hiroshi; Teramae, Naoki; Onoue, Takeshi.

    1997-01-01

    Nitrates containing uranium nitrate are charged in a molten salt electrolytic vessel, and a heat treatment is applied to prepare molten salts. An anode and a cathode each made of a graphite rod are disposed in the molten salts. AC voltage is applied between the anode and the cathode to conduct electrolysis of the molten salts. Uranium oxides are deposited as a recovered product of uranium, on the surface of the anode. The nitrates containing uranium nitrate are preferably a mixture of one or more nitrates selected from sodium nitrate, potassium nitrate, calcium nitrate and magnesium nitrate with uranium nitrate. The nitrates may be liquid wastes of nitrates. The temperature for the electrolysis of the molten salts is preferably from 150 to 300degC. The voltage for the electrolysis of the molten salts is preferably an AC voltage of from 2 to 6V, more preferably from 4 to 6V. (I.N.)

  7. Process for recovering uranium

    Science.gov (United States)

    MacWood, G. E.; Wilder, C. D.; Altman, D.

    1959-03-24

    A process useful in recovering uranium from deposits on stainless steel liner surfaces of calutrons is presented. The deposit is removed from the stainless steel surface by washing with aqueous nitric acid. The solution obtained containing uranium, chromium, nickel, copper, and iron is treated with an excess of ammonium hydroxide to precipitnte the uranium, iron, and chromium and convert the nickel and copper to soluble ammonio complexions. The precipitated material is removed, dried and treated with carbon tetrachloride at an elevated temperature of about 500 to 600 deg C to form a vapor mixture of UCl/ sub 4/, UCl/sub 5/, FeCl/sub 3/, and CrCl/sub 4/. The UCl/sub 4/ is separated from this vapor mixture by selective fractional condensation at a temperature of about 500 to 400 deg C.

  8. Recovering oil from shale

    Energy Technology Data Exchange (ETDEWEB)

    Leahey, T; Wilson, H

    1920-11-13

    To recover oil free from inorganic impurities and water, and utilize the oil vapor and tarry matter for the production of heat, shale is heated in a retort at a temperature of not less than 120/sup 0/C. The vapors pass by a pipe into a water jacketed condenser from which the condensate and gas pass through a pipe into a chamber and then by a pipe to a setting chamber from where the light oils are decanted through a pipe into a tank. The heavy oil is siphoned through a pipe into a tank, while the gas passes through a pipe into a scrubber and then into a drier, exhauster and pipe to the flue and ports, above the fire-bars, into the retort. Air is introduced through a pipe, flue, and ports.

  9. 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...

  10. 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.

  11. 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...

  12. 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.

  13. Degree of Milling Effect on Cold Water Rice Quality

    Directory of Open Access Journals (Sweden)

    Ujjwol Subedi

    2018-05-01

    Full Text Available The aim of this study was to examine the effects of degree of milling on various rice parameters such as proximate composition, and cooking properties using mathematical model. The experiments were performed in the laboratory of Food Research Division, Nepal Agricultural Research Council. The three different medium type rice varieties of Nepal (Lumle-2, Chhomrong and Machhapuchre-3 were exposed to five different degrees of milling (0%, 6%, 8%, 10% and 12%. The degree of milling (DM level significantly (P≤0.05 affected the milling recovery; head rice yield, nutrient content as well as cooking properties of the rice. Increase in DM resulted in further reduction of protein content, fat content, minerals, milled rice and head rice yield after bran layer was further removed. A positive correlation between DM used in present model, amylose content, kernel elongation and gruel solid loss was observed, however, with an increase in DM; amylose content, kernel elongation and gruel solid loss were found to be increased. Adopting 6 to 8% DM for commercial milling of rice might help to prevent quantitative, qualitative and nutritional loss along with retention of good cooking characteristics.

  14. 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

  15. 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...

  16. Promising mutant variety of rice evolved through gamma irradiation

    International Nuclear Information System (INIS)

    Prasad, S.C.; Sinha, S.K.

    1980-01-01

    Rice occupies a major share in crop production in the Chotanagpur plateau of Bihar State. Uplands are roughly 40% in area where traditional low yielding rice, known as ''gora'' is cultivated as directly sown crop. Despite introduction of high yielding rice varieties, gora group of rices continue to prevail. It is therefore desired to increase the productivity level of the gora rice by mutation breeding. One such mutant known as ''gora mutant'' was obtained through gamma irradiation (10 kR) of variety Brown gora. The maturity of both parent and mutant remaining constant (ie. 100 days), there is some improvement in other characteristics like plant height, tillering capacity and kernel character. The parent being tall, shy in tillering and red bold kernel, the mutant has dwarfish characteristics, profuse tillering habit and white kernel with fine grains. The yielding capacity of mutant derivative is 30-40% higher than the parent Brown gora. This variety is in pre-release stage, and the farmers have taken great liking for it. (author)

  17. 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.

  18. 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.

  19. Effects of milling on functional properties of rice flour.

    Science.gov (United States)

    Kadan, R S; Bryant, R J; Miller, J A

    2008-05-01

    A commercial long-grain rice flour (CRF) and the flours made by using a pin mill and the Udy mill from the same batch of broken second-head white long-grain rice were evaluated for their particle size and functional properties. The purpose of this study was to compare the commercial rice flour milling method to the pin and Udy milling methods used in our laboratory and pilot plant. The results showed that pin milled flour had more uniform particle size than the other 2 milled flours. The chalky kernels found in broken white milled rice were pulverized more into fines in both Udy milled flour and CRF than in the pin milled flour. The excessive amount of fines in flours affected their functional properties, for example, WSI and their potential usage in the novel foods such as rice breads (RB). The RB made from CRF collapsed more than loaves made from pin milled Cypress long-grain flours.

  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. 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...

  2. Resistance of Rice Varieties to the Stored-Product Insect, Sitophilus zeamais (Coleoptera: Curculionidae).

    Science.gov (United States)

    Antunes, Catarina; Mendes, Raquel; Lima, Arlindo; Barros, Graça; Fields, Paul; Da Costa, Luísa Beirão; Rodrigues, José Carlos; Silva, Maria José; Correia, Augusto Manuel; Carvalho, Maria Otilia

    2016-02-01

    Four common Portuguese rice varieties--Thaibonnet, Gladio, Albatros, and Eurosis--were tested for their relative susceptibility to Sitophilus zeamais Motschulsky, a common pest of stored rice in Portugal and in tropical countries. Physical (moisture content, hardness, length, and width) and chemical (by attenuated total reflection-Fourier transform infrared spectroscopy) properties of rice kernels were measured. Insect bioassays measured median developmental time, Dobie's index of susceptibility, percentage of damaged grains and weight loss, and progeny developed. This was done for paddy, brown rice, and polished rice for each variety. There were small, but significant, differences in insect resistance among the varieties. However, it was different for paddy and polished rice. In paddy, these differences were correlated with hull damage, and Eurosis was the most susceptible variety. In polished rice, resistance was correlated with hardness, and Thaibonnet was the most susceptible variety. In general, paddy rice was more resistant to insect attack, followed by polished rice and then brown rice. Paddy kernels selected with undamaged hull were completely resistant to attack. Implications for IPM and breeding for resistant varieties are discussed. © The Authors 2015. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  3. 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

  4. 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....

  5. 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

  6. 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.

  7. 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.

  8. 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

  9. 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

  10. 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…

  11. 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

  12. 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.

  13. 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.

  14. 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

  15. 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.

  16. 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....

  17. 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....

  18. (PGMS) rice

    African Journals Online (AJOL)

    user

    2011-04-18

    Apr 18, 2011 ... tics, led us to predict that pollen cell abortion in this type of rice when ... averages of natural day-light-lengths and temperatures were used. A natural long ... blocks were allowed to grow under natural growth conditions (which.

  19. 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.

  20. 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.

  1. 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.

  2. Review of the cost components of introducing industrially fortified rice.

    Science.gov (United States)

    Roks, Eveline

    2014-09-01

    Micronutrient deficiencies affect over two billion people worldwide, particularly in developing countries. Fortification of staple foods with multiple micronutrients is a cost-effective strategy to increase vitamin and mineral intake. The objective of this paper is to review the cost elements of industrially fortified rice by identifying the costs related to the implementation of rice fortification programs, using the experience of the United Nations World Food Programme in its pilot countries. The actual total costs of rice fortification are not easily captured. Core cost elements include the production of fortified rice kernels, transportation to the point of blending, blending of fortified with unfortified rice, costs related to sales or distribution, quality control and assurance, and additional planning. In the introduction phase, organizations or coalitions seeking to advance rice fortification will face additional costs related to the initiation of rice fortification. In the scale-up phase, greater efficiency in the supply chain and economies of scale can be expected. Different cost elements are normally borne by different stakeholders. This makes the implementation of rice fortification programs a feasible option to reach vulnerable populations with inadequate access to affordable nutrition solutions. © 2014 New York Academy of Sciences.

  3. 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...

  4. Effect of zinc on grain characteristics of draught-resistant rice mutants

    International Nuclear Information System (INIS)

    Abo-Hegazi, A.M.T.; Rofail, N.B.; Eissa, E.A.; Hassan, A.M.

    1996-01-01

    Through the use of Instrumental Neutron Activation Analysis (INAA), zinc concentration was determined in kernels resulted on plants of six drought-resistant rice mutant lines fertilized with zinc sulphate. It was found that zinc fertilization increased zinc residues in the kernels with varying concentrations depending on the line, each line reacted and responded to zinc independently. Zinc content in the kernels ranged from 5.63 to 91.4 ppm in the unfertilized control lines. This range was enlarged due to zinc fertilization of the plants to be from 93.51 to 554.53 ppm. It was also noticed that zinc fertilization increased seed heaviness in varying degrees depending on the line itself. This increase may be due to the increase in kernel thickness rather than in kernel width or length. (author). 26 refs., 3 figs

  5. 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.

  6. 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.

  7. 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....

  8. Proximate Nutritional Evaluation of Gamma Irradiated Black Rice (Oryza sativa L. cv. Cempo ireng)

    Science.gov (United States)

    Riyatun; Suharyana; Ramelan, A. H.; Sutarno; Saputra, O. A.; Suryanti, V.

    2018-03-01

    Black rice is a type of pigmented rice with black bran covering the endosperm of the rice kernel. The main objective of the present study was to provide details information on the proximate composition of third generation of gamma irradiated black rice (Oryza sativa L. cv. Cempo ireng). In respect to the control, generally speaking, there were no significant changes of moisture, lipids, proteins, carbohydrates and fibers contents have been observed for the both gamma irradiated black rice. However, the 200-BR has slightly better nutritional value than that of 300-BR and the control. The mineral contents of 200-BR increased significantly of about 35% than the non-gamma irradiated black rice.

  9. 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

  10. 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.

  11. Effects of soaking and acidification on physicochemical properties of calcium-fortified rice.

    Science.gov (United States)

    Sirisoontaralak, Porntip; Limboon, Pailin; Jatuwong, Sujitra; Chavanalikit, Arusa

    2016-06-01

    Calcium-fortified rice was prepared by soaking milled rice in calcium lactate solution, steaming and drying, and physicochemical properties were determined to evaluate effects of calcium concentration (0, 30, 50 g L(-1) ), soaking temperature (ambient temperature, 40 °C, 60 °C) and acidification. Calcium-fortified rice had less lightness. More total solid loss was observed, especially at high soaking temperature. Harder texture was detected with increased calcium concentration. Calcium fortification lowered pasting viscosity of milled rice. Panelists accepted all fortified rice; however, only rice soaked at 50 g L(-1) concentration could be claimed as a good source of calcium. Increasing of soaking temperature induced more penetration of calcium to rice kernels but calcium was lost more easily after washing. With addition of acetic acid to the soaking solution, enriched calcium content was comparable to that of high soaking temperature but with better retention after washing and calcium solubility was improved. Acid induced reduction of lightness and cooked rice hardness but increased total solid loss and pasting viscosity. Although the taste of acetic acid remained, panelists still accepted the fortified rice. Calcium-fortified rice (190.47-194.3 mg 100 g(-1) ) could be successfully produced by soaking milled rice in 50 g L(-1) calcium lactate solution at 40 °C or at ambient temperature with acidification. © 2015 Society of Chemical Industry. © 2015 Society of Chemical Industry.

  12. Development of techniques for storing rough rice in cold regions, 1: Storage of rough rice at country elevator with natural heat radiation in winter

    International Nuclear Information System (INIS)

    Takekura, K.; Kawamura, S.; Itoh, K.

    2003-01-01

    An on-farm experiment in which 361 metric tons of rough rice was stored in a silo from November until July was conducted at a country elevator in Hokkaido to develop new techniques for storing rough rice in cold regions. The temperature of the rough rice near the inner silo wall decreased to below ice point (-5°C) due to natural heat radiation in winter, which the temperature of the rough rice in the center of the silo was maintained at almost the same temperature as that at the beginning of storage (5°C). Ventilation in the upper vacant space of the silo prevented moisture condensation on the inside surface of the silo during storage. When the cold rough rice was unloaded from the silo in summer, an unheated forced-air drier was used to increase the temperature of rough rice to above the dew point temperature of surrounding air. During the unloading and rewarming process, the moisture content of the rough rice increased due to moisture condensation on the grain from the air. However, the husks first absorbed the condensation and then the moisture slowly permeated into the brown rice kernel. Thus the rewarming process didn't cause any fissures in the brown rice. The results of the experiment indicate that condensation on rough rice doesn't give rise to any problems

  13. NPS-NRL-Rice-UIUC Collaboration on Navy Atmosphere-Ocean Coupled Models on Many-Core Computer Architectures Annual Report

    Science.gov (United States)

    2015-09-30

    DISTRIBUTION STATEMENT A: Distribution approved for public release; distribution is unlimited. NPS-NRL- Rice -UIUC Collaboration on Navy Atmosphere...portability. There is still a gap in the OCCA support for Fortran programmers who do not have accelerator experience. Activities at Rice /Virginia Tech are...for automated data movement and for kernel optimization using source code analysis and run-time detective work. In this quarter the Rice /Virginia

  14. 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.

  15. 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

  16. 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.

  17. 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.

  18. 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

  19. 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)

  20. 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...

  1. 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…

  2. 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

  3. 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

  4. Kernel-based whole-genome prediction of complex traits: a review.

    Science.gov (United States)

    Morota, Gota; Gianola, Daniel

    2014-01-01

    Prediction of genetic values has been a focus of applied quantitative genetics since the beginning of the 20th century, with renewed interest following the advent of the era of whole genome-enabled prediction. Opportunities offered by the emergence of high-dimensional genomic data fueled by post-Sanger sequencing technologies, especially molecular markers, have driven researchers to extend Ronald Fisher and Sewall Wright's models to confront new challenges. In particular, kernel methods are gaining consideration as a regression method of choice for genome-enabled prediction. Complex traits are presumably influenced by many genomic regions working in concert with others (clearly so when considering pathways), thus generating interactions. Motivated by this view, a growing number of statistical approaches based on kernels attempt to capture non-additive effects, either parametrically or non-parametrically. This review centers on whole-genome regression using kernel methods applied to a wide range of quantitative traits of agricultural importance in animals and plants. We discuss various kernel-based approaches tailored to capturing total genetic variation, with the aim of arriving at an enhanced predictive performance in the light of available genome annotation information. Connections between prediction machines born in animal breeding, statistics, and machine learning are revisited, and their empirical prediction performance is discussed. Overall, while some encouraging results have been obtained with non-parametric kernels, recovering non-additive genetic variation in a validation dataset remains a challenge in quantitative genetics.

  5. Kernel-based whole-genome prediction of complex traits: a review

    Directory of Open Access Journals (Sweden)

    Gota eMorota

    2014-10-01

    Full Text Available Prediction of genetic values has been a focus of applied quantitative genetics since the beginning of the 20th century, with renewed interest following the advent of the era of whole genome-enabled prediction. Opportunities offered by the emergence of high-dimensional genomic data fueled by post-Sanger sequencing technologies, especially molecular markers, have driven researchers to extend Ronald Fisher and Sewall Wright's models to confront new challenges. In particular, kernel methods are gaining consideration as a regression method of choice for genome-enabled prediction. Complex traits are presumably influenced by many genomic regions working in concert with others (clearly so when considering pathways, thus generating interactions. Motivated by this view, a growing number of statistical approaches based on kernels attempt to capture non-additive effects, either parametrically or non-parametrically. This review centers on whole-genome regression using kernel methods applied to a wide range of quantitative traits of agricultural importance in animals and plants. We discuss various kernel-based approaches tailored to capturing total genetic variation, with the aim of arriving at an enhanced predictive performance in the light of available genome annotation information. Connections between prediction machines born in animal breeding, statistics, and machine learning are revisited, and their empirical prediction performance is discussed. Overall, while some encouraging results have been obtained with non-parametric kernels, recovering non-additive genetic variation in a validation dataset remains a challenge in quantitative genetics.

  6. Process of recovering bituminous materials

    Energy Technology Data Exchange (ETDEWEB)

    1920-08-22

    A modification of the process covered by German Patent 389,393 for recovering bituminous materials from oil shale by extraction is disclosed consisting, in place of or besides wood spirit oil, of acetone oil, suitably of boiling point 80 to 130/sup 0/C, being used as the extraction medium.

  7. 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.

  8. Improvement of local varieties of rice (Oryza glaberrima) for resistance to shattering and grain quality by induced mutations

    Energy Technology Data Exchange (ETDEWEB)

    Cisse, F; Dione, M; Kelly, S [Institute d` Economie Rurale, Station de Recherche Agronomique, Mopti (Mali)

    1997-12-01

    In Mali, a large area of rice is planted with the local rice, O. glaberrima which under conditions of low rainfall and flood water is more hardy to stress than the introduced O. sativa cultivars. A program to improve the local varieties of O. glaberrima by induced mutations was started in 1988. Ten local varieties were irradiated with 20 and 30 krad. In M{sub 4} of cv. `Gorbal`, irradiated with 20 krads, 13 variants were selected. Five of these were evaluated in M{sub 5} for their agronomic performance. The induced mutants in the remaining 9 varieties were highly sterile with 90% or more sterility in the M{sub 2} and M{sub 3}. Irradiation with 20-30 krad gave high survival (70-95%), and several mutants with white kernel were obtained from the red seeded types. Nearly two-third of the identified mutants had white caryopsis. There is better consumer acceptance of the white seeded type of rice than the red seeded varieties in Mali and the white seeded mutants may have an added premium in the market. The field performance of the M{sub 5} mutants was investigated. Preliminary results showed that some of mutants derived from cv. `Gorbal` were early in maturity and had more panicles per plant, but had a lower 1000-kernel weight, and did not differ from the parent in grain yield. Additional trials are planned to establish potential of the mutants for yield and quality. Three more cultivars of O. glaberrima - `Haira`, `Tombo` and `Yele` - were irradiated with 20 and 60 krads, and gave 75, 81 and 72% seed viability, respectively. M{sub 1} showed reduced plant height. Selection for non-shattering of grains shall be carried out in M{sub 2}. Any plants which are non-shattering but sterile shall be crossed with the parent to recover the mutant types. The taxonomic status of cv. `Gorbal` is not very clear. Isozyme patterns suggest that this cultivar may belong to O. sativa and not to O. glaberrima. To establish its taxonomic status, crosses shall be made with O. sativa and O

  9. Improvement of local varieties of rice (Oryza glaberrima) for resistance to shattering and grain quality by induced mutations

    International Nuclear Information System (INIS)

    Cisse, F.; Dione, M.; Kelly, S.

    1997-01-01

    In Mali, a large area of rice is planted with the local rice, O. glaberrima which under conditions of low rainfall and flood water is more hardy to stress than the introduced O. sativa cultivars. A program to improve the local varieties of O. glaberrima by induced mutations was started in 1988. Ten local varieties were irradiated with 20 and 30 krad. In M 4 of cv. 'Gorbal', irradiated with 20 krads, 13 variants were selected. Five of these were evaluated in M 5 for their agronomic performance. The induced mutants in the remaining 9 varieties were highly sterile with 90% or more sterility in the M 2 and M 3 . Irradiation with 20-30 krad gave high survival (70-95%), and several mutants with white kernel were obtained from the red seeded types. Nearly two-third of the identified mutants had white caryopsis. There is better consumer acceptance of the white seeded type of rice than the red seeded varieties in Mali and the white seeded mutants may have an added premium in the market. The field performance of the M 5 mutants was investigated. Preliminary results showed that some of mutants derived from cv. 'Gorbal' were early in maturity and had more panicles per plant, but had a lower 1000-kernel weight, and did not differ from the parent in grain yield. Additional trials are planned to establish potential of the mutants for yield and quality. Three more cultivars of O. glaberrima - 'Haira', 'Tombo' and 'Yele' - were irradiated with 20 and 60 krads, and gave 75, 81 and 72% seed viability, respectively. M 1 showed reduced plant height. Selection for non-shattering of grains shall be carried out in M 2 . Any plants which are non-shattering but sterile shall be crossed with the parent to recover the mutant types. The taxonomic status of cv. 'Gorbal' is not very clear. Isozyme patterns suggest that this cultivar may belong to O. sativa and not to O. glaberrima. To establish its taxonomic status, crosses shall be made with O. sativa and O. glaberrima. (author). 2 tabs

  10. 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%.

  11. 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.

  12. Generalized multiple kernel learning with data-dependent priors.

    Science.gov (United States)

    Mao, Qi; Tsang, Ivor W; Gao, Shenghua; Wang, Li

    2015-06-01

    Multiple kernel learning (MKL) and classifier ensemble are two mainstream methods for solving learning problems in which some sets of features/views are more informative than others, or the features/views within a given set are inconsistent. In this paper, we first present a novel probabilistic interpretation of MKL such that maximum entropy discrimination with a noninformative prior over multiple views is equivalent to the formulation of MKL. Instead of using the noninformative prior, we introduce a novel data-dependent prior based on an ensemble of kernel predictors, which enhances the prediction performance of MKL by leveraging the merits of the classifier ensemble. With the proposed probabilistic framework of MKL, we propose a hierarchical Bayesian model to learn the proposed data-dependent prior and classification model simultaneously. The resultant problem is convex and other information (e.g., instances with either missing views or missing labels) can be seamlessly incorporated into the data-dependent priors. Furthermore, a variety of existing MKL models can be recovered under the proposed MKL framework and can be readily extended to incorporate these priors. Extensive experiments demonstrate the benefits of our proposed framework in supervised and semisupervised settings, as well as in tasks with partial correspondence among multiple views.

  13. Treating effluents; recovering coal, etc

    Energy Technology Data Exchange (ETDEWEB)

    Jones, F B; Bury, E

    1920-02-18

    Liquor obtained by scrubbing coal gas with sea-water or fresh water, and containing or having added to it finely-divided carbonaceous material in suspension, is subjected to a froth-flotation process to recover the carbonaceous matter and organic materials in the froth, and render the remaining liquor innocuous. Liquor obtained by scrubbing distillation gases, such as coal gas, may be used as a frothing-agent in a froth flotation process for the recovery of carbonaceous substances such as coal from materials containing them, thereby producing a froth containing the coal, etc., and also the organic materials from the liquor. In some cases the effluent may be diluted with sea-water, and, in recovering carbonaceous shales, there may be added to the liquor a small proportion of paraffin oil.

  14. Methods of recovering alkali metals

    Science.gov (United States)

    Krumhansl, James L; Rigali, Mark J

    2014-03-04

    Approaches for alkali metal extraction, sequestration and recovery are described. For example, a method of recovering alkali metals includes providing a CST or CST-like (e.g., small pore zeolite) material. The alkali metal species is scavenged from the liquid mixture by the CST or CST-like material. The alkali metal species is extracted from the CST or CST-like material.

  15. 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 ...

  16. 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.

  17. 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 ...

  18. 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 ...

  19. 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...

  20. 7 CFR 51.1441 - Half-kernel.

    Science.gov (United States)

    2010-01-01

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

  1. 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...

  2. 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...

  3. 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...

  4. 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

  5. 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...

  6. 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.

  7. 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...

  8. 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

  9. 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.)

  10. 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.

  11. 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 ...

  12. Rice peasants and rice research in Colombia

    NARCIS (Netherlands)

    Spijkers, P.A.N.M.

    1983-01-01

    Rice has been grown as a food crop in Latin America from early colonial times. In Colombia rice became a prominent subsistence crop especially on the north coast where it has been grown since the 17th century, sometimes also as a commercial crop. During the last twenty years there has been a sharp

  13. Upgraded RECOVER system - CASDAC system

    International Nuclear Information System (INIS)

    Yamamoto, Yoichi; Koyama, Kinji

    1992-03-01

    The CASDAC (Containment And Surveillance Data Authenticated Communication) system has been developed by JAERI for nuclear safeguards and physical protection of nuclear material. This system was designed and constructed as an upgraded RECOVER system, design concept of which was based on the original RECOVER system and also the TRANSEAVER system. Both of them were developed several years ago as a remote monitoring system for continual verification of security and safeguards status of nuclear material. The system consists of two subsystems, one of them is a Grand Command Center (GCC) subsystem and the other is a facility subsystem. Communication between the two subsystems is controlled through the international telephone line network. Therefore all communication data are encrypted to prevent access by an unauthorized person who may intend to make a falsification, or tapping. The facility subsystem has an appropriate measure that ensure data security and reliable operation under unattended mode of operator. The software of this system is designed so as to be easily used in other different types of computers. This report describes the outline of the CASDAC system and the results of its performance test. This work has been carried out in the framework of Japan Support Programme for Agency Safeguards (JASPAS) as a project, JA-1. (author)

  14. 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.

  15. Process of recovering shale oil

    Energy Technology Data Exchange (ETDEWEB)

    1949-01-17

    A process is disclosed for recovering oil from shale rock by means of channels cut in the shale deposit, to which heat is carried for warming the shale mass and which are separated from the fume channels formed in the shale by parts of the shale rock, characterized in that heating elements are put down in the heating channels, which occupy less cross section than these channels, and in the so-formed space between the channel wall and the heating element a filling is placed, which facilitates heat transfer between the heating element and the shale and simultaneously prevents a streaming of the oily product gasified out of the shale from working into the heating element and stopping it.

  16. Recovering uranium from phosphoric acid

    International Nuclear Information System (INIS)

    Anon.

    1979-01-01

    Wet-process phosphoric acid contains a significant amount of uranium. This uranium totals more than 1,500 tons/yr in current U.S. acid output--and projections put the uranium level at 8,000 tons/yr in the year 2000. Since the phosphoric acid is a major raw material for fertilizers, uranium finds its way into those products and is effectively lost as a resource, while adding to the amount of radioactive material that can contaminate the food chain. So, resource-conservation and environmental considerations both make recovery of the uranium from phosphoric acid desirable. This paper describes the newly developed process for recovering uranium from phosphoric acid by using solvent-extraction technique. After many extractants had been tested, the researchers eventually selected the combination of di (2-ethylhexyl) phosphoric acid (DEPA) and trioctylphosphine oxide (TOPO) as the most suitable. The flowscheme of the process is included

  17. METHOD OF RECOVERING URANIUM COMPOUNDS

    Science.gov (United States)

    Poirier, R.H.

    1957-10-29

    S>The recovery of uranium compounds which have been adsorbed on anion exchange resins is discussed. The uranium and thorium-containing residues from monazite processed by alkali hydroxide are separated from solution, and leached with an alkali metal carbonate solution, whereby the uranium and thorium hydrorides are dissolved. The carbonate solution is then passed over an anion exchange resin causing the uranium to be adsorbed while the thorium remains in solution. The uranium may be recovered by contacting the uranium-holding resin with an aqueous ammonium carbonate solution whereby the uranium values are eluted from the resin and then heating the eluate whereby carbon dioxide and ammonia are given off, the pH value of the solution is lowered, and the uranium is precipitated.

  18. Uranium material removing and recovering device

    International Nuclear Information System (INIS)

    Takita, Shin-ichi.

    1997-01-01

    A uranium material removing and recovering device for use in removing surplus uranium heavy metal (UO 2 ) generated in a uranium handling facility comprises a uranium material removing device and a uranium material recovering device. The uranium material removing device comprises an adsorbing portion filled with a uranium adsorbent, a control portion for controlling the uranium adsorbent of the uranium adsorbing portion by a controlling agent, a uranium adsorbing device connected thereto and a jetting device for jetting the adsorbing liquid to equipments deposited with uranium. The recovering device comprises a recovering apparatus for recovering uranium materials deposited with the adsorbent liquid removed by the jetting device and a recovering tank for storing the recovered uranium materials. The device of the present invention can remove surplus uranium simply and safely, mitigate body's load upon removing and recovering operations, facilitate the processing for the exchange of the adsorbent and reduces the radioactive wastes. (T.M.)

  19. 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.

  20. Neglecting rice milling yield and quality underestimates economic losses from high-temperature stress.

    Directory of Open Access Journals (Sweden)

    Nathaniel B Lyman

    Full Text Available Future increases in global surface temperature threaten those worldwide who depend on rice production for their livelihoods and food security. Past analyses of high-temperature stress on rice production have focused on paddy yield and have failed to account for the detrimental impact of high temperatures on milling quality outcomes, which ultimately determine edible (marketable rice yield and market value. Using genotype specific rice yield and milling quality data on six common rice varieties from Arkansas, USA, combined with on-site, half-hourly and daily temperature observations, we show a nonlinear effect of high-temperature stress exposure on yield and milling quality. A 1 °C increase in average growing season temperature reduces paddy yield by 6.2%, total milled rice yield by 7.1% to 8.0%, head rice yield by 9.0% to 13.8%, and total milling revenue by 8.1% to 11.0%, across genotypes. Our results indicate that failure to account for changes in milling quality leads to understatement of the impacts of high temperatures on rice production outcomes. These dramatic losses result from reduced paddy yield and increased percentages of chalky and broken kernels, which together decrease the quantity and market value of milled rice. Recently published estimates show paddy yield reductions of up to 10% across the major rice-producing regions of South and Southeast Asia due to rising temperatures. The results of our study suggest that the often-cited 10% figure underestimates the economic implications of climate change for rice producers, thus potentially threatening future food security for global rice producers and consumers.

  1. 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

  2. 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.

  3. 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...

  4. Mineralization of nitrogen from nitrogen-15 labeled crop residues and utilization by rice

    International Nuclear Information System (INIS)

    Norman, R.J.; Gilmour, J.T.; Wells, B.R.

    1990-01-01

    The availability of N from the residues of the previous crop to the subsequent rice (Oryza sativa L.) crop is largely unknown. The objectives of this study were to (1) measure the mineralization of N from 15 N-labeled rice, soybean (Glycine max L.), and wheat (Triticum aestivum L.) residues and the uptake by a subsequent rice crop; and (2) compare the 15 N tracer method with the standard fertilizer-N response method used in field studies to quantify the N contribution from the crop residue to the next crop. Nitrogen mineralization from decomposing crop residues was measured by soil sampling prior to seeding the rice crop and after seeding by plant sampling the rice at maturity. The minimum estimate of the amount of residue N mineralized from the time of residue incorporation until rice harvest was 9, 52, and 38% of the rice, soybean, and wheat residue N, respectively. The amount of residue N recovered in the rice crop was 3, 11, and 37% of the rice, soybean, and wheat residue N, respectively. The lower the C/N ratio and the higher the amount of N in the residue, the lower was the amount of residue N recovered in the soil organic fraction at harvest and the higher was the amount of residue N mineralized. The 15 N tracer method compared favorably with the fertilizer N response method when the uptake efficiency of the fertilizer N was taken into account

  5. 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.

  6. Physical, milling, cooking, and pasting characteristics of different rice varieties grown in the valley of Kashmir India

    Directory of Open Access Journals (Sweden)

    Tanveer Ahmad Rather

    2016-12-01

    Full Text Available In the present study, three different rice varieties, namely frome chena (FC, safaid chena (SC, and barkat chena (BC, were evaluated for various quality aspects in terms of physical, milling, cooking, and pasting characteristics. Among the three rice varieties SC had the highest thousand kernel weight and length breadth ratio (L/B. While as, BC had the lowest thousand kernel weight and FC had lowest L/B. Bulk density was found to be highest for FC followed by SC and BC. FC had density of 769.01 kg/m3. Milling characteristic in terms of broken percentage and head rice yield showed non-significant difference between the varieties. Head rice yield was below 70% in all the three varieties. All the three varieties took similar time to cook and cooking time varied non-significantly between 23.66 and 25.83 min. L/B ratio after cooking was found to be highest for FC followed by BC and SC. Elongation ratio of rice after cooking did not varied significantly between varieties. Elongation ratio after cooking ranged from 1.60 to 1.70. Pasting profile of rice flour was determined using rapid visco analyzer. Significant difference was observed in pasting profile of studied rice varieties.

  7. 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

  8. 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

  9. 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

  10. Rice SUB1A constrains remodeling of the transcriptome and metabolome during submergence and post-submergence recovery”.

    Science.gov (United States)

    The rice (Oryza sativa L.) ethylene-responsive transcription factor SUB1A confers tolerance to prolonged, complete submergence by limiting underwater elongation growth. Rice encoding SUB1A-1 also recovers photosynthetic function and re-commences development towards flowering more rapidly after desu...

  11. 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...

  12. 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...

  13. 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.

  14. 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

  15. 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...

  16. 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...

  17. 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.

  18. 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

  19. 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

  20. 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.

  1. 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.

  2. 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

  3. 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

  4. 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.

  5. 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

  6. 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

  7. 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

  8. 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

  9. 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

  10. 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.)

  11. 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...

  12. 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

  13. 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

  14. 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...

  15. 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 ...

  16. 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

  17. 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...

  18. 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...

  19. 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...

  20. 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...

  1. 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

  2. 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...

  3. 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.

  4. 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 .

  5. Effect of increased plant density and fertilizer dose on the yield of rice variety IR-6

    International Nuclear Information System (INIS)

    Amin, M.; Khan, M.A.; Khan, E.A.; Ramazan, M.

    2004-01-01

    An experiment to evaluate the effect of increased plant density and fertilizer dose on yield of rice variety IR-6 was conducted at the farm of Faculty of Agriculture, Gomal University Dera Ismail Khan. Increase plant density significantly increase number of panicles per square meter, sterility and straw yield while increased fertilizer dose of NPK increase plant height, sterility, normal kernels, and 1000 grain weight. Interaction of increased plant density and fertilizer dose was found to be non significant except sterility percentage and straw yield. However efforts are required for increasing yield per unit area of rice. (author)

  6. Rice (Oryza) hemoglobins

    Science.gov (United States)

    Hemoglobins (Hbs) corresponding to non-symbiotic (nsHb) and truncated (tHb) Hbs have been identified in rice (Oryza). This review discusses the major findings from the current studies on rice Hbs. At the molecular level, a family of the nshb genes, consisting of hb1, hb2, hb3, hb4 and hb5, and a sin...

  7. 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...

  8. 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)

  9. 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.

  10. 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.

  11. 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.

  12. Bran data of total flavonoid and total phenolic contents, oxygen radical absorbance capacity, and profiles of proanthocyanidins and whole grain physical traits of 32 red and purple rice varieties

    Directory of Open Access Journals (Sweden)

    Ming-Hsuan Chen

    2016-09-01

    Full Text Available Phytochemicals in red and purple bran rice have potential health benefit to humans. We determined the phytochemicals in brans of 32 red and purple global rice varieties. The description of the origin and physical traits of the whole grain (color, length, width, thickness and 100-kernel weight of this germplasm collection are provided along with data of total flavonoid and total phenolic contents, oxygen radical absorbance capacity and total proanthocyanidin contents. The contents and proportions of individual oligomers, from degree of polymerization of monomers to 14-mers, and polymers in bran of these 32 rice varieties are presented (DOI: http://dx.doi.org/10.1016/j.foodchem.2016.04.004 [1]. Keywords: Purple rice, Red rice, Black rice, Proanthocyanidins, Tannins, Flavonoids, Rice bran

  13. Relações granulométricas no processo de brunimento de arroz Granulometry relationship in the rice milling process

    Directory of Open Access Journals (Sweden)

    Carlos A. S. Luz

    2005-04-01

    Full Text Available O brunimento é uma das etapas de beneficiamento do arroz que tem grande importância sobre o rendimento de engenho. Neste trabalho, analisaram-se relações granulométricas de frações de grãos na massa de arroz e seus efeitos sobre o rendimento de engenho, durante o processo de brunimento. As amostras usadas foram 78 g de arroz descascado, tendo essas partido de amostras originais de 100 g. Foram testadas cinco relações de composição de amostras a serem brunidas, variando as quantidades de grãos quebrados e de quirera que acompanhavam a massa de grãos inteiros, que foram: 1 somente grãos inteiros; 2 6,16 g de quebrados e 1,04 g de quirera, conforme amostra original; 3 3,60 g de quebrados e 3,60 g de quirera adicionados aos inteiros; 4 7,20 g de quebrados adicionados aos inteiros, e 5 7,20 g de quirera adicionada aos inteiros. Os procedimentos foram executados com uso de engenho de provas e com classificação manual. O rendimento de engenho foi significativamente superior, após a operação de brunimento de arroz, quando existem, na massa a ser brunida, grãos quebrados e quirera, variando entre 3,60 g a 7,20 g e 1,04 g a 7,20 g, respectivamente, comparada ao brunimento da massa composta por 100% de grãos inteiros.Milling yield using five different rates of broken and head rice was tested. The samples were arranged to have different amounts of big and small broken kernels in the mass of grains. The size of each fraction of broken grains was established according to the Brazilian Rules of Rice Classification. The paddy sample had 100 g and the brown rice sample had 78 g. The brown rice was milled by adding different proportions of broken kernels to make five treatments as follows: 1 only whole kernels; 2 6.16 g of big broken kernels and 1.04 g of small broken kernels were used as they appear in the original lot; 3 3.6 g of big broken kernels and 3.6 g of small broken kernels were added to the whole kernels; 4 7.2 g of big broken

  14. Effect of processing on residues of chlorpyrifos in stored corn and rice

    International Nuclear Information System (INIS)

    Tejada, A.W.; Calumpang, S.M.F.; Gambalan, N.B.

    1990-01-01

    The effect of processing on residues of chlorpyrifos in rice and corn was determined. Chlorpyrifos solution (0.1%) sprayed on jute sacks containing corn resulted in absorption of residues in kernel and cob up to six months. A similar trend was observed in rice. Radiotracer studies revealed very low levels of bound residues (0.2 - 0.8 mg/kg) present in rice only. The usual practice of washing rice and corn before cooking reduced chlorpyrifos residues as much as 57% to 100%. Residues in wash water declined with each washing. Cooking further reduced the residues of chlorpyrifos only when volatilization was possible. Chlorpyrifos appeared to be persistent. Cooking rice in plot with the lid on did not produce any substantial reduction in the chlorpyrifos content. The practice of storing rice and corn in the Philippines does not give rice to chlorpyrifos residues which may exceed the recommended daily intake of 0.01 mg/kg-bw. (Auth.) 13 refs., 12 tabs., 3 figs

  15. Piloting a Commercial Model for Fortified Rice: Lessons Learned From Brazil.

    Science.gov (United States)

    Milani, Peiman; Spohrer, Rebecca; Garrett, Greg; Kreis, Katharine

    2016-05-18

    Two billion people worldwide have micronutrient deficiencies. Food fortification is a proven intervention to increase essential micronutrient availability in diets without requiring consumer behavioral change. Fortification of rice has high potential reach; however, cost, technology, market, and cultural constraints have prevented its wider adoption. From 2010 to 2014, PATH and Global Alliance for Improved Nutrition implemented a pilot project in Brazil testing a model to scale up rice fortification through commercial channels. The project focused on 5 areas: (1) building fortified rice kernel production capacity; (2) supply chain development; (3) distribution channel and market development; (4) demand generation; and (5) advocacy and knowledge dissemination. Primary data were collected in 2 rounds of quantitative research 6 months apart and conducted in 2 regions in Brazil. Secondary data were sourced from published literature, socioeconomic and demographic data, and sales figures from the project's rice miller partner. Postmortem analysis was conducted by the project team with input from external sources. Although the project successfully launched a fortified rice product and a category brand platform, it was unsuccessful in reaching meaningful scale. Market and industry dynamics affected producers' willingness to launch new fortified products. Consumers' strong attachment to rice combined with a weak understanding of micronutrient malnutrition hampered demand creation efforts. This project showed that a purely commercial approach is insufficient for sustainable scale-up of fortified rice to achieve public health goals in a 3- to 5-year period. © The Author(s) 2016.

  16. Effect of solvent on the extraction of phenolic compounds and antioxidant capacity of hazelnut kernel.

    Science.gov (United States)

    Fanali, Chiara; Tripodo, Giusy; Russo, Marina; Della Posta, Susanna; Pasqualetti, Valentina; De Gara, Laura

    2018-03-22

    Hazelnut kernel phenolic compounds were recovered applying two different extraction approaches, namely ultrasound-assisted solid/liquid extraction (UA-SLE) and solid-phase extraction (SPE). Different solvents were tested evaluating total phenolic compounds and total flavonoids contents together to antioxidant activity. The optimum extraction conditions, in terms of the highest value of total phenolic compounds extracted together to other parameters like simplicity and cost were selected for method validation and individual phenolic compounds analysis. The UA-SLE protocol performed using 0.1 g of defatted sample and 15 mL of extraction solvent (1 mL methanol/1 mL water/8 mL methanol 0.1% formic acid/5 mL acetonitrile) was selected. The analysis of hazelnut kernel individual phenolic compounds was obtained by HPLC coupled with DAD and MS detections. Quantitative analysis was performed using a mixture of six phenolic compounds belonging to phenolic classes' representative of hazelnut. Then, the method was fully validated and the resulting RSD% values for retention time repeatability were below 1%. A good linearity was obtained giving R 2 no lower than 0.997.The accuracy of the extraction method was also assessed. Finally, the method was applied to the analysis of phenolic compounds in three different hazelnut kernel varieties observing a similar qualitative profile with differences in the quantity of detected compounds. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  17. 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

  18. 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.

  19. 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...

  20. 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.

  1. 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...

  2. 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.

  3. 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/

  4. 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)

  5. 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

  6. Dissection of Genetic Factors underlying Wheat Kernel Shape and Size in an Elite × Nonadapted Cross using a High Density SNP Linkage Map

    Directory of Open Access Journals (Sweden)

    Ajay Kumar

    2016-03-01

    Full Text Available Wheat kernel shape and size has been under selection since early domestication. Kernel morphology is a major consideration in wheat breeding, as it impacts grain yield and quality. A population of 160 recombinant inbred lines (RIL, developed using an elite (ND 705 and a nonadapted genotype (PI 414566, was extensively phenotyped in replicated field trials and genotyped using Infinium iSelect 90K assay to gain insight into the genetic architecture of kernel shape and size. A high density genetic map consisting of 10,172 single nucleotide polymorphism (SNP markers, with an average marker density of 0.39 cM/marker, identified a total of 29 genomic regions associated with six grain shape and size traits; ∼80% of these regions were associated with multiple traits. The analyses showed that kernel length (KL and width (KW are genetically independent, while a large number (∼59% of the quantitative trait loci (QTL for kernel shape traits were in common with genomic regions associated with kernel size traits. The most significant QTL was identified on chromosome 4B, and could be an ortholog of major rice grain size and shape gene or . Major and stable loci also were identified on the homeologous regions of Group 5 chromosomes, and in the regions of (6A and (7A genes. Both parental genotypes contributed equivalent positive QTL alleles, suggesting that the nonadapted germplasm has a great potential for enhancing the gene pool for grain shape and size. This study provides new knowledge on the genetic dissection of kernel morphology, with a much higher resolution, which may aid further improvement in wheat yield and quality using genomic tools.

  7. Dissection of Genetic Factors underlying Wheat Kernel Shape and Size in an Elite × Nonadapted Cross using a High Density SNP Linkage Map.

    Science.gov (United States)

    Kumar, Ajay; Mantovani, E E; Seetan, R; Soltani, A; Echeverry-Solarte, M; Jain, S; Simsek, S; Doehlert, D; Alamri, M S; Elias, E M; Kianian, S F; Mergoum, M

    2016-03-01

    Wheat kernel shape and size has been under selection since early domestication. Kernel morphology is a major consideration in wheat breeding, as it impacts grain yield and quality. A population of 160 recombinant inbred lines (RIL), developed using an elite (ND 705) and a nonadapted genotype (PI 414566), was extensively phenotyped in replicated field trials and genotyped using Infinium iSelect 90K assay to gain insight into the genetic architecture of kernel shape and size. A high density genetic map consisting of 10,172 single nucleotide polymorphism (SNP) markers, with an average marker density of 0.39 cM/marker, identified a total of 29 genomic regions associated with six grain shape and size traits; ∼80% of these regions were associated with multiple traits. The analyses showed that kernel length (KL) and width (KW) are genetically independent, while a large number (∼59%) of the quantitative trait loci (QTL) for kernel shape traits were in common with genomic regions associated with kernel size traits. The most significant QTL was identified on chromosome 4B, and could be an ortholog of major rice grain size and shape gene or . Major and stable loci also were identified on the homeologous regions of Group 5 chromosomes, and in the regions of (6A) and (7A) genes. Both parental genotypes contributed equivalent positive QTL alleles, suggesting that the nonadapted germplasm has a great potential for enhancing the gene pool for grain shape and size. This study provides new knowledge on the genetic dissection of kernel morphology, with a much higher resolution, which may aid further improvement in wheat yield and quality using genomic tools. Copyright © 2016 Crop Science Society of America.

  8. Factors Affecting Planting Depth and Standing of Rice Seedling in Parachute Rice Transplanting

    Science.gov (United States)

    Astika, I. W.; Subrata, I. D. M.; Pramuhadi, G.

    2018-05-01

    Parachute rice transplanting is a simple and practical rice transplanting method. It can be done manually or mechanically, with various possible designs of machines or tools. This research aimed at quantitatively formulating related factors to the planting depth and standing of rice seedling. Parachute seedlings of rice were grown at several sizes of parachute soil bulb sizes. The trays were specially designed with a 3D printer having bulb sizes 7, 8, 9, 10 mm in square sides and 15 mm depth. At seedling ages of 8-12 days after sowing the seedling bulbs were drops into puddled soil. Soil hardness was set at 3 levels of hardness, measured in hardness index using golf ball test. Angle of dropping was set at 3 levels: 0°, 30°and 45° from the vertical axis. The height of droppings was set at 100 cm, 75 cm, and 50 cm. The relationship between bulb size, height of dropping, soil hardness, dropping angle and planting depth was formulated with ANN. Most of input variables did not significantly affect the planting depth, except that hard soil significantly differs from mild soil and soft soil. The dropping also resulted in various positions of the planted seedlings: vertical standing, sloped, and falling. However, at any position of the planted seedlings, the seedlings would recover themselves into normally vertical position. With this result, the design of planting machinery, as well as the manual planting operation, can be made easier.

  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. Persistence of malathion residues in stored milled rice: Direct and indirect applications

    International Nuclear Information System (INIS)

    Arshad, J.H.

    1990-01-01

    Two experiments were carried out: (i) to study the persistence of malathion residues in stored milled rice following multiple applications of 14 C-malathion to the bagged rice and (ii) to determine the degradation of malathion in stored milled rice and stored paddy following direct and single application of 14 C-malathion. The storage conditions were similar to those found in the local rice godowns. Three applications of malathion to the bagged milled rice resulted in the accumulation of malathion and its metabolites in and/or on the rice grains over the storage period. After 9 months' storage, ca. 4% of the total applied radioactivity, which amounted to 10 μg/g equivalent of 14 C residues, were found in and/or on the grains. About one fourth of the residue remained as the unchanged parent compound. On the other hand, when 14 C-malathion at the 10 ppm level was mixed directly with the milled rice or paddy prior to storage, the amount of malathion (recovered in the chloroform extracts) decreased from 6.2 μg/g at zero time to 2.9 μg/g after 3 months' storage for the milled rice samples. The major metabolite in the milled rice and paddy samples was malathion monocarboxylic acid with trace amounts of malathion dicarboxylic acid and malaoxon. (author). 5 refs, 3 tabs

  12. 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...

  13. Uptake and metabolism of [14C]-aspartate by developing kernels of maize (Zea mays L.)

    International Nuclear Information System (INIS)

    Muhitch, M.J.

    1990-01-01

    Pulse-chase experiments were performed to determine the metabolic fate of [14C]-aspartate in the pedicel region and subsequent uptake into the endosperm. Kernels were removed from the cob, leaving the pedicel attached but removing glumes, palea, and lemma. The basal tips were incubated in [14C]-aspartate for 0.5 h, followed by a 2 h chase period with unlabeled aspartate. In contrast to a previous study in which 70% of the 14C from aspartate was recovered in the organic acid fraction (Lyznik, et al., Phytochemistry 24: 425, 1985), only 20 to 25% of the radioactivity found in the 2 h chase period. While a small amount of the 14C transiently appeared in alanine at the beginning of the chase period, the most heavily labeled non-fed amino acid was glutamine, which accounted for 21% of the radioactivity within the pedicel amino acid fraction by 0.5 h into the chase period. There was no evidence for asparagine synthesis within the pedicel region of the kernel. 14C recovered from the endosperm in the form of amino acids were aspartate (60%), glutamine (20%), glutamate (15%), and alanine (5%). These results suggest that some of the maternally supplied amino acids undergo metabolic conversion to other amino acids before being taken up by the endosperm

  14. 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.

  15. 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...

  16. Recovering recyclable materials from shredder residue

    Science.gov (United States)

    Jody, Bassam J.; Daniels, Edward J.; Bonsignore, Patrick V.; Brockmeier, Norman F.

    1994-02-01

    Each year, about 11 million tons of metals are recovered in the United States from about 10 million discarded automobiles. The recovered metals account for about 75 percent of the total weight of the discarded vehicles. The balance of the material, known as shredder residue, amounts to about three million tons annually and is currently landfilled. The residue contains a diversity of potentially recyclable materials, including polyurethane foams, iron oxides, and certain thermoplastics. This article discusses a process under development at Argonne National Laboratory to separate and recover the recyclable materials from this waste stream. The process consists essentially of two stages. First, a physical separation is used to recover the foams and the metal oxides, followed by a chemical process to extract certain thermoplastics. The status of the technology and the process economics are reviewed here.

  17. Automated monitoring of recovered water quality

    Science.gov (United States)

    Misselhorn, J. E.; Hartung, W. H.; Witz, S. W.

    1974-01-01

    Laboratory prototype water quality monitoring system provides automatic system for online monitoring of chemical, physical, and bacteriological properties of recovered water and for signaling malfunction in water recovery system. Monitor incorporates whenever possible commercially available sensors suitably modified.

  18. 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....

  19. 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

  20. Recovery and subsequent characterization of polyhydroxybutyrate from Rhodococcus equi cells grown on crude palm kernel oil

    Directory of Open Access Journals (Sweden)

    Nadia Altaee

    2016-07-01

    Full Text Available The gram-positive bacterium Rhodococcus equi was isolated from fertile soil, and mineral salt media (MM and trace elements were used to provide the necessary elements for its growth and PHB production in addition to using crude palm kernel oil (CPKO 1% as the carbon source. Gas chromatography (GC demonstrated that the composition of the recovered biopolymer was homopolymer polyhydroxybutyrate (PHB. The strain of the present study has a dry biomass of 1.43 (g/l with 38% PHB, as determined by GC. The recovered PHB was characterized by NMR to study the chemical structure. In addition, DSC and TGA were used to study the thermal properties of the recovered polymer, where the melting temperature (Tm was 173 °C, the glass transition temperature (Tg was 2.79 °C, and the decomposition temperature (Td was 276 °C. Gel permeation chromatography (GPC was used to study the molecular mass of the recovered PHB in addition to comparing the results with other studies using different bacteria and substrates, where the molecular weight was 642 kDa, to enable its usage in many applications. The present study demonstrated the use of an inexpensive substrate for PHB production, i.e., using gram-positive bacteria to produce PHB polymer with characterization.

  1. Transfer of gaseous iodine from atmosphere to rough rice, brown rice and polished rice

    International Nuclear Information System (INIS)

    Sumiya, Misako; Uchida, Shigeo; Muramatsu, Yasuyuki; Ohmomo, Yoichiro; Yamaguchi, Shuho; Obata, Hitoshi.

    1987-01-01

    Experiments were carried out in order to obtain information required for establishing transfer coefficients of gaseous iodine (I 2 ) to rough rice, brown rice and polished rice. The gaseous iodine deposited on young rice plants before the heading period was scarcely found in the rough rice harvested at the full ripe stage. The biological half life of iodine in hull, however, was much slower than that in leaves of 14 days. The translocation of iodine from leaves and stalks to rough rice was not clearly recognized. Therefore, it was deduced that iodine found in brown rice mainly should originate from that deposited on the hull. The distribution ratios of iodine between rough rice and brown rice, and between brown rice and polished rice were 100:4 and 100:30 on 100 grains basis, respectively. If average normalized deposition velocity (V d(m) ) or derived deposition velocity (V s ) are given, the transfer coefficients of gaseous iodine to rough rice (TF r ), brown rice (TF b ) and polished rice (TF p ) could be calculated. (author)

  2. 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.

  3. 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.

  4. 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.

  5. 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

  6. 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.

  7. 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....

  8. 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

  9. The role of Tre6P and SnRK1 in maize early kernel development and events leading to stress-induced kernel abortion.

    Science.gov (United States)

    Bledsoe, Samuel W; Henry, Clémence; Griffiths, Cara A; Paul, Matthew J; Feil, Regina; Lunn, John E; Stitt, Mark; Lagrimini, L Mark

    2017-04-12

    Drought stress during flowering is a major contributor to yield loss in maize. Genetic and biotechnological improvement in yield sustainability requires an understanding of the mechanisms underpinning yield loss. Sucrose starvation has been proposed as the cause for kernel abortion; however, potential targets for genetic improvement have not been identified. Field and greenhouse drought studies with maize are expensive and it can be difficult to reproduce results; therefore, an in vitro kernel culture method is presented as a proxy for drought stress occurring at the time of flowering in maize (3 days after pollination). This method is used to focus on the effects of drought on kernel metabolism, and the role of trehalose 6-phosphate (Tre6P) and the sucrose non-fermenting-1-related kinase (SnRK1) as potential regulators of this response. A precipitous drop in Tre6P is observed during the first two hours after removing the kernels from the plant, and the resulting changes in transcript abundance are indicative of an activation of SnRK1, and an immediate shift from anabolism to catabolism. Once Tre6P levels are depleted to below 1 nmol∙g -1 FW in the kernel, SnRK1 remained active throughout the 96 h experiment, regardless of the presence or absence of sucrose in the medium. Recovery on sucrose enriched medium results in the restoration of sucrose synthesis and glycolysis. Biosynthetic processes including the citric acid cycle and protein and starch synthesis are inhibited by excision, and do not recover even after the re-addition of sucrose. It is also observed that excision induces the transcription of the sugar transporters SUT1 and SWEET1, the sucrose hydrolyzing enzymes CELL WALL INVERTASE 2 (INCW2) and SUCROSE SYNTHASE 1 (SUSY1), the class II TREHALOSE PHOSPHATE SYNTHASES (TPS), TREHALASE (TRE), and TREHALOSE PHOSPHATE PHOSPHATASE (ZmTPPA.3), previously shown to enhance drought tolerance (Nuccio et al., Nat Biotechnol (October 2014):1-13, 2015). The impact

  10. 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.

  11. 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.

  12. 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

  13. 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

  14. 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.

  15. 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...

  16. Prevalence of Rice Yellow Mottle Virus (RYMV) on Rice Plants ...

    African Journals Online (AJOL)

    Abstract. Incidence of Rice yellow mottle virus (RYMV) on rice plants (ofada) grown in two local government areas (LGAs) of Ogun State had been evaluated during a two year field survey. Six month old rice plants were observed for symptom expression and leaf samples collected for serological indexing. Of the 60 leaf ...

  17. 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.

  18. Marker-assisted backcrossing: a useful method for rice improvement.

    Science.gov (United States)

    Hasan, Muhammad Mahmudul; Rafii, Mohd Y; Ismail, Mohd R; Mahmood, Maziah; Rahim, Harun A; Alam, Md Amirul; Ashkani, Sadegh; Malek, Md Abdul; Latif, Mohammad Abdul

    2015-03-04

    The world's population is increasing very rapidly, reducing the cultivable land of rice, decreasing table water, emerging new diseases and pests, and the climate changes are major issues that must be addressed to researchers to develop sustainable crop varieties with resistance to biotic and abiotic stresses. However, recent scientific discoveries and advances particularly in genetics, genomics and crop physiology have opened up new opportunities to reduce the impact of these stresses which would have been difficult if not impossible as recently as the turn of the century. Marker assisted backcrossing (MABC) is one of the most promising approaches is the use of molecular markers to identify and select genes controlling resistance to those factors. Regarding this, MABC can contribute to develop resistant or high-yielding or quality rice varieties by incorporating a gene of interest into an elite variety which is already well adapted by the farmers. MABC is newly developed efficient tool by which using large population sizes (400 or more plants) for the backcross F 1 generations, it is possible to recover the recurrent parent genotype using only two or three backcrosses. So far, many high yielding, biotic and abiotic stresses tolerance, quality and fragrance rice varieties have been developed in rice growing countries through MABC within the shortest timeframe. Nowadays, MABC is being used widely in plant breeding programmes to develop new variety/lines especially in rice. This paper reviews recent literature on some examples of variety/ line development using MABC strategy.

  19. Potassium hydroxide pulping of rice straw in biorefinery initiatives.

    Science.gov (United States)

    Jahan, M Sarwar; Haris, Fahmida; Rahman, M Mostafizur; Samaddar, Purabi Rani; Sutradhar, Shrikanta

    2016-11-01

    Rice straw is supposed to be one of the most important lignocellulosic raw materials for pulp mill in Asian countries. The major problem in rice straw pulping is silica. The present research is focused on the separation of silica from the black liquor of rice straw pulping by potassium hydroxide (KOH) and pulp evaluation. Optimum KOH pulping conditions of rice straw were alkali charge 12% as NaOH, cooking temperature 150°C for 2h and material to liquor ratio, 1:6. At this condition pulp yield was 42.4% with kappa number 10.3. KOH pulp bleached to 85% brightness by D0EpD1 bleaching sequences with ClO2 consumption of 25kg/ton of pulp. Silica and lignin were separated from the black liquor of KOH pulping. The amount of recovered silica, lignin and hemicelluloses were 10.4%, 8.4% and 13.0%. The papermaking properties of KOH pulp from rice straw were slightly better than those of corresponding NaOH pulp. Copyright © 2016 Elsevier Ltd. All rights reserved.

  20. 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.

  1. 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.

  2. 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.

  3. 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

  4. 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.

  5. 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.

  6. 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.

  7. 7 CFR 868.310 - Grades and grade requirements for the classes Long Grain Milled Rice, Medium Grain Milled Rice...

    Science.gov (United States)

    2010-01-01

    ... Grain Milled Rice, Medium Grain Milled Rice, Short Grain Milled Rice, and Mixed Milled Rice. (See also Â... Milled Rice Principles Governing Application of Standards § 868.310 Grades and grade requirements for the classes Long Grain Milled Rice, Medium Grain Milled Rice, Short Grain Milled Rice, and Mixed Milled Rice...

  8. Cognitive bias in symptomatic and recovered agoraphobics.

    Science.gov (United States)

    Stoler, L S; McNally, R J

    1991-01-01

    Symptomatic agoraphobics, recovered agoraphobics, and normal control subjects completed a series of sentence stems that had either ambiguous or unambiguous meanings, and had either a potentially threatening or a nonthreatening connotation. The written completions made by subjects to these stems were classified as indicating either a biased (i.e. threat-related) or unbiased interpretation of the meaning of the stem, and if a biased interpretation was made, whether the subject indicated efforts at adaptive coping with the perceived threat. Results indicated that symptomatic agoraphobics exhibited strong biases for interpreting information as threatening, relative to normal control subjects. Moreover, recovered agoraphobics resembled symptomatic agoraphobics more than normal control subjects, thus indicating that cognitive biases may persist following cessation of panic attacks and reductions in avoidance behavior. However, recovered agoraphobics also exhibited tendencies to cope adaptively with perceived threats whereas symptomatic agoraphobics did not.

  9. Ergonomic analysis jobs in recovered factories.

    Science.gov (United States)

    Cuenca, Gabriela; Zotta, Gastón

    2012-01-01

    With the advent of the deep economic crisis in Argentina on 2001, the recovery of companies through to the creation of the Cooperatives Working Self-Management or Factories Recovered by its workers was constituted as one of the ways in which the salaried disobeyed the increasing unemployment. When the companies turn into recovered factories they tend to leave of side practices that have been seen like imposed by the previous organization and not understanding them as a primary condition for the execution of his tasks. Safety and ergonomics are two disciplines that are no longer considered relevant to the daily work. Therefore this investigation aims to revalue, undergo semantic to give back to a place in every organization analyzed. This research developed a self-diagnostic tool for working conditions, and the environment, present in the recovered factories.

  10. Extraction of rice bran oil from local rice husk

    International Nuclear Information System (INIS)

    Anwar, J.; Zaman, W.; Salman, M.; Jabeen, N.

    2006-01-01

    Rice Bran Oil is widely used in pharmaceutical, food and chemical industries due to its unique properties and high medicinal value. In the present work, extraction of rice bran oil from different samples of rice husk collected from local rice shellers by solvent extraction method has been studied. Experiments were conducted using a soxhelt apparatus, to extract rice bran oil using hexane, petroleum ether, ethanol and methanol as the solvents and the yields obtained under different conditions were compared. Batch extraction tests showed that the rate of extraction decreases with time and the solution approaches saturation at an exponential rate. (author)

  11. Effect of Azolla Based - Organic Fertilizer, Rock Phosphate and Rice Hull Ash on Rice Yield and Chemical Properties of Alfisols

    Directory of Open Access Journals (Sweden)

    Sudadi

    2014-07-01

    Full Text Available The application of chemical fertilizer for long time may adverse soil environment. Organic agriculture, for example combination use of azolla based-organic fertilizer, phosphate rock and rice hull ash, was one of ways that able to recover it. Research was conducted in Sukosari, Jumantono, Karanganyar while soi chemical properties analysis was analysed in Soil Chemistry and Fertility Laboratory, Fac. of Agriculture, Sebelas Maret University April to November 2013. Research design used was RAKL with 5 treatments, each repeated 5 times. The treatments applied were P0 (control, P1 ( azola inoculum dosage 250 g/m2 + phosphate rock + rice hull ash equal to 150 kg/ha KCl, P2 (azola inoculum dosage 500 g/m2 + phosphate rock equal to 150kg/ha, SP-36 + rice hull ash equal to 100 kg/ha KCl, P3 (manure dosage of 5 ton/ha,P4 (Urea 250 kg/ha + SP-36 150 kg/ha + KCl 100 kg/ha. Data analysed statistically by F test (Fisher test with level of confident 95% followed by DMRT (Duncan Multiple Range Test if any significant differences. The result showed that the treatment combination of azolla, phosphate rock and rice hull ash increase soil organic matter content, cation exchange capacity, available-P and exchangeable-K as well as rice yield ( (at harvest-dry grain weight and milled-dry grain weight.

  12. 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

  13. 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.

  14. 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 ...

  15. 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

  16. 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...

  17. 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.

  18. 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.

  19. 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/

  20. 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...

  1. 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...

  2. 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 ...

  3. 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...

  4. 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 ...

  5. 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

  6. 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

  7. 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

  8. 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.

  9. 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.

  10. 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.

  11. 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

  12. 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...

  13. 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…

  14. 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

  15. 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…

  16. 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

  17. 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

  18. Method of recovering hydrocarbons from oil shale

    Energy Technology Data Exchange (ETDEWEB)

    Walton, D.K.; Slusser, M.S.

    1970-11-24

    A method is described for recovering hydrocarbons from an oil-shale formation by in situ retorting. A well penetrating the formation is heated and gas is injected until a pressure buildup within the well is reached, due to a decrease in the conductivity of naturally occurring fissures within the formation. The well is then vented, in order to produce spalling of the walls. This results in the formation of an enlarged cavity containing rubberized oil shale. A hot gas then is passed through the rubberized oil shale in order to retort hydrocarbons and these hydrocarbons are recovered from the well. (11 claims)

  19. Waste heat recovering device for reactors

    International Nuclear Information System (INIS)

    Sonoda, Masanobu; Shiraishi, Tadashi; Mizuno, Hiroyuki; Sekine, Yasuhiro.

    1982-01-01

    Purpose: To enable utilization of auxiliary-equipment-cooling water from a non-regenerative heat exchanger as a heat source, as well as prevent radioactive contamination. Constitution: A water warming device for recovering the heat of auxiliary equipment cooling water from a non-regenerative heat exchanger is disposed at the succeeding stage of the heat exchanger. Heat exchange is performed in the water warming device between the auxiliary equipment cooling water and a heat source water set to a higher pressure and recycled through the water warming device. The heat recovered from the auxiliary equipment cooling water is utilized in the heat source water for operating relevant equipments. (Aizawa, K.)

  20. Solid recovered fuels in the steel industry.

    Science.gov (United States)

    Kepplinger, Werner L; Tappeiner, Tamara

    2012-04-01

    By using waste materials as alternative fuels in metallurgical plants it is possible to minimize the traditionally used reducing agents, such as coke, coal, oil or natural gas. Moreover, by using waste materials in the metallurgical industry it is feasible to recover these materials as far as possible. This also represents another step towards environmental protection because carbon dioxide emissions can be reduced, if the H(2) content of the waste material is greater in comparison with that of the substituted fuel and the effects of global warming can therefore be reduced. In the present article various solid recovered fuels and their applications in the metallurgical industry are detailed.

  1. 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.

  2. 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.

  3. 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....

  4. 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.

  5. Gasification of rice husks

    Energy Technology Data Exchange (ETDEWEB)

    Marzetti, P. (ENEA, Rome (Italy). Dipt. Fonti Alternative e Risparmio Energetico)

    The paper outlines the thermochemical processes and equipment involved in the gasification of rice husks. An assessment is made of the feasibility (availability, technology requirements, economics of production and marketing) of this renewable energy source. Results, reported here in tabular form, of experimental trials at an Italian pilot plant (producing, with the use of 165 kg/h of rice husks, 350,000 kcal/h of gas with a conversion yield of 70%) indicated good feasibility. More research is required to improve the combustion qualities of the final product.

  6. 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

  7. Department of Defense Recovering Warrior Task Force

    Science.gov (United States)

    2014-09-02

    accessible and available to the Veterans Benefits Administration ( VBA ) as soon as possible381; however, because military service records include health...programs are meeting expectations ........................................... 35 Facilitating Access to Health Care...Enduring RW Mission, Facilitating RW Recovery and Transition, and Facilitating Access to Health Care. SUMMARY 2  DoD Recovering Warrior Task Force

  8. Recovering Parameters of Johnson's SB Distribution

    Science.gov (United States)

    Bernard R. Parresol

    2003-01-01

    A new parameter recovery model for Johnson's SB distribution is developed. This latest alternative approach permits recovery of the range and both shape parameters. Previous models recovered only the two shape parameters. Also, a simple procedure for estimating the distribution minimum from sample values is presented. The new methodology...

  9. Process for recovering oil from shale, etc

    Energy Technology Data Exchange (ETDEWEB)

    1920-08-20

    A process is described for recovering oil from oil-shale and the like, by the direct action of the hot gases obtained by burning the carbonized shale residue. It is immediately carried out in separate adjacent chambers, through which the feed goes from one to the other intermittently, from the upper to the lower.

  10. Recovering uranium from coal in situ

    International Nuclear Information System (INIS)

    Terry, R.C.

    1978-01-01

    An underground carbonaceous deposit containing other mineral values is burned in situ. The underground hot zone is cooled down to temperature below the boiling point of a leachig solution. The leaching solution is percolated through the residial ash, with the pregnant solution recovered for separation of the mineral values in surface facilities

  11. Applications for Energy Recovering Free Electron Lasers

    Energy Technology Data Exchange (ETDEWEB)

    George Neil

    2007-08-01

    The availability of high-power, high-brilliance sources of tunable photons from energy-recovered Free Electron Lasers is opening up whole new fields of application of accelerators in industry. This talk will review some of the ideas that are already being put into production, and some of the newer ideas that are still under development.

  12. 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

  13. 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.

  14. Photochemical oxidants injury in rice plants. III. Effect of ozone on physiological activities in rice plants

    Energy Technology Data Exchange (ETDEWEB)

    Nakamura, H; Saka, H

    1978-01-01

    Experiments were made to determine the effect of photochemical oxidants on physiological activities of rice plants. Rice plants were fumigated with ozone at concentrations of 0.12-0.20 ppm for 2-3 hr to investigate acute injury and at 0.05 and 0.09 ppm for daily exposure from 3.0 leaf stage to assess the effect of ozone on growth. It was observed that malondialdehyde produced by disruption of the components of the membrane increased in the leaves exposed to ozone. Ozone reduced the RuBP-carboxylase activity in both young and old leaves 12-24 hr after fumigation. In the young leaves the activity of this enzyme recovered to some extent after 48 hr, but it did not show any recovery in the old leaves. On the other hand, ozone remarkably increased the peroxidase activity and slightly increased acid phosphatase in all leaves. Abnormally high ethylene evolution and oxygen uptake were detected in leaves soon after ozone fumigation. In general, high molecular protein and chlorophyll contents in the detached leaves decreased with incubation in dark, particularly in the old ones. These phenomena were more accelerated by ozone fumigation. Kinetin and benzimidazole showed significant effects on chlorophyll retention in ozone-exposed leaves. Reduction of plant growth and photosynthetic rate was recognized even in low concentration of ozone in daily exposure at 0.05 and 0.09 ppm. From these results it was postulated that ozone may cause the senescence of leaves in rice plants.

  15. Fractionation of hemicelluloses and lignin from rice straw by combining autohydrolysis and optimised mild organosolv delignification

    NARCIS (Netherlands)

    Moniz, Patrícia; Lino, João; Duarte, Luís C.; Roseiro, Luísa B.; Boeriu, Carmen G.; Pereira, Helena; Carvalheiro, Florbela

    2015-01-01

    An integrated strategy was followed to valorise rice straw, one of the most relevant biomass feedstocks available worldwide, to selectively recover solubilised hemicelluloses and lignin. The pathway encompassed the use of autohydrolysis to hydrolyse the hemicelluloses and an ethanol-based

  16. Rice as commodity and anti-commodity

    NARCIS (Netherlands)

    Richards, P.

    2016-01-01

    On the Upper West Africa coast rice belongs to two species — African rice (Oryza glaberrima Steud.) and Asian rice (Oryza sativa L.). African rice was domesticated in the region, perhaps three millennia ago, from a presumed wild ancestor, O. barthii. Asian rice was introduced via trans-Saharan

  17. Diseases of wild rice

    Science.gov (United States)

    Diseases are much more pronounced in cultivated wild rice than in natural stands, most likely due to the narrower genetic base of the populations, plant stress due to high planting density and floodwater removal prior to harvest, and high relative humidity in the plant canopy. Yield losses occur as ...

  18. Promising rice mutants

    International Nuclear Information System (INIS)

    Hakim, L.; Azam, M.A.; Miah, A.J.; Mansur, M.A.; Akanda, H.R.

    1988-01-01

    Two induced mutants namely, Mut NS 1 (tall) and Mut NS 5 (semi-dwarf) derived from rice variety Nizersail were evaluated for various agronomic characters at four locations in Bangladesh. Both the mutants matured about three weeks earlier and yielded significantly higher than the parent variety Nizersail. (author). 3 tabs., 9 refs

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. Investigating differences in light stable isotopes between Thai jasmine rice and Sungyod rice

    Science.gov (United States)

    Kukusamude, C.; Kongsri, S.

    2017-10-01

    We report the differences in light stable isotopes between two kinds of Thai rice (Thai jasmine and Sungyod rice). Thai jasmine rice and Sungyod rice were cultivated in the northeast and the south of Thailand. Light isotopes including 13C, 15N and 18O of Thai jasmine rice and Sungyod rice samples were carried out using isotope ratio mass spectrometry (IRMS). Thai jasmine rice (Khao Dawk Mali 105) was cultivated from Thung Kula Rong Hai area, whereas Sungyod rice was cultivated from Phathalung province. Hypothesis testing of difference of each isotope between Thai jasmine rice and Sungyod rice was also studied. The study was the feasibility test whether the light stable isotopes can be the variables to identify Thai jasmine rice and Sungyod rice. The result shows that there was difference in the isotope patterns of Thai jasmine rice and Sungyod rice. Our results may provide the useful information in term of stable isotope profiles of Thai rice.

  7. Separation of oil palm shell and kernel by using kaolinite media

    Directory of Open Access Journals (Sweden)

    Sukpong Sirinupong

    2003-05-01

    Full Text Available The objective of this research is to investigate the possibility of using kaolinite from Ranong province as media in the oil palm shell and kernel separation process by means of heavy media separation. The effect of specific gravity of the slurry, type and amount of dispersant and type of clays on suspension of media and efficiency of separation were studied. It was found that the specific gravity of oil palm shell and kernel are 1.40 and 1.20 respectively. While the average specific gravity of kaolinite grade MRD-B85, RANONG-325 and commercial clay from Univanich Group. PCL., are 2.54, 2.65 and 2.46 respectively. It was apparent that the viscosity of clay slurry increased with the specific gravity of the slurry. For MRD-B85 and RANONG- 325 clays which have the average particle sizes of 10 and 12 microns, the pH of their slurries of about 5.84 and 6.33 respectively were obtained and at these conditions stability of the slurry rarely occurred and they could not be used for separation. However, these clays can also be utilized as media when dispersant such asCalgon or sodium silicate is applied to their slurries. It was found that the efficiency of separation depends on specific gravity and viscosity of the slurry, type and particle size of kaolinite and dosage of dispersant. The optimum separating conditions for MRD-B85 clay were the dosage of Calgon of 0.15% (or 1.5 kg/t of clay at the specific gravity of the slurry of 1.20-1.24 (27-32% Solids in which a pH of 6.14 and viscosity of 104 cP to very low value (could not be measured were obtained. Thus, kernel yielded 97.57-100% and shell contamination of 1.48-6.32% was achieved. While sodium silicate was applied to the slurry about 0.15% at the specific gravity of 1.22, pH of 6.74 and viscosity of 238 cP were obtained and kernel could be recovered 100% with shell contamination of 8.36%. When 0.15% Calgon or 0.25% sodium silicate was introduced to the RANONG-325 clay slurry at the specific gravity

  8. Radiation disinfestation of Basmati rice

    International Nuclear Information System (INIS)

    Rao, V.S.; Gholap, A.S.; Adhikari, H.R.; Nair, P.M.

    1994-01-01

    Effect of low dose γ-radiation on prepackaged Basmati rice was studied in order to achieve disinfestation of rice. Basmati rice procured from local market was repacked in 1 kg pouches made from high density polyethylene (HDP) and biaxially oriented polypropylene: low density polyethylene (BOPP/LDP) laminate and irradiated at doses from 0.25-1.0 kGy. Within one month of storage at room temperature, unirradiated (control) Basmati rice developed heavy infestation. No infestation was observed in any of the irradiated samples even at 0.25 kGy and the rice could be stored for 6 months in a clean state. Irradiation (at 0.25 kGy) did not alter the moisture content of the rice. Likewise, no significant change was noted due to irradiation in the functional properties of rice such as swelling index and water absorption and in total volatile components responsible for flavour of Basmati rice. In organoleptic evaluation, no significant difference was found between the acceptability of irradiated (0.25 kGy) and control rice. These results are significant in view of the high export potential of Basmati rice and the transit losses at present due to infestation. (author). 24 refs., 5 tabs., 1 fig

  9. Recovering of images degraded by atmosphere

    Science.gov (United States)

    Lin, Guang; Feng, Huajun; Xu, Zhihai; Li, Qi; Chen, Yueting

    2017-08-01

    Remote sensing images are seriously degraded by multiple scattering and bad weather. Through the analysis of the radiative transfer procedure in atmosphere, an image atmospheric degradation model considering the influence of atmospheric absorption multiple scattering and non-uniform distribution is proposed in this paper. Based on the proposed model, a novel recovering method is presented to eliminate atmospheric degradation. Mean-shift image segmentation and block-wise deconvolution are used to reduce time cost, retaining a good result. The recovering results indicate that the proposed method can significantly remove atmospheric degradation and effectively improve contrast compared with other removal methods. The results also illustrate that our method is suitable for various degraded remote sensing, including images with large field of view (FOV), images taken in side-glance situations, image degraded by atmospheric non-uniform distribution and images with various forms of clouds.

  10. 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.

  11. 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.

  12. 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...

  13. 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.

  14. 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.

  15. 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...

  16. Method for recovering uranium from sea water

    International Nuclear Information System (INIS)

    Schwochau, K.; Astheimer, L.; Schenk, H.J.; Schmitz, J.

    1977-04-01

    In view of the augmenting uranium demand for energy supply and of the anticipated depletion of the actually assured and economic uranium resources the possibility of recovering uranium from sea water receives increasing attention. It is the purpose of the present report to give a detailed discussion of fundamental problems involved and a critical survey of hitherto proposed processes of recovery and to recommend some general directives for further work. (orig.) [de

  17. Recovering hydrocarbons with surfactants from lignin

    Energy Technology Data Exchange (ETDEWEB)

    Naae, D.G.; Whittington, L.E.; Ledoux, W.A.; Debons, F.E.

    1988-11-29

    This patent describes a method of recovering hydrocarbons from an underground hydrocarbon formation penetrated by at least one injection well and at least one production well, which comprises: injecting into the formation through an injection well a surfactant slug comprising about 0.1% to about 10% by weight of surfactants produced from lignin, the surfactants produced by placing lignin in contact with water, converting the lignin into low molecular weight lignin phenols by reducing the lignin in the presence of a reducing agent of carbon monoxide or hydrogen creating a reduction reaction mixture comprising oil soluble lignin phenols, the reduction occurring at a temperature greater than about 200/sup 0/C and a pressure greater than about 100 psi, recovering the oil soluble lignin phenols from the reduction mixture, and converting the lignin phenols into lignin surfactants by a reaction selected from the group consisting of alkoxylation, sulfonation, sulfation, aklylation, sulfomethylation, and alkoxysulfation; injecting into the formation through the injection well a drive fluid to push the surfactant slug towards a production well; and recovering hydrocarbons at the production well.

  18. 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.

  19. 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.

  20. Impact of Day Intervals on Sequential Infestations of the Rice Leaffolder (Guenée (Lepidoptera: Pyralidae and the White-Backed Rice Planthopper (Horváth on Rice Grain Damage

    Directory of Open Access Journals (Sweden)

    Li-Ben Jiang

    2014-01-01

    Full Text Available The present study illustrates that different day intervals (DIs between the sequential infestations of two pest species, the rice leaffolder (RLF Cnaphalocrocis medinalis Guenée (Lepidoptera: Pyralidae and the white-backed rice planthopper (WBPH Sogatella furcifera Horváth (Hemiptera: Delphacidae, have a significant impact on the rice yield loss rate (YLR and on the carbohydrate contents of rice plants. For WBPH release after RLF release (WRARR, the YLR decreased with the increasing DIs, and the YLR at the 24 DI was significantly lower compared to that at the 6 and 12 DIs and had a minimum value for a simultaneous infestation of the two pest species (SITS. In contrast, for RLF release after WBPH release (RRAWR, the YLR at the 24 DI had a maximum value and was significantly higher compared to that at the 6 and 12 DIs and the SITS. These findings indicate that damaged rice plants gradually recover, with an increase in the DI for WRARR. The above results were demonstrated by biochemical tests. Therefore, the sequential infestation of the two pest species and their DIs should be considered for integrated pest management (IPM and control strategies for rice pests.

  1. 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

  2. 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

  3. Study of Rice Marketing System in Iran

    OpenAIRE

    Feizabadi, Yaser

    2011-01-01

    Rice comes second after wheat in Iran`s food consumption economy. Rising population and recent growth in GDP has made Iran one of the greatest rice importer countries all over the world. That is why rice marketing has always been a controversial issue in Iran`s agricultural economics. To study rice marketing system in Iran, this paper aims to calculate rice marketing margin, market efficiency and marketing cost coefficient in seaside Mazandaran province( where 70 percent of domestic rice prod...

  4. 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.

  5. 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.

  6. 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.

  7. 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

  8. 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

  9. 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...

  10. Milling, Nutritional, Physical and Cooking Properties of Four Basmati Rice Varieties

    Directory of Open Access Journals (Sweden)

    Pravin Ojha

    2018-05-01

    Full Text Available Rice is one of the most popular staple foods produced contributing higher most in agriculture gross domestic production in Nepal. Thus, nutritional, physicochemical, and cooking properties of rice might interplay important roles in their production and farming practice, therefore, it is inevitable to understand these characteristic features. However, there has been only limited information available on such properties, therefore we aimed to examine nutritional, physicochemical and cooking properties of four Basmati varieties of rice namely Red Basmati, White Basmati, Black Basmati and Pokhareli Basmati. These rice varieties were purchased from different places in Nepal in paddy form. In this study various parameters associated with milling, nutritional, physical and cooking properties were evaluated. To measure protein contents in rice, Kjeldal method was implied. Among the varieties, the protein content was maximum in Red Basmati (7.74% and minimum in Black Basmati (6.51%. The milled rice percentage and head rice recovery were maximum in Pokhareli Basmati represented by 72.02±0.10 and 67.46±0.42, respectively, while and minimum in White Basmati represented by 68.17±0.50 and 65.11±0.28, respectively. The kernel elongation ratio and volume expansion ratio was maximum in Red Basmati represented by 1.62 and 2.85 respectively. Water uptake ratio was maximum 3.11 in Black Basmati and minimum of 2.18 in Red Basmati. Gruel loss was found lowest 1.05% in Red Basmati and highest represented by 2.40% in Black Basmati. The highest starch iodine blue value of 0.21 was observed in Red Basmati and lowest of 0.12 in Black Basmati. The Red Basmati was found to have the better cooking quality among all varieties.

  11. 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

  12. 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...

  13. 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...

  14. 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

  15. 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

  16. 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

  17. Nicaragua - Rice and Banana Farmers

    Data.gov (United States)

    Millennium Challenge Corporation — This report is an impact evaluation of two components of the Rural Business Development Program (RBD) in Nicaragua, specifically the components benefitting rice and...

  18. 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.

  19. 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.

  20. 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.

  1. Sorghum and rice: Mali

    International Nuclear Information System (INIS)

    2003-01-01

    Agriculture is the mainstay of the Malian economy and yet cereal imports absorb 6.5% of GDP. Food self-sufficiency is therefore a national priority. The Joint FAO/IAEA Division is supporting a programme to improve local varieties of sorghum and rice by using nuclear techniques to develop new cultivars that will produce higher yields under Mali's semi-arid climatic conditions. (IAEA)

  2. An Ensemble Approach to Building Mercer Kernels with Prior Information

    Science.gov (United States)

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

    2005-01-01

    This paper presents a new methodology for automatic knowledge driven data mining based on the theory of Mercer Kernels, which are highly nonlinear symmetric positive definite mappings from the original image space to a very high, possibly dimensional feature space. we describe a new method called Mixture Density Mercer Kernels to learn kernel function directly from data, rather than using pre-defined kernels. These data adaptive kernels can encode prior knowledge in the kernel using a Bayesian formulation, thus allowing for physical information to be encoded in the model. Specifically, we demonstrate the use of the algorithm in situations with extremely small samples of data. We compare the results with existing algorithms on data from the Sloan Digital Sky Survey (SDSS) and demonstrate the method's superior performance against standard methods. The code for these experiments has been generated with the AUTOBAYES tool, which automatically generates efficient and documented C/C++ code from abstract statistical model specifications. The core of the system is a schema library which contains templates for learning and knowledge discovery algorithms like different versions of EM, or numeric optimization methods like conjugate gradient methods. The template instantiation is supported by symbolic-algebraic computations, which allows AUTOBAYES to find closed-form solutions and, where possible, to integrate them into the code.

  3. 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.

  4. 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.

  5. 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.

  6. 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

  7. 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.

  8. Diversity of some endophytic fungi associated with rice black bug Paraeucosmetus pallicornis on rice plant

    OpenAIRE

    Nur, Amin; La Daha; Nurariaty, Agus; Ade, Rosmana; Muh., Fadlan

    2015-01-01

    A new rice insect pest was sighted in some rice producing areas of South Sulawesi Province, Indonesia. This pest is rice black bugs Paraeucosmetus pallicornis. The research aimed to isolation of fungi associated with rice black bugs Paraeucosmetus pallicornis, so as to know the cause of a bitter taste to the rice. The isolation of the fungi consist of three kinds of treatment, namely rice black bugs without sterilization, with sterilization and rice black bugs cut and sterilized. The resul...

  9. Combination of mass spectrometry-based targeted lipidomics and supervised machine learning algorithms in detecting adulterated admixtures of white rice.

    Science.gov (United States)

    Lim, Dong Kyu; Long, Nguyen Phuoc; Mo, Changyeun; Dong, Ziyuan; Cui, Lingmei; Kim, Giyoung; Kwon, Sung Won

    2017-10-01

    The mixing of extraneous ingredients with original products is a common adulteration practice in food and herbal medicines. In particular, authenticity of white rice and its corresponding blended products has become a key issue in food industry. Accordingly, our current study aimed to develop and evaluate a novel discrimination method by combining targeted lipidomics with powerful supervised learning methods, and eventually introduce a platform to verify the authenticity of white rice. A total of 30 cultivars were collected, and 330 representative samples of white rice from Korea and China as well as seven mixing ratios were examined. Random forests (RF), support vector machines (SVM) with a radial basis function kernel, C5.0, model averaged neural network, and k-nearest neighbor classifiers were used for the classification. We achieved desired results, and the classifiers effectively differentiated white rice from Korea to blended samples with high prediction accuracy for the contamination ratio as low as five percent. In addition, RF and SVM classifiers were generally superior to and more robust than the other techniques. Our approach demonstrated that the relative differences in lysoGPLs can be successfully utilized to detect the adulterated mixing of white rice originating from different countries. In conclusion, the present study introduces a novel and high-throughput platform that can be applied to authenticate adulterated admixtures from original white rice samples. Copyright © 2017 Elsevier Ltd. All rights reserved.

  10. Recovering a hidden polarization by ghost polarimetry.

    Science.gov (United States)

    Janassek, Patrick; Blumenstein, Sébastien; Elsäßer, Wolfgang

    2018-02-15

    By exploiting polarization correlations of light from a broadband fiber-based amplified spontaneous emission source we succeed in reconstructing a hidden polarization in a ghost polarimetry experiment in close analogy to ghost imaging and ghost spectroscopy. Thereby, an original linear polarization state in the object arm of a Mach-Zehnder interferometer configuration which has been camouflaged by a subsequent depolarizer is recovered by correlating it with light from a reference beam. The variation of a linear polarizer placed inside the reference beam results in a Malus law type second-order intensity correlation with high contrast, thus measuring a ghost polarigram.

  11. Recovering valuable metals from recycled photovoltaic modules.

    Science.gov (United States)

    Yi, Youn Kyu; Kim, Hyun Soo; Tran, Tam; Hong, Sung Kil; Kim, Myong Jun

    2014-07-01

    Recovering valuable metals such as Si, Ag, Cu, and Al has become a pressing issue as end-of-life photovoltaic modules need to be recycled in the near future to meet legislative requirements in most countries. Of major interest is the recovery and recycling of high-purity silicon (> 99.9%) for the production of wafers and semiconductors. The value of Si in crystalline-type photovoltaic modules is estimated to be -$95/kW at the 2012 metal price. At the current installed capacity of 30 GW/yr, the metal value in the PV modules represents valuable resources that should be recovered in the future. The recycling of end-of-life photovoltaic modules would supply > 88,000 and 207,000 tpa Si by 2040 and 2050, respectively. This represents more than 50% of the required Si for module fabrication. Experimental testwork on crystalline Si modules could recover a > 99.98%-grade Si product by HNO3/NaOH leaching to remove Al, Ag, and Ti and other metal ions from the doped Si. A further pyrometallurgical smelting at 1520 degrees C using CaO-CaF2-SiO2 slag mixture to scavenge the residual metals after acid leaching could finally produce > 99.998%-grade Si. A process based on HNO3/NaOH leaching and subsequent smelting is proposed for recycling Si from rejected or recycled photovoltaic modules. Implications: The photovoltaic industry is considering options of recycling PV modules to recover metals such as Si, Ag, Cu, Al, and others used in the manufacturing of the PV cells. This is to retain its "green" image and to comply with current legislations in several countries. An evaluation of potential resources made available from PV wastes and the technologies used for processing these materials is therefore of significant importance to the industry. Of interest are the costs of processing and the potential revenues gained from recycling, which should determine the viability of economic recycling of PV modules in the future.

  12. Process and system for recovering energy

    International Nuclear Information System (INIS)

    Trichet, J.-C.

    1975-01-01

    The invention concerns a system for heating a room or similar, using a 'dibare' cycle working with a less volatile fluid and a more volatile fluid and employing a coupling between a fractionated separation area working at high pressure and a fractionated mixing zone working at low pressure. The invention relates to the following uses: heating a room or building, drying any material and recovering the thermal discharge from a motive cycle, particularly the recovery of the thermal discharge of an electric nuclear power station to carry out district heating [fr

  13. Apparatus for recovering oil from Posidonien shale

    Energy Technology Data Exchange (ETDEWEB)

    1920-04-13

    Equipment for recovering oil from shale and the like, as well as the distilling of coal is characterized in that a number of chambers provided in a known way with upper and lower air supply are arranged open to the receiver of the oil vapors through removable domes which can be attached to the usual oil-vapor carry-off. Arrangement is characterized in that the domes are movable to the side, so that they can be interchangeably attached to the different chambers.

  14. Process for recovering cesium from cesium alum

    International Nuclear Information System (INIS)

    Mein, P.G.

    1984-01-01

    Cesium is recovered from cesium alum, CsAl(SO 4 ) 2 , by an aqueous conversion and precipitation reaction using a critical stoichiometric excess of a water-soluble permanganate to form solid cesium permanganate (CsMnO 4 ) free from cesium alum. The other metal salts remain in solution, providing the final pH does not cause hydroxides of aluminium or iron to form. The precipitate is separated from the residual solution to obtain CsMnO 4 of high purity

  15. Recovering an obstacle using integral equations

    KAUST Repository

    Rundell, William

    2009-05-01

    We consider the inverse problem of recovering the shape, location and surface properties of an object where the surrounding medium is both conductive and homogeneous and we measure Cauchy data on an accessible part of the exterior boundary. It is assumed that the physical situation is modelled by harmonic functions and the boundary condition on the obstacle is one of Dirichlet type. The purpose of this paper is to answer some of the questions raised in a recent paper that introduced a nonlinear integral equation approach for the solution of this type of problem.

  16. Long-term storage of recovered krypton

    International Nuclear Information System (INIS)

    Horii, Yuji; Yamamoto, Yoshimasa

    1983-01-01

    Various storage methods for krypton-85 recovered from a nuclear fuel reprocessing plant are under development in many countries. These methods include:(1) direct storage in pressurized cylinders, (2) storage of krypton adsorbed on charcoal or zeolite in pressurized cylinders and (3) immobilization (encapsulation) in zeolite. A krypton storage facility using pressurized cylinders has been constructed in the krypton recovery pilot plant in Tokaimura and other methods are now under development. These three methods are evaluated and the features of the constructed facility are also reported. (author)

  17. Recovering the fine structures in solar images

    Science.gov (United States)

    Karovska, Margarita; Habbal, S. R.; Golub, L.; Deluca, E.; Hudson, Hugh S.

    1994-01-01

    Several examples of the capability of the blind iterative deconvolution (BID) technique to recover the real point spread function, when limited a priori information is available about its characteristics. To demonstrate the potential of image post-processing for probing the fine scale and temporal variability of the solar atmosphere, the BID technique is applied to different samples of solar observations from space. The BID technique was originally proposed for correction of the effects of atmospheric turbulence on optical images. The processed images provide a detailed view of the spatial structure of the solar atmosphere at different heights in regions with different large-scale magnetic field structures.

  18. The Haitian Rice Tariff

    Directory of Open Access Journals (Sweden)

    Mats Lundahl

    2016-04-01

    Full Text Available Se ha argumentado que los problemas agríco-las de Haití derivan de la tarifa del arroz de a mediados de los años noventa. Antes, supues-tamente, Haití fue autosuficiente, abastecida por su producción doméstica. Después de la reducción, el mercado haitiano se inundó en importaciones de arroz barato de los EEUU, lo cual despojó a los campesinos de sus fincas, convirtiendolos en migrantes internos, hacia los empleos de bajo pago de las ciudades. El artículo rechaza ese argumento y demuestra que es falso. La malnutrición fue un fenómeno extendido en Haití mucho antes de la reducción de la tarifa del arroz, la cual tampoco tuvo un gran impacto en la importación y la producción doméstica del arroz. Lo que sí impulsó el aumento de las importaciones fue el crecimiento de la población. También el artículo argumenta que un aumento de la tarifa del arroz no solucionará el problema de la alimentación que sufre Haití. English: It has been argued that Haiti’s agricultural problems derive from the reduction of the rice tariff in the mid-1990s. Before that Haiti was allegedly able to meet its food needs by domestic production. After the reduction the Haitian market was swamped by imports of cheap American rice which drove the farmers off their lands and forced them to migrate to low-wage industrial jobs in the cities. The article demonstrates that the argument is false. Malnutrition was widespread in Haiti long before the rice tariff reduction, and the latter did not have much of an impact on rice imports and domestic production. Instead, the main driving force behind imports appears to be population growth. It is also shown that an increase of the rice tariff will not solve Haiti’s food problem.

  19. Five years post whiplash injury: Symptoms and psychological factors in recovered versus non-recovered

    Directory of Open Access Journals (Sweden)

    Stålnacke Britt-Marie

    2010-07-01

    Full Text Available Abstract Background Few studies have focused on the differences between persons who are recovered after whiplash injury and those who suffer from persistent disability. The primary aim of this study was therefore to examine differences in symptoms, psychological factors and life satisfaction between subjects classified as recovered and those with persistent disability five years after whiplash injury based on the Neck Disability Index (NDI. Methods A set of questionnaires was answered by 158 persons (75 men, 83 women to assess disability (NDI, pain intensity (VAS, whiplash-related symptoms (Rivermead Post-Concussion Symptoms Questionnaire, RPQ, post-traumatic stress (Impact of Event Scale, IES, depression (Beck's depression inventory, BDI and life satisfaction (LiSat-11. The participants were divided into three groups based on the results of the NDI: recovered (34.8%, mild disability (37.3% and moderate/severe disability (27.3%. Results The moderate/severe group reported significantly higher VAS, BDI and IES scores and lower level of physical health and psychological health compared to the mild and the recovered groups. Less significant differences were reported between the mild and the recovered groups. Conclusions The group with the highest disability score reported most health problems with pain, symptoms, depression, post-traumatic stress and decreased life satisfaction. These findings indicate that classifying these subjects into subgroups based on disability levels makes it possible to optimize the management and treatment after whiplash injury.

  20. Nutritional test of rice in rats

    International Nuclear Information System (INIS)

    Horii, Masaji; Yoshikawa, Seiji

    1980-01-01

    Behaviors on N derived from rice were followed up by means of 15 N-labeled rice. In the first test, the single unpolished rice diet and the diet of rice and bean lecithin (4.5%) produced urinary excretion of 10 - 12% of 15 N, and that of rice and mannan from devil's tongue (3%), 16 - 20%. The single unpolished rice diet showed slightly more urinary excretion of 15 N, and the other 2 diets showed a similar proportion of 15 N in 3 days. The results indicated that the diet containing mannan from devil's tongue resulted in a poor N absorption by rice, a large quantity of N being excreted over a long period of time. This suggested differences and time lags in the excretion of rice N into the stool and urine depending on the diet constitution. With the unpolished rice diet, a small quantity of rice protein was not absorbed, but was excreted. In the 2nd test with 15 N-polished rice, the urinary excretion rate was 11.44% for a single rice diet, 11.16% for a mixed diet of rice and bean (1:1 in protein), 10.99% for rice and egg yolk, 9.66% for rice, bean and egg yolk and 8.10% for rice and bean lecithin. This decrease in urinary excretion indicated a corresponding increase in absorption of rice protein. (Chiba, N.)

  1. PROCESS OF RECOVERING URANIUM FROM ITS ORES

    Science.gov (United States)

    Galvanek, P. Jr.

    1959-02-24

    A process is presented for recovering uranium from its ores. The crushed ore is mixed with 5 to 10% of sulfuric acid and added water to about 5 to 30% of the weight of the ore. This pugged material is cured for 2 to 3 hours at 100 to 110 deg C and then cooled. The cooled mass is nitrate-conditioned by mixing with a solution equivalent to 35 pounds of ammunium nitrate and 300 pounds of water per ton of ore. The resulting pulp containing 70% or more solids is treated by upflow percolation with a 5% solution of tributyl phosphate in kerosene at a rate equivalent to a residence time of about one hour to extract the solubilized uranium. The uranium is recovered from the pregnant organic liquid by counter-current washing with water. The organic extractant may be recycled. The uranium is removed from the water solution by treating with ammonia to precipitate ammonium diuranate. The filtrate from the last step may be recycled for the nitrate-conditioning treatment.

  2. Recovering energy and materials from hazardous waste

    Energy Technology Data Exchange (ETDEWEB)

    Anon.

    2003-12-01

    The tannery industry faces growing environmental concerns because of the high hazardous metal content of its process waste. The formation, during the tanning process, of the highly toxic hexavalent chromium precludes the use of conventional thermal incineration processes. Borge Tannery in Norway, which processes 600 cattle hides per day, has solved the problem by using new PyroArc technology. The PyroArc waste processing plant can treat all of the tannery's production wastes, transforming them into useful products such as fuel gas and re-usable metal. The fuel gas consists mainly of carbon monoxide, hydrogen and nitrogen, and has a calorific value of about 4 MJ/Nm{sub 3}. About 65-70% of the energy content of the source material (waste or biomass) is recovered in the gas, and this is used to produce steam and/or electricity in a gas engine with a capacity of 580 kW. A further 20-25% of the initial energy content is recovered as heat or low-pressure steam. The plant is designed to be self-sufficient in energy (1.5 MW) and to meet the tannery's maximum requirements for hot water and steam. (UK)

  3. Recovering method for high level radioactive material

    International Nuclear Information System (INIS)

    Fukui, Toshiki

    1998-01-01

    Offgas filters such as of nuclear fuel reprocessing facilities and waste control facilities are burnt, and the burnt ash is melted by heating, and then the molten ashes are brought into contact with a molten metal having a low boiling point to transfer the high level radioactive materials in the molten ash to the molten metal. Then, only the molten metal is evaporated and solidified by drying, and residual high level radioactive materials are recovered. According to this method, the high level radioactive materials in the molten ashes are transferred to the molten metal and separated by the difference of the distribution rate of the molten ash and the molten metal. Subsequently, the molten metal to which the high level radioactive materials are transferred is heated to a temperature higher than the boiling point so that only the molten metal is evaporated and dried to be removed, and residual high level radioactive materials are recovered easily. On the other hand, the molten ash from which the high level radioactive material is removed can be discarded as ordinary industrial wastes as they are. (T.M.)

  4. When will the Antarctic Ozone Hole Recover?

    Science.gov (United States)

    Newman, Paul A.; Nash, Eric R.; Kawa, S. Randolph; Montzka, Steve

    2006-01-01

    The Antarctic ozone hole develops each year and culminates by early Spring. Antarctic ozone values have been monitored since 1979 using satellite observations from the .TOMS instrument. The severity of the hole has been assessed from TOMS using the minimum total ozone value from the October monthly mean (depth of the hole) and by calculating the average size during the September-October period. Ozone is mainly destroyed by halogen catalytic cycles, and these losses are modulated by temperature variations in the collar of the polar lower stratospheric vortex. In this presentation, we show the relationships of halogens and temperature to, both the size and depth of the hole. Because atmospheric halogen levels are responding to international agreements that limit or phase out production, the amount of halogens in the stratosphere should decrease over the next few decades. Using projections of halogen levels combined with age-of-air estimates, we find that the ozone hole is recovering at an extremely slow rate and that large ozone holes will regularly recur over the next 2 decades. The ozone hole will begin to show first signs of recovery in about 2023, and the hole will fully recover to pre-1980 levels in approximately 2070. This 2070 recovery is 20 years later than recent projections.

  5. 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

  6. 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...

  7. Effects of Feeding Purple Rice ( L. Var. Glutinosa on the Quality of Pork and Pork Products

    Directory of Open Access Journals (Sweden)

    Sanchai Jaturasitha

    2016-04-01

    Full Text Available Purple rice is a strain of glutaneous rice rich in anthocyanins and γ-oryzanol. Both types of compounds are involved in antioxidant and lipid metabolism of mammals. Three experimental diet types were used which consisted approximately by half either of purple rice, white rice or corn. Diets were fed to 3×10 pigs growing from about 30 to 100 kg. Meat samples were investigated either as raw or cured loin chops or as smoked bacon produced from the belly. Various physicochemical traits were assessed and data were evaluated by analysis of variance. Traits describing water-holding capacity (drip, thaw, and cooking losses and tenderness (sensory grading, shear force of the meat were mostly not significantly affected by the diet type. However, purple rice feeding of pigs resulted in lower fat and cholesterol contents of loin and smoked bacon compared to white rice, but not compared to corn feeding except of the fat content of the loin. The shelf life of the raw loin chops was improved by purple rice as well. In detail, the occurrence of thiobarbituric acid reactive substances after 9 days of chilled storage was three to four times higher in the white rice and corn diets than with purple rice. The n-6:n-3 ratio in the raw loin chops was 9:1 with purple rice and clearly higher with 12:1 with the other diets, meat lipids. Level and kind of effect of purple rice found in raw meat was not always recovered in the cured loin chops and the smoked bacon. Still the impression of flavor and color, as well as overall acceptability were best in the smoked bacon from the purple-rice fed pigs, whereas this effect did not occur in the cured loin chops. These findings suggest that purple rice has a certain, useful, bioactivity in pigs concerning meat quality, but some of these effects are of low practical relevance. Further studies have to show ways how transiency and low recovery in meat products of some of the effects can be counteracted.

  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. Identification of genetic loci underlying the kernel fissure-resistance exhibited by 'cypress' and 'saber'

    Science.gov (United States)

    The economic value of broken rice is about half that of whole milled rice, so one goal of producers, millers, and rice breeders is to reduce broken grains that result from the dehusking and milling processes One of the primary causes of rice breakage is fissuring, or cracking, of the rice before it ...

  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. Recovering heat from waste air from stables

    Energy Technology Data Exchange (ETDEWEB)

    1983-01-01

    A milk cow gives off 35.7 kW h/d via its body, excreta and urine. 68.4% of this is body heat. Part of this waste heat escapes with the waste air from the cowsheds. The heat can be recovered from the waste air by an air/air heat exchanger. The air is collected and taken to a heat exchanger. In the heat exchanger, fresh air is heated by the waste air, and is distributed over the cowshed by a system of ducts. The heated waste air escapes through a central chimney at the end of the heat exchanger. It is sensible to fit the heat exchanger above the cowshed roof, if there is sufficient space available and the chimney should run upwards from the cowshed. A double heat exchanger makes it possible to allocate each half of the cowshed to half of the heat exchanger.

  15. Process for recovering cesium from cesium alum

    International Nuclear Information System (INIS)

    Mein, P.G.

    1984-01-01

    Cesium is recovered from cesium alum, CsAl(SO 4 ) 2 , by a two-reaction sequence in which the cesium alum is first dissolved in an aqueous hydroxide solution to form cesium alum hydroxide, CsAl(OH) 3 , and potassium sulfate, K 2 SO 4 . Part of the K 2 SO 4 precipitates and is separated from the supernatant solution. In the second reaction, a water-soluble permanganate, such as potassium permanganate, KMnO 4 , is added to the supernatant. This reaction forms a precipitate of cesium permanganate, CsMnO 4 . This precipitate may be separated from the residual solution to obtain cesium permanganate of high purity, which can be sold as a product or converted into other cesium compounds

  16. Process for recovering cesium from pollucite

    International Nuclear Information System (INIS)

    Mein, P.G.

    1985-01-01

    Cesium is recovered from a cesium-bearing mineral such as pollucite by extraction with hydrochloric acid to obtain an extract of cesium chloride and other alkali metal and polyvalent metal chlorides. The iron and aluminum chlorides can be precipitated as the hydroxides and separated from the solution of the alkali metal chlorides to which is added potassium permanganate or other water-soluble permanganate to selectively precipitate cesium permanganate. The cesium precipitate is then separated from the residual solution containing the metal chlorides. The cesium permanganate, which is in a very pure form, can be converted to other cesium compounds by reaction with a reducing agent to obtain cesium carbonate and cesium delta manganese dioxide

  17. 21 CFR 137.350 - Enriched rice.

    Science.gov (United States)

    2010-04-01

    ... 21 Food and Drugs 2 2010-04-01 2010-04-01 false Enriched rice. 137.350 Section 137.350 Food and... Related Products § 137.350 Enriched rice. (a) The foods for which definitions and standards of identity are prescribed by this section are forms of milled rice (except rice coated with talc and glucose and...

  18. Evaluation of the antioxidant activity of rice bran extracts using different antioxidant assays

    Directory of Open Access Journals (Sweden)

    Rehman Bajwa, Jawad -ur-

    2006-09-01

    Full Text Available In the present work the antioxidant activity of different solvent (100% methanol, 80% methanol, 100% acetone, 80% acetone extracts of rice bran was evaluated following different antioxidant assays and using sunflower oil as oxidation substrate. The rice bran extracts were evaluated from the estimate of % inhibition of peroxidation in linoleic acid system, total phenolics content (TPC and loss of β-carotene in a linoleic acid system. Additionally, crude concentrated rice bran extracts were added into the sunflower oil samples and stored under ambient conditions. The extent of oxidative deterioration was followed by the measurement of peroxide-, p-anisidine-, conjugated diene-, and triene- values. The general order of antioxidant efficacy of rice bran extracts as determined by various antioxidant assays was 80% methanolic extract > 100% methanolic  extract > 80% acetone extract > 100% acetone extract. The results of the present comprehensive analysis demonstrate that rice bran extracts of the Super Kernel variety indigenous to Pakistan are a viable source of natural antioxidants and might be exploited for functional foods and nutraceutical applications.Se evalúa la actividad antioxidante diferentes extractos (100% metanol, 80% metanol, 100% acetona and 80% acetona de salvado de arroz -var. Super Kernel- mediante diferentes ensayos y utilizando aceite de girasol como substrato. Los ensayos utilizados fueron la estimación del % de inhibición de la peroxidación en sistemas con ácido linoleico, el contenido total en compuestos fenólicos y la pérdida de β-caroteno en sistemas con ácido linoleico. Adicionalmente, los concentrados de extractos de salvado de arroz se añadieron a aceite de girasol y las muestras se almacenaron a temperatura ambiente. La extensión de la oxidación se evaluó mediante el índice de peróxidos, el índice de p-anisidina, así como la formación de dienos y trienos conjugados. El orden de la eficacia antioxidante

  19. 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.

  20. 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.

  1. 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.

  2. 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)

  3. 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

  4. 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.

  5. 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.

  6. Biodiesel from “Morelos” Rice: Synthesis, Oxidative Stability, and Corrosivity

    Directory of Open Access Journals (Sweden)

    J. Zuñiga-Díaz

    2018-01-01

    Full Text Available Rice bran is a by-product of great production worldwide and its use for the synthesis of biodiesel does not affect the food chain and therefore it is an excellent alternative for the production of biofuels with low carbon footprint. In this work, the synthesis of biodiesel was carried out from the raw rice bran oil of a kernel variety called “Morelos rice.” The stability and corrosivity characteristics of biodiesel were determined. Biodiesel stability was determined both under storage conditions and under accelerated oxidation conditions, and its corrosivity was evaluated by electrochemical impedance spectroscopy at 110°C under aerated conditions. The results showed that, due to the high instability of the rice bran, its raw oil had a high content of free fatty acids. The synthesized biodiesel showed excellent stability under storage conditions of up to five months, and its oxidative stability was much higher than that established in international standards. On the other hand, biodiesel showed low corrosivity and this was only significant once oxidative degradation began.

  7. Membrane separation and characterisation of lignin and its derived products obtained by a mild ethanol organosolv treatment of rice straw

    NARCIS (Netherlands)

    Moniz, Patrícia; Serralheiro, Cláudia; Matos, Cristina T.; Boeriu, Carmen G.; Frissen, Augustinus E.; Duarte, Luís C.; Roseiro, Luísa B.; Pereira, Helena; Carvalheiro, Florbela

    2018-01-01

    An organosolv process using ethanol-water was optimized in order to recover high quality lignin from rice-straw previously pre-treated by autohydrolysis at 210 °C. The results showed a selective and appreciable removal of lignin under very mild conditions and the highest delignification yield

  8. 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.

  9. 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....

  10. 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.

  11. 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.

  12. 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.

  13. Asian wild rice is a hybrid swarm with extensive gene flow and feralization from domesticated rice

    OpenAIRE

    Wang, Hongru; Garrett Vieira, Filipe Jorge; Crawford, Jacob E.; Chu, Chengcai; Nielsen, Rasmus

    2017-01-01

    The domestication history of rice remains controversial, with multiple studies reaching different conclusions regarding its origin(s). These studies have generally assumed that populations of living wild rice, O. rufipogon, are descendants of the ancestral population that gave rise to domesticated rice, but relatively little attention has been paid to the origins and history of wild rice itself. Here, we investigate the genetic ancestry of wild rice by analyzing a diverse panel of rice genome...

  14. 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.

  15. 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

  16. Zinc fertilization of flooded rice

    International Nuclear Information System (INIS)

    1981-02-01

    Local scientists studied Zn fertilization of flooded rice soils in Bangladesh, India, Indonesia, the Republic of Korea, Egypt, the Philippines, Thailand and Turkey. Diagnosis of Zn deficiency was carried out for submerged rice soils. Soil maps were prepared, designating areas as low, medium and high in Zn, based on Zn extraction with DTPA and HCl solutions and on rice leaf analysis. The effectiveness of various Zn fertilizer sources and methods of application in field and greenhouse experiments was measured, using 65 Zn. The percent Zn derived from fertilizer was shown to be a much more sensitive measure of efficiency than yield or total uptake

  17. 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.

  18. 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

  19. 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

  20. 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.

  1. 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.

  2. 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.

  3. 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...

  4. 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...

  5. Self-Recovering Sensor-Actor Networks

    Directory of Open Access Journals (Sweden)

    Maryam Kamali

    2010-07-01

    Full Text Available Wireless sensor-actor networks are a recent development of wireless networks where both ordinary sensor nodes and more sophisticated and powerful nodes, called actors, are present. In this paper we formalize a recently introduced algorithm that recovers failed actor communication links via the existing sensor infrastructure. We prove via refinement that the recovery is terminating in a finite number of steps and is distributed, thus self-performed by the actors. Most importantly, we prove that the recovery can be done at different levels, via different types of links, such as direct actor links or indirect links between the actors, in the latter case reusing the wireless infrastructure of sensors. This leads to identifying coordination classes, e.g., for delegating the most security sensitive coordination to the direct actor-actor coordination links, the least real-time constrained coordination to indirect links, and the safety critical coordination to both direct actor links and indirect sensor paths between actors. Our formalization is done using the theorem prover in the RODIN platform.

  6. Method for chromatographically recovering scandium and yttrium

    International Nuclear Information System (INIS)

    Snyder, T.S.; Stoltz, R.A.

    1991-01-01

    This paper describes a method for chromatographically recovering scandium and yttrium from the residue of a sand chlorinator. It comprises: providing a residue from a sand chlorinator, the residue containing scandium, yttrium, sodium, calcium and at least one radioactive metal of the group consisting of radium, thorium and uranium; digesting the residue with an acid to produce an aqueous liquid containing scandium, yttrium, sodium, calcium and at least one radioactive metal of the group consisting of radium, thorium and uranium; feeding the metal containing liquid through a cation exchanger; eluding the cation exchanger with an acid eluant to to produce: a first eluate containing at least half of the total weight of the calcium and sodium in the feed liquid; a second eluate containing at least half of the total weight of the one or more radioactive metals in the feed liquid; a third eluate containing at least half of the yttrium in the feed liquid, and a fourth eluate containing at least half of the weight of the scandium in the feed liquid

  7. Small Sized Drone Fall Recover Mechanism Design

    Science.gov (United States)

    LIU, Tzu-Heng; CHAO, Fang-Lin; LIOU, Jhen-Yuan

    2017-12-01

    Drones uses four motors to rotate clockwise, counter-clockwise, or change in rotational speed to change its status of motion. The problem of Unmanned Aerial Vehicle turnover causes personal loses and harm local environment. Designs of devices that can let falling drones recover are discussed. The models attempt to change the orientation, so that the drone may be able to improve to the point where it can take off again. The design flow included looking for functional elements, using simplify model to estimate primary functional characteristics, and find the appropriate design parameters. For reducing the complexity, we adopted the simple rotate mechanism with rotating arms to change the fuselage angle and reduce the dependence on the extra-components. A rough model was built to verify structure, and then the concept drawing and prototype were constructed. We made the prototype through the integration of mechanical part and the electronic control circuit. The electronic control module that selected is Arduino-mini pro. Through the Bluetooth modules, user can start the rebound mechanism by the motor control signal. Protections frames are added around each propeller to improve the body rotate problem. Limited by current size of Arduino module, motor and rebound mechanism make the main chassis more massive than the commercial product. However, built-in sensor and circuit miniaturization will improve it in future.

  8. 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.

  9. 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 (...

  10. 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.

  11. Rice vaikib salavanglaist / Tõnis Erilaid

    Index Scriptorium Estoniae

    Erilaid, Tõnis, 1943-

    2005-01-01

    Euroopasse visiidile sõitev USA välisminister Condoleezza Rice külastab Saksamaad, Rumeeniat, Ukrainat ja Belgiat. Süüdistusi CIA lennukite maandumiste ja salavanglate kohta ei olevat tal kavas kommenteerida

  12. Red Yeast Rice: An Introduction

    Science.gov (United States)

    ... rice are used in food products in Chinese cuisine, including Peking duck. Others have been sold as ... Medicine . 2010;170(19):1722–1727. Halbert SC, French B, Gordon RY, et al. Tolerability of red ...

  13. indica rice (Oryza sativa L.)

    African Journals Online (AJOL)

    Jane

    2011-07-18

    Jul 18, 2011 ... fresh weight, regeneration, proline level and total protein content in salt sensitive indica rice cv. IR 64. For callus ... INTRODUCTION. Salinity is one of the ... Proline is reported to reduce the enzyme denaturation caused due.

  14. 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)

  15. Mutant heterosis in rice

    International Nuclear Information System (INIS)

    1987-01-01

    In the variety TKM6 a high yielding semidwarf mutant has been induced. This TKM6 mutant was used in test crosses with a number of other varieties and mutants to examine the extent of heterosis of dwarfs in rice and to select superior crosses. An excerpt of the published data is given. It appears from the backcross of the mutant with its original variety, that an increase in number of productive tillers occurs in the hybrid, leading to a striking grain yield increase, while the semi-dwarf culm length (the main mutant character) reverts to the normal phenotype. In the cross with IR8 on the other hand, there is only a minimal increase in tiller number but a substantial increase in TGW leading to more than 30% yield increase over the better parent

  16. Characterization of isolates of meloidogyne from rice-wheat production fields in Nepal.

    Science.gov (United States)

    Pokharel, Ramesh R; Abawi, George S; Zhang, Ning; Duxbury, John M; Smart, Christine D

    2007-09-01

    Thirty-three isolates of root-knot nematode were recovered from soil samples from rice-wheat fields in Nepal and maintained on rice cv. BR 11. The isolates were characterized using morphology, host range and DNA sequence analyses in order to ascertain their identity. Results indicated phenotypic similarity (juvenile measurements, perennial pattern, host range and gall shape) of the Nepalese isolates with Meloidogyne graminicola, with minor variations. The rice varieties LA 110 and Labelle were susceptible to all of the Nepalese isolates, but differences in the aggressiveness of the isolates were observed. Phylogenetic analyses based on the sequences of partial internal transcribed spacer (ITS) of the rRNA genes indicated that all Nepalese isolates formed a distinct clade with known isolates of M. graminicola with high bootstrap support. Furthermore, two groups were identified within the M. graminicola clade. No correlation between ITS haplotype and aggressiveness or host range was found among the tested isolates.

  17. 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

  18. 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

  19. 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.

  20. 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.

  1. Rice Photosynthetic Productivity and PSII Photochemistry under Nonflooded Irrigation

    Directory of Open Access Journals (Sweden)

    Haibing He

    2014-01-01

    Full Text Available Nonflooded irrigation is an important water-saving rice cultivation technology, but little is known on its photosynthetic mechanism. The aims of this work were to investigate photosynthetic characteristics of rice during grain filling stage under three nonflooded irrigation treatments: furrow irrigation with plastic mulching (FIM, furrow irrigation with nonmulching (FIN, and drip irrigation with plastic mulching (DI. Compared with the conventional flooding (CF treatment, those grown in the nonflooded irrigation treatments showed lower net photosynthetic rate (PN, lower maximum quantum yield (Fv/Fm, and lower effective quantum yield of PSII photochemistry (ΦPSII. And the poor photosynthetic characteristics in the nonflooded irrigation treatments were mainly attributed to the low total nitrogen content (TNC. Under non-flooded irrigation, the PN, Fv/Fm, and ΦPSII significantly decreased with a reduction in the soil water potential, but these parameters were rapidly recovered in the DI and FIM treatments when supplementary irrigation was applied. Moreover, The DI treatment always had higher photosynthetic productivity than the FIM and FIN treatments. Grain yield, matter translocation, and dry matter post-anthesis (DMPA were the highest in the CF treatment, followed by the DI, FIM, and FIN treatments in turn. In conclusion, increasing nitrogen content in leaf of rice plants could be a key factor to improve photosynthetic capacity in nonflooded irrigation.

  2. Properties and Possible Applications for Lignin Streams Obtained from Rice Straw Processing

    DEFF Research Database (Denmark)

    Mussatto, Solange I.

    This study aimed to evaluate the chemical and physical properties of lignin streams recovered from rice straw processing and to study the extraction of antioxidant phenolic compounds from these materials. The evaluated samples included two different cellulignin fermentation residues (FR’s) and an......This study aimed to evaluate the chemical and physical properties of lignin streams recovered from rice straw processing and to study the extraction of antioxidant phenolic compounds from these materials. The evaluated samples included two different cellulignin fermentation residues (FR......’s) and an acid-precipitated lignin from alkaline-deacetylated black liquor (DBLL). For comparison, a standard lignin sample (Kraft lignin, from Sigma-Aldrich) was also assayed. Besides providing a better understanding about such materials, the obtained results made also possible to propose some potential...

  3. Realistic Simulation of Rice Plant

    Directory of Open Access Journals (Sweden)

    Wei-long DING

    2011-09-01

    Full Text Available The existing research results of virtual modeling of rice plant, however, is far from perfect compared to that of other crops due to its complex structure and growth process. Techniques to visually simulate the architecture of rice plant and its growth process are presented based on the analysis of the morphological characteristics at different stages. Firstly, the simulations of geometrical shape, the bending status and the structural distortion of rice leaves are conducted. Then, by using an improved model for bending deformation, the curved patterns of panicle axis and various types of panicle branches are generated, and the spatial shape of rice panicle is therefore created. Parametric L-system is employed to generate its topological structures, and finite-state automaton is adopted to describe the development of geometrical structures. Finally, the computer visualization of three-dimensional morphologies of rice plant at both organ and individual levels is achieved. The experimental results showed that the proposed methods of modeling the three-dimensional shapes of organs and simulating the growth of rice plant are feasible and effective, and the generated three-dimensional images are realistic.

  4. Increasing rice plant growth by Trichoderma sp.

    Science.gov (United States)

    Doni, Febri; Isahak, Anizan; Zain, Che Radziah Che Mohd; Sulaiman, Norela; Fathurahman, F.; Zain, Wan Nur Syazana Wan Mohd.; Kadhimi, Ahsan A.; Alhasnawi, Arshad Naji; Anhar, Azwir; Yusoff, Wan Mohtar Wan

    2016-11-01

    Trichoderma sp. is a plant growth promoting fungi in many crops. Initial observation on the ability to enhance rice germination and vigor have been reported. In this study, the effectiveness of a local isolate Trichoderma asprellum SL2 to enhance rice seedling growth was assessed experimentally under greenhouse condition using a completely randomized design. Results showed that inoculation of rice plants with Trichoderma asprellum SL2 significantly increase rice plants height, root length, wet weight, leaf number and biomass compared to untreated rice plants (control). The result of this study can serve as a reference for further work on the application of beneficial microorganisms to enhance rice production.

  5. 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

  6. 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)

  7. 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).

  8. 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.

  9. 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

  10. 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.

  11. 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.

  12. 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

  13. 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....

  14. 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.

  15. 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

  16. 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 ...

  17. 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.

  18. 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

  19. 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.

  20. 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

  1. 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 ...

  2. 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...

  3. 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 ...

  4. 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....

  5. 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 ...

  6. 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

  7. 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....

  8. 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

  9. 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 ...

  10. 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 ...

  11. 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

  12. 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.

  13. 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.

  14. 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…

  15. 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.

  16. 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

  17. 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 ...

  18. 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].

  19. 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

  20. 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...