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. 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.

  3. 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.

  4. 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.

  5. 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

  6. 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%.

  7. 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...

  8. 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.

  9. 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 ...

  10. 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

  11. 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...

  12. 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

  13. 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.

  14. 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...

  15. 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.

  16. 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.

  17. 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.

  18. 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

  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. 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.

  1. 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)

  2. 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

  3. 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...

  4. 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...

  5. 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 ...

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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

  11. 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...

  12. 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.

  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. 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...

  15. 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.

  16. 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...

  17. 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.

  18. 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

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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

  4. 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),

  5. 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.

  6. 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.

  7. 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

  8. 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.

  9. 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

  10. 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...

  11. 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.

  12. 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

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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

  19. 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

  20. 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

  1. 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.

  2. 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.

  3. 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

  4. 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.

  5. 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.

  6. 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

  7. 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.

  8. 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.

  9. 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.

  10. 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...

  11. 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

  12. 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.

  13. 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.

  14. 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.

  15. 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)

  16. 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

  17. 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...

  18. 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

  19. Determination of Optimal Harvest Time of Chuchung Variety Green Rice(®) (Oryza sativa L.) with High Contents of GABA, γ-Oryzanol, and α-Tocopherol.

    Science.gov (United States)

    Kim, Hoon; Kim, Oui-Woung; Ha, Ae Wha; Park, Soojin

    2016-06-01

    In our previous study, an early-maturing variety of rice (Oryza sativa L.), Jinbu can have feature with unique green color, various phytochemicals as well as nutritive components by the optimal early harvesting, called Green Rice(®) (GR). The aims of the present field experiments were to evaluate the changes in the weight of 1,000 kernels, yield, and contents of proximate and bioactive compounds in Chuchung, a mid-late maturing variety, during the pre-harvest maturation of rough rice and to research the appropriate harvest time and potent bioactivity of Chuchung GR. The weights of 1,000 kernels of Chuchung GR dramatically increased until 27 days after heading (DAH). The yields of Chuchung GR declined after 27 DAH and significantly declined to 0.0% after 45 DAH. The caloric value and total mineral contents were higher in the GR than in the full ripe stage, the brown rice (BR). In the GR, the contents of bioactive compounds, such as γ-aminobutyric acid, γ-oryzanol, and α-tocopherol, were much higher (P<0.05) than those in the BR, specifically during 24~27 DAH. Therefore, bioactive Chuchung GR can be produced with a reasonable yield at 24~27 DAH and it could be useful for applications in various nutritive and functional food products.

  20. Determination of Optimal Harvest Time of Chuchung Variety Green Rice® (Oryza sativa L.) with High Contents of GABA, γ-Oryzanol, and α-Tocopherol

    Science.gov (United States)

    Kim, Hoon; Kim, Oui-Woung; Ha, Ae Wha; Park, Soojin

    2016-01-01

    In our previous study, an early-maturing variety of rice (Oryza sativa L.), Jinbu can have feature with unique green color, various phytochemicals as well as nutritive components by the optimal early harvesting, called Green Rice® (GR). The aims of the present field experiments were to evaluate the changes in the weight of 1,000 kernels, yield, and contents of proximate and bioactive compounds in Chuchung, a mid-late maturing variety, during the pre-harvest maturation of rough rice and to research the appropriate harvest time and potent bioactivity of Chuchung GR. The weights of 1,000 kernels of Chuchung GR dramatically increased until 27 days after heading (DAH). The yields of Chuchung GR declined after 27 DAH and significantly declined to 0.0% after 45 DAH. The caloric value and total mineral contents were higher in the GR than in the full ripe stage, the brown rice (BR). In the GR, the contents of bioactive compounds, such as γ-aminobutyric acid, γ-oryzanol, and α-tocopherol, were much higher (P<0.05) than those in the BR, specifically during 24~27 DAH. Therefore, bioactive Chuchung GR can be produced with a reasonable yield at 24~27 DAH and it could be useful for applications in various nutritive and functional food products. PMID:27390725

  1. 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.

  2. 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] ...

  3. 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...

  4. 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...

  5. 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 ...

  6. 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...

  7. 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...

  8. 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...

  9. 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.

  10. 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.

  11. 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...

  12. Effect of Intermittent Drying Conditions on Fissuring Percentage and Process Duration of Long and Medium Rough Rice Varieties

    Directory of Open Access Journals (Sweden)

    A. Ghasemi

    2016-02-01

    Full Text Available One of the factors which affect the quality of rice during milling is internal fissures created during and after drying operation. In many industrial countries intermittent drying method is hired to reduce the moisture content of rough rice in order to reduce the drying time and maintain the quality of the final product. A high percentage of rice breakage during milling process, at least in Iran, necessitates performing the intermittent drying process and optimize it for Iranian varieties. In this study, the effect of this method (drying-tempering and continuous drying method (no tempering on fissuring percentage of Hashemi (long grain and Koohsar (medium grain varieties was investigated. The experiments were carried out at constant drying and tempering temperature of 60 °C, drying durations of 20, 40 and 60 min, and tempering durations of 0 (continuous drying, 40, 80, 120, 160, 200, 240 min. The results revealed that the tempering process significantly reduced the drying time and fissured kernels percentage. Moreover, for both varieties it was observed that the rice fissuring decreased significantly by continuing the tempering process until certain durations. Overall, for optimization of intermittent drying process in terms of the considered qualitative parameters, i.e. reducing energy consumption and losses, conducting 160 and 200 min tempering process after 40 min drying was found appropriate for Hashemi and Koohsar varieties, respectively. In addition, according to the higher fissuring for Koohsar (medium grain compared to Hashemi (long grain, it can be concluded that physical properties such as kernel slenderness ratio is effective on its fissuring.

  13. 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

  14. The influence of extraction methods on composition and antioxidant properties of rice bran oil

    Directory of Open Access Journals (Sweden)

    Noppawat Pengkumsri

    2015-09-01

    Full Text Available AbstractThe current study was employed to assess the influence of the different extraction methods on total tocols, γ-oryzanol content, and antioxidant properties of Chiang Mai Black rice, Mali Red rice, and Suphanburi-1 Brown rice bran oil. Rice bran oil (RBO was extracted by Hexane, Hot pressed, Cold pressed, and Supercritical Fluid Extraction (SFe methods. High yield of RBO was extracted by hexane and SFe methods. Total and subgroups of tocols, and γ-oryzanol content were determined by HPLC. The hexane extracted sample accounts for high content of γ-oryzanol and tocols. Besides, all of RBO extracts contain a significantly high amount of γ-tocotrienol. In vitro antioxidant assay results indicated that superior quality of oil was recovered by hexane extraction. The temperature in the extraction process also affects the value of the oil. Superior quality of oil was recovered by hexane extraction, in terms of phytochemical contents and antioxidant properties compared to other tested extraction methods. Further, thorough study of factors compromising the quality and quantity of RBO recovery is required for the development of enhanced functional foods and other related products.

  15. 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...

  16. 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...

  17. 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...

  18. 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.

  19. 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

  20. 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. ...

  1. 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.

  2. Comparative study on nutritional and sensory quality of barnyard and foxtail millet food products with traditional rice products.

    Science.gov (United States)

    Verma, Suman; Srivastava, Sarita; Tiwari, Neha

    2015-08-01

    Millets have the potential to contribute to food security and nutrition, but still these are underutilized crops. The present study was undertaken with a view to analyse the physico-chemical, functional and nutritional composition of foxtail millet, barnyard millet and rice and to compare the sensory quality and nutritive value of food products from foxtail and barnyard millet with rice. Analysis of physico- chemical and functional characteristics revealed that the thousand kernel weight of foxtail millet, barnyard millet and rice was 2.5, 3.0 and 18.3 g, respectively and thousand kernel volume was 1.6, 13 2.0 and 7.1 ml, respectively. The water absorption capacity of foxtail millet, barnyard millet and rice was 1.90, 1.96 and 1.98 ml/g, respectively and water solubility index was 2.8, 1.2 and 1.0 %, respectively. Viscosity was measured for foxtail millet (1650.6 cps), barnyard millet (1581 cps) and rice (1668.3 cps). Analysis of nutritional composition showed that the moisture content of foxtail millet, barnyard millet and rice was 9.35, 11.93 and 11.91 %, respectively. The total ash, crude protein, crude fat, crude fibre and carbohydrate of foxtail millet were 3.10, 10.29, 3.06, 4.25 and 69.95 %, respectively, for barnyard millet were 4.27, 6.93, 2.02, 2.98 and 71.87 %, respectively and the corresponding values for rice were 0.59, 6.19, 0.53, 0.21 and 80.58 %, respectively. The energy value for foxtail millet, barnyard millet and rice was 349, 407 and 352 Kcal, respectively. The foxtail millet contained 30.10 mg/100 g calcium and 3.73 mg/100 g iron whereas barnyard millet contained 23.16 mg/100 g calcium and 6.91 mg/100 g iron. Values of 10 mg/100 g calcium and 0.10 mg/100 g iron were observed for rice. The formulated products viz. laddu, halwa and biryani from foxtail millet, barnyard millet and rice (control) were analysed for their sensory qualities. Among the products prepared, there was non significant difference with regard to the

  3. 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.

  4. 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`.

  5. 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.

  6. 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...

  7. 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...

  8. 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

  9. 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…

  10. 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.

  11. 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.

  12. 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.

  13. 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....

  14. A two-stage bioprocess for hydrogen and methane production from rice straw bioethanol residues.

    Science.gov (United States)

    Cheng, Hai-Hsuan; Whang, Liang-Ming; Wu, Chao-Wei; Chung, Man-Chien

    2012-06-01

    This study evaluates a two-stage bioprocess for recovering hydrogen and methane while treating organic residues of fermentative bioethanol from rice straw. The obtained results indicate that controlling a proper volumetric loading rate, substrate-to-biomass ratio, or F/M ratio is important to maximizing biohydrogen production from rice straw bioethanol residues. Clostridium tyrobutyricum, the identified major hydrogen-producing bacteria enriched in the hydrogen bioreactor, is likely utilizing lactate and acetate for biohydrogen production. The occurrence of acetogenesis during biohydrogen fermentation may reduce the B/A ratio and lead to a lower hydrogen production. Organic residues remained in the effluent of hydrogen bioreactor can be effectively converted to methane with a rate of 2.8 mmol CH(4)/gVSS/h at VLR of 4.6 kg COD/m(3)/d. Finally, approximately 75% of COD in rice straw bioethanol residues can be removed and among that 1.3% and 66.1% of COD can be recovered in the forms of hydrogen and methane, respectively. Copyright © 2012 Elsevier Ltd. All rights reserved.

  15. 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

  16. 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.

  17. 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

  18. 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

  19. 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...

  20. 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.

  1. 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

  2. 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

  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. 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

  5. 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...

  6. 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....

  7. 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

  8. 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...

  9. 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.

  10. 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 ...

  11. 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.

  12. 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.

  13. 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...

  14. 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.

  15. 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.

  16. 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

  17. 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.

  18. 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

  19. 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

  20. 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 ...

  1. 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

  2. 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

  3. 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)

  4. 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

  5. 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...

  6. 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.

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

    African Journals Online (AJOL)

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

  8. 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....

  9. 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.

  10. 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.)

  11. 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.

  12. 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...

  13. A correlation study of proximate composition, physical and cooking properties of new high yielding and disease resistant rice varieties

    Directory of Open Access Journals (Sweden)

    Nuzhat Rasool

    2015-12-01

    Full Text Available The present study was aimed to compare proximate composition, physical, and cooking properties of locally cultivated rice varieties of Kashmir division viz.; SR-1, K-448, and K-39. Various physiochemical properties were studied. The relationship between physical, proximate composition, and cooking properties was determined using Pearson’s correlation. Length–breadth (L/B ratio showed a significant positive correlation with kernel length and negative correlation with thousand kernel weight, with a correlation coefficient (r of 0.893 and −0.855, respectively, (p  0.05. Solid loss in gruel was observed to have a negative correlation with L/B ratio (r = −0.432, p > 0.05, water uptake ratio (r = −0.742, p < 0.05, and cooking time (r = −0.678, p < 0.05. The rice cultivars with higher cooking time showed lower gruel solid loss and vice versa. Water uptake was observed to be positively correlated with L/B ratio (r = 0.768, p < 0.05. Among all the cultivars studied, K-448 variety has potential for consumers’ preference and it could be used for breeding programs for the improvement of valuable grain quality traits.

  14. 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.

  15. 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.

  16. 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

  17. 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...

  18. 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.

  19. 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.

  20. 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.

  1. 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...

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

    DEFF Research Database (Denmark)

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

    2009-01-01

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

  3. 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

  4. 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.

  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. 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. 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

  8. 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.

  9. 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)

  10. 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...

  11. 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.

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

    Science.gov (United States)

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

    2015-05-01

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

  13. 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...

  14. 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 ...

  15. 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 ...

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

    Directory of Open Access Journals (Sweden)

    Mohammed D. ABDULMALIK

    2008-06-01

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

  17. 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.

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

    Science.gov (United States)

    Tezuka, Taro

    2018-06-01

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

  19. 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.

  20. 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

  1. 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%.

  2. 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.

  3. 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.

  4. 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

  5. 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.

  6. 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...

  7. Reduced multiple empirical kernel learning machine.

    Science.gov (United States)

    Wang, Zhe; Lu, MingZhe; Gao, Daqi

    2015-02-01

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

  8. Not any type of rice performs equally to improve lactose-induced diarrhea characteristics in rats: is amylose an antidiarrheal factor?

    Directory of Open Access Journals (Sweden)

    Ana Lia Felipoff

    Full Text Available The effectiveness of different types of rice in relation to their ability to accelerate diarrhea recovering was evaluated in a rat model of osmotic diarrhea (OD. Animals (90-100 g received protein free diet until reaching up to 20% weight loss, followed by lactose rich diet (LRD to induce osmotic diarrhea. Rats presenting osmotic diarrhea were divided into 4 groups, which received lactose rich diet for 4 days from 8 am to 8 pm, and one of three experimental products containing 6% rice flour differing in amylose content during the night: high (HA, intermediate (IA, and low (LA. A group fed stock diet containing equivalent amount of lactose was taken as control and allowed to recover spontaneously. Amylose and viscosity (cp at 25 °C, 10 rpm of final products were determined. Effectiveness was expressed as the ratio between percentages of normal vs. diarrheic stools during the treatment. Fecal characteristics in this rat model improved only as result of feeding high amylose content (HA type of rice. In this experimental model of osmotic diarrhea in young rats, the antidiarrheal effects of rice were strongly dependent on the type of diet used and appear to be related to its amylose content.

  9. 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....

  10. 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...

  11. 7 CFR 981.61 - Redetermination of kernel weight.

    Science.gov (United States)

    2010-01-01

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

  12. 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

  13. 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...

  14. 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.

  15. 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

  16. 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...

  17. 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...

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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

  3. 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

  4. 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.

  5. 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...

  6. 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...

  7. 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

  8. 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.

  9. 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....

  10. Adaptive Metric Kernel Regression

    DEFF Research Database (Denmark)

    Goutte, Cyril; Larsen, Jan

    1998-01-01

    Kernel smoothing is a widely used nonparametric pattern recognition technique. By nature, it suffers from the curse of dimensionality and is usually difficult to apply to high input dimensions. In this paper, we propose an algorithm that adapts the input metric used in multivariate regression...... by minimising a cross-validation estimate of the generalisation error. This allows one to automatically adjust the importance of different dimensions. The improvement in terms of modelling performance is illustrated on a variable selection task where the adaptive metric kernel clearly outperforms the standard...

  11. 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...

  12. 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.

  13. 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...

  14. 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....

  15. 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

  16. Characterization of Gluten-free Bread Prepared From Maize, Rice and Tapioca Flours using the Hydrocolloid Seaweed Agar-Agar

    OpenAIRE

    Alvarenga, Nuno Bartolomeu; Cebola Lidon, Fernando; Belga, Elisa; Motrena, Patrícia; Guerreiro, Suse; Carvalho, Maria João; Canada, João

    2011-01-01

    Disponível em livre acesso no sítio do DOAJ em http://recent-science.com/index This work aims to check the rheological, physicochemical and sensory characteristics of gluten-free bread produced with corn, rice and tapioca flours, using the hydrocolloid seaweed agar-agar. Relatively to wheat bread, it was found that the pH was slightly lower in gluten-free bread. In the crust only the brightness remained significantly different between both bread types, but in the kernel, the parameters a*,...

  17. Convergence of barycentric coordinates to barycentric kernels

    KAUST Repository

    Kosinka, Jiří

    2016-02-12

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

  18. Convergence of barycentric coordinates to barycentric kernels

    KAUST Repository

    Kosinka, Jiří ; Barton, Michael

    2016-01-01

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

  19. 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.

  20. 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.

  1. 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

  2. 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)

  3. 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.

  4. 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...

  5. 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.

  6. 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.

  7. 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

  8. 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)

  9. 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....

  10. 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.

  11. Evolution kernel for the Dirac field

    International Nuclear Information System (INIS)

    Baaquie, B.E.

    1982-06-01

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

  12. 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.

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

    DEFF Research Database (Denmark)

    Feragen, Aasa; Hauberg, Søren

    2016-01-01

    Radial kernels are well-suited for machine learning over general geodesic metric spaces, where pairwise distances are often the only computable quantity available. We have recently shown that geodesic exponential kernels are only positive definite for all bandwidths when the input space has strong...... linear properties. This negative result hints that radial kernel are perhaps not suitable over geodesic metric spaces after all. Here, however, we present evidence that large intervals of bandwidths exist where geodesic exponential kernels have high probability of being positive definite over finite...... datasets, while still having significant predictive power. From this we formulate conjectures on the probability of a positive definite kernel matrix for a finite random sample, depending on the geometry of the data space and the spread of the sample....

  14. Genetic dissection of the maize kernel development process via conditional QTL mapping for three developing kernel-related traits in an immortalized F2 population.

    Science.gov (United States)

    Zhang, Zhanhui; Wu, Xiangyuan; Shi, Chaonan; Wang, Rongna; Li, Shengfei; Wang, Zhaohui; Liu, Zonghua; Xue, Yadong; Tang, Guiliang; Tang, Jihua

    2016-02-01

    Kernel development is an important dynamic trait that determines the final grain yield in maize. To dissect the genetic basis of maize kernel development process, a conditional quantitative trait locus (QTL) analysis was conducted using an immortalized F2 (IF2) population comprising 243 single crosses at two locations over 2 years. Volume (KV) and density (KD) of dried developing kernels, together with kernel weight (KW) at different developmental stages, were used to describe dynamic changes during kernel development. Phenotypic analysis revealed that final KW and KD were determined at DAP22 and KV at DAP29. Unconditional QTL mapping for KW, KV and KD uncovered 97 QTLs at different kernel development stages, of which qKW6b, qKW7a, qKW7b, qKW10b, qKW10c, qKV10a, qKV10b and qKV7 were identified under multiple kernel developmental stages and environments. Among the 26 QTLs detected by conditional QTL mapping, conqKW7a, conqKV7a, conqKV10a, conqKD2, conqKD7 and conqKD8a were conserved between the two mapping methodologies. Furthermore, most of these QTLs were consistent with QTLs and genes for kernel development/grain filling reported in previous studies. These QTLs probably contain major genes associated with the kernel development process, and can be used to improve grain yield and quality through marker-assisted selection.

  15. 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

  16. A trace ratio maximization approach to multiple kernel-based dimensionality reduction.

    Science.gov (United States)

    Jiang, Wenhao; Chung, Fu-lai

    2014-01-01

    Most dimensionality reduction techniques are based on one metric or one kernel, hence it is necessary to select an appropriate kernel for kernel-based dimensionality reduction. Multiple kernel learning for dimensionality reduction (MKL-DR) has been recently proposed to learn a kernel from a set of base kernels which are seen as different descriptions of data. As MKL-DR does not involve regularization, it might be ill-posed under some conditions and consequently its applications are hindered. This paper proposes a multiple kernel learning framework for dimensionality reduction based on regularized trace ratio, termed as MKL-TR. Our method aims at learning a transformation into a space of lower dimension and a corresponding kernel from the given base kernels among which some may not be suitable for the given data. The solutions for the proposed framework can be found based on trace ratio maximization. The experimental results demonstrate its effectiveness in benchmark datasets, which include text, image and sound datasets, for supervised, unsupervised as well as semi-supervised settings. Copyright © 2013 Elsevier Ltd. All rights reserved.

  17. 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 ...

  18. 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...

  19. 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...

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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...

  7. 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

  8. 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...

  9. 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...

  10. 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 .

  11. 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

  12. 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.

  13. 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.

  14. Not any type of rice performs equally to improve lactose-induced diarrhea characteristics in rats: is amylose an antidiarrheal factor?

    OpenAIRE

    Felipoff,Ana Lia; Zuleta,Angela; Sambucetti,Maria Elena; Rio,Maria Esther

    2012-01-01

    The effectiveness of different types of rice in relation to their ability to accelerate diarrhea recovering was evaluated in a rat model of osmotic diarrhea (OD). Animals (90-100 g) received protein free diet until reaching up to 20% weight loss, followed by lactose rich diet (LRD) to induce osmotic diarrhea. Rats presenting osmotic diarrhea were divided into 4 groups, which received lactose rich diet for 4 days from 8 am to 8 pm, and one of three experimental products containing 6% rice flou...

  15. 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

  16. Characterization of cytoplasmic male sterility of rice with Lead Rice cytoplasm in comparison with that with Chinsurah Boro II cytoplasm.

    Science.gov (United States)

    Itabashi, Etsuko; Kazama, Tomohiko; Toriyama, Kinya

    2009-02-01

    Rice with LD-type cytoplasmic male sterility (CMS) possesses the cytoplasm of 'Lead Rice' and its fertility is recovered by a nuclear fertility restorer gene Rf1. Rf1 promotes processing of a CMS-associated mitochondrial RNA of atp6-orf79, which consists of atp6 and orf79, in BT-CMS with the cytoplasm of 'Chinsurah Boro II'. In this study, we found that LD-cytoplasm contained a sequence variant of orf79 downstream of atp6. Northern blot analysis showed that atp6-orf79 RNA of LD-cytoplasm was co-transcribed and was processed in the presence of Rf1 in the same manner as in BT-cytoplasm. Western blot analysis showed that the ORF79 peptide did not accumulate in an LD-CMS line, while ORF79 accumulated in a BT-CMS line and was diminished by Rf1. These results suggest that accumulation of ORF79 is not the cause of CMS in LD-cytoplasm and the mechanism of male-sterility induction/fertility restoration in LD-CMS is different from that in BT-CMS.

  17. 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.

  18. The integral first collision kernel method for gamma-ray skyshine analysis[Skyshine; Gamma-ray; First collision kernel; Monte Carlo calculation

    Energy Technology Data Exchange (ETDEWEB)

    Sheu, R.-D.; Chui, C.-S.; Jiang, S.-H. E-mail: shjiang@mx.nthu.edu.tw

    2003-12-01

    A simplified method, based on the integral of the first collision kernel, is presented for performing gamma-ray skyshine calculations for the collimated sources. The first collision kernels were calculated in air for a reference air density by use of the EGS4 Monte Carlo code. These kernels can be applied to other air densities by applying density corrections. The integral first collision kernel (IFCK) method has been used to calculate two of the ANSI/ANS skyshine benchmark problems and the results were compared with a number of other commonly used codes. Our results were generally in good agreement with others but only spend a small fraction of the computation time required by the Monte Carlo calculations. The scheme of the IFCK method for dealing with lots of source collimation geometry is also presented in this study.

  19. Alkaline coal fly ash amendments are recommended for improving rice-peanut crops

    Energy Technology Data Exchange (ETDEWEB)

    Swain, D.K.; Ghosh, B.C. [Agricultural and Food Engineering Department, Indi an Inst. of Technology, Kharagpur, West Bengal (India); Rautaray, S.K. [RRLRRS, Gerua Via-Hajo, Dist-Kamrup, Assam (India)

    2007-05-15

    A field experiment investigating amendments of organic material including farmyard manure, paper factory sludge and crop residues combined with fly ash, lime and chemical fertilizer in a rice-peanut cropping system was conducted during 1997-98 and 1998-99 at the Indian Institute of Technology, Kharagpur, India. The soil was an acid lateritic (Halustaf) sandy loam. For rice, an N:P:K level of 90:26.2:33.3 kg/ha was supplied through the organic materials and chemical fertilizer to all the treatments except control and fly ash alone. The required quantities of organic materials were added to supply 30 kg N/ha and the balance amount of N, P and K was supplied through chemical fertilizer. Amendment materials as per fertilization treatments were incorporated to individual plots 15 days before planting of rice during the rainy season. The residual effects were studied on the following peanut crop with application of N:P:K at 30:26.2:33.3 kg/ha through chemical fertilizer alone in all treatments, apart from the control. An application of fly ash at 10 t/ha in combination with chemical fertilizer and organic materials increased the grain yield of rice by 11% compared to chemical fertilizer alone. The residual effect of both lime and fly ash applications combined with direct application of chemical fertilizer increased peanut yields by 30% and 24%, respectively, compared to chemical fertilizer alone. Treatments with fly ash or lime increased P and K uptake in both the crops and oil content in peanut kernel compared to those without the amendments. Alkaline coal fly ash proved to be a better amendment than lime for improving productivity of an acid lateritic soil and enriching the soil with P and K.

  20. 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.

  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. Point kernels and superposition methods for scatter dose calculations in brachytherapy

    International Nuclear Information System (INIS)

    Carlsson, A.K.

    2000-01-01

    Point kernels have been generated and applied for calculation of scatter dose distributions around monoenergetic point sources for photon energies ranging from 28 to 662 keV. Three different approaches for dose calculations have been compared: a single-kernel superposition method, a single-kernel superposition method where the point kernels are approximated as isotropic and a novel 'successive-scattering' superposition method for improved modelling of the dose from multiply scattered photons. An extended version of the EGS4 Monte Carlo code was used for generating the kernels and for benchmarking the absorbed dose distributions calculated with the superposition methods. It is shown that dose calculation by superposition at and below 100 keV can be simplified by using isotropic point kernels. Compared to the assumption of full in-scattering made by algorithms currently in clinical use, the single-kernel superposition method improves dose calculations in a half-phantom consisting of air and water. Further improvements are obtained using the successive-scattering superposition method, which reduces the overestimates of dose close to the phantom surface usually associated with kernel superposition methods at brachytherapy photon energies. It is also shown that scatter dose point kernels can be parametrized to biexponential functions, making them suitable for use with an effective implementation of the collapsed cone superposition algorithm. (author)

  3. Online learning control using adaptive critic designs with sparse kernel machines.

    Science.gov (United States)

    Xu, Xin; Hou, Zhongsheng; Lian, Chuanqiang; He, Haibo

    2013-05-01

    In the past decade, adaptive critic designs (ACDs), including heuristic dynamic programming (HDP), dual heuristic programming (DHP), and their action-dependent ones, have been widely studied to realize online learning control of dynamical systems. However, because neural networks with manually designed features are commonly used to deal with continuous state and action spaces, the generalization capability and learning efficiency of previous ACDs still need to be improved. In this paper, a novel framework of ACDs with sparse kernel machines is presented by integrating kernel methods into the critic of ACDs. To improve the generalization capability as well as the computational efficiency of kernel machines, a sparsification method based on the approximately linear dependence analysis is used. Using the sparse kernel machines, two kernel-based ACD algorithms, that is, kernel HDP (KHDP) and kernel DHP (KDHP), are proposed and their performance is analyzed both theoretically and empirically. Because of the representation learning and generalization capability of sparse kernel machines, KHDP and KDHP can obtain much better performance than previous HDP and DHP with manually designed neural networks. Simulation and experimental results of two nonlinear control problems, that is, a continuous-action inverted pendulum problem and a ball and plate control problem, demonstrate the effectiveness of the proposed kernel ACD methods.

  4. 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.

  5. 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)

  6. 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.

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

    Science.gov (United States)

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

  8. Basic studies on the efficacy of gamma irradiation as insect disinfestation and sterilising techniques for stored rice insects

    International Nuclear Information System (INIS)

    Abdul Rahim Muda.

    1987-01-01

    Basic laboratory evaluations on the efficacy of gamma irradiation on the insect sitophilus zeamais, Motch. showed this method of insect control is effective to disinfest both internal and surface infestations in stored milled rice, and substantially reduced reproductive potentials of the weevil. Adult emergence of treated larvae developing within the rice kernel reduced by an average of 82% for treatment doses of 0.05 to 1 kGy. All emerged adults died within 16 days upon emergence at all tested doses. Radiated adult insects showed 100% mortality within 18 days at doses above 0.15 kGy; 26 days at 0.1 kGy and 33 days at 0.05 kGy. However none of the tested doses recorded total immediate mortality after treatment. Significant sterility effects through 93% reduction in F 1 progenies can be achieved by sterilising both parents; but none of the tested doses showed potential for employment as male sterilising technique alone. (author)

  9. TaGS5-3A, a grain size gene selected during wheat improvement for larger kernel and yield.

    Science.gov (United States)

    Ma, Lin; Li, Tian; Hao, Chenyang; Wang, Yuquan; Chen, Xinhong; Zhang, Xueyong

    2016-05-01

    Grain size is a dominant component of grain weight in cereals. Earlier studies have shown that OsGS5 plays a major role in regulating both grain size and weight in rice via promotion of cell division. In this study, we isolated TaGS5 homoeologues in wheat and mapped them on chromosomes 3A, 3B and 3D. Temporal and spatial expression analysis showed that TaGS5 homoeologues were preferentially expressed in young spikes and developing grains. Two alleles of TaGS5-3A, TaGS5-3A-T and TaGS5-3A-G were identified in wheat accessions, and a functional marker was developed to discriminate them. Association analysis revealed that TaGS5-3A-T was significantly correlated with larger grain size and higher thousand kernel weight. Biochemical assays showed that TaGS5-3A-T possesses a higher enzymatic activity than TaGS5-3A-G. Transgenic rice lines overexpressing TaGS5-3A-T also exhibited larger grain size and higher thousand kernel weight than TaGS5-3A-G lines, and the transcript levels of cell cycle-related genes in TaGS5-3A-T lines were higher than those in TaGS5-3A-G lines. Furthermore, systematic evolution analysis in diploid, tetraploid and hexaploid wheat showed that TaGS5-3A underwent strong artificial selection during wheat polyploidization events and the frequency changes of two alleles demonstrated that TaGS5-3A-T was favoured in global modern wheat cultivars. These results suggest that TaGS5-3A is a positive regulator of grain size and its favoured allele TaGS5-3A-T exhibits a larger potential application in wheat high-yield breeding. © 2015 Society for Experimental Biology, Association of Applied Biologists and John Wiley & Sons Ltd.

  10. 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.

  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. Binary Solvent Extraction of Tocols, γ-Oryzanol, and Ferulic Acid from Rice Bran Using Alkaline Treatment Combined with Ultrasonication.

    Science.gov (United States)

    Truong, Hoa Thi; Luu, Phuong Duc; Imamura, Kiyoshi; Matsubara, Takeo; Takahashi, Hideki; Takenaka, Norimichi; Boi, Luu Van; Maeda, Yasuaki

    2017-06-21

    Alkaline treatment (Alk) combined with ultrasound-assisted extraction (UAE) (Alk+UAE) was examined as a means of extracting tocols and γ-oryzanol from rice bran into an organic phase while simultaneously recovering ferulic acid into an aqueous phase. The tocols and γ-oryzanol/ferulic acid yields were determined using high-performance liquid chromatography with fluorescence and UV detection. The effects of extraction conditions were evaluated by varying the Alk treatment temperature and extraction duration. The maximum yields of tocols and γ-oryzanol were obtained at 25 °C over a time span of 30 min. When the temperature was increased to 80 °C, the yield of ferulic acid increased dramatically, whereas the recovery of γ-oryzanol slightly decreased. Employing the Alk+UAE procedure, the recovered concentrations of tocols, γ-oryzanol, and ferulic acid were in the ranges of 146-518, 1591-3629, and 352-970 μg/g, respectively. These results are in good agreement with those reported for rice bran samples from Thailand.

  13. Kernel bundle EPDiff

    DEFF Research Database (Denmark)

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

    2011-01-01

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

  14. RiceAtlas, a spatial database of global rice calendars and production.

    Science.gov (United States)

    Laborte, Alice G; Gutierrez, Mary Anne; Balanza, Jane Girly; Saito, Kazuki; Zwart, Sander J; Boschetti, Mirco; Murty, M V R; Villano, Lorena; Aunario, Jorrel Khalil; Reinke, Russell; Koo, Jawoo; Hijmans, Robert J; Nelson, Andrew

    2017-05-30

    Knowing where, when, and how much rice is planted and harvested is crucial information for understanding the effects of policy, trade, and global and technological change on food security. We developed RiceAtlas, a spatial database on the seasonal distribution of the world's rice production. It consists of data on rice planting and harvesting dates by growing season and estimates of monthly production for all rice-producing countries. Sources used for planting and harvesting dates include global and regional databases, national publications, online reports, and expert knowledge. Monthly production data were estimated based on annual or seasonal production statistics, and planting and harvesting dates. RiceAtlas has 2,725 spatial units. Compared with available global crop calendars, RiceAtlas is nearly ten times more spatially detailed and has nearly seven times more spatial units, with at least two seasons of calendar data, making RiceAtlas the most comprehensive and detailed spatial database on rice calendar and production.

  15. 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.

  16. 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.

  17. 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

  18. 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.

  19. A framework for optimal kernel-based manifold embedding of medical image data.

    Science.gov (United States)

    Zimmer, Veronika A; Lekadir, Karim; Hoogendoorn, Corné; Frangi, Alejandro F; Piella, Gemma

    2015-04-01

    Kernel-based dimensionality reduction is a widely used technique in medical image analysis. To fully unravel the underlying nonlinear manifold the selection of an adequate kernel function and of its free parameters is critical. In practice, however, the kernel function is generally chosen as Gaussian or polynomial and such standard kernels might not always be optimal for a given image dataset or application. In this paper, we present a study on the effect of the kernel functions in nonlinear manifold embedding of medical image data. To this end, we first carry out a literature review on existing advanced kernels developed in the statistics, machine learning, and signal processing communities. In addition, we implement kernel-based formulations of well-known nonlinear dimensional reduction techniques such as Isomap and Locally Linear Embedding, thus obtaining a unified framework for manifold embedding using kernels. Subsequently, we present a method to automatically choose a kernel function and its associated parameters from a pool of kernel candidates, with the aim to generate the most optimal manifold embeddings. Furthermore, we show how the calculated selection measures can be extended to take into account the spatial relationships in images, or used to combine several kernels to further improve the embedding results. Experiments are then carried out on various synthetic and phantom datasets for numerical assessment of the methods. Furthermore, the workflow is applied to real data that include brain manifolds and multispectral images to demonstrate the importance of the kernel selection in the analysis of high-dimensional medical images. Copyright © 2014 Elsevier Ltd. All rights reserved.

  20. 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

  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. A Fourier-series-based kernel-independent fast multipole method

    International Nuclear Information System (INIS)

    Zhang Bo; Huang Jingfang; Pitsianis, Nikos P.; Sun Xiaobai

    2011-01-01

    We present in this paper a new kernel-independent fast multipole method (FMM), named as FKI-FMM, for pairwise particle interactions with translation-invariant kernel functions. FKI-FMM creates, using numerical techniques, sufficiently accurate and compressive representations of a given kernel function over multi-scale interaction regions in the form of a truncated Fourier series. It provides also economic operators for the multipole-to-multipole, multipole-to-local, and local-to-local translations that are typical and essential in the FMM algorithms. The multipole-to-local translation operator, in particular, is readily diagonal and does not dominate in arithmetic operations. FKI-FMM provides an alternative and competitive option, among other kernel-independent FMM algorithms, for an efficient application of the FMM, especially for applications where the kernel function consists of multi-physics and multi-scale components as those arising in recent studies of biological systems. We present the complexity analysis and demonstrate with experimental results the FKI-FMM performance in accuracy and efficiency.

  3. Transgene Flow from Glufosinate-Resistant Rice to Improved and Weedy Rice in China

    Directory of Open Access Journals (Sweden)

    Yong-liang LU

    2014-09-01

    Full Text Available The development of transgenic rice with novel traits in China can increase rice productivity, but transgene flow to improved or weedy rice has become a major concern. We aimed to evaluate the potential maximum frequencies of transgene flow from glufosinate-resistant rice to improved rice cultivars and weedy rice. Treatments were arranged in randomized complete blocks with three replicates. Experiments were conducted between 2009 and 2010 at the Center for Environmental Safety Supervision and Inspection for Genetically Modified Plants, China National Rice Research Institute, Hangzhou, China. Glufosinate-resistant japonica rice 99-1 was the pollen donor. The pollen recipients were two inbred japonica rice (Chunjiang 016 and Xiushui 09, two inbred indica rice (Zhongzu 14 and Zhongzao 22, two indica hybrid rice (Zhongzheyou 1 and Guodao 1, and one weedy indica rice (Taizhou weedy rice. The offspring of recipients were planted in the field and sprayed with a commercial dose of glufosinate. Leaf tissues of survivors were analyzed by polymerase chain reaction to detect the presence of the transgene. The frequency of gene flow ranged from 0 to 0.488%. In 2009, the order of gene flow frequency was as follows: weedy rice > Chunjiang 016 > Xiushui 09 and Zhongzu 14 > Guodao 1, Zhongzheyou 1 and Zhongzao 22. Gene flow frequencies were generally higher in 2009 than in 2010, but did not differ significantly among rice materials. Gene flow frequency was the highest in weedy rice followed by the inbred japonica rice. The risk of gene flow differed significantly between years and year-to-year variance could mask risk differences among pollen recipients. Gene flow was generally lesser in taller pollen recipients than in shorter ones, but plant height only accounted for about 30% of variation in gene flow. When flowering synchrony was maximized, as in this study, low frequencies of gene flow occurred from herbicide-resistant japonica rice to other cultivars and

  4. 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

  5. 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

  6. Improving prediction of heterodimeric protein complexes using combination with pairwise kernel.

    Science.gov (United States)

    Ruan, Peiying; Hayashida, Morihiro; Akutsu, Tatsuya; Vert, Jean-Philippe

    2018-02-19

    Since many proteins become functional only after they interact with their partner proteins and form protein complexes, it is essential to identify the sets of proteins that form complexes. Therefore, several computational methods have been proposed to predict complexes from the topology and structure of experimental protein-protein interaction (PPI) network. These methods work well to predict complexes involving at least three proteins, but generally fail at identifying complexes involving only two different proteins, called heterodimeric complexes or heterodimers. There is however an urgent need for efficient methods to predict heterodimers, since the majority of known protein complexes are precisely heterodimers. In this paper, we use three promising kernel functions, Min kernel and two pairwise kernels, which are Metric Learning Pairwise Kernel (MLPK) and Tensor Product Pairwise Kernel (TPPK). We also consider the normalization forms of Min kernel. Then, we combine Min kernel or its normalization form and one of the pairwise kernels by plugging. We applied kernels based on PPI, domain, phylogenetic profile, and subcellular localization properties to predicting heterodimers. Then, we evaluate our method by employing C-Support Vector Classification (C-SVC), carrying out 10-fold cross-validation, and calculating the average F-measures. The results suggest that the combination of normalized-Min-kernel and MLPK leads to the best F-measure and improved the performance of our previous work, which had been the best existing method so far. We propose new methods to predict heterodimers, using a machine learning-based approach. We train a support vector machine (SVM) to discriminate interacting vs non-interacting protein pairs, based on informations extracted from PPI, domain, phylogenetic profiles and subcellular localization. We evaluate in detail new kernel functions to encode these data, and report prediction performance that outperforms the state-of-the-art.

  7. Rice production in relation to soil quality under different rice-based cropping systems

    Science.gov (United States)

    Tran Ba, Linh; Sleutel, Steven; Nguyen Van, Qui; Thi, Guong Vo; Le Van, Khoa; Cornelis, Wim

    2016-04-01

    Soil quality of shallow paddy soils may be improved by introducing upland crops and thus a more diverse crop cultivation pattern. Yet, the causal relationship between crop performance and enhanced soil traits in rice-upland crop rotations remains elusive. The objectives of this study were to (i) find correlations among soil properties under different rice-upland crop systems and link selected soil properties to rice growth and yield, (ii) present appropriate values of soil parameters for sustainable rice productivity in heavy clay soil, (iii) evaluate the effect of rotating rice with upland crops on rice yield and economic benefit in a long-term experiment. A rice-upland crop rotational field experiment in the Vietnamese Mekong delta was conducted for 10 years using a randomized complete block design with four treatments and four replications. Treatments were: (i) rice-rice-rice (control - conventional system as farmers' practice), (ii) rice-maize-rice, (iii) rice-mung bean-rice, and (iv) rice-mung bean-maize. Soil and plant sampling were performed after harvest of the rice crop at the end of the final winter-spring cropping season (i.e. year 10). Results show differences in rice growth and yield, and economic benefit as an effect of the crop rotation system. These differences were linked with changes in bulk density, soil porosity, soil aggregate stability index, soil penetration resistance, soil macro-porosity, soil organic carbon, acid hydrolysable soil C and soil nutrient elements, especially at soil depth of 20-30 cm. This is evidenced by the strong correlation (P < 0.01) between rice plant parameters, rice yield and soil properties such as bulk density, porosity, penetration resistance, soil organic carbon and Chydrolysable. It turned out that good rice root growth and rice yield corresponded to bulk density values lower than 1.3 Mg m-3, soil porosity higher than 50%, penetration resistance below 1.0 MPa, and soil organic carbon above 25 g kg-1. The optimal

  8. RPAN: rice pan-genome browser for ∼3000 rice genomes.

    Science.gov (United States)

    Sun, Chen; Hu, Zhiqiang; Zheng, Tianqing; Lu, Kuangchen; Zhao, Yue; Wang, Wensheng; Shi, Jianxin; Wang, Chunchao; Lu, Jinyuan; Zhang, Dabing; Li, Zhikang; Wei, Chaochun

    2017-01-25

    A pan-genome is the union of the gene sets of all the individuals of a clade or a species and it provides a new dimension of genome complexity with the presence/absence variations (PAVs) of genes among these genomes. With the progress of sequencing technologies, pan-genome study is becoming affordable for eukaryotes with large-sized genomes. The Asian cultivated rice, Oryza sativa L., is one of the major food sources for the world and a model organism in plant biology. Recently, the 3000 Rice Genome Project (3K RGP) sequenced more than 3000 rice genomes with a mean sequencing depth of 14.3×, which provided a tremendous resource for rice research. In this paper, we present a genome browser, Rice Pan-genome Browser (RPAN), as a tool to search and visualize the rice pan-genome derived from 3K RGP. RPAN contains a database of the basic information of 3010 rice accessions, including genomic sequences, gene annotations, PAV information and gene expression data of the rice pan-genome. At least 12 000 novel genes absent in the reference genome were included. RPAN also provides multiple search and visualization functions. RPAN can be a rich resource for rice biology and rice breeding. It is available at http://cgm.sjtu.edu.cn/3kricedb/ or http://www.rmbreeding.cn/pan3k. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

  9. 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.

  10. Genetic Analysis of Kernel Traits in Maize-Teosinte Introgression Populations

    Directory of Open Access Journals (Sweden)

    Zhengbin Liu

    2016-08-01

    Full Text Available Seed traits have been targeted by human selection during the domestication of crop species as a way to increase the caloric and nutritional content of food during the transition from hunter-gather to early farming societies. The primary seed trait under selection was likely seed size/weight as it is most directly related to overall grain yield. Additional seed traits involved in seed shape may have also contributed to larger grain. Maize (Zea mays ssp. mays kernel weight has increased more than 10-fold in the 9000 years since domestication from its wild ancestor, teosinte (Z. mays ssp. parviglumis. In order to study how size and shape affect kernel weight, we analyzed kernel morphometric traits in a set of 10 maize-teosinte introgression populations using digital imaging software. We identified quantitative trait loci (QTL for kernel area and length with moderate allelic effects that colocalize with kernel weight QTL. Several genomic regions with strong effects during maize domestication were detected, and a genetic framework for kernel traits was characterized by complex pleiotropic interactions. Our results both confirm prior reports of kernel domestication loci and identify previously uncharacterized QTL with a range of allelic effects, enabling future research into the genetic basis of these traits.

  11. SU-E-T-154: Calculation of Tissue Dose Point Kernels Using GATE Monte Carlo Simulation Toolkit to Compare with Water Dose Point Kernel

    Energy Technology Data Exchange (ETDEWEB)

    Khazaee, M [shahid beheshti university, Tehran, Tehran (Iran, Islamic Republic of); Asl, A Kamali [Shahid Beheshti University, Tehran, Iran., Tehran, Tehran (Iran, Islamic Republic of); Geramifar, P [Shariati Hospital, Tehran, Iran., Tehran, Tehran (Iran, Islamic Republic of)

    2015-06-15

    Purpose: the objective of this study was to assess utilizing water dose point kernel (DPK)instead of tissue dose point kernels in convolution algorithms.to the best of our knowledge, in providing 3D distribution of absorbed dose from a 3D distribution of the activity, the human body is considered equivalent to water. as a Result tissue variations are not considered in patient specific dosimetry. Methods: In this study Gate v7.0 was used to calculate tissue dose point kernel. the beta emitter radionuclides which have taken into consideration in this simulation include Y-90, Lu-177 and P-32 which are commonly used in nuclear medicine. the comparison has been performed for dose point kernels of adipose, bone, breast, heart, intestine, kidney, liver, lung and spleen versus water dose point kernel. Results: In order to validate the simulation the Result of 90Y DPK in water were compared with published results of Papadimitroulas et al (Med. Phys., 2012). The results represented that the mean differences between water DPK and other soft tissues DPKs range between 0.6 % and 1.96% for 90Y, except for lung and bone, where the observed discrepancies are 6.3% and 12.19% respectively. The range of DPK difference for 32P is between 1.74% for breast and 18.85% for bone. For 177Lu, the highest difference belongs to bone which is equal to 16.91%. For other soft tissues the least discrepancy is observed in kidney with 1.68%. Conclusion: In all tissues except for lung and bone, the results of GATE for dose point kernel were comparable to water dose point kernel which demonstrates the appropriateness of applying water dose point kernel instead of soft tissues in the field of nuclear medicine.

  12. SU-E-T-154: Calculation of Tissue Dose Point Kernels Using GATE Monte Carlo Simulation Toolkit to Compare with Water Dose Point Kernel

    International Nuclear Information System (INIS)

    Khazaee, M; Asl, A Kamali; Geramifar, P

    2015-01-01

    Purpose: the objective of this study was to assess utilizing water dose point kernel (DPK)instead of tissue dose point kernels in convolution algorithms.to the best of our knowledge, in providing 3D distribution of absorbed dose from a 3D distribution of the activity, the human body is considered equivalent to water. as a Result tissue variations are not considered in patient specific dosimetry. Methods: In this study Gate v7.0 was used to calculate tissue dose point kernel. the beta emitter radionuclides which have taken into consideration in this simulation include Y-90, Lu-177 and P-32 which are commonly used in nuclear medicine. the comparison has been performed for dose point kernels of adipose, bone, breast, heart, intestine, kidney, liver, lung and spleen versus water dose point kernel. Results: In order to validate the simulation the Result of 90Y DPK in water were compared with published results of Papadimitroulas et al (Med. Phys., 2012). The results represented that the mean differences between water DPK and other soft tissues DPKs range between 0.6 % and 1.96% for 90Y, except for lung and bone, where the observed discrepancies are 6.3% and 12.19% respectively. The range of DPK difference for 32P is between 1.74% for breast and 18.85% for bone. For 177Lu, the highest difference belongs to bone which is equal to 16.91%. For other soft tissues the least discrepancy is observed in kidney with 1.68%. Conclusion: In all tissues except for lung and bone, the results of GATE for dose point kernel were comparable to water dose point kernel which demonstrates the appropriateness of applying water dose point kernel instead of soft tissues in the field of nuclear medicine

  13. 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...

  14. Influence of irradiated chitosan on rice plants growing in hydroponic medium contaminated with salt and heavy metals

    International Nuclear Information System (INIS)

    Lam, N.D.; Diep, T.B.; Kume, Tamikazu

    2000-01-01

    Effect of chitosan and radiation-degraded chitosan on rice seedlings of a Vietnam's original variety was investigated. Potential of irradiated chitosan in plant tolerance for several stress factors (salt, zinc, and vanadium) also was studied as well. Chitosan represented in hydroponic medium clearly inhibited the growth of rice seedlings at concentrations arranging from 50 ppm. Radiation processing of chitosan with dose higher than 100 kGy reduced toxicity of chitosan and the efficacy was of dose proportion. Rice plant of 203 origin was almost normally grown in hydroponic solution containing chitosan that has been irradiated with dose of 150 and 200 kGy. Irradiated chitosan increased plant resistance to environmental stress caused by vanadium (V); thereby the seedlings could be recovered completely, even gained in biomass. This effect was not appeared when applied chitosan to rice in media contaminated by zinc (Zn) and salt (NaCl). The selectness of irradiated chitosan on various stress factors partly clarified the assistant action of chitosan in the vanadium intoxication because chelating with metal ions could not be evaluated as main mechanism. (author)

  15. 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/

  16. 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.

  17. Analysis of rice purchase decision on rice consumer in Bandung city

    Science.gov (United States)

    Kusno, K.; Imannurdin, A.; Syamsiyah, N.; Djuwendah, E.

    2018-03-01

    This study was conducted at three kinds of purchase location which were traditional market, rice kiosk, and supermarket in Bandung City, with survey data of 108 respondents which were selected by systematic random sampling. The aim of this study is to (1) identify consumer characteristics, (2) identify which atribute is considered by consumer in buying rice, and (3) analyze the relationship between purchase decision and income class. Data were analyzed by descriptive analysis and Chi Square test. The results showed most consumers in the traditional market were middle-educated and lower middle-income, at the rice kiosk, the consumer were generally middle-educated and middle-income, and in the supermarkets, the majority were high-educated and upper middle-income consumers. “Kepulenan” be the first priority of most consumers, but for the lower-middle class, the main priority was price. Thus, in case of scarcity and rice price increase, the government should immediately arrange market operations which targeting to lower-middle class consumers. There was a significant relationship between (1) the quality of rice consumed, (2) the frequency of rice purchase per month, and (3) attitudes toward rice price increase; each with the income class. Although the price of rice increase, consumers of middle and upper-middle were remain loyal to the quality of rice they consumed. This indicates rice market in Bandung city is an ideal market for premium rice so that traders and producers are expected to maintain the quality of rice, such as keep using superior seeds and applying good cultivation based on Good Agricultural Practice (GAP) rules.

  18. Local coding based matching kernel method for image classification.

    Directory of Open Access Journals (Sweden)

    Yan Song

    Full Text Available This paper mainly focuses on how to effectively and efficiently measure visual similarity for local feature based representation. Among existing methods, metrics based on Bag of Visual Word (BoV techniques are efficient and conceptually simple, at the expense of effectiveness. By contrast, kernel based metrics are more effective, but at the cost of greater computational complexity and increased storage requirements. We show that a unified visual matching framework can be developed to encompass both BoV and kernel based metrics, in which local kernel plays an important role between feature pairs or between features and their reconstruction. Generally, local kernels are defined using Euclidean distance or its derivatives, based either explicitly or implicitly on an assumption of Gaussian noise. However, local features such as SIFT and HoG often follow a heavy-tailed distribution which tends to undermine the motivation behind Euclidean metrics. Motivated by recent advances in feature coding techniques, a novel efficient local coding based matching kernel (LCMK method is proposed. This exploits the manifold structures in Hilbert space derived from local kernels. The proposed method combines advantages of both BoV and kernel based metrics, and achieves a linear computational complexity. This enables efficient and scalable visual matching to be performed on large scale image sets. To evaluate the effectiveness of the proposed LCMK method, we conduct extensive experiments with widely used benchmark datasets, including 15-Scenes, Caltech101/256, PASCAL VOC 2007 and 2011 datasets. Experimental results confirm the effectiveness of the relatively efficient LCMK method.

  19. Determination of trace metals in non-conventional oilseeds and oil bearing resources by atomic absorption spectrometry

    International Nuclear Information System (INIS)

    Anwer, T.; Kazi, T.G.; Bhanger, M.I.; Iqbal, S.; Anwar, F.

    2003-01-01

    The presence of small amount of trace metals in oil and fats is well known to produce deleterious effect. Crude oils and fat of rice bran varieties (super, 86), mango kernel and muskmelon were evaluated for the determination of Ca, Mg, and Zn by using atomic absorption spectrometric technique. Both rice bran varieties (super, 86) were found to contain high calcium content 12.72, 12.11 micro g/g respectively. In case of Mg, highest content noted in mango kernel 9.91 micro g/g and lowest concentration was in rice bran (super) 2.23 micro g/g. The concentration of Zn was high in rice bran (86) 21.0 micro g/g followed by mango kernel 14.4 micro g/g, rice bran (super) 12.20 micro g/g and muskmelon 8.71 micro g/g. The information gained in present study provides baseline for the stability of these oils. (author)

  20. 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

  1. 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...

  2. 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

  3. 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

  4. 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...

  5. 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.

  6. 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...

  7. 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.

  8. PhosphoRice: a meta-predictor of rice-specific phosphorylation sites

    Directory of Open Access Journals (Sweden)

    Que Shufu

    2012-02-01

    Full Text Available Abstract Background As a result of the growing body of protein phosphorylation sites data, the number of phosphoprotein databases is constantly increasing, and dozens of tools are available for predicting protein phosphorylation sites to achieve fast automatic results. However, none of the existing tools has been developed to predict protein phosphorylation sites in rice. Results In this paper, the phosphorylation site predictors, NetPhos 2.0, NetPhosK, Kinasephos, Scansite, Disphos and Predphosphos, were integrated to construct meta-predictors of rice-specific phosphorylation sites using several methods, including unweighted voting, unreduced weighted voting, reduced unweighted voting and weighted voting strategies. PhosphoRice, the meta-predictor produced by using weighted voting strategy with parameters selected by restricted grid search and conditional random search, performed the best at predicting phosphorylation sites in rice. Its Matthew's Correlation Coefficient (MCC and Accuracy (ACC reached to 0.474 and 73.8%, respectively. Compared to the best individual element predictor (Disphos_default, PhosphoRice archieved a significant increase in MCC of 0.071 (P Conclusions PhosphoRice is a powerful tool for predicting unidentified phosphorylation sites in rice. Compared to the existing methods, we found that our tool showed greater robustness in ACC and MCC. PhosphoRice is available to the public at http://bioinformatics.fafu.edu.cn/PhosphoRice.

  9. 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.

  10. 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

  11. 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....

  12. 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...

  13. Imazethapyr and imazapic, bispyribac-sodium and penoxsulam: Zooplankton and dissipation in subtropical rice paddy water

    Energy Technology Data Exchange (ETDEWEB)

    Reimche, Geovane B., E-mail: geovane_reimche@yahoo.com.br [Department of Plant Protection, Federal University of Santa Maria (UFSM), 97105-900 Santa Maria, RS (Brazil); Machado, Sérgio L.O. [Department of Plant Protection, Federal University of Santa Maria (UFSM), 97105-900 Santa Maria, RS (Brazil); Oliveira, Maria Angélica [Department of Biology, Federal University of Santa Maria, Santa Maria, RS (Brazil); Zanella, Renato; Dressler, Valderi Luiz; Flores, Erico M.M. [Department of Chemistry, Federal University of Santa Maria, Santa Maria, RS (Brazil); Gonçalves, Fábio F. [School of Chemistry and Food, Federal Foundation University of Rio Grande (FURG), 95500-000 Santo Antônio da Patrulha, RS (Brazil); Donato, Filipe F.; Nunes, Matheus A.G. [Department of Chemistry, Federal University of Santa Maria, Santa Maria, RS (Brazil)

    2015-05-01

    Herbicides are very effective at eliminating weed and are largely used in rice paddy around the world, playing a fundamental role in maximizing yield. Therefore, considering the flooded environment of rice paddies, it is necessary to understand the side effects on non-target species. Field experiment studies were carried out during two rice growing seasons in order to address how the commonly-used herbicides imazethapyr and imazapic, bispyribac-sodium and penoxsulam, used at recommended dosage, affect water quality and the non-target zooplankton community using outdoor rice field microcosm set-up. The shortest (4.9 days) and longest (12.2 days) herbicide half-life mean, estimated of the dissipation rate (k) is shown for imazethapyr and bispyribac-sodium, respectively. Some water quality parameters (pH, conductivity, hardness, BOD{sub 5}, boron, potassium, magnesium, phosphorus and chlorides) achieved slightly higher values at the herbicide treatment. Zooplankton community usually quickly recovered from the tested herbicide impact. Generally, herbicides led to an increase of cladocera, copepods and nauplius population, while rotifer population decreased, with recovery at the end of the experiment (88 days after herbicide treatment). - Highlights: • Selective herbicides in paddy rice fields, do not affect water quality. • Zooplankton communities show good response with herbicide dissipation. • The use of commercial herbicide mixture has strong effects on freshwater Rotifers.

  14. 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)

  15. 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

  16. [Nitrogen cycling in rice-duck mutual ecosystem during double cropping rice growth season].

    Science.gov (United States)

    Zhang, Fan; Chen, Yuan-Quan; Sui, Peng; Gao, Wang-Sheng

    2012-01-01

    Raising duck in paddy rice field is an evolution of Chinese traditional agriculture. In May-October 2010, a field experiment was conducted in a double cropping rice region of Hunan Province, South-central China to study the nitrogen (N) cycling in rice-duck mutual ecosystem during early rice and late rice growth periods, taking a conventional paddy rice field as the control. Input-output analysis method was adopted. The N output in the early rice-duck mutual ecosystem was 239.5 kg x hm(-2), in which, 12.77 kg x hm(-2) were from ducks, and the N output in the late rice-duck mutual ecosystem was 338.7 kg x hm(-2), in which, 23.35 kg x hm(-2) were from ducks. At the present N input level, there existed soil N deficit during the growth seasons of both early rice and late rice. The N input from duck sub-system was mainly from the feed N, and the cycling rate of the duck feces N recycled within the system was 2.5% during early rice growth season and 3.5% during late rice growth season. After late rice harvested, the soil N sequestration was 178.6 kg x hm(-2).

  17. 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.

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

    International Nuclear Information System (INIS)

    Lelievre Bernard; Feugier, Andre.

    1973-01-01

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

  19. New Fukui, dual and hyper-dual kernels as bond reactivity descriptors.

    Science.gov (United States)

    Franco-Pérez, Marco; Polanco-Ramírez, Carlos-A; Ayers, Paul W; Gázquez, José L; Vela, Alberto

    2017-06-21

    We define three new linear response indices with promising applications for bond reactivity using the mathematical framework of τ-CRT (finite temperature chemical reactivity theory). The τ-Fukui kernel is defined as the ratio between the fluctuations of the average electron density at two different points in the space and the fluctuations in the average electron number and is designed to integrate to the finite-temperature definition of the electronic Fukui function. When this kernel is condensed, it can be interpreted as a site-reactivity descriptor of the boundary region between two atoms. The τ-dual kernel corresponds to the first order response of the Fukui kernel and is designed to integrate to the finite temperature definition of the dual descriptor; it indicates the ambiphilic reactivity of a specific bond and enriches the traditional dual descriptor by allowing one to distinguish between the electron-accepting and electron-donating processes. Finally, the τ-hyper dual kernel is defined as the second-order derivative of the Fukui kernel and is proposed as a measure of the strength of ambiphilic bonding interactions. Although these quantities have never been proposed, our results for the τ-Fukui kernel and for τ-dual kernel can be derived in zero-temperature formulation of the chemical reactivity theory with, among other things, the widely-used parabolic interpolation model.

  20. Quasi-Dual-Packed-Kerneled Au49 (2,4-DMBT)27 Nanoclusters and the Influence of Kernel Packing on the Electrochemical Gap.

    Science.gov (United States)

    Liao, Lingwen; Zhuang, Shengli; Wang, Pu; Xu, Yanan; Yan, Nan; Dong, Hongwei; Wang, Chengming; Zhao, Yan; Xia, Nan; Li, Jin; Deng, Haiteng; Pei, Yong; Tian, Shi-Kai; Wu, Zhikun

    2017-10-02

    Although face-centered cubic (fcc), body-centered cubic (bcc), hexagonal close-packed (hcp), and other structured gold nanoclusters have been reported, it was unclear whether gold nanoclusters with mix-packed (fcc and non-fcc) kernels exist, and the correlation between kernel packing and the properties of gold nanoclusters is unknown. A Au 49 (2,4-DMBT) 27 nanocluster with a shell electron count of 22 has now been been synthesized and structurally resolved by single-crystal X-ray crystallography, which revealed that Au 49 (2,4-DMBT) 27 contains a unique Au 34 kernel consisting of one quasi-fcc-structured Au 21 and one non-fcc-structured Au 13 unit (where 2,4-DMBTH=2,4-dimethylbenzenethiol). Further experiments revealed that the kernel packing greatly influences the electrochemical gap (EG) and the fcc structure has a larger EG than the investigated non-fcc structure. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

  1. Effects of Extraction Methods on Phytochemicals of Rice Bran Oils Produced from Colored Rice.

    Science.gov (United States)

    Mingyai, Sukanya; Srikaeo, Khongsak; Kettawan, Aikkarach; Singanusong, Riantong; Nakagawa, Kiyotaka; Kimura, Fumiko; Ito, Junya

    2018-02-01

    Rice bran oil (RBO) especially from colored rice is rich in phytochemicals and has become popular in food, cosmetic, nutraceutical and pharmaceutical applications owing to its offering health benefits. This study determined the contents of phytochemicals including oryzanols, phytosterols, tocopherols (Toc) and tocotrienols (T3) in RBOs extracted using different methods namely cold-press extraction (CPE), solvent extraction (SE) and supercritical CO 2 extraction (SC-CO 2 ). Two colored rice, Red Jasmine rice (RJM, red rice) and Hom-nin rice (HN, black rice), were studied in comparison with the popular Thai fragrant rice Khao Dawk Mali 105 (KDML 105, white rice). RBOs were found to be the rich source of oryzanols, phytosterols, Toc and T3. Rice varieties had a greater effect on the phytochemicals concentrations than extraction methods. HN rice showed the significantly highest concentration of all phytochemicals, followed by RJM and KDML 105 rice, indicating that colored rice contained high concentration of phytochemicals in the oil than non-colored rice. The RBO samples extracted by the CPE method had a greater concentration of the phytochemicals than those extracted by the SC-CO 2 and SE methods, respectively. In terms of phytochemical contents, HN rice extracted using CPE method was found to be the best.

  2. Optimal kernel shape and bandwidth for atomistic support of continuum stress

    International Nuclear Information System (INIS)

    Ulz, Manfred H; Moran, Sean J

    2013-01-01

    The treatment of atomistic scale interactions via molecular dynamics simulations has recently found favour for multiscale modelling within engineering. The estimation of stress at a continuum point on the atomistic scale requires a pre-defined kernel function. This kernel function derives the stress at a continuum point by averaging the contribution from atoms within a region surrounding the continuum point. This averaging volume, and therefore the associated stress at a continuum point, is highly dependent on the bandwidth and shape of the kernel. In this paper we propose an effective and entirely data-driven strategy for simultaneously computing the optimal shape and bandwidth for the kernel. We thoroughly evaluate our proposed approach on copper using three classical elasticity problems. Our evaluation yields three key findings: firstly, our technique can provide a physically meaningful estimation of kernel bandwidth; secondly, we show that a uniform kernel is preferred, thereby justifying the default selection of this kernel shape in future work; and thirdly, we can reliably estimate both of these attributes in a data-driven manner, obtaining values that lead to an accurate estimation of the stress at a continuum point. (paper)

  3. 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.

  4. 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.

  5. A multi-resolution approach to heat kernels on discrete surfaces

    KAUST Repository

    Vaxman, Amir

    2010-07-26

    Studying the behavior of the heat diffusion process on a manifold is emerging as an important tool for analyzing the geometry of the manifold. Unfortunately, the high complexity of the computation of the heat kernel - the key to the diffusion process - limits this type of analysis to 3D models of modest resolution. We show how to use the unique properties of the heat kernel of a discrete two dimensional manifold to overcome these limitations. Combining a multi-resolution approach with a novel approximation method for the heat kernel at short times results in an efficient and robust algorithm for computing the heat kernels of detailed models. We show experimentally that our method can achieve good approximations in a fraction of the time required by traditional algorithms. Finally, we demonstrate how these heat kernels can be used to improve a diffusion-based feature extraction algorithm. © 2010 ACM.

  6. 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.

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

    Science.gov (United States)

    Jaturasitha, Sanchai; Ratanapradit, Punnares; Piawong, Witapong; Kreuzer, Michael

    2016-01-01

    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. PMID:26949957

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

    Science.gov (United States)

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

  9. A Heterogeneous Multi-core Architecture with a Hardware Kernel for Control Systems

    DEFF Research Database (Denmark)

    Li, Gang; Guan, Wei; Sierszecki, Krzysztof

    2012-01-01

    Rapid industrialisation has resulted in a demand for improved embedded control systems with features such as predictability, high processing performance and low power consumption. Software kernel implementation on a single processor is becoming more difficult to satisfy those constraints. This pa......Rapid industrialisation has resulted in a demand for improved embedded control systems with features such as predictability, high processing performance and low power consumption. Software kernel implementation on a single processor is becoming more difficult to satisfy those constraints......). Second, a heterogeneous multi-core architecture is investigated, focusing on its performance in relation to hard real-time constraints and predictable behavior. Third, the hardware implementation of HARTEX is designated to support the heterogeneous multi-core architecture. This hardware kernel has...... several advantages over a similar kernel implemented in software: higher-speed processing capability, parallel computation, and separation between the kernel itself and the applications being run. A microbenchmark has been used to compare the hardware kernel with the software kernel, and compare...

  10. Combining Lactic Acid Spray with Near-Infrared Radiation Heating To Inactivate Salmonella enterica Serovar Enteritidis on Almond and Pine Nut Kernels.

    Science.gov (United States)

    Ha, Jae-Won; Kang, Dong-Hyun

    2015-07-01

    The aim of this study was to investigate the efficacy of near-infrared radiation (NIR) heating combined with lactic acid (LA) sprays for inactivating Salmonella enterica serovar Enteritidis on almond and pine nut kernels and to elucidate the mechanisms of the lethal effect of the NIR-LA combined treatment. Also, the effect of the combination treatment on product quality was determined. Separately prepared S. Enteritidis phage type (PT) 30 and non-PT 30 S. Enteritidis cocktails were inoculated onto almond and pine nut kernels, respectively, followed by treatments with NIR or 2% LA spray alone, NIR with distilled water spray (NIR-DW), and NIR with 2% LA spray (NIR-LA). Although surface temperatures of nuts treated with NIR were higher than those subjected to NIR-DW or NIR-LA treatment, more S. Enteritidis survived after NIR treatment alone. The effectiveness of NIR-DW and NIR-LA was similar, but significantly more sublethally injured cells were recovered from NIR-DW-treated samples. We confirmed that the enhanced bactericidal effect of the NIR-LA combination may not be attributable to cell membrane damage per se. NIR heat treatment might allow S. Enteritidis cells to become permeable to applied LA solution. The NIR-LA treatment (5 min) did not significantly (P > 0.05) cause changes in the lipid peroxidation parameters, total phenolic contents, color values, moisture contents, and sensory attributes of nut kernels. Given the results of the present study, NIR-LA treatment may be a potential intervention for controlling food-borne pathogens on nut kernel products. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

  11. 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.)

  12. Studies on some agronomic and quality characteristics of 271 induced early mutants of rice (Oryza sativa L. cv. Nizersail)

    International Nuclear Information System (INIS)

    Rahman, Mostafizur; Miah, A.J.; Mansur, M.A.; Kaul, A.K.

    1980-01-01

    Nizersail, the most popular, recommended rice variety in Bangladesh, was subjected to gamma-irradiation (10 - 25 kR) or ethyl methane sulfonate (EMS) (0.75 - 1.50%) treatments to obtain the mutants with stiff straw and early maturity. In the M 2 generation, 29 gamma-ray- and 8 EMS-induced mutants were selected mainly for short culm length and earliness. Further selections were made in the segregating M 3 and M 4 populations, and finally 400 plants with short culm length were obtained. These 400 selections were grown in M 5 lines, and 271 of these lines were analyzed for several characters. Heading time had singificantly shifted towards earliness in 40 lines. Yield per plant, 1,000-kernel weight, the length/breadth ratio of kernels, alkali spreading index value (indicator of amylose content) and dye-binding capacity (indicator of protein content) were significantly higher than those in the mother variety in 10 - 30% of the lines examined. However, no positive correlation among these characters was observed. Significant negative correlations were observed between heading time and 1,000-kernel weight, and between yield per plant and dye-binding capacity. These results suggest that the early heading plants may produce fewer tillers with bolder seeds, and that high yielding types may not simultaneously show high protein content. (Kaihara, S.)

  13. 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.

  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. DETERMINATION OF SPATIAL INTEGRATION AND SUBSTITUTION OF FOREIGN RICE FOR LOCAL RICE IN GHANA

    Directory of Open Access Journals (Sweden)

    Philip Kofi ADOM

    2014-11-01

    Full Text Available This study tested for spatial integration in the rice market and the substitution of imported rice for local rice in Ghana. It is established that the markets for domestic imported rice are well-integrated, but not complete. The imperfect spatial integration of domestic foreign rice markets implies that the market provides opportunities for arbitrage. Price leadership roles are found to be determined by the kind of sub-inter-regional-trade network defined. However, in all, the Accra market emerged as a dominant market leader in the domestic foreign rice market. There is evidence of significant regional substitution of foreign rice for local rice in the long run, but the result is mixed in the short run. The result that local rice is not a perfect substitute for imported rice implies that price disincentive measures such as increasing the import tariffs on foreign rice will only produce a mild effect on increasing the producer price faced by local rice farmers, but aggravate the burden on households’ budget.

  16. [Effects of fish on field resource utilization and rice growth in rice-fish coculture].

    Science.gov (United States)

    Zhang, Jian; Hu, Liang Liang; Ren, Wei Zheng; Guo, Liang; Wu, Min Fang; Tang, Jian Jun; Chen, Xin

    2017-01-01

    Rice field can provide habitat for fish and other aquatic animals. Rice-fish coculture can increase rice yield and simultaneously reduce the use of chemicals through reducing rice pest occurrence and nutrient complementary use. However, how fish uses food sources (e.g. phytoplankton, weeds, duckweed, macro-algal and snail) from rice field, and whether the nutrients releasing from those food sources due to fish transforming can improve rice growth are still unknown. Here, we conducted two field experiments to address these questions. One was to investigate the pattern of fish activity in the field using the method of video recording. The other was to examine the utilization of field resources by fish using stable isotope technology. Rice growth and rice yield were also exa-mined. Results showed that fish tended to be more active and significantly expanded the activity range in the rice-fish coculture compared to fish monoculture (fish not living together with rice plants). The contributions of 3 potential aquatic organisms (duckweed, phytoplankton and snail) to fish dietary were 22.7%, 34.8% and 30.0% respectively under rice-fish coculture without feed. Under the treatment with feed, however, the contributions of these 3 aquatic organisms to the fish die-tary were 8.9%, 5.9% and 1.6% respectively. The feed contribution was 71.0%. Rice-fish coculture significantly increased the nitrogen concentration in rice leaves, prolonged tillering stage by 10-12 days and increased rice spike rate and yield. The results suggested that raising fish in paddy field may transform the nutrients contained in field resources to bioavailable for rice plants through fish feeding activity, which can improve rice growth and rice yield.

  17. 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

  18. 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.

  19. 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.

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

    African Journals Online (AJOL)

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

  1. A framework for dense triangular matrix kernels on various manycore architectures

    KAUST Repository

    Charara, Ali

    2017-06-06

    We present a new high-performance framework for dense triangular Basic Linear Algebra Subroutines (BLAS) kernels, ie, triangular matrix-matrix multiplication (TRMM) and triangular solve (TRSM), on various manycore architectures. This is an extension of a previous work on a single GPU by the same authors, presented at the EuroPar\\'16 conference, in which we demonstrated the effectiveness of recursive formulations in enhancing the performance of these kernels. In this paper, the performance of triangular BLAS kernels on a single GPU is further enhanced by implementing customized in-place CUDA kernels for TRMM and TRSM, which are called at the bottom of the recursion. In addition, a multi-GPU implementation of TRMM and TRSM is proposed and we show an almost linear performance scaling, as the number of GPUs increases. Finally, the algorithmic recursive formulation of these triangular BLAS kernels is in fact oblivious to the targeted hardware architecture. We, therefore, port these recursive kernels to homogeneous x86 hardware architectures by relying on the vendor optimized BLAS implementations. Results reported on various hardware architectures highlight a significant performance improvement against state-of-the-art implementations. These new kernels are freely available in the KAUST BLAS (KBLAS) open-source library at https://github.com/ecrc/kblas.

  2. A framework for dense triangular matrix kernels on various manycore architectures

    KAUST Repository

    Charara, Ali; Keyes, David E.; Ltaief, Hatem

    2017-01-01

    We present a new high-performance framework for dense triangular Basic Linear Algebra Subroutines (BLAS) kernels, ie, triangular matrix-matrix multiplication (TRMM) and triangular solve (TRSM), on various manycore architectures. This is an extension of a previous work on a single GPU by the same authors, presented at the EuroPar'16 conference, in which we demonstrated the effectiveness of recursive formulations in enhancing the performance of these kernels. In this paper, the performance of triangular BLAS kernels on a single GPU is further enhanced by implementing customized in-place CUDA kernels for TRMM and TRSM, which are called at the bottom of the recursion. In addition, a multi-GPU implementation of TRMM and TRSM is proposed and we show an almost linear performance scaling, as the number of GPUs increases. Finally, the algorithmic recursive formulation of these triangular BLAS kernels is in fact oblivious to the targeted hardware architecture. We, therefore, port these recursive kernels to homogeneous x86 hardware architectures by relying on the vendor optimized BLAS implementations. Results reported on various hardware architectures highlight a significant performance improvement against state-of-the-art implementations. These new kernels are freely available in the KAUST BLAS (KBLAS) open-source library at https://github.com/ecrc/kblas.

  3. 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

  4. 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.

  5. 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.

  6. Low-Resolution Tactile Image Recognition for Automated Robotic Assembly Using Kernel PCA-Based Feature Fusion and Multiple Kernel Learning-Based Support Vector Machine

    Directory of Open Access Journals (Sweden)

    Yi-Hung Liu

    2014-01-01

    Full Text Available In this paper, we propose a robust tactile sensing image recognition scheme for automatic robotic assembly. First, an image reprocessing procedure is designed to enhance the contrast of the tactile image. In the second layer, geometric features and Fourier descriptors are extracted from the image. Then, kernel principal component analysis (kernel PCA is applied to transform the features into ones with better discriminating ability, which is the kernel PCA-based feature fusion. The transformed features are fed into the third layer for classification. In this paper, we design a classifier by combining the multiple kernel learning (MKL algorithm and support vector machine (SVM. We also design and implement a tactile sensing array consisting of 10-by-10 sensing elements. Experimental results, carried out on real tactile images acquired by the designed tactile sensing array, show that the kernel PCA-based feature fusion can significantly improve the discriminating performance of the geometric features and Fourier descriptors. Also, the designed MKL-SVM outperforms the regular SVM in terms of recognition accuracy. The proposed recognition scheme is able to achieve a high recognition rate of over 85% for the classification of 12 commonly used metal parts in industrial applications.

  7. 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 ...

  8. 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...

  9. 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.

  10. 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

  11. 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.

  12. 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.

  13. A survey of kernel-type estimators for copula and their applications

    Science.gov (United States)

    Sumarjaya, I. W.

    2017-10-01

    Copulas have been widely used to model nonlinear dependence structure. Main applications of copulas include areas such as finance, insurance, hydrology, rainfall to name but a few. The flexibility of copula allows researchers to model dependence structure beyond Gaussian distribution. Basically, a copula is a function that couples multivariate distribution functions to their one-dimensional marginal distribution functions. In general, there are three methods to estimate copula. These are parametric, nonparametric, and semiparametric method. In this article we survey kernel-type estimators for copula such as mirror reflection kernel, beta kernel, transformation method and local likelihood transformation method. Then, we apply these kernel methods to three stock indexes in Asia. The results of our analysis suggest that, albeit variation in information criterion values, the local likelihood transformation method performs better than the other kernel methods.

  14. Effects of White Rice, Brown Rice and Germinated Brown Rice on Antioxidant Status of Type 2 Diabetic Rats

    OpenAIRE

    Imam, Mustapha Umar; Musa, Siti Nor Asma; Azmi, Nur Hanisah; Ismail, Maznah

    2012-01-01

    Oxidative stress is implicated in the pathogenesis of diabetic complications, and can be increased by diet like white rice (WR). Though brown rice (BR) and germinated brown rice (GBR) have high antioxidant potentials as a result of their bioactive compounds, reports of their effects on oxidative stress-related conditions such as type 2 diabetes are lacking. We hypothesized therefore that if BR and GBR were to improve antioxidant status, they would be better for rice consuming populations inst...

  15. Irradiation performance of coated fuel particles with fission product retaining kernel additives

    International Nuclear Information System (INIS)

    Foerthmann, R.

    1979-10-01

    The four irradiation experiments FRJ2-P17, FRJ2-P18, FRJ2-P19, and FRJ2-P20 for testing the efficiency of fission product-retaining kernel additives in coated fuel particles are described. The evaluation of the obtained experimental data led to the following results: - zirconia and alumina kernel additives are not suitable for an effective fission product retention in oxide fuel kernels, - alumina-silica kernel additives reduce the in-pile release of Sr 90 and Ba 140 from BISO-coated particles at temperatures of about 1200 0 C by two orders of magnitude, and the Cs release from kernels by one order of magnitude, - effective transport coefficients including all parameters which contribute to kernel release are given for (Th,U)O 2 mixed oxide kernels and low enriched UO 2 kernels containing 5 wt.% alumina-silica additives: 10g sub(K)/cm 2 s -1 = - 36 028/T + 6,261 (Sr 90), 10g Dsub(K)/cm 2 c -2 = - 29 646/T + 5,826 (Cs 134/137), alumina-silica kernel additives are ineffective for retaining Ag 110 m in coated particles. However, also an intact SiC-interlayer was found not to be effective at temperatures above 1200 0 C, - the penetration of the buffer layer by fission product containing eutectic additive melt during irradiation can be avoided by using additives which consist of alumina and mullite without an excess of silica, - annealing of LASER-failed irradiated particles and the irradiation test FRJ12-P20 indicate that the efficiency of alumina-silica kernel additives is not altered if the coating becomes defect. (orig.) [de

  16. Pathway-Based Kernel Boosting for the Analysis of Genome-Wide Association Studies

    Science.gov (United States)

    Manitz, Juliane; Burger, Patricia; Amos, Christopher I.; Chang-Claude, Jenny; Wichmann, Heinz-Erich; Kneib, Thomas; Bickeböller, Heike

    2017-01-01

    The analysis of genome-wide association studies (GWAS) benefits from the investigation of biologically meaningful gene sets, such as gene-interaction networks (pathways). We propose an extension to a successful kernel-based pathway analysis approach by integrating kernel functions into a powerful algorithmic framework for variable selection, to enable investigation of multiple pathways simultaneously. We employ genetic similarity kernels from the logistic kernel machine test (LKMT) as base-learners in a boosting algorithm. A model to explain case-control status is created iteratively by selecting pathways that improve its prediction ability. We evaluated our method in simulation studies adopting 50 pathways for different sample sizes and genetic effect strengths. Additionally, we included an exemplary application of kernel boosting to a rheumatoid arthritis and a lung cancer dataset. Simulations indicate that kernel boosting outperforms the LKMT in certain genetic scenarios. Applications to GWAS data on rheumatoid arthritis and lung cancer resulted in sparse models which were based on pathways interpretable in a clinical sense. Kernel boosting is highly flexible in terms of considered variables and overcomes the problem of multiple testing. Additionally, it enables the prediction of clinical outcomes. Thus, kernel boosting constitutes a new, powerful tool in the analysis of GWAS data and towards the understanding of biological processes involved in disease susceptibility. PMID:28785300

  17. Pathway-Based Kernel Boosting for the Analysis of Genome-Wide Association Studies.

    Science.gov (United States)

    Friedrichs, Stefanie; Manitz, Juliane; Burger, Patricia; Amos, Christopher I; Risch, Angela; Chang-Claude, Jenny; Wichmann, Heinz-Erich; Kneib, Thomas; Bickeböller, Heike; Hofner, Benjamin

    2017-01-01

    The analysis of genome-wide association studies (GWAS) benefits from the investigation of biologically meaningful gene sets, such as gene-interaction networks (pathways). We propose an extension to a successful kernel-based pathway analysis approach by integrating kernel functions into a powerful algorithmic framework for variable selection, to enable investigation of multiple pathways simultaneously. We employ genetic similarity kernels from the logistic kernel machine test (LKMT) as base-learners in a boosting algorithm. A model to explain case-control status is created iteratively by selecting pathways that improve its prediction ability. We evaluated our method in simulation studies adopting 50 pathways for different sample sizes and genetic effect strengths. Additionally, we included an exemplary application of kernel boosting to a rheumatoid arthritis and a lung cancer dataset. Simulations indicate that kernel boosting outperforms the LKMT in certain genetic scenarios. Applications to GWAS data on rheumatoid arthritis and lung cancer resulted in sparse models which were based on pathways interpretable in a clinical sense. Kernel boosting is highly flexible in terms of considered variables and overcomes the problem of multiple testing. Additionally, it enables the prediction of clinical outcomes. Thus, kernel boosting constitutes a new, powerful tool in the analysis of GWAS data and towards the understanding of biological processes involved in disease susceptibility.

  18. Dose calculation methods in photon beam therapy using energy deposition kernels

    International Nuclear Information System (INIS)

    Ahnesjoe, A.

    1991-01-01

    The problem of calculating accurate dose distributions in treatment planning of megavoltage photon radiation therapy has been studied. New dose calculation algorithms using energy deposition kernels have been developed. The kernels describe the transfer of energy by secondary particles from a primary photon interaction site to its surroundings. Monte Carlo simulations of particle transport have been used for derivation of kernels for primary photon energies form 0.1 MeV to 50 MeV. The trade off between accuracy and calculational speed has been addressed by the development of two algorithms; one point oriented with low computional overhead for interactive use and one for fast and accurate calculation of dose distributions in a 3-dimensional lattice. The latter algorithm models secondary particle transport in heterogeneous tissue by scaling energy deposition kernels with the electron density of the tissue. The accuracy of the methods has been tested using full Monte Carlo simulations for different geometries, and found to be superior to conventional algorithms based on scaling of broad beam dose distributions. Methods have also been developed for characterization of clinical photon beams in entities appropriate for kernel based calculation models. By approximating the spectrum as laterally invariant, an effective spectrum and dose distribution for contaminating charge particles are derived form depth dose distributions measured in water, using analytical constraints. The spectrum is used to calculate kernels by superposition of monoenergetic kernels. The lateral energy fluence distribution is determined by deconvolving measured lateral dose distributions by a corresponding pencil beam kernel. Dose distributions for contaminating photons are described using two different methods, one for estimation of the dose outside of the collimated beam, and the other for calibration of output factors derived from kernel based dose calculations. (au)

  19. Boundary singularity of Poisson and harmonic Bergman kernels

    Czech Academy of Sciences Publication Activity Database

    Engliš, Miroslav

    2015-01-01

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

  20. 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…

  1. 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.

  2. Methodical characterization of rice ( Oryza sativa bran oil from Pakistan

    Directory of Open Access Journals (Sweden)

    Mahmood, Zahid

    2005-06-01

    Full Text Available The hexane-extracted oil content of four varieties of rice (Oryza sativa viz. Super Kernel, 386, 385 and Basmati, bran was ranged 14.70-19.10 %. Other physical and chemical parameters of the extracted oils were as follow: Iodine value 112.40, 109.80, 105.1 and 103.70; refractive index ( 40 °C 1.4650, 1.4680, 1.4657 and 1.4660; density ( 40 °C 0.919, 0.913, 0.909 and 0.911; saponification value 183, 177, 186 and 190; unsaponifiable matter 6.15, 5.60, 4.98 and 5.40 % respectively. Tocopherols ( α, γ and δ in the oils were: 284.00, 175.12, 180.42, 300.06; 83.40, 98.70, 120.70, 90.60; 75.16, 57.20, 39.32, 83.00 mg/kg respectively. The contents of tocotrienols ( α, γ and δ in the oils were: 120.30, 106.00, 95.20, 135.74; 196.00, 125.00, 210.0, 276.41; 72.50, 20.00, 39.30, 64.00 mg/kg respectively. The amount of γ - Oryzanol in the investigated oils was ranged 415.12-802.05 The induction periods (Rancimat, 20 L/h, 120 °C of the crude oils were 6.81, 5.99, 6.39 and 7.40 h respectively. The major sterol fractions of the oils consisted of campesterol ranged (10.10-19.20%, stigmasterol (14.00-19.28 %, b -sitosterol (49.30-58.20 %, and D5 ,avenasterol (8.14-13.05 %. The investigated varieties ( Super Kernel, 386, 385 and Basmati of rice bran oil were found to contain high levels of oleic acid 42.67, 38.59, 40.68 and 36.78 % followed by linoleic and palmitic acids 31.58, 33.80, 28.70, 30.51 and 17.00, 14.88, 19.63, 20.00 % respectively. The contents of myristic, stearic and arachidic acids was 1.50, 2.02, 4.28, 1.00; 2.64, 2.87, 4.02, 7.48; and 1.28, 3.00, 1.00, 1.00 % respectively. A number of parameters of the investigated rice bran oils indigenous to Pakistan were comparable to those of typical rice bran and some other vegetable oils, reported in the literature. The results of the present analysis as compared with those of different vegetable oils demonstrated rice bran to be a potential oil source and thus could be useful

  3. 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.

  4. 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

  5. Mutant-inducing effect of γ-ray irradiation for hybrid rice F1 derived from cross of black glutinous rice x wild rice

    International Nuclear Information System (INIS)

    Mao Dezhi; Tang Yilan

    1998-01-01

    The hybrid rice F 1 plant derived from the back crossing of glutinous rice x wild rice was irradiated with γ-ray. The result of investigation to the induced mutant showed that through the selection and backcross, a black glutinous rice strain with the short stem, cold tolerance and high yield was developed. The analysis of the ability of heredity variance showed that the selection was effective for the husk colour, black glutinous and black Indica rice, but ineffective for the white Indica rice and seed setting

  6. Australian wild rice reveals pre-domestication origin of polymorphism deserts in rice genome.

    Science.gov (United States)

    Krishnan S, Gopala; Waters, Daniel L E; Henry, Robert J

    2014-01-01

    Rice is a major source of human food with a predominantly Asian production base. Domestication involved selection of traits that are desirable for agriculture and to human consumers. Wild relatives of crop plants are a source of useful variation which is of immense value for crop improvement. Australian wild rices have been isolated from the impacts of domestication in Asia and represents a source of novel diversity for global rice improvement. Oryza rufipogon is a perennial wild progenitor of cultivated rice. Oryza meridionalis is a related annual species in Australia. We have examined the sequence of the genomes of AA genome wild rices from Australia that are close relatives of cultivated rice through whole genome re-sequencing. Assembly of the resequencing data to the O. sativa ssp. japonica cv. Nipponbare shows that Australian wild rices possess 2.5 times more single nucleotide polymorphisms than in the Asian wild rice and cultivated O. sativa ssp. indica. Analysis of the genome of domesticated rice reveals regions of low diversity that show very little variation (polymorphism deserts). Both the perennial and annual wild rice from Australia show a high degree of conservation of sequence with that found in cultivated rice in the same 4.58 Mbp region on chromosome 5, which suggests that some of the 'polymorphism deserts' in this and other parts of the rice genome may have originated prior to domestication due to natural selection. Analysis of genes in the 'polymorphism deserts' indicates that this selection may have been due to biotic or abiotic stress in the environment of early rice relatives. Despite having closely related sequences in these genome regions, the Australian wild populations represent an invaluable source of diversity supporting rice food security.

  7. Australian wild rice reveals pre-domestication origin of polymorphism deserts in rice genome.

    Directory of Open Access Journals (Sweden)

    Gopala Krishnan S

    Full Text Available BACKGROUND: Rice is a major source of human food with a predominantly Asian production base. Domestication involved selection of traits that are desirable for agriculture and to human consumers. Wild relatives of crop plants are a source of useful variation which is of immense value for crop improvement. Australian wild rices have been isolated from the impacts of domestication in Asia and represents a source of novel diversity for global rice improvement. Oryza rufipogon is a perennial wild progenitor of cultivated rice. Oryza meridionalis is a related annual species in Australia. RESULTS: We have examined the sequence of the genomes of AA genome wild rices from Australia that are close relatives of cultivated rice through whole genome re-sequencing. Assembly of the resequencing data to the O. sativa ssp. japonica cv. Nipponbare shows that Australian wild rices possess 2.5 times more single nucleotide polymorphisms than in the Asian wild rice and cultivated O. sativa ssp. indica. Analysis of the genome of domesticated rice reveals regions of low diversity that show very little variation (polymorphism deserts. Both the perennial and annual wild rice from Australia show a high degree of conservation of sequence with that found in cultivated rice in the same 4.58 Mbp region on chromosome 5, which suggests that some of the 'polymorphism deserts' in this and other parts of the rice genome may have originated prior to domestication due to natural selection. CONCLUSIONS: Analysis of genes in the 'polymorphism deserts' indicates that this selection may have been due to biotic or abiotic stress in the environment of early rice relatives. Despite having closely related sequences in these genome regions, the Australian wild populations represent an invaluable source of diversity supporting rice food security.

  8. Perspectives for practical application of the combined fuel kernels in VVER-type reactors

    International Nuclear Information System (INIS)

    Baranov, V.; Ternovykh, M.; Tikhomirov, G.; Khlunov, A.; Tenishev, A.; Kurina, I.

    2011-01-01

    The paper considers the main physical processes that take place in fuel kernels under real operation conditions of VVER-type reactors. Main attention is given to the effects induced by combinations of layers with different physical properties inside of fuel kernels on these physical processes. Basic neutron-physical characteristics were calculated for some combined fuel kernels in fuel rods of VVER-type reactors. There are many goals in development of the combined fuel kernels, and these goals define selecting the combinations and compositions of radial layers inside of the kernels. For example, the slower formation of the rim-layer on outer surface of the kernels made of enriched uranium dioxide can be achieved by introduction of inner layer made of natural or depleted uranium dioxide. Other potential goals (lower temperature in the kernel center, better conditions for burn-up of neutron poisons, better retention of toxic materials) could be reached by other combinations of fuel compositions in central and peripheral zones of the fuel kernels. Also, the paper presents the results obtained in experimental manufacturing of the combined fuel pellets. (authors)

  9. Ethanol production from rice on radioactively contaminated field toward sustainable rice farming

    International Nuclear Information System (INIS)

    Yokoyama, Shinya; Izumi, Bintaro; Oki, Kazuo

    2011-01-01

    Radioactive species such as 137 Cs were discharged from Fukushima Daiichi Nuclear Power Plant which was severely damaged by the enormous earthquake and tsunami. Cropland has been radioactively contaminated by 137 Cs etc. and it seems impossible to plant rice due to the non-suitability for food. According to the reports, 137 Cs transferred into the rice from soil is less than 1% on the average. Therefore, it is expected that the concentration of 137 Cs in bioethanol will be well below the tentative restriction value even if bioethanol could be produced from the rice. It is proposed that the rice field should be filled with water to avoid the flow of runoff contaminated by radioactive cesium compounds because they are insoluble in aqueous phase and that bioethanol should be produced from the rice in order to maintain the multifunction of rice field and to continue the agriculture. If rice farming is halted and neglected, agricultural function of rice field as well as local community will be permanently destroyed. (author)

  10. Dry co-digestion of sewage sludge and rice straw under mesophilic and thermophilic anaerobic conditions.

    Science.gov (United States)

    Chu, Xiangqian; Wu, Guangxue; Wang, Jiaquan; Hu, Zhen-Hu

    2015-12-01

    Dry anaerobic digestion of sewage sludge can recover biogas as energy; however, its low C/N ratio limits it as a single substrate in the anaerobic digestion. Rice straw is an abundant agricultural residue in China, which is rich in carbon and can be used as carbon source. In the present study, the performance of dry co-digestion of sewage sludge and rice straw was investigated under mesophilic (35 °C) and thermophilic (55 °C) conditions. The operational factors impacting dry co-digestion of sewage sludge and rice straw such as C/N ratio, moisture content, and initial pH were explored under mesophilic conditions. The results show that low C/N ratios resulted in a higher biogas production rate, but a lower specific biogas yield; low moisture content of 65 % resulted in the instability of the digestion system and a low specific biogas yield. Initial pH ranging 7.0-9.0 did not affect the performance of the anaerobic digestion. The C/N ratio of 26-29:1, moisture content of 70-80 %, and pH 7.0-9.0 resulted in good performance in the dry mesophilic co-digestion of sewage sludge and rice straw. As compared with mesophilic digestion, thermophilic co-digestion of sewage sludge and rice straw significantly enhanced the degradation efficiency of the substrates and the specific biogas yield (p sewage sludge under mesophilic and thermophilic conditions.

  11. 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 ...

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

    Science.gov (United States)

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

  13. 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...

  14. 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...

  15. Effect of Interplanting with Zero Tillage and Straw Manure on Rice Growth and Rice Quality

    Directory of Open Access Journals (Sweden)

    Shi-ping LIU

    2007-09-01

    Full Text Available The interplanting with zero-tillage of rice, i.e. direct sowing rice 10–20 days before wheat harvesting, and remaining about 30-cm high stubble after cutting wheat or rice with no tillage, is a new cultivation technology in wheat-rice rotation system. To study the effects of interplanting with zero tillage and straw manure on rice growth and quality, an experiment was conducted in a wheat-rotation rotation system. Four treatments, i.e. ZIS (Zero-tillage, straw manure and rice interplanting, ZI (Zero-tillage, no straw manure and rice interplanting, PTS (Plowing tillage, straw manure and rice transplanting, and PT (Plowing tillage, no straw manure and rice transplanting, were used. ZIS reduced plant height, leaf area per plant and the biomass of rice plants, but the biomass accumulation of rice at the late stage was quicker than that under conventional transplanting cultivation. In the first year (2002, there was no significant difference in rice yield among the four treatments. However, rice yield decreased in interplanting with zero-tillage in the second year (2003. Compared with the transplanting treatments, the number of filled grains per panicle decreased but 1000-grain weight increased in interplanting with zero-tillage, which were the main factors resulting in higher yield. Interplanting with zero-tillage improved the milling and appearance qualities of rice. The rates of milled and head rice increased while chalky rice rate and chalkiness decreased in interplanting with zero-tillage. Zero-tillage and interplanting also affected rice nutritional and cooking qualities. In 2002, ZIS showed raised protein content, decreased amylose content, softer gel consistency, resulting in improved rice quality. In 2003, zero-tillage and interplanting decreased protein content and showed similar amylose content as compared with transplanting treatments. Moreover, protein content in PTS was obviously increased in comparison with the other three treatments

  16. An overview of the sustainability of rice agroecosystem through rice-fish integration

    International Nuclear Information System (INIS)

    Ahyaudin Ali

    2002-01-01

    Rice-fish integration in the rice agroecosystem has been introduced and is expanding in Malaysia. This type of farm integration has resulted in land optimization, thus enabling farmers to grow both fish and rice in one farming system. Introducing fish into the ricefield has also increased seasonal income as well as reduced pesticide use. Although basic ecological knowledge on rice-fish integration has allowed rice-fish integration to be introduced, further research is required to allow for fine tuning of the methodologies used. Thus research on the ecology, management, production methods and the characterization of rice-fish farming system of Malaysia is needed. Further characterization and description is needed on the ecology of the rice-fish farming system of Malaysia in terms of production, food webs, nutrient flow and system diversity. To increase the sustainability efficiency and productivity of the system, implementation of management techniques formulated through research is required. (Author)

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

    NARCIS (Netherlands)

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

    2010-01-01

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

  18. 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.

  19. 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

  20. DNA sequence+shape kernel enables alignment-free modeling of transcription factor binding.

    Science.gov (United States)

    Ma, Wenxiu; Yang, Lin; Rohs, Remo; Noble, William Stafford

    2017-10-01

    Transcription factors (TFs) bind to specific DNA sequence motifs. Several lines of evidence suggest that TF-DNA binding is mediated in part by properties of the local DNA shape: the width of the minor groove, the relative orientations of adjacent base pairs, etc. Several methods have been developed to jointly account for DNA sequence and shape properties in predicting TF binding affinity. However, a limitation of these methods is that they typically require a training set of aligned TF binding sites. We describe a sequence + shape kernel that leverages DNA sequence and shape information to better understand protein-DNA binding preference and affinity. This kernel extends an existing class of k-mer based sequence kernels, based on the recently described di-mismatch kernel. Using three in vitro benchmark datasets, derived from universal protein binding microarrays (uPBMs), genomic context PBMs (gcPBMs) and SELEX-seq data, we demonstrate that incorporating DNA shape information improves our ability to predict protein-DNA binding affinity. In particular, we observe that (i) the k-spectrum + shape model performs better than the classical k-spectrum kernel, particularly for small k values; (ii) the di-mismatch kernel performs better than the k-mer kernel, for larger k; and (iii) the di-mismatch + shape kernel performs better than the di-mismatch kernel for intermediate k values. The software is available at https://bitbucket.org/wenxiu/sequence-shape.git. rohs@usc.edu or william-noble@uw.edu. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

  1. Multiple Kernel Sparse Representation based Orthogonal Discriminative Projection and Its Cost-Sensitive Extension.

    Science.gov (United States)

    Zhang, Guoqing; Sun, Huaijiang; Xia, Guiyu; Sun, Quansen

    2016-07-07

    Sparse representation based classification (SRC) has been developed and shown great potential for real-world application. Based on SRC, Yang et al. [10] devised a SRC steered discriminative projection (SRC-DP) method. However, as a linear algorithm, SRC-DP cannot handle the data with highly nonlinear distribution. Kernel sparse representation-based classifier (KSRC) is a non-linear extension of SRC and can remedy the drawback of SRC. KSRC requires the use of a predetermined kernel function and selection of the kernel function and its parameters is difficult. Recently, multiple kernel learning for SRC (MKL-SRC) [22] has been proposed to learn a kernel from a set of base kernels. However, MKL-SRC only considers the within-class reconstruction residual while ignoring the between-class relationship, when learning the kernel weights. In this paper, we propose a novel multiple kernel sparse representation-based classifier (MKSRC), and then we use it as a criterion to design a multiple kernel sparse representation based orthogonal discriminative projection method (MK-SR-ODP). The proposed algorithm aims at learning a projection matrix and a corresponding kernel from the given base kernels such that in the low dimension subspace the between-class reconstruction residual is maximized and the within-class reconstruction residual is minimized. Furthermore, to achieve a minimum overall loss by performing recognition in the learned low-dimensional subspace, we introduce cost information into the dimensionality reduction method. The solutions for the proposed method can be efficiently found based on trace ratio optimization method [33]. Extensive experimental results demonstrate the superiority of the proposed algorithm when compared with the state-of-the-art methods.

  2. 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.

  3. Feature Selection and Kernel Learning for Local Learning-Based Clustering.

    Science.gov (United States)

    Zeng, Hong; Cheung, Yiu-ming

    2011-08-01

    The performance of the most clustering algorithms highly relies on the representation of data in the input space or the Hilbert space of kernel methods. This paper is to obtain an appropriate data representation through feature selection or kernel learning within the framework of the Local Learning-Based Clustering (LLC) (Wu and Schölkopf 2006) method, which can outperform the global learning-based ones when dealing with the high-dimensional data lying on manifold. Specifically, we associate a weight to each feature or kernel and incorporate it into the built-in regularization of the LLC algorithm to take into account the relevance of each feature or kernel for the clustering. Accordingly, the weights are estimated iteratively in the clustering process. We show that the resulting weighted regularization with an additional constraint on the weights is equivalent to a known sparse-promoting penalty. Hence, the weights of those irrelevant features or kernels can be shrunk toward zero. Extensive experiments show the efficacy of the proposed methods on the benchmark data sets.

  4. 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.

  5. 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.

  6. Fuzzy-based multi-kernel spherical support vector machine for ...

    Indian Academy of Sciences (India)

    In the proposed classifier, we design a new multi-kernel function based on the fuzzy triangular membership function. Finally, a newly developed multi-kernel function is incorporated into the spherical support vector machine to enhance the performance significantly. The experimental results are evaluated and performance is ...

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

    Science.gov (United States)

    Binol, Hamidullah; Bal, Abdullah; Cukur, Huseyin

    2015-10-01

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

  8. Objective evaluation of whiteness of cooked rice and rice cakes using a portable spectrophotometer.

    Science.gov (United States)

    Goto, Hajime; Asanome, Noriyuki; Suzuki, Keitaro; Sano, Tomoyoshi; Saito, Hiroshi; Abe, Yohei; Chuba, Masaru; Nishio, Takeshi

    2014-03-01

    The whiteness of cooked rice and rice cakes was evaluated using a portable spectrophotometer with a whiteness index (WI). Also, by using boiled rice for measurement of Mido values by Mido Meter, it was possible to infer the whiteness of cooked rice without rice cooking. In the analysis of varietal differences of cooked rice, 'Tsuyahime', 'Koshihikari' and 'Koshinokaori' showed high whiteness, while 'Satonoyuki' had inferior whiteness. The whiteness of rice cakes made from 'Koyukimochi' and 'Dewanomochi' was higher than the whiteness of those made from 'Himenomochi' and 'Koganemochi'. While there was a significant correlation (r = 0.84) between WI values and whiteness scores of cooked rice by the sensory test, no correlation was detected between the whiteness scores and Mido values, indicating that the values obtained by a spectrophotometer differ from those obtained by a Mido Meter. Thus, a spectrophotometer may be a novel device for measurement of rice eating quality.

  9. 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

  10. Finite frequency traveltime sensitivity kernels for acoustic anisotropic media: Angle dependent bananas

    KAUST Repository

    Djebbi, Ramzi

    2013-08-19

    Anisotropy is an inherent character of the Earth subsurface. It should be considered for modeling and inversion. The acoustic VTI wave equation approximates the wave behavior in anisotropic media, and especially it\\'s kinematic characteristics. To analyze which parts of the model would affect the traveltime for anisotropic traveltime inversion methods, especially for wave equation tomography (WET), we drive the sensitivity kernels for anisotropic media using the VTI acoustic wave equation. A Born scattering approximation is first derived using the Fourier domain acoustic wave equation as a function of perturbations in three anisotropy parameters. Using the instantaneous traveltime, which unwraps the phase, we compute the kernels. These kernels resemble those for isotropic media, with the η kernel directionally dependent. They also have a maximum sensitivity along the geometrical ray, which is more realistic compared to the cross-correlation based kernels. Focusing on diving waves, which is used more often, especially recently in waveform inversion, we show sensitivity kernels in anisotropic media for this case.

  11. Finite frequency traveltime sensitivity kernels for acoustic anisotropic media: Angle dependent bananas

    KAUST Repository

    Djebbi, Ramzi; Alkhalifah, Tariq Ali

    2013-01-01

    Anisotropy is an inherent character of the Earth subsurface. It should be considered for modeling and inversion. The acoustic VTI wave equation approximates the wave behavior in anisotropic media, and especially it's kinematic characteristics. To analyze which parts of the model would affect the traveltime for anisotropic traveltime inversion methods, especially for wave equation tomography (WET), we drive the sensitivity kernels for anisotropic media using the VTI acoustic wave equation. A Born scattering approximation is first derived using the Fourier domain acoustic wave equation as a function of perturbations in three anisotropy parameters. Using the instantaneous traveltime, which unwraps the phase, we compute the kernels. These kernels resemble those for isotropic media, with the η kernel directionally dependent. They also have a maximum sensitivity along the geometrical ray, which is more realistic compared to the cross-correlation based kernels. Focusing on diving waves, which is used more often, especially recently in waveform inversion, we show sensitivity kernels in anisotropic media for this case.

  12. Physical, physicochemical and nutritional characteristics of Bhoja chaul, a traditional ready-to-eat dry heat parboiled rice product processed by an improvised soaking technique.

    Science.gov (United States)

    Dutta, Himjyoti; Mahanta, Charu Lata; Singh, Vasudeva; Das, Barnali Baruah; Rahman, Narzu

    2016-01-15

    Bhoja chaul is a traditional whole rice product processed by the dry heat parboiling technique of low amylose/waxy paddy that is eaten after soaking in water and requires no cooking. The essential steps in Bhoja chaul making are soaking paddy in water, roasting with sand, drying and milling. In this study, the product was prepared from a low amylose variety and a waxy rice variety by an improvised laboratory scale technique. Bhoja chaul prepared in the laboratory by this technique was studied for physical, physicochemical, and textural properties. Improvised method shortened the processing time and gave a product with good textural characteristics. Shape of the rice kernels became bolder on processing. RVA studies and DSC endotherms suggested molecular damage and amylose-lipid complex formation by the linear B-chains of amylopectin, respectively. X-ray diffractography indicated formation of partial B-type pattern. Shifting of the crystalline region of the XRD curve towards lower values of Bragg's angle was attributed to the overall increase in inter-planar spacing of the crystalline lamellae. Resistant starch was negligible. Bhoja chaul may be useful for children and people with poor state of digestibility. Copyright © 2014 Elsevier Ltd. All rights reserved.

  13. The influence of maize kernel moisture on the sterilizing effect of gamma rays

    International Nuclear Information System (INIS)

    Khanymova, T.; Poloni, E.

    1980-01-01

    The influence of 4 levels of maize kernel moisture (16, 20, 25 and 30%) on gamma-ray sterilizing effect was studied and the after-effect of radiation on the microorganisms at short term storage was followed up. Maize kernels of the hybrid Knezha-36 produced in 1975 were used. Gamma-ray treatment of the kernels was effected by GUBEh-4000 irradiator at doses of 0.2 and 0.3 Mrad and after that they were stored for a month at 12 deg and 25 deg C and controlled moisture conditions. Surface and subepidermal infection of the kernels was determined immediately post irradiation and at the end of the experiment. Non-irradiated kernels were used as controls. Results indicated that the initial kernel moisture has a considerable influence on the sterilizing effect of gamma-rays at the rates used in the experiment and affects to a considerable extent the post-irradiation recovery of organisms. The speed of recovery was highest in the treatment with 30% moisture and lowest in the treatment with 16% kernel moisture. Irradiation of the kernels causes pronounced changes on the surface and subepidermal infection. This was due to the unequal radio resistance to the microbial components and to the modifying effect of the moisture holding capacity. The useful effect of maize kernel irradiation was more prolonged at 12 deg C than at 25 deg C

  14. Puffing of okara/rice blends using a rice cake machine.

    Science.gov (United States)

    Xie, M; Huff, H; Hsieh, F; Mustapha, A

    2008-10-01

    Okara is the insoluble byproduct of soymilk and tofu manufactures. It is cheap, high in nutrients, and possesses great potential to be applied to functional human foods. In this study, a puffed okara/rice cake product was developed with blends of okara pellets and parboiled rice. Consumer preference and acceptance tests were conducted for the product. Okara pellets were prepared by grinding the strands obtained from extruding a mixture of dried okara and rice flour (3:2, w/w) with a twin-screw extruder. Okara pellets and parboiled rice were blended in 4 ratios, 90:10, 70:30, 40:60, and 0:100 (w/w), and tempered to 14% and 17% moisture. The blends were puffed at 221, 232, and 243 degrees C for 4, 5, or 6 s. The okara/rice cakes were evaluated for specific volume (SPV), texture, color, and percent weight loss after tumbling. Overall, the decrease in okara content and increase in moisture, heating temperature and time led to greater specific volume (SPV) and hardness, lighter color, and lower percent weight loss after tumbling. The consumer tests indicated that the okara/rice cake containing 70% okara pellets was preferred and the 90% one was liked the least. The possible drivers of liking for the puffed okara/rice cakes could be the okara content, hardness, SPV, bright color, and percent weight loss after tumbling.

  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. 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.

  17. 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...

  18. RiceAtlas, a spatial database of global rice calendars and production

    NARCIS (Netherlands)

    Laborte, Alice G.; Gutierrez, Mary Anne; Balanza, Jane Girly; Saito, Kazuki; Zwart, Sander; Boschetti, Mirco; Murty, M. V.R.; Villano, Lorena; Aunario, Jorrel Khalil; Reinke, Russell; Koo, Jawoo; Hijmans, Robert J.; Nelson, Andrew

    2017-01-01

    Knowing where, when, and how much rice is planted and harvested is crucial information for understanding the effects of policy, trade, and global and technological change on food security. We developed RiceAtlas, a spatial database on the seasonal distribution of the world's rice production. It

  19. The Potency of White Rice (Oryza sativa), Black Rice (Oryza sativa L. indica), and Red Rice (Oryza nivara) as Antioxidant and Tyrosinase Inhibitor

    Science.gov (United States)

    Batubara, I.; Maharni, M.; Sadiah, S.

    2017-04-01

    Rice is known to have many beneficial biological activities and is often used as “bedak dingin”, a face powder. The content of vitamins, minerals, fiber, and several types of antioxidants, such as ferulic acid, phytic acid, tocopherol, and oryzanols [1-2] are predicted to be potential as a tyrosinase inhibitor. The purpose of this study is to determine the potency of extracts from there types of rice, namely white, red, and black rice as an antioxidant and tyrosinase inhibitor. The rice was extracted with three different solvents, n-hexane, ethyl acetate, and methanol. The results showed that the highest antioxidant activity using 1,1-diphenyl-2-picrylhydrazyl method was found in the methanol extract of black rice (IC50 290 μg/mL). Meanwhile, ethyl acetate extract of white rice has the highest antioxidant activity withphosphomolybdic acid method (41 mmol α-tocopherol equivalents/g sample). Thus, methanol extract of black rice and ethyl acetate extract of white rice are potential as an antioxidant. For tyrosinase inhibitor, n-hexane extract of red rice (IC50 3156 μg/mL) was the most active extract. The active component for radical scavenging is polar compound and for antioxidant by phosphomolybdate method is less polar compounds in black rice methanol extract based on TLC bioautogram. In conclusion, the black rice is the most potent in antioxidant while red rice is for tyrosinase inhibition.

  20. Mapping QTLs controlling kernel dimensions in a wheat inter-varietal RIL mapping population.

    Science.gov (United States)

    Cheng, Ruiru; Kong, Zhongxin; Zhang, Liwei; Xie, Quan; Jia, Haiyan; Yu, Dong; Huang, Yulong; Ma, Zhengqiang

    2017-07-01

    Seven kernel dimension QTLs were identified in wheat, and kernel thickness was found to be the most important dimension for grain weight improvement. Kernel morphology and weight of wheat (Triticum aestivum L.) affect both yield and quality; however, the genetic basis of these traits and their interactions has not been fully understood. In this study, to investigate the genetic factors affecting kernel morphology and the association of kernel morphology traits with kernel weight, kernel length (KL), width (KW) and thickness (KT) were evaluated, together with hundred-grain weight (HGW), in a recombinant inbred line population derived from Nanda2419 × Wangshuibai, with data from five trials (two different locations over 3 years). The results showed that HGW was more closely correlated with KT and KW than with KL. A whole genome scan revealed four QTLs for KL, one for KW and two for KT, distributed on five different chromosomes. Of them, QKl.nau-2D for KL, and QKt.nau-4B and QKt.nau-5A for KT were newly identified major QTLs for the respective traits, explaining up to 32.6 and 41.5% of the phenotypic variations, respectively. Increase of KW and KT and reduction of KL/KT and KW/KT ratios always resulted in significant higher grain weight. Lines combining the Nanda 2419 alleles of the 4B and 5A intervals had wider, thicker, rounder kernels and a 14% higher grain weight in the genotype-based analysis. A strong, negative linear relationship of the KW/KT ratio with grain weight was observed. It thus appears that kernel thickness is the most important kernel dimension factor in wheat improvement for higher yield. Mapping and marker identification of the kernel dimension-related QTLs definitely help realize the breeding goals.

  1. Effect of Rice bran on the Quality of Rice Flour Breads (Gluten-free)

    OpenAIRE

    仲上, 晴世; 矢部, えん; Haruyo, Nakagami; En, Yabe

    2016-01-01

    Over recent years progress has been made in the development of substitute foods for allergy patients. One such is rice flour bread. However, typically rice flour bread uses polysaccharide thickener in substitution for the gluten in wheat. Most polysaccharide thickeners are of dietary fiber origin, and the nutritive value is poor. Therefore, in this study, I made rice flour bread adding rice bran in place of polysaccharide thickener. Various nutrients are included in rice bran, including vitam...

  2. A Heterogeneous Multi-core Architecture with a Hardware Kernel for Control Systems

    DEFF Research Database (Denmark)

    Li, Gang; Guan, Wei; Sierszecki, Krzysztof

    2012-01-01

    Rapid industrialisation has resulted in a demand for improved embedded control systems with features such as predictability, high processing performance and low power consumption. Software kernel implementation on a single processor is becoming more difficult to satisfy those constraints....... This paper presents a multi-core architecture incorporating a hardware kernel on FPGAs, intended for high performance applications in control engineering domain. First, the hardware kernel is investigated on the basis of a component-based real-time kernel HARTEX (Hard Real-Time Executive for Control Systems...

  3. Pollen source effects on growth of kernel structures and embryo chemical compounds in maize.

    Science.gov (United States)

    Tanaka, W; Mantese, A I; Maddonni, G A

    2009-08-01

    Previous studies have reported effects of pollen source on the oil concentration of maize (Zea mays) kernels through modifications to both the embryo/kernel ratio and embryo oil concentration. The present study expands upon previous analyses by addressing pollen source effects on the growth of kernel structures (i.e. pericarp, endosperm and embryo), allocation of embryo chemical constituents (i.e. oil, protein, starch and soluble sugars), and the anatomy and histology of the embryos. Maize kernels with different oil concentration were obtained from pollinations with two parental genotypes of contrasting oil concentration. The dynamics of the growth of kernel structures and allocation of embryo chemical constituents were analysed during the post-flowering period. Mature kernels were dissected to study the anatomy (embryonic axis and scutellum) and histology [cell number and cell size of the scutellums, presence of sub-cellular structures in scutellum tissue (starch granules, oil and protein bodies)] of the embryos. Plants of all crosses exhibited a similar kernel number and kernel weight. Pollen source modified neither the growth period of kernel structures, nor pericarp growth rate. By contrast, pollen source determined a trade-off between embryo and endosperm growth rates, which impacted on the embryo/kernel ratio of mature kernels. Modifications to the embryo size were mediated by scutellum cell number. Pollen source also affected (P embryo chemical compounds. Negative correlations among embryo oil concentration and those of starch (r = 0.98, P embryos with low oil concentration had an increased (P embryo/kernel ratio and allocation of embryo chemicals seems to be related to the early established sink strength (i.e. sink size and sink activity) of the embryos.

  4. 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

  5. Searching remote homology with spectral clustering with symmetry in neighborhood cluster kernels.

    Directory of Open Access Journals (Sweden)

    Ujjwal Maulik

    Full Text Available Remote homology detection among proteins utilizing only the unlabelled sequences is a central problem in comparative genomics. The existing cluster kernel methods based on neighborhoods and profiles and the Markov clustering algorithms are currently the most popular methods for protein family recognition. The deviation from random walks with inflation or dependency on hard threshold in similarity measure in those methods requires an enhancement for homology detection among multi-domain proteins. We propose to combine spectral clustering with neighborhood kernels in Markov similarity for enhancing sensitivity in detecting homology independent of "recent" paralogs. The spectral clustering approach with new combined local alignment kernels more effectively exploits the unsupervised protein sequences globally reducing inter-cluster walks. When combined with the corrections based on modified symmetry based proximity norm deemphasizing outliers, the technique proposed in this article outperforms other state-of-the-art cluster kernels among all twelve implemented kernels. The comparison with the state-of-the-art string and mismatch kernels also show the superior performance scores provided by the proposed kernels. Similar performance improvement also is found over an existing large dataset. Therefore the proposed spectral clustering framework over combined local alignment kernels with modified symmetry based correction achieves superior performance for unsupervised remote homolog detection even in multi-domain and promiscuous domain proteins from Genolevures database families with better biological relevance. Source code available upon request.sarkar@labri.fr.

  6. Leaf development of cultivated rice and weedy red rice under elevated temperature scenarios

    OpenAIRE

    Streck,Nereu A.; Uhlmann,Lilian O.; Gabriel,Luana F.

    2013-01-01

    The objective of this study was to simulate leaf development of cultivated rice genotypes and weedy red rice biotypes in climate change scenarios at Santa Maria, RS, Brazil. A leaf appearance (LAR) model adapted for rice was used to simulate the accumulated leaf number, represented by the Haun Stage, from crop emergence to flag leaf appearance (EM-FL). Three cultivated rice genotypes and two weedy red rice biotypes in six emergence dates were used. The LAR model was run for each emergence dat...

  7. 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

  8. The global kernel k-means algorithm for clustering in feature space.

    Science.gov (United States)

    Tzortzis, Grigorios F; Likas, Aristidis C

    2009-07-01

    Kernel k-means is an extension of the standard k -means clustering algorithm that identifies nonlinearly separable clusters. In order to overcome the cluster initialization problem associated with this method, we propose the global kernel k-means algorithm, a deterministic and incremental approach to kernel-based clustering. Our method adds one cluster at each stage, through a global search procedure consisting of several executions of kernel k-means from suitable initializations. This algorithm does not depend on cluster initialization, identifies nonlinearly separable clusters, and, due to its incremental nature and search procedure, locates near-optimal solutions avoiding poor local minima. Furthermore, two modifications are developed to reduce the computational cost that do not significantly affect the solution quality. The proposed methods are extended to handle weighted data points, which enables their application to graph partitioning. We experiment with several data sets and the proposed approach compares favorably to kernel k -means with random restarts.

  9. 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

  10. Relationship between processing score and kernel-fraction particle size in whole-plant corn silage.

    Science.gov (United States)

    Dias Junior, G S; Ferraretto, L F; Salvati, G G S; de Resende, L C; Hoffman, P C; Pereira, M N; Shaver, R D

    2016-04-01

    Kernel processing increases starch digestibility in whole-plant corn silage (WPCS). Corn silage processing score (CSPS), the percentage of starch passing through a 4.75-mm sieve, is widely used to assess degree of kernel breakage in WPCS. However, the geometric mean particle size (GMPS) of the kernel-fraction that passes through the 4.75-mm sieve has not been well described. Therefore, the objectives of this study were (1) to evaluate particle size distribution and digestibility of kernels cut in varied particle sizes; (2) to propose a method to measure GMPS in WPCS kernels; and (3) to evaluate the relationship between CSPS and GMPS of the kernel fraction in WPCS. Composite samples of unfermented, dried kernels from 110 corn hybrids commonly used for silage production were kept whole (WH) or manually cut in 2, 4, 8, 16, 32 or 64 pieces (2P, 4P, 8P, 16P, 32P, and 64P, respectively). Dry sieving to determine GMPS, surface area, and particle size distribution using 9 sieves with nominal square apertures of 9.50, 6.70, 4.75, 3.35, 2.36, 1.70, 1.18, and 0.59 mm and pan, as well as ruminal in situ dry matter (DM) digestibilities were performed for each kernel particle number treatment. Incubation times were 0, 3, 6, 12, and 24 h. The ruminal in situ DM disappearance of unfermented kernels increased with the reduction in particle size of corn kernels. Kernels kept whole had the lowest ruminal DM disappearance for all time points with maximum DM disappearance of 6.9% at 24 h and the greatest disappearance was observed for 64P, followed by 32P and 16P. Samples of WPCS (n=80) from 3 studies representing varied theoretical length of cut settings and processor types and settings were also evaluated. Each WPCS sample was divided in 2 and then dried at 60 °C for 48 h. The CSPS was determined in duplicate on 1 of the split samples, whereas on the other split sample the kernel and stover fractions were separated using a hydrodynamic separation procedure. After separation, the

  11. 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.

  12. TOWARDS FINDING A NEW KERNELIZED FUZZY C-MEANS CLUSTERING ALGORITHM

    Directory of Open Access Journals (Sweden)

    Samarjit Das

    2014-04-01

    Full Text Available Kernelized Fuzzy C-Means clustering technique is an attempt to improve the performance of the conventional Fuzzy C-Means clustering technique. Recently this technique where a kernel-induced distance function is used as a similarity measure instead of a Euclidean distance which is used in the conventional Fuzzy C-Means clustering technique, has earned popularity among research community. Like the conventional Fuzzy C-Means clustering technique this technique also suffers from inconsistency in its performance due to the fact that here also the initial centroids are obtained based on the randomly initialized membership values of the objects. Our present work proposes a new method where we have applied the Subtractive clustering technique of Chiu as a preprocessor to Kernelized Fuzzy CMeans clustering technique. With this new method we have tried not only to remove the inconsistency of Kernelized Fuzzy C-Means clustering technique but also to deal with the situations where the number of clusters is not predetermined. We have also provided a comparison of our method with the Subtractive clustering technique of Chiu and Kernelized Fuzzy C-Means clustering technique using two validity measures namely Partition Coefficient and Clustering Entropy.

  13. 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

  14. Migration of ThO2 kernels under the influence of a temperature gradient

    International Nuclear Information System (INIS)

    Smith, C.L.

    1976-11-01

    BISO coated ThO 2 fertile fuel kernels will migrate up the thermal gradients imposed across coated particles during HTGR operation. Thorium dioxide kernel migration has been studied as a function of temperature (1300 to 1700 0 C) and ThO 2 kernel burnup (0.9 to 5.8 percent FIMA) in out-of-pile, postirradiation thermal gradient heating experiments. The studies were conducted to obtain descriptions of migration rates that will be used in core design studies to evaluate the impact of ThO 2 migration on fertile fuel performance in an operating HTGR and to define characteristics needed by any comprehensive model describing ThO 2 kernel migration. The kinetics data generated in these postirradiation studies are consistent with in-pile data collected by investigators at Oak Ridge National Laboratory, which supports use of the more precise postirradiation heating results in HTGR core design studies. Observations of intergranular carbon deposits on the cool side of migrating kernels support the assumption that the kinetics of kernel migration are controlled by solid state diffusion within irradiated ThO 2 kernels. The migration is characterized by a period of no migration (incubation period) followed by migration at the equilibrium rate for ThO 2 . The incubation period decreases with increasing temperature and kernel burnup. The improved understanding of the kinetics of ThO 2 kernel migration provided by this work will contribute to an optimization of HTGR core design and an increased confidence in fuel performance predictions

  15. 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.)

  16. Nutrition quality of extraction mannan residue from palm kernel cake on brolier chicken

    Science.gov (United States)

    Tafsin, M.; Hanafi, N. D.; Kejora, E.; Yusraini, E.

    2018-02-01

    This study aims to find out the nutrient residue of palm kernel cake from mannan extraction on broiler chicken by evaluating physical quality (specific gravity, bulk density and compacted bulk density), chemical quality (proximate analysis and Van Soest Test) and biological test (metabolizable energy). Treatment composed of T0 : palm kernel cake extracted aquadest (control), T1 : palm kernel cake extracted acetic acid (CH3COOH) 1%, T2 : palm kernel cake extracted aquadest + mannanase enzyme 100 u/l and T3 : palm kernel cake extracted acetic acid (CH3COOH) 1% + enzyme mannanase 100 u/l. The results showed that mannan extraction had significant effect (P<0.05) in improving the quality of physical and numerically increase the value of crude protein and decrease the value of NDF (Neutral Detergent Fiber). Treatments had highly significant influence (P<0.01) on the metabolizable energy value of palm kernel cake residue in broiler chickens. It can be concluded that extraction with aquadest + enzyme mannanase 100 u/l yields the best nutrient quality of palm kernel cake residue for broiler chicken.

  17. 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...

  18. 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...

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

    Directory of Open Access Journals (Sweden)

    Rosanna Zivoli

    2016-01-01

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

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

    African Journals Online (AJOL)

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

  1. Gaussian processes with optimal kernel construction for neuro-degenerative clinical onset prediction

    Science.gov (United States)

    Canas, Liane S.; Yvernault, Benjamin; Cash, David M.; Molteni, Erika; Veale, Tom; Benzinger, Tammie; Ourselin, Sébastien; Mead, Simon; Modat, Marc

    2018-02-01

    Gaussian Processes (GP) are a powerful tool to capture the complex time-variations of a dataset. In the context of medical imaging analysis, they allow a robust modelling even in case of highly uncertain or incomplete datasets. Predictions from GP are dependent of the covariance kernel function selected to explain the data variance. To overcome this limitation, we propose a framework to identify the optimal covariance kernel function to model the data.The optimal kernel is defined as a composition of base kernel functions used to identify correlation patterns between data points. Our approach includes a modified version of the Compositional Kernel Learning (CKL) algorithm, in which we score the kernel families using a new energy function that depends both the Bayesian Information Criterion (BIC) and the explained variance score. We applied the proposed framework to model the progression of neurodegenerative diseases over time, in particular the progression of autosomal dominantly-inherited Alzheimer's disease, and use it to predict the time to clinical onset of subjects carrying genetic mutation.

  2. A Comparative Study of Pairwise Learning Methods Based on Kernel Ridge Regression.

    Science.gov (United States)

    Stock, Michiel; Pahikkala, Tapio; Airola, Antti; De Baets, Bernard; Waegeman, Willem

    2018-06-12

    Many machine learning problems can be formulated as predicting labels for a pair of objects. Problems of that kind are often referred to as pairwise learning, dyadic prediction, or network inference problems. During the past decade, kernel methods have played a dominant role in pairwise learning. They still obtain a state-of-the-art predictive performance, but a theoretical analysis of their behavior has been underexplored in the machine learning literature. In this work we review and unify kernel-based algorithms that are commonly used in different pairwise learning settings, ranging from matrix filtering to zero-shot learning. To this end, we focus on closed-form efficient instantiations of Kronecker kernel ridge regression. We show that independent task kernel ridge regression, two-step kernel ridge regression, and a linear matrix filter arise naturally as a special case of Kronecker kernel ridge regression, implying that all these methods implicitly minimize a squared loss. In addition, we analyze universality, consistency, and spectral filtering properties. Our theoretical results provide valuable insights into assessing the advantages and limitations of existing pairwise learning methods.

  3. A Novel Extreme Learning Machine Classification Model for e-Nose Application Based on the Multiple Kernel Approach.

    Science.gov (United States)

    Jian, Yulin; Huang, Daoyu; Yan, Jia; Lu, Kun; Huang, Ying; Wen, Tailai; Zeng, Tanyue; Zhong, Shijie; Xie, Qilong

    2017-06-19

    A novel classification model, named the quantum-behaved particle swarm optimization (QPSO)-based weighted multiple kernel extreme learning machine (QWMK-ELM), is proposed in this paper. Experimental validation is carried out with two different electronic nose (e-nose) datasets. Being different from the existing multiple kernel extreme learning machine (MK-ELM) algorithms, the combination coefficients of base kernels are regarded as external parameters of single-hidden layer feedforward neural networks (SLFNs). The combination coefficients of base kernels, the model parameters of each base kernel, and the regularization parameter are optimized by QPSO simultaneously before implementing the kernel extreme learning machine (KELM) with the composite kernel function. Four types of common single kernel functions (Gaussian kernel, polynomial kernel, sigmoid kernel, and wavelet kernel) are utilized to constitute different composite kernel functions. Moreover, the method is also compared with other existing classification methods: extreme learning machine (ELM), kernel extreme learning machine (KELM), k-nearest neighbors (KNN), support vector machine (SVM), multi-layer perceptron (MLP), radical basis function neural network (RBFNN), and probabilistic neural network (PNN). The results have demonstrated that the proposed QWMK-ELM outperforms the aforementioned methods, not only in precision, but also in efficiency for gas classification.

  4. 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

  5. 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.

  6. Glufosinate herbicide-tolerant (LibertyLink) rice vs. conventional rice in diets for growing-finishing swine.

    Science.gov (United States)

    Cromwell, G L; Henry, B J; Scott, A L; Gerngross, M F; Dusek, D L; Fletcher, D W

    2005-05-01

    Genetically modified (GM) rice (LibertyLink, event LLRICE62) that is tolerant to glufosinate ammonium (Liberty) herbicide was compared with a near-isogenic (NI) conventional medium-grain brown rice (cultivar, Bengal) and a commercially milled long-grain brown rice in diets for growing-finishing pigs. The GM and NI rice were grown in 2000. The GM rice was from fields treated (GM+) or not treated (GM-) with glufosinate herbicide. The GM- and NI rice were grown using herbicide regimens typical of southern United States rice production practices. The four rice grains were similar in composition. Growing-finishing pigs (n = 96) were fed fortified rice-soybean meal diets containing the four different rice grains from 25 to 106 kg BW. Diets contained 0.99% lysine initially (growing phase), with lysine decreased to 0.80% (early finishing phase) and 0.65% (late finishing phase), when pigs reached 51 and 77 kg, respectively. The percentage of rice in the four diets was constant during each of the three phases (72.8, 80.0, and 85.8% for the growing, early-finishing, and late-finishing phases, respectively). There were six pen replicates (three pens of barrows and three pens of gilts) and four pigs per pen for each dietary treatment. All pigs were slaughtered at the termination of the study to collect carcass data. At the end of the 98-d experiment, BW gain, feed intake (as-fed basis), and feed:gain ratio did not differ (P > 0.05) for pigs fed the GM+ vs. conventional rice diets, but growth performance traits of pigs fed the GM+ rice diets were superior (P glufosinate herbicide-tolerant rice was similar in composition and nutritional value to conventional rice for growing-finishing pigs.

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

    Science.gov (United States)

    Wang, Hongru; Vieira, Filipe G; Crawford, Jacob E; Chu, Chengcai; Nielsen, Rasmus

    2017-06-01

    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 genomes consisting of 203 domesticated and 435 wild rice accessions. We show that most modern wild rice is heavily admixed with domesticated rice through both pollen- and seed-mediated gene flow. In fact, much presumed wild rice may simply represent different stages of feralized domesticated rice. In line with this hypothesis, many presumed wild rice varieties show remnants of the effects of selective sweeps in previously identified domestication genes, as well as evidence of recent selection in flowering genes possibly associated with the feralization process. Furthermore, there is a distinct geographical pattern of gene flow from aus , indica , and japonica varieties into colocated wild rice. We also show that admixture from aus and indica is more recent than gene flow from japonica , possibly consistent with an earlier spread of japonica varieties. We argue that wild rice populations should be considered a hybrid swarm, connected to domesticated rice by continuous and extensive gene flow. © 2017 Wang et al.; Published by Cold Spring Harbor Laboratory Press.

  8. An Economic Risk Analysis of Weed Suppressive Rice Cultivars in Rice Production

    Science.gov (United States)

    Weeds are a major constraint to rice production. In the United States, most rice cultivars are not inherently weed-suppressive and require substantial herbicide inputs to achieve agronomic and economic viability. Intensive herbicide application in rice also has many potential drawbacks, resulting in...

  9. Probabilistic wind power forecasting based on logarithmic transformation and boundary kernel

    International Nuclear Information System (INIS)

    Zhang, Yao; Wang, Jianxue; Luo, Xu

    2015-01-01

    Highlights: • Quantitative information on the uncertainty of wind power generation. • Kernel density estimator provides non-Gaussian predictive distributions. • Logarithmic transformation reduces the skewness of wind power density. • Boundary kernel method eliminates the density leakage near the boundary. - Abstracts: Probabilistic wind power forecasting not only produces the expectation of wind power output, but also gives quantitative information on the associated uncertainty, which is essential for making better decisions about power system and market operations with the increasing penetration of wind power generation. This paper presents a novel kernel density estimator for probabilistic wind power forecasting, addressing two characteristics of wind power which have adverse impacts on the forecast accuracy, namely, the heavily skewed and double-bounded nature of wind power density. Logarithmic transformation is used to reduce the skewness of wind power density, which improves the effectiveness of the kernel density estimator in a transformed scale. Transformations partially relieve the boundary effect problem of the kernel density estimator caused by the double-bounded nature of wind power density. However, the case study shows that there are still some serious problems of density leakage after the transformation. In order to solve this problem in the transformed scale, a boundary kernel method is employed to eliminate the density leak at the bounds of wind power distribution. The improvement of the proposed method over the standard kernel density estimator is demonstrated by short-term probabilistic forecasting results based on the data from an actual wind farm. Then, a detailed comparison is carried out of the proposed method and some existing probabilistic forecasting methods

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

    DEFF Research Database (Denmark)

    Christiansen, Asger Nyman; Carstensen, Jens Michael

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

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

    Science.gov (United States)

    Warfield, Colleen Y.; Gilchrist, David G.

    1999-01-01

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

  12. Soil to rice transfer factors for 210Pb: a study on rice grown in India

    International Nuclear Information System (INIS)

    Karunakara, N.; Rao, Chetan; Ujwal, P.; Yashodhara, I.; Sudeep Kumara; Somashekarappa, H.M.; Bhaskara Shenoy, K.; Ravi, P.M.

    2013-01-01

    India is the second largest producer of rice (Oryza sativa L.) in the world and rice is the essential component of the diet for the majority of the population of India. However, detailed studies aimed at evaluation of radionuclide transfer factors (F v ) for rice grown in India are almost non-existent. This paper presents soil to rice transfer factors for 210 Pb for rice grown in natural field conditions on the West Coast of India. A rice field was developed very close to the Kaiga nuclear power plant for the field studies. For a comparative study of radionuclide transfer factors, rice samples were also collected from the rice fields of nearby villages. The soil to un-hulled rice grain 210 Pb varied in the range <1.2 x10 -2 to 8.1 x 10 -1 with a mean of 1.4 x 10 -1 . The mean values of un-hulled grain to white rice processing retention factors (F r ) was 0.03 for 210 Pb. Using the processing retention factors the soil to white rice transfer factor was estimated and found to have the mean value of 4.2 x 10 -3 . The study has shown that the transfer of 210 Pb was retained in the root and its transfer to above ground organs of rice plant is significantly lower. (author)

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

    DEFF Research Database (Denmark)

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

    2014-01-01

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

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

    Science.gov (United States)

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

  15. 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.

  16. Characterisation and final disposal behaviour of theoria-based fuel kernels in aqueous phases

    International Nuclear Information System (INIS)

    Titov, M.

    2005-08-01

    Two high-temperature reactors (AVR and THTR) operated in Germany have produced about 1 million spent fuel elements. The nuclear fuel in these reactors consists mainly of thorium-uranium mixed oxides, but also pure uranium dioxide and carbide fuels were tested. One of the possible solutions of utilising spent HTR fuel is the direct disposal in deep geological formations. Under such circumstances, the properties of fuel kernels, and especially their leaching behaviour in aqueous phases, have to be investigated for safety assessments of the final repository. In the present work, unirradiated ThO 2 , (Th 0.906 ,U 0.094 )O 2 , (Th 0.834 ,U 0.166 )O 2 and UO 2 fuel kernels were investigated. The composition, crystal structure and surface of the kernels were investigated by traditional methods. Furthermore, a new method was developed for testing the mechanical properties of ceramic kernels. The method was successfully used for the examination of mechanical properties of oxide kernels and for monitoring their evolution during contact with aqueous phases. The leaching behaviour of thoria-based oxide kernels and powders was investigated in repository-relevant salt solutions, as well as in artificial leachates. The influence of different experimental parameters on the kernel leaching stability was investigated. It was shown that thoria-based fuel kernels possess high chemical stability and are indifferent to presence of oxidative and radiolytic species in solution. The dissolution rate of thoria-based materials is typically several orders of magnitude lower than of conventional UO 2 fuel kernels. The life time of a single intact (Th,U)O 2 kernel under aggressive conditions of salt repository was estimated as about hundred thousand years. The importance of grain boundary quality on the leaching stability was demonstrated. Numerical Monte Carlo simulations were performed in order to explain the results of leaching experiments. (orig.)

  17. A comparative study of competitiveness between different genotypes of weedy rice (Oryza sativa) and cultivated rice.

    Science.gov (United States)

    Dai, Lei; Dai, Weimin; Song, Xiaoling; Lu, Baorong; Qiang, Sheng

    2014-01-01

    Competition from weedy rice can cause serious yield losses to cultivated rice. However, key traits that facilitate competitiveness are still not well understood. To explore the mechanisms behind the strong growth and competitive ability, replacement series experiments were established with six genotypes of weedy rice from different regions and one cultivated rice cultivar. (1) Weedy rice from southern China had the greatest impact on growth and yield of cultivated rice throughout the entire growing season. Weedy rice from the northeast was very competitive during the early vegetative stage while the competitive effects of eastern weedy rice were more detrimental at later crop-growth stages. (2) As the proportion of weedy rice increased, plant height, tillers, above-ground biomass, and yield of cultivated rice significantly declined; the crop always being at disadvantage regardless of proportion. (3) Weedy biotypes with greater diversity as estimated by their Shannon indexes were more detrimental to the growth and yield of cultivated rice. Geographic origin (latitude) of weedy rice biotype, its mixture proportion under competition with the crop and its genetic diversity are determinant factors of the outcome of competition and the associated decline in the rice crop yield. © 2013 Society of Chemical Industry. © 2013 Society of Chemical Industry.

  18. Diversity of global rice markets and the science required for consumer-targeted rice breeding

    Science.gov (United States)

    With the ever-increasing global demand for high quality rice in both local production regions and with Western consumers, we have a strong desire to understand better the importance of different quality traits that make up the rice grain and obtain a full picture of rice quality demographics. Rice ...

  19. Laboratory Screening for Resistance in Rice to Rice Stem Borer Chilo Suppressalis Walker

    International Nuclear Information System (INIS)

    Singgih Sutrisno

    2004-01-01

    Rice stem borer Chilo suppressalis Walker is one of the major insect pests in rice in Indonesia. The use of insect pest resistant variety of rice is one of the effective techniques against pests. Breeding of resistance to insect pests rice crops often faced difficulties in obtaining a lot of insect amounts due to the unavailability of enough number insects pests in the field so that a laboratory bioassay is needed. In this experiments five rice varieties were used: a Pelita I/1, Atomita I, Cisadane, Cisanggarung, and IR 36. Rice seedling 7 days of age were put in 1 liter plastic vials for rice resistance test against the attack of insect pest C. suppressalis. The parameters observed were larval and pupal viability, pupal weight, and eggs production. The larval and pupal viability which were reared on of Pelita I/1 and Atomita I rice seedlings were 68.5 % - 55.5 % and 57.3 % - 46.7 % respectively. The respective lowest percentages were found in IR 36 which was about 41.3 % - 29.8 % .The experiment results on the parameters of pupal weight and egg production showed similar results to that on the parameters of larval and pupal viability. Rice variety of IR 36 showed more resistance to the other varieties, while Pelita I/1 and Atomita I showed the most susceptible to the attack of insect pest C. suppressalis. (author)

  20. Kernel Clustering with a Differential Harmony Search Algorithm for Scheme Classification

    Directory of Open Access Journals (Sweden)

    Yu Feng

    2017-01-01

    Full Text Available This paper presents a kernel fuzzy clustering with a novel differential harmony search algorithm to coordinate with the diversion scheduling scheme classification. First, we employed a self-adaptive solution generation strategy and differential evolution-based population update strategy to improve the classical harmony search. Second, we applied the differential harmony search algorithm to the kernel fuzzy clustering to help the clustering method obtain better solutions. Finally, the combination of the kernel fuzzy clustering and the differential harmony search is applied for water diversion scheduling in East Lake. A comparison of the proposed method with other methods has been carried out. The results show that the kernel clustering with the differential harmony search algorithm has good performance to cooperate with the water diversion scheduling problems.

  1. CLASS-PAIR-GUIDED MULTIPLE KERNEL LEARNING OF INTEGRATING HETEROGENEOUS FEATURES FOR CLASSIFICATION

    Directory of Open Access Journals (Sweden)

    Q. Wang

    2017-10-01

    Full Text Available In recent years, many studies on remote sensing image classification have shown that using multiple features from different data sources can effectively improve the classification accuracy. As a very powerful means of learning, multiple kernel learning (MKL can conveniently be embedded in a variety of characteristics. The conventional combined kernel learned by MKL can be regarded as the compromise of all basic kernels for all classes in classification. It is the best of the whole, but not optimal for each specific class. For this problem, this paper proposes a class-pair-guided MKL method to integrate the heterogeneous features (HFs from multispectral image (MSI and light detection and ranging (LiDAR data. In particular, the one-against-one strategy is adopted, which converts multiclass classification problem to a plurality of two-class classification problem. Then, we select the best kernel from pre-constructed basic kernels set for each class-pair by kernel alignment (KA in the process of classification. The advantage of the proposed method is that only the best kernel for the classification of any two classes can be retained, which leads to greatly enhanced discriminability. Experiments are conducted on two real data sets, and the experimental results show that the proposed method achieves the best performance in terms of classification accuracies in integrating the HFs for classification when compared with several state-of-the-art algorithms.

  2. Creation of transgenic rice plants producing small interfering RNA of Rice tungro spherical virus.

    Science.gov (United States)

    Le, Dung Tien; Chu, Ha Duc; Sasaya, Takahide

    2015-01-01

    Rice tungro spherical virus (RTSV), also known as Rice waika virus, does not cause visible symptoms in infected rice plants. However, the virus plays a critical role in spreading Rice tungro bacilliform virus (RTBV), which is the major cause of severe symptoms of rice tungro disease. Recent studies showed that RNA interference (RNAi) can be used to develop virus-resistance transgenic rice plants. In this report, we presented simple procedures and protocols needed for the creation of transgenic rice plants capable of producing small interfering RNA specific against RTSV sequences. Notably, our study showed that 60 out of 64 individual hygromycin-resistant lines (putative transgenic lines) obtained through transformation carried transgenes designed for producing hairpin double-stranded RNA. Northern blot analyses revealed the presence of small interfering RNA of 21- to 24-mer in 46 out of 56 confirmed transgenic lines. Taken together, our study indicated that transgenic rice plants carrying an inverted repeat of 500-bp fragments encoding various proteins of RTSV can produce small interfering RNA from the hairpin RNA transcribed from that transgene. In light of recent studies with other viruses, it is possible that some of these transgenic rice lines might be resistant to RTSV.

  3. A Non-destructive and Continuous Measurement of Gelatinization of Rice in Rice Cooking Process

    OpenAIRE

    Hagura, Yoshio; Suzuki, Kanichi

    2002-01-01

    A non-destructive and continuous method to measure gelatinization of rice samples in a rice-water system during rice cooking process was examined. An aluminum pot and a lid of a rice cooker were used as two electrode plates, and changes in dielectric properties (capacitance : C, and dielectric dissipation factor : tan δ) of the samples in the rice cooking process were measured by a capacitance meter. Differential scanning calorimetry (DSC) was used to measure gelatinization enthalpy and to de...

  4. 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.

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

    Science.gov (United States)

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

    2014-01-01

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

  6. 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...

  7. Rice varieties in relation to rice bread quality.

    Science.gov (United States)

    Han, Hye Min; Cho, Jun Hyeon; Kang, Hang Won; Koh, Bong Kyung

    2012-05-01

    It is difficult to predict rice bread quality only from the amylose content (AC) or dough characteristics of new lines produced by rice breeding programmes. This study investigated the AC relative to bread baking quality of rice varieties developed in Korea, and identified specific characteristics that contribute to rice bread quality. Manmibyeo, Jinsumi, Seolgaeng and Hanareumbyeo were classified as low AC, YR24088 Acp9, Suweon517, Chenmaai and Goamibyeo as intermediate AC and Milyang261 as high AC. Suweon517, Milyang261 and Manmibyeo had a high water absorption index (WAI), while Goamibyeo, YR24088 Acp9, Jinsumi, Seolgaeng, Hanareumbyeo and Chenmaai had a low WAI. The gelatinisation enthalpy of flour varied from 9.2 J g(-1) in Milyang261 to 14.8 J g(-1) in YR24088 Acp9. After 7 days of storage the rate of flour retrogradation and crumb firmness were weakly correlated, with the exception of Jinsumi. Bread volumes of Jinsumi, Chenmaai, YR24088 Acp9 and Goamibyeo were comparable to that of wheat flour, but the rest were unsuited to bread making because of their low volume and hard crumb texture. Based on volume, texture and crumb firmness ratio, Chenmaai and Goamibyeo were the most appropriate varieties for making bread. An intermediate AC and low WAI were the primary indicators of rice bread flour quality. Copyright © 2011 Society of Chemical Industry.

  8. Salinity alters the protein composition of rice endosperm and the physicochemical properties of rice flour.

    Science.gov (United States)

    Baxter, Graeme; Zhao, Jian; Blanchard, Christopher

    2011-09-01

    Salinity is one of the major threats to production of rice and other agricultural crops worldwide. Although numerous studies have shown that salinity can severely reduce rice yield, little is known about its impact on the chemical composition, processing and sensory characteristics of rice. The objective of the current study was to investigate the effect of salinity on the pasting and textural properties of rice flour as well as on the protein content and composition of rice endosperm. Rice grown under saline conditions had significantly lower yields but substantially higher protein content. The increase in protein content was mainly attributed to increases in the amount of glutelin, with lesser contributions from albumin. Salinity also altered the relative proportions of the individual peptides within the glutelin fraction. Flours obtained from rice grown under saline conditions showed significantly higher pasting temperatures, but lower peak and breakdown viscosities. Rice gels prepared from the flour showed significantly higher hardness and adhesiveness values, compared to the freshwater controls. Salinity can significantly affect the pasting and textural characteristics of rice flour. Although some of the effects could be attributed to changes in protein content of the rice flour, especially the increased glutelin level, the impact of salinity on the physicochemical properties of rice is rather complex and may involve the interrelated effects of other rice components such as starch and lipids. Copyright © 2011 Society of Chemical Industry.

  9. 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.

  10. Introducing etch kernels for efficient pattern sampling and etch bias prediction

    Science.gov (United States)

    Weisbuch, François; Lutich, Andrey; Schatz, Jirka

    2018-01-01

    Successful patterning requires good control of the photolithography and etch processes. While compact litho models, mainly based on rigorous physics, can predict very well the contours printed in photoresist, pure empirical etch models are less accurate and more unstable. Compact etch models are based on geometrical kernels to compute the litho-etch biases that measure the distance between litho and etch contours. The definition of the kernels, as well as the choice of calibration patterns, is critical to get a robust etch model. This work proposes to define a set of independent and anisotropic etch kernels-"internal, external, curvature, Gaussian, z_profile"-designed to represent the finest details of the resist geometry to characterize precisely the etch bias at any point along a resist contour. By evaluating the etch kernels on various structures, it is possible to map their etch signatures in a multidimensional space and analyze them to find an optimal sampling of structures. The etch kernels evaluated on these structures were combined with experimental etch bias derived from scanning electron microscope contours to train artificial neural networks to predict etch bias. The method applied to contact and line/space layers shows an improvement in etch model prediction accuracy over standard etch model. This work emphasizes the importance of the etch kernel definition to characterize and predict complex etch effects.

  11. Assessing the impacts of climate change on rice yields in the main rice areas of China

    International Nuclear Information System (INIS)

    Yao, Fengmei; Xu, Yinglong; Lin, Erda; Yokozawa, Masayuki; Zhang, Jiahua

    2007-01-01

    This paper assesses the impact of climate change on irrigated rice yield using B2 climate change scenario from the Regional Climate Model (RCM) and CERES-rice model during 2071--2090. Eight typical rice stations ranging in latitude, longitude, and elevation that are located in the main rice ecological zones of China are selected for impact assessment. First, Crop Estimation through Resource and Environment Synthesis (CERES)-rice model is validated using farm experiment data in selected stations. The simulated results represent satisfactorily the trend of flowering duration and yields. The deviation of simulation within ± 10% of observed flowering duration and ± 15% of observed yield. Second, the errors of the outputs of RCM due to the difference of topography between station point and grid point is corrected. The corrected output of the RCM used for simulating rice flowering duration and yield is more reliable than the not corrected. Without CO2 direct effect on crop, the results from the assessment explore that B2 climate change scenario would have a negative impact on rice yield at most rice stations and have little impacts at Fuzhou and Kunming. To find the change of inter-annual rice yield, a preliminary assessment is made based on comparative cumulative probability at low and high yield and the coefficient variable of yield between the B2 scenario and baseline. Without the CO2 direct effect on rice yield, the result indicates that frequency for low yield would increase and it reverses for high yield, and the variance for rice yield would increase. It is concluded that high frequency at low yield and high variances of rice yield could pose a threat to rice yield at most selected stations in the main rice areas of China. With the CO2 direct effect on rice yield, rice yield increase in all selected stations

  12. Assessing the impacts of climate change on rice yields in the main rice areas of China

    Energy Technology Data Exchange (ETDEWEB)

    Yao, Fengmei [College of Earth Sciences, The Graduate University of the Chinese Academy of Sciences, 19A, Yuquan Road, Beijing, 100049 (China); Xu, Yinglong; Lin, Erda [Agricultural Environment and Sustainable Development Institute, Chinese Academy of Agricultural Sciences, Beijing, 100081 (China); Yokozawa, Masayuki [National Institute for Agro-environmental Sciences, Tsukuba 305-8604 (Japan); Zhang, Jiahua [Chinese Academy of Meteorological Sciences, Beijing, 100081 (China)

    2007-02-15

    This paper assesses the impact of climate change on irrigated rice yield using B2 climate change scenario from the Regional Climate Model (RCM) and CERES-rice model during 2071--2090. Eight typical rice stations ranging in latitude, longitude, and elevation that are located in the main rice ecological zones of China are selected for impact assessment. First, Crop Estimation through Resource and Environment Synthesis (CERES)-rice model is validated using farm experiment data in selected stations. The simulated results represent satisfactorily the trend of flowering duration and yields. The deviation of simulation within {+-} 10% of observed flowering duration and {+-} 15% of observed yield. Second, the errors of the outputs of RCM due to the difference of topography between station point and grid point is corrected. The corrected output of the RCM used for simulating rice flowering duration and yield is more reliable than the not corrected. Without CO2 direct effect on crop, the results from the assessment explore that B2 climate change scenario would have a negative impact on rice yield at most rice stations and have little impacts at Fuzhou and Kunming. To find the change of inter-annual rice yield, a preliminary assessment is made based on comparative cumulative probability at low and high yield and the coefficient variable of yield between the B2 scenario and baseline. Without the CO2 direct effect on rice yield, the result indicates that frequency for low yield would increase and it reverses for high yield, and the variance for rice yield would increase. It is concluded that high frequency at low yield and high variances of rice yield could pose a threat to rice yield at most selected stations in the main rice areas of China. With the CO2 direct effect on rice yield, rice yield increase in all selected stations.

  13. Multiple kernel learning using single stage function approximation for binary classification problems

    Science.gov (United States)

    Shiju, S.; Sumitra, S.

    2017-12-01

    In this paper, the multiple kernel learning (MKL) is formulated as a supervised classification problem. We dealt with binary classification data and hence the data modelling problem involves the computation of two decision boundaries of which one related with that of kernel learning and the other with that of input data. In our approach, they are found with the aid of a single cost function by constructing a global reproducing kernel Hilbert space (RKHS) as the direct sum of the RKHSs corresponding to the decision boundaries of kernel learning and input data and searching that function from the global RKHS, which can be represented as the direct sum of the decision boundaries under consideration. In our experimental analysis, the proposed model had shown superior performance in comparison with that of existing two stage function approximation formulation of MKL, where the decision functions of kernel learning and input data are found separately using two different cost functions. This is due to the fact that single stage representation helps the knowledge transfer between the computation procedures for finding the decision boundaries of kernel learning and input data, which inturn boosts the generalisation capacity of the model.

  14. Dynamic PET Image reconstruction for parametric imaging using the HYPR kernel method

    Science.gov (United States)

    Spencer, Benjamin; Qi, Jinyi; Badawi, Ramsey D.; Wang, Guobao

    2017-03-01

    Dynamic PET image reconstruction is a challenging problem because of the ill-conditioned nature of PET and the lowcounting statistics resulted from short time-frames in dynamic imaging. The kernel method for image reconstruction has been developed to improve image reconstruction of low-count PET data by incorporating prior information derived from high-count composite data. In contrast to most of the existing regularization-based methods, the kernel method embeds image prior information in the forward projection model and does not require an explicit regularization term in the reconstruction formula. Inspired by the existing highly constrained back-projection (HYPR) algorithm for dynamic PET image denoising, we propose in this work a new type of kernel that is simpler to implement and further improves the kernel-based dynamic PET image reconstruction. Our evaluation study using a physical phantom scan with synthetic FDG tracer kinetics has demonstrated that the new HYPR kernel-based reconstruction can achieve a better region-of-interest (ROI) bias versus standard deviation trade-off for dynamic PET parametric imaging than the post-reconstruction HYPR denoising method and the previously used nonlocal-means kernel.

  15. 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...

  16. Surface and top-of-atmosphere radiative feedback kernels for CESM-CAM5

    Science.gov (United States)

    Pendergrass, Angeline G.; Conley, Andrew; Vitt, Francis M.

    2018-02-01

    Radiative kernels at the top of the atmosphere are useful for decomposing changes in atmospheric radiative fluxes due to feedbacks from atmosphere and surface temperature, water vapor, and surface albedo. Here we describe and validate radiative kernels calculated with the large-ensemble version of CAM5, CESM1.1.2, at the top of the atmosphere and the surface. Estimates of the radiative forcing from greenhouse gases and aerosols in RCP8.5 in the CESM large-ensemble simulations are also diagnosed. As an application, feedbacks are calculated for the CESM large ensemble. The kernels are freely available at https://doi.org/10.5065/D6F47MT6" target="_blank">https://doi.org/10.5065/D6F47MT6, and accompanying software can be downloaded from https://github.com/apendergrass/cam5-kernels" target="_blank">https://github.com/apendergrass/cam5-kernels.

  17. 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

  18. 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

  19. 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....

  20. Combined Kernel-Based BDT-SMO Classification of Hyperspectral Fused Images

    Directory of Open Access Journals (Sweden)

    Fenghua Huang

    2014-01-01

    Full Text Available To solve the poor generalization and flexibility problems that single kernel SVM classifiers have while classifying combined spectral and spatial features, this paper proposed a solution to improve the classification accuracy and efficiency of hyperspectral fused images: (1 different radial basis kernel functions (RBFs are employed for spectral and textural features, and a new combined radial basis kernel function (CRBF is proposed by combining them in a weighted manner; (2 the binary decision tree-based multiclass SMO (BDT-SMO is used in the classification of hyperspectral fused images; (3 experiments are carried out, where the single radial basis function- (SRBF- based BDT-SMO classifier and the CRBF-based BDT-SMO classifier are used, respectively, to classify the land usages of hyperspectral fused images, and genetic algorithms (GA are used to optimize the kernel parameters of the classifiers. The results show that, compared with SRBF, CRBF-based BDT-SMO classifiers display greater classification accuracy and efficiency.

  1. 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

  2. Cytoplasmic-genetic male sterility gene provides direct evidence for some hybrid rice recently evolving into weedy rice

    Science.gov (United States)

    Zhang, Jingxu; Lu, Zuomei; Dai, Weimin; Song, Xiaoling; Peng, Yufa; Valverde, Bernal E.; Qiang, Sheng

    2015-01-01

    Weedy rice infests paddy fields worldwide at an alarmingly increasing rate. There is substantial evidence indicating that many weedy rice forms originated from or are closely related to cultivated rice. There is suspicion that the outbreak of weedy rice in China may be related to widely grown hybrid rice due to its heterosis and the diversity of its progeny, but this notion remains unsupported by direct evidence. We screened weedy rice accessions by both genetic and molecular marker tests for the cytoplasmic male sterility (CMS) genes (Wild abortive, WA, and Boro type, BT) most widely used in the production of indica and japonica three-line hybrid rice as a diagnostic trait of direct parenthood. Sixteen weedy rice accessions of the 358 tested (4.5%) contained the CMS-WA gene; none contained the CMS-BT gene. These 16 accessions represent weedy rices recently evolved from maternal hybrid rice derivatives, given the primarily maternal inheritance of this trait. Our results provide key direct evidence that hybrid rice can be involved in the evolution of some weedy rice accessions, but is not a primary factor in the recent outbreak of weedy rice in China. PMID:26012494

  3. Cytoplasmic-genetic male sterility gene provides direct evidence for some hybrid rice recently evolving into weedy rice.

    Science.gov (United States)

    Zhang, Jingxu; Lu, Zuomei; Dai, Weimin; Song, Xiaoling; Peng, Yufa; Valverde, Bernal E; Qiang, Sheng

    2015-05-27

    Weedy rice infests paddy fields worldwide at an alarmingly increasing rate. There is substantial evidence indicating that many weedy rice forms originated from or are closely related to cultivated rice. There is suspicion that the outbreak of weedy rice in China may be related to widely grown hybrid rice due to its heterosis and the diversity of its progeny, but this notion remains unsupported by direct evidence. We screened weedy rice accessions by both genetic and molecular marker tests for the cytoplasmic male sterility (CMS) genes (Wild abortive, WA, and Boro type, BT) most widely used in the production of indica and japonica three-line hybrid rice as a diagnostic trait of direct parenthood. Sixteen weedy rice accessions of the 358 tested (4.5%) contained the CMS-WA gene; none contained the CMS-BT gene. These 16 accessions represent weedy rices recently evolved from maternal hybrid rice derivatives, given the primarily maternal inheritance of this trait. Our results provide key direct evidence that hybrid rice can be involved in the evolution of some weedy rice accessions, but is not a primary factor in the recent outbreak of weedy rice in China.

  4. Steerability of Hermite Kernel

    Czech Academy of Sciences Publication Activity Database

    Yang, Bo; Flusser, Jan; Suk, Tomáš

    2013-01-01

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

  5. 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...

  6. Discriminative kernel feature extraction and learning for object recognition and detection

    DEFF Research Database (Denmark)

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

    2015-01-01

    Feature extraction and learning is critical for object recognition and detection. By embedding context cue of image attributes into the kernel descriptors, we propose a set of novel kernel descriptors called context kernel descriptors (CKD). The motivation of CKD is to use the spatial consistency...... even in high-dimensional space. In addition, the latent connection between Rényi quadratic entropy and the mapping data in kernel feature space further facilitates us to capture the geometric structure as well as the information about the underlying labels of the CKD using CSQMI. Thus the resulting...... codebook and reduced CKD are discriminative. We report superior performance of our algorithm for object recognition on benchmark datasets like Caltech-101 and CIFAR-10, as well as for detection on a challenging chicken feet dataset....

  7. Overview of real-time kernels at the Superconducting Super Collider Laboratory

    International Nuclear Information System (INIS)

    Low, K.; Acharya, S.; Allen, M.; Faught, E.; Haenni, D.; Kalbfleisch, C.

    1991-01-01

    The Superconducting Super Collider Laboratory (SSCL) will have many subsystems that will require real-time microprocessor control. Examples of such Sub-systems requiring real-time controls are power supply ramp generators and quench protection monitors for the superconducting magnets. The authors plan on using a commercial multitasking real-time kernel in these systems. These kernels must perform in a consistent, reliable and efficient manner. Actual performance measurements have been conducted on four different kernels, all running on the same hardware platform. The measurements fall into two categories. Throughput measurements covering the 'non-real-time' aspects of the kernel include process creation/termination times, interprocess communication facilities involving messages, semaphores and shared memory and memory allocation/deallocation. Measurements concentrating on real-time response are context switch times, interrupt latencies and interrupt task response

  8. Overview of real-time kernels at the Superconducting Super Collider Laboratory

    International Nuclear Information System (INIS)

    Low, K.; Acharya, S.; Allen, M.; Faught, E.; Haenni, D.; Kalbfleisch, C.

    1991-05-01

    The Superconducting Super Collider Laboratory (SSCL) will have many subsystems that will require real-time microprocessor control. Examples of such sub-systems requiring real-time controls are power supply ramp generators and quench protection monitors for the superconducting magnets. We plan on using a commercial multitasking real-time kernel in these systems. These kernels must perform in a consistent, reliable and efficient manner. Actual performance measurements have been conducted on four different kernels, all running on the same hardware platform. The measurements fall into two categories. Throughput measurements covering the ''non-real-time'' aspects of the kernel include process creation/termination times, interprocess communication facilities involving messages, semaphores and shared memory and memory allocation/deallocation. Measurements concentrating on real-time response are context switch times, interrupt latencies and interrupt task response. 6 refs., 2 tabs

  9. Transcriptional changes of rice in response to rice black-streaked dwarf virus.

    Science.gov (United States)

    Ahmed, Mohamed M S; Ji, Wen; Wang, Muyue; Bian, Shiquan; Xu, Meng; Wang, Weiyun; Zhang, Jiangxiang; Xu, Zhihao; Yu, Meimei; Liu, Qiaoquan; Zhang, Changquan; Zhang, Honggen; Tang, Shuzhu; Gu, Minghong; Yu, Hengxiu

    2017-09-10

    Rice black-streaked dwarf virus (RBSDV), a member of the genus Fijivirus in the family Reoviridae, causes significant economic losses in rice production in China and many other Asian countries. Although a great deal of effort has been made to elucidate the interactions among the virus, insect vectors, host and environmental conditions, few RBSDV proteins involved in pathogenesis have been identified, and the biological basis of disease development in rice remains largely unknown. Transcriptomic information associated with the disease development in rice would be helpful to unravel the biological mechanism. To determine how the rice transcriptome changes in response to RBSDV infection, we carried out RNA-Seq to perform a genome-wide gene expression analysis of a susceptible rice cultivar KTWYJ3. The transcriptomes of RBSDV-infected samples were compared to those of RBSDV-free (healthy) at two time points (time points are represented by group I and II). The results derived from the differential expression analysis in RBSDV-infected libraries vs. healthy ones in group I revealed that 102 out of a total of 281 significant differentially expressed genes (DEGs) were up-regulated and 179 DEGs were down-regulated. Of the 2592 identified DEGs in group II, 1588 DEGs were up-regulated and 1004 DEGs were down-regulated. A total of 66 DEGs were commonly identified in both groups. Of these 66 DEGs, expression patterns for 36 DEGs were similar in both groups. Our analysis demonstrated that some genes related to disease defense and stress resistance were up-regulated while genes associated with chloroplast were down-regulated in response to RBSDV infection. In addition, some genes associated with plant-height were differentially expressed. This result indicates those genes might be involved in dwarf symptoms caused by RBSDV. Taken together, our results provide a genome-wide transcriptome analysis for rice plants in response to RBSDV infection which may contribute to the

  10. Integrated rice-duck farming mitigates the global warming potential in rice season.

    Science.gov (United States)

    Xu, Guochun; Liu, Xin; Wang, Qiangsheng; Yu, Xichen; Hang, Yuhao

    2017-01-01

    Integrated rice-duck farming (IRDF), as a mode of ecological agriculture, is an important way to realize sustainable development of agriculture. A 2-year split-plot field experiment was performed to evaluate the effects of IRDF on methane (CH 4 ) and nitrous oxide (N 2 O) emissions and its ecological mechanism in rice season. This experiment was conducted with two rice farming systems (FS) of IRDF and conventional farming (CF) under four paddy-upland rotation systems (PUR): rice-fallow (RF), annual straw incorporating in rice-wheat rotation system (RWS), annual straw-based biogas residues incorporating in rice-wheat rotation system (RWB), and rice-green manure (RGM). During the rice growing seasons, IRDF decreased the CH 4 emission by 8.80-16.68%, while increased the N 2 O emission by 4.23-15.20%, when compared to CF. Given that CH 4 emission contributed to 85.83-96.22% of global warming potential (GWP), the strong reduction in CH 4 emission led to a significantly lower GWP of IRDF as compared to CF. The reason for this trend was because IRDF has significant effect on dissolved oxygen (DO) and soil redox potential (Eh), which were two pivotal factors for CH 4 and N 2 O emissions in this study. The IRDF not only mitigates the GWP, but also increases the rice yield by 0.76-2.43% compared to CF. Moreover, compared to RWS system, RF, RWB and RGM systems significantly reduced CH 4 emission by 50.17%, 44.89% and 39.51%, respectively, while increased N 2 O emission by 10.58%, 14.60% and 23.90%, respectively. And RWS system had the highest GWP. These findings suggest that mitigating GWP and improving rice yield could be simultaneously achieved by the IRDF, and employing suitable PUR would benefit for relieving greenhouse effect. Copyright © 2016 Elsevier B.V. All rights reserved.

  11. 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.

  12. 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.

  13. Pencil kernel correction and residual error estimation for quality-index-based dose calculations

    International Nuclear Information System (INIS)

    Nyholm, Tufve; Olofsson, Joergen; Ahnesjoe, Anders; Georg, Dietmar; Karlsson, Mikael

    2006-01-01

    Experimental data from 593 photon beams were used to quantify the errors in dose calculations using a previously published pencil kernel model. A correction of the kernel was derived in order to remove the observed systematic errors. The remaining residual error for individual beams was modelled through uncertainty associated with the kernel model. The methods were tested against an independent set of measurements. No significant systematic error was observed in the calculations using the derived correction of the kernel and the remaining random errors were found to be adequately predicted by the proposed method

  14. Engineered Dwarf Male-Sterile Rice: A Promising Genetic Tool for Facilitating Recurrent Selection in Rice.

    Science.gov (United States)

    Ansari, Afsana; Wang, Chunlian; Wang, Jian; Wang, Fujun; Liu, Piqing; Gao, Ying; Tang, Yongchao; Zhao, Kaijun

    2017-01-01

    Rice is a crop feeding half of the world's population. With the continuous raise of yield potential via genetic improvement, rice breeding has entered an era where multiple genes conferring complex traits must be efficiently manipulated to increase rice yield further. Recurrent selection is a sound strategy for manipulating multiple genes and it has been successfully performed in allogamous crops. However, the difficulties in emasculation and hand pollination had obstructed efficient use of recurrent selection in autogamous rice. Here, we report development of the dwarf male-sterile rice that can facilitate recurrent selection in rice breeding. We adopted RNAi technology to synergistically regulate rice plant height and male fertility to create the dwarf male-sterile rice. The RNAi construct pTCK-EGGE, targeting the OsGA20ox2 and OsEAT1 genes, was constructed and used to transform rice via Agrobacterium -mediated transformation. The transgenic T0 plants showing largely reduced plant height and complete male-sterile phenotypes were designated as the dwarf male-sterile plants. Progenies of the dwarf male-sterile plants were obtained by pollinating them with pollens from the wild-type. In the T1 and T2 populations, half of the plants were still dwarf male-sterile; the other half displayed normal plant height and male fertility which were designated as tall and male-fertile plants. The tall and male-fertile plants are transgene-free and can be self-pollinated to generate new varieties. Since emasculation and hand pollination for dwarf male-sterile rice plants is no longer needed, the dwarf male-sterile rice can be used to perform recurrent selection in rice. A dwarf male-sterile rice-based recurrent selection model has been proposed.

  15. A Walk-based Semantically Enriched Tree Kernel Over Distributed Word Representations

    DEFF Research Database (Denmark)

    Srivastava, Shashank; Hovy, Dirk

    2013-01-01

    We propose a walk-based graph kernel that generalizes the notion of tree-kernels to continuous spaces. Our proposed approach subsumes a general framework for word-similarity, and in particular, provides a flexible way to incorporate distributed representations. Using vector representations......, such an approach captures both distributional semantic similarities among words as well as the structural relations between them (encoded as the structure of the parse tree). We show an efficient formulation to compute this kernel using simple matrix multiplication operations. We present our results on three...

  16. On defining and computing fuzzy kernels on L-valued simple graphs

    International Nuclear Information System (INIS)

    Bisdorff, R.; Roubens, M.

    1996-01-01

    In this paper we introduce the concept of fuzzy kernels defined on valued-finite simple graphs in a sense close to fuzzy preference modelling. First we recall the classic concept of kernel associated with a crisp binary relation defined on a finite set. In a second part, we introduce fuzzy binary relations. In a third part, we generalize the crisp kernel concept to such fuzzy binary relations and in a last part, we present an application to fuzzy choice functions on fuzzy outranking relations

  17. Accuracy of approximations of solutions to Fredholm equations by kernel methods

    Czech Academy of Sciences Publication Activity Database

    Gnecco, G.; Kůrková, Věra; Sanguineti, M.

    2012-01-01

    Roč. 218, č. 14 (2012), s. 7481-7497 ISSN 0096-3003 R&D Projects: GA ČR GAP202/11/1368; GA MŠk OC10047 Grant - others:CNR-AV ČR(CZ-IT) Project 2010–2012 “Complexity of Neural -Network and Kernel Computational Models Institutional research plan: CEZ:AV0Z10300504 Keywords : approximate solutions to integral equations * radial and kernel-based networks * Gaussian kernels * model complexity * analysis of algorithms Subject RIV: IN - Informatics, Computer Science Impact factor: 1.349, year: 2012

  18. Adaptive kernel regression for freehand 3D ultrasound reconstruction

    Science.gov (United States)

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

    2017-03-01

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

  19. Heat exposure, cardiovascular stress and work productivity in rice harvesters in India: implications for a climate change future.

    Science.gov (United States)

    Sahu, Subhashis; Sett, Moumita; Kjellstrom, Tord

    2013-01-01

    Excessive workplace heat exposures create well-known risks of heat stroke, and it limits the workers' capacity to sustain physical activity. There is very limited evidence available on how these effects reduce work productivity, while the quantitative relationship between heat and work productivity is an essential basis for climate change impact assessments. We measured hourly heat exposure in rice fields in West Bengal and recorded perceived health problems via interviews of 124 rice harvesters. In a sub-group (n = 48) heart rate was recorded every minute in a standard work situation. Work productivity was recorded as hourly rice bundle collection output. The hourly heat levels (WBGT = Wet Bulb Globe Temperature) were 26-32°C (at air temperatures of 30-38°C), exceeding international standards. Most workers reported exhaustion and pain during work on hot days. Heart rate recovered quickly at low heat, but more slowly at high heat, indicating cardiovascular strain. The hourly number of rice bundles collected was significantly reduced at WBGT>26°C (approximately 5% per°C of increased WBGT). We conclude that high heat exposure in agriculture caused heat strain and reduced work productivity. This reduction will be exacerbated by climate change and may undermine the local economy.

  20. Review of Palm Kernel Oil Processing And Storage Techniques In South East Nigeria

    Directory of Open Access Journals (Sweden)

    Okeke CG

    2017-06-01

    Full Text Available An assessment of palm kernel processing and storage in South-Eastern Nigeria was carried out by investigative survey approach. The survey basically ascertained the extent of mechanization applicable in the area to enable the palm kernel processors and agricultural policy makers, device the modalities for improving palm kernel processing in the area. According to the results obtained from the study, in Abia state, 85% of the respondents use mechanical method while 15% use manual method in cracking their kernels. In Imo state, 83% of the processors use mechanical method while 17% use manual method. In Enugu and Ebonyi state, 70% and 50% of the processors respectively use mechanical method. It is only in Anambra state that greater number of the processors (50% use manual method while 45% use mechanical means. It is observable from the results that palm kernel oil extraction has not received much attention in mechanization. The ANOVA of the palm kernel oil extraction technique in South- East Nigeria showed significant difference in both the study area and oil extraction techniques at 5% level of probability. Results further revealed that in Abia State, 70% of the processors use complete fractional process in refining the palm kernel oil; 25% and 5% respectively use incomplete fractional process and zero refining process. In Anambra, 60% of the processors use complete fractional process and 40% use incomplete fractional process. Zero refining method is not applicable in Anambra state. In Enugu sate, 53% use complete fractional process while 25% and 22% respectively use zero refining and incomplete fractional process in refining the palm kernel oil. Imo state, mostly use complete fractional process (85% in refining palm kernel oil. About 10% use zero refining method while 5% of the processors use incomplete fractional process. Plastic containers and metal drums are dominantly used in most areas in south-east Nigeria for the storage of palm kernel oil.

  1. 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.

  2. Kernel-Correlated Levy Field Driven Forward Rate and Application to Derivative Pricing

    Energy Technology Data Exchange (ETDEWEB)

    Bo Lijun [Xidian University, Department of Mathematics (China); Wang Yongjin [Nankai University, School of Business (China); Yang Xuewei, E-mail: xwyangnk@yahoo.com.cn [Nanjing University, School of Management and Engineering (China)

    2013-08-01

    We propose a term structure of forward rates driven by a kernel-correlated Levy random field under the HJM framework. The kernel-correlated Levy random field is composed of a kernel-correlated Gaussian random field and a centered Poisson random measure. We shall give a criterion to preclude arbitrage under the risk-neutral pricing measure. As applications, an interest rate derivative with general payoff functional is priced under this pricing measure.

  3. 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

  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. 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...

  6. Learning a peptide-protein binding affinity predictor with kernel ridge regression

    Science.gov (United States)

    2013-01-01

    Background The cellular function of a vast majority of proteins is performed through physical interactions with other biomolecules, which, most of the time, are other proteins. Peptides represent templates of choice for mimicking a secondary structure in order to modulate protein-protein interaction. They are thus an interesting class of therapeutics since they also display strong activity, high selectivity, low toxicity and few drug-drug interactions. Furthermore, predicting peptides that would bind to a specific MHC alleles would be of tremendous benefit to improve vaccine based therapy and possibly generate antibodies with greater affinity. Modern computational methods have the potential to accelerate and lower the cost of drug and vaccine discovery by selecting potential compounds for testing in silico prior to biological validation. Results We propose a specialized string kernel for small bio-molecules, peptides and pseudo-sequences of binding interfaces. The kernel incorporates physico-chemical properties of amino acids and elegantly generalizes eight kernels, comprised of the Oligo, the Weighted Degree, the Blended Spectrum, and the Radial Basis Function. We provide a low complexity dynamic programming algorithm for the exact computation of the kernel and a linear time algorithm for it’s approximation. Combined with kernel ridge regression and SupCK, a novel binding pocket kernel, the proposed kernel yields biologically relevant and good prediction accuracy on the PepX database. For the first time, a machine learning predictor is capable of predicting the binding affinity of any peptide to any protein with reasonable accuracy. The method was also applied to both single-target and pan-specific Major Histocompatibility Complex class II benchmark datasets and three Quantitative Structure Affinity Model benchmark datasets. Conclusion On all benchmarks, our method significantly (p-value ≤ 0.057) outperforms the current state-of-the-art methods at predicting

  7. 75 FR 56911 - Request for Public Comment on the United States Standards for Rough Rice, Brown Rice for...

    Science.gov (United States)

    2010-09-17

    ... for Rough Rice, Brown Rice for Processing, and Milled Rice AGENCY: Grain Inspection, Packers and... reviewing the United States Standards and grading procedures for Rough Rice, Brown Rice for Processing, and Milled Rice under the Agriculture Marketing Act of 1946 (AMA). Since the standards were last revised...

  8. The uranium recovery from UO{sub 2} kernel production effluent

    Energy Technology Data Exchange (ETDEWEB)

    Chen, Xiaotong, E-mail: chenxiaotong@tsinghua.edu.cn; He, Linfeng; Liu, Bing; Tang, Yaping; Tang, Chunhe

    2016-12-15

    Graphical abstract: In this study, a flow sheet including evaporation, flocculation, filtration, adsorption, and reverse osmosis was established for the UO{sub 2} kernel production effluent of HTR spherical fuel elements. The uranium recovery could reach 99.9% after the treatment, with almost no secondary pollution produced. Based on the above experimental results, the treating flow process in this study would be feasible for laboratory- and engineering-scale treatment of UO{sub 2} kernel production effluent of HTR spherical fuel elements. - Highlights: • A flow sheet including evaporation, flocculation, filtration, adsorption, and reverse osmosis was established for the UO{sub 2} kernel production effluent. • The uranium recovery could reach 99.9% after the treatment, with almost no secondary pollution produced. • The treating flow process would be feasible for laboratory- and engineering-scale treatment of UO{sub 2} kernel production effluent. - Abstract: For the fabrication of coated particle fuel elements of high temperature gas cooled reactors, the ceramic UO{sub 2} kernels are prepared through chemical gelation of uranyl nitrate solution droplets, which produces radioactive effluent with components of ammonia, uranium, organic compounds and ammonium nitrate. In this study, a flow sheet including evaporation, flocculation, filtration, adsorption, and reverse osmosis was established for the effluent treating. The uranium recovery could reach 99.9% after the treatment, with almost no secondary pollution produced.

  9. 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

  10. Detoxification of Jatropha curcas kernel cake by a novel Streptomyces fimicarius strain.

    Science.gov (United States)

    Wang, Xing-Hong; Ou, Lingcheng; Fu, Liang-Liang; Zheng, Shui; Lou, Ji-Dong; Gomes-Laranjo, José; Li, Jiao; Zhang, Changhe

    2013-09-15

    A huge amount of kernel cake, which contains a variety of toxins including phorbol esters (tumor promoters), is projected to be generated yearly in the near future by the Jatropha biodiesel industry. We showed that the kernel cake strongly inhibited plant seed germination and root growth and was highly toxic to carp fingerlings, even though phorbol esters were undetectable by HPLC. Therefore it must be detoxified before disposal to the environment. A mathematic model was established to estimate the general toxicity of the kernel cake by determining the survival time of carp fingerling. A new strain (Streptomyces fimicarius YUCM 310038) capable of degrading the total toxicity by more than 97% in a 9-day solid state fermentation was screened out from 578 strains including 198 known strains and 380 strains isolated from air and soil. The kernel cake fermented by YUCM 310038 was nontoxic to plants and carp fingerlings and significantly promoted tobacco plant growth, indicating its potential to transform the toxic kernel cake to bio-safe animal feed or organic fertilizer to remove the environmental concern and to reduce the cost of the Jatropha biodiesel industry. Microbial strain profile essential for the kernel cake detoxification was discussed. Copyright © 2013 Elsevier B.V. All rights reserved.

  11. 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…

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

    Directory of Open Access Journals (Sweden)

    Xianglin ZHU

    2014-06-01

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

  13. Moisture Adsorption Isotherm and Storability of Hazelnut Inshells and Kernels Produced in Oregon, USA.

    Science.gov (United States)

    Jung, Jooyeoun; Wang, Wenjie; McGorrin, Robert J; Zhao, Yanyun

    2018-02-01

    Moisture adsorption isotherms and storability of dried hazelnut inshells and kernels produced in Oregon were evaluated and compared among cultivars, including Barcelona, Yamhill, and Jefferson. Experimental moisture adsorption data fitted to Guggenheim-Anderson-de Boer (GAB) model, showing less hygroscopic properties in Yamhill than other cultivars of inshells and kernels due to lower content of carbohydrate and protein, but higher content of fat. The safe levels of moisture content (MC, dry basis) of dried inshells and kernels for reaching kernel water activity (a w ) ≤0.65 were estimated using the GAB model as 11.3% and 5.0% for Barcelona, 9.4% and 4.2% for Yamhill, and 10.7% and 4.9% for Jefferson, respectively. Storage conditions (2 °C at 85% to 95% relative humidity [RH], 10 °C at 65% to 75% RH, and 27 °C at 35% to 45% RH), times (0, 4, 8, or 12 mo), and packaging methods (atmosphere vs. vacuum) affected MC, a w , bioactive compounds, lipid oxidation, and enzyme activity of dried hazelnut inshells or kernels. For inshells packaged at woven polypropylene bag, MC and a w of inshells and kernels (inside shells) increased at 2 and 10 °C, but decreased at 27 °C during storage. For kernels, lipid oxidation and polyphenol oxidase activity also increased with extended storage time (P adsorption and physicochemical and enzymatic stability during storage. Moisture adsorption isotherm of hazelnut inshells and kernels is useful for predicting the storability of nuts. This study found that water adsorption and storability varied among the different cultivars of nuts, in which Yamhill was less hygroscopic than Barcelona and Jefferson, thus more stable during storage. For ensuring food safety and quality of nuts during storage, each cultivar of kernels should be dried to a certain level of MC. Lipid oxidation and enzyme activity of kernel could be increased with extended storage time. Vacuum packaging was recommended to kernels for reducing moisture adsorption

  14. RICD: A rice indica cDNA database resource for rice functional genomics

    Directory of Open Access Journals (Sweden)

    Zhang Qifa

    2008-11-01

    Full Text Available Abstract Background The Oryza sativa L. indica subspecies is the most widely cultivated rice. During the last few years, we have collected over 20,000 putative full-length cDNAs and over 40,000 ESTs isolated from various cDNA libraries of two indica varieties Guangluai 4 and Minghui 63. A database of the rice indica cDNAs was therefore built to provide a comprehensive web data source for searching and retrieving the indica cDNA clones. Results Rice Indica cDNA Database (RICD is an online MySQL-PHP driven database with a user-friendly web interface. It allows investigators to query the cDNA clones by keyword, genome position, nucleotide or protein sequence, and putative function. It also provides a series of information, including sequences, protein domain annotations, similarity search results, SNPs and InDels information, and hyperlinks to gene annotation in both The Rice Annotation Project Database (RAP-DB and The TIGR Rice Genome Annotation Resource, expression atlas in RiceGE and variation report in Gramene of each cDNA. Conclusion The online rice indica cDNA database provides cDNA resource with comprehensive information to researchers for functional analysis of indica subspecies and for comparative genomics. The RICD database is available through our website http://www.ncgr.ac.cn/ricd.

  15. Physicochemical and Antioxidant Properties of Rice Bran Oils Produced from Colored Rice Using Different Extraction Methods.

    Science.gov (United States)

    Mingyai, Sukanya; Kettawan, Aikkarach; Srikaeo, Khongsak; Singanusong, Riantong

    2017-06-01

    This study investigated the physicochemical and antioxidant properties of rice bran oil (RBO) produced from the bran of three rice varities; Khao Dawk Mali 105 (white rice), Red Jasmine rice (red rice) and Hom-nin rice (black rice) using three extraction methods including cold-press extraction (CPE), solvent extraction (SE) and supercritical CO 2 extraction (SC-CO 2 ). Yields, color, acid value (AV), free fatty acid (FFA), peroxide value (PV), iodine value (IV), total phenolic compound (TPC), γ-oryzanol, α-tocopherol and fatty acid profile were analyzed. It was found that the yields obtained from SE, SC-CO 2 and CPE extractions were 17.35-20.19%, 14.76-18.16% and 3.22-6.22%, respectively. The RBO from the bran of red and black rice samples exhibited high antioxidant activities. They also contained higher amount of γ-oryzanol and α-tocopherol than those of white rice sample. In terms of extraction methods, SC-CO 2 provided better qualities of RBO as evidenced by their physicochemical and antioxidant properties. This study found that RBO produced from the bran of black rice samples using SC-CO 2 extraction method showed the best physicochemical and antioxidant properties.

  16. Dynamic viscoelasticity of protease-treated rice batters for gluten-free rice bread making.

    Science.gov (United States)

    Honda, Yuji; Inoue, Nanami; Sugimoto, Reina; Matsumoto, Kenji; Koda, Tomonori; Nishioka, Akihiro

    2018-03-01

    Papain (cysteine protease), subtilisin (Protin SD-AY10, serine protease), and bacillolysin (Protin SD-NY10, metallo protease) increased the specific volume of gluten-free rice breads by 19-63% compared to untreated bread. In contrast, Newlase F (aspartyl protease) did not expand the volume of the rice bread. In a rheological analysis, the viscoelastic properties of the gluten-free rice batters also depended on the protease categories. Principal component analysis (PCA) analysis suggested that the storage and loss moduli (G' and G″, respectively) at 35 °C, and the maximum values of G' and G″, were important factors in the volume expansion. Judging from the PCA of the viscoelastic parameters of the rice batters, papain and Protin SD-AY10 improved the viscoelasticity for gluten-free rice bread making, and Protin SD-NY effectively expanded the gluten-free rice bread. The rheological properties differed between Protin SD-NY and the other protease treatments.

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

    OpenAIRE

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

    2016-01-01

    The efficacy of color sorting on reducing aflatoxin levels in shelled apricot kernels was assessed. Naturally-contaminated kernels were submitted to an electronic optical sorter or blanched, peeled, and manually sorted to visually identify and sort discolored kernels (dark and spotted) from healthy ones. The samples obtained from the two sorting approaches were ground, homogenized, and analysed by HPLC-FLD for their aflatoxin content. A mass balance approach was used to measure the distributi...

  18. From GCM energy kernels to Weyl-Wigner Hamiltonians: a particular mapping

    International Nuclear Information System (INIS)

    Galetti, D.

    1984-01-01

    A particular mapping is established which directly connects GCM energy kernels to Weyl-Wigner Hamiltonians, under the assumption of gaussian overlap kernel. As an application of this mapping scheme the collective Hamiltonians for some giant resonances are derived. (Author) [pt

  19. Migration of the ThO2 kernels under the influence of a temperature gradient

    International Nuclear Information System (INIS)

    Smith, C.L.

    1977-01-01

    Biso-coated ThO 2 fertile fuel kernels will migrate up the thermal gradients imposed across coated particles during high-temperature gas-cooled reactor (HTGR) operation. Thorium dioxide kernel migration has been studied as a function of temperature (1290 to 1705 0 C) (1563 to 1978 K) and ThO 2 kernel burnup (0.9 to 5.8 percent FIMA) in out-of-pile postirradiation thermal gradient heating experiments. The studies were conducted to obtain descriptions of migration rates that will be used in core design studies to evaluate the impact of ThO 2 migration on fertile fuel performance in an operating HTGR and to define characteristics needed by any comprehensive model describing ThO 2 kernel migration. The kinetics data generated in these postirradiation studies are consistent with in-pile data collected by investigators at Oak Ridge National Laboratory, which supports use of the more precise postirradiation heating results in HTGR core design studies. Observations of intergranular carbon deposits on the cool side of migrating kernels support the assumption that the kinetics of kernel migration are controlled by solid-state diffusion within irradiated ThO 2 kernels. The migration is characterized by a period of no migration (incubation period), followed by migration at the equilibrium rate for ThO 2 . The incubation period decreases with increasing temperature and kernel burnup. The improved understanding of the kinetics of ThO 2 kernel migration provided by this work will contribute to an optimization of HTGR core design and an increased confidence in fuel performance predictions

  20. 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.