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Sample records for sisal execution kernel

  1. Proceedings: Sisal `93

    Energy Technology Data Exchange (ETDEWEB)

    Feo, J.T. [ed.

    1993-10-01

    This report contain papers on: Programmability and performance issues; The case of an iterative partial differential equation solver; Implementing the kernal of the Australian Region Weather Prediction Model in Sisal; Even and quarter-even prime length symmetric FFTs and their Sisal Implementations; Top-down thread generation for Sisal; Overlapping communications and computations on NUMA architechtures; Compiling technique based on dataflow analysis for funtional programming language Valid; Copy elimination for true multidimensional arrays in Sisal 2.0; Increasing parallelism for an optimization that reduces copying in IF2 graphs; Caching in on Sisal; Cache performance of Sisal Vs. FORTRAN; FFT algorithms on a shared-memory multiprocessor; A parallel implementation of nonnumeric search problems in Sisal; Computer vision algorithms in Sisal; Compilation of Sisal for a high-performance data driven vector processor; Sisal on distributed memory machines; A virtual shared addressing system for distributed memory Sisal; Developing a high-performance FFT algorithm in Sisal for a vector supercomputer; Implementation issues for IF2 on a static data-flow architechture; and Systematic control of parallelism in array-based data-flow computation. Selected papers have been indexed separately for inclusion in the Energy Science and Technology Database.

  2. Bioenergy from sisal residues

    Energy Technology Data Exchange (ETDEWEB)

    Jungersen, G. [Dansk Teknologisk Inst. (Denmark); Kivaisi, A.; Rubindamayugi, M. [Univ. of Dar es Salaam (Tanzania, United Republic of)

    1998-05-01

    The main objectives of this report are: To analyse the bioenergy potential of the Tanzanian agro-industries, with special emphasis on the Sisal industry, the largest producer of agro-industrial residues in Tanzania; and to upgrade the human capacity and research potential of the Applied Microbiology Unit at the University of Dar es Salaam, in order to ensure a scientific and technological support for future operation and implementation of biogas facilities and anaerobic water treatment systems. The experimental work on sisal residues contains the following issues: Optimal reactor set-up and performance; Pre-treatment methods for treatment of fibre fraction in order to increase the methane yield; Evaluation of the requirement for nutrient addition; Evaluation of the potential for bioethanol production from sisal bulbs. The processing of sisal leaves into dry fibres (decortication) has traditionally been done by the wet processing method, which consumes considerable quantities of water and produces large quantities of waste water. The Tanzania Sisal Authority (TSA) is now developing a dry decortication method, which consumes less water and produces a waste product with 12-15% TS, which is feasible for treatment in CSTR systems (Continously Stirred Tank Reactors). (EG)

  3. Mechanical characterization of sisal reinforced cement mortar

    OpenAIRE

    R. Fujiyama; F. Darwish; M.V. Pereira

    2014-01-01

    This work aims at evaluating the mechanical behavior of sisal fiber reinforced cement mortar. The composite material was produced from a mixture of sand, cement, and water. Sisal fibers were added to the mixture in different lengths. Mechanical characterization of both the composite and the plain mortar was carried out using three point bend, compression, and impact tests. Specimens containing notches of different root radii were loaded in three point bending in an effort to determine the eff...

  4. Sapogeninas esteroídicas em sisal Steroidal sapogenins in sisal

    Directory of Open Access Journals (Sweden)

    Marco Antonio Teixeira Zullo

    1989-01-01

    Full Text Available Foram determinados os teores de sapogeninas esteroídicas hecogenina e tigogenina em folhas secas de sisal (Agave sisalana e dos híbridos de A. amaniensis x A. Angustifolia, obtidos no Instituto Agronômico. Esses híbridos mostraram maiores teores de sapogeninas, 220-480mg/100g, do que o sisal, 140 ± 28mg/100g, assim como maiores teores de tigogenina (148-217mg/100g. Apenas o híbrido 003B apresentou teor de hecogenina (99 ± 16mg/100g significativamente maior que o encontrado no sisal comum (26 ± 3mg/100g.The hecogenin and tigogenin contents were determined in dried leaves of sisal (Agave sisalana and of the hybrids of A. amaniensis x A. angustifolía, obtained in the Experimental Station of the Instituto Agronômico, Campinas, State of São Paulo, Brazil. The hybrids showed higher sapogenin contents (220-480mg/100g than sisal (140 ± 28mg/100g, as well as higher tigogenin content (148-217mg/100g. The hybrid 003B was the only one that showed significantly higher hecogenin content (99 ± 16mg/100g than sisal (26 ± 3mg/100g.

  5. Sisal organosolv pulp as reinforcement for cement based composites

    OpenAIRE

    Joaquim, Ana Paula; Tonoli, Gustavo Henrique Denzin; Santos, Sérgio Francisco Dos; Savastano Junior, Holmer

    2009-01-01

    The present work describes non-conventional sisal (Agave sisalana) chemical (organosolv) pulp from residues of cordage as reinforcement to cement based materials. Sisal organosolv pulp was produced in a 1:1 ethanol/water mixture and post chemically and physically characterized in order to compare its properties with sisal kraft pulp. Cement based composites reinforced with organosolv or kraft pulps and combined with polypropylene (PP) fibres were produced by the slurry de-watering and pressin...

  6. Mechanical characterization of sisal reinforced cement mortar

    Directory of Open Access Journals (Sweden)

    R. Fujiyama

    2014-01-01

    Full Text Available This work aims at evaluating the mechanical behavior of sisal fiber reinforced cement mortar. The composite material was produced from a mixture of sand, cement, and water. Sisal fibers were added to the mixture in different lengths. Mechanical characterization of both the composite and the plain mortar was carried out using three point bend, compression, and impact tests. Specimens containing notches of different root radii were loaded in three point bending in an effort to determine the effect of the fibers on the fracture toughness of the material. The results obtained indicate that, while fiber reinforcement leads to a decrease in compressive strength, J-integral calculations at maximum load for the different notch root radii have indicated, particularly for the case of long fibers, a significant superiority of the reinforced material in comparison with the plain cement mortar, in consistence with the impact test data.

  7. Additives effect on chemical composition and quality of sisal co-product silage

    Directory of Open Access Journals (Sweden)

    Luiz Gustavo Neves Brandão

    2013-12-01

    Full Text Available Fermentation profile and nutritional value of sisal co-product silage (SC subjected to seven treatments (additives, were evaluated. The SC was ensiled in natura and added with: soy meal, urea, wheat meal, palm kernel cake, A. sisalana dust, licuri cake and cottonseed cake. Experimental silos with capacity for approximately 15 kg of silage, were used. The silos were opened 60 days after ensilage process. It was used a completely randomized design with three replications. The SC in natura present low values of dry mater (DM 12.3% and the additives increased dry matter silages, exception for urea. The SC silage additivated with soybean meal (pH 4.9 and palm kernel cake (butyric acid = 0.07% DM differed, respectively, for pH and butyric acid, compared with in natura SC silage (pH = 4.1 and butyric acid = 0.03% DM. The addition of soybean meal, urea, cottonseed meal, wheat bran and palm kernel, increased crude protein (CP of in natura SC silage. The NDF in silage increased with addition of cottonseed meal or palm kernel cake (60.1 and 66.2% DM in relation in natura SC silage (42.9% DM. The in natura and additivated silages of SC were considered as good or excellent quality.

  8. COMPOSITE FRIEND SISAL / POLYESTER TREATED IN SURFACE

    Directory of Open Access Journals (Sweden)

    Jayna K. Dionisio Santos

    2011-09-01

    Full Text Available The use of composites in manufacturing equipment and products is taking a very important space in the industry in general. Moreover these materials have unique characteristics when analyzed separately from constituents who are part of them. However it is know that cares must be taken in their manufacture, as the use of appropriate process and the composition of each element, in addition to adherence fiber / matrix, which is a major factor in obtaining of the final mechanical strength of the product. One should also take into account whether the composites are environmentally friendly. For this reason, in this work, a composite partially ecological was made, using as reinforcement, a sisal woven and, as matrix, the polyester resin. Seeking to improve the adherence fiber / matrix, a treatment in sisal woven was performed with aqueous solution of sodium hydroxide (NaOH at a concentration of 3%. The composite subjected to this treatment presented, in bending test, a better mechanical performance, with an increase of 27% in the flexion strength and of 54% in maximum strain, but there was a reduction of about 15% in its flexural modulus.

  9. Investigation on mechanical properties of woven alovera/sisal/kenaf ...

    Indian Academy of Sciences (India)

    1Department of Mechanical Engineering, Sri Sai Ram Institute of Technology, ... ASTM American Society for Testing and Materials ... stress [9]. Naturally the sisal fibres have the characteristics of higher wear ... In this research work an effort.

  10. Performance of a sisal fibre fixed-bed anaerobic digester for biogas ...

    African Journals Online (AJOL)

    A single stage anaerobic digester employing a sisal fibre waste fixed bed was studied for biogas production from sisal pulp waste. The fibre was colonized by microorganisms involved in biogas production. The sisal pulp waste to be digested was fed from the top and was sprinkled intermittently with recirculating leachate ...

  11. Life cycle assessment of sisal fibre – Exploring how local practices can influence environmental performance

    NARCIS (Netherlands)

    Broeren, M.L.M.; Dellaert, S.N.C.; Cok, B.; Patel, M.K.; Worrell, E.; Shen, L.

    2017-01-01

    Sisal fibre can potentially replace glass fibre in natural fibre composites. This study focuses on the environmental performance of sisal fibre production by quantifying the greenhouse gas (GHG) emissions and energy use of producing sisal fibre in Tanzania and Brazil using life cycle assessment

  12. Sisal organosolv pulp as reinforcement for cement based composites

    Directory of Open Access Journals (Sweden)

    Ana Paula Joaquim

    2009-09-01

    Full Text Available The present work describes non-conventional sisal (Agave sisalana chemical (organosolv pulp from residues of cordage as reinforcement to cement based materials. Sisal organosolv pulp was produced in a 1:1 ethanol/water mixture and post chemically and physically characterized in order to compare its properties with sisal kraft pulp. Cement based composites reinforced with organosolv or kraft pulps and combined with polypropylene (PP fibres were produced by the slurry de-watering and pressing method as a crude simulation of the Hatschek process. Composites were evaluated at 28 days of age, after exposition to accelerated carbonation and after 100 soak/dry cycles. Composites containing organosolv pulp presented lower mechanical strength, water absorption and apparent porosity than composites reinforced with kraft pulp. The best mechanical performance after ageing was also achieved by samples reinforced with kraft pulp. The addition of PP fibres favoured the maintenance of toughness after ageing. Accelerated carbonation promoted the densification of the composites reinforced with sisal organosolv + PP fibres.

  13. Profiling application potential for alkali treated sisal fiber ...

    African Journals Online (AJOL)

    The effect of alkali treatment on sisal fiber from the plant agave sisalana in appropriation for composite material application is presented. Effectiveness of the fiber's reinforcement potential within polypropylene (PP) matrix is evaluated through morphological analysis, crystallinity levels, and tensile, where ultimate tensile ...

  14. Biogas systems for sisal and other agro-industrial residues

    Energy Technology Data Exchange (ETDEWEB)

    Jungersen, G [Danish Technological Inst., Section for Biotechnology, Taastrup (Denmark)

    1998-12-31

    Most of the East-African agro-industries are generating very large quantities of organic residues from production and processing of different crops. In the East-African Region the most important of these crops are: Sisal, Sugar, Coffee, Cashew nuts and Pineapple. In other 3. world countries, Palm oil and Cassava (Tapioca starch) processing are main producers of organic waste products. Moreover, large quantities of organic residues are generated from other food processing activities like breweries, consumption of bananas etc. The following pages give examples of setups and system designs of anaerobic treatment systems for some of the residues mentioned above. When considering anaerobic treatment of sisal residues, which constitutes the main agro-industrial biomass resource in Tanzania, two major issues should be considered: Optimal reactor set-up and performance; And optionally, potential methods for pre-treatment of fibre fraction in order to increase the methane yield. The sisal liquid residues are degraded very fast and efficiently in UASB systems. At COD loading rates less than 11 kg COD/m{sup 3} x day, the reduction in organic matter is more than 90% and methane yields obtained are between 373 and 377 ml CH{sub 4}/g COD reduced. The treatment of sisal solid residues in CSTR systems has been examined both at mesophilic (37 deg. C) and thermophilic temperatures (55 deg. C.). (EG)

  15. Biogas systems for sisal and other agro-industrial residues

    Energy Technology Data Exchange (ETDEWEB)

    Jungersen, G. [Danish Technological Inst., Section for Biotechnology, Taastrup (Denmark)

    1997-12-31

    Most of the East-African agro-industries are generating very large quantities of organic residues from production and processing of different crops. In the East-African Region the most important of these crops are: Sisal, Sugar, Coffee, Cashew nuts and Pineapple. In other 3. world countries, Palm oil and Cassava (Tapioca starch) processing are main producers of organic waste products. Moreover, large quantities of organic residues are generated from other food processing activities like breweries, consumption of bananas etc. The following pages give examples of setups and system designs of anaerobic treatment systems for some of the residues mentioned above. When considering anaerobic treatment of sisal residues, which constitutes the main agro-industrial biomass resource in Tanzania, two major issues should be considered: Optimal reactor set-up and performance; And optionally, potential methods for pre-treatment of fibre fraction in order to increase the methane yield. The sisal liquid residues are degraded very fast and efficiently in UASB systems. At COD loading rates less than 11 kg COD/m{sup 3} x day, the reduction in organic matter is more than 90% and methane yields obtained are between 373 and 377 ml CH{sub 4}/g COD reduced. The treatment of sisal solid residues in CSTR systems has been examined both at mesophilic (37 deg. C) and thermophilic temperatures (55 deg. C.). (EG)

  16. Mechanical and thermal properties of water glass coated sisal fibre-reinforced polypropylene composite

    CSIR Research Space (South Africa)

    Phiri, G

    2012-10-01

    Full Text Available ?C). Figure 1 shows the processing steps followed to produce composite samples. Up to 15% fibre loading could be achieved and the sisal fibres were coated with water glass to improve fire resistance. In order to improve the adhesion between sisal... preparation process: (A) WG coated fibre, (B) High speed granulator, (C) Composite granules, (D) Single screw extruder, (E) Injection moulder and (F) Composite samples (dumbbells) Mechanical and thermal properties of water glass coated sisal fi bre...

  17. Durability of Cement Composites Reinforced with Sisal Fiber

    Science.gov (United States)

    Wei, Jianqiang

    This dissertation focuses mainly on investigating the aging mechanisms and degradation kinetics of sisal fiber, as well as the approaches to mitigate its degradation in the matrix of cement composites. In contrast to previous works reported in the literature, a novel approach is proposed in this study to directly determine the fiber's degradation rate by separately studying the composition changes, mechanical and physical properties of the embedded sisal fibers. Cement hydration is presented to be a crucial factor in understanding fiber degradation behavior. The degradation mechanisms of natural fiber consist of mineralization of cell walls, alkali hydrolysis of lignin and hemicellulose, as well as the cellulose decomposition which includes stripping of cellulose microfibrils and alkaline hydrolysis of amorphous regions in cellulose chains. Two mineralization mechanisms, CH-mineralization and self-mineralization, are proposed. The degradation kinetics of sisal fiber in the cement matrix are also analyzed and a model to predict the degradation rate of cellulose for natural fiber embedded in cement is outlined. The results indicate that the time needed to completely degrade the cellulose in the matrix with cement replacement by 30wt.% metakaolin is 13 times longer than that in pure cement. A novel and scientific method is presented to determine accelerated aging conditions, and to evaluating sisal fiber's degradation rate and durability of natural fiber-reinforced cement composites. Among the static aggressive environments, the most effective approach for accelerating the degradation of natural fiber in cement composites is to soak the samples or change the humidity at 70 °C and higher temperature. However, the dynamic wetting and drying cycling treatment has a more accelerating effect on the alkali hydrolysis of fiber's amorphous components evidenced by the highest crystallinity indices, minimum content of holocellulose, and lowest tensile strength. Based on the

  18. Insulation Characteristics of Sisal Fibre/Epoxy Composites

    Directory of Open Access Journals (Sweden)

    A. Shalwan

    2017-01-01

    Full Text Available Using natural fibres in civil engineering is the aim of many industrial and academics sectors to overcome the impact of synthetic fibres on environments. One of the potential applications of natural fibres composites is to be implemented in insulation components. Thermal behaviour of polymer composites based on natural fibres is recent ongoing research. In this article, thermal characteristics of sisal fibre reinforced epoxy composites are evaluated for treated and untreated fibres considering different volume fractions of 0–30%. The results revealed that the increase in the fibre volume fraction increased the insulation performance of the composites for both treated and untreated fibres. More than 200% insulation rate was achieved at the volume fraction of 20% of treated sisal fibres. Untreated fibres showed about 400% insulation rate; however, it is not recommended to use untreated fibres from mechanical point of view. The results indicated that there is potential of using the developed composites for insulation purposes.

  19. Mechanical Behaviour of Sisal Fibre Reinforced Cement Composites

    OpenAIRE

    M. Aruna

    2014-01-01

    Emphasis on the advancement of new materials and technology has been there for the past few decades. The global development towards using cheap and durable materials from renewable resources contributes to sustainable development. An experimental investigation of mechanical behaviour of sisal fibre-reinforced concrete is reported for making a suitable building material in terms of reinforcement. Fibre reinforced Composite is one such material, which has reformed the concept of high strength. ...

  20. Obtaining nanofibers from sisal to reinforce nanocomposites biodegradable matrixes

    International Nuclear Information System (INIS)

    Oliveira, Francieli B. de; Teixeira, Eliangela de M.; Marconcini, Jose M.; Mattoso, Luiz H.C.; Teodoro, Kelcilene B.R.

    2009-01-01

    Cellulose nanofibers have been extracted by acid hydrolysis from sisal fibers. They are seen a good source material due to availability and low cost. The nanofibers was evaluated by thermal degradation behavior using thermogravimetry (TG), crystallinity by X-ray diffraction and morphological structure was investigated by atomic force microscopy (AFM) experiments. The resulting nanofibers was shown high crystallinity and a network of rodlike cellulose elements. The nanofibers will be incorporated as reinforcement in a biodegradable matrix and evaluated. (author)

  1. Efficacy of Thermally Conditioned Sisal FRP Composite on the Shear Characteristics of Reinforced Concrete Beams

    Directory of Open Access Journals (Sweden)

    Tara Sen

    2013-01-01

    Full Text Available The development of commercially viable composites based on natural resources for a wide range of applications is on the rise. Efforts include new methods of production and the utilization of natural reinforcements to make biodegradable composites with lignocellulosic fibers, for various engineering applications. In this work, thermal conditioning of woven sisal fibre was carried out, followed by the development of woven sisal fibre reinforced polymer composite system, and its tensile and flexural behaviour was characterized. It was observed that thermal conditioning improved the tensile strength and the flexural strength of the woven sisal fibre composites, which were observed to bear superior values than those in the untreated ones. Then, the efficacy of woven sisal fibre reinforced polymer composite for shear strengthening of reinforced concrete beams was evaluated using two types of techniques: full and strip wrapping techniques. Detailed analysis of the load deflection behaviour and fracture study of reinforced concrete beams strengthened with woven sisal under shearing load were carried out, and it was concluded that woven sisal FRP strengthened beams, underwent very ductile nature of failure, without any delamination or debonding of sisal FRP, and also increased the shear strength and the first crack load of the reinforced concrete beams.

  2. Caracterização tecnológica de híbridos de sisal Technological characterization of sisal hybrids

    Directory of Open Access Journals (Sweden)

    Anisio Azzini

    1989-01-01

    Full Text Available No presente estudo procedeu-se à caracterização tecnológica de alguns híbridos de sisal em comparação com a espécie comum (Agave sisalana Perr., colhidos no Centro Experimental de Campinas em 1987. A densidade básica (0,172 a 0,249g/cm³ e o teor de matéria seca (16,91 a 24,82% cresceram da base para a extremidade das folhas de sisal, contrastando com os teores de fibra têxtil (37,71 a 23,43% e celulósica (21,75 a 14,56%, que decresceram a partir da base das folhas. As fibras celulósicas na base das folhas foram mais curtas; com maior lúmen e menor parede celular. O comprimento das fibras celulósicas do sisal comum (2,63mm foi maior que os híbridos (1,39 a 2,09mm: estes não apresentaram superioridade tecnológica em relação ao sisal comum.Some sisal hybrids were studied in comparison to the common sisal (Agave sisalana Perr. regarding some technological characteristics. The basic density (0.172 to 0.249 g/cm³ and the dry matter (16.91 to 24.82% increased from the base to top region of sisal leaf. On the other hand, the content of textile fibers decreased from the base to the top of the leaves (37.71 to 23.43. The same trend was observed for cellulosic fibers (21.75 to 14.56%. The cellulosic fibers in the leaf base were shorter, with more lumen and less cell wall. The length of cellulosic fiber on common sisal (2.63mm was longer than for hybrids (1.39 to 2.09mm. The sisal hybrids didn't show technological superiority over the common sisal.

  3. Morphology and crystallinity of sisal nanocellulose after sonication

    Science.gov (United States)

    Sosiati, H.; Wijayanti, D. A.; Triyana, K.; Kamiel, B.

    2017-09-01

    Different preparation methods on the natural fibers resulted in different morphology. However, the relationships between type of natural fibers, preparation methods and the morphology of produced nanocellulose could not be exactly defined. The sisal nanocellulose was presently prepared by alkalization and bleaching followed by sonication to verify changes in the morphology and crystallinity of nanocellulose related to the formation mechanism. The extracted microcellulose was subjected to scanning electron microscopy (SEM) and x-ray diffraction (XRD) analysis. The isolated cellulose nanospheres were examined with respect to morphology by SEM and transmission electron microscopy (TEM) and, to crystallinity by electron diffraction analysis. Bleaching after alkalization made the microfibrils clearly separated from each other to the individual fiber whose width of the single fiber was ranging from 6 to 13 µm. The XRD crystallinity index (CI) of microcellulose gradually increased after the chemical treatments; 83.12% for raw sisal fiber, 88.57% for alkali treated fiber and 94.03% for bleached fibers. The ultrasonic agitation after bleaching that was carried out at 750 Watt, 20 kHz and amplitude of 39% for 2 h produces homogeneous cellulose nanospheres less than 50 nm in diameter with relatively low crystallinity. The electron diffraction analysis confirmed that the low crystallinity of produced nnocellulose is related to the effect of chemical treatment done before sonication.

  4. Screening life cycle assessment study of a sisal fibre reinforced micro-concrete structural insulated panel

    CSIR Research Space (South Africa)

    Ampofo-Anti, N

    2013-12-01

    Full Text Available First international conference on composites, biocomposites and nanocomposites, DUT, Durban, South Africa, 2-4 December 2013 SCREENING LIFE CYCLE ASSESSMENT STUDY OFA SISAL FIBRE REINFORCED MICRO-CONCRETE STRUCTURAL INSULATED PANEL Naa Lamkai Ampofo...

  5. Assessment of the mechanical properties of sisal fiber-reinforced silty clay using triaxial shear tests.

    Science.gov (United States)

    Wu, Yankai; Li, Yanbin; Niu, Bin

    2014-01-01

    Fiber reinforcement is widely used in construction engineering to improve the mechanical properties of soil because it increases the soil's strength and improves the soil's mechanical properties. However, the mechanical properties of fiber-reinforced soils remain controversial. The present study investigated the mechanical properties of silty clay reinforced with discrete, randomly distributed sisal fibers using triaxial shear tests. The sisal fibers were cut to different lengths, randomly mixed with silty clay in varying percentages, and compacted to the maximum dry density at the optimum moisture content. The results indicate that with a fiber length of 10 mm and content of 1.0%, sisal fiber-reinforced silty clay is 20% stronger than nonreinforced silty clay. The fiber-reinforced silty clay exhibited crack fracture and surface shear fracture failure modes, implying that sisal fiber is a good earth reinforcement material with potential applications in civil engineering, dam foundation, roadbed engineering, and ground treatment.

  6. Viscoelastic and thermal properties of woven sisal fabric reinforced natural rubber biocomposites

    CSIR Research Space (South Africa)

    John, MJ

    2009-01-01

    Full Text Available This study explores the dynamic mechanical behavior of woven sisal fabric reinforced natural rubber composites. The influence of chemical modification on the viscoelastic properties has also been determined. Moreover, the effect of frequency...

  7. Efeito da omissão de macronutrientes em sisal Macronutrients deficiency on sisal (Agave sisalana perr.

    Directory of Open Access Journals (Sweden)

    Antonio Luiz de Barbos Salgado

    1982-01-01

    Full Text Available Plantas de sisal (Agave sisalana Perr. foram cultivadas em casa de vegetação, em vasos contendo areia lavada e irrigados com solução nutritiva completa e com soluções nutritivas com a omissão de cada macronutriente. As plantas mostraram, na ausência de cada nutriente, os sintomas típicos de sua carência, relacionados com baixos teores do respectivo elemento nas folhas, e redução no seu crescimento e desenvolvimento.Sisal plants were cultivated in washed sand during twenty-one months. The plants were irrigated with complete nutrient solution and solutions with absence of each macronutrient (N, P, K, Ca, Mg e S. The plants, in the absence of each macronutrient, showed typical symptoms which were related to the low level of the respective element in the leaf. The growing of the leaves was reduced by the absence of the macronutrients.

  8. Characterization and treatment of sisal fiber residues for cement-based composite application

    OpenAIRE

    Lima,Paulo R. L.; Santos,Rogério J.; Ferreira,Saulo R.; Toledo Filho,Romildo D.

    2014-01-01

    Sisal fiber is an important agricultural product used in the manufacture of ropes, rugs and also as a reinforcement of polymeric or cement-based composites. However, during the fiber production process a large amount of residues is generated which currently have a low potential for commercial use. The aim of this study is to characterize the agricultural residues by the production and improvement of sisal fiber, called field bush and refugo and verify the potentiality of their use in the rein...

  9. A multi-scale investigation of the mechanical behavior of durable sisal fiber cement composites

    OpenAIRE

    Silva, Flávio de Andrade; Toledo Filho, Romildo D.; Mobasher, Barzin; Chawla, Nikhilesh

    2010-01-01

    Durable sisal fiber cement composites reinforced with long unidirectional aligned fibers were developed and their mechanical behavior was characterized in a multi-scale level. Tensile tests were performed in individual sisal fibers. Weibull statistics were used to quantify the degree of variability in fiber strength at different gage lengths. The fiber-matrix pull-out behavior was evaluated at several curing ages and embedded lengths. The composite's mechanical response was measured under dir...

  10. Efficacy of Thermally Conditioned Sisal FRP Composite on the Shear Characteristics of Reinforced Concrete Beams

    OpenAIRE

    Sen, Tara; Reddy, H. N. Jagannatha

    2013-01-01

    The development of commercially viable composites based on natural resources for a wide range of applications is on the rise. Efforts include new methods of production and the utilization of natural reinforcements to make biodegradable composites with lignocellulosic fibers, for various engineering applications. In this work, thermal conditioning of woven sisal fibre was carried out, followed by the development of woven sisal fibre reinforced polymer composite system, and its tensile and flex...

  11. Poliolefinas reforçadas com fibras vegetais curtas: sisal × curauá Polyolefins reinforced with short vegetal fibers: sisal vs. curauá

    Directory of Open Access Journals (Sweden)

    Márcia A. S. Spinacé

    2011-01-01

    Full Text Available É crescente o interesse nos compósitos poliméricos reforçados com fibras vegetais curtas em substituição às fibras de vidro, pois as fibras naturais provêm de fontes renováveis, não são abrasivas aos equipamentos de processamento, são biodegradáveis, e possuem baixa densidade comparada às fibras de vidro. Elas apresentam início de degradação em torno de 200 °C, sendo adequadas para reforçar poliolefinas que são processadas até essa temperatura ou termofíxos. Várias fibras vegetais vêm sendo usadas como reforço, dentre elas o curauá e o sisal; no entanto, há grande controvérsia na literatura sobre as propriedades finais dos compósitos. Neste trabalho comparamos as propriedades de compósitos de polietileno de alta densidade ou polipropileno com 20% em massa de fibras curtas de sisal ou de curauá com ou sem agentes de acoplagem. Todos foram processados por extrusão e moldados por injeção, exatamente nas mesmas condições, e os resultados foram comparados em termos das propriedades mecânicas. As fibras de curauá apresentam resistência à tração superior às fibras de sisal e os compósitos com fibras de curauá apresentaram resistência à tração e flexão ligeiramente superior aos compósitos com fibra de sisal. No caso da resistência ao impacto a situação se inverte. Como o sisal é mais frágil que o curauá, durante o processamento ocorre maior quebra da fibra provocando essa diferenciação nas propriedades mecânicas dos compósitos.There is growing interest in reinforced polymer composites using short vegetal fibers to replace glass fibers for several reasons. The composite fibers are produced from renewable resources, being biodegradable and less abrasive to the processing equipment, in addition to possessing a lower density than the glass fibers. Since their thermal degradation onset is at 200 °C, they can be used to reinforce thermoplastics processed below this temperature and thermosets

  12. 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

  13. Gamma radiation effect on sisal / polyurethane composites without coupling agents

    Directory of Open Access Journals (Sweden)

    Marina Cardoso Vasco

    Full Text Available Abstract Natural fibers and polyurethane based composites may present chemical bonding between the components of the polymer and the lignin of the fiber. The incidence of radiation can cause degradation of the polymeric material and alter its mechanical properties. The objective of this study was to obtain and characterize cold pressed composites from polyurethane derived from castor oil and sisal fibers, without coupling agents, through thermogravimetric and mechanical tests, before and after the incidence of 25 kGy dose of gamma radiation. Woven composites that were not irradiated had maximum values of 4.40 GPa for flexural elastic modulus on three point flexural test and dispersed fiber composite that were not irradiated had maximum values of 2.25 GPa. These materials are adequate for use in non-structural applications in radiotherapy and radiodiagnostic rooms.

  14. Gamma radiation effect on sisal / polyurethane composites without coupling agents

    Energy Technology Data Exchange (ETDEWEB)

    Vasco, Marina Cardoso; Claro Neto, Salvador; Nascimento, Eduardo Mauro; Azevedo, Elaine, E-mail: marina.mcv@gmail.com [University of Patras (Greece); Universidade de Sao Paulo (USP) Sao Carlos, SP (Brazil); Universidade Tecnologica Federal do Parana (UTFPR), Curitiba, PR (Brazil)

    2017-04-15

    Natural fibers and polyurethane based composites may present chemical bonding between the components of the polymer and the lignin of the fiber. The incidence of radiation can cause degradation of the polymeric material and alter its mechanical properties. The objective of this study was to obtain and characterize cold pressed composites from polyurethane derived from castor oil and sisal fibers, without coupling agents, through thermogravimetric and mechanical tests, before and after the incidence of 25 kGy dose of gamma radiation. Woven composites that were not irradiated had maximum values of 4.40 GPa for flexural elastic modulus on three point flexural test and dispersed fiber composite that were not irradiated had maximum values of 2.25 GPa. These materials are adequate for use in non-structural applications in radiotherapy and radiodiagnostic rooms. (author)

  15. Improving degradation resistance of sisal fiber in concrete through fiber surface treatment

    Science.gov (United States)

    Wei, Jianqiang; Meyer, Christian

    2014-01-01

    As part of an ongoing effort to improve the sustainability of reinforced concrete, recycled concrete aggregate is being considered together with natural fibers such as sisal fiber as replacement of synthetic reinforcement. Since natural fibers are known to undergo potential deterioration in the alkaline cement matrix especially in outdoor erosive environment, they need to be treated to improve their durability. This paper describes two such methods (thermal and Na2CO3 treatment) and evaluates their effects on the degradation resistance of sisal fiber and durability of sisal fiber-reinforced concrete with recycled concrete aggregate. Concrete specimens were subjected to cycles of wetting and drying to accelerate aging. The microstructure, tensile strength and Young's modulus of sisal fiber as well as the weight loss of the composite were evaluated. Of primary interest were the effects on compressive and splitting tensile strength of sisal fiber-reinforced concrete. Thermal treatment and Na2CO3 surface treatment were shown to improve the durability of the composite as measured by splitting tensile strength by 36.5% and 46.2% and the compressive strength by 31.1% and 45.4%, respectively. The mechanisms of these two treatment methods were also analyzed. The thermal treatment achieved improvement of cellulose's crystallization, which ensured the initial strength and improved durability of sisal fiber. A layer consisting of calcium carbonate sediments, which protects the internals of a fiber from the strong alkali solution formed in the cement hydration process, was formed and filled in pits and cavities on the Na2CO3 treated sisal fiber's surface to improve their corrosion resistance and durability and reduced the detrimental effects of Na+ ions on concrete.

  16. Robotic intelligence kernel

    Science.gov (United States)

    Bruemmer, David J [Idaho Falls, ID

    2009-11-17

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

  17. Sistema radicular do fórmio, sisal e bambu imperial Root systems of new zealand flax, sisal, and imperial bamboo

    Directory of Open Access Journals (Sweden)

    Júlio César Medina

    1963-01-01

    Full Text Available Os autores apresentam e discutem os resultados de estudos preliminares sôbre o sistema radicular do fórmio (Phormium tenax Forster, sisal (Agave sisalana Perrine e bambu .imperial (Bambusa vulgaris Schrad. var. vittata A. ,& C, Riv.. Concluem, que o sistema radicular do fórmio é relativamente raso, o do sisal bastante superficial é o do bambu imperial se limitada às primeiras carnadas do solo.Results of preliminary studies on root-systems of New Zealand flax (Phormium tenax Forster, sisal (Agave sisalana Perrine, and imperial bamboo (Bambusa vulgaris Schrad. var. vittata A. & C. Riv. plants by the method of soil block, are apresented and discussed by the authors. According to local soil conditions, it is concluded that the root-system of New Zealand flax is relatively superficial, with the main concentration of roots in the 12 in. soil top layer. In sisal, the root-systems of the three plants investigated were found to occur in the soil surface layer, with more of 90% of the roots in the top 6 in. Finally, in the imperial bamboo clump atudied, the main concentration of roots was found in the layer 6-12 in. deep.

  18. Bio-composites fabricated by sandwiching sisal fibers with polypropylene (PP)

    International Nuclear Information System (INIS)

    Sosiati, H.; Nahyudin, A.; Fauzi, I.; Wijayanti, D. A.; Triyana, K.

    2016-01-01

    Sisal fibers reinforced polypropylene (PP) composites were successfully fabricated using sandwiching sisal fibers with PP sheets. The ratio of fiber and polymer matrix was 50:50 (wt. %). Untreated short and long sisal fibers, and alkali treated short sisal fibers in 6% NaOH at 100°C for 1 and 3 h were used as reinforcement or fillers. A small amount (3 wt. %) of maleic anhydride grafted polypropylene (MAPP) was added as a coupling agent. Scanning electron microscopy (SEM) and Fourier transform infrared (FTIR) spectroscopy were used to characterize the surface morphology and chemical composition of the fibers, respectively. Flexural test of sisal/PP composites was done according to ASTM D 790-02. The results showed that flexural strength of untreated long fiber reinforced composite is much higher than that of the untreated and alkali treated short fibers reinforced composites with and without the addition of MAPP. Alkalization related to fiber surface modification, fiber length/fiber orientation and a composite fabrication technique are important factors in contributing to the fiber distribution within the matrix, the bonding between the fiber and the matrix and the enhancement of flexural strength of the bio-composite.

  19. Bio-composites fabricated by sandwiching sisal fibers with polypropylene (PP)

    Science.gov (United States)

    Sosiati, H.; Nahyudin, A.; Fauzi, I.; Wijayanti, D. A.; Triyana, K.

    2016-04-01

    Sisal fibers reinforced polypropylene (PP) composites were successfully fabricated using sandwiching sisal fibers with PP sheets. The ratio of fiber and polymer matrix was 50:50 (wt. %). Untreated short and long sisal fibers, and alkali treated short sisal fibers in 6% NaOH at 100°C for 1 and 3 h were used as reinforcement or fillers. A small amount (3 wt. %) of maleic anhydride grafted polypropylene (MAPP) was added as a coupling agent. Scanning electron microscopy (SEM) and Fourier transform infrared (FTIR) spectroscopy were used to characterize the surface morphology and chemical composition of the fibers, respectively. Flexural test of sisal/PP composites was done according to ASTM D 790-02. The results showed that flexural strength of untreated long fiber reinforced composite is much higher than that of the untreated and alkali treated short fibers reinforced composites with and without the addition of MAPP. Alkalization related to fiber surface modification, fiber length/fiber orientation and a composite fabrication technique are important factors in contributing to the fiber distribution within the matrix, the bonding between the fiber and the matrix and the enhancement of flexural strength of the bio-composite.

  20. Bio-composites fabricated by sandwiching sisal fibers with polypropylene (PP)

    Energy Technology Data Exchange (ETDEWEB)

    Sosiati, H., E-mail: hsosiati@gmail.com [Nanomaterials Research Group, LPPT Universitas Gadjah Mada (Indonesia); Nahyudin, A., E-mail: ahmadnahyudin@yahoo.co.id; Fauzi, I., E-mail: ikhsannurfauzi@gmail.com; Wijayanti, D. A., E-mail: wijayantidwiastuti@gmail.com [Department of Physics, Faculty of Mathematics and Natural Sciences, Gadjah Mada University (Indonesia); Triyana, K., E-mail: triyana@ugm.ac.id [Nanomaterials Research Group, LPPT Universitas Gadjah Mada (Indonesia); Department of Physics, Faculty of Mathematics and Natural Sciences, Gadjah Mada University (Indonesia)

    2016-04-19

    Sisal fibers reinforced polypropylene (PP) composites were successfully fabricated using sandwiching sisal fibers with PP sheets. The ratio of fiber and polymer matrix was 50:50 (wt. %). Untreated short and long sisal fibers, and alkali treated short sisal fibers in 6% NaOH at 100°C for 1 and 3 h were used as reinforcement or fillers. A small amount (3 wt. %) of maleic anhydride grafted polypropylene (MAPP) was added as a coupling agent. Scanning electron microscopy (SEM) and Fourier transform infrared (FTIR) spectroscopy were used to characterize the surface morphology and chemical composition of the fibers, respectively. Flexural test of sisal/PP composites was done according to ASTM D 790-02. The results showed that flexural strength of untreated long fiber reinforced composite is much higher than that of the untreated and alkali treated short fibers reinforced composites with and without the addition of MAPP. Alkalization related to fiber surface modification, fiber length/fiber orientation and a composite fabrication technique are important factors in contributing to the fiber distribution within the matrix, the bonding between the fiber and the matrix and the enhancement of flexural strength of the bio-composite.

  1. Evaluation of Methane from Sisal Leaf Residue and Palash Leaf Litter

    Science.gov (United States)

    Arisutha, S.; Baredar, P.; Deshpande, D. M.; Suresh, S.

    2014-12-01

    The aim of this study is to evaluate methane production from sisal leaf residue and palash leaf litter mixed with different bulky materials such as vegetable market waste, hostel kitchen waste and digested biogas slurry in a laboratory scale anaerobic reactor. The mixture was prepared with 1:1 proportion. Maximum methane content of 320 ml/day was observed in the case of sisal leaf residue mixed with vegetable market waste as the feed. Methane content was minimum (47 ml/day), when palash leaf litter was used as feed. This was due to the increased content of lignin and polyphenol in the feedstock which were of complex structure and did not get degraded directly by microorganisms. Sisal leaf residue mixtures also showed highest content of volatile fatty acids (VFAs) as compared to palash leaf litter mixtures. It was observed that VFA concentration in the digester first increased, reached maximum (when pH was minimum) and then decreased.

  2. THE USE OF SISAL FIBRE AS REINFORCEMENT IN CEMENT BASED COMPOSITES

    Directory of Open Access Journals (Sweden)

    Romildo Dias Tolêdo Filho

    1999-08-01

    Full Text Available ABSTRACT The inclusion of fibre reinforcement in concrete, mortar and cement paste can enhance many of the engineering properties of the basic materials, such as fracture toughness, flexural strength and resistance to fatigue, impact, thermal shock and spalling. In recent years, a great deal of interest has been created worldwide on the potential applications of natural fibre reinforced, cement based composites. Investigations have been carried out in many countries on various mechanical properties, physical performance and durability of cement based matrices reinforced with naturally occurring fibres including sisal, coconut, jute, bamboo and wood fibres. These fibres have always been considered promising as reinforcement of cement based matrices because of their availability, low cost and low consumption of energy. In this review, the general properties of the composites are described in relation to fibre content, length, strength and stiffness. A chronological development of sisal fibre reinforced, cement based matrices is reported and experimental data are provided to illustrate the performance of sisal fibre reinforced cement composites. A brief description on the use of these composite materials as building products has been included. The influence of sisal fibres on the development of plastic shrinkage in the pre-hardened state, on tensile, compressive and bending strength in the hardened state of mortar mixes is discussed. Creep and drying shrinkage of the composites and the durability of natural fibres in cement based matrices are of particular interest and are also highlighted. The results show that the composites reinforced with sisal fibres are reliable materials to be used in practice for the production of structural elements to be used in rural and civil construction. This material could be a substitute asbestos-cement composite, which is a serious hazard to human and animal health and is prohibited in industrialized countries. The

  3. Striving for Diversity, Accessibility and Quality: Evaluating SiSAL Journal

    Directory of Open Access Journals (Sweden)

    Jo Mynard

    2014-06-01

    Full Text Available After establishing a journal, it is important to evaluate its progress to ensure that the principles that underpin its existence continue to be a priority. In this article, the author reports on measures that were used to evaluate Studies in Self-Access Learning (SiSAL Journal. The research was designed to investigate the three principles that the journal values: diversity, accessibility and quality. The results identified some successful factors such as accessibility and favourable perceptions of SiSAL Journal’s quality. However, the results also identified areas that could be improved to further increase diversity and to encourage submissions from more authors based in different locations.

  4. Herbicidas no transplante de mudas de sisal (Agave sisalana perr. Weed control and herbicide selectivity to sisal (Agave sisalana perr.

    Directory of Open Access Journals (Sweden)

    Antonio Luiz de Barros Salgado

    1980-01-01

    Full Text Available Com o objetivo de verificar a eficiência de hebraicas no controle de plantas daninhas e sua seletividade à cultura do sisal, foi instalado, em setembro de 1976, um experimento de campo em solo argiloso, com os seguintes tratamentos (i.a./hectare trifluralin a 0,84 e 0,96kg em pré-plantio com incorporação; alachlor a 2,40 e 3,26kg; metribuzin a 0,70 e 0,84kg; bromacil a 1,60 e 2,40kg; terbacil a 1,60 e 2,40kg; diuron a 2,40 e 3,20kg; simazine a 3,20 e 4,00kg; fluometuron a 1,20 e 1,60kg, todos em pré-emergência; uma testemunha carpida e outra sem capina. Foram feitas avaliações de controle do mato aos 67 e 114 dias e da condição da cultura aos 600 dias após a aplicação. Aos 114 dias, o controle de gramíneas foi acima de 90% pelo trifluralin, bromacil e terbacil, em torno de 80% pelo simazine, e inferior a 75% pelos demais; para dícotiledôneas, o controle foi de 90 a 100% pelo bromacil e terbacil, e de 80 a 85%o pelo simazine. Nenhum dos tratamentos afetou a cultura durante o período considerado, que foi de 600 dias. Aos 550 dias, fez-se avaliação da área coberta por reinfestação do mato, tendo o terbacil controlado ainda 75 e 95% do total, respectivamente, para as doses menor e maior; o trifluralin, 60 e 70% e, os demais, abaixo de 45%. Na avaliação final da cultura, aos 600 dias, foram considerados: população de plantas, número de plantas com perfilhos e condição da cultura. Os tratamentos que realizaram melhor controle do mato apresentaram também os melhores índices de desenvolvimento da cultura, atestando sua seletividade.The weed control with herbicides and its selectivity to sisal were studied on a clay soil field trial. The treatments (in a.i./ha were: 0.84 and 0.96kg of pre-plant incorporated trifluralin; 2.40 and 3.26kg of alachlor; 0.70 and 0.84kg of metribuzin; 1.60 and 2.40kg of bromacil; 1.60 and 2.40kg of terbacil; 2.40 and 3.20k- of diuron; 3.20 and 4.00kg of simazine; 1.20 and 1.60kg of fluometuron

  5. Study of the influence from chemical treatments of sisal fibers on the properties of composites with nitrile rubber

    OpenAIRE

    Iozzi, Marco A.; Martins, Gilson S.; Martins, Maria A.; Ferreira, Fábio C.; Job, Aldo E.; Mattoso, Luiz H. C.

    2010-01-01

    A influência de diferentes tratamentos das fibras de sisal nas propriedades dos compósitos de borracha nitrílica/fibras de sisal, e borracha nitrílica/carbonato de cálcio/fibras de sisal foi investigada. Os compósitos, com fibras curtas aleatoriamente distribuídas, foram processados em moinho de dois rolos e caracterizados através de ensaios mecânicos de resistência à tração, microscopia eletrônica de varredura (MEV), análise por termogravimetria (TG) e calorimetria exploratória diferencial (...

  6. 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...

  7. 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.

  8. Mechanical, Thermal Degradation, and Flammability Studies on Surface Modified Sisal Fiber Reinforced Recycled Polypropylene Composites

    Directory of Open Access Journals (Sweden)

    Arun Kumar Gupta

    2012-01-01

    Full Text Available The effect of surface treated sisal fiber on the mechanical, thermal, flammability, and morphological properties of sisal fiber (SF reinforced recycled polypropylene (RPP composites was investigated. The surface of sisal fiber was modified with different chemical reagent such as silane, glycidyl methacrylate (GMA, and O-hydroxybenzene diazonium chloride (OBDC to improve the compatibility with the matrix polymer. The experimental results revealed an improvement in the tensile strength to 11%, 20%, and 31.36% and impact strength to 78.72%, 77%, and 81% for silane, GMA, and OBDC treated sisal fiber reinforced recycled Polypropylene (RPP/SF composites, respectively, as compared to RPP. The thermogravimetric analysis (TGA, differential scanning calorimeter (DSC, and heat deflection temperature (HDT results revealed improved thermal stability as compared with RPP. The flammability behaviour of silane, GMA, and OBDC treated SF/RPP composites was studied by the horizontal burning rate by UL-94. The morphological analysis through scanning electron micrograph (SEM supports improves surface interaction between fiber surface and polymer matrix.

  9. Properties of SBS and sisal fiber composites: ecological material for shoe manufacturing

    Directory of Open Access Journals (Sweden)

    José Carlos Krause de Verney

    2008-12-01

    Full Text Available The worldwide trend toward using cheap, atoxic and durable materials from renewable resources contributes to sustainable development. Thus, the investigation of the potential use of vegetal fibers as reinforcing agent in polymeric composites has gained new significance. Sisal fiber has emerged as a reinforcing material for polymers used in automobile, footwear and civil industries. In this work, properties such as hardness, tensile strength and tear strength of polymer composites composed by block copolymer styrene-butadiene-styrene (SBS and 5, 10 and 20% by weight of sisal fiber were evaluated. The influence of conventional polymer processing techniques such as single-screw and double-screw extrusion, as well as the addition of coupling agent on the composite mechanical performance was investigated. Also, the morphology and thermal stability of the composites were analyzed. The addition of 2 wt. (% maleic anhydride as coupling agent between sisal fiber and SBS has improved the composite mechanical performance and the processing in a double-screw extruder has favored the sisal fiber distribution in the SBS matrix.

  10. The applications of sisal fibre-based materials in the built environment: opportunities for South Africa

    CSIR Research Space (South Africa)

    Dlungwana, Sihle

    2017-12-01

    Full Text Available of sisal fibre-based materials in the built environment: opportunities for South Africa Sihle Dlungwana, Joe Mapiravana, Naa Lamkai Ampofo-Anti and Nozonke Dumani Introduction: The building sector represented the largest uptake globally of natural fibre...

  11. Assessment of the Mechanical Properties of Sisal Fiber-Reinforced Silty Clay Using Triaxial Shear Tests

    Directory of Open Access Journals (Sweden)

    Yankai Wu

    2014-01-01

    Full Text Available Fiber reinforcement is widely used in construction engineering to improve the mechanical properties of soil because it increases the soil’s strength and improves the soil’s mechanical properties. However, the mechanical properties of fiber-reinforced soils remain controversial. The present study investigated the mechanical properties of silty clay reinforced with discrete, randomly distributed sisal fibers using triaxial shear tests. The sisal fibers were cut to different lengths, randomly mixed with silty clay in varying percentages, and compacted to the maximum dry density at the optimum moisture content. The results indicate that with a fiber length of 10 mm and content of 1.0%, sisal fiber-reinforced silty clay is 20% stronger than nonreinforced silty clay. The fiber-reinforced silty clay exhibited crack fracture and surface shear fracture failure modes, implying that sisal fiber is a good earth reinforcement material with potential applications in civil engineering, dam foundation, roadbed engineering, and ground treatment.

  12. Effect of Coconut, Sisal and Jute Fibers on the Properties of Starch/Gluten/Glycerol Matrix

    Science.gov (United States)

    Coconut, sisal and jute fibers were added as reinforcement materials in a biodegradable polymer matrix comprised of starch/gluten/glycerol. The content of fibers used in the composites varied from 5% to 30% by weight of the total polymers (starch and gluten). Materials were processed in a Haake torq...

  13. hybrid effect on the mechanical properties of sisal fiber and e-glass

    African Journals Online (AJOL)

    cles was added and the “mix” was vigorously stirred and poured into a mould. Appropriate quantities of fibers (sisal or E-glass) were im- pregnated in the “resin mix” which ultimately cured to give a solid laminate. 2.3. Tensile test. Standard tensile specimens were cut from the hybrid and non-hybrid composite lami-. Nigerian ...

  14. Fibra de sisal como envoltório na drenagem agrícola

    Directory of Open Access Journals (Sweden)

    Viviane F. Silva

    2014-06-01

    Full Text Available O trabalho foi realizado objetivando analisar o desempenho do sistema de drenagem com fibra de sisal envolto orgânico como material alternativo.  A pesquisa foi realizada no Laboratório de Engenharia de Irrigação e Drenagem da Universidade Federal de Campina Grande. Usando-se um sistema experimental composto de nove tanques construídos de alvenaria e impermeabilizados internamente. Os tratamentos foram dispostos em um arranjo fatorial com três tipos de tubos, Drenoflex, Kananet e tubo de PVC liso próprio para Esgoto envolto com fibra de sisal num delineamento inteiramente casualizado com três repetições. Foram avaliados a carga hidráulica de entrada (he, fluxo(q e resistência de entrada(re e analisados  estatisticamente, utilizando-se o software ASSISTAT . A comparação dos tubos Drenoflex, PVC liso e Kananet envolto com fibra de sisal, as médias da carga hidráulica na entrada para os tubos variando os valores de 0,40486 a 0,35543, sendo significativo para o tubo Kananet, devido possuir furos maiores facilitando assim a passagem da água pelo tubo. E em relação à resistência de entrada na interação entre os tubos drenantes e a fibra de sisal diferiu estatisticamente com o tubo PVC liso. O desempenho do sistema drenante com envolto de fibra de sisal é considerado muito bom.

  15. Effects of wood saw dust ash admixed with treated sisal fibre on the geotechnical properties of lateritic soil

    Directory of Open Access Journals (Sweden)

    John Engbonye SANI

    2017-12-01

    Full Text Available The preliminary investigation conducted on the lateritic soil collected at Shika, Zaria shows that it falls under A-7-6 (10 classification for AASHTO (1986 and CL according to unified soil classification system USCS (ASTM 1992. The soil was treated with both wood saw dust ash (WSDA and treated sisal fiber, in stepped concentration of 0,2,4,6, and 8% for WSDA and 0, 0.25, 0.5, 0.75 and 1% treated sisal fibre by dry weight of soil using Standard proctor. The Sisal Fibre was treated with Sodium Borohydride (NaBH4 (1% wt/vol for 60 minutes at room temperature to remove the cellulose content present in the Fibre. Statistical analysis was carried out on the obtained results using XLSTART 2017 software and analysis of variance with the Microsoft Excel Analysis Tool Pak Software Package. The liquid limit (LL of the soil was found to be 48% while the plastic limit(PL is 21.27%. The maximum dry density(MDDhowever, decreases generally from a value of 1.85 Mg/m3 to 1.68Mg/m3 at 0.25% sisal fiber content/0% WSDA. It has its least value of 1.57Mg/m3 at 1% sisal fiber and 8% WSDA. The OMC increased from 18 % of the natural soil to 23.7% at 0.75% sisal fiber / 6% WSDA content. There was a general increase in the value of UCS of the soil-sisal fibre mixture with WSDA content from 100 kN/m2 of the natural soil to 696 kN/m2 at 0.75 % sisal fibre content / 6% WSDA. The UCS value met the standard of 687-1373 kN/m2 requirements of sub base for adequate lime and cement stabilization, respectively (Ingas and Metcalf 1972.

  16. 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.

  17. 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...

  18. Propriedades de compósitos híbridos de borracha nitrílica, fibras de sisal e carbonato de cálcio Properties of nitrile rubber, sisal fiber and calcium carbonate hybrid composites

    Directory of Open Access Journals (Sweden)

    Marco A. Iozzi

    2004-06-01

    Full Text Available Neste trabalho, estudou-se a influência do teor de carbonato de cálcio nas propriedades mecânicas e térmicas da borracha nitrílica, e do comprimento das fibras de sisal nas propriedades mecânicas dos compósitos de borracha nitrílica/fibras de sisal, e borracha nitrílica/carbonato de cálcio/fibras de sisal. Os materiais foram caracterizados através de ensaios mecânicos de resistência à tração, microscopia eletrônica de varredura (MEV, e termogravimetria (TG. O melhor desempenho mecânico dos compósitos com as fibras curtas aleatoriamente distribuídas foi obtido para o comprimento das fibras de 6 mm, e teor de carbonato de 67 pcr. A análise térmica mostrou que os compósitos são estáveis até cerca de 300 °C. Os resultados mostraram que os materiais obtidos possuem uma boa relação custo/benefício tornando promissora sua utilização.In this work, nitrile rubber with sisal fibers composites and nitrile rubber with calcium carbonate and sisal fibers composites were developed. The influence from the calcium carbonate amount and size of sisal fibers on the composite properties was studied. The composites, with short fibers randomly distributed, were characterized by mechanical analysis, scanning electron microscopy (SEM, and thermogravimetric analysis (TGA. The optimal size of sisal fibers to reinforce the nitrile matrix was 6 mm. The ideal volume of calcium carbonate was 67 phr. TGA analysis demonstrated that the composites are stable up to 300 °C. The materials developed have a good cost/benefits relation, being therefore promising their utilization.

  19. 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`.

  20. Mechanical and water absorption behaviour of banana/sisal reinforced hybrid composites

    International Nuclear Information System (INIS)

    Venkateshwaran, N.; ElayaPerumal, A.; Alavudeen, A.; Thiruchitrambalam, M.

    2011-01-01

    Highlights: → It explores the utilization of waste banana fiber. → Improving the mechanical property by hybridization. → Results show its usefulness to low cost application. -- Abstract: The tensile, flexural, impact and water absorption tests were carried out using banana/epoxy composite material. Initially, optimum fiber length and weight percentage were determined. To improve the mechanical properties, banana fiber was hybridised with sisal fiber. This study showed that addition of sisal fiber in banana/epoxy composites of up to 50% by weight results in increasing the mechanical properties and decreasing the moisture absorption property. Morphological analysis was carried out to observe fracture behaviour and fiber pull-out of the samples using scanning electron microscope.

  1. Cellulose whiskers from sisal fibers: a study about the variable of extraction by acid hydrolysis

    International Nuclear Information System (INIS)

    Teodoro, Kelcilene B.R.; Teixeira, Eliangela de Morais; Correa, Ana Carolina; Campos, Adriana de; Marconcini, Jose Manoel; Mattoso, Luiz Henrique Capparelli

    2011-01-01

    The incorporation of cellulosic nanostructures in polymeric matrices has been studied due to their properties of biodegradation, and expected higher mechanical performance than the traditional composites. In this work, cellulose nanofibers were obtained from sisal bleached with reagents without chlorine, where it was used an acid mixture, with acetic acid and nitric acid, and after the bleached fibers were submitted to acid hydrolysis. The influence of the temperature and time of hydrolysis on the morphology and dimensions, crystallinity and thermal stability were analyzed by scanning transmission electronic microscopy (TEM), x-ray diffraction (XRD) and thermogravimetric analysis (TGA), respectively. The hydrolysis condition of 60 deg C and 15 minutes showed to be the most effective condition to obtain whiskers from sisal fibers, resulting in nanostructures with higher crystallinity and thermal. (author)

  2. Sisal, caso paradigmático de estudio: Prácticas de vida y basura

    OpenAIRE

    Ulsía Urrea Mariño

    2016-01-01

    Estudio del puerto de Sisal, Yucatán, México, sobre las prácticas de vida cotidiana ligadas a la basura, residuos y desechos en tres espacios de análisis (casa, vecindario y lugares de trabajo) y su relación con la economía subterránea, construcción de vivienda y pesca.

  3. Thermal performance of sisal fiber-cement roofing tiles for rural constructions

    OpenAIRE

    Tonoli,Gustavo Henrique Denzin; Santos,Sérgio Francisco dos; Rabi,José Antonio; Santos,Wilson Nunes dos; Savastano Junior,Holmer

    2011-01-01

    Roofing provides the main protection against direct solar radiation in animal housing. Appropriate thermal properties of roofing materials tend to improve the thermal comfort in the inner ambient. Nonasbestos fiber-cement roofing components reinforced with cellulose pulp from sisal (Agave sisalana) were produced by slurry and dewatering techniques, with an optional addition of polypropylene fibers. Nonasbestos tiles were evaluated and compared with commercially available asbestos-cement sheet...

  4. Sisal, caso paradigmático de estudio: Prácticas de vida y basura

    Directory of Open Access Journals (Sweden)

    Ulsía Urrea Mariño

    2016-06-01

    Full Text Available Estudio del puerto de Sisal, Yucatán, México, sobre las prácticas de vida cotidiana ligadas a la basura, residuos y desechos en tres espacios de análisis (casa, vecindario y lugares de trabajo y su relación con la economía subterránea, construcción de vivienda y pesca.

  5. Interface Bond Improvement of Sisal Fibre Reinforced Polylactide Composites with Added Epoxy Oligomer.

    Science.gov (United States)

    Hao, Mingyang; Wu, Hongwu; Qiu, Feng; Wang, Xiwen

    2018-03-07

    To improve the interfacial bonding of sisal fiber-reinforced polylactide biocomposites, polylactide (PLA) and sisal fibers (SF) were melt-blended to fabricate bio-based composites via in situ reactive interfacial compatibilization with addition of a commercial grade epoxy-functionalized oligomer Joncryl ADR @ -4368 (ADR). The FTIR (Fourier Transform infrared spectroscopy) analysis and SEM (scanning electron microscope) characterization demonstrated that the PLA molecular chain was bonded to the fiber surface and the epoxy-functionalized oligomer played a hinge-like role between the sisal fibers and the PLA matrix, which resulted in improved interfacial adhesion between the fibers and the PLA matrix. The interfacial reaction and microstructures of composites were further investigated by thermal and rheological analyses, which indicated that the mobility of the PLA molecular chain in composites was restricted because of the introduction of the ADR oligomer, which in turn reflected the improved interfacial interaction between SF and the PLA matrix. These results were further justified with the calculation of activation energies of glass transition relaxation (∆ E a ) by dynamic mechanical analysis. The mechanical properties of PLA/SF composites were simultaneously reinforced and toughened with the addition of ADR oligomer. The interfacial interaction and structure-properties relationship of the composites are the key points of this study.

  6. Impact of Surface Modification and Nanoparticle on Sisal Fiber Reinforced Polypropylene Nano composites

    International Nuclear Information System (INIS)

    Ibrahim, I. D.; Jamiru, T.; Sadiku, E. R.; Agwuncha, S. Ch.; Kupolati, W. K.

    2016-01-01

    The use of plant fibers, polymer, and nanoparticles for composite has gained global attention, especially in the packaging, automobile, aviation, building, and construction industries. Nano composites materials are currently in use as a replacement for traditional materials due to their superior properties, such as high strength-to-weight ratio, cost effectiveness, and environmental friendliness. Sisal fiber (SF) was treated with 5% NaOH for 2 hours at 70"°C. A mixed blend of sisal fiber and recycled polypropylene (rPP) was produced at four different fiber loadings: 10, 20, 30, and 40 wt.%, while nano clay was added at 1, 3, and 5 wt.%. Maleic anhydride grafted polypropylene (MAPP) was used as the compatibilizer for all composites prepared except the untreated sisal fibers. The characterization results showed that the fiber treatment, addition of MAPP, and nano clay improved the mechanical properties and thermal stability and reduced water absorption of the SF/rPP nano composites. The tensile strength, tensile modulus, and impact strength increased by 32.80, 37.62, and 5.48%, respectively, when compared to the untreated SF/rPP composites. Water absorption was reduced due to the treatment of fiber and the incorporation of MAPP and nano clay.

  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. 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

  9. 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

  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. 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

  12. Propriedades mecânicas de tração de compósitos poliéster/tecidos híbridos sisal/vidro Properties of polyester/hibrid sisal-glass fabrics

    Directory of Open Access Journals (Sweden)

    Laura H. de Carvalho

    2006-03-01

    Full Text Available O desempenho e o custo de compósitos podem ser alterados por hibridização e, neste sentido, é relativamente comum o uso combinado de fibras e reforços minerais no desenvolvimento destes materiais. No presente trabalho o desempenho mecânico de compósitos poliéster insaturado/ tecidos híbridos sisal-vidro foram investigados em função do teor de fibra e direção do teste. Foram confeccionados três tecidos híbridos (com 30, 40 e 50% em peso de vidro com fios de sisal no urdume e fibras de vidro na trama. Os compósitos foram moldados por compressão à temperatura ambiente com os tecidos alinhados. Os resultados indicam que houve um aumento nas propriedades mecânicas de tração de todos os compósitos com o aumento do teor de fibras. Para os compósitos reforçados por tecidos com baixo teor de fibra de vidro, as propriedades tenderam a ser mais elevadas quando os testes foram conduzidos na direção do sisal, enquanto que para os tecidos com elevado teor de vidro, o oposto foi observado. Estes comportamentos foram associados ao teor de fibra de vidro na direção do teste e ao diâmetro das fibras de sisal. Em baixos teores de fibra o sisal agiria como inclusão ou defeito, prejudicando as propriedades mecânicas; em elevados teores as propriedades do vidro suplantariam os defeitos provocados pelo sisal.Hybridization can alter both mechanical performance and cost of polymer composites, and novel composite materials can be obtained by the combination of both fibrous and mineral reinforcements. In the present work the mechanical performance of unsaturated polyester/hybrid sisal-glass fabrics was determined as a function of fibre content and test direction. Three different hybrid fabrics (30, 40 and 50% w/w glass content with sisal strings in the warp and glass roving in the weft were hand weaved. Aligned fabric compression moulded composites were obtained at room temperature. The results showed enhanced properties with fibre content

  13. Estudo dos efeitos da acetilação em fibras de sisal Study of the effects of acetylation treatments on sisal fiber

    Directory of Open Access Journals (Sweden)

    Fernanda F. M. Lopes

    2010-07-01

    Full Text Available O emprego de fibras vegetais na confecção de compósitos tem grande viabilidade, no que diz respeito ao uso de materiais oriundos de fontes renováveis, à biodegradabilidade e aos benefícios socioeconômicos gerados na produção de matéria-prima vegetal. As fibras de sisal são altamente higroscópicas e esta característica se apresenta como um dos principais problemas na produção de compósitos induzindo a variações dimensionais sob a influência da umidade, deposição dos produtos da matriz em seus poros e a degradação. Os tratamentos de acetilação nas fibras de sisal foram aplicados em diferentes temperaturas e tempos reacionais, e a eficiência desses tratamentos, considerando-se a redução da hidrofilicidade e a manutenção do desempenho mecânico das fibras, foi avaliada pela capacidade de absorção de água por imersão, ensaios de resistência mecânica e por espectroscopia de infravermelho. Fibras acetiladas apresentaram reduções de peso por absorção de até 50% quando comparadas com as não tratadas. Os tratamentos por 3 h apresentaram as maiores perdas na resistência mecânica e a 120 °C por 1h indicaram as melhores características físico-mecânicas, além de incremento satisfatório de grupos apolares com o tratamento.The use of vegetable fibers in composites is highly viable regarding about the use of materials from renewable sources, the biodegradability and the socioeconomic advantages in the production of raw vegetable. The sisal fibers are highly hygroscopic and this is a main problem in the production of composites, inducing dimensional changes under moisture influence, deposition of the matrix products and degradation. The treatment of the acetylation was applied at different temperatures and reaction times, and the efficiency of treatments, considering the reduction of the hydrophilicity and maintenance of the mechanical properties, was evaluated by water sorption, mechanical properties and the

  14. Infiltração de sal de alumínio em fibras de sisal para obtenção de fibras de alumina Infiltration of aluminum salt into sisal to produce alumina fibers

    Directory of Open Access Journals (Sweden)

    T. E. Andrade Jr.

    2005-03-01

    Full Text Available O sisal é um recurso estratégico para a região Nordeste e, particularmente, para o estado do Rio Grande do Norte, por ser uma cultura renovável e adaptada às condições do semi-árido. Em virtude das condições adversas de clima e solo, o sisal é, em algumas regiões, o único produto agrícola rentável passível de plantio. Agregar valor aos produtos manufaturados a partir do sisal contribui não só para o desenvolvimento científico e tecnológico da região, como também para a geração de renda para a população dos municípios potiguares produtores de sisal. Da planta extraem-se fibras ligninocelulósicas utilizadas na produção artesanal de cordas e industrial de mantas e tapetes. Uma outra alternativa é o aproveitamento da estrutura da fibra para a produção de fibras de alumina (Al2O3 pela biomodelagem. Este processo consiste na reprodução da estruturas natural do material de partida. O objetivo deste trabalho foi estudar as condições de infiltração da fibra de sisal com sal de alumínio para posterior conversão da estrutura em fibras de alumina. Inicialmente, as fibras de sisal foram pré-tratadas com hidróxido de sódio, infiltradas com uma solução saturada de sal de alumínio (Al2Cl6 e sinterizadas entre 1400 °C e 1650 °C. A caracterização das fibras de alumina foi feita por difração de raios X e microscopia eletrônica de varredura. Os resultados mostraram a conversão completa apenas da superfície da fibra de sisal em alfa-Al2O3, resultando em baixa resistência ao manuseio. Novos métodos de infiltração são propostos com o objetivo de reproduzir-se a estrutura interna da fibra de sisal, resultando em fibras materiais com melhor resistência mecânica.Sisal is a renewable agricultural resource adapted to the hostile climatic and soil conditions particularly encountered in the semi-arid areas of the state of Rio Grande do Norte, located in Northeastern Brazil. Consequently, sisal has played a

  15. DESINFESTAÇÃO DE REBENTOS DE SISAL PARA UTILIZAÇÃO IN VITRO

    Directory of Open Access Journals (Sweden)

    Flavia Monique Sales Nobrega

    2015-08-01

    Full Text Available Em todo o mundo, o sisal (Agave sisalana é conhecido pelo alto teor de suas fibras, amplamente utilizadas na fabricação de utensílios, na indústria automotiva, na indústria química e na construção cívil. No entanto, alguns fatores podem inviabilizar o desenvolvimento da cultura, a exemplo de doenças, como a podridão do colo, causada por fungos do gênero Pythium sp. Visando à obtenção de mudas sadias e livres de patógenos buscou-se, com este trabalho, definir um protocolo eficiente para a desinfestação de rebentos de sisal, utilizando-se diferentes concentrações e diversas combinações do antibiótico Citrofloxacino e do Fungicida Baytan®. Os explantes foram desinfestados em soluções com detergente neutro, hipoclorito de sódio e formaldeído e, em seguida, submetidos a soluções com diferentes concentrações do antibiótico e do fungicida combinados e só então cultivados em meio MS. Foram realizadas avaliações aos 7, 15 e 21 dias, após o cultivo, para análise da taxa de contaminação bacteriana e fúngica. Observou-se, portanto, que a utilização de 0,5% do fungicida Baytan®, associado a 1% do antibiótico Citrofloxacino, foi mais eficiente na descontaminação de explantes de sisal.

  16. Consumo e desempenho produtivo de ovinos alimentados com dietas que continham coprodutos do desfibramento do sisal

    Directory of Open Access Journals (Sweden)

    R.D. Santos

    2011-12-01

    Full Text Available Avaliaram-se o desempenho produtivo e o consumo de nutrientes e frações fibrosas em ovinos alimentados com dietas contendo coprodutos do desfibramento do sisal, Agave sisalana. Foram utilizados 24 ovinos, machos, alojados em baias individuais. O delineamento experimental utilizado foi o inteiramente ao acaso, com quatro tratamentos e seis repetições. Os tratamentos consistiram em quatro dietas isoproteicas, em que: i dieta padrão, contendo 38% de volumoso (silagem de milheto e 62% de concentrado (milho, farelo de soja e ureia; ii inclusão de 20% da silagem de mucilagem do sisal em substituição à silagem de milheto; iii inclusão de 20% da silagem de mucilagem associada ao pó da batedeira como aditivo em substituição à silagem de milheto; iv inclusão de 20% do feno da mucilagem em substituição à silagem de milheto. O peso corporal final, os ganhos médio diário e total e a conversão alimentar dos ovinos não foram influenciados pelas dietas avaliadas (P>0,05. Os consumos dos nutrientes, em g/dia e em %PC e g/kg0,75, não sofreram influência das dietas. Os resultados indicam que as dietas à base de coprodutos do sisal podem ser utilizadas como alternativa volumosa, além de possibilitar o aumento da rentabilidade da atividade na região semiárida brasileira.

  17. A necrose da base da fôlha do sisal

    Directory of Open Access Journals (Sweden)

    J. C. Medina

    1943-04-01

    Full Text Available Sisal (Agave sisalana Perrine growing in various localities of the State of São Paulo is often heavely damaged by "leaf basal necrose", whose symptoms are identical with the "leaf foot disease" reported from Java, East Africa and Belgian Congo. The affected leaves show in the initial stages small spots of black, slightly shrivelled tissue on the lower part of the leaf. These gradually spread out. During the later stages the affected leaves bent over at this point. Only approximately mature leaves of plants between 18 to 30 months old are affected. This disturbance was first observed in Anapolis, Araraquara and Campinas. It was thought to be due to K deficiency in the soil. In order to prove this a small fertilizer experiment was established at Campinas mainly to study the effect of potassium sulfate as a control measure for this "disease". The experiment also included calcium carbonate and control plots, each treatment being replicated three times. The results demonstrated that the trouble can be easily controled by the use ot potassium sulfate applied in the first year of cultivation (two years after planting in the nursery. At all plots not treated with K the typical black spots appeared on the leaves about one year after planting. Considerable damage was caused by this physiological disturbance in all these plots, up to 86,6% of the plants and 15,4% of all leaves being damaged at the three control plots 18 months after planting. The "leaf basal necrose" is until now the single prevalent and destructive "disease" of sisal in the State of São Paulo, where the plant is generally cultivated on K deficient soils. This explains its occurrence in almost all plantations. To avoid this disturbance sisal should be cultivated on rich soils and fertilised with K sulfate if grown on poor ones.

  18. Evaluation gamma radiation in composite sisal fiber- polyurethane derived of castor oil by bending test

    International Nuclear Information System (INIS)

    Souza, Felipe H. de; Geraldo, Ricardo R.; Vasco, Marina C.; Azevedo, Elaine; Claro Neto, Salvador

    2015-01-01

    Materials used for making furniture and accessories or positioning in X -ray examination rooms should not exhale volatile organic compounds and are resistant to ionizing radiation. One solution is the use of vegetable fiber and polyurethane composites of vegetable origin, since they are biodegradable, derived from renewable raw materials and have no volatile organic compounds. The main difficulty in developing this material is fiber adhesion with the polymer. The objective of this study is to evaluate the mechanical properties of composite sisal fiber composite, without further treatment, and polyurethane derived from castor oil, with a dose of 25 kGy gamma radiation, subjected to 3 points bending tests. (author)

  19. 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...

  20. 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...

  1. 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...

  2. Efeito do tratamento das fibras nas propriedades do biocompósito de amido termoplástico/policaprolactona/sisal Effect of fiber treatments on properties of thermoplastic starch/polycaprolactone/sisal biocomposites

    Directory of Open Access Journals (Sweden)

    Adriana de Campos

    2011-01-01

    Full Text Available Fibras de sisal com quatro tratamentos, a saber: fibra lavada com água, lavada com cicloexano/etanol, tratamento alcalino (NaOH e tratamento com peróxido alcalino (branqueamento, foram incorporadas na blenda amido termoplástico/policaprolactona 80/20 (TPS/PCL. As propriedades morfológicas, mecânicas e térmicas dos biocompósitos TPS/PCL/Sisal foram analisadas. Os compósitos com a fibra branqueada apresentaram os melhores resultados de resistência à tração e estabilidade térmica. Verificou-se também melhora da adesão fibra-matriz no compósito com a fibra branqueada, com aumento de 145% na resistência à tração.Sisal fibers treated with four methods, namely washing with water, washing with cyclohexane/ethanol, alkali treatment (NaOH and bleaching (alkaline peroxide treatment, were incorporated in thermoplastic starch/polycaprolactone 80/20 (TPS/PCL samples. Morphological, mechanical and thermal properties of TPS/PCL/Sisal biocomposites were analysed. The best results were obtained with the composite using the bleached fiber, which had improved tensile strength and thermal stability. An increased adhesion between the fiber and matrix was also observed with the bleached fiber, with 145% increase in the tensile strength

  3. 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...

  4. 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...

  5. 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...

  6. 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.

  7. 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...

  8. Acid hydrolysis of sisal cellulose: studies aiming at nano fibers and bio ethanol preparation

    International Nuclear Information System (INIS)

    Paula, Mauricio P. de; Lacerda, Talita M.; Zambon, Marcia D.; Frollini, Elisabete

    2009-01-01

    The hydrolysis of cellulose can result in nanofibers and also is an important stage in the bioethanol production process. In order to evaluate the influence of acid (sulfuric) concentration, temperature, and native cellulose (sisal) pretreatment on cellulose hydrolysis, the acid concentration was varied between 5% and 30% (v/v) in the temperature range from 60 to 100 deg C using native and alkali-treated (mercerized) sisal cellulose. The following techniques were used to evaluate the residual (non-hydrolysed) cellulose characteristics: viscometry, average degree of polymerization (DP), X-ray diffraction, crystallinity index, and Scanning Electron Microscopy. The sugar cane liquor was analyzed in terms of sugar composition, using High Performance Liquid Chromatography (HPLC). The results showed that increasing the concentration of sulfuric acid and temperature afforded residual cellulose with lower molecular weight and, up to specific acid concentrations, higher crystallinity indexes, when compared to the original cellulose values, and increased the glucose (the bioethanol precursor ) production of the liquor, which was favored for mercerized cellulose. (author)

  9. A severidade de corte no sisal e analise tecnológica da fibra

    Directory of Open Access Journals (Sweden)

    J. C. Medina

    1947-01-01

    Full Text Available In this paper it is presented a detailed fiber analysis of leaves of twenty mature sisal plants taken from four positions on the plant: 1 first developped leaves (75°; 2 leaves usually cut for fiber extraction (50° ; 3 leaves adjacent to the central bud (25° ; and 4 young leaves not yet unfolded from the central bud (0°. The results herein reported are against the prevailing opinion that the sisal leaf only matures after it has unfolded from the central bud. Neither the physical nor the chemical fiber characteristics were adversely affected even if cutting was carried out up to the very young leaves. This practice, however, cannot yet be advised, as it desirability also depends on the effects of the severe cutting upon the subsequent rate of growth of the new leaves. A cutting trial including the cut of all leaves every four months is still in progress. Preliminary results have shown that the plants of this treatment were able to develop eight leaves until the second cut, with an average fiber content of 3,7%.

  10. Enzymatic grafting of simple phenols on flax and sisal pulp fibres using laccases.

    Science.gov (United States)

    Aracri, Elisabetta; Fillat, Amanda; Colom, José F; Gutiérrez, Ana; Del Río, José C; Martínez, Angel T; Vidal, Teresa

    2010-11-01

    Flax and sisal pulps were treated with two laccases (from Pycnoporus cinnabarinus, PcL and Trametes villosa, TvL, respectively), in the presence of different phenolic compounds (syringaldehyde, acetosyringone and p-coumaric acid in the case of flax pulp, and coniferaldehyde, sinapaldehyde, ferulic acid and sinapic acid in the case of sisal pulp). In most cases the enzymatic treatments resulted in increased kappa number of pulps suggesting the incorporation of the phenols into fibres. The covalent binding of these compounds to fibres was evidenced by the analysis of the treated pulps, after acetone extraction, by pyrolysis coupled with gas chromatography/mass spectrometry in the absence and/or in the presence of tetramethylammonium hydroxide (TMAH) as methylating agent. The highest extents of phenol incorporation were observed with the p-hydroxycinnamic acids, p-coumaric and ferulic acids. The present work shows for the first time the use of analytical pyrolysis as an effective approach to study fibre functionalization by laccase-induced grafting of phenols. Copyright 2010 Elsevier Ltd. All rights reserved.

  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. Variable Kernel Density Estimation

    OpenAIRE

    Terrell, George R.; Scott, David W.

    1992-01-01

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

  13. 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

  14. Thermal performance of sisal fiber-cement roofing tiles for rural constructions Desempenho térmico de telhas de fibrocimento reforçadas com polpa de sisal para construções rurais

    Directory of Open Access Journals (Sweden)

    Gustavo Henrique Denzin Tonoli

    2011-02-01

    Full Text Available Roofing provides the main protection against direct solar radiation in animal housing. Appropriate thermal properties of roofing materials tend to improve the thermal comfort in the inner ambient. Nonasbestos fiber-cement roofing components reinforced with cellulose pulp from sisal (Agave sisalana were produced by slurry and dewatering techniques, with an optional addition of polypropylene fibers. Nonasbestos tiles were evaluated and compared with commercially available asbestos-cement sheets and ceramic tiles (frequently chosen as roofing materials for animal housing. Thermal conductivity and thermal diffusivity of tiles were determined by the parallel hot-wire method, along with the evaluation of the downside surface temperature. Cement-based components reinforced with sisal pulp presented better thermal performance at room temperature (25ºC, while those reinforced with sisal pulp added by polypropylene fibers presented better thermal performance at 60ºC. Non-asbestos cement tiles provided more efficient protection against radiation than asbestos corrugated sheets.O telhado fornece a principal proteção contra a radiação solar direta em galpões para animais. Propriedades térmicas apropriadas dos materiais contribuem para o melhor conforto térmico no interior das construções. Telhas sem amianto reforçadas com polpa de celulose de sisal (Agave sisalana e com adição opcional de fibras de polipropileno foram produzidas pela técnica de mistura e sucção do excesso de água. Telhas corrugadas de cimento amianto, telhas cerâmicas e telhas à base de cimento reforçadas com polpa de celulose (com ou sem adição de fibras sintéticas foram comparadas quanto às suas propriedades térmicas. A condutividade térmica e a difusividade térmica foram determinadas pelo método do fio quente paralelo, assim como a temperatura da superfície inferior das telhas foi avaliada em diferentes períodos. Telhas de cimento reforçados com polpa de

  15. 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

  16. UTILIZATION OF MICRO SISAL FIBERS AS REINFORCEMENT AGENT AND POLYPROPYLENE OR POLYLACTIC ACID AS POLYMER MATRICES IN BIOCOMPOSITES MANUFACTURE

    Directory of Open Access Journals (Sweden)

    Subyakto Subyakto

    2013-06-01

    Full Text Available Sisal (Agave sisalana as a perennial tropical plant grows abundantly in Indonesia. Its fibers can be used as the reinforcement agent of biocomposite products. Utilization of sisal as natural fiber has some notable benefits compared to synthetic fibers, such as renewable, light in weight, and low in cost. Manufacture of biocomposite requires the use of matrix such as thermoplastic polymer, e.g. polypropylene (PP and polylactic acid (PLA to bond together with the reinforcement agent (e.g. sisal fibers. In relevant, experiment was conducted on biocomposites manufacture that comprised sisal fibers and PP as well as PLA. Sisal fibers were converted into pulp, then refined to micro-size fibrillated fibers such that their diameter reduced to about 10 μm, and dried in an oven. The dry microfibrillated sisal pulp fibers cellulose (MSFC were thoroughly mixed with either PP or PLA with varying ratios of MSFC/PP as well as MSFC/PLA, and then shaped into the mat (i.e. MSFC-PP and MSFC-PLA biocomposites. Two kinds of shaping was employed, i.e. hot-press molding and injection molding. In the hot-press molding, the ratio of  MSFC/PP as well as MSFC/PLA ranged about 30/70-50/50. Meanwhile in the injection (employed only on assembling the MSFC-PLA biocomposite, the ratio of MSFC/PLA varied about 10/90-30/70. The resulting shaped MSFC-PP and MSFC-PLA biocomposites were then tested of its physical and mechanical properties. With the hot-press molding device, the physical and mechanical (strength properties of MSFC-PLA biocomposite were higher than those of  MSFC-PP biocomposite. The optimum ratio of  MSFC/PP as well as MSFC/PLA reached concurrently at 40/60. The strengths of MSFC-PP as well as MSFC-PLA biocomposites were greater than those of individual polymer (PP and PLA. With the injection molding device, only the MSFC-PLA  biocomposite  was formed  and its strengths  reached  maximum  at 30/70  ratio.  The particular strengths (MOR and MOE of MSFC

  17. Mechanical and thermal properties of sisal fiber-reinforced rubber seed oil-based polyurethane composites

    International Nuclear Information System (INIS)

    Bakare, I.O.; Okieimen, F.E.; Pavithran, C.; Abdul Khalil, H.P.S.; Brahmakumar, M.

    2010-01-01

    The development of high-performance composite materials from locally sourced and renewable materials was investigated. Rubber seed oil polyurethane resin synthesized using rubber seed monoglyceride derived from glycerolysis of the oil was used as matrix in the composite samples. Rubber seed oil-based polyurethane composite reinforced with unidirectional sisal fibers were prepared and characterized. Results showed that the properties of unidirectional fiber-reinforced rubber seed oil-based polyurethane composites gave good thermal and mechanical properties. Also, the values of tensile strengths and flexural moduli of the polyurethane composites were more than tenfold and about twofold higher than un-reinforced rubber seed oil-based polyurethane. The improved thermal stability and the scanning electron micrographs of the fracture surface of the composites were attributed to good fiber-matrix interaction. These results indicate that high-performance 'all natural products' composite materials can be developed from resources that are readily available locally.

  18. Uso de fibra natural de sisal em blocos de concreto para alvenaria estrutural

    OpenAIRE

    Indara Soto Izquierdo

    2011-01-01

    A utilização de fibras vegetais como reforço constitui um grande interesse na obtenção de novos materiais para a construção civil produto de seu baixo custo, alta disponibilidade e reduzido consumo de energia para sua produção. Este trabalho avalia a incorporação de fibras de sisal, de comprimento 20 e 40 mm, e fração volumétrica de 0,5 e 1%, em concretos para a alvenaria de blocos estruturais e determina o uso destas unidades na execução de prismas e mini-paredes. Foram realizados os testes ...

  19. Evaluation of ionic liquid treated sisal (agave sisalana) fiber as sorbent in biodiesel spill

    Science.gov (United States)

    Costa, E.; Silva, A.; Mattedi, S.

    2018-04-01

    The global economic development continually demands the use of energy resources, among which various types of oils are widely used. Despite their undeniable economic importance, environmental accidents with these occur frequently. Thus, the search for efficient and low-cost mitigating measures is recurrent. In this context, techniques that use natural adsorbents, such as vegetable fibers, have been studied, since they combine efficiency, selectivity, low cost and sustainability. Studies have been carried out using various types of fibers, natural or chemically treated. The interest in treating the fiber lies in the fact that, changing the chemical structure of the fiber, its oil sorption capacity is increased. Due to the offered advantages, an alternative and promising type of surface treatment using ionic liquids was performed, to the detriment of traditional treatments. Thus, the technical feasibility of the use of sisal fiber treated with ionic liquid for adsorption of biodiesel was studied.

  20. Measurement and analysis of thrust force in drilling sisal-glass fiber reinforced polymer composites

    Science.gov (United States)

    Ramesh, M.; Gopinath, A.

    2017-05-01

    Drilling of composite materials is difficult when compared to the conventional materials because of its in-homogeneous nature. The force developed during drilling play a major role in the surface quality of the hole and minimizing the damages around the surface. This paper focuses the effect of drilling parameters on thrust force in drilling of sisal-glass fiber reinforced polymer composite laminates. The quadratic response models are developed by using response surface methodology (RSM) to predict the influence of cutting parameters on thrust force. The adequacy of the models is checked by using the analysis of variance (ANOVA). A scanning electron microscope (SEM) analysis is carried out to analyze the quality of the drilled surface. From the results, it is found that, the feed rate is the most influencing parameter followed by spindle speed and the drill diameter is the least influencing parameter on the thrust force.

  1. Comparison of thermal behavior of natural and hot-washed sisal fibers based on their main components: Cellulose, xylan and lignin. TG-FTIR analysis of volatile products

    Energy Technology Data Exchange (ETDEWEB)

    Benítez-Guerrero, Mónica, E-mail: monica_benitez_guerrero@yahoo.es [Departamento de Ingeniería Civil, Materiales y Fabricación, Universidad de Málaga, Escuela de Ingenierías, C/ Dr. Ortiz Ramos s/n, Campus Teatinos, 29071 Málaga (Spain); López-Beceiro, Jorge [Departamento de Ingeniería Industrial II, Escola Politécnica Superior, Universidade da Coruña, Avda. Mendizábal, 15403 Ferrol (Spain); Sánchez-Jiménez, Pedro E. [Instituto de Ciencia de Materiales de Sevilla, CSIC-Universidad de Sevilla, C/ Américo Vespucio 49, 41092 Sevilla (Spain); Pascual-Cosp, José [Departamento de Ingeniería Civil, Materiales y Fabricación, Universidad de Málaga, Escuela de Ingenierías, C/ Dr. Ortiz Ramos s/n, Campus Teatinos, 29071 Málaga (Spain)

    2014-04-01

    Highlights: • Thermal decomposition of sisal fibers has been discussed. • Decompositions of lignocellulosic components and sisal are compared by TXRD and TG-FTIR. • Hot washing reduces the temperature range in which sisal decomposition occurs. • Sisal cellulose decomposition goes by an alternative route to levoglucosan generation. - Abstract: This paper presents in a comprehensive way the thermal behavior of natural and hot-washed sisal fibers, based on the fundamental components of lignocellulosic materials: cellulose, xylan and lignin. The research highlights the influence exerted on the thermal stability of sisal fibers by other constituents such as non-cellulosic polysaccharides (NCP) and mineral matter. Thermal changes were investigated by thermal X-ray diffraction (TXRD), analyzing the crystallinity index (%Ic) of cellulosic samples, and by simultaneous thermogravimetric and differential thermal analysis coupled with Fourier-transformed infrared spectrometry (TG/DTA-FTIR), which allowed to examine the evolution of the main volatile compounds evolved during the degradation under inert and oxidizing atmospheres. The work demonstrates the potential of this technique to elucidate different steps during the thermal decomposition of sisal, providing extensible results to other lignocellulosic fibers, through the analysis of the evolution of CO{sub 2}, CO, H{sub 2}O, CH{sub 4}, acetic acid, formic acid, methanol, formaldehyde and 2-butanone, and comparing it with the volatile products from pyrolysis of the biomass components. The hydroxyacetaldehyde detected during pyrolysis of sisal is indicative of an alternative route to that of levoglucosan, generated during cellulose pyrolysis. Hot-washing at 75 °C mostly extracts non-cellulosic components of low decomposition temperature, and reduces the range of temperature in which sisal decomposition occurs, causing a retard in the pyrolysis stage and increasing Tb{sub NCP} and Tb{sub CEL}, temperatures at the

  2. 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 ...

  3. 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] ...

  4. 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...

  5. 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...

  6. Caracterização química e estrutural de fibra de sisal da variedade Agave sisalana Chemical and structural characterization of sisal fibers from Agave sisalana variety

    Directory of Open Access Journals (Sweden)

    Adriana R. Martin

    2009-01-01

    Full Text Available Nos últimos anos, o interesse pelo uso de fibras naturais em materiais compósitos poliméricos tem aumentado significativamente. Neste trabalho foram investigadas as propriedades, químicas, físicas, térmicas e estruturais da fibra de sisal brasileira da variedade Agave sisalana. Nosso objetivo foi avaliar a qualidade e o desempenho desta fibra para aplicações industriais. Foram realizados ensaios de resistência à tração, análise da composição química, difração de raios X, e estudos por microscopia eletrônica de varredura (MEV ao longo do comprimento da fibra. A fibra de sisal brasileira apresentou propriedades mecânicas e térmicas dentro da faixa relatada na literatura, mostrando-se adequada para ser utilizada em materiais compósitos poliméricos.In recent years, the interest in the use of natural fibers in polymeric composite materials has increased significantly. In this work were investigated the structural, thermal, chemical, and physical properties of Brazilian sisal fiber from Agave sisalana variety. Our aim was to evaluate the quality and the performance of this fiber for industrial applications. Mechanical properties, chemical composition, X ray diffraction, and scanning electron microscopy (SEM have been investigated with fibers along their length. The Brazilian sisal fibers studied have exhibited mechanical and thermal properties within the range reported in the literature and were suitable for use in polymeric composites.

  7. Multivariate realised kernels

    DEFF Research Database (Denmark)

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

    2011-01-01

    We propose a multivariate realised kernel to estimate the ex-post covariation of log-prices. We show this new consistent estimator is guaranteed to be positive semi-definite and is robust to measurement error of certain types and can also handle non-synchronous trading. It is the first estimator...... which has these three properties which are all essential for empirical work in this area. We derive the large sample asymptotics of this estimator and assess its accuracy using a Monte Carlo study. We implement the estimator on some US equity data, comparing our results to previous work which has used...

  8. Clustering via Kernel Decomposition

    DEFF Research Database (Denmark)

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

    2006-01-01

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

  9. Utilização de pós residuais e fibra de sisal em blocos de concreto

    OpenAIRE

    Indara Soto Izquierdo

    2015-01-01

    A pesquisa tem como enfoque fundamental a aplicação de novos materiais alternativos para uma construção sustentável. Pós residuais, provenientes do resíduo orgânico e do setor mineral, e fibras de sisal constituem bons exemplos de materiais não convencionais. Dessa forma, o objetivo principal foi avaliar a incorporação dos pós residuais e da fibra de sisal no concreto para a fabricação de blocos de concreto e elementos de alvenaria. Foram estudados três relações cimento: agregado, de 1:15, 1:...

  10. DESENVOLVIMENTO DE TECIDOS DE SISAL PARA UTILIZAÇÃO EM COMPÓSITOS POLIMÉRICOS

    Directory of Open Access Journals (Sweden)

    Camila Cruz da Silva

    2010-01-01

    Full Text Available A utilização das fibras naturais (lignocelulosicas como reforço, em materiais compósitos polimérico, é algo que vem crescendo significativamente dia, após dia. Devido ao fato desses materiais serem biodegradáveis, provém de fontes renováveis, desenvolvendo assim as regiões onde são extraídas possibilitando dessa forma a permanência do homem no campo, fazendo parte assim de um modelo ecologicamente correto. Dentre essas fibras dá um destaque a fibra de sisal,onde esta está sendo bastante estudada e utilizada na indústria automobilística. A fibra é extraída da folha do agave sisalina, e que foi introduzida no Brasil em meados de 1900, tendo como maiores produtores os estados da Bahia, Paraíba e Rio Grande do Norte. O objetivo deste trabalho é o desenvolvimento de dois tecidos de sisal para a utilização em materiais compósitos poliméricos, já que estes não são encontrados na indústria. Dessa forma foram fabricados dois tecidos sendo um do tipo plano e o outro do tipo plano basket, onde estes foram obtidos em teares manuais. PALAVRAS-CHAVE: Materiais Compósitos, Sisal e Tecidos.

  11. 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...

  12. Resíduos de sisal como reforço em compósitos de polipropileno virgem e reciclado Virgin and recycled polypropylene composites reinforced with sisal by-product

    Directory of Open Access Journals (Sweden)

    Francisco Rosário

    2011-01-01

    Full Text Available Foram estudadas as propriedades térmicas e mecânicas de compósitos de polipropileno, virgem e reciclado, reforçados com 30% em massa de fibras residuais de sisal, assim como o perfil de processamento e a morfologia da matriz polimérica. Para tanto, foram determinadas a resistência à tração, o módulo de Young, alongamento na ruptura, e energia de impacto. As amostras também foram caracterizadas por MEV, DMTA e TG. Para ambos os compósitos de polipropileno, virgem e reciclado, com a adição das fibras, o alongamento na ruptura mostrou uma queda significativa, enquanto que a resistência à tração não sofreu grandes variações. Houve um aumento significativo nos valores de tração na ruptura e de energia de impacto com a adição das fibras de sisal na matriz de polipropileno. As análises térmicas mostraram ligações secundárias, como as ligações polares, entre as fibras e a matriz, concordando com o comportamento mecânico dos compósitos. Constatou-se que a temperatura de transição vítrea não variou após a adição da fibra.The mechanical and thermal properties of virgin and recycled polypropylene composites reinforced with 30% by mass of residual sisal fibers were studied, in addition to an analysis of the extrusion process and morphology of the polymeric matrix. Tensile strength, Young's modulus, elongation at break, and impact energy were determined. The samples were also characterized by SEM, DMTA and TG analyses. Elongation at break of the composites presented a significant decrease, while the tensile strength was not affected significantly by addition of sisal fibers. A significant increase was observed in the tension of rupture and in the impact energy of the composite reinforced with sisal fiber. The thermal analyses indicated secondary interactions, such as polar interactions, between the fibers and the matrix, consistent with the mechanical behavior of the composites. The glass transition temperature has not

  13. Caracterização mecânica de laminados cimentíceos esbeltos reforçados com fibras de sisal Mechanical characterization of cement-based thin-walled laminates reinforced with sisal fibre

    Directory of Open Access Journals (Sweden)

    Paulo R. L. Lima

    2007-12-01

    Full Text Available Com a proibição progressiva do uso de fibras de asbesto na fabricação de laminados à base de cimento, novos produtos têm sido desenvolvidos para suprir esta demanda do setor construtivo. A utilização de fibras de sisal como substituto ao asbesto, além de ser uma proposta ecológica tem grande importância socioeconômica, pois agregará valor a um produto cultivado com sucesso no semi-árido nordestino. Produziram-se, neste trabalho, placas laminadas com matriz de argamassa reforçadas com fibras longas de sisal. Ensaios de flexão em três pontos foram realizados com o objetivo de se estudar a influência da adição de fibras (3%, do número de camadas (2 e 3, da orientação das camadas (0 e 90° e da pressão de moldagem (0 e 2 MPa sobre o comportamento à flexão dos laminados. Os resultados indicam que a adição de fibras de sisal aumentou, para todos os casos estudados, a capacidade de absorver energia, a resistência à flexão pós-fissuração e a deflexão última do material. Os laminados reforçados com 3% de fibras de sisal, distribuídas em três camadas ortogonais à direção do carregamento e submetidos à pressão de moldagem de 2 MPa, apresentaram o melhor comportamento mecânico.Because of hazards to human and animal health, the use of asbestos and its products is being prohibited all around the world and academic institutions and fibre cement producers have been engaged in intensive research to find asbestos-free cement products. The application of natural fibres such as sisal to replace asbestos fibres can bring economical and ecological benefits due to their availability, low cost, low consumption of energy and suitability to the semi-arid area of the Northeast of Brazil (where not many plants can grow. In this paper, cement-based laminates reinforced with continuous sisal fibre were produced. Three point bending tests were carried out to evaluate the influence of addition of fibre (3%, number of layers of

  14. sisal fibre

    African Journals Online (AJOL)

    eobe

    2015-10-04

    Oct 4, 2015 ... control); 55.68 for specimen B; 42.82 for specimen C; 78.7 for specimen D and 81.34 for specimen E. ... savings, light weight, cleaner environment, low cost, high specific strength and ... composites are in automobile, aerospace and aircraft parts due to ..... The TIRA test 2810 system was set in tensile mode.

  15. 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.

  16. 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...

  17. Execution and executability

    Science.gov (United States)

    Bradford, Robert W.; Harrison, Denise

    2015-09-01

    "We have a new strategy to grow our organization." Developing the plan is just the start. Implementing it in the organization is the real challenge. Many organizations don't fail due to lack of strategy; they struggle because it isn't effectively implemented. After working with hundreds of companies on strategy development, Denise and Robert have distilled the critical areas where organizations need to focus in order to enhance profitability through superior execution. If these questions are important to your organization, you'll find useful answers in the following articles: Do you find yourself overwhelmed by too many competing priorities? How do you limit how many strategic initiatives/projects your organization is working on at one time? How do you balance your resource requirements (time and money) with the availability of these resources? How do you balance your strategic initiative requirements with the day-to-day requirements of your organization?

  18. 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...

  19. 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. ...

  20. Tendências tecnológicas do uso do sisal em compósitos a partir da prospecção em documentos de patentes

    Directory of Open Access Journals (Sweden)

    Felipe Scopel

    2013-01-01

    Full Text Available As fibras naturais têm sido pesquisadas e empregadas de maneira crescente no desenvolvimento de produtos com sustentabilidade econômica, social e ambiental, sendo o sisal uma das mais importantes para o Brasil, pela sua posição de liderança na produção mundial. O presente artigo analisa a evolução temporal e o interesse das empresas e instituições em tecnologias associadas ao sisal, a partir de informações e indicadores extraídos de documentos de patentes no período de 1960 a 2009. Foi verificado o crescente patenteamento associado ao sisal em áreas de química, ciência dos materiais e dos polímeros, com destaque para o reforço do de compósitos plásticos. Além do crescente número de patentes, houve também um expressivo aumento do número de empresas e instituições titulares das patentes, o que reflete a possível desconcentração do mercado nesse crescimento do interesse pelas tecnologias associadas ao sisal. O Brasil, apesar da sua proeminência na produção do sisal, possui pequena presença no patenteamento mundial. Também foi verificada a importância da análise de patentes para o acompanhamento da evolução das tecnologias e interesses, pela disponibilidade de informações públicas que podem ser transformadas em indicadores úteis para análise de tecnologia e mercado associados ao sisal ou a outras áreas tecnológicas.

  1. 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...

  2. 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.

  3. 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...

  4. 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....

  5. Effect of acid concentration and pulp properties on hydrolysis reactions of mercerized sisal.

    Science.gov (United States)

    Lacerda, Talita M; Zambon, Márcia D; Frollini, Elisabete

    2013-03-01

    The influence of sulfuric acid concentration (H2SO4 5-25%, 100°C), crystallinity and fibers size on the hydrolysis reaction of sisal pulps were investigated, with the goal of evaluating both the liquor composition, as an important step in the production of bioethanol, and the residual non-hydrolyzed pulp, to determine its potential application as materials. Aliquots were withdrawn from the reaction media, and the liquor composition was analyzed by HPLC. The residual non-hydrolyzed pulps were characterized by SEM, their average molar mass and crystallinity index, and their size distribution was determined using a fiber analyzer. Sulfuric acid 25% led to the highest glucose content (approximately 10gL(-1)), and this acid concentration was chosen to evaluate the influence of both the fiber size and crystallinity of the starting pulp on hydrolysis. The results showed that fibers with higher length and lower crystallinity favored glucose production in approximately 12%, with respect to the highly crystalline shorter fibers. Copyright © 2012 Elsevier Ltd. All rights reserved.

  6. Ovicidal activity of succinic acid isolated from sisal waste (Agave sisalana against gastrointestinal nematodes of goats

    Directory of Open Access Journals (Sweden)

    Nathália Silva de Souza Santos

    Full Text Available ABSTRACT: This study was conducted to evaluate the in vitro anthelmintic activity of the succinic acid (SA isolated from sisal waste against gastrointestinal nematodes of goats, using the egg hatching and larvae motility assays. In addition, potential cytotoxicity of SA on Vero cell cultures was investigated by means of MTT (3-4,5-dimethylthiazol-2-yl, 2,5diphenyltetrazolium bromide test. The SA induced a significant inhibition of egg hatching (P<0.05 at all concentrations tested (60 to 250µg mL-1, and the concentrations to inhibit 50% (EC50 and 90% (EC90 values (mean ± standard deviation were 90.3±2.8 and 130.6±3.5µg mL-1, respectively. The SA has not shown larvicidal activity. The SA was less toxic to the Vero cells, with the mean percentage of cell viability equal to 85±6.2% at the concentration of 130µg mL-1. The results suggested that SA has potential anthelmintic effect; although, more research is needed to confirm its activity in vivo.

  7. Biogas production from UASB and polyurethane carrier reactors treating sisal processing wastewater

    Energy Technology Data Exchange (ETDEWEB)

    Rubindamayugi, M S.T.; Salakana, L K.P. [Univ. of Dar es Salaam, Faculty of Science, Applied Microbiology Unit (Tanzania, United Republic of)

    1998-12-31

    The fundamental benefits which makes anaerobic digestion technology (ADT) attractive to the poor developing include the low cost and energy production potential of the technology. In this study the potential of using UASB reactor and Polyurethane Carrier Reactor (PCR) as pollution control and energy recovery systems from sisal wastewater were investigated in lab-scale reactors. The PCR demonstrated the shortest startup period, whereas the UASB reactor showed the highest COD removal efficiency 79%, biogas production rate (4.5 l biogas/l/day) and process stability than the PCR under similar HRT of 15 hours and OLR of 8.2 g COD/l/day. Both reactor systems became overloaded at HRT of 6 hours and OLR of 15.7 g COD/l/day, biogas production ceased and reactors acidified to pH levels which are inhibiting to methanogenesis. Based on the combined results on reactor performances, the UASB reactor is recommended as the best reactor for high biogas production and treatment efficiency. It was estimated that a large-scale UASB reactor can be designed under the same loading conditions to produce 2.8 m{sup 3} biogas form 1 m{sup 3} of wastewater of 5.16 kg COD/m{sup 3}. Wastewater from one decortication shift can produce 9,446 m{sup 3} og biogas. The energy equivalent of such fuel energy is indicated. (au)

  8. Biogas production from UASB and polyurethane carrier reactors treating sisal processing wastewater

    Energy Technology Data Exchange (ETDEWEB)

    Rubindamayugi, M.S.T.; Salakana, L.K.P. [Univ. of Dar es Salaam, Faculty of Science, Applied Microbiology Unit (Tanzania, United Republic of)

    1997-12-31

    The fundamental benefits which makes anaerobic digestion technology (ADT) attractive to the poor developing include the low cost and energy production potential of the technology. In this study the potential of using UASB reactor and Polyurethane Carrier Reactor (PCR) as pollution control and energy recovery systems from sisal wastewater were investigated in lab-scale reactors. The PCR demonstrated the shortest startup period, whereas the UASB reactor showed the highest COD removal efficiency 79%, biogas production rate (4.5 l biogas/l/day) and process stability than the PCR under similar HRT of 15 hours and OLR of 8.2 g COD/l/day. Both reactor systems became overloaded at HRT of 6 hours and OLR of 15.7 g COD/l/day, biogas production ceased and reactors acidified to pH levels which are inhibiting to methanogenesis. Based on the combined results on reactor performances, the UASB reactor is recommended as the best reactor for high biogas production and treatment efficiency. It was estimated that a large-scale UASB reactor can be designed under the same loading conditions to produce 2.8 m{sup 3} biogas form 1 m{sup 3} of wastewater of 5.16 kg COD/m{sup 3}. Wastewater from one decortication shift can produce 9,446 m{sup 3} og biogas. The energy equivalent of such fuel energy is indicated. (au)

  9. Natural sisal fibers derived hierarchical porous activated carbon as capacitive material in lithium ion capacitor

    Science.gov (United States)

    Yang, Zhewei; Guo, Huajun; Li, Xinhai; Wang, Zhixing; Yan, Zhiliang; Wang, Yansen

    2016-10-01

    Lithium-ion capacitor (LIC) is a novel advanced electrochemical energy storage (EES) system bridging gap between lithium ion battery (LIB) and electrochemical capacitor (ECC). In this work, we report that sisal fiber activated carbon (SFAC) was synthesized by hydrothermal treatment followed by KOH activation and served as capacitive material in LIC for the first time. Different particle structure, morphology, specific surface area and heteroatoms affected the electrochemical performance of as-prepared materials and corresponding LICs. When the mass ratio of KOH to char precursor was 2, hierarchical porous structured SFAC-2 was prepared and exhibited moderate specific capacitance (103 F g-1 at 0.1 A g-1), superior rate capability and cyclic stability (88% capacity retention after 5000 cycles at 1 A g-1). The corresponding assembled LIC (LIC-SC2) with optimal comprehensive electrochemical performance, displayed the energy density of 83 Wh kg-1, the power density of 5718 W kg-1 and superior cyclic stability (92% energy density retention after 1000 cycles at 0.5 A g-1). It is worthwhile that the source for activated carbon is a natural and renewable one and the synthesis method is eco-friendly, which facilitate that hierarchical porous activated carbon has potential applications in the field of LIC and other energy storage systems.

  10. Inclusão de feixes de sisal na produção de painéis MDP de eucalipto

    DEFF Research Database (Denmark)

    de Almeida Mesquita, Ricardo G; Mendes, Lourival Marin; Mendes, Rafael Farinassi

    2015-01-01

    of the plastic industry. This lignocellulose material has gained prominence due to several mechanical and economic characteristics. Thus, the aim of this study was to evaluate the potential use of sisal bundles in association with eucalyptus particles for the production of MDP panels. Panels were prepared...... with the substitution on eucalyptus wood for sisal bundles in the panels’ core in doses of 0, 5, 10, 15, 20 and 25%. The MDP panels were produced with face/core 40/60 (base dry mass of the particles), urea-formaldehyde adhesive, nominal density of 0,70 g.cm-3 and pressing cycle of 8 minutes, 3,92 MPa pressure...

  11. Evaluation gamma radiation in composite sisal fiber- polyurethane derived of castor oil by bending test; Avaliacao da influencia da radiacao gama em compositos de fibra de sisal - poliuretano derivado de oleo de mamona atraves de ensaios de flexao

    Energy Technology Data Exchange (ETDEWEB)

    Souza, Felipe H. de; Geraldo, Ricardo R.; Vasco, Marina C.; Azevedo, Elaine, E-mail: helunica@yahoo.com.br [Universidade Tecnologica Federal do Parana (UTFPR), Curitiba, PR (Brazil); Claro Neto, Salvador [Universidade de Sao Paulo (USP), Sao Carlos, SP (Brazil). Instituto de Quimica

    2015-07-01

    Materials used for making furniture and accessories or positioning in X -ray examination rooms should not exhale volatile organic compounds and are resistant to ionizing radiation. One solution is the use of vegetable fiber and polyurethane composites of vegetable origin, since they are biodegradable, derived from renewable raw materials and have no volatile organic compounds. The main difficulty in developing this material is fiber adhesion with the polymer. The objective of this study is to evaluate the mechanical properties of composite sisal fiber composite, without further treatment, and polyurethane derived from castor oil, with a dose of 25 kGy gamma radiation, subjected to 3 points bending tests. (author)

  12. VALORIZAÇÃO DOS RESÍDUOS DE SISAL: UMA PROPOSTA PARA A REGIÃO DO SEMIARIDO DO ESTADO DA BAHIA

    Directory of Open Access Journals (Sweden)

    Antonivalda Tosta Dias

    2015-01-01

    Full Text Available O presente estudo tem como objetivo apresentar uma proposta para a valorizaçãodos resíduos de sisal que reduza e/ou elimine o passivo ambiental existente naRegião Sisaleira da Bahia. Este trabalho foi desenvolvido em duas etapas. Naprimeira etapa, foi feito um diagnóstico visual dos problemas fitossanitáriosassociados ao beneficiamento do sisal na Comunidade Rose do município deSantaluz, complementado com análise das propriedades químicas dos solos(arenoso e argiloso em seis unidades produtivas, onde foram avaliados locaiscom ou sem o resíduo do sisal nas profundidades de 0 - 20cm e 20 - 40cm. Nasegunda etapa, foi montado um experimento de compostagem na UniversidadeEstadual de Feira de Santana, com os seguintes tratamentos: T! - resíduo desisal, T2 - resíduo de sisal + poda de árvores + urina humana + esterco de cabra,T3 - resíduo de sisal + poda de árvores + esterco de cabra e T4 - resíduo de sisal+ poda de árvores + urina humana + esterco de cabra. Estes resíduos foramdispostos em camadas de 20cm, exceto o tratamento T4, em que a matéria primafoi homogeneizada antes da montagem das pilhas. Foram avaliados osparâmetros físicos e químicos do composto formado. Os resultados encontradosna primeira etapa demonstram que não existe um local definitivo para odesfibramento do sisal que é descartado no campo, ocupando áreas antesprodutivas por mais de dois anos, tempo necessário para sua degradação. Oresíduo é um meio adequado para produção de moscas. O solo, por sua vez, érico em matéria orgânica, entretanto, o teor de nutrientes foi muito maior no localcom a presença do resíduo de sisal. O composto orgânico em todos ostratamentos apresentou teores de nutrientes e metais pesados de acordo com osvalores pré-estabelecidos pelo MAPA, com exceção do nitrogênio que ficouabaixo do exigido. É possível obter um composto orgânico de boa qualidade apartir da mistura de resíduos de sisal com outros componentes

  13. 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 ...

  14. Experimental and numerical research on the potentialities of layered reinforcement configuration of continuous sisal fibers for thin mortar panels

    OpenAIRE

    Barros, Joaquim A. O.; Silva, Flávio de A.; Toledo-Filho, Romildo D.

    2016-01-01

    This work is dedicated to the assessment of the flexural capacity of thin mortar panels (about 12 mm thick) reinforced with unidirectional continuous layers of sisal fibers. By adopting five stacked layers, each one involved in a mortar layer of about 1 mm thickness, which constitute a fiber volume of 10%, a maximum flexural strength of 30 MPa was obtained at a deflection of around 1/10 of the specimen’s span length. At this deflection the toughness is 46 times higher the elastic ...

  15. Seasonal abundance of crustaceans associated with artisanal fishery of blue crab (Callinectes sapidus) in Sisal, Yucatan, Mexico

    OpenAIRE

    Celis-Sánchez, José Alfredo; Estrella-Canto, Arely de Jesús; Poot-López, Gaspar Román; González-Salas, Carlos; López-Rocha, Jorge Alberto

    2014-01-01

    Seasonal abundance and selectivity of the main crustacean species associated with blue crab fishing was studied at the port of Sisal, Yucatan, Mexico. For this purpose, 52 crab traps were used, which were divided into four parallel transects placed 100, 150, 200 and 250 m of the shoreline. Each transect consisted of 13 traps 20 m from each other. Traps were set at dusk and checked at dawn, standardizing the fishing effort to 17 hours/trap/day. A total of 832 organisms from eight species were ...

  16. 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...

  17. 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.

  18. 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...

  19. 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.

  20. 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

  1. 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...

  2. 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.

  3. 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.

  4. 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....

  5. Estudio del comportamiento de la escayola reforzada con fibras de sisal, para componentes en viviendas de bajo coste

    Directory of Open Access Journals (Sweden)

    de Oteiza San José, Ignacio

    1993-08-01

    Full Text Available The present article is a brief description of the work done for the elaboration of the doctoral thesis and its conclusions. Starting from the possibilities of using plaster in developing countries, due to its abundance and low cost, a series of mechanical tests have been carried out in order to learn about the physical and mechanical properties of plaster reinforced with sisal fibres for its future use in components for low cost housing.

    El presente artículo es una breve descripción de los trabajos realizados para la elaboración de la tesis doctoral y de las conclusiones de la misma. Partiendo de las posibilidades de utilización en los países en vías de desarrollo del material de escayola, por su abundancia y bajo coste, se llevan a cabo una serie de ensayos mecánicos, con el fin de conocer las propiedades físicas y mecánicas de la escayola reforzada con fibras de sisal, para una futura aplicación en componentes para viviendas de bajo coste.

  6. A Visual Approach to Investigating Shared and Global Memory Behavior of CUDA Kernels

    KAUST Repository

    Rosen, Paul

    2013-06-01

    We present an approach to investigate the memory behavior of a parallel kernel executing on thousands of threads simultaneously within the CUDA architecture. Our top-down approach allows for quickly identifying any significant differences between the execution of the many blocks and warps. As interesting warps are identified, we allow further investigation of memory behavior by visualizing the shared memory bank conflicts and global memory coalescence, first with an overview of a single warp with many operations and, subsequently, with a detailed view of a single warp and a single operation. We demonstrate the strength of our approach in the context of a parallel matrix transpose kernel and a parallel 1D Haar Wavelet transform kernel. © 2013 The Author(s) Computer Graphics Forum © 2013 The Eurographics Association and Blackwell Publishing Ltd.

  7. A Visual Approach to Investigating Shared and Global Memory Behavior of CUDA Kernels

    KAUST Repository

    Rosen, Paul

    2013-01-01

    We present an approach to investigate the memory behavior of a parallel kernel executing on thousands of threads simultaneously within the CUDA architecture. Our top-down approach allows for quickly identifying any significant differences between the execution of the many blocks and warps. As interesting warps are identified, we allow further investigation of memory behavior by visualizing the shared memory bank conflicts and global memory coalescence, first with an overview of a single warp with many operations and, subsequently, with a detailed view of a single warp and a single operation. We demonstrate the strength of our approach in the context of a parallel matrix transpose kernel and a parallel 1D Haar Wavelet transform kernel. © 2013 The Author(s) Computer Graphics Forum © 2013 The Eurographics Association and Blackwell Publishing Ltd.

  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. 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

  10. 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....

  11. 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

  12. Executive Dysfunction

    Science.gov (United States)

    Rabinovici, Gil D.; Stephens, Melanie L.; Possin, Katherine L.

    2015-01-01

    Purpose of Review: Executive functions represent a constellation of cognitive abilities that drive goal-oriented behavior and are critical to the ability to adapt to an ever-changing world. This article provides a clinically oriented approach to classifying, localizing, diagnosing, and treating disorders of executive function, which are pervasive in clinical practice. Recent Findings: Executive functions can be split into four distinct components: working memory, inhibition, set shifting, and fluency. These components may be differentially affected in individual patients and act together to guide higher-order cognitive constructs such as planning and organization. Specific bedside and neuropsychological tests can be applied to evaluate components of executive function. While dysexecutive syndromes were first described in patients with frontal lesions, intact executive functioning relies on distributed neural networks that include not only the prefrontal cortex, but also the parietal cortex, basal ganglia, thalamus, and cerebellum. Executive dysfunction arises from injury to any of these regions, their white matter connections, or neurotransmitter systems. Dysexecutive symptoms therefore occur in most neurodegenerative diseases and in many other neurologic, psychiatric, and systemic illnesses. Management approaches are patient specific and should focus on treatment of the underlying cause in parallel with maximizing patient function and safety via occupational therapy and rehabilitation. Summary: Executive dysfunction is extremely common in patients with neurologic disorders. Diagnosis and treatment hinge on familiarity with the clinical components and neuroanatomic correlates of these complex, high-order cognitive processes. PMID:26039846

  13. Complex use of cottonseed kernels

    Energy Technology Data Exchange (ETDEWEB)

    Glushenkova, A I

    1977-01-01

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

  14. Kernel regression with functional response

    OpenAIRE

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

    2011-01-01

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

  15. GRIM : Leveraging GPUs for Kernel integrity monitoring

    NARCIS (Netherlands)

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

    2016-01-01

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

  16. Paramecium: An Extensible Object-Based Kernel

    NARCIS (Netherlands)

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

    1995-01-01

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

  17. Local Observed-Score Kernel Equating

    Science.gov (United States)

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

    2014-01-01

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

  18. Veto-Consensus Multiple Kernel Learning

    NARCIS (Netherlands)

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

    2016-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Senyue Zhang

    2016-01-01

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

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

    Science.gov (United States)

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

    2018-05-01

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

  1. Wigner functions defined with Laplace transform kernels.

    Science.gov (United States)

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

    2011-10-24

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

  2. 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.

  3. 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....

  4. 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....

  5. Evaluation of anthelmintic activity of liquid waste of Agave sisalana (sisal in goats Avaliação da atividade anti-helmíntica do resíduo líquido de Agave sisalana (sisal em caprinos

    Directory of Open Access Journals (Sweden)

    Luciana Ferreira Domingues

    2010-12-01

    Full Text Available It was evaluated the anthelmintic activity of Agave sisalana (sisal juice against gastrointestinal nematodes and its potential toxic effects in goats. In vitro tests showed more than 95% reduction in larval counts of the genus Haemonchus spp. at concentrations between 86.5 and 146.3 mg.mL-1. In vivo the percent reduction of larvae of the fourth (L4 and fifth (L5 stages of Haemonchus, Oesophagostomum and Trichostrongylus was less than 95% in groups GI and GII, and between 80 and 90% in group GIII. A. sisalana juice at the concentrations tested in vitro was effective against gastrointestinal nematodes in goats; however, its anthelmintic efficacy was reduced when administered to animals.Foi avaliada a atividade anti-helmíntica do suco de Agave sisalana (sisal contra nematódeos gastrintestinais e possíveis efeitos tóxicos em caprinos. Nos testes in vitro, encontrou-se redução superior a 95% na contagem de larvas do gênero Haemonchus spp. nas concentrações entre 86,5 e 146,3 mg.mL-1. In vivo, o percentual de redução de larvas de quarto (L4 e quinto (L5 estágios de Haemonchus, Oesophagostomum e Trichostrongylus foi inferior a 95% para o GI e GII, e entre 80 e 90% para o GIII. O suco de A. sisalana nas concentrações testadas in vitro foi efetivo contra nematódeos gastrintestinais de caprinos, apresentando, no entanto, reduzida eficácia anti-helmíntica quando administrado nos animais.

  6. 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.

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

    KAUST Repository

    Abdelfattah, Ahmad

    2013-01-01

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

  8. 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.

  9. 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.

  10. Estudo da influência de tratamentos químicos da fibra de sisal nas propriedades de compósitos com borracha nitrílica Study of the influence from chemical treatments of sisal fibers on the properties of composites with nitrile rubber

    Directory of Open Access Journals (Sweden)

    Marco A. Iozzi

    2010-01-01

    Full Text Available A influência de diferentes tratamentos das fibras de sisal nas propriedades dos compósitos de borracha nitrílica/fibras de sisal, e borracha nitrílica/carbonato de cálcio/fibras de sisal foi investigada. Os compósitos, com fibras curtas aleatoriamente distribuídas, foram processados em moinho de dois rolos e caracterizados através de ensaios mecânicos de resistência à tração, microscopia eletrônica de varredura (MEV, análise por termogravimetria (TG e calorimetria exploratória diferencial (DSC. O tratamento de mercerização das fibras levou a uma maior adesão na interface fibra/matriz. O uso combinado de 67 pcr de carbonato com 33 pcr de fibras de sisal mercerizadas produziu um compósito com aumento significativo no módulo de elasticidade e sem perda da resistência à tração de ruptura. Os resultados da análise térmica mostraram que os compósitos são termicamente estáveis até cerca de 300 °C. Os materiais obtidos possuem uma boa relação custo/benefício tornando promissora sua utilização.In this work, composites were produced with nitrile rubber and sisal fibers, and nitrile rubber with calcium carbonate and sisal fibers. The composites were processed on a two-roll mixing mill and their properties were investigated with regard to the influence of chemical treatments of the fibers. The composites, with short fibers randomly distributed, were characterized by mechanical analysis, scanning electron microscopy (SEM, thermogravimetric analysis (TGA and differential scanning calorimetry (DSC. Mercerization treatment of the fibers promoted increasing the adhesion between the fiber and the rubber matrix. The composites of nitrile rubber with 67 pcr of calcium carbonate and 33 pcr of mercerized sisal fibers showed the best mechanical properties. Thermal analysis demonstrated that the composites are thermally stable up to 300 °C. The materials developed have a good cost/benefit relationship making their utilization

  11. Executive summary

    NARCIS (Netherlands)

    van Nimwegen, N.; van Nimwegen, N.; van der Erf, R.

    2009-01-01

    The Demography Monitor 2008 gives a concise overview of current demographic trends and related developments in education, the labour market and retirement for the European Union and some other countries. This executive summary highlights the major findings of the Demography Monitor 2008 and further

  12. A class of kernel based real-time elastography algorithms.

    Science.gov (United States)

    Kibria, Md Golam; Hasan, Md Kamrul

    2015-08-01

    In this paper, a novel real-time kernel-based and gradient-based Phase Root Seeking (PRS) algorithm for ultrasound elastography is proposed. The signal-to-noise ratio of the strain image resulting from this method is improved by minimizing the cross-correlation discrepancy between the pre- and post-compression radio frequency signals with an adaptive temporal stretching method and employing built-in smoothing through an exponentially weighted neighborhood kernel in the displacement calculation. Unlike conventional PRS algorithms, displacement due to tissue compression is estimated from the root of the weighted average of the zero-lag cross-correlation phases of the pair of corresponding analytic pre- and post-compression windows in the neighborhood kernel. In addition to the proposed one, the other time- and frequency-domain elastography algorithms (Ara et al., 2013; Hussain et al., 2012; Hasan et al., 2012) proposed by our group are also implemented in real-time using Java where the computations are serially executed or parallely executed in multiple processors with efficient memory management. Simulation results using finite element modeling simulation phantom show that the proposed method significantly improves the strain image quality in terms of elastographic signal-to-noise ratio (SNRe), elastographic contrast-to-noise ratio (CNRe) and mean structural similarity (MSSIM) for strains as high as 4% as compared to other reported techniques in the literature. Strain images obtained for the experimental phantom as well as in vivo breast data of malignant or benign masses also show the efficacy of our proposed method over the other reported techniques in the literature. Copyright © 2015 Elsevier B.V. All rights reserved.

  13. 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...

  14. 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.

  15. 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.

  16. Kernel principal component analysis for change detection

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg; Morton, J.C.

    2008-01-01

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

  17. Application of foam column as green technology for concentration of saponins from sisal (Agave sisalana and Juá (Ziziphus joazeiro

    Directory of Open Access Journals (Sweden)

    B. D. Ribeiro

    2013-12-01

    Full Text Available Saponins, molecules classified as triterpenic or steroidal glycosides, are metabolites distributed in all the plant kingdom that can be used for the production of foods, cosmetics, and pharmaceuticals, as well as in soil bioremediation. Saponins are normally extracted from natural resources with water, ethanol and/or methanol, and then concentrated by liquid-liquid partitioning with n-butanol. An alternative concentration method is with a foam column, by which the saponins can be concentrated via preferential adsorption at a gas-liquid interface. Therefore, the objective of this work was the use of a foam column for the concentration of saponins from juá and sisal, evaluating parameters such as: initial working volume in the column, saponin concentration in the extracts from juá and sisal, air flow rate, pH, Raschig rings loading and operation time. When a gradient air flow rate and 25 g of Raschig rings were used, 82.6% of the jua saponins loaded onto the system were recovered in a 3.46-fold concentrated solution after 9 h of operation. Regarding sisal saponins, a concentration factor of 1.98 was observed with 90.5% of saponin recovery during 4.5 h of operation.

  18. Synthesis of Hierarchical Sisal-Like V2O5 with Exposed Stable {001} Facets as Long Life Cathode Materials for Advanced Lithium-Ion Batteries.

    Science.gov (United States)

    Wu, Naiteng; Du, Wuzhou; Liu, Guilong; Zhou, Zhan; Fu, Hong-Ru; Tang, Qianqian; Liu, Xianming; He, Yan-Bing

    2017-12-20

    Vanadium pentoxide (V 2 O 5 ) is considered a promising cathode material for advanced lithium-ion batteries owing to its high specific capacity and low cost. However, the application of V 2 O 5 -based electrodes has been hindered because of their inferior conductivity, cycling stability, and power performance. Herein, hierarchical sisal-like V 2 O 5 microstructures consisting of primary one-dimensional (1D) nanobelts with [001] facets orientation growth and rich oxygen vacancies are synthesized through a facile hydrothermal process using polyoxyethylene-20-cetyl-ether as the surface control agent, followed by calcination. The primary 1D nanobelt shortens the transfer path of electrons and ions, and the stable {001} facets could reduce the side reaction at the interface of electrode/electrolyte, simultaneously. Moreover, the formation of low valence state vanadium would generate the oxygen vacancies to facilitate lithium-ion diffusion. As a result, the sisal-like V 2 O 5 manifests excellent electrochemical performances, including high specific capacity (297 mA h g -1 at a current of 0.1 C) and robust cycling performance (capacity fading 0.06% per cycle). This work develops a controllable method to craft the hierarchical sisal-like V 2 O 5 microstructures with excellent high rate and long-term cyclic stability.

  19. 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

  20. 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

  1. Hilbertian kernels and spline functions

    CERN Document Server

    Atteia, M

    1992-01-01

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

  2. Computing the sparse matrix vector product using block-based kernels without zero padding on processors with AVX-512 instructions

    Directory of Open Access Journals (Sweden)

    Bérenger Bramas

    2018-04-01

    Full Text Available The sparse matrix-vector product (SpMV is a fundamental operation in many scientific applications from various fields. The High Performance Computing (HPC community has therefore continuously invested a lot of effort to provide an efficient SpMV kernel on modern CPU architectures. Although it has been shown that block-based kernels help to achieve high performance, they are difficult to use in practice because of the zero padding they require. In the current paper, we propose new kernels using the AVX-512 instruction set, which makes it possible to use a blocking scheme without any zero padding in the matrix memory storage. We describe mask-based sparse matrix formats and their corresponding SpMV kernels highly optimized in assembly language. Considering that the optimal blocking size depends on the matrix, we also provide a method to predict the best kernel to be used utilizing a simple interpolation of results from previous executions. We compare the performance of our approach to that of the Intel MKL CSR kernel and the CSR5 open-source package on a set of standard benchmark matrices. We show that we can achieve significant improvements in many cases, both for sequential and for parallel executions. Finally, we provide the corresponding code in an open source library, called SPC5.

  3. Análise cromossômica em bulbilhos de sisal (Agave spp. cultivados em diferentes municípios baianos, Brasil Chromosomal analysis of immature bulbs of sisal (Agave spp. cultivated in different districts in Bahia, Brazil

    Directory of Open Access Journals (Sweden)

    Sandra Regina de Oliveira Domingos Queiroz

    2012-12-01

    Full Text Available O plantio de sisal tornou-se uma das atividades econômicas mais importantes na região do semiárido baiano, onde as adversidades ambientais impedem o plantio de outras culturas. Diante da importância econômica, estudos de citogenética são necessários, pois podem fornecer informações que auxiliem na produção de linhagens melhoradas. A análise de bulbilhos, coletados de cinco localidades diferentes da Bahia, mostrou a presença de indivíduos diplóides e pentaplóides, com comprimento cromossômico variando de 24,56 µm até 0,43 µm nos diferentes exemplares. A formulação cariotípica para o híbrido n° 11648 (2n = 2x = 60, coletado no município de Valente, foi de 2mv + 38m + 10sm + 8st + 2t. Já para os pentaplóides (2n = 5x = 142 c.a. coletadas nos municípios de Conceição do Coité e Valente a classificação cromossômica encontrada foi: 14m + 66sm + 38st + 2a + 22t e 82m + 48sm + 12st, respectivamente. Fatores como maior comprimento genômico, presença de cromossomos acrocêntricos, subtelocêntricos e telocêntricos nos cariótipos bimodais e a diminuição na quantidade de cromossomos grandes com conseqüente aumento no número de cromossomos pequenos podem indicar o andamento de um processo divergente.Sisal plantations have become one of the more important economic activities in the semiarid region of Bahia, where the environmental adversities are too harsh for most other agricultural operations. In the face of economic importance, cytogenetic studies of sisal are necessary because they could provide information that would aid in the production of improved lineages. In this study, the analyses of the immature bulbs, collected from five different areas in Bahia, showed the presence of diploid and pentaploid individuals, with chromosomal lengths varying from 24.56 µm to 0.43 µm in the different samples. The karyotype formulation for the hybrid n° 11648 (2n = 2x = 60, collected in the district of Valente, was 2mv + 38

  4. 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.

  5. 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

  6. Efeito da argila calcinada sobre a durabilidade de argamassas reforçadas com fibras curtas de sisal Effect of calcined clay on aging of sisal short fiber reinforced mortar

    Directory of Open Access Journals (Sweden)

    João de Farias Filho

    2010-10-01

    Full Text Available O interesse pelo uso de fibras vegetais como reforço de matrizes, à base de cimento, tem crescido em todo o mundo nos últimos anos, sendo limitado pela baixa durabilidade das fibras no meio alcalino. Com o tempo, as fibras podem mineralizar devido à migração de hidróxido de cálcio (CH da matriz para o lúmen e paredes das fibro-células. Procurou-se consumir, no presente estudo, o CH livre utilizando-se resíduo de tijolo moído e metacaulinita em substituição parcial, de 20 e 40% em peso, do cimento portland. Compósitos com fibras de sisal e matrizes cimento-pozolana foram submetidos a ensaios de resistência a flexão, após 28 dias de cura em água, 135 e 180 dias de envelhecimento natural e após 94 ciclos de molhagem e secagem. Os resultados indicaram que é possível consumir todo o CH da matriz, o que resultou na manutenção da tenacidade inicial do compósito e no aumento da sua resistência a flexão após exposição natural ou ciclos de molhagem e secagem.In the last few years a growing interest in the use of sisal fibers as reinforcement in cement based composites has been observed. However, the main concern for its use is related with the durability of the fibers in the alkaline water of concrete as they can mineralize due to the migration of calcium hydroxide to the fiber lumen and cell walls. In this study, the alkalinity of the matrix was reduced using metakaolin and crushed waste calcined clay bricks as cement replacement. The percentage of cement replacement ranged from 20 to 40% on weight basis. Flexural tests were carried out in the composites after 28 days of cure in water, 135 and 180 days of ageing in the open air and after 94 cycles of wetting and drying. These results indicated that the mixture with cement replacement consumed all calcium hydroxide and kept the toughness over time.

  7. 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.

  8. 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.

  9. 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

  10. 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)

  11. 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...

  12. 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…

  13. 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

  14. Executive summary

    International Nuclear Information System (INIS)

    1981-02-01

    This paper is an 'executive summary' of work undertaken to review proposals for transport, handling and emplacement of high level radioactive wastes in an underground repository, appropriate to the U.K. context, with particular reference to: waste block size and configuration; self-shielded or partially-shielded block; stages of disposal; transportation within the repository; emplacement in vertical holes or horizontal tunnels; repository access by adit, incline or shaft; and costs. The paper contains a section on general conclusions and recommendations. (U.K.)

  15. Bayesian Kernel Mixtures for Counts.

    Science.gov (United States)

    Canale, Antonio; Dunson, David B

    2011-12-01

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

  16. 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%.

  17. 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.

  18. A influência do espaçamento sôbre o ciclo vegetativo do sisal

    Directory of Open Access Journals (Sweden)

    J. C. Medina

    1946-01-01

    Full Text Available The present paper deals with the influence of different rates of spacing on the poling of sisal plants (Agave sisalana Perrine. The results were obtained from spacing trials (four randomized blocks of nine treatments carried out at the Ribeirão Preto and Pindorama Experimental Stations. The percentages of poling plants, up to the 5th leaf cutting, were 20,0% and 91,7% for the narrowest (1,2 x 2,0 m and widest (2,0 x 3,0 m spacings tried in Pindorama, while in Ribeirão Preto they were 12,5% and 02,5%, respectivelly. According to these results it may be concluded that the narrow spaced plants were less liable to early poling than the wide spacing ones. The trial at Ribeirão Preto also indicated that among the plants, grown under the same conditions, those producing leaves at a faster rate were the first to pole. At that Station, the yearly average lenf production per plant (for all treatments up to the 4th leaf cutting, has been 41,5 leaves for those plants poling after 63 months ; 38,0 leaves for those poling after 74 months ; and 35,3 leaves for those plants not poled up to 5 th cutting.

  19. Executive summary

    International Nuclear Information System (INIS)

    2002-01-01

    On 18 May 2001, the Finnish Parliament ratified the Decision in Principle on the final disposal facility for spent nuclear fuel at Olkiluoto, within the municipality of Eurajoki. The Municipality Council and the government has made positive decisions earlier, at the end of 2000, and in compliance with the Nuclear Energy Act, Parliament's ratification was then required. The decision is valid for the spent fuel generated by the existing Finnish nuclear power plants and means that the construction of the final disposal facility is considered to be in line with the overall good of society. Earlier steps included, amongst others, the approval of the technical project by the Safety Authority. Future steps include construction of an underground rock characterisation facility, ONKALO (2003-2004), and application for separate construction and operating licences for the final disposal facility (from about 2010). How did this political and societal decision come about? The FSC Workshop provided the opportunity to present the history leading up to the Decision in Principle (DiP), and to examine future perspectives with an emphasis on stakeholder involvement. This Executive Summary gives an overview of the presentations and discussions that took place at the workshop. It presents, for the most part, a factual account of the individual presentations and of the discussions that took place. It relies importantly on the notes that were taken at the meeting. Most materials are elaborated upon in a fuller way in the texts that the various speakers and session moderators contributed for these proceedings. The structure of the Executive Summary follows the structure of the workshop itself. Complementary to this Summary and also provided with this document, is a NEA Secretariat's perspective aiming to place the results of all discussions, feedback and site visit into an international perspective. (authors)

  20. Executing application function calls in response to an interrupt

    Science.gov (United States)

    Almasi, Gheorghe; Archer, Charles J.; Giampapa, Mark E.; Gooding, Thomas M.; Heidelberger, Philip; Parker, Jeffrey J.

    2010-05-11

    Executing application function calls in response to an interrupt including creating a thread; receiving an interrupt having an interrupt type; determining whether a value of a semaphore represents that interrupts are disabled; if the value of the semaphore represents that interrupts are not disabled: calling, by the thread, one or more preconfigured functions in dependence upon the interrupt type of the interrupt; yielding the thread; and if the value of the semaphore represents that interrupts are disabled: setting the value of the semaphore to represent to a kernel that interrupts are hard-disabled; and hard-disabling interrupts at the kernel.

  1. Automatic performance tuning of parallel and accelerated seismic imaging kernels

    KAUST Repository

    Haberdar, Hakan

    2014-01-01

    With the increased complexity and diversity of mainstream high performance computing systems, significant effort is required to tune parallel applications in order to achieve the best possible performance for each particular platform. This task becomes more and more challenging and requiring a larger set of skills. Automatic performance tuning is becoming a must for optimizing applications such as Reverse Time Migration (RTM) widely used in seismic imaging for oil and gas exploration. An empirical search based auto-tuning approach is applied to the MPI communication operations of the parallel isotropic and tilted transverse isotropic kernels. The application of auto-tuning using the Abstract Data and Communication Library improved the performance of the MPI communications as well as developer productivity by providing a higher level of abstraction. Keeping productivity in mind, we opted toward pragma based programming for accelerated computation on latest accelerated architectures such as GPUs using the fairly new OpenACC standard. The same auto-tuning approach is also applied to the OpenACC accelerated seismic code for optimizing the compute intensive kernel of the Reverse Time Migration application. The application of such technique resulted in an improved performance of the original code and its ability to adapt to different execution environments.

  2. 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 ...

  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. 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 ...

  5. 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 ...

  6. 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...

  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. 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...

  9. 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...

  10. 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...

  11. 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

  12. 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...

  13. 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.

  14. 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...

  15. 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

  16. 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.)

  17. Resistência mecânica de compósitos cimentícios leves utilizando resíduos industriais e fibras de sisal Mechanical resistence of lightweight cement composites utilizing industrial residues and fibers of sisal

    Directory of Open Access Journals (Sweden)

    Nivaldo T. de Arruda Filho

    2012-08-01

    Full Text Available A valorização de materiais alternativos incorporados com resíduos como opção ao convencional deve possibilitar a geração de um produto com qualidade, estética, produtividade e com potencial de reduzir impactos da poluição ambiental. Este trabalho foi realizado com o objetivo de desenvolver elementos construtivos para forro e divisórias, a partir de matrizes cimentícias com incorporação de resíduos industriais (resíduo cerâmico, etil vinil acetato - EVA e fibras de sisal. Desenvolveram-se técnicas de moldagem em matrizes cimentícias autoadensáveis e se avaliou a resistência mecânica dos novos compósitos. Uma placa com resíduos de EVA foi produzida e, através de trabalhos de reologia, encontrou-se a pasta matriz de revestimento desta placa, com teor adequado de adições pozolânicas e aditivo superplastificante. Avaliaram-se as resistências mecânicas das placas, da pasta matriz de revestimento encontrada, com e sem adição de fibras, e do novo compósito formado pela união desses dois elementos. Utilizou-se a técnica de alinhamento de fibras com o intuito de incrementar resistência ao novo compósito leve. A adição da matriz com fibras alinhadas melhorou a resistência a flexão do novo compósito.The appreciation of alternative materials incorporated in waste as an option to conventional material should enable to generate a product with quality, aesthetics, productivity and reduce the potential impacts of environmental pollution. This study aims to develop constructive elements for ceilings and walls from cementitious matrix incorporating industrial waste (ceramic waste, ethyl vinyl acetate - EVA and sisal fibers. Moulding techniques to produce self-compacting cementitious matrices were developed and the strength of the new composites were evaluated. A plate with EVA waste was produced and through rheology studies, a matrix plaster for coating of plate surface was found, with appropriate content of pozzolanic and

  18. 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.

  19. 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 ...

  20. Estudo das propriedades de compósitos biodegradáveis de amido/glúten de milho/glicerol reforçados com fibras de sisal Study of properties of biodegradable composites of starch/gluten/glycerol reinforced with sisal fibers

    Directory of Open Access Journals (Sweden)

    Elisângela Corradini

    2008-01-01

    Full Text Available Neste estudo, fibras de sisal foram utilizadas como reforço para a matriz constituída de amido, glúten de milho e glicerol. O teor de fibra em relação a matriz variou de 5 a 30%. O processamento da matriz e dos compósitos foi realizado em um reômetro de torque Haake à 130 °C, 50 rpm por 10 minutos. As misturas obtidas foram moldadas por compressão à quente. As propriedades mecânicas; termodinâmico-mecânico (DMTA e de absorção de água foram investigadas em função do teor de fibras na matriz de amido/glúten de milho/glicerol. O aumento do conteúdo de fibra provocou uma melhoria nas propriedades mecânicas dos compósitos com relação à matriz. O compósito reforçado com 30% de fibra de sisal apresentou aumento no módulo de elasticidade e tensão na ruptura de aproximadamente de 560 e 162%, respectivamente e diminuição nos valores de elongação na ruptura de 81%. Os resultados obtidos por DMTA mostraram aumento progressivo do módulo de armazenamento (E' e diminuição do módulo de amortecimento (tan d com o aumento do teor de fibra, confirmando o efeito de reforço das fibras de sisal na matriz de amido/glúten de milho/glicerol. A incorporação das fibras na matriz também provocou diminuição da absorção de umidade e no coeficiente de difusão de água. A análise da morfologia dos compósitos mostrou boa dispersão das fibras na matriz.Biocomposites using starch/gluten/glycerol as matrix and sisal fibers were produced by melt-mixing in an intensive batch mixer connected to a torque rheometer at 130 °C. The samples were compression molded and than characterized by water absorption and mechanical test. In tensile test, the increasing in the Young's modulus and ultimate tensile strenght were respectively of aproximately 560 and 162% in relation to matrix, whereas elongation at break decreased. The storage modulus increased with increasing fiber content whereas tan d curves decreased, confirming the reinforcing

  1. VEGETAL COVERING IN CUT SLOPES BY MEANS OF GEOCELLS OF RUBBERIZED SISAL BIOBLANKETS IN BRASILIA/DF, BRAZIL

    Directory of Open Access Journals (Sweden)

    Maurizio Sponga

    2005-05-01

    Full Text Available The strongly wavy relief transposition for implantation of highways has became intensely used in the last decades by means of tunnels, cuts and fillings, causing impacts to the landscape in result of some factors, as decapitation of surfaces, abrupt transformation of land morphology, disequilibrium of superficial and sub superficial water circulation, waste handling sistems, enchainment of erosive processes etc. As an alleviating measure of part of the impacts generated for the excavations for constructing the roadways, procedures of containment and vegetal resetting of surfaces for reduction of the erosive processes and stabilization of mass movements are adopted. The found terrain are very diversified and several occasions the vegetal covering becomes difficult in reason of the physical-chemical characteristics for germination to be inadequate. In areas of high risk to the occupation with stability problems, commonly they use covering with projected concrete for containment of hillsides, that parallelly causes strong environmental and visual impact in the intervention area, and furthermore, possibly, not consisting insolutions duly adequate or definitive for these situations.The search for alternatives is frequent in academic medium as much as in the private initiative for techniques for containment of hillsides and more economic erosion control, looking for lesser ambient impacts and better results. The search of these alternatives gradually becomes technically systemizing itself, aiming at the recovery of the conditions of dynamic balance of the impacted landscapes due to the explosive increase of social and environmental problems intrinsically related.In this direction, it will be presented the description of a work of vegetal covering by grass in plates, antierosive bioblanket and geocells in fibers of rubberized sisal for the confinement of soil in cut slopes of a highway in Brasilia/DF, in Brazil. This technique presented excellent

  2. 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.

  3. 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.

  4. 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.

  5. 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

  6. 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.

  7. 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...

  8. 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.

  9. 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

  10. 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

  11. 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

  12. Whiskers de fibra de sisal obtidos sob diferentes condições de hidrólise ácida: efeito do tempo e da temperatura de extração Whiskers from sisal fibers obtained under different acid hydrolysis conditions: effect of time and temperature of extraction

    Directory of Open Access Journals (Sweden)

    Kelcilene B. R. Teodoro

    2011-01-01

    Full Text Available Neste trabalho, os efeitos de diferentes condições de tempo e temperatura usados para a preparação de whiskers de sisal foram investigados com o objetivo de se determinar a influência destes parâmetros experimentais na morfologia, cristalinidade e estabilidade térmica dos materiais preparados. A obtenção dos whiskers deu-se após o pré-branqueamento da fibra de sisal com solução alcalina de peróxido de hidrogênio. A fibra branqueada foi submetida ao processo de hidrólise com solução de ácido sulfúrico 60% (m/m sob três diferentes condições de temperatura e tempos de extração: 45 °C e 60 minutos (WS45_60; 45 °C e 75 minutos (WS45_75 e 60 °C e 30 minutos (WS60_30. Os whiskers foram caracterizados quanto à morfologia por microscopia eletrônica de transmissão (MET, quanto à cristalinidade (DRX, carga superficial (potencial zeta , teor de enxofre (análise elementar e quanto à estabilidade térmica por termogravimetria (TGA. Os resultados mostraram que os whiskers de sisal apresentaram comprimento e diâmetro médios e 210 nm e 5 nm respectivamente. Devido à alta aglomeração dos whiskers, diferenças relativas às características dimensionais não puderam ser determinadas. Os resultados obtidos revelaram uma forte dependência da cristalinidade final dos whiskers com a temperatura e tempo de extração. O uso de temperatura mais alta (60 °C associado a um menor tempo de extração (30 minutos resulta em whiskers com boa estabilidade térmica (235 °C, maior cristalinidade e sem o comprometimento da estrutura cristalina da celulose.In this work, the effects of different conditions of time and temperature, used for the preparation of whiskers from sisal, were investigated to determine the influence of experimental parameters on morphology, crystallinity and thermal stability of materials prepared. The whiskers were obtained after the bleaching of sisal raw fiber with a solution of hydrogen peroxide alkaline. The

  13. 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...

  14. 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...

  15. 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.

  16. 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

  17. 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...

  18. 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...

  19. 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.

  20. 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

  1. 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

  2. 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.

  3. 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.

  4. Quantum logic in dagger kernel categories

    NARCIS (Netherlands)

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

    2009-01-01

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

  5. Quantum logic in dagger kernel categories

    NARCIS (Netherlands)

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

    2011-01-01

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

  6. Symbol recognition with kernel density matching.

    Science.gov (United States)

    Zhang, Wan; Wenyin, Liu; Zhang, Kun

    2006-12-01

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

  7. Flexible Scheduling in Multimedia Kernels: An Overview

    NARCIS (Netherlands)

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

    1999-01-01

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

  8. Reproducing kernel Hilbert spaces of Gaussian priors

    NARCIS (Netherlands)

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

    2008-01-01

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

  9. A synthesis of empirical plant dispersal kernels

    Czech Academy of Sciences Publication Activity Database

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

    2017-01-01

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

  10. Analytic continuation of weighted Bergman kernels

    Czech Academy of Sciences Publication Activity Database

    Engliš, Miroslav

    2010-01-01

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

  11. On convergence of kernel learning estimators

    NARCIS (Netherlands)

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

    2009-01-01

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

  12. Analytic properties of the Virasoro modular kernel

    Energy Technology Data Exchange (ETDEWEB)

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

    2017-06-15

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

  13. Kernel based subspace projection of hyperspectral images

    DEFF Research Database (Denmark)

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

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

  14. 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

  15. Scattering kernels and cross sections working group

    International Nuclear Information System (INIS)

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

    1998-01-01

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

  16. 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...

  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. 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

  19. 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...

  20. 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...

  1. 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...

  2. 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...

  3. 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

  4. 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...

  5. 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.

  6. 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 .

  7. Lipophilic extractives from several nonwoody lignocellulosic crops (flax, hemp, sisal, abaca) and their fate during alkaline pulping and TCF/ECF bleaching.

    Science.gov (United States)

    Marques, Gisela; del Río, José C; Gutiérrez, Ana

    2010-01-01

    The fate of lipophilic extractives from several nonwoody species (flax, hemp, sisal and abaca) used for the manufacturing of cellulose pulps, was studied during soda/anthraquinone (AQ) pulping and totally chorine free (TCF) and elemental chlorine free (ECF) bleaching. With this purpose, the lipophilic extracts from the raw materials and their unbleached and bleached industrial pulps, were analyzed by gas chromatography-mass spectrometry. Aldehydes, hydroxyfatty acids and esterified compounds such as ester waxes, sterol esters and alkylferulates strongly decreased after soda/AQ pulping while alkanes, alcohols, free sterols and sterol glycosides survived the cooking process. Among the lipophilic extractives that remained in the unbleached pulps, some amounts of free sterols were still present in the TCF pulps whereas they were practically absent in the ECF pulps. Sterol glycosides were also removed after both TCF and ECF bleaching. By contrast, saturated fatty acids, fatty alcohols and alkanes were still present in both bleached pulps.

  8. 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...

  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. Generalization Performance of Regularized Ranking With Multiscale Kernels.

    Science.gov (United States)

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

    2016-05-01

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

  11. 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.

  12. 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.

  13. Caracterização mecânica e térmica de compósitos de poli (cloreto de vinila reforçados com fibras de sisal Mechanical and thermal characterization of the polyvinyl chloride-sisal fibers composites

    Directory of Open Access Journals (Sweden)

    Gilson S. Martins

    2004-12-01

    Full Text Available Compósitos de PVC, plastificados com diferentes sistemas de plastificação e reforçados com fibras de sisal, foram processados em moinho de dois rolos. A influência do tipo e teor do plastificante, do comprimento e do teor das fibras nas propriedades dos compósitos obtidos foi estudada. Dois tipos de plastificantes foram usados, um líquido (do tipo poliéster e um sólido permanente (copolímero etileno/ acetato de vinila/ monóxido de carbono. As fibras usadas foram previamente lavadas com água a 80 °C por uma hora. Os compósitos, com fibras curtas aleatoriamente distribuídas, foram caracterizados através de ensaio mecânico de resistência à tração, microscopia eletrônica de varredura (MEV, e análises térmicas de calorimetria exploratória diferencial (DSC e análise por termogravimetria (TG. O comprimento ótimo de fibra obtido para os compósitos foi de 6 mm. O uso do plastificante sólido mostrou-se viável e promoveu uma maior molhabilidade da fibra pela matriz nos compósitos, principalmente para teores acima de 40 pcr. As análises térmicas mostraram que a substituição do plastificante líquido pelo plastificante sólido não afetou a estabilidade térmica das matrizes e dos compósitos.Composites consisting of flexible polyvinyl chloride (PVC, plasticized with two different types of plasticizers and reinforced with sisal fibers, were processed on a two-roll mixing mill. Two plasticizers were used, a liquid plasticizer (polyester and a permanent solid plasticizer (ethylene/ vinyl acetate/ carbon monoxide copolymer - Elvaloy® , to form two kinds of polymeric matrices. For each one of these matrices, the influence of plasticizers type, plasticizers content, size and quantity of sisal fibers in the composite properties has been studied. The fibers were washed with water at 80 °C during one hour. The composites with randomly distributed short fibers were characterized by mechanical analysis, scanning electron microscopy

  14. Analytic scattering kernels for neutron thermalization studies

    International Nuclear Information System (INIS)

    Sears, V.F.

    1990-01-01

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

  15. Quantized kernel least mean square algorithm.

    Science.gov (United States)

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

    2012-01-01

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

  16. Kernel-based tests for joint independence

    DEFF Research Database (Denmark)

    Pfister, Niklas; Bühlmann, Peter; Schölkopf, Bernhard

    2018-01-01

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

  17. Wilson Dslash Kernel From Lattice QCD Optimization

    Energy Technology Data Exchange (ETDEWEB)

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

    2015-07-01

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

  18. A Kernel for Protein Secondary Structure Prediction

    OpenAIRE

    Guermeur , Yann; Lifchitz , Alain; Vert , Régis

    2004-01-01

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

  19. Scalar contribution to the BFKL kernel

    International Nuclear Information System (INIS)

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

    2010-01-01

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

  20. Weighted Bergman Kernels for Logarithmic Weights

    Czech Academy of Sciences Publication Activity Database

    Engliš, Miroslav

    2010-01-01

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

  1. Heat kernels and zeta functions on fractals

    International Nuclear Information System (INIS)

    Dunne, Gerald V

    2012-01-01

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

  2. Tabled Execution in Scheme

    Energy Technology Data Exchange (ETDEWEB)

    Willcock, J J; Lumsdaine, A; Quinlan, D J

    2008-08-19

    Tabled execution is a generalization of memorization developed by the logic programming community. It not only saves results from tabled predicates, but also stores the set of currently active calls to them; tabled execution can thus provide meaningful semantics for programs that seemingly contain infinite recursions with the same arguments. In logic programming, tabled execution is used for many purposes, both for improving the efficiency of programs, and making tasks simpler and more direct to express than with normal logic programs. However, tabled execution is only infrequently applied in mainstream functional languages such as Scheme. We demonstrate an elegant implementation of tabled execution in Scheme, using a mix of continuation-passing style and mutable data. We also show the use of tabled execution in Scheme for a problem in formal language and automata theory, demonstrating that tabled execution can be a valuable tool for Scheme users.

  3. 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

  4. 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.

  5. 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.

  6. 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...

  7. 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.

  8. 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...

  9. Tutoring executives online

    DEFF Research Database (Denmark)

    Bignoux, Stephane; Sund, Kristian J.

    2018-01-01

    Studies of learning and student satisfaction in the context of online university programmes have largely neglected programmes catering specifically to business executives. Such executives have typically been away from higher education for a number of years, and have collected substantial practical...... experience in the subject matters they are taught. Their expectations in terms of both content and delivery may therefore be different from non-executive students. We explore perceptions of the quality of tutoring in the context of an online executive MBA programme through participant interviews. We find...... that in addition to some of the tutor behaviours already discussed in the literature, executive students look specifically for practical industry knowledge and experience in tutors, when judging how effective a tutor is. This has implications for both the recruitment and training of online executive MBA tutors....

  10. Tutoring Executives Online

    DEFF Research Database (Denmark)

    Bignoux, Stephane; Sund, Kristian J.

    2016-01-01

    Studies of learning and student satisfaction in the context of online university programs have largely neglected programs catering specifically to business executives. Such executives have typically been away from higher education for a number of years, and have collected substantial practical...... experience in the subject matters they are taught. Their expectations in terms of both content and delivery may therefore be different from non-executive students. We explore perceptions of the quality of tutoring in the context of an online executive MBA program through participant interviews. We find...... that in addition to some of the tutor behaviors already discussed in the literature, executive students look specifically for practical industry knowledge and experience in tutors, when judging how effective a tutor is. This has implications for both the recruitment and training of online executive MBA tutors....

  11. 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....

  12. 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

  13. Composição bromatológica do co-produto do desfibramento do sisal tratado com uréia Chemical composition of the sisal co-product treated with urea

    Directory of Open Access Journals (Sweden)

    Mário Marcos de Santana Faria

    2008-03-01

    Full Text Available O trabalho foi desenvolvido com o objetivo de avaliar os efeitos da amonização com uréia pecuária sobre a composição bromatológica do co-produto do processamento do sisal (Agave sisalana, Perrine em diferentes tempos de estocagens. Foram utilizados 300 kg do co-produto, igualmente distribuídos em 60 sacos de polietileno preto, onde se adicionou uréia nas concentrações de 0, 2, 4, 6 e 8% (base matéria seca - MS nos tempos de estocagem de 0, 2, 4 e 6 semanas. Determinaram-se os teores de matéria seca (MS, proteína bruta (PB, fibra em detergente neutro (FDN, fibra em detergente ácido (FDA e carboidratos não fibrosos (CNF. O consumo (CMS e a digestibilidade (DMS de MS foram obtidos por estimativa. O delineamento utilizado foi inteiramente casualizado (DIC, com 20 tratamentos e três repetições, seguindo o esquema fatorial 5 ´ 4 (cinco doses de uréia e quatro períodos de estocagem. A análise de variância revelou significância para o efeito da dose de uréia para as variáveis PB e MS. Para FDA, CNF e DMS, houve efeito significativo da interação dose de uréia ´ período de fermentação, ao passo que para FDN não houve significância de nenhum dos fatores. O teor de PB cresceu linearmente com a adição de uréia. Além disso, foi observado acréscimo nos teores de FDA, em função do decréscimo dos teores de CNF. As diminuições dos teores de CNF com o aumento dos níveis de uréia indicam que estes foram usados, provavelmente, para a síntese microbiana ou carreados com o efluente. Conclui-se que a adição de até 8% de uréia elevou os teores de PB e, com o aumento do tempo de estocagem, reduziu os teores de CNF e a DMS.The experiment was carried out to evaluate addition effects of five urea levels with four ammonization periods on Agave sisalana residue chemical composition in the different storage times. It was used 300 kg of this co-product, equally distributed in 60 black polyethylene bags, which urea was added

  14. Optimizing The Performance of Streaming Numerical Kernels On The IBM Blue Gene/P PowerPC 450

    KAUST Repository

    Malas, Tareq

    2011-07-01

    Several emerging petascale architectures use energy-efficient processors with vectorized computational units and in-order thread processing. On these architectures the sustained performance of streaming numerical kernels, ubiquitous in the solution of partial differential equations, represents a formidable challenge despite the regularity of memory access. Sophisticated optimization techniques beyond the capabilities of modern compilers are required to fully utilize the Central Processing Unit (CPU). The aim of the work presented here is to improve the performance of streaming numerical kernels on high performance architectures by developing efficient algorithms to utilize the vectorized floating point units. The importance of the development time demands the creation of tools to enable simple yet direct development in assembly to utilize the power-efficient cores featuring in-order execution and multiple-issue units. We implement several stencil kernels for a variety of cached memory scenarios using our Python instruction simulation and generation tool. Our technique simplifies the development of efficient assembly code for the IBM Blue Gene/P supercomputer\\'s PowerPC 450. This enables us to perform high-level design, construction, verification, and simulation on a subset of the CPU\\'s instruction set. Our framework has the capability to implement streaming numerical kernels on current and future high performance architectures. Finally, we present several automatically generated implementations, including a 27-point stencil achieving a 1.7x speedup over the best previously published results.

  15. 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.

  16. 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.

  17. 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.

  18. 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

  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. 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....

  1. Analysis of Advanced Fuel Kernel Technology

    International Nuclear Information System (INIS)

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

    2010-03-01

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

  2. Learning Rotation for Kernel Correlation Filter

    KAUST Repository

    Hamdi, Abdullah

    2017-08-11

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

  3. Research of Performance Linux Kernel File Systems

    Directory of Open Access Journals (Sweden)

    Andrey Vladimirovich Ostroukh

    2015-10-01

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

  4. Fixed kernel regression for voltammogram feature extraction

    International Nuclear Information System (INIS)

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

    2009-01-01

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

  5. Reciprocity relation for multichannel coupling kernels

    International Nuclear Information System (INIS)

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

    1981-01-01

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

  6. 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.

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

    DEFF Research Database (Denmark)

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

    2013-01-01

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

  8. Freqüência e severidade de corte das fôlhas do sisal(*. Influência sôbre o desenvolvimento das plantas, produção e características da fibra Frequency and severity of leaf cutting upon the growth, longevity and yield of the sisal plant

    Directory of Open Access Journals (Sweden)

    J. C. Medina

    1954-01-01

    Full Text Available O A. apresenta nêste artigo os resultados obtidos em uma experiência de corte das folhas do sisal (Agave sisalana Perrine, na qual se procurou comparar os efeitos da combinação de diversas freqüências e severidades de corte sobre o desenvolvimento, produção e longevidade da planta, assim como sôbre as características tecnológicas da fibra. Ficou provado que, com cortes freqüentes e severos, o ciclo de vida das plantas fica bastante prolongado, ao mesmo tempo que a produção de fibras por unidade de área decai sensivelmente, em conseqüência da redução de tamanho das fôlhas e menor conteúdo de fibras nas fôlhas das plantas submetidas a êsse sistema de corte. Os exames de laboratório demonstraram que, enquanto as características químicas das fibras não eram afetadas pelos sistemas de corte estudados, as características físicas eram, pelo contrário, sensivelmente afetados pelo corte freqüente e severo.This paper describes the results obtained with the sisal plant (Agave sisalana Perrine in a cutting trial located in the "Estação Experimental Central do Instituto Agronômico", at Campinas. This trial was designed to compare the effects of four cutting cycles, combined with three levels of severity of cutting, upon growth, longevity, and yield of the sisal plant, and on the quality of its fiber. The experiment was laid out in 4 randomized blocks of 4 plots, each plot having 3 sub-plots. Sub-plot size was of twelve plants spaced 2.5 x 1.5 m and arranged in two rows of 6 plants each. The results can be summarized as follows : (a The life cycle of the sisal plant was greatly influenced by the cutting method used. The greater the frequency and severity of cutting the slower was the growth of the plant and the longer it took to pole. (b Light cutting at six to twelve-month cycles was conducive to early poling, and the plant yielded fewer, though heavier, leaves. (c Heavy cutting at a three-month cycle reduced plant size

  9. Essays in Executive Compensation

    NARCIS (Netherlands)

    D. Zhang (Dan)

    2012-01-01

    textabstractThis dissertation focuses on how executive compensation is designed and its implications for corporate finance and government regulations. Chapter 2 analyzes several proposals to restrict CEO compensation and calibrates two models of executive compensation that describe how firms would

  10. 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.

  11. The Kernel Estimation in Biosystems Engineering

    Directory of Open Access Journals (Sweden)

    Esperanza Ayuga Téllez

    2008-04-01

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

  12. Consistent Valuation across Curves Using Pricing Kernels

    Directory of Open Access Journals (Sweden)

    Andrea Macrina

    2018-03-01

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

  13. Aligning Biomolecular Networks Using Modular Graph Kernels

    Science.gov (United States)

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

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

  14. Pareto-path multitask multiple kernel learning.

    Science.gov (United States)

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

    2015-01-01

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

  15. Formal truncations of connected kernel equations

    International Nuclear Information System (INIS)

    Dixon, R.M.

    1977-01-01

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

  16. Scientific Computing Kernels on the Cell Processor

    Energy Technology Data Exchange (ETDEWEB)

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

    2007-04-04

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

  17. Delimiting areas of endemism through kernel interpolation.

    Science.gov (United States)

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

    2015-01-01

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

  18. Delimiting areas of endemism through kernel interpolation.

    Directory of Open Access Journals (Sweden)

    Ubirajara Oliveira

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

  19. 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

  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.

  1. 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 ...

  2. 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

  3. 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...

  4. 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.

  5. 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.

  6. 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/

  7. 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...

  8. 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...

  9. 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 ...

  10. 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...

  11. 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 ...

  12. 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

  13. 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

  14. 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

  15. 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.

  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. 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.

  18. 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

  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. 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…

  1. 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

  2. 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…

  3. 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

  4. 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

  5. Ffuzz: Towards full system high coverage fuzz testing on binary executables.

    Directory of Open Access Journals (Sweden)

    Bin Zhang

    Full Text Available Bugs and vulnerabilities in binary executables threaten cyber security. Current discovery methods, like fuzz testing, symbolic execution and manual analysis, both have advantages and disadvantages when exercising the deeper code area in binary executables to find more bugs. In this paper, we designed and implemented a hybrid automatic bug finding tool-Ffuzz-on top of fuzz testing and selective symbolic execution. It targets full system software stack testing including both the user space and kernel space. Combining these two mainstream techniques enables us to achieve higher coverage and avoid getting stuck both in fuzz testing and symbolic execution. We also proposed two key optimizations to improve the efficiency of full system testing. We evaluated the efficiency and effectiveness of our method on real-world binary software and 844 memory corruption vulnerable programs in the Juliet test suite. The results show that Ffuzz can discover software bugs in the full system software stack effectively and efficiently.

  6. Ffuzz: Towards full system high coverage fuzz testing on binary executables.

    Science.gov (United States)

    Zhang, Bin; Ye, Jiaxi; Bi, Xing; Feng, Chao; Tang, Chaojing

    2018-01-01

    Bugs and vulnerabilities in binary executables threaten cyber security. Current discovery methods, like fuzz testing, symbolic execution and manual analysis, both have advantages and disadvantages when exercising the deeper code area in binary executables to find more bugs. In this paper, we designed and implemented a hybrid automatic bug finding tool-Ffuzz-on top of fuzz testing and selective symbolic execution. It targets full system software stack testing including both the user space and kernel space. Combining these two mainstream techniques enables us to achieve higher coverage and avoid getting stuck both in fuzz testing and symbolic execution. We also proposed two key optimizations to improve the efficiency of full system testing. We evaluated the efficiency and effectiveness of our method on real-world binary software and 844 memory corruption vulnerable programs in the Juliet test suite. The results show that Ffuzz can discover software bugs in the full system software stack effectively and efficiently.

  7. 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.

  8. 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.

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

    DEFF Research Database (Denmark)

    Feragen, Aasa; Hauberg, Søren

    2016-01-01

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

  10. 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.

  11. Study of alteration in the mechanical properties in hybrid nanocomposite of polypropylene/sisal fibers/mineral clay irradiated with gamma rays

    Energy Technology Data Exchange (ETDEWEB)

    Pereira, Nilson C.; Terence, Mauro C.; Miranda, Leila F., E-mail: nilpereira@mackenzie.com.b [Universidade Presbiteriana Mackenzie, Sao Paulo, SP (Brazil). Escola de Engenharia. Curso de Engenharia de Materiais

    2009-07-01

    A new material class formed with reinforced filler, hybrid of organic and inorganic materials provides the technological development of materials with modified properties. And among great numbers of properties that can be modified by presence of hybrid filler to stand out the tension resistance. Polymer shows behavior of tensions and deformation that are not related of simple form. The answer of this material at mechanicals solicitations depends of structural factors and externals variables. As structural factors can be, for example, molecular weight, ramifications and crosslink. As external variables can be, for example, temperature, time or velocity of deformation, kind of solicitation and others. This work was possible to verify as nanostructures materials behavior, mechanically, after were submitted gamma radiation. This work utilized as polymeric matrix, recycled polypropylene, and as hybrid filler, a mixture of montimorillonite mineral clay with natural sisal fibers. It is known that form to magnify the tensile resistance is increase the number of crosslink of principal chain for gamma radiation. After irradiation the polypropylene was crosslinked structures that are result recombination of radicals formed during process of irradiation. It.s known that radicals formed occur preferentially in the amorphous region of polymer. Considering that polymeric matrix polypropylene, without addition fillers suffer strong structural influence when irradiated, was possible verify change in the extension, tensile strength and also maxim tensile in rupture, when this matrix was incorporated with fillers hybrids. (author)

  12. Study of alteration in the mechanical properties in hybrid nanocomposite of polypropylene/sisal fibers/mineral clay irradiated with gamma rays

    International Nuclear Information System (INIS)

    Pereira, Nilson C.; Terence, Mauro C.; Miranda, Leila F.

    2009-01-01

    A new material class formed with reinforced filler, hybrid of organic and inorganic materials provides the technological development of materials with modified properties. And among great numbers of properties that can be modified by presence of hybrid filler to stand out the tension resistance. Polymer shows behavior of tensions and deformation that are not related of simple form. The answer of this material at mechanicals solicitations depends of structural factors and externals variables. As structural factors can be, for example, molecular weight, ramifications and crosslink. As external variables can be, for example, temperature, time or velocity of deformation, kind of solicitation and others. This work was possible to verify as nanostructures materials behavior, mechanically, after were submitted gamma radiation. This work utilized as polymeric matrix, recycled polypropylene, and as hybrid filler, a mixture of montimorillonite mineral clay with natural sisal fibers. It is known that form to magnify the tensile resistance is increase the number of crosslink of principal chain for gamma radiation. After irradiation the polypropylene was crosslinked structures that are result recombination of radicals formed during process of irradiation. It.s known that radicals formed occur preferentially in the amorphous region of polymer. Considering that polymeric matrix polypropylene, without addition fillers suffer strong structural influence when irradiated, was possible verify change in the extension, tensile strength and also maxim tensile in rupture, when this matrix was incorporated with fillers hybrids. (author)

  13. 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

  14. 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

  15. The Executive as Integrator.

    Science.gov (United States)

    Cohn, Hans M.

    1983-01-01

    Argues that although the executive has many tasks, he or she must view internal organizational integration as a primary task, making use of organizational charts, job descriptions, statements of goals and objectives, evaluations, and feedback devices. (RH)

  16. Learning molecular energies using localized graph kernels

    Science.gov (United States)

    Ferré, Grégoire; Haut, Terry; Barros, Kipton

    2017-03-01

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

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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...

  7. 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.

  8. 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.

  9. 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...

  10. 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.

  11. 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.

  12. Educating Executive Function

    Science.gov (United States)

    Blair, Clancy

    2016-01-01

    Executive functions are thinking skills that assist with reasoning, planning, problem solving, and managing one’s life. The brain areas that underlie these skills are interconnected with and influenced by activity in many different brain areas, some of which are associated with emotion and stress. One consequence of the stress-specific connections is that executive functions, which help us to organize our thinking, tend to be disrupted when stimulation is too high and we are stressed out, or too low when we are bored and lethargic. Given their central role in reasoning and also in managing stress and emotion, scientists have conducted studies, primarily with adults, to determine whether executive functions can be improved by training. By and large, results have shown that they can be, in part through computer-based videogame-like activities. Evidence of wider, more general benefits from such computer-based training, however, is mixed. Accordingly, scientists have reasoned that training will have wider benefits if it is implemented early, with very young children as the neural circuitry of executive functions is developing, and that it will be most effective if embedded in children’s everyday activities. Evidence produced by this research, however, is also mixed. In sum, much remains to be learned about executive function training. Without question, however, continued research on this important topic will yield valuable information about cognitive development. PMID:27906522

  13. 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

  14. 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

  15. Estudo Etnobotânico de plantas medicinais utilizadas pela Comunidade do Sisal no município de Catu, Bahia, Brasil

    Directory of Open Access Journals (Sweden)

    F.R.G Neto

    2014-12-01

    Full Text Available A utilização de plantas medicinais é instintiva nos animais, visto que alguns destes buscam raízes, cascas, folhas ou frutos na tentativa de resolver seus males. O homem, por sua vez, aprendeu a utilizar estas informações empiricamente para fazer uso destes vegetais. A medicina popular é uma importante alternativa, provavelmente, a mais usada para a cura de doenças por parte de populações indígenas, quilombolas ou rurais. A Etnobotânica, por sua vez, encarrega-se de estudar e interpretar essa relação dos homens com o mundo vegetal. Devido ao seu grande potencial biológico e cultural, o Brasil apresenta uma infinidade de conhecimentos tradicionais e espécies vegetais importantes, o que torna esse país uma grande fonte de pesquisa na área. Visando avaliar o conhecimento tradicional da população rural do Sisal, Catu/Bahia, relacionado ao uso de plantas medicinais, este trabalho iniciou-se em julho de 2009, constando de entrevistas semi-estruturadas e estruturadas, gravações, registros fotográficos, coleta do material botânico indicado nas entrevistas com os informantes, tratamento do material coletado e incorporação ao Herbário da Universidade do Estado da Bahia (HUNEB. Foram identificadas e coletadas 54 espécies distribuídas em 46 gêneros e 28 famílias, sendo Lamiacaeae e Asteraceae as mais representativas. A maioria das plantas é constituída de ervas e cultivada nos quintais dos moradores. O estudo revelou que a comunidade apresenta uma medicina popular bastante rica, com grande diversidade de espécies vegetais e usos por parte da população.

  16. 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.

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

    African Journals Online (AJOL)

    SERVER

    2008-04-17

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

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

    African Journals Online (AJOL)

    STORAGESEVER

    2009-01-05

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

  19. 3-D waveform tomography sensitivity kernels for anisotropic media

    KAUST Repository

    Djebbi, Ramzi; Alkhalifah, Tariq Ali

    2014-01-01

    The complications in anisotropic multi-parameter inversion lie in the trade-off between the different anisotropy parameters. We compute the tomographic waveform sensitivity kernels for a VTI acoustic medium perturbation as a tool to investigate

  20. 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

  1. 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...

  2. MIV Project: Executive Summary

    DEFF Research Database (Denmark)

    Ravazzotti, Mariolina T.; Jørgensen, John Leif; Neefs, Marc

    1997-01-01

    Under the ESA contract #11453/95/NL/JG(SC), aiming at assessing the feasibility of Rendez-vous and docking of unmanned spacecrafts, a reference mission scenario was defined. This report gives an executive summary of the achievements and results from the project.......Under the ESA contract #11453/95/NL/JG(SC), aiming at assessing the feasibility of Rendez-vous and docking of unmanned spacecrafts, a reference mission scenario was defined. This report gives an executive summary of the achievements and results from the project....

  3. 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

  4. On Improving Convergence Rates for Nonnegative Kernel Density Estimators

    OpenAIRE

    Terrell, George R.; Scott, David W.

    1980-01-01

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

  5. 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...

  6. 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

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

    Science.gov (United States)

    1997-10-01

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

  8. Salus: Kernel Support for Secure Process Compartments

    Directory of Open Access Journals (Sweden)

    Raoul Strackx

    2015-01-01

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

  9. Local Kernel for Brains Classification in Schizophrenia

    Science.gov (United States)

    Castellani, U.; Rossato, E.; Murino, V.; Bellani, M.; Rambaldelli, G.; Tansella, M.; Brambilla, P.

    In this paper a novel framework for brain classification is proposed in the context of mental health research. A learning by example method is introduced by combining local measurements with non linear Support Vector Machine. Instead of considering a voxel-by-voxel comparison between patients and controls, we focus on landmark points which are characterized by local region descriptors, namely Scale Invariance Feature Transform (SIFT). Then, matching is obtained by introducing the local kernel for which the samples are represented by unordered set of features. Moreover, a new weighting approach is proposed to take into account the discriminative relevance of the detected groups of features. Experiments have been performed including a set of 54 patients with schizophrenia and 54 normal controls on which region of interest (ROI) have been manually traced by experts. Preliminary results on Dorso-lateral PreFrontal Cortex (DLPFC) region are promising since up to 75% of successful classification rate has been obtained with this technique and the performance has improved up to 85% when the subjects have been stratified by sex.

  10. KERNEL MAD ALGORITHM FOR RELATIVE RADIOMETRIC NORMALIZATION

    Directory of Open Access Journals (Sweden)

    Y. Bai

    2016-06-01

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

  11. Construction and evaluation of normalized cDNA libraries enriched with full-length sequences for rapid discovery of new genes from Sisal (Agave sisalana Perr.) different developmental stages.

    Science.gov (United States)

    Zhou, Wen-Zhao; Zhang, Yan-Mei; Lu, Jun-Ying; Li, Jun-Feng

    2012-10-12

    To provide a resource of sisal-specific expressed sequence data and facilitate this powerful approach in new gene research, the preparation of normalized cDNA libraries enriched with full-length sequences is necessary. Four libraries were produced with RNA pooled from Agave sisalana multiple tissues to increase efficiency of normalization and maximize the number of independent genes by SMART™ method and the duplex-specific nuclease (DSN). This procedure kept the proportion of full-length cDNAs in the subtracted/normalized libraries and dramatically enhanced the discovery of new genes. Sequencing of 3875 cDNA clones of libraries revealed 3320 unigenes with an average insert length about 1.2 kb, indicating that the non-redundancy of libraries was about 85.7%. These unigene functions were predicted by comparing their sequences to functional domain databases and extensively annotated with Gene Ontology (GO) terms. Comparative analysis of sisal unigenes and other plant genomes revealed that four putative MADS-box genes and knotted-like homeobox (knox) gene were obtained from a total of 1162 full-length transcripts. Furthermore, real-time PCR showed that the characteristics of their transcripts mainly depended on the tight expression regulation of a number of genes during the leaf and flower development. Analysis of individual library sequence data indicated that the pooled-tissue approach was highly effective in discovering new genes and preparing libraries for efficient deep sequencing.

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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

  17. 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.

  18. Data-driven execution of fast multipole methods

    KAUST Repository

    Ltaief, Hatem

    2013-09-17

    Fast multipole methods (FMMs) have O (N) complexity, are compute bound, and require very little synchronization, which makes them a favorable algorithm on next-generation supercomputers. Their most common application is to accelerate N-body problems, but they can also be used to solve boundary integral equations. When the particle distribution is irregular and the tree structure is adaptive, load balancing becomes a non-trivial question. A common strategy for load balancing FMMs is to use the work load from the previous step as weights to statically repartition the next step. The authors discuss in the paper another approach based on data-driven execution to efficiently tackle this challenging load balancing problem. The core idea consists of breaking the most time-consuming stages of the FMMs into smaller tasks. The algorithm can then be represented as a directed acyclic graph where nodes represent tasks and edges represent dependencies among them. The execution of the algorithm is performed by asynchronously scheduling the tasks using the queueing and runtime for kernels runtime environment, in a way such that data dependencies are not violated for numerical correctness purposes. This asynchronous scheduling results in an out-of-order execution. The performance results of the data-driven FMM execution outperform the previous strategy and show linear speedup on a quad-socket quad-core Intel Xeon system.Copyright © 2013 John Wiley & Sons, Ltd. Copyright © 2013 John Wiley & Sons, Ltd.

  19. Executions in The Bahamas

    Directory of Open Access Journals (Sweden)

    Lofquist, William Steele

    2010-01-01

    Full Text Available The stories of those who have been executed in the Bahamas are heretofore untold. In telling these stories and in linking them to the changing course of Bahamian history, the present research adds an important dimension to our understanding of Bahamian history and politics. The major theme of this effort is that the changing practice of the death penalty is much more than a consequence of changes in crime. The use of the death penalty parallels the changing interests of colonial rulers, the changing practice of slavery, and the changing role of the Bahamas in colonial and regional affairs. Four distinctive eras of death penalty practice can be identified: (1 the slave era, where executions and commutations were used liberally and with a clear racial patterning; (2 a long era of stable colonialism, a period of marginalization and few executions; (3 an era of unstable colonialism characterized by intensive and efficient use of the death penalty; and (4 the current independence era of high murder rates and equally high impediments to the use of executions.

  20. Executive functions in synesthesia

    NARCIS (Netherlands)

    Rouw, Romke; van Driel, Joram; Knip, Koen; Richard Ridderinkhof, K.

    2013-01-01

    In grapheme-color synesthesia, a number or letter can evoke two different and possibly conflicting (real and synesthetic) color sensations at the same time. In this study, we investigate the relationship between synesthesia and executive control functions. First, no general skill differences were

  1. School Executive Website Study

    Science.gov (United States)

    Thiede, Robert

    2009-01-01

    The School Executive Website will be a one-stop, online site for officials who are looking for educational data, best practices, product reviews, school documents, professional opinions, and/or job-related networking. The format of the website is designed in certain sections similar to other current and popular websites, such as Angie's List.com,…

  2. Healthcare. Executive Summary

    Science.gov (United States)

    Carnevale, Anthony P.; Smith, Nicole; Gulish, Artem; Beach, Bennett H.

    2012-01-01

    This executive summary highlights several findings about healthcare. These are: (1) Healthcare is 18 percent of the U.S. economy, twice as high as in other countries; (2) There are two labor markets in healthcare: high-skill, high-wage professional and technical jobs and low-skill, low-wage support jobs; (3) Demand for postsecondary education in…

  3. EXECUTIVE FUNCTIONING IN SCHIZOPHRENIA

    Directory of Open Access Journals (Sweden)

    Gricel eOrellana

    2013-06-01

    Full Text Available The executive function (EF is a set of abilities, which allows us to invoke voluntary control of our behavioral responses. These functions enable human beings to develop and carry out plans, make up analogies, obey social rules, solve problems, adapt to unexpected circumstances, do many tasks simultaneously and locate episodes in time and place. EF includes divided attention and sustained attention, working memory, set-shifting, flexibility, planning and the regulation of goal directed behavior and can be defined as a brain function underlying the human faculty to act or think not only in reaction to external events but also in relation with internal goals and states. EF is mostly associated with dorsolateral prefrontal cortex (PFC. Besides EF, PFC is involved in self-regulation of behavior, i.e. the ability to regulate behavior according to internal goals and constraints, particularly in less structured situations. Self-regulation of behavior is subtended by ventral medial /orbital PFC. Impairment of EF is one of the most commonly observed deficits in schizophrenia through the various disease stages. Impairment in tasks measuring conceptualization, planning, cognitive flexibility, verbal fluency, ability to solve complex problems and working memory occur in schizophrenia. Disorders detected by executive tests are consistent with evidence from functional neuroimaging, which have shown PFC dysfunction in patients while performing these kinds of tasks. Schizophrenics also exhibit deficit in odor identifying, decision-making and self-regulation of behavior suggesting dysfunction of the orbital PFC. However, impairment in executive tests is explained by dysfunction of prefronto-striato-thalamic, prefronto-parietal and prefronto-temporal neural networks mainly. Disorders in executive functions may be considered central facts with respect to schizophrenia and it has been suggested that negative symptoms may be explained by that executive dysfunction.

  4. Educating executive function.

    Science.gov (United States)

    Blair, Clancy

    2017-01-01

    Executive functions are thinking skills that assist with reasoning, planning, problem solving, and managing one's life. The brain areas that underlie these skills are interconnected with and influenced by activity in many different brain areas, some of which are associated with emotion and stress. One consequence of the stress-specific connections is that executive functions, which help us to organize our thinking, tend to be disrupted when stimulation is too high and we are stressed out, or too low when we are bored and lethargic. Given their central role in reasoning and also in managing stress and emotion, scientists have conducted studies, primarily with adults, to determine whether executive functions can be improved by training. By and large, results have shown that they can be, in part through computer-based videogame-like activities. Evidence of wider, more general benefits from such computer-based training, however, is mixed. Accordingly, scientists have reasoned that training will have wider benefits if it is implemented early, with very young children as the neural circuitry of executive functions is developing, and that it will be most effective if embedded in children's everyday activities. Evidence produced by this research, however, is also mixed. In sum, much remains to be learned about executive function training. Without question, however, continued research on this important topic will yield valuable information about cognitive development. WIREs Cogn Sci 2017, 8:e1403. doi: 10.1002/wcs.1403 For further resources related to this article, please visit the WIREs website. © 2016 Wiley Periodicals, Inc.

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

    NARCIS (Netherlands)

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

    2016-01-01

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

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

    DEFF Research Database (Denmark)

    Petersen, Annette

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

  7. AVALIAÇÃO DO DESEMPENHO TÉRMICO DE BEZERREIROS COM ECO-FORRO DE PARTÍCULAS DE MADEIRA E FIBRA DE SISAL / EVALUATION OF THE THERMAL PERFORMANCE OF CALVES’ SHELTER WITH ECO-LINING OF WOOD PARTICLES AND SISAL FIBER

    Directory of Open Access Journals (Sweden)

    M. R. Cabral

    2017-09-01

    Full Text Available Este trabalho teve como objetivo avaliar o potencial de utilização do eco-forro constituído de painéis de partículas de madeira de maravalha de Pinus spp. e fibras de sisal aglutinados com resina poliuretana à base de óleo de mamona (PU-mamona quando aplicados em bezerreiros cobertos com telhas de fibrocimento. Nesse estudo foi aferida a temperatura interna do bezerreiro, temperatura de globo negro, umidade relativa, no período da primavera, durante 21 dias e determinados os índices de conforto ITGU, ITU e CTR. Os resultados obtidos indicaram que a temperatura de globo negro e os índices de conforto ITGU e CTR dos bezerreiros com eco-forro foi inferior àquelas aferidas em bezerreiros desprovido de forro. As imagens termográficas comprovaram que o eco-forro diminuí a transferência de calor e radiação para o interior da instalação.

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

    Directory of Open Access Journals (Sweden)

    Yan Song

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

  9. Protein fold recognition using geometric kernel data fusion.

    Science.gov (United States)

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

    2014-07-01

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

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

    International Nuclear Information System (INIS)

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

    1975-01-01

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

  11. Unsupervised multiple kernel learning for heterogeneous data integration.

    Science.gov (United States)

    Mariette, Jérôme; Villa-Vialaneix, Nathalie

    2018-03-15

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

  12. 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)

  13. What executives should remember.

    Science.gov (United States)

    Drucker, Peter F

    2006-02-01

    In more than 30 essays for Harvard Business Review, Peter Drucker (1909-2005) urged readers to take on the hard work of thinking--always combined, he insisted, with decisive action. He closely analyzed the phenomenon of knowledge work--the growing call for employees who use their minds rather than their hands--and explained how it challenged the conventional wisdom about the way organizations should be run. He was intrigued by employees who knew more about certain subjects than their bosses or colleagues but who still had to cooperate with others in a large organization. As the business world matured in the second half of the twentieth century, executives came to think that they knew how to run companies--and Drucker took it upon himself to poke holes in their assumptions, lest organizations become stale. But he did so sympathetically, operating from the premise that his readers were intelligent, hardworking people of goodwill. Well suited to HBR's format of practical, idea-based essays for executives, his clear-eyed, humanistic writing enriched the magazine time and again. This article is a compilation of the savviest management advice Drucker offered HBR readers over the years--in short, his greatest hits. It revisits the following insightful, influential contributions: "The Theory of the Business" (September-October 1994), "Managing for Business Effectiveness" (May-June 1963), "What Business Can Learn from Nonprofits" (July-August 1989), "The New Society of Organizations" (September-October 1992), "The Information Executives Truly Need" (January-February 1995), "Managing Oneself" (March-April 1999 republished January 2005), "They're Not Employees, They're People" (February 2002), "What Makes an Effective Executive" (June 2004).

  14. INTERNATIONALIZATION OF CHINESE EXECUTIVES

    OpenAIRE

    Lingfang Fayol-Song

    2012-01-01

    Over the last two decades, Chinese nationals have increasingly been employed by multinational companies (MNCs) operating in China taking positions previously occupied by foreign expatriates from investor countries. The development of local managers has therefore become crucial in the field of human resource management because the success of these companies depends greatly upon the ability and competence of their executive management class. The present paper addresses the issue of how to devel...

  15. Concurrent Models for Object Execution

    OpenAIRE

    Diertens, Bob

    2012-01-01

    In previous work we developed a framework of computational models for the concurrent execution of functions on different levels of abstraction. It shows that the traditional sequential execution of function is just a possible implementation of an abstract computational model that allows for the concurrent execution of functions. We use this framework as base for the development of abstract computational models that allow for the concurrent execution of objects.

  16. Executive Energy Leadership Academy | NREL

    Science.gov (United States)

    Executive Energy Leadership Academy Executive Energy Leadership Academy NREL's Executive Energy Leadership Academy is a nationally renowned program that provides non-technical business, governmental, and foreground. Leadership Program The Leadership Program is designed for community and industry leaders with an

  17. 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.

  18. 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.

  19. 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.

  20. 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)

  1. 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

  2. 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.

  3. 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.

  4. Surf Zone Sediment Size Variation, Morphodynamics, and Hydrodynamics During Sea/Land Breeze and El-Norte Storm in Sisal, Yucatan, Mexico

    Science.gov (United States)

    Alrushaid, T.; Figlus, J.; Torres-Freyermuth, A.; Puleo, J. A.; Dellapenna, T. M.

    2016-02-01

    Coastlines around the world are under ever-increasing pressure due to population trends, commerce, and geophysical processes like tropical storms and erosion. This multi-institutional field campaign was conducted to improve our understanding of complex nearshore processes under varying forcing conditions on a microtidal, sandy beach located in Sisal, Yucatan from 3/27 to 4/12/2014. Hydrodynamics, morphodynamics, and textural variability were investigated during: (1) a cold front event (referred to as El-Norte); (2) land breeze (LB); and (3) sea breeze (SB). The instrumentation layout included three surf/swash zone cross-shore transects where water elevation, suspended sediment concentration, bed load, and current velocities were measured, as well as several offshore ADCP for hydrodynamic measurements. TKE, τb, ɛ and were estimated using the data obtained from surf zone ADV. In addition, Hs and Tsin the surf zone were computed using measurements from ADV pressure sensors, while a separate pressure transducer was used to obtain water free-surface elevation within the swash zone. During SB cycles the study area experienced wind velocities reaching up to 12ms-1, and 15ms-1 during El-Norte. Elevated wind stress during El-Norte resulted in Hs of 1.5m and 0.6m in water depths of 10m and 0.4m, respectively. Surface sediment grab samples during SB/LB cycles showed that the swash zone had a moderately well sorted distribution with a mean grain size of 0.5mm, while poor sorting and a mean grain size of 0.7mm were found during El-Norte. Additionally, measured bathymetry data showed evidence for offshore sandbar migration during strong offshore currents (0.4ms-1) during El-Norte, while onshore sandbar migration was evident during SB/LB periods (0.3ms-1 and 0.1ms-1, respectively). This study highlights how different weather forcing conditions affect hydrodynamics, morphodynamics, and textural variability on a sandy beach. Aside from furthering our knowledge on these complex

  5. 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.

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

    DEFF Research Database (Denmark)

    Christoffersen, Peter; Heston, Steven; Jacobs, Kris

    2013-01-01

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

  7. 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.

  8. 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.

  9. Rational kernels for Arabic Root Extraction and Text Classification

    Directory of Open Access Journals (Sweden)

    Attia Nehar

    2016-04-01

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

  10. 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.

  11. 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.

  12. 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

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

    Directory of Open Access Journals (Sweden)

    Diego Peluffo-Ordóñez

    2017-08-01

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

  14. 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

  15. 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

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

    Directory of Open Access Journals (Sweden)

    Reza Mokhtari

    2012-01-01

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

  17. Kernel and divergence techniques in high energy physics separations

    Science.gov (United States)

    Bouř, Petr; Kůs, Václav; Franc, Jiří

    2017-10-01

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

  18. Rebootless Linux Kernel Patching with Ksplice Uptrack at BNL

    International Nuclear Information System (INIS)

    Hollowell, Christopher; Pryor, James; Smith, Jason

    2012-01-01

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

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

    DEFF Research Database (Denmark)

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

    2015-01-01

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

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

    DEFF Research Database (Denmark)

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

    2006-01-01

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

  1. China's SOE Executives

    DEFF Research Database (Denmark)

    Brødsgaard, Kjeld Erik; Hubbard, Paul; Cai, Guilong

    2017-01-01

    Drawing on a database tracking the career of 1,250 top Chinese executives from 1,084 publicly-listed state-owned enterprises (SOEs), this article analyzes differences in career incentives for subsidiaries controlled by the central government compared to those controlled by local governments. It a...... of promotion. However, in the case of central SOE subsidiaries, leaders are more likely to be promoted based on financial performance. For both central and local 'direct' SOE groups age is a significant negative factor for promotion, whereas tenure is a significant positive factor....

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

    Directory of Open Access Journals (Sweden)

    Chuang Lin

    2015-01-01

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

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

    Science.gov (United States)

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

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

    Directory of Open Access Journals (Sweden)

    Hailun Wang

    2017-01-01

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

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

    International Nuclear Information System (INIS)

    Damunir; Sri Rinanti Susilowati; Ariyani Kusuma Dewi

    2015-01-01

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

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

    International Nuclear Information System (INIS)

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

    1983-01-01

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

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

    International Nuclear Information System (INIS)

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

    2007-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Hjalmar Rosengren

    2006-12-01

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

  9. 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.

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

    NARCIS (Netherlands)

    Jansen, P.G.; Wygerink, Emiel

    1996-01-01

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

  11. MARMER, a flexible point-kernel shielding code

    International Nuclear Information System (INIS)

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

    1990-01-01

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

  12. MARMER, a flexible point-kernel shielding code

    Energy Technology Data Exchange (ETDEWEB)

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

    1990-01-01

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

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

    African Journals Online (AJOL)

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

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

    Science.gov (United States)

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

    2014-06-15

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

  15. Notes on a storage manager for the Clouds kernel

    Science.gov (United States)

    Pitts, David V.; Spafford, Eugene H.

    1986-01-01

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

  16. On Convergence of Kernel Density Estimates in Particle Filtering

    Czech Academy of Sciences Publication Activity Database

    Coufal, David

    2016-01-01

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

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

    African Journals Online (AJOL)

    Gwla10

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

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

    African Journals Online (AJOL)

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

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

    International Nuclear Information System (INIS)

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

    2008-01-01

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

  20. Deep sequencing of RNA from ancient maize kernels

    DEFF Research Database (Denmark)

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

    2013-01-01

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

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

    African Journals Online (AJOL)

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

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

    NARCIS (Netherlands)

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

    2000-01-01

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

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

    African Journals Online (AJOL)

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

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

    Science.gov (United States)

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

    2011-07-28

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

  5. Fractional quantum integral operator with general kernels and applications

    Science.gov (United States)

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

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

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

    Directory of Open Access Journals (Sweden)

    Caroline M. Gevaert

    2016-12-01

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

  7. Corruption clubs: empirical evidence from kernel density estimates

    NARCIS (Netherlands)

    Herzfeld, T.; Weiss, Ch.

    2007-01-01

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

  8. A compact kernel for the calculus of inductive constructions

    Indian Academy of Sciences (India)

    CIC) implemented inside the Matita Interactive Theorem Prover. The design of the new kernel has been completely revisited since the first release, resulting in a remarkably compact implementation of about 2300 lines of OCaml code. The work ...

  9. Finite Gaussian Mixture Approximations to Analytically Intractable Density Kernels

    DEFF Research Database (Denmark)

    Khorunzhina, Natalia; Richard, Jean-Francois

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

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

    African Journals Online (AJOL)

    GREGORY

    2011-12-16

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

  11. Improved Interpolation Kernels for Super-resolution Algorithms

    DEFF Research Database (Denmark)

    Rasti, Pejman; Orlova, Olga; Tamberg, Gert

    2016-01-01

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

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

    African Journals Online (AJOL)

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

  13. Controller synthesis for L2 behaviors using rational kernel representations

    NARCIS (Netherlands)

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

    2008-01-01

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

  14. Recent sea level change analysed with kernel EOF

    DEFF Research Database (Denmark)

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

    2009-01-01

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

  15. Polynomial kernels for deletion to classes of acyclic digraphs

    NARCIS (Netherlands)

    Mnich, Matthias; van Leeuwen, E.J.

    2017-01-01

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

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

    African Journals Online (AJOL)

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

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

    African Journals Online (AJOL)

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

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

    International Nuclear Information System (INIS)

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

    1994-01-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2008-06-24

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

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

    Science.gov (United States)

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

    2015-10-01

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

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

    Science.gov (United States)

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

    2012-01-01

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

  2. Structured Kernel Subspace Learning for Autonomous Robot Navigation.

    Science.gov (United States)

    Kim, Eunwoo; Choi, Sungjoon; Oh, Songhwai

    2018-02-14

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

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

    NARCIS (Netherlands)

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

    2017-01-01

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

  4. Single pass kernel k-means clustering method

    Indian Academy of Sciences (India)

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

  5. Szegö Kernels and Asymptotic Expansions for Legendre Polynomials

    Directory of Open Access Journals (Sweden)

    Roberto Paoletti

    2017-01-01

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

  6. Magnetic resonance imaging of single rice kernels during cooking

    NARCIS (Netherlands)

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

    2004-01-01

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

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

    KAUST Repository

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

    2013-01-01

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

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

    DEFF Research Database (Denmark)

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

    2011-01-01

    There is significant current interest in decoding mental states from neuroimages. In this context kernel methods, e.g., support vector machines (SVM) are frequently adopted to learn statistical relations between patterns of brain activation and experimental conditions. In this paper we focus on v...

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

    African Journals Online (AJOL)

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

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

    DEFF Research Database (Denmark)

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

    2014-01-01

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

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

    Science.gov (United States)

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

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

    Science.gov (United States)

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

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

    DEFF Research Database (Denmark)

    Christiansen, Asger Nyman; Carstensen, Jens Michael

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

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

    International Nuclear Information System (INIS)

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

    1975-08-01

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

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

    Science.gov (United States)

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

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

    Science.gov (United States)

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

  17. Build and Execute Environment

    Energy Technology Data Exchange (ETDEWEB)

    2017-04-21

    At exascale, the challenge becomes to develop applications that run at scale and use exascale platforms reliably, efficiently, and flexibly. Workflows become much more complex because they must seamlessly integrate simulation and data analytics. They must include down-sampling, post-processing, feature extraction, and visualization. Power and data transfer limitations require these analysis tasks to be run in-situ or in-transit. We expect successful workflows will comprise multiple linked simulations along with tens of analysis routines. Users will have limited development time at scale and, therefore, must have rich tools to develop, debug, test, and deploy applications. At this scale, successful workflows will compose linked computations from an assortment of reliable, well-defined computation elements, ones that can come and go as required, based on the needs of the workflow over time. We propose a novel framework that utilizes both virtual machines (VMs) and software containers to create a workflow system that establishes a uniform build and execution environment (BEE) beyond the capabilities of current systems. In this environment, applications will run reliably and repeatably across heterogeneous hardware and software. Containers, both commercial (Docker and Rocket) and open-source (LXC and LXD), define a runtime that isolates all software dependencies from the machine operating system. Workflows may contain multiple containers that run different operating systems, different software, and even different versions of the same software. We will run containers in open-source virtual machines (KVM) and emulators (QEMU) so that workflows run on any machine entirely in user-space. On this platform of containers and virtual machines, we will deliver workflow software that provides services, including repeatable execution, provenance, checkpointing, and future proofing. We will capture provenance about how containers were launched and how they interact to annotate

  18. Guidelines for Automation Project Execution

    OpenAIRE

    Takkinen, Heidi

    2011-01-01

    The purpose of this Master’s thesis was to create instructions for executing an automation project. Sarlin Oy Ab needed directions on how to execute an automation project. Sarlin is starting up a new business area offering total project solutions for customers. Sarlin focuses on small and minor automation projects on domestic markets. The thesis represents issues related to project execution starting from the theory of the project to its kick-off and termination. Site work is one importan...

  19. Editor, Executive and Entrepreneur

    DEFF Research Database (Denmark)

    Bøe-Lillegraven, Tor; Wilberg, Erik

    2016-01-01

    To survive in today’s increasingly complex business environments, firms must embrace strategic paradoxes: contradictory yet interrelated objectives that persist over time. This can be one of toughest of all leadership challenges, as managers must accept inconsistency and contradictions....... In this article, we develop and empirically test a set of hypotheses related to ambidexterity, a key example of a paradoxical strategy. Through our analysis of data from a survey of executive leaders, we find a link between organizational ambidexterity and strategic planning, suggesting that the complexities...... of navigating in explorative ventures require more explicit strategy work than the old certainties of a legacy business. We identify and discuss inherent paradoxes and their implications for firm performance in 22 industry-specific strategies, where empirical industry data shows a pattern of conflict between...

  20. Executable Use Cases

    DEFF Research Database (Denmark)

    Jørgensen, Jens Bæk; Bossen, Claus

    2004-01-01

    and into the work processes they're to support. However, prototypes typically provide an explicit representation only of the system itself. Executable use cases, on the other hand, can also describe the environment. EUCs are designed to: narrow the gap between informal ideas about requirements and the formalization...... modeling. This article describes a case study in which developers used EUCs to prototype an electronic patient record system for hospitals in Aarhus, Denmark.......Many software experts argue that when we design a new system, we should create an explicit description of the environment in which the proposed system is to be used. The argument becomes crucial for pervasive computing, which aims to tightly integrate systems into their environments...