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Sample records for anulus fibrosus predicted

  1. Changes with Age and the Effect of Recombinant Human BMP-2 on Proteoglycan and Collagen Gene Expression in Rabbit Anulus Fibrosus Cells

    Institute of Scientific and Technical Information of China (English)

    Qin-Ming FEI; Xiao-Xing JIANG; Tong-Yi CHEN; Jun LI; Hideki MURAKAMI; Kai-Jow TSAI; William C. HUTTON

    2006-01-01

    In order to compare the difference between young and old intervertebral disc cells and their responsiveness to recombinant human bone morphogenetic protein-2 (rhBMP-2), disc cells were isolated from the anulus fibrosus (AF) and transition zones of lumbar discs from eight old and eight young New Zealand white rabbits. Compared with the cells from the young rabbits, cells from old rabbits respond less to rhBMP-2 treatment with respect to sulfated-glycosaminoglycan (sGAG) synthesis and aggrecan gene expression. But in collagen Ⅰ and collagen Ⅱ gene expressions, there are no significant differences between the old and the young. When comparing sGAG content, aggrecan, and collagen Ⅱ gene expression of the old AF cells after rhBMP-2 treatment with that of the young AF cells without rhBMP-2 treatment, the old AF cells with rhBMP-2 treatment have a greater capacity to synthesize sGAG bound in the cells and to release sGAG in the media, as well as to express aggrecan and collagen Ⅱ gene. It can be concluded that old AF cells after rhBMP-2 treatment have a greater capacity to synthesize sGAG and express aggrecan and collagen Ⅱ as compared to young AF cells without rhBMP-2 treatment. Thus rhBMP-2 can reverse the decline in the anabolic capacity of the disc cells with ageing. So it seems that rhBMP-2 has potential for use as an agent to retard a key component of disc degeneration and loss of disc matrix.

  2. Identification of rabbit annulus fibrosus-derived stem cells.

    Directory of Open Access Journals (Sweden)

    Chen Liu

    Full Text Available Annulus fibrosus (AF injuries can lead to substantial deterioration of intervertebral disc (IVD which characterizes degenerative disc disease (DDD. However, treatments for AF repair/regeneration remain challenging due to the intrinsic heterogeneity of AF tissue at cellular, biochemical, and biomechanical levels. In this study, we isolated and characterized a sub-population of cells from rabbit AF tissue which formed colonies in vitro and could self-renew. These cells showed gene expression of typical surface antigen molecules characterizing mesenchymal stem cells (MSCs, including CD29, CD44, and CD166. Meanwhile, they did not express negative markers of MSCs such as CD4, CD8, and CD14. They also expressed Oct-4, nucleostemin, and SSEA-4 proteins. Upon induced differentiation they showed typical osteogenesis, chondrogenesis, and adipogenesis potential. Together, these AF-derived colony-forming cells possessed clonogenicity, self-renewal, and multi-potential differentiation capability, the three criteria characterizing MSCs. Such AF-derived stem cells may potentially be an ideal candidate for DDD treatments using cell therapies or tissue engineering approaches.

  3. Modelling the failure precursor mechanism of lamellar fibrous tissues, example of the annulus fibrosus.

    Science.gov (United States)

    Mengoni, Marlène; Jones, Alison C; Wilcox, Ruth K

    2016-10-01

    The aims of this study were to assess the damage and failure strengths of lamellar fibrous tissues, such as the anterior annulus fibrosus (AF), and to develop a mathematical model of damage propagation of the lamellae and inter-lamellar connections. This level of modelling is needed to accurately predict the effect of damage and failure induced by trauma or clinical interventions. 26 ovine anterior AF cuboid specimens from 11 lumbar intervertebral discs were tested in radial tension and mechanical parameters defining damage and failure were extracted from the in-vitro data. Equivalent 1D analytical models were developed to represent the specimen strength and the damage propagation, accounting for the specimen dimensions and number of lamellae. Model parameters were calibrated on the in-vitro data. Similar to stiffness values reported for other orientations, the outer annulus was found stronger than the inner annulus in the radial direction, with failure at higher stress values. The inner annulus failed more progressively, showing macroscopic failure at a higher strain value. The 1D analytical model of damage showed that lamellar damage is predominant in the failure mechanism of the AF. The analytical model of the connections between lamellae allowed us to represent separately damage processes in the lamellae and the inter-lamellar connections, which cannot be experimentally tested individually. PMID:27442918

  4. Challenges and strategies in the repair of ruptured annulus fibrosus

    Directory of Open Access Journals (Sweden)

    CC Guterl

    2013-01-01

    Full Text Available Lumbar discectomy is the surgical procedure most frequently performed for patients suffering from low back pain and sciatica. Disc herniation as a consequence of degenerative or traumatic processes is commonly encountered as the underlying cause for the painful condition. While discectomy provides favourable outcome in a majority of cases, there are conditions where unmet requirements exist in terms of treatment, such as large disc protrusions with minimal disc degeneration; in these cases, the high rate of recurrent disc herniation after discectomy is a prevalent problem. An effective biological annular repair could improve the surgical outcome in patients with contained disc herniations but otherwise minor degenerative changes. An attractive approach is a tissue-engineered implant that will enable/stimulate the repair of the ruptured annulus. The strategy is to develop three-dimensional scaffolds and activate them by seeding cells or by incorporating molecular signals that enable new matrix synthesis at the defect site, while the biomaterial provides immediate closure of the defect and maintains the mechanical properties of the disc. This review is structured into (1 introduction, (2 clinical problems, current treatment options and needs, (3 biomechanical demands, (4 cellular and extracellular components, (5 biomaterials for delivery, scaffolding and support, (6 pre-clinical models for evaluation of newly developed cell- and material-based therapies, and (7 conclusions. This article highlights that an interdisciplinary approach is necessary for successful development of new clinical methods for annulus fibrosus repair. This will benefit from a close collaboration between research groups with expertise in all areas addressed in this review.

  5. A combined biomaterial and cellular approach for annulus fibrosus rupture repair

    NARCIS (Netherlands)

    Pirvu, Tatiana; Blanquer, Sebastien B. G.; Benneker, Lorin M.; Grijpma, Dirk W.; Richards, Robert G.; Alini, Mauro; Eglin, David; Grad, Sibylle; Li, Zhen

    2015-01-01

    Recurrent intervertebral disc (IVD) herniation and degenerative disc disease have been identified as the most important factors contributing to persistent pain and disability after surgical discectomy. An annulus fibrosus (AF) closure device that provides immediate closure of the AF rupture, restore

  6. Development of poly(trimethylene carbonate) network implants for annulus fibrosus tissue engineering

    NARCIS (Netherlands)

    Blanquer, S.B.G.; Sharifi, S.; Grijpma, D.W.

    2012-01-01

    Purpose: Intervertebral disk degeneration is the main cause of chronic back pain. Disk degeneration often leads to tearing of the annulus fibrosus (AF) and extrusion of the nucleus pulposus (NP), which compresses the nerves. Current treatment involves removing the herniated NP and suturing the damag

  7. An annulus fibrosus closure device based on a biodegradable shape-memory polymer network

    NARCIS (Netherlands)

    Sharifi, Shahriar; van Kooten, Theo G.; Kranenburg, Hendrik-Jan C.; Meij, Bjorn P.; Behl, Marc; Lendlein, Andreas; Grijpma, Dirk W.

    2013-01-01

    Injuries to the intervertebral disc caused by degeneration or trauma often lead to tearing of the annulus fibrosus (AF) and extrusion of the nucleus pulposus (NP). This can compress nerves and cause lower back pain. In this study, the characteristics of poly(D,L-lactide-co-trimethylene carbonate) ne

  8. Role of calcium signaling in down-regulation of aggrecan induced by cyclic tensile strain in annulus fibrosus cells

    Institute of Scientific and Technical Information of China (English)

    GUO Zhi-liang; ZHOU Yue; LI Hua-zhuang; CAO Guo-yong; TENG Hai-jun

    2006-01-01

    Objective:To study the role of intracellular calcium signal pathway in the down-regulation of aggrecan induced by cyclic tensile strain in the annulus fibrosus cells. Methods :The expression of aggrecan mRNA and core protein were respectively detected with RT-PCR and western blot after the channels transmitting calcium ions were blocked with EGTA, gadolinium and verapamil. Results:EGTA, gadolinium and verapamil partially prevented the effects of cyclic tensile strain on the expression of aggrecan in annulus fibrosus cells. Conclusion:The calcium signaling is involved in the down-regulation of proteoglycan resulting from cyclic tensile strain in the annulus fibrosus cells.

  9. Qualitative and quantitative assessment of collagen and elastin in annulus fibrosus of the physiologic and scoliotic intervertebral discs.

    Science.gov (United States)

    Kobielarz, Magdalena; Szotek, Sylwia; Głowacki, Maciej; Dawidowicz, Joanna; Pezowicz, Celina

    2016-09-01

    The biophysical properties of the annulus fibrosus of the intervertebral disc are determined by collagen and elastin fibres. The progression of scoliosis is accompanied by a number of pathological changes concerning these structural proteins. This is a major cause of dysfunction of the intervertebral disc. The object of the study were annulus fibrosus samples excised from intervertebral discs of healthy subjects and patients treated surgically for scoliosis in the thoracolumbar or lumbar spine. The research material was subjected to structural analysis by light microscopy and quantitative analysis of the content of collagen types I, II, III and IV as well as elastin by immunoenzymatic test (ELISA). A statistical analysis was conducted to assess the impact of the sampling site (Mann-Whitney test, α=0.05) and scoliosis (Wilcoxon matched pairs test, α=0.05) on the obtained results. The microscopic studies conducted on scoliotic annulus fibrosus showed a significant architectural distortion of collagen and elastin fibres. Quantitative biochemical assays demonstrated region-dependent distribution of only collagen types I and II in the case of healthy intervertebral discs whereas in the case of scoliotic discs region-dependent distribution concerned all examined proteins of the extracellular matrix. Comparison of scoliotic and healthy annulus fibrosus revealed a significant decrease in the content of collagen type I and elastin as well as a slight increase in the proportion of collagen types III and IV. The content of collagen type II did not differ significantly between both groups. The observed anomalies are a manifestation of degenerative changes affecting annulus fibrosus of the intervertebral disc in patients suffering from scoliosis. PMID:27177214

  10. [Progress and challenges in tissue engineering of intervertebral disc annulus fibrosus].

    Science.gov (United States)

    Zhou, Pinghui; Guo, Qianping; Ling, Feng; Qian, Zhonglai; Li, Bin

    2016-03-01

    Degenerative disc disease (DDD) is a leading cause of low back pain, which severely affects the quality of life and incurs significant medical cost. Annulus fibrosus(AF) injuries can lead to substantial deterioration of intervertebral disc degeneration. However, the AF repair/regeneration remains a challenge due to the intrinsic cellular, biochemical and biomechanical heterogeneity of AF tissue. Tissue engineering would be a promising approach for AF regeneration. This article aims to provide a brief overview of the fundamental aspects of AF, the current achievements and future challenges of AF tissue engineering. A multidisciplinary approach is proposed for future studies to fully mimic the native AF tissue and its microenvironment, including choosing adequate cell source, preparing scaffolds with hierarchical microstructures, supplementing appropriate growth factors, and enforcing suitable mechanical stimulation. Hopefully, the engineered AF tissues would be effectively used to facilitate the treatment of DDD in the future. PMID:27273986

  11. Mechanics of oriented electrospun nanofibrous scaffolds for annulus fibrosus tissue engineering.

    Science.gov (United States)

    Nerurkar, Nandan L; Elliott, Dawn M; Mauck, Robert L

    2007-08-01

    Engineering a functional replacement for the annulus fibrosus (AF) of the intervertebral disc is contingent upon recapitulation of AF structure, composition, and mechanical properties. In this study, we propose a new paradigm for AF tissue engineering that focuses on the reconstitution of anatomic fiber architecture and uses constitutive modeling to evaluate construct function. A modified electrospinning technique was utilized to generate aligned nanofibrous polymer scaffolds for engineering the basic functional unit of the AF, a single lamella. Scaffolds were tested in uniaxial tension at multiple fiber orientations, demonstrating a nonlinear dependence of modulus on fiber angle that mimicked the nonlinearity and anisotropy of native AF. A homogenization model previously applied to native AF successfully described scaffold mechanical response, and parametric studies demonstrated that nonfibrillar matrix, along with fiber connectivity, are key contributors to tensile mechanics for engineered AF. We demonstrated that AF cells orient themselves along the aligned scaffolds and deposit matrix that contributes to construct mechanics under loading conditions relevant to the in vivo environment. The homogenization model was applied to cell-seeded constructs and provided quantitative measures for the evolution of matrix and interfibrillar interactions. Finally, the model demonstrated that at fiber angles of the AF (28 degrees -44 degrees ), engineered material behaved much like native tissue, suggesting that engineered constructs replicate the physiologic behavior of the single AF lamella. Constitutive modeling provides a powerful tool for analysis of engineered AF neo-tissue and native AF tissue alike, highlighting key mechanical design criteria for functional AF tissue engineering.

  12. Unusual cause of acute low-back pain: sudden annulus fibrosus rupture

    Directory of Open Access Journals (Sweden)

    Ali Fahir Ozer

    2012-06-01

    Full Text Available Low-back pain is a common problem in neurosurgery practice, and an algorithm has been developed for assessing these cases. However, one subgroup of these patients shares several clinical features and these individuals are not easy to categorize and diagnose. We present our observations for 8 of these patients, individuals with low-back pain caused by atypical annulus fibrosus rupture (AAR. The aim of this study is to show the consequences of overlooked annular tears on acute onset of low back pain. Eight patients with acute-onset severe low-back pain were admitted. Physical examinations were normal and each individual was examined neurologically and assessed with neuroradiologic studies [plain x-rays, magnetic resonance imaging (MRI, discography and computed tomography (CT discography]. AAR was ultimately diagnosed with provocative discography. In all cases, MRI showed a healthy disc or mild degeneration, whereas discography and CT discography demonstrated disc disease. Anterior interbody cage implantation was performed in 3 of the 8 cases and posterior dynamic stabilization was carried out in 3 cases. The other 2 individuals refused surgery, and we were informed that one of them developed disc herniation at the affected level 1 year after our diagnosis. Clinical and radiological outcomes were evaluated. In cases where AAR is suspected, MRI, discography, and CT discography should be performed in addition to routine neuroradiologic studies.

  13. Fibrin-genipin adhesive hydrogel for annulus fibrosus repair: performance evaluation with large animal organ culture, in situ biomechanics, and in vivo degradation tests

    OpenAIRE

    Likhitpanichkul, M.; Dreischarf, M; S Illien-Junger; BA Walter; T Nukaga; RG Long; Sakai, D; AC Hecht; JC Iatridis

    2014-01-01

    Annulus fibrosus (AF) defects from annular tears, herniation, and discectomy procedures are associated with painful conditions and accelerated intervertebral disc (IVD) degeneration. Currently, no effective treatments exist to repair AF damage, restore IVD biomechanics and promote tissue regeneration. An injectable fibrin-genipin adhesive hydrogel (Fib-Gen) was evaluated for its performance repairing large AF defects in a bovine caudal IVD model using ex vivo organ culture and biomechanical t...

  14. Protective effect of niacinamide on interleukin-1beta-induced annulus fibrosus type II collagen degeneration in vitro.

    Science.gov (United States)

    Duan, Deyu; Yang, Shuhua; Shao, Zengwu; Wang, Hong; Xiong, Xiaoqian

    2007-02-01

    The protective effect of niacinamide on interleukin-1beta (IL-1beta)-induced annulus fibrosus (AF) type II collagen degeneration in vitro and the mechanism were investigated. Chiba's intervertebral disc (IVD) culture models in rabbits were established and 48 IVDs from 12 adult Japanese white rabbits were randomly divided into 4 groups: normal control group, niacinamide-treated group, type II collagen degneration group (IL-1beta) and treatment group (niacinamide+IL-1beta). After culture for one week, AFs were collected for inducible nitric oxide synthase (iNOS), cysteine containing aspartate specific protease-3 (Caspase-3) and type II collagen immunohistochemical examination, and type II collagen reverse transcription polymerase chain reaction (RT-PCR). The results showed that rate of iNOS positive staining AF cells in the 4 groups was 17.6%, 10.9%, 73.9% and 19.3% respectively. The positive rate in treatment group was significantly lower than in the type II collagen degeneration group (Pniacinamide could effectively inhibit IL-1beta stimulated increase of iNOS and Caspase-3 in AF, and alleviate IL-1beta-caused destruction and synthesis inhibition of type II collagen. Niacinamide is of potential for clinical treatment of IVD degeneration.

  15. Comparison of phenotype characteristics of rat annulus fibrosus cells cultured on flexible silicone membrane and in plastic plate

    Institute of Scientific and Technical Information of China (English)

    GUO Zhi-liang; CHENG Min; CAO Guo-yong; LI Hua-zhuang; TENG Hai-jun; ZHOU Yue

    2006-01-01

    Objective:To compare the phenotype characteristics of rat annulus fibrosus (AF) cells cultured on flexible silicone membranes and those in plastic plates. Methods :The morphology of AF cells cultured in different substrates was examined. Proteoglycan was stained by toluidine blue. Contents of collagen type I , collagen type Ⅱ and aggrecan mRNAs were determined by reverse transcription-polymerase chain reaction (RT-PCR). The expression of integrin β1 was monitored by flow cytometry. By using propidium iodide (PI), the cell cycle in AF cells was analyzed. Cell adhesion to silicone membrane was also measured. Results:The AF cells cultured on different substrates were morphologically undistinguishable.Toluidine blue staining showed that there was also no difference between AF cells cultured on these 2 substrates. They still had the same expression levels of collagen type Ⅰ , collagen type Ⅱ , aggrecan mRNAs,and integrin β1. No significant difference was observed in the distribution of the cell cycle. AF cells grew well on silicone membrane. Conclusion:AF cells cultured on flexible silicone membrane maintain the stability of phenotype and may be appropriate for further studying the metabolic responses to mechanical stimuli at the cellular level.

  16. Do mechanical strain and TNF-α interact to amplify pro-inflammatory cytokine production in human annulus fibrosus cells?

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    Likhitpanichkul, Morakot; Torre, Olivia M; Gruen, Jadry; Walter, Benjamin A; Hecht, Andrew C; Iatridis, James C

    2016-05-01

    During intervertebral disc (IVD) injury and degeneration, annulus fibrosus (AF) cells experience large mechanical strains in a pro-inflammatory milieu. We hypothesized that TNF-α, an initiator of IVD inflammation, modifies AF cell mechanobiology via cytoskeletal changes, and interacts with mechanical strain to enhance pro-inflammatory cytokine production. Human AF cells (N=5, Thompson grades 2-4) were stretched uniaxially on collagen-I coated chambers to 0%, 5% (physiological) or 15% (pathologic) strains at 0.5Hz for 24h under hypoxic conditions with or without TNF-α (10ng/mL). AF cells were treated with anti-TNF-α and anti-IL-6. ELISA assessed IL-1β, IL-6, and IL-8 production and immunocytochemistry measured F-actin, vinculin and α-tubulin in AF cells. TNF-α significantly increased AF cell pro-inflammatory cytokine production compared to basal conditions (IL-1β:2.0±1.4-84.0±77.3, IL-6:10.6±9.9-280.9±214.1, IL-8:23.9±26.0-5125.1±4170.8pg/ml for basal and TNF-α treatment, respectively) as expected, but mechanical strain did not. Pathologic strain in combination with TNF-α increased IL-1β, and IL-8 but not IL-6 production of AF cells. TNF-α treatment altered F-actin and α-tubulin in AF cells, suggestive of altered cytoskeletal stiffness. Anti-TNF-α (infliximab) significantly inhibited pro-inflammatory cytokine production while anti-IL-6 (atlizumab) did not. In conclusion, TNF-α altered AF cell mechanobiology with cytoskeletal remodeling that potentially sensitized AF cells to mechanical strain and increased TNF-α-induced pro-inflammatory cytokine production. Results suggest an interaction between TNF-α and mechanical strain and future mechanistic studies are required to validate these observations.

  17. Three-dimensional development of tensile pre-strained annulus fibrosus cells for tissue regeneration: An in-vitro study

    International Nuclear Information System (INIS)

    Prior research has investigated the immediate response after application of tensile strain on annulus fibrosus (AF) cells for the past decade. Although mechanical strain can produce either catabolic or anabolic consequences to the cell monolayer, little is known on how to translate these findings into further tissue engineering applications. Till to date, the application and effect of tensile pre-strained cells to construct a three-dimensional (3D) AF tissue remains unknown. This study aims to investigate the effect of tensile pre-strained exposure of 1 to 24 h on the development of AF pellet culture for 3 weeks. Equibiaxial cyclic tensile strain was applied on AF monolayer cells over a period of 24 h, which was subsequently developed into a cell pellet. Investigation on cellular proliferation, phenotypic gene expression, and histological changes revealed that tensile pre-strain for 24 h had significant and lasting effect on the AF tissue development, with enhanced cell proliferation, and up-regulation of collagen type I, II, and aggrecan expression. Our results demonstrated the regenerative ability of AF cell pellets subjected to 24 h tensile pre-straining. Knowledge on the effects of tensile pre-strain exposure is necessary to optimize AF development for tissue reconstruction. Moreover, the tensile pre-strained cells may further be utilized in either cell therapy to treat mild disc degeneration disease, or the development of a disc construct for total disc replacement. - Highlights: • Establishment of tensile pre-strained cell line population for annulus development. • Tensile strain limits collagen gene expression declination in monolayer culture. • Tensile pre-strained cells up-regulate their matrix protein in 3D pellet culture

  18. Protective Effect of Niacinamide on interleukin-1β-induced Annulus Fibrosus Type Ⅱ Collagen Degeneration in vitro

    Institute of Scientific and Technical Information of China (English)

    DUAN Deyu; YANG Shuhua; SHAO Zengwu; WANG Hong; XIONG Xiaoqian

    2007-01-01

    The protective effect of niacinamide on interleukin-1β (IL-1β)-induced annulus fibrosus (AF) type Ⅱ collagen degeneration in vitro and the mechanism were investigated. Chiba's intervertebrai disc (IVD) culture models in rabbits were established and 48 IVDs from 12 adult Japanese white rabbits were randomly divided into 4 groups: normal control group, niacinamide-treated group, type Ⅱ collagen degneration group (IL-1β) and treatment group (niacinamide+IL-1β). After culture for one week, AFs were collected for inducible nitric oxide synthase (iNOS), cysteine containing aspartate specific protease-3 (Caspase-3) and type Ⅱ collagen immunohistochemical examination, and type Ⅱ collagen reverse transcription polymerase chain reaction (RT-PCR). The results showed that rate of iNOS positive staining AF cells in the 4 groups was 17.6%, 10.9%, 73.9% and 19.3% respectively. The positive rate in treatment group was significantly lower than in the type Ⅱ collagen degeneration group (P<0.01). Rate of Caspase-3 positive staining AF cells in the 4 groups was 3.4%, 4.2%, 17.6% and 10.3% respectively. The positive rate in treatment group was lower than in the type Ⅱ collagen degeneration group (P<0.01). Type Ⅱ collagen staining demonstrated that lamellar structure and continuity of collagen in treatment group was better reversed than in the degeneration group. RT-PCR revealed that the expression of type Ⅱ collagen in treatment group was significantly stronger than that in type Ⅱ collagen degeneration group (P<0.01). It was concluded that niacinamide could effectively inhibit IL-1β stimulated increase of iNOS and Caspase-3 in AF, and alleviate IL-1β-caused destruction and synthesis inhibition of type Ⅱ collagen. Niacinamide is of potential for clinical treatment of IVD degeneration.

  19. Three-dimensional development of tensile pre-strained annulus fibrosus cells for tissue regeneration: An in-vitro study

    Energy Technology Data Exchange (ETDEWEB)

    Chuah, Yon Jin [School of Chemical and Biomedical Engineering, Nanyang Technological University, 62 Nanyang Drive, Singapore 637459 (Singapore); Lee, Wu Chean [University Hospital Conventry & Warwickshire NHS Trust, Clifford Bridge Road, West Midlands CV2, 2DX (United Kingdom); Wong, Hee Kit [Department of Orthopedic Surgery, National University Health System, NUHS Tower Block Level 11, 1E Kent Ridge Road, Singapore 119228 (Singapore); Kang, Yuejun, E-mail: yuejun.kang@ntu.edu.sg [School of Chemical and Biomedical Engineering, Nanyang Technological University, 62 Nanyang Drive, Singapore 637459 (Singapore); Hee, Hwan Tak, E-mail: HTHee@ntu.edu.sg [School of Chemical and Biomedical Engineering, Nanyang Technological University, 62 Nanyang Drive, Singapore 637459 (Singapore); Pinnacle Spine & Scoliosis Centre, 3 Mount Elizabeth, Mount Elizabeth Medical Centre, #04-07, Singapore 228510 (Singapore); School of Physical and Mathematical Sciences, Nanyang Technological University, 21 Nanyang Link, Singapore 637459 (Singapore)

    2015-02-01

    Prior research has investigated the immediate response after application of tensile strain on annulus fibrosus (AF) cells for the past decade. Although mechanical strain can produce either catabolic or anabolic consequences to the cell monolayer, little is known on how to translate these findings into further tissue engineering applications. Till to date, the application and effect of tensile pre-strained cells to construct a three-dimensional (3D) AF tissue remains unknown. This study aims to investigate the effect of tensile pre-strained exposure of 1 to 24 h on the development of AF pellet culture for 3 weeks. Equibiaxial cyclic tensile strain was applied on AF monolayer cells over a period of 24 h, which was subsequently developed into a cell pellet. Investigation on cellular proliferation, phenotypic gene expression, and histological changes revealed that tensile pre-strain for 24 h had significant and lasting effect on the AF tissue development, with enhanced cell proliferation, and up-regulation of collagen type I, II, and aggrecan expression. Our results demonstrated the regenerative ability of AF cell pellets subjected to 24 h tensile pre-straining. Knowledge on the effects of tensile pre-strain exposure is necessary to optimize AF development for tissue reconstruction. Moreover, the tensile pre-strained cells may further be utilized in either cell therapy to treat mild disc degeneration disease, or the development of a disc construct for total disc replacement. - Highlights: • Establishment of tensile pre-strained cell line population for annulus development. • Tensile strain limits collagen gene expression declination in monolayer culture. • Tensile pre-strained cells up-regulate their matrix protein in 3D pellet culture.

  20. 兔髓核与纤维环细胞生物学特性差异的研究%Different biological characteristics between nucleus pulposus and annulus fibrosus cells in rabbits

    Institute of Scientific and Technical Information of China (English)

    谢健; 童培建; 肖鲁伟; 金红婷; 吴承亮; 单乐天; 毛强; 潘佳菲

    2013-01-01

    Objective:To compare biological characteristics between nucleus pulposus and annulus fibrosus cells in vitro model.Methods:Five New Zealand white rabbits (2 to 3 kg,either gender) were isolated nucleus pulposus and annulus fibrosus under sterilized condition,then cultured in nutrient solution with 15% FBS and DMEM/F12 (1∶1) by enzyme digestion combined with tissue block method.When 90% cells fused,subcultring were performed.Cell morphology were observed by inverted phase contrast microscope,cell viability were detected by trypan blue staining,histological were observed by a toluidine blue and HE staining,cell proliferation were tested by MTT method,then the cell morphology,viability,proliferation between nucleus pulposus and annulus fibrosus were compared.Results:There were no obvioualy differences between nucleus pulposus and annulus fibrosus in original and the first strain.Physalides were appeared in annulus fibrosus on the second generation.The strapping time was later,and activity was lower in nucleus pulposus than annulus fibrosus.The growth of cell proliferation in nucleus pulposus was lower than annulus fibrosus from the ninth day.Conclusion:The cell activity in annulus fibrosus is higher than nucleus pulposus.Digenerative disc disease may caused by recession of nucleus pulposus,local biomechnical changes,furether caused structure change and function loss of annulus fibrosus.%目的:同时建立兔髓核细胞与纤维环细胞体外培养模型,比较两者生物学特性差异.方法:新西兰大白兔5只(2~3 kg,雌雄不限),无菌条件下分离髓核及纤维环,酶消化法联合组织块法含15%FBS的DMEM/F12(1∶1)培养液培养,当细胞90%融合后进行传代培养.通过倒置相差显微镜观测细胞形态,台盼蓝染色测定细胞活力,甲苯胺蓝和HE染色进行组织学观察,MTT法测定细胞增殖,分析比较髓核细胞与纤维环细胞形态、活力、增殖的差异.结果:原代及第1代髓核细胞和纤维

  1. The effect of the fibre orientation of electrospun scaffolds on the matrix production of rabbit annulus fibrosus-derived stem cells

    Institute of Scientific and Technical Information of China (English)

    Chen Liu; Caihong Zhu; Jun Li; Pinghui Zhou; Min Chen; Huilin Yang; Bin Li

    2015-01-01

    Annulus fibrosus (AF) tissue engineering has recently received increasing attention as a treatment for intervertebral disc (IVD) degeneration;however, such engineering remains challenging because of the remarkable complexity of AF tissue. In order to engineer a functional AF replacement, the fabrication of cell-scaffold constructs that mimic the cellular, biochemical and structural features of native AF tissue is critical. In this study, we fabricated aligned fibrous polyurethane scaffolds using an electrospinning technique and used them for culturing AF-derived stem/progenitor cells (AFSCs). Random fibrous scaffolds, also prepared via electrospinning, were used as a control. We compared the morphology, proliferation, gene expression and matrix production of AFSCs on aligned scaffolds and random scaffolds. There was no apparent difference in the attachment or proliferation of cells cultured on aligned scaffolds and random scaffolds. However, compared to cells on random scaffolds, the AFSCs on aligned scaffolds were more elongated and better aligned, and they exhibited higher gene expression and matrix production of collagen-I and aggrecan. The gene expression and protein production of collagen-II did not appear to differ between the two groups. Together, these findings indicate that aligned fibrous scaffolds may provide a favourable microenvironment for the differentiation of AFSCs into cells similar to outer AF cells, which predominantly produce collagen-I matrix.

  2. Biaxial mechanics and inter-lamellar shearing of stem-cell seeded electrospun angle-ply laminates for annulus fibrosus tissue engineering.

    Science.gov (United States)

    Driscoll, Tristan P; Nakasone, Ryan H; Szczesny, Spencer E; Elliott, Dawn M; Mauck, Robert L

    2013-06-01

    The annulus fibrosus (AF) of the intervertebral disk plays a critical role in vertebral load transmission that is heavily dependent on the microscale structure and composition of the tissue. With degeneration, both structure and composition are compromised, resulting in a loss of AF mechanical function. Numerous tissue engineering strategies have addressed the issue of AF degeneration, but few have focused on recapitulation of AF microstructure and function. One approach that allows for generation of engineered AF with appropriate (+/-)30° lamellar microstructure is the use of aligned electrospun scaffolds seeded with mesenchymal stem cells (MSCs) and assembled into angle-ply laminates (APL). Previous work indicates that opposing lamellar orientation is necessary for development of near native uniaxial tensile properties. However, most native AF tensile loads are applied biaxially, as the disk is subjected to multi-axial loads and is constrained by its attachments to the vertebral bodies. Thus, the objective of this study was to evaluate the biaxial mechanical response of engineered AF bilayers, and to determine the importance of opposing lamellar structure under this loading regime. Opposing bilayers, which replicate native AF structure, showed a significantly higher modulus in both testing directions compared to parallel bilayers, and reached ∼60% of native AF biaxial properties. Associated with this increase in biaxial properties, significantly less shear, and significantly higher stretch in the fiber direction, was observed. These results provide additional insight into native tissue structure-function relationships, as well as new benchmarks for engineering functional AF tissue constructs.

  3. Fibrin-genipin adhesive hydrogel for annulus fibrosus repair: performance evaluation with large animal organ culture, in situ biomechanics, and in vivo degradation tests

    Directory of Open Access Journals (Sweden)

    M Likhitpanichkul

    2014-07-01

    Full Text Available Annulus fibrosus (AF defects from annular tears, herniation, and discectomy procedures are associated with painful conditions and accelerated intervertebral disc (IVD degeneration. Currently, no effective treatments exist to repair AF damage, restore IVD biomechanics and promote tissue regeneration. An injectable fibrin-genipin adhesive hydrogel (Fib-Gen was evaluated for its performance repairing large AF defects in a bovine caudal IVD model using ex vivo organ culture and biomechanical testing of motion segments, and for its in vivo longevity and biocompatibility in a rat model by subcutaneous implantation. Fib-Gen sealed AF defects, prevented IVD height loss, and remained well-integrated with native AF tissue following approximately 14,000 cycles of compression in 6-day organ culture experiments. Fib-Gen repair also retained high viability of native AF cells near the repair site, reduced nitric oxide released to the media, and showed evidence of AF cell migration into the gel. Biomechanically, Fib-Gen fully restored compressive stiffness to intact levels validating organ culture findings. However, only partial restoration of tensile and torsional stiffness was obtained, suggesting opportunities to enhance this formulation. Subcutaneous implantation results, when compared with the literature, suggested Fib-Gen exhibited similar biocompatibility behaviour to fibrin alone but degraded much more slowly. We conclude that injectable Fib-Gen successfully sealed large AF defects, promoted functional restoration with improved motion segment biomechanics, and served as a biocompatible adhesive biomaterial that had greatly enhanced in vivo longevity compared to fibrin. Fib-Gen offers promise for AF repairs that may prevent painful conditions and accelerated degeneration of the IVD, and warrants further material development and evaluation.

  4. Prediction

    CERN Document Server

    Sornette, Didier

    2010-01-01

    This chapter first presents a rather personal view of some different aspects of predictability, going in crescendo from simple linear systems to high-dimensional nonlinear systems with stochastic forcing, which exhibit emergent properties such as phase transitions and regime shifts. Then, a detailed correspondence between the phenomenology of earthquakes, financial crashes and epileptic seizures is offered. The presented statistical evidence provides the substance of a general phase diagram for understanding the many facets of the spatio-temporal organization of these systems. A key insight is to organize the evidence and mechanisms in terms of two summarizing measures: (i) amplitude of disorder or heterogeneity in the system and (ii) level of coupling or interaction strength among the system's components. On the basis of the recently identified remarkable correspondence between earthquakes and seizures, we present detailed information on a class of stochastic point processes that has been found to be particu...

  5. FABRICATION AND ANALYSIS OF A NOVEL TISSUE ENGINEERED COMPOSITE BIPHASIC SCAFFOLD FOR ANNULUS FIBROSUS AND NUCLEUS PULPOSUS%新型一体化纤维环-髓核双相支架的制备与评估

    Institute of Scientific and Technical Information of China (English)

    许海委; 徐宝山; 杨强; 李秀兰; 马信龙; 夏群; 张春秋; 伍耀宏

    2013-01-01

    Objective To fabricate a novel composite scaffold with acellular demineralized bone matrix/acellular nucleus pulposus matrix and to verify the feasibility of using it as a scaffold for intervertebral disc tissue engineering through detecting physical and chemical properties. Methods Pig proximal femoral cancellous bone rings (10 mm in external diameter, 5 mm in internal diameter, and 3 mm in thickness) were fabricated, and were dealed with degreasing, decalcification, and decellularization to prepare the annulus fibrosus phase of scaffold. Nucleus pulposus was taken from pig tails, decellularized with Triton X-100 and deoxycholic acid, crushed and centrifugalized to prepare nucleus pulposus extracellular mtrtix which was injected into the center of annulus fibrosus phase. Then the composite scaffold was freeze-dryed, cross-linked with ultraviolet radiation/carbodiimide and disinfected for use. The scaffold was investigated by general observation, HE staining, and scanning electron microscopy, as well as porosity measurement, water absorption rate, and compressive elastic modulus. Adipose-derived stem cells (ADSCs) were cultured with different concentrations of scaffold extract (25%, 50%, and 100%) to assess cytotoxicity of the scaffold. The cell viability of ADSCs seeded on the scaffold was detected by Live/Dead staining. Results The scaffold was white by general observation. The HE staining revealed that there was no cell fragments on the scaffold, and the dye homogeneously distributed. The scanning electron microscopy showed that the pore of the annulus fibrosus phase interconnected and the pore size was uniform; acellular nucleus pulposus matrix microfilament interconnected forming a uniform network structure, and the junction of the scaffold was closely connected. The novel porous scaffold had a good pore interconnectivity with (343.00 ± 88.25) urn pore diameter of the annulus fibrosus phase, 82.98% ± 7.02% porosity and 621.53% ± 53.31% water absorption rate

  6. Study of building an integrated annulus fibrosus-nucleus pulposus biphasic scaffold based on bone matrix gelatin and cartilage matrix%以骨基质明胶及软骨基质构建一体化纤维环-髓核双相支架的实验研究

    Institute of Scientific and Technical Information of China (English)

    伍耀宏; 徐宝山; 杨强; 马信龙; 夏群; 李秀兰; 胡永成; 张杨; 张春秋

    2013-01-01

    Objective To fabricate an integrated annulus fibrosus-nucleus pulposus biphasic scaffolds based on bone matrix gelatin and acellular cartilage matrix,and to detect its property and cell compatibility.Methods An integrated annulus fibrosus-nucleus pulposus biphasic scaffold was fabricated by the following steps: preparing the hollow bone matrix gelatin ring,injecting the acellular cartilage homogenate into the center of the bone matrix gelatin ring,and freeze drying.Sample slices were stained with Hoechst 33258,picrosirius and HE.The internal structure of the scaffold was observed under a scanning electron microscope.The porosity and water absorption of the scaffold were also evaluated.Compressive mechanical property under wet situation was tested.The annulus fibrosus and nucleus pulposus cells were isolated from sheep disc and separately implanted into the corresponding sites of the scaffold,and biocompatibility of the scaffold was evaluated by scanning electron microscope and live/dead cell staining.Results Hoechst 33258 staining showed no residual cells,picrosirius staining was positive,and HE staining showed two parts linked closely.Under scanning electron microscope,the scaffold had porous structure,and the average pore size was 401.4±13.1 μm for annulus fibrosus,and 112.4±21.8 μm for nucleus pulposus.The porosity and water absorption of the scaffold was 73.37%±2.56% and 655.7%±78.6%,respectively.The average compressive elastic modulus of the scaffold (49.06 ±15.57) kpa was smaller than that of the native disc (135.9±28.9) kPa.Scanning electron microscope showed cells adhered on the scaffold surface,with secreted matrix around them,and live/dead cells staining showed cells with good activity on scaffolds.Conclusion The integrated annulus fibrosus-nucleus pulposus scaffold based on bone matrix gelatin and cartilage matrix is an ideal artificial disc material,in view of well pore size,closely linked boundary,and good biocompatibility.%目的 以

  7. 来源于长管状骨的组织工程纤维环支架的理化特性及细胞生物学相容性研究%Study of physicochemical characteristics and biocompatibility of a novel tissue engineering annulus fibrosus scaffold derived from long bone

    Institute of Scientific and Technical Information of China (English)

    伍耀宏; 徐宝山; 杨强; 李秀兰; 张杨; 马信龙; 夏群; 闫中胜; 许海委

    2013-01-01

    , immunofluorescence staining of collagen type Ⅰ, Sirius red staining, SEM observation, pore diameter measurement, biomechanics test. The toxicity of leaching liquor from scaffolds was assessed by MTT assay, annulus fibrosus (AF) cells were isolated from goat and pass down to P1, and AF cells were seeded onto scaffolds with a syringe, cell - scaffold hybrids were assessed by LIVE / DEAD staining, scanning electron microscope ( SEM) and HE staining after 48 h cultrue in vitro. [ Results] The scaffold showed smooth and white surface under the gross observation, no residual cells were observed by Hoechst 33258 and HE staining, sirius red staining showed deep red staining scaffold. Immunofluorescence staining positive for collagen type Ⅰ, pores evenly distributed and connected in scaffolds with a average pore size of (401. 4 ± 13. 1) μm under the SEM, and the average compressive elastic modulus of integrated scaffold was 47. 75±6. 32kPa. MTT assay demonstrated no significant difference among the groups ( P > 0. 05) , LIVE/DEAD cells staining showed cells with good activity, SEM and HE staining showed cell adhesion on the stent scaffold surface and filamentous secretion surrounded cells. [ Conclusion ] The hollow ring scaffold decellularized thoroughly, has good pore structure and non -toxicity and good biocompatibility, shares similar mechanical property and composition with annulus fibrosus, therefore, it is a suitable candidate as an alternative cell - carrier for annulus fibrosus tissue engineering.

  8. CHALLENGES AND STRATEGIES IN THE REPAIR OF RUPTURED ANNULUS FIBROSUS

    NARCIS (Netherlands)

    Guterl, Clare C.; See, Eugene Y.; Blanquer, Sebastien B. G.; Pandit, Abhay; Ferguson, Stephen J.; Benneker, Lorin M.; Grijpma, Dirk W.; Sakai, Daisuke; Eglin, David; Alini, Mauro; Iatridis, James C.; Grad, Sibylle

    2013-01-01

    Lumbar discectomy is the surgical procedure most frequently performed for patients suffering from low back pain and sciatica. Disc herniation as a consequence of degenerative or traumatic processes is commonly encountered as the underlying cause for the painful condition. While discectomy provides f

  9. Challenges and strategies in the repair of ruptured annulus fibrosus

    NARCIS (Netherlands)

    Guterl, C.C.; See, E.Y.; Blanquer, S.B.G.; Pandit, A.; Ferguson, S.J.; Benneker, L.M.; Grijpma, D.W.; Sakai, D.; Eglin, D.; Alini, M.; Iatridis, J.C.; Grad, S.

    2013-01-01

    Lumbar discectomy is the surgical procedure most frequently performed for patients suffering from low back pain and sciatica. Disc herniation as a consequence of degenerative or traumatic processes is commonly encountered as the underlying cause for the painful condition. While discectomy provides f

  10. Successful Predictions

    Science.gov (United States)

    Pierrehumbert, R.

    2012-12-01

    In an observational science, it is not possible to test hypotheses through controlled laboratory experiments. One can test parts of the system in the lab (as is done routinely with infrared spectroscopy of greenhouse gases), but the collective behavior cannot be tested experimentally because a star or planet cannot be brought into the lab; it must, instead, itself be the lab. In the case of anthropogenic global warming, this is all too literally true, and the experiment would be quite exciting if it weren't for the unsettling fact that we and all our descendents for the forseeable future will have to continue making our home in the lab. There are nonetheless many routes though which the validity of a theory of the collective behavior can be determined. A convincing explanation must not be a"just-so" story, but must make additional predictions that can be verified against observations that were not originally used in formulating the theory. The field of Earth and planetary climate has racked up an impressive number of such predictions. I will also admit as "predictions" statements about things that happened in the past, provided that observations or proxies pinning down the past climate state were not available at the time the prediction was made. The basic prediction that burning of fossil fuels would lead to an increase of atmospheric CO2, and that this would in turn alter the Earth's energy balance so as to cause tropospheric warming, is one of the great successes of climate science. It began in the lineage of Fourier, Tyndall and Arrhenius, and was largely complete with the the radiative-convective modeling work of Manabe in the 1960's -- all well before the expected warming had progressed far enough to be observable. Similarly, long before the increase in atmospheric CO2 could be detected, Bolin formulated a carbon cycle model and used it to predict atmospheric CO2 out to the year 2000; the actual values come in at the high end of his predicted range, for

  11. Prediction Markets

    DEFF Research Database (Denmark)

    Horn, Christian Franz; Ivens, Bjørn Sven; Ohneberg, Michael;

    2014-01-01

    In recent years, Prediction Markets gained growing interest as a forecasting tool among researchers as well as practitioners, which resulted in an increasing number of publications. In order to track the latest development of research, comprising the extent and focus of research, this article...

  12. Diagnostics and therapy of spinal disc herniation; Diagnostik und Therapie des Bandscheibenvorfalls

    Energy Technology Data Exchange (ETDEWEB)

    Zimmer, A.; Reith, W. [Universitaetsklinikum des Saarlandes, Klinik fuer Diagnostische und Interventionelle Neuroradiologie, Homburg/Saar (Germany)

    2014-11-15

    Degenerative processes in a movement segment of the vertebral column, which can potentially give rise to herniation of elements of the nucleus pulposus, are complex and of variable clinical and radiological dimensions; however the mere assumption that degenerative changes precede disc herniation remains a matter of debate. By definition, spinal disc herniation (SDH) refers to components of the gelatinous nucleus pulposus protruding beyond the dorsal level of the vertebral body margin through tears in the annulus fibrosus. Clinical presentation may include pain, paresis and sensory disturbances. Magnetic resonance imaging (MRI) is considered the gold standard in the diagnosis of SDH. In the majority of patients a conservative approach with physical therapy exercises and adequate analgesic and antiphlogistic medical treatment results in a substantial improvement of symptoms. (orig.) [German] Degenerative Prozesse eines Bewegungssegments, die in einem Prolaps des Nucleus pulposus resultieren koennen, sind vielschichtig und von unterschiedlicher klinischer und radiologischer Auspraegung. Selbst die Annahme, dass Bandscheibenvorfaellen eine Degeneration vorangeht, ist keineswegs unumstritten. Definitionsgemaess spricht man von einem Bandscheibenvorfall (BSV), wenn das Gewebe des gelatinoesen Nucleus pulposus durch eine Dehiszenz im Anulus fibrosus ueber das Niveau der normalen dorsalen Begrenzung des Bandscheibenfachs hinaus prolabiert. Klinisch kann dies mit Schmerzen, Paresen und Sensibilitaetsstoerungen einhergehen. Die Magnetresonanztomographie gilt als Goldstandard in der Diagnostik eines BSV. In der Mehrzahl der Faelle fuehrt ein konservatives Vorgehen zu einer deutlichen Besserung der Symptomatik im Verlauf. (orig.)

  13. Predicting protein structure classes from function predictions

    DEFF Research Database (Denmark)

    Sommer, I.; Rahnenfuhrer, J.; de Lichtenberg, Ulrik;

    2004-01-01

    We introduce a new approach to using the information contained in sequence-to-function prediction data in order to recognize protein template classes, a critical step in predicting protein structure. The data on which our method is based comprise probabilities of functional categories; for given......-to-structure prediction methods....

  14. Nonparametric bootstrap prediction

    OpenAIRE

    Fushiki, Tadayoshi; Komaki, Fumiyasu; Aihara, Kazuyuki

    2005-01-01

    Ensemble learning has recently been intensively studied in the field of machine learning. `Bagging' is a method of ensemble learning and uses bootstrap data to construct various predictors. The required prediction is then obtained by averaging the predictors. Harris proposed using this technique with the parametric bootstrap predictive distribution to construct predictive distributions, and showed that the parametric bootstrap predictive distribution gives asymptotically better prediction tha...

  15. Predictive modeling of complications.

    Science.gov (United States)

    Osorio, Joseph A; Scheer, Justin K; Ames, Christopher P

    2016-09-01

    Predictive analytic algorithms are designed to identify patterns in the data that allow for accurate predictions without the need for a hypothesis. Therefore, predictive modeling can provide detailed and patient-specific information that can be readily applied when discussing the risks of surgery with a patient. There are few studies using predictive modeling techniques in the adult spine surgery literature. These types of studies represent the beginning of the use of predictive analytics in spine surgery outcomes. We will discuss the advancements in the field of spine surgery with respect to predictive analytics, the controversies surrounding the technique, and the future directions. PMID:27286683

  16. Nonlinear Combustion Instability Prediction

    Science.gov (United States)

    Flandro, Gary

    2010-01-01

    The liquid rocket engine stability prediction software (LCI) predicts combustion stability of systems using LOX-LH2 propellants. Both longitudinal and transverse mode stability characteristics are calculated. This software has the unique feature of being able to predict system limit amplitude.

  17. Testing earthquake predictions

    Science.gov (United States)

    Luen, Brad; Stark, Philip B.

    2008-01-01

    Statistical tests of earthquake predictions require a null hypothesis to model occasional chance successes. To define and quantify 'chance success' is knotty. Some null hypotheses ascribe chance to the Earth: Seismicity is modeled as random. The null distribution of the number of successful predictions - or any other test statistic - is taken to be its distribution when the fixed set of predictions is applied to random seismicity. Such tests tacitly assume that the predictions do not depend on the observed seismicity. Conditioning on the predictions in this way sets a low hurdle for statistical significance. Consider this scheme: When an earthquake of magnitude 5.5 or greater occurs anywhere in the world, predict that an earthquake at least as large will occur within 21 days and within an epicentral distance of 50 km. We apply this rule to the Harvard centroid-moment-tensor (CMT) catalog for 2000-2004 to generate a set of predictions. The null hypothesis is that earthquake times are exchangeable conditional on their magnitudes and locations and on the predictions - a common "nonparametric" assumption in the literature. We generate random seismicity by permuting the times of events in the CMT catalog. We consider an event successfully predicted only if (i) it is predicted and (ii) there is no larger event within 50 km in the previous 21 days. The P-value for the observed success rate is <0.001: The method successfully predicts about 5% of earthquakes, far better than 'chance' because the predictor exploits the clustering of earthquakes - occasional foreshocks - which the null hypothesis lacks. Rather than condition on the predictions and use a stochastic model for seismicity, it is preferable to treat the observed seismicity as fixed, and to compare the success rate of the predictions to the success rate of simple-minded predictions like those just described. If the proffered predictions do no better than a simple scheme, they have little value.

  18. Mechanical behavior of annulus fibrosus: a microstructural model of fibers reorientation.

    OpenAIRE

    Ambard, Dominique; Cherblanc, Fabien

    2009-01-01

    International audience Experimental uniaxial tensile tests have been carried out on annulus tissue samples harvested on pig and lamb lumbar intervertebral discs. When subjecting the samples to loading cycles, the stress-strain curves exhibit strong non-linearities and hysteresis. This particular behavior results from the anisotropic microstructure of annulus tissue composed of woven oriented collagen fibers embedded in the extracellular matrix. During uniaxial tension, the collagen fibers ...

  19. Treatment of the degenerated intervertebral disc; closure, repair and regeneration of the annulus fibrosus

    NARCIS (Netherlands)

    Sharifi, Shahriar; Bulstra, Sjoerd K.; Grijpma, Dirk W.; Kuijer, Roel

    2015-01-01

    Degeneration of the intervertebral disc (IVD) and disc herniation are two causes of low back pain. The aetiology of these disorders is unknown, but tissue weakening, which primarily occurs due to inherited genetic factors, ageing, nutritional compromise and loading history, is the basic factor causi

  20. 3D segmentation of annulus fibrosus and nucleus pulposus from T2-weighted magnetic resonance images

    Science.gov (United States)

    Castro-Mateos, Isaac; Pozo, Jose M.; Eltes, Peter E.; Del Rio, Luis; Lazary, Aron; Frangi, Alejandro F.

    2014-12-01

    Computational medicine aims at employing personalised computational models in diagnosis and treatment planning. The use of such models to help physicians in finding the best treatment for low back pain (LBP) is becoming popular. One of the challenges of creating such models is to derive patient-specific anatomical and tissue models of the lumbar intervertebral discs (IVDs), as a prior step. This article presents a segmentation scheme that obtains accurate results irrespective of the degree of IVD degeneration, including pathological discs with protrusion or herniation. The segmentation algorithm, employing a novel feature selector, iteratively deforms an initial shape, which is projected into a statistical shape model space at first and then, into a B-Spline space to improve accuracy. The method was tested on a MR dataset of 59 patients suffering from LBP. The images follow a standard T2-weighted protocol in coronal and sagittal acquisitions. These two image volumes were fused in order to overcome large inter-slice spacing. The agreement between expert-delineated structures, used here as gold-standard, and our automatic segmentation was evaluated using Dice Similarity Index and surface-to-surface distances, obtaining a mean error of 0.68 mm in the annulus segmentation and 1.88 mm in the nucleus, which are the best results with respect to the image resolution in the current literature.

  1. Predictive systems ecology.

    Science.gov (United States)

    Evans, Matthew R; Bithell, Mike; Cornell, Stephen J; Dall, Sasha R X; Díaz, Sandra; Emmott, Stephen; Ernande, Bruno; Grimm, Volker; Hodgson, David J; Lewis, Simon L; Mace, Georgina M; Morecroft, Michael; Moustakas, Aristides; Murphy, Eugene; Newbold, Tim; Norris, K J; Petchey, Owen; Smith, Matthew; Travis, Justin M J; Benton, Tim G

    2013-11-22

    Human societies, and their well-being, depend to a significant extent on the state of the ecosystems that surround them. These ecosystems are changing rapidly usually in response to anthropogenic changes in the environment. To determine the likely impact of environmental change on ecosystems and the best ways to manage them, it would be desirable to be able to predict their future states. We present a proposal to develop the paradigm of predictive systems ecology, explicitly to understand and predict the properties and behaviour of ecological systems. We discuss the necessary and desirable features of predictive systems ecology models. There are places where predictive systems ecology is already being practised and we summarize a range of terrestrial and marine examples. Significant challenges remain but we suggest that ecology would benefit both as a scientific discipline and increase its impact in society if it were to embrace the need to become more predictive.

  2. Predictability of conversation partners

    CERN Document Server

    Takaguchi, Taro; Sato, Nobuo; Yano, Kazuo; Masuda, Naoki

    2011-01-01

    Recent developments in sensing technologies have enabled us to examine the nature of human social behavior in greater detail. By applying an information theoretic method to the spatiotemporal data of cell-phone locations, Song et al. (2010) found that human mobility patterns are remarkably predictable. Inspired by their work, we address a similar predictability question in a different kind of human social activity: conversation events. The predictability in the sequence of one's conversation partners is defined as the degree to which one's next conversation partner can be predicted given the current partner. We quantify this predictability by using the mutual information. We examine the predictability of conversation events for each individual using the longitudinal data of face-to-face interactions collected from two company offices in Japan. Each subject wears a name tag equipped with an infrared sensor node, and conversation events are marked when signals are exchanged between close sensor nodes. We find t...

  3. Visualizing Risk Prediction Models

    OpenAIRE

    Vanya Van Belle; Ben Van Calster

    2015-01-01

    Objective Risk prediction models can assist clinicians in making decisions. To boost the uptake of these models in clinical practice, it is important that end-users understand how the model works and can efficiently communicate its results. We introduce novel methods for interpretable model visualization. Methods The proposed visualization techniques are applied to two prediction models from the Framingham Heart Study for the prediction of intermittent claudication and stroke after atrial fib...

  4. Pyroshock prediction procedures

    Science.gov (United States)

    Piersol, Allan G.

    2002-05-01

    Given sufficient effort, pyroshock loads can be predicted by direct analytical procedures using Hydrocodes that analytically model the details of the pyrotechnic explosion and its interaction with adjacent structures, including nonlinear effects. However, it is more common to predict pyroshock environments using empirical procedures based upon extensive studies of past pyroshock data. Various empirical pyroshock prediction procedures are discussed, including those developed by the Jet Propulsion Laboratory, Lockheed-Martin, and Boeing.

  5. Predictability of Conversation Partners

    Science.gov (United States)

    Takaguchi, Taro; Nakamura, Mitsuhiro; Sato, Nobuo; Yano, Kazuo; Masuda, Naoki

    2011-08-01

    Recent developments in sensing technologies have enabled us to examine the nature of human social behavior in greater detail. By applying an information-theoretic method to the spatiotemporal data of cell-phone locations, [C. Song , ScienceSCIEAS0036-8075 327, 1018 (2010)] found that human mobility patterns are remarkably predictable. Inspired by their work, we address a similar predictability question in a different kind of human social activity: conversation events. The predictability in the sequence of one’s conversation partners is defined as the degree to which one’s next conversation partner can be predicted given the current partner. We quantify this predictability by using the mutual information. We examine the predictability of conversation events for each individual using the longitudinal data of face-to-face interactions collected from two company offices in Japan. Each subject wears a name tag equipped with an infrared sensor node, and conversation events are marked when signals are exchanged between sensor nodes in close proximity. We find that the conversation events are predictable to a certain extent; knowing the current partner decreases the uncertainty about the next partner by 28.4% on average. Much of the predictability is explained by long-tailed distributions of interevent intervals. However, a predictability also exists in the data, apart from the contribution of their long-tailed nature. In addition, an individual’s predictability is correlated with the position of the individual in the static social network derived from the data. Individuals confined in a community—in the sense of an abundance of surrounding triangles—tend to have low predictability, and those bridging different communities tend to have high predictability.

  6. Is Time Predictability Quantifiable?

    DEFF Research Database (Denmark)

    Schoeberl, Martin

    2012-01-01

    -case execution time. To compare different approaches we would like to quantify time predictability. That means we need to measure time predictability. In this paper we discuss the different approaches for these measurements and conclude that time predictability is practically not quantifiable. We can only......Computer architects and researchers in the realtime domain start to investigate processors and architectures optimized for real-time systems. Optimized for real-time systems means time predictable, i.e., architectures where it is possible to statically derive a tight bound of the worst...... compare the worst-case execution time bounds of different architectures....

  7. Improved nonlinear prediction method

    Science.gov (United States)

    Adenan, Nur Hamiza; Md Noorani, Mohd Salmi

    2014-06-01

    The analysis and prediction of time series data have been addressed by researchers. Many techniques have been developed to be applied in various areas, such as weather forecasting, financial markets and hydrological phenomena involving data that are contaminated by noise. Therefore, various techniques to improve the method have been introduced to analyze and predict time series data. In respect of the importance of analysis and the accuracy of the prediction result, a study was undertaken to test the effectiveness of the improved nonlinear prediction method for data that contain noise. The improved nonlinear prediction method involves the formation of composite serial data based on the successive differences of the time series. Then, the phase space reconstruction was performed on the composite data (one-dimensional) to reconstruct a number of space dimensions. Finally the local linear approximation method was employed to make a prediction based on the phase space. This improved method was tested with data series Logistics that contain 0%, 5%, 10%, 20% and 30% of noise. The results show that by using the improved method, the predictions were found to be in close agreement with the observed ones. The correlation coefficient was close to one when the improved method was applied on data with up to 10% noise. Thus, an improvement to analyze data with noise without involving any noise reduction method was introduced to predict the time series data.

  8. Predicting AD conversion

    DEFF Research Database (Denmark)

    Liu, Yawu; Mattila, Jussi; Ruiz, Miguel �ngel Mu�oz;

    2013-01-01

    To compare the accuracies of predicting AD conversion by using a decision support system (PredictAD tool) and current research criteria of prodromal AD as identified by combinations of episodic memory impairment of hippocampal type and visual assessment of medial temporal lobe atrophy (MTA) on MRI...

  9. Prediction of Antibody Epitopes

    DEFF Research Database (Denmark)

    Nielsen, Morten; Marcatili, Paolo

    2015-01-01

    self-proteins. Given the sequence or the structure of a protein of interest, several methods exploit such features to predict the residues that are more likely to be recognized by an immunoglobulin.Here, we present two methods (BepiPred and DiscoTope) to predict linear and discontinuous antibody...

  10. Evaluating prediction uncertainty

    Energy Technology Data Exchange (ETDEWEB)

    McKay, M.D. [Los Alamos National Lab., NM (United States)

    1995-03-01

    The probability distribution of a model prediction is presented as a proper basis for evaluating the uncertainty in a model prediction that arises from uncertainty in input values. Determination of important model inputs and subsets of inputs is made through comparison of the prediction distribution with conditional prediction probability distributions. Replicated Latin hypercube sampling and variance ratios are used in estimation of the distributions and in construction of importance indicators. The assumption of a linear relation between model output and inputs is not necessary for the indicators to be effective. A sequential methodology which includes an independent validation step is applied in two analysis applications to select subsets of input variables which are the dominant causes of uncertainty in the model predictions. Comparison with results from methods which assume linearity shows how those methods may fail. Finally, suggestions for treating structural uncertainty for submodels are presented.

  11. Predictable return distributions

    DEFF Research Database (Denmark)

    Pedersen, Thomas Quistgaard

    This paper provides detailed insights into predictability of the entire stock and bond return distribution through the use of quantile regression. This allows us to examine speci…c parts of the return distribution such as the tails or the center, and for a suf…ciently …ne grid of quantiles we can...... predictable as a function of economic state variables. The results are, however, very different for stocks and bonds. The state variables primarily predict only location shifts in the stock return distribution, while they also predict changes in higher-order moments in the bond return distribution. Out......-of-sample analyses show that the relative accuracy of the state variables in predicting future returns varies across the distribution. A portfolio study shows that an investor with power utility can obtain economic gains by applying the empirical return distribution in portfolio decisions instead of imposing an...

  12. Structural prediction in aphasia

    Directory of Open Access Journals (Sweden)

    Tessa Warren

    2015-05-01

    Full Text Available There is considerable evidence that young healthy comprehenders predict the structure of upcoming material, and that their processing is facilitated when they encounter material matching those predictions (e.g., Staub & Clifton, 2006; Yoshida, Dickey & Sturt, 2013. However, less is known about structural prediction in aphasia. There is evidence that lexical prediction may be spared in aphasia (Dickey et al., 2014; Love & Webb, 1977; cf. Mack et al, 2013. However, predictive mechanisms supporting facilitated lexical access may not necessarily support structural facilitation. Given that many people with aphasia (PWA exhibit syntactic deficits (e.g. Goodglass, 1993, PWA with such impairments may not engage in structural prediction. However, recent evidence suggests that some PWA may indeed predict upcoming structure (Hanne, Burchert, De Bleser, & Vashishth, 2015. Hanne et al. tracked the eyes of PWA (n=8 with sentence-comprehension deficits while they listened to reversible subject-verb-object (SVO and object-verb-subject (OVS sentences in German, in a sentence-picture matching task. Hanne et al. manipulated case and number marking to disambiguate the sentences’ structure. Gazes to an OVS or SVO picture during the unfolding of a sentence were assumed to indicate prediction of the structure congruent with that picture. According to this measure, the PWA’s structural prediction was impaired compared to controls, but they did successfully predict upcoming structure when morphosyntactic cues were strong and unambiguous. Hanne et al.’s visual-world evidence is suggestive, but their forced-choice sentence-picture matching task places tight constraints on possible structural predictions. Clearer evidence of structural prediction would come from paradigms where the content of upcoming material is not as constrained. The current study used self-paced reading study to examine structural prediction among PWA in less constrained contexts. PWA (n=17 who

  13. Wind power prediction models

    Science.gov (United States)

    Levy, R.; Mcginness, H.

    1976-01-01

    Investigations were performed to predict the power available from the wind at the Goldstone, California, antenna site complex. The background for power prediction was derived from a statistical evaluation of available wind speed data records at this location and at nearby locations similarly situated within the Mojave desert. In addition to a model for power prediction over relatively long periods of time, an interim simulation model that produces sample wind speeds is described. The interim model furnishes uncorrelated sample speeds at hourly intervals that reproduce the statistical wind distribution at Goldstone. A stochastic simulation model to provide speed samples representative of both the statistical speed distributions and correlations is also discussed.

  14. Zephyr - The prediction models

    Energy Technology Data Exchange (ETDEWEB)

    Nielsen, T.S.; Madsen, H.; Nielsen, H.Aa. [Informatics and Mathematical Modelling - DTU, Kgs. Lyngby (Denmark); Landberg, L.; Giebel, G. [Risoe National Lab., Roskilde (Denmark)

    2006-07-01

    This paper briefly describes new models and methods for predicting the wind power output from wind farms. The system is being developed in a project which has the research organization Risoe and the department of Informatics and Mathematical Modelling (IMM) as the modelling team and all the Danish utilities as partners and users. The new models are evaluated for five wind farms in Denmark as well as one wind farm in Spain. It is shown that the predictions based on conditional parametric models are superior to the predictions obtained by state-of-the-art parametric models. (au)

  15. On Prediction of EOP

    CERN Document Server

    Malkin, Z

    2009-01-01

    Two methods of prediction of the Pole coordinates and TAI-UTC were tested -- extrapolation of the deterministic components and ARIMA. It was found that each of these methods is most effective for certain length of prognosis. For short-time prediction ARIMA algorithm yields more accurate prognosis, and for long-time one extrapolation is preferable. So, the combined algorithm is being used in practice of IAA EOP Service. The accuracy of prognosis is close to accuracy of IERS algorithms. For prediction of nutation the program KSV-1996-1 by T. Herring is being used.

  16. Genomic Prediction in Barley

    DEFF Research Database (Denmark)

    Edriss, Vahid; Cericola, Fabio; Jensen, Jens D;

    Genomic prediction uses markers (SNPs) across the whole genome to predict individual breeding values at an early growth stage potentially before large scale phenotyping. One of the applications of genomic prediction in plant breeding is to identify the best individual candidate lines to contribute...... to next generation. The main goal of this study was to see the potential of using genomic prediction in a commercial Barley breeding program. The data used in this study was from Nordic Seed company which is located in Denmark. Around 350 advanced lines were genotyped with 9K Barely chip from...... Illumina. Traits used in this study were grain yield, plant height and heading date. Heading date is number days it takes after 1st June for plant to head. Heritabilities were 0.33, 0.44 and 0.48 for yield, height and heading, respectively for the average of nine plots. The GBLUP model was used for genomic...

  17. Genomic Prediction in Barley

    DEFF Research Database (Denmark)

    Edriss, Vahid; Cericola, Fabio; Jensen, Jens D;

    2015-01-01

    Genomic prediction uses markers (SNPs) across the whole genome to predict individual breeding values at an early growth stage potentially before large scale phenotyping. One of the applications of genomic prediction in plant breeding is to identify the best individual candidate lines to contribute...... to next generation. The main goal of this study was to see the potential of using genomic prediction in a commercial Barley breeding program. The data used in this study was from Nordic Seed company which is located in Denmark. Around 350 advanced lines were genotyped with 9K Barely chip from...... Illumina. Traits used in this study were grain yield, plant height and heading date. Heading date is number days it takes after 1st June for plant to head. Heritabilities were 0.33, 0.44 and 0.48 for yield, height and heading, respectively for the average of nine plots. The GBLUP model was used for genomic...

  18. Epitope prediction methods

    DEFF Research Database (Denmark)

    Karosiene, Edita

    leucocyte antigen (HLA) molecules, are encoded by extremely polymorphic genes on chromosome 6. Due to this polymorphism, thousands of different MHC molecules exist, making the experimental identification of peptide-MHC interactions a very costly procedure. This has primed the need for in silico peptide......-MHC prediction methods, and over the last decade several such methods have been successfully developed and used for epitope discovery purposes. My PhD project has been dedicated to improve methods for predicting peptide-MHC interactions by developing new strategies for training prediction algorithms based...... on machine learning techniques. Several MHC class I binding prediction algorithms have been developed and due to their high accuracy they are used by many immunologists to facilitate the conventional experimental process of epitope discovery. However, the accuracy of these methods depends on data defining...

  19. Predictable grammatical constructions

    DEFF Research Database (Denmark)

    Lucas, Sandra

    2015-01-01

    My aim in this paper is to provide evidence from diachronic linguistics for the view that some predictable units are entrenched in grammar and consequently in human cognition, in a way that makes them functionally and structurally equal to nonpredictable grammatical units, suggesting...... that these predictable units should be considered grammatical constructions on a par with the nonpredictable constructions. Frequency has usually been seen as the only possible argument speaking in favor of viewing some formally and semantically fully predictable units as grammatical constructions. However, this paper...... semantically and formally predictable. Despite this difference, [méllo INF], like the other future periphrases, seems to be highly entrenched in the cognition (and grammar) of Early Medieval Greek language users, and consequently a grammatical construction. The syntactic evidence speaking in favor of [méllo...

  20. Predicting toxicity of nanoparticles

    OpenAIRE

    BURELLO ENRICO; Worth, Andrew

    2011-01-01

    A statistical model based on a quantitative structure–activity relationship accurately predicts the cytotoxicity of various metal oxide nanoparticles, thus offering a way to rapidly screen nanomaterials and prioritize testing.

  1. Robust Distributed Online Prediction

    CERN Document Server

    Dekel, Ofer; Shamir, Ohad; Xiao, Lin

    2010-01-01

    The standard model of online prediction deals with serial processing of inputs by a single processor. However, in large-scale online prediction problems, where inputs arrive at a high rate, an increasingly common necessity is to distribute the computation across several processors. A non-trivial challenge is to design distributed algorithms for online prediction, which maintain good regret guarantees. In \\cite{DMB}, we presented the DMB algorithm, which is a generic framework to convert any serial gradient-based online prediction algorithm into a distributed algorithm. Moreover, its regret guarantee is asymptotically optimal for smooth convex loss functions and stochastic inputs. On the flip side, it is fragile to many types of failures that are common in distributed environments. In this companion paper, we present variants of the DMB algorithm, which are resilient to many types of network failures, and tolerant to varying performance of the computing nodes.

  2. 'Red Flag' Predictions

    DEFF Research Database (Denmark)

    Hallin, Carina Antonia; Andersen, Torben Juul; Tveterås, Sigbjørn

    -generation prediction markets and outline its unique features as a third-generation prediction market. It is argued that frontline employees gain deep insights when they execute operational activities on an ongoing basis in the organization. The experiential learning from close interaction with internal and external...... stakeholders provides unique insights not otherwise available to senior management. We outline a methodology to agglomerate these insights in a performance barometer as an important source for problem identification and innovation....

  3. Stuck pipe prediction

    KAUST Repository

    Alzahrani, Majed

    2016-03-10

    Disclosed are various embodiments for a prediction application to predict a stuck pipe. A linear regression model is generated from hook load readings at corresponding bit depths. A current hook load reading at a current bit depth is compared with a normal hook load reading from the linear regression model. A current hook load greater than a normal hook load for a given bit depth indicates the likelihood of a stuck pipe.

  4. Operational Dust Prediction

    Science.gov (United States)

    Benedetti, Angela; Baldasano, Jose M.; Basart, Sara; Benincasa, Francesco; Boucher, Olivier; Brooks, Malcolm E.; Chen, Jen-Ping; Colarco, Peter R.; Gong, Sunlin; Huneeus, Nicolas; Jones, Luke; Lu, Sarah; Menut, Laurent; Morcrette, Jean-Jacques; Mulcahy, Jane; Nickovic, Slobodan; Garcia-Pando, Carlos P.; Reid, Jeffrey S.; Sekiyama, Thomas T.; Tanaka, Taichu Y.; Terradellas, Enric; Westphal, Douglas L.; Zhang, Xiao-Ye; Zhou, Chun-Hong

    2014-01-01

    Over the last few years, numerical prediction of dust aerosol concentration has become prominent at several research and operational weather centres due to growing interest from diverse stakeholders, such as solar energy plant managers, health professionals, aviation and military authorities and policymakers. Dust prediction in numerical weather prediction-type models faces a number of challenges owing to the complexity of the system. At the centre of the problem is the vast range of scales required to fully account for all of the physical processes related to dust. Another limiting factor is the paucity of suitable dust observations available for model, evaluation and assimilation. This chapter discusses in detail numerical prediction of dust with examples from systems that are currently providing dust forecasts in near real-time or are part of international efforts to establish daily provision of dust forecasts based on multi-model ensembles. The various models are introduced and described along with an overview on the importance of dust prediction activities and a historical perspective. Assimilation and evaluation aspects in dust prediction are also discussed.

  5. Aircraft noise prediction

    Science.gov (United States)

    Filippone, Antonio

    2014-07-01

    This contribution addresses the state-of-the-art in the field of aircraft noise prediction, simulation and minimisation. The point of view taken in this context is that of comprehensive models that couple the various aircraft systems with the acoustic sources, the propagation and the flight trajectories. After an exhaustive review of the present predictive technologies in the relevant fields (airframe, propulsion, propagation, aircraft operations, trajectory optimisation), the paper addresses items for further research and development. Examples are shown for several airplanes, including the Airbus A319-100 (CFM engines), the Bombardier Dash8-Q400 (PW150 engines, Dowty R408 propellers) and the Boeing B737-800 (CFM engines). Predictions are done with the flight mechanics code FLIGHT. The transfer function between flight mechanics and the noise prediction is discussed in some details, along with the numerical procedures for validation and verification. Some code-to-code comparisons are shown. It is contended that the field of aircraft noise prediction has not yet reached a sufficient level of maturity. In particular, some parametric effects cannot be investigated, issues of accuracy are not currently addressed, and validation standards are still lacking.

  6. Solar Cycle Prediction

    CERN Document Server

    Petrovay, K

    2010-01-01

    A review of solar cycle prediction methods and their performance is given, including forecasts for cycle 24 and focusing on aspects of the solar cycle prediction problem that have a bearing on dynamo theory. The scope of the review is further restricted to the issue of predicting the amplitude (and optionally the epoch) of an upcoming solar maximum no later than right after the start of the given cycle. Prediction methods form three main groups. Precursor methods rely on the value of some measure of solar activity or magnetism at a specified time to predict the amplitude of the following solar maximum. Their implicit assumption is that each numbered solar cycle is a consistent unit in itself, while solar activity seems to consist of a series of much less tightly intercorrelated individual cycles. Extrapolation methods, in contrast, are based on the premise that the physical process giving rise to the sunspot number record is statistically homogeneous, i.e., the mathematical regularities underlying its variati...

  7. Prediction model Perla

    International Nuclear Information System (INIS)

    Prediction model Perla presents one of a tool for an evaluation of a stream ecological status. It enables a comparing with a standard. The standard is formed by a dataset of sites from all area of the Czech Republic. The sites were influenced by a human activity as few as possible. 8 variables were used for prediction (distance from source, elevation, stream width and depth, slope, substrate roughness, longitude and latitude. All of them were statistically important for benthic communities. Results do not response ecoregions, but rather stream size (type). B (EQItaxonu), EQISi, EQIASPT a EQIH appears applicable for assessment using the prediction model and for natural and human stress differentiating. Limiting values of the indices for good ecological status are suggested. On the contrary, using of EQIEPT a EQIekoprof indices would be possible only with difficulties. (authors)

  8. Partially predictable chaos

    CERN Document Server

    Wernecke, Hendrik; Gros, Claudius

    2016-01-01

    For a chaotic system pairs of initially close-by trajectories become eventually fully uncorrelated on the attracting set. This process of decorrelation is split into an initial decrease characterized by the maximal Lyapunov exponent and a subsequent diffusive process on the chaotic attractor causing the final loss of predictability. The time scales of both processes can be either of the same or of very different orders of magnitude. In the latter case the two trajectories linger within a finite but small distance (with respect to the overall size of the attractor) for exceedingly long times and therefore remain partially predictable. We introduce a 0-1 indicator for chaos capable of describing this scenario, arguing, in addition, that the chaotic closed braids found close to a period-doubling transition are generically partially predictable.

  9. Predicting the Sunspot Cycle

    Science.gov (United States)

    Hathaway, David H.

    2009-01-01

    The 11-year sunspot cycle was discovered by an amateur astronomer in 1844. Visual and photographic observations of sunspots have been made by both amateurs and professionals over the last 400 years. These observations provide key statistical information about the sunspot cycle that do allow for predictions of future activity. However, sunspots and the sunspot cycle are magnetic in nature. For the last 100 years these magnetic measurements have been acquired and used exclusively by professional astronomers to gain new information about the nature of the solar activity cycle. Recently, magnetic dynamo models have evolved to the stage where they can assimilate past data and provide predictions. With the advent of the Internet and open data policies, amateurs now have equal access to the same data used by professionals and equal opportunities to contribute (but, alas, without pay). This talk will describe some of the more useful prediction techniques and reveal what they say about the intensity of the upcoming sunspot cycle.

  10. Linguistic Structure Prediction

    CERN Document Server

    Smith, Noah A

    2011-01-01

    A major part of natural language processing now depends on the use of text data to build linguistic analyzers. We consider statistical, computational approaches to modeling linguistic structure. We seek to unify across many approaches and many kinds of linguistic structures. Assuming a basic understanding of natural language processing and/or machine learning, we seek to bridge the gap between the two fields. Approaches to decoding (i.e., carrying out linguistic structure prediction) and supervised and unsupervised learning of models that predict discrete structures as outputs are the focus. W

  11. Atmospheric predictability revisited

    Directory of Open Access Journals (Sweden)

    Lizzie S. R. Froude

    2013-06-01

    Full Text Available This article examines the potential to improve numerical weather prediction (NWP by estimating upper and lower bounds on predictability by re-visiting the original study of Lorenz (1982 but applied to the most recent version of the European Centre for Medium Range Weather Forecasts (ECMWF forecast system, for both the deterministic and ensemble prediction systems (EPS. These bounds are contrasted with an older version of the same NWP system to see how they have changed with improvements to the NWP system. The computations were performed for the earlier seasons of DJF 1985/1986 and JJA 1986 and the later seasons of DJF 2010/2011 and JJA 2011 using the 500-hPa geopotential height field. Results indicate that for this field, we may be approaching the limit of deterministic forecasting so that further improvements might only be obtained by improving the initial state. The results also show that predictability calculations with earlier versions of the model may overestimate potential forecast skill, which may be due to insufficient internal variability in the model and because recent versions of the model are more realistic in representing the true atmospheric evolution. The same methodology is applied to the EPS to calculate upper and lower bounds of predictability of the ensemble mean forecast in order to explore how ensemble forecasting could extend the limits of the deterministic forecast. The results show that there is a large potential to improve the ensemble predictions, but for the increased predictability of the ensemble mean, there will be a trade-off in information as the forecasts will become increasingly smoothed with time. From around the 10-d forecast time, the ensemble mean begins to converge towards climatology. Until this point, the ensemble mean is able to predict the main features of the large-scale flow accurately and with high consistency from one forecast cycle to the next. By the 15-d forecast time, the ensemble mean has lost

  12. Zephyr - the prediction models

    DEFF Research Database (Denmark)

    Nielsen, Torben Skov; Madsen, Henrik; Nielsen, Henrik Aalborg;

    2001-01-01

    This paper briefly describes new models and methods for predicationg the wind power output from wind farms. The system is being developed in a project which has the research organization Risø and the department of Informatics and Mathematical Modelling (IMM) as the modelling team and all the Danish...... utilities as partners and users. The new models are evaluated for five wind farms in Denmark as well as one wind farm in Spain. It is shown that the predictions based on conditional parametric models are superior to the predictions obatined by state-of-the-art parametric models....

  13. RETAIL BANKRUPTCY PREDICTION

    Directory of Open Access Journals (Sweden)

    Johnny Pang

    2013-01-01

    Full Text Available This study reintroduces the famous discriminant functions from Edward Altman and Begley, Ming and Watts (BMW that were used to predict bankrupts. We will formulate three new discriminant functions which differ from Altman’s and BMW’s re-estimated Altman model. Altman’s models as well as Begley, Ming and Watts’s re-estimated Altman model apply to publicly traded industries, whereas the new models formulated in this study are based on retail companies. The three new functions will provide better predictions on retail bankruptcy and they will minimize the chance of misclassifications.

  14. Prediction method abstracts

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1994-12-31

    This conference was held December 4--8, 1994 in Asilomar, California. The purpose of this meeting was to provide a forum for exchange of state-of-the-art information concerning the prediction of protein structure. Attention if focused on the following: comparative modeling; sequence to fold assignment; and ab initio folding.

  15. THE PREDICTION OF OVULATION

    Institute of Scientific and Technical Information of China (English)

    WANGXin-Xing; ZHAShu-Wei; WUZhou-Ya

    1989-01-01

    The authors present their work on the prediction of ovulation in forty-five women with normal menstrual cycles for a total of 72 cycles by several indices, including ultrasonography, BBT graph, cervical mucus and mittelschmerz, LH peak values were also determined for reference in 20 cases ( 20 cycles ), Results are as follows:

  16. Predicting coronary heart disease

    DEFF Research Database (Denmark)

    Sillesen, Henrik; Fuster, Valentin

    2012-01-01

    Atherosclerosis is the leading cause of death and disabling disease. Whereas risk factors are well known and constitute therapeutic targets, they are not useful for prediction of risk of future myocardial infarction, stroke, or death. Therefore, methods to identify atherosclerosis itself have bee...

  17. Predicting Lotto Numbers

    NARCIS (Netherlands)

    Jorgensen, C.B.; Suetens, S.; Tyran, J.R.

    2011-01-01

    We investigate the "law of small numbers" using a unique panel data set on lotto gambling. Because we can track individual players over time, we can measure how they react to outcomes of recent lotto drawings. We can therefore test whether they behave as if they believe they can predict lotto number

  18. Prediction of resonant oscillation

    DEFF Research Database (Denmark)

    2010-01-01

    The invention relates to methods for prediction of parametric rolling of vessels. The methods are based on frequency domain and time domain information in order do set up a detector able to trigger an alarm when parametric roll is likely to occur. The methods use measurements of e.g. pitch and roll...

  19. Predicting service life margins

    Science.gov (United States)

    Egan, G. F.

    1971-01-01

    Margins are developed for equipment susceptible to malfunction due to excessive time or operation cycles, and for identifying limited life equipment so monitoring and replacing is accomplished before hardware failure. Method applies to hardware where design service is established and where reasonable expected usage prediction is made.

  20. Gate valve performance prediction

    International Nuclear Information System (INIS)

    The Electric Power Research Institute is carrying out a program to improve the performance prediction methods for motor-operated valves. As part of this program, an analytical method to predict the stem thrust required to stroke a gate valve has been developed and has been assessed against data from gate valve tests. The method accounts for the loads applied to the disc by fluid flow and for the detailed mechanical interaction of the stem, disc, guides, and seats. To support development of the method, two separate-effects test programs were carried out. One test program determined friction coefficients for contacts between gate valve parts by using material specimens in controlled environments. The other test program investigated the interaction of the stem, disc, guides, and seat using a special fixture with full-sized gate valve parts. The method has been assessed against flow-loop and in-plant test data. These tests include valve sizes from 3 to 18 in. and cover a considerable range of flow, temperature, and differential pressure. Stem thrust predictions for the method bound measured results. In some cases, the bounding predictions are substantially higher than the stem loads required for valve operation, as a result of the bounding nature of the friction coefficients in the method

  1. Predicting Classroom Success.

    Science.gov (United States)

    Kessler, Ronald P.

    A study was conducted at Rancho Santiago College (RSC) to identify personal and academic factors that are predictive of students' success in their courses. The study examined the following possible predictors of success: language and math test scores; background characteristics; length of time out of high school; high school background; college…

  2. Predicting Intrinsic Motivation

    Science.gov (United States)

    Martens, Rob; Kirschner, Paul A.

    2004-01-01

    Intrinsic motivation can be predicted from participants' perceptions of the social environment and the task environment (Ryan & Deci, 2000)in terms of control, relatedness and competence. To determine the degree of independence of these factors 251 students in higher vocational education (physiotherapy and hotel management) indicated the extent to…

  3. Predictability of critical transitions

    Science.gov (United States)

    Zhang, Xiaozhu; Kuehn, Christian; Hallerberg, Sarah

    2015-11-01

    Critical transitions in multistable systems have been discussed as models for a variety of phenomena ranging from the extinctions of species to socioeconomic changes and climate transitions between ice ages and warm ages. From bifurcation theory we can expect certain critical transitions to be preceded by a decreased recovery from external perturbations. The consequences of this critical slowing down have been observed as an increase in variance and autocorrelation prior to the transition. However, especially in the presence of noise, it is not clear whether these changes in observation variables are statistically relevant such that they could be used as indicators for critical transitions. In this contribution we investigate the predictability of critical transitions in conceptual models. We study the quadratic integrate-and-fire model and the van der Pol model under the influence of external noise. We focus especially on the statistical analysis of the success of predictions and the overall predictability of the system. The performance of different indicator variables turns out to be dependent on the specific model under study and the conditions of accessing it. Furthermore, we study the influence of the magnitude of transitions on the predictive performance.

  4. Towards Predictive Association Theories

    DEFF Research Database (Denmark)

    Kontogeorgis, Georgios; Tsivintzelis, Ioannis; Michelsen, Michael Locht;

    2011-01-01

    Association equations of state like SAFT, CPA and NRHB have been previously applied to many complex mixtures. In this work we focus on two of these models, the CPA and the NRHB equations of state and the emphasis is on the analysis of their predictive capabilities for a wide range of applications...

  5. PREDICTION OF OVULATION

    Institute of Scientific and Technical Information of China (English)

    LIUYong; CHENSu-Ru; ZHOUJin-Ting; LIUJi-Ying

    1989-01-01

    The purpose or this research is: I) to observe the secretory pattern of five reproductive hormones in Chinese women with normal menstrual cyclcs, especially at the prc-ovulatory peroid; 2) to study whether urinary LH measurement could be used instead of serum LH measurement; 3) to evaluate the significance of LH-EIA kit (Right-Day) for ovulation prediction.

  6. Prediction in OLAP Cube

    Directory of Open Access Journals (Sweden)

    Abdellah Sair

    2012-05-01

    Full Text Available Data warehouses are now offering an adequate solution for managing large volumes of data. Online analysis supports OLAP data warehouses in the process of decision support and visualization tools offer, structure and operation of data warehouse. On the other hand, data mining allows the extraction of knowledge with technical description, classification, explanation and prediction. It is therefore possible to better understand the data by coupling on-line analysis with data mining through a unified analysis process. Continuing the work of R. Ben Messaoud, where exploitation of the coupling of on-line analysis and data mining focuses on the description, visualization, classification and explanation, we propose extending the OLAP prediction capabilities. To integrate the prediction in the heart of OLAP, an approach based on automatic learning with regression trees is proposed in order to predict the value of an aggregate or a measure. We will try to express our approach using data from a service management reviews to know that it would be the average obtained by the students if we open a new module, for a department at a certain criterion.

  7. Can observers predict trustworthiness?

    NARCIS (Netherlands)

    M. Belot; V. Bhaskar; J. van de Ven

    2009-01-01

    We analyze experimental evidence on whether untrained subjects can predict how trustworthy an individual is. Two players on a TV show play a high stakes prisoner's dilemma with pre-play communication. Our subjects report probabilistic beliefs that each player cooperates, before and after communicati

  8. Chloride ingress prediction

    DEFF Research Database (Denmark)

    Frederiksen, Jens Mejer; Geiker, Mette Rica

    2008-01-01

    Prediction of chloride ingress into concrete is an important part of durability design of reinforced concrete structures exposed to chloride containing environment. This paper presents experimentally based design parameters for Portland cement concretes with and without silica fume and fly ash in...

  9. Predicting Major Solar Eruptions

    Science.gov (United States)

    Kohler, Susanna

    2016-05-01

    Coronal mass ejections (CMEs) and solar flares are two examples of major explosions from the surface of the Sun but theyre not the same thing, and they dont have to happen at the same time. A recent study examines whether we can predict which solar flares will be closely followed by larger-scale CMEs.Image of a solar flare from May 2013, as captured by NASAs Solar Dynamics Observatory. [NASA/SDO]Flares as a Precursor?A solar flare is a localized burst of energy and X-rays, whereas a CME is an enormous cloud of magnetic flux and plasma released from the Sun. We know that some magnetic activity on the surface of the Sun triggers both a flare and a CME, whereas other activity only triggers a confined flare with no CME.But what makes the difference? Understanding this can help us learn about the underlying physical drivers of flares and CMEs. It also might help us to better predict when a CME which can pose a risk to astronauts, disrupt radio transmissions, and cause damage to satellites might occur.In a recent study, Monica Bobra and Stathis Ilonidis (Stanford University) attempt to improve our ability to make these predictions by using a machine-learning algorithm.Classification by ComputerUsing a combination of 6 or more features results in a much better predictive success (measured by the True Skill Statistic; higher positive value = better prediction) for whether a flare will be accompanied by a CME. [Bobra Ilonidis 2016]Bobra and Ilonidis used magnetic-field data from an instrument on the Solar Dynamics Observatory to build a catalog of solar flares, 56 of which were accompanied by a CME and 364 of which were not. The catalog includes information about 18 different features associated with the photospheric magnetic field of each flaring active region (for example, the mean gradient of the horizontal magnetic field).The authors apply a machine-learning algorithm known as a binary classifier to this catalog. This algorithm tries to predict, given a set of features

  10. Comparing Spatial Predictions

    KAUST Repository

    Hering, Amanda S.

    2011-11-01

    Under a general loss function, we develop a hypothesis test to determine whether a significant difference in the spatial predictions produced by two competing models exists on average across the entire spatial domain of interest. The null hypothesis is that of no difference, and a spatial loss differential is created based on the observed data, the two sets of predictions, and the loss function chosen by the researcher. The test assumes only isotropy and short-range spatial dependence of the loss differential but does allow it to be non-Gaussian, non-zero-mean, and spatially correlated. Constant and nonconstant spatial trends in the loss differential are treated in two separate cases. Monte Carlo simulations illustrate the size and power properties of this test, and an example based on daily average wind speeds in Oklahoma is used for illustration. Supplemental results are available online. © 2011 American Statistical Association and the American Society for Qualitys.

  11. STRATEGY PATTERNS PREDICTION MODEL

    Directory of Open Access Journals (Sweden)

    Aram Baruch Gonzalez Perez

    2014-01-01

    Full Text Available Multi-agent systems are broadly known for being able to simulate real-life situations which require the interaction and cooperation of individuals. Opponent modeling can be used along with multi-agent systems to model complex situations such as competitions like soccer games. In this study, a model for predicting opponent moves based on their target is presented. The model is composed by an offline step (learning phase and an online one (execution phase. The offline step gets and analyses previous experiences while the online step uses the data generated by offline analysis to predict opponent moves. This model is illustrated by an experiment with the RoboCup 2D Soccer Simulator. The proposed model was tested using 22 games to create the knowledge base and getting an accuracy rate over 80%.

  12. Predictive Hypothesis Identification

    CERN Document Server

    Hutter, Marcus

    2008-01-01

    While statistics focusses on hypothesis testing and on estimating (properties of) the true sampling distribution, in machine learning the performance of learning algorithms on future data is the primary issue. In this paper we bridge the gap with a general principle (PHI) that identifies hypotheses with best predictive performance. This includes predictive point and interval estimation, simple and composite hypothesis testing, (mixture) model selection, and others as special cases. For concrete instantiations we will recover well-known methods, variations thereof, and new ones. PHI nicely justifies, reconciles, and blends (a reparametrization invariant variation of) MAP, ML, MDL, and moment estimation. One particular feature of PHI is that it can genuinely deal with nested hypotheses.

  13. Predicting Lotto Numbers

    DEFF Research Database (Denmark)

    Jørgensen, Claus Bjørn; Suetens, Sigrid; Tyran, Jean-Robert

    numbers based on recent drawings. While most players pick the same set of numbers week after week without regards of numbers drawn or anything else, we find that those who do change, act on average in the way predicted by the law of small numbers as formalized in recent behavioral theory. In particular......We investigate the “law of small numbers” using a unique panel data set on lotto gambling. Because we can track individual players over time, we can measure how they react to outcomes of recent lotto drawings. We can therefore test whether they behave as if they believe they can predict lotto......, on average they move away from numbers that have recently been drawn, as suggested by the “gambler’s fallacy”, and move toward numbers that are on streak, i.e. have been drawn several weeks in a row, consistent with the “hot hand fallacy”....

  14. Predictability of Critical Transitions

    CERN Document Server

    Zhang, Xiaozhu; Hallerberg, Sarah

    2015-01-01

    Critical transitions in multistable systems have been discussed as models for a variety of phenomena ranging from the extinctions of species to socio-economic changes and climate transitions between ice-ages and warm-ages. From bifurcation theory we can expect certain critical transitions to be preceded by a decreased recovery from external perturbations. The consequences of this critical slowing down have been observed as an increase in variance and autocorrelation prior to the transition. However especially in the presence of noise it is not clear, whether these changes in observation variables are statistically relevant such that they could be used as indicators for critical transitions. In this contribution we investigate the predictability of critical transitions in conceptual models. We study the the quadratic integrate-and-fire model and the van der Pol model, under the influence of external noise. We focus especially on the statistical analysis of the success of predictions and the overall predictabil...

  15. Predicting Bankruptcy in Pakistan

    Directory of Open Access Journals (Sweden)

    Abdul RASHID

    2011-09-01

    Full Text Available This paper aims to identify the financial ratios that are most significant in bankruptcy prediction for the non-financial sector of Pakistan based on a sample of companies which became bankrupt over the time period 1996-2006. Twenty four financial ratios covering four important financial attributes, namely profitability, liquidity, leverage, and turnover ratios, were examined for a five-year period prior bankruptcy. The discriminant analysis produced a parsimonious model of three variables viz. sales to total assets, EBIT to current liabilities, and cash flow ratio. Our estimates provide evidence that the firms having Z-value below zero fall into the “bankrupt” whereas the firms with Z-value above zero fall into the “non-bankrupt” category. The model achieved 76.9% prediction accuracy when it is applied to forecast bankruptcies on the underlying sample.

  16. Chaos detection and predictability

    CERN Document Server

    Gottwald, Georg; Laskar, Jacques

    2016-01-01

    Distinguishing chaoticity from regularity in deterministic dynamical systems and specifying the subspace of the phase space in which instabilities are expected to occur is of utmost importance in as disparate areas as astronomy, particle physics and climate dynamics.   To address these issues there exists a plethora of methods for chaos detection and predictability. The most commonly employed technique for investigating chaotic dynamics, i.e. the computation of Lyapunov exponents, however, may suffer a number of problems and drawbacks, for example when applied to noisy experimental data.   In the last two decades, several novel methods have been developed for the fast and reliable determination of the regular or chaotic nature of orbits, aimed at overcoming the shortcomings of more traditional techniques. This set of lecture notes and tutorial reviews serves as an introduction to and overview of modern chaos detection and predictability techniques for graduate students and non-specialists.   The book cover...

  17. Candidate Prediction Models and Methods

    DEFF Research Database (Denmark)

    Nielsen, Henrik Aalborg; Nielsen, Torben Skov; Madsen, Henrik;

    2005-01-01

    This document lists candidate prediction models for Work Package 3 (WP3) of the PSO-project called ``Intelligent wind power prediction systems'' (FU4101). The main focus is on the models transforming numerical weather predictions into predictions of power production. The document also outlines the...

  18. STRATEGY PATTERNS PREDICTION MODEL

    OpenAIRE

    Aram Baruch Gonzalez Perez; Jorge Adolfo Ramirez Uresti

    2014-01-01

    Multi-agent systems are broadly known for being able to simulate real-life situations which require the interaction and cooperation of individuals. Opponent modeling can be used along with multi-agent systems to model complex situations such as competitions like soccer games. In this study, a model for predicting opponent moves based on their target is presented. The model is composed by an offline step (learning phase) and an online one (execution phase). The offline step gets and analyses p...

  19. Nominal model predictive control

    OpenAIRE

    Grüne, Lars

    2013-01-01

    5 p., to appear in Encyclopedia of Systems and Control, Tariq Samad, John Baillieul (eds.); International audience; Model Predictive Control is a controller design method which synthesizes a sampled data feedback controller from the iterative solution of open loop optimal control problems.We describe the basic functionality of MPC controllers, their properties regarding feasibility, stability and performance and the assumptions needed in order to rigorously ensure these properties in a nomina...

  20. Multivariate respiratory motion prediction

    International Nuclear Information System (INIS)

    In extracranial robotic radiotherapy, tumour motion is compensated by tracking external and internal surrogates. To compensate system specific time delays, time series prediction of the external optical surrogates is used. We investigate whether the prediction accuracy can be increased by expanding the current clinical setup by an accelerometer, a strain belt and a flow sensor. Four previously published prediction algorithms are adapted to multivariate inputs—normalized least mean squares (nLMS), wavelet-based least mean squares (wLMS), support vector regression (SVR) and relevance vector machines (RVM)—and evaluated for three different prediction horizons. The measurement involves 18 subjects and consists of two phases, focusing on long term trends (M1) and breathing artefacts (M2). To select the most relevant and least redundant sensors, a sequential forward selection (SFS) method is proposed. Using a multivariate setting, the results show that the clinically used nLMS algorithm is susceptible to large outliers. In the case of irregular breathing (M2), the mean root mean square error (RMSE) of a univariate nLMS algorithm is 0.66 mm and can be decreased to 0.46 mm by a multivariate RVM model (best algorithm on average). To investigate the full potential of this approach, the optimal sensor combination was also estimated on the complete test set. The results indicate that a further decrease in RMSE is possible for RVM (to 0.42 mm). This motivates further research about sensor selection methods. Besides the optical surrogates, the sensors most frequently selected by the algorithms are the accelerometer and the strain belt. These sensors could be easily integrated in the current clinical setup and would allow a more precise motion compensation. (paper)

  1. Predictive Game Theory

    Science.gov (United States)

    Wolpert, David H.

    2005-01-01

    Probability theory governs the outcome of a game; there is a distribution over mixed strat.'s, not a single "equilibrium". To predict a single mixed strategy must use our loss function (external to the game's players. Provides a quantification of any strategy's rationality. Prove rationality falls as cost of computation rises (for players who have not previously interacted). All extends to games with varying numbers of players.

  2. Time-predictable architectures

    CERN Document Server

    Rochange, Christine; Uhrig , Sascha

    2014-01-01

    Building computers that can be used to design embedded real-time systems is the subject of this title. Real-time embedded software requires increasingly higher performances. The authors therefore consider processors that implement advanced mechanisms such as pipelining, out-of-order execution, branch prediction, cache memories, multi-threading, multicorearchitectures, etc. The authors of this book investigate the timepredictability of such schemes.

  3. Multivariate respiratory motion prediction

    Science.gov (United States)

    Dürichen, R.; Wissel, T.; Ernst, F.; Schlaefer, A.; Schweikard, A.

    2014-10-01

    In extracranial robotic radiotherapy, tumour motion is compensated by tracking external and internal surrogates. To compensate system specific time delays, time series prediction of the external optical surrogates is used. We investigate whether the prediction accuracy can be increased by expanding the current clinical setup by an accelerometer, a strain belt and a flow sensor. Four previously published prediction algorithms are adapted to multivariate inputs—normalized least mean squares (nLMS), wavelet-based least mean squares (wLMS), support vector regression (SVR) and relevance vector machines (RVM)—and evaluated for three different prediction horizons. The measurement involves 18 subjects and consists of two phases, focusing on long term trends (M1) and breathing artefacts (M2). To select the most relevant and least redundant sensors, a sequential forward selection (SFS) method is proposed. Using a multivariate setting, the results show that the clinically used nLMS algorithm is susceptible to large outliers. In the case of irregular breathing (M2), the mean root mean square error (RMSE) of a univariate nLMS algorithm is 0.66 mm and can be decreased to 0.46 mm by a multivariate RVM model (best algorithm on average). To investigate the full potential of this approach, the optimal sensor combination was also estimated on the complete test set. The results indicate that a further decrease in RMSE is possible for RVM (to 0.42 mm). This motivates further research about sensor selection methods. Besides the optical surrogates, the sensors most frequently selected by the algorithms are the accelerometer and the strain belt. These sensors could be easily integrated in the current clinical setup and would allow a more precise motion compensation.

  4. Thinking about Aid Predictability

    OpenAIRE

    Andrews, Matthew; Wilhelm, Vera

    2008-01-01

    Researchers are giving more attention to aid predictability. In part, this is because of increases in the number of aid agencies and aid dollars and the growing complexity of the aid community. A growing body of research is examining key questions: Is aid unpredictable? What causes unpredictability? What can be done about it? This note draws from a selection of recent literature to bring s...

  5. Predicting helpful product reviews

    OpenAIRE

    O'Mahony, Michael P.; Cunningham, Pádraig; Smyth, Barry

    2010-01-01

    Millions of users are today posting user-generated content online, expressing their opinions on all manner of goods and services, topics and social affairs. While undoubtedly useful,user-generated content presents consumers with significant challenges in terms of information overload and quality considerations. In this paper, we address these issues in the context of product reviews and present a brief survey of our work to date on predicting review helpfulness. In particular, the performa...

  6. The Predictive Audit Framework

    OpenAIRE

    Kuenkaikaew, Siripan; Vasarhelyi, Miklos A.

    2013-01-01

    Assurance is an essential part of the business process of the modern enterprise. Auditing is a widely used assurance method made mandatory for public companies since 1934. The traditional (retroactive) audit provides after-the-fact audit reports, and is of limited value in the ever changing modern business environment because it is slow and backwards looking. Contemporary auditing and monitoring technologies could shorten the audit and assurance time frame. This paper proposes the predictive ...

  7. Predicting appointment breaking.

    Science.gov (United States)

    Bean, A G; Talaga, J

    1995-01-01

    The goal of physician referral services is to schedule appointments, but if too many patients fail to show up, the value of the service will be compromised. The authors found that appointment breaking can be predicted by the number of days to the scheduled appointment, the doctor's specialty, and the patient's age and gender. They also offer specific suggestions for modifying the marketing mix to reduce the incidence of no-shows. PMID:10142384

  8. Eclipse prediction in Mesopotamia.

    Science.gov (United States)

    Steele, J. M.

    2000-02-01

    Among the many celestial phenomena observed in ancient Mesopotamia, eclipses, particularly eclipses of the Moon, were considered to be among the astrologically most significant events. In Babylon, by at least the middle of the seventh century BC, and probably as early as the middle of the eighth century BC, astronomical observations were being systematically conducted and recorded in a group of texts which we have come to call Astronomical Diaries. These Diaries contain many observations and predictions of eclipses. The predictions generally include the expected time of the eclipse, apparently calculated quite precisely. By the last three centuries BC, the Babylonian astronomers had developed highly advanced mathematical theories of the Moon and planets. This paper outlines the various methods which appear to have been formulated by the Mesopotamian astronomers to predict eclipses of the Sun and the Moon. It also considers the question of which of these methods were actually used in compiling the Astronomical Diaries, and speculates why these particular methods were used.

  9. Is Suicide Predictable?

    Directory of Open Access Journals (Sweden)

    S Asmaee

    2012-04-01

    Full Text Available Background:The current study aimed to test the hypothesis: Is suicide predictable? And try to classify the predictive factors in multiple suicide attempts.Methods:A cross-sectional study was administered to 223 multiple attempters, women who came to a medical poison centre after a suicide attempt.The participants were young, poor, and single.A Logistic Regression Analiysis was used to classify the predictive factors of suicide.Results:Women who had multiple suicide attempts exhibited a significant tendency to attempt suicide again. They had a history for more than two years of multiple suicide attempts, from three to as many as 18 times, plus mental illnesses such as depression and substance abuse.They also had a positive history of mental illnesses.Conclusion:Results indicate that contributing factors for another suicide attempt include previous suicide attempts, mental illness (depression,or a positive history of mental illnesses in the family affecting them at a young age, and substance abuse.

  10. The accuracy of MRI in the detection of Lumbar Disc Containment

    Directory of Open Access Journals (Sweden)

    Weiner Bradley K

    2008-10-01

    Full Text Available Abstract Background MRI has proven to be an extremely valuable tool in the assessment of normal and pathological spinal anatomy. Accordingly, it is commonly used to assess containment of discal material by the outer fibers of the anulus fibrosus and posterior longitudinal ligaments. Determination of such containment is important to determine candidacy for intradiscal techniques and has prognostic significance. The accuracy of MRI in detecting containment has been insufficiently documented. Methods The MRI's of fifty consecutive patients undergoing open lumbar microdiscectomy were prospectively evaluated for disc containment by a neuroradiologist and senior spinal surgeon using criteria available in the literature and the classification of Macnab/McCulloch. An independent surgeon then performed the surgery and documented the actual containment status using the same methods. Statistical evaluation of accuracy was undertaken. Results MRI was found to be 72% sensitive, 68% specific, and 70% accurate in detecting containment status of lumbar herniated discs. Conclusion MRI may be inaccurate in assessing containment status of lumbar disc herniations in 30% of cases. Given the importance of containment for patient selection for indirect discectomy techniques and intradiscal therapies, coupled with prognostic significance; other methods to assess containment should be employed to assess containment when such alternative interventions are being considered.

  11. Anisotropic Multishell Analytical Modeling of an Intervertebral Disk Subjected to Axial Compression.

    Science.gov (United States)

    Demers, Sébastien; Nadeau, Sylvie; Bouzid, Abdel-Hakim

    2016-04-01

    Studies on intervertebral disk (IVD) response to various loads and postures are essential to understand disk's mechanical functions and to suggest preventive and corrective actions in the workplace. The experimental and finite-element (FE) approaches are well-suited for these studies, but validating their findings is difficult, partly due to the lack of alternative methods. Analytical modeling could allow methodological triangulation and help validation of FE models. This paper presents an analytical method based on thin-shell, beam-on-elastic-foundation and composite materials theories to evaluate the stresses in the anulus fibrosus (AF) of an axisymmetric disk composed of multiple thin lamellae. Large deformations of the soft tissues are accounted for using an iterative method and the anisotropic material properties are derived from a published biaxial experiment. The results are compared to those obtained by FE modeling. The results demonstrate the capability of the analytical model to evaluate the stresses at any location of the simplified AF. It also demonstrates that anisotropy reduces stresses in the lamellae. This novel model is a preliminary step in developing valuable analytical models of IVDs, and represents a distinctive groundwork that is able to sustain future refinements. This paper suggests important features that may be included to improve model realism. PMID:26833355

  12. Gene expression of collagen types Ⅸ and X in the lumbar disc

    Institute of Scientific and Technical Information of China (English)

    西永明; 胡有谷; 吕振华; 郑红军; 陈岩; 齐宗华

    2004-01-01

    Objective: To study gene expression of collagen types IX and X in human lumbar intervertebral discs during aging and degeneration and to explore the role of collagen types IX and X in disc degeneration.Methods: Fetal, adult and pathologic specimens were subjected to in situ hybridization with cDNA probes to investigate mRNA-expressions of types IX and X collagen gene.Results: In fetal intervertebral discs, positive mRNA hybridization signals of type IX collagen were concentrated in the nucleus pulposus and the inner layer of anulns fibrosns. Interstitial matrix of the nucleus pulposns also showed positive type X collagen staining. Positive mRNA hybridization signals of types IX and X were not detected in the middle and outer layers of anulus fibrosus. In adult specimens, expression of type IX collagen mRNA was markedly decreased. No hybridization signals of type X collagen was observed. As for pathological specimens, there was no gene expression of type IX collagen. In severe degenerated discs from adults, there were focal positive expressions of type X collagen. Conclusions: Obvious changes of collagen gene expression occur with aging. Expression of type IX collagen decreases in adult and pathological discs. Results of type X collagen expression suggest that type X collagen is expressed only in older adult and senile discs (I. E., when disc degeneration has already reached a terminal stage ),indicating the terminal stage of degeneration.

  13. Aeroacoustic Prediction Codes

    Science.gov (United States)

    Gliebe, P; Mani, R.; Shin, H.; Mitchell, B.; Ashford, G.; Salamah, S.; Connell, S.; Huff, Dennis (Technical Monitor)

    2000-01-01

    This report describes work performed on Contract NAS3-27720AoI 13 as part of the NASA Advanced Subsonic Transport (AST) Noise Reduction Technology effort. Computer codes were developed to provide quantitative prediction, design, and analysis capability for several aircraft engine noise sources. The objective was to provide improved, physics-based tools for exploration of noise-reduction concepts and understanding of experimental results. Methods and codes focused on fan broadband and 'buzz saw' noise and on low-emissions combustor noise and compliment work done by other contractors under the NASA AST program to develop methods and codes for fan harmonic tone noise and jet noise. The methods and codes developed and reported herein employ a wide range of approaches, from the strictly empirical to the completely computational, with some being semiempirical analytical, and/or analytical/computational. Emphasis was on capturing the essential physics while still considering method or code utility as a practical design and analysis tool for everyday engineering use. Codes and prediction models were developed for: (1) an improved empirical correlation model for fan rotor exit flow mean and turbulence properties, for use in predicting broadband noise generated by rotor exit flow turbulence interaction with downstream stator vanes: (2) fan broadband noise models for rotor and stator/turbulence interaction sources including 3D effects, noncompact-source effects. directivity modeling, and extensions to the rotor supersonic tip-speed regime; (3) fan multiple-pure-tone in-duct sound pressure prediction methodology based on computational fluid dynamics (CFD) analysis; and (4) low-emissions combustor prediction methodology and computer code based on CFD and actuator disk theory. In addition. the relative importance of dipole and quadrupole source mechanisms was studied using direct CFD source computation for a simple cascadeigust interaction problem, and an empirical combustor

  14. Coal extraction - environmental prediction

    Energy Technology Data Exchange (ETDEWEB)

    C. Blaine Cecil; Susan J. Tewalt

    2002-08-01

    To predict and help minimize the impact of coal extraction in the Appalachian region, the U.S. Geological Survey (USGS) is addressing selected mine-drainage issues through the following four interrelated studies: spatial variability of deleterious materials in coal and coal-bearing strata; kinetics of pyrite oxidation; improved spatial geologic models of the potential for drainage from abandoned coal mines; and methodologies for the remediation of waters discharged from coal mines. As these goals are achieved, the recovery of coal resources will be enhanced. 2 figs.

  15. Mathematics of Predicting Growth

    OpenAIRE

    Nielsen, Ron W

    2015-01-01

    Abstract. Mathematical methods of analysis of data and of predicting growth are discussed. The starting point is the analysis of the growth rates, which can be expressed as a function of time or as a function of the size of the growing entity. Application of these methods is illustrated using the world economic growth but they can be applied to any type of growth.Keywords. Growth rate, Differential equations, Gross Domestic Product, Economic growth.JEL. C01, C20, C50, C53, C60, C65, C80

  16. Foundations of predictive analytics

    CERN Document Server

    Wu, James

    2012-01-01

    Drawing on the authors' two decades of experience in applied modeling and data mining, Foundations of Predictive Analytics presents the fundamental background required for analyzing data and building models for many practical applications, such as consumer behavior modeling, risk and marketing analytics, and other areas. It also discusses a variety of practical topics that are frequently missing from similar texts. The book begins with the statistical and linear algebra/matrix foundation of modeling methods, from distributions to cumulant and copula functions to Cornish--Fisher expansion and o

  17. Asphalt pavement temperature prediction

    OpenAIRE

    Minhoto, Manuel; Pais, Jorge; Pereira, Paulo

    2006-01-01

    A 3-D finite element model (FEM) was developed to calculate the lemperature of an asphtalt rubber pavement localed in the Northeast of Portugal. The goal of the case study presented in this paper is to show the good accuracy temperature prediction tha can be obtained with this model when compared with the field pavement thermal condition obtained during a year. lnput data to the model are the hourly values for solar radiation and temperature and the mean daily value of wind speed obtained fr...

  18. Essays on Earnings Predictability

    DEFF Research Database (Denmark)

    Bruun, Mark

    This dissertation addresses the prediction of corporate earnings. The thesis aims to examine whether the degree of precision in earnings forecasts can be increased by basing them on historical financial ratios. Furthermore, the intent of the dissertation is to analyze whether accounting standards...... forecasts can be generated based on historical timeseries patterns of financial ratios. This is done by modeling the return on equity and the growth-rate in equity as two separate but correlated timeseries processes which converge to a long-term, constant level. Empirical results suggest that these earnings...

  19. Predicting Lotto Numbers

    DEFF Research Database (Denmark)

    Suetens, Sigrid; Galbo-Jørgensen, Claus B.; Tyran, Jean-Robert Karl

    2016-01-01

    as formalized in recent behavioral theory. In particular, players tend to bet less on numbers that have been drawn in the preceding week, as suggested by the ‘gambler’s fallacy’, and bet more on a number if it was frequently drawn in the recent past, consistent with the ‘hot-hand fallacy’.......We investigate the ‘law of small numbers’ using a data set on lotto gambling that allows us to measure players’ reactions to draws. While most players pick the same set of numbers week after week, we find that those who do change react on average as predicted by the law of small numbers...

  20. Predicting Lotto Numbers

    DEFF Research Database (Denmark)

    Suetens, Sigrid; Galbo-Jørgensen, Claus B.; Tyran, Jean-Robert Karl

    2015-01-01

    formalized in recent behavioral theory. In particular, players tend to bet less on numbers that have been drawn in the preceding week, as suggested by the ‘gambler’s fallacy’, and bet more on a number if it was frequently drawn in the recent past, consistent with the ‘hot-hand fallacy’.......We investigate the ‘law of small numbers’ using a data set on lotto gambling that allows us to measure players’ reactions to draws. While most players pick the same set of numbers week after week, we find that those who do change react on average as predicted by the law of small numbers as...

  1. Vertebral Fracture Prediction

    DEFF Research Database (Denmark)

    2008-01-01

    Vertebral Fracture Prediction A method of processing data derived from an image of at least part of a spine is provided for estimating the risk of a future fracture in vertebraeof the spine. Position data relating to at least four neighbouring vertebrae of the spine is processed. The curvature...... of the spine at at least two of the neighbouring vertebrae is calculated. The different curvature values are computed to obtain a value representative of the degree of irregularity in curvature of the spine and using the degree of irregularity, an estimate of the risk of a future fracture in vertebrae...

  2. Predicting Sustainable Work Behavior

    DEFF Research Database (Denmark)

    Hald, Kim Sundtoft

    2013-01-01

    Sustainable work behavior is an important issue for operations managers – it has implications for most outcomes of OM. This research explores the antecedents of sustainable work behavior. It revisits and extends the sociotechnical model developed by Brown et al. (2000) on predicting safe behavior....... Employee characteristics and general attitudes towards safety and work condition are included in the extended model. A survey was handed out to 654 employees in Chinese factories. This research contributes by demonstrating how employee- characteristics and general attitudes towards safety and work...... condition influence their sustainable work behavior. A new definition of sustainable work behavior is proposed....

  3. Neurological abnormalities predict disability

    DEFF Research Database (Denmark)

    Poggesi, Anna; Gouw, Alida; van der Flier, Wiesje;

    2014-01-01

    was performed. MRI assessment included age-related white matter changes (ARWMC) grading (mild, moderate, severe according to the Fazekas' scale), count of lacunar and non-lacunar infarcts, and global atrophy rating. Of the 633 (out of the 639 enrolled) patients with follow-up information (mean age 74.1 ± 5......, presence and number of neurological examination abnormalities predicted global functional decline independent of MRI lesions typical of the aging brain and other determinants of disability in the elderly. Systematically checking for neurological examination abnormalities in older patients may be cost...

  4. Predicting Lotto Numbers

    OpenAIRE

    Jorgensen, C.B.; Suetens, S.; Tyran, J.R.

    2011-01-01

    We investigate the “law of small numbers” using a unique panel data set on lotto gambling. Because we can track individual players over time, we can measure how they react to outcomes of recent lotto drawings. We can therefore test whether they behave as if they believe they can predict lotto numbers based on recent drawings. While most players pick the same set of numbers week after week without regards of numbers drawn or anything else, we find that those who do change, act on average in th...

  5. Predicting Alloreactivity in Transplantation

    Directory of Open Access Journals (Sweden)

    Kirsten Geneugelijk

    2014-01-01

    Full Text Available Human leukocyte Antigen (HLA mismatching leads to severe complications after solid-organ transplantation and hematopoietic stem-cell transplantation. The alloreactive responses underlying the posttransplantation complications include both direct recognition of allogeneic HLA by HLA-specific alloantibodies and T cells and indirect T-cell recognition. However, the immunogenicity of HLA mismatches is highly variable; some HLA mismatches lead to severe clinical B-cell- and T-cell-mediated alloreactivity, whereas others are well tolerated. Definition of the permissibility of HLA mismatches prior to transplantation allows selection of donor-recipient combinations that will have a reduced chance to develop deleterious host-versus-graft responses after solid-organ transplantation and graft-versus-host responses after hematopoietic stem-cell transplantation. Therefore, several methods have been developed to predict permissible HLA-mismatch combinations. In this review we aim to give a comprehensive overview about the current knowledge regarding HLA-directed alloreactivity and several developed in vitro and in silico tools that aim to predict direct and indirect alloreactivity.

  6. Compressor map prediction tool

    Science.gov (United States)

    Ravi, Arjun; Sznajder, Lukasz; Bennett, Ian

    2015-08-01

    Shell Global Solutions uses an in-house developed system for remote condition monitoring of centrifugal compressors. It requires field process data collected during operation to calculate and assess the machine's performance. Performance is assessed by comparing live results of polytropic head and efficiency versus design compressor curves provided by the Manufacturer. Typically, these design curves are given for specific suction conditions. The further these conditions on site deviate from those prescribed at design, the less accurate the health assessment of the compressor becomes. To address this specified problem, a compressor map prediction tool is proposed. The original performance curves of polytropic head against volumetric flow for varying rotational speeds are used as an input to define a range of Mach numbers within which the non-dimensional invariant performance curve of head and volume flow coefficient is generated. The new performance curves of polytropic head vs. flow for desired set of inlet conditions are then back calculated using the invariant non-dimensional curve. Within the range of Mach numbers calculated from design data, the proposed methodology can predict polytropic head curves at a new set of inlet conditions within an estimated 3% accuracy. The presented methodology does not require knowledge of detailed impeller geometry such as throat areas, blade number, blade angles, thicknesses nor other aspects of the aerodynamic design - diffusion levels, flow angles, etc. The only required mechanical design feature is the first impeller tip diameter. Described method makes centrifugal compressor surveillance activities more accurate, enabling precise problem isolation affecting machine's performance.

  7. Cooling pond temperature prediction

    International Nuclear Information System (INIS)

    A model is described which predicts temperature responses in the environment that are associated with the operation of a natural gas fueled thermoelectric power generation station. The model is a piecewise computer simulation, limited at present to closed cooling water systems. However, the techniques developed should be applicable to a much larger class of cooling system. The problem encountered consists of two parts: (1) data characterization and (2) modeling. An efficient characterization scheme for the environmental variables greatly simplifies the task of modeling. Methods borrowed from signal theory, but not yet applied to this field are applicable to and greatly simplify the digital computer investigation of environmental data. An optimal data set, from the point of view of information per unit cost, is described for the model

  8. Permeability prediction in chalks

    DEFF Research Database (Denmark)

    Alam, Mohammad Monzurul; Fabricius, Ida Lykke; Prasad, Manika

    2011-01-01

    The velocity of elastic waves is the primary datum available for acquiring information about subsurface characteristics such as lithology and porosity. Cheap and quick (spatial coverage, ease of measurement) information of permeability can be achieved, if sonic velocity is used for permeability......-permeability relationships were replaced by relationships between velocity of elastic waves and permeability using laboratory data, and the relationships were then applied to well-log data. We found that the permeability prediction in chalk and possibly other sediments with large surface areas could be improved...... significantly using the effective specific surface as the fluid-flow concept. The FZI unit is appropriate for highly permeable sedimentary rocks such as sandstones and limestones that have small surface areas....

  9. Motor degradation prediction methods

    Energy Technology Data Exchange (ETDEWEB)

    Arnold, J.R.; Kelly, J.F.; Delzingaro, M.J.

    1996-12-01

    Motor Operated Valve (MOV) squirrel cage AC motor rotors are susceptible to degradation under certain conditions. Premature failure can result due to high humidity/temperature environments, high running load conditions, extended periods at locked rotor conditions (i.e. > 15 seconds) or exceeding the motor`s duty cycle by frequent starts or multiple valve stroking. Exposure to high heat and moisture due to packing leaks, pressure seal ring leakage or other causes can significantly accelerate the degradation. ComEd and Liberty Technologies have worked together to provide and validate a non-intrusive method using motor power diagnostics to evaluate MOV rotor condition and predict failure. These techniques have provided a quick, low radiation dose method to evaluate inaccessible motors, identify degradation and allow scheduled replacement of motors prior to catastrophic failures.

  10. Motor degradation prediction methods

    International Nuclear Information System (INIS)

    Motor Operated Valve (MOV) squirrel cage AC motor rotors are susceptible to degradation under certain conditions. Premature failure can result due to high humidity/temperature environments, high running load conditions, extended periods at locked rotor conditions (i.e. > 15 seconds) or exceeding the motor's duty cycle by frequent starts or multiple valve stroking. Exposure to high heat and moisture due to packing leaks, pressure seal ring leakage or other causes can significantly accelerate the degradation. ComEd and Liberty Technologies have worked together to provide and validate a non-intrusive method using motor power diagnostics to evaluate MOV rotor condition and predict failure. These techniques have provided a quick, low radiation dose method to evaluate inaccessible motors, identify degradation and allow scheduled replacement of motors prior to catastrophic failures

  11. Plume rise predictions

    International Nuclear Information System (INIS)

    Anyone involved with diffusion calculations becomes well aware of the strong dependence of maximum ground concentrations on the effective stack height, h/sub e/. For most conditions chi/sub max/ is approximately proportional to h/sub e/-2, as has been recognized at least since 1936 (Bosanquet and Pearson). Making allowance for the gradual decrease in the ratio of vertical to lateral diffusion at increasing heights, the exponent is slightly larger, say chi/sub max/ approximately h/sub e/-2.3. In inversion breakup fumigation, the exponent is somewhat smaller; very crudely, chi/sub max/ approximately h/sub e/-1.5. In any case, for an elevated emission the dependence of chi/sub max/ on h/sub e/ is substantial. It is postulated that a really clever ignorant theoretician can disguise his ignorance with dimensionless constants. For most sources the effective stack height is considerably larger than the actual source height, h/sub s/. For instance, for power plants with no downwash problems, h/sub e/ is more than twice h/sub s/ whenever the wind is less than 10 m/sec, which is most of the time. This is unfortunate for anyone who has to predict ground concentrations, for he is likely to have to calculate the plume rise, Δh. Especially when using h/sub e/ = h/sub s/ + Δh instead of h/sub s/ may reduce chi/sub max/ by a factor of anywhere from 4 to infinity. Factors to be considered in making plume rise predictions are discussed

  12. Predicting the physics of particles

    International Nuclear Information System (INIS)

    A brief account is presented of the goals and methods of particle theorists, stressing the measurable quantities they would like to predict, the conventional starting points for such predictions, and some of the techniques used to arrive at a prediction. (author)

  13. Update on protein structure prediction

    DEFF Research Database (Denmark)

    Hubbard, T; Tramontano, A; Barton, G;

    1996-01-01

    Computational tools for protein structure prediction are of great interest to molecular, structural and theoretical biologists due to a rapidly increasing number of protein sequences with no known structure. In October 1995, a workshop was held at IRBM to predict as much as possible about a number...... of proteins of biological interest using ab initio pre!diction of fold recognition methods. 112 protein sequences were collected via an open invitation for target submissions. 17 were selected for prediction during the workshop and for 11 of these a prediction of some reliability could be made. We believe...

  14. Modeling and Prediction Overview

    Energy Technology Data Exchange (ETDEWEB)

    Ermak, D L

    2002-10-18

    Effective preparation for and response to the release of toxic materials into the atmosphere hinges on accurate predictions of the dispersion pathway, concentration, and ultimate fate of the chemical or biological agent. Of particular interest is the threat to civilian populations within major urban areas, which are likely targets for potential attacks. The goals of the CBNP Modeling and Prediction area are: (1) Development of a suite of validated, multi-scale, atmospheric transport and fate modeling capabilities for chemical and biological agent releases within the complex urban environment; (2) Integration of these models and related user tools into operational emergency response systems. Existing transport and fate models are being adapted to treat the complex atmospheric flows within and around structures (e.g., buildings, subway systems, urban areas) and over terrain. Relevant source terms and the chemical and physical behavior of gas- and particle-phase species (e.g., losses due to deposition, bio-agent viability, degradation) are also being developed and incorporated into the models. Model validation is performed using both laboratory and field data. CBNP is producing and testing a suite of models with differing levels of complexity and fidelity to address the full range of user needs and applications. Lumped-parameter transport models are being developed for subway systems and building interiors, supplemented by the use of computational fluid dynamics (CFD) models to describe the circulation within large, open spaces such as auditoriums. Both sophisticated CFD transport models and simpler fast-response models are under development to treat the complex flow around individual structures and arrays of buildings. Urban parameterizations are being incorporated into regional-scale weather forecast, meteorological data assimilation, and dispersion models for problems involving larger-scale urban and suburban areas. Source term and dose response models are being

  15. Earthquake prediction with electromagnetic phenomena

    Energy Technology Data Exchange (ETDEWEB)

    Hayakawa, Masashi, E-mail: hayakawa@hi-seismo-em.jp [Hayakawa Institute of Seismo Electomagnetics, Co. Ltd., University of Electro-Communications (UEC) Incubation Center, 1-5-1 Chofugaoka, Chofu Tokyo, 182-8585 (Japan); Advanced Wireless & Communications Research Center, UEC, Chofu Tokyo (Japan); Earthquake Analysis Laboratory, Information Systems Inc., 4-8-15, Minami-aoyama, Minato-ku, Tokyo, 107-0062 (Japan); Fuji Security Systems. Co. Ltd., Iwato-cho 1, Shinjyuku-ku, Tokyo (Japan)

    2016-02-01

    Short-term earthquake (EQ) prediction is defined as prospective prediction with the time scale of about one week, which is considered to be one of the most important and urgent topics for the human beings. If this short-term prediction is realized, casualty will be drastically reduced. Unlike the conventional seismic measurement, we proposed the use of electromagnetic phenomena as precursors to EQs in the prediction, and an extensive amount of progress has been achieved in the field of seismo-electromagnetics during the last two decades. This paper deals with the review on this short-term EQ prediction, including the impossibility myth of EQs prediction by seismometers, the reason why we are interested in electromagnetics, the history of seismo-electromagnetics, the ionospheric perturbation as the most promising candidate of EQ prediction, then the future of EQ predictology from two standpoints of a practical science and a pure science, and finally a brief summary.

  16. Earthquake prediction with electromagnetic phenomena

    International Nuclear Information System (INIS)

    Short-term earthquake (EQ) prediction is defined as prospective prediction with the time scale of about one week, which is considered to be one of the most important and urgent topics for the human beings. If this short-term prediction is realized, casualty will be drastically reduced. Unlike the conventional seismic measurement, we proposed the use of electromagnetic phenomena as precursors to EQs in the prediction, and an extensive amount of progress has been achieved in the field of seismo-electromagnetics during the last two decades. This paper deals with the review on this short-term EQ prediction, including the impossibility myth of EQs prediction by seismometers, the reason why we are interested in electromagnetics, the history of seismo-electromagnetics, the ionospheric perturbation as the most promising candidate of EQ prediction, then the future of EQ predictology from two standpoints of a practical science and a pure science, and finally a brief summary

  17. Protein Chemical Shift Prediction

    CERN Document Server

    Larsen, Anders S

    2014-01-01

    The protein chemical shifts holds a large amount of information about the 3-dimensional structure of the protein. A number of chemical shift predictors based on the relationship between structures resolved with X-ray crystallography and the corresponding experimental chemical shifts have been developed. These empirical predictors are very accurate on X-ray structures but tends to be insensitive to small structural changes. To overcome this limitation it has been suggested to make chemical shift predictors based on quantum mechanical(QM) calculations. In this thesis the development of the QM derived chemical shift predictor Procs14 is presented. Procs14 is based on 2.35 million density functional theory(DFT) calculations on tripeptides and contains corrections for hydrogen bonding, ring current and the effect of the previous and following residue. Procs14 is capable at performing predictions for the 13CA, 13CB, 13CO, 15NH, 1HN and 1HA backbone atoms. In order to benchmark Procs14, a number of QM NMR calculatio...

  18. Predictability of blocking

    International Nuclear Information System (INIS)

    Tibaldi and Molteni (1990, hereafter referred to as TM) had previously investigated operational blocking predictability by the ECMWF model and the possible relationships between model systematic error and blocking in the winter season of the Northern Hemisphere, using seven years of ECMWF operational archives of analyses and day 1 to 10 forecasts. They showed that fewer blocking episodes than in the real atmosphere were generally simulated by the model, and that this deficiency increased with increasing forecast time. As a consequence of this, a major contribution to the systematic error in the winter season was shown to derive from the inability of the model to properly forecast blocking. In this study, the analysis performed in TM for the first seven winter seasons of the ECMWF operational model is extended to the subsequent five winters, during which model development, reflecting both resolution increases and parametrisation modifications, continued unabated. In addition the objective blocking index developed by TM has been applied to the observed data to study the natural low frequency variability of blocking. The ability to simulate blocking of some climate models has also been tested

  19. An exact prediction of

    International Nuclear Information System (INIS)

    We propose that the expectation value of a circular BPS-Wilson loop in N=4 supersymmetric Yang--Mills can be calculated exactly, to all orders in a 1/N expansion and to all orders in g2N. Using the AdS/CFT duality, this result yields a prediction of the value of the string amplitude with a circular boundary to all orders in α' and to all orders in gs. We then compare this result with string theory. We find that the gauge theory calculation, for large g2N and to all orders in the 1/N2 expansion, does agree with the leading string theory calculation, to all orders in gs and to lowest order in α'. We also find a relation between the expectation value of any closed smooth Wilson loop and the loop related to it by an inversion that takes a point along the loop to infinity, and compare this result, again successfully, with string theory

  20. Predictive Analysis for Social Processes II: Predictability and Warning Analysis

    CERN Document Server

    Colbaugh, Richard

    2009-01-01

    This two-part paper presents a new approach to predictive analysis for social processes. Part I identifies a class of social processes, called positive externality processes, which are both important and difficult to predict, and introduces a multi-scale, stochastic hybrid system modeling framework for these systems. In Part II of the paper we develop a systems theory-based, computationally tractable approach to predictive analysis for these systems. Among other capabilities, this analytic methodology enables assessment of process predictability, identification of measurables which have predictive power, discovery of reliable early indicators for events of interest, and robust, scalable prediction. The potential of the proposed approach is illustrated through case studies involving online markets, social movements, and protest behavior.

  1. Melanoma risk prediction models

    Directory of Open Access Journals (Sweden)

    Nikolić Jelena

    2014-01-01

    Full Text Available Background/Aim. The lack of effective therapy for advanced stages of melanoma emphasizes the importance of preventive measures and screenings of population at risk. Identifying individuals at high risk should allow targeted screenings and follow-up involving those who would benefit most. The aim of this study was to identify most significant factors for melanoma prediction in our population and to create prognostic models for identification and differentiation of individuals at risk. Methods. This case-control study included 697 participants (341 patients and 356 controls that underwent extensive interview and skin examination in order to check risk factors for melanoma. Pairwise univariate statistical comparison was used for the coarse selection of the most significant risk factors. These factors were fed into logistic regression (LR and alternating decision trees (ADT prognostic models that were assessed for their usefulness in identification of patients at risk to develop melanoma. Validation of the LR model was done by Hosmer and Lemeshow test, whereas the ADT was validated by 10-fold cross-validation. The achieved sensitivity, specificity, accuracy and AUC for both models were calculated. The melanoma risk score (MRS based on the outcome of the LR model was presented. Results. The LR model showed that the following risk factors were associated with melanoma: sunbeds (OR = 4.018; 95% CI 1.724- 9.366 for those that sometimes used sunbeds, solar damage of the skin (OR = 8.274; 95% CI 2.661-25.730 for those with severe solar damage, hair color (OR = 3.222; 95% CI 1.984-5.231 for light brown/blond hair, the number of common naevi (over 100 naevi had OR = 3.57; 95% CI 1.427-8.931, the number of dysplastic naevi (from 1 to 10 dysplastic naevi OR was 2.672; 95% CI 1.572-4.540; for more than 10 naevi OR was 6.487; 95%; CI 1.993-21.119, Fitzpatricks phototype and the presence of congenital naevi. Red hair, phototype I and large congenital naevi were

  2. PREDICTING TURBINE STAGE PERFORMANCE

    Science.gov (United States)

    Boyle, R. J.

    1994-01-01

    This program was developed to predict turbine stage performance taking into account the effects of complex passage geometries. The method uses a quasi-3D inviscid-flow analysis iteratively coupled to calculated losses so that changes in losses result in changes in the flow distribution. In this manner the effects of both the geometry on the flow distribution and the flow distribution on losses are accounted for. The flow may be subsonic or shock-free transonic. The blade row may be fixed or rotating, and the blades may be twisted and leaned. This program has been applied to axial and radial turbines, and is helpful in the analysis of mixed flow machines. This program is a combination of the flow analysis programs MERIDL and TSONIC coupled to the boundary layer program BLAYER. The subsonic flow solution is obtained by a finite difference, stream function analysis. Transonic blade-to-blade solutions are obtained using information from the finite difference, stream function solution with a reduced flow factor. Upstream and downstream flow variables may vary from hub to shroud and provision is made to correct for loss of stagnation pressure. Boundary layer analyses are made to determine profile and end-wall friction losses. Empirical loss models are used to account for incidence, secondary flow, disc windage, and clearance losses. The total losses are then used to calculate stator, rotor, and stage efficiency. This program is written in FORTRAN IV for batch execution and has been implemented on an IBM 370/3033 under TSS with a central memory requirement of approximately 4.5 Megs of 8 bit bytes. This program was developed in 1985.

  3. Predictions From Eternal Inflation

    Science.gov (United States)

    Leichenauer, Stefan

    We investigate the physics of eternal inflation, particularly the use of multiverse ideas to explain the observed values of the cosmological constant and the coincidences of cosmological timescales. We begin by reviewing eternal inflation, the multiverse, and the resulting measure problem. Then follows a detailed study of proposals to solve the measure problem, both analytical and numerical, including an analysis of their predictions for cosmological observables. A key outcome of this investigation is that the traditional anthropic calculations, which take into account the necessity of galaxies and heavy elements to produce observers, are redundant in our framework. The cosmological coincidence problem, the seemingly coincidental equality of the timescales of observation and of vacuum domination, is solved for the first time without appeal to detailed anthropic assumptions: very general geometric considerations do the job automatically. We also estimate a 10% likelihood that evidence for eternal inflation will be found in upcoming measurements of the energy density of the universe. Encouraged by this success, we go on to construct a modified version of the light-cone time measure which has conceptual advantages but also reproduces the phenomenology of its predecessor. We complete our study of the measure problem by noting that for a wide class of proposed solutions, including the one developed here, there is an implicit assumption being made about a catastrophic end to the universe. Finally, as a by-product of this research program we find geometries which violate some of the accepted common knowledge on holographic entropy bounds. We point this out and conjecture a general result.

  4. Long Range Aircraft Trajectory Prediction

    OpenAIRE

    Magister, Tone

    2009-01-01

    The subject of the paper is the improvement of the aircraft future trajectory prediction accuracy for long-range airborne separation assurance. The strategic planning of safe aircraft flights and effective conflict avoidance tactics demand timely and accurate conflict detection based upon future four–dimensional airborne traffic situation prediction which is as accurate as each aircraft flight trajectory prediction. The improved kinematics model of aircraft relative flight considering flight ...

  5. Predicting cognitive change within domains

    OpenAIRE

    Duff, Kevin; Beglinger, Leigh J.; Moser, David J.; Paulsen, Jane S.

    2010-01-01

    Standardized regression based (SRB) formulas, a method for predicting cognitive change across time, traditionally use baseline performance on a neuropsychological measure to predict future performance on that same measure. However, there are instances in which the same tests may not be given at follow-up assessments (e.g., lack of continuity of provider, avoiding practice effects). The current study sought to expand this methodology by developing SRBs to predict performance on different tests...

  6. Predicting Acoustics in Class Rooms

    DEFF Research Database (Denmark)

    Christensen, Claus Lynge; Rindel, Jens Holger

    2005-01-01

    Typical class rooms have fairly simple geometries, even so room acoustics in this type of room is difficult to predict using today's room acoustic computer modeling software. The reasons why acoustics of class rooms are harder to predict than acoustics of complicated concert halls might be explai......Typical class rooms have fairly simple geometries, even so room acoustics in this type of room is difficult to predict using today's room acoustic computer modeling software. The reasons why acoustics of class rooms are harder to predict than acoustics of complicated concert halls might...... with surface scattering is presented. Each of the two scattering effects is modeled as frequency dependent functions....

  7. Neural Correlates of Predictive Saccades.

    Science.gov (United States)

    Lee, Stephen M; Peltsch, Alicia; Kilmade, Maureen; Brien, Donald C; Coe, Brian C; Johnsrude, Ingrid S; Munoz, Douglas P

    2016-08-01

    Every day we generate motor responses that are timed with external cues. This phenomenon of sensorimotor synchronization has been simplified and studied extensively using finger tapping sequences that are executed in synchrony with auditory stimuli. The predictive saccade paradigm closely resembles the finger tapping task. In this paradigm, participants follow a visual target that "steps" between two fixed locations on a visual screen at predictable ISIs. Eventually, the time from target appearance to saccade initiation (i.e., saccadic RT) becomes predictive with values nearing 0 msec. Unlike the finger tapping literature, neural control of predictive behavior described within the eye movement literature has not been well established and is inconsistent, especially between neuroimaging and patient lesion studies. To resolve these discrepancies, we used fMRI to investigate the neural correlates of predictive saccades by contrasting brain areas involved with behavior generated from the predictive saccade task with behavior generated from a reactive saccade task (saccades are generated toward targets that are unpredictably timed). We observed striking differences in neural recruitment between reactive and predictive conditions: Reactive saccades recruited oculomotor structures, as predicted, whereas predictive saccades recruited brain structures that support timing in motor responses, such as the crus I of the cerebellum, and structures commonly associated with the default mode network. Therefore, our results were more consistent with those found in the finger tapping literature. PMID:27054397

  8. Predicting Marital Success with PREPARE: A Predictive Validity Study.

    Science.gov (United States)

    Fowers, Blaine J.; Olson, David H.

    1986-01-01

    Assessed the utility of the premarital inventory, PREPARE, in predicting marital success. Conducted a three-year follow-up study with couples (N=164) who took PREPARE during their engagement. Found that the PREPARE scores from three months before marriage could predict with 80-90% accuracy which couples were separated and divorced from those that…

  9. Predictability and Prediction for an Experimental Cultural Market

    Science.gov (United States)

    Colbaugh, Richard; Glass, Kristin; Ormerod, Paul

    Individuals are often influenced by the behavior of others, for instance because they wish to obtain the benefits of coordinated actions or infer otherwise inaccessible information. In such situations this social influence decreases the ex ante predictability of the ensuing social dynamics. We claim that, interestingly, these same social forces can increase the extent to which the outcome of a social process can be predicted very early in the process. This paper explores this claim through a theoretical and empirical analysis of the experimental music market described and analyzed in [1]. We propose a very simple model for this music market, assess the predictability of market outcomes through formal analysis of the model, and use insights derived through this analysis to develop algorithms for predicting market share winners, and their ultimate market shares, in the very early stages of the market. The utility of these predictive algorithms is illustrated through analysis of the experimental music market data sets [2].

  10. Predicting epileptic seizures in advance.

    Directory of Open Access Journals (Sweden)

    Negin Moghim

    Full Text Available Epilepsy is the second most common neurological disorder, affecting 0.6-0.8% of the world's population. In this neurological disorder, abnormal activity of the brain causes seizures, the nature of which tend to be sudden. Antiepileptic Drugs (AEDs are used as long-term therapeutic solutions that control the condition. Of those treated with AEDs, 35% become resistant to medication. The unpredictable nature of seizures poses risks for the individual with epilepsy. It is clearly desirable to find more effective ways of preventing seizures for such patients. The automatic detection of oncoming seizures, before their actual onset, can facilitate timely intervention and hence minimize these risks. In addition, advance prediction of seizures can enrich our understanding of the epileptic brain. In this study, drawing on the body of work behind automatic seizure detection and prediction from digitised Invasive Electroencephalography (EEG data, a prediction algorithm, ASPPR (Advance Seizure Prediction via Pre-ictal Relabeling, is described. ASPPR facilitates the learning of predictive models targeted at recognizing patterns in EEG activity that are in a specific time window in advance of a seizure. It then exploits advanced machine learning coupled with the design and selection of appropriate features from EEG signals. Results, from evaluating ASPPR independently on 21 different patients, suggest that seizures for many patients can be predicted up to 20 minutes in advance of their onset. Compared to benchmark performance represented by a mean S1-Score (harmonic mean of Sensitivity and Specificity of 90.6% for predicting seizure onset between 0 and 5 minutes in advance, ASPPR achieves mean S1-Scores of: 96.30% for prediction between 1 and 6 minutes in advance, 96.13% for prediction between 8 and 13 minutes in advance, 94.5% for prediction between 14 and 19 minutes in advance, and 94.2% for prediction between 20 and 25 minutes in advance.

  11. Solomonoff Prediction and Occam's Razor

    NARCIS (Netherlands)

    Sterkenburg, T.F.

    2016-01-01

    Algorithmic information theory gives an idealized notion of compressibility that is often presented as an objective measure of simplicity. It is suggested at times that Solomonoff prediction, or algorithmic information theory in a predictive setting, can deliver an argument to justify Occam’s razor.

  12. Dividend Predictability Around the World

    DEFF Research Database (Denmark)

    Rangvid, Jesper; Schmeling, Maik; Schrimpf, Andreas

    We show that dividend growth predictability by the dividend yield is the rule rather than the exception in global equity markets. Dividend predictability is weaker, however, in large and developed markets where dividends are smoothed more, the typical firm is large, and volatility is lower. Our f...

  13. Predicting responses in multiple environments

    NARCIS (Netherlands)

    Malosetti Zunin, Marcos; Bustos-Korts, Daniela; Boer, Martin P.; Eeuwijk, van Fred A.

    2016-01-01

    Prediction of the phenotypes for a set of genotypes across multiple environments is a fundamental task in any plant breeding program. Genomic prediction (GP) can assist selection decisions by combining incomplete phenotypic information over multiple environments (MEs) with dense sets of markers.

  14. Can Satellites Aid Earthquake Predictions?

    Institute of Scientific and Technical Information of China (English)

    John Roach; 李晓辉

    2004-01-01

    @@ Earthquake prediction is an imprecise science, and to illustrate the point,many experts point to the story of Tangshen①, China. On July 28, 1976, a magnitude② 7. 6 earthquake struck the city of Tangshen, China, without warning. None of the signs of the successful prediction from a year and half earlier were present. An estimated 250,000 people died.

  15. Zephyr - the next generation prediction

    DEFF Research Database (Denmark)

    Giebel, G.; Landberg, L.; Nielsen, Torben Skov;

    2001-01-01

    Two of the most successful short-term prediction models (and the only ones in operational use at utilities) are going to be merged into one: the Risø model, developed by Landberg and the Wind Power Prediction Tool WPPT, developed at the Department of Mathematical Modelling IMM of the Danish Techn...

  16. Regional downscaling of decadal predictions

    Science.gov (United States)

    Feldmann, H.

    2014-12-01

    During the last years the research field of decadal predictions gained increased attention. Its intention is to exploit the predictability derived from slowly varying components of the climate system on inter-annual to decadal time-scales. Such predictions are mostly performed using ensembles of global earth system models. The prediction systems are able to achieve a relatively high predictive skill over some oceanic regions, like the North Atlantic sector. But potential users of decadal predictions are often interested in forecasts over land areas and require a higher resolution, too. Therefore, the German research program MiKlip develops a decadal ensemble predictions system with regional downscaling as an additional option. Dynamical downscaling and a statistical-dynamical downscaling approach are applied within the MiKlip regionalization module. The global prediction system consists of the MPI-ESM model. Different RCMs are used for the downscaling, e.g. CCLM and REMO. The focus regions are Europe and Western Africa. Hindcast experiments for the period 1960 - 2013 were performed to assess the general skill of the prediction system. Of special interest is the value added by the regional downscaling. For mean quantities, like annual mean temperature and precipitation, the predictive skill is comparable between the global and the downscaled systems. For extremes on the other hand there seems to be an improvement by the RCM ensemble. The skill strongly varies on sub-continental regions and with the season. The lead time up to which a positive predictive skill can be achieved depends on the parameter and season, too. A further goal is to assess the potential for valuable information, which can be derived from predicting long-term variations of the European climate. The leading mode of decadal variability in the European/Atlantic sector is the Atlantic Multidecadal Variation (AMV). The potential predictability from AMV teleconnections especially for extreme value

  17. Prediction of molecular crystal structures

    CERN Document Server

    Beyer, T

    2001-01-01

    The ab initio prediction of molecular crystal structures is a scientific challenge. Reliability of first-principle prediction calculations would show a fundamental understanding of crystallisation. Crystal structure prediction is also of considerable practical importance as different crystalline arrangements of the same molecule in the solid state (polymorphs)are likely to have different physical properties. A method of crystal structure prediction based on lattice energy minimisation has been developed in this work. The choice of the intermolecular potential and of the molecular model is crucial for the results of such studies and both of these criteria have been investigated. An empirical atom-atom repulsion-dispersion potential for carboxylic acids has been derived and applied in a crystal structure prediction study of formic, benzoic and the polymorphic system of tetrolic acid. As many experimental crystal structure determinations at different temperatures are available for the polymorphic system of parac...

  18. Prediction, Regression and Critical Realism

    DEFF Research Database (Denmark)

    Næss, Petter

    2004-01-01

    This paper considers the possibility of prediction in land use planning, and the use of statistical research methods in analyses of relationships between urban form and travel behaviour. Influential writers within the tradition of critical realism reject the possibility of predicting social...... of prediction necessary and possible in spatial planning of urban development. Finally, the political implications of positions within theory of science rejecting the possibility of predictions about social phenomena are addressed....... phenomena. This position is fundamentally problematic to public planning. Without at least some ability to predict the likely consequences of different proposals, the justification for public sector intervention into market mechanisms will be frail. Statistical methods like regression analyses are commonly...

  19. Predictability of Mobile Phone Associations

    DEFF Research Database (Denmark)

    Jensen, Bjørn Sand; Larsen, Jan; Hansen, Lars Kai;

    2010-01-01

    Prediction and understanding of human behavior is of high importance in many modern applications and research areas ranging from context-aware services, wireless resource allocation to social sciences. In this study we collect a novel dataset using standard mobile phones and analyze how...... the predictability of mobile sensors, acting as proxies for humans, change with time scale and sensor type such as GSM and WLAN. Applying recent information theoretic methods, it is demonstrated that an upper bound on predictability is relatively high for all sensors given the complete history (typically above 90......%). The relation between time scale and the predictability bound is examined for GSM and WLAN sensors, and both are found to have predictable and non-trivial behavior even on quite short time scales. The analysis provides valuable insight into aspects such as time scale and spatial quantization, state...

  20. Universal Prediction of Selected Bits

    CERN Document Server

    Lattimore, Tor; Gavane, Vaibhav

    2011-01-01

    Many learning tasks can be viewed as sequence prediction problems. For example, online classification can be converted to sequence prediction with the sequence being pairs of input/target data and where the goal is to correctly predict the target data given input data and previous input/target pairs. Solomonoff induction is known to solve the general sequence prediction problem, but only if the entire sequence is sampled from a computable distribution. In the case of classification and discriminative learning though, only the targets need be structured (given the inputs). We show that the normalised version of Solomonoff induction can still be used in this case, and more generally that it can detect any recursive sub-pattern (regularity) within an otherwise completely unstructured sequence. It is also shown that the unnormalised version can fail to predict very simple recursive sub-patterns.

  1. Numerical weather prediction model tuning via ensemble prediction system

    Science.gov (United States)

    Jarvinen, H.; Laine, M.; Ollinaho, P.; Solonen, A.; Haario, H.

    2011-12-01

    This paper discusses a novel approach to tune predictive skill of numerical weather prediction (NWP) models. NWP models contain tunable parameters which appear in parameterizations schemes of sub-grid scale physical processes. Currently, numerical values of these parameters are specified manually. In a recent dual manuscript (QJRMS, revised) we developed a new concept and method for on-line estimation of the NWP model parameters. The EPPES ("Ensemble prediction and parameter estimation system") method requires only minimal changes to the existing operational ensemble prediction infra-structure and it seems very cost-effective because practically no new computations are introduced. The approach provides an algorithmic decision making tool for model parameter optimization in operational NWP. In EPPES, statistical inference about the NWP model tunable parameters is made by (i) generating each member of the ensemble of predictions using different model parameter values, drawn from a proposal distribution, and (ii) feeding-back the relative merits of the parameter values to the proposal distribution, based on evaluation of a suitable likelihood function against verifying observations. In the presentation, the method is first illustrated in low-order numerical tests using a stochastic version of the Lorenz-95 model which effectively emulates the principal features of ensemble prediction systems. The EPPES method correctly detects the unknown and wrongly specified parameters values, and leads to an improved forecast skill. Second, results with an atmospheric general circulation model based ensemble prediction system show that the NWP model tuning capacity of EPPES scales up to realistic models and ensemble prediction systems. Finally, a global top-end NWP model tuning exercise with preliminary results is published.

  2. The Theory of Linear Prediction

    CERN Document Server

    Vaidyanathan, PP

    2007-01-01

    Linear prediction theory has had a profound impact in the field of digital signal processing. Although the theory dates back to the early 1940s, its influence can still be seen in applications today. The theory is based on very elegant mathematics and leads to many beautiful insights into statistical signal processing. Although prediction is only a part of the more general topics of linear estimation, filtering, and smoothing, this book focuses on linear prediction. This has enabled detailed discussion of a number of issues that are normally not found in texts. For example, the theory of vecto

  3. Confidence scores for prediction models

    DEFF Research Database (Denmark)

    Gerds, Thomas Alexander; van de Wiel, MA

    2011-01-01

    modelling strategy is applied to different training sets. For each modelling strategy we estimate a confidence score based on the same repeated bootstraps. A new decomposition of the expected Brier score is obtained, as well as the estimates of population average confidence scores. The latter can be used...... to distinguish rival prediction models with similar prediction performances. Furthermore, on the subject level a confidence score may provide useful supplementary information for new patients who want to base a medical decision on predicted risk. The ideas are illustrated and discussed using data from cancer...

  4. Adaptive filtering prediction and control

    CERN Document Server

    Goodwin, Graham C

    2009-01-01

    Preface1. Introduction to Adaptive TechniquesPart 1. Deterministic Systems2. Models for Deterministic Dynamical Systems3. Parameter Estimation for Deterministic Systems4. Deterministic Adaptive Prediction5. Control of Linear Deterministic Systems6. Adaptive Control of Linear Deterministic SystemsPart 2. Stochastic Systems7. Optimal Filtering and Prediction8. Parameter Estimation for Stochastic Dynamic Systems9. Adaptive Filtering and Prediction10. Control of Stochastic Systems11. Adaptive Control of Stochastic SystemsAppendicesA. A Brief Review of Some Results from Systems TheoryB. A Summary o

  5. Dividend Predictability around the World

    DEFF Research Database (Denmark)

    Rangvid, Jesper; Schmeling, Maik; Schrimpf, Andreas

    The common perception in the literature is that current dividend yields are uninformative about future dividends, but contain some information about future stock returns. In this paper, we show that this finding reverses when looking at a broad panel of countries outside the U.S.. In particular, we...... demonstrate that aggregate dividend growth rates are highly predictable by the dividend yield and that dividend predictability is clearly stronger than return predictability in medium-sized and smaller countries that account for the majority of countries in the world. We show that this is true both in the...

  6. Arctic Sea Ice Predictability and the Sea Ice Prediction Network

    Science.gov (United States)

    Wiggins, H. V.; Stroeve, J. C.

    2014-12-01

    Drastic reductions in Arctic sea ice cover have increased the demand for Arctic sea ice predictions by a range of stakeholders, including local communities, resource managers, industry and the public. The science of sea-ice prediction has been challenged to keep up with these developments. Efforts such as the SEARCH Sea Ice Outlook (SIO; http://www.arcus.org/sipn/sea-ice-outlook) and the Sea Ice for Walrus Outlook have provided a forum for the international sea-ice prediction and observing community to explore and compare different approaches. The SIO, originally organized by the Study of Environmental Change (SEARCH), is now managed by the new Sea Ice Prediction Network (SIPN), which is building a collaborative network of scientists and stakeholders to improve arctic sea ice prediction. The SIO synthesizes predictions from a variety of methods, including heuristic and from a statistical and/or dynamical model. In a recent study, SIO data from 2008 to 2013 were analyzed. The analysis revealed that in some years the predictions were very successful, in other years they were not. Years that were anomalous compared to the long-term trend have proven more difficult to predict, regardless of which method was employed. This year, in response to feedback from users and contributors to the SIO, several enhancements have been made to the SIO reports. One is to encourage contributors to provide spatial probability maps of sea ice cover in September and the first day each location becomes ice-free; these are an example of subseasonal to seasonal, local-scale predictions. Another enhancement is a separate analysis of the modeling contributions. In the June 2014 SIO report, 10 of 28 outlooks were produced from models that explicitly simulate sea ice from dynamic-thermodynamic sea ice models. Half of the models included fully-coupled (atmosphere, ice, and ocean) models that additionally employ data assimilation. Both of these subsets (models and coupled models with data

  7. Chemiluminescent prediction of service life

    Science.gov (United States)

    Hassell, J. A.; Mendenhall, G. D.; Nathan, R. A.

    1976-01-01

    Technique can be used to predict polymer degradation under actual expected-use conditions, without imposing artificial conditions. Smooth or linear correlations are obtained between chemiluminescence and physical properties of purified polymer gums.

  8. Prediction based on mean subset

    DEFF Research Database (Denmark)

    Øjelund, Henrik; Brown, P. J.; Madsen, Henrik;

    2002-01-01

    Shrinkage methods have traditionally been applied in prediction problems. In this article we develop a shrinkage method (mean subset) that forms an average of regression coefficients from individual subsets of the explanatory variables. A Bayesian approach is taken to derive an expression of how...... the coefficient vectors from each subset should be weighted. It is not computationally feasible to calculate the mean subset coefficient vector for larger problems, and thus we suggest an algorithm to find an approximation to the mean subset coefficient vector. In a comprehensive Monte Carlo simulation study......, it is found that the proposed mean subset method has superior prediction performance than prediction based on the best subset method, and in some settings also better than the ridge regression and lasso methods. The conclusions drawn from the Monte Carlo study is corroborated in an example in which prediction...

  9. Predictive Models and Computational Embryology

    Science.gov (United States)

    EPA’s ‘virtual embryo’ project is building an integrative systems biology framework for predictive models of developmental toxicity. One schema involves a knowledge-driven adverse outcome pathway (AOP) framework utilizing information from public databases, standardized ontologies...

  10. Trading network predicts stock price.

    Science.gov (United States)

    Sun, Xiao-Qian; Shen, Hua-Wei; Cheng, Xue-Qi

    2014-01-16

    Stock price prediction is an important and challenging problem for studying financial markets. Existing studies are mainly based on the time series of stock price or the operation performance of listed company. In this paper, we propose to predict stock price based on investors' trading behavior. For each stock, we characterize the daily trading relationship among its investors using a trading network. We then classify the nodes of trading network into three roles according to their connectivity pattern. Strong Granger causality is found between stock price and trading relationship indices, i.e., the fraction of trading relationship among nodes with different roles. We further predict stock price by incorporating these trading relationship indices into a neural network based on time series of stock price. Experimental results on 51 stocks in two Chinese Stock Exchanges demonstrate the accuracy of stock price prediction is significantly improved by the inclusion of trading relationship indices.

  11. Trading Network Predicts Stock Price

    Science.gov (United States)

    Sun, Xiao-Qian; Shen, Hua-Wei; Cheng, Xue-Qi

    2014-01-01

    Stock price prediction is an important and challenging problem for studying financial markets. Existing studies are mainly based on the time series of stock price or the operation performance of listed company. In this paper, we propose to predict stock price based on investors' trading behavior. For each stock, we characterize the daily trading relationship among its investors using a trading network. We then classify the nodes of trading network into three roles according to their connectivity pattern. Strong Granger causality is found between stock price and trading relationship indices, i.e., the fraction of trading relationship among nodes with different roles. We further predict stock price by incorporating these trading relationship indices into a neural network based on time series of stock price. Experimental results on 51 stocks in two Chinese Stock Exchanges demonstrate the accuracy of stock price prediction is significantly improved by the inclusion of trading relationship indices.

  12. Prediction for new magnetoelectric fluorides

    NARCIS (Netherlands)

    Nenert, G.; Palstra, T. T. M.

    2007-01-01

    We use symmetry considerations in order to predict new magnetoelectric fluorides. In addition to these magnetoelectric properties, we discuss which among these fluorides are the ones susceptible to present multiferroic properties. We emphasize that several materials exhibit ferromagnetic properties.

  13. Aeroacoustic Prediction and Noise Reduction

    OpenAIRE

    Delfs, Jan Werner

    2011-01-01

    An overview is given about aeroacoustic prediction and noise reduction technology from the field of aircraft noise. The simulation philosophy of the prediction methods is related to real world application, i.e. high Reynolds number flows, typical for aircraft. Noise reduction concepts are studied in two ways i) through a silent by design approach and b) by add-on treatments for existing aircraft components. Challenges are identified for future research.

  14. Challenges in Aircraft Noise Prediction

    OpenAIRE

    Filippone A

    2014-01-01

    This contribution addresses the problem of aircraft noise prediction using theoretical methods. The problem is set in context with the needs at several levels to produce noise characterisation from commercial aircraft powered by gas turbine engines. We describe very briefly the computational model (whilst referring the reader to the appropriate literature), and provide examples of noise predictions and comparisons with measured data, where possible. We focus on the issue of stochastic analysi...

  15. Predicting Strategy and Listening Comprehension

    OpenAIRE

    Yongmei Jiang

    2009-01-01

    The author found certain potential obstacles that students encounter in their listening class, which she believes should be removed by a good class teaching method. However, traditional listening class fails. She goes on to explore integrating strategies into listening class, among the many strategies she choose the prediction strategy and describes it in three stages: Pre-listening, while-listening, and post-listening. Then a real model of applying prediction in listening class is given, who...

  16. Can Scientific Impact Be Predicted?

    OpenAIRE

    Dong, Yuxiao; Johnson, Reid A.; Chawla, Nitesh V

    2016-01-01

    A widely used measure of scientific impact is citations. However, due to their heavy-tailed distribution, citations are fundamentally difficult to predict. Instead, to characterize scientific impact, we address two analogous questions asked by many scientific researchers: "How will my h-index evolve over time, and which of my previously or newly published papers will contribute to it?" To answer these questions, we perform two related tasks. First, we develop a model to predict authors' futur...

  17. Prediction of molecular crystal structures

    Energy Technology Data Exchange (ETDEWEB)

    Beyer, Theresa

    2001-07-01

    The ab initio prediction of molecular crystal structures is a scientific challenge. Reliability of first-principle prediction calculations would show a fundamental understanding of crystallisation. Crystal structure prediction is also of considerable practical importance as different crystalline arrangements of the same molecule in the solid state (polymorphs)are likely to have different physical properties. A method of crystal structure prediction based on lattice energy minimisation has been developed in this work. The choice of the intermolecular potential and of the molecular model is crucial for the results of such studies and both of these criteria have been investigated. An empirical atom-atom repulsion-dispersion potential for carboxylic acids has been derived and applied in a crystal structure prediction study of formic, benzoic and the polymorphic system of tetrolic acid. As many experimental crystal structure determinations at different temperatures are available for the polymorphic system of paracetamol (acetaminophen), the influence of the variations of the molecular model on the crystal structure lattice energy minima, has also been studied. The general problem of prediction methods based on the assumption that the experimental thermodynamically stable polymorph corresponds to the global lattice energy minimum, is that more hypothetical low lattice energy structures are found within a few kJ mol{sup -1} of the global minimum than are likely to be experimentally observed polymorphs. This is illustrated by the results for molecule I, 3-oxabicyclo(3.2.0)hepta-1,4-diene, studied for the first international blindtest for small organic crystal structures organised by the Cambridge Crystallographic Data Centre (CCDC) in May 1999. To reduce the number of predicted polymorphs, additional factors to thermodynamic criteria have to be considered. Therefore the elastic constants and vapour growth morphologies have been calculated for the lowest lattice energy

  18. Working postures: prediction and evaluation

    OpenAIRE

    Delleman, N.J.

    1999-01-01

    To date, workstation designers cannot see the effects of a design on working posture before a mock-up/prototype is available. At that moment, usually the margin for creating the conditions required for adopting favourable working postures is still very limited. Posture prediction at an early design phase, i.e. at the CAD screen, would enhance full consider-ation of ergonomics among other design aspects, as well as reducing costs for proper workstation design. For prediction, however, the dete...

  19. Seasonal Drought Prediction in India

    Science.gov (United States)

    Shah, R.; Mishra, V.

    2015-12-01

    Drought is among the most costly natural disasters in India. Seasonal prediction of drought can assist planners to manage agriculture and water resources. Such information can be valuable for a country like India where 60% of agriculture is rain-fed. Here we evaluate precipitation and temperature forecast from the NCEP's CFSV2 for seasonal drought prediction in India. We demonstrate the utility of the seasonal prediction of precipitation and temperature for drought forecast at 1-2 months lead time at a high spatial resolution. Precipitation from CFSv2 showed moderate correlations with observed up to two months lead. For one month lead, we found a significant correlation between CFSv2 and observed precipitation during winter season. Air temperature from the CFSv2 showed a good correlation with observed temperature during the winter. We forced the Variable Infiltration Capacity (VIC) model with the CFSv2 forecast of precipitation and air temperature to generate forecast of hydrologic variables such as soil moisture and total runoff. We find that errors of the prediction reduce for the two month lead time in the majority of the study domain except the northern India. Skills of Initial Hydrologic Conditions combined with moderate skills of forcings based on the CFSv2 showed ability of drought prediction in India. The developed system was able to successfully predict observed top layer soil moisture and observed drought based on satellite remote sensing in India.

  20. Prediction of interannual climate variations

    International Nuclear Information System (INIS)

    It has been known for some time that the behavior of the short-term fluctuations of the earth's atmosphere resembles that of a chaotic non-linear dynamical system, and that the day-to-day weather cannot be predicted beyond a few weeks. However, it has also been found that the interactions of the atmosphere with the underlying oceans and the land surfaces can produce fluctuations whose time scales are much longer than the limits of deterministic prediction of weather. It is, therefore, natural to ask whether it is possible that the seasonal and longer time averages of climate fluctuations can be predicted with sufficient skill to be beneficial for social and economic applications, even though the details of day-to-day weather cannot be predicted beyond a few weeks. The main objective of the workshop was to address this question by assessing the current state of knowledge on predictability of seasonal and interannual climate variability and to investigate various possibilities for its prediction. (orig./KW)

  1. Reward positivity: Reward prediction error or salience prediction error?

    Science.gov (United States)

    Heydari, Sepideh; Holroyd, Clay B

    2016-08-01

    The reward positivity is a component of the human ERP elicited by feedback stimuli in trial-and-error learning and guessing tasks. A prominent theory holds that the reward positivity reflects a reward prediction error signal that is sensitive to outcome valence, being larger for unexpected positive events relative to unexpected negative events (Holroyd & Coles, 2002). Although the theory has found substantial empirical support, most of these studies have utilized either monetary or performance feedback to test the hypothesis. However, in apparent contradiction to the theory, a recent study found that unexpected physical punishments also elicit the reward positivity (Talmi, Atkinson, & El-Deredy, 2013). The authors of this report argued that the reward positivity reflects a salience prediction error rather than a reward prediction error. To investigate this finding further, in the present study participants navigated a virtual T maze and received feedback on each trial under two conditions. In a reward condition, the feedback indicated that they would either receive a monetary reward or not and in a punishment condition the feedback indicated that they would receive a small shock or not. We found that the feedback stimuli elicited a typical reward positivity in the reward condition and an apparently delayed reward positivity in the punishment condition. Importantly, this signal was more positive to the stimuli that predicted the omission of a possible punishment relative to stimuli that predicted a forthcoming punishment, which is inconsistent with the salience hypothesis. PMID:27184070

  2. Strategy and methodology of dynamical analogue prediction

    Institute of Scientific and Technical Information of China (English)

    REN; HongLi; CHOU; JiFan

    2007-01-01

    In order to effectively improve numerical prediction level by using current models and data, the strategy and methodology of dynamical analogue prediction (DAP) is deeply studied in the present paper. A new idea to predict the prediction errors of dynamical model on the basis of historical analogue information is put forward so as to transform the dynamical prediction problem into the estimation problem of prediction errors. In terms of such an idea, a new prediction method of final analogue correction of errors (FACE) is developed. Furthermore, the FACE is applied to extra-seasonal prediction experiments on an operational atmosphere-ocean coupled general circulation model. Prediction results of summer mean circulation and total precipitation show that the FACE can to some extent reduce prediction errors, recover prediction variances, and improve prediction skills. Besides, sensitive experiments also show that predictions based on the FACE are evidently influenced by the number of analogues, analogue-selected variables and analogy metric.

  3. Classical universes are perfectly predictable!

    Science.gov (United States)

    Schmidt, Jan Hendrik

    I argue that in a classical universe, all the events that ever happen are encoded in each of the universe's parts. This conflicts with a statement which is widely believed to lie at the basis of relativity theory: that the events in a space-time region R determine only the events in R's domain of dependence but not those in other space-time regions. I show how, from this understanding, a new prediction method (which I call the 'Smoothness Method') can be obtained which allows us to predict future events on the basis of local observational data. Like traditional prediction methods, this method makes use of so-called ' ceteris paribus clauses', i.e. assumptions about the unobserved parts of the universe. However, these assumptions are used in a way which enables us to predict the behaviour of open systems with arbitrary accuracy, regardless of the influence of their environment-which has not been achieved by traditional methods. In a sequel to this paper (Schmidt, 1998), I will prove the Uniqueness and Predictability Theorems on which the Smoothness Method is based, and comment in more detail on its mathematical properties.

  4. Prediction Analysis for Measles Epidemics

    Science.gov (United States)

    Sumi, Ayako; Ohtomo, Norio; Tanaka, Yukio; Sawamura, Sadashi; Olsen, Lars Folke; Kobayashi, Nobumichi

    2003-12-01

    A newly devised procedure of prediction analysis, which is a linearized version of the nonlinear least squares method combined with the maximum entropy spectral analysis method, was proposed. This method was applied to time series data of measles case notification in several communities in the UK, USA and Denmark. The dominant spectral lines observed in each power spectral density (PSD) can be safely assigned as fundamental periods. The optimum least squares fitting (LSF) curve calculated using these fundamental periods can essentially reproduce the underlying variation of the measles data. An extension of the LSF curve can be used to predict measles case notification quantitatively. Some discussions including a predictability of chaotic time series are presented.

  5. Prediction Method for Regional Logistics

    Institute of Scientific and Technical Information of China (English)

    QIU Ying; LU Huapu; WANG Haiwei

    2008-01-01

    Currently applied prediction methods of regional freight traffic and freight ton-kilometer forecasting were analyzed using typical Chinese regional goods transportation characteristics.The review of prediction methods showes that practical planning experts tend to apply the traditional methods which are easier to implement.The comparison also demonstrates that a combination of traditional methods is more effective than the simple models for practical planning.Research using the statistical data for the Yangtze Delta,Pearl River Delta,and Bohai Rim areas shows that ignoring differences between transport modes impacts the prediction accuracy.The four main transport modes suit different methods.The results show that the power model is better for railways,and the linear model is better for highways and waterways.Thus a combined model gives better results for all modes.The results for regional systems can be generalized to national transportation systems.

  6. Link Prediction via Matrix Completion

    CERN Document Server

    Pech, Ratha; Pan, Liming; Cheng, Hong; Zhou, Tao

    2016-01-01

    Inspired by practical importance of social networks, economic networks, biological networks and so on, studies on large and complex networks have attracted a surge of attentions in the recent years. Link prediction is a fundamental issue to understand the mechanisms by which new links are added to the networks. We introduce the method of robust principal component analysis (robust PCA) into link prediction, and estimate the missing entries of the adjacency matrix. On one hand, our algorithm is based on the sparsity and low rank property of the matrix, on the other hand, it also performs very well when the network is dense. This is because a relatively dense real network is also sparse in comparison to the complete graph. According to extensive experiments on real networks from disparate fields, when the target network is connected and sufficiently dense, whatever it is weighted or unweighted, our method is demonstrated to be very effective and with prediction accuracy being considerably improved comparing wit...

  7. Spatial prediction and ordinary kriging

    Energy Technology Data Exchange (ETDEWEB)

    Cressie, N.

    1988-05-01

    Suppose data /Z(s/sub i/):i = 1,...,n/ are observed at spatial locations /s/sub i/:i = 1,...,n/. From these data, an unknown Z(s/sub 0/) is to be predicted at a known location s/sub 0/, or, if Z(s/sub 0/) has a component of measurement error, then a smooth version S(s/sub 0/) should be predicted. This article considers the assumptions needed to carry out the spatial prediction using ordinary kriging, and looks at how nugget effect, range, and sill of the variogram affect the predictor. It is concluded that certain commonly held interpretations of these variogram parameters should be modified.

  8. Evoked emotions predict food choice.

    Directory of Open Access Journals (Sweden)

    Jelle R Dalenberg

    Full Text Available In the current study we show that non-verbal food-evoked emotion scores significantly improve food choice prediction over merely liking scores. Previous research has shown that liking measures correlate with choice. However, liking is no strong predictor for food choice in real life environments. Therefore, the focus within recent studies shifted towards using emotion-profiling methods that successfully can discriminate between products that are equally liked. However, it is unclear how well scores from emotion-profiling methods predict actual food choice and/or consumption. To test this, we proposed to decompose emotion scores into valence and arousal scores using Principal Component Analysis (PCA and apply Multinomial Logit Models (MLM to estimate food choice using liking, valence, and arousal as possible predictors. For this analysis, we used an existing data set comprised of liking and food-evoked emotions scores from 123 participants, who rated 7 unlabeled breakfast drinks. Liking scores were measured using a 100-mm visual analogue scale, while food-evoked emotions were measured using 2 existing emotion-profiling methods: a verbal and a non-verbal method (EsSense Profile and PrEmo, respectively. After 7 days, participants were asked to choose 1 breakfast drink from the experiment to consume during breakfast in a simulated restaurant environment. Cross validation showed that we were able to correctly predict individualized food choice (1 out of 7 products for over 50% of the participants. This number increased to nearly 80% when looking at the top 2 candidates. Model comparisons showed that evoked emotions better predict food choice than perceived liking alone. However, the strongest predictive strength was achieved by the combination of evoked emotions and liking. Furthermore we showed that non-verbal food-evoked emotion scores more accurately predict food choice than verbal food-evoked emotions scores.

  9. Predicting nitrogen excretion from cattle.

    Science.gov (United States)

    Reed, K F; Moraes, L E; Casper, D P; Kebreab, E

    2015-05-01

    Manure nitrogen (N) from cattle production facilities can lead to negative environmental effects, such as contribution to greenhouse gas emissions, leaching and runoff to aqueous ecosystems leading to eutrophication, and acid rain. To mitigate these effects and to improve the efficiency of N use, accurate prediction of N excretion and secretions are required. A genetic algorithm was implemented to select models to predict fecal, urinary, and total manure N excretions, and milk N secretions from 3 classes of animals: lactating dairy cows, heifers and dry cows, and steers. Two tiers of model classes were developed for each category of animals based on model input requirements. A total of 6 models for heifers and dry cows and steers and an additional 2 models for lactating dairy cattle were developed. Evaluation of the models using K-fold cross validation based on all data and using the most recent 6 yr of data showed better prediction for total manure N and fecal N compared with urinary N excretion, which was the most variable response in the database. Compared with extant models from the literature, the models developed in this study resulted in a significant improvement in prediction error for fecal and urinary N excretions from lactating cows. For total manure production by lactating cows, extant and new models were comparable in their prediction ability. Both proposed and extant models performed better than the prediction methods used by the US Environmental Protection Agency for the national inventory of greenhouse gases. Therefore, the proposed models are recommended for use in estimation of manure N from various classes of animals. PMID:25747829

  10. Evoked emotions predict food choice.

    Science.gov (United States)

    Dalenberg, Jelle R; Gutjar, Swetlana; Ter Horst, Gert J; de Graaf, Kees; Renken, Remco J; Jager, Gerry

    2014-01-01

    In the current study we show that non-verbal food-evoked emotion scores significantly improve food choice prediction over merely liking scores. Previous research has shown that liking measures correlate with choice. However, liking is no strong predictor for food choice in real life environments. Therefore, the focus within recent studies shifted towards using emotion-profiling methods that successfully can discriminate between products that are equally liked. However, it is unclear how well scores from emotion-profiling methods predict actual food choice and/or consumption. To test this, we proposed to decompose emotion scores into valence and arousal scores using Principal Component Analysis (PCA) and apply Multinomial Logit Models (MLM) to estimate food choice using liking, valence, and arousal as possible predictors. For this analysis, we used an existing data set comprised of liking and food-evoked emotions scores from 123 participants, who rated 7 unlabeled breakfast drinks. Liking scores were measured using a 100-mm visual analogue scale, while food-evoked emotions were measured using 2 existing emotion-profiling methods: a verbal and a non-verbal method (EsSense Profile and PrEmo, respectively). After 7 days, participants were asked to choose 1 breakfast drink from the experiment to consume during breakfast in a simulated restaurant environment. Cross validation showed that we were able to correctly predict individualized food choice (1 out of 7 products) for over 50% of the participants. This number increased to nearly 80% when looking at the top 2 candidates. Model comparisons showed that evoked emotions better predict food choice than perceived liking alone. However, the strongest predictive strength was achieved by the combination of evoked emotions and liking. Furthermore we showed that non-verbal food-evoked emotion scores more accurately predict food choice than verbal food-evoked emotions scores. PMID:25521352

  11. Plans for Aeroelastic Prediction Workshop

    Science.gov (United States)

    Heeg, Jennifer; Ballmann, Josef; Bhatia, Kumar; Blades, Eric; Boucke, Alexander; Chwalowski, Pawel; Dietz, Guido; Dowell, Earl; Florance, Jennifer P.; Hansen, Thorsten; Mani, Mori; Marvriplis, Dimitri; Perry, Boyd, III; Ritter, Markus; Schuster, David M.; Smith, Marilyn; Taylor, Paul; Whiting, Brent; Wieseman, Carol C.

    2011-01-01

    This paper summarizes the plans for the first Aeroelastic Prediction Workshop. The workshop is designed to assess the state of the art of computational methods for predicting unsteady flow fields and aeroelastic response. The goals are to provide an impartial forum to evaluate the effectiveness of existing computer codes and modeling techniques, and to identify computational and experimental areas needing additional research and development. Three subject configurations have been chosen from existing wind tunnel data sets where there is pertinent experimental data available for comparison. For each case chosen, the wind tunnel testing was conducted using forced oscillation of the model at specified frequencies

  12. Wind energy prediction; Prediccion eolica

    Energy Technology Data Exchange (ETDEWEB)

    Xiberta, B. J.; Florez, M. V. E.

    2004-07-01

    On March 12th, 2004 the Spanish Government modified the legal situation of the renewable energies following the approval of RD 436/2004. This makes necessary the development of wind energy prediction models for its entrance to the daily electricity market like the conventional energies. The improvement of physical models, meteorological models, or a combination of both, is necessary for the prediction of the wind generation. This will guarantee the wind energy full utilization and the participation in the electrical market, as well as the remuneration of the complementary services and the regulation of reactive electricity. In this way wind energy turns into a perfectly manageable one. (Author)

  13. Methods for Predicting Stock Indexes

    Directory of Open Access Journals (Sweden)

    Martha Cecilia García

    2013-11-01

    Full Text Available This paper presents a literature review on methods that have been used in the last two decades to predict Stock Market Indexes. Methods studied range from those enabling to grab the linear characteristics present in the stock market indexes, going through those that focus on non-linear features and finally hybrid methods that are more robust, since they capture linear and non-linear features. In addition, this research includes methods that use macroeconomic variables to predict indexes from different stock exchanges around the world.

  14. Can we predict nuclear proliferation

    International Nuclear Information System (INIS)

    The author aims at improving nuclear proliferation prediction capacities, i.e. the capacities to identify countries susceptible to acquire nuclear weapons, to interpret sensitive activities, and to assess nuclear program modalities. He first proposes a retrospective assessment of counter-proliferation actions since 1945. Then, based on academic studies, he analyzes what causes and motivates proliferation, with notably the possibility of existence of a chain phenomenon (mechanisms driving from one program to another). He makes recommendations for a global approach to proliferation prediction, and proposes proliferation indices and indicators

  15. Prediction of eyespot infection risks

    Directory of Open Access Journals (Sweden)

    M. Váòová

    2012-12-01

    Full Text Available The objective of the study was to design a prediction model for eyespot (Tapesia yallundae infection based on climatic factors (temperature, precipitation, air humidity. Data from experiment years 1994-2002 were used to study correlations between the eyespot infection index and individual weather characteristics. The model of prediction was constructed using multiple regression when a separate parameter is assigned to each factor, i.e. the frequency of days with optimum temperatures, humidity, and precipitation. The correlation between relative air humidity and precipitation and the infection index is significant.

  16. Four Centuries of Return Predictability

    OpenAIRE

    Benjamin Golez; Peter Koudijs

    2014-01-01

    We analyze four centuries of stock prices and dividends in the Dutch, English, and U.S. market. With the exception of the post-1945 period, the dividend-to-price ratio is stationary and predicts returns throughout all four centuries. “Excess volatility” is thus a pervasive feature of financial markets. The dividend-to-price ratio also predicts dividend growth rates in all but the most recent period. Cash-flows were therefore much more important for price movements before 1945, and the dominan...

  17. CERAPP: Collaborative Estrogen Receptor Activity Prediction Project

    Data.gov (United States)

    U.S. Environmental Protection Agency — Data from a large-scale modeling project called CERAPP (Collaborative Estrogen Receptor Activity Prediction Project) demonstrating using predictive computational...

  18. TRITIUM RESERVOIR STRUCTURAL PERFORMANCE PREDICTION

    Energy Technology Data Exchange (ETDEWEB)

    Lam, P.S.; Morgan, M.J

    2005-11-10

    The burst test is used to assess the material performance of tritium reservoirs in the surveillance program in which reservoirs have been in service for extended periods of time. A materials system model and finite element procedure were developed under a Savannah River Site Plant-Directed Research and Development (PDRD) program to predict the structural response under a full range of loading and aged material conditions of the reservoir. The results show that the predicted burst pressure and volume ductility are in good agreement with the actual burst test results for the unexposed units. The material tensile properties used in the calculations were obtained from a curved tensile specimen harvested from a companion reservoir by Electric Discharge Machining (EDM). In the absence of exposed and aged material tensile data, literature data were used for demonstrating the methodology in terms of the helium-3 concentration in the metal and the depth of penetration in the reservoir sidewall. It can be shown that the volume ductility decreases significantly with the presence of tritium and its decay product, helium-3, in the metal, as was observed in the laboratory-controlled burst tests. The model and analytical procedure provides a predictive tool for reservoir structural integrity under aging conditions. It is recommended that benchmark tests and analysis for aged materials be performed. The methodology can be augmented to predict performance for reservoir with flaws.

  19. Evoked Emotions Predict Food Choice

    NARCIS (Netherlands)

    Dalenberg, J.R.; Gutjar, S.; Horst, ter G.J.; Graaf, de C.; Renken, R.; Jager, G.

    2014-01-01

    In the current study we show that non-verbal food-evoked emotion scores significantly improve food choice prediction over merely liking scores. Previous research has shown that liking measures correlate with choice. However, liking is no strong predictor for food choice in real life environments. Th

  20. Detecting failure of climate predictions

    Science.gov (United States)

    Runge, Michael C.; Stroeve, Julienne C.; Barrett, Andrew P.; McDonald-Madden, Eve

    2016-01-01

    The practical consequences of climate change challenge society to formulate responses that are more suited to achieving long-term objectives, even if those responses have to be made in the face of uncertainty1, 2. Such a decision-analytic focus uses the products of climate science as probabilistic predictions about the effects of management policies3. Here we present methods to detect when climate predictions are failing to capture the system dynamics. For a single model, we measure goodness of fit based on the empirical distribution function, and define failure when the distribution of observed values significantly diverges from the modelled distribution. For a set of models, the same statistic can be used to provide relative weights for the individual models, and we define failure when there is no linear weighting of the ensemble models that produces a satisfactory match to the observations. Early detection of failure of a set of predictions is important for improving model predictions and the decisions based on them. We show that these methods would have detected a range shift in northern pintail 20 years before it was actually discovered, and are increasingly giving more weight to those climate models that forecast a September ice-free Arctic by 2055.

  1. Working postures: prediction and evaluation

    NARCIS (Netherlands)

    Delleman, N.J.

    1999-01-01

    To date, workstation designers cannot see the effects of a design on working posture before a mock-up/prototype is available. At that moment, usually the margin for creating the conditions required for adopting favourable working postures is still very limited. Posture prediction at an early design

  2. The Predictive Value of IQ.

    Science.gov (United States)

    Sternberg, Robert J.; Grigorenko, Elena L.; Bundy, Donald A.

    2001-01-01

    Reviews findings on the predictive validity of psychometric tests of intelligence. Concludes that conventional tests of intelligence can be useful but only if they are interpreted very carefully, taking into account the factors that can affect them, and in conjunction with other measures. (Author)

  3. Prediction models in complex terrain

    DEFF Research Database (Denmark)

    Marti, I.; Nielsen, Torben Skov; Madsen, Henrik;

    2001-01-01

    The objective of the work is to investigatethe performance of HIRLAM in complex terrain when used as input to energy production forecasting models, and to develop a statistical model to adapt HIRLAM prediction to the wind farm. The features of the terrain, specially the topography, influence...

  4. Solution Patterns Predicting Pythagorean Triples

    Science.gov (United States)

    Ezenweani, Ugwunna Louis

    2013-01-01

    Pythagoras Theorem is an old mathematical treatise that has traversed the school curricula from secondary to tertiary levels. The patterns it produced are quite interesting that many researchers have tried to generate a kind of predictive approach to identifying triples. Two attempts, namely Diophantine equation and Brahmagupta trapezium presented…

  5. Evaluation of environmental impact predictions

    International Nuclear Information System (INIS)

    An analysis and evaluation of the ecological monitoring program at the Surry Nuclear Power Plant showed that predictions of potential environmental impact made in the Final Environmental Statement (FES), which were based on generally accepted ecological principles, were not completely substantiated by environmental monitoring data. The Surry Nuclear Power Plant (Units 1 and 2) was chosen for study because of the facility's relatively continuous operating history and the availability of environmental data adequate for analysis. Preoperational and operational fish monitoring data were used to assess the validity of the FES prediction that fish would congregate in the thermal plume during winter months and would avoid the plume during summer months. Analysis of monitoring data showed that fish catch per unit effort (CPE) was generally high in the thermal plume during winter months; however, the highest fish catches occurred in the plume during the summer. Possible explanations for differences between the FES prediction and results observed in analysis of monitoring data are discussed, and general recommendations are outlined for improving impact assessment predictions

  6. Prediction of regional wind power

    Energy Technology Data Exchange (ETDEWEB)

    Nielsen, T.S.; Madsen, H.; Nielsen, H.Aa. [Informatics and Mathematical Modelling - DTU, Kgs. Lyngby (Denmark); Landberg, L.; Giebel, G. [Risoe National Lab., Roskilde (Denmark)

    2006-07-01

    This paper presents a new concept for predicting the total wind power production in a larger region based on a combination of on-line measurements of power production from selected wind farms, power measurements for all wind turbines in the area and numerical weather predictions of wind speed and wind direction. The models are implemented in the Zephyr/WPPT system an on-line software system for calculating short-term predictions of wind power currently being developed by IMM and Risoe in coorporation with Elsam, Eltra, Elkraft and SEAS the major electrical utilities with respect to wind power in Denmark. Zephyr/WPPT employs statistical models to describe the relationship between power production and the numerical weather predictions. The statistical models belong to the class of conditional parametric models a model class particular useful for estimating non-linear relationships on-line. The estimation is furthermore made adaptively in order to allow for slow changes in the system e.g. caused by the annual variations of the climate. (au)

  7. On sieve bootstrap prediction intervals.

    OpenAIRE

    Andrés M. Alonso; Peña, Daniel; Romo Urroz, Juan

    2003-01-01

    In this paper we consider a sieve bootstrap method for constructing nonparametric prediction intervals for a general class of linear processes. We show that the sieve bootstrap provides consistent estimators of the conditional distribution of future values given the observed data.

  8. Cancer Risk Prediction and Assessment

    Science.gov (United States)

    Cancer prediction models provide an important approach to assessing risk and prognosis by identifying individuals at high risk, facilitating the design and planning of clinical cancer trials, fostering the development of benefit-risk indices, and enabling estimates of the population burden and cost of cancer.

  9. Can Creativity Predict Cognitive Reserve?

    Science.gov (United States)

    Palmiero, Massimiliano; Di Giacomo, Dina; Passafiume, Domenico

    2016-01-01

    Cognitive reserve relies on the ability to effectively cope with aging and brain damage by using alternate processes to approach tasks when standard approaches are no longer available. In this study, the issue if creativity can predict cognitive reserve has been explored. Forty participants (mean age: 61 years) filled out: the Cognitive Reserve…

  10. Predictibility in Nowcasting of Precipitation

    Science.gov (United States)

    Zawadzki, I.; Sourcel, M.; Berenguer, M.

    2009-05-01

    Present short term precipitation forecasting is based on two methods: Lagrangian persistence (nowcasting) and numerical weather prediction (NWP). An improvement over these methods is obtained by the combination of the two. The obvious shortcoming of nowcasting is its severe limitation in capturing new development or dissipation of precipitation. NWP has the ability to predict both but very imprecisely. An attempt to correct model errors by post-processing leads to some improvement in the skill of NWP, but the improvement, although significative, is not very impressive. The goal of our effort is to take a step back and to describe, in a quantitative manner, a) the nature of the uncertainties affecting Lagrangian persistence and NWP forecasts, as well as to determineb) the physical causes of the uncertainties. We quantify the uncertainties in short term forecasting due to limitation of nowcasting algorithms and NWP to capture correctly some of the physical phenomena that determine the predictability of precipitation. The first factor considered is the diurnal cycle that appears as the one physically determined factors that limit the precision of short term prediction. We study the cycle in radar mosaics over US and compare this to nowcasts and model outputs. The seasonal and geographical dependence of the diurnal cycle is quantitatively evaluated.

  11. Bankruptcy Prediction with Rough Sets

    NARCIS (Netherlands)

    J.C. Bioch (Cor); V. Popova (Viara)

    2001-01-01

    textabstractThe bankruptcy prediction problem can be considered an or dinal classification problem. The classical theory of Rough Sets describes objects by discrete attributes, and does not take into account the order- ing of the attributes values. This paper proposes a modification of the Rough Set

  12. Prediction for new magnetoelectric fluorides

    OpenAIRE

    Nenert, G.; Palstra, T. T. M.

    2007-01-01

    We use symmetry considerations in order to predict new magnetoelectric fluorides. In addition to these magnetoelectric properties, we discuss which among these fluorides are the ones susceptible to present multiferroic properties. We emphasize that several materials exhibit ferromagnetic properties. This ferromagnetism should enhance the interplay between the magnetic and dielectric properties in these materials.

  13. Prediction of Malaysian monthly GDP

    Science.gov (United States)

    Hin, Pooi Ah; Ching, Soo Huei; Yeing, Pan Wei

    2015-12-01

    The paper attempts to use a method based on multivariate power-normal distribution to predict the Malaysian Gross Domestic Product next month. Letting r(t) be the vector consisting of the month-t values on m selected macroeconomic variables, and GDP, we model the month-(t+1) GDP to be dependent on the present and l-1 past values r(t), r(t-1),…,r(t-l+1) via a conditional distribution which is derived from a [(m+1)l+1]-dimensional power-normal distribution. The 100(α/2)% and 100(1-α/2)% points of the conditional distribution may be used to form an out-of sample prediction interval. This interval together with the mean of the conditional distribution may be used to predict the month-(t+1) GDP. The mean absolute percentage error (MAPE), estimated coverage probability and average length of the prediction interval are used as the criterions for selecting the suitable lag value l-1 and the subset from a pool of 17 macroeconomic variables. It is found that the relatively better models would be those of which 2 ≤ l ≤ 3, and involving one or two of the macroeconomic variables given by Market Indicative Yield, Oil Prices, Exchange Rate and Import Trade.

  14. Detecting failure of climate predictions

    Science.gov (United States)

    Runge, Michael C.; Stroeve, Julienne C.; Barrett, Andrew P.; McDonald-Madden, Eve

    2016-09-01

    The practical consequences of climate change challenge society to formulate responses that are more suited to achieving long-term objectives, even if those responses have to be made in the face of uncertainty. Such a decision-analytic focus uses the products of climate science as probabilistic predictions about the effects of management policies. Here we present methods to detect when climate predictions are failing to capture the system dynamics. For a single model, we measure goodness of fit based on the empirical distribution function, and define failure when the distribution of observed values significantly diverges from the modelled distribution. For a set of models, the same statistic can be used to provide relative weights for the individual models, and we define failure when there is no linear weighting of the ensemble models that produces a satisfactory match to the observations. Early detection of failure of a set of predictions is important for improving model predictions and the decisions based on them. We show that these methods would have detected a range shift in northern pintail 20 years before it was actually discovered, and are increasingly giving more weight to those climate models that forecast a September ice-free Arctic by 2055.

  15. Predictive implications of Gompertz's law

    Science.gov (United States)

    Richmond, Peter; Roehner, Bertrand M.

    2016-04-01

    Gompertz's law tells us that for humans above the age of 35 the death rate increases exponentially with a doubling time of about 10 years. Here, we show that the same law continues to hold up to age 106. At that age the death rate is about 50%. Beyond 106 there is so far no convincing statistical evidence available because the number of survivors are too small even in large nations. However, assuming that Gompertz's law continues to hold beyond 106, we conclude that the mortality rate becomes equal to 1 at age 120 (meaning that there are 1000 deaths in a population of one thousand). In other words, the upper bound of human life is near 120. The existence of this fixed-point has interesting implications. It allows us to predict the form of the relationship between death rates at age 35 and the doubling time of Gompertz's law. In order to test this prediction, we first carry out a transversal analysis for a sample of countries comprising both industrialized and developing nations. As further confirmation, we also develop a longitudinal analysis using historical data over a time period of almost two centuries. Another prediction arising from this fixed-point model, is that, above a given population threshold, the lifespan of the oldest persons is independent of the size of their national community. This prediction is also supported by empirical evidence.

  16. Prediction of natural gas consumption

    International Nuclear Information System (INIS)

    Distributors of natural gas need to predict future consumption in order to purchase a sufficient supply on contract. Distributors that offer their customers equal payment plans need to predict the consumption of each customer 12 months in advance. Estimates of previous consumption are often used for months when meters are inaccessible, or bimonthly-read meters. Existing methods of predicting natural gas consumption, and a proposed new method for each local region are discussed. The proposed model distinguishes the consumption load factors from summer to other seasons by attempting to adjust them by introducing two parameters. The problem is then reduced to a quadratic programming problem. However, since it is not necessary to use both parameters simultaneously, the problem can be solved with a simple iterative procedure. Results show that the new model can improve the two-equation model to a certain scale. The adjustment to heat load factor can reduce the error of prediction markedly while that to base load factor influences the error marginally. 3 refs., 11 figs., 2 tabs

  17. Cast iron - a predictable material

    Directory of Open Access Journals (Sweden)

    Jorg C. Sturm

    2011-02-01

    Full Text Available High strength compacted graphite iron (CGI or alloyed cast iron components are substituting previously used non-ferrous castings in automotive power train applications. The mechanical engineering industry has recognized the value in substituting forged or welded structures with stiff and light-weight cast iron castings. New products such as wind turbines have opened new markets for an entire suite of highly reliable ductile iron cast components. During the last 20 years, casting process simulation has developed from predicting hot spots and solidification to an integral assessment tool for foundries for the entire manufacturing route of castings. The support of the feeding related layout of the casting is still one of the most important duties for casting process simulation. Depending on the alloy poured, different feeding behaviors and self-feeding capabilities need to be considered to provide a defect free casting. Therefore, it is not enough to base the prediction of shrinkage defects solely on hot spots derived from temperature fields. To be able to quantitatively predict these defects, solidification simulation had to be combined with density and mass transport calculations, in order to evaluate the impact of the solidification morphology on the feeding behavior as well as to consider alloy dependent feeding ranges. For cast iron foundries, the use of casting process simulation has become an important instrument to predict the robustness and reliability of their processes, especially since the influence of alloying elements, melting practice and metallurgy need to be considered to quantify the special shrinkage and solidification behavior of cast iron. This allows the prediction of local structures, phases and ultimately the local mechanical properties of cast irons, to asses casting quality in the foundry but also to make use of this quantitative information during design of the casting. Casting quality issues related to thermally driven

  18. Summertime Thunderstorms Prediction in Belarus

    Science.gov (United States)

    Lapo, Palina; Sokolovskaya, Yaroslava; Krasouski, Aliaksandr; Svetashev, Alexander; Turishev, Leonid; Barodka, Siarhei

    2015-04-01

    Mesoscale modeling with the Weather Research & Forecasting (WRF) system makes it possible to predict thunderstorm formation events by direct numerical simulation. In the present study, we analyze the feasibility and quality of thunderstorm prediction on the territory of Belarus for the summer period of 2014 based on analysis of several characteristic parameters in WRF modeling results that can serve as indicators of thunderstorms formation. These parameters include vertical velocity distribution, convective available potential energy (CAPE), K-index, SWEAT-index, Thompson index, lifted condensation level (LCL), and others, all of them being indicators of favorable atmospheric conditions for thunderstorms development. We perform mesoscale simulations of several cases of thunderstorm development in Belarus with WRF-ARW modeling system using 3 km grid spacing, WSM6 microphysics parameterization and explicit convection (no convective parameterization). Typical modeling duration makes 48 hours, which is equivalent to next-day thunderstorm prediction in operational use. We focus our attention to most prominent cases of intense thunderstorms in Minsk. For validation purposes, we use radar and satellite data in addition to surface observations. In summertime, the territory of Belarus is quite often under the influence of atmospheric fronts and stationary anticyclones. In this study, we subdivide thunderstorm cases under consideration into 2 categories: thunderstorms related to free convection and those related to forced convection processes. Our aim is to study the differences in thunderstorm indicator parameters between these two categories of thunderstorms in order to elaborate a set of parameters that can be used for operational thunderstorm forecasting. For that purpose, we analyze characteristic features of thunderstorms development on cold atmospheric fronts as well as thunderstorms formation in stable air masses. Modeling results demonstrate good predictive skill

  19. Predictive Technologies: Can Smart Tools Augment the Brain's Predictive Abilities?

    Science.gov (United States)

    Pezzulo, Giovanni; D'Ausilio, Alessandro; Gaggioli, Andrea

    2016-01-01

    The ability of "looking into the future"-namely, the capacity of anticipating future states of the environment or of the body-represents a fundamental function of human (and animal) brains. A goalkeeper who tries to guess the ball's direction; a chess player who attempts to anticipate the opponent's next move; or a man-in-love who tries to calculate what are the chances of her saying yes-in all these cases, people are simulating possible future states of the world, in order to maximize the success of their decisions or actions. Research in neuroscience is showing that our ability to predict the behavior of physical or social phenomena is largely dependent on the brain's ability to integrate current and past information to generate (probabilistic) simulations of the future. But could predictive processing be augmented using advanced technologies? In this contribution, we discuss how computational technologies may be used to support, facilitate or enhance the prediction of future events, by considering exemplificative scenarios across different domains, from simpler sensorimotor decisions to more complex cognitive tasks. We also examine the key scientific and technical challenges that must be faced to turn this vision into reality. PMID:27199648

  20. Positive parity pentaquarks pragmatically predicted

    International Nuclear Information System (INIS)

    We consider the possibility that the lightest pentaquark is a parity-even state, with one unit of orbital angular momentum. Working within the framework of a constituent quark model, we show that dominant spin-flavor interactions render certain parity-even states lighter than any pentaquark with all quarks in the spatial ground state. For such states, we focus on predicting the mass and decays of other members of the same SU(3) flavor multiplet. Specifically, we consider the strangeness -2 cascade pentaquarks, which are relatively immune to mixing. We take into account flavor SU(3) breaking effects originating from the strange quark mass as well as from the structure of the spin-flavor exchange interactions themselves. We predict the lightest cascade pentaquarks at approximately 1906 MeV, with a full width ∼3 times larger than that of the Θ+

  1. Simulation, situated conceptualization, and prediction.

    Science.gov (United States)

    Barsalou, Lawrence W

    2009-05-12

    Based on accumulating evidence, simulation appears to be a basic computational mechanism in the brain that supports a broad spectrum of processes from perception to social cognition. Further evidence suggests that simulation is typically situated, with the situated character of experience in the environment being reflected in the situated character of the representations that underlie simulation. A basic architecture is sketched of how the brain implements situated simulation. Within this framework, simulators implement the concepts that underlie knowledge, and situated conceptualizations capture patterns of multi-modal simulation associated with frequently experienced situations. A pattern completion inference mechanism uses current perception to activate situated conceptualizations that produce predictions via simulations on relevant modalities. Empirical findings from perception, action, working memory, conceptual processing, language and social cognition illustrate how this framework produces the extensive prediction that characterizes natural intelligence.

  2. Time-Predictable Computer Architecture

    Directory of Open Access Journals (Sweden)

    Schoeberl Martin

    2009-01-01

    Full Text Available Today's general-purpose processors are optimized for maximum throughput. Real-time systems need a processor with both a reasonable and a known worst-case execution time (WCET. Features such as pipelines with instruction dependencies, caches, branch prediction, and out-of-order execution complicate WCET analysis and lead to very conservative estimates. In this paper, we evaluate the issues of current architectures with respect to WCET analysis. Then, we propose solutions for a time-predictable computer architecture. The proposed architecture is evaluated with implementation of some features in a Java processor. The resulting processor is a good target for WCET analysis and still performs well in the average case.

  3. Time-Predictable Virtual Memory

    DEFF Research Database (Denmark)

    Puffitsch, Wolfgang; Schoeberl, Martin

    2016-01-01

    Virtual memory is an important feature of modern computer architectures. For hard real-time systems, memory protection is a particularly interesting feature of virtual memory. However, current memory management units are not designed for time-predictability and therefore cannot be used...... in such systems. This paper investigates the requirements on virtual memory from the perspective of hard real-time systems and presents the design of a time-predictable memory management unit. Our evaluation shows that the proposed design can be implemented efficiently. The design allows address translation...... and address range checking in constant time of two clock cycles on a cache miss. This constant time is in strong contrast to the possible cost of a miss in a translation look-aside buffer in traditional virtual memory organizations. Compared to a platform without a memory management unit, these two additional...

  4. Algorithms for Protein Structure Prediction

    DEFF Research Database (Denmark)

    Paluszewski, Martin

    -trace. Here we present three different approaches for reconstruction of C-traces from predictable measures. In our first approach [63, 62], the C-trace is positioned on a lattice and a tabu-search algorithm is applied to find minimum energy structures. The energy function is based on half-sphere-exposure (HSE......) and contact number (CN) measures only. We show that the HSE measure is much more information-rich than CN, nevertheless, HSE does not appear to provide enough information to reconstruct the C-traces of real-sized proteins. Our experiments also show that using tabu search (with our novel tabu definition......) is more robust than standard Monte Carlo search. In the second approach for reconstruction of C-traces, an exact branch and bound algorithm has been developed [67, 65]. The model is discrete and makes use of secondary structure predictions, HSE, CN and radius of gyration. We show how to compute good lower...

  5. Predicting Failures in Power Grids

    CERN Document Server

    Chertkov, Michael; Stepanov, Mikhail G

    2010-01-01

    Here we develop an approach to predict power grid weak points, and specifically to efficiently identify the most probable failure modes in load distribution for a given power network. This approach is applied to two examples: Guam's power system and also the IEEE RTS-96 system, both modeled within the static Direct Current power flow model. Our algorithm is a power network adaption of the worst configuration heuristics, originally developed to study low probability events in physics and failures in error-correction. One finding is that, if the normal operational mode of the grid is sufficiently healthy, the failure modes, also called instantons, are sufficiently sparse, i.e. the failures are caused by load fluctuations at only a few buses. The technique is useful for discovering weak links which are saturated at the instantons. It can also identify overutilized and underutilized generators, thus providing predictive capability for improving the reliability of any power network.

  6. The ethics of earthquake prediction.

    Science.gov (United States)

    Sol, Ayhan; Turan, Halil

    2004-10-01

    Scientists' responsibility to inform the public about their results may conflict with their responsibility not to cause social disturbance by the communication of these results. A study of the well-known Brady-Spence and Iben Browning earthquake predictions illustrates this conflict in the publication of scientifically unwarranted predictions. Furthermore, a public policy that considers public sensitivity caused by such publications as an opportunity to promote public awareness is ethically problematic from (i) a refined consequentialist point of view that any means cannot be justified by any ends, and (ii) a rights view according to which individuals should never be treated as a mere means to ends. The Parkfield experiment, the so-called paradigm case of cooperation between natural and social scientists and the political authorities in hazard management and risk communication, is also open to similar ethical criticism. For the people in the Parkfield area were not informed that the whole experiment was based on a contested seismological paradigm.

  7. WAVE ASSIMILATION AND NUMERICAL PREDICTION

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    An adjoint variational method for wave data assimilation in the LAGFD-WAM wave model is proposed. The adjoint equation of the wavenumber energy spectrum balance equation is derived. And fortunately, its characteristic equations are the same as those in the LAGFD-WAM wave model. Simple experiments on the functional optimization and assimilation effectiveness during the prediction period indicated that the adjoint variational method is effective for wave assimilation and that the initial optimization of the wave model is important for the short-range wave prediction. All of this is under the assumption that the wind field is accurate, the method is the important first step for combined wind and wave data assimilation systems.

  8. Predicting responses from Rasch measures.

    Science.gov (United States)

    Linacre, John M

    2010-01-01

    There is a growing family of Rasch models for polytomous observations. Selecting a suitable model for an existing dataset, estimating its parameters and evaluating its fit is now routine. Problems arise when the model parameters are to be estimated from the current data, but used to predict future data. In particular, ambiguities in the nature of the current data, or overfit of the model to the current dataset, may mean that better fit to the current data may lead to worse fit to future data. The predictive power of several Rasch and Rasch-related models are discussed in the context of the Netflix Prize. Rasch-related models are proposed based on Singular Value Decomposition (SVD) and Boltzmann Machines.

  9. On long term climate prediction

    Energy Technology Data Exchange (ETDEWEB)

    Thatcher, M.

    1990-08-01

    On the occasion of the opening of The Hadley Centre in Bracknell, Berkshire on May 25, 1990, Britain's Prime Minister, the Rt. Hon. Margaret Thatcher, FRS, related the significance of the Centre to the Scientific Assessment Report of the Inter-Governmental Panel on Climate Change which was published on the same day. The Report confirms that greenhouse gases are increasing substantially as a result of man's activites; that this will warm the Earth's surface, with serious consequences for us all, and that these consequences are capable of prediction. We want to predict them more accurately. Calling the Report an authoritative early warning system which could be ignored only at great risk to future generations, Mrs. Margaret Thatcher described the role of the Centre in enabling the establishment of a realistic international program and timetable for action.

  10. Predicting percolation thresholds in networks

    CERN Document Server

    Radicchi, Filippo

    2014-01-01

    We consider different methods, that do not rely on numerical simulations of the percolation process, to approximate percolation thresholds in networks. We perform a systematic analysis on synthetic graphs and a collection of 109 real networks to quantify their effectiveness and reliability as prediction tools. Our study reveals that the inverse of the largest eigenvalue of the non-backtracking matrix of the graph often provides a tight lower bound for true percolation threshold. However, in more than 40% of the cases, this indicator is less predictive than the naive expectation value based solely on the moments of the degree distribution. We find that the performance of all indicators becomes worse as the value of the true percolation threshold grows. Thus, none of them represents a good proxy for robustness of extremely fragile networks.

  11. Action semantics modulate action prediction.

    Science.gov (United States)

    Springer, Anne; Prinz, Wolfgang

    2010-11-01

    Previous studies have demonstrated that action prediction involves an internal action simulation that runs time-locked to the real action. The present study replicates and extends these findings by indicating a real-time simulation process (Graf et al., 2007), which can be differentiated from a similarity-based evaluation of internal action representations. Moreover, results showed that action semantics modulate action prediction accuracy. The semantic effect was specified by the processing of action verbs and concrete nouns (Experiment 1) and, more specifically, by the dynamics described by action verbs (Experiment 2) and the speed described by the verbs (e.g., "to catch" vs. "to grasp" vs. "to stretch"; Experiment 3). These results propose a linkage between action simulation and action semantics as two yet unrelated domains, a view that coincides with a recent notion of a close link between motor processes and the understanding of action language.

  12. MPC-Relevant Prediction-Error Identification

    DEFF Research Database (Denmark)

    Jørgensen, John Bagterp; Jørgensen, Sten Bay

    2007-01-01

    A prediction-error-method tailored for model based predictive control is presented. The prediction-error method studied are based on predictions using the Kalman filter and Kalman predictors for a linear discrete-time stochastic state space model. The linear discrete-time stochastic state space m...

  13. Neural Networks for protein Structure Prediction

    DEFF Research Database (Denmark)

    Bohr, Henrik

    1998-01-01

    This is a review about neural network applications in bioinformatics. Especially the applications to protein structure prediction, e.g. prediction of secondary structures, prediction of surface structure, fold class recognition and prediction of the 3-dimensional structure of protein backbones...

  14. Predicting Comprehension from Students’ Summaries

    OpenAIRE

    Dascălu, Mihai; Larise Stavarache, Lucia; Dessus, Philippe; Trausan-Matu, Stefan; McNamara, Danielle,; Bianco, Maryse

    2015-01-01

    Comprehension among young students represents a key component of their formation throughout the learning process. Moreover, scaffolding students as they learn to coherently link information, while organically construct- ing a solid knowledge base, is crucial to students’ development, but requires regular assessment and progress tracking. To this end, our aim is to provide an automated solution for analyzing and predicting students’ comprehension levels by extracting a combination of reading s...

  15. Prediction for RNA planar pseudoknots

    Institute of Scientific and Technical Information of China (English)

    Li Hengwu; Zhu Daming; Liu Zhendong; Li Hong

    2007-01-01

    Based on m-stems and semi-extensible structure, a model is presented to represent RNA planar pseudoknots, and corresponding dynamic programming algorithm is designed and implemented to predict arbitrary planar pseudoknots and simple non-planar pseudoknots with O(n4) time and O(n3) space. The algorithm folds total 245 sequences in the Pseudobase database, and the test results indicate that the algorithm has good accuracy, sensitivity and specificity.

  16. Prediction of future asset prices

    Science.gov (United States)

    Seong, Ng Yew; Hin, Pooi Ah; Ching, Soo Huei

    2014-12-01

    This paper attempts to incorporate trading volumes as an additional predictor for predicting asset prices. Denoting r(t) as the vector consisting of the time-t values of the trading volume and price of a given asset, we model the time-(t+1) asset price to be dependent on the present and l-1 past values r(t), r(t-1), ....., r(t-1+1) via a conditional distribution which is derived from a (2l+1)-dimensional power-normal distribution. A prediction interval based on the 100(α/2)% and 100(1-α/2)% points of the conditional distribution is then obtained. By examining the average lengths of the prediction intervals found by using the composite indices of the Malaysia stock market for the period 2008 to 2013, we found that the value 2 appears to be a good choice for l. With the omission of the trading volume in the vector r(t), the corresponding prediction interval exhibits a slightly longer average length, showing that it might be desirable to keep trading volume as a predictor. From the above conditional distribution, the probability that the time-(t+1) asset price will be larger than the time-t asset price is next computed. When the probability differs from 0 (or 1) by less than 0.03, the observed time-(t+1) increase in price tends to be negative (or positive). Thus the above probability has a good potential of being used as a market indicator in technical analysis.

  17. Are Some Semantic Changes Predictable?

    DEFF Research Database (Denmark)

    Schousboe, Steen

    2010-01-01

      Historical linguistics is traditionally concerned with phonology and syntax. With the exception of grammaticalization - the development of auxiliary verbs, the syntactic rather than localistic use of prepositions, etc. - semantic change has usually not been described as a result of regular deve...... developments, but only as specific meaning changes in individual words. This paper will suggest some regularities in semantic change, regularities which, like sound laws, have predictive power and can be tested against recorded languages....

  18. Neuroanatomy Predicts Individual Risk Attitudes

    OpenAIRE

    Gilaie-Dotan, Sharon; Tymula, Agnieszka; Cooper, Nicole; Kable, Joseph W.; Glimcher, Paul W.; Levy, Ifat

    2014-01-01

    Over the course of the last decade a multitude of studies have investigated the relationship between neural activations and individual human decision-making. Here we asked whether the anatomical features of individual human brains could be used to predict the fundamental preferences of human choosers. To that end, we quantified the risk attitudes of human decision-makers using standard economic tools and quantified the gray matter cortical volume in all brain areas using standard neurobiologi...

  19. Preconditioned Continuation Model Predictive Control

    OpenAIRE

    Knyazev, Andrew; Fujii, Yuta; Malyshev, Alexander,

    2015-01-01

    Model predictive control (MPC) anticipates future events to take appropriate control actions. Nonlinear MPC (NMPC) describes systems with nonlinear models and/or constraints. A Continuation/GMRES Method for NMPC, suggested by T. Ohtsuka in 2004, uses the GMRES iterative algorithm to solve a forward difference approximation $Ax=b$ of the Continuation NMPC (CNMPC) equations on every time step. The coefficient matrix $A$ of the linear system is often ill-conditioned, resulting in poor GMRES conv...

  20. Evoked Emotions Predict Food Choice

    OpenAIRE

    Dalenberg, Jelle R.; Swetlana Gutjar; ter Horst, Gert J.; Kees de Graaf; Renken, Remco J.; Gerry Jager

    2014-01-01

    In the current study we show that non-verbal food-evoked emotion scores significantly improve food choice prediction over merely liking scores. Previous research has shown that liking measures correlate with choice. However, liking is no strong predictor for food choice in real life environments. Therefore, the focus within recent studies shifted towards using emotion-profiling methods that successfully can discriminate between products that are equally liked. However, it is unclear how well ...

  1. On Predictive Least Squares Principles

    OpenAIRE

    Wei, C. Z.

    1992-01-01

    Recently, Rissanen proposed a new model selection criterion PLS that selects the model that minimizes the accumulated squares of prediction errors. Usually, the information-based criteria, such as AIC and BIC, select the model that minimizes a loss function which can be expressed as a sum of two terms. One measures the goodness of fit and the other penalizes the complexity of the selected model. In this paper we provide such an interpretation for PLS. Using this relationship, we give sufficie...

  2. Colored Noise Prediction Based on Neural Network

    Institute of Scientific and Technical Information of China (English)

    Gao Fei; Zhang Xiaohui

    2003-01-01

    A method for predicting colored noise by introducing prediction of nonhnear time series is presented By adopting three kinds of neural networks prediction models, the colored noise prediction is studied through changing the filter bandwidth for stochastic noise and the sampling rate for colored noise The results show that colored noise can be predicted The prediction error decreases with the increasing of the sampling rate or the narrowing of the filter bandwidth. If the parameters are selected properly, the prediction precision can meet the requirement of engineering implementation. The results offer a new reference way for increasing the ability for detecting weak signal in signal processing system

  3. A contrail cirrus prediction model

    Directory of Open Access Journals (Sweden)

    U. Schumann

    2012-05-01

    Full Text Available A new model to simulate and predict the properties of a large ensemble of contrails as a function of given air traffic and meteorology is described. The model is designed for approximate prediction of contrail cirrus cover and analysis of contrail climate impact, e.g. within aviation system optimization processes. The model simulates the full contrail life-cycle. Contrail segments form between waypoints of individual aircraft tracks in sufficiently cold and humid air masses. The initial contrail properties depend on the aircraft. The advection and evolution of the contrails is followed with a Lagrangian Gaussian plume model. Mixing and bulk cloud processes are treated quasi analytically or with an effective numerical scheme. Contrails disappear when the bulk ice content is sublimating or precipitating. The model has been implemented in a "Contrail Cirrus Prediction Tool" (CoCiP. This paper describes the model assumptions, the equations for individual contrails, and the analysis-method for contrail-cirrus cover derived from the optical depth of the ensemble of contrails and background cirrus. The model has been applied for a case study and compared to the results of other models and in-situ contrail measurements. The simple model reproduces a considerable part of observed contrail properties. Mid-aged contrails provide the largest contributions to the product of optical depth and contrail width, important for climate impact.

  4. A contrail cirrus prediction model

    Directory of Open Access Journals (Sweden)

    U. Schumann

    2011-11-01

    Full Text Available A new model to simulate and predict the properties of a large ensemble of contrails as a function of given air traffic and meteorology is described. The model is designed for approximate prediction of contrail cirrus cover and analysis of contrail climate impact, e.g. within aviation system optimization processes. The model simulates the full contrail life-cycle. Contrail segments form between waypoints of individual aircraft tracks in sufficiently cold and humid air masses. The initial contrail properties depend on the aircraft. The advection and evolution of the contrails is followed with a Lagrangian Gaussian plume model. Mixing and bulk cloud processes are treated quasi analytically or with an effective numerical scheme. Contrails disappear when the bulk ice content is sublimating or precipitating. The model has been implemented in a "Contrail Cirrus Prediction Tool" (CoCiP. This paper describes the model assumptions, the equations for individual contrails, and the analysis-method for contrail-cirrus cover derived from the optical depth of the ensemble of contrails and background cirrus. The model has been applied for a case study and compared to the results of other models and in-situ contrail measurements. The simple model reproduces a considerable part of observed contrail properties. Mid-aged contrails provide the largest contributions to the product of optical depth and contrail width, important for climate impact.

  5. Neuroanatomy predicts individual risk attitudes.

    Science.gov (United States)

    Gilaie-Dotan, Sharon; Tymula, Agnieszka; Cooper, Nicole; Kable, Joseph W; Glimcher, Paul W; Levy, Ifat

    2014-09-10

    Over the course of the last decade a multitude of studies have investigated the relationship between neural activations and individual human decision-making. Here we asked whether the anatomical features of individual human brains could be used to predict the fundamental preferences of human choosers. To that end, we quantified the risk attitudes of human decision-makers using standard economic tools and quantified the gray matter cortical volume in all brain areas using standard neurobiological tools. Our whole-brain analysis revealed that the gray matter volume of a region in the right posterior parietal cortex was significantly predictive of individual risk attitudes. Participants with higher gray matter volume in this region exhibited less risk aversion. To test the robustness of this finding we examined a second group of participants and used econometric tools to test the ex ante hypothesis that gray matter volume in this area predicts individual risk attitudes. Our finding was confirmed in this second group. Our results, while being silent about causal relationships, identify what might be considered the first stable biomarker for financial risk-attitude. If these results, gathered in a population of midlife northeast American adults, hold in the general population, they will provide constraints on the possible neural mechanisms underlying risk attitudes. The results will also provide a simple measurement of risk attitudes that could be easily extracted from abundance of existing medical brain scans, and could potentially provide a characteristic distribution of these attitudes for policy makers. PMID:25209279

  6. Prediction During Natural Language Comprehension.

    Science.gov (United States)

    Willems, Roel M; Frank, Stefan L; Nijhof, Annabel D; Hagoort, Peter; van den Bosch, Antal

    2016-06-01

    The notion of prediction is studied in cognitive neuroscience with increasing intensity. We investigated the neural basis of 2 distinct aspects of word prediction, derived from information theory, during story comprehension. We assessed the effect of entropy of next-word probability distributions as well as surprisal A computational model determined entropy and surprisal for each word in 3 literary stories. Twenty-four healthy participants listened to the same 3 stories while their brain activation was measured using fMRI. Reversed speech fragments were presented as a control condition. Brain areas sensitive to entropy were left ventral premotor cortex, left middle frontal gyrus, right inferior frontal gyrus, left inferior parietal lobule, and left supplementary motor area. Areas sensitive to surprisal were left inferior temporal sulcus ("visual word form area"), bilateral superior temporal gyrus, right amygdala, bilateral anterior temporal poles, and right inferior frontal sulcus. We conclude that prediction during language comprehension can occur at several levels of processing, including at the level of word form. Our study exemplifies the power of combining computational linguistics with cognitive neuroscience, and additionally underlines the feasibility of studying continuous spoken language materials with fMRI. PMID:25903464

  7. Research on Population Prediction of Guizhou Province

    Institute of Scientific and Technical Information of China (English)

    Shuang; YU; Guang; LI

    2013-01-01

    In accordance with population development of Guizhou Province in 1977-2007,this paper adopts natural growth method,model prediction method and gray system GM (1,1) model prediction method to predict population of Guizhou Province in 2020. On the basis of overall consideration of many factors of population development and future development trend of Guizhou Province,it analyzes advantages and disadvantages of three prediction methods,and obtains the prediction value of total population of Guizhou Province in 2020.

  8. Prediction of PARP Inhibition with Proteochemometric Modelling and Conformal Prediction.

    Science.gov (United States)

    Cortés-Ciriano, Isidro; Bender, Andreas; Malliavin, Thérèse

    2015-06-01

    Poly(ADP-ribose) polymerases (PARPs) play a key role in DNA damage repair. PARP inhibitors act as chemo- and radio- sensitizers and thus potentiate the cytotoxicity of DNA damaging agents. Although PARP inhibitors are currently investigated as chemotherapeutic agents, their cross-reactivity with other members of the PARP family remains unclear. Here, we apply Proteochemometric Modelling (PCM) to model the activity of 181 compounds on 12 human PARPs. We demonstrate that PCM (R0 (2) test =0.65-0.69; RMSEtest =0.95-1.01 °C) displays higher performance on the test set (interpolation) than Family QSAR and Family QSAM (Tukey's HSD, α 0.05), and outperforms Inductive Transfer knowledge among targets (Tukey's HSD, α 0.05). We benchmark the predictive signal of 8 amino acid and 11 full-protein sequence descriptors, obtaining that all of them (except for SOCN) perform at the same level of statistical significance (Tukey's HSD, α 0.05). The extrapolation power of PCM to new compounds (RMSE=1.02±0.80 °C) and targets (RMSE=1.03±0.50 °C) is comparable to interpolation, although the extrapolation ability is not uniform across the chemical and the target space. For this reason, we also provide confidence intervals calculated with conformal prediction. In addition, we present the R package conformal, which permits the calculation of confidence intervals for regression and classification caret models. PMID:27490382

  9. Wine Expertise Predicts Taste Phenotype.

    Science.gov (United States)

    Hayes, John E; Pickering, Gary J

    2012-03-01

    Taste phenotypes have long been studied in relation to alcohol intake, dependence, and family history, with contradictory findings. However, on balance - with appropriate caveats about populations tested, outcomes measured and psychophysical methods used - an association between variation in taste responsiveness and some alcohol behaviors is supported. Recent work suggests super-tasting (operationalized via propylthiouracil (PROP) bitterness) not only associates with heightened response but also with more acute discrimination between stimuli. Here, we explore relationships between food and beverage adventurousness and taste phenotype. A convenience sample of wine drinkers (n=330) were recruited in Ontario and phenotyped for PROP bitterness via filter paper disk. They also filled out a short questionnaire regarding willingness to try new foods, alcoholic beverages and wines as well as level of wine involvement, which was used to classify them as a wine expert (n=110) or wine consumer (n=220). In univariate logisitic models, food adventurousness predicted trying new wines and beverages but not expertise. Likewise, wine expertise predicted willingness to try new wines and beverages but not foods. In separate multivariate logistic models, willingness to try new wines and beverages was predicted by expertise and food adventurousness but not PROP. However, mean PROP bitterness was higher among wine experts than wine consumers, and the conditional distribution functions differed between experts and consumers. In contrast, PROP means and distributions did not differ with food adventurousness. These data suggest individuals may self-select for specific professions based on sensory ability (i.e., an active gene-environment correlation) but phenotype does not explain willingness to try new stimuli.

  10. Numerical Prediction of a Seaway

    CERN Document Server

    Dommermuth, Douglas G; Brucker, Kyle A; O'Shea, Thomas T; Wyatt, Donald C

    2014-01-01

    The ability of three wave theories to predict statistics and the crest kinematics of a seaway is quantified. The three wave theories are high-order spectral (HOS) theory, free-surface mapping (FSM), and volume-of-fluid (VOF). Issues associated with applying these methods are discussed, including free-surface adjustment, smoothing and filtering, and forcing. Two long-crested regular waves with varying bandwidth and moderate steepness are used to benchmark the performance of the wave theories. As a more stringent test, a broad-banded long-crested seaway is simulated.

  11. Statistics-Free Sports Prediction

    OpenAIRE

    Dubbs, Alexander

    2015-01-01

    We use a simple machine learning model, logistically-weighted regularized linear least squares regression, in order to predict baseball, basketball, football, and hockey games. We do so using only the thirty-year record of which visiting teams played which home teams, on what date, and what the final score was. No real "statistics" are used. The method works best in basketball, likely because it is high-scoring and has long seasons. It works better in football and hockey than in baseball, but...

  12. Predicting word sense annotation agreement

    DEFF Research Database (Denmark)

    Martinez Alonso, Hector; Johannsen, Anders Trærup; Lopez de Lacalle, Oier;

    2015-01-01

    High agreement is a common objective when annotating data for word senses. However, a number of factors make perfect agreement impossible, e.g. the limitations of the sense inventories, the difficulty of the examples or the interpretation preferences of the annotations. Estimating potential...... agreement is thus a relevant task to supplement the evaluation of sense annotations. In this article we propose two methods to predict agreement on word-annotation instances. We experiment with a continuous representation and a three-way discretization of observed agreement. In spite of the difficulty...

  13. Climate Prediction through Statistical Methods

    CERN Document Server

    Akgun, Bora; Tuter, Levent; Kurnaz, Mehmet Levent

    2008-01-01

    Climate change is a reality of today. Paleoclimatic proxies and climate predictions based on coupled atmosphere-ocean general circulation models provide us with temperature data. Using Detrended Fluctuation Analysis, we are investigating the statistical connection between the climate types of the present and these local temperatures. We are relating this issue to some well-known historic climate shifts. Our main result is that the temperature fluctuations with or without a temperature scale attached to them, can be used to classify climates in the absence of other indicators such as pan evaporation and precipitation.

  14. Predicting the Impact of Earthquakes

    International Nuclear Information System (INIS)

    Consistently monitor seismicity over the world to alert civilian security forces, assess hazards, model and test building and industrial facilities behavior in the event of an earthquake. Thanks to instruments unique in Europe, CEA researchers acquired extensive know-how and international renown in the field. The recent commissioning of the CENALT Tsunami Warning Center and the setup of the SEISM Institute for research on earthquake hazards is just another proof of their expertise. For want of being able to predict earthquakes, these organizations aim at limiting losses in human lives and material damage. (authors)

  15. Easily magnetic anomalies earthquake prediction

    Directory of Open Access Journals (Sweden)

    Jiang Min

    2016-01-01

    Full Text Available Low power consumption long time offset magnetic field detector (earthquake prediction .The design of the hardware circuit of the magnetic field detector seismic geomagnetic acquisition and pre processing module mainly includes. Electronic compass, compass. monitoring device while the magnetic azimuth for monitoring and analyzing the object, GSM, but it can also be applied to other seismic precursor information analysis, such as earthquake precursory infrasound abnormality, only need infrasound abnormality intelligent sensor replace geomagnetic anomaly intelligent sensor, and modify the relevant parameters can be.

  16. Focus on astronomical predictable events

    DEFF Research Database (Denmark)

    Jacobsen, Aase Roland

    2006-01-01

    At the Steno Museum Planetarium we have for many occasions used a countdown clock to get focus om astronomical events. A countdown clock can provide actuality to predictable events, for example The Venus Transit, Opportunity landing on Mars and The Solar Eclipse. The movement of the clock attracs...... the public and makes a point of interest in a small exhibit area. A countdown clock can be simple, but it is possible to expand the concept to an eye-catching part of a museum....

  17. Aviation turbulence processes, detection, prediction

    CERN Document Server

    Lane, Todd

    2016-01-01

    Anyone who has experienced turbulence in flight knows that it is usually not pleasant, and may wonder why this is so difficult to avoid. The book includes papers by various aviation turbulence researchers and provides background into the nature and causes of atmospheric turbulence that affect aircraft motion, and contains surveys of the latest techniques for remote and in situ sensing and forecasting of the turbulence phenomenon. It provides updates on the state-of-the-art research since earlier studies in the 1960s on clear-air turbulence, explains recent new understanding into turbulence generation by thunderstorms, and summarizes future challenges in turbulence prediction and avoidance.

  18. Radiometers Optimize Local Weather Prediction

    Science.gov (United States)

    2010-01-01

    Radiometrics Corporation, headquartered in Boulder, Colorado, engaged in Small Business Innovation Research (SBIR) agreements with Glenn Research Center that resulted in a pencil-beam radiometer designed to detect supercooled liquid along flight paths -- a prime indicator of dangerous icing conditions. The company has brought to market a modular radiometer that resulted from the SBIR work. Radiometrics' radiometers are used around the world as key tools for detecting icing conditions near airports and for the prediction of weather conditions like fog and convective storms, which are known to produce hail, strong winds, flash floods, and tornadoes. They are also employed for oceanographic research and soil moisture studies.

  19. Prediction of burnout. Chapter 14

    International Nuclear Information System (INIS)

    A broad survey is made of the effect on burnout heat flux of various system parameters to give the reader a better initial idea of the significance of changes in individual parameters. A detailed survey is then made of various correlation equations for predicting burnout for steam -water in uniformly heated tubes, annuli, rectangular channels and rod clusters, giving details of recommended equations. Finally comments are made on the influence of heat-flux profile and swirl flow on burnout, and on the definition of dryout margin. (author)

  20. MR imaging of lumbar herniated intervertebral disc and spinal stenosis: Correlation with CT

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Won Jae; Park, Kil Sun; Chang, Kee Hyun; Han, Moon Hee; Kim, Hyun Jip; Han, Man Chung; Kim, Chu Wan [Seoul National University College of Medicine, Seoul (Korea, Republic of)

    1989-12-15

    MR imagings obtained in 40 patients with surgically proven lumbar herniated intervertebral disc (HIVD) and/or spinal stenosis were retrospectively analysed and compared with CT scans, in order to evaluate the MR findings of HIVD and spinal stenosis, and to assess the diagnostic accuracy of MR. The MR imaging was performed on a 2.0 T superconducting unit, using multislice spin echo (SE) and gradient echo (GE) techniques. The results were as follows: 1. The texture of vertebral body with spinal stenosis had the tendency to be more heterogeneous than that with HIVD. 2. The signal intensity of the diseased disc was isointense relative to normal disc in 81 % (60/74) and the remainder (19%) was hypointense on both T1 weighted SE and GE images. There was no significant difference in signal intensity among HIVD, HIVD combined with spinal stenosis and spinal stenosis groups, but there was the tendency of lower signal intensity of the diseased disc in patients with severe degenerative change of spine in both T1 weighted SE imaged and GE image. 3. The diagnostic accuracy of MR was 92%, which was similar to that of CT. 4. T1 weighted SE image appears superior to GE image in evaluation of most of the structural differentiation, but as for differentiating between lumina and ligamentum flavum, and for the vacuum phenomenon, GE image seems to be better than T1 weighted SE image. In conclusion, MR appears to be better than CT as a initial imaging modality in evaluation of the patients with suspected lumbar spinal stenosis or HIVD because MR has the capability of demonstrating rupture of anulus fibrosus in sagittal plane.

  1. The relationship between disc degeneration and flexibility of the lumbar spine

    Energy Technology Data Exchange (ETDEWEB)

    Tanaka, Nobuhiro; Fujimoto, Yoshinori; Ochi, Mitsuo [Hiroshima Univ. (Japan). Graduate School of Biomedical Sciences; An, H.S.; Lim, T.H.; Fujiwara, Atsushi [Rush-Presbyterian-St. Luke' s Medical Center, Chicago, IL (United States)

    2003-04-01

    The purpose of this study was to investigate the relationship between grade of degeneration of intervertebral discs and 3-dimensional biomechanical characteristics of the motion segment under multidirectional loading conditions. The material used in this study consisted of 114 lumbar motion segments from T12-L1 to L5-S1 retrieved from 47 fresh cadaver spines (average age at death, 68 years; range, 39 to 87 years). The severity of degeneration (grades I to V according to Thomson's system) was determined by examining magnetic resonance (MR) images and cryomicrotome sections. Pure unconstrained moments with dead weights were applied to the motion segments in 6 load steps. The directions of loading included flexion, extension, right and left axial rotation, and right and left lateral bending. Segments from the upper lumbar levels (T12-L1 to L3-4) tended to have greater rotational movement in flexion, extension, and axial rotation with disc degeneration up to grade IV, but the motion decreased when the disc degeneration reached grade V. In the lower lumbar spine, motion in axial rotation and lateral bending at L4-5 and L5-S1 was increased in grade III. These results suggest that kinematic properties of the lumbar spine are related to disc degeneration. Disc degeneration, particularly in grades III and IV, in which radial tears of the anulus fibrosus are found, was generally associated with greater motion. Disc space collapse and osteophyte formation, as found in grade V, resulted in stabilization of the motion segments. (author)

  2. Improving the prediction of chaotic time series

    Institute of Scientific and Technical Information of China (English)

    李克平; 高自友; 陈天仑

    2003-01-01

    One of the features of deterministic chaos is sensitive to initial conditions. This feature limits the prediction horizons of many chaotic systems. In this paper, we propose a new prediction technique for chaotic time series. In our method, some neighbouring points of the predicted point, for which the corresponding local Lyapunov exponent is particularly large, would be discarded during estimating the local dynamics, and thus the error accumulated by the prediction algorithm is reduced. The model is tested for the convection amplitude of Lorenz systems. The simulation results indicate that the prediction technique can improve the prediction of chaotic time series.

  3. Predicting outcomes: Sports and stocks.

    Science.gov (United States)

    Wood, G

    1992-06-01

    Many gamblers and most fans, players, and coaches offer causal explanations for long runs of good or bad performance in sports and financial analysts are quick to offer explanations for the daily performance of the stock market. The records of professional basketball and baseball teams and the Dow Jones daily closing average for a ten year period were evaluated for trends (streaks). The records of teams were also evaluated to assess whether the record against opponents, the home court or home field advantage, and-for baseball teams-the record of the winning and losing pitcher (excluding the current game) predicted the outcome of individual games. Recent performance is, at best, a very weak predictor of current performance and the three best predictors for baseball (pitching, home field, and record against opponent) together accounted for only 1.7% of the variance in the outcomes of individual games. We overestimate our ability to predict. This overconfidence is likely to play a role in maintaining gambling behaviors. PMID:24241784

  4. Predictive implications of Gompertz's law

    CERN Document Server

    Richmond, Peter

    2015-01-01

    Gompertz's law tells us that for humans above the age of 35 the death rate increases exponentially with a doubling time of about 10 years. Here, we show that the same law continues to hold even for ages over 100. Beyond 106 there is so far no statistical evidence available because the number of survivors is too small even in the largest nations. However assuming that Gompertz's law continues to hold beyond 106, we conclude that the mortality rate becomes equal to 1 at age 120 (meaning that there are 1,000 deaths in a population of one thousand). In other words, the upper bound of human life is near 120. The existence of this fixed-point has interesting implications. It allows us to predict the form of the relationship between death rates at age 35 and the doubling time of Gompertz's law. In order to test this prediction, we first carry out a transversal analysis for a sample of countries comprising both industrialized and developing nations. As further confirmation, we also develop a longitudinal analysis usi...

  5. Mechanism and prediction of burnout

    International Nuclear Information System (INIS)

    The lecture begins by discussing the definitions of burnout and the various parametric effects as seen from the results for burnout measurements in uniformly heated round tubes. The correlations which are developed from these measurements and their applications to the case of non-uniform axial distribution of heat flux is then discussed in general terms as an illustration of the importance of knowing more about the nature and mechanism of the burnout. The next section of the lecture is concerned with summarizing broadly the various possible mechanisms in both the sub-cooled region and the quality region. It transpires that, for tubes of reasonable length, the normal first occurrence of burnout is in the annular flow regime. A discussion of burnout mechanisms in this regime then follows, with descriptions of the various experimental techniques evolved to study the mechanism. The final section of the lecture is concerned with prediction methods for burnout in annular flow and the application of these methods to prediction of burnout in round tubes, annuli and rod bundles, with a variety of fluids

  6. Monthly Extended Predicting Experiments with Nonlinear Regional Prediction. Part Ⅰ: Prediction of Zonal Mean Flow

    Institute of Scientific and Technical Information of China (English)

    CHEN Bomin; JI Liren; YANG Peicai; ZHANG Daomin

    2006-01-01

    Systematic errors have recently been founded to be distinct in the zonal mean component forecasts,which account for a large portion of the total monthly-mean forecast errors. To overcome the difficulty of numerical model, the monthly pentad-mean nonlinear dynamic regional prediction models of the zonal meangeopotential height at 200, 300, 500, and 700 hPa based on a large number of historical data (NCEP/NCAR reanalysis data) were constituted by employing the local approximation of the phase space reconstruction theory and nonlinear spatio-temporal series prediction method. The 12-month forecast experiments of 1996indicated that the results of the nonlinear model are better than those of the persistent, climatic prediction,and T42L9 model either over the high- and mid-latitude areas of the Northern and Southern Hemispheres or the tropical area. The root-mean-square of the monthly-mean height of T42L9 model was considerably decreased with a change of 30.4%, 26.6%, 82.6%, and 39.4%, respectively, over the high- and mid-latitudes of the Northern Hemisphere, over the high- and mid-latitudes of the Southern Hemisphere, over the tropics and over the globe, and also the corresponding anomaly correlation coefficients over the four areas were respectively increased by 0.306-0.312, 0.304-0.429, 0.739-0.746, and 0.360-0.400 (averagely a relative change of 11.0% over the globe) by nonlinear correction after integration, implying that the forecasts given by nonlinear model include more useful information than those of T42L9 model.

  7. Use of Feedback in Clinical Prediction

    Science.gov (United States)

    Schroeder, Harold E.

    1972-01-01

    Results indicated that predictive accuracy is greater when feedback is applied to the basis for the prediction than when applied to gut" impressions. Judges forming hypotheses were also able to learn from experience. (Author)

  8. Limits on lexical prediction during reading.

    Science.gov (United States)

    Luke, Steven G; Christianson, Kiel

    2016-08-01

    Efficient language processing may involve generating expectations about upcoming input. To investigate the extent to which prediction might facilitate reading, a large-scale survey provided cloze scores for all 2689 words in 55 different text passages. Highly predictable words were quite rare (5% of content words), and most words had a more-expected competitor. An eye-tracking study showed sensitivity to cloze probability but no mis-prediction cost. Instead, the presence of a more-expected competitor was found to be facilitative in several measures. Further, semantic and morphosyntactic information was highly predictable even when word identity was not, and this information facilitated reading above and beyond the predictability of the full word form. The results are consistent with graded prediction but inconsistent with full lexical prediction. Implications for theories of prediction in language comprehension are discussed. PMID:27376659

  9. Statistical prediction of Late Miocene climate

    Digital Repository Service at National Institute of Oceanography (India)

    Fernandes, A.A.; Gupta, S.M.

    The theory of statistical prediction of paleoclimate (Imbrie and Kipp, 1971), which includes multiple regression analysis and factor analysis is reviewed. Necessary software is listed. An application to predicting palaeo oceanographic parameters...

  10. Prediction of Recovery from Coma After CPR

    Science.gov (United States)

    ... PATIENTS AND THEIR FAMILIES PREDICTION OF RECOVERY FROM COMA AFTER CPR This summary will provide you with ... tests that help doctors predict poor recovery from coma after CPR. In this case, poor recovery means ...

  11. Prediction of Unsteady Transonic Aerodynamics Project

    Data.gov (United States)

    National Aeronautics and Space Administration — An accurate prediction of aero-elastic effects depends on an accurate prediction of the unsteady aerodynamic forces. Perhaps the most difficult speed regime is...

  12. Dopamine signals mimic reward prediction errors

    OpenAIRE

    Schoenbaum, Geoffrey; Esber, Guillem R; Iordanova, Mihaela D.

    2013-01-01

    Modern theories of associative learning center on a prediction error. A study finds that artificial activation of dopamine neurons can substitute for missing reward prediction errors to rescue blocked learning.

  13. Protein Residue Contacts and Prediction Methods

    Science.gov (United States)

    Adhikari, Badri

    2016-01-01

    In the field of computational structural proteomics, contact predictions have shown new prospects of solving the longstanding problem of ab initio protein structure prediction. In the last few years, application of deep learning algorithms and availability of large protein sequence databases, combined with improvement in methods that derive contacts from multiple sequence alignments, have shown a huge increase in the precision of contact prediction. In addition, these predicted contacts have also been used to build three-dimensional models from scratch. In this chapter, we briefly discuss many elements of protein residue–residue contacts and the methods available for prediction, focusing on a state-of-the-art contact prediction tool, DNcon. Illustrating with a case study, we describe how DNcon can be used to make ab initio contact predictions for a given protein sequence and discuss how the predicted contacts may be analyzed and evaluated. PMID:27115648

  14. Dissociating Prediction Failure: Considerations from Music Perception

    DEFF Research Database (Denmark)

    Ross, Suzi; Hansen, Niels Christian

    2016-01-01

    Dissociating Prediction Failure: Considerations from Music Perception The Journal of Neuroscience, 16 March 2016, 36(11): 3103-3105;......Dissociating Prediction Failure: Considerations from Music Perception The Journal of Neuroscience, 16 March 2016, 36(11): 3103-3105;...

  15. PREDICTION OF AIRCRAFT NOISE LEVELS

    Science.gov (United States)

    Clark, B. J.

    1994-01-01

    Methods developed at the NASA Lewis Research Center for predicting the noise contributions from various aircraft noise sources have been incorporated into a computer program for predicting aircraft noise levels either in flight or in ground test. The noise sources accounted for include fan inlet and exhaust, jet, flap (for powered lift), core (combustor), turbine, and airframe. Noise propagation corrections are available in the program for atmospheric attenuation, ground reflections, extra ground attenuation, and shielding. The capacity to solve the geometrical relationships between an aircraft in flight and an observer on the ground has been included in the program to make it useful in evaluating noise estimates and footprints for various proposed engine installations. The program contains two main routines for employing the noise prediction routines. The first main routine consists of a procedure to calculate at various observer stations the time history of the noise from an aircraft flying at a specified set of speeds, orientations, and space coordinates. The various components of the noise are computed by the program. For each individual source, the noise levels are free field with no corrections for propagation losses other than spherical divergence. The total spectra may then be corrected for the usual effects of atmospheric attenuation, extra ground attenuation, ground reflection, and aircraft shielding. Next, the corresponding values of overall sound pressure level, perceived noise level, and tone-weighted perceived noise level are calculated. From the time history at each point, true effective perceived noise levels are calculated. Thus, values of effective perceived noise levels, maximum perceived noise levels, and tone-weighted perceived noise levels are found for a grid of specified points on the ground. The second main routine is designed to give the usual format of one-third octave sound pressure level values at a fixed radius for a number of user

  16. Predicting landfalling hurricane numbers from basin hurricane numbers: statistical analysis and predictions

    OpenAIRE

    Jewson, Stephen; Laepple, Thomas; O'Shay, Adam; Penzer, Jeremy; Bellone, Enrica; Nzerem, Kechi

    2007-01-01

    One possible method for predicting landfalling hurricane numbers is to first predict the number of hurricanes in the basin and then convert that prediction to a prediction of landfalling hurricane numbers using an estimated proportion. Should this work better than just predicting landfalling hurricane numbers directly? We perform a basic statistical analysis of this question in the context of a simple abstract model, and convert some previous predictions of basin numbers into landfalling numb...

  17. The role of prediction in social neuroscience

    OpenAIRE

    Elliot Clayton Brown; Martin eBrüne

    2012-01-01

    Research has shown that the brain is constantly making predictions about future events. Theories of prediction in perception, action and learning suggest that the brain serves to reduce the discrepancies between expectation and actual experience, i.e. by reducing the prediction error. Forward models of action and perception propose the generation of a predictive internal representation of the expected sensory outcome, which is matched to the actual sensory feedback. Shared neural representati...

  18. ADAPTIVE GENERALIZED PREDICTIVE CONTROL OF SWITCHED SYSTEMS

    Institute of Scientific and Technical Information of China (English)

    WANG Yi-jing; WANG Long

    2005-01-01

    The problem of adaptive generalized predictive control which consists of output prediction errors for a class of switched systems is studied. The switching law is determined by the output predictive errors of a finite number of subsystems. For the single subsystem and multiple subsystems cases, it is proved that the given direct algorithm of generalized predictive control guarantees the global convergence of the system. This algorithm overcomes the inherent drawbacks of the slow convergence and large transient errors for the conventional adaptive control.

  19. Long-term orbital lifetime predictions

    Science.gov (United States)

    Dreher, P. E.; Lyons, A. T.

    1990-10-01

    Long-term orbital lifetime predictions are analyzed. Predictions were made for three satellites: the Solar Max Mission (SMM), the Long Duration Exposure Facility (LDEF), and the Pegasus Boiler Plate (BP). A technique is discussed for determining an appropriate ballistic coefficient to use in the lifetime prediction. The orbital decay rate should be monitored regularly. Ballistic coefficient updates should be done whenever there is a significant change in the actual decay rate or in the solar activity prediction.

  20. Academic Training: Predicting Natural Catastrophes

    CERN Multimedia

    Françoise Benz

    2005-01-01

    2005-2006 ACADEMIC TRAINING PROGRAMME LECTURE SERIES 12, 13, 14, 15, 16 December from 11:00 to 12:00 - Main Auditorium, bldg. 500 Predicting Natural Catastrophes E. OKAL / Northwestern University, Evanston, USA 1. Tsunamis -- Introduction Definition of phenomenon - basic properties of the waves Propagation and dispersion Interaction with coasts - Geological and societal effects Origin of tsunamis - natural sources Scientific activities in connection with tsunamis. Ideas about simulations 2. Tsunami generation The earthquake source - conventional theory The earthquake source - normal mode theory The landslide source Near-field observation - The Plafker index Far-field observation - Directivity 3. Tsunami warning General ideas - History of efforts Mantle magnitudes and TREMOR algorithms The challenge of 'tsunami earthquakes' Energy-moment ratios and slow earthquakes Implementation and the components of warning centers 4. Tsunami surveys Principles and methodologies Fifteen years of field surveys and re...

  1. Prospects for Predicting Cycle 24

    Indian Academy of Sciences (India)

    Arnab Rai Choudhuri

    2008-03-01

    Although we have reliable data of solar polar fields only from the mid-1970s, it seems that the polar field at a minimum is well correlated with the next cycle, but the strength of the cycle is not correlated with the polar field produced at its end. We explain this by suggesting that the Babcock–Leighton mechanism of poloidal field generation from tilted active regions involves randomness, whereas the other aspects of the dynamo process are more ordered. To model actual cycles, we have to ‘correct’ our theoretical dynamo model by ‘feeding’ information about the polar field at the minima. Following this process, we find that our model fits the observed sunspot numbers of cycles 21–23 reasonably well and predicts that cycle 24 will be the weakest in a century.

  2. The Predictiveness of Achievement Goals

    Directory of Open Access Journals (Sweden)

    Huy P. Phan

    2013-11-01

    Full Text Available Using the Revised Achievement Goal Questionnaire (AGQ-R (Elliot & Murayama, 2008, we explored first-year university students’ achievement goal orientations on the premise of the 2 × 2 model. Similar to recent studies (Elliot & Murayama, 2008; Elliot & Thrash, 2010, we conceptualized a model that included both antecedent (i.e., enactive learning experience and consequence (i.e., intrinsic motivation and academic achievement of achievement goals. Two hundred seventy-seven university students (151 women, 126 men participated in the study. Structural equation modeling procedures yielded evidence that showed the predictive effects of enactive learning experience and mastery goals on intrinsic motivation. Academic achievement was influenced intrinsic motivation, performance-approach goals, and enactive learning experience. Enactive learning experience also served as an antecedent of the four achievement goal types. On the whole, evidence obtained supports the AGQ-R and contributes, theoretically, to 2 × 2 model.

  3. Nutritional prediction of pressure ulcers.

    Science.gov (United States)

    Breslow, R A; Bergstrom, N

    1994-11-01

    This article focuses on nutritional risk factors that predict the development of pressure ulcers in hospital and nursing home patients. Cross-sectional studies associate inadequate energy and protein intake; underweight; low triceps skinfold measurement; and low serum albumin, low serum cholesterol, and low hemoglobin levels with pressure ulcers. Prospective studies identify inadequate energy and protein intake, a poor score on the Braden scale (a risk assessment instrument that includes a nutrition component), and possibly low serum albumin level as risk factors for developing a pressure ulcer. Nutritionists should provide a high-energy, high-protein diet for patients at risk of development of pressure ulcers to improve their dietary intake and nutritional status.

  4. Sunspot prediction using neural networks

    Science.gov (United States)

    Villarreal, James; Baffes, Paul

    1990-01-01

    The earliest systematic observance of sunspot activity is known to have been discovered by the Chinese in 1382 during the Ming Dynasty (1368 to 1644) when spots on the sun were noticed by looking at the sun through thick, forest fire smoke. Not until after the 18th century did sunspot levels become more than a source of wonderment and curiosity. Since 1834 reliable sunspot data has been collected by the National Oceanic and Atmospheric Administration (NOAA) and the U.S. Naval Observatory. Recently, considerable effort has been placed upon the study of the effects of sunspots on the ecosystem and the space environment. The efforts of the Artificial Intelligence Section of the Mission Planning and Analysis Division of the Johnson Space Center involving the prediction of sunspot activity using neural network technologies are described.

  5. Predictable response from MCR operators

    International Nuclear Information System (INIS)

    Operating Philosophy in a nuclear power plant is the driving influence that leads to obtaining a predictable response to any operating challenge in the Main Control Room. This means that for any event or abnormal situation in the plant, every operator will take the unit to the required state, every time. This is a must in our industry. This can be achieved by clearly identifying the challenges that face the operating staff. It is essential that a balanced review be done so that there is not over emphasis on any aspect of the operator's ability to respond. The major areas discussed in this presentation are Plant, Procedures and People. Discussion will bring focus to the use of procedures and how to identify good practices that require reinforcement at the simulator, and how to identify potential vulnerabilities. The three overheads will be reviewed to illustrate the systematic approach used at Darlington Nuclear. (author)

  6. Time-predictable Stack Caching

    DEFF Research Database (Denmark)

    Abbaspourseyedi, Sahar

    completely. Thus, in systems with hard deadlines the worst-case execution time (WCET) of the real-time software running on them needs to be bounded. Modern architectures use features such as pipelining and caches for improving the average performance. These features, however, make the WCET analysis more...... keeping the timepredictability of the design intact. Moreover, we provide a solution for reducing the cost of context switching in a system using the stack cache. In design of these caches, we use custom hardware and compiler support for delivering time-predictable stack data accesses. Furthermore......Embedded systems are computing systems for controlling and interacting with physical environments. Embedded systems with special timing constraints where the system needs to meet deadlines are referred to as real-time systems. In hard real-time systems, missing a deadline causes the system to fail...

  7. Comparison of Prediction-Error-Modelling Criteria

    DEFF Research Database (Denmark)

    Jørgensen, John Bagterp; Jørgensen, Sten Bay

    2007-01-01

    Single and multi-step prediction-error-methods based on the maximum likelihood and least squares criteria are compared. The prediction-error methods studied are based on predictions using the Kalman filter and Kalman predictors for a linear discrete-time stochastic state space model, which...

  8. Prediction of twin-arginine signal peptides

    DEFF Research Database (Denmark)

    Bendtsen, Jannick Dyrløv; Nielsen, Henrik; Widdick, D.;

    2005-01-01

    peptides and 84% of the annotated cleavage sites of these Tat signal peptides were correctly predicted. This method generates far less false positive predictions on various datasets than using simple pattern matching. Moreover, on the same datasets TatP generates less false positive predictions than...

  9. Applications for predictive microbiology to food packaging

    Science.gov (United States)

    Predictive microbiology has been used for several years in the food industry to predict microbial growth, inactivation and survival. Predictive models provide a useful tool in risk assessment, HACCP set-up and GMP for the food industry to enhance microbial food safety. This report introduces the c...

  10. NEURAL METHODS FOR THE FINANCIAL PREDICTION

    Directory of Open Access Journals (Sweden)

    Jerzy Balicki

    2016-06-01

    Full Text Available Artificial neural networks can be used to predict share investment on the stock market, assess the reliability of credit client or predicting banking crises. Moreover, this paper discusses the principles of cooperation neural network algorithms with evolutionary method, and support vector machines. In addition, a reference is made to other methods of artificial intelligence, which are used in finance prediction.

  11. Return Predictability, Model Uncertainty, and Robust Investment

    DEFF Research Database (Denmark)

    Lukas, Manuel

    Stock return predictability is subject to great uncertainty. In this paper we use the model confidence set approach to quantify uncertainty about expected utility from investment, accounting for potential return predictability. For monthly US data and six representative return prediction models, we...

  12. Link prediction via generalized coupled tensor factorisation

    DEFF Research Database (Denmark)

    Ermiş, Beyza; Evrim, Acar Ataman; Taylan Cemgil, A.

    2012-01-01

    This study deals with the missing link prediction problem: the problem of predicting the existence of missing connections between entities of interest. We address link prediction using coupled analysis of relational datasets represented as heterogeneous data, i.e., datasets in the form of matrice...

  13. Predictive Analytics in Information Systems Research

    NARCIS (Netherlands)

    G. Shmueli (Galit); O.R. Koppius (Otto)

    2011-01-01

    textabstractThis research essay highlights the need to integrate predictive analytics into information systems research and shows several concrete ways in which this goal can be accomplished. Predictive analytics include empirical methods (statistical and other) that generate data predictions as wel

  14. PEMS. Advanced predictive emission monitoring

    Energy Technology Data Exchange (ETDEWEB)

    Sandvig Nielsen, J.

    2010-07-15

    In the project PEMS have been developed for boilers, internal combustion engines and gas turbines. The PEMS models have been developed using two principles: The one called ''first principles'' is based on thermo-kinetic modeling of the NO{sub x}-formation by modeling conditions (like temperature, pressure and residence time) in the reaction zones. The other one is data driven using artificial neural network (ANN) and includes no physical properties and no thermo-kinetic formulation. Models of first principles have been developed for gas turbines and gas engines. Data driven models have been developed for gas turbines, gas engines and boilers. The models have been tested on data from sites located in Denmark and the Middle East. Weel and Sandvig has conducted the on-site emission measurements used for development and testing the PEMS models. For gas turbines, both the ''first principles'' and the data driven models have performed excellent considering the ability to reproduce the emission levels of NO{sub x} according to the input variables used for calibration. Data driven models for boilers and gas engines have performed excellent as well. The rather comprehensive first principle model, developed for gas engines, did not perform as well in the prediction of NO{sub x}. Possible a more complex model formulation is required for internal combustion engines. In general, both model types have been validated on data extracted from the data set used for calibration. The data for validation have been selected randomly as individual samplings, and is scattered over the entire measuring campaign. For one natural gas engine a secondary measuring campaign was conducted half a year later than the campaign used for training the data driven model. In the meantime, this engine had been through a refurbishment that included new pistons, piston rings and cylinder linings and cleaning of the cylinder heads. Despite the refurbishment, the

  15. Monthly Extended Predicting Experiments with Nonlinear Regional Prediction. Part Ⅱ: Improvement of Wave Component Prediction

    Institute of Scientific and Technical Information of China (English)

    CHEN Bomin; JI Liren; YANG Peicai; ZHANG Daomin

    2006-01-01

    Based on Chen et al. (2006), the scheme of the combination of the pentad-mean zonal height departure nonlinear prediction with the T42L9 model prediction was designed, in which the pentad zonal heights at all the 12-initial-value-input isobar levels from 50 hPa to 1000 hPa except 200, 300, 500, and 700 hPa were derived from nonlinear forecasts of the four levels by means of a good correlation between neighboring levels.Then the above pentad zonal heights at 12 isobar-levels were transformed to the spectrum coefficients of the temperature at each integration step of T42L9 model. At last, the nudging was made. On account of a variety of error accumulation, the pentad zonal components of the monthly height at isobar levels output by T42L9 model were replaced by the corresponding nonlinear results once more when integration was over.Multiple case experiments showed that such combination of two kinds of prediction made an improvement in the wave component as a result of wave-flow nonlinear interaction while reducing the systematical forecast errors. Namely the monthly-mean height anomaly correlation coefficients over the high- and mid-latitudes of the Northern Hemisphere, over the Southern Hemisphere and over the globe increased respectively from 0.249 to 0.347, from 0.286 to 0.387, and from 0.343 to 0.414 (relative changes of 31.5%, 41.0%, and 18.3%).The monthly-mean root-mean-square error (RMSE) of T42L9 model over the three areas was considerably decreased, the relative change over the globe reached 44.2%. The monthly-mean anomaly correlation coefficients of wave 4-9 over the areas were up to 0.392, 0.200, and 0.295, with the relative change of 53.8%, 94.1%,and 61.2%, and correspondingly their RMSEs were decreased respectively with the rate of 8.5%, 6.3%, and 8.1%. At the same time the monthly-mean pattern of parts of cases were presented better.

  16. Conditional prediction intervals of wind power generation

    DEFF Research Database (Denmark)

    Pinson, Pierre; Kariniotakis, Georges

    2010-01-01

    A generic method for the providing of prediction intervals of wind power generation is described. Prediction intervals complement the more common wind power point forecasts, by giving a range of potential outcomes for a given probability, their so-called nominal coverage rate. Ideally they inform...... on the characteristics of prediction errors for providing conditional interval forecasts. By simultaneously generating prediction intervals with various nominal coverage rates, one obtains full predictive distributions of wind generation. Adapted resampling is applied here to the case of an onshore Danish wind farm...... to the case of a large number of wind farms in Europe and Australia among others is finally discussed....

  17. Predictive Functional Control for Fractional Order System

    Directory of Open Access Journals (Sweden)

    Morteza Abdolhosseini

    2014-01-01

    Full Text Available The fractional calculus is the area of mathematics that handles derivatives and integrals of any arbitrary order (fractional or integer, real or complex order. Predictive Functional Control (PFC is one of the most popular methods of model predictive control. The implementation of the predictive functional controller (PFC on the fractional order systems has been presented in this paper. The effect of various approximations, sensitivity analysis, tuning of predictive functional controller parameters, the effect of delay and noise analysis of the fractional-order system has been considered. It has been shown that, in fractional order system, predictive functional control gives acceptable results

  18. Adaptive nonlinear prediction of ocean reverberation

    Institute of Scientific and Technical Information of China (English)

    GAN Weiming; LI Fenghua

    2009-01-01

    An adaptive nonlinear prediction algorithm is proposed to predict ocean reverber-ation based on the phase space reconstruction of nonlinear dynamic system. The prediction algorithm is tested by experimental reverberation data measured in two areas, and the one-step forward prediction results are in good agreement with the experimental data. If the errors between the predicted and experimental data are chosen as the variable to detect the target in the reverberation series, the reverberation is suppressed and the signal-to-reverberation ratio is improved.

  19. Protein secondary structure: category assignment and predictability

    DEFF Research Database (Denmark)

    Andersen, Claus A.; Bohr, Henrik; Brunak, Søren

    2001-01-01

    In the last decade, the prediction of protein secondary structure has been optimized using essentially one and the same assignment scheme known as DSSP. We present here a different scheme, which is more predictable. This scheme predicts directly the hydrogen bonds, which stabilize the secondary...... structures. Single sequence prediction of the new three category assignment gives an overall prediction improvement of 3.1% and 5.1%, compared to the DSSP assignment and schemes where the helix category consists of a-helix and 3(10)-helix, respectively. These results were achieved using a standard feed-forward...

  20. BDDCS Class Prediction for New Molecular Entities

    DEFF Research Database (Denmark)

    Broccatelli, Fabio; Cruciani, Gabriele; Benet, Leslie Z.;

    2012-01-01

    M) predicts high versus low intestinal permeability rate, and vice versa, at least when uptake transporters or paracellular transport is not involved. We recently published a collection of over 900 marketed drugs classified for BDDCS. We suggest that a reliable model for predicting BDDCS class, integrated...... descriptors calculated or derived from the VolSurf+ software. For each molecule, a probability of BDDCS class membership was given, based on predicted EoM, FDA solubility (FDAS) and their confidence scores. The accuracy in predicting FDAS was 78% in training and 77% in validation, while for EoM prediction...

  1. A Prospect of Earthquake Prediction Research

    CERN Document Server

    Ogata, Yosihiko

    2013-01-01

    Earthquakes occur because of abrupt slips on faults due to accumulated stress in the Earth's crust. Because most of these faults and their mechanisms are not readily apparent, deterministic earthquake prediction is difficult. For effective prediction, complex conditions and uncertain elements must be considered, which necessitates stochastic prediction. In particular, a large amount of uncertainty lies in identifying whether abnormal phenomena are precursors to large earthquakes, as well as in assigning urgency to the earthquake. Any discovery of potentially useful information for earthquake prediction is incomplete unless quantitative modeling of risk is considered. Therefore, this manuscript describes the prospect of earthquake predictability research to realize practical operational forecasting in the near future.

  2. The predictability of consumer visitation patterns

    CERN Document Server

    Krumme, Coco; Cebrián, Manuel; Alex,; Pentland,; Moro, Esteban; 10.1038/srep01645

    2013-01-01

    We consider hundreds of thousands of individual economic transactions to ask: how predictable are consumers in their merchant visitation patterns? Our results suggest that, in the long-run, much of our seemingly elective activity is actually highly predictable. Notwithstanding a wide range of individual preferences, shoppers share regularities in how they visit merchant locations over time. Yet while aggregate behavior is largely predictable, the interleaving of shopping events introduces important stochastic elements at short time scales. These short- and long-scale patterns suggest a theoretical upper bound on predictability, and describe the accuracy of a Markov model in predicting a person's next location. We incorporate population-level transition probabilities in the predictive models, and find that in many cases these improve accuracy. While our results point to the elusiveness of precise predictions about where a person will go next, they suggest the existence, at large time-scales, of regularities ac...

  3. Entropy and the Predictability of Online Life

    CERN Document Server

    Sinatra, Roberta

    2014-01-01

    Using mobile phone records and information theory measures, our daily lives have been recently shown to follow strict statistical regularities, and our movement patterns are to a large extent predictable. Here, we apply entropy and predictability measures to two data sets of the behavioral actions and the mobility of a large number of players in the virtual universe of a massive multiplayer online game. We find that movements in virtual human lives follow the same high levels of predictability as offline mobility, where future movements can to some extent be predicted well if the temporal correlations of visited places are accounted for. Time series of behavioral actions show similar high levels of predictability, even when temporal correlations are neglected. Entropy conditional on specific behavioral actions reveals that in terms of predictability negative behavior has a wider variety than positive actions. The actions which contain information to best predict an individual's subsequent action are negative,...

  4. Predicting Well-Being in Europe?

    DEFF Research Database (Denmark)

    Hussain, M. Azhar

    2015-01-01

    Has the worst financial and economic crisis since the 1930s reduced the subjective wellbeing function's predictive power? Regression models for happiness are estimated for the three first rounds of the European Social Survey (ESS); 2002, 2004 and 2006. Several explanatory variables are significant...... with the expected signs and an average determination coefficient around 0.25. Based on these estimated parameters happiness is predicted for the latest three rounds of the ESS; 2008, 2010 and 2012. Happiness is slightly underestimated in both 2008 and 2010, e.g. actual happiness generally is above predicted...... happiness. Nevertheless, 73% of the predictions in 2008 and 57% of predictions in 2010 were within the margin of error. These correct prediction percentages are not unusually low - rather they are slightly higher than before the crisis. It is surprising that happiness predictions are not adversely affected...

  5. Neural network prediction of solar cycle 24

    Institute of Scientific and Technical Information of China (English)

    A. Ajabshirizadeh; N. Masoumzadeh Jouzdani; Shahram Abbassi

    2011-01-01

    The ability to predict the future behavior of solar activity has become extremely import due to its effect on the environment near the Earth. Predictions of both the amplitude and timing of the next solar cycle will assist in estimating the various consequences of space weather. The level of solar activity is usually expressed by international sunspot number (Rz). Several prediction techniques have been applied and have achieved varying degrees of success in the domain of solar activity prediction.We predict a solar index (Rz) in solar cycle 24 by using a neural network method. The neural network technique is used to analyze the time series of solar activity. According to our predictions of yearly sunspot number, the maximum of cycle 24 will occur in the year 2013 and will have an annual mean sunspot number of 65. Finally, we discuss our results in order to compare them with other suggested predictions.

  6. Predicting Electronic Failure from Smoke

    Energy Technology Data Exchange (ETDEWEB)

    Tanaka, T.J.

    1999-01-15

    Smoke can cause electronic equipment to fail through increased leakage currents and shorts. Sandia National Laboratories is studying the increased leakage currents caused by smoke with varying characteristics. The objective is to develop models to predict the failure of electronic equipment exposed to smoke. This requires the collection of data on the conductivity of smoke and knowledge of critical electrical systems that control high-consequence operations. We have found that conductivity is a function of the type of fuel, how it is burned, and smoke density. Video recordings of highly biased dc circuits exposed in a test chamber show that during a fire, smoke is attracted to high voltages and can build fragile carbon bridges that conduct leakage currents. The movement of air breaks the bridges, so the conductivity decreases after the fire is extinguished and the test chamber is vented. During the fire, however, electronic equipment may not operate correctly, leading to problems for critical operations dependent on electronic control. The potential for electronic failure is highly dependent on the type of electrical circuit, and Sandia National Laboratories plans to include electrical circuit modeling in the failure models.

  7. Predictive properties of visual adaptation.

    Science.gov (United States)

    Chopin, Adrien; Mamassian, Pascal

    2012-04-10

    What humans perceive depends in part on what they have previously experienced. After repeated exposure to one stimulus, adaptation takes place in the form of a negative correlation between the current percept and the last displayed stimuli. Previous work has shown that this negative dependence can extend to a few minutes in the past, but the precise extent and nature of the dependence in vision is still unknown. In two experiments based on orientation judgments, we reveal a positive dependence of a visual percept with stimuli presented remotely in the past, unexpectedly and in contrast to what is known for the recent past. Previous theories of adaptation have postulated that the visual system attempts to calibrate itself relative to an ideal norm or to the recent past. We propose instead that the remote past is used to estimate the world's statistics and that this estimate becomes the reference. According to this new framework, adaptation is predictive: the most likely forthcoming percept is the one that helps the statistics of the most recent percepts match that of the remote past.

  8. PTIR: Predicted Tomato Interactome Resource.

    Science.gov (United States)

    Yue, Junyang; Xu, Wei; Ban, Rongjun; Huang, Shengxiong; Miao, Min; Tang, Xiaofeng; Liu, Guoqing; Liu, Yongsheng

    2016-01-01

    Protein-protein interactions (PPIs) are involved in almost all biological processes and form the basis of the entire interactomics systems of living organisms. Identification and characterization of these interactions are fundamental to elucidating the molecular mechanisms of signal transduction and metabolic pathways at both the cellular and systemic levels. Although a number of experimental and computational studies have been performed on model organisms, the studies exploring and investigating PPIs in tomatoes remain lacking. Here, we developed a Predicted Tomato Interactome Resource (PTIR), based on experimentally determined orthologous interactions in six model organisms. The reliability of individual PPIs was also evaluated by shared gene ontology (GO) terms, co-evolution, co-expression, co-localization and available domain-domain interactions (DDIs). Currently, the PTIR covers 357,946 non-redundant PPIs among 10,626 proteins, including 12,291 high-confidence, 226,553 medium-confidence, and 119,102 low-confidence interactions. These interactions are expected to cover 30.6% of the entire tomato proteome and possess a reasonable distribution. In addition, ten randomly selected PPIs were verified using yeast two-hybrid (Y2H) screening or a bimolecular fluorescence complementation (BiFC) assay. The PTIR was constructed and implemented as a dedicated database and is available at http://bdg.hfut.edu.cn/ptir/index.html without registration. PMID:27121261

  9. Global scale predictability of floods

    Science.gov (United States)

    Weerts, Albrecht; Gijsbers, Peter; Sperna Weiland, Frederiek

    2016-04-01

    Flood (and storm surge) forecasting at the continental and global scale has only become possible in recent years (Emmerton et al., 2016; Verlaan et al., 2015) due to the availability of meteorological forecast, global scale precipitation products and global scale hydrologic and hydrodynamic models. Deltares has setup GLOFFIS a research-oriented multi model operational flood forecasting system based on Delft-FEWS in an open experimental ICT facility called Id-Lab. In GLOFFIS both the W3RA and PCRGLOB-WB model are run in ensemble mode using GEFS and ECMWF-EPS (latency 2 days). GLOFFIS will be used for experiments into predictability of floods (and droughts) and their dependency on initial state estimation, meteorological forcing and the hydrologic model used. Here we present initial results of verification of the ensemble flood forecasts derived with the GLOFFIS system. Emmerton, R., Stephens, L., Pappenberger, F., Pagano, T., Weerts, A., Wood, A. Salamon, P., Brown, J., Hjerdt, N., Donnelly, C., Cloke, H. Continental and Global Scale Flood Forecasting Systems, WIREs Water (accepted), 2016 Verlaan M, De Kleermaeker S, Buckman L. GLOSSIS: Global storm surge forecasting and information system 2015, Australasian Coasts & Ports Conference, 15-18 September 2015,Auckland, New Zealand.

  10. Holistic processing predicts face recognition.

    Science.gov (United States)

    Richler, Jennifer J; Cheung, Olivia S; Gauthier, Isabel

    2011-04-01

    The concept of holistic processing is a cornerstone of face-recognition research. In the study reported here, we demonstrated that holistic processing predicts face-recognition abilities on the Cambridge Face Memory Test and on a perceptual face-identification task. Our findings validate a large body of work that relies on the assumption that holistic processing is related to face recognition. These findings also reconcile the study of face recognition with the perceptual-expertise work it inspired; such work links holistic processing of objects with people's ability to individuate them. Our results differ from those of a recent study showing no link between holistic processing and face recognition. This discrepancy can be attributed to the use in prior research of a popular but flawed measure of holistic processing. Our findings salvage the central role of holistic processing in face recognition and cast doubt on a subset of the face-perception literature that relies on a problematic measure of holistic processing.

  11. Predicting the outcome of roulette

    Science.gov (United States)

    Small, Michael; Tse, Chi Kong

    2012-09-01

    There have been several popular reports of various groups exploiting the deterministic nature of the game of roulette for profit. Moreover, through its history, the inherent determinism in the game of roulette has attracted the attention of many luminaries of chaos theory. In this paper, we provide a short review of that history and then set out to determine to what extent that determinism can really be exploited for profit. To do this, we provide a very simple model for the motion of a roulette wheel and ball and demonstrate that knowledge of initial position, velocity, and acceleration is sufficient to predict the outcome with adequate certainty to achieve a positive expected return. We describe two physically realizable systems to obtain this knowledge both incognito and in situ. The first system relies only on a mechanical count of rotation of the ball and the wheel to measure the relevant parameters. By applying these techniques to a standard casino-grade European roulette wheel, we demonstrate an expected return of at least 18%, well above the -2.7% expected of a random bet. With a more sophisticated, albeit more intrusive, system (mounting a digital camera above the wheel), we demonstrate a range of systematic and statistically significant biases which can be exploited to provide an improved guess of the outcome. Finally, our analysis demonstrates that even a very slight slant in the roulette table leads to a very pronounced bias which could be further exploited to substantially enhance returns.

  12. Predicting the outcome of roulette

    CERN Document Server

    Small, Michael

    2012-01-01

    There have been several popular reports of various groups exploiting the deterministic nature of the game of roulette for profit. Moreover, through its history the inherent determinism in the game of roulette has attracted the attention of many luminaries of chaos theory. In this paper we provide a short review of that history and then set out to determine to what extent that determinism can really be exploited for profit. To do this, we provide a very simple model for the motion of a roulette wheel and ball and demonstrate that knowledge of initial position, velocity and acceleration is sufficient to predict the outcome with adequate certainty to achieve a positive expected return. We describe two physically realisable systems to obtain this knowledge both incognito and {\\em in situ}. The first system relies only on a mechanical count of rotation of the ball and the wheel to measure the relevant parameters. By applying this techniques to a standard casino-grade European roulette wheel we demonstrate an expec...

  13. Entropy and the Predictability of Online Life

    Directory of Open Access Journals (Sweden)

    Roberta Sinatra

    2014-01-01

    Full Text Available Using mobile phone records and information theory measures, our daily lives have been recently shown to follow strict statistical regularities, and our movement patterns are, to a large extent, predictable. Here, we apply entropy and predictability measures to two datasets of the behavioral actions and the mobility of a large number of players in the virtual universe of a massive multiplayer online game. We find that movements in virtual human lives follow the same high levels of predictability as offline mobility, where future movements can, to some extent, be predicted well if the temporal correlations of visited places are accounted for. Time series of behavioral actions show similar high levels of predictability, even when temporal correlations are neglected. Entropy conditional on specific behavioral actions reveals that in terms of predictability, negative behavior has a wider variety than positive actions. The actions that contain the information to best predict an individual’s subsequent action are negative, such as attacks or enemy markings, while the positive actions of friendship marking, trade and communication contain the least amount of predictive information. These observations show that predicting behavioral actions requires less information than predicting the mobility patterns of humans for which the additional knowledge of past visited locations is crucial and that the type and sign of a social relation has an essential impact on the ability to determine future behavior.

  14. The MULTICOM toolbox for protein structure prediction

    Directory of Open Access Journals (Sweden)

    Cheng Jianlin

    2012-04-01

    Full Text Available Abstract Background As genome sequencing is becoming routine in biomedical research, the total number of protein sequences is increasing exponentially, recently reaching over 108 million. However, only a tiny portion of these proteins (i.e. ~75,000 or Results To meet the need, we have developed a comprehensive MULTICOM toolbox consisting of a set of protein structure and structural feature prediction tools. These tools include secondary structure prediction, solvent accessibility prediction, disorder region prediction, domain boundary prediction, contact map prediction, disulfide bond prediction, beta-sheet topology prediction, fold recognition, multiple template combination and alignment, template-based tertiary structure modeling, protein model quality assessment, and mutation stability prediction. Conclusions These tools have been rigorously tested by many users in the last several years and/or during the last three rounds of the Critical Assessment of Techniques for Protein Structure Prediction (CASP7-9 from 2006 to 2010, achieving state-of-the-art or near performance. In order to facilitate bioinformatics research and technological development in the field, we have made the MULTICOM toolbox freely available as web services and/or software packages for academic use and scientific research. It is available at http://sysbio.rnet.missouri.edu/multicom_toolbox/.

  15. Predictability of threshold exceedances in dynamical systems

    Science.gov (United States)

    Bódai, Tamás

    2015-12-01

    In a low-order model of the general circulation of the atmosphere we examine the predictability of threshold exceedance events of certain observables. The likelihood of such binary events-the cornerstone also for the categoric (as opposed to probabilistic) prediction of threshold exceedances-is established from long time series of one or more observables of the same system. The prediction skill is measured by a summary index of the ROC curve that relates the hit- and false alarm rates. Our results for the examined systems suggest that exceedances of higher thresholds are more predictable; or in other words: rare large magnitude, i.e., extreme, events are more predictable than frequent typical events. We find this to hold provided that the bin size for binning time series data is optimized, but not necessarily otherwise. This can be viewed as a confirmation of a counterintuitive (and seemingly contrafactual) statement that was previously formulated for more simple autoregressive stochastic processes. However, we argue that for dynamical systems in general it may be typical only, but not universally true. We argue that when there is a sufficient amount of data depending on the precision of observation, the skill of a class of data-driven categoric predictions of threshold exceedances approximates the skill of the analogous model-driven prediction, assuming strictly no model errors. Therefore, stronger extremes in terms of higher threshold levels are more predictable both in case of data- and model-driven prediction. Furthermore, we show that a quantity commonly regarded as a measure of predictability, the finite-time maximal Lyapunov exponent, does not correspond directly to the ROC-based measure of prediction skill when they are viewed as functions of the prediction lead time and the threshold level. This points to the fact that even if the Lyapunov exponent as an intrinsic property of the system, measuring the instability of trajectories, determines predictability

  16. Prediction of rates of inbreeding in populations selected on best linear unbiased prediction of breeding value.

    OpenAIRE

    Bijma, P.; Woolliams, John

    2000-01-01

    Predictions for the rate of inbreeding (DeltaF) in populations with discrete generations undergoing selection on best linear unbiased prediction (BLUP) of breeding value were developed. Predictions were based on the concept of long-term genetic contributions using a recently established relationship between expected contributions and rates of inbreeding and a known procedure for predicting expected contributions. Expected contributions of individuals were predicted using a linear model, u(i)(...

  17. Prediction of tar ball formation

    Energy Technology Data Exchange (ETDEWEB)

    Khelifa, A.; Gamble, L. [Environment Canada, Ottawa, ON (Canada). Emergencies Science and Technology Division, Environmental Technology Centre, Science and Technology Branch

    2006-07-01

    The presence of small tar balls ranging in size from less than a millimetre to 60 centimetres have been observed during cleanup assessment operations following accidental oil spills on water. The tar balls are composed of heavy oil residues and suspended particulate matter (SPM) from the water column. They can be found on shorelines, settled on the seafloor and floating at or near the water surface. Their abundance on the shorelines varies from site to site and depends on the conditions of the spill and mixing conditions. Aggregation between SPM and micro-sized oil droplets occurs naturally in coastal waters and enhances the dispersion of spilled oil. Although tar balls are among the important end states of spilled oil in the marine environment, no model exists to estimate the percentage of the spilled oil that becomes tar balls. This paper offered some insight into the modeling of tar ball formation. Current modeling understanding of oil-SPM aggregate formation was used to predict tar ball formation. The formation of oil droplets was examined with respect to a range of conditions under which the formation of large droplets is expected. The role of aggregation was then presented to demonstrate the effects of concentration and type of SPM on the buoyancy of tar balls. Good agreement was found between modeling results and field data reported in the literature regarding the size and density of tar balls. Oil viscosity and mixing energy were found to be the main factors controlling the formation of tar balls. The aggregation of tar balls with SPM and shoreline material results in significant increases or decreases in density, depending on the type and concentration of SPM. 42 refs., 2 tabs., 6 figs.

  18. Predictive Approaches to Control of Complex Systems

    CERN Document Server

    Karer, Gorazd

    2013-01-01

    A predictive control algorithm uses a model of the controlled system to predict the system behavior for various input scenarios and determines the most appropriate inputs accordingly. Predictive controllers are suitable for a wide range of systems; therefore, their advantages are especially evident when dealing with relatively complex systems, such as nonlinear, constrained, hybrid, multivariate systems etc. However, designing a predictive control strategy for a complex system is generally a difficult task, because all relevant dynamical phenomena have to be considered. Establishing a suitable model of the system is an essential part of predictive control design. Classic modeling and identification approaches based on linear-systems theory are generally inappropriate for complex systems; hence, models that are able to appropriately consider complex dynamical properties have to be employed in a predictive control algorithm. This book first introduces some modeling frameworks, which can encompass the most frequ...

  19. Video Traffic Prediction Using Neural Networks

    Directory of Open Access Journals (Sweden)

    Miloš Oravec

    2008-10-01

    Full Text Available In this paper, we consider video stream prediction for application in services likevideo-on-demand, videoconferencing, video broadcasting, etc. The aim is to predict thevideo stream for an efficient bandwidth allocation of the video signal. Efficient predictionof traffic generated by multimedia sources is an important part of traffic and congestioncontrol procedures at the network edges. As a tool for the prediction, we use neuralnetworks – multilayer perceptron (MLP, radial basis function networks (RBF networksand backpropagation through time (BPTT neural networks. At first, we briefly introducetheoretical background of neural networks, the prediction methods and the differencebetween them. We propose also video time-series processing using moving averages.Simulation results for each type of neural network together with final comparisons arepresented. For comparison purposes, also conventional (non-neural prediction isincluded. The purpose of our work is to construct suitable neural networks for variable bitrate video prediction and evaluate them. We use video traces from [1].

  20. Prediction of aspiration in myasthenia gravis.

    Science.gov (United States)

    Koopman, Wilma J; Wiebe, Samuel; Colton-Hudson, Angela; Moosa, Tas; Smith, Dean; Bach, David; Nicolle, Michael W

    2004-02-01

    Prediction of the risk of dysphagia and aspiration is important in the management of myasthenia gravis (MG). We assessed the ability of four bedside clinical tools to predict aspiration in 20 MG patients. Patients completed a self-directed questionnaire, underwent clinical neurological assessment and a bedside speech pathology assessment, and were assessed with the quantitative myasthenia gravis (QMG) score. The ability of these tools to predict aspiration was compared with the results of a modified barium swallow. Seven patients aspirated, 4 silently. The total self-directed questionnaire score, two specific questions on the self-directed questionnaire, the prediction based on clinical neurological assessment, and the QMG bulbar subset score all correlated with aspiration. The speech pathology prediction was highly sensitive but less specific. This pilot study shows that simple clinical tools can predict which MG patients are at risk of aspiration. PMID:14755491

  1. Improve consensus via decentralized predictive mechanisms

    Science.gov (United States)

    Zhang, H.-T.; Chen, M. Z. Q.; Zhou, T.

    2009-05-01

    For biogroups and groups of self-driven agents, making decisions often depends on interactions among group members. In this paper, we seek to understand the fundamental predictive mechanisms used by group members in order to perform such coordinated behaviors. In particular, we show that the future dynamics of each node in the network can be predicted solely using local information provided by its neighbors. Using this predicted future dynamics information, we propose a decentralized predictive consensus protocol, which yields drastic improvements in terms of both consensus speed and internal communication cost. In natural science, this study provides an evidence for the idea that some decentralized predictive mechanisms may exist in widely-spread biological swarms/flocks. From the industrial point of view, incorporation of a decentralized predictive mechanism allows for not only a significant increase in the speed of convergence towards consensus but also a reduction in the communication energy required to achieve a predefined consensus performance.

  2. Applications of Neural Networks in Spinning Prediction

    Institute of Scientific and Technical Information of China (English)

    程文红; 陆凯

    2003-01-01

    The neural network spinning prediction model (BP and RBF Networks) trained by data from the mill can predict yarn qualities and spinning performance. The input parameters of the model are as follows: yarn count, diameter, hauteur, bundle strength, spinning draft, spinning speed, traveler number and twist.And the output parameters are: yarn evenness, thin places, tenacity and elongation, ends-down.Predicting results match the testing data well.

  3. Towards the perfect prediction of soccer matches

    OpenAIRE

    Heuer, Andreas; Rubner, Oliver

    2012-01-01

    We present a systematic approach to the prediction of soccer matches. First, we show that the information about chances for goals is by far more informative than about the actual results. Second, we present a multivariate regression approach and show how the prediction quality increases with increasing information content. This prediction quality can be explicitly expressed in terms of just two parameters. Third, by disentangling the systematic and random components of soccer matches we can i...

  4. Empirical studies on stock return predictability

    OpenAIRE

    Wang, Jingya

    2016-01-01

    This thesis includes three essays on topics related to the predictability of market returns. I investigate i) the predictability of market returns from an adjusted version of cay ratio (cayadj), ii) the explanatory power of a conditional version of the consumption-CAPM which uses predictor variables to scale the pricing kernel, and iii) whether information about future market returns can be extracted from a large set of commodity data.The first essay studies the predictive ability of cayadj ....

  5. Sparse preconditioning for model predictive control

    OpenAIRE

    Knyazev, Andrew; Malyshev, Alexander,

    2015-01-01

    We propose fast O(N) preconditioning, where N is the number of gridpoints on the prediction horizon, for iterative solution of (non)-linear systems appearing in model predictive control methods such as forward-difference Newton-Krylov methods. The Continuation/GMRES method for nonlinear model predictive control, suggested by T. Ohtsuka in 2004, is a specific application of the Newton-Krylov method, which uses the GMRES iterative algorithm to solve a forward difference approximation of the opt...

  6. Recommendations for PDF usage in LHC predictions

    CERN Document Server

    Placakyte, Ringaile

    2016-01-01

    A short review of the currently available modern parton distribution functions (PDFs)and the theory predictions obtained using those PDFs for several benchmark processes at LHC, including Higgs boson production, is presented in this write-up. It includes the discussion on theory assumptions made in the determination procedure of PDFs and an impact on the differences in the obtained predictions, followed by the alternative to PDF4LHC recommendations for the usage of PDF sets for theory predictions at the LHC.

  7. Predictive Functional Control for a Parallel Robot

    OpenAIRE

    Vivas, Oscar Andrès; Poignet, Philippe; Pierrot, François

    2003-01-01

    This paper presents an efficient application of a model based predictive control in parallel mechanisms. A predictive functional control control strategy based on a simplified dynamic model is implemented. Experimental results are shown for the H4 robot, a fully parallel structure providing 3 degrees of freedom (dof) in translation and 1 dof in rotation. Predictive functional control, computed torque control and PID control strategies are compared in complex machining tasks trajectories. The ...

  8. Two Comments on Predictive Picture Coding

    Institute of Scientific and Technical Information of China (English)

    1998-01-01

    Two comments on predictive picture coding are given in this paper. 1) In lossy coding, the reconstructed values of picture samples, not its original values, should be used in the prediction formula. 2) In the design of optimum predictors, the minimum entropy or subjective assessment or other criterions, could be used, depending on the applications of the prediction encoder, instead of the minimum mean square error (MMSE) criterion.

  9. Predicting of Ukrainian Horticulture Market Development

    OpenAIRE

    Sokil, Yana

    2013-01-01

    For determination of community needs in garden-stuffs and berries for period 2012-2015 it is suggested to carry out prediction of consumption level of horticulture products by the construction of neuron network on the basis of architecture “8-4-1” multilayered perceptron. Initial and predicted rows of consumption level of horticulture products with the purpose of possibility exposure of the predicted volumes of horticultural products consumption for period 2012-2015 and used for developmen...

  10. Final Technical Report: Increasing Prediction Accuracy.

    Energy Technology Data Exchange (ETDEWEB)

    King, Bruce Hardison [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Hansen, Clifford [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Stein, Joshua [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2015-12-01

    PV performance models are used to quantify the value of PV plants in a given location. They combine the performance characteristics of the system, the measured or predicted irradiance and weather at a site, and the system configuration and design into a prediction of the amount of energy that will be produced by a PV system. These predictions must be as accurate as possible in order for finance charges to be minimized. Higher accuracy equals lower project risk. The Increasing Prediction Accuracy project at Sandia focuses on quantifying and reducing uncertainties in PV system performance models.

  11. Towards the perfect prediction of soccer matches

    CERN Document Server

    Heuer, Andreas

    2012-01-01

    We present a systematic approach to the prediction of soccer matches. First, we show that the information about chances for goals is by far more informative than about the actual results. Second, we present a multivariate regression approach and show how the prediction quality increases with increasing information content. This prediction quality can be explicitly expressed in terms of just two parameters. Third, by disentangling the systematic and random components of soccer matches we can identify the optimum level of predictability. These concepts are exemplified for the German Bundesliga.

  12. The U.S. Earthquake Prediction Program

    Science.gov (United States)

    Wesson, R.L.; Filson, J.R.

    1981-01-01

    Following on from the concepts of plate tectonics, the earth sciences are now embarking on a challenging course- the time prediction of geologic phenomena. Earthquake prediction is an outstanding example of this. However, earthquake prediction is not the only scientific goal. The destructive power of a large earthquake requires that we also take mitigating actions; these include earthquake engineering research to design construction that will resist earthquake shaking. Nevertheless, earthquake prediction has a vital role to play not only in the saving of lives, but in the reduction of economic loss and social disruption from large earthquakes.

  13. Theoretical prediction of crystal structures of rubrene

    Science.gov (United States)

    Obata, Shigeaki; Miura, Toshiaki; Shimoi, Yukihiro

    2014-01-01

    We theoretically predict crystal structures and molecular arrangements for rubrene molecule using CONFLEX program and compare them with the experimental ones. The most, second-most, and fourth-most stable predicted crystal structures show good agreement with the triclinic, orthorhombic, and monoclinic polymorphs of rubrene, respectively. The change in molecular conformation is also predicted between crystalline and gas phases: the tetracene backbone takes flat conformation in crystalline phase as in the observed structure. Meanwhile, it is twisted in gas phase. The theoretical prediction method used in this work provides the successful results on the determination of the three kinds of crystal structures and molecular arrangements for rubrene molecule.

  14. Predictions of High Energy Experimental Results

    Directory of Open Access Journals (Sweden)

    Comay E.

    2010-10-01

    Full Text Available Eight predictions of high energy experimental results are presented. The predictions contain the $Sigma ^+$ charge radius and results of two kinds of experiments using energetic pionic beams. In addition, predictions of the failure to find the following objects are presented: glueballs, pentaquarks, Strange Quark Matter, magnetic monopoles searched by their direct interaction with charges and the Higgs boson. The first seven predictions rely on the Regular Charge-Monopole Theory and the last one relies on mathematical inconsistencies of the Higgs Lagrangian density.

  15. Programming Useful Life Prediction (PULP) Project

    Data.gov (United States)

    National Aeronautics and Space Administration — Accurately predicting Remaining Useful Life (RUL) provides significant benefits—it increases safety and reduces financial and labor resource requirements....

  16. Implementation of short-term prediction

    Energy Technology Data Exchange (ETDEWEB)

    Landberg, L.; Joensen, A.; Giebel, G. [and others

    1999-03-01

    This paper will giver a general overview of the results from a EU JOULE funded project (`Implementing short-term prediction at utilities`, JOR3-CT95-0008). Reference will be given to specialised papers where applicable. The goal of the project was to implement wind farm power output prediction systems in operational environments at a number of utilities in Europe. Two models were developed, one by Risoe and one by the Technical University of Denmark (DTU). Both prediction models used HIRLAM predictions from the Danish Meteorological Institute (DMI). (au) EFP-94; EU-JOULE. 11 refs.

  17. Improved interpretation and validation of CFD predictions

    DEFF Research Database (Denmark)

    Popiolek, Z.; Melikov, Arsen Krikor

    2004-01-01

    The mean velocity in rooms predicted by CFD simulations based on RANS equations differs from the mean (in time) magnitude of the velocity, i.e. the mean speed, in rooms measured by low velocity thermal anemometers with omnidirectional sensor. This discrepancy results in incorrect thermal comfort...... assessment by the CFD predictions as well as incorrect validation of the predicted velocity field. In this paper the discrepancies are discussed and identified, and a method for estimating of the mean speed based on the CFD predictions of mean velocity and kinetic turbulence energy is suggested. The method...

  18. An overview of service lifetime prediction (SLP)

    Energy Technology Data Exchange (ETDEWEB)

    Jorgensen, G. [National Renewable Energy Laboratory, Golden, CO (United States)

    1995-11-01

    This report describes the need for service life prediction for photovoltaic cells and associated devices, coatings, and other related technologies. Information regarding outdoor exposure tests is given.

  19. Fracture Toughness Prediction for MWCNT Reinforced Ceramics

    Energy Technology Data Exchange (ETDEWEB)

    Henager, Charles H.; Nguyen, Ba Nghiep

    2013-09-01

    This report describes the development of a micromechanics model to predict fracture toughness of multiwall carbon nanotube (MWCNT) reinforced ceramic composites to guide future experimental work for this project. The modeling work described in this report includes (i) prediction of elastic properties, (ii) development of a mechanistic damage model accounting for matrix cracking to predict the composite nonlinear stress/strain response to tensile loading to failure, and (iii) application of this damage model in a modified boundary layer (MBL) analysis using ABAQUS to predict fracture toughness and crack resistance behavior (R-curves) for ceramic materials containing MWCNTs at various volume fractions.

  20. Computer loss experience and predictions

    Science.gov (United States)

    Parker, Donn B.

    1996-03-01

    The types of losses organizations must anticipate have become more difficult to predict because of the eclectic nature of computers and the data communications and the decrease in news media reporting of computer-related losses as they become commonplace. Total business crime is conjectured to be decreasing in frequency and increasing in loss per case as a result of increasing computer use. Computer crimes are probably increasing, however, as their share of the decreasing business crime rate grows. Ultimately all business crime will involve computers in some way, and we could see a decline of both together. The important information security measures in high-loss business crime generally concern controls over authorized people engaged in unauthorized activities. Such controls include authentication of users, analysis of detailed audit records, unannounced audits, segregation of development and production systems and duties, shielding the viewing of screens, and security awareness and motivation controls in high-value transaction areas. Computer crimes that involve highly publicized intriguing computer misuse methods, such as privacy violations, radio frequency emanations eavesdropping, and computer viruses, have been reported in waves that periodically have saturated the news media during the past 20 years. We must be able to anticipate such highly publicized crimes and reduce the impact and embarrassment they cause. On the basis of our most recent experience, I propose nine new types of computer crime to be aware of: computer larceny (theft and burglary of small computers), automated hacking (use of computer programs to intrude), electronic data interchange fraud (business transaction fraud), Trojan bomb extortion and sabotage (code security inserted into others' systems that can be triggered to cause damage), LANarchy (unknown equipment in use), desktop forgery (computerized forgery and counterfeiting of documents), information anarchy (indiscriminate use of

  1. Drought Predictability and Prediction in a Changing Climate: Assessing Current Predictive Knowledge and Capabilities, User Requirements and Research Priorities

    Science.gov (United States)

    Schubert, Siegfried

    2011-01-01

    Drought is fundamentally the result of an extended period of reduced precipitation lasting anywhere from a few weeks to decades and even longer. As such, addressing drought predictability and prediction in a changing climate requires foremost that we make progress on the ability to predict precipitation anomalies on subseasonal and longer time scales. From the perspective of the users of drought forecasts and information, drought is however most directly viewed through its impacts (e.g., on soil moisture, streamflow, crop yields). As such, the question of the predictability of drought must extend to those quantities as well. In order to make progress on these issues, the WCRP drought information group (DIG), with the support of WCRP, the Catalan Institute of Climate Sciences, the La Caixa Foundation, the National Aeronautics and Space Administration, the National Oceanic and Atmospheric Administration, and the National Science Foundation, has organized a workshop to focus on: 1. User requirements for drought prediction information on sub-seasonal to centennial time scales 2. Current understanding of the mechanisms and predictability of drought on sub-seasonal to centennial time scales 3. Current drought prediction/projection capabilities on sub-seasonal to centennial time scales 4. Advancing regional drought prediction capabilities for variables and scales most relevant to user needs on sub-seasonal to centennial time scales. This introductory talk provides an overview of these goals, and outlines the occurrence and mechanisms of drought world-wide.

  2. Initial value predictability of intrinsic oceanic modes and implications for decadal prediction over North America

    Energy Technology Data Exchange (ETDEWEB)

    Branstator, Grant [National Center for Atmospheric Research, Boulder, CO (United States)

    2014-12-09

    The overall aim of our project was to quantify and characterize predictability of the climate as it pertains to decadal time scale predictions. By predictability we mean the degree to which a climate forecast can be distinguished from the climate that exists at initial forecast time, taking into consideration the growth of uncertainty that occurs as a result of the climate system being chaotic. In our project we were especially interested in predictability that arises from initializing forecasts from some specific state though we also contrast this predictability with predictability arising from forecasting the reaction of the system to external forcing – for example changes in greenhouse gas concentration. Also, we put special emphasis on the predictability of prominent intrinsic patterns of the system because they often dominate system behavior. Highlights from this work include: • Development of novel methods for estimating the predictability of climate forecast models. • Quantification of the initial value predictability limits of ocean heat content and the overturning circulation in the Atlantic as they are represented in various state of the art climate models. These limits varied substantially from model to model but on average were about a decade with North Atlantic heat content tending to be more predictable than North Pacific heat content. • Comparison of predictability resulting from knowledge of the current state of the climate system with predictability resulting from estimates of how the climate system will react to changes in greenhouse gas concentrations. It turned out that knowledge of the initial state produces a larger impact on forecasts for the first 5 to 10 years of projections. • Estimation of the predictability of dominant patterns of ocean variability including well-known patterns of variability in the North Pacific and North Atlantic. For the most part these patterns were predictable for 5 to 10 years. • Determination of

  3. Meta-analysis of clinical prediction models

    NARCIS (Netherlands)

    Debray, T.P.A.

    2013-01-01

    The past decades there has been a clear shift from implicit to explicit diagnosis and prognosis. This includes appreciation of clinical -diagnostic and prognostic- prediction models, which is likely to increase with the introduction of fully computerized patient records. Prediction models aim to pro

  4. Unreachable Setpoints in Model Predictive Control

    DEFF Research Database (Denmark)

    Rawlings, James B.; Bonné, Dennis; Jørgensen, John Bagterp;

    2008-01-01

    In this work, a new model predictive controller is developed that handles unreachable setpoints better than traditional model predictive control methods. The new controller induces an interesting fast/slow asymmetry in the tracking response of the system. Nominal asymptotic stability of the optimal...

  5. Efficient marker data utilization in genomic prediction

    DEFF Research Database (Denmark)

    Edriss, Vahid

    of editing marker data, methods to handle missing genotypes and prediction using haplotypes constructed with an advanced method. The results of this study show that the accuracy of genomc prediction increases by: optimal criteria for marker data editing parameters, proper handling of missing genotypes using...

  6. Predictability in models of the atmospheric circulation.

    NARCIS (Netherlands)

    Houtekamer, P.L.

    1992-01-01

    It will be clear from the above discussions that skill forecasts are still in their infancy. Operational skill predictions do not exist. One is still struggling to prove that skill predictions, at any range, have any quality at all. It is not clear what the statistics of the analysis error are. The

  7. An online railway traffic prediction model

    NARCIS (Netherlands)

    Kecman, P.; Goverde, R.M.P.

    2013-01-01

    Prediction of train positions in time and space is required for traffic control and passenger information. However, in practice only the last measured train delays are known and dispatchers must predict the arrival times of trains without adequate computer support. This paper presents a real-time to

  8. Space Weather Prediction and Exascale Computing

    OpenAIRE

    Lapenta, Giovanni; Markidis, Stefano; Poedts, Stefaan; Vucinic, Dean

    2013-01-01

    Space weather can have a great effect on Earth's climate. Predicting the impact of space environment disturbances on Earth presents a challenge to scientists. Here, the ExaScience Lab's efforts are presented, which use exascale computing and new visualization tools to predict the arrival and impact of space events on Earth.

  9. Tail Risk Premia and Return Predictability

    DEFF Research Database (Denmark)

    Bollerslev, Tim; Todorov, Viktor; Xu, Lai

    The variance risk premium, defined as the difference between actual and risk-neutralized expectations of the forward aggregate market variation, helps predict future market returns. Relying on new essentially model-free estimation procedure, we show that much of this predictability may......-varying economic uncertainty and changes in risk aversion, or market fears, respectively....

  10. Prediction of treatment response to adalimumab

    DEFF Research Database (Denmark)

    Krintel, Sophine B; Dehlendorff, C; Hetland, M L;

    2016-01-01

    At least 30% of patients with rheumatoid arthritis (RA) do not respond to biologic agents, which emphasizes the need of predictive biomarkers. We aimed to identify microRNAs (miRNAs) predictive of response to adalimumab in 180 treatment-naïve RA patients enrolled in the OPtimized treatment...

  11. Intelligent Predictive Control of Nonlienar Processes Using

    DEFF Research Database (Denmark)

    Nørgård, Peter Magnus; Sørensen, Paul Haase; Poulsen, Niels Kjølstad;

    1996-01-01

    This paper presents a novel approach to design of generalized predictive controllers (GPC) for nonlinear processes. A neural network is used for modelling the process and a gain-scheduling type of GPC is subsequently designed. The combination of neural network models and predictive control has fr...

  12. Predicting Information Flows in Network Traffic.

    Science.gov (United States)

    Hinich, Melvin J.; Molyneux, Robert E.

    2003-01-01

    Discusses information flow in networks and predicting network traffic and describes a study that uses time series analysis on a day's worth of Internet log data. Examines nonlinearity and traffic invariants, and suggests that prediction of network traffic may not be possible with current techniques. (Author/LRW)

  13. Asset Pricing Restrictions on Predictability : Frictions Matter

    NARCIS (Netherlands)

    F.A. de Roon (Frans); M. Szymanowska (Marta)

    2011-01-01

    textabstractU.S. stock portfolios sorted on size, momentum, transaction costs, M/B, I/A and ROA ratios, and industry classi…cation show considerable levels and variation of return predictability, inconsistent with asset pricing models. This means that a predictable risk premium is not equal to compe

  14. Staying Power of Churn Prediction Models

    NARCIS (Netherlands)

    Risselada, Hans; Verhoef, Peter C.; Bijmolt, Tammo H. A.

    2010-01-01

    In this paper, we study the staying power of various churn prediction models. Staying power is defined as the predictive performance of a model in a number of periods after the estimation period. We examine two methods, logit models and classification trees, both with and without applying a bagging

  15. LocTree3 prediction of localization

    DEFF Research Database (Denmark)

    Goldberg, T.; Hecht, M.; Hamp, T.;

    2014-01-01

    The prediction of protein sub-cellular localization is an important step toward elucidating protein function. For each query protein sequence, LocTree2 applies machine learning (profile kernel SVM) to predict the native sub-cellular localization in 18 classes for eukaryotes, in six for bacteria a...

  16. Differential Prediction Generalization in College Admissions Testing

    Science.gov (United States)

    Aguinis, Herman; Culpepper, Steven A.; Pierce, Charles A.

    2016-01-01

    We introduce the concept of "differential prediction generalization" in the context of college admissions testing. Specifically, we assess the extent to which predicted first-year college grade point average (GPA) based on high-school grade point average (HSGPA) and SAT scores depends on a student's ethnicity and gender and whether this…

  17. Prediction of Railway Passenger Traffic Volume

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    The current situation of the railway passenger traffic (RPT) andthe traffic marketing is analyzed. The grey model theory is adopted to establish a prediction model for the railway passenger traffic volume (RPTV). The RPTV from 2001 to 2005 is predicted with the proposed model, and a few suggestions are put forward.

  18. PREDICTING ADVERTISING EXPENDITURES USING INTENTION SURVEYS

    NARCIS (Netherlands)

    ALSEM, KJ; LEEFLANG, PSH

    1994-01-01

    In this article we study the use of intention surveys to predict the effects of a possible entrant. The case under investigation deals with the introduction of private broadcasting in the Netherlands. Several predictions of the advertising expenditures in various media are given which depend on a nu

  19. Prediction in ungauged estuaries: An integrated theory

    NARCIS (Netherlands)

    Savenije, H.H.G.

    2015-01-01

    Many estuaries in the world are ungauged. The International Association of Hydrological Sciences completed its science decade on Prediction in Ungauged Basins (PUB) in 2012 (Hrachowitz et al., 2013). Prediction on the basis of limited data is a challenge in hydrology, but not less so in estuaries, w

  20. Fuzzy Predictions for Strategic Decision Making

    DEFF Research Database (Denmark)

    Hallin, Carina Antonia; Andersen, Torben Juul; Tveterås, Sigbjørn

    This article theorizes a new way to predict firm performance based on aggregation of sensing among frontline employees about changes in operational capabilities to update strategic action plans. We frame the approach in the context of first- and second-generation prediction markets and outline its...

  1. Predicting facial characteristics from complex polygenic variations

    DEFF Research Database (Denmark)

    Fagertun, Jens; Wolffhechel, Karin Marie Brandt; Pers, Tune;

    2015-01-01

    traits in a linear regression. We show in this proof-of-concept study for facial trait prediction from genome-wide SNP data that some facial characteristics can be modeled by genetic information: facial width, eyebrow width, distance between eyes, and features involving mouth shape are predicted with...

  2. The Real World Significance of Performance Prediction

    Science.gov (United States)

    Pardos, Zachary A.; Wang, Qing Yang; Trivedi, Shubhendu

    2012-01-01

    In recent years, the educational data mining and user modeling communities have been aggressively introducing models for predicting student performance on external measures such as standardized tests as well as within-tutor performance. While these models have brought statistically reliable improvement to performance prediction, the real world…

  3. Beautiful mass predictions from scalar lattice QCD

    Energy Technology Data Exchange (ETDEWEB)

    Samuel, S.; Moriarty, K.J.M.

    1986-07-31

    Scalar lattice QCD methods are used to accurately predict the masses of hadrons with beauty, that is, states which contain a b quark. These states have not yet been seen in the laboratory. The accuracy of the predictions (approx.=25 MeV) make the calculation a good test of lattice methods as well as providing useful guidance for experimentalists.

  4. The mechanisms of prediction in language comprehension

    NARCIS (Netherlands)

    Szewczyk, J.M.

    2016-01-01

    Title: The mechanisms of prediction in language comprehension Author: Jakub Szewczyk Abstract: This thesis proefschrift focuses on two topics related to language perception: the role of animacy in language processing, and the mechanisms of language prediction. Animacy is one of the most basic dist

  5. Evolution of property predictability during conceptual design

    DEFF Research Database (Denmark)

    Salonen, Mikko; Hansen, Claus Thorp; Perttula, Matti

    2005-01-01

    refer to the designers’ confidence in predicting product properties based on the available information. In the case study, with use of the produced design models at four different stages of concept concretisation, the designers evaluated their confidence in predicting product properties related...

  6. Evolution of property predictability during conceptual design

    DEFF Research Database (Denmark)

    Salonen, Mikko; Hansen, Claus Thorp; Perttula, Matti

    2005-01-01

    on design work. By the term property predictability, we refer to the designers’ confidence in predicting product properties based on the available information. Since knowledge about the design problem and solution space grows as the design process progresses, our main hypothesis for the study...

  7. Model predictive control classical, robust and stochastic

    CERN Document Server

    Kouvaritakis, Basil

    2016-01-01

    For the first time, a textbook that brings together classical predictive control with treatment of up-to-date robust and stochastic techniques. Model Predictive Control describes the development of tractable algorithms for uncertain, stochastic, constrained systems. The starting point is classical predictive control and the appropriate formulation of performance objectives and constraints to provide guarantees of closed-loop stability and performance. Moving on to robust predictive control, the text explains how similar guarantees may be obtained for cases in which the model describing the system dynamics is subject to additive disturbances and parametric uncertainties. Open- and closed-loop optimization are considered and the state of the art in computationally tractable methods based on uncertainty tubes presented for systems with additive model uncertainty. Finally, the tube framework is also applied to model predictive control problems involving hard or probabilistic constraints for the cases of multiplic...

  8. Emotional intelligence predicts success in medical school.

    Science.gov (United States)

    Libbrecht, Nele; Lievens, Filip; Carette, Bernd; Côté, Stéphane

    2014-02-01

    Accumulating evidence suggests that effective communication and interpersonal sensitivity during interactions between doctors and patients impact therapeutic outcomes. There is an important need to identify predictors of these behaviors, because traditional tests used in medical admissions offer limited predictions of "bedside manners" in medical practice. This study examined whether emotional intelligence would predict the performance of 367 medical students in medical school courses on communication and interpersonal sensitivity. One of the dimensions of emotional intelligence, the ability to regulate emotions, predicted performance in courses on communication and interpersonal sensitivity over the next 3 years of medical school, over and above cognitive ability and conscientiousness. Emotional intelligence did not predict performance on courses on medical subject domains. The results suggest that medical schools may better predict who will communicate effectively and show interpersonal sensitivity if they include measures of emotional intelligence in their admission systems. PMID:24219393

  9. Predictability Horizon of Oceanic Rogue Waves

    CERN Document Server

    Alam, Reza

    2014-01-01

    Prediction is a central goal and a yet-unresolved challenge in the investigation of oceanic rogue waves. Here we define a horizon of predictability for oceanic rogue waves and derive, via extensive computational experiments, the first statistically-converged predictability time-scale for these structures. We show that this time-scale is a function of the sea state as well as the strength (i.e. overall height) of the expected rogue wave. The presented predictability time-scale establishes a quantitative metric on the combined temporal effect of the variety of mechanisms that together lead to the formation of a rogue wave, and is crucial for the assessment of validity of rogue waves predictions, as well as for the critical evaluation of results from the widely-used model equations. The methodology and presented results can have similar implications in other systems admitting rogue waves, e.g. nonlinear optics and plasma physics.

  10. Community Detection Based on Link Prediction Methods

    CERN Document Server

    Cheng, Hui-Min

    2016-01-01

    Community detection and link prediction are both of great significance in network analysis, which provide very valuable insights into topological structures of the network from diffrent perspectives. In this paper, we propose a novel community detection algorithm with inclusion of link prediction, motivated by the question whether link prediction can be devoted to improve the accuracy of community partition. For link prediction, we propose two novel indices to compute the similarity between each pair of nodes, one of which aims to add missing links, and the other tries to remove spurious edges. Extensive experiments are conducted on benchmark data sets, and the results of our proposed algorithm are compared with two classes of baselines. In conclusion, our proposed algorithm is competitive, revealing that link prediction does improve the precision of community detection.

  11. Hybrid Predictive Control for Dynamic Transport Problems

    CERN Document Server

    Núñez, Alfredo A; Cortés, Cristián E

    2013-01-01

    Hybrid Predictive Control for Dynamic Transport Problems develops methods for the design of predictive control strategies for nonlinear-dynamic hybrid discrete-/continuous-variable systems. The methodology is designed for real-time applications, particularly the study of dynamic transport systems. Operational and service policies are considered, as well as cost reduction. The control structure is based on a sound definition of the key variables and their evolution. A flexible objective function able to capture the predictive behaviour of the system variables is described. Coupled with efficient algorithms, mainly drawn from the area of computational intelligence, this is shown to optimize performance indices for real-time applications. The framework of the proposed predictive control methodology is generic and, being able to solve nonlinear mixed-integer optimization problems dynamically, is readily extendable to other industrial processes. The main topics of this book are: ●hybrid predictive control (HPC) ...

  12. Predicting the duration of the Syrian insurgency

    Directory of Open Access Journals (Sweden)

    Ulrich Pilster

    2014-08-01

    Full Text Available While there were several relatively short uprisings in Northern Africa and the Middle East during the Arab Spring, the dispute between the rebels and government forces in Syria has evolved into a full-scale civil war. We try to predict the length of the Syrian insurgency with a three-stage technique. Using out-of-sample techniques, we first assess the predictive capacity of 69 explanatory variables for insurgency duration. After determining the model with the highest predictive power, we categorize Syria according to the variables in this final model. Based on in-sample approaches, we then predict the duration of the Syrian uprising for three different scenarios. The most realistic point prediction is 5.12 years from the insurgency’s start, which suggests an end date between the end of 2016 and early 2017.

  13. Greatly improving consensus performance via predictive mechanism

    CERN Document Server

    Zhang, Hai-Tao; Chen, Michael ZhiQiang; Zhou, Tao

    2007-01-01

    An important natural phenomenon surfaces that ultrafast consensus can be achieved by introducing the predictive mechanism. By predicting the dynamics of the network several steps ahead and using this information in the design of the consensus protocol of each agent, it is shown that drastic improvement can be achieved in terms of the speed of convergence towards consensus without changing the topology of the network. Moreover, with the predictive mechanism, the range of sampling rates leading to consensus convergence is broadly expanded compared to the routine consensus protocol. In natural science, this study provides support for the idea that some predictive mechanisms exist in widely-spread biological swarms, flocks, and schools. From the industrial engineering point of view, inclusion of an efficient predictive mechanism allows for not only a significant increase in the speed of convergence toward consensus but also a reduction of the communication energy required to achieve a predefined consensus perform...

  14. Customer Churn Prediction for Broadband Internet Services

    Science.gov (United States)

    Huang, B. Q.; Kechadi, M.-T.; Buckley, B.

    Although churn prediction has been an area of research in the voice branch of telecommunications services, more focused studies on the huge growth area of Broadband Internet services are limited. Therefore, this paper presents a new set of features for broadband Internet customer churn prediction, based on Henley segments, the broadband usage, dial types, the spend of dial-up, line-information, bill and payment information, account information. Then the four prediction techniques (Logistic Regressions, Decision Trees, Multilayer Perceptron Neural Networks and Support Vector Machines) are applied in customer churn, based on the new features. Finally, the evaluation of new features and a comparative analysis of the predictors are made for broadband customer churn prediction. The experimental results show that the new features with these four modelling techniques are efficient for customer churn prediction in the broadband service field.

  15. Bounded link prediction for very large networks

    CERN Document Server

    Cui, Wei; Xu, Zhongqi

    2015-01-01

    Evaluation of link prediction methods is a hard task in very large complex networks because of the inhibitive computational cost. By setting a lower bound of the number of common neighbors (CN), we propose a new framework to efficiently and precisely evaluate the performances of CN-based similarity indices in link prediction for very large heterogeneous networks. Specifically, we propose a fast algorithm based on the parallel computing scheme to obtain all the node pairs with CN values larger than the lower bound. Furthermore, we propose a new measurement, called self-predictability, to quantify the performance of the CN-based similarity indices in link prediction, which on the other side can indicate the link predictability of a network.

  16. Decadal climate predictions using sequential learning algorithms

    CERN Document Server

    Strobach, Ehud

    2015-01-01

    Ensembles of climate models are commonly used to improve climate predictions and assess the uncertainties associated with them. Weighting the models according to their performances holds the promise of further improving their predictions. Here, we use an ensemble of decadal climate predictions to demonstrate the ability of sequential learning algorithms (SLAs) to reduce the forecast errors and reduce the uncertainties. Three different SLAs are considered, and their performances are compared with those of an equally weighted ensemble, a linear regression and the climatology. Predictions of four different variables--the surface temperature, the zonal and meridional wind, and pressure--are considered. The spatial distributions of the performances are presented, and the statistical significance of the improvements achieved by the SLAs is tested. Based on the performances of the SLAs, we propose one to be highly suitable for the improvement of decadal climate predictions.

  17. Bounded link prediction in very large networks

    Science.gov (United States)

    Cui, Wei; Pu, Cunlai; Xu, Zhongqi; Cai, Shimin; Yang, Jian; Michaelson, Andrew

    2016-09-01

    Evaluating link prediction methods is a hard task in very large complex networks due to the prohibitive computational cost. However, if we consider the lower bound of node pairs' similarity scores, this task can be greatly optimized. In this paper, we study CN index in the bounded link prediction framework, which is applicable to enormous heterogeneous networks. Specifically, we propose a fast algorithm based on the parallel computing scheme to obtain all node pairs with CN values larger than the lower bound. Furthermore, we propose a general measurement, called self-predictability, to quantify the performance of similarity indices in link prediction, which can also indicate the link predictability of networks with respect to given similarity indices.

  18. Emotional intelligence predicts success in medical school.

    Science.gov (United States)

    Libbrecht, Nele; Lievens, Filip; Carette, Bernd; Côté, Stéphane

    2014-02-01

    Accumulating evidence suggests that effective communication and interpersonal sensitivity during interactions between doctors and patients impact therapeutic outcomes. There is an important need to identify predictors of these behaviors, because traditional tests used in medical admissions offer limited predictions of "bedside manners" in medical practice. This study examined whether emotional intelligence would predict the performance of 367 medical students in medical school courses on communication and interpersonal sensitivity. One of the dimensions of emotional intelligence, the ability to regulate emotions, predicted performance in courses on communication and interpersonal sensitivity over the next 3 years of medical school, over and above cognitive ability and conscientiousness. Emotional intelligence did not predict performance on courses on medical subject domains. The results suggest that medical schools may better predict who will communicate effectively and show interpersonal sensitivity if they include measures of emotional intelligence in their admission systems.

  19. Wind Power Prediction Considering Nonlinear Atmospheric Disturbances

    Directory of Open Access Journals (Sweden)

    Yagang Zhang

    2015-01-01

    Full Text Available This paper considers the effect of nonlinear atmospheric disturbances on wind power prediction. A Lorenz system is introduced as an atmospheric disturbance model. Three new improved wind forecasting models combined with a Lorenz comprehensive disturbance are put forward in this study. Firstly, we define the form of the Lorenz disturbance variable and the wind speed perturbation formula. Then, different artificial neural network models are used to verify the new idea and obtain better wind speed predictions. Finally we separately use the original and improved wind speed series to predict the related wind power. This proves that the corrected wind speed provides higher precision wind power predictions. This research presents a totally new direction in the wind prediction field and has profound theoretical research value and practical guiding significance.

  20. Massive Predictive Modeling using Oracle R Enterprise

    CERN Document Server

    CERN. Geneva

    2014-01-01

    R is fast becoming the lingua franca for analyzing data via statistics, visualization, and predictive analytics. For enterprise-scale data, R users have three main concerns: scalability, performance, and production deployment. Oracle's R-based technologies - Oracle R Distribution, Oracle R Enterprise, Oracle R Connector for Hadoop, and the R package ROracle - address these concerns. In this talk, we introduce Oracle's R technologies, highlighting how each enables R users to achieve scalability and performance while making production deployment of R results a natural outcome of the data analyst/scientist efforts. The focus then turns to Oracle R Enterprise with code examples using the transparency layer and embedded R execution, targeting massive predictive modeling. One goal behind massive predictive modeling is to build models per entity, such as customers, zip codes, simulations, in an effort to understand behavior and tailor predictions at the entity level. Predictions...

  1. Machine learning methods for metabolic pathway prediction

    Directory of Open Access Journals (Sweden)

    Karp Peter D

    2010-01-01

    Full Text Available Abstract Background A key challenge in systems biology is the reconstruction of an organism's metabolic network from its genome sequence. One strategy for addressing this problem is to predict which metabolic pathways, from a reference database of known pathways, are present in the organism, based on the annotated genome of the organism. Results To quantitatively validate methods for pathway prediction, we developed a large "gold standard" dataset of 5,610 pathway instances known to be present or absent in curated metabolic pathway databases for six organisms. We defined a collection of 123 pathway features, whose information content we evaluated with respect to the gold standard. Feature data were used as input to an extensive collection of machine learning (ML methods, including naïve Bayes, decision trees, and logistic regression, together with feature selection and ensemble methods. We compared the ML methods to the previous PathoLogic algorithm for pathway prediction using the gold standard dataset. We found that ML-based prediction methods can match the performance of the PathoLogic algorithm. PathoLogic achieved an accuracy of 91% and an F-measure of 0.786. The ML-based prediction methods achieved accuracy as high as 91.2% and F-measure as high as 0.787. The ML-based methods output a probability for each predicted pathway, whereas PathoLogic does not, which provides more information to the user and facilitates filtering of predicted pathways. Conclusions ML methods for pathway prediction perform as well as existing methods, and have qualitative advantages in terms of extensibility, tunability, and explainability. More advanced prediction methods and/or more sophisticated input features may improve the performance of ML methods. However, pathway prediction performance appears to be limited largely by the ability to correctly match enzymes to the reactions they catalyze based on genome annotations.

  2. Predictive Modelling and Time: An Experiment in Temporal Archaeological Predictive Models

    Directory of Open Access Journals (Sweden)

    David Ebert

    2006-08-01

    Full Text Available One of the most common criticisms of archaeological predictive modelling is that it fails to account for temporal or functional differences in sites. However, a practical solution to temporal or functional predictive modelling has proven to be elusive. This article discusses temporal predictive modelling, focusing on the difficulties of employing temporal variables, then introduces and tests a simple methodology for the implementation of temporal modelling. The temporal models thus created are then compared to a traditional predictive model.

  3. Dynamical functional prediction and classification, with application to traffic flow prediction

    OpenAIRE

    Chiou, Jeng-Min

    2013-01-01

    Motivated by the need for accurate traffic flow prediction in transportation management, we propose a functional data method to analyze traffic flow patterns and predict future traffic flow. In this study we approach the problem by sampling traffic flow trajectories from a mixture of stochastic processes. The proposed functional mixture prediction approach combines functional prediction with probabilistic functional classification to take distinct traffic flow patterns into account. The proba...

  4. The Residual-based Predictiveness Curve - A Visual Tool to Assess the Performance of Prediction Models

    OpenAIRE

    Casalicchio, Giuseppe; Bischl, Bernd; Boulesteix, Anne-Laure; Schmid, Matthias

    2015-01-01

    It is agreed among biostatisticians that prediction models for binary outcomes should satisfy two essential criteria: First, a prediction model should have a high discriminatory power, implying that it is able to clearly separate cases from controls. Second, the model should be well calibrated, meaning that the predicted risks should closely agree with the relative frequencies observed in the data. The focus of this work is on the predictiveness curve, which has been proposed by Huang et ...

  5. DPRESS: Localizing estimates of predictive uncertainty

    Directory of Open Access Journals (Sweden)

    Clark Robert D

    2009-07-01

    Full Text Available Abstract Background The need to have a quantitative estimate of the uncertainty of prediction for QSAR models is steadily increasing, in part because such predictions are being widely distributed as tabulated values disconnected from the models used to generate them. Classical statistical theory assumes that the error in the population being modeled is independent and identically distributed (IID, but this is often not actually the case. Such inhomogeneous error (heteroskedasticity can be addressed by providing an individualized estimate of predictive uncertainty for each particular new object u: the standard error of prediction su can be estimated as the non-cross-validated error st* for the closest object t* in the training set adjusted for its separation d from u in the descriptor space relative to the size of the training set. The predictive uncertainty factor γt* is obtained by distributing the internal predictive error sum of squares across objects in the training set based on the distances between them, hence the acronym: Distributed PRedictive Error Sum of Squares (DPRESS. Note that st* and γt*are characteristic of each training set compound contributing to the model of interest. Results The method was applied to partial least-squares models built using 2D (molecular hologram or 3D (molecular field descriptors applied to mid-sized training sets (N = 75 drawn from a large (N = 304, well-characterized pool of cyclooxygenase inhibitors. The observed variation in predictive error for the external 229 compound test sets was compared with the uncertainty estimates from DPRESS. Good qualitative and quantitative agreement was seen between the distributions of predictive error observed and those predicted using DPRESS. Inclusion of the distance-dependent term was essential to getting good agreement between the estimated uncertainties and the observed distributions of predictive error. The uncertainty estimates derived by DPRESS were

  6. Neural Fuzzy Inference System-Based Weather Prediction Model and Its Precipitation Predicting Experiment

    Directory of Open Access Journals (Sweden)

    Jing Lu

    2014-11-01

    Full Text Available We propose a weather prediction model in this article based on neural network and fuzzy inference system (NFIS-WPM, and then apply it to predict daily fuzzy precipitation given meteorological premises for testing. The model consists of two parts: the first part is the “fuzzy rule-based neural network”, which simulates sequential relations among fuzzy sets using artificial neural network; and the second part is the “neural fuzzy inference system”, which is based on the first part, but could learn new fuzzy rules from the previous ones according to the algorithm we proposed. NFIS-WPM (High Pro and NFIS-WPM (Ave are improved versions of this model. It is well known that the need for accurate weather prediction is apparent when considering the benefits. However, the excessive pursuit of accuracy in weather prediction makes some of the “accurate” prediction results meaningless and the numerical prediction model is often complex and time-consuming. By adapting this novel model to a precipitation prediction problem, we make the predicted outcomes of precipitation more accurate and the prediction methods simpler than by using the complex numerical forecasting model that would occupy large computation resources, be time-consuming and which has a low predictive accuracy rate. Accordingly, we achieve more accurate predictive precipitation results than by using traditional artificial neural networks that have low predictive accuracy.

  7. Childhood asthma prediction models: a systematic review.

    Science.gov (United States)

    Smit, Henriette A; Pinart, Mariona; Antó, Josep M; Keil, Thomas; Bousquet, Jean; Carlsen, Kai H; Moons, Karel G M; Hooft, Lotty; Carlsen, Karin C Lødrup

    2015-12-01

    Early identification of children at risk of developing asthma at school age is crucial, but the usefulness of childhood asthma prediction models in clinical practice is still unclear. We systematically reviewed all existing prediction models to identify preschool children with asthma-like symptoms at risk of developing asthma at school age. Studies were included if they developed a new prediction model or updated an existing model in children aged 4 years or younger with asthma-like symptoms, with assessment of asthma done between 6 and 12 years of age. 12 prediction models were identified in four types of cohorts of preschool children: those with health-care visits, those with parent-reported symptoms, those at high risk of asthma, or children in the general population. Four basic models included non-invasive, easy-to-obtain predictors only, notably family history, allergic disease comorbidities or precursors of asthma, and severity of early symptoms. Eight extended models included additional clinical tests, mostly specific IgE determination. Some models could better predict asthma development and other models could better rule out asthma development, but the predictive performance of no single model stood out in both aspects simultaneously. This finding suggests that there is a large proportion of preschool children with wheeze for which prediction of asthma development is difficult.

  8. Predicting community composition from pairwise interactions

    Science.gov (United States)

    Friedman, Jonathan; Higgins, Logan; Gore, Jeff

    The ability to predict the structure of complex, multispecies communities is crucial for understanding the impact of species extinction and invasion on natural communities, as well as for engineering novel, synthetic communities. Communities are often modeled using phenomenological models, such as the classical generalized Lotka-Volterra (gLV) model. While a lot of our intuition comes from such models, their predictive power has rarely been tested experimentally. To directly assess the predictive power of this approach, we constructed synthetic communities comprised of up to 8 soil bacteria. We measured the outcome of competition between all species pairs, and used these measurements to predict the composition of communities composed of more than 2 species. The pairwise competitions resulted in a diverse set of outcomes, including coexistence, exclusion, and bistability, and displayed evidence for both interference and facilitation. Most pair outcomes could be captured by the gLV framework, and the composition of multispecies communities could be predicted for communities composed solely of such pairs. Our results demonstrate the predictive ability and utility of simple phenomenology, which enables accurate predictions in the absence of mechanistic details.

  9. COMBINING CLASSIFIERS FOR CREDIT RISK PREDICTION

    Institute of Scientific and Technical Information of China (English)

    Bhekisipho TWALA

    2009-01-01

    Credit risk prediction models seek to predict quality factors such as whether an individual will default (bad applicant) on a loan or not (good applicant). This can be treated as a kind of machine learning (ML) problem. Recently, the use of ML algorithms has proven to be of great practical value in solving a variety of risk problems including credit risk prediction. One of the most active areas of recent research in ML has been the use of ensemble (combining) classifiers. Research indicates that ensemble individual classifiers lead to a significant improvement in classification performance by having them vote for the most popular class. This paper explores the predicted behaviour of five classifiers for different types of noise in terms of credit risk prediction accuracy, and how could such accuracy be improved by using pairs of classifier ensembles. Benchmarking results on five credit datasets and comparison with the performance of each individual classifier on predictive accuracy at various attribute noise levels are presented. The experimental evaluation shows that the ensemble of classifiers technique has the potential to improve prediction accuracy.

  10. Body size prediction from juvenile skeletal remains.

    Science.gov (United States)

    Ruff, Christopher

    2007-05-01

    There are currently no methods for predicting body mass from juvenile skeletal remains and only a very limited number for predicting stature. In this study, stature and body mass prediction equations are generated for each year from 1 to 17 years of age using a subset of the Denver Growth Study sample, followed longitudinally (n = 20 individuals, 340 observations). Radiographic measurements of femoral distal metaphyseal and head breadth are used to predict body mass and long bone lengths are used to predict stature. In addition, pelvic bi-iliac breadth and long bone lengths are used to predict body mass in older adolescents. Relative prediction errors are equal to or smaller than those associated with similar adult estimation formulae. Body proportions change continuously throughout growth, necessitating age-specific formulae. Adult formulae overestimate stature and body mass in younger juveniles, but work well in 17-year-olds from the sample, indicating that in terms of body proportions they are representative of the general population. To illustrate use of the techniques, they are applied to the juvenile Homo erectus (ergaster) KNM-WT 15000 skeleton. New body mass and stature estimates for this specimen are similar to previous estimates derived using other methods. Body mass estimates range from 50 to 53 kg, and stature was probably slightly under 157 cm, although a precise stature estimate is difficult to determine due to differences in linear body proportions between KNM-WT 15000 and the Denver reference sample. PMID:17295297

  11. Predicting intrinsic disorder in proteins: an overview

    Institute of Scientific and Technical Information of China (English)

    Bo He; Kejun Wang; Yunlong Liu; Bin Xue; Vladimir N Uversky; A Keith Dunker

    2009-01-01

    The discovery of intrinsically disordered proteins IDP I.e., biologically active proteins that do not possess stable secondary and/or tertiary structures came as an unexpected surprise, as the existence of such proteins is in contradiction to the traditional "sequence---,structure--,function" paradigm. Accurate prediction of a protein's predisposition to be intrinsically disordered is a necessary prerequisite for the further understanding of principles and mechanisms of protein folding and function, and is a key for the elaboration of a new structural and functional hierarchy of proteins. Therefore, prediction of IDPs has attracted the attention of many researchers, and a number of prediction tools have been developed. Predictions of disorder, in turn, are playing major roles in directing labora-tory experiments that are leading to the discovery of ever more disordered proteins, and thereby leading to a positive feedback loop in the investigation of these proteins, in this review of algorithms for intrinsic disorder prediction, the basic concepts of various prediction methods for IDPs are summarized, the strengths and shortcomings of many of the methods are analyzed, and the difficulties and directions of future development of IDP prediction techniques are discussed.

  12. Correction of deposition predictions with data assimilation

    International Nuclear Information System (INIS)

    Model predictions for rapid assessment and prognosis of possible radiological consequences after an accidental release of radionuclides play an important role in nuclear emergency management. Radiological measurements (e. g., dose rate measurements) can be used to improve such model predictions. This paper describes a method for combining model predictions and measurements (data assimilation) in the deposition model of the European radiological decision support system RODOS. The data assimilation approach is based on the Ensemble Kalman Filter, a Monte Carlo variant of the Kalman filter. (orig.)

  13. Generalised empirical method for predicting surface subsidence

    International Nuclear Information System (INIS)

    Based on a simplified strata parameter, i.e. the ratio of total thickness of the strong rock beds in an overburden to the overall thickness of the overburden, a Generalised Empirical Method (GEM) is described for predicting the maximum subsidence and the shape of a complete transverse subsidence profile due to a single completely extracted longwall panel. In the method, a nomogram for predicting the maximum surface subsidence is first developed from the data collected from subsidence measurements worldwide. Then, a method is developed for predicting the shapes of complete transfer subsidence profiles for a horizontal seam and ground surface and is verified by case studies. 13 refs., 9 figs., 2 tabs

  14. Predicting Dyspnea Inducers by Molecular Topology

    Directory of Open Access Journals (Sweden)

    María Gálvez-Llompart

    2013-01-01

    Full Text Available QSAR based on molecular topology (MT is an excellent methodology used in predicting physicochemical and biological properties of compounds. This approach is applied here for the development of a mathematical model capable to recognize drugs showing dyspnea as a side effect. Using linear discriminant analysis, it was found a four-variable regression equations enabling a predictive rate of about 81% and 73% in the training and test sets of compounds, respectively. These results demonstrate that QSAR-MT is an efficient tool to predict the appearance of dyspnea associated with drug consumption.

  15. Link prediction in complex networks: A survey

    Science.gov (United States)

    Lü, Linyuan; Zhou, Tao

    2011-03-01

    Link prediction in complex networks has attracted increasing attention from both physical and computer science communities. The algorithms can be used to extract missing information, identify spurious interactions, evaluate network evolving mechanisms, and so on. This article summaries recent progress about link prediction algorithms, emphasizing on the contributions from physical perspectives and approaches, such as the random-walk-based methods and the maximum likelihood methods. We also introduce three typical applications: reconstruction of networks, evaluation of network evolving mechanism and classification of partially labeled networks. Finally, we introduce some applications and outline future challenges of link prediction algorithms.

  16. Predictive Navigation by Understanding Human Motion Patterns

    Directory of Open Access Journals (Sweden)

    Shu-Yun Chung

    2011-03-01

    Full Text Available To make robots coexist and share the environments with humans, robots should understand the behaviors or the intentions of humans and further predict their motions. In this paper, an A*-based predictive motion planner is represented for navigation tasks. A generalized pedestrian motion model is proposed and trained by the statistical learning method. To deal with the uncertainty, a localization, tracking and prediction framework is also introduced. The corresponding recursive Bayesian formula represented as DBNs (Dynamic Bayesian Networks is derived for real time operation. Finally, the simulations and experiments are shown to validate the idea of this paper.

  17. ACHIEVING BETTER UNDERSTANDING BY LISTENING WITH PREDICTION

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    The skill of Listening with comprehension is anessential part of communication and basic to ESL/EFL learning.Prediction is also a key process in un-derstanding spoken language.This article intends tooffer a definition for prediction in ESL/EFL listening,examines its foundations,draws some insights into itsnature,and illustrates how to develop and employprediction in pre-listening and while-listening stages,also how to‘repair’prediction in the post-listeningstage,in an attempt to help listeners achieve the goalof better understanding.

  18. U.S.-Japan Quake Prediction Research

    OpenAIRE

    Kisslinger, Carl; Mikumo, Takeshi; Kanamori, Hiroo

    1988-01-01

    For the seventh time since 1964, a seminar on earthquake prediction has been convened under the U.S.-Japan Cooperation in Science Program. The purpose of the seminar was to provide an opportunity for researchers from the two countries to share recent progress and future plans in the continuing effort to develop the scientific basis for predicting earthquakes and practical means for implementing prediction technology as it emerges. Thirty-six contributors, 15 from Japan and 21 from the U.S., m...

  19. Unbalanced Regressions and the Predictive Equation

    DEFF Research Database (Denmark)

    Osterrieder, Daniela; Ventosa-Santaulària, Daniel; Vera-Valdés, J. Eduardo

    in the theoretical predictive equation by suggesting a data generating process, where returns are generated as linear functions of a lagged latent I(0) risk process. The observed predictor is a function of this latent I(0) process, but it is corrupted by a fractionally integrated noise. Such a process may arise due...... an instrumental variable approach and discuss issues of validity and relevance. Applying the procedure to the prediction of daily returns on the S&P 500, our empirical analysis confirms return predictability and a positive risk-return trade-off....

  20. Calorimeter prediction based on multiple exponentials

    Energy Technology Data Exchange (ETDEWEB)

    Smith, M.K. E-mail: mks@lanl.gov; Bracken, D.S

    2002-05-21

    Calorimetry allows very precise measurements of nuclear material to be carried out, but it also requires relatively long measurement times to do so. The ability to accurately predict the equilibrium response of a calorimeter would significantly reduce the amount of time required for calorimetric assays. An algorithm has been developed that is effective at predicting the equilibrium response. This multi-exponential prediction algorithm is based on an iterative technique using commercial fitting routines that fit a constant plus a variable number of exponential terms to calorimeter data. Details of the implementation and the results of trials on a large number of calorimeter data sets will be presented.

  1. Calorimeter prediction based on multiple exponentials

    International Nuclear Information System (INIS)

    Calorimetry allows very precise measurements of nuclear material to be carried out, but it also requires relatively long measurement times to do so. The ability to accurately predict the equilibrium response of a calorimeter would significantly reduce the amount of time required for calorimetric assays. An algorithm has been developed that is effective at predicting the equilibrium response. This multi-exponential prediction algorithm is based on an iterative technique using commercial fitting routines that fit a constant plus a variable number of exponential terms to calorimeter data. Details of the implementation and the results of trials on a large number of calorimeter data sets will be presented

  2. Calorimeter prediction based on multiple exponentials

    CERN Document Server

    Smith, M K

    2002-01-01

    Calorimetry allows very precise measurements of nuclear material to be carried out, but it also requires relatively long measurement times to do so. The ability to accurately predict the equilibrium response of a calorimeter would significantly reduce the amount of time required for calorimetric assays. An algorithm has been developed that is effective at predicting the equilibrium response. This multi-exponential prediction algorithm is based on an iterative technique using commercial fitting routines that fit a constant plus a variable number of exponential terms to calorimeter data. Details of the implementation and the results of trials on a large number of calorimeter data sets will be presented.

  3. Trust-based collective view prediction

    CERN Document Server

    Luo, Tiejian; Xu, Guandong; Zhou, Jia

    2013-01-01

    Collective view prediction is to judge the opinions of an active web user based on unknown elements by referring to the collective mind of the whole community. Content-based recommendation and collaborative filtering are two mainstream collective view prediction techniques. They generate predictions by analyzing the text features of the target object or the similarity of users' past behaviors. Still, these techniques are vulnerable to the artificially-injected noise data, because they are not able to judge the reliability and credibility of the information sources. Trust-based Collective View

  4. The devil is in the specificity: the negative effect of prediction specificity on prediction accuracy.

    Science.gov (United States)

    Yoon, Song-Oh; Suk, Kwanho; Goo, Jin Kyung; Lee, Jiheon; Lee, Seon Min

    2013-07-01

    In the research reported here, we proposed and demonstrated the prediction-specificity effect, which states that people's prediction of the general outcome of an event (e.g., the winner of a soccer match) is less accurate when the prediction question is framed in a more specific manner (e.g., guessing the score) rather than in a less specific manner (e.g., guessing the winner). We demonstrated this effect by examining people's predictions on actual sports games both in field and laboratory studies. In Study 1, the analysis of 19 billion bets from a commercial sports-betting business provided evidence for the effect of prediction specificity. This effect was replicated in three controlled laboratory studies, in which participants predicted the outcomes of a series of soccer matches. Furthermore, the negative effect of prediction specificity was mediated by participants' underweighting of important holistic information during decision making. PMID:23660410

  5. Echo state network prediction method and its application in flue gas turbine condition prediction

    Science.gov (United States)

    Wang, Shaohong; Chen, Tao; Xu, Xiaoli

    2010-12-01

    On the background of the complex production process of fluid catalytic cracking energy recovery system in large-scale petrochemical refineries, this paper introduced an improved echo state network (ESN) model prediction method which is used to address the condition trend prediction problem of the key power equipment--flue gas turbine. Singular value decomposition method was used to obtain the ESN output weight. Through selecting the appropriate parameters and discarding small singular value, this method overcame the defective solution problem in the prediction by using the linear regression algorithm, improved the prediction performance of echo state network, and gave the network prediction process. In order to solve the problem of noise contained in production data, the translation-invariant wavelet transform analysis method is combined to denoise the noisy time series before prediction. Condition trend prediction results show the effectiveness of the proposed method.

  6. The devil is in the specificity: the negative effect of prediction specificity on prediction accuracy.

    Science.gov (United States)

    Yoon, Song-Oh; Suk, Kwanho; Goo, Jin Kyung; Lee, Jiheon; Lee, Seon Min

    2013-07-01

    In the research reported here, we proposed and demonstrated the prediction-specificity effect, which states that people's prediction of the general outcome of an event (e.g., the winner of a soccer match) is less accurate when the prediction question is framed in a more specific manner (e.g., guessing the score) rather than in a less specific manner (e.g., guessing the winner). We demonstrated this effect by examining people's predictions on actual sports games both in field and laboratory studies. In Study 1, the analysis of 19 billion bets from a commercial sports-betting business provided evidence for the effect of prediction specificity. This effect was replicated in three controlled laboratory studies, in which participants predicted the outcomes of a series of soccer matches. Furthermore, the negative effect of prediction specificity was mediated by participants' underweighting of important holistic information during decision making.

  7. The Yin and the Yang of Prediction: An fMRI Study of Semantic Predictive Processing.

    Directory of Open Access Journals (Sweden)

    Kirsten Weber

    Full Text Available Probabilistic prediction plays a crucial role in language comprehension. When predictions are fulfilled, the resulting facilitation allows for fast, efficient processing of ambiguous, rapidly-unfolding input; when predictions are not fulfilled, the resulting error signal allows us to adapt to broader statistical changes in this input. We used functional Magnetic Resonance Imaging to examine the neuroanatomical networks engaged in semantic predictive processing and adaptation. We used a relatedness proportion semantic priming paradigm, in which we manipulated the probability of predictions while holding local semantic context constant. Under conditions of higher (versus lower predictive validity, we replicate previous observations of reduced activity to semantically predictable words in the left anterior superior/middle temporal cortex, reflecting facilitated processing of targets that are consistent with prior semantic predictions. In addition, under conditions of higher (versus lower predictive validity we observed significant differences in the effects of semantic relatedness within the left inferior frontal gyrus and the posterior portion of the left superior/middle temporal gyrus. We suggest that together these two regions mediated the suppression of unfulfilled semantic predictions and lexico-semantic processing of unrelated targets that were inconsistent with these predictions. Moreover, under conditions of higher (versus lower predictive validity, a functional connectivity analysis showed that the left inferior frontal and left posterior superior/middle temporal gyrus were more tightly interconnected with one another, as well as with the left anterior cingulate cortex. The left anterior cingulate cortex was, in turn, more tightly connected to superior lateral frontal cortices and subcortical regions-a network that mediates rapid learning and adaptation and that may have played a role in switching to a more predictive mode of processing in

  8. The Yin and the Yang of Prediction: An fMRI Study of Semantic Predictive Processing.

    Science.gov (United States)

    Weber, Kirsten; Lau, Ellen F; Stillerman, Benjamin; Kuperberg, Gina R

    2016-01-01

    Probabilistic prediction plays a crucial role in language comprehension. When predictions are fulfilled, the resulting facilitation allows for fast, efficient processing of ambiguous, rapidly-unfolding input; when predictions are not fulfilled, the resulting error signal allows us to adapt to broader statistical changes in this input. We used functional Magnetic Resonance Imaging to examine the neuroanatomical networks engaged in semantic predictive processing and adaptation. We used a relatedness proportion semantic priming paradigm, in which we manipulated the probability of predictions while holding local semantic context constant. Under conditions of higher (versus lower) predictive validity, we replicate previous observations of reduced activity to semantically predictable words in the left anterior superior/middle temporal cortex, reflecting facilitated processing of targets that are consistent with prior semantic predictions. In addition, under conditions of higher (versus lower) predictive validity we observed significant differences in the effects of semantic relatedness within the left inferior frontal gyrus and the posterior portion of the left superior/middle temporal gyrus. We suggest that together these two regions mediated the suppression of unfulfilled semantic predictions and lexico-semantic processing of unrelated targets that were inconsistent with these predictions. Moreover, under conditions of higher (versus lower) predictive validity, a functional connectivity analysis showed that the left inferior frontal and left posterior superior/middle temporal gyrus were more tightly interconnected with one another, as well as with the left anterior cingulate cortex. The left anterior cingulate cortex was, in turn, more tightly connected to superior lateral frontal cortices and subcortical regions-a network that mediates rapid learning and adaptation and that may have played a role in switching to a more predictive mode of processing in response to the

  9. Predicting missing links via correlation between nodes

    CERN Document Server

    Liao, Hao; Zhang, Yi-Cheng

    2014-01-01

    As a fundamental problem in many different fields, link prediction aims to estimate the likelihood of an existing link between two nodes based on the observed information. Since this problem is related to many applications ranging from uncovering missing data to predicting the evolution of networks, link prediction has been intensively investigated recently and many methods have been proposed so far. The essential challenge of link prediction is to estimate the similarity between nodes. Most of the existing methods are based on the common neighbor index and its variants. In this paper, we propose to calculate the similarity between nodes by the correlation coefficient. This method is found to be very effective when applied to calculate similarity based on high order paths. We finally fuse the correlation-based method with the resource allocation method, and find that the combined method can substantially outperform the existing methods, especially in sparse networks.

  10. Empirical Prediction of Aircraft Landing Gear Noise

    Science.gov (United States)

    Golub, Robert A. (Technical Monitor); Guo, Yue-Ping

    2005-01-01

    This report documents a semi-empirical/semi-analytical method for landing gear noise prediction. The method is based on scaling laws of the theory of aerodynamic noise generation and correlation of these scaling laws with current available test data. The former gives the method a sound theoretical foundation and the latter quantitatively determines the relations between the parameters of the landing gear assembly and the far field noise, enabling practical predictions of aircraft landing gear noise, both for parametric trends and for absolute noise levels. The prediction model is validated by wind tunnel test data for an isolated Boeing 737 landing gear and by flight data for the Boeing 777 airplane. In both cases, the predictions agree well with data, both in parametric trends and in absolute noise levels.

  11. Predicting growth fluctuation in network economy

    CERN Document Server

    Maeno, Yoshiharu

    2011-01-01

    This study presents a method to predict the growth fluctuation of firms interdependent in a network economy. The risk of downward growth fluctuation of firms is calculated from the statistics on Japanese industry.

  12. Speech Intelligibility Prediction Based on Mutual Information

    DEFF Research Database (Denmark)

    Jensen, Jesper; Taal, Cees H.

    2014-01-01

    This paper deals with the problem of predicting the average intelligibility of noisy and potentially processed speech signals, as observed by a group of normal hearing listeners. We propose a model which performs this prediction based on the hypothesis that intelligibility is monotonically related...... to the mutual information between critical-band amplitude envelopes of the clean signal and the corresponding noisy/processed signal. The resulting intelligibility predictor turns out to be a simple function of the mean-square error (mse) that arises when estimating a clean critical-band amplitude using...... a minimum mean-square error (mmse) estimator based on the noisy/processed amplitude. The proposed model predicts that speech intelligibility cannot be improved by any processing of noisy critical-band amplitudes. Furthermore, the proposed intelligibility predictor performs well ( ρ > 0.95) in predicting...

  13. Trend prediction of chaotic time series

    Institute of Scientific and Technical Information of China (English)

    Li Aiguo; Zhao Cai; Li Zhanhuai

    2007-01-01

    To predict the trend of chaotic time series in time series analysis and time series data mining fields, a novel predicting algorithm of chaotic time series trend is presented, and an on-line segmenting algorithm is proposed to convert a time series into a binary string according to ascending or descending trend of each subsequence. The on-line segmenting algorithm is independent of the prior knowledge about time series. The naive Bayesian algorithm is then employed to predict the trend of chaotic time series according to the binary string. The experimental results of three chaotic time series demonstrate that the proposed method predicts the ascending or descending trend of chaotic time series with few error.

  14. LIFE PREDICTION APPROACH FOR RANDOM MULTIAXIAL FATIGUE

    Institute of Scientific and Technical Information of China (English)

    Wang Lei; Wang Dejun

    2005-01-01

    According to the concept of critical plane, a life prediction approach for random multiaxial fatigue is presented. First, the critical plane under the multiaxial random loading is determined based on the concept of the weight-averaged maximum shear strain direction. Then the shear and normal strain histories on the determined critical plane are calculated and taken as the subject of multiaxial load simplifying and multiaxial cycle counting. Furthermore, a multiaxial fatigue life prediction model including the parameters resulted from multiaxial cycle counting is presented and applied to calculating the fatigue damage generated from each cycle. Finally, the cumulative damage is added up using Miner's linear rule, and the fatigue prediction life is given. The experiments under multiaxial loading blocks are used for the verification of the proposed method. The prediction has a good correction with the experimental results.

  15. Asthma Medication Ratio Predicts Emergency Depart...

    Data.gov (United States)

    U.S. Department of Health & Human Services — According to findings reported in Asthma Medication Ratio Predicts Emergency Department Visits and Hospitalizations in Children with Asthma, published in Volume 3,...

  16. Predictive Analytics with Big Social Data

    DEFF Research Database (Denmark)

    Buus Lassen, Niels; Madsen, René; Vatrapu, Ravi

    Recent research in the field of computational social science have shown how data resulting from the widespread adoption and use of social media channels such as twitter can be used to predict outcomes such as movie revenues, election winners, localized moods, and epidemic outbreaks. Underlying......, we demonstrate how social media data from twitter and facebook can be used to predict the quarterly sales of iPhones and revenues of H&M respectively. Based on a conceptual model of social data consisting of social graph (actors, actions, activities, and artefacts) and social text (topics, keywords...... into a prediction of the global revenue of the fast fashion company, H&M. We discuss the findings and conclude with implications for predictive analytics with big social data....

  17. Computational nanotoxicology: Predicting toxicity of nanoparticles

    Science.gov (United States)

    Burello, Enrico; Worth, Andrew

    2011-03-01

    A statistical model based on a quantitative structure-activity relationship accurately predicts the cytotoxicity of various metal oxide nanoparticles, thus offering a way to rapidly screen nanomaterials and prioritize testing.

  18. Common cause failure prediction using data mapping

    Energy Technology Data Exchange (ETDEWEB)

    Kvam, Paul H.; Miller, J. Glenn

    2002-06-01

    To estimate power plant reliability, a probabilistic safety assessment might combine failure data from various sites. Because dependent failures are a critical concern in the nuclear industry, combining failure data from component groups of different sizes is a challenging problem. One procedure, called data mapping, translates failure data across component group sizes. This includes common cause failures, which are simultaneous failure events of two or more components in a group. In this paper, we present a framework for predicting future plant reliability using mapped common cause failure data. The prediction technique is motivated by discrete failure data from emergency diesel generators at US plants. The underlying failure distributions are based on homogeneous Poisson processes. Both Bayesian and frequentist prediction methods are presented, and if non-informative prior distributions are applied, the upper prediction bounds for the generators are the same.

  19. Vitamin D Levels Predict Multiple Sclerosis Progression

    Science.gov (United States)

    ... Research Matters NIH Research Matters February 3, 2014 Vitamin D Levels Predict Multiple Sclerosis Progression Among people ... sclerosis (MS), those with higher blood levels of vitamin D had better outcomes during 5 years of ...

  20. Prediction methods and databases within chemoinformatics

    DEFF Research Database (Denmark)

    Jónsdóttir, Svava Osk; Jørgensen, Flemming Steen; Brunak, Søren

    2005-01-01

    about drugs and drug candidates, and of databases with relevant properties. Access to experimental data and numerical methods for selecting and utilizing these data is crucial for developing accurate predictive in silico models. Many interesting predictive methods for classifying the suitability......MOTIVATION: To gather information about available databases and chemoinformatics methods for prediction of properties relevant to the drug discovery and optimization process. RESULTS: We present an overview of the most important databases with 2-dimensional and 3-dimensional structural information...... of chemical compounds as potential drugs, as well as for predicting their physico-chemical and ADMET properties have been proposed in recent years. These methods are discussed, and some possible future directions in this rapidly developing field are described....

  1. Improving personalized link prediction by hybrid diffusion

    CERN Document Server

    Liu, Jin-Hu; Zhou, Tao

    2016-01-01

    Inspired by traditional link prediction and to solve the problem of recommending friends in social networks, we introduce the personalized link prediction in this paper, in which each individual will get equal number of diversiform predictions. While the performances of many classical algorithms are not satisfactory under this framework, thus new algorithms are in urgent need. Motivated by previous researches in other fields, we generalize heat conduction process to the framework of personalized link prediction and find that this method outperforms many classical similarity-based algorithms, especially in the performance of diversity. In addition, we demonstrate that adding one ground node who is supposed to connect all the nodes in the system will greatly benefit the performance of heat conduction. Finally, better hybrid algorithms composed of local random walk and heat conduction have been proposed. Numerical results show that the hybrid algorithms can outperform other algorithms simultaneously in all four ...

  2. A method for predicting monthly rainfall patterns

    International Nuclear Information System (INIS)

    A brief survey is made of previous methods that have been used to predict rainfall trends or drought spells in different parts of the earth. The basic methodologies or theoretical strategies used in these methods are compared with contents of a recent theory of Sun-Weather/Climate links (Njau, 1985a; 1985b; 1986; 1987a; 1987b; 1987c) which point towards the possibility of practical climatic predictions. It is shown that not only is the theoretical basis of each of these methodologies or strategies fully incorporated into the above-named theory, but also this theory may be used to develop a technique by which future monthly rainfall patterns can be predicted in further and finer details. We describe the latter technique and then illustrate its workability by means of predictions made on monthly rainfall patterns in some East African meteorological stations. (author). 43 refs, 11 figs, 2 tabs

  3. Predictability of extreme events in social media

    CERN Document Server

    Miotto, José M

    2014-01-01

    It is part of our daily social-media experience that seemingly ordinary items (videos, news, publications, etc.) unexpectedly gain an enormous amount of attention. Here we investigate how unexpected these events are. We propose a method that, given some information on the items, quantifies the predictability of events, i.e., the potential of identifying in advance the most successful items defined as the upper bound for the quality of any prediction based on the same information. Applying this method to different data, ranging from views in YouTube videos to posts in Usenet discussion groups, we invariantly find that the predictability increases for the most extreme events. This indicates that, despite the inherently stochastic collective dynamics of users, efficient prediction is possible for the most extreme events.

  4. Computational materials science: Predictions of pinning

    Science.gov (United States)

    Paruch, Patrycja; Ghosez, Philippe

    2016-06-01

    A multiscale model has been implemented that provides accurate predictions of the behaviour of ferroelectric materials in electric fields, and might aid efforts to design devices such as sensors and digital memory. See Letter p.360

  5. Predictive coding as a model of cognition.

    Science.gov (United States)

    Spratling, M W

    2016-08-01

    Previous work has shown that predictive coding can provide a detailed explanation of a very wide range of low-level perceptual processes. It is also widely believed that predictive coding can account for high-level, cognitive, abilities. This article provides support for this view by showing that predictive coding can simulate phenomena such as categorisation, the influence of abstract knowledge on perception, recall and reasoning about conceptual knowledge, context-dependent behavioural control, and naive physics. The particular implementation of predictive coding used here (PC/BC-DIM) has previously been used to simulate low-level perceptual behaviour and the neural mechanisms that underlie them. This algorithm thus provides a single framework for modelling both perceptual and cognitive brain function. PMID:27118562

  6. Diffusion changes predict cognitive and functional outcome

    DEFF Research Database (Denmark)

    Jokinen, Hanna; Schmidt, Reinhold; Ropele, Stefan;

    2013-01-01

    A study was undertaken to determine whether diffusion-weighted imaging (DWI) abnormalities in normal-appearing brain tissue (NABT) and in white matter hyperintensities (WMH) predict longitudinal cognitive decline and disability in older individuals independently of the concomitant magnetic...

  7. Predicting risky behavior in social communities

    CERN Document Server

    Simpson, Olivia

    2016-01-01

    Predicting risk profiles of individuals in networks (e.g.~susceptibility to a particular disease, or likelihood of smoking) is challenging for a variety of reasons. For one, `local' features (such as an individual's demographic information) may lack sufficient information to make informative predictions; this is especially problematic when predicting `risk,' as the relevant features may be precisely those that an individual is disinclined to reveal in a survey. Secondly, even if such features are available, they still may miss crucial information, as `risk' may be a function not just of an individual's features but also those of their friends and social communities. Here, we predict individual's risk profiles as a function of both their local features and those of their friends. Instead of modeling influence from the social network directly (which proved difficult as friendship links may be sparse and partially observed), we instead model influence by discovering social communities in the network that may be ...

  8. Social monitoring research for predicting mass incidents

    Institute of Scientific and Technical Information of China (English)

    2009-01-01

    @@ Based on surveys of resident attitude, a social monitoring research team with the CAS Institute of Psychology has established a predicting model on the possibility of mass incidents, that is, collective conflicts against the administration.

  9. Prediction of deformity in spinal tuberculosis

    NARCIS (Netherlands)

    Jutte, Paul; Wuite, Sander; The, Bertram; van Altena, Richard; Veldhuizen, Albert

    2007-01-01

    Tuberculosis of the spine may cause kyphosis, which may in turn cause late paraplegia, respiratory compromise, and unsightly deformity. Surgical correction therefore may be considered for large or progressive deformities. We retrospectively analyzed clinical and radiographic parameters to predict th

  10. A Course in... Model Predictive Control.

    Science.gov (United States)

    Arkun, Yaman; And Others

    1988-01-01

    Describes a graduate engineering course which specializes in model predictive control. Lists course outline and scope. Discusses some specific topics and teaching methods. Suggests final projects for the students. (MVL)

  11. On the predictability of ice avalanches

    Directory of Open Access Journals (Sweden)

    A. Pralong

    2005-01-01

    Full Text Available The velocity of unstable large ice masses from hanging glaciers increases as a power-law function of time prior to failure. This characteristic acceleration presents a finite-time singularity at the theoretical time of failure and can be used to forecast the time of glacier collapse. However, the non-linearity of the power-law function makes the prediction difficult. The effects of the non-linearity on the predictability of a failure are analyzed using a non-linear regression method. Predictability strongly depends on the time window when the measurements are performed. Log-periodic oscillations have been observed to be superimposed on the motion of large unstable ice masses. The value of their amplitude, frequency and phase are observed to be spatially homogeneous over the whole unstable ice mass. Inclusion of a respective term in the function describing the acceleration of unstable ice masses greatly increases the accuracy of the prediction.

  12. Predicting missing links via correlation between nodes

    Science.gov (United States)

    Liao, Hao; Zeng, An; Zhang, Yi-Cheng

    2015-10-01

    As a fundamental problem in many different fields, link prediction aims to estimate the likelihood of an existing link between two nodes based on the observed information. Since this problem is related to many applications ranging from uncovering missing data to predicting the evolution of networks, link prediction has been intensively investigated recently and many methods have been proposed so far. The essential challenge of link prediction is to estimate the similarity between nodes. Most of the existing methods are based on the common neighbor index and its variants. In this paper, we propose to calculate the similarity between nodes by the Pearson correlation coefficient. This method is found to be very effective when applied to calculate similarity based on high order paths. We finally fuse the correlation-based method with the resource allocation method, and find that the combined method can substantially outperform the existing methods, especially in sparse networks.

  13. Dynamo theory prediction of solar activity

    Science.gov (United States)

    Schatten, Kenneth H.

    1988-01-01

    The dynamo theory technique to predict decadal time scale solar activity variations is introduced. The technique was developed following puzzling correlations involved with geomagnetic precursors of solar activity. Based upon this, a dynamo theory method was developed to predict solar activity. The method was used successfully in solar cycle 21 by Schatten, Scherrer, Svalgaard, and Wilcox, after testing with 8 prior solar cycles. Schatten and Sofia used the technique to predict an exceptionally large cycle, peaking early (in 1990) with a sunspot value near 170, likely the second largest on record. Sunspot numbers are increasing, suggesting that: (1) a large cycle is developing, and (2) that the cycle may even surpass the largest cycle (19). A Sporer Butterfly method shows that the cycle can now be expected to peak in the latter half of 1989, consistent with an amplitude comparable to the value predicted near the last solar minimum.

  14. The art of predicting nuclear masses

    International Nuclear Information System (INIS)

    A review of recent advances in the theoretical analysis of nuclear mass models and their predictive power is presented. After introducing two tests which probe the ability of nuclear mass models to extrapolate, three models are analyzed in detail: the liquid drop model (LDM), the liquid drop model plus empirical shell corrections (LDMM) and the Duflo–Zuker mass formula (DZ). The DZ model is exhibited as the most predictive model. The Garvey–Kelson mass relations are also discussed. It is shown that their fulfillment probes the consistency of the most commonly used mass formulae, and that they can be used in an iterative process to predict nuclear masses in the neighborhood of nuclei with measured masses, offering a simple and reproducible procedure for short range mass predictions. (author)

  15. Predictive Blacklisting as an Implicit Recommendation System

    CERN Document Server

    Soldo, Fabio; Markopoulou, Athina

    2009-01-01

    A widely used defense practice against malicious traffic on the Internet is through blacklists: lists of prolific attack sources are compiled and shared. The goal of blacklists is to predict and block future attack sources. Existing blacklisting techniques have focused on the most prolific attack sources and, more recently, on collaborative blacklisting. In this paper, we formulate the problem of forecasting attack sources (also referred to as predictive blacklisting) based on shared attack logs as an implicit recommendation system. We compare the performance of existing approaches against the upper bound for prediction, and we demonstrate that there is much room for improvement. Inspired by the recent Netflix competition, we propose a multi-level prediction model that is adjusted and tuned specifically for the attack forecasting problem. Our model captures and combines various factors, namely: attacker-victim history (using time-series) and attackers and/or victims interactions (using neighborhood models). W...

  16. Time Series Prediction Based on Chaotic Attractor

    Institute of Scientific and Technical Information of China (English)

    LIKe-Ping; CHENTian-Lun; GAOZi-You

    2003-01-01

    A new prediction technique is proposed for chaotic time series. The usefulness of the technique is that it can kick off some false neighbor points which are not suitable for the local estimation of the dynamics systems. A time-delayed embedding is used to reconstruct the underlying attractor, and the prediction model is based on the time evolution of the topological neighboring in the phase space. We use a feedforward neural network to approximate the local dominant Lyapunov exponent, and choose the spatial neighbors by the Lyapunov exponent. The model is tested for the Mackey-Glass equation and the convection amplitude of lorenz systems. The results indicate that this prediction technique can improve the prediction of chaotic time series.

  17. Financial distress prediction and operating leases

    NARCIS (Netherlands)

    Lückerath – Rovers, M.

    2009-01-01

    This study investigates whether including operating lease commitments in financial distress prediction models would increase the classification accuracy of these models. Classification accuracy measures the percentages of correctly classified companies in either of the two categories (healthy or fin

  18. Alpha complexes in protein structure prediction

    DEFF Research Database (Denmark)

    Winter, Pawel; Fonseca, Rasmus

    2015-01-01

    Reducing the computational effort and increasing the accuracy of potential energy functions is of utmost importance in modeling biological systems, for instance in protein structure prediction, docking or design. Evaluating interactions between nonbonded atoms is the bottleneck of such computatio...

  19. Predicting Engine Parameters using the Optical Spectrum

    Data.gov (United States)

    National Aeronautics and Space Administration — The Optical Plume Anomaly Detection (OPAD) system is under development to predict engine anomalies and engine parameters of the Space Shuttle's Main Engine (SSME)....

  20. Clinical studies of biomarkers in suicide prediction

    OpenAIRE

    Jokinen, Jussi

    2007-01-01

    Suicide is a major clinical problem in psychiatry and suicidal behaviours can be seen as a nosological entity per se. Predicting suicide is difficult due to its low base-rate and the limited specificity of clinical predictors. Prospective biological studies suggest that dysfunctions in the hypothalamo pituitary adrenal (HPA) axis and the serotonergic system have predictive power for suicide in mood disorders. Suicide attempt is the most robust clinical predictor making suici...

  1. Price dynamics in political prediction markets

    OpenAIRE

    Majumder, Saikat Ray; Diermeier, Daniel; Thomas A. Rietz; Amaral, Luís A. Nunes

    2009-01-01

    Prediction markets, in which contract prices are used to forecast future events, are increasingly applied to various domains ranging from political contests to scientific breakthroughs. However, the dynamics of such markets are not well understood. Here, we study the return dynamics of the oldest, most data-rich prediction markets, the Iowa Electronic Presidential Election “winner-takes-all” markets. As with other financial markets, we find uncorrelated returns, power-law decaying volatility ...

  2. CRITICAL REVIEW OF PROSTATE CANCER PREDICTIVE TOOLS

    OpenAIRE

    Shahrokh F. Shariat; Michael W Kattan; Vickers, Andrew J; Karakiewicz, Pierre I; Scardino, Peter T.

    2009-01-01

    Prostate cancer is a very complex disease, and the decision-making process requires the clinician to balance clinical benefits, life expectancy, comorbidities, and potential treatment related side effects. Accurate prediction of clinical outcomes may help in the difficult process of making decisions related to prostate cancer. In this review, we discuss attributes of predictive tools and systematically review those available for prostate cancer. Types of tools include probability formulas, lo...

  3. Predicting chromatin organization using histone marks

    OpenAIRE

    Huang, Jialiang; Marco, Eugenio; Pinello, Luca; Yuan, Guo-Cheng

    2015-01-01

    Genome-wide mapping of three dimensional chromatin organization is an important yet technically challenging task. To aid experimental effort and to understand the determinants of long-range chromatin interactions, we have developed a computational model integrating Hi-C and histone mark ChIP-seq data to predict two important features of chromatin organization: chromatin interaction hubs and topologically associated domain (TAD) boundaries. Our model accurately and robustly predicts these feat...

  4. Lumbar spine: pretest predictability of CT findings

    Energy Technology Data Exchange (ETDEWEB)

    Giles, D.J.; Thomas, R.J.; Osborn, A.G.; Clayton, P.D.; Miller, M.H.; Bahr, A.L.; Frederick, P.R.; O' Connor, G.D.; Ostler, D.

    1984-03-01

    Demographic and symptomatic data gathered from 460 patients referred for lumbosacral CT examinations were analyzed to determine if the prescan probability of normal or abnormal findings could be predicted accurately. The authors were unable to predict the presence of herniated disk on the basis of patient-supplied data alone. Age was the single most significant predictor of an abnormality and was sharply related to degenerative disease and spinal stenosis.

  5. Adaboost Ensemble Classifiers for Corporate Default Prediction

    OpenAIRE

    Suresh Ramakrishnan; Maryam Mirzaei; Mahmoud Bekri

    2015-01-01

    This study aims to show a substitute technique to corporate default prediction. Data mining techniques have been extensively applied for this task, due to its ability to notice non-linear relationships and show a good performance in presence of noisy information, as it usually happens in corporate default prediction problems. In spite of several progressive methods that have widely been proposed, this area of research is not out dated and still needs further examination. In this study, the pe...

  6. DRIVER MODERATOR METHOD FOR RETAIL SALES PREDICTION

    OpenAIRE

    ÖZDEN GÜR ALI

    2013-01-01

    We introduce a new method for stock keeping unit (SKU)-store level sales prediction in the presence of promotions to support order quantity and promotion planning decisions for retail managers. The method leverages the marketing literature to generate features, and data mining techniques to train a model that provides accurate sales predictions for existing and new SKUs, as well as consistent, actionable insights into category, store and promotion dynamics. The proposed "Driver Moderator" met...

  7. Video Quality Prediction over Wireless 4G

    KAUST Repository

    Lau, Chun Pong

    2013-04-14

    In this paper, we study the problem of video quality prediction over the wireless 4G network. Video transmission data is collected from a real 4G SCM testbed for investigating factors that affect video quality. After feature transformation and selection on video and network parameters, video quality is predicted by solving as regression problem. Experimental results show that the dominated factor on video quality is the channel attenuation and video quality can be well estimated by our models with small errors.

  8. Service life prediction and cementitious composites

    DEFF Research Database (Denmark)

    Stoklund Larsen, E.

    The present Ph.D.thesis describes and discusses the applicability of a systematic methodology recommended by CIB W80/RILEM-PSL for sevice life prediction. The report describes the most important inherent and environmental factors affecting the service life of structures of cementitious composites....... On the basis of this discription of factors and experience from a test programme described in SBI Report 222, Service life prediction and fibre reinforced cementitious composites, the applicabillity of the CIB/RILEM methodology is discussed....

  9. Entropy and the Predictability of Online Life

    OpenAIRE

    Roberta Sinatra; Michael Szell

    2013-01-01

    Using mobile phone records and information theory measures, our daily lives have been recently shown to follow strict statistical regularities, and our movement patterns are, to a large extent, predictable. Here, we apply entropy and predictability measures to two datasets of the behavioral actions and the mobility of a large number of players in the virtual universe of a massive multiplayer online game. We find that movements in virtual human lives follow the same high levels of predictabili...

  10. Review of prediction for thermal contact resistance

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    Theoretical prediction research on thermal contact resistance is reviewed in this paper. In general, modeling or simulating the thermal contact resistance involves several aspects, including the descriptions of surface topography, the analysis of micro mechanical deformation, and the thermal models. Some key problems are proposed for accurately predicting the thermal resistance of two solid contact surfaces. We provide a perspective on further promising research, which would be beneficial to understanding mechanisms and engineering applications of the thermal contact resistance in heat transport phenomena.

  11. Genetic models of homosexuality: generating testable predictions

    OpenAIRE

    Gavrilets, Sergey; Rice, William R.

    2006-01-01

    Homosexuality is a common occurrence in humans and other species, yet its genetic and evolutionary basis is poorly understood. Here, we formulate and study a series of simple mathematical models for the purpose of predicting empirical patterns that can be used to determine the form of selection that leads to polymorphism of genes influencing homosexuality. Specifically, we develop theory to make contrasting predictions about the genetic characteristics of genes influencing homosexuality inclu...

  12. Combination prediction method of chaotic time series

    Institute of Scientific and Technical Information of China (English)

    ZHAO DongHua; RUAN Jiong; CAI ZhiJie

    2007-01-01

    In the present paper, we propose an approach of combination prediction of chaotic time series. The method is based on the adding-weight one-rank local-region method of chaotic time series. The method allows us to define an interval containing a future value with a given probability, which is obtained by studying the prediction error distribution. Its effectiveness is shown with data generated by Logistic map.

  13. Imaging language pathways predicts postoperative naming deficits

    OpenAIRE

    Powell, H.W.R.; Parker, G J M; Alexander, D. C.; Symms, M.R.; Boulby, P. A.; Barker, G.J.; Thompson, P J; Koepp, M J.; Duncan, J.S.

    2008-01-01

    Naming difficulties are a well recognised, but difficult to predict, complication of anterior temporal lobe resection (ATLR) for refractory epilepsy. We used MR tractography preoperatively to demonstrate the structural connectivity of language areas in patients undergoing dominant hemisphere ATLR. Greater lateralisation of tracts to the dominant hemisphere was associated with greater decline in naming function. We suggest that this method has the potential to predict language deficits in pati...

  14. Opportune maintenance and predictive maintenance decision support

    OpenAIRE

    Thomas, Edouard; Levrat, Eric; Iung, Benoît; Cocheteux, Pierre

    2009-01-01

    Conventional maintenance strategies on a single component are being phased out in favour of more predictive maintenance actions. These new kinds of actions are performed in order to control the global performances of the whole industrial system. They are anticipative in nature, which allows a maintenance expert to consider non-already-planned maintenance actions. Two questions naturally emerge: when to perform a predictive maintenance action; how a maintenance expert can take advantage of a g...

  15. Efficient particle continuation model predictive control

    OpenAIRE

    Knyazev, Andrew; Malyshev, Alexander,

    2015-01-01

    Continuation model predictive control (MPC), introduced by T. Ohtsuka in 2004, uses Krylov-Newton approaches to solve MPC optimization and is suitable for nonlinear and minimum time problems. We suggest particle continuation MPC in the case, where the system dynamics or constraints can discretely change on-line. We propose an algorithm for on-line controller implementation of continuation MPC for ensembles of predictions corresponding to various anticipated changes and demonstrate its numeric...

  16. Rater Wealth Predicts Perceptions of Outgroup Competence

    OpenAIRE

    Chan, Wayne; McCrae, Robert R.; Rogers, Darrin L.; Weimer, Amy A.; Greenberg, David M.; Terracciano, Antonio

    2011-01-01

    National income has a pervasive influence on the perception of ingroup stereotypes, with high status and wealthy targets perceived as more competent. In two studies we investigated the degree to which economic wealth of raters related to perceptions of outgroup competence. Raters’ economic wealth predicted trait ratings when 1) raters in 48 other cultures rated Americans’ competence and 2) Mexican Americans rated Anglo Americans’ competence. Rater wealth also predicted ratings of interpersona...

  17. Passenger flows prediction in major transportation hubs

    OpenAIRE

    Ozerova, O. O.

    2013-01-01

    Purpose. An effective organization of passenger traffic, due to the reliability prediction of traffic flow in passenger transport hubs. In order to determine the parameters of prospective passenger transport areas it is essential to analyze the impact of various factors and determine the most influential ones. Methodology. The article presents the method of paired linear correlation for a more influential factors on passengers in intercity and commuter and possible use in predicting the linea...

  18. Models for Predictive Railway Traffic Management

    OpenAIRE

    Kecman, P.

    2014-01-01

    The potential growth in transport demand in the next decade and beyond requires a change from reactive to proactive traffic control to maintain and improve the reliability of railway traffic. In order to enable an anticipative approach to traffic management, it is necessary to develop the tools for monitoring, prediction and optimisation of the traffic operations. This thesis presents the models that can be used as components for a decision support system for predictive traffic management.

  19. Quinstant Dark Energy Predictions for Structure Formation

    CERN Document Server

    Nodal, Yoelsy Leyva; Cardone, V F

    2009-01-01

    We explore the predictions of a class of dark energy models, quinstant dark energy, concerning the structure formation in the Universe, both in the linear and non-linear regimes. Quinstant dark energy is considered to be formed by quintessence and a negative cosmological constant. We conclude that these models give good predictions for structure formation in the linear regime, but fail to do so in the non-linear one, for redshifts larger than one.

  20. Utility gains through infrared predictive maintenance

    Science.gov (United States)

    Black, James E., Jr.

    1991-03-01

    The use of the infrared technology at Davis-Besse for predictive maintenance applications has proven itself. Since late 1987, the infrared work has been conducted in-house to support other techniques or as a sole predictive maintenance technique. The topic of this paper will be to review some of the applications and the results achieved. The areas which will be reviewed are in the Electrical Distribution System, the Control Rod Drive System and steam applications.

  1. The role of prediction in social neuroscience

    Directory of Open Access Journals (Sweden)

    Elliot Clayton Brown

    2012-05-01

    Full Text Available Research has shown that the brain is constantly making predictions about future events. Theories of prediction in perception, action and learning suggest that the brain serves to reduce the discrepancies between expectation and actual experience, i.e. by reducing the prediction error. Forward models of action and perception propose the generation of a predictive internal representation of the expected sensory outcome, which is matched to the actual sensory feedback. Shared neural representations have been found when experiencing one’s own and observing others’ actions, rewards, errors and emotions such as fear and pain. These general principles of the ‘predictive brain’ are well established and have already begun to be applied to social aspects of cognition. The application and relevance of these predictive principles to social cognition are discussed. Evidence is presented to argue that simple non-social cognitive processes can be extended to explain complex cognitive processes required for social interaction, with common neural activity seen for both social and non-social cognitions. A number of studies are included which demonstrate that bottom-up sensory input and top-down expectancies can be modulated by social information. The concept of competing social forward models and a partially distinct category of social prediction errors are introduced. The evolutionary implications of a ‘social predictive brain’ are also mentioned, along with the implications on psychopathology. The review presents a number of testable hypotheses and novel comparisons that aim to stimulate further discussion and integration between currently disparate fields of research, with regard to computational models, behavioural and neurophysiological data. This promotes a relatively new platform for inquiry in social neuroscience with implications in social learning, theory of mind, empathy, the evolution of the social brain and potential strategies for

  2. Prediction of enteric methane emissions from cattle.

    Science.gov (United States)

    Moraes, Luis E; Strathe, Anders B; Fadel, James G; Casper, David P; Kebreab, Ermias

    2014-07-01

    Agriculture has a key role in food production worldwide and it is a major component of the gross domestic product of several countries. Livestock production is essential for the generation of high quality protein foods and the delivery of foods in regions where animal products are the main food source. Environmental impacts of livestock production have been examined for decades, but recently emission of methane from enteric fermentation has been targeted as a substantial greenhouse gas source. The quantification of methane emissions from livestock on a global scale relies on prediction models because measurements require specialized equipment and may be expensive. The predictive ability of current methane emission models remains poor. Moreover, the availability of information on livestock production systems has increased substantially over the years enabling the development of more detailed methane prediction models. In this study, we have developed and evaluated prediction models based on a large database of enteric methane emissions from North American dairy and beef cattle. Most probable models of various complexity levels were identified using a Bayesian model selection procedure and were fitted under a hierarchical setting. Energy intake, dietary fiber and lipid proportions, animal body weight and milk fat proportion were identified as key explanatory variables for predicting emissions. Models here developed substantially outperformed models currently used in national greenhouse gas inventories. Additionally, estimates of repeatability of methane emissions were lower than the ones from the literature and multicollinearity diagnostics suggested that prediction models are stable. In this context, we propose various enteric methane prediction models which require different levels of information availability and can be readily implemented in national greenhouse gas inventories of different complexity levels. The utilization of such models may reduce errors

  3. Learning to predict slip for ground robots

    Science.gov (United States)

    Angelova, Anelia; Matthies, Larry; Helmick, Daniel; Sibley, Gabe; Perona, Pietro

    2006-01-01

    In this paper we predict the amount of slip an exploration rover would experience using stereo imagery by learning from previous examples of traversing similar terrain. To do that, the information of terrain appearance and geometry regarding some location is correlated to the slip measured by the rover while this location is being traversed. This relationship is learned from previous experience, so slip can be predicted later at a distance from visual information only.

  4. Predictive uncertainty in auditory sequence processing

    OpenAIRE

    Niels Chr.Hansen; MarcusT.Pearce

    2014-01-01

    Previous studies of auditory expectation have focused on the expectedness perceived by listeners retrospectively in response to events. In contrast, this research examines predictive uncertainty - a property of listeners’ prospective state of expectation prior to the onset of an event. We examine the information-theoretic concept of Shannon entropy as a model of predictive uncertainty in music cognition. This is motivated by the Statistical Learning Hypothesis, which proposes that schematic e...

  5. Predicting meningococcal disease outbreaks in structured populations.

    Science.gov (United States)

    Ranta, J; Mäkelä, P H; Arjas, E

    2004-03-30

    Rational decision making on whether some form of intervention would be necessary to control the spread of a meningococcal epidemic is based on predictions concerning its potential natural progression. Unfortunately, reliable predictions are difficult to make during the early stages of an outbreak. A stochastic discrete time epidemic model was applied to adaptively predict the development of outbreaks of meningococcal disease in 'closed' populations such as military garrisons or boarding schools, which are further divided into subgroups called 'units'. The performance of the adaptive method was assessed by using 3 simulated epidemics representing substantially different realizations in a 'garrison' of 20 units, with 68 men in each. Predictions of the weekly number of disease cases, of the number of carriers, and of the number of new infections were computed. Simulations suggest that predictions based only on the observed numbers of disease cases are generally inaccurate. These predictions can be improved if temporal observations on asymptomatic carriers in different units are utilized together with observed time series of the disease. A sample of 15 per cent from all units can be sufficient for a major improvement if the alternative is to obtain a full sample of only some units. Exploiting fully such information requires computer intensive Markov chain Monte Carlo methods. PMID:15027081

  6. Assessment of NASA's Aircraft Noise Prediction Capability

    Science.gov (United States)

    Dahl, Milo D. (Editor)

    2012-01-01

    A goal of NASA s Fundamental Aeronautics Program is the improvement of aircraft noise prediction. This document provides an assessment, conducted from 2006 to 2009, on the current state of the art for aircraft noise prediction by carefully analyzing the results from prediction tools and from the experimental databases to determine errors and uncertainties and compare results to validate the predictions. The error analysis is included for both the predictions and the experimental data and helps identify where improvements are required. This study is restricted to prediction methods and databases developed or sponsored by NASA, although in many cases they represent the current state of the art for industry. The present document begins with an introduction giving a general background for and a discussion on the process of this assessment followed by eight chapters covering topics at both the system and the component levels. The topic areas, each with multiple contributors, are aircraft system noise, engine system noise, airframe noise, fan noise, liner physics, duct acoustics, jet noise, and propulsion airframe aeroacoustics.

  7. Cephalometric methods of prediction in orthognathic surgery.

    Science.gov (United States)

    Kolokitha, Olga-Elpis; Topouzelis, Nikolaos

    2011-09-01

    Over the past decade the growing number of adult patients seeking for orthodontic treatment made orthognathic surgery popular. Surgical and orthodontic techniques have developed to the point where combined orthodontic and surgical treatment is now feasible to manage dentofacial deformity problems very satisfactorily. The prediction of orthognathic treatment outcome is an important part of orthognathic planning and the process of patient' inform consent. The predicted results must be presented to the patients prior to treatment in order to assess the treatment's feasibility, optimize case management and increase patient understanding and acceptance of the recommended treatment. Cephalometrics is a routine part of the diagnosis and treatment planning process and also allows the clinician to evaluate changes following orthognathic surgery. Traditionally cephalometry has been employed manually; nowadays computerized cephalometric systems are very popular. Cephalometric prediction in orthognathic surgery can be done manually or by computers, using several currently available software programs, alone or in combination with video images. Both manual and computerized cephalometric prediction methods are two-dimensional and cannot fully describe three-dimensional phenomena. Today, three-dimensional prediction methods are available, such as three-dimensional computerized tomography (3DCT), 3D magnetic resonance imaging (3DMRI) and surface scan/cone-beam CT. The aim of this article is to present and discuss the different methods of cephalometric prediction of the orthognathic surgery outcome.

  8. Understanding Predictability and Exploration in Human Mobility

    CERN Document Server

    Cuttone, Andrea; González, Marta C

    2016-01-01

    Predictive models for human mobility have important applications in many fields such as traffic control, ubiquitous computing and contextual advertisement. The predictive performance of models in literature varies quite broadly, from as high as 93% to as low as under 40%. In this work we investigate which factors influence the accuracy of next-place prediction, using a high-precision location dataset of more than 400 users for periods between 3 months and one year. We show that it is easier to achieve high accuracy when predicting the time-bin location than when predicting the next place. Moreover we demonstrate how the temporal and spatial resolution of the data can have strong influence on the accuracy of prediction. Finally we uncover that the exploration of new locations is an important factor in human mobility, and we measure that on average 20-25% of transitions are to new places, and approx. 70% of locations are visited only once. We discuss how these mechanisms are important factors limiting our abili...

  9. Referential Choice: Predictability and Its Limits

    Science.gov (United States)

    Kibrik, Andrej A.; Khudyakova, Mariya V.; Dobrov, Grigory B.; Linnik, Anastasia; Zalmanov, Dmitrij A.

    2016-01-01

    We report a study of referential choice in discourse production, understood as the choice between various types of referential devices, such as pronouns and full noun phrases. Our goal is to predict referential choice, and to explore to what extent such prediction is possible. Our approach to referential choice includes a cognitively informed theoretical component, corpus analysis, machine learning methods and experimentation with human participants. Machine learning algorithms make use of 25 factors, including referent’s properties (such as animacy and protagonism), the distance between a referential expression and its antecedent, the antecedent’s syntactic role, and so on. Having found the predictions of our algorithm to coincide with the original almost 90% of the time, we hypothesized that fully accurate prediction is not possible because, in many situations, more than one referential option is available. This hypothesis was supported by an experimental study, in which participants answered questions about either the original text in the corpus, or about a text modified in accordance with the algorithm’s prediction. Proportions of correct answers to these questions, as well as participants’ rating of the questions’ difficulty, suggested that divergences between the algorithm’s prediction and the original referential device in the corpus occur overwhelmingly in situations where the referential choice is not categorical. PMID:27721800

  10. Environmental impact prediction using remote sensing images

    Institute of Scientific and Technical Information of China (English)

    Pezhman ROUDGARMI; Masoud MONAVARI; Jahangir FEGHHI; Jafar NOURI; Nematollah KHORASANI

    2008-01-01

    Environmental impact prediction is an important step in many environmental studies. Awide variety of methods have been developed in this concern. During this study, remote sensing images were used for environmental impact prediction in Robatkarim area, Iran, during the years of 2005~2007. It was assumed that environmental impact could be predicted using time series satellite imageries. Natural vegetation cover was chosen as a main environmental element and a case study. Environmental impacts of the regional development on natural vegetation of the area were investigated considering the changes occurred on the extent of natural vegetation cover and the amount of biomass. Vegetation data, land use and land cover classes (as activity factors) within several years were prepared using satellite images. The amount ofbiomass was measured by Soil-adjusted Vegetation Index (SAVI) and Normalized Difference Vegetation Index (NDVI) based on satellite images. The resulted biomass estimates were tested by the paired samples t-test method. No significant difference was observed between the average biomass of estimated and control samples at the 5% significance level. Finally, regression models were used for the environmental impacts prediction. All obtained regression models for prediction of impacts on natural vegetation cover show values over 0.9 for both correlation coefficient and R-squared. According to the resulted methodology, the prediction models of projects and plans impacts can also be developed for other environmental elements which may be derived using time series remote sensing images.

  11. Seasonal prediction of ocean surface waves.

    Science.gov (United States)

    Dobrynin, Mikhail; Brune, Sebastian; Fröhlich, Kristina; Bunzel, Felix; Pohlmann, Holger; Müller, Wolfgang A.; Baehr, Johanna

    2016-04-01

    Due to the short-term nature of wind, storms and surface ocean waves dynamics, the seasonal prediction of ocean wave requires a robust prediction system which can realistically represent the variably of sea level pressure and wind on a seasonal scale. The seasonal prediction system based on the mixed resolution CMIP5 version of the Max Planck Institute for Meteorology Earth System Model (MPI-ESM MR) provides a skilful seasonal prediction of sea level pressure and wind. The system is initialised every six months by reanalysis and observations in the atmospheric, ocean and sea ice components of the model. The seasonal prediction system was extended by the wave model WAM, which is running offline, using the wind re-forecast provided by the MPI-ESM MR. Our 10-member wave re-forecast over the period from 1982 to 2012 demonstrates a skilful prediction of the wave height up to 2-4 months in the Pacific, Equatorial Atlantic and Indian Ocean depending on the season. We evaluate our re-forecast by statistical metrics such as the anomaly correlation, spread-error ratio, and root-mean-square-error using the ERA-Interim forced wave reanalysis and buoys measurements as a reference.

  12. Using Deep Learning for Compound Selectivity Prediction.

    Science.gov (United States)

    Zhang, Ruisheng; Li, Juan; Lu, Jingjing; Hu, Rongjing; Yuan, Yongna; Zhao, Zhili

    2016-01-01

    Compound selectivity prediction plays an important role in identifying potential compounds that bind to the target of interest with high affinity. However, there is still short of efficient and accurate computational approaches to analyze and predict compound selectivity. In this paper, we propose two methods to improve the compound selectivity prediction. We employ an improved multitask learning method in Neural Networks (NNs), which not only incorporates both activity and selectivity for other targets, but also uses a probabilistic classifier with a logistic regression. We further improve the compound selectivity prediction by using the multitask learning method in Deep Belief Networks (DBNs) which can build a distributed representation model and improve the generalization of the shared tasks. In addition, we assign different weights to the auxiliary tasks that are related to the primary selectivity prediction task. In contrast to other related work, our methods greatly improve the accuracy of the compound selectivity prediction, in particular, using the multitask learning in DBNs with modified weights obtains the best performance. PMID:26892071

  13. Prediction of critical heat flux using ANFIS

    Energy Technology Data Exchange (ETDEWEB)

    Zaferanlouei, Salman, E-mail: zaferanlouei@gmail.co [Nuclear Engineering and Physics Department, Faculty of Nuclear Engineering, Center of Excellence in Nuclear Engineering, Amirkabir University of Technology (Tehran Polytechnic), 424 Hafez Avenue, Tehran (Iran, Islamic Republic of); Rostamifard, Dariush; Setayeshi, Saeed [Nuclear Engineering and Physics Department, Faculty of Nuclear Engineering, Center of Excellence in Nuclear Engineering, Amirkabir University of Technology (Tehran Polytechnic), 424 Hafez Avenue, Tehran (Iran, Islamic Republic of)

    2010-06-15

    The prediction of Critical Heat Flux (CHF) is essential for water cooled nuclear reactors since it is an important parameter for the economic efficiency and safety of nuclear power plants. Therefore, in this study using Adaptive Neuro-Fuzzy Inference System (ANFIS), a new flexible tool is developed to predict CHF. The process of training and testing in this model is done by using a set of available published field data. The CHF values predicted by the ANFIS model are acceptable compared with the other prediction methods. We improve the ANN model that is proposed by to avoid overfitting. The obtained new ANN test errors are compared with ANFIS model test errors, subsequently. It is found that the ANFIS model with root mean square (RMS) test errors of 4.79%, 5.04% and 11.39%, in fixed inlet conditions and local conditions and fixed outlet conditions, respectively, has superior performance in predicting the CHF than the test error obtained from MLP Neural Network in fixed inlet and outlet conditions, however, ANFIS also has acceptable result to predict CHF in fixed local conditions.

  14. Clinical prediction rule for nonmelanoma skin cancer

    Directory of Open Access Journals (Sweden)

    John Alexander Nova

    2015-01-01

    Full Text Available Background: Skin cancer is the most frequent neoplasia in the world. Even though ultraviolet radiation is the main cause, established prevention campaigns have not proved to be effective for controlling the incidence of this disease. Objective: To develop clinical prediction rules based on medical consultation and a questionnaire to estimate the risk of developing nonmelanoma skin cancer. Methods: This study was developed in several steps. They were: Identifying risk factors that could be possible predictors of nonmelanoma skin cancer; their clinical validation; developing a prediction rule using logistic regression; and collecting information from 962 patients in a case and control design (481 cases and 481 controls. We developed independent prediction rules for basal cell and squamous cell carcinomas. Finally, we evaluated reliability for each of the variables. Results: The variables that made up the final prediction rule were: Family history of skin cancer, history of outdoor work, age, phototypes 1-3 and the presence of poikiloderma of civatte, actinic keratosis and conjunctivitis in band. Prediction rules specificity was 87% for basal cell carcinomas and 92% for squamous cell carcinomas. Inter- and intra-observer reliability was good except for the conjunctivitis in band variable. Conclusions: The prediction rules let us calculate the individual risk of developing basal cell carcinoma and squamous cell carcinoma. This is an economic easy-to-apply tool that could be useful in primary and secondary prevention of skin cancer.

  15. MJO prediction skill, predictability, and teleconnection impacts in the Beijing Climate Center Atmospheric General Circulation Model

    Science.gov (United States)

    Wu, Jie; Ren, Hong-Li; Zuo, Jinqing; Zhao, Chongbo; Chen, Lijuan; Li, Qiaoping

    2016-09-01

    This study evaluates performance of Madden-Julian oscillation (MJO) prediction in the Beijing Climate Center Atmospheric General Circulation Model (BCC_AGCM2.2). By using the real-time multivariate MJO (RMM) indices, it is shown that the MJO prediction skill of BCC_AGCM2.2 extends to about 16-17 days before the bivariate anomaly correlation coefficient drops to 0.5 and the root-mean-square error increases to the level of the climatological prediction. The prediction skill showed a seasonal dependence, with the highest skill occurring in boreal autumn, and a phase dependence with higher skill for predictions initiated from phases 2-4. The results of the MJO predictability analysis showed that the upper bounds of the prediction skill can be extended to 26 days by using a single-member estimate, and to 42 days by using the ensemble-mean estimate, which also exhibited an initial amplitude and phase dependence. The observed relationship between the MJO and the North Atlantic Oscillation was accurately reproduced by BCC_AGCM2.2 for most initial phases of the MJO, accompanied with the Rossby wave trains in the Northern Hemisphere extratropics driven by MJO convection forcing. Overall, BCC_AGCM2.2 displayed a significant ability to predict the MJO and its teleconnections without interacting with the ocean, which provided a useful tool for fully extracting the predictability source of subseasonal prediction.

  16. Prediction of dementia in primary care patients.

    Directory of Open Access Journals (Sweden)

    Frank Jessen

    Full Text Available BACKGROUND: Current approaches for AD prediction are based on biomarkers, which are however of restricted availability in primary care. AD prediction tools for primary care are therefore needed. We present a prediction score based on information that can be obtained in the primary care setting. METHODOLOGY/PRINCIPAL FINDINGS: We performed a longitudinal cohort study in 3.055 non-demented individuals above 75 years recruited via primary care chart registries (Study on Aging, Cognition and Dementia, AgeCoDe. After the baseline investigation we performed three follow-up investigations at 18 months intervals with incident dementia as the primary outcome. The best set of predictors was extracted from the baseline variables in one randomly selected half of the sample. This set included age, subjective memory impairment, performance on delayed verbal recall and verbal fluency, on the Mini-Mental-State-Examination, and on an instrumental activities of daily living scale. These variables were aggregated to a prediction score, which achieved a prediction accuracy of 0.84 for AD. The score was applied to the second half of the sample (test cohort. Here, the prediction accuracy was 0.79. With a cut-off of at least 80% sensitivity in the first cohort, 79.6% sensitivity, 66.4% specificity, 14.7% positive predictive value (PPV and 97.8% negative predictive value of (NPV for AD were achieved in the test cohort. At a cut-off for a high risk population (5% of individuals with the highest risk score in the first cohort the PPV for AD was 39.1% (52% for any dementia in the test cohort. CONCLUSIONS: The prediction score has useful prediction accuracy. It can define individuals (1 sensitively for low cost-low risk interventions, or (2 more specific and with increased PPV for measures of prevention with greater costs or risks. As it is independent of technical aids, it may be used within large scale prevention programs.

  17. The Prediction of Rice Gene by Fgenesh

    Institute of Scientific and Technical Information of China (English)

    ZHANG Sheng-li; LI Dong-fang; ZHANG Gai-sheng; WANG Jun-wei; NIU Na

    2008-01-01

    This study has been carried out to give some scientific reasons for genome annotation, shorten the annotating time, and improve the results of gene prediction. Taking the sequence of the 6th chromosome, which has more length sequences than others, of Oryza sativa L. ssp. japonica cv. Nipponbare as analysis data in this research, the gene prediction of monocots module, rice, has been done by using Fgenesh ver. 2.0, and the predicting results have been explored particularly by bioinformatics methods. Results showed that the number of predicted genes for this chromosome was very close to the number of TIGR annotated genes. The majority of the predicted genes were multi-exon genes which had a percentage of 77.52. Length range was very big in the predicted genes. According to the significant match number, multi-exon genes can be predicted more veracity than single exon genes and the support can be reached up to 100% by TIGR annotation and up to 78% by cDNA. From the angle of predicted exons location of multi-exon genes, the internal exons and last exons had a high support of cDNA. The length of internal exons was relatively short in high (>95% length, >78% similarity) cDNA and/or TIGR annotation support multi-exon genes, but the first exons and last exons were on the reverse. The majority of single exon genes which had more than 95% in length, and 78% in similarity support by cDNA and/or TIGR annotation was relatively short in length. From the angle of exon number, the majority of the multi-exon genes of high (> 95% length, > 78% similarity) cDNA and/or TIGR annotation support had no more than 5 exon number. It was concluded that the rice gene prediction by Fgenesh was very good but needed modification manually to some extent according to cDNA support after aligning the predicting sequence of genes with cDNA database of rice.

  18. Genomic Prediction Accounting for Residual Heteroskedasticity.

    Science.gov (United States)

    Ou, Zhining; Tempelman, Robert J; Steibel, Juan P; Ernst, Catherine W; Bates, Ronald O; Bello, Nora M

    2015-11-12

    Whole-genome prediction (WGP) models that use single-nucleotide polymorphism marker information to predict genetic merit of animals and plants typically assume homogeneous residual variance. However, variability is often heterogeneous across agricultural production systems and may subsequently bias WGP-based inferences. This study extends classical WGP models based on normality, heavy-tailed specifications and variable selection to explicitly account for environmentally-driven residual heteroskedasticity under a hierarchical Bayesian mixed-models framework. WGP models assuming homogeneous or heterogeneous residual variances were fitted to training data generated under simulation scenarios reflecting a gradient of increasing heteroskedasticity. Model fit was based on pseudo-Bayes factors and also on prediction accuracy of genomic breeding values computed on a validation data subset one generation removed from the simulated training dataset. Homogeneous vs. heterogeneous residual variance WGP models were also fitted to two quantitative traits, namely 45-min postmortem carcass temperature and loin muscle pH, recorded in a swine resource population dataset prescreened for high and mild residual heteroskedasticity, respectively. Fit of competing WGP models was compared using pseudo-Bayes factors. Predictive ability, defined as the correlation between predicted and observed phenotypes in validation sets of a five-fold cross-validation was also computed. Heteroskedastic error WGP models showed improved model fit and enhanced prediction accuracy compared to homoskedastic error WGP models although the magnitude of the improvement was small (less than two percentage points net gain in prediction accuracy). Nevertheless, accounting for residual heteroskedasticity did improve accuracy of selection, especially on individuals of extreme genetic merit.

  19. A Predictive Model for Root Caries Incidence.

    Science.gov (United States)

    Ritter, André V; Preisser, John S; Puranik, Chaitanya P; Chung, Yunro; Bader, James D; Shugars, Daniel A; Makhija, Sonia; Vollmer, William M

    2016-01-01

    This study aimed to find the set of risk indicators best able to predict root caries (RC) incidence in caries-active adults utilizing data from the Xylitol for Adult Caries Trial (X-ACT). Five logistic regression models were compared with respect to their predictive performance for incident RC using data from placebo-control participants with exposed root surfaces at baseline and from two study centers with ancillary data collection (n = 155). Prediction performance was assessed from baseline variables and after including ancillary variables [smoking, diet, use of removable partial dentures (RPD), toothbrush use, income, education, and dental insurance]. A sensitivity analysis added treatment to the models for both the control and treatment participants (n = 301) to predict RC for the control participants. Forty-nine percent of the control participants had incident RC. The model including the number of follow-up years at risk, the number of root surfaces at risk, RC index, gender, race, age, and smoking resulted in the best prediction performance, having the highest AUC and lowest Brier score. The sensitivity analysis supported the primary analysis and gave slightly better performance summary measures. The set of risk indicators best able to predict RC incidence included an increased number of root surfaces at risk and increased RC index at baseline, followed by white race and nonsmoking, which were strong nonsignificant predictors. Gender, age, and increased number of follow-up years at risk, while included in the model, were also not statistically significant. The inclusion of health, diet, RPD use, toothbrush use, income, education, and dental insurance variables did not improve the prediction performance. PMID:27160516

  20. Verification of FAC prediction model in pipe wall thinning prediction software 'FALSET'

    International Nuclear Information System (INIS)

    Flow accelerated corrosion (FAC) and liquid droplet impingement erosion (LDI) are the main pipe wall thinning phenomena in piping system of power plants. At present, the management is based on thinning rate and residual lifetime evaluation using pipe wall thickness measurement results. For future improvement of the management, introduction of domestic prediction code is expected. Yoneda et al. have developed original prediction software for pipe wall thinning 'FALSET', which is one-dimensional prediction for maximum thinning rate in each element in pipelines by simplifying their prediction models for local thinning rate of FAC/LDI. In this study, FAC prediction model in FALSET was verified with FAC data in domestic PWR secondary system, and prediction accuracy at present was discussed. (author)

  1. How Agribusiness Uses Climate Predictions: Implications for Climate Research and Provision of Predictions.

    Science.gov (United States)

    Sonka, S. T.; Changnon, S. A., Jr.; Hofing, S. L.

    1992-12-01

    The paper presents an analysis of climate prediction needs and uses within six important subsegments of the agribusiness sector. Results are based on a mail survey of 114 managers. Although nearly 70% of the respondents indicated some use of climate predictions in the last year, only 1 in 8 of the respondents used that information in a specific decision. Lack of sufficient accuracy and prediction lead time were identified as two important impediments to current use of climate predictions. Estimates of necessary accuracy levels and lead time are reported both for the group average and by segments of need. Recommendations are offered regarding research needs to enhance climate prediction and activities of the government and the private sector to improve use of climate predictions.

  2. DMC modified algorithm based on time series prediction principle

    Institute of Scientific and Technical Information of China (English)

    齐维贵; 朱学莉

    2002-01-01

    The application of heating load prediction and predictive control to the heat supply system for energysaving and high quality heat supply is discussed by first introducing the time series prediction principle, and thesequence model, parameter identification and least variance prediction principle, and then giving the heatingload and model error prediction based on this principle. As an improvement of DMC algorithm, the load predic-tion is used as a set point of DMC, and the prediction error is used as a corrected value of predictive control.Finally, the simulation results of two prediction methods to heat supply system are given.

  3. Predicting AD conversion: comparison between prodromal AD guidelines and computer assisted PredictAD tool.

    Directory of Open Access Journals (Sweden)

    Yawu Liu

    Full Text Available To compare the accuracies of predicting AD conversion by using a decision support system (PredictAD tool and current research criteria of prodromal AD as identified by combinations of episodic memory impairment of hippocampal type and visual assessment of medial temporal lobe atrophy (MTA on MRI and CSF biomarkers.Altogether 391 MCI cases (158 AD converters were selected from the ADNI cohort. All the cases had baseline cognitive tests, MRI and/or CSF levels of Aβ1-42 and Tau. Using baseline data, the status of MCI patients (AD or MCI three years later was predicted using current diagnostic research guidelines and the PredictAD software tool designed for supporting clinical diagnostics. The data used were 1 clinical criteria for episodic memory loss of the hippocampal type, 2 visual MTA, 3 positive CSF markers, 4 their combinations, and 5 when the PredictAD tool was applied, automatically computed MRI measures were used instead of the visual MTA results. The accuracies of diagnosis were evaluated with the diagnosis made 3 years later.The PredictAD tool achieved the overall accuracy of 72% (sensitivity 73%, specificity 71% in predicting the AD diagnosis. The corresponding number for a clinician's prediction with the assistance of the PredictAD tool was 71% (sensitivity 75%, specificity 68%. Diagnosis with the PredictAD tool was significantly better than diagnosis by biomarkers alone or the combinations of clinical diagnosis of hippocampal pattern for the memory loss and biomarkers (p≤0.037.With the assistance of PredictAD tool, the clinician can predict AD conversion more accurately than the current diagnostic criteria.

  4. Geostatistical enhancement of european hydrological predictions

    Science.gov (United States)

    Pugliese, Alessio; Castellarin, Attilio; Parajka, Juraj; Arheimer, Berit; Bagli, Stefano; Mazzoli, Paolo; Montanari, Alberto; Blöschl, Günter

    2016-04-01

    Geostatistical Enhancement of European Hydrological Prediction (GEEHP) is a research experiment developed within the EU funded SWITCH-ON project, which proposes to conduct comparative experiments in a virtual laboratory in order to share water-related information and tackle changes in the hydrosphere for operational needs (http://www.water-switch-on.eu). The main objective of GEEHP deals with the prediction of streamflow indices and signatures in ungauged basins at different spatial scales. In particular, among several possible hydrological signatures we focus in our experiment on the prediction of flow-duration curves (FDCs) along the stream-network, which has attracted an increasing scientific attention in the last decades due to the large number of practical and technical applications of the curves (e.g. hydropower potential estimation, riverine habitat suitability and ecological assessments, etc.). We apply a geostatistical procedure based on Top-kriging, which has been recently shown to be particularly reliable and easy-to-use regionalization approach, employing two different type of streamflow data: pan-European E-HYPE simulations (http://hypeweb.smhi.se/europehype) and observed daily streamflow series collected in two pilot study regions, i.e. Tyrol (merging data from Austrian and Italian stream gauging networks) and Sweden. The merger of the two study regions results in a rather large area (~450000 km2) and might be considered as a proxy for a pan-European application of the approach. In a first phase, we implement a bidirectional validation, i.e. E-HYPE catchments are set as training sites to predict FDCs at the same sites where observed data are available, and vice-versa. Such a validation procedure reveals (1) the usability of the proposed approach for predicting the FDCs over the entire river network of interest using alternatively observed data and E-HYPE simulations and (2) the accuracy of E-HYPE-based predictions of FDCs in ungauged sites. In a

  5. Femoral neck trabecular patterns predict osteoporotic fractures

    International Nuclear Information System (INIS)

    In this paper we show that texture analysis of femoral neck trabecular patterns can be used to predict osteoporotic fractures. The study is based on a sample of 123 women aged 44-66 years with and without fractures. We analyzed trabecular patterns using the Co-occurrence Matrix texture analysis algorithm and compared the predictive utility of the textural data with densitometry. Logistic regression was used to estimate the predictive utility, exp(B), of clinical and textural data per standard deviation. Reproducibility was also demonstrated using paired films at 1-year intervals (CoV=4.5%). Bone mass estimated by DEXA measurements of the spine and hip were the most predictive of fractures giving a two-fold increase in fractures per s.d. bone mass loss (95% CI: 1.2-3.1, p<0.005). Age was also highly predictive with fracture risk increasing by 1.07-fold per year (95% CI: 1.01-1.14, p<0.02). Trabecular texture was found to give a lower, but significant, prediction of fracture of 1.5-fold per s.d. trabecular pattern loss (95% CI: 0.96-2.31, p<0.05). Combining age, weight, and trabecular texture increased the fracture prediction to 1.78-fold per s.d. (95% CI: 1.19-2.67). Combining trabecular texture with densitometry increased the predictive ability to 2.06-fold per s.d. (95% CI: 1.32-3.22) and combined with age and weight as well increased exp(B) to 2.1-fold per s.d. (95% CI: 1.32-3.35). This shows that osteoporotic trabecular texture changes can be ''measured.'' Moreover, the combination of age, weight, and trabecular texture is more predictive than either alone. We propose therefore that this trabecular texture analysis is both reproducible and clinically meaningful. The application of such methods could be used to improve the estimation of fracture risk in conjunction with other clinical data, or where densitometry data cannot be obtained (e.g., in retrospective studies)

  6. Causal impressions: predicting when, not just whether.

    Science.gov (United States)

    Young, Michael E; Rogers, Ester T; Beckmann, Joshua S

    2005-03-01

    In 1739, David Hume established the so-called cues to causality--environmental cues that are important to the inference of causality. Although this descriptive account has been corroborated experimentally, it has not been established why these cues are useful, except that they may reflect statistical regularities in the environment. One of the cues to causality, covariation, helps predict whether an effect will occur, but not its time of occurrence. In the present study, evidence is provided that spatial and temporal contiguity improve an observer's ability to predict when an effect will occur, thus complementing the utility of covariation as a predictor of whether an effect will occur. While observing Michotte's (1946/1963) launching effect, participants showed greater accuracy and precision in their predictions of the onset of movement by the launched object when there was spatial and temporal contiguity. Furthermore, when auditory cues that bridged a delayed launch were included, causal ratings and predictability were similarly affected. These results suggest that the everyday inference of causality relies on our ability to predict whether and when an effect will occur.

  7. Compressor Part II: Volute Flow Predictions

    Directory of Open Access Journals (Sweden)

    Yu-Tai Lee

    1999-01-01

    Full Text Available A numerical method that solves the Reynolds-averaged Navier-Stokes equations is used to study an inefficient component of a shipboard air-conditioning HCFC-124 compressor system. This high-loss component of the centrifugal compressor was identified as the volute through a series of measurements given in Part I of the paper. The predictions were made using three grid topologies. The first grid closes the connection between the cutwater and the discharge diffuser. The other two grids connect the cutwater area with the discharge diffuser. Experiments were performed to simulate both the cutwater conditions used in the predictions. Surface pressures along the outer wall and near the inlet of the volute were surveyed for comparisons with the predictions. Good agreements between the predicted results and the measurements validate the calculations. Total pressure distributions and flow stream traces from the prediction results support the loss distribution through the volute. A modified volute configuration is examined numerically for further loss comparison.

  8. Evaluation of CASP8 model quality predictions

    KAUST Repository

    Cozzetto, Domenico

    2009-01-01

    The model quality assessment problem consists in the a priori estimation of the overall and per-residue accuracy of protein structure predictions. Over the past years, a number of methods have been developed to address this issue and CASP established a prediction category to evaluate their performance in 2006. In 2008 the experiment was repeated and its results are reported here. Participants were invited to infer the correctness of the protein models submitted by the registered automatic servers. Estimates could apply to both whole models and individual amino acids. Groups involved in the tertiary structure prediction categories were also asked to assign local error estimates to each predicted residue in their own models and their results are also discussed here. The correlation between the predicted and observed correctness measures was the basis of the assessment of the results. We observe that consensus-based methods still perform significantly better than those accepting single models, similarly to what was concluded in the previous edition of the experiment. © 2009 WILEY-LISS, INC.

  9. Metabolic Network Prediction of Drug Side Effects.

    Science.gov (United States)

    Shaked, Itay; Oberhardt, Matthew A; Atias, Nir; Sharan, Roded; Ruppin, Eytan

    2016-03-23

    Drug side effects levy a massive cost on society through drug failures, morbidity, and mortality cases every year, and their early detection is critically important. Here, we describe the array of model-based phenotype predictors (AMPP), an approach that leverages medical informatics resources and a human genome-scale metabolic model (GSMM) to predict drug side effects. AMPP is substantially predictive (AUC > 0.7) for >70 drug side effects, including very serious ones such as interstitial nephritis and extrapyramidal disorders. We evaluate AMPP's predictive signal through cross-validation, comparison across multiple versions of a side effects database, and co-occurrence analysis of drug side effect associations in scientific abstracts (hypergeometric p value = 2.2e-40). AMPP outperforms a previous biochemical structure-based method in predicting metabolically based side effects (aggregate AUC = 0.65 versus 0.59). Importantly, AMPP enables the identification of key metabolic reactions and biomarkers that are predictive of specific side effects. Taken together, this work lays a foundation for future detection of metabolically grounded side effects during early stages of drug development. PMID:27135366

  10. A New Way to Predict Forecast Skill

    Institute of Scientific and Technical Information of China (English)

    谭季青; 谢正辉; 纪立人

    2003-01-01

    Forecast skill (Anomaly Correlated Coefficient, ACC) is a quantity to show the forecast quality ofthe products of numerical weather forecasting models. Predicting forecast skill, which is the foundationof ensemble forecasting, means submitting products to predict their forecast quality before they are used.Checking the reason is to understand the predictability for the real cases. This kind of forecasting servicehas been put into operational use by statistical methods previously at the National Meteorological Center(NMC), USA (now called the National Center for Environmental Prediction (NCEP)) and European Centerfor Medium-range Weather Forecast (ECMWF). However, this kind of service is far from satisfactorybecause only a single variable is used with the statistical method. In this paper, a new way based onthe Grey Control Theory with multiple predictors to predict forecast skill of forecast products of theT42L9 of the NMC, China Meteorological Administration (CMA) is introduced. The results show: (1)The correlation coefficients between "forecasted" and real forecast skill range from 0.56 to 0.7 at differentseasons during the two-year period. (2) The grey forecasting model GM(1,8) forecasts successfully thehigh peaks, the increasing or decreasing tendency, and the turning points of the change of forecast skill ofcases from 5 January 1990 to 29 February 1992.

  11. Perception range prediction for IR pilot sight

    Science.gov (United States)

    Weiss, A. Robert; Großmann, Peter; Repasi, Endre; Ritt, Gunnar; Wittenstein, Wolfgang

    2008-04-01

    The increasing use of IR pilot sight in helicopters calls for a reliable prediction of perception ranges for a variety of objects, especially those needed for orientation and those posing as a potential hazard, like power poles, masts, isolated trees etc. Since the visibility of objects in the IR depends mainly on the temperature differences between those objects and a given background and only marginally on illumination, range prediction techniques used for the visual range or light-amplified vision are only of very limited use. While range predictions based on the Johnson criterion do offer some insight into expected ranges, the inherently nominal nature of distance estimates thus obtained hampers their use for an actual field-deployable pre-flight consulting procedure. In order to overcome those limitations, long-term simultaneous measurements of relevant objects and background temperatures and weather data were carried out and used for temperature prediction from prevalent weather conditions. Together with a perception model derived from extensive observer experiments based on synthetic images of the UH Tiger Pilot Sight Unit we developed a perception range prediction package which is currently evaluated by the weather service of the Bundeswehr. We will present results from the observer experiments together with the derived perception models. These are then compared to actual perception ranges as obtained from flight experiments.

  12. Gaze location prediction for broadcast football video.

    Science.gov (United States)

    Cheng, Qin; Agrafiotis, Dimitris; Achim, Alin M; Bull, David R

    2013-12-01

    The sensitivity of the human visual system decreases dramatically with increasing distance from the fixation location in a video frame. Accurate prediction of a viewer's gaze location has the potential to improve bit allocation, rate control, error resilience, and quality evaluation in video compression. Commercially, delivery of football video content is of great interest because of the very high number of consumers. In this paper, we propose a gaze location prediction system for high definition broadcast football video. The proposed system uses knowledge about the context, extracted through analysis of a gaze tracking study that we performed, to build a suitable prior map. We further classify the complex context into different categories through shot classification thus allowing our model to prelearn the task pertinence of each object category and build the prior map automatically. We thus avoid the limitation of assigning the viewers a specific task, allowing our gaze prediction system to work under free-viewing conditions. Bayesian integration of bottom-up features and top-down priors is finally applied to predict the gaze locations. Results show that the prediction performance of the proposed model is better than that of other top-down models that we adapted to this context. PMID:23996558

  13. Improving personalized link prediction by hybrid diffusion

    Science.gov (United States)

    Liu, Jin-Hu; Zhu, Yu-Xiao; Zhou, Tao

    2016-04-01

    Inspired by traditional link prediction and to solve the problem of recommending friends in social networks, we introduce the personalized link prediction in this paper, in which each individual will get equal number of diversiform predictions. While the performances of many classical algorithms are not satisfactory under this framework, thus new algorithms are in urgent need. Motivated by previous researches in other fields, we generalize heat conduction process to the framework of personalized link prediction and find that this method outperforms many classical similarity-based algorithms, especially in the performance of diversity. In addition, we demonstrate that adding one ground node that is supposed to connect all the nodes in the system will greatly benefit the performance of heat conduction. Finally, better hybrid algorithms composed of local random walk and heat conduction have been proposed. Numerical results show that the hybrid algorithms can outperform other algorithms simultaneously in all four adopted metrics: AUC, precision, recall and hamming distance. In a word, this work may shed some light on the in-depth understanding of the effect of physical processes in personalized link prediction.

  14. Numerical prediction experiment on Typhoon Maggie (9903)

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    The movement of Typhoon Maggie (9903) in June 1999 is one of the rare cases ever seen in the history. At 00U on June 6 Maggie was located at about 70 km to the southwest of Taiwan. When it arrived at the coastal region of Shanwei City (22.8°N, 116.5°E), it turned suddenly to move south westward along the southern China coastal line. On June 7 Maggie finally turned to move northward,making landfall to the north of Shangchuan Island. The experimental numerical prediction system on typhoon movement that was designed based on MM5 is proved quite successful for the 48h prediction of Maggie' s movement and rainfall. The mean prediction error of typhoon track is 81 km for 0~24 h and 74 km for 24~48 h.The location of typhoon center in the initial field of the model is approximately 100 km away from the actual observations. In order to modify the location of typhoon center, a bogus typhoon was introduced into the model and the prediction of typhoon track was improved in 0~24 h time interval. But the prediction error was enlarged in 24~36 h.We also performed a sensitivity experiment of changing the land of southern China into the ocean.It is found that the orientation of South China coastal line and the topography have no obvious effect on the movement of Typhoon Maggie.

  15. Modelling the predictive performance of credit scoring

    Directory of Open Access Journals (Sweden)

    Shi-Wei Shen

    2013-02-01

    Full Text Available Orientation: The article discussed the importance of rigour in credit risk assessment.Research purpose: The purpose of this empirical paper was to examine the predictive performance of credit scoring systems in Taiwan.Motivation for the study: Corporate lending remains a major business line for financial institutions. However, in light of the recent global financial crises, it has become extremely important for financial institutions to implement rigorous means of assessing clients seeking access to credit facilities.Research design, approach and method: Using a data sample of 10 349 observations drawn between 1992 and 2010, logistic regression models were utilised to examine the predictive performance of credit scoring systems.Main findings: A test of Goodness of fit demonstrated that credit scoring models that incorporated the Taiwan Corporate Credit Risk Index (TCRI, micro- and also macroeconomic variables possessed greater predictive power. This suggests that macroeconomic variables do have explanatory power for default credit risk.Practical/managerial implications: The originality in the study was that three models were developed to predict corporate firms’ defaults based on different microeconomic and macroeconomic factors such as the TCRI, asset growth rates, stock index and gross domestic product.Contribution/value-add: The study utilises different goodness of fits and receiver operator characteristics during the examination of the robustness of the predictive power of these factors.

  16. Predicting Resistance Mutations Using Protein Design Algorithms

    Energy Technology Data Exchange (ETDEWEB)

    Frey, K.; Georgiev, I; Donald, B; Anderson, A

    2010-01-01

    Drug resistance resulting from mutations to the target is an unfortunate common phenomenon that limits the lifetime of many of the most successful drugs. In contrast to the investigation of mutations after clinical exposure, it would be powerful to be able to incorporate strategies early in the development process to predict and overcome the effects of possible resistance mutations. Here we present a unique prospective application of an ensemble-based protein design algorithm, K*, to predict potential resistance mutations in dihydrofolate reductase from Staphylococcus aureus using positive design to maintain catalytic function and negative design to interfere with binding of a lead inhibitor. Enzyme inhibition assays show that three of the four highly-ranked predicted mutants are active yet display lower affinity (18-, 9-, and 13-fold) for the inhibitor. A crystal structure of the top-ranked mutant enzyme validates the predicted conformations of the mutated residues and the structural basis of the loss of potency. The use of protein design algorithms to predict resistance mutations could be incorporated in a lead design strategy against any target that is susceptible to mutational resistance.

  17. Estimating Predictability Redundancy and Surrogate Data Method

    CERN Document Server

    Pecen, L

    1995-01-01

    A method for estimating theoretical predictability of time series is presented, based on information-theoretic functionals---redundancies and surrogate data technique. The redundancy, designed for a chosen model and a prediction horizon, evaluates amount of information between a model input (e.g., lagged versions of the series) and a model output (i.e., a series lagged by the prediction horizon from the model input) in number of bits. This value, however, is influenced by a method and precision of redundancy estimation and therefore it is a) normalized by maximum possible redundancy (given by the precision used), and b) compared to the redundancies obtained from two types of the surrogate data in order to obtain reliable classification of a series as either unpredictable or predictable. The type of predictability (linear or nonlinear) and its level can be further evaluated. The method is demonstrated using a numerically generated time series as well as high-frequency foreign exchange data and the theoretical ...

  18. The 1986-87 atomic mass predictions

    Science.gov (United States)

    Haustein, P. E.

    1987-12-01

    A project to perform a comprehensive update of the atomic mass predictions has recently been concluded and will be published shortly in Atomic Data and Nuclear Data Tables. The project evolved from an ongoing comparison between available mass predictions and reports of newly measured masses of isotopes throughout the mass surface. These comparisons have highlighted a variety of features in current mass models which are responsible for predictions that diverge from masses determined experimentally. The need for a comprehensive update of the atomic mass predictions was therefore apparent and the project was organized and began at the last mass conference (AMCO-VII). Project participants included: Pape and Anthony; Dussel, Caurier and Zuker; Möller and Nix; Möller, Myers, Swiatecki and Treiner; Comay, Kelson, and Zidon; Satpathy and Nayak; Tachibana, Uno, Yamada and Yamada; Spanier and Johansson; Jänecke and Masson; and Wapstra, Audi and Hoekstra. An overview of the new atomic mass predictions may be obtained by written request.

  19. Predictive aging results in radiation environments

    Science.gov (United States)

    Gillen, Kenneth T.; Clough, Roger L.

    1993-06-01

    We have previously derived a time-temperature-dose rate superposition methodology, which, when applicable, can be used to predict polymer degradation versus dose rate, temperature and exposure time. This methodology results in predictive capabilities at the low dose rates and long time periods appropriate, for instance, to ambient nuclear power plant environments. The methodology was successfully applied to several polymeric cable materials and then verified for two of the materials by comparisons of the model predictions with 12 year, low-dose-rate aging data on these materials from a nuclear environment. In this paper, we provide a more detailed discussion of the methodology and apply it to data obtained on a number of additional nuclear power plant cable insulation (a hypalon, a silicone rubber and two ethylene-tetrafluoroethylenes) and jacket (a hypalon) materials. We then show that the predicted, low-dose-rate results for our materials are in excellent agreement with long-term (7-9 year) low-dose-rate results recently obtained for the same material types actually aged under bnuclear power plant conditions. Based on a combination of the modelling and long-term results, we find indications of reasonably similar degradation responses among several different commercial formulations for each of the following "generic" materials: hypalon, ethylene-tetrafluoroethylene, silicone rubber and PVC. If such "generic" behavior can be further substantiated through modelling and long-term results on additional formulations, predictions of cable life for other commercial materials of the same generic types would be greatly facilitated.

  20. Predicting Parkinson's disease - why, when, and how?

    Science.gov (United States)

    Postuma, R B; Montplaisir, J

    2009-12-01

    Parkinson's disease (PD) is a progressive disorder with a presymptomatic interval; that is, there is a period during which the pathologic process has begun, but motor signs required for the clinical diagnosis are absent. There is considerable interest in discovering markers to diagnose this preclinical stage. Current predictive marker development stems mainly from two principles; first, that pathologic processes occur in lower brainstem regions before substantia nigra involvement and second, that redundancy and compensatory responses cause symptoms to emerge only after advanced degeneration. Decreased olfaction has recently been demonstrated to predict PD in prospective pathologic studies, although the lead time may be relatively short and the positive predictive value and specificity are low. Screening patients for depression and personality changes, autonomic symptoms, subtle motor dysfunction on quantitative testing, sleepiness and insomnia are other potential simple markers. More invasive measures such as detailed autonomic testing, cardiac MIBG-scintigraphy, transcranial ultrasound, and dopaminergic functional imaging may be especially useful in those at high risk or for further defining risk in those identified through primary screening. Despite intriguing leads, direct testing of preclinical markers has been limited, mainly because there is no reliable way to identify preclinical disease. Idiopathic RBD is characterized by loss of normal atonia with REM sleep. Approximately 50% of affected individuals will develop PD or dementia within 10 years. This provides an unprecedented opportunity to test potential predictive markers before clinical disease onset. The results of marker testing in idiopathic RBD with its implications for disease prediction will be detailed. PMID:20082967