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Sample records for anulus fibrosus predicted

  1. Elastic fibers in the anulus fibrosus of the dog intervertebral disc.

    Science.gov (United States)

    Johnson, E F; Caldwell, R W; Berryman, H E; Miller, A; Chetty, K

    1984-01-01

    A light microscopic investigation of the anulus fibrosus in cervical intervertebral discs of the dog was conducted to ascertain the arrangement and distribution of elastic fibers. Elastic fibers were observed in all lamellae of the anulus fibrosus. However, collagenous fibers were the predominant type of connective tissue fiber, and elastic fibers were randomly dispersed among them. Intralamellar (collagenous and elastic) fibers were vertically and obliquely oriented in both superficial and deep lamellae of the anulus fibrosus. All intralamellar fibers were densely and regularly arranged in superficial lamellae, but they were more loosely organized in deep lamellae. A narrow border of interlamellar, elastic fibers was observed between broader, contiguous lamellae in the superficial zone of the anulus fibrosus. Interlamellar elastic fibers wer vertically and obliquely arranged in superficial lamellae; however, they were radially oriented in deep lamellae. The deepest lamella of the anulus fibrosus consisted of a loose, three-dimensional network of intermeshing collagenous and elastic fibers. These observations suggest that elastic fibers are integral components of the articular and shock absorption mechanisms of the anulus fibrosus, and the cervical intervertebral disc of the dog is a suitable model for experimental investigation of the role of elastic fibers in intervertebral disc herniation. PMID:6720244

  2. Mechanisms for mechanical damage in the intervertebral disc annulus fibrosus.

    Science.gov (United States)

    Iatridis, J C James C; ap Gwynn, Iolo

    2004-08-01

    Intervertebral disc degeneration results in disorganization of the laminate structure of the annulus that may arise from mechanical microfailure. Failure mechanisms in the annulus were investigated using composite lamination theory and other analyses to calculate stresses in annulus layers, interlaminar shear stress, and the region of stress concentration around a fiber break. Scanning electron microscopy (SEM) was used to evaluate failure patterns in the annulus and evaluate novel structural features of the disc tissue. Stress concentrations in the annulus due to an isolated fiber break were localized to approximately 5 microm away from the break, and only considered a likely cause of annulus fibrosus failure (i.e., radial tears in the annulus) under extreme loading conditions or when collagen damage occurs over a relatively large region. Interlaminar shear stresses were calculated to be relatively large, to increase with layer thickness (as reported with degeneration), and were considered to be associated with propagation of circumferential tears in the annulus. SEM analysis of intervertebral disc annulus fibrosus tissue demonstrated a clear laminate structure, delamination, matrix cracking, and fiber failure. Novel structural features noted with SEM also included the presence of small tubules that appear to run along the length of collagen fibers in the annulus and a distinct collagenous structure representative of a pericellular matrix in the nucleus region. PMID:15212921

  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. Annulus fibrosus calcification in the cervical spine: Radiologic-pathologic correlation

    International Nuclear Information System (INIS)

    Intervertebral disc calcification can be secondary to a variety of pathologic processes including some of the arthritidies, metabolic diseases, and trauma. The annulus fibrosus is the most commonly calcified component and may mimic vertebral body fracture, limbus vertebra, or a persistent ring apophysis. We describe two young patients who developed calcification in the anterior annulus fibrosus and present radiologic-pathologic correlation in this condition in another case. This calcification may actually be secondary to subclinical or chronic stress on the involved intervertebral disc. (orig.)

  5. 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.

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

    NARCIS (Netherlands)

    Blanquer, Sebastien B. G.; Sharifi, Shahriar; Grijpma, Dirk 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. 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.

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

    Science.gov (United States)

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

    2013-11-01

    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) networks with shape-memory properties have been evaluated in order to prepare biodegradable AF closure devices that can be implanted minimally invasively. Four different macromers with (D,L-lactide) to trimethylene carbonate (DLLA:TMC) molar ratios of 80:20, 70:30, 60:40 and 40:60 with terminal methacrylate groups and molecular weights of approximately 30 kg mol(-1) were used to prepare the networks by photo-crosslinking. The mechanical properties of the samples and their shape-memory properties were determined at temperatures of 0 °C and 40 °C by tensile tests- and cyclic, thermo-mechanical measurements. At 40 °C all networks showed rubber-like behavior and were flexible with elastic modulus values of 1.7-2.5 MPa, which is in the range of the modulus values of human annulus fibrosus tissue. The shape-memory characteristics of the networks were excellent with values of the shape-fixity and the shape-recovery ratio higher than 98 and 95%, respectively. The switching temperatures were between 10 and 39 °C. In vitro culture and qualitative immunocytochemistry of human annulus fibrosus cells on shape-memory films with DLLA:TMC molar ratios of 60:40 showed very good ability of the networks to support the adhesion and growth of human AF cells. When the polymer network films were coated by adsorption of fibronectin, cell attachment, cell spreading, and extracellular matrix production was further improved. Annulus fibrosus closure devices were prepared from these AF cell-compatible materials by photo-polymerizing the reactive precursors in a mold. Insertion of the multifunctional implant in the disc of a cadaveric canine spine showed that these shape-memory devices could be

  9. Radial tensile properties of the lumbar annulus fibrosus are site and degeneration dependent.

    Science.gov (United States)

    Fujita, Y; Duncan, N A; Lotz, J C

    1997-11-01

    We conducted an in vitro study of the radial tensile properties of the annulus fibrosus. The stress-strain response was nonlinear, with a mean tangent modulus of 0.19 MPa at zero strain and 0.47 MPa at 70% of the yield strain. We also investigated whether these properties varied as a function of location within the disc and degree of degeneration. Specimens harvested from the middle layers of the annulus were stiffer and failed at smaller strain magnitudes than those from the inner or outer annulus (analysis of covariance, p stress compared with normal discs. Similarity between our data and those reported for the annulus in compression suggests that these values reflect the material behavior of the interlaminar matrix and are an order of magnitude smaller than values used in previous analytical representations of this tissue. We expect that awareness of these data will result in improved understanding of the physical behavior and tolerance to injury of the annulus fibrosus. PMID:9497805

  10. Role of biomolecules on annulus fibrosus micromechanics: effect of enzymatic digestion on elastic and failure properties.

    Science.gov (United States)

    Isaacs, Jessica L; Vresilovic, Edward; Sarkar, Sumona; Marcolongo, Michele

    2014-12-01

    Uniaxial tension was applied to selectively digested single lamellar human cadaveric annulus fibrosus specimens to investigate the role of different biomolecules in annular biomechanics. Single layered and inter-lamellar annulus fibrosus samples were obtained from 10 isolated cadaveric lumbar intervertebral discs in one of four orientations: longitudinal, transverse, radial, and circumferential. Within each orientation the samples were subjected to a selective enzymatic digestion protocol with collagenase, elastase, chondroitinase ABC, or 1× Phosphate Buffered Saline. Uniaxial tensile tests were performed to failure at a strain rate of 0.005s(-1). Failure stress and strain, and elastic moduli were compared among the digested conditions. The collagenase- and elastase-treated groups had the most significant effect on the mechanical properties among the orientation groups, decreasing the failure stress for both interlaminar and intralaminar groups. Collagenase-treated groups showed an increase in the failure strain following enzymatic digestion for the intralaminar groups and one interlaminar testing direction (circumferential). The chondroitinase ABC-treated group only had a significant impact on the single layer orientations, decreasing the failure stress and strain (intralaminar group). The digested properties described provide insights into the laminar mechanical behavior and the role of the molecular components to the annular mechanical behavior. Understanding annular mechanics may prove insightful in diagnosis, prevention and repair of debilitating intervertebral disc disorders and manufacturing of tissue-engineered annulus. PMID:25212387

  11. 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

  12. Functional probe for annulus fibrosus-targeted intervertebral disc degeneration imaging.

    Science.gov (United States)

    Kim, Hye-Yeong; Mcclincy, Michael; Vo, Nam V; Sowa, Gwendolyn A; Kang, James D; Bai, Mingfeng

    2013-10-01

    Intervertebral disc degeneration (IDD) is closely associated with low back pain. Typically nonsurgical treatment of IDD is the most effective when detected early. As such, establishing reliable imaging methods for the early diagnosis of disc degeneration is critical. The cellular and tissue localization of a facile functional fluorescent probe, HYK52, that labels disc annulus fibrosus is reported. HYK52 was synthesized with high yield and purity via a two-step chemical reaction. Rabbit disc cell studies and ex vivo tissue staining images indicated intracellular localization and intervertebral disc (IVD) tissue binding of HYK52 with negligible cytotoxicity. Moreover, HYK52 is purposefully designed with a functional terminal carboxyl group to allow for coupling with various signaling molecules for multimodal imaging applications. These results suggest that this IVD-targeted probe may have great potential in early diagnosis of IDD. PMID:23839314

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

    Science.gov (United States)

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

    2015-02-01

    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, restores disc height, reduces further disc degeneration and enhances self-repair capacities is an unmet clinical need. In this study, a poly(trimethylene carbonate) (PTMC) scaffold seeded with human bone marrow derived mesenchymal stromal cells (MSCs) and covered with a poly(ester-urethane) (PU) membrane was assessed for AF rupture repair in a bovine organ culture annulotomy model under dynamic load for 14 days. PTMC scaffolds combined with the sutured PU membrane restored disc height of annulotomized discs and prevented herniation of nucleus pulposus (NP) tissue. Implanted MSCs showed an up-regulated gene expression of type V collagen, a potential AF marker, indicating in situ differentiation capability. Furthermore, MSCs delivered within PTMC scaffolds induced an up-regulation of anabolic gene expression and down-regulation of catabolic gene expression in adjacent native disc tissue. In conclusion, the combined biomaterial and cellular approach has the potential to hinder herniation of NP tissue, stabilize disc height, and positively modulate cell phenotype of native disc tissue. PMID:25542789

  14. 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.

  15. Photobiomodulation on human annulus fibrosus cells during the intervertebral disk degeneration: extracellular matrix-modifying enzymes.

    Science.gov (United States)

    Hwang, Min Ho; Kim, Kyoung Soo; Yoo, Chang Min; Shin, Jae Hee; Nam, Hyo Geun; Jeong, Jin Su; Kim, Joo Han; Lee, Kwang Ho; Choi, Hyuk

    2016-05-01

    Destruction of extracellular matrix (ECM) leads to degeneration of the intervertebral disk (IVD), which is a major contributor to many spine disorders. IVD degeneration is induced by pro-inflammatory cytokines, such as tumor necrosis factor-alpha (TNF-α) and interleukin-1 beta (IL-1β), which are secreted by immune cells, including macrophages and neutrophils. The cytokines modulate ECM-modifying enzymes such as matrix metalloproteinases (MMPs) and tissue inhibitors of metalloproteinases (TIMPs) in human annulus fibrosus (AF) cells. The resulting imbalance in catabolic and anabolic enzymes can cause generalized back, neck, and low back pain (LBP). Photobiomodulation (PBM) is known to regulate inflammatory responses and wound healing. The aim of this study was to mimic the degenerative IVD microenvironment, and to investigate the effect of a variety of PBM conditions (wavelength: 635, 525, and 470 nm; energy density: 16, 32, and 64 J/cm(2)) on the production of ECM-modifying-enzymes by AF cells under degenerative conditions induced by macrophage-conditioned medium (MCM), which contains pro-inflammatory cytokines such as TNF-α and IL-β secreted by macrophage during the development of intervertebral disk inflammation. We showed that the MCM-stimulated AF cells express imbalanced ratios of TIMPs (TIMP-1 and TIMP-2) and MMPs (MMP-1 and MMP-3). PBM selectively modulated the production of ECM-modifying enzymes in AF cells. These results suggest that PBM can be a therapeutic tool for degenerative IVD disorders. PMID:26987527

  16. 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...

  17. 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.

  18. 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

  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. 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.

  1. 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

  2. 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.

  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

    OpenAIRE

    Woollard, W.J.

    2006-01-01

    In this chapter we will look at the ways in which you can use ICT in the classroom to support hypothesis and prediction and how modern technology is enabling: pattern seeking, extrapolation and interpolation to meet the challenges of the information explosion of the 21st century.

  5. 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...

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

    OpenAIRE

    Weiner Bradley K; Patel Rikin

    2008-01-01

    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. Me...

  7. Climate prediction and predictability

    Science.gov (United States)

    Allen, Myles

    2010-05-01

    Climate prediction is generally accepted to be one of the grand challenges of the Geophysical Sciences. What is less widely acknowledged is that fundamental issues have yet to be resolved concerning the nature of the challenge, even after decades of research in this area. How do we verify or falsify a probabilistic forecast of a singular event such as anthropogenic warming over the 21st century? How do we determine the information content of a climate forecast? What does it mean for a modelling system to be "good enough" to forecast a particular variable? How will we know when models and forecasting systems are "good enough" to provide detailed forecasts of weather at specific locations or, for example, the risks associated with global geo-engineering schemes. This talk will provide an overview of these questions in the light of recent developments in multi-decade climate forecasting, drawing on concepts from information theory, machine learning and statistics. I will draw extensively but not exclusively from the experience of the climateprediction.net project, running multiple versions of climate models on personal computers.

  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. 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...... provides a comprehensive review and classification of the literature related to the topic of Prediction Markets. Overall, 316 relevant articles, published in the timeframe from 2007 through 2013, were identified and assigned to a herein presented classification scheme, differentiating between descriptive...... works, articles of theoretical nature, application-oriented studies and articles dealing with the topic of law and policy. The analysis of the research results reveals that more than half of the literature pool deals with the application and actual function tests of Prediction Markets. The results are...

  11. 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.)

  12. 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....

  13. Making detailed predictions makes (some) predictions worse

    Science.gov (United States)

    Kelly, Theresa F.

    In this paper, we investigate whether making detailed predictions about an event makes other predictions worse. Across 19 experiments, 10,895 participants, and 415,960 predictions about 724 professional sports games, we find that people who made detailed predictions about sporting events (e.g., how many hits each baseball team would get) made worse predictions about more general outcomes (e.g., which team would win). We rule out that this effect is caused by inattention or fatigue, thinking too hard, or a differential reliance on holistic information about the teams. Instead, we find that thinking about game-relevant details before predicting winning teams causes people to give less weight to predictive information, presumably because predicting details makes information that is relatively useless for predicting the winning team more readily accessible in memory and therefore incorporated into forecasts. Furthermore, we show that this differential use of information can be used to predict what kinds of games will and will not be susceptible to the negative effect of making detailed predictions.

  14. Downstream prediction using a nonlinear prediction method

    Science.gov (United States)

    Adenan, N. H.; Noorani, M. S. M.

    2013-11-01

    The estimation of river flow is significantly related to the impact of urban hydrology, as this could provide information to solve important problems, such as flooding downstream. The nonlinear prediction method has been employed for analysis of four years of daily river flow data for the Langat River at Kajang, Malaysia, which is located in a downstream area. The nonlinear prediction method involves two steps; namely, the reconstruction of phase space and prediction. The reconstruction of phase space involves reconstruction from a single variable to the m-dimensional phase space in which the dimension m is based on optimal values from two methods: the correlation dimension method (Model I) and false nearest neighbour(s) (Model II). The selection of an appropriate method for selecting a combination of preliminary parameters, such as m, is important to provide an accurate prediction. From our investigation, we gather that via manipulation of the appropriate parameters for the reconstruction of the phase space, Model II provides better prediction results. In particular, we have used Model II together with the local linear prediction method to achieve the prediction results for the downstream area with a high correlation coefficient. In summary, the results show that Langat River in Kajang is chaotic, and, therefore, predictable using the nonlinear prediction method. Thus, the analysis and prediction of river flow in this area can provide river flow information to the proper authorities for the construction of flood control, particularly for the downstream area.

  15. Learning predictive clustering rules

    OpenAIRE

    Ženko, Bernard; Džeroski, Sašo; Struyf, Jan

    2005-01-01

    The two most commonly addressed data mining tasks are predictive modelling and clustering. Here we address the task of predictive clustering, which contains elements of both and generalizes them to some extent. We propose a novel approach to predictive clustering called predictive clustering rules, present an initial implementation and its preliminary experimental evaluation.

  16. 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...

  17. Predictability of social interactions

    OpenAIRE

    Xu, Kevin S.

    2013-01-01

    The ability to predict social interactions between people has profound applications including targeted marketing and prediction of information diffusion and disease propagation. Previous work has shown that the location of an individual at any given time is highly predictable. This study examines the predictability of social interactions between people to determine whether interaction patterns are similarly predictable. I find that the locations and times of interactions for an individual are...

  18. Numerical earthquake prediction

    International Nuclear Information System (INIS)

    Can earthquakes be predicted? How should people overcome the difficulties encountered in the study of earthquake prediction? This issue can take inspiration from the experiences of weather forecast. Although weather forecasting took a period of about half a century to advance from empirical to numerical forecast, it has achieved significant success. A consensus has been reached among the Chinese seismological community that earthquake prediction must also develop from empirical forecasting to physical prediction. However, it is seldom mentioned that physical prediction is characterized by quantitatively numerical predictions based on physical laws. This article discusses five key components for numerical earthquake prediction and their current status. We conclude that numerical earthquake prediction should now be put on the planning agenda and its roadmap designed, seismic stations should be deployed and observations made according to the needs of numerical prediction, and theoretical research should be carried out. (authors)

  19. 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

  20. Optimal predictive model selection

    OpenAIRE

    Barbieri, Maria Maddalena; Berger, James O.

    2004-01-01

    Often the goal of model selection is to choose a model for future prediction, and it is natural to measure the accuracy of a future prediction by squared error loss. Under the Bayesian approach, it is commonly perceived that the optimal predictive model is the model with highest posterior probability, but this is not necessarily the case. In this paper we show that, for selection among normal linear models, the optimal predictive model is often the median probability model, which is defined a...

  1. Predictive software design measures

    OpenAIRE

    Love, Randall James

    1994-01-01

    This research develops a set of predictive measures enabling software testers and designers to identify and target potential problem areas for additional and/or enhanced testing. Predictions are available as early in the design process as requirements allocation and as late as code walk-throughs. These predictions are based on characteristics of the design artifacts prior to coding. Prediction equations are formed at established points in the software development process...

  2. 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.

  3. Predicting Predictable about Natural Catastrophic Extremes

    Science.gov (United States)

    Kossobokov, Vladimir

    2015-04-01

    By definition, an extreme event is rare one in a series of kindred phenomena. Usually (e.g. in Geophysics), it implies investigating a small sample of case-histories with a help of delicate statistical methods and data of different quality, collected in various conditions. Many extreme events are clustered (far from independent) and follow fractal or some other "strange" distribution (far from uniform). Evidently, such an "unusual" situation complicates search and definition of reliable precursory behaviors to be used for forecast/prediction purposes. Making forecast/prediction claims reliable and quantitatively probabilistic in the frames of the most popular objectivists' viewpoint on probability requires a long series of "yes/no" forecast/prediction outcomes, which cannot be obtained without an extended rigorous test of the candidate method. The set of errors ("success/failure" scores and space-time measure of alarms) and other information obtained in such a control test supplies us with data necessary to judge the candidate's potential as a forecast/prediction tool and, eventually, to find its improvements. This is to be done first in comparison against random guessing, which results confidence (measured in terms of statistical significance). Note that an application of the forecast/prediction tools could be very different in cases of different natural hazards, costs and benefits that determine risks, and, therefore, requires determination of different optimal strategies minimizing reliable estimates of realistic levels of accepted losses. In their turn case specific costs and benefits may suggest a modification of the forecast/prediction tools for a more adequate "optimal" application. Fortunately, the situation is not hopeless due to the state-of-the-art understanding of the complexity and non-linear dynamics of the Earth as a Physical System and pattern recognition approaches applied to available geophysical evidences, specifically, when intending to predict

  4. Predictable or not predictable? The MOV question

    International Nuclear Information System (INIS)

    Over the past 8 years, the nuclear industry has struggled to understand the dynamic phenomena experienced during motor-operated valve (MOV) operation under differing flow conditions. For some valves and designs, their operational functionality has been found to be predictable; for others, unpredictable. Although much has been accomplished over this period of time, especially on modeling valve dynamics, the unpredictability of many valves and designs still exists. A few valve manufacturers are focusing on improving design and fabrication techniques to enhance product reliability and predictability. However, this approach does not address these issues for installed and inpredictable valves. This paper presents some of the more promising techniques that Wyle Laboratories has explored with potential for transforming unpredictable valves to predictable valves and for retrofitting installed MOVs. These techniques include optimized valve tolerancing, surrogated material evaluation, and enhanced surface treatments

  5. 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...

  6. 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.

  7. Predicting transformers oil parameters

    OpenAIRE

    Shaban, K.; El-Hag, A.; Matveev, A.

    2009-01-01

    In this paper different configurations of artificial neural networks are applied to predict various transformers oil parameters. The prediction is performed through modeling the relationship between the transformer insulation resistance extracted from the Megger test and the breakdown strength, interfacial tension, acidity and the water content of the transformers oil. The process of predicting these oil parameters statuses is carried out using two different configurations of neural networks....

  8. Is Suicide Predictable?

    OpenAIRE

    Asmaee, S; Mosavi, N; R Abdul Rashid; H Habi; Seghatoleslam, T; Naseri, A.

    2012-01-01

    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...

  9. '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...

  10. Predicting the MJO

    Science.gov (United States)

    Hendon, H.

    2003-04-01

    Extended range prediction of the Madden Julian Oscillation (MJO) and seasonal prediction of MJO activity are reviewed. Skillful prediction of individual MJO events offers the possibility of forecasting increased risk of cyclone development throughout the global tropics, altered risk of extreme rainfall events in both tropics and extratropics, and displacement of storm tracks with 3-4 week lead times. The level of MJO activity within a season, which affects the mean intensity of the Australian summer monsoon and possibly the evolution of ENSO, may be governed by variations of sea surface temperature that are predictable with lead times of a few seasons. The limit of predictability for individual MJO events is unknown. Empirical-statistical schemes are skillful out to about 3 weeks and have better skill than dynamical forecast models at lead times longer than about 5 days. The dynamical forecast models typically suffer from a poor representation (or complete lack) of the MJO and large initial error. They are better used to ascertain the global impacts of the lack of the MJO rather than for determination of the limit of predictability. Dynamical extended range prediction within a GCM that has a good representation of the MJO indicates potential skill comparable to the empirical schemes. Examples of operational extended range prediction with POAMA, the new coupled seasonal forecast model at the Bureau of Meteorology that also reasonably simulates the MJO, will be presented.

  11. 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.

  12. Zephyr - the prediction models

    DEFF Research Database (Denmark)

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

    2001-01-01

    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. 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...

  14. 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...

  15. Error mode prediction.

    Science.gov (United States)

    Hollnagel, E; Kaarstad, M; Lee, H C

    1999-11-01

    The study of accidents ('human errors') has been dominated by efforts to develop 'error' taxonomies and 'error' models that enable the retrospective identification of likely causes. In the field of Human Reliability Analysis (HRA) there is, however, a significant practical need for methods that can predict the occurrence of erroneous actions--qualitatively and quantitatively. The present experiment tested an approach for qualitative performance prediction based on the Cognitive Reliability and Error Analysis Method (CREAM). Predictions of possible erroneous actions were made for operators using different types of alarm systems. The data were collected as part of a large-scale experiment using professional nuclear power plant operators in a full scope simulator. The analysis showed that the predictions were correct in more than 70% of the cases, and also that the coverage of the predictions depended critically on the comprehensiveness of the preceding task analysis. PMID:10582035

  16. 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.

  17. Evaluating prediction uncertainty

    International Nuclear Information System (INIS)

    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

  18. 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...

  19. Is Time Predictability Quantifiable?

    DEFF Research Database (Denmark)

    Schoeberl, Martin

    2012-01-01

    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-case execu......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......-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...

  20. Ground motion predictions

    International Nuclear Information System (INIS)

    Nuclear generated ground motion is defined and then related to the physical parameters that cause it. Techniques employed for prediction of ground motion peak amplitude, frequency spectra and response spectra are explored, with initial emphasis on the analysis of data collected at the Nevada Test Site (NTS). NTS postshot measurements are compared with pre-shot predictions. Applicability of these techniques to new areas, for example, Plowshare sites, must be questioned. Fortunately, the Atomic Energy Commission is sponsoring complementary studies to improve prediction capabilities primarily in new locations outside the NTS region. Some of these are discussed in the light of anomalous seismic behavior, and comparisons are given showing theoretical versus experimental results. In conclusion, current ground motion prediction techniques are applied to events off the NTS. Predictions are compared with measurements for the event Faultless and for the Plowshare events, Gasbuggy, Cabriolet, and Buggy I. (author)

  1. 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

  2. Predicting geomagnetic activity indices

    International Nuclear Information System (INIS)

    Complete text of publication follows. Magnetically active times, e.g., Kp > 5, are notoriously difficult to predict, precisely the times when such predictions are crucial to the space weather users. Taking advantage of the routinely available solar wind measurements at Lagrangian point (L1) and nowcast Kps, Kp and Dst forecast models based on neural networks were developed with the focus on improving the forecast for active times. To satisfy different needs and operational constraints, three models were developed: (1) a model that inputs nowcast Kp and solar wind parameters and predicts Kp 1 hr ahead; (2) a model with the same input as model 1 and predicts Kp 4 hr ahead; and (3) a model that inputs only solar wind parameters and predicts Kp 1 hr ahead (the exact prediction lead time depends on the solar wind speed and the location of the solar wind monitor.) Extensive evaluations of these models and other major operational Kp forecast models show that, while the new models can predict Kps more accurately for all activities, the most dramatic improvements occur for moderate and active times. Similar Dst models were developed. Information dynamics analysis of Kp, suggests that geospace is more dominated by internal dynamics near solar minimum than near solar maximum, when it is more directly driven by external inputs, namely solar wind and interplanetary magnetic field (IMF).

  3. 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.

  4. 3D segmentation of annulus fibrosus and nucleus pulposus from T2-weighted magnetic resonance images

    International Nuclear Information System (INIS)

    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. (paper)

  5. 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 ...

  6. 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

  7. 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.

  8. Repair, regenerative and supportive therapies of the annulus fibrosus: achievements and challenges

    OpenAIRE

    Bron, J.L.; Helder, M N; Meisel, H. J.; Royen, Van, Paul; Smit, T. H.

    2009-01-01

    Lumbar discectomy is a very effective therapy for neurological decompression in patients suffering from sciatica due to hernia nuclei pulposus. However, high recurrence rates and persisting post-operative low back pain in these patients require serious attention. In the past decade, tissue engineering strategies have been developed mainly targeted to the regeneration of the nucleus pulposus (NP) of the intervertebral disc. Accompanying techniques that deal with the damaged annulus fibrous are...

  9. 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...

  10. 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...

  11. Predicted value of $0 \\, \

    CERN Document Server

    Maedan, Shinji

    2016-01-01

    Assuming that the lightest neutrino mass $ m_0 $ is measured, we study the influence of error of the measured $ m_0 $ on the uncertainty of the predicted value of the neutrinoless double beta decay ($0 \\, \

  12. 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...

  13. 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.

  14. Nuclear level density predictions

    OpenAIRE

    Bucurescu Dorel; von Egidy Till

    2015-01-01

    Simple formulas depending only on nuclear masses were previously proposed for the parameters of the Back-Shifted Fermi Gas (BSFG) model and of the Constant Temperature (CT) model of the nuclear level density, respectively. They are now applied for the prediction of the level density parameters of all nuclei with available masses. Both masses from the new 2012 mass table and from different models are considered and the predictions are discussed in connection with nuclear regions most affected ...

  15. Predictive graph mining

    OpenAIRE

    Karwath, Andreas; De Raedt, Luc

    2004-01-01

    Graph mining approaches are extremely popular and effective in molecular databases. The vast majority of these approaches first derive interesting, i.e. frequent, patterns and then use these as features to build predictive models. Rather than building these models in a two step indirect way, the SMIREP system introduced in this paper, derives predictive rule models from molecular data directly. SMIREP combines the SMILES and SMARTS representation languages that are popular in computational ch...

  16. 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.

  17. 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.

  18. 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...

  19. 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 are not more accurate than the simpler forecasts based on a historical timeseries of earnings. Secondly, the dissertation shows how accounting standards affect analysts’ earnings predictions. Accounting conservatism contributes to a more volatile earnings process, which lowers the accuracy of...... analysts’ earnings forecasts. Furthermore, the dissertation shows how the stock market’s reaction to the disclosure of information about corporate earnings depends on how well corporate earnings can be predicted. The dissertation indicates that the stock market’s reaction to the disclosure of earnings...

  20. Neurological abnormalities predict disability

    DEFF Research Database (Denmark)

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

    2014-01-01

    To investigate the role of neurological abnormalities and magnetic resonance imaging (MRI) lesions in predicting global functional decline in a cohort of initially independent-living elderly subjects. The Leukoaraiosis And DISability (LADIS) Study, involving 11 European centres, was primarily aimed...... at evaluating age-related white matter changes (ARWMC) as an independent predictor of the transition to disability (according to Instrumental Activities of Daily Living scale) or death in independent elderly subjects that were followed up for 3 years. At baseline, a standardized neurological examination...... abnormality independently predicted transition to disability or death [HR (95 % CI) 1.53 (1.01-2.34)]. The hazard increased with increasing number of abnormalities. Among MRI lesions, only ARWMC of severe grade independently predicted disability or death [HR (95 % CI) 2.18 (1.37-3.48)]. In our cohort...

  1. 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)

  2. 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...... prediction, so we have investigated the use of velocity data to predict permeability. The compressional velocity fromwireline logs and core plugs of the chalk reservoir in the South Arne field, North Sea, has been used for this study. We compared various methods of permeability prediction from velocities....... The relationships between permeability and porosity from core data were first examined using Kozeny’s equation. The data were analyzed for any correlations to the specific surface of the grain, Sg, and to the hydraulic property defined as the flow zone indicator (FZI). These two methods use two...

  3. 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.

  4. 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.

  5. Epitope prediction methods

    DEFF Research Database (Denmark)

    Karosiene, Edita

    introduces the NetMHCIIpan-3.0 predictor based on artificial neural networks, which is capable of giving binding affinities to any human MHC class II molecule. Chapter 4 of this thesis gives an overview of bioinformatics tools developed by the Immunological Bioinformatics group at Center for Biological...... 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...... the MHC molecule in question, making it difficult for the non-expert end-user to choose the most suitable predictor. The first paper in this thesis presents a new, publicly available, consensus method for MHC class I predictions. The NetMHCcons predictor combines three state-of-the-art prediction...

  6. Scorecard on weather predictions

    Science.gov (United States)

    Richman, Barbara T.

    No matter that several northern and eastern states were pelted by snow and sleet early in March, as far as longterm weather forecasters are concerned, winter ended on February 28. Now is the time to review their winter seasonal forecasts to determine how accurate were those predictions issued at the start of winter.The National Weather Service (NWS) predicted on November 27, 1981, that the winter season would bring colder-than-normal temperatures to the eastern half of the United States, while temperatures were expected to be higher than normal in the westernmost section (see Figure 1). The NWS made no prediction for the middle of the country, labeling the area ‘indeterminate,’ or having the same chance of experiencing above-normal temperatures as below-normal temperatures, explained Donald L. Gilman, chief of the NWS long-range forecasting group.

  7. PREDICTION OF RECESSION

    OpenAIRE

    Lee, Young Sub; Zhu, Qian

    2010-01-01

    The purpose of our research is to examine the predictive power of inverted yield curve for the recession in the near future. The data used in this research are between Jan 1, 1959 to Nov, 2008. There are 8 recessions during this period, including current one. We conducted two sets of tests. The first set consists of spread between 10-year Treasury bond and 3-month Treasury bill and spread between 10-year Treasury bond and 3-month LIBOR; and we find the predictive power of spread between 10-ye...

  8. 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

  9. 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

  10. Is genetic evolution predictable?

    Science.gov (United States)

    Stern, David L; Orgogozo, Virginie

    2009-02-01

    Ever since the integration of Mendelian genetics into evolutionary biology in the early 20th century, evolutionary geneticists have for the most part treated genes and mutations as generic entities. However, recent observations indicate that all genes are not equal in the eyes of evolution. Evolutionarily relevant mutations tend to accumulate in hotspot genes and at specific positions within genes. Genetic evolution is constrained by gene function, the structure of genetic networks, and population biology. The genetic basis of evolution may be predictable to some extent, and further understanding of this predictability requires incorporation of the specific functions and characteristics of genes into evolutionary theory. PMID:19197055

  11. 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.

  12. 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.

  13. 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.

  14. 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...

  15. 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

  16. 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.

  17. Polarization predictions for LEAR

    International Nuclear Information System (INIS)

    Large polarization properties have recently been experimentally found in quasi-two-body reactions. From these results, the additive quark model and assumptions on the relative size of some participant matrix elements (which will be motivated elsewhere as properties of colour confinement), we present prediction for the reactions pp- to YY-. (Author)

  18. 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...

  19. 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...

  20. 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...

  1. Prediction of regulatory elements

    DEFF Research Database (Denmark)

    Sandelin, Albin

    2008-01-01

    -lab methods are time consuming and expensive, it is not realistic to identify TFBS for all uncharacterized genes in the genome by purely experimental means. Computational methods aimed at predicting potential regulatory regions can increase the efficiency of wet-lab experiments significantly. Here, methods...

  2. Predictive models in urology.

    Science.gov (United States)

    Cestari, Andrea

    2013-01-01

    Predictive modeling is emerging as an important knowledge-based technology in healthcare. The interest in the use of predictive modeling reflects advances on different fronts such as the availability of health information from increasingly complex databases and electronic health records, a better understanding of causal or statistical predictors of health, disease processes and multifactorial models of ill-health and developments in nonlinear computer models using artificial intelligence or neural networks. These new computer-based forms of modeling are increasingly able to establish technical credibility in clinical contexts. The current state of knowledge is still quite young in understanding the likely future direction of how this so-called 'machine intelligence' will evolve and therefore how current relatively sophisticated predictive models will evolve in response to improvements in technology, which is advancing along a wide front. Predictive models in urology are gaining progressive popularity not only for academic and scientific purposes but also into the clinical practice with the introduction of several nomograms dealing with the main fields of onco-urology. PMID:23423686

  3. 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...

  4. 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…

  5. 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

  6. Predicting Lotto Numbers

    DEFF Research Database (Denmark)

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

    2016-01-01

    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...

  7. 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

  8. 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...

  9. Predicting Anthracycline Benefit

    DEFF Research Database (Denmark)

    Bartlett, John M S; McConkey, Christopher C; Munro, Alison F;

    2015-01-01

    PURPOSE: Evidence supporting the clinical utility of predictive biomarkers of anthracycline activity is weak, with a recent meta-analysis failing to provide strong evidence for either HER2 or TOP2A. Having previously shown that duplication of chromosome 17 pericentromeric alpha satellite as...... measured with a centromere enumeration probe (CEP17) predicted sensitivity to anthracyclines, we report here an individual patient-level pooled analysis of data from five trials comparing anthracycline-based chemotherapy with CMF (cyclophosphamide, methotrexate, and fluorouracil) as adjuvant chemotherapy...... for early breast cancer. PATIENTS AND METHODS: Fluorescent in situ hybridization for CEP17, HER2, and TOP2A was performed in three laboratories on samples from 3,846 of 4,864 eligible patients from five trials evaluating anthracycline-containing chemotherapy versus CMF. Methodologic differences did...

  10. 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%.

  11. 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...

  12. 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...

  13. 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.

  14. 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...

  15. 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 ...

  16. 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)

  17. 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.

  18. 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...

  19. Individualizing fracture risk prediction

    OpenAIRE

    van Geel, Tineke A. C. M.; van den Bergh, Joop P. W.; Dinant, Geert Jan; Geusens, Piet

    2010-01-01

    Low bone mineral density (BMD) and clinical factors (CRF) have been identified as factors associated with an increased relative risk of fractures. From this observation and for clinical decision making, the concept of prediction of the individual absolute risk of fractures has emerged. It refers to the individual's risk for fractures over a certain time period, e.g. the next 5 and 10 years. Two individualized fracture risk calculation tools that are increasingly used and are available on the ...

  20. 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

  1. 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...

  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. Numbers, Predictions and War

    OpenAIRE

    J.W. Grobbelaar

    2012-01-01

    Die subtitel van hierdie boek: 'Using history to evaluate combat forces and predict the outcome of battles', is 'n goeie beskrywing van die ambisieuse oogmerk van die skrywer. In die boek word 'n studie beskryf wat by die Historical Evaluation and Research Organization (afgekort: HERO) onderneem is om 'n wiskundige model daar te stel waarmee die uitkoms van enige veldslag voorspel kan word. As basis tot die studie word twee fundamentele aannames gemaak:

  5. Predicting Human Cooperation

    Science.gov (United States)

    Nay, John J.; Vorobeychik, Yevgeniy

    2016-01-01

    The Prisoner’s Dilemma has been a subject of extensive research due to its importance in understanding the ever-present tension between individual self-interest and social benefit. A strictly dominant strategy in a Prisoner’s Dilemma (defection), when played by both players, is mutually harmful. Repetition of the Prisoner’s Dilemma can give rise to cooperation as an equilibrium, but defection is as well, and this ambiguity is difficult to resolve. The numerous behavioral experiments investigating the Prisoner’s Dilemma highlight that players often cooperate, but the level of cooperation varies significantly with the specifics of the experimental predicament. We present the first computational model of human behavior in repeated Prisoner’s Dilemma games that unifies the diversity of experimental observations in a systematic and quantitatively reliable manner. Our model relies on data we integrated from many experiments, comprising 168,386 individual decisions. The model is composed of two pieces: the first predicts the first-period action using solely the structural game parameters, while the second predicts dynamic actions using both game parameters and history of play. Our model is successful not merely at fitting the data, but in predicting behavior at multiple scales in experimental designs not used for calibration, using only information about the game structure. We demonstrate the power of our approach through a simulation analysis revealing how to best promote human cooperation. PMID:27171417

  6. 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.

  7. Prediction in projection

    Science.gov (United States)

    Garland, Joshua; Bradley, Elizabeth

    2015-12-01

    Prediction models that capture and use the structure of state-space dynamics can be very effective. In practice, however, one rarely has access to full information about that structure, and accurate reconstruction of the dynamics from scalar time-series data—e.g., via delay-coordinate embedding—can be a real challenge. In this paper, we show that forecast models that employ incomplete reconstructions of the dynamics—i.e., models that are not necessarily true embeddings—can produce surprisingly accurate predictions of the state of a dynamical system. In particular, we demonstrate the effectiveness of a simple near-neighbor forecast technique that works with a two-dimensional time-delay reconstruction of both low- and high-dimensional dynamical systems. Even though correctness of the topology may not be guaranteed for incomplete reconstructions like this, the dynamical structure that they do capture allows for accurate predictions—in many cases, even more accurate than predictions generated using a traditional embedding. This could be very useful in the context of real-time forecasting, where the human effort required to produce a correct delay-coordinate embedding is prohibitive.

  8. 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.

  9. 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

  10. Disruption prediction at JET

    International Nuclear Information System (INIS)

    The sudden loss of the plasma magnetic confinement, known as disruption, is one of the major issue in a nuclear fusion machine as JET (Joint European Torus). Disruptions pose very serious problems to the safety of the machine. The energy stored in the plasma is released to the machine structure in few milliseconds resulting in forces that at JET reach several Mega Newtons. The problem is even more severe in the nuclear fusion power station where the forces are in the order of one hundred Mega Newtons. The events that occur during a disruption are still not well understood even if some mechanisms that can lead to a disruption have been identified and can be used to predict them. Unfortunately it is always a combination of these events that generates a disruption and therefore it is not possible to use simple algorithms to predict it. This thesis analyses the possibility of using neural network algorithms to predict plasma disruptions in real time. This involves the determination of plasma parameters every few milliseconds. A plasma boundary reconstruction algorithm, XLOC, has been developed in collaboration with Dr. D. O'Brien and Dr. J. Ellis capable of determining the plasma wall/distance every 2 milliseconds. The XLOC output has been used to develop a multilayer perceptron network to determine plasma parameters as li and qψ with which a machine operational space has been experimentally defined. If the limits of this operational space are breached the disruption probability increases considerably. Another approach for prediction disruptions is to use neural network classification methods to define the JET operational space. Two methods have been studied. The first method uses a multilayer perceptron network with softmax activation function for the output layer. This method can be used for classifying the input patterns in various classes. In this case the plasma input patterns have been divided between disrupting and safe patterns, giving the possibility of

  11. On identified predictive control

    Science.gov (United States)

    Bialasiewicz, Jan T.

    1993-01-01

    Self-tuning control algorithms are potential successors to manually tuned PID controllers traditionally used in process control applications. A very attractive design method for self-tuning controllers, which has been developed over recent years, is the long-range predictive control (LRPC). The success of LRPC is due to its effectiveness with plants of unknown order and dead-time which may be simultaneously nonminimum phase and unstable or have multiple lightly damped poles (as in the case of flexible structures or flexible robot arms). LRPC is a receding horizon strategy and can be, in general terms, summarized as follows. Using assumed long-range (or multi-step) cost function the optimal control law is found in terms of unknown parameters of the predictor model of the process, current input-output sequence, and future reference signal sequence. The common approach is to assume that the input-output process model is known or separately identified and then to find the parameters of the predictor model. Once these are known, the optimal control law determines control signal at the current time t which is applied at the process input and the whole procedure is repeated at the next time instant. Most of the recent research in this field is apparently centered around the LRPC formulation developed by Clarke et al., known as generalized predictive control (GPC). GPC uses ARIMAX/CARIMA model of the process in its input-output formulation. In this paper, the GPC formulation is used but the process predictor model is derived from the state space formulation of the ARIMAX model and is directly identified over the receding horizon, i.e., using current input-output sequence. The underlying technique in the design of identified predictive control (IPC) algorithm is the identification algorithm of observer/Kalman filter Markov parameters developed by Juang et al. at NASA Langley Research Center and successfully applied to identification of flexible structures.

  12. 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

  13. 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...... phase equilibria in mixtures containing glycols. The importance of considering the solvation of CO2–water (in CPA) when the model is applied to multicomponent mixtures as well as of the multiple associations in heavy glycol–water mixtures (in NRHB) is investigated....

  14. Chloride ingress prediction

    DEFF Research Database (Denmark)

    Frederiksen, Jens Mejer; Geiker, Mette Rica

    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...... marine atmospheric and submersed South Scandinavian environment. The design parameters are based on sequential measurements of 86 chloride profiles taken over ten years from 13 different types of concrete. The design parameters provide the input for an analytical model for chloride profiles as function...

  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. 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...

  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. 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....

  19. Stress Prediction System

    Science.gov (United States)

    1995-01-01

    NASA wanted to know how astronauts' bodies would react under various gravitational pulls and space suit weights. Under contract to NASA, the University of Michigan's Center for Ergonomics developed a model capable of predicting what type of stress and what degree of load a body could stand. The algorithm generated was commercialized with the ISTU (Isometric Strength Testing Unit) Functional Capacity Evaluation System, which simulates tasks such as lifting a heavy box or pushing a cart and evaluates the exertion expended. It also identifies the muscle group that limits the subject's performance. It is an effective tool of personnel evaluation, selection and job redesign.

  20. 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...

  1. 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.

  2. Energy Predictions 2011

    International Nuclear Information System (INIS)

    Even as the recession begins to subside, the energy sector is still likely to experience challenging conditions as we enter 2011. It should be remembered how very important a role energy plays in driving the global economy. Serving as a simple yet global and unified measure of economic recovery, it is oil's price range and the strength and sustainability of the recovery which will impact the ways in which all forms of energy are produced and consumed. The report aims for a closer insight into these predictions: What will happen with M and A (Mergers and Acquisitions) in the energy industry?; What are the prospects for renewables?; Will the water-energy nexus grow in importance?; How will technological leaps and bounds affect E and P (exploration and production) operations?; What about electric cars? This is the second year Deloitte's Global Energy and Resources Group has published its predictions for the year ahead. The report is based on in-depth interviews with clients, industry analysts, and senior energy practitioners from Deloitte member firms around the world.

  3. 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.

  4. 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.

  5. Predictive assessment of reading.

    Science.gov (United States)

    Wood, Frank B; Hill, Deborah F; Meyer, Marianne S; Flowers, D Lynn

    2005-12-01

    Study 1 retrospectively analyzed neuropsychological and psychoeducational tests given to N=220 first graders, with follow-up assessments in third and eighth grade. Four predictor constructs were derived: (1) Phonemic Awareness, (2) Picture Vocabulary, (3) Rapid Naming, and (4) Single Word Reading. Together, these accounted for 88%, 76%, 69%, and 69% of the variance, respectively, in first, third, and eighth grade Woodcock Johnson Broad Reading and eighth grade Gates-MacGinitie. When Single Word Reading was excluded from the predictors, the remaining predictors still accounted for 71%, 65%, 61%, and 65% of variance in the respective outcomes. Secondary analyses of risk of low outcome showed sensitivities/specificities of 93.0/91.0, and 86.4/84.9, respectively, for predicting which students would be in the bottom 15% and 30% of actual first grade WJBR. Sensitivities/specificities were 84.8/83.3 and 80.2/81.3, respectively, for predicting the bottom 15% and 30% of actual third grade WJBR outcomes; eighth grade outcomes had sensitivities/specificities of 80.0/80.0 and 85.7/83.1, respectively, for the bottom 15% and 30% of actual eighth grade WJBR scores. Study 2 cross-validated the concurrent predictive validities in an N=500 geographically diverse sample of late kindergartners through third graders, whose ethnic and racial composition closely approximated the national early elementary school population. New tests of the same four predictor domains were used, together taking only 15 minutes to administer by teachers; the new Woodcock-Johnson III Broad Reading standard score was the concurrent criterion, whose testers were blind to the predictor results. This cross-validation showed 86% of the variance accounted for, using the same regression weights as used in Study 1. With these weights, sensitivity/specificity values for the 15% and 30% thresholds were, respectively, 91.3/88.0 and 94.1/89.1. These validities and accuracies are stronger than others reported for

  6. 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

  7. 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

  8. Chloride ingress prediction

    DEFF Research Database (Denmark)

    Frederiksen, Jens Mejer; Geiker, Mette Rica

    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 the state-of-the art: an analytical model which describes chloride profiles in concrete as function of depth and...... makes physical sense for the design engineer, i.e. the achieved chloride diffusion coefficients at 1 year and 100 years, D1 and D100 respectively, and the corresponding achieved chloride concentrations at the exposed concrete surface, C1 and C100. Data from field exposure supports the assumption of time...... dependent surface chloride concentrations and the diffusion coefficients. Model parameters for Portland cement concretes with and without silica fume and fly ash in marine atmospheric and submerged South Scandinavian environment are suggested in a companion paper based on 10 years field exposure data....

  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. 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

  11. 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)

  12. 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

  13. 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.

  14. 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.

  15. Anterior surgery in the thoracic and lumbar spine: endoscopic techniques in children.

    Science.gov (United States)

    Crawford, Alvin H

    2005-01-01

    Therapeutic modalities for disorders of the pediatric spine must include video-assisted thoracoscopy. The endoscopic approach to the spine has involved an evolutionary approach. What began as an isolated drainage of a vertebral abscess has continued as a method of single diskectomy, release of the anulus fibrosus with or without ligation of segmental vessels, rib resection for costoplasty, rib harvesting for intervertebral fusion and, most recently, insertion of correctional implants with or without spinal fusion. Video-assisted thoracoscopic surgery offers the potential to decrease surgical morbidity associated with traditional open procedures. The ability of video-assisted thoracoscopic surgery to achieve spinal release and the results of early outcomes and cost are comparable to those of open thoracotomy. The improvement in video technology with multichip cameras has significantly improved and enhanced the ability to identify structures in the chest through small incisions (portals). This technology allows spine surgeons to perform surgical intervention comparable to thoracotomy. Instead of using a 9- to 12-inch incision, four to five portals of approximately 2 cm are used; thus, the cosmetic efects of the scoliosis surgery are enhanced. The potential benefits of this procedure include diminished postoperative pain, decreased length of hospitalization, increased wound care, and early return to prehospital activities. PMID:15948482

  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. 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.

  18. Update on protein structure prediction

    DEFF Research Database (Denmark)

    Hubbard, T; Tramontano, A; Barton, G; Jones, D; Sippl, M; Valencia, A; Lesk, A; Moult, J; Rost, B; Sander, C; Schneider, R; Lahm, A; Leplae, R; Buta, C; Eisenstein, M; Fjellstrom, O; Floeckner, H; Grossmann, JG; Hansen, J; Citterich, MH; Jørgensen, Flemming Steen; MarchlerBauer, A; Osuna, J; Park, J; Reinhardt, A; dePouplana, LR; RojoDominguez, A; Saudek, V; Sinclair, J; Sturrock, S; Venclovas, C; Vinals, C

    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 that this was a worthwhile experiment showing that the use of a range of independent prediction methods and thorough use of existing databases can lead to credible and useful ab initio structure predictions....

  19. Introduction: Long term prediction

    International Nuclear Information System (INIS)

    Making a decision upon the right choice of a material appropriate to a given application should be based on taking into account several parameters as follows: cost, standards, regulations, safety, recycling, chemical properties, supplying, transformation, forming, assembly, mechanical and physical properties as well as the behaviour in practical conditions. Data taken from a private communication (J.H.Davidson) are reproduced presenting the life time range of materials from a couple of minutes to half a million hours corresponding to applications from missile technology up to high-temperature nuclear reactors or steam turbines. In the case of deep storage of nuclear waste the time required is completely different from these values since we have to ensure the integrity of the storage system for several thousand years. The vitrified nuclear wastes should be stored in metallic canisters made of iron and carbon steels, stainless steels, copper and copper alloys, nickel alloys or titanium alloys. Some of these materials are passivating metals, i.e. they develop a thin protective film, 2 or 3 nm thick - the so-called passive films. These films prevent general corrosion of the metal in a large range of chemical condition of the environment. In some specific condition, localized corrosion such as the phenomenon of pitting, occurs. Consequently, it is absolutely necessary to determine these chemical condition and their stability in time to understand the behavior of a given material. In other words the corrosion system is constituted by the complex material/surface/medium. For high level nuclear wastes the main features for resolving problem are concerned with: geological disposal; deep storage in clay; waste metallic canister; backfill mixture (clay-gypsum) or concrete; long term behavior; data needed for modelling and for predicting; choice of appropriate solution among several metallic candidates. The analysis of the complex material/surface/medium is of great importance

  20. Useful theories make predictions.

    Science.gov (United States)

    Howes, Andrew

    2012-01-01

    Stephen and Van Orden (this issue) propose that there is a complex system approach to cognitive science, and collectively the authors of the papers presented in this issue believe that this approach provides the means to drive a revolution in the science of the mind. Unfortunately, however illuminating, this explanation is absent and hyperbole is all too extensive. In contrast, I argue (1) that dynamic systems theory is not new to cognitive science and does not provide a basis for a revolution, (2) it is not necessary to reject cognitive science in order to explain the constraints imposed by the body and the environment, (3) it is not necessary, as Silberstein and Chemero (this issue) appear to do, to reject cognitive science in order to explain consciousness, and (4) our understanding of pragmatics is not advanced by Gibbs and Van Orden's (this issue) "self-organized criticality".? Any debate about the future of cognitive science could usefully focus on predictive adequacy. Unfortunately, this is not the approach taken by the authors of this issue. PMID:22253181

  1. 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...

  2. 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

  3. 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

  4. 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.

  5. 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

  6. Predicting periodontitis progression?

    Science.gov (United States)

    Ferraiolo, Debra M

    2016-03-01

    Data sourcesCochrane Library, Ovid, Medline, Embase and LILACS were searched using no language restrictions and included information up to July 2014. Bibliographic references of included articles and related review articles were hand searched. On-line hand searching of recent issues of key periodontal journals was performed (Journal of Clinical Periodontology, Journal of Dental Research, Journal of Periodontal Research, Journal of Periodontology, Oral Health and Preventive Dentistry).Study selectionProspective and retrospective cohort studies were used for answering the question of prediction since there were no randomised controlled trials on this topic. Risk of bias was assessed using the validated Newcastle-Ottawa quality assessment scale for non-randomised studies. Cross-sectional studies were included in the summary of currently reported risk assessment tools but not for risk of progression of disease, due to the inability to properly assess bias in these types of studies. Titles and abstracts were scanned by two reviewers independently.Full reports were obtained for those articles meeting inclusion criteria or those with insufficient information in the title to make a decision. Any published risk assessment tool was considered. The tool was defined to include any composite measure of patient-level risk directed towards determining the probability for further disease progression in adults with periodontitis. Periodontitis was defined to include both chronic and aggressive forms in the adult population. Outcomes included changes in attachment levels and/or deepening of periodontal pockets in millimeters in study populations undergoing supportive periodontal therapy.Data extraction and synthesisData extraction was performed independently and in collaboration by two reviewers; completed evidence tables were reviewed by three reviewers. Studies were each given a descriptive summary to assess the quantity of data as well as further assessment of study variations

  7. 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.

  8. Airframe noise prediction

    Science.gov (United States)

    1990-11-01

    This Data Item 90023, an addition to the Noise Sub-series, provides the FORTRAN listing of a computer program for a semi-empirical method that calculates the far-field airframe aerodynamic noise generated by turbo-fan powered transport aircraft or gliders in one-third octave bands over a frequency range specified by the user. The overall sound pressure level is also output. The results apply for a still, lossless atmosphere; other ESDU methods may be used to correct for atmospheric attenuation, ground reflection, lateral attenuation, and wind and temperature gradients. The position of the aircraft relative to the observer is input in terms of the height at minimum range, and the elevation and azimuthal angles to the aircraft; if desired the user may obtain results over a range of those angles in 10 degree intervals. The method sums the contributions made by various components, results for which can also be output individually. The components are: the wind (conventional or delta), tailplane, fin, flaps (single/double slotted or triple slotted), leading-edge slats, and undercarriage legs and wheels (one/two wheel or four wheel units). The program requires only geometric data for each component (area and span in the case of lifting elements, flap deflection angle, and leg length and wheel diameter for the undercarriage). The program was validated for aircraft with take-off masses from 42,000 to 390,000 kg (92,000 to 860,000 lb) at airspeeds from 70 to 145 m/s (135 to 280 kn). Comparisons with available experimental data suggest a prediction rms accuracy of 1 dB at minimum range, rising to between 2 and 3 dB at 60 degrees to either side.

  9. Method-level bug prediction

    OpenAIRE

    Giger, Emanuel; D'Ambros, Marco; Pinzger, Martin; Gall, Harald

    2012-01-01

    Researchers proposed a wide range of approaches to build effective bug prediction models that take into account multiple aspects of the software development process. Such models achieved good prediction performance, guiding developers towards those parts of their system where a large share of bugs can be expected. However, most of those approaches predict bugs on file-level. This often leaves developers with a considerable amount of effort to examine all methods of a file until a bug is locat...

  10. Networked and Distributed Predictive Control

    CERN Document Server

    Christofides, Panagiotis D; De La Pena, David Munoz

    2011-01-01

    "Networked and Distributed Predictive Control" presents rigorous, yet practical, methods for the design of networked and distributed predictive control systems - the first book to do so. The design of model predictive control systems using Lyapunov-based techniques accounting for the influence of asynchronous and delayed measurements is followed by a treatment of networked control architecture development. This shows how networked control can augment dedicated control systems in a natural way and takes advantage of additional, potentially asynchronous and delayed measurements to main

  11. 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 ...

  12. 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...

  13. Interoceptive predictions in the brain.

    Science.gov (United States)

    Barrett, Lisa Feldman; Simmons, W Kyle

    2015-07-01

    Intuition suggests that perception follows sensation and therefore bodily feelings originate in the body. However, recent evidence goes against this logic: interoceptive experience may largely reflect limbic predictions about the expected state of the body that are constrained by ascending visceral sensations. In this Opinion article, we introduce the Embodied Predictive Interoception Coding model, which integrates an anatomical model of corticocortical connections with Bayesian active inference principles, to propose that agranular visceromotor cortices contribute to interoception by issuing interoceptive predictions. We then discuss how disruptions in interoceptive predictions could function as a common vulnerability for mental and physical illness. PMID:26016744

  14. Predicting Parameters in Deep Learning

    OpenAIRE

    Denil, Misha; Shakibi, Babak; Dinh, Laurent; Ranzato, Marc'Aurelio; De Freitas, Nando

    2013-01-01

    We demonstrate that there is significant redundancy in the parameterization of several deep learning models. Given only a few weight values for each feature it is possible to accurately predict the remaining values. Moreover, we show that not only can the parameter values be predicted, but many of them need not be learned at all. We train several different architectures by learning only a small number of weights and predicting the rest. In the best case we are able to predict more than 95% of...

  15. Risk prediction for invasive candidiasis

    Directory of Open Access Journals (Sweden)

    Armin Ahmed

    2014-01-01

    Full Text Available Over past few years, treatment of invasive candidiasis (IC has evolved from targeted therapy to prophylaxis, pre-emptive and empirical therapy. Numerous predisposing factors for IC have been grouped together in various combinations to design risk prediction models. These models in general have shown good negative predictive value, but poor positive predictive value. They are useful in selecting the population which is less likely to benefit from empirical antifungal therapy and thus prevent overuse of antifungal agents. Current article deals with various risk prediction models for IC and their external validation studies.

  16. 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

  17. EVA Performance Prediction

    Science.gov (United States)

    Peacock, Brian; Maida, James; Rajulu, Sudhakar

    2004-01-01

    out for EVA activities are based more on extensive domain experience than any formal analytic structure. Conversely, physical task analysis for industrial and structured evidence from training and EV A contexts. Again on earth there is considerable evidence of human performance degradation due to encumbrance and fatigue. These industrial models generally take the form of a discounting equation. The development of performance estimates for space operations, such as timeline predictions for EVA is generally based on specific input from training activity, for example in the NBL or KC135. uniformed services tasks on earth are much more formalized. Human performance data in the space context has two sources: first there is the micro analysis of performance in structured tasks by the space physiology community and second there is the less structured evidence from training and EV A contexts.

  18. 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].

  19. 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.

  20. 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.

  1. 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...

  2. 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...

  3. 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...

  4. 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

  5. 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.

  6. Prediction models in complex terrain

    DEFF Research Database (Denmark)

    Marti, I.; Nielsen, Torben Skov; Madsen, Henrik; Navarro, J.; Barquero, C.G.

    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 the...... performance of HIRLAM in particular with respect to wind predictions. To estimate the performance of the model two spatial resolutions (0,5 Deg. and 0.2 Deg.) and different sets of HIRLAM variables were used to predict wind speed and energy production. The predictions of energy production for the wind farms...... are calculated using on-line measurements of power production as well as HIRLAM predictions as input thus taking advantage of the auto-correlation, which is present in the power production for shorter pediction horizons. Statistical models are used to discribe the relationship between observed energy...

  7. Time-predictable Stack Caching

    DEFF Research Database (Denmark)

    Abbaspourseyedi, Sahar

    complicated and less imprecise. Time-predictable computer architectures provide solutions to this problem. As accesses to the data in caches are one source of timing unpredictability, devising methods for improving the timepredictability of caches are important. Stack data, with statically analyzable...... addresses, provides an opportunity to predict and tighten the WCET of accesses to data in caches. In this thesis, we introduce the time-predictable stack cache design and implementation within a time-predictable processor. We introduce several optimizations to our design for tightening the WCET while...... 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, for...

  8. 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...

  9. 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...

  10. Earthquake prediction by Kina Method

    International Nuclear Information System (INIS)

    Earthquake prediction has been one of the earliest desires of the man. Scientists have worked hard to predict earthquakes for a long time. The results of these efforts can generally be divided into two methods of prediction: 1) Statistical Method, and 2) Empirical Method. In the first method, earthquakes are predicted using statistics and probabilities, while the second method utilizes variety of precursors for earthquake prediction. The latter method is time consuming and more costly. However, the result of neither method has fully satisfied the man up to now. In this paper a new method entitled 'Kiana Method' is introduced for earthquake prediction. This method offers more accurate results yet lower cost comparing to other conventional methods. In Kiana method the electrical and magnetic precursors are measured in an area. Then, the time and the magnitude of an earthquake in the future is calculated using electrical, and in particular, electrical capacitors formulas. In this method, by daily measurement of electrical resistance in an area we make clear that the area is capable of earthquake occurrence in the future or not. If the result shows a positive sign, then the occurrence time and the magnitude can be estimated by the measured quantities. This paper explains the procedure and details of this prediction method. (authors)

  11. Predicting emergency diesel starting performance

    International Nuclear Information System (INIS)

    The US Department of Energy effort to extend the operational lives of commercial nuclear power plants has examined methods for predicting the performance of specific equipment. This effort focuses on performance prediction as a means for reducing equipment surveillance, maintenance, and outages. Realizing these goals will result in nuclear plants that are more reliable, have lower maintenance costs, and have longer lives. This paper describes a monitoring system that has been developed to predict starting performance in emergency diesels. A prototype system has been built and tested on an engine at Sandia National Laboratories. 2 refs

  12. Confidence scores for prediction models

    DEFF Research Database (Denmark)

    Gerds, Thomas Alexander; van de Wiel, MA

    2011-01-01

    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...... 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...

  13. 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

  14. 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...

  15. Predictive Data Mining in KPP

    Directory of Open Access Journals (Sweden)

    Dr. R.K. Chauhan

    2012-09-01

    Full Text Available In this paper, we have provided the Genetic Algorithm (GA used for prediction process in Knowledge Penetration Process (KPP. The said GA is implemented and its efficiency is analysed.

  16. Prediction tools in surgical oncology.

    Science.gov (United States)

    Isariyawongse, Brandon K; Kattan, Michael W

    2012-07-01

    Artificial neural networks, prediction tables, and clinical nomograms allow physicians to transmit an immense amount of prognostic information in a format that exhibits comprehensibility and brevity. Current models demonstrate the feasibility to accurately predict many oncologic outcomes, including pathologic stage, recurrence-free survival, and response to adjuvant therapy. Although emphasis should be placed on the independent validation of existing prediction tools, there is a paucity of models in the literature that focus on quality of life outcomes. The unification of tools that predict oncologic and quality of life outcomes into a comparative effectiveness table will furnish patients with cancer with the information they need to make a highly informed and individualized treatment decision. PMID:22583992

  17. Data for decay Heat Predictions

    International Nuclear Information System (INIS)

    These proceedings of a specialists' meeting on data for decay heat predictions are based on fission products yields, on delayed neutrons and on comparative evaluations on evaluated and experimental data for thermal and fast fission. Fourteen conferences were analysed

  18. 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...

  19. History of earthquake prediction researches

    International Nuclear Information System (INIS)

    The main procedures of diffusion of knowledge on earthquake prediction researches in space and time have been reconstructed. Scientific and economic constraint factors that caused difficulties or accelerations in seismic precursors researches have been investigated and commented

  20. Prediction of molecular crystal structures

    International Nuclear Information System (INIS)

    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-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 structures

  1. 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...

  2. 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.

  3. 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...

  4. 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

  5. Predictive Modelling of Cellular Load

    OpenAIRE

    Carolan, Emmett; McLoone, Seamus; Farrell, Ronan

    2015-01-01

    This work examines the temporal dynamics of cellular load in four Irish regions. Large scale underutilisation of network resources is identified both at the regional level and at the level of individual cells. Cellular load is modeled and prediction intervals are generated. These prediction intervals are used to put an upper bound on usage in a particular cell at a particular time. Opportunities for improvements in network utilization by incorporating these upper bounds on usage are identifie...

  6. 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...

  7. 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...

  8. 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)

  9. Predicting Predictable: Accuracy and Reliability of Earthquake Forecasts

    Science.gov (United States)

    Kossobokov, V. G.

    2014-12-01

    Earthquake forecast/prediction is an uncertain profession. The famous Gutenberg-Richter relationship limits magnitude range of prediction to about one unit. Otherwise, the statistics of outcomes would be related to the smallest earthquakes and may be misleading when attributed to the largest earthquakes. Moreover, the intrinsic uncertainty of earthquake sizing allows self-deceptive picking of justification "just from below" the targeted magnitude range. This might be important encouraging evidence but, by no means, can be a "helpful" additive to statistics of a rigid testing that determines reliability and efficiency of a farecast/prediction method. Usually, earthquake prediction is classified in respect to expectation time while overlooking term-less identification of earthquake prone areas, as well as spatial accuracy. The forecasts are often made for a "cell" or "seismic region" whose area is not linked to the size of target earthquakes. This might be another source for making a wrong choice in parameterization of an forecast/prediction method and, eventually, for unsatisfactory performance in a real-time application. Summing up, prediction of time and location of an earthquake of a certain magnitude range can be classified into categories listed in the Table below - Classification of earthquake prediction accuracy Temporal, in years Spatial, in source zone size (L) Long-term 10 Long-range Up to 100 Intermediate-term 1 Middle-range 5-10 Short-term 0.01-0.1 Narrow-range 2-3 Immediate 0.001 Exact 1 Note that a wide variety of possible combinations that exist is much larger than usually considered "short-term exact" one. In principle, such an accurate statement about anticipated seismic extreme might be futile due to the complexities of the Earth's lithosphere, its blocks-and-faults structure, and evidently nonlinear dynamics of the seismic process. The observed scaling of source size and preparation zone with earthquake magnitude implies exponential scales for

  10. 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.

  11. Prediction of GNSS satellite clocks

    International Nuclear Information System (INIS)

    This thesis deals with the characterisation and prediction of GNSS-satellite-clocks. A prerequisite to develop powerful algorithms for the prediction of clock-corrections is the thorough study of the behaviour of the different clock-types of the satellites. In this context the predicted part of the IGU-clock-corrections provided by the Analysis Centers (ACs) of the IGS was compared to the IGS-Rapid-clock solutions to determine reasonable estimates of the quality of already existing well performing predictions. For the shortest investigated interval (three hours) all ACs obtain almost the same accuracy of 0,1 to 0,4 ns. For longer intervals the individual predictions results start to diverge. Thus, for a 12-hours- interval the differences range from nearly 10 ns (GFZ, CODE) until up to some 'tens of ns'. Based on the estimated clock corrections provided via the IGS Rapid products a simple quadratic polynomial turns out to be sufficient to describe the time series of Rubidium-clocks. On the other hand Cesium-clocks show a periodical behaviour (revolution period) with an amplitude of up to 6 ns. A clear correlation between these amplitudes and the Sun elevation angle above the orbital planes can be demonstrated. The variability of the amplitudes is supposed to be caused by temperature-variations affecting the oscillator. To account for this periodical behaviour a quadratic polynomial with an additional sinus-term was finally chosen as prediction model both for the Cesium as well as for the Rubidium clocks. The three polynomial-parameters as well as amplitude and phase shift of the periodic term are estimated within a least-square-adjustment by means of program GNSS-VC/static. Input-data are time series of the observed part of the IGU clock corrections. With the estimated parameters clock-corrections are predicted for various durations. The mean error of the prediction of Rubidium-clock-corrections for an interval of six hours reaches up to 1,5 ns. For the 12-hours

  12. Lightning prediction using radiosonde data

    Energy Technology Data Exchange (ETDEWEB)

    Weng, L.Y.; Bin Omar, J.; Siah, Y.K.; Bin Zainal Abidin, I.; Ahmad, S.K. [Univ. Tenaga, Darul Ehsan (Malaysia). College of Engineering

    2008-07-01

    Lightning is a natural phenomenon in tropical regions. Malaysia experiences very high cloud-to-ground lightning density, posing both health and economic concerns to individuals and industries. In the commercial sector, power lines, telecommunication towers and buildings are most frequently hit by lightning. In the event that a power line is hit and the protection system fails, industries which rely on that power line would cease operations temporarily, resulting in significant monetary loss. Current technology is unable to prevent lightning occurrences. However, the ability to predict lightning would significantly reduce damages from direct and indirect lightning strikes. For that reason, this study focused on developing a method to predict lightning with radiosonde data using only a simple back propagation neural network model written in C code. The study was performed at the Kuala Lumpur International Airport (KLIA). In this model, the parameters related to wind were disregarded. Preliminary results indicate that this method shows some positive results in predicting lighting. However, a larger dataset is needed in order to obtain more accurate predictions. It was concluded that future work should include wind parameters to fully capture all properties for lightning formation, subsequently its prediction. 8 refs., 5 figs.

  13. 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.

  14. 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.

  15. Sentence-Level Attachment Prediction

    Science.gov (United States)

    Albakour, M.-Dyaa; Kruschwitz, Udo; Lucas, Simon

    Attachment prediction is the task of automatically identifying email messages that should contain an attachment. This can be useful to tackle the problem of sending out emails but forgetting to include the relevant attachment (something that happens all too often). A common Information Retrieval (IR) approach in analyzing documents such as emails is to treat the entire document as a bag of words. Here we propose a finer-grained analysis to address the problem. We aim at identifying individual sentences within an email that refer to an attachment. If we detect any such sentence, we predict that the email should have an attachment. Using part of the Enron corpus for evaluation we find that our finer-grained approach outperforms previously reported document-level attachment prediction in similar evaluation settings.

  16. 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...

  17. 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.

  18. Predicting performance of parallel computations

    Science.gov (United States)

    Mak, Victor W.; Lundstrom, Stephen F.

    1990-01-01

    An accurate and computationally efficient method for predicting the performance of a class of parallel computations running on concurrent systems is described. A parallel computation is modeled as a task system with precedence relationships expressed as a series-parallel directed acyclic graph. Resources in a concurrent system are modeled as service centers in a queuing network model. Using these two models as inputs, the method outputs predictions of expected execution time of the parallel computation and the concurrent system utilization. The method is validated against both detailed simulation and actual execution on a commercial multiprocessor. Using 100 test cases, the average error of the prediction when compared to simulation statistics is 1.7 percent, with a standard deviation of 1.5 percent; the maximum error is about 10 percent.

  19. 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.

  20. 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.

  1. 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

  2. Parity and Predictability of Competitions

    CERN Document Server

    Ben-Naim, E; Vázquez, F

    2006-01-01

    We present an extensive statistical analysis of the results of all sports competitions in five major sports leagues in England and the United States. We characterize the parity among teams by the variance in the winning fraction from season-end standings data and quantify the predictability of games by the frequency of upsets from game results data. We introduce a novel mathematical model in which the underdog team wins with a fixed upset probability. This model quantitatively relates the parity among teams with the predictability of the games, and it can be used to estimate the upset frequency from standings data.

  3. 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...

  4. 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)

  5. 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

  6. 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

  7. Algorithms for Protein Structure Prediction

    OpenAIRE

    Paluszewski, Martin

    2008-01-01

    The problem of predicting the three-dimensional structure of a protein given itsamino acid sequence is one of the most important open problems in bioinformatics.One of the carbon atoms in amino acids is the C-atom and the overallstructure of a protein is often represented by a so-called C-trace.Here we present three different approaches for reconstruction of C-tracesfrom predictable measures. In our first approach [63, 62], the C-trace is positionedon a lattice and a tabu-search algorithm is ...

  8. 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.

  9. Protein structural domains: definition and prediction.

    Science.gov (United States)

    Ezkurdia, Iakes; Tress, Michael L

    2011-11-01

    Recognition and prediction of structural domains in proteins is an important part of structure and function prediction. This unit lists the range of tools available for domain prediction, and describes sequence and structural analysis tools that complement domain prediction methods. Also detailed are the basic domain prediction steps, along with suggested strategies for different protein sequences and potential pitfalls in domain boundary prediction. The difficult problem of domain orientation prediction is also discussed. All the resources necessary for domain boundary prediction are accessible via publicly available Web servers and databases and do not require computational expertise. PMID:22045561

  10. Zephyr - the next generation prediction

    DEFF Research Database (Denmark)

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

    2001-01-01

    Java2TM platform and Enterprise Java Beans technology, and it will ensure that the best forecasts are given on all prediction horizons from the short range (0-9 hours) to the long range (36-48 hours). This is because the IMM approach uses online data and advanced statistical methods, which is...

  11. 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…

  12. 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 predi...

  13. 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.

  14. 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.

  15. 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

  16. 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.

  17. 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.

  18. Intermediate-term earthquake prediction.

    Science.gov (United States)

    Keilis-Borok, V I

    1996-04-30

    An earthquake of magnitude M and linear source dimension L(M) is preceded within a few years by certain patterns of seismicity in the magnitude range down to about (M - 3) in an area of linear dimension about 5L-10L. Prediction algorithms based on such patterns may allow one to predict approximately 80% of strong earthquakes with alarms occupying altogether 20-30% of the time-space considered. An area of alarm can be narrowed down to 2L-3L when observations include lower magnitudes, down to about (M - 4). In spite of their limited accuracy, such predictions open a possibility to prevent considerable damage. The following findings may provide for further development of prediction methods: (i) long-range correlations in fault system dynamics and accordingly large size of the areas over which different observed fields could be averaged and analyzed jointly, (ii) specific symptoms of an approaching strong earthquake, (iii) the partial similarity of these symptoms worldwide, (iv) the fact that some of them are not Earth specific: we probably encountered in seismicity the symptoms of instability common for a wide class of nonlinear systems. PMID:11607660

  19. 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

  20. 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

  1. The PredictAD project

    DEFF Research Database (Denmark)

    Antila, Kari; Lötjönen, Jyrki; Thurfjell, Lennart;

    2013-01-01

    objective of the PredictAD project was to find and integrate efficient biomarkers from heterogeneous patient data to make early diagnosis and to monitor the progress of AD in a more efficient, reliable and objective manner. The project focused on discovering biomarkers from biomolecular data...

  2. 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…

  3. 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)

  4. 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.

  5. Multimodal Imaging Measures Predict Rearrest

    Directory of Open Access Journals (Sweden)

    Vaughn R Steele

    2015-08-01

    Full Text Available Rearrest has been predicted by hemodynamic activity in the anterior cingulate cortex (ACC during error-processing (Aharoni et al., 2013. Here we evaluate the predictive power after adding an additional imaging modality in a subsample of 45 incarcerated males from Aharoni et al. Event-related potentials (ERPs and hemodynamic activity were collected during a Go/NoGo response inhibition task. Neural measures of error-processing were obtained from the ACC and two ERP components, the error-related negativity (ERN/Ne and the error positivity (Pe. Measures from the Pe and ACC differentiated individuals who were and were not subsequently rearrested. Cox regression, logistic regression, and support vector machine (SVM neuroprediction models were calculated. Each of these models proved successful in predicting rearrest and SVM provided the strongest results. Multimodal neuroprediction SVM models with out of sample cross-validating accurately predicted rearrest (83.33%. Offenders with increased Pe amplitude and decreased ACC activation, suggesting abnormal error-processing, were at greatest risk of rearrest.

  6. 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.

  7. Evoked Emotions Predict Food Choice

    NARCIS (Netherlands)

    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. Th

  8. Predicting sporadic Grid data transfers

    International Nuclear Information System (INIS)

    The increasingly common practice of (1) replicating datasets and (2) using resources as distributed data stores in Grid environments has lead to the problem of determining which replica can be accessed most efficiently. Due to diverse performance characteristics and load variations of several components in the end-to-end path linking these various locations, selecting a replica location from among many requires accurate prediction information of end-to-end data transfer times between the sources and sinks. In this paper, we present a prediction system that is based on combining end-to-end application throughput observations and network load variations, drawing from their merits of capturing whole system performance and variations in load patterns respectively. We develop a set of regression models to derive predictions that characterize the effect of network load variations on file transfer times. We apply these techniques to the GridFTP data movement tool, part of the Globus Toolkit(sup TM), and observe performance gains of up to 10% in prediction accuracy when compared to approaches based on past system behavior in isolation

  9. Predicting microbial traits with phylogenies.

    Science.gov (United States)

    Goberna, Marta; Verdú, Miguel

    2016-04-01

    Phylogeny reflects genetic and phenotypic traits in Bacteria and Archaea. The phylogenetic conservatism of microbial traits has prompted the application of phylogeny-based algorithms to predict unknown trait values of extant taxa based on the traits of their evolutionary relatives to estimate, for instance, rRNA gene copy numbers, gene contents or tolerance to abiotic conditions. Unlike the 'macrobial' world, microbial ecologists face scenarios potentially compromising the accuracy of trait reconstruction methods, as, for example, extremely large phylogenies and limited information on the traits of interest. We review 990 bacterial and archaeal traits from the literature and support that phylogenetic trait conservatism is widespread through the tree of life, while revealing that it is generally weak for ecologically relevant phenotypic traits and high for genetically complex traits. We then perform a simulation exercise to assess the accuracy of phylogeny-based trait predictions in common scenarios faced by microbial ecologists. Our simulations show that ca. 60% of the variation in phylogeny-based trait predictions depends on the magnitude of the trait conservatism, the number of species in the tree, the proportion of species with unknown trait values and the mean distance in the tree to the nearest neighbour with a known trait value. Results are similar for both binary and continuous traits. We discuss these results under the light of the reviewed traits and provide recommendations for the use of phylogeny-based trait predictions for microbial ecologists. PMID:26371406

  10. 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

  11. Modeling uncertainty: Predictive accuracy as a proxy for predictive confidence

    OpenAIRE

    Rich, Robert; Tracy, Joseph

    2003-01-01

    This paper evaluates current strategies for the empirical modeling of forecast behavior. In particular, we focus on the reliability of using proxies from time series models of heteroskedasticity to describe changes in predictive confidence. We address this issue by examining the relationship between ex post forecast errors and ex ante measures of forecast uncertainty from data on inflation forecasts from the Survey of Professional Forecasters. The results provide little evidence of a strong l...

  12. 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

  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, is...

  14. BDDCS Class Prediction for New Molecular Entities

    DEFF Research Database (Denmark)

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

    2012-01-01

    the prediction, which showed highest accuracy in predicting classes 2 and 3 with respect to the most populated class 1. For class 4 drugs a general lack of predictability was observed. A linear discriminant analysis (LDA) confirming the degree of accuracy for the prediction of the different BDDCS classes is tied...

  15. 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+

  16. 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.

  17. 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.

  18. 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.......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...

  19. Predicting Virtual Learning Environment Adoption

    DEFF Research Database (Denmark)

    Penjor, Sonam; Zander, Pär-Ola Mikael

    2016-01-01

    This study investigates the significance of Rogers’ Diffusion of Innovations (DOI) theory with regard to the use of a Virtual Learning Environment (VLE) at the Royal University of Bhutan (RUB). The focus is on different adoption types and characteristics of users. Rogers’ DOI theory is applied...... towards VLE adoption by academic staff at RUB. Few predictors were consistent with previous research on VLE adoption. There were also significant differences from previous research on predictors such as the deviation in adopter frequency from that predicted by Rogers DOI theory. Therefore, it can...... be concluded that it is misleading to rely on the DOI theory in the way it is currently operationalised for predicting VLE use....

  20. Confidence Estimation in Structured Prediction

    CERN Document Server

    Mejer, Avihai

    2011-01-01

    Structured classification tasks such as sequence labeling and dependency parsing have seen much interest by the Natural Language Processing and the machine learning communities. Several online learning algorithms were adapted for structured tasks such as Perceptron, Passive- Aggressive and the recently introduced Confidence-Weighted learning . These online algorithms are easy to implement, fast to train and yield state-of-the-art performance. However, unlike probabilistic models like Hidden Markov Model and Conditional random fields, these methods generate models that output merely a prediction with no additional information regarding confidence in the correctness of the output. In this work we fill the gap proposing few alternatives to compute the confidence in the output of non-probabilistic algorithms.We show how to compute confidence estimates in the prediction such that the confidence reflects the probability that the word is labeled correctly. We then show how to use our methods to detect mislabeled wor...

  1. 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......) 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...... bounds for partial structures very fast. Using these lower bounds, we are able to find global minimum structures in a huge conformational space in reasonable time. We show that many of these global minimum structures are of good quality compared to the native structure. Our branch and bound algorithm...

  2. 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.

  3. 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.

  4. 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.

  5. The Variables Predicting Couple Burnout

    OpenAIRE

    Çapri, Burhan; Gökçakan, Zafer

    2013-01-01

    The purpose of the study is to investigate the contributions of variables concerned with socio-demographic features, career burnout, marital adjustment, spouse support, marriage and relationship on the prediction of couple burnout of married individuals. The research group consisted of 435 married females (n= 235) and males (n= 200), who are university staff in different units of Mersin University, selected randomly from the population and who accepted to join the study voluntarily. In order ...

  6. 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...

  7. Predictive Overlapping Co-Clustering

    OpenAIRE

    Sarkar, Chandrima; Srivastava, Jaideep

    2014-01-01

    In the past few years co-clustering has emerged as an important data mining tool for two way data analysis. Co-clustering is more advantageous over traditional one dimensional clustering in many ways such as, ability to find highly correlated sub-groups of rows and columns. However, one of the overlooked benefits of co-clustering is that, it can be used to extract meaningful knowledge for various other knowledge extraction purposes. For example, building predictive models with high dimensiona...

  8. 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...

  9. Black holes, singularities and predictability

    International Nuclear Information System (INIS)

    The paper favours the view that singularities may play a central role in quantum gravity. The author reviews the arguments leading to the conclusion, that in the process of black hole formation and evaporation, an initial pure state evolves to a final density matrix, thus signaling a breakdown in ordinary quantum dynamical evolution. Some related issues dealing with predictability in the dynamical evolution, are also discussed. (U.K.)

  10. 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...

  11. 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 ...

  12. Is quantum theory predictably complete?

    International Nuclear Information System (INIS)

    Quantum theory (QT) provides statistical predictions for various physical phenomena. To verify these predictions a considerable amount of data has been accumulated in the 'measurements' performed on the ensembles of identically prepared physical systems or in the repeated 'measurements' on some trapped 'individual physical systems'. The outcomes of these measurements are, in general, some numerical time series registered by some macroscopic instruments. The various empirical probability distributions extracted from these time series were shown to be consistent with the probabilistic predictions of QT. More than 70 years ago the claim was made that QT provided the most complete description of 'individual' physical systems and outcomes of the measurements performed on 'individual' physical systems were obtained in an intrinsically random way. Spin polarization correlation experiments (SPCEs), performed to test the validity of Bell inequalities, clearly demonstrated the existence of strong long-range correlations and confirmed that the beams hitting far away detectors somehow preserve the memory of their common source which would be destroyed if the individual counts of far away detectors were purely random. Since the probabilities describe the random experiments and are not the attributes of the 'individual' physical systems, the claim that QT provides a complete description of 'individual' physical systems seems not only unjustified but also misleading and counter productive. In this paper, we point out that we even do not know whether QT is predictably complete because it has not been tested carefully enough. Namely, it was not proven that the time series of existing experimental data did not contain some stochastic fine structures that could have been averaged out by describing them in terms of the empirical probability distributions. In this paper, we advocate various statistical tests that could be used to search for such fine structures in the data and to

  13. Software Structure and WCET Predictability

    OpenAIRE

    Gebhard, Gernot; Cullmann, Christoph; Heckmann, Reinhold

    2011-01-01

    Being able to compute worst-case execution time bounds for tasks of an embedded software system with hard real-time constraints is crucial to ensure the correct (timing) behavior of the overall system. Any means to increase the (static) time predictability of the embedded software are of high interest -- especially due to the ever-growing complexity of such software systems. In this paper we study existing coding proposals and guidelines, such as MISRA-C, and investigate whether they simplify...

  14. 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

  15. 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.

  16. 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.

  17. 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

  18. Predicting the mechanism of phospholipidosis

    Directory of Open Access Journals (Sweden)

    Lowe Robert

    2012-01-01

    Full Text Available Abstract The mechanism of phospholipidosis is still not well understood. Numerous different mechanisms have been proposed, varying from direct inhibition of the breakdown of phospholipids to the binding of a drug compound to the phospholipid, preventing breakdown. We have used a probabilistic method, the Parzen-Rosenblatt Window approach, to build a model from the ChEMBL dataset which can predict from a compound's structure both its primary pharmaceutical target and other targets with which it forms off-target, usually weaker, interactions. Using a small dataset of 182 phospholipidosis-inducing and non-inducing compounds, we predict their off-target activity against targets which could relate to phospholipidosis as a side-effect of a drug. We link these targets to specific mechanisms of inducing this lysosomal build-up of phospholipids in cells. Thus, we show that the induction of phospholipidosis is likely to occur by separate mechanisms when triggered by different cationic amphiphilic drugs. We find that both inhibition of phospholipase activity and enhanced cholesterol biosynthesis are likely to be important mechanisms. Furthermore, we provide evidence suggesting four specific protein targets. Sphingomyelin phosphodiesterase, phospholipase A2 and lysosomal phospholipase A1 are shown to be likely targets for the induction of phospholipidosis by inhibition of phospholipase activity, while lanosterol synthase is predicted to be associated with phospholipidosis being induced by enhanced cholesterol biosynthesis. This analysis provides the impetus for further experimental tests of these hypotheses.

  19. 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

  20. Clinical importance of predicting radiosensitivity

    International Nuclear Information System (INIS)

    Full text: The optimal use of radiation therapy in cancer treatment is hampered by the application of normal tissue tolerance limits that are derived from population averages. Such limits do not reflect the considerable differences in susceptibility to radiation injury that exist among individuals. Development of assays that accurately predicted normal tissue tolerance in individual patients would permit real application of the concept of treatment to tolerance. By adjusting doses upwards or downwards to achieve a uniform probability of complication in each patient, the therapeutic ratio, i e., the probability of an uncomplicated cure, would be increased for the population as a whole. Although the pathogenesis of radiation injury is highly complex, clinical studies have demonstrated a significant correlation between the in vitro radiosensitivity of patients' fibroblasts and their risk of developing late connective tissue type complications of radiotherapy. While such assays lack the precision and practicality to be used clinically, they do establish the principle of prediction of normal tissue tolerance. Newer assays using surrogate endpoints for cell survival and incorporating insights into the effects of radiation on cellular growth, differentiation, senescence and cytokine production are being developed. Such assays may, in the future, be complemented or replaced by molecular and/or cytogenetic probes to derive robust estimates of individual tolerance. The goal of accurate prediction of individual tolerance for clinical use, while not imminent, does seem achievable

  1. 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.

  2. 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

  3. Predicting Abraham model solvent coefficients

    OpenAIRE

    Bradley, Jean-Claude; Abraham, Michael H; Acree, William E; Lang, Andrew SID

    2015-01-01

    Background The Abraham general solvation model can be used in a broad set of scenarios involving partitioning and solubility, yet is limited to a set of solvents with measured Abraham coefficients. Here we extend the range of applicability of Abraham’s model by creating open models that can be used to predict the solvent coefficients for all organic solvents. Results We created open random forest models for the solvent coefficients e, s, a, b, and v that had out-of-bag R2 values of 0.31, 0.77...

  4. Algorithms for appliance usage prediction

    OpenAIRE

    Truong, Ngoc Cuong

    2014-01-01

    Demand-Side Management (DSM) is one of the key elements of future Smart Electricity Grids. DSM involves mechanisms to reduce or shift the consumption of electricity in an attempt to minimise peaks. By so doing it is possible to avoid using expensive peaking plants that are also highly carbon emitting. A key challenge in DSM, however, is the need to predict energy usage from specific home appliances accurately so that consumers can be notified to shift or reduce the use of high energy-consumin...

  5. 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.

  6. Uncertainties in debris growth predictions

    International Nuclear Information System (INIS)

    The growth of artificial space debris in Earth orbit may pose a significant hazard to satellites in the future though the collision hazard to operational spacecraft is presently manageable. The stability of the environment is dependent on the growth of debris from satellite deployment, mission operations and fragmentation events. Growth trends of the trackable on-orbit population are investigated highlighting the complexities and limitations of using the data that supports this modeling. The debris produced by breakup events may be a critical aspect of the present and future environment. As a result, growth predictions produced using existing empirically-based models may have large, possibly even unacceptable, uncertainties

  7. 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.

  8. $\\Theta+$: Another Explanation and Prediction

    CERN Document Server

    Kishimoto, T; Kishimoto, Tadafumi; Sato, Toru

    2003-01-01

    Recently the so-called $\\Theta^+$ resonance has been reported first from SPring8\\cite{nakano} and many following experiments showed clear evidence of the state. The existence of $\\Theta^+$ is now confirmed. Since $\\Theta^+$ exclusively decays into either $K^+ n$ or $K^0 p$, it is explained to be the long waited penta-quark state which includes $ u u d d \\bar{s}$ quarks. However, one yet has to obtain consistent picture of $\\Theta^+$. We try to explain $\\Theta^+$ in a conventional picture and show that such picture leads to new prediction on kaon and pion system.

  9. 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.

  10. Link prediction in Foursquare network

    OpenAIRE

    Fortuna, Rok; Marovt, Urban

    2016-01-01

    Foursquare is an online social network and can be represented with a bipartite network of users and venues. A user-venue pair is connected if a user has checked-in at that venue. In the case of Foursquare, network analysis techniques can be used to enhance the user experience. One such technique is link prediction, which can be used to build a personalized recommendation system of venues. Recommendation systems in bipartite networks are very often designed using the global ranking method and ...

  11. 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 of...

  12. 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.

  13. 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)

  14. 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.

  15. 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)

  16. Seizure prediction and its applications.

    Science.gov (United States)

    Iasemidis, Leon D

    2011-10-01

    Epilepsy is characterized by intermittent, paroxysmal, hypersynchronous electrical activity that may remain localized and/or spread and severely disrupt the brain's normal multitask and multiprocessing function. Epileptic seizures are the hallmarks of such activity. The ability to issue warnings in real time of impending seizures may lead to novel diagnostic tools and treatments for epilepsy. Applications may range from a warning to the patient to avert seizure-associated injuries, to automatic timely administration of an appropriate stimulus. Seizure prediction could become an integral part of the treatment of epilepsy through neuromodulation, especially in the new generation of closed-loop seizure control systems. PMID:21939848

  17. Radio Channel State Prediction by Kalman Filter

    Directory of Open Access Journals (Sweden)

    Peter Ziacik

    2005-01-01

    Full Text Available In this article there is the description Kalman filter using as a radio channel state predictor. Simulator of prediction has been created in MATLAB environment and it is capable to simulate the prediction of radio signal envelope by Clark’s model of radio channel, which is implemented to the simulator. Simulations were realized for prediction range 0.41 ms and 6.24 ms and as comparing criterion we used the prediction error. It is clear from simulations, that with the duration of prediction the prediction error is enlarging, which may cause the erroneous decision of adaptation algorithms.

  18. 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.

  19. 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...

  20. PIPS: pathogenicity island prediction software.

    Directory of Open Access Journals (Sweden)

    Siomar C Soares

    Full Text Available The adaptability of pathogenic bacteria to hosts is influenced by the genomic plasticity of the bacteria, which can be increased by such mechanisms as horizontal gene transfer. Pathogenicity islands play a major role in this type of gene transfer because they are large, horizontally acquired regions that harbor clusters of virulence genes that mediate the adhesion, colonization, invasion, immune system evasion, and toxigenic properties of the acceptor organism. Currently, pathogenicity islands are mainly identified in silico based on various characteristic features: (1 deviations in codon usage, G+C content or dinucleotide frequency and (2 insertion sequences and/or tRNA genetic flanking regions together with transposase coding genes. Several computational techniques for identifying pathogenicity islands exist. However, most of these techniques are only directed at the detection of horizontally transferred genes and/or the absence of certain genomic regions of the pathogenic bacterium in closely related non-pathogenic species. Here, we present a novel software suite designed for the prediction of pathogenicity islands (pathogenicity island prediction software, or PIPS. In contrast to other existing tools, our approach is capable of utilizing multiple features for pathogenicity island detection in an integrative manner. We show that PIPS provides better accuracy than other available software packages. As an example, we used PIPS to study the veterinary pathogen Corynebacterium pseudotuberculosis, in which we identified seven putative pathogenicity islands.

  1. 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

  2. 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.

  3. 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.

  4. 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 ...

  5. 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

  6. 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...

  7. 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;...

  8. Detection and Prediction of Epileptic Seizures

    DEFF Research Database (Denmark)

    Duun-Henriksen, Jonas

    monitoring of their brain waves. More specifically, three issues were investigated: The feasibility of automatic seizure prediction, optimization of automatic seizure detection algorithms, and the link between intra- and extracranial EEG. Regarding feasibility of automatic seizure prediction, neither the...

  9. Protein Residue Contacts and Prediction Methods.

    Science.gov (United States)

    Adhikari, Badri; Cheng, Jianlin

    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

  10. The Use of Linear Programming for Prediction.

    Science.gov (United States)

    Schnittjer, Carl J.

    The purpose of the study was to develop a linear programming model to be used for prediction, test the accuracy of the predictions, and compare the accuracy with that produced by curvilinear multiple regression analysis. (Author)

  11. 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

  12. 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...

  13. Prediction Markets to Forecast Electricity Demand

    OpenAIRE

    Luciano I. de Castro; Cramton, Peter

    2009-01-01

    Forecasting electricity demand for future years is an essential step in resource planning. A common approach is for the system operator to predict future demand from the estimates of individual distribution companies. However, the predictions thus obtained may be of poor quality, since the reporting incentives are unclear. We propose a prediction market as a form of forecasting future demand for electricity. We describe how to implement a simple prediction market for continuous variables, usi...

  14. 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.

  15. 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.

  16. 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...

  17. 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.

  18. Numerical prediction of slamming loads

    DEFF Research Database (Denmark)

    Seng, Sopheak; Jensen, Jørgen J; Pedersen, Preben T

    2012-01-01

    calculations in a realistic wave environment.Both the global and the local slamming loads are assessed numerically using a finite-volume formulation with the free surface captured by a volume-of-fluid technique. This numerical procedure is justified by comprehensive validation studies where numerically......It is important to include the contribution of the slamming-induced response in the structural design of large vessels with a significant bow flare. At the same time it is a challenge to develop rational tools to determine the slamming-induced loads and the prediction of their occurrence. Today it...... is normal practice to apply a standard sea-keeping procedure to determine the relative velocity distribution between the water surface and the hull and then to estimate the bottom slamming loads and the bow-flare slamming loads based on two-dimensional formulations similarly to water-entry problems...

  19. 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)

  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. 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.......  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...

  2. 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.

  3. Rhythmic complexity and predictive coding

    DEFF Research Database (Denmark)

    Vuust, Peter; Witek, Maria A G

    2014-01-01

    ofmusic (“meter”). Finally, we review empirical studies of the neural and behavioral effects ofsyncopation, polyrhythm and groove, and propose how these studies can be seen as specialcases of the PC theory.We argue that musical rhythm exploits the brain’s general principlesof prediction and propose......Musical rhythm, consisting of apparently abstract intervals of accented temporal events,has a remarkable capacity to move our minds and bodies. How does the cognitive systemenable our experiences of rhythmically complex music? In this paper, we describe somecommon forms of rhythmic complexity...... in music and propose the theory of predictivecoding (PC) as a framework for understanding how rhythm and rhythmic complexit y areprocessed in the brain. We also consider why we feel so compelled by rhythmic tensionin music. First, we consider theories of rhythm and meter perception, which...

  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. Predicting cooling tower plume dispersion

    International Nuclear Information System (INIS)

    An assessment of the effects of visible cooling tower plumes on the local environment can be a necessary part of any proposal for a new large industrial process. Predictions of the dispersion of plumes from cooling towers are based on methods developed for chimney emissions. However, the kinds of criteria used to judge the acceptability of cooling tower plumes are different from those used for stack plumes. The frequency of long elevated plumes and the frequency of ground fogging are the two main issues. It is shown that events associated with significant plumes visibility are dependent both on the operating characteristics of the tower and on the occurrence of certain meteorological conditions. The dependence on atmospheric conditions is shown to be fairly complex and simple performance criteria based on the exit conditions from the tower are not sufficient for assessments. (author)

  6. Predicting Neutrinoless Double Beta Decay

    CERN Document Server

    Hirsch, M; Valle, J W F; Moral, A V; Ma, Ernest

    2005-01-01

    We give predictions for the neutrinoless double beta decay rate in a simple variant of the A_4 family symmetry model. We show that there is a lower bound for the neutrinoless double beta decay amplitude even in the case of normal hierarchical neutrino masses, corresponding to an effective mass parameter |m_{ee}| >= 0.17 \\sqrt{\\Delta m^2_{ATM}}. This result holds both for the CP conserving and CP violating cases. In the latter case we show explicitly that the lower bound on |m_{ee}| is sensitive to the value of the Majorana phase. We conclude therefore that in our scheme, neutrinoless double beta decay may be accessible to the next generation of high sensitivity experiments.

  7. Pretest Predictions for Ventilation Tests

    International Nuclear Information System (INIS)

    The objective of this calculation is to predict the temperatures of the ventilating air, waste package surface, concrete pipe walls, and insulation that will be developed during the ventilation tests involving various test conditions. The results will be used as input to the following three areas: (1) Decisions regarding testing set-up and performance. (2) Assessing how best to scale the test phenomena measured. (3) Validating numerical approach for modeling continuous ventilation. The scope of the calculation is to identify the physical mechanisms and parameters related to thermal response in the ventilation tests, and develop and describe numerical methods that can be used to calculate the effects of continuous ventilation. Sensitivity studies to assess the impact of variation of linear power densities (linear heat loads) and ventilation air flow rates are included. The calculation is limited to thermal effect only

  8. Evolution of property predictability during conceptual design

    DEFF Research Database (Denmark)

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

    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 is that the...... level of property predictability will increase along with the progression of the design process as well....

  9. 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.

  10. 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...

  11. 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

  12. 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.

  13. 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.

  14. 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

  15. 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...... integrate expertise 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...

  16. Efficient marker data utilization in genomic prediction

    DEFF Research Database (Denmark)

    Edriss, Vahid

    Genomic prediction is a novel method to recognize the best animals for breeding. The aim of this PhD is to improve the accuracy of genomic prediction in dairy cattle by effeiently utilizing marker data. The thesis focuses on three aspects for improving the genomc prediction, which are: criteria 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...

  17. Evolution of property predictability during conceptual design

    DEFF Research Database (Denmark)

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

    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 to the...... requirements set for the task. As a result, we identified three different patterns of property predictability behaviour. These patterns consist of properties of which predictability is relatively high throughout the early phases of the design process, properties of which predictability shows a high increase...

  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. 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...

  20. 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,...

  1. 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.

  2. An Introduction to Artificial Prediction Markets

    CERN Document Server

    Barbu, Adrian

    2011-01-01

    Prediction markets are used in real life to predict outcomes of interest such as presidential elections. This paper presents a mathematical theory of artificial prediction markets for supervised learning of conditional probability estimators. The artificial prediction market is a novel method for fusing the prediction information of features or trained classifiers, where the fusion result is the contract price on the possible outcomes. The market can be trained online by updating the participants' budgets using training examples. Inspired by the real prediction markets, the equations that govern the market are derived from simple and reasonable assumptions. Efficient numerical algorithms are presented for solving these equations. The obtained artificial prediction market is shown to be a maximum likelihood estimator. It generalizes linear aggregation, existent in boosting and random forest, as well as logistic regression and some kernel methods. Furthermore, the market mechanism allows the aggregation of spec...

  3. Quantitative T2 magnetic resonance imaging compared to morphological grading of the early cervical intervertebral disc degeneration: an evaluation approach in asymptomatic young adults.

    Directory of Open Access Journals (Sweden)

    Chun Chen

    Full Text Available OBJECTIVE: The objective of this study was to evaluate the efficacy of quantitative T2 magnetic resonance imaging (MRI for quantifying early cervical intervertebral disc (IVD degeneration in asymptomatic young adults by correlating the T2 value with Pfirrmann grade, sex, and anatomic level. METHODS: Seventy asymptomatic young subjects (34 men and 36 women; mean age, 22.80±2.11 yr; range, 18-25 years underwent 3.0-T MRI to obtain morphological data (one T1-fast spin echo (FSE and three-plane T2-FSE, used to assign a Pfirrmann grade (I-V and for T2 mapping (multi-echo spin echo. T2 values in the nucleus pulposus (NP, n = 350 and anulus fibrosus (AF, n = 700 were obtained. Differences in T2 values between sexes and anatomic level were evaluated, and linear correlation analysis of T2 values versus degenerative grade was conducted. FINDINGS: Cervical IVDs of healthy young adults were commonly determined to be at Pfirrmann grades I and II. T2 values of NPs were significantly higher than those of AF at all anatomic levels (P0.05. T2 values decreased linearly with degenerative grade. Linear correlation analysis revealed a strong negative association between the Pfirrmann grade and the T2 values of the NP (P = 0.000 but not the T2 values of the AF (P = 0.854. However, non-degenerated discs (Pfirrmann grades I and II showed a wide range of T2 relaxation time. T2 values according to disc degeneration level classification were as follows: grade I (>62.03 ms, grade II (54.60-62.03 ms, grade III (<54.60 ms. CONCLUSIONS: T2 quantitation provides a more sensitive and robust approach for detecting and characterizing the early stage of cervical IVD degeneration and to create a reliable quantitative in healthy young adults.

  4. 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.

  5. A Female Ligamentous Cervical Spine Finite Element Model Validated for Physiological Loads.

    Science.gov (United States)

    Östh, Jonas; Brolin, Karin; Svensson, Mats Y; Linder, Astrid

    2016-06-01

    Mathematical cervical spine models allow for studying of impact loading that can cause whiplash associated disorders (WAD). However, existing models only cover the male anthropometry, despite the female population being at a higher risk of sustaining WAD in automotive rear-end impacts. The aim of this study is to develop and validate a ligamentous cervical spine intended for biomechanical research on the effect of automotive impacts. A female model has the potential to aid the design of better protection systems as well as improve understanding of injury mechanisms causing WAD. A finite element (FE) mesh was created from surface data of the cervical vertebrae of a 26-year old female (stature 167 cm, weight 59 kg). Soft tissues were generated from the skeletal geometry and anatomical literature descriptions. Ligaments were modeled with nonlinear elastic orthotropic membrane elements, intervertebral disks as composites of nonlinear elastic bulk elements, and orthotropic anulus fibrosus fiber layers, while cortical and trabecular bones were modeled as isotropic plastic-elastic. The model has geometrical features representative of the female cervical spine-the largest average difference compared with published anthropometric female data was the vertebral body depth being 3.4% shorter for the model. The majority the cervical segments compare well with respect to biomechanical data at physiological loads, with the best match for flexion-extension loads and less biofidelity for axial rotation. An average female FE ligamentous cervical spine model was developed and validated with respect to physiological loading. In flexion-extension simulations with the developed female model and an existing average male cervical spine model, a greater range of motion (ROM) was found in the female model. PMID:26974520

  6. 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.

  7. DC Motor Control Predictive Models

    Directory of Open Access Journals (Sweden)

    Ravinesh Singh

    2006-01-01

    Full Text Available DC motor speed and position controls are fundamental in vehicles in general and robotics in particular. This study presents a mathematical model for correlating the interactions of some DC motor control parameters such as duty cycle, terminal voltage, frequency and load on some responses such as output current, voltage and speed by means of response surface methodology. For this exercise, a five-level full factorial design was chosen for experimentation using a peripheral interface controller (PIC-based universal pulse width modulation (PWM H-Bridge motor controller built in-house. The significance of the mathematical model developed was ascertained using regression analysis method. The results obtained show that the mathematical models are useful not only for predicting optimum DC motor parameters for achieving the desired quality but for speed and position optimization. Using the optimal combination of these parameters is useful in minimizing the power consumption and realization of the optimal speed and invariably position control of DC motor operations.

  8. Predictive Modeling of Tokamak Configurations*

    Science.gov (United States)

    Casper, T. A.; Lodestro, L. L.; Pearlstein, L. D.; Bulmer, R. H.; Jong, R. A.; Kaiser, T. B.; Moller, J. M.

    2001-10-01

    The Corsica code provides comprehensive toroidal plasma simulation and design capabilities with current applications [1] to tokamak, reversed field pinch (RFP) and spheromak configurations. It calculates fixed and free boundary equilibria coupled to Ohm's law, sources, transport models and MHD stability modules. We are exploring operations scenarios for both the DIII-D and KSTAR tokamaks. We will present simulations of the effects of electron cyclotron heating (ECH) and current drive (ECCD) relevant to the Quiescent Double Barrier (QDB) regime on DIII-D exploring long pulse operation issues. KSTAR simulations using ECH/ECCD in negative central shear configurations explore evolution to steady state while shape evolution studies during current ramp up using a hyper-resistivity model investigate startup scenarios and limitations. Studies of high bootstrap fraction operation stimulated by recent ECH/ECCD experiments on DIIID will also be presented. [1] Pearlstein, L.D., et al, Predictive Modeling of Axisymmetric Toroidal Configurations, 28th EPS Conference on Controlled Fusion and Plasma Physics, Madeira, Portugal, June 18-22, 2001. * Work performed under the auspices of the U.S. Department of Energy by the University of California, Lawrence Livermore National Laboratory under contract No. W-7405-Eng-48.

  9. 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

  10. 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.

  11. 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...

  12. 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/.

  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. 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)(...

  15. Prediction of mountain stream morphology

    Science.gov (United States)

    Wohl, Ellen; Merritt, David

    2005-08-01

    We use a large and diverse data set from mountain streams around the world to explore relationships between reach-scale channel morphology and control variables. The data set includes 177 step-pool reaches, 44 plane-bed reaches, and 114 pool-riffle reaches from the western United States, Panama, and New Zealand. We performed several iterations of stepwise discriminant analysis on these data. A three-variable discriminant function using slope (S), D84, and channel width (w) produced an error rate of 24% for the entire data set. Seventy percent of plane-bed reaches were correctly classified (16% incorrectly classified as pool-riffle and 14% incorrectly classified as step-pool). Sixty-seven percent of pool-riffle channels were correctly classified (31% incorrectly classified as plane-bed and 2% as step-pool). Eighty-nine percent of step-pool reaches were correctly classified (9% incorrectly classified as plane-bed and 2% as pool-riffle). The partial R2 values and F tests indicate that S is by far the most significant single explanatory variable. Comparison of the eight discriminant functions developed using different data sets indicates that no single variable is present in all functions, suggesting that the discriminant functions are sensitive to the specific stream reaches being analyzed. However, the three-variable discriminant function developed from the entire data set correctly classified 69% of the 159 channels included in an independent validation data set. The ability to accurately classify channel type in other regions using the three-variable discriminant function developed from the entire data set has important implications for water resources management, such as facilitating prediction of channel morphology using regional S-w-D84 relations calibrated with minimal field work.

  16. 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.

  17. An iterative approach of protein function prediction

    Directory of Open Access Journals (Sweden)

    Chi Xiaoxiao

    2011-11-01

    Full Text Available Abstract Background Current approaches of predicting protein functions from a protein-protein interaction (PPI dataset are based on an assumption that the available functions of the proteins (a.k.a. annotated proteins will determine the functions of the proteins whose functions are unknown yet at the moment (a.k.a. un-annotated proteins. Therefore, the protein function prediction is a mono-directed and one-off procedure, i.e. from annotated proteins to un-annotated proteins. However, the interactions between proteins are mutual rather than static and mono-directed, although functions of some proteins are unknown for some reasons at present. That means when we use the similarity-based approach to predict functions of un-annotated proteins, the un-annotated proteins, once their functions are predicted, will affect the similarities between proteins, which in turn will affect the prediction results. In other words, the function prediction is a dynamic and mutual procedure. This dynamic feature of protein interactions, however, was not considered in the existing prediction algorithms. Results In this paper, we propose a new prediction approach that predicts protein functions iteratively. This iterative approach incorporates the dynamic and mutual features of PPI interactions, as well as the local and global semantic influence of protein functions, into the prediction. To guarantee predicting functions iteratively, we propose a new protein similarity from protein functions. We adapt new evaluation metrics to evaluate the prediction quality of our algorithm and other similar algorithms. Experiments on real PPI datasets were conducted to evaluate the effectiveness of the proposed approach in predicting unknown protein functions. Conclusions The iterative approach is more likely to reflect the real biological nature between proteins when predicting functions. A proper definition of protein similarity from protein functions is the key to predicting

  18. Multiple architecture system for wind speed prediction

    International Nuclear Information System (INIS)

    A new approach based on multiple architecture system (MAS) for the prediction of wind speed is proposed. The motivation behind the proposed approach is to combine the complementary predictive powers of multiple models in order to improve the performance of the prediction process. The proposed MAS can be implemented by associating the predictions obtained from the different regression algorithms (MLR, MLP, RBF and SVM) making up the ensemble by three fusion strategies (simple, weighted and non-linear). The efficiency of the proposed approach has been assessed on a real data set recorded from seven locations in Algeria during a period of 10 years. The experimental results point out that the proposed MAS approach is capable of improving the precision of the wind speed prediction compared to the traditional prediction methods.

  19. 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

  20. 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].

  1. 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...

  2. Return Predictability, Model Uncertainty, and Robust Investment

    OpenAIRE

    Lukas, Manuel

    2013-01-01

    Stock return predictability is subject to great uncertainty. In this paper we usethe model confidence set approach to quantify uncertainty about expected utilityfrom investment, accounting for potential return predictability. For monthly USdata and six representative return prediction models, we find that confidence setsare very wide, change significantly with the predictor variables, and frequentlyinclude expected utilities for which the investor prefers not to invest. The lattermotivates a ...

  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. Mobile Homophily and Social Location Prediction

    OpenAIRE

    Bapierre, Halgurt; Jesdabodi, Chakajkla; Groh, Georg

    2015-01-01

    The mobility behavior of human beings is predictable to a varying degree e.g. depending on the traits of their personality such as the trait extraversion - introversion: the mobility of introvert users may be more dominated by routines and habitual movement patterns, resulting in a more predictable mobility behavior on the basis of their own location history while, in contrast, extrovert users get about a lot and are explorative by nature, which may hamper the prediction of their mobility. Ho...

  5. Do university entrance exams predict academic achievement?

    OpenAIRE

    Häkkinen, Iida

    2004-01-01

    The study examines which factors predict academic performance at university and compares the predictive values of subject-related entrance exams and indicators of past school performance. The results show that in the fields of engineering and social sciences entrance exams predict both graduation and the number of study credits better than past performance. In education past school performance is a better predictor of graduation. Changing the admission rule to school grades would affect the a...

  6. 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.

  7. 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 ....

  8. 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...

  9. Shape Prediction Linear Algorithm Using Fuzzy

    Directory of Open Access Journals (Sweden)

    Navjot Kaur

    2012-10-01

    Full Text Available The goal of the proposed method is to develop shape prediction algorithm using fuzzy that is computationally fast and invariant. To predict the overlapping and joined shapes accurately, a method of shape prediction based on erosion and over segmentation is used to estimate values for dependent variables from previously unseen predictor values based on the variation in an underlying learning data set.

  10. RESULTS FROM A SIMPLE PREDICTION CONTEST

    OpenAIRE

    Calvin Blackwell

    2011-01-01

    In a prediction contest participants compete for a prize by submitting guesses regarding an unknown variable; the winner of the contest is the participant who submits the most accurate guess. In this paper the results of a simple prediction contest are reported. In the contest, certain members of the administration of a medium-sized university were asked to predict the number of freshmen deposits the university would receive by its spring deadline. Contest participants were told that the cont...

  11. Topology and prediction of RNA pseudoknots

    DEFF Research Database (Denmark)

    Reidys, Christian; Huang, Fenix; Andersen, Jørgen Ellegaard;

    2011-01-01

    Motivation: Several dynamic programming algorithms for predicting RNA structures with pseudoknots have been proposed that differ dramatically from one another in the classes of structures considered. Results: Here, we use the natural topological classification of RNA structures in terms of...... dynamic programming approach for energy minimization, partition function and stochastic sampling. It admits a topology-dependent parametrization of pseudoknot penalties that increases the sensitivity and positive predictive value of predicted base pairs by 10–20% compared with earlier approaches. More...

  12. 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 ...

  13. 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.

  14. Essays on Return Predictability in Financial Markets

    OpenAIRE

    Mang, Chan R.

    2012-01-01

    My thesis examines return predictability in government bond markets and currency markets. In Chapter 1, I take the term structure model in Cochrane and Piazzesi (2008) and construct currency market prices. The implied currency market prices are then counterfactually volatile and predictable, at least with respect to commonly used predictor variables. Getting the model closer to currency market data means reducing bond risk compensation but doing so nearly eliminates predictability in bond mar...

  15. Video Traffic Prediction Using Neural Networks

    OpenAIRE

    Miloš Oravec; Miroslav Petráš; Filip Pilka

    2008-01-01

    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 n...

  16. AIDS: predicting cases nationally and locally.

    OpenAIRE

    Tennison, B R; Hagard, S

    1988-01-01

    Models for predicting the future course of the AIDS epidemic can be divided into five types: trend extrapolation models, compartment models, models based on the incubation period, comparison models, and models produced by expert committees. To predict the numbers of cases of AIDS in the United Kingdom and in East Anglia and Cambridge a two stage approach was chosen using trend extrapolation for the national case reports followed by reduction in scale to the two localities. The method predicte...

  17. Mining Twitter Data for Resource Usage Prediction

    OpenAIRE

    2012-01-01

    This thesis investigates the predictability of Twitter traffic for topic-related websites’ resource requirements by developing and implementing a data mining methodology. The new traffic correlation mining process is able to extract traffic surges and develop potential predictive mining and correlation techniques between Twitter and the corresponding forum. Thorough testing of this data mining methodology has been performed, and the results show that using Twitter data to predict imminent res...

  18. 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...

  19. 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.

  20. Earthquake prediction decision and risk matrix

    Science.gov (United States)

    Zou, Qi-Jia

    1993-08-01

    The issuance of an earthquake prediction must cause widespread social responses. It is suggested and discussed in this paper that the comprehensive decision issue for earthquake prediction considering the factors of the social and economic cost. The method of matrix decision for earthquake prediction (MDEP) is proposed in this paper and it is based on the risk matrix. The goal of decision is that search the best manner issuing earthquake prediction so that minimize the total losses of economy. The establishment and calculation of the risk matrix is discussed, and the decision results taking account of economic factors and not considering the economic factors are compared by examples in this paper.

  1. RNA structure prediction: progress and perspective

    CERN Document Server

    Shi, Ya-Zhou; Wang, Feng-Hua; Tan, Zhi-Jie

    2014-01-01

    Many recent exciting discoveries have revealed the versatility of RNAs and their importance in a variety of cellular functions which are strongly coupled to RNA structures. To understand the functions of RNAs, some structure prediction models have been developed in recent years. In this review, the progress in computational models for RNA structure prediction is introduced and the distinguishing features of many outstanding algorithms are discussed, emphasizing three dimensional (3D) structure prediction. A promising coarse-grained model for predicting RNA 3D structure, stability and salt effect is also introduced briefly. Finally, we discuss the major challenges in the RNA 3D structure modeling.

  2. 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.

  3. Prediction of reliability of PDC CPU board

    International Nuclear Information System (INIS)

    To predict the reliability of electronic equipment including digital control systems, the data from MIL-HDBK217 and Bellcore TR-332 is used. But these data have some weakness that is old or based on inaccurate specification and environment condition. Each data shows different prediction results because each one has specific failure data and prediction methods The reliability of Wolsong 1 PDC CPU board was evaluated with various data to identify effects of different data. The results were analyzed with experienced failure data and vendor data. Through the analysis, it was demonstrated that the predicted failure rate is sensitive to the selection of data and method

  4. 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.

  5. 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...

  6. 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.

  7. 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.

  8. Stock market index prediction using neural networks

    Science.gov (United States)

    Komo, Darmadi; Chang, Chein-I.; Ko, Hanseok

    1994-03-01

    A neural network approach to stock market index prediction is presented. Actual data of the Wall Street Journal's Dow Jones Industrial Index has been used for a benchmark in our experiments where Radial Basis Function based neural networks have been designed to model these indices over the period from January 1988 to Dec 1992. A notable success has been achieved with the proposed model producing over 90% prediction accuracies observed based on monthly Dow Jones Industrial Index predictions. The model has also captured both moderate and heavy index fluctuations. The experiments conducted in this study demonstrated that the Radial Basis Function neural network represents an excellent candidate to predict stock market index.

  9. 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.

  10. 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....

  11. 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

  12. 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.

  13. Initial Value Predictability of Intrinsic Oceanic Modes and Implications for Decadal Prediction over North America

    Energy Technology Data Exchange (ETDEWEB)

    Branstator, Grant

    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 artclimate 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 tbe 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

  14. Transfer of predictive signals across saccades

    Directory of Open Access Journals (Sweden)

    PetraVetter

    2012-06-01

    Full Text Available Predicting visual information facilitates efficient processing of visual signals. Higher visual areas can support the processing of incoming visual information by generating predictive models that are fed back to lower visual areas. Functional brain imaging has previously shown that predictions interact with visual input already at the level of the primary visual cortex (V1; Alink et al., 2010; Harrison et al., 2007. Given that fixation changes up to four times a second in natural viewing conditions, cortical predictions are effective in V1 only if they are fed back in time for the processing of the next stimulus and at the corresponding new retinotopic position. Here, we tested whether spatio-temporal predictions are updated before, during or shortly after an interhemifield saccade is executed, and thus, whether the predictive signal is transferred swiftly across hemifields. Using an apparent motion illusion, we induced an internal motion model that is known to produce a spatio-temporal prediction signal along the apparent motion trace in V1 (Muckli et al., 2005, Alink et al., 2010. We presented participants with both visually predictable and unpredictable targets on the apparent motion trace. During the task, participants saccaded across the illusion whilst detecting the target. As found previously, predictable stimuli were detected more frequently than unpredictable stimuli. Furthermore, we found that the detection advantage of predictable targets is detectable as early as 50-100 ms after saccade offset. This result demonstrates the rapid nature of the transfer of a spatio-temporally precise predictive signal across hemifields, in a paradigm previously shown to modulate V1.

  15. 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

  16. 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...

  17. 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 and...

  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. 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

  20. 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)

  1. Prediction of treatment response to adalimumab

    DEFF Research Database (Denmark)

    Krintel, S 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 algori...

  2. 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 be......-varying economic uncertainty and changes in risk aversion, or market fears, respectively....

  3. 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...

  4. Protein secondary structure: category assignment and predictability

    DEFF Research Database (Denmark)

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

    2001-01-01

    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...

  5. How to Establish Clinical Prediction Models.

    Science.gov (United States)

    Lee, Yong Ho; Bang, Heejung; Kim, Dae Jung

    2016-03-01

    A clinical prediction model can be applied to several challenging clinical scenarios: screening high-risk individuals for asymptomatic disease, predicting future events such as disease or death, and assisting medical decision-making and health education. Despite the impact of clinical prediction models on practice, prediction modeling is a complex process requiring careful statistical analyses and sound clinical judgement. Although there is no definite consensus on the best methodology for model development and validation, a few recommendations and checklists have been proposed. In this review, we summarize five steps for developing and validating a clinical prediction model: preparation for establishing clinical prediction models; dataset selection; handling variables; model generation; and model evaluation and validation. We also review several studies that detail methods for developing clinical prediction models with comparable examples from real practice. After model development and vigorous validation in relevant settings, possibly with evaluation of utility/usability and fine-tuning, good models can be ready for the use in practice. We anticipate that this framework will revitalize the use of predictive or prognostic research in endocrinology, leading to active applications in real clinical practice. PMID:26996421

  6. 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

  7. Audiovisual biofeedback improves motion prediction accuracy

    OpenAIRE

    Pollock, Sean; Lee, Danny; Keall, Paul; Kim, Taeho

    2013-01-01

    Purpose: The accuracy of motion prediction, utilized to overcome the system latency of motion management radiotherapy systems, is hampered by irregularities present in the patients’ respiratory pattern. Audiovisual (AV) biofeedback has been shown to reduce respiratory irregularities. The aim of this study was to test the hypothesis that AV biofeedback improves the accuracy of motion prediction.

  8. 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...

  9. 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.

  10. A blind test of photometric redshift prediction

    OpenAIRE

    Hogg, David W.; Cohen, Judith G.; Blandford, Roger; Gwyn, Stephen D. J.; Hartwick, F. D. A.; Mobasher, B.; Mazzei, Paula; Sawicki, Marcin; Lin, Huan; Yee, H. K. C.; Connolly, Andrew J; Brunner, Robert J.; Csabai, Istvan; Dickinson, Mark; SubbaRao, Mark U.

    1998-01-01

    Results of a blind test of photometric redshift predictions against spectroscopic galaxy redshifts obtained in the Hubble Deep Field with the Keck Telescope are presented. The best photometric redshift schemes predict spectroscopic redshifts with a redshift accuracy of |Delta-z|

  11. 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

  12. Ultrasonic echolucent carotid plaques predict future strokes

    DEFF Research Database (Denmark)

    Grønholdt, Marie-Louise; Nordestgaard, B G; Schroeder, T V; Vorstrup, S; Sillesen, H

    2001-01-01

    We tested prospectively the hypothesis that stroke development can be predicted by echolucency of carotid atherosclerotic plaques in previously symptomatic and asymptomatic patients.......We tested prospectively the hypothesis that stroke development can be predicted by echolucency of carotid atherosclerotic plaques in previously symptomatic and asymptomatic patients....

  13. Predicting User Actions in Software Processes

    CERN Document Server

    Deynet, Michael

    2011-01-01

    This paper describes an approach for user (e.g. SW architect) assisting in software processes. The approach observes the user's action and tries to predict his next step. For this we use approaches in the area of machine learning (sequence learning) and adopt these for the use in software processes. Keywords: Software engineering, Software process description languages, Software processes, Machine learning, Sequence prediction

  14. 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.

  15. 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…

  16. 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.

  17. 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.

  18. 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) ...

  19. 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...

  20. The Link Prediction Problem in Bipartite Networks

    CERN Document Server

    Kunegis, Jérôme; Albayrak, Sahin

    2010-01-01

    We define and study the link prediction problem in bipartite networks, specializing general link prediction algorithms to the bipartite case. In a graph, a link prediction function of two vertices denotes the similarity or proximity of the vertices. Common link prediction functions for general graphs are defined using paths of length two between two nodes. Since in a bipartite graph adjacency vertices can only be connected by paths of odd lengths, these functions do not apply to bipartite graphs. Instead, a certain class of graph kernels (spectral transformation kernels) can be generalized to bipartite graphs when the positive-semidefinite kernel constraint is relaxed. This generalization is realized by the odd component of the underlying spectral transformation. This construction leads to several new link prediction pseudokernels such as the matrix hyperbolic sine, which we examine for rating graphs, authorship graphs, folksonomies, document--feature networks and other types of bipartite networks.

  1. 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...

  2. 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.

  3. 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

  4. 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...

  5. Nonlinear chaotic model for predicting storm surges

    Directory of Open Access Journals (Sweden)

    M. Siek

    2010-09-01

    Full Text Available This paper addresses the use of the methods of nonlinear dynamics and chaos theory for building a predictive chaotic model from time series. The chaotic model predictions are made by the adaptive local models based on the dynamical neighbors found in the reconstructed phase space of the observables. We implemented the univariate and multivariate chaotic models with direct and multi-steps prediction techniques and optimized these models using an exhaustive search method. The built models were tested for predicting storm surge dynamics for different stormy conditions in the North Sea, and are compared to neural network models. The results show that the chaotic models can generally provide reliable and accurate short-term storm surge predictions.

  6. 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.

  7. 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.

  8. 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...

  9. 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.

  10. Are GMO's Predictions Prescient? Using them to predict Vanguard's Mutual Fund Returns

    OpenAIRE

    Tower, Edward

    2007-01-01

    Each month, GMO publishes on the web its predictions of the real rate of return for various asset styles over the next seven years. Its web library also retains its quarterly predictions, dating back to the end of the second quarter of 2000. I ask whether these predictions are accurate. My technique is to compare the predictions with the performance of the Vanguard mutual funds that invest in these styles.

  11. 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 ...

  12. Cloud Prediction of Protein Structure and Function with PredictProtein for Debian

    OpenAIRE

    Cedric Staniewski; Burkhard Rost; Eva Reisinger; Christian Mertes; Julia Ertl; Simon Domke; Christof Angermüller; Ariane Böhm; Milot Mirdita; Martin Steinegger; László Kaján; Esmeralda Vicedo; Guy Yachdav

    2013-01-01

    We report the release of PredictProtein for the Debian operating system and derivatives, such as Ubuntu, Bio-Linux, and Cloud BioLinux. The PredictProtein suite is available as a standard set of open source Debian packages. The release covers the most popular prediction methods from the Rost Lab, including methods for the prediction of secondary structure and solvent accessibility (profphd), nuclear localization signals (predictnls), and intrinsically disordered regions (norsnet). We also pre...

  13. 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

  14. 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.

  15. 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.

  16. 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

  17. 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.

  18. 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.

  19. Development of anomalous detection using movie prediction

    International Nuclear Information System (INIS)

    In this research, the new method to predict the near-future of the movie images captured by video camera based on the combination of the Principle Component Analysis (PCA) and the Singular Spectral Analysis (SSA). In the normal condition of machines, the real-time captured movie is supposed to correspond to the predicted one. If the error between the both becomes significantly large, it may suggest some anomalous motion of the machines. So the movie prediction method has a possibility of the sensitive anomalous detection system. (author)

  20. 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...... find that confidence sets are very wide, change significantly with the predictor variables, and frequently include expected utilities for which the investor prefers not to invest. The latter motivates a robust investment strategy maximizing the minimal element of the confidence set. The robust investor...

  1. 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.

  2. 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.

  3. 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.

  4. 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

  5. Domestic Heat Demand Prediction using Neural Networks

    OpenAIRE

    Bakker, Vincent; Molderink, Albert; Hurink, Johann L.; Smit, Gerard J.M.

    2008-01-01

    By combining a cluster of microCHP appliances, a virtual power plant can be formed. To use such a virtual power plant, a good heat demand prediction of individual households is needed since the heat demand determines the production capacity. In this paper we present the results of using neural networks techniques to predict the heat demand of individual households. This prediction is required to determine the electricity production capacity of the large fleet of microCHP appliances. All predic...

  6. 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.)

  7. 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...

  8. 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

  9. Fast Prediction of RNA-RNA Interaction

    Science.gov (United States)

    Salari, Raheleh; Backofen, Rolf; Sahinalp, S. Cenk

    Regulatory antisense RNAs are a class of ncRNAs that regulate gene expression by prohibiting the translation of an mRNA by establishing stable interactions with a target sequence. There is great demand for efficient computational methods to predict the specific interaction between an ncRNA and its target mRNA(s). There are a number of algorithms in the literature which can predict a variety of such interactions - unfortunately at a very high computational cost. Although some existing target prediction approaches are much faster, they are specialized for interactions with a single binding site.

  10. Energy based prediction models for building acoustics

    DEFF Research Database (Denmark)

    Brunskog, Jonas

    2012-01-01

    In order to reach robust and simplified yet accurate prediction models, energy based principle are commonly used in many fields of acoustics, especially in building acoustics. This includes simple energy flow models, the framework of statistical energy analysis (SEA) as well as more elaborated...... principles as, e.g., wave intensity analysis (WIA). The European standards for building acoustic predictions, the EN 12354 series, are based on energy flow and SEA principles. In the present paper, different energy based prediction models are discussed and critically reviewed. Special attention is placed on...

  11. Predictive Analytics with Big Social Data

    DEFF Research Database (Denmark)

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

    , pronouns, and sentiments), we develop and evaluate linear regression models that transform (a) iPhone tweets into a prediction of the quarterly iPhone sales with an average error close to the established prediction models from investment banks (Lassen, Madsen, & Vatrapu, 2014)and (b) facebook likes......, 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...

  12. 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.

  13. 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.

  14. 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

  15. 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.

  16. Local backbone structure prediction of proteins.

    Science.gov (United States)

    de Brevern, Alexandre G; Benros, Cristina; Gautier, Romain; Valadié, Héléne; Hazout, Serge; Etchebest, Catherine

    2004-01-01

    A statistical analysis of the PDB structures has led us to define a new set of small 3D structural prototypes called Protein Blocks (PBs). This structural alphabet includes 16 PBs, each one is defined by the (phi, psi) dihedral angles of 5 consecutive residues. The amino acid distributions observed in sequence windows encompassing these PBs are used to predict by a Bayesian approach the local 3D structure of proteins from the sole knowledge of their sequences. LocPred is a software which allows the users to submit a protein sequence and performs a prediction in terms of PBs. The prediction results are given both textually and graphically. PMID:15724288

  17. 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

  18. 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.

  19. 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

  20. 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

  1. 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

  2. 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.

  3. Prediction errors and local Lyapunov exponents

    CERN Document Server

    Kennel, M B; Sidorowich, J J S; Matthew B Kennel; Henry D I Abarbanel

    1994-01-01

    It is frequently asserted that in a chaotic system two initially close points will separate at an exponential rate governed by the largest global Lyapunov exponent. Local Lyapunov exponents, however, are more directly relevant to predictability. The difference between the local and global Lyapunov exponents, the large variations of local exponents over an attractor, and the saturation of error growth near the size of the attractor---all result in non-exponential scalings in errors at both short and long prediction times, sometimes even obscuring evidence of exponential growth. Failure to observe exponential error scaling cannot rule out deterministic chaos as an explanation. We demonstrate a simple model that quantitatively predicts observed error scaling from the local Lyapunov exponents, for both short and surprisingly long times. We comment on the relevance to atmospheric predictability as studied in the meteorological literature.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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

  9. 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.

  10. 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 ...

  11. 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.

  12. 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.

  13. 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)....

  14. 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 ...

  15. Prediction of twin-arginine signal peptides

    DEFF Research Database (Denmark)

    Bendtsen, Jannick Dyrløv; Nielsen, Henrik; Widdick, D.; Palmer, T.; Brunak, Søren

    2005-01-01

    publicly available method, TatP, for prediction of bacterial Tat signal peptides. Results: We have retrieved sequence data for Tat substrates in order to train a computational method for discrimination of Sec and Tat signal peptides. The TatP method is able to positively classify 91% of 35 known Tat signal...... complementary rule based prediction method. Conclusion: The method developed here is able to discriminate Tat signal peptides from cytoplasmic proteins carrying a similar motif, as well as from Sec signal peptides, with high accuracy. The method allows filtering of input sequences based on Perl syntax regular...... expressions, whereas hydrophobicity discrimination of Tat- and Sec- signal peptides is carried out by an artificial neural network. A potential cleavage site of the predicted Tat signal peptide is also reported. The TatP prediction server is available as a public web server at http://www.cbs.dtu.dk/services/TatP/....

  16. 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 ...

  17. 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....

  18. 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...

  19. 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)

  20. 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.

  1. Fracture predictions in Zircaloy fuel cladding

    International Nuclear Information System (INIS)

    Predictions of the maximum initial allowable temperature required to achieve a 40-year life in dry storage are made for Zircaloy clad spent fuel. Maximum initial temperatures of 360 to 4050C for irradiated spent fuel cladding (wet pool storage) are predicted. The technique utilized in this work is based on the deformation and fracture map methodology. Maps are presented for temperatures between 50 and 8500C and stresses between 5 and 500 MPa. These maps are then combined with both the known temperature history (an exponentially decaying one) of Zircaloy fuel cladding in dry storage and a life fracture rule to predict the rupture life of the cladding in dry storage. Predictions of the deformation and fracture map methodology are shown to be in good agreement with constant stress-constant temperature data

  2. 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

  3. Surface Roughness Prediction Techniques for CNC Turning

    Directory of Open Access Journals (Sweden)

    B. Sidda Reddy

    2008-01-01

    Full Text Available This study deals with the development of a surface roughness prediction model for machining aluminum alloys using multiple regression and artificial neural networks. The experiments have been conducted using full factorial design in the design of experiments (DOE on CNC turning machine with carbide cutting tool. A second order multiple regression model in terms of machining parameters has been developed for the prediction of surface roughness. The adequacy of the developed model is verified by using co-efficient of determination, analysis of variance (ANOVA, residual analysis and also the neural network model has been developed using multilayer perception back propagation algorithm using train data and tested using test data. To judge the efficiency and ability of the model to predict surface roughness values percentage deviation and average percentage deviation has been used. The experimental results show, artificial neural network model predicts with high accuracy compared with multiple regression model.

  4. 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,...

  5. 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

  6. 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...

  7. Prediction of Thermodynamic Properties for Halogenated Hydrocarbon

    Science.gov (United States)

    Higashi, Yukihiro

    The predictive methods of thermodynamic properties are discussed with respect to the halogenated hydrocarbons using as working fluids for refrigeration and heat pump cycles. The methods introduced into this paper can be calculated by the limited information; critical properties, normal boiling point and acentric factor. The results of prediction are compared with the experimental values of PVT property, vapor pressure and saturated liquid density. On the basis of these comparisons, Lydersen's method for predicting the critical properties, the generalized vapor pressure correlation by Ashizawa et, al., and Hankinson-Thomson's method for predicting saturated liquid density can be recommended. With respect to the equation of state, either Soave equation or Peng-Robinson equation is effective in calculating the thermodynamic properties except high density region.

  8. Software architecture and design for reliability predictability

    CERN Document Server

    Semegn, Assefa D

    2011-01-01

    Reliability prediction of a software product is complex due to interdependence and interactions among components and the difficulty of representing this behavior with tractable models. Models developed by making simplifying assumptions about the software

  9. 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.

  10. Point Rainfall Prediction using Data Mining Technique

    Directory of Open Access Journals (Sweden)

    T.R. Sivaramakrishnan

    2012-07-01

    Full Text Available Rainfall prediction is usually done for a region but spot quantitative precipitation forecast is required for individual township, harbours and stations with vital installation. With recent successful attempt for prediction of rainfall at a coastal station in east coast of India, a methodology to predict spot rainfall using association rule mining for an interior station Trichirappalli (10º48' N/78º41' E of south India has been developed and the results are presented here. The data is filtered using discretization approach based on the best fit ranges and then association mining is performed on dataset using Predictive Apriori algorithm and then the data need be validated using K* classifier approach. The results show that the overall classification accuracy for occurrence and non occurrence of the rainfall on wet and dry days using the data mining technique is satisfactory.

  11. 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)

  12. 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

  13. 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...

  14. Genome Majority Vote Improves Gene Predictions

    OpenAIRE

    Wall, Michael E.; Raghavan, Sindhu; Cohn, Judith D; Dunbar, John

    2011-01-01

    Author Summary The genetic code tells us precisely how a DNA sequence will be translated into a protein. However, it is more difficult to identify where translation will start and stop in the entire length of an organism's genome sequence. Computer software can predict where the start sites are, and this is successful most of the time; however, errors do occur. We hypothesized that some errors might be corrected by comparing predictions for the genome sequences of closely related organisms. T...

  15. 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 ...

  16. 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...

  17. Multiyear predictability of tropical marine productivity

    OpenAIRE

    Séférian, Roland; Bopp, Laurent; Gehlen, Marion; SWINGEDOUW, Didier; Mignot, Juliette; Guilyardi, Eric; Servonnat, Jérôme

    2014-01-01

    With the emergence of decadal predictability simulations, research toward forecasting variations of the climate system now covers a large range of timescales. However, assessment of the capacity to predict natural variations of relevant biogeochemical variables like carbon fluxes, pH, or marine primary productivity remains unexplored. Among these, the net primary productivity (NPP) is of particular relevance in a forecasting perspective. Indeed, in regions like the tropical Pacific (30 degree...

  18. Parental Education Predicts Corticostriatal Functionality in Adulthood

    OpenAIRE

    Gianaros, Peter J.; Manuck, Stephen B.; Sheu, Lei K.; Kuan, Dora C. H.; Votruba-Drzal, Elizabeth; Craig, Anna E.; Hariri, Ahmad R.

    2010-01-01

    Socioeconomic disadvantage experienced in early development predicts ill health in adulthood. However, the neurobiological pathways linking early disadvantage to adult health remain unclear. Lower parental education—a presumptive indicator of early socioeconomic disadvantage—predicts health-impairing adult behaviors, including tobacco and alcohol dependencies. These behaviors depend, in part, on the functionality of corticostriatal brain systems that 1) show developmental plasticity and early...

  19. 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.

  20. Predicting nutrient responses in poultry: future challenges.

    Science.gov (United States)

    Gous, R M

    2007-02-01

    Predicting the response of poultry to nutrients has progressed to a stage where it is now not only possible to predict voluntary feed intake accurately, but broiler feeds and feeding programmes may now be optimised using the more advanced simulation models. Development of such prediction models has stimulated useful and purposeful research targeted at filling the gaps in our knowledge of critical aspects of the theory incorporated into these models. The aim of this paper was to review some of these past developments, discuss the controversy that exists in designing and interpreting response experiments, and highlight some of the most recent challenges related to the prediction of responses to nutrients by poultry. These latter include differences, brought about by selection for diverse goals, that have become apparent between modern broiler strains in their responses in feed intake and mortality, which are not independent of level of feeding or strain of broiler, as was previously believed. Uniformity, an important quality criterion in broiler processing, is also not independent of level of feeding, and the effect may now be predicted using stochastic models. It is not yet clear whether breast meat yield, the carcass component of broilers yielding the highest returns, is a function of the strain of broiler or simply that of the protein weight of the bird when processed. An important aspect of response prediction is dealing with constraints to performance: whereas it is relatively straightforward to simulate the potential performance of a broiler, such performance is often constrained by the physical, social and infectious environment, among others, providing a challenge to modellers attempting to predict actual performance. Some of these constraints to potential performance have not yet been adequately described, but are now receiving attention, suggesting that nutrient responses in poultry have the potential to be more accurately predicted in the future. PMID