Calibration of probabilistic quantitative precipitation forecasts with an artificial neural network

A feed-forward neural network is configured to calibrate the bias of a high-resolution probabilistic quantitative precipitation forecast (PQPF) produced by a 12-km version of the NCEP Regional Spectral Model (RSM) ensemble forecast system. Twice-daily forecasts during the 2002-2003 cool season (1 November-31 March, inclusive) are run over four U.S. Geological Survey (USGS) hydrologic unit regions of the southwest United States. Calibration is performed via a cross-validation procedure, where four months are used for training and the excluded month is used for testing. The PQPFs before and after the calibration over a hydrological unit region are evaluated by comparing the joint probability distribution of forecasts and observations. Verification is performed on the 4-km stage IV grid, which is used as "truth." The calibration procedure improves the Brier score (BrS), conditional bias (reliability) and forecast skill, such as the Brier skill score (BrSS) and the ranked probability skill score (RPSS), relative to the sample frequency for all geographic regions and most precipitation thresholds. However, the procedure degrades the resolution of the PQPFs by systematically producing more forecasts with low nonzero forecast probabilities that drive the forecast distribution closer to the climatology of the training sample. The problem of degrading the resolution is most severe over the Colorado River basin and the Great Basin for relatively high precipitation thresholds where the sample of observed events is relatively small. © 2007 American Meteorological Society

Short-range probabilistic quantitative precipitation forecasts over the southwest United States by the RSM ensemble system

The National Centers for Environmental Prediction (NCEP) Regional Spectral Model (RSM) is used to produce twice-daily (0000 and 1200 UTC), high-resolution ensemble forecasts to 24 h. The forecasts are performed at an equivalent horizontal grid spacing of 12 km for the period 1 November 2002 to 31 March 2003 over the southwest United States. The performance of 6-h accumulated precipitation is assessed for 32 U.S. Geological Survey hydrologic catchments. Multiple accuracy and skill measures are used to evaluate probabilistic quantitative precipitation forecasts. NCEP stage-IV precipitation analyses are used as "truth," with verification performed on the stage-IV 4-km grid. The RSM ensemble exhibits a ubiquitous wet bias. The bias manifests itself in areal coverage, frequency of occurrence, and total accumulated precipitation over every region and during every 6-h period. The biases become particularly acute starting with the 1800-0000 UTC interval, which leads to a spurious diurnal cycle and the 1200 UTC cycle being more adversely affected than the 0000 UTC cycle. Forecast quality and value exhibit marked variability over different hydrologic regions. The forecasts are highly skillful along coastal California and the windward slopes of the Sierra Nevada Mountains, but they generally lack skill over the Great Basin and the Colorado basin except over mountain peaks. The RSM ensemble is able to discriminate precipitation events and provide useful guidance to a wide range of users over most regions of California, which suggests that mitigation of the conditional biases through statistical postprocessing would produce major improvements in skill. © 2007 American Meteorological Society

Behaviors of beryllium compensation doping in InGaAsP grown by gas source molecular beam epitaxy

We report structural properties as well as electrical and optical behaviors of beryllium (Be)-doped InGaAsP lattice-matched to InP grown by gas source molecular beam epitaxy. P type layers present a high degree of compensation on the order of 1018 cm−3, and for Be densities below 9.5×1017 cm−3, they are found to be n type. Enhanced incorporation of oxygen during Be doping is observed by secondary ion mass spectroscopy. Be in forms of interstitial donors or donor-like Be-O complexes for cell temperatures below 800°C is proposed to account for such anomalous compensation behaviors. A constant photoluminescence energy of 0.98 eV without any Moss-Burstein shift for Be doping levels up to 1018 cm−3 along with increased emission intensity due to passivation effect of Be is also observed. An increasing number of minority carriers tend to relax via Be defect state-related Shockley-Read-Hall recombination with the increase of Be doping density

A comparative review of dynamic neural networks and hidden Markov model methods for mobile on-device speech recognition

The adoption of high-accuracy speech recognition algorithms without an effective evaluation of their impact on the target computational resource is impractical for mobile and embedded systems. In this paper, techniques are adopted to minimise the required computational resource for an effective mobile-based speech recognition system. A Dynamic Multi-Layer Perceptron speech recognition technique, capable of running in real time on a state-of-the-art mobile device, has been introduced. Even though a conventional hidden Markov model when applied to the same dataset slightly outperformed our approach, its processing time is much higher. The Dynamic Multi-layer Perceptron presented here has an accuracy level of 96.94% and runs significantly faster than similar techniques

Spatial Symmetry of Superconducting Gap in YBa2Cu3O7-\delta Obtained from Femtosecond Spectroscopy

The polarized femtosecond spectroscopies obtained from well characterized (100) and (110) YBa2Cu3O7-\delta thin films are reported. This bulk-sensitive spectroscopy, combining with the well-textured samples, serves as an effective probe to quasiparticle relaxation dynamics in different crystalline orientations. The significant anisotropy in both the magnitude of the photoinduced transient reflectivity change and the characteristic relaxation time indicates that the nature of the relaxation channel is intrinsically different in various axes and planes. By the orientation-dependent analysis, d-wave symmetry of the bulk-superconducting gap in cuprate superconductors emerges naturally.Comment: 8 pages, 4 figures. To be published in Physical Review B, Rapid Communication

A biologically inspired network design model

A network design problem is to select a subset of links in a transport network that satisfy passengers or cargo transportation demands while minimizing the overall costs of the transportation. We propose a mathematical model of the foraging behaviour of slime mould P. polycephalum to solve the network design problem and construct optimal transport networks. In our algorithm, a traffic flow between any two cities is estimated using a gravity model. The flow is imitated by the model of the slime mould. The algorithm model converges to a steady state, which represents a solution of the problem. We validate our approach on examples of major transport networks in Mexico and China. By comparing networks developed in our approach with the man-made highways, networks developed by the slime mould, and a cellular automata model inspired by slime mould, we demonstrate the flexibility and efficiency of our approach

Parameter estimation for robust HMM analysis of ChIP-chip data

Tiling arrays are an important tool for the study of transcriptional activity, protein-DNA interactions and chromatin structure on a genome-wide scale at high resolution. Although hidden Markov models have been used successfully to analyse tiling array data, parameter estimation for these models is typically ad hoc. Especially in the context of ChIP-chip experiments, no standard procedures exist to obtain parameter estimates from the data. Common methods for the calculation of maximum likelihood estimates such as the Baum-Welch algorithm or Viterbi training are rarely applied in the context of tiling array analysis. Results: Here we develop a hidden Markov model for the analysis of chromatin structure ChIP-chip tiling array data, using t emission distributions to increase robustness towards outliers. Maximum likelihood estimates are used for all model parameters. Two different approaches to parameter estimation are investigated and combined into an efficient procedure. Conclusion: We illustrate an efficient parameter estimation procedure that can be used for HMM based methods in general and leads to a clear increase in performance when compared to the use of ad hoc estimates. The resulting hidden Markov model outperforms established methods like TileMap in the context of histone modification studies.13 page(s

Investigation of contact deformation and wear characteristics of discrete track recording media

The even semester 2014/2015 Technical Information Engineering University of Semarang (USM) has been running the Competency Based Curriculum (CBC) in the management of learning. Conversions that occur in some subjects at an increase in scheduled meetings in the classroom or in the laboratory. Computer Networks is one of the subjects who experienced a conversion. In the curriculum in 2008, Computer Networking has a number of credits 3. From the 2 credits 3 credits are for credits 1 credits for theory and practical credits. While at the CBC in 2013, Computer Networking has 4 credits, with details of 2 credits 2 credits theory and practicum. As lecture and instructor Computer Network, researchers interested in studying the effect of applying the CBC in 2013 in the subje ct of Computer Network. Does the addition of meeting practical and theoretical material renewal in accordance with the expected competencies?. Researchers tried applying the CBC in 2013 by conducting action research. Implementation of the research was conducted during an ongoing lecture that even semester 2015/2016. The results of the study during the first half of researchers will compare with the achievements that never existed when the old curriculum still in use. The goals of this research is, subjects in the Computer Network has always been one of the subjects that the content of the material and its application in the lab was able to follow the needs of the workforc

Abi1 gene silencing by short hairpin RNA impairs Bcr-Abl-induced cell adhesion and migration in vitro and leukemogenesis in vivo

Abl interactor (Abi) 1 was first identified as the downstream target of Abl tyrosine kinases and was found to be dysregulated in leukemic cells expressing oncogenic Bcr-Abl and v-Abl. Although the accumulating evidence supports a role of Abi1 in actin cytoskeleton remodeling and growth factor/receptor signaling, it is not clear how it contributes to Bcr-Abl-induced leukemogenesis. We show here that Abi1 gene silencing by short hairpin RNA attenuated the Bcr-Abl-induced abnormal actin remodeling, membrane-type 1 metalloproteinase clustering and inhibited cell adhesion and migration on fibronectin-coated surfaces. Although the knock down of Abi1 expression did not affect growth factor-independent growth of Bcr-Abl-transformed Ba/F3 cells in vitro, it impeded competitive expansion of these cells in non obese diabetic (NOD)/ severe combined immuno-deficiency (SCID) mice. Remarkably, the knock down of Abi1 expression in Bcr-Abl-transformed Ba/F3 cells impaired the leukemogenic potential of these cells in NOD/SCID mice. Abi1 contributes to Bcr-Abl-induced leukemogenesis in part through Src family kinases, as the knock down of Abi1 expression attenuates Bcr-Abl-stimulated activation of Lyn. Together, these data provide for the first time the direct evidence that supports a critical role of Abi1 pathway in the pathogenesis of Bcr-Abl-induced leukemia

Fifteen new risk loci for coronary artery disease highlight arterial-wall-specific mechanisms

Coronary artery disease (CAD) is a leading cause of morbidity and mortality worldwide. Although 58 genomic regions have been associated with CAD thus far, most of the heritability is unexplained, indicating that additional susceptibility loci await identification. An efficient discovery strategy may be larger-scale evaluation of promising associations suggested by genome-wide association studies (GWAS). Hence, we genotyped 56,309 participants using a targeted gene array derived from earlier GWAS results and performed meta-analysis of results with 194,427 participants previously genotyped, totaling 88,192 CAD cases and 162,544 controls. We identified 25 new SNP-CAD associations (P < 5 × 10(-8), in fixed-effects meta-analysis) from 15 genomic regions, including SNPs in or near genes involved in cellular adhesion, leukocyte migration and atherosclerosis (PECAM1, rs1867624), coagulation and inflammation (PROCR, rs867186 (p.Ser219Gly)) and vascular smooth muscle cell differentiation (LMOD1, rs2820315). Correlation of these regions with cell-type-specific gene expression and plasma protein levels sheds light on potential disease mechanisms