Completions and Complete Representations

2013 ◽  
pp. 61-89 ◽  
Author(s):  
Robin Hirsch ◽  
Ian Hodkinson
Keyword(s):  
Complete Representations

EXOTIC BIRCH-LEAFMINING SAWFLIES (HYMENOPTERA: TENTHREDINIDAE) IN ALBERTA: DISTRIBUTIONS, SEASONAL ACTIVITIES, AND THE POTENTIAL FOR COMPETITION

1997 ◽  
Vol 129 (2) ◽  
pp. 319-333 ◽  
Author(s):  
Scott C. Digweed ◽  
John R. Spence ◽  
David W. Langor
Keyword(s):  
Urban Trees ◽  
Seasonal Activity ◽  
Mature Trees ◽  
Sticky Traps ◽  
Rural Location ◽  
Three Generations ◽  
Complete Representations ◽  
Fenusa Pusilla ◽  
Profenusa Thomsoni ◽  
Southern Alberta

AbstractThe exotic birch-leafmining sawflies Fenusa pusilla (Lepeletier), Profenusa thomsoni (Konow), and Heterarthrus nemoratus (Fallen) occurred in Alberta during 1992–1995, but only the first two were abundant. Birch-leafmining sawflies occurred at all sites surveyed in central and southern Alberta, and appeared to be expanding their ranges northward. Adult F. pusilla began emerging in mid-May (approximately 220 DD05), and there were one to three generations per year, depending on location and year. Female F. pusilla were relatively less abundant on young than on mature trees. Profenusa thomsoni began attacking trees in June (between 400 and 550 DD05), and was invariably univoltine. Both species were more abundant and were active earlier on urban trees than at a nearby rural location. The highest catches and most complete representations of seasonal activity were obtained using yellow sticky traps. Larval F. pusilla and P. thomsoni are unlikely to compete directly for leaf resources because their leafmining activities are separated spatially and temporally, but they probably compete intraspecifically.

Topologically complete representations of inverse semigroups

2002 ◽  
Vol 66 (1) ◽  
pp. 121-130 ◽  
Author(s):  
Grigori I. Zhitomirski
Keyword(s):  
Inverse Semigroups ◽  
Complete Representations

scholarly journals Variationally complete representations are polar

2001 ◽  
Vol 129 (11) ◽  
pp. 3445-3446 ◽  
Author(s):  
Antonio J. Di Scala ◽  
Carlos Olmos
Keyword(s):  
Complete Representations

scholarly journals Data-driven models reveal the organization of diverse cognitive functions in the brain

2019 ◽  
Author(s):  
Tomoya Nakai ◽  
Shinji Nishimoto
Keyword(s):  
Cognitive Processes ◽  
Brain Activity ◽  
Quantitative Model ◽  
Task Type ◽  
Hierarchical Organization ◽  
Human Cognition ◽  
Cognitive Tasks ◽  
Cortical Organization ◽  
Brain Functions ◽  
Complete Representations

AbstractOur daily life is realized by the complex orchestrations of diverse brain functions including perception, decision, and action. One of the central issues in cognitive neuroscience is to reveal the complete representations underlying such diverse functions. Recent studies have revealed representations of natural perceptual experiences using encoding models1–5. However, there has been little attempt to build a quantitative model describing the cortical organization of multiple active, cognitive processes. Here, we measured brain activity using functional MRI while subjects performed over 100 cognitive tasks, and examined cortical representations with two voxel-wise encoding models6. A sparse task-type encoding model revealed a hierarchical organization of cognitive tasks, their representation in cognitive space, and their mapping onto the cortex. A cognitive factor encoding model utilizing continuous intermediate features by using metadata-based inferences7 predicted brain activation patterns for more than 80 % of the cerebral cortex and decoded more than 95 % of tasks, even under novel task conditions. This study demonstrates the usability of quantitative models of natural cognitive processes and provides a framework for the comprehensive cortical organization of human cognition.

Numerical Methods in Atmospheric Models

2018 ◽  
Author(s):  
Fedor Mesinger ◽  
Miodrag Rančić ◽  
R. James Purser
Keyword(s):  
Numerical Methods ◽  
Weather Forecasting ◽  
Simulation Models ◽  
Climate Simulation ◽  
Atmospheric Flows ◽  
Massively Parallel Computers ◽  
Computational Environment ◽  
Atmospheric Equations ◽  
Complete Representations ◽  
Computational Speed

The astonishing development of computer technology since the mid-20th century has been accompanied by a corresponding proliferation in the numerical methods that have been developed to improve the simulation of atmospheric flows. This article reviews some of the numerical developments concern the ongoing improvements of weather forecasting and climate simulation models. Early computers were single-processor machines with severely limited memory capacity and computational speed, requiring simplified representations of the atmospheric equations and low resolution. As the hardware evolved and memory and speed increased, it became feasible to accommodate more complete representations of the dynamic and physical atmospheric processes. These more faithful representations of the so-called primitive equations included dynamic modes that are not necessarily of meteorological significance, which in turn led to additional computational challenges. Understanding which problems required attention and how they should be addressed was not a straightforward and unique process, and it resulted in the variety of approaches that are summarized in this article. At about the turn of the century, the most dramatic developments in hardware were the inauguration of the era of massively parallel computers, together with the vast increase in the amount of rapidly accessible memory that the new architectures provided. These advances and opportunities have demanded a thorough reassessment of the numerical methods that are most successfully adapted to this new computational environment. This article combines a survey of the important historical landmarks together with a somewhat speculative review of methods that, at the time of writing, seem to hold out the promise of further advancing the art and science of atmospheric numerical modeling.

Performance evaluation of compressive sensing matching pursuit backtracking iterative hard thresholding algorithm for improving reconstruction

2020 ◽  
pp. 1-10
Author(s):  
Viswanadham Ravuri ◽  
Sudheer Kumar Terlapu ◽  
S.S. Naik
Keyword(s):  
Compressive Sensing ◽  
Matching Pursuit ◽  
Linear Equations ◽  
Optimal Strategies ◽  
Original Algorithm ◽  
Iterative Hard Thresholding ◽  
Complete Representations ◽  
Complete Study ◽  
Thresholding Algorithm ◽  
Sparse Solutions

 Now-a-days due to advancements in technologies most of the applications in signal processing were using the models based on the sparse signal. Sub optimal strategies were used in these models to estimate the sparsest coefficients. In this work various algorithms were analyzed to address its optimal solutions. The sparsest solution can be found for the linear equations which are under determined. In this work, a complete study is carried out based on Compressive Sensing Matching Pursuit Back Tracking Iterative Hard Threshold (CMPBIHT) algorithm in the real-world scenario. As the BIHT algorithm may often fail to converge and its performance seems to be degraded if the conditions fail. To address these challenges, we have modified the BIHT algorithm to guarantee the convergence using the proposed method, even in this regime. Further the proposed CMPBIHT algorithm is evaluated and compared with the state of art techniques and it is observed that the proposed algorithm retains the similarities of the original algorithm. In this proposed model we have adopted the Compressive Sensing (CS) schemes along with Orthogonal Matching Pursuit (OMP). With this proposal we are able to solve the least squares problem for the new residual. We also investigated the reliability in sparse solutions along with compressive sensing techniques while decoding and over complete representations. An extensive research is carried out at the reconstruction side with the fundamental theme of CS, IHT and OMP techniques. The simulation results perform better efficiency at the reconstruction of the Gaussians signals by guaranteeing the productions in the residual error and noise. Further the proposed algorithm performs better at the reconstruction with nominal complexity in each of the iteration computationally.

Dynamic Properties of Static-Recursive Model Systems of Transportation and Location

1984 ◽  
Vol 16 (11) ◽  
pp. 1503-1519 ◽  
Author(s):  
S H Putman
Keyword(s):  
Land Use ◽  
Dynamic Properties ◽  
Urban Transportation ◽  
Empirical Work ◽  
Model Systems ◽  
System Structure ◽  
Model Structure ◽  
The Past ◽  
General Terms ◽  
Complete Representations

In the past decade there have been a number of efforts aimed at the development of more-complete representations of urban transportation and land-use interactions. In this paper, it is suggested that there is a great deal to be learned from experimentation with existing as well as emerging techniques. Systems of models are discussed in general terms with particular reference to the implications of selecting one system over another. A report is given of some empirical work with an integrated transportation and land-use model structure and the consequences of the model-system structure for the empirical work are discussed.

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