104,553 research outputs found
T. Casper
No full textT. Casper is standing against a wall. He is dressed in a collared shirt, necktie, sweater, and a blazer. Mr. Casper is a journalist.https://mavmatrix.uta.edu/specialcollections_startelegram1940s/1205/thumbnail.jp
Extending CasPer: A Regression Survey
No full textThe CasPer algorithm is a constructive neural network algorithm. CasPer creates cascade network architectures in a similar manner to Cascade Correlation. CasPer, however, uses a modified form of the RPROP algorithm, termed Progressive RPROP, to train the whole network after the addition of each new hidden neuron. Previous work with CasPer has shown that it builds networks which generalise better than CasCor, often using less hidden neurons. This work adds two extensions to CasPer. First, an enhancement to the RPROP algorithm, SARPROP, is used to train newly installed hidden neurons. The second extension involves the use of a pool of hidden neurons, each trained using SARPROP, with the best performing neuron selected for insertion into the network. These extensions are benchmarked on a number of regression problems and are shown to result in CasPer producing networks which generalise better than those produced by the original CasPer algorithm. 1 Introduction The CasPer algorithm has b..
Extending and Benchmarking the CasPer Algorithm
No full textThe CasPer algorithm is a constructive neural network algorithm. CasPer creates cascade network architectures in a similar manner to Cascade Correlation. CasPer, however, uses a modified form of the RPROP algorithm, termed Progressive RPROP, to train the whole network after the addition of each new hidden neuron. Previous work with CasPer has shown that it builds networks which generalise better than CasCor, often using less hidden neurons. This work adds two extensions to CasPer. First, an enhancement to the RPROP algorithm, SARPROP, is used to train newly installed hidden neurons. The second extension involves the use of a pool of hidden neurons, each trained using SARPROP, with the best performing selected for insertion into the network. These extensions are shown to result in CasPer producing more compact networks which often generalise better than those produced by the original CasPer algorithm. Keywords - Neural, Network, Constructive, Cascade, RPROP. 1 INTRODUCTION The CasPer..
C-2383: Richmond, Utah, Casper W. Merrill residence. Sec 22 T 14N R1E. 1945
No full textC-2383: Richmond, Utah, Casper W. Merrill residence. Sec 22 T 14N R1E. 1945 (3 photos
CASPER coupled air-sea processes and electromagnetic ducting research
No full textThe Coupled Air–Sea Processes and Electromagnetic Ducting Research (CASPER) project aims to better quantify atmospheric effects on the propagation of radar and communication signals in the marine environment. Such effects are associated with vertical gradients of temperature and water vapor in the marine atmospheric surface layer (MASL) and in the capping inversion of the marine atmospheric boundary layer (MABL), as well as the horizontal variations of these vertical gradients. CASPER field measurements emphasized simultaneous characterization of electromagnetic (EM) wave propagation, the propagation environment, and the physical processes that gave rise to the measured refractivity conditions. CASPER modeling efforts utilized state-of-the-art large-eddy simulations (LESs) with a dynamically coupled MASL and phase-resolved ocean surface waves. CASPER-East was the first of two planned field campaigns, conducted in October and November 2015 offshore of Duck, North Carolina. This article highlights the scientific motivations and objectives of CASPER and provides an overview of the CASPER-East field campaign. The CASPER-East sampling strategy enabled us to obtain EM wave propagation loss as well as concurrent environmental refractive conditions along the propagation path. This article highlights the initial results from this sampling strategy showing the range-dependent propagation loss, the atmospheric and upper-oceanic variability along the propagation range, and the MASL thermodynamic profiles measured during CASPER-East
The Communication Strategies and Customer's Requirements Definition at the Early Design Stages: An Empirical Study on Italian Luxury Automotive Brands
No full textAbstractAt the early stages of the product development, it is important to set up customer's requirements and translate these into the technical specifications with the highest level of precision since the changes in the late design phases have extremely high cost. These requirements are directly dependent on the correct and complete definition of perceived quality attributes. Such attention to the details is vital for the luxury car manufacturers since they are seeking to fulfill customer requirements with the high level of personalization. This research based on the perceived quality framework and presents findings from the empirical study of leading Italian luxury vehicle manufacturers. This research contributes to the existing debate regarding the correct definition of the customer's requirements and communication strategies. Moreover, it highlights possible ways to reduce information asymmetry between car manufacturers and customers
Letter, [Author unclear] to Paulina T. Merritt
No full textHandwritten letter to Paulina Merritt from an unknown author, October 1, 1876.
Casper: Debugging Null Dereferences with Dynamic Causality Traces
No full textFixing a software error requires understanding its root cause. In this paper, we introduce "causality traces", crafted execution traces augmented with the information needed to reconstruct the causal chain from the root cause of a bug to an execution error. We propose an approach and a tool, called Casper, for dynamically constructing causality traces for null dereference errors. The core idea of Casper is to inject special values, called "ghosts", into the execution stream to construct the causality trace at runtime. We evaluate our contribution by providing and assessing the causality traces of 14 real null dereference bugs collected over six large, popular open-source projects. Over this data set, Casper builds a causality trace in less than 5 seconds
Casper: Debugging Null Dereferences with Dynamic Causality Traces
No full textFixing a software error requires understanding its root cause. In this paper, we introduce "causality traces", crafted execution traces augmented with the information needed to reconstruct the causal chain from the root cause of a bug to an execution error. We propose an approach and a tool, called Casper, for dynamically constructing causality traces for null dereference errors. The core idea of Casper is to inject special values, called "ghosts", into the execution stream to construct the causality trace at runtime. We evaluate our contribution by providing and assessing the causality traces of 14 real null dereference bugs collected over six large, popular open-source projects. Over this data set, Casper builds a causality trace in less than 5 seconds
Casper: Debugging Null Dereferences with Dynamic Causality Traces
No full textFixing a software error requires understanding its root cause. In this paper, we introduce "causality traces", crafted execution traces augmented with the information needed to reconstruct the causal chain from the root cause of a bug to an execution error. We propose an approach and a tool, called Casper, for dynamically constructing causality traces for null dereference errors. The core idea of Casper is to inject special values, called "ghosts", into the execution stream to construct the causality trace at runtime. We evaluate our contribution by providing and assessing the causality traces of 14 real null dereference bugs collected over six large, popular open-source projects. Over this data set, Casper builds a causality trace in less than 5 seconds
- …
