Microscopic simulation of electronic noise in semiconductormaterials and devices

We present a microscopic interpretation of electronic noise in semiconductor materials and two-terminal devices. The theory is based on Monte Carlo simulations of the carrier motion self-consistently coupled with a Poisson solver. Current and voltage noise operations are applied and their respective representations discussed. As application we consider the cases of homogeneous materials, resistors, n⁺nn ⁺ structures, and Schottky-barrier diodes. Phenomena associated with coupling between fluctuations in carrier velocity and self-consistent electric field are quantitatively investigated for the first time. At increasing applied fields hot-carrier effects are found to be of relevant importance in all the cases considered here. As a general result, noise spectroscopy is found to be a source of valuable information to investigate and characterize transport properties of semiconductor materials and devices     

Entities,identities, identifiers and credentials — what does it all mean?

This paper looks at the concepts of entities, identities, identifiers and credentials, their definitions, and how they combine to authenticate an identity to an account, or function, within a service. Credentials can be divided into several different types on the basis of their use, origin and characteristics. In particular, types such as composite, dynamic and derived credentials will be considered, and their applicability within an identity management system. Each credential must be managed through its entire life cycle from initial registration, general use and suspension, to deletion. The notion of public (i.e. freely distributable) and private (i.e. known only to you) aspects of a credential is explored. The bindings, by trusted third parties, of identifiers and public credentials into permits and instruments of proof is explained along with the convenience, but greater exposure, of local information. Several scenarios are analysed in terms of how different types of credentials are employed during the authentication process.     

An integrated system to remote monitor and control anaerobic wastewater treatment plants through the internet.

The TELEMAC project brings new methodologies from the Information and Science Technologies field to the world of water treatment. TELEMAC offers an advanced remote management system which adapts to most of the anaerobic wastewater treatment plants that do not benefit from a local expert in wastewater treatment. The TELEMAC system takes advantage of new sensors to better monitor the process dynamics and to run automatic controllers that stabilise the treatment plant, meet the depollution requirements and provide a biogas quality suitable for cogeneration. If the automatic system detects a failure which cannot be solved automatically or locally by a technician, then an expert from the TELEMAC Control Centre is contacted via the internet and manages the problem.     

Perceived stress management skill mediates the relationship between optimism and positive mood following radical prostatectomy.

This study evaluated relations among optimism, perceived stress management skills (PSMS), and positive mood in 46 men who had surgical treatment for localized prostate cancer. The authors found that optimism, PSMS, and positive mood scores were positively correlated. Positive mood was unrelated to demographic and disease-related control variables. In a hierarchical regression model controlling for PSMS, the relationship between optimism and positive mood became nonsignificant, whereas PSMS remained a correlate of positive mood. Results suggest that the relationship between optimism and positive mood may be mediated by belief in being able to use stress management techniques effectively. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Role of Ponded Turbidity Currents in Reservoir Trap Efficiency

The capacity to store water in a reservoir declines as it traps sediment. A river entering a reservoir forms a prograding delta. Coarse sediment (e.g., sand) deposits in the fluvial topset and avalanching foreset of the delta, and is typically trapped with an efficiency near 100%. The trap efficiency of fine sediment (e.g., mud), on the other hand, may be below 100%, because some of this sediment may pass out of the reservoir without settling out. Here, a model of trap efficiency of mud is developed in terms of the mechanics of a turbidity current that plunges on the foreset. The dam causes a sustained turbidity current to reflect and form a muddy pond bounded upstream by a hydraulic jump. If the interface of this muddy pond rises above any vent or overflow point at the dam, the trap efficiency of mud drops below 100%. A model of the coevolution of topset, foreset, and bottomset in a reservoir that captures the dynamics of the internal muddy pond is presented. Numerical implementation, comparison against an experiment, and application to a field-scale case provide the basis for a physical understanding of the processes that determine reservoir trap efficiency.     

Executing algorithms with hypercube topology on torusmulticomputers

Many parallel algorithms use hypercubes as the communication topology among their processes. When such algorithms are executed on hypercube multicomputers the communication cost is kept minimum since processes can be allocated to processors in such a way that only communication between neighbor processors is required. However, the scalability of hypercube multicomputers is constrained by the fact that the interconnection cost-per-node increases with the total number of nodes. From scalability point of view, meshes and toruses are more interesting classes of interconnection topologies. This paper focuses on the execution of algorithms with hypercube communication topology on multicomputers with mesh or torus interconnection topologies. The proposed approach is based on looking at different embeddings of hypercube graphs onto mesh or torus graphs. The paper concentrates on toruses since an already known embedding, which is called standard embedding, is optimal for meshes. In this paper, an embedding of hypercubes onto toruses of any given dimension is proposed. This novel embedding is called xor embedding. The paper presents a set of performance figures for both the standard and the xor embeddings and shows that the latter outperforms the former for any torus. In addition, it is proven that for a one-dimensional torus (a ring) the xor embedding is optimal in the sense that it minimizes the execution time of a class of parallel algorithms with hypercube topology. This class of algorithms is frequently found in real applications, such as FFT and some class of sorting algorithms     

Experiments of Fast Learning with High Order Boltzmann Machines

This work reports the results obtained with the application of High Order Boltzmann Machines without hidden units to construct classifiers for some problems that represent different learning paradigms. The Boltzmann Machine weight updating algorithm remains the same even when some of the units can take values in a discrete set or in a continuous interval. The absence of hidden units and the restriction to classification problems allows for the estimation of the connection statistics, without the computational cost involved in the application of simulated annealing. In this setting, the learning process can be sped up several orders of magnitude with no appreciable loss of quality of the results obtained.