Vertical eddy diffusion coefficient from the LANDSAT imagery

Analysis of five stable cases of the smoke plumes that originated in eastern Cabo Frio (22 deg 59'S; 42 deg 02'W), Brazil using LANDSAT imagery is presented for different months and years. From these images the lateral standard deviation (sigma sub y) and the lateral eddy diffusion coefficient (K sub y) are obtained from the formula based on Taylor's theory of diffusion by continuous moment. The rate of kinetic energy dissipation (e) is evaluated from the diffusion parameters sigma sub y and K sub y. Then, the vertical diffusion coefficient (K sub z) is estimated using Weinstock's formulation. These results agree well with the previous experimental values obtained over water surfaces by various workers. Values of e and K sub z show the weaker mixing processes in the marine stable boundary layer. The data sample is apparently to small to include representative active turbulent regions because such regions are so intermittent in time and in space. These results form a data base for use in the development and validation of mesoscale atmospheric diffusion models

A study of atmospheric diffusion from the LANDSAT imagery

LANDSAT multispectral scanner data of the smoke plumes which originated in eastern Cabo Frio, Brazil and crossed over into the Atlantic Ocean, are analyzed to illustrate how high resolution LANDSAT imagery can aid meteorologists in evaluating specific air pollution events. The eleven LANDSAT images selected are for different months and years. The results show that diffusion is governed primarily by water and air temperature differences. With colder water, low level air is very stable and the vertical diffusion is minimal; but water warmer than the air induces vigorous diffusion. The applicability of three empirical methods for determining the horizontal eddy diffusivity coefficient in the Gaussian plume formula was evaluated with the estimated standard deviation of the crosswind distribution of material in the plume from the LANDSAT imagery. The vertical diffusion coefficient in stable conditions is estimated using Weinstock's formulation. These results form a data base for use in the development and validation of meso scale atmospheric diffusion models

A petri net approach to the modelling and analysis of flexible manufacturing systems

In this paper we present an approach for modelling and analyzing flexible manufacturing systems (FMSs) using Petri nets. In this approach, we first build a Petri net model (PNM) of the given FMS in a bottom-up fashion and then analyze important qualitative aspects of FMS behaviour such as existence/absence of deadlocks and buffer overflows. The basis for our approach is a theorem we state and prove for computing the invariants of the union of a finite number of Petri nets when the invariants of the individual nets are known. We illustrate our approach using two typical manufacturing systems: an automated transfer line and a simple FMS

Study of atmospheric diffusion using LANDSAT

The parameters of diffusion patterns of atmospheric pollutants under different conditions were investigated for use in the Gaussian model for calculation of pollution concentration. Value for the divergence pattern of concentration distribution along the Y axis were determined using LANDSAT images. Multispectral scanner images of a point source plume having known characteristics, wind and temperature data, and cloud cover and solar elevation data provided by LANDSAT, were analyzed using the 1-100 system for image analysis. These measured values are compared with pollution transport as predicted by the Pasquill-Gifford, Juelich, and Hoegstroem atmospheric models

Deadlock prevention and deadlock avoidance in flexible manufacturing systems using petri net models

Deadlocks constitute an important issue to be addressed in the design and operation of FMSs. It is shown that prevention and avoidance of FMS deadlocks can be implemented using Petri net models. For deadlock prevention, the reachability graph of a Petri net model of the given FMS is used, whereas for deadlock avoidance, a Petri-net-based online controller is proposed. The modeling of the General Electric FMS at Erie, PA, is discussed. For such real-world systems, deadlock prevention using the reachability graph is not feasible. A generic, Petri-net-based online controller for implementing deadlock avoidance in such real-world FMSs is developed

Performance modelling of a fault-tolerant real-time multiprocessor using stochastic Petri nets

The fault-tolerant multiprocessor (FTMP) is a bus-based multiprocessor architecture with real-time and fault-tolerance features and is used in critical aerospace applications. A preliminary performance evaluation is of crucial importance in the design of such systems. In this paper, we review stochastic Petri nets (SPN) and developspn-based performance models for FTMP. These performance models enable efficient computation of important performance measures such as processing power, bus contention, bus utilization, and waiting times

DUAL-RAIL GATE STRUCTURE FOR A COMPLEX DATA PATH

Dual-rail domino gates are restricted to create a reliable critical data path. According to this critical data path, the handshake circuits are greatly simplified, that provides the pipeline high throughput in addition to low power consumption. This paper presents a higher-throughput and ultralow-power asynchronous domino logic pipeline design method, targeting to latch-free and very fine-grain or gate-level design. The information pathways are comprised of a combination of dual-rail and single-rail domino gates. The 4 phase bundled-data protocol design most carefully resembles the style of synchronous circuits. Furthermore, the stable critical data path enables the adoption of single-rail domino gates within the noncritical data pathways. An 8 × 8 array style multiplier can be used for evaluating the suggested pipeline method. This saves lots of power by reduction of the overhead of logic circuits. In contrast to a bundled-data asynchronous domino logic pipeline, the suggested pipeline saves energy within the best situation and also the worst situation when processing different data patterns

Radiação Solar Total Dentro E Fora De Floresta Tropical Úmida De Terra Firme (Tucuruí, Pará)

Measurements of global solar radiation within and outside the tropical forest were made on 7th november 1986 in the area of the Tucurui, Para. The intensities of solar radiation at 3 sensors distributed randomly on the forest floor and one sensor located in an open area (standar sensor) are avaluated and intercompared. The average solar radiation which reachead the forest was 4.7% of the incident radiation over an open area. The diferences among the measurements of sensors and the etandar eeneorwae atributed to heterogeneous spatial distribution of sunlight penetration into the forest floor.Medidas de radiação solar global foram executadas dentro e fora de mata tropical úmida de terra firme durante o dia 07 de novembro de 1986, em Tucuruí, Pará. As intensidades de radiação solar incidentes em 3 sensores instalados aleatoriamente no chão da floresta e um sensor localizado em área aberta (sensor padrão) são avaliadas e intercomparadas. A radiação média que atinge o chão da floreeta foi 4.7% da radiação incidente em área aberta adjacente à floresta. As diferenças entre as medidas dos sensores da mata e o padrão pode ser atribuída à distribuição espacial heterogênea da radiação solar que alcança o chão da floresta

Increasing peptide identifications and decreasing search times for ETD spectra by pre-processing and calculation of parent precursor charge

<p>Abstract</p> <p>Background</p> <p>Electron Transfer Dissociation [ETD] can dissociate multiply charged precursor polypeptides, providing extensive peptide backbone cleavage. ETD spectra contain charge reduced precursor peaks, usually of high intensity, and whose pattern is dependent on its parent precursor charge. These charge reduced precursor peaks and associated neutral loss peaks should be removed before these spectra are searched for peptide identifications. ETD spectra can also contain ion-types other than c and z<b>˙</b>. Modifying search strategies to accommodate these ion-types may aid in increased peptide identifications. Additionally, if the precursor mass is measured using a lower resolution instrument such as a linear ion trap, the charge of the precursor is often not known, reducing sensitivity and increasing search times. We implemented algorithms to remove these precursor peaks, accommodate new ion-types in noise filtering routine in OMSSA and to estimate any unknown precursor charge, using Linear Discriminant Analysis [LDA].</p> <p>Results</p> <p>Spectral pre-processing to remove precursor peaks and their associated neutral losses prior to protein sequence library searches resulted in a 9.8% increase in peptide identifications at a 1% False Discovery Rate [FDR] compared to previous OMSSA filter. Modifications to the OMSSA noise filter to accommodate various ion-types resulted in a further 4.2% increase in peptide identifications at 1% FDR. Moreover, ETD spectra when searched with charge states obtained from the precursor charge determination algorithm is shown to be up to 3.5 times faster than the general range search method, with a minor 3.8% increase in sensitivity.</p> <p>Conclusion</p> <p>Overall, there is an 18.8% increase in peptide identifications at 1% FDR by incorporating the new precursor filter, noise filter and by using the charge determination algorithm, when compared to previous versions of OMSSA.</p

Integrated analytical models for flexible manufacturing systems

Product form queueing networks (PFQN) and generalized stochastic Petri nets (GSPN) have emerged as the principal performance modelling tools for flexible manufacturing systems (FMS). In this paper, we present integrated PFQN-GSPN models, which combine the computational efficiency of PFQN and representational power of GSPN by employing the principle of flow-equivalence. We show that FMS that include non-product form characteristics such as dynamic routing and synchronization can be evaluated efficiently and accurately using the integrated models