888 resultados para Supervisory Control and Data Acquisition (SCADA) Topology


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Molluscan shells may display a variety of colors, which formation, inheritance, and evolutionary significance are not Well understood. Here we report a new variant of the Pacific abalone Haliotis discus hannai that displays a novel orange shell coloration (O-type) that is clearly distinguishable from the Wild green-shelled abalone (G-type). Controlled mating experiments between O- and G-type abalones demonstrated apparent Mendelian segregations (1:1 or 3:1) in shell colors in F-2 families, which support the notion that the O- and G-types are under strict genetic control at a single locus With a recessive o (for orange shell) allele and a dominant G (for green shell) allele. Feeding with different diets caused modifications of shell color within each genotype, ranging from orange to yellow for O-type and green to dark-brown for the G-type, without affecting the distinction between genotypes. A previously described bluish-purple (B-type) shell color was found in one of the putative oo X oG crosses, suggesting that the B-type may be it recessive allele belonging to the same locus. The new O-type variant had no effect on the growth of Pacific abalone on the early seed-stage. This Study demonstrates that shell color in Pacific abalone is subject to genetic control as well as dietary modification, and the latter probably offers selective advantages in camouflage and predator avoidance.

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We combine theories of optimal pump-dump control and the related transient probe absorption spectroscopy in order to elucidate the relation between these two optical processes and the possibility of experimental realization. In the weak response regime, we identify the globally optimal pair of pump-dump control fields, and further propose a second-order difference detection scheme to monitor the wave packets dynamics that is jointly controlled by both the pump and dump fields. The globally optimal solution serves also as the initial input for the iterative search for the optimal control fields in the strong response regime. We use a model I-2 molecule to demonstrate numerically the pump-dump control and the detection of a highly vibrationally excited wave packet focusing dynamics on the ground X surface in both the weak and strong response regimes. The I2B surface serves as the intermediate to assist the pump-dump control and the optical detection processes. Demonstrated in the strong response regime are the optimal pair of pump-dump molecular-pi pulses that invert nearly total population onto the predefined target region within a half period of vibration motion. (C) 1999 American Institute of Physics. [S0021-9606(99)00115-4].

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This thesis proposes a computational model of how children may come to learn the meanings of words in their native language. The proposed model is divided into two separate components. One component produces semantic descriptions of visually observed events while the other correlates those descriptions with co-occurring descriptions of those events in natural language. The first part of this thesis describes three implementations of the correlation process whereby representations of the meanings of whole utterances can be decomposed into fragments assigned as representations of the meanings of individual words. The second part of this thesis describes an implemented computer program that recognizes the occurrence of simple spatial motion events in simulated video input.

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Barnes, D. P., Lee, M. H., Hardy, N. W. (1983). A control and monitoring system for multiple-sensor industrial robots. In Proc. 3rd. Int. Conf. Robot Vision and Sensory Controls, Cambridge, MA. USA., 471-479.

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The increased diversity of Internet application requirements has spurred recent interests in flexible congestion control mechanisms. Window-based congestion control schemes use increase rules to probe available bandwidth, and decrease rules to back off when congestion is detected. The parameterization of these control rules is done so as to ensure that the resulting protocol is TCP-friendly in terms of the relationship between throughput and packet loss rate. In this paper, we propose a novel window-based congestion control algorithm called SIMD (Square-Increase/Multiplicative-Decrease). Contrary to previous memory-less controls, SIMD utilizes history information in its control rules. It uses multiplicative decrease but the increase in window size is in proportion to the square of the time elapsed since the detection of the last loss event. Thus, SIMD can efficiently probe available bandwidth. Nevertheless, SIMD is TCP-friendly as well as TCP-compatible under RED, and it has much better convergence behavior than TCP-friendly AIMD and binomial algorithms proposed recently.

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Buildings consume 40% of Ireland's total annual energy translating to 3.5 billion (2004). The EPBD directive (effective January 2003) places an onus on all member states to rate the energy performance of all buildings in excess of 50m2. Energy and environmental performance management systems for residential buildings do not exist and consist of an ad-hoc integration of wired building management systems and Monitoring & Targeting systems for non-residential buildings. These systems are unsophisticated and do not easily lend themselves to cost effective retrofit or integration with other enterprise management systems. It is commonly agreed that a 15-40% reduction of building energy consumption is achievable by efficiently operating buildings when compared with typical practice. Existing research has identified that the level of information available to Building Managers with existing Building Management Systems and Environmental Monitoring Systems (BMS/EMS) is insufficient to perform the required performance based building assessment. The cost of installing additional sensors and meters is extremely high, primarily due to the estimated cost of wiring and the needed labour. From this perspective wireless sensor technology provides the capability to provide reliable sensor data at the required temporal and spatial granularity associated with building energy management. In this paper, a wireless sensor network mote hardware design and implementation is presented for a building energy management application. Appropriate sensors were selected and interfaced with the developed system based on user requirements to meet both the building monitoring and metering requirements. Beside the sensing capability, actuation and interfacing to external meters/sensors are provided to perform different management control and data recording tasks associated with minimisation of energy consumption in the built environment and the development of appropriate Building information models(BIM)to enable the design and development of energy efficient spaces.

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Phages belonging to the 936 group represent one of the most prevalent and frequently isolated phages in dairy fermentation processes using Lactococcus lactis as the primary starter culture. In recent years extensive research has been carried out to characterise this phage group at a genomic level in an effort to understand how the 936 group phages dominate this particular niche and cause regular problems during large scale milk fermentations. This thesis describes a large scale screening of industrial whey samples, leading to the isolation of forty three genetically different lactococcal phages. Using multiplex PCR, all phages were identified as members of the 936 group. The complete genome of thirty eight of these phages was determined using next generation sequencing technologies which identified several regions of divergence. These included the structural region surrounding the major tail protein, the replication region as well as the genes involved in phage DNA packing. For a number of phages the latter genomic region was found to harbour genes encoding putative orphan methyltransferases. Using small molecule real time (SMRT) sequencing and heterologous gene expression, the target motifs for several of these MTases were determined and subsequently shown to actively protect phage DNA from restriction endonuclease activity. Comparative analysis of the thirty eight phages with fifty two previously sequenced members of this group showed that the core genome consists of 28 genes, while the non-core genome was found to fluctuate irrespective of geographical location or time of isolation. This study highlights the continued need to perform large scale characterisation of the bacteriophage populations infecting industrial fermentation facilities in effort to further our understanding dairy phages and ways to control their proliferation.

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An enterprise information system (EIS) is an integrated data-applications platform characterized by diverse, heterogeneous, and distributed data sources. For many enterprises, a number of business processes still depend heavily on static rule-based methods and extensive human expertise. Enterprises are faced with the need for optimizing operation scheduling, improving resource utilization, discovering useful knowledge, and making data-driven decisions.

This thesis research is focused on real-time optimization and knowledge discovery that addresses workflow optimization, resource allocation, as well as data-driven predictions of process-execution times, order fulfillment, and enterprise service-level performance. In contrast to prior work on data analytics techniques for enterprise performance optimization, the emphasis here is on realizing scalable and real-time enterprise intelligence based on a combination of heterogeneous system simulation, combinatorial optimization, machine-learning algorithms, and statistical methods.

On-demand digital-print service is a representative enterprise requiring a powerful EIS.We use real-life data from Reischling Press, Inc. (RPI), a digit-print-service provider (PSP), to evaluate our optimization algorithms.

In order to handle the increase in volume and diversity of demands, we first present a high-performance, scalable, and real-time production scheduling algorithm for production automation based on an incremental genetic algorithm (IGA). The objective of this algorithm is to optimize the order dispatching sequence and balance resource utilization. Compared to prior work, this solution is scalable for a high volume of orders and it provides fast scheduling solutions for orders that require complex fulfillment procedures. Experimental results highlight its potential benefit in reducing production inefficiencies and enhancing the productivity of an enterprise.

We next discuss analysis and prediction of different attributes involved in hierarchical components of an enterprise. We start from a study of the fundamental processes related to real-time prediction. Our process-execution time and process status prediction models integrate statistical methods with machine-learning algorithms. In addition to improved prediction accuracy compared to stand-alone machine-learning algorithms, it also performs a probabilistic estimation of the predicted status. An order generally consists of multiple series and parallel processes. We next introduce an order-fulfillment prediction model that combines advantages of multiple classification models by incorporating flexible decision-integration mechanisms. Experimental results show that adopting due dates recommended by the model can significantly reduce enterprise late-delivery ratio. Finally, we investigate service-level attributes that reflect the overall performance of an enterprise. We analyze and decompose time-series data into different components according to their hierarchical periodic nature, perform correlation analysis,

and develop univariate prediction models for each component as well as multivariate models for correlated components. Predictions for the original time series are aggregated from the predictions of its components. In addition to a significant increase in mid-term prediction accuracy, this distributed modeling strategy also improves short-term time-series prediction accuracy.

In summary, this thesis research has led to a set of characterization, optimization, and prediction tools for an EIS to derive insightful knowledge from data and use them as guidance for production management. It is expected to provide solutions for enterprises to increase reconfigurability, accomplish more automated procedures, and obtain data-driven recommendations or effective decisions.

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Cells respond to environmental stimuli by fine-tuned regulation of gene expression. Here we investigated the dose-dependent modulation of gene expression at high temporal resolution in response to nutrient and stress signals in yeast. The GAL1 activity in cell populations is modulated in a well-defined range of galactose concentrations, correlating with a dynamic change of histone remodeling and RNA polymerase II (RNAPII) association. This behavior is the result of a heterogeneous induction delay caused by decreasing inducer concentrations across the population. Chromatin remodeling appears to be the basis for the dynamic GAL1 expression, because mutants with impaired histone dynamics show severely truncated dose-response profiles. In contrast, the GRE2 promoter operates like a rapid off/on switch in response to increasing osmotic stress, with almost constant expression rates and exclusively temporal regulation of histone remodeling and RNAPII occupancy. The Gal3 inducer and the Hog1 mitogen-activated protein (MAP) kinase seem to determine the different dose-response strategies at the two promoters. Accordingly, GAL1 becomes highly sensitive and dose independent if previously stimulated because of residual Gal3 levels, whereas GRE2 expression diminishes upon repeated stimulation due to acquired stress resistance. Our analysis reveals important differences in the way dynamic signals create dose-sensitive gene expression outputs.

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Review of: Rights of the Accused, Crime Control and Protection of Victims. Edited by Eliahu Harnon & Alex Stein. A special volume of the Israel Law Review, Vol. 31, Nos. 1-3, Winter-Summer 1997. Published by the Faculty of Law, Hebrew University, Jerusalem.

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Analysis of the generic attacks and countermeasures for block cipher based message authentication code algorithms (MAC) in sensor applications is undertaken; the conclusions are used in the design of two new MAC constructs Quicker Block Chaining MAC1 (QBC-MAC1) and Quicker Block Chaining MAC2 (QBC-MAC2). Using software simulation we show that our new constructs point to improvements in usage of CPU instruction clock cycle and energy requirement when benchmarked against the de facto Cipher Block Chaining MAC (CBC-MAC) based construct used in the TinySec security protocol for wireless sensor networks.

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We consider the optimum design of pilot-symbol-assisted modulation (PSAM) schemes with feedback. The received signal is periodically fed back to the transmitter through a noiseless delayed link and the time-varying channel is modeled as a Gauss-Markov process. We optimize a lower bound on the channel capacity which incorporates the PSAM parameters and Kalman-based channel estimation and prediction. The parameters available for the capacity optimization are the data power adaptation strategy, pilot spacing and pilot power ratio, subject to an average power constraint. Compared to the optimized open-loop PSAM (i.e., the case where no feedback is provided from the receiver), our results show that even in the presence of feedback delay, the optimized power adaptation provides higher information rates at low signal-to-noise ratios (SNR) in medium-rate fading channels. However, in fast fading channels, even the presence of modest feedback delay dissipates the advantages of power adaptation.

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The US National Oceanic and Atmospheric Administration (NOAA) Fisheries Continuous Plankton Recorder (CPR) Survey has sampled four routes: Boston–Nova Scotia (1961–present), New York toward Bermuda (1976–present), Narragansett Bay–Mount Hope Bay–Rhode Island Sound (1998–present) and eastward of Chesapeake Bay (1974–1980). NOAA involvement began in 1974 when it assumed responsibility for the existing Boston–Nova Scotia route from what is now the UK's Sir Alister Hardy Foundation for Ocean Science (SAHFOS). Training, equipment and computer software were provided by SAHFOS to ensure continuity for this and standard protocols for any new routes. Data for the first 14 years of this route were provided to NOAA by SAHFOS. Comparison of collection methods; sample processing; and sample identification, staging and counting techniques revealed near-consistency between NOAA and SAHFOS. One departure involved phytoplankton counting standards. This has since been addressed and the data corrected. Within- and between-survey taxonomic and life-stage names and their consistency through time were, and continue to be, an issue. For this, a cross-reference table has been generated that contains the SAHFOS taxonomic code, NOAA taxonomic code, NOAA life-stage code, National Oceanographic Data Center (NODC) taxonomic code, Integrated Taxonomic Information System (ITIS) serial number and authority and consistent use/route. This table is available for review/use by other CPR surveys. Details of the NOAA and SAHFOS comparison and analytical techniques unique to NOAA are presented.