961 resultados para System components


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Accurate data of the natural conditions and agricultural systems with a good spatial resolution are a key factor to tackle food insecurity in developing countries. A broad variety of approaches exists to achieve precise data and information about agriculture. One system, especially developed for smallholder agriculture in East Africa, is the Farm Management Handbook of Kenya. It was first published in 1982/83 and fully revised in 2012, now containing 7 volumes. The handbooks contain detailed information on climate, soils, suitable crops and soil care based on scientific research results of the last 30 years. The density of facts leads to time consuming extraction of all necessary information. In this study we analyse the user needs and necessary components of a system for decision support for smallholder farming in Kenya based on a geographical information system (GIS). Required data sources were identified, as well as essential functions of the system. We analysed the results of our survey conducted in 2012 and early 2013 among agricultural officers. The monitoring of user needs and the problem of non-adaptability of an agricultural information system on the level of extension officers in Kenya are the central objectives. The outcomes of the survey suggest the establishment of a decision support tool based on already available open source GIS components. The system should include functionalities to show general information for a specific location and should provide precise recommendations about suitable crops and management options to support agricultural guidance on farm level.

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A revolution\0\0\0 in earthmoving, a $100 billion industry, can be achieved with three components: the GPS location system, sensors and computers in bulldozers, and SITE CONTROLLER, a central computer system that maintains design data and directs operations. The first two components are widely available; I built SITE CONTROLLER to complete the triangle and describe it here. SITE CONTROLLER assists civil engineers in the design, estimation, and construction of earthworks, including hazardous waste site remediation. The core of SITE CONTROLLER is a site modelling system that represents existing and prospective terrain shapes, roads, hydrology, etc. Around this core are analysis, simulation, and vehicle control tools. Integrating these modules into one program enables civil engineers and contractors to use a single interface and database throughout the life of a project.

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In this report, a face recognition system that is capable of detecting and recognizing frontal and rotated faces was developed. Two face recognition methods focusing on the aspect of pose invariance are presented and evaluated - the whole face approach and the component-based approach. The main challenge of this project is to develop a system that is able to identify faces under different viewing angles in realtime. The development of such a system will enhance the capability and robustness of current face recognition technology. The whole-face approach recognizes faces by classifying a single feature vector consisting of the gray values of the whole face image. The component-based approach first locates the facial components and extracts them. These components are normalized and combined into a single feature vector for classification. The Support Vector Machine (SVM) is used as the classifier for both approaches. Extensive tests with respect to the robustness against pose changes are performed on a database that includes faces rotated up to about 40 degrees in depth. The component-based approach clearly outperforms the whole-face approach on all tests. Although this approach isproven to be more reliable, it is still too slow for real-time applications. That is the reason why a real-time face recognition system using the whole-face approach is implemented to recognize people in color video sequences.

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In this paper we present a component based person detection system that is capable of detecting frontal, rear and near side views of people, and partially occluded persons in cluttered scenes. The framework that is described here for people is easily applied to other objects as well. The motivation for developing a component based approach is two fold: first, to enhance the performance of person detection systems on frontal and rear views of people and second, to develop a framework that directly addresses the problem of detecting people who are partially occluded or whose body parts blend in with the background. The data classification is handled by several support vector machine classifiers arranged in two layers. This architecture is known as Adaptive Combination of Classifiers (ACC). The system performs very well and is capable of detecting people even when all components of a person are not found. The performance of the system is significantly better than a full body person detector designed along similar lines. This suggests that the improved performance is due to the components based approach and the ACC data classification structure.

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Colour image segmentation based on the hue component presents some problems due to the physical process of image formation. One of that problems is colour clipping, which appear when at least one of the sensor components is saturated. We have designed a system, that works for a trained set of colours, to recover the chromatic information of those pixels on which colour has been clipped. The chromatic correction method is based on the fact that hue and saturation are invariant to the uniform scaling of the three RGB components. The proposed method has been validated by means of a specific colour image processing board that has allowed its execution in real time. We show experimental results of the application of our method

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Process supervision is the activity focused on monitoring the process operation in order to deduce conditions to maintain the normality including when faults are present Depending on the number/distribution/heterogeneity of variables, behaviour situations, sub-processes, etc. from processes, human operators and engineers do not easily manipulate the information. This leads to the necessity of automation of supervision activities. Nevertheless, the difficulty to deal with the information complicates the design and development of software applications. We present an approach called "integrated supervision systems". It proposes multiple supervisors coordination to supervise multiple sub-processes whose interactions permit one to supervise the global process

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This paper addresses the application of a PCA analysis on categorical data prior to diagnose a patients data set using a Case-Based Reasoning (CBR) system. The particularity is that the standard PCA techniques are designed to deal with numerical attributes, but our medical data set contains many categorical data and alternative methods as RS-PCA are required. Thus, we propose to hybridize RS-PCA (Regular Simplex PCA) and a simple CBR. Results show how the hybrid system produces similar results when diagnosing a medical data set, that the ones obtained when using the original attributes. These results are quite promising since they allow to diagnose with less computation effort and memory storage

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In this session we look at how to model flow of control and interactions between components using UML Activity and Sequence Diagrams. This is an introductory session and so for Activity Diagrams we only cover branching, forks and joins and swim lanes, and for Sequence we cover lifelines, messages and returns, and alt, par and opt frames.

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Back injuries identification and diagnoses in the transition of the Taylor model to the flexiblemodel of production organization, demands a parallel intervention of prevention actors at work. This study uses simultaneously three intervention models (structured action analysis, muscle skeletal symptoms questionnaires and muscle skeletal assessment) for work activities in a packaging plant. In this study seventy and two (72) operative workers participated (28 workers with muscle skeletal evaluation). In an intervention period of 10 months, the physical, cognitive, organizational components and productive process dynamics were evaluated from the muscle skeletal demands issues. The differences established between objective exposure at risk, back injury risk perception, appreciation and a vertebral spine evaluation, in prior and post intervention, determines the structure for a muscle skeletal risk management system. This study explains that back injury symptoms can be more efficiently reduced among operative workers combining measures registered and the adjustment between dynamics, the changes at work and efficient gestures development. Relevance: the results of this study can be used to pre ent back injuries in workers of flexible production processes.

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La sang és un subproducte amb un alt potencial de valorització que s'obté en quantitats importants en els escorxadors industrials. Actualment, la majoria de sistemes de recollida de la sang no segueixen unes mesures d'higiene estrictes, pel que esdevé un producte de baixa qualitat microbiològica. Conseqüentment, l'aprofitament de la sang és una sortida poc estimulant des del punt de vista econòmic, ja que acostuma a perdre les qualitats que permetrien l'obtenció de productes d'alt valor afegit. El capítol I del present treball s'inclou dins d'un projecte que proposa la inoculació de bacteris de l'àcid làctic (LAB) com un cultiu bioconservador de la sang, un sistema senzill i de baix cost que cerca l'estabilitat de la sang, tant microbiològica com fisicoquímica, durant el període del seu emmagatzematge. El capítol II s'emmarca dins d'un projecte que cerca la millora de l'aprofitament integral de la sang que, en el cas de la fracció plasmàtica, es centra en l'estudi de la funcionalitat dels seus principals constituents. Conèixer la contribució dels components majoritaris ha de permetre la millora de la funcionalitat dels ingredients alimentaris derivats. Els resultats presentats en aquesta tesi poden ajudar a la valorització de la sang porcina d'escorxadors industrials, mitjançant els coneixements adquirits pel que fa a la millora del seu sistema de recollida i del desenvolupament d'ingredients alimentaris amb interessants propietats funcionals.

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We present a general Multi-Agent System framework for distributed data mining based on a Peer-to-Peer model. Agent protocols are implemented through message-based asynchronous communication. The framework adopts a dynamic load balancing policy that is particularly suitable for irregular search algorithms. A modular design allows a separation of the general-purpose system protocols and software components from the specific data mining algorithm. The experimental evaluation has been carried out on a parallel frequent subgraph mining algorithm, which has shown good scalability performances.

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The CAFS search engine is a real machine in a virtual machine world; it is the hardware component of ICL's CAFS system. The paper is an introduction and prelude to the set of papers in this volume on CAFS applications. It defines The CAFS system and its context together with the function of its hardware and software components. It examines CAFS' role in the broad context of application development and information systems; it highlights some techniques and applications which exploit the CAFS system. Finally, it concludes with some suggestions for possible further developments. 'Search out thy wit for secret policies And we will make thee famous through the world' Henry VI, 1:3

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This study proposes an objective integrated seasonal forecasting system for producing well-calibrated probabilistic rainfall forecasts for South America. The proposed system has two components: ( i) an empirical model that uses Pacific and Atlantic sea surface temperature anomalies as predictors for rainfall and ( ii) a multimodel system composed of three European coupled ocean - atmosphere models. Three-month lead austral summer rainfall predictions produced by the components of the system are integrated ( i. e., combined and calibrated) using a Bayesian forecast assimilation procedure. The skill of empirical, coupled multimodel, and integrated forecasts obtained with forecast assimilation is assessed and compared. The simple coupled multimodel ensemble has a comparable level of skill to that obtained using a simplified empirical approach. As for most regions of the globe, seasonal forecast skill for South America is low. However, when empirical and coupled multimodel predictions are combined and calibrated using forecast assimilation, more skillful integrated forecasts are obtained than with either empirical or coupled multimodel predictions alone. Both the reliability and resolution of the forecasts have been improved by forecast assimilation in several regions of South America. The Tropics and the area of southern Brazil, Uruguay, Paraguay, and northern Argentina have been found to be the two most predictable regions of South America during the austral summer. Skillful rainfall forecasts are generally only possible during El Nino or La Nina years rather than in neutral years.

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The anisotropic and isotropic components of the ν2, ν5 rotation-vibrational Raman bands of 13CH3F were obtained separately. The two upper states are coupled by a strong second-order Coriolis resonance. The anisotropic spectrum was analyzed by means of a program system due to R. Escribano. A contour simulation and a least-squares fit of 233 assigned transitions yielded values for ν5, ΔA5, ΔA2, and Aζ5a, 5b(z). The 13C shifts of ν2 and ν5 were obtained from the isotropic spectrum.

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Polyculture is traditionally a low-input agricultural system and is important in many developing countries. Polycultures of interplanted crops often support fewer pests at lower densities than monoculture and tend to increase number of natural enemies. Also Yellow Sticky Plastic Sheet Traps have proved useful for trapping aphids. A field study was conducted to study the effectiveness of these potential pest management techniques along with the partially resistant (Cardinal) and susceptible (Desiree) potato cultivars, by using their different combinations for the management of Myzus persicae (Sulzer). Berseem, Trifolium alexandrinum (L.) (family: Leguminosae) was used for intercropping with potatoes. The different combinations (treatments) used in this study were: 1) Cardinal-berseem mixed cropping+yellow sticky plastic sheet traps 2) Cardinal-berseem mixed cropping 3) Cardinal+yellow sticky plastic sheet traps 4) Cardinal separately+berseem (as land area equivalents in relation to the mixed cropping treatments) 5) Cardinal (sole crop). Treatments 6-10 were the same treatments, but with Desiree as the potato cultivar. All these treatments were used to evaluate their effects as management techniques for M. persicae, their percent parasitism, percent emergence rate of the parasitoid, Aphidius matricariae Haliday and yield of Cardinal and Desiree. Mixed cropping of Cardinal and berseem together with the yellow sticky plastic sheet traps reduced aphids by over 90% compared with numbers on the sole Cardinal crop. This combination proved in this experiment the most effective for reducing the aphid populations as compared with all other treatments. Maximum percent parasitism i.e. 6.97 and 6.94% (almost double that in the other treatments) was recorded in the potato berseem mixed cropping, with and without traps respectively. In the same two treatments, yield was increased significantly as compared with all other treatments. However no significant effects of any of the variable was evident on the percent emergence of A. matricariae.