61 resultados para distributed programming abstractions


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Cooperative transmission can be seen as a "virtual" MIMO system, where themultiple transmit antennas are in fact implemented distributed by the antennas both at the source and the relay terminal. Depending on the system design, diversity/multiplexing gainsare achievable. This design involves the definition of the type of retransmission (incrementalredundancy, repetition coding), the design of the distributed space-time codes, the errorcorrecting scheme, the operation of the relay (decode&forward or amplify&forward) and thenumber of antennas at each terminal. Proposed schemes are evaluated in different conditionsin combination with forward error correcting codes (FEC), both for linear and near-optimum(sphere decoder) receivers, for its possible implementation in downlink high speed packetservices of cellular networks. Results show the benefits of coded cooperation over directtransmission in terms of increased throughput. It is shown that multiplexing gains areobserved even if the mobile station features a single antenna, provided that cell wide reuse of the relay radio resource is possible.

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This paper presents a programming environment for supporting learning in STEM, particularly mobile robotic learning. It was designed to maintain progressive learning for people with and without previous knowledge of programming and/or robotics. The environment was multi platform and built with open source tools. Perception, mobility, communication, navigation and collaborative behaviour functionalities can be programmed for different mobile robots. A learner is able to programme robots using different programming languages and editor interfaces: graphic programming interface (basic level), XML-based meta language (intermediate level) or ANSI C language (advanced level). The environment supports programme translation transparently into different languages for learners or explicitly on learners’ demand. Learners can access proposed challenges and learning interfaces by examples. The environment was designed to allow characteristics such as extensibility, adaptive interfaces, persistence and low software/hardware coupling. Functionality tests were performed to prove programming environment specifications. UV BOT mobile robots were used in these tests

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The control of the right application of medical protocols is a key issue in hospital environments. For the automated monitoring of medical protocols, we need a domain-independent language for their representation and a fully, or semi, autonomous system that understands the protocols and supervises their application. In this paper we describe a specification language and a multi-agent system architecture for monitoring medical protocols. We model medical services in hospital environments as specialized domain agents and interpret a medical protocol as a negotiation process between agents. A medical service can be involved in multiple medical protocols, and so specialized domain agents are independent of negotiation processes and autonomous system agents perform monitoring tasks. We present the detailed architecture of the system agents and of an important domain agent, the database broker agent, that is responsible of obtaining relevant information about the clinical history of patients. We also describe how we tackle the problems of privacy, integrity and authentication during the process of exchanging information between agents.

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Possibilistic Defeasible Logic Programming (P-DeLP) is a logic programming language which combines features from argumentation theory and logic programming, incorporating the treatment of possibilistic uncertainty at the object-language level. In spite of its expressive power, an important limitation in P-DeLP is that imprecise, fuzzy information cannot be expressed in the object language. One interesting alternative for solving this limitation is the use of PGL+, a possibilistic logic over Gödel logic extended with fuzzy constants. Fuzzy constants in PGL+ allow expressing disjunctive information about the unknown value of a variable, in the sense of a magnitude, modelled as a (unary) predicate. The aim of this article is twofold: firstly, we formalize DePGL+, a possibilistic defeasible logic programming language that extends P-DeLP through the use of PGL+ in order to incorporate fuzzy constants and a fuzzy unification mechanism for them. Secondly, we propose a way to handle conflicting arguments in the context of the extended framework.

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In the last decade defeasible argumentation frameworks have evolved to become a sound setting to formalize commonsense, qualitative reasoning. The logic programming paradigm has shown to be particularly useful for developing different argument-based frameworks on the basis of different variants of logic programming which incorporate defeasible rules. Most of such frameworks, however, are unable to deal with explicit uncertainty, nor with vague knowledge, as defeasibility is directly encoded in the object language. This paper presents Possibilistic Logic Programming (P-DeLP), a new logic programming language which combines features from argumentation theory and logic programming, incorporating as well the treatment of possibilistic uncertainty. Such features are formalized on the basis of PGL, a possibilistic logic based on G¨odel fuzzy logic. One of the applications of P-DeLP is providing an intelligent agent with non-monotonic, argumentative inference capabilities. In this paper we also provide a better understanding of such capabilities by defining two non-monotonic operators which model the expansion of a given program P by adding new weighed facts associated with argument conclusions and warranted literals, respectively. Different logical properties for the proposed operators are studied

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The performance of a hydrologic model depends on the rainfall input data, both spatially and temporally. As the spatial distribution of rainfall exerts a great influence on both runoff volumes and peak flows, the use of a distributed hydrologic model can improve the results in the case of convective rainfall in a basin where the storm area is smaller than the basin area. The aim of this study was to perform a sensitivity analysis of the rainfall time resolution on the results of a distributed hydrologic model in a flash-flood prone basin. Within such a catchment, floods are produced by heavy rainfall events with a large convective component. A second objective of the current paper is the proposal of a methodology that improves the radar rainfall estimation at a higher spatial and temporal resolution. Composite radar data from a network of three C-band radars with 6-min temporal and 2 × 2 km2 spatial resolution were used to feed the RIBS distributed hydrological model. A modification of the Window Probability Matching Method (gauge-adjustment method) was applied to four cases of heavy rainfall to improve the observed rainfall sub-estimation by computing new Z/R relationships for both convective and stratiform reflectivities. An advection correction technique based on the cross-correlation between two consecutive images was introduced to obtain several time resolutions from 1 min to 30 min. The RIBS hydrologic model was calibrated using a probabilistic approach based on a multiobjective methodology for each time resolution. A sensitivity analysis of rainfall time resolution was conducted to find the resolution that best represents the hydrological basin behaviour.

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Concurrent aims to be a different type of task distribution system compared to what MPI like system do. It adds a simple but powerful application abstraction layer to distribute the logic of an entire application onto a swarm of clusters holding similarities with volunteer computing systems. Traditional task distributed systems will just perform simple tasks onto the distributed system and wait for results. Concurrent goes one step further by letting the tasks and the application decide what to do. The programming paradigm is then totally async without any waits for results and based on notifications once a computation has been performed.

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Virtual Laboratories are an indispensablespace for developing practical activities in a Virtual Environment. In the field of Computer and Software Engineering different types of practical activities have tobe performed in order to obtain basic competences which are impossible to achieve by other means. This paper specifies an ontology for a general virtual laboratory.The proposed ontology provides a mechanism to select the best resources needed in a Virtual Laboratory once a specific practical activity has been defined and the maincompetences that students have to achieve in the learning process have been fixed. Furthermore, the proposed ontology can be used to develop an automatic and wizardtool that creates a Moodle Classroom using the practical activity specification and the related competences.

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The activated sludge process - the main biological technology usually applied towastewater treatment plants (WWTP) - directly depends on live beings (microorganisms), and therefore on unforeseen changes produced by them. It could be possible to get a good plant operation if the supervisory control system is able to react to the changes and deviations in the system and can take thenecessary actions to restore the system’s performance. These decisions are oftenbased both on physical, chemical, microbiological principles (suitable to bemodelled by conventional control algorithms) and on some knowledge (suitable to be modelled by knowledge-based systems). But one of the key problems in knowledge-based control systems design is the development of an architecture able to manage efficiently the different elements of the process (integrated architecture), to learn from previous cases (spec@c experimental knowledge) and to acquire the domain knowledge (general expert knowledge). These problems increase when the process belongs to an ill-structured domain and is composed of several complex operational units. Therefore, an integrated and distributed AIarchitecture seems to be a good choice. This paper proposes an integrated and distributed supervisory multi-level architecture for the supervision of WWTP, that overcomes some of the main troubles of classical control techniques and those of knowledge-based systems applied to real world systems

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Previous genetic studies have demonstrated that natal homing shapes the stock structure of marine turtle nesting populations. However, widespread sharing of common haplotypes based on short segments of the mitochondrial control region often limits resolution of the demographic connectivity of populations. Recent studies employing longer control region sequences to resolve haplotype sharing have focused on regional assessments of genetic structure and phylogeography. Here we synthesize available control region sequences for loggerhead turtles from the Mediterranean Sea, Atlantic, and western Indian Ocean basins. These data represent six of the nine globally significant regional management units (RMUs) for the species and include novel sequence data from Brazil, Cape Verde, South Africa and Oman. Genetic tests of differentiation among 42 rookeries represented by short sequences (380 bp haplotypes from 3,486 samples) and 40 rookeries represented by long sequences (~800 bp haplotypes from 3,434 samples) supported the distinction of the six RMUs analyzed as well as recognition of at least 18 demographically independent management units (MUs) with respect to female natal homing. A total of 59 haplotypes were resolved. These haplotypes belonged to two highly divergent global lineages, with haplogroup I represented primarily by CC-A1, CC-A4, and CC-A11 variants and haplogroup II represented by CC-A2 and derived variants. Geographic distribution patterns of haplogroup II haplotypes and the nested position of CC-A11.6 from Oman among the Atlantic haplotypes invoke recent colonization of the Indian Ocean from the Atlantic for both global lineages. The haplotypes we confirmed for western Indian Ocean RMUs allow reinterpretation of previous mixed stock analysis and further suggest that contemporary migratory connectivity between the Indian and Atlantic Oceans occurs on a broader scale than previously hypothesized. This study represents a valuable model for conducting comprehensive international cooperative data management and research in marine ecology.

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Species structure and composition in Mediterranean riparian forests are determined by hydrological features, longitudinal zonation, and riverbank topography. This study assesses the distribution of four native riparian plants along the riverbank topographic gradient in three river stretches in southern Spain, with special emphasis on the occupation of adult and young feet of each species. The studied stretches suffered minimal human disturbances, displayed semi-arid conditions, and had wide riparian areas to allow the development of the target species: black alder (Alnus glutinosa), salvia leaf willow (Salix salviifolia), narrow-leafed ash (Fraxinus angustifolia), and oleander (Nerium oleander). Thalweg height was used to define the riverbank topographic gradient. The results showed a preferential zone for black alder and salvia leaf willow in the range of 0-150 cm from the channel thalweg, with adult alders and willows being more common between 51 and 150 cm and young alders being more common under 50 cm. Conversely, narrow-leafed ash and oleander were much more frequent, and showed greater development, in the ranges of 151-200 cm and 201-250 cm, respectively, whereas the young feet of both species covered the entire topographic range. Adult feet of the four species were spatially segregated along the riverbank topographic gradient, indicating their differential ability to cope with water stress from the non-tolerant alders and willows to more tolerant narrow-leafed ash trees and oleanders. Young feet, however, showed a strategy more closely linked to the initial availability of colonisation sites within riparian areas to the dispersion strategy of each species and to the distribution of adult feet. In Mediterranean areas, where riparian management has traditionally faced great challenges, the incorporation of species preferences along riverbank gradients could improve the performance of restoration projects.

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In this paper we address the problem of extracting representative point samples from polygonal models. The goal of such a sampling algorithm is to find points that are evenly distributed. We propose star-discrepancy as a measure for sampling quality and propose new sampling methods based on global line distributions. We investigate several line generation algorithms including an efficient hardware-based sampling method. Our method contributes to the area of point-based graphics by extracting points that are more evenly distributed than by sampling with current algorithms