952 resultados para Multicast application level
Resumo:
Association rule mining has made many advances in the area of knowledge discovery. However, the quality of the discovered association rules is a big concern and has drawn more and more attention recently. One problem with the quality of the discovered association rules is the huge size of the extracted rule set. Often for a dataset, a huge number of rules can be extracted, but many of them can be redundant to other rules and thus useless in practice. Mining non-redundant rules is a promising approach to solve this problem. In this paper, we firstly propose a definition for redundancy; then we propose a concise representation called Reliable basis for representing non-redundant association rules for both exact rules and approximate rules. An important contribution of this paper is that we propose to use the certainty factor as the criteria to measure the strength of the discovered association rules. With the criteria, we can determine the boundary between redundancy and non-redundancy to ensure eliminating as many redundant rules as possible without reducing the inference capacity of and the belief to the remaining extracted non-redundant rules. We prove that the redundancy elimination based on the proposed Reliable basis does not reduce the belief to the extracted rules. We also prove that all association rules can be deduced from the Reliable basis. Therefore the Reliable basis is a lossless representation of association rules. Experimental results show that the proposed Reliable basis can significantly reduce the number of extracted rules.
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Background: There are innumerable diabetes studies that have investigated associations between risk factors, protective factors, and health outcomes; however, these individual predictors are part of a complex network of interacting forces. Moreover, there is little awareness about resilience or its importance in chronic disease in adulthood, especially diabetes. Thus, this is the first study to: (1) extensively investigate the relationships among a host of predictors and multiple adaptive outcomes; and (2) conceptualise a resilience model among people with diabetes. Methods: This cross-sectional study was divided into two research studies. Study One was to translate two diabetes-specific instruments (Problem Areas In Diabetes, PAID; Diabetes Coping Measure, DCM) into a Chinese version and to examine their psychometric properties for use in Study Two in a convenience sample of 205 outpatients with type 2 diabetes. In Study Two, an integrated theoretical model is developed and evaluated using the structural equation modelling (SEM) technique. A self-administered questionnaire was completed by 345 people with type 2 diabetes from the endocrine outpatient departments of three hospitals in Taiwan. Results: Confirmatory factor analyses confirmed a one-factor structure of the PAID-C which was similar to the original version of the PAID. Strong content validity of the PAID-C was demonstrated. The PAID-C was associated with HbA1c and diabetes self-care behaviours, confirming satisfactory criterion validity. There was a moderate relationship between the PAID-C and the Perceived Stress Scale, supporting satisfactory convergent validity. The PAID-C also demonstrated satisfactory stability and high internal consistency. A four-factor structure and strong content validity of the DCM-C was confirmed. Criterion validity demonstrated that the DCM-C was significantly associated with HbA1c and diabetes self-care behaviours. There was a statistical correlation between the DCM-C and the Revised Ways of Coping Checklist, suggesting satisfactory convergent validity. Test-retest reliability demonstrated satisfactory stability of the DCM-C. The total scale of the DCM-C showed adequate internal consistency. Age, duration of diabetes, diabetes symptoms, diabetes distress, physical activity, coping strategies, and social support were the most consistent factors associated with adaptive outcomes in adults with diabetes. Resilience was positively associated with coping strategies, social support, health-related quality of life, and diabetes self-care behaviours. Results of the structural equation modelling revealed protective factors had a significant direct effect on adaptive outcomes; however, the construct of risk factors was not significantly related to adaptive outcomes. Moreover, resilience can moderate the relationships among protective factors and adaptive outcomes, but there were no interaction effects of risk factors and resilience on adaptive outcomes. Conclusion: This study contributes to an understanding of how risk factors and protective factors work together to influence adaptive outcomes in blood sugar control, health-related quality of life, and diabetes self-care behaviours. Additionally, resilience is a positive personality characteristic and may be importantly involved in the adjustment process among people living with type 2 diabetes.
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Purpose Multi-level diode-clamped inverters have the challenge of capacitor voltage balancing when the number of DC-link capacitors is three or more. On the other hand, asymmetrical DC-link voltage sources have been applied to increase the number of voltage levels without increasing the number of switches. The purpose of this paper is to show that an appropriate multi-output DC-DC converter can resolve the problem of capacitor voltage balancing and utilize the asymmetrical DC-link voltages advantages. Design/methodology/approach A family of multi-output DC-DC converters is presented in this paper. The application of these converters is to convert the output voltage of a photovoltaic (PV) panel to regulate DC-link voltages of an asymmetrical four-level diode-clamped inverter utilized for domestic applications. To verify the versatility of the presented topology, simulations have been directed for different situations and results are presented. Some related experiments have been developed to examine the capabilities of the proposed converters. Findings The three-output voltage-sharing converters presented in this paper have been mathematically analysed and proven to be appropriate to improve the quality of the residential application of PV by means of four-level asymmetrical diode-clamped inverter supplying highly resistive loads. Originality/value This paper shows that an appropriate multi-output DC-DC converter can resolve the problem of capacitor voltage balancing and utilize the asymmetrical DC-link voltages advantages and that there is a possibility of operation at high-modulation index despite reference voltage magnitude and power factor variations.
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Vehicular ad hoc network (VANET) is a wireless ad hoc network that operates in a vehicular environment to provide communication between vehicles. VANET can be used by a diverse range of applications to improve road safety. Cooperative collision warning system (CCWS) is one of the safety applications that can provide situational awareness and warning to drivers by exchanging safety messages between cooperative vehicles. Currently, the routing strategies for safety message dissemination in CCWS are scoped broadcast. However, the broadcast schemes are not efficient as a warning message is sent to a large number of vehicles in the area, rather than only the endangered vehicles. They also cannot prioritize the receivers based on their critical time to avoid collision. This paper presents a more efficient multicast routing scheme that can reduce unnecessary transmissions and also use adaptive transmission range. The multicast scheme involves methods to identify an abnormal vehicle, the vehicles that may be endangered by the abnormal vehicle, and the latest time for each endangered vehicle to receive the warning message in order to avoid the danger. We transform this multicast routing problem into a delay-constrained minimum Steiner tree problem. Therefore, we can use existing algorithms to solve the problem. The advantages of our multicast routing scheme are mainly its potential to support various road traffic scenarios, to optimize the wireless channel utilization, and to prioritize the receivers.
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Osteoporotic spinal fractures are a major concern in ageing Western societies. This study develops a multi-scale finite element (FE) model of the osteoporotic lumbar vertebral body to study the mechanics of vertebral compression fracture at both the apparent (whole vertebral body) and micro-structural (internal trabecular bone core)levels. Model predictions were verified against experimental data, and found to provide a reasonably good representation of the mechanics of the osteoporotic vertebral body. This novel modelling methodology will allow detailed investigation of how trabecular bone loss in osteoporosis affects vertebral stiffness and strength in the lumbar spine.
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Traditional speech enhancement methods optimise signal-level criteria such as signal-to-noise ratio, but such approaches are sub-optimal for noise-robust speech recognition. Likelihood-maximising (LIMA) frameworks on the other hand, optimise the parameters of speech enhancement algorithms based on state sequences generated by a speech recogniser for utterances of known transcriptions. Previous applications of LIMA frameworks have generated a set of global enhancement parameters for all model states without taking in account the distribution of model occurrence, making optimisation susceptible to favouring frequently occurring models, in particular silence. In this paper, we demonstrate the existence of highly disproportionate phonetic distributions on two corpora with distinct speech tasks, and propose to normalise the influence of each phone based on a priori occurrence probabilities. Likelihood analysis and speech recognition experiments verify this approach for improving ASR performance in noisy environments.
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Multi-level concrete buildings requrre substantial temporary formwork structures to support the slabs during construction. The primary function of this formwork is to safely disperse the applied loads so that the slab being constructed, or the portion of the permanent structure already constructed, is not overloaded. Multi-level formwork is a procedure in which a limited number of formwork and shoring sets are cycled up the building as construction progresses. In this process, each new slab is supported by a number of lower level slabs. The new slab load is, essentially, distributed to these supporting slabs in direct proportion to their relative stiffness. When a slab is post-tensioned using draped tendons, slab lift occurs as a portion of the slab self-weight is balanced. The formwork and shores supporting that slab are unloaded by an amount equivalent to the load balanced by the post-tensioning. This produces a load distribution inherently different from that of a conventionally reinforced slab. Through , theoretical modelling and extensive on-site shore load measurement, this research examines the effects of post-tensioning on multilevel formwork load distribution. The research demonstrates that the load distribution process for post-tensioned slabs allows for improvements to current construction practice. These enhancements include a shortening of the construction period; an improvement in the safety of multi-level form work operations; and a reduction in the quantity of form work materials required for a project. These enhancements are achieved through the general improvement in safety offered by post-tensioning during the various formwork operations. The research demonstrates that there is generally a significant improvement in the factors of safety over those for conventionally reinforced slabs. This improvement in the factor of safety occurs at all stages of the multi-level formwork operation. The general improvement in the factors of safety with post-tensioned slabs allows for a shortening of the slab construction cycle time. Further, the low level of load redistribution that occurs during the stripping operations makes post-tensioned slabs ideally suited to reshoring procedures. Provided the overall number of interconnected levels remains unaltered, it is possible to increase the number of reshored levels while reducing the number of undisturbed shoring levels without altering the factors of safety, thereby, reducing the overall quantity of formwork and shoring materials.
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The main goal of this research is to design an efficient compression al~ gorithm for fingerprint images. The wavelet transform technique is the principal tool used to reduce interpixel redundancies and to obtain a parsimonious representation for these images. A specific fixed decomposition structure is designed to be used by the wavelet packet in order to save on the computation, transmission, and storage costs. This decomposition structure is based on analysis of information packing performance of several decompositions, two-dimensional power spectral density, effect of each frequency band on the reconstructed image, and the human visual sensitivities. This fixed structure is found to provide the "most" suitable representation for fingerprints, according to the chosen criteria. Different compression techniques are used for different subbands, based on their observed statistics. The decision is based on the effect of each subband on the reconstructed image according to the mean square criteria as well as the sensitivities in human vision. To design an efficient quantization algorithm, a precise model for distribution of the wavelet coefficients is developed. The model is based on the generalized Gaussian distribution. A least squares algorithm on a nonlinear function of the distribution model shape parameter is formulated to estimate the model parameters. A noise shaping bit allocation procedure is then used to assign the bit rate among subbands. To obtain high compression ratios, vector quantization is used. In this work, the lattice vector quantization (LVQ) is chosen because of its superior performance over other types of vector quantizers. The structure of a lattice quantizer is determined by its parameters known as truncation level and scaling factor. In lattice-based compression algorithms reported in the literature the lattice structure is commonly predetermined leading to a nonoptimized quantization approach. In this research, a new technique for determining the lattice parameters is proposed. In the lattice structure design, no assumption about the lattice parameters is made and no training and multi-quantizing is required. The design is based on minimizing the quantization distortion by adapting to the statistical characteristics of the source in each subimage. 11 Abstract Abstract Since LVQ is a multidimensional generalization of uniform quantizers, it produces minimum distortion for inputs with uniform distributions. In order to take advantage of the properties of LVQ and its fast implementation, while considering the i.i.d. nonuniform distribution of wavelet coefficients, the piecewise-uniform pyramid LVQ algorithm is proposed. The proposed algorithm quantizes almost all of source vectors without the need to project these on the lattice outermost shell, while it properly maintains a small codebook size. It also resolves the wedge region problem commonly encountered with sharply distributed random sources. These represent some of the drawbacks of the algorithm proposed by Barlaud [26). The proposed algorithm handles all types of lattices, not only the cubic lattices, as opposed to the algorithms developed by Fischer [29) and Jeong [42). Furthermore, no training and multiquantizing (to determine lattice parameters) is required, as opposed to Powell's algorithm [78). For coefficients with high-frequency content, the positive-negative mean algorithm is proposed to improve the resolution of reconstructed images. For coefficients with low-frequency content, a lossless predictive compression scheme is used to preserve the quality of reconstructed images. A method to reduce bit requirements of necessary side information is also introduced. Lossless entropy coding techniques are subsequently used to remove coding redundancy. The algorithms result in high quality reconstructed images with better compression ratios than other available algorithms. To evaluate the proposed algorithms their objective and subjective performance comparisons with other available techniques are presented. The quality of the reconstructed images is important for a reliable identification. Enhancement and feature extraction on the reconstructed images are also investigated in this research. A structural-based feature extraction algorithm is proposed in which the unique properties of fingerprint textures are used to enhance the images and improve the fidelity of their characteristic features. The ridges are extracted from enhanced grey-level foreground areas based on the local ridge dominant directions. The proposed ridge extraction algorithm, properly preserves the natural shape of grey-level ridges as well as precise locations of the features, as opposed to the ridge extraction algorithm in [81). Furthermore, it is fast and operates only on foreground regions, as opposed to the adaptive floating average thresholding process in [68). Spurious features are subsequently eliminated using the proposed post-processing scheme.
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Radioactive wastes are by-products of the use of radiation technologies. As with many technologies, the wastes are required to be disposed of in a safe manner so as to minimise risk to human health. This study examines the requirements for a hypothetical repository and develops techniques for decision making to permit the establishment of a shallow ground burial facility to receive an inventory of low-level radioactive wastes. Australia’s overall inventory is used as an example. Essential and desirable siting criteria are developed and applied to Australia's Northern Territory resulting in the selection of three candidate sites for laboratory investigations into soil behaviour. The essential quantifiable factors which govern radionuclide migration and ultimately influence radiation doses following facility closure are reviewed. Simplified batch and column procedures were developed to enable laboratory determination of distribution and retardation coefficient values for use in one-dimensional advection-dispersion transport equations. Batch and column experiments were conducted with Australian soils sampled from the three identified candidate sites using a radionuclide representative of the current national low-level radioactive waste inventory. The experimental results are discussed and site soil performance compared. The experimental results are subsequently used to compare the relative radiation health risks between each of the three sites investigated. A recommendation is made as to the preferred site to construct an engineered near-surface burial facility to receive the Australian low-level radioactive waste inventory.
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Analysis by enzyme-linked immunosorbent assay showed that Rice tungro bacilliform virus (RTBV) accumulated in a cyclic pattern from early to late stages of infection in tungro-susceptible variety, Taichung Native 1 (TN1), and resistant variety, Balimau Putih, singly infected with RTBV or co-infected with RTBV+Rice tungro spherical virus (RTSV). These changes in virus accumulation resulted in differences in RTBV levels and incidence of infection. The virus levels were expressed relative to those of the susceptible variety and the incidence of infection was assessed at different weeks after inoculation. At a particular time point, RTBV levels in TN1 or Balimau Putih singly infected with RTBV were not significantly different from the virus level in plants co-infected with RTBV+RTSV. The relative RTBV levels in Balimau Putih either singly infected with RTBV or co-infected with RTBV+RTSV were significantly lower than those in TN1. The incidence of RTBV infection varied at different times in Balimau Putih but not in TN1, and to determine the actual infection, the number of plants that became infected at least once anytime during the 4wk observation period was considered. Considering the changes in RTBV accumulation, new parameters for analyzing RTBV resistance were established. Based on these parameters, Balimau Putih was characterized having resistance to virus accumulation although the actual incidence of infection was >75%.
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In this paper, the commonly used switching schemes for sliding mode control of power converters is analyzed and designed in the frequency domain. Particular application of a distribution static compensator (DSTATCOM) in voltage control mode is investigated in a power distribution system. Tsypkin's method and describing function is used to obtain the switching conditions for the two-level and three-level voltage source inverters. Magnitude conditions of carrier signals are developed for robust switching of the inverter under carrier-based modulation scheme of sliding mode control. The existence of border collision bifurcation is identified to avoid the complex switching states of the inverter. The load bus voltage of an unbalanced three-phase nonstiff radial distribution system is controlled using the proposed carrier-based design. The results are validated using PSCAD/EMTDC simulation studies and through a scaled laboratory model of DSTATCOM that is developed for experimental verification
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It is important to examine the nature of the relationships between roadway, environmental, and traffic factors and motor vehicle crashes, with the aim to improve the collective understanding of causal mechanisms involved in crashes and to better predict their occurrence. Statistical models of motor vehicle crashes are one path of inquiry often used to gain these initial insights. Recent efforts have focused on the estimation of negative binomial and Poisson regression models (and related deviants) due to their relatively good fit to crash data. Of course analysts constantly seek methods that offer greater consistency with the data generating mechanism (motor vehicle crashes in this case), provide better statistical fit, and provide insight into data structure that was previously unavailable. One such opportunity exists with some types of crash data, in particular crash-level data that are collected across roadway segments, intersections, etc. It is argued in this paper that some crash data possess hierarchical structure that has not routinely been exploited. This paper describes the application of binomial multilevel models of crash types using 548 motor vehicle crashes collected from 91 two-lane rural intersections in the state of Georgia. Crash prediction models are estimated for angle, rear-end, and sideswipe (both same direction and opposite direction) crashes. The contributions of the paper are the realization of hierarchical data structure and the application of a theoretically appealing and suitable analysis approach for multilevel data, yielding insights into intersection-related crashes by crash type.
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With an increasing level of collaboration amongst researchers, software developers and industry practitioners in the past three decades, building information modelling (BIM) is now recognized as an emerging technological and procedural shift within the architect, engineering and construction (AEC) industry. BIM is not only considered as a way to make a profound impact on the professions of AEC, but is also regarded as an approach to assist the industry to develop new ways of thinking and practice. Despite the widespread development and recognition of BIM, a succinct and systematic review of the existing BIM research and achievement is scarce. It is also necessary to take stock on existing applications and have a fresh look at where BIM should be heading and how it can benefit from the advances being made. This paper first presents a review of BIM research and achievement in AEC industry. A number of suggestions are then made for future research in BIM. This paper maintains that the value of BIM during design and construction phases is well documented over the last decade, and new research needs to expand the level of development and analysis from design/build stage to postconstruction and facility asset management. New research in BIM could also move beyond the traditional building type to managing the broader range of facilities and built assets and providing preventative maintenance schedules for sustainable and intelligent buildings
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Studies indicate project success should be viewed from the different perspectives of the individual stakeholders. Project managers are owner’s agents. In order to allow early corrective actions to take place in case a project is diverted from plan, to accurately report perceived success of the stakeholders by project managers is essential, though there has been little systematic research in this area. The aim of this paper is to report the findings of an empirical study that compares the level of alignment between project managers and key stakeholders on a list of project performance indicators. A telephone survey involving 18 complex project managers and various key project stakeholder groups was conducted in this study. Krippendorff’s Kappa alpha reliability test was used to assess the alignment levels between project managers and stakeholders. Despite the overall agreement level between project manager and stakeholders is only medium; results have also identified 12 performance indicators that have significant level of agreement between project managers and stakeholders.