972 resultados para soft systems


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In this paper conditional hidden Markov model (HMM) filters and conditional Kalman filters (KF) are coupled together to improve demodulation of differential encoded signals in noisy fading channels. We present an indicator matrix representation for differential encoded signals and the optimal HMM filter for demodulation. The filter requires O(N3) calculations per time iteration, where N is the number of message symbols. Decision feedback equalisation is investigated via coupling the optimal HMM filter for estimating the message, conditioned on estimates of the channel parameters, and a KF for estimating the channel states, conditioned on soft information message estimates. The particular differential encoding scheme examined in this paper is differential phase shift keying. However, the techniques developed can be extended to other forms of differential modulation. The channel model we use allows for multiplicative channel distortions and additive white Gaussian noise. Simulation studies are also presented.

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It is not uncommon to hear a person of interest described by their height, build, and clothing (i.e. type and colour). These semantic descriptions are commonly used by people to describe others, as they are quick to communicate and easy to understand. However such queries are not easily utilised within intelligent video surveillance systems, as they are difficult to transform into a representation that can be utilised by computer vision algorithms. In this paper we propose a novel approach that transforms such a semantic query into an avatar in the form of a channel representation that is searchable within a video stream. We show how spatial, colour and prior information (person shape) can be incorporated into the channel representation to locate a target using a particle-filter like approach. We demonstrate state-of-the-art performance for locating a subject in video based on a description, achieving a relative performance improvement of 46.7% over the baseline. We also apply this approach to person re-detection, and show that the approach can be used to re-detect a person in a video steam without the use of person detection.

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Low-molecular-mass organogelators (LMOGs) based on photochromic molecules aggregate in selected solvents to form gels through various spatio-temporal interactions. The factors that control the mode of aggregation of the chromophoric core in the LMOGs during gelation, gelation-induced changes in fluorescence, the formation of stacked superstructures of extended pi-conjugated systems, and so forth are discussed with selected examples. Possible ways of generating various light-harvesting assemblies are proposed, and some unresolved questions, future challenges, and their possible solutions on this topic are presented.

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Fruit size and quality are major problems in early-season stonefruit cultivars grown in Australia and South-East Asia. In Australia, Thailand and Vietnam, new training and trellising systems are being developed to improve yield and fruit quality. Australian trials found that new training systems, such as the Open Tatura system, are more productive compared with standard vase-trained trees. We established new crop-loading indices for low-chill stonefruit to provide a guide for optimum fruit thinning based on fruit number per canopy surface and butt cross sectional area. Best management practices were developed for low-chill stonefruit cultivation using growth retardants, optimizing leaf nitrogen concentrations and controlling rates and timing of irrigation. Regulated deficit irrigation (RDI) improved fruit sugar concentrations by restricting water application during stage II of fruit growth. New pest and disease control measures are also being developed using a new generation of fruit fly baits. Soft insecticides such as (Spinosad) are used at significantly lower concentrations and have lower mammalian toxicity than the organophosphates currently registered in Australia. In addition, fruit fly exclusion netting effectively eliminated fruit fly and many other insect pests from the orchard with no increase in diseases. This netting system increased sugar concentrations of peach and nectarine by as much as 30%. Economic analyses showed that the break-even point can be reduced from 12 to 6 years Open Tatura trellising and exclusion netting.

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Pythium soft rot (PSR) of ginger caused by a number of Pythium species is of the most concern worldwide. In Australia, PSR outbreaks associated with Pythium myriotylum was recorded in 2007. Our recent pathogenicity tests in Petri dishes conducted on ginger rhizomes and pot trials on ginger plants showed that Pythiogeton (Py.) ramosum, an uncommon studied oomycete in Pythiaceae, was also pathogenic to ginger at high temperature (30–35 °C). Ginger sticks excised from the rhizomes were colonised by Py. ramosum which caused soft rot and browning lesions. Ginger plants inoculated with Py. ramosum showed initial symptoms of wilting and leave yellowing, which were indistinguishable from those of Pythium soft rot of ginger, at 10 days after inoculation. In addition, morphological and phylogenetic studies indicated that isolates of Py. ramosum were quite variable and our isolates obtained from soft rot ginger were divided into two groups based on these variations. This is also for the first time Py. ramosum is reported as a pathogen on ginger at high temperatures.

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As one of the most widely used wireless network technologies, IEEE 802.11 wireless local area networks (WLANs) have found a dramatically increasing number of applications in soft real-time networked control systems (NCSs). To fulfill the real-time requirements in such NCSs, most of the bandwidth of the wireless networks need to be allocated to high-priority data for periodic measurements and control with deadline requirements. However, existing QoS-enabled 802.11 medium access control (MAC) protocols do not consider the deadline requirements explicitly, leading to unpredictable deadline performance of NCS networks. Consequentially, the soft real-time requirements of the periodic traffic may not be satisfied, particularly under congested network conditions. This paper makes two main contributions to address this problem in wireless NCSs. Firstly, a deadline-constrained MAC protocol with QoS differentiation is presented for IEEE 802.11 soft real-time NCSs. It handles periodic traffic by developing two specific mechanisms: a contention-sensitive backoff mechanism, and an intra-traffic-class QoS differentiation mechanism. Secondly, a theoretical model is established to describe the deadline-constrained MAC protocol and evaluate its performance of throughput, delay and packet-loss ratio in wireless NCSs. Numerical studies are conducted to validate the accuracy of the theoretical model and to demonstrate the effectiveness of the new MAC protocol.

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Soft matter provides diverse opportunities for the development of electrolytes for all solid state lithium batteries. Here we review soft matter solid electrolytes for lithium batteriesthat are primarily obtained starting from liquid electrolytic systems. This concept of solid electrolyte synthesis from liquid is significantly different from prevalent approaches. The novelty of our approach is discussed in the light of various fundamental issues and in relation to its application to rechargeable lithium batteries.

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Networked digital technologies and Open Access (OA) are transforming the processes and institutions of research, knowledge creation and dissemination globally: enabling new forms of collaboration, allowing researchers to be seen and heard in new ways and reshaping relationships between stakeholders across the global academic publishing system. This article draws on Joseph Nye’s concept of ‘Soft Power’ to explore the role that OA is playing in helping to reshape academic publishing in China. It focusses on two important areas of OA development: OA journals and national-level repositories. OA is being supported at the highest levels, and there is potential for it to play an important role in increasing the status and impact of Chinese scholarship. Investments in OA also have the potential to help China to re-position itself within international copyright discourses: moving beyond criticism for failure to enforce the rights of foreign copyright owners and progressing an agenda that places greater emphasis on equality of access to the resources needed to foster innovation. However, the potential for OA to help China to build and project its soft power is being limited by the legacies of the print era, as well as the challenges of efficiently governing the national research and innovation systems.

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Agricultural pests are responsible for millions of dollars in crop losses and management costs every year. In order to implement optimal site-specific treatments and reduce control costs, new methods to accurately monitor and assess pest damage need to be investigated. In this paper we explore the combination of unmanned aerial vehicles (UAV), remote sensing and machine learning techniques as a promising technology to address this challenge. The deployment of UAVs as a sensor platform is a rapidly growing field of study for biosecurity and precision agriculture applications. In this experiment, a data collection campaign is performed over a sorghum crop severely damaged by white grubs (Coleoptera: Scarabaeidae). The larvae of these scarab beetles feed on the roots of plants, which in turn impairs root exploration of the soil profile. In the field, crop health status could be classified according to three levels: bare soil where plants were decimated, transition zones of reduced plant density and healthy canopy areas. In this study, we describe the UAV platform deployed to collect high-resolution RGB imagery as well as the image processing pipeline implemented to create an orthoimage. An unsupervised machine learning approach is formulated in order to create a meaningful partition of the image into each of the crop levels. The aim of the approach is to simplify the image analysis step by minimizing user input requirements and avoiding the manual data labeling necessary in supervised learning approaches. The implemented algorithm is based on the K-means clustering algorithm. In order to control high-frequency components present in the feature space, a neighbourhood-oriented parameter is introduced by applying Gaussian convolution kernels prior to K-means. The outcome of this approach is a soft K-means algorithm similar to the EM algorithm for Gaussian mixture models. The results show the algorithm delivers decision boundaries that consistently classify the field into three clusters, one for each crop health level. The methodology presented in this paper represents a venue for further research towards automated crop damage assessments and biosecurity surveillance.

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In this paper, we consider the design and bit-error performance analysis of linear parallel interference cancellers (LPIC) for multicarrier (MC) direct-sequence code division multiple access (DS-CDMA) systems. We propose an LPIC scheme where we estimate and cancel the multiple access interference (MAT) based on the soft decision outputs on individual subcarriers, and the interference cancelled outputs on different subcarriers are combined to form the final decision statistic. We scale the MAI estimate on individual subcarriers by a weight before cancellation. In order to choose these weights optimally, we derive exact closed-form expressions for the bit-error rate (BER) at the output of different stages of the LPIC, which we minimize to obtain the optimum weights for the different stages. In addition, using an alternate approach involving the characteristic function of the decision variable, we derive BER expressions for the weighted LPIC scheme, matched filter (MF) detector, decorrelating detector, and minimum mean square error (MMSE) detector for the considered multicarrier DS-CDMA system. We show that the proposed BER-optimized weighted LPIC scheme performs better than the MF detector and the conventional LPIC scheme (where the weights are taken to be unity), and close to the decorrelating and MMSE detectors.

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We present the x-ray absorption data at the oxygen K-edge using total yield technique for Gd1−xPrxba2Cu3O7 (x= 0.0, 0.2, 0.4, 0.6, 0.8, and 1.0). The data clearly to oxygen that the holes doped in the GdBa2Cu3O7 due to oxygen composition are not removed by Pr doping even for the x = 1.0 sample, suggesting that Pr is predominantly in the formally trivalent state. However, the data also clearly indicate the evidence of hybridization effects between the Pr3+ and the adjacent CuO2 layers. This is suggested to be responsible for the progressive suppression of Tc and the metallicity with Pr doping in these systems.

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In this paper, we present the design and bit error performance analysis of weighted linear parallel interference cancellers (LPIC) for multicarrier (MC) DS-CDMA systems. We propose an LPIC scheme where we estimate (and cancel) the multiple access interference (MAI) based on the soft outputs on individual subcarriers, and the interference cancelled outputs on different subcarriers are combined to form the final decision statistic. We scale the MAI estimate on individual subcarriers by a weight before cancellation; these weights are so chosen to maximize the signal-to-interference ratios at the individual subcarrier outputs. For this weighted LPIC scheme, using an approach involving the characteristic function of the decision variable, we derive exact bit error rate (BER) expressions for different cancellation stages. Using the same approach, we also derive exact BER expressions for the matched filter (MF) and decorrelating detectors for the considered MC DS-CDMA system. We show that the proposed weighted LPIC scheme performs better than the MF detector and the conventional LPIC (where the weights are taken to be unity), and close to the decorrelating detector.

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This review highlights the physics aspects of soft condensed matter to show that these are novel systems to explore cooperative behaviour in condensed matter under equilibrium and non-equilibrium conditions. A case is made for focusing research in this-area in our country.

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We report microscopic structural and dynamical measurements on binary mixtures of homopolymers and polymer grafted nanoparticles at high densities in good solvent. We find strong and unexpected anomalies in the structure and dynamics of these binary mixtures, including appearance of spontaneous orientational alignment, as a function of added homopolymers of different molecular weights. Our experiments point to the possibility of exploiting the phase space in density and homopolymer size, of such hybrid systems, to create new materials with novel structural and physical properties.

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Ensuring reliable operation over an extended period of time is one of the biggest challenges facing present day electronic systems. The increased vulnerability of the components to atmospheric particle strikes poses a big threat in attaining the reliability required for various mission critical applications. Various soft error mitigation methodologies exist to address this reliability challenge. A general solution to this problem is to arrive at a soft error mitigation methodology with an acceptable implementation overhead and error tolerance level. This implementation overhead can then be reduced by taking advantage of various derating effects like logical derating, electrical derating and timing window derating, and/or making use of application redundancy, e. g. redundancy in firmware/software executing on the so designed robust hardware. In this paper, we analyze the impact of various derating factors and show how they can be profitably employed to reduce the hardware overhead to implement a given level of soft error robustness. This analysis is performed on a set of benchmark circuits using the delayed capture methodology. Experimental results show upto 23% reduction in the hardware overhead when considering individual and combined derating factors.