939 resultados para Distance between Experts’ Statements


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In this paper we discuss a new type of query in Spatial Databases, called Trip Planning Query (TPQ). Given a set of points P in space, where each point belongs to a category, and given two points s and e, TPQ asks for the best trip that starts at s, passes through exactly one point from each category, and ends at e. An example of a TPQ is when a user wants to visit a set of different places and at the same time minimize the total travelling cost, e.g. what is the shortest travelling plan for me to visit an automobile shop, a CVS pharmacy outlet, and a Best Buy shop along my trip from A to B? The trip planning query is an extension of the well-known TSP problem and therefore is NP-hard. The difficulty of this query lies in the existence of multiple choices for each category. In this paper, we first study fast approximation algorithms for the trip planning query in a metric space, assuming that the data set fits in main memory, and give the theory analysis of their approximation bounds. Then, the trip planning query is examined for data sets that do not fit in main memory and must be stored on disk. For the disk-resident data, we consider two cases. In one case, we assume that the points are located in Euclidean space and indexed with an Rtree. In the other case, we consider the problem of points that lie on the edges of a spatial network (e.g. road network) and the distance between two points is defined using the shortest distance over the network. Finally, we give an experimental evaluation of the proposed algorithms using synthetic data sets generated on real road networks.

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Ongoing work towards appearance-based 3D hand pose estimation from a single image is presented. A large database of synthetic hand views is generated using a 3D hand model and computer graphics. The views display different hand shapes as seen from arbitrary viewpoints. Each synthetic view is automatically labeled with parameters describing its hand shape and viewing parameters. Given an input image, the system retrieves the most similar database views, and uses the shape and viewing parameters of those views as candidate estimates for the parameters of the input image. Preliminary results are presented, in which appearance-based similarity is defined in terms of the chamfer distance between edge images.

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This thesis elaborates on the problem of preprocessing a large graph so that single-pair shortest-path queries can be answered quickly at runtime. Computing shortest paths is a well studied problem, but exact algorithms do not scale well to real-world huge graphs in applications that require very short response time. The focus is on approximate methods for distance estimation, in particular in landmarks-based distance indexing. This approach involves choosing some nodes as landmarks and computing (offline), for each node in the graph its embedding, i.e., the vector of its distances from all the landmarks. At runtime, when the distance between a pair of nodes is queried, it can be quickly estimated by combining the embeddings of the two nodes. Choosing optimal landmarks is shown to be hard and thus heuristic solutions are employed. Given a budget of memory for the index, which translates directly into a budget of landmarks, different landmark selection strategies can yield dramatically different results in terms of accuracy. A number of simple methods that scale well to large graphs are therefore developed and experimentally compared. The simplest methods choose central nodes of the graph, while the more elaborate ones select central nodes that are also far away from one another. The efficiency of the techniques presented in this thesis is tested experimentally using five different real world graphs with millions of edges; for a given accuracy, they require as much as 250 times less space than the current approach which considers selecting landmarks at random. Finally, they are applied in two important problems arising naturally in large-scale graphs, namely social search and community detection.

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Large probabilistic graphs arise in various domains spanning from social networks to biological and communication networks. An important query in these graphs is the k nearest-neighbor query, which involves finding and reporting the k closest nodes to a specific node. This query assumes the existence of a measure of the "proximity" or the "distance" between any two nodes in the graph. To that end, we propose various novel distance functions that extend well known notions of classical graph theory, such as shortest paths and random walks. We argue that many meaningful distance functions are computationally intractable to compute exactly. Thus, in order to process nearest-neighbor queries, we resort to Monte Carlo sampling and exploit novel graph-transformation ideas and pruning opportunities. In our extensive experimental analysis, we explore the trade-offs of our approximation algorithms and demonstrate that they scale well on real-world probabilistic graphs with tens of millions of edges.

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In many real world situations, we make decisions in the presence of multiple, often conflicting and non-commensurate objectives. The process of optimizing systematically and simultaneously over a set of objective functions is known as multi-objective optimization. In multi-objective optimization, we have a (possibly exponentially large) set of decisions and each decision has a set of alternatives. Each alternative depends on the state of the world, and is evaluated with respect to a number of criteria. In this thesis, we consider the decision making problems in two scenarios. In the first scenario, the current state of the world, under which the decisions are to be made, is known in advance. In the second scenario, the current state of the world is unknown at the time of making decisions. For decision making under certainty, we consider the framework of multiobjective constraint optimization and focus on extending the algorithms to solve these models to the case where there are additional trade-offs. We focus especially on branch-and-bound algorithms that use a mini-buckets algorithm for generating the upper bound at each node of the search tree (in the context of maximizing values of objectives). Since the size of the guiding upper bound sets can become very large during the search, we introduce efficient methods for reducing these sets, yet still maintaining the upper bound property. We define a formalism for imprecise trade-offs, which allows the decision maker during the elicitation stage, to specify a preference for one multi-objective utility vector over another, and use such preferences to infer other preferences. The induced preference relation then is used to eliminate the dominated utility vectors during the computation. For testing the dominance between multi-objective utility vectors, we present three different approaches. The first is based on a linear programming approach, the second is by use of distance-based algorithm (which uses a measure of the distance between a point and a convex cone); the third approach makes use of a matrix multiplication, which results in much faster dominance checks with respect to the preference relation induced by the trade-offs. Furthermore, we show that our trade-offs approach, which is based on a preference inference technique, can also be given an alternative semantics based on the well known Multi-Attribute Utility Theory. Our comprehensive experimental results on common multi-objective constraint optimization benchmarks demonstrate that the proposed enhancements allow the algorithms to scale up to much larger problems than before. For decision making problems under uncertainty, we describe multi-objective influence diagrams, based on a set of p objectives, where utility values are vectors in Rp, and are typically only partially ordered. These can be solved by a variable elimination algorithm, leading to a set of maximal values of expected utility. If the Pareto ordering is used this set can often be prohibitively large. We consider approximate representations of the Pareto set based on ϵ-coverings, allowing much larger problems to be solved. In addition, we define a method for incorporating user trade-offs, which also greatly improves the efficiency.

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We obtain an upper bound on the time available for quantum computation for a given quantum computer and decohering environment with quantum error correction implemented. First, we derive an explicit quantum evolution operator for the logical qubits and show that it has the same form as that for the physical qubits but with a reduced coupling strength to the environment. Using this evolution operator, we find the trace distance between the real and ideal states of the logical qubits in two cases. For a super-Ohmic bath, the trace distance saturates, while for Ohmic or sub-Ohmic baths, there is a finite time before the trace distance exceeds a value set by the user. © 2010 The American Physical Society.

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PURPOSE: To develop a mathematical model that can predict refractive changes after Descemet stripping endothelial keratoplasty (DSEK). METHODS: A mathematical formula based on the Gullstrand eye model was generated to estimate the change in refractive power of the eye after DSEK. This model was applied to four DSEK cases retrospectively, to compare measured and predicted refractive changes after DSEK. RESULTS: The refractive change after DSEK is determined by calculating the difference in the power of the eye before and after DSEK surgery. The power of the eye post-DSEK surgery can be calculated with modified Gullstrand eye model equations that incorporate the change in the posterior radius of curvature and change in the distance between the principal planes of the cornea and lens after DSEK. Analysis of this model suggests that the ratio of central to peripheral graft thickness (CP ratio) and central thickness can have significant effect on refractive change where smaller CP ratios and larger graft thicknesses result in larger hyperopic shifts. This model was applied to four patients, and the average predicted hyperopic shift in the overall power of the eye was calculated to be 0.83 D. This change reflected in a mean of 93% (range, 75%-110%) of patients' measured refractive shifts. CONCLUSIONS: This simplified DSEK mathematical model can be used as a first step for estimating the hyperopic shift after DSEK. Further studies are necessary to refine the validity of this model.

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The adrenergic receptors (ARs) (subtypes alpha 1, alpha 2, beta 1, and beta 2) are a prototypic family of guanine nucleotide binding regulatory protein-coupled receptors that mediate the physiological effects of the hormone epinephrine and the neurotransmitter norepinephrine. We have previously assigned the genes for beta 2- and alpha 2-AR to human chromosomes 5 and 10, respectively. By Southern analysis of somatic cell hybrids and in situ chromosomal hybridization, we have now mapped the alpha 1-AR gene to chromosome 5q32----q34, the same position as beta 2-AR, and the beta 1-AR gene to chromosome 10q24----q26, the region where alpha 2-AR is located. In mouse, both alpha 2- and beta 1-AR genes were assigned to chromosome 19, and the alpha 1-AR locus was localized to chromosome 11. Pulsed field gel electrophoresis has shown that the alpha 1- and beta 2-AR genes in humans are within 300 kilobases (kb) and the distance between the alpha 2- and beta 1-AR genes is less than 225 kb. The proximity of these two pairs of AR genes and the sequence similarity that exists among all the ARs strongly suggest that they are evolutionarily related. Moreover, they likely arose from a common ancestral receptor gene and subsequently diverged through gene duplication and chromosomal duplication to perform their distinctive roles in mediating the physiological effects of catecholamines. The AR genes thus provide a paradigm for understanding the evolution of such structurally conserved yet functionally divergent families of receptor molecules.

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Collaborative approaches in leadership and management are increasingly acknowledged to play a key role in successful institutions in the learning and skills sector (LSS) (Ofsted, 2004). Such approaches may be important in bridging the potential 'distance' (psychological, cultural, interactional and geographical) (Collinson, 2005) that may exist between 'leaders' and 'followers', fostering more democratic communal solidarity. This paper reports on a 2006-07 research project funded by the Centre for Excellence in Leadership (CEL) that aimed to collect and analyse data on 'collaborative leadership' (CL) in the learning and skills sector. The project investigated collaborative leadership and its potential for benefiting staff through trust and knowledge-sharing in communities of practice (CoPs). The project forms part of longer-term educational research investigating leadership in a collaborative inquiry process (Jameson et al., 2006). The research examined the potential for CL to benefit institutions, analysing respondents' understanding of and resistance to collaborative practices. Quantitative and qualitative data from senior managers and lecturers was analysed using electronic data in SPSS and Tropes Zoom. The project aimed to recommend systems and practices for more inclusive, diverse leadership (Lumby et al., 2005). Collaborative leadership has increasingly gained international prominence as emphasis shifted towards team leadership beyond zero-sum 'leadership'/ 'followership' polarities into more mature conceptions of shared leadership spaces, within which synergistic leadership spaces can be mediated. The relevance of collaboration within the LSS has been highlighted following a spate of recent government-driven policy developments in FE. The promotion of CL addresses concerns about the apparent 'remoteness' of some senior managers, and the 'neo-management' control of professionals which can increase 'distance' between leaders and 'followers' and may de-professionalise staff in an already disempowered sector. Positive benefit from 'collaborative advantage' tends to be assumed in idealistic interpretations of CL, but potential 'collaborative inertia' may be problematic in a sector characterised by rapid top-down policy changes and continuous external audit and surveillance. Constant pressure for achievement against goals leaves little time for democratic group negotiations, despite the desires of leaders to create a more collaborative ethos. Yet prior models of intentional communities of practice potentially offer promise for CL practice to improve group performance despite multiple constraints. The CAMEL CoP model (JISC infoNet, 2006) was linked to the project, providing one practical way of implementing CL within situated professional networks.The project found that a good understanding of CL was demonstrated by most respondents, who thought it could enable staff to share power and work in partnership to build trust and conjoin skills, abilities and experience to achieve common goals for the good of the sector. However, although most respondents expressed agreement with the concept and ideals of CL, many thought this was currently an idealistically democratic, unachievable pipe dream in the LSS. Many respondents expressed concerns with the 'audit culture' and authoritarian management structures in FE. While there was a strong desire to see greater levels of implementation of CL, and 'collaborative advantage' from the 'knowledge sharing benefit potential' of team leadership, respondents also strongly advised against the pitfalls of 'collaborative inertia'. A 'distance' between senior leadership views and those of staff lower down the hierarchy regarding aspects of leadership performance in the sector was reported. Finally, the project found that more research is needed to investigate CL and develop innovative methods of practical implementation within autonomous communities of professional practice.

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The study of alternative combination rules in DS theory when evidence is in conflict has emerged again recently as an interesting topic, especially in data/information fusion applications. These studies have mainly focused on investigating which alternative would be appropriate for which conflicting situation, under the assumption that a conflict is identified. The issue of detection (or identification) of conflict among evidence has been ignored. In this paper, we formally define when two basic belief assignments are in conflict. This definition deploys quantitative measures of both the mass of the combined belief assigned to the emptyset before normalization and the distance between betting commitments of beliefs.We argue that only when both measures are high, it is safe to say the evidence is in conflict. This definition can be served as a prerequisite for selecting appropriate combination rules.

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By means of extensive first-principles calculations we studied the ferroelectric phase transition and the associated isotope effect in KH2PO4 (KDP). Our calculations revealed that the spontaneous polarization of the ferroelectric phase is due to electronic charge redistributions and ionic displacements which are a consequence of proton ordering, and not vice versa. The experimentally observed double-peaked proton distribution in the paraelectric phase cannot be explained by a dynamics of only protons. This requires, instead, collective displacements within clusters that include also the heavier ions. These tunneling clusters can explain the recent evidence of tunneling obtained from Compton scattering measurements. The sole effect of mass change upon deuteration is not sufficient to explain the huge isotope effect. Instead, we find that structural modifications deeply connected with the chemistry of the H bonds produce a feedback effect on tunneling that strongly enhances the phenomenon. The resulting influence of the geometric changes on the isotope effect agrees with experimental data from neutron scattering. Calculations under pressure allowed us to analyze the issue of universality in the disappearance of ferroelectricity upon compression. Compressing DKDP so that the distance between the two peaks in the deuteron distribution is the same as for protons in KDP, corresponds to a modification of the underlying double-well potential, which becomes 23 meV shallower. This energy difference is what is required to modify the O-O distance in such a way as to have the same distribution for protons and deuterons. At the high pressures required experimentally, the above feedback mechanism is crucial to explain the magnitude of the geometrical effect.

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Dense deployment of wireless local area network (WLAN) access points (APs) is an important part of the next generation Wi-Fi and standardization (802.11ax) efforts are underway. Increasing demand for WLAN connectivity motivates such dense deployments, especially in geographical areas with large numbers of users, such as stadiums, large enterprises, multi-tenant buildings, and urban cities. Although densification of WLAN APs guarantees coverage, it is susceptible to increased interference and uncoordinated association of stations (STAs) to APs, which degrade network throughput. Therefore, to improve network throughput, algorithms are proposed in this thesis to optimally coordinate AP associations in the presence of interference. In essence, coordination of APs in dense WLANs (DWLANs) is achieved through coordination of STAs' associations with APs. While existing approaches suggest tuning of APs' beacon powers or using transmit power control (TPC) for association control, here, the signal-to-interference-plus-noise ratio (SINRs) of STAs and the clear channel assessment (CCA) threshold of the 802.11 MAC protocol are employed. The proposed algorithms in this thesis enhance throughput and minimize coverage holes inherent in cell breathing and TPC techniques by not altering the transmit powers of APs, which determine cell coverage. Besides uncoordinated AP associations, unnecessary frequent transmission deferment is envisaged as another problem in DWLANs due to the clear channel assessment aspect of the carrier sensing multiple access collision avoidance (CSMA/CA) scheme in 802.11 standards and the short spatial reuse distance between co-channel APs. To address this problem in addition to AP association coordination, an algorithm is proposed for CCA threshold adjustment in each AP cell, such that CCA threshold used in one cell mitigates transmission deferment in neighboring cells. Performance evaluation reveals that the proposed association optimization algorithms achieve significant gain in throughput when compared with the default strongest signal first (SSF) association scheme in the current 802.11 standard. Also, further gain in throughput is observed when the CCA threshold adjustment is combined with the optimized association. Results show that when STA-AP association is optimized and CCA threshold is adjusted in each cell, throughput improves. Finally, transmission delay and the number of packet re-transmissions due to collision and contention significantly decrease.

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In Schizosaccharomyces pombe (fission yeast), the transition from G2 phase of the cell cycle to mitosis is under strict regulation. The activation of Cdc2, a cyclin dependent serine/threonine protein kinase, is the critical control step in this process. The Cdc2/Cyclin-B (Cdc13) complex is regulated by Wee1 tyrosine kinase and Cdc25 tyrosine phosphatase, which work antagonistically to control progression into mitosis. Hyperactivation of the Cdc2/Cdc13 complex by phosphorylation results in premature mitosis, and as a consequence leads to genome instability. This is referred to as mitotic catastrophe, a lethal phenotype associated with chromosomal segregation abnormalities including chromosome breakage. Six mitotic catastrophe loci were found, five of which have been characterized and identified as various activators and repressors of the core mitotic control. The locus for mcs3 remains unknown. I used tetrad analysis in this study to determine the linkage distance between three genes suspected of flanking the region in which mcs3 is located. Linkage distances obtained in this study confirm that the SPBC428.10 and met17, as well as SPBC428.10 and wpl1 are tightly linked, suggesting this is an area of low recombination. Further linkage analysis should be conducted to determine the precise location of mcs3-12.

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A series of Hunig's base tethered ammonium ionic liquids have been used to catalyse the Knoevenagel condensation of aldehydes/ketones with malononitrile and ethyl cyanoacetate. The reactions were performed under homogeneous and under biphasic, liquid-liquid and liquid-silica supported ionic liquid, conditions with the biphasic systems employing cyclohexene as the second phase. By increasing the distance between the ammonium head group and Hunig's base the activity of the catalyst was found to increase. Higher activity, in general, was found under homogeneous reaction conditions; however, the recyclability of the catalyst was improved by supporting the BIL under biphasic conditions. (c) 2007 Elsevier B.V. All rights reserved.

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Adults are proficient at reaching to grasp objects of interest in a cluttered workspace. The issue of concern, obstacle avoidance, was studied in 3 groups of young children aged 11-12, 9-10, and 7-8 years (n = 6 in each) and in 6 adults aged 18-24 years. Adults slowed their movements and decreased their maximum grip aperture when an obstacle was positioned close to a target object (the effect declined as the distance between target and obstacle increased). The children showed the same pattern, but the magnitude of the effect was quite different. In contrast to the adults, the obstacle continued to have a large effect when it was some distance from the target (and provided no physical obstruction to movement).