Weighted composition followed by differentiation between weighted Banach spaces of holomorphic functions

2010 Mathematics Subject Classification: 47B33, 47B38.

Determining the change of Brillouin frequency shift by using the similarity matching method

We have proposed a similarity matching method (SMM) to obtain the change of Brillouin frequency shift (BFS), in which the change of BFS can be determined from the frequency difference between detecting spectrum and selected reference spectrum by comparing their similarity. We have also compared three similarity measures in the simulation, which has shown that the correlation coefficient is more accurate to determine the change of BFS. Compared with the other methods of determining the change of BFS, the SMM is more suitable for complex Brillouin spectrum profiles. More precise result and much faster processing speed have been verified in our simulation and experiments. The experimental results have shown that the measurement uncertainty of the BFS has been improved to 0.72 MHz by using the SMM, which is almost one-third of that by using the curve fitting method, and the speed of deriving the BFS change by the SMM is 120 times faster than that by the curve fitting method.

Permanent matching of coupled optical bottle resonators with better than 0.16 GHz precision

The fabrication precision is one of the most critical challenges to the creation of practical photonic circuits composed of coupled high Q-factor microresonators. While very accurate transient tuning of microresonators based on local heating has been reported, the record precision of permanent resonance positioning achieved by post-processing is still within 1 and 5 GHz. Here we demonstrate two coupled bottle microresonators fabricated at the fiber surface with resonances that are matched with a better than 0.16 GHz precision. This corresponds to a better than 0.17 Å precision in the effective fiber radius variation. The achieved fabrication precision is only limited by the resolution of our optical spectrum analyzer and can be potentially improved by an order of magnitude.

Binocular summation, binocular fusion and the transition to diplopia

The visual system combines spatial signals from the two eyes to achieve single vision. But if binocular disparity is too large, this perceptual fusion gives way to diplopia. We studied and modelled the processes underlying fusion and the transition to diplopia. The likely basis for fusion is linear summation of inputs onto binocular cortical cells. Previous studies of perceived position, contrast matching and contrast discrimination imply the computation of a dynamicallyweighted sum, where the weights vary with relative contrast. For gratings, perceived contrast was almost constant across all disparities, and this can be modelled by allowing the ocular weights to increase with disparity (Zhou, Georgeson & Hess, 2014). However, when a single Gaussian-blurred edge was shown to each eye perceived blur was invariant with disparity (Georgeson & Wallis, ECVP 2012) – not consistent with linear summation (which predicts that perceived blur increases with disparity). This blur constancy is consistent with a multiplicative form of combination (the contrast-weighted geometric mean) but that is hard to reconcile with the evidence favouring linear combination. We describe a 2-stage spatial filtering model with linear binocular combination and suggest that nonlinear output transduction (eg. ‘half-squaring’) at each stage may account for the blur constancy.

Handwritten and machine-printed text discrimination using a template matching approach

We propose a novel template matching approach for the discrimination of handwritten and machine-printed text. We first pre-process the scanned document images by performing denoising, circles/lines exclusion and word-block level segmentation. We then align and match characters in a flexible sized gallery with the segmented regions, using parallelised normalised cross-correlation. The experimental results over the Pattern Recognition & Image Analysis Research Lab-Natural History Museum (PRImA-NHM) dataset show remarkably high robustness of the algorithm in classifying cluttered, occluded and noisy samples, in addition to those with significant high missing data. The algorithm, which gives 84.0% classification rate with false positive rate 0.16 over the dataset, does not require training samples and generates compelling results as opposed to the training-based approaches, which have used the same benchmark.

Weighted Sum of Correlated Lognormals: Convolution Integral Solution

Probability density function (pdf) for sum of n correlated lognormal variables is deducted as a special convolution integral. Pdf for weighted sums (where weights can be any real numbers) is also presented. The result for four dimensions was checked by Monte Carlo simulation.

Az ellenzék ereje - általánosított súlyozott szavazási játékok (Minority power - generalized weighted voting games)

A hagyományos szavazási játékok speciális átruházható hasznosságú, kooperatív játékok, úgynevezett egyszerű játékok, ahol a játékosok a pártok, és az egyes koalíciók értéke 1 vagy 0 attól függően, hogy az adott koalíció elég erős-e az adott jogszabály elfogadásához, vagy sem. Ebben a cikkben bevezetjük az általánosított súlyozott szavazási játékok fogalmát, ahol a pártok mandátumainak száma a valószínűségi változó. Magyar példákon keresztül mutatjuk be az új megközelítés használhatóságát. / === / Voting games are cooperative games with transferable utility, so-called simple games, where the players are parties and the value of a coalition may be 0 or 1 depending on its ability to pass a new law. The authors introduce the concept of generalized weighted voting games where the parties' strengths are random variables. taking examples from Hungary to illustrate the use of this approach.

Matching human resource and corporate strategies

Increasing use of the term, Strategic Human Resource Management (SHRM), reflects the recognition of the interdependencies between corporate strategy, organization and human resource management in the functioning of the firm. Dyer and Holder (1988) proposed a comprehensive Human Resource Strategic Typology consisting of three strategic types--inducement, investment and involvement. This research attempted to empirically validate their typology and also test the performance implications of the match between corporate strategy and HR strategy. Hypotheses were tested to determine the relationships between internal consistency in HRM sub-systems, match between corporate strategy and HR strategy, and firm performance. Data were collected by a mail survey of 998 senior HR executives of whom 263 returned the completed questionnaire. Financial information on 909 firms was collected from secondary sources like 10-K reports and CD-Disclosure. Profitability ratios were indexed to industry averages. Confirmatory Factor Analysis using LISREL provided support in favor of the six-factor HR measurement model; the six factors were staffing, training, compensation, appraisal, job design and corporate involvement. Support was also found for the presence of a second-order factor labeled "HR Strategic Orientation" explaining the variations among the six factors. LISREL analysis also supported the congruence hypothesis that HR Strategic Orientation significantly affects firm performance. There was a significant associative relationship between HR Strategy and Corporate Strategy. However, the contingency effects of the match between HR and Corporate strategies were not supported. Several tests were conducted to show that the survey results are not affected by non-response bias nor by mono-method bias. Implications of these findings for both researchers and practitioners are discussed. ^

Estimation of average annual daily traffic (AADT) using geographically weighted regression (GWR) method and geographic information system (GIS)

Annual average daily traffic (AADT) is important information for many transportation planning, design, operation, and maintenance activities, as well as for the allocation of highway funds. Many studies have attempted AADT estimation using factor approach, regression analysis, time series, and artificial neural networks. However, these methods are unable to account for spatially variable influence of independent variables on the dependent variable even though it is well known that to many transportation problems, including AADT estimation, spatial context is important. ^ In this study, applications of geographically weighted regression (GWR) methods to estimating AADT were investigated. The GWR based methods considered the influence of correlations among the variables over space and the spatially non-stationarity of the variables. A GWR model allows different relationships between the dependent and independent variables to exist at different points in space. In other words, model parameters vary from location to location and the locally linear regression parameters at a point are affected more by observations near that point than observations further away. ^ The study area was Broward County, Florida. Broward County lies on the Atlantic coast between Palm Beach and Miami-Dade counties. In this study, a total of 67 variables were considered as potential AADT predictors, and six variables (lanes, speed, regional accessibility, direct access, density of roadway length, and density of seasonal household) were selected to develop the models. ^ To investigate the predictive powers of various AADT predictors over the space, the statistics including local r-square, local parameter estimates, and local errors were examined and mapped. The local variations in relationships among parameters were investigated, measured, and mapped to assess the usefulness of GWR methods. ^ The results indicated that the GWR models were able to better explain the variation in the data and to predict AADT with smaller errors than the ordinary linear regression models for the same dataset. Additionally, GWR was able to model the spatial non-stationarity in the data, i.e., the spatially varying relationship between AADT and predictors, which cannot be modeled in ordinary linear regression. ^

Enhanced skip -list search algorithm in 3-layer mediator framework

The Three-Layer distributed mediation architecture, designed by Secure System Architecture laboratory, employed a layered framework of presence, integration, and homogenization mediators. The architecture does not have any central component that may affect the system reliability. A distributed search technique was adapted in the system to increase its reliability. An Enhanced Chord-like algorithm (E-Chord) was designed and deployed in the integration layer. The E-Chord is a skip-list algorithm based on Distributed Hash Table (DHT) which is a distributed but structured architecture. DHT is distributed in the sense that no central unit is required to maintain indexes, and it is structured in the sense that indexes are distributed over the nodes in a systematic manner. Each node maintains three kind of routing information: a frequency list, a successor/predecessor list, and a finger table. None of the nodes in the system maintains all indexes, and each node knows about some other nodes in the system. These nodes, also called composer mediators, were connected in a P2P fashion. ^ A special composer mediator called a global mediator initiates the keyword-based matching decomposition of the request using the E-Chord. It generates an Integrated Data Structure Graph (IDSG) on the fly, creates association and dependency relations between nodes in the IDSG, and then generates a Global IDSG (GIDSG). The GIDSG graph is a plan which guides the global mediator how to integrate data. It is also used to stream data from the mediators in the homogenization layer which connected to the data sources. The connectors start sending the data to the global mediator just after the global mediator creates the GIDSG and just before the global mediator sends the answer to the presence mediator. Using the E-Chord and GIDSG made the mediation system more scalable than using a central global schema repository since all the composers in the integration layer are capable of handling and routing requests. Also, when a composer fails, it would only minimally affect the entire mediation system. ^

Notes on sufficient conditions for a graph to be Hamiltonian

The first part of this paper deals with an extension of Dirac's Theorem to directed graphs. It is related to a result often referred to as the Ghouila-Houri Theorem. Here we show that the requirement of being strongly connected in the hypothesis of the Ghouila-Houri Theorem is redundant. The Second part of the paper shows that a condition on the number of edges for a graph to be hamiltonian implies Ore's condition on the degrees of the vertices.

Network construction and graph theoretical analysis of functional language networks in pediatric epilepsy

This dissertation introduces a new approach for assessing the effects of pediatric epilepsy on the language connectome. Two novel data-driven network construction approaches are presented. These methods rely on connecting different brain regions using either extent or intensity of language related activations as identified by independent component analysis of fMRI data. An auditory description decision task (ADDT) paradigm was used to activate the language network for 29 patients and 30 controls recruited from three major pediatric hospitals. Empirical evaluations illustrated that pediatric epilepsy can cause, or is associated with, a network efficiency reduction. Patients showed a propensity to inefficiently employ the whole brain network to perform the ADDT language task; on the contrary, controls seemed to efficiently use smaller segregated network components to achieve the same task. To explain the causes of the decreased efficiency, graph theoretical analysis was carried out. The analysis revealed no substantial global network feature differences between the patient and control groups. It also showed that for both subject groups the language network exhibited small-world characteristics; however, the patient's extent of activation network showed a tendency towards more random networks. It was also shown that the intensity of activation network displayed ipsilateral hub reorganization on the local level. The left hemispheric hubs displayed greater centrality values for patients, whereas the right hemispheric hubs displayed greater centrality values for controls. This hub hemispheric disparity was not correlated with a right atypical language laterality found in six patients. Finally it was shown that a multi-level unsupervised clustering scheme based on self-organizing maps, a type of artificial neural network, and k-means was able to fairly and blindly separate the subjects into their respective patient or control groups. The clustering was initiated using the local nodal centrality measurements only. Compared to the extent of activation network, the intensity of activation network clustering demonstrated better precision. This outcome supports the assertion that the local centrality differences presented by the intensity of activation network can be associated with focal epilepsy.^

Next generation of recommender systems: Algorithms and applications

Personalized recommender systems aim to assist users in retrieving and accessing interesting items by automatically acquiring user preferences from the historical data and matching items with the preferences. In the last decade, recommendation services have gained great attention due to the problem of information overload. However, despite recent advances of personalization techniques, several critical issues in modern recommender systems have not been well studied. These issues include: (1) understanding the accessing patterns of users (i.e., how to effectively model users' accessing behaviors); (2) understanding the relations between users and other objects (i.e., how to comprehensively assess the complex correlations between users and entities in recommender systems); and (3) understanding the interest change of users (i.e., how to adaptively capture users' preference drift over time). To meet the needs of users in modern recommender systems, it is imperative to provide solutions to address the aforementioned issues and apply the solutions to real-world applications. ^ The major goal of this dissertation is to provide integrated recommendation approaches to tackle the challenges of the current generation of recommender systems. In particular, three user-oriented aspects of recommendation techniques were studied, including understanding accessing patterns, understanding complex relations and understanding temporal dynamics. To this end, we made three research contributions. First, we presented various personalized user profiling algorithms to capture click behaviors of users from both coarse- and fine-grained granularities; second, we proposed graph-based recommendation models to describe the complex correlations in a recommender system; third, we studied temporal recommendation approaches in order to capture the preference changes of users, by considering both long-term and short-term user profiles. In addition, a versatile recommendation framework was proposed, in which the proposed recommendation techniques were seamlessly integrated. Different evaluation criteria were implemented in this framework for evaluating recommendation techniques in real-world recommendation applications. ^ In summary, the frequent changes of user interests and item repository lead to a series of user-centric challenges that are not well addressed in the current generation of recommender systems. My work proposed reasonable solutions to these challenges and provided insights on how to address these challenges using a simple yet effective recommendation framework.^