Interest Points as a Focus Measure in Multi-Spectral Imaging

A novel multi-spectral focus measure that is based on algorithms for interest point detection, particularly on the FAST (Features from Accelerated Segment Test), Fast Hessian and Harris-Laplace detector, is described in this paper. The proposed measure methods are compared with commonly used focus measure techniques like energy of image gradient, sum-modified Laplacian, Tenenbaum's algorithm or spatial frequency when testing their reliability and performance. The measures have been tested on a newly created database containing 420 images acquired in visible, near-infrared and thermal spectrum (7 objects in each spectrum). Algorithms based on the interest point detectors proved to be good focus measures satisfying all the requirements described in the paper, especially in thermal spectrum. It is shown that these algorithms outperformed all commonly used methods in thermal spectrum and therefore can serve as a new and more accurate focus measure

Psychometric evaluation of the Disabilities of the Arm, Shoulder and Hand (DASH) with Dupuytren's contracture: validity evidence using Rasch modeling

Background Dupuytren’s contracture is a progressive, fibroproliferative disorder that causes fixed finger contractures and can lead to disability. With the advances of new therapeutic interventions, the necessity to assess the functional repercussions of this condition using valid, reliable and sensitive outcome measures is of growing interest. The Disabilities of the Arm, Shoulder and Hand (DASH) is one frequently used patient-reported outcome measure but its reliability and validity have never been demonstrated specifically for a population affected with Dupuytren’s contracture. The objective of this study was to evaluate the psychometric properties of the DASH, with focus on validity evidence using the Rasch measurement model. Methods Secondary analysis was performed on data collected as part of a randomised clinical trial. One hundred fifty-three participants diagnosed with Dupuytren’s contracture completed the DASH at four time points (pre-op, 3, 6 and 12 months post-op). Baseline data were analysed using traditional analysis and to test whether they adhered to the expectations of the Rasch model. Post-intervention data were subsequently included and analyzed to determine the effect of the intervention on the items. Results DASH scores demonstrated large ceiling effects at all time points. Initial fit to the Rasch model revealed that the DASH did not adhere to the expectations of the Rasch partial credit model (χ2 = 119.92; p < 0.05). Multiple items displayed inadequate response categories and two items displayed differential item functioning by gender. Items were transformed and one item deleted leading to an adequate fit. Remaining items fit the Rasch model but still do not target well the population under study. Conclusions The original version of the 30-item DASH did not display adequate validity evidence for use in a population with Dupuytren’s contracture. Further development is required to improve the DASH for this population

New urban settlements in a perspective of public and private interests

Changes of land use pattern and urban form could be seen as a dynamic result of the trade off by public and private interests. Private interest – individual residents or firms – tries, according to micro economic theory, to maximize their individual utility. Public interests – conveyed by government institutions on different geographical levels - on the other hand, try according to macro economic theories to maximize the general welfare in a community according to the preferences of the political system. The focus is to measure the importance of spatial locations factors regarding new residential and commercial buildings in relation to the existing urban form, political guidelines and ecological features. In the region transportation infrastructure systems, as high speed commuting train and highways, have been implemented in the middle of the period. The time period investigated is 1992-2000. The importances of the location factors were obtained by logistic regression analysis and transformation of the ß -values into elasticities. The dependent variables were settlements of new urban elements in pixels of 50*50 meters. Independent variables where distances to existing urban elements, presence of public interests and some ecological features as south faced hill slopes, distance to water areas and geology. Results from this projects reveals that new urban settlements in general are located in proximity to existing urban settlements of the same kind, in remotness to existing urban focal points and to some extend within planned areas. National/regional transportation nodes do not have any apparent influence on the location. A general conclusion from this investigation is that the built environment develops towards a further dispersed rural spatial pattern though with some correspondence to the comprehensive land use plan.

Interactive Time-Series of Measures for Exploring Dynamic Networks

International audienceWe present MeasureFlow, an interface to visually and interactively explore dynamic networks through time-series of network measures such as link number, graph density, or node activation. When networks contain many time steps, become large and more dense, or contain high frequencies of change, traditional visualizations that focus on network topology, such as animations or small multiples , fail to provide adequate overviews and thus fail to guide the analyst towards interesting time points and periods. Measure-Flow presents a complementary approach that relies on visualizing time-series of common network measures to provide a detailed yet comprehensive overview of when changes are happening and which network measures they involve. As dynamic networks undergo changes of varying rates and characteristics, network measures provide important hints on the pace and nature of their evolution and can guide an analysts in their exploration; based on a set of interactive and signal-processing methods, MeasureFlow allows an analyst to select and navigate periods of interest in the network. We demonstrate MeasureFlow through case studies with real-world data

Is housing overvalued?

This paper examines whether it is more expensive to own a house or to rent. The paper assesses houses as ‘overvalued’ if home buyers pay too much, in the sense that they would be better off renting than buying. This involves comparing the financial cost of renting a home with the cost of owning a similar dwelling, where the latter depends on the purchase price, interest rates, repairs, council rates and so on. The paper also briefly examines non-financial costs but find these are small, on average. This paper finds if real house prices grow at their historical average pace, then owning a home is about as expensive as renting. If prices grow more slowly, as some forecasters predict, the framework used in this paper suggests that the average home buyer would be financially better off renting. House prices are decomposed into contributions from rents, interest rates and expected capital gains, which may help policymakers in the detection of housing bubbles. Recent data do not show signs of a bubble

Continuous Average Straightness in Spatial Graphs

The Straightness is a measure designed to characterize a pair of vertices in a spatial graph. It is defined as the ratio of the Euclidean distance to the graph distance between these vertices. It is often used as an average, for instance to describe the accessibility of a single vertex relatively to all the other vertices in the graph, or even to summarize the graph as a whole. In some cases, one needs to process the Straightness between not only vertices, but also any other points constituting the graph of interest. Suppose for instance that our graph represents a road network and we do not want to limit ourselves to crossroad-to-crossroad itineraries, but allow any street number to be a starting point or destination. In this situation, the standard approach consists in: 1) discretizing the graph edges, 2) processing the vertex-to-vertex Straightness considering the additional vertices resulting from this discretization, and 3) performing the appropriate average on the obtained values. However, this discrete approximation can be computationally expensive on large graphs, and its precision has not been clearly assessed. In this article, we adopt a continuous approach to average the Straightness over the edges of spatial graphs. This allows us to derive 5 distinct measures able to characterize precisely the accessibility of the whole graph, as well as individual vertices and edges. Our method is generic and could be applied to other measures designed for spatial graphs. We perform an experimental evaluation of our continuous average Straightness measures, and show how they behave differently from the traditional vertex-to-vertex ones. Moreover, we also study their discrete approximations, and show that our approach is globally less demanding in terms of both processing time and memory usage. Our R source code is publicly available under an open source license

Votes and Vetoes: The Political Determinants of Commercial Openness

Societal theories of trade policy stress the importance of domestic interest groups, whereas statist theories focus on the effects of domestic institutions. Debates over the relative merits of these approaches have been fierce, but little systematic empirical research has been brought to bear on the relative merits of these theories. In this paper, we argue that, while societal and statist factors are generally regarded as having independent and competing effects, it is more fruitful to view the influence of each type of factor as conditional on the other. As societal explanations contend, deteriorating macroeconomic conditions are a potent source of protectionist pressures. The extent to which such conditions reduce commercial openness, however, depends centrally on the domestic institutions through which societal pressures must filter to influence policy. Two institutional features stand out. First, in states marked by greater fragmentation and more “veto points,” it is harder to change existing policies because any number of actors can block such change. Consequently, we expect the effects of macroeconomic conditions on trade policy to be weaker in fragmented states than in those characterized by a highly centralized national government. Second, we expect both fragmentation and the societal pressures stemming from the economy to have a more potent impact on trade policy in democracies than in other regimes, since the electoral constraints facing democratic leaders force them to respond to demands made by key segments of society. The results of our statistical tests covering more than one hundred countries during the period from 1980 to 2000 strongly support these arguments.http://deepblue.lib.umich.edu/bitstream/2027.42/40098/3/wp712.pd

Mathematics Course Placement Using Holistic Measures: Possibilities for Community College Students.

Background/Context: Most community colleges across the country use a placement test to determine students’ readiness for college-level coursework, yet these tests are admittedly imperfect instruments. Researchers have documented significant problems stemming from overreliance on placement testing, including placement error and misdiagnosis of remediation needs. They have also described significant consequences of misplacement, which can hinder the educational progression and attainment of community college students. Purpose/Objective/Research Question/Focus of Study: We explore possibilities for placing community college students in mathematics courses using a holistic approach that considers measures beyond placement test scores. This includes academic background measures, such as high school GPA and math courses taken, and indicators of noncognitive constructs, such as motivation, time use, and social support. Setting: The study draws upon administrative data from a large urban community college district in California that serves over 100,000 students each semester. The data enable us to link students’ placement testing results, survey data, background information, and transcript records. Research Design: We first use the supplemental survey data gathered during routine placement testing to conduct predictive exercises that identify severe placement errors under existing placement practices. We then move beyond prediction and evaluate student outcomes in two colleges where noncognitive indicators were directly factored into placement algorithms. Findings/Results: Using high school background information and noncognitive indicators to predict success reveals as many as one quarter of students may be misassigned to their math courses by status quo practices. In our subsequent analysis we find that students placed under a holistic approach that considered noncognitive indicators in addition to placement test scores performed no differently from higher scoring peers in the same course. Conclusions/Recommendations: The findings suggest a holistic approach to mathematics course placement may improve placement accuracy and provide access to higher level mathematics courses for community college students without compromising their likelihood of success