Three-dimensional reconstruction of fracture surfaces: Area matching algorithms for automatic parallax measurements

This paper describes two solutions for systematic measurement of surface elevation that can be used for both profile and surface reconstructions for quantitative fractography case studies. The first one is developed under Khoros graphical interface environment. It consists of an adaption of the almost classical area matching algorithm, that is based on cross-correlation operations, to the well-known method of parallax measurements from stereo pairs. A normalization function was created to avoid false cross-correlation peaks, driving to the true window best matching solution at each region analyzed on both stereo projections. Some limitations to the use of scanning electron microscopy and the types of surface patterns are also discussed. The second algorithm is based on a spatial correlation function. This solution is implemented under the NIH Image macro programming, combining a good representation for low contrast regions and many improvements on overall user interface and performance. Its advantages and limitations are also presented.

Cebus cf. apella exhibits rapid acquisition of complex stimulus relations and emergent performance by exclusion

A "second generation" matching-to-sample procedure that minimizes past sources of artifacts involves (1) successive discrimination between sample stimuli, (2) stimulus displays ranging from four to 16 comparisons, (3) variable stimulus locations to avoid unwanted stimulus-location control, and (4) high accuracy levels (e.g., 90% correct on a 16-choice task in which chance accuracy is 6%). Examples of behavioral engineering with experienced capuchin monkeys included four-choice matching problems with video images of monkeys with substantially above-chance matching in a single session and 90% matching within six sessions. Exclusion performance was demonstrated by interspersing non-identical sample-comparison pairs within a baseline of a nine-comparison identity-matching-to-sample procedure with pictures as stimuli. The test for exclusion presented the newly "mapped" stimulus in a situation in which exclusion was not possible. Degradation of matching between physically non-identical forms occurred while baseline identity accuracy was sustained at high levels, thus confirming that Cebus cf. apella is capable of exclusion. Additionally, exclusion performance when baseline matching relations involved non-identical stimuli was shown.

An Empirical Study of Non-Rigid Surface Feature Matching of Human from 3D Video

This paper presents an empirical study of affine invariant feature detectors to perform matching on video sequences of people with non-rigid surface deformation. Recent advances in feature detection and wide baseline matching have focused on static scenes. Video frames of human movement capture highly non-rigid deformation such as loose hair, cloth creases, skin stretching and free flowing clothing. This study evaluates the performance of six widely used feature detectors for sparse temporal correspondence on single view and multiple view video sequences. Quantitative evaluation is performed of both the number of features detected and their temporal matching against and without ground truth correspondence. Recall-accuracy analysis of feature matching is reported for temporal correspondence on single view and multiple view sequences of people with variation in clothing and movement. This analysis identifies that existing feature detection and matching algorithms are unreliable for fast movement with common clothing.

The population health performance of medical students at two medical schools

Public Health and medicine are complimentary disciplines dedicated to the health and well-being of humankind. Worldwide, medical school accreditation bodies require the inclusion of population health in medical education. In 2003, the Institutes of Medicine (IOM) recommended that all medical students receive basic public health training in population-based prevention. The purpose of this study was to (1) examine the public health clinical performance of third-year medical students at two independent medical schools, (2) compare the public health clinical practice performance of the schools, and (3) identify underlying predictors of high and low public health clinical performance at one of the medical schools. ^ This study is unique in its analysis and report of observed medical student public health clinical practices. The cohort consisted of 751 third-year medical students who completed a required clinical performance exam using trained standardized patients. Medical student performance scores on 24 consensus public health items derived from nine patient cases were analyzed.^ The analysis showed nearly identical results for both medical schools at the 60%, 65%, and 70% pass rate. Students performed poorly on items associated with prevention, behavioral science, and surveillance. Factors associated with high student performance included being from an underrepresented minority, matching to a primary care residency, and high class ranking. A review of medical school curriculum at both schools revealed a lack of training in four public health domains. Nationally, 32% of medical students reported inadequate training in public health in the year 2006.^ These findings suggest more dedicated teaching time for public health domains is needed at the medical schools represented in this study. Finally, more research is needed to assess attainment of public health knowledge and skills for medical students nationwide if we are to meet the recommendations of the IOM. ^

Corporate decision-making: A case study of decision support systems and financial performance in health care organizations

The purpose of this study was twofold: (1) To describe the relation of the intensity of DSS implementation to financial performance as an empirical exploration of improved performance at the organizational level. (2) To describe the relation of the intensity of DSS implementation to the type of organizational decision culture. A multiple case study design was utilized to compare three groups of paired cases. A pattern matching strategy was applied in this study. Four predictions were specified and compared to the empirical data. A progressively upward trend in the scores was predicted for the following theoretical relationships. (1) The greater the number of DSSs, the higher the sophistication index. (2) The greater the number of DSSs, the higher the financial ratios. (3) The greater the number of DSSs, the higher the culture score. (4) The higher the culture score, the higher the financial ratios. The data did not support any of the predicted trends except the relation between the number of DSSs and the financial ratios. The Income/Revenue ratio indicates the efficiency of a company's operations. One would expect that this ratio would be most affected by the operational and financial decision support systems. The majority of the systems measured in the study supported decisions tangential to the patient service areas. The evidence suggested that the type and number of decision support systems affects the bottom line. ^

AROUSAL, FATIGUE AND MENTAL PERFORMANCE: THE EFFECTS OF FASTING ON COGNITION

This study examined the effects of skipping breakfast on selected aspects of children's cognition, specifically their memory (both immediate and one week following presentation of stimuli), mental tempo, and problem solving accuracy. Test instruments used included the Hagen Central/Incidental Recall Test, Matching Familiar Figures Test, McCarthy Digit Span and Tapping Tests. The study population consisted of 39 nine-to eleven year old healthy children who were admitted for overnight stays at a clinical research setting for two nights approximately one week apart. The study was designed to be able to adequately monitor and control subjects' food consumption. The design chosen was the cross-over design where randomly on either the first or second visit, the child skipped breakfast. In this way, subjects acted as their own controls. Subjects were tested at noon of both visits, this representing an 18-hour fast.^ Analysis focused on whether or not fasting for this period of time affected an individual's performance. Results indicated that for most of the tests, subjects were not significantly affected by skipping breakfast for one morning. However, on tests of short-term central and incidental recall, subjects who had skipped breakfast recalled significantly more of the incidental cues although they did so at no apparent expense to their storing of central information. In the area of problem-solving accuracy, subjects skipping breakfast at time two made significantly more errors on hard sections of the MFF Test. It should be noted that although a large number of tests were conducted, these two tests showed the only significant differences.^ These significant results in the areas of short-term incidental memory and in problem solving accuracy were interpreted as being an effect of subject fatigue. That is, when subjects missed breakfast, they were more likely to become fatigued and in the novel environment presented in the study setting, it is probable that these subjects responded by entering Class II fatigue which is characterized by behavioral excitability, diffused attention and altered performance patterns. ^

A two-dimensional analysis of the impact of outward FDI on performance at home: evidence from Japanese manufacturing firms

This paper empirically investigates two areas of changes in firm behavior and performance at home before and after investing abroad. The first change is dependent upon the type of foreign direct investment (FDI): horizontal FDI or vertical FDI. The second change is dependent upon the firm’s domestic activities: production activities or non-production activities. From a theoretical standpoint, the impact of outward FDIs differs not only by type, but according to the firm’s activities. By exploiting two types of firm-level data that enable us to distinguish between production and non-production activities, our paper provides a detailed picture of the intra-firm changes in behavior and performance that occur as a result of production globalization.

Impacts of FTA utilization on firm performance

The international export and investment activities of firms have been widely studied by scholars. In particular, prior studies have focused on two main hypotheses about firms engaged in international activities such as exporting and investing abroad; namely, self-selection of more productive firms into international activities and learning-by-doing international activities. This paper is the first study that explores these hypotheses in regard to firms’ use of free trade agreements (FTAs). We first estimate the propensity score for firms’ use of FTA schemes, and find that larger firms are more likely to participate. Then, by conducting matching analysis using the propensity scores, we find that the use of FTA schemes does not change employment in firms, but does result in more local inputs used and increased exports.

MultiFarm: A benchmark for multilingual ontology matching

In this paper we present the MultiFarm dataset, which has been designed as a benchmark for multilingual ontology matching. The MultiFarm dataset is composed of a set of ontologies translated in different languages and the corresponding alignments between these ontologies. It is based on the OntoFarm dataset, which has been used successfully for several years in the Ontology Alignment Evaluation Initiative (OAEI). By translating the ontologies of the OntoFarm dataset into eight different languages – Chinese, Czech, Dutch, French, German, Portuguese, Russian, and Spanish – we created a comprehensive set of realistic test cases. Based on these test cases, it is possible to evaluate and compare the performance of matching approaches with a special focus on multilingualism.

Multiple Hashing Integration for Real-Time Large Scale Part-to-Part Video Matching

A real-time large scale part-to-part video matching algorithm, based on the cross correlation of the intensity of motion curves, is proposed with a view to originality recognition, video database cleansing, copyright enforcement, video tagging or video result re-ranking. Moreover, it is suggested how the most representative hashes and distance functions - strada, discrete cosine transformation, Marr-Hildreth and radial - should be integrated in order for the matching algorithm to be invariant against blur, compression and rotation distortions: (R; _) 2 [1; 20]_[1; 8], from 512_512 to 32_32pixels2 and from 10 to 180_. The DCT hash is invariant against blur and compression up to 64x64 pixels2. Nevertheless, although its performance against rotation is the best, with a success up to 70%, it should be combined with the Marr-Hildreth distance function. With the latter, the image selected by the DCT hash should be at a distance lower than 1.15 times the Marr-Hildreth minimum distance.

Explicit context matching in content-based publish/subscribe systems

Although context could be exploited to improve performance, elasticity and adaptation in most distributed systems that adopt the publish/subscribe (P/S) communication model, only a few researchers have focused on the area of context-aware matching in P/S systems and have explored its implications in domains with highly dynamic context like wireless sensor networks (WSNs) and IoT-enabled applications. Most adopted P/S models are context agnostic or do not differentiate context from the other application data. In this article, we present a novel context-aware P/S model. SilboPS manages context explicitly, focusing on the minimization of network overhead in domains with recurrent context changes related, for example, to mobile ad hoc networks (MANETs). Our approach represents a solution that helps to efficiently share and use sensor data coming from ubiquitous WSNs across a plethora of applications intent on using these data to build context awareness. Specifically, we empirically demonstrate that decoupling a subscription from the changing context in which it is produced and leveraging contextual scoping in the filtering process notably reduces (un)subscription cost per node, while improving the global performance/throughput of the network of brokers without fltering the cost of SIENA-like topology changes.

Sources of selection bias in evaluating social programs: An interpretation of conventional measures and evidence on the effectiveness of matching as a program evaluation method

This paper decomposes the conventional measure of selection bias in observational studies into three components. The first two components are due to differences in the distributions of characteristics between participant and nonparticipant (comparison) group members: the first arises from differences in the supports, and the second from differences in densities over the region of common support. The third component arises from selection bias precisely defined. Using data from a recent social experiment, we find that the component due to selection bias, precisely defined, is smaller than the first two components. However, selection bias still represents a substantial fraction of the experimental impact estimate. The empirical performance of matching methods of program evaluation is also examined. We find that matching based on the propensity score eliminates some but not all of the measured selection bias, with the remaining bias still a substantial fraction of the estimated impact. We find that the support of the distribution of propensity scores for the comparison group is typically only a small portion of the support for the participant group. For values outside the common support, it is impossible to reliably estimate the effect of program participation using matching methods. If the impact of participation depends on the propensity score, as we find in our data, the failure of the common support condition severely limits matching compared with random assignment as an evaluation estimator.

A Performance Evaluation of Surface Normals-Based Descriptors for Recognition of Objects using CAD-Models

This paper describes a study and analysis of surface normal-base descriptors for 3D object recognition. Specifically, we evaluate the behaviour of descriptors in the recognition process using virtual models of objects created from CAD software. Later, we test them in real scenes using synthetic objects created with a 3D printer from the virtual models. In both cases, the same virtual models are used on the matching process to find similarity. The difference between both experiments is in the type of views used in the tests. Our analysis evaluates three subjects: the effectiveness of 3D descriptors depending on the viewpoint of camera, the geometry complexity of the model and the runtime used to do the recognition process and the success rate to recognize a view of object among the models saved in the database.

Matching research and innovation policies in EU countries. Bruegel Working Paper 2015/16, December 2015

The European Union has prioritised the pursuit of innovation based growth and targeting of resources to promote research and development, but performance on innovation remains weak.With the lack of results comes fatigue, waning interest and mounting criticism about policy. Should the EU abandon its ambition to become the most innovative region in the world?We examine EU member state research and innovation policies. We assess whether the deployment of innovation policy instruments in EU countries matches their innovation capacity performance relative to other EU countries.We find a relative homogeneity of policy mixes in EU countries, despite the fairly wide and stable differences in their innovation capacities.Our analysis therefore provides a rationale for a more comprehensive review of innovation policy mixes to assess their adequacy in addressing country specific innovation challenges.

Applying machine learning to catalogue matching in astrophysics

We present the results of applying automated machine learning techniques to the problem of matching different object catalogues in astrophysics. In this study, we take two partially matched catalogues where one of the two catalogues has a large positional uncertainty. The two catalogues we used here were taken from the H I Parkes All Sky Survey (HIPASS) and SuperCOSMOS optical survey. Previous work had matched 44 per cent (1887 objects) of HIPASS to the SuperCOSMOS catalogue. A supervised learning algorithm was then applied to construct a model of the matched portion of our catalogue. Validation of the model shows that we achieved a good classification performance (99.12 per cent correct). Applying this model to the unmatched portion of the catalogue found 1209 new matches. This increases the catalogue size from 1887 matched objects to 3096. The combination of these procedures yields a catalogue that is 72 per cent matched.