Miracle-dz/UniFAR-FTUs huggingface dataset:
Efficient mean-shift tracking via a new similarity measure

The mean shift algorithm has achieved considerable success in object tracking due to its simplicity and robustness. It finds local minima of a similarity measure between the color histograms or kernel density estimates of the model and target image. The most typically used similarity measures are the Bhattacharyya coefficient or the Kullback-Leibler divergence. In practice, these approaches face three difficulties. First, the spatial information of the target is lost when the color histogram is employed, which precludes the application of more elaborate motion models. Second, the classical similarity measures are not very discriminative. Third, the sample-based classical similarity measures require a calculation that is quadratic in the number of samples, making real-time performance difficult. To deal with these difficulties we propose a new, simple-to-compute and more discriminative similarity measure in spatial-feature spaces. The new similarity measure allows the mean shift algorithm to track more general motion models in an integrated way. To reduce the complexity of the computation to linear order we employ the recently proposed improved fast Gauss transform. This leads to a very efficient and robust nonparametric spatial-feature tracking algorithm. The algorithm is tested on several image sequences and shown to achieve robust and reliable frame-rate tracking.
On Individual Cursedness - How personality shapes individuals' sensitivity to incur a winner's curse -

The winner's curse is a well-known deviation from rational self-interest in decision-making under asymmetric information. Yet, most prominent explanations for the curse have experimentally been ruled out so far. In particular, the curse did neither seem to emanate from a lack of experience with a given task (Grosskopf et al. 2007), nor from the complexity of the decision task, nor level-k thinking, nor a disability to infer information from others' actions (Charness and Levin 2009), (Ivanov et al. 2010). This paper elicits individuals' sensitivity to incur a winner's curse in a common-value auction where the explanations above do not apply, tracks down the potential source of the curse, and tests to what extent individuals' cursedness evolves (Fudenberg 2006). It finds that the curse is tightly associated with a relatively stable individual characteristic - individuals' personality traits. Personality traits explain individuals' initial cursedness, and also govern whether individuals unlearn, or instead, acquire the curse. I review biological evidence on how personality influences individuals' handling of information to explain why personality matters here.
The Kernel of Maximum Agreement Subtrees

A Maximum Agreement SubTree (MAST) is a largest subtree common to a set of trees and serves as a summary of common substructure in the trees. A single MAST can be misleading, however, since there can be an exponential number of MASTs, and two MASTs for the same tree set do not even necessarily share any leaves. In this paper, we introduce the notion of the Kernel Agreement SubTree (KAST), which is the summary of the common substructure in all MASTs, and show that it can be calculated in polynomial time (for trees with bounded degree). Suppose the input trees represent competing hypotheses for a particular phylogeny. We explore the utility of the KAST as a method to discern the common structure of confidence, and as a measure of how confident we are in a given tree set. We also show the trend of the KAST, as compared to other consensus methods, on the set of all trees visited during a Bayesian analysis of flatworm genomes.
Diffraction Amplitudes from Periodic Neumann Surface: Low Grazing Limit of Incidence (III)

This paper deals with the singular behavior of the diffraction of transverse magnetic (TM) waves by a perfectly conductive triangular periodic surface at a low grazing limit of incidence. The wave field above the highest excursion of the surface is represented as a sum of Floquet modes with modified diffraction amplitudes, whereas the wave field inside a triangular groove is written as a sum of guided modes with unknown mode amplitudes. Then, two sets of equations are derived for such amplitudes. From the equation sets, all the amplitudes are analytically shown to vanish at a low grazing limit of incidence. From this fact, it is concluded analytically that no diffraction takes place and only reflection occurs at a low grazing limit of incidence for any period length and any triangle height. This theoretical result is verified by a numerical example. key words: singular behavior, diffraction amplitude, modified diffraction amplitude, triangular grating
Visual Registration of Industrial Metallic Object from Local Contour Descriptors

This article introduces an innovative visual registration process suitable for textureless objects. Because our framework is industrial, the process is designed for metallic, complex free-form objects containing multiple bores. This technique is based on a new contour descriptor, invariant under affine transformation, which characterizes the neighborhood of a closed contour. The affine invariance is exploited in the learning stage to produce a lightweight model. Moreover, during the learning stage, this descriptor is combined to a 2D/3D pattern, concept likewise presented in this article. Once associated, the 2D/3D information wealth of this descriptor allows a pose estimation from a single match. This ability is exploited in the registration process to drastically reduce the complexity of the algorithm and increase efficiently its robustness to the difficult problem of repetitive patterns. Evaluations on a cylinder head, a car door and a binding beam confirm both the robustness and the precision of the process
Disease-Specific Risk Prediction through Stability Selection using Electronic Health Records

Disease-specific risk prediction aims at assessing the risk of a patient in developing a target disease based on his/her health profile. As electronic health records (EHRs) become more prevalent, a large number of features can be constructed in order to characterize patient profiles. This wealth of data provides unprecedented opportunities for data mining researchers to address important biomedical questions. Practical data mining challenges include: How to correctly select and rank those features based on their prediction power? What predictive model performs the best in predicting a target disease using those features? In this paper, we propose top-k stability selection, which generalizes a powerful sparse learning method for feature selection by overcoming its limitation on parameter selection. In particular, our proposed top-k stability selection includes the original stability selection method as a special case given k = 1. Moreover, we show that the top-k stability selection is more robust by utilizing more information from selection probabilities than the original stability selection, and provides stronger theoretical properties. In a large set of real clinical prediction datasets, the top-k stability selection methods outperform many existing feature selection methods including the original stability selection. We also compare three competitive classification methods (SVM, logistic regression and random forest) to demonstrate the effectiveness of selected features by our proposed method in the context of clinical prediction applications. Finally, through several clinical applications on predicting heart failure related symptoms, we show that top-k stability selection can successfully identify important features that are clinically meaningful.
Charging and Billing for Composite Services in a Multi-Service Provider Environment: The IMS Case

In a saturating telecommunications marketplace network operators want to rapidly deploy services with minimum capital investment, while maximizing on revenue from service usage by customers. One way to achieve this is to create interfaces for 3rd party service and content providers to offer their applications and services to users. Composing and bundling of these services will essentially create new services for the user and achieve rapid deployment of enhanced services. Effective accounting of service usage requires mechanisms for billing and charging of these services. Achieving this in an environment where the network operator interacts directly with the 3rd party providers may become complicated. This work defines a framework that would allow for the effective charging and billing of services composed from 3rd party service and content providers. We propose the use of a service composer who mediates between an IMS network operator and the many content providers to create new services that are composed from independent applications; the composer simplifies the technical and business aspects of service provision while ensuring that charging and billing occurs within the network.
Assessing Raman Spectroscopy as a Prescreening Tool for the Selection of Archaeological Bone for Stable Isotopic Analysis

Stable isotope analyses for paleodiet investigations require good preservation of bone protein, the collagen, to obtain reliable stable isotope values. Burial environments cause diagenetic alterations to collagen, especially in the leaching of the organic bone content. The survival of bone protein may be assessed by the weight % collagen, % carbon and % nitrogen yields, but these values are achieved only after destructive chemical processing. A non-destructive method of determining whether bone is suitably preserved would be desirable, as it would be less costly than chemical processing, and would also preserve skeletal collections. Raman analysis is one such potential non-destructive screening method. In previous applications, Raman spectroscopy has been used to test both the alteration of the mineral portion of bone, as well as to indicate the relative amount of organic material within the bone structure. However, there has been no research to test the relationship between the Raman spectroscopic results and the survival of bone protein. We use a set of 41 bone samples from the prehistoric archaeological site of Ban Non Wat, Northeast Thailand, to assess if Raman spectroscopy analysis of the organic-phosphate ratio has a significant correlation with the weight % collagen, and carbon and nitrogen yields obtained by isotopic analysis. The correlation coefficients are highly statistically significant in all cases (r = 0.716 for collagen, r = 0.630 for carbon and r = 0.706 for nitrogen, p≤0.001 for all) with approximately or close to half of the variation in each explained by variation in the organic-phosphate ratio (51.2% for collagen, 39.6% for carbon, and 49.8% for nitrogen). Although the Raman screening method cannot directly quantify the extent of collagen survival, it could be of use in the selection of bone most likely to have viable protein required for reliable results from stable isotope analysis.
Negotiating Identities, Negotiating Environments: an interpretation of the experiences of students with disabilities

This paper explores the experiences of nine students with disabilities pursuing degrees at a large Canadian university. An ethnographic approach was followed using face-to-face, unstructured interviews and a focus group to generate data. The analysis focuses on how these students negotiate disabled and non-disabled identities while negotiating the physical environment of the university campus. I argue that these negotiatory processes are necessarily interconnected and inherently contradictory.
View-based 3-D object recognition using shock graphs

The shock graph is an emerging shape representation for object recognition, in which a 2-D silhouette is decomposed into a set of qualitative parts, captured in a directed acyclic graph. Although a number of approaches have been proposed for shock graph matching, these approaches do not address the equally important indexing problem. We extend our previous work in both shock graph matching and hierarchical structure indexing to propose the first unified framework for view-based 3-D object recognition using shock graphs. The heart of the framework is an improved spectral characterization of shock graph structure that not only drives a powerful indexing mechanism (to retrieve similar candidates from a large database), but also drives a matching algorithm that can accommodate noise and occlusion. We describe the components of our system and evaluate its performance using both unoccluded and occluded queries. The large set of recognition trials (over 25,000) from a large database (over 1400 views) represents one of the most ambitious shock graph-based recognition experiments conducted to date.
The impact of eye movements on a verbal creativity task

Bilateral eye movements (EMs) have been shown to induce cognitive enhancements for episodic memory, attention, and divergent thinking. Increased interhemispheric interaction has been suggested as a possible mechanism behind the EM effect, but other theories, including an increase in attentional control following EMs have also been proposed. The present research explored whether the bilateral EM effect could be extended to a creativity task that draws heavily on convergent thinking. Participants were randomly assigned to one of four EM conditions (bilateral, centre control, right-centre, or left-centre) and were presented with compound remote associate problems. After 7 s, participants were asked to make a solution/non-solution judgement to a target word presented in the left or right visual field. Bilateral and right-centre EM conditions exhibited enhanced performance on the task, with the bilateral condition demonstrating the best performance for solution targets and the right-centre condition presenting the best performance for non-solution targets. The implications of these findings are discussed in light of the neural components of creativity and theories surrounding the effects of EMs on cognition.
Personality traits and parenting: neuroticism, extraversion, and openness to experience as discriminative factors

This study used variable‐ and person‐oriented approaches to examine the relationship between personality traits (at age 33) and parenting (at age 36) among 94 mothers and 78 fathers. The SEM revealed that Openness to Experience (O), low Neuroticism (N), and Extraversion (E) were related to parental nurturance; low O to parental restrictiveness; and low N to parental knowledge about the child's activities. Cluster analysis based on the three parenting factors yielded six gender‐related parenting types with distinguishable personality profiles. Authoritative parents (mostly mothers) and emotionally involved parents (mostly fathers), who were high in nurturance and high to moderate in parental knowledge, were high in E and high to moderate in O. Authoritarian parents (mostly fathers) and emotionally detached parents (mostly mothers), who were low in nurturance, high to moderate in restrictiveness, and moderate to low in parental knowledge, were low in O and E. Permissive parents, who were low in restrictiveness and parental knowledge and moderate in nurturance, were high in N, E, and O. Engaged parents, who were high in nurturance, restrictiveness, and parental knowledge, were moderate in all personality traits. Agreeableness and Conscientiousness did not differ between the parenting types. Copyright © 2002 John Wiley & Sons, Ltd.
`Getting Through the List': Judgecraft and Legitimacy in the Lower Courts

This article examines the judgecraft required when judicial officers actively manage the time pressures created by long and unpredictable case lists. It considers the implications of this time management for the legitimate exercise of judicial authority. In particular, we focus on the strategy of altering the temporal sequence of the list by standing matters down and recalling them later in the list. This strategy, especially when initiated by the judicial officer, is analysed in light of the temporal goals of getting through the list on the day and moving cases along towards final resolution, and the ideological and practical requirements of legitimate judicial authority within the adversary system. The article is based on a court observation study of the general criminal list, concentrating on the role of the presiding judicial officer — the magistrate — in the lower courts of Australia. The research demonstrates that magistrates exercise considerable judgecraft which achieves temporal goals and can create space for a more engaged and therefore more legitimate decision-making process; however, their capacity to do so is limited by the judicial role and the roles allocated to others by conventional adversarial norms and practices.
Testing an L2 Reading Strategy Programme

This paper discusses some of the difficulties associated with using standardised reading tests in assessing students' use of reading strategies for expository text in short-term intervention programmes. Alternative approaches can be used, including identifying omitted structural material, unscrambling texts, and identifying and correcting illogical texts. Such testing approaches help to illustrate transfer "across tasks with the same underlying structure but different surface formats" (from the original intervention study) (Brown, Armbruster, and Baker 1986:69).
Becker Meets Ricardo: Multisector Matching with Social and Cognitive Skills

This paper presents a tractable framework for studying frictionless matching in school, work, and marriage when individuals have heterogeneous social and cognitive skills. In the model, there are gains to specialization and team production, but specialization requires communication and coordination between team members, and individuals with more social skills communicate and coordinate at lower resource cost. The theory delivers full task specialization in the labor and education markets, but incomplete specialization in marriage. It also captures well-known matching patterns in each of these sectors, including the commonly observed many-to-one matches in firms and schools. Equilibrium is equivalent to the solution of an utilitarian social planner solving a linear programming problem.
The Validity of Kolb Learning Styles and Neo-Piagetian Developmental Levels in College Biology

The Kolb learning styles and neo-Piagetian development levels of 366 students enrolled in a non-majors college biology course were assessed. Students then completed a one-semester lecture/lab course within one of two instructional methods - inquiry or expository. The predicted interaction between Kolb's thinking/feeling learning dimension and instructional method was not found. Instead, as predicted by neo-Piagetian developmental theory, the thinking/feeling dimension and developmental level both correlated positively with course achievement under both instructional methods. Also as predicted by developmental theory, a significant correlation between the Kolb thinking/feeling learning dimension and developmental level was found. Thus, the value of attempting to match instructional method with Kolb's thinking and feeling learning styles, which may in fact reflect differences in developmental level, is questioned. On the other hand, the finding that developmental level did predict success within both instructional approaches supports neo-Piagetian theory and implies that instruction should be designed to improve reasoning abilities.
Feelybean: communicating touch over distance

Increasingly, due to work or study reasons, many couples find themselves living apart, in different cities or even countries, experiencing the challenges of a long distance relationship. Much research has been conducted into helping couples overcome the problems associated with long distance relationships (LDRs) and many steps have been made towards solving it through enabling them to keep in contact via video, audio, or visual artifacts. Our approach supplements these traditional communication mediums by exploiting ""touch" - a sensation that is dominant in almost every relationship. We designed, built and tested a prototype touch device, with the intention of bringing couples closer together during a regular Skype conversation, by allowing each to feel the other's touch. Our study showed that participants found touching each other in this way was intriguing, enabling them to feel the other person's hand touching theirs at a distance, and in doing so bridging the distance between them.
Factors Influencing the Pursuit of Health and Science Careers for Canadian Adolescents in Transition from School to Work

Previous research separately acknowledges two emerging trends in adolescence but neglects to integrate them. These are that many changes have occurred in the school to work transitional processes, and that there is substantial need for adolescents, especially young women, to pursue science career pathways. In this study, we link these trends and develop predictive, interactive models of science pursuit for 836 Canadian secondary school graduates living through a period of massive change in school to work transitional processes. Separate logit analyses were conducted for males and females. Results suggest that young women are not under-represented in the pursuit of science careers in high school. Young women aspire more frequently to medical and health sciences, and young men to natural sciences, engineering and mathematics. For young women, father's occupation in science, curriculum track and level of occupational expectation were significant in the model, correctly predicting 72% of membership in science. For males, socioeconomic status, family support, level of occupational expectation, regional unemployment levels and items measuring work environment were significant in the model that predicted 81% of membership in science. The findings suggest the salience of gender-differentiated school to work transition models in determining pursuit of health and science career pathways.
A compiler-level intermediate representation based binary analysis and rewriting system

This paper presents component techniques essential for converting executables to a high-level intermediate representation (IR) of an existing compiler. The compiler IR is then employed for three distinct applications: binary rewriting using the compiler's binary back-end, vulnerability detection using source-level symbolic execution, and source-code recovery using the compiler's C backend. Our techniques enable complex high-level transformations not possible in existing binary systems, address a major challenge of input-derived memory addresses in symbolic execution and are the first to enable recovery of a fully functional source-code. We present techniques to segment the flat address space in an executable containing undifferentiated blocks of memory. We demonstrate the inadequacy of existing variable identification methods for their promotion to symbols and present our methods for symbol promotion. We also present methods to convert the physically addressed stack in an executable (with a stack pointer) to an abstract stack (without a stack pointer). Our methods do not use symbolic, relocation, or debug information since these are usually absent in deployed executables. We have integrated our techniques with a prototype x86 binary framework called SecondWrite that uses LLVM as IR. The robustness of the framework is demonstrated by handling executables totaling more than a million lines of source-code, produced by two different compilers (gcc and Microsoft Visual Studio compiler), three languages (C, C++, and Fortran), two operating systems (Windows and Linux) and a real world program (Apache server).