Miracle-dz/UniFAR-FTUs huggingface dataset:
Understanding the Success of Perfect Information Monte Carlo Sampling in Game Tree Search

Perfect Information Monte Carlo (PIMC) search is a practical technique for playing imperfect information games that are too large to be optimally solved. Although PIMC search has been criticized in the past for its theoretical deficiencies, in practice it has often produced strong results in a variety of domains. In this paper, we set out to resolve this discrepancy. The contributions of the paper are twofold. First, we use synthetic game trees to identify game properties that result in strong or weak performance for PIMC search as compared to an optimal player. Second, we show how these properties can be detected in real games, and demonstrate that they do indeed appear to be good predictors of the strength of PIMC search. Thus, using the tools established in this paper, it should be possible to decide a priori whether PIMC search will be an effective approach to new and unexplored games.
Exoskeleton control for lower-extremity assistance based on adaptive frequency oscillators: Adaptation of muscle activation and movement frequency

In this article, we analyze a novel strategy for assisting the lower extremities based on adaptive frequency oscillators. Our aim is to use the control algorithm presented here as a building block for the control of powered lower-limb exoskeletons. The algorithm assists cyclic movements of the human extremities by synchronizing actuator torques with the estimated net torque exerted by the muscles. Synchronization is produced by a nonlinear dynamical system combining an adaptive frequency oscillator with a form of adaptive Fourier analysis. The system extracts, in real time, the fundamental frequency component of the net muscle torque acting on a specific joint. Said component, nearly sinusoidal in shape, is the basis for the assistive torque waveform delivered by the exoskeleton. The action of the exoskeleton can be interpreted as a virtual reduction in the mechanical impedance of the leg. We studied the ability of human subjects to adapt their muscle activation to the assistive torque. Ten subjects swung their extended leg while coupled to a stationary hip joint exoskeleton. The experiment yielded a significant decrease, with respect to unassisted movement, of the activation levels of an agonist/antagonist pair of muscles controlling the hip joint’s motion, which suggests the exoskeleton control has potential for assisting human gait. A moderate increase in swing frequency was observed as well. We theorize that the increase in frequency can be explained by the impedance model of the assisted leg. Per this model, subjects adjust their swing frequency in order to control the amount of reduction in net muscle torque.
Smart Traffic Lights: A First Parallel Computing Approach

Optimal traffic light scheduling is a fundamental problem in modern urban areas. It has severe impact on traffic flow management, energy consumption and vehicular emissions, as well as on urban noise. The vast number of traffic lights in modern cities increases the complexity of the scheduling problem and, at the same time, urgently needs for efficient algorithms that optimize the light cycle programs. In this work, we propose a solution for the traffic light scheduling problem by using Differential Evolution, and investigate the benefits of parallelism on this complex problem. For understanding the impact in the city, the popular micro-simulator SUMO is used. We evaluate our approach on close-to-reality problem scenarios consisting of two large urban areas located in the cities of Málaga, Spain, and Paris, France. Our results are promising and encourage further investigation of parallel approaches to enable scalability.
Fusion of Conditional Random Field and SignalP for Protein Cleavage Site Prediction

Prediction of protein cleavage sites is an important step in drug design. Recent research has demonstrated that conditional random fields are capable of predicting the cleavage site locations of signal peptides, and their performance is comparable to that of SignalP—a state-of-the-art predictor based on hidden Markov models and neural networks. This paper investigates the degree of complementarity between CRF-based predictors and SignalP and proposes using the complementary properties to fuse the two predictors. It was found that about 40% of the sequences that are incorrectly predicted by SignalP can be correctly predicted by CRF, and that about 30% of the sequences that are incorrectly predicted by CRF can be correctly predicted by SignalP. This suggests that the two predictors complement each other. The paper also shows that the performance of CRF can be further improved by constructing the state features from spatially dispersed amino acids in the training sequences.
VARIATION IN VIABILITY SELECTION AMONG COHORTS OF JUVENILE RED SQUIRRELS (TAMIASCIURUS HUDSONICUS)

Abstract Selection will result in observable changes in traits only if it acts consistently in space and time, but few estimates of selection in natural populations have been temporally replicated. Here we estimate viability selection on nestling growth rates for 13 cohorts (1989–2001) of red squirrels (Tamiasciurus hudsonicus) from a natural population located in southwestern Yukon, Canada. Directional selection on nestling growth rates varied in magnitude and direction from one cohort to the next. The magnitude of directional selection was relatively weak in most years (median β′ = 0.24), but there were episodes of very strong viability selection (β′ > 0.5) in some cohorts. We found no evidence of significant stabilizing or disruptive selection on this trait. Examination of viability selection episodes over shorter time periods suggested that the strength of selection on juveniles in this population was positively related to the time scale over which selection was measured. Viability selection from birth to emergence from the natal nest (50 days of age) and from emergence to successful recruitment (100 days of age) were positively correlated, but were both independent of selection on nestling growth rates from recruitment to potential breeding age (one year). The strength of directional selection on growth rates prior to recruitment was negatively correlated with spring temperature whereas selection from recruitment to breeding was positively correlated with the abundance of spruce cones produced in the previous fall. Episodes of strong directional selection from birth to breeding age appear to be due to potentially rare combinations of environmental conditions. As a result, predicting the occurrence of very strong episodes of selection will be extremely difficult, but predicting the microevolutionary responses to observed selection on individual cohorts remains feasible.
Breast Cancer Diagnosis and Prognosis Via Linear Programming

Two medical applications of linear programming are described in this paper. Specifically, linear programming-based machine learning techniques are used to increase the accuracy and objectivity of breast cancer diagnosis and prognosis. The first application to breast cancer diagnosis utilizes characteristics of individual cells, obtained from a minimally invasive fine needle aspirate, to discriminate benign from malignant breast lumps. This allows an accurate diagnosis without the need for a surgical biopsy. The diagnostic system in current operation at University of Wisconsin Hospitals was trained on samples from 569 patients and has had 100% chronological correctness in diagnosing 131 subsequent patients. The second application, recently put into clinical practice, is a method that constructs a surface that predicts when breast cancer is likely to recur in patients that have had their cancers excised. This gives the physician and the patient better information with which to plan treatment, and may eliminate the need for a prognostic surgical procedure. The novel feature of the predictive approach is the ability to handle cases for which cancer has not recurred (censored data) as well as cases for which cancer has recurred at a specific time. The prognostic system has an expected error of 13.9 to 18.3 months, which is better than prognosis correctness by other available techniques.
Robust and Efficient 3-D Reconstruction by Self-Calibration

We present a very robust and ecient scheme for 3-D reconstruction from point correspondences over multiple images taken by uncalibrated cameras. Our method is based on iterative projective reconstruction followed by Euclidean upgrading. We accelerate the time-consuming iterations for projective reconstruction by using the power method for eigenvalue computation, accelerating the power method itself, and introducing SOR for further acceleration. Using simulated and real video images, we demonstrate that our techniques dramatically speed up the computation, in some cases about 8,000 times faster.
Clever tracking user behaviour over the web: enabling researchers to respect the user

Concerns over automatically tracking users' actions while respecting consent, privacy and users' rights motivated the development of CleverTracker. CleverTracker is a remote action-tracking software framework, which researchers can use to collect data about users' interactions with applications while respecting ethical issues. Users are in control of the recording process (through start and stop functionality), can opt out from it and can view the collected data. The open source framework is designed to support desktop, web application and multiple programming languages.
Distributed Coordination in Modular Precision Assembly Systems Distributed Coordination in Modular Precision Assembly Systems

A promising approach to enabling the rapid deployment and reconfiguration of automated assembly systems is to make use of cooperating, modular, robust robotic agents. Over the past 5 years, the authors have been constructing just such a system suitable for assembly of high-precision, high-value products. Within this environment, each robotic agent executes its own program, coordinating its activity with that of its peers to produce globally cooperative precision behavior. To simplify the problems associated with deploying such systems, each agent adheres to a strict notion of modularity, both physically and computationally. The intent is to provide an architecture within which it is straightforward to specify strategies for the robust execution of potentially complex and fragile cooperative behaviors. The underlying behaviors use a runtime environment that includes tools to automatically sequence the activities of an agent. Taken together, these abstractions enable a designer to rapidly and effectively describe the high-level behavior of a collection of agents while relying on a set of formally correct control strategies to properly execute and sequence the necessary continuous behaviors. KEY WORDS—robotics, automated assembly, distributed systems, sensor-based control
The application of discriminant analysis for mapping cereals and pasture using object-based features

ABSTRACT High mapping accuracies occur where crops differ spectrally (e.g.>90.0%; canola, corn, soybeans) and vice versa (e.g. <75.0%; cereals and pasture). Developing improved mapping methods has been an ongoing priority of Agriculture and Agri-Food Canada (AAFC) remote-sensing science. To this end, this study tests a data-driven object-based classification method using Discriminant Analysis (DA) method for mapping cereals and pasture from satellite data. In this approach, variables (number >400) derived from the image segmentation and object-based feature extraction of multi-date and multi-band optical (RapidEye) and microwave (RADARSAT-2) imagery were applied in a data-driven approach. We use in situ and satellite information collected over two study sites with different levels of heterogeneity (Winnipeg, Brandon) situated in the Canadian Prairies during the 2013 growing season to assess: (a) the type of DA model that most accurately classifies the cereals and pasture cover classes; and (b) how the classification accuracies obtained by the application of this DA model compare to those obtained from more traditional Maximum Likelihood (ML), Decision Tree (DT), and Random Forest (RF) classifications. We found that our DA-based approach was able to map cereals and pastures at our two study sites with the highest accuracies, but these accuracies did not improve significantly with the use of more complex DA model (including priori classification probabilities, more input principle components (PCs), the use of weights proportional to field area). Our results are encouraging for the wider application of the data-driven pre-processing of the inputs to the image classification by DA.
Improving and Balancing Software Qualities

This Technical Briefing describes the nature of Software Qualities (SQs), ilities, or non-functional requirements (reliability, usability, affordability, etc.), and discusses the importance of understanding their nature and interrelationships, and of bringing them into balance in the practice of software engineering.The relevance and timeliness of this topic reflects the current and future trends toward more software-intensive systems, with greater complexity, autonomy, speed of change, and need for interoperability within systems of systems, given the frequent system shortfalls and overruns that occur when their SQ balance is not achieved.It discusses the weaknesses of current SQ standards and guidance, and summarizes research toward strengthening current SQ definitions and relationships.This includes a set of initial SQ ontology elements and relationships, examples of their application to some key SQs, an identification of further research and development needed to make the ontology fully useful and evolvable, and the nature of an international collaborative effort to help improve current practices via a Qualipedia for accessing the evolving body of knowledge for improving SQ engineering.
Variational Bayesian Kalman filtering in dynamical tomography

The problem of dynamical tomography consists in reconstructing a temporal sequence of images from their noisy projections. For this purpose, a recursive algorithm is usually used, like for instance the Kalman Filter (KF), due to the dynamical structure of the problem. However, since it needs the inverse of innovation matrix, KF may suffer from a huge computational cost in cases of images with very high dimensions. To solve this issue, we develop a new suboptimal version of the KF based on a Variational Bayesian (VB) approach. The proposed Variational Bayesian KF (VBKF) algorithm is compared to the KF with simulations in a small problem (images 32×32). As expected, the image quality of VBKF is as good as the KF and the VBKF algorithm is four times faster than the KF. Furthermore, in realistic high dimensional problems in which the practical implementation of KF becomes impossible, the VBKF gives an attractive alternative since it can be millions times faster than the KF
Resolving the Democracy Paradox

Increasing levels of democratic freedoms should, in theory, improve women’s access to political positions. Yet studies demonstrate that democracy does little to improve women’s legislative representation. To resolve this paradox, we investigate how variations in the democratization process—including pre-transition legacies, historical experiences with elections, the global context of transition, and post-transition democratic freedoms and quotas—affect women’s representation in developing nations. We find that democratization’s effect is curvilinear. Women in non-democratic regimes often have high levels of legislative representation but little real political power. When democratization occurs, women’s representation initially drops, but with increasing democratic freedoms and additional elections, it increases again. The historical context of transition further moderates these effects. Prior to 1995, women’s representation increased most rapidly in countries transitioning from civil strife—but only when accompanied by gender quotas. After 1995 and the Beijing Conference on Women, the effectiveness of quotas becomes more universal, with the exception of post-communist countries. In these nations, quotas continue to do little to improve women’s representation. Our results, based on pooled time series analysis from 1975 to 2009, demonstrate that it is not democracy—as measured by a nation’s level of democratic freedoms at a particular moment in time—but rather the democratization process that matters for women’s legislative representation.
Towards low bit rate mobile visual search with multiple-channel coding

In this paper, we propose a multiple-channel coding scheme to extract compact visual descriptors for low bit rate mobile visual search. Different from previous visual search scenarios that send the query image, we make use of the ever growing mobile computational capability to directly extract compact visual descriptors at the mobile end. Meanwhile, stepping forward from the state-of-the-art compact descriptor extractions, we exploit the rich contextual cues at the mobile end (such as GPS tags for mobile visual search and 2D barcodes or RFID tags for mobile product search), together with the visual statistics at the reference database, to learn multiple coding channels. Therefore, we describe the query with one of many forms of high-dimensional visual signature, which is subsequently mapped to one or more channels and compressed. The compression function within each channel is learnt based on a novel robust PCA scheme, with specific consideration to preserve the retrieval ranking capability of the original signature. We have deployed our scheme on both iPhone4 and HTC DESIRE 7 to search ten million landmark images in a low bit rate setting. Quantitative comparisons to the state-of-the-arts demonstrate our significant advantages in descriptor compactness (with orders of magnitudes improvement) and retrieval mAP in mobile landmark, product, and CD/book cover search.
A fully implicit alternating direction method of multipliers for the minimization of convex problems with an application to motion segmentation

Motivated by a variational formulation of the motion segmentation problem, we propose a fully implicit variant of the (linearized) alternating direction method of multipliers for the minimization of convex functionals over a convex set. The new scheme does not require a step size restriction for stability and thus approaches the minimum using considerably fewer iterates. In numerical experiments on standard image sequences, the scheme often significantly outperforms other state of the art methods.
Neonatal deletion and selective expansion of mouse T cells by exposure to rabies virus nucleocapsid superantigen

The nucleocapsid (NC) of the rabies virus behaves as an exogenous superantigen (SAg) in humans. In the present report, we analyzed whether it is also a SAg in mice by studying the effect of NC on T cell receptor (TCR) V beta expression in BALB/c mice. Repeated injection of NC in newborn BALB/c mice led to a marked reduction by two- to sixfold of V beta 6 expressing CD4+ T cells in spleen and in peripheral blood. Decrease of V beta 6-expressing CD3+ mature T cells was also observed in thymus. Single NC injection in footpad resulted in a three- to sixfold expansion of V beta 6 CD4+ T cells, but not of CD8+ T cells, in the draining lymph nodes of BALB/c mice. The intensity of the stimulation was dose dependent and was maximal 3 d after the NC injection. The clonal deletion of T cells bearing a particular V beta demonstrates that NC is a SAg in mice. T cells, especially CD4+ T cells, are an essential factor in host resistance to rabies virus and also in the pathophysiology of paralysis; thus, we postulate that a rabies virus component, which stimulates T cells, such as a SAg, may increase virus immunopathogenicity. To evaluate this hypothesis, we compared the course of rabies in adult BALB/c lacking V beta 6, 7, 8.1, and 9 T cells and in normal BALB/c. Immune-related paralysis was decreased in BALB/c missing the NC target V beta T cells. Transfer of V beta 6 but not of V beta 8.1-3 T cells into recipient mice lacking V beta 6, 7, 8.1, and 9 allowed the immune-related paralysis to evolve. Taken together, these results strongly support the hypothesis that T cells expressing rabies SAg-specific V beta 6 T cells, are involved in the genesis of the immunopathology that is characteristic of paralytic rabies.
A proposal for an owl rules language

Although the OWLWeb Ontology Language adds considerable expressive power to the Semantic Web it does have expressive limitations, particularly with respect to what can be said about properties. Wepresent ORL (OWL Rules Language), a Horn clause rules extension to OWL that overcomes many of these limitations. ORL extends OWL in a syntactically and semantically coherent manner: the basic syntax for ORL rules is an extension of the abstract syntax for OWL DL and OWLLite; ORL rules are given formal meaning via an extension of the OWLDL model-theoretic semantics; ORL rules are given an XML syntax basedon the OWL XML presentation syntax; and a mapping from ORL rules to RDF graphs is given based on the OWL RDF/XML exchange syntax. Wediscuss the expressive power of ORL, showing that the ontology consistency problem is undecidable, provide several examples of ORLusage, and discuss how reasoning support for ORL might be provided.
LBK2013: A balanced; annotated national corpus for Norwegian Bokmål

At the Department of Linguistics and Scandinavian Studies (ILN) and the University of Oslo, the task of assembling a balanced corpus representing modern Norwegian Bokmal has reached a significant milestone. The Corpus for Bokmal Lexicography (LBK) now consists of more than 100,000,000 words. These documents have been selected based on a statistical analysis of reading habits in the general population of Norway. The documents have been subject to both manual bibliographic annotation, as well as automatic morphological annotation for each document. LBK will play a central part of a set of interconnected lexical resources, the aim of which is to provide an extensive documentation of Norwegian Bokmal that covers lexical and other linguistic/lexico-syntactic aspects. This paper presents LBK2013, a subset of LBK that we consider to be an accurate and comprehensive representation of modern written Norwegian Bokmal. A description of the corpus, as well as a number of related projects are described.