Miracle-dz/UniFAR-FTUs huggingface dataset:
Outdoor Terrain Traversability Analysis for Robot Navigation using a Time-Of-Flight Camera

Autonomous robotic systems operating in unstructured outdoor environments need to estimate the traversability of the terrain in order to navigate safely. Traversability estimation is a challenging problem, as the traversability is a complex function of both the terrain characteristics, such as slopes, vegetation, rocks, etc and the robot mobility characteristics, i.e. locomotion method, wheels, etc. It is thus required to analyze in real-time the 3D characteristics of the terrain and pair this data to the robot capabilities. Stereo cameras or 3D laser range finders are generally used as input devices for traversability analysis and two main approaches can be distinguished. There are the methods as the ones advocated by Labayrade (1) and Mufti (2) who assume a (piecewise) planar ground plane. They estimate the ground plane, set a threshold and consider objects with distances to the ground plane further than this threshold as obstacles. Other methods, as the ones proposed by Birk (3) and Helmick (4) search for specific types of objects (rocks, canyons) and classify the image based on this data. To our knowledge, time-of-flight cameras have until now not been used for these kind of applications, simply because there were no sensors capable of coping with outdoor conditions, especially due to the interference of solar irradiation. This situation is changing now, with the advent of outdoor-capable sensors. Therefore, we present in this paper an approach for outdoor terrain traversability which mixes 2D and 3D information for terrain classification. The methodology towards time-of-flight-based terrain traversability analysis extends our previous work on stereobased terrain classification approaches (5). Following this strategy, the RGB data stream is segmented to group pixels belonging to the same physical objects. From the Depth data stream, the v−disparity (1) is calculated to estimate the ground plane, which leads to a first estimation of the terrain traversability. From this estimation, a number of pixels are selected which have a high probability of belonging to the ground plane (low distance to the estimated ground plane). The mean a and b color values in the Lab color space of these pixels are recorded as c. The presented methodology then classifies all image pixels as traversable or not by estimating for each pixel a traversability score which is based upon the analysis of the segmented color image and the v-disparity depth image. For each pixel i in the image, the color difference ‖ci − c‖ and the obstacle density in the region where the pixel belongs to are calculated. The obstacle density δi is here defined as: δi = 〈o∈Ai〉 〈Ai〉 , where o denotes the pixels marked as obstacles (high distance to the estimated ground plane) and Ai denotes the segment where pixel i belongs to. This allows us to define a traversability score as τi = δi‖ci− c‖, which is used for classification. This is done by setting up a dynamic threshold, as a function of the distance measured.
Using online services in untrusted environments: a privacy-preserving architecture

While online service providers are sometimes accused of forwarding identifying customer information as name and address to untrusted third parties, comparatively little attention is paid to the input data that customers provide explicitly to the service. If the input data is sensitive but the service provider is not completely trustworthy, this constitutes a serious privacy problem. From a privacy-defending point of view, the most desirable situation would be for the service not to require any kind of sensitive information at any time, while still yielding useful results for the customer. This paper presents a service architecture that allows for the use of a restricted number of services without requiring the transmission of unencrypted customer data to the service provider. The supported services include the execution of basic database and arithmetic operations that can be combined in numerous useful ways. The basic idea of this architecture is to transform sensitive data on the client side before transferring it to the service provider. The latter processes the transformed data without being able to draw any further conclusions from it. The pseudo-result obtained is returned to the customer who applies a special retransformation to obtain the actual result.
Religious Desecration and Ethnic Violence

Abstract : Desecration of religious places has drawn the attention of the world media, academics and policymakers on a number of occasions. The desecration of the Church of the Nativity, the cross-desecration by both Orthodox and Muslims of the Balkans, the desecration of the Sikh Golden Temple, the destruction of the Bamiyan Buddha Monolith by the Taliban in Afghanistan and many others have attracted world condemnation. However, there has been little or no cross-sectional research or academic enquiry into the causes or impacts of desecration. The question of what constitutes desecration and what are the impacts of desecration are the subject of this study. This study attempts to establish that desecration could be a factor for protest, rebellion and violence, often independent of political, economic and social factors. The study begins with a discussion about the concept of the sacred and profane followed by an analysis of what factors influence sacredness. Based on a historical perspective of desecration and pollution a causal relationship is established to explain why believers consider desecration to be a challenge and resort to protests, rebellion or violence. Finally, the hypotheses are demonstrated qualitatively, through a number of cases studies.
Noise in Grover’s quantum search algorithm

Grover's quantum algorithm improves any classical search algorithm. We show how random Gaussian noise at each step of the algorithm can be modeled easily because of the exact recursion formulas available for computing the quantum amplitude in Grover's algorithm. We study the algorithm's intrinsic robustess when no quantum correction codes are used, and evaluate how much noise the algorithm can bear with, in terms of the size of the phone book and a desired probability of finding the correct result. The algorithm loses efficiency when noise is added, but does not slow down. We also study the maximal noise under which the iterated quantum algorithm is just as slow as the classical algorithm. In all cases, the width of the allowed noise scales with the size of the phone book as ${N}^{\ensuremath{-}2/3}. $
Boundaries of Israeli Assistant Principals’ Instructional Leadership

ABSTRACT Whereas school principals’ instructional leadership has received research attention, assistant principals’ instructional leadership role has been relatively neglected. The current research explored those instructional leadership responsibilities that assistant principals do not perform. Data collection included interviews with a diverse sample of 34 Israeli assistant principals. Data analysis was a four-stage process of condensing, coding, categorizing, and theorizing. This study emphasizes the need for a framework that specifically defines the instructional responsibilities of assistant principals, possibly while excluding instructional practices that involve strategic leadership, authority, and personnel management. Implications and further research are discussed.
An unsupervised method for author extraction from web pages containing user-generated content

In this paper, we address the problem of author extraction (AE) from user generated content (UGC) pages. Most existing solutions for web information extraction, including AE, adopt supervised approaches, which require expensive manual annotation. We propose a novel unsupervised approach for automatically collecting and labeling training data based on two key observations of author names: (1) people tend to use a single name across sites if their preferred names are available; (2) people tend to create unique usernames to easily distinguish themselves from others, e.g. travelbug61. Our AE solution only requires features extracted from a single UGC page instead of relying on clues from multiple UGC pages. We conducted extensive experiments. (1) The evaluation of automatically labeled author field data shows 95.0% precision. (2) Our method achieves an F1 score of 96.1%, which significantly outperforms a state-of-the-art supervised approach with single page features (F1 score: 68.4%) and has a comparable performance to its multiple page solution (F1 score: 95.4%). (3) We also examine the robustness of our approach on various UGC pages from forums and review sites, and achieve promising results as well.
Solar harvest prediction supported by cloud cover forecasts

Solar harvest prediction is used in energy-harvesting sensor networks to achieve perpetual node operation. Existing approaches only exploit local knowledge and thus fail in unforeseeable, changing weather conditions. We investigate the benefit of incorporating global knowledge in terms of fractional sky cloudiness, so-called cloud cover. We propose and evaluate two methods that combine local information of a node's harvest pattern with global cloud cover forecasts. We evaluate their performance with solar traces collected by three solar-harvesting sensor nodes and compare the results with existing prediction algorithms. We find that (i) harvest predictions using cloud cover forecasts improve overall prediction precision, (ii) prediction errors in changing weather conditions are considerably reduced, and (iii) coarse-grained cloud cover forecasts require low extra network traffic while sacrificing little prediction precision.
CALCULATION OF FIRST EXCURSION PROBABILITIES BY SUBSET SIMULATION

A new simulation approach, called ‘subset simulation’, is applied to computing small first excursion probabilities for dynamical systems with stochastic excitations. The basic idea is to express the first excursion probability as a product of larger conditional failure probabilities by introducing intermediate failure boundaries. With a proper choice of the intermediate boundaries, the original problem of calculating a small failure probability, which is computationally demanding, is reduced to calculating a sequence of conditional probabilities, which are efficiently estimated by simulation using a special Markov chain. The proposed method is robust to the type of structural model (e.g., linear or nonlinear) and stochastic excitation model (e.g., stationary or nonstationary). Numerical studies are presented to demonstrate the efficiency of the method.
A Comparative Study of Rectangular and Circular Microstrip Fed Patch Antenna at 2.45 GHz

A Comparative study of rectangular and circular shape microstrip fed patch antennas for bluetooth application is presented in this paper. The resonance frequency is chosen at 2.45 GHz which is suitable for industrial scientific and medical (ISM) band applications. Computer Simulation Technology (CST) microwave studio is used as the software environment to design and compare the performance of the antennas. Based on the results and analysis, it is noted that the rectangular patch antenna shows about 6 dB higher return loss than the return loss of circular patch antenna. In addition, rectangular patch antenna has improved gain value of 7.12 dB than that of the circular patch with gain of 6.87 dB. However, circular patch antenna offers 5.5 MHz higher bandwidth as compared with the rectangular patch. The radiation efficiency of both rectangular and circular shaped microstrip fed patch antennas is nearly the same.
A polymorphism of the interleukin-6 gene promoter and idiopathic recurrent miscarriage.

BACKGROUND Cytokines have been described to play a major role in the pathogenesis of idiopathic recurrent miscarriage (IRM). We investigated the association between IRM and a polymorphism of the interleukin-6 (IL-6) gene and IL-6 serum levels. METHODS In a prospective case-control study, we studied 161 women with IRM and 124 healthy controls. Peripheral venous puncture, DNA extraction and PCR were employed to genotype women for the presence of a polymorphism at position -174 in the promoter region of IL-6. Serum IL-6 levels were assessed by a commercially available ELISA. RESULTS Allele frequencies among women with IRM and controls were 63.4 and 58.1% respectively for allele G (wild type), and 36.6 and 41.9% respectively for allele C (mutant). No association between allele C and the occurrence of IRM was found (odds ratio 0.8; 95% confidence interval = 0.57-1.12; P = NS). IL-6 serum levels were not significantly different between genotypes and between the study and control groups. CONCLUSIONS This is the first report on an IL-6 polymorphism in IRM. Although known to alter IL-6 expression, the IL-6 polymorphism investigated was not associated with IRM and alterations in IL-6 serum levels in a Middle-European Caucasian population.
Lexical units as the centrepiece of a wordnet

Semantic relations are the cornerstone of any wordnet. In most wordnets created thus far, however, the nature of the arguments of such relations is unclear. The synset, usually considered the basic unit of a wordnet, relies on the notion of synonymy, distinctly difficult to define, and on the even more vague notion of a concept. We argue that the synset should be consistently replaced by the lexical unit as the fundamental unit of a wordnet. A wordnet is a lexical database that operates as a dictionary or a thesaurus. Users expect words in such a resource, and they can understand words even without the benefits of syntax. Semantic or lexico-semantic relations, then, link meanings bound to words, or more generally to lexical units. The practical effect of this work is the adoption of lexical units as the basic building blocks of a Polish WordNet namedplWordNet.
Brain MRI abnormalities in schizophrenia: same genes or same environment?

Background. Structural brain volume abnormalities are among the most extensively studied endophenotypes in schizophrenia. Bivariate genetic model fitting (adjusted to account for selection) was used to quantify the genetic relationship between schizophrenia and brain volumes and to estimate the heritability of these volumes. Method. We demonstrated by simulation that the adjusted genetic model produced unbiased estimates for endophenotype heritability and the genetic and environmental correlations. The model was applied to brain volumes (whole brain, hippocampus, third and lateral ventricles) in a sample of 14 monozygotic (MZ) twin pairs concordant for schizophrenia, 10 MZ discordant pairs, 17 MZ control pairs, 22 discordant sibling pairs, three concordant sibling pairs, and 114 healthy control subjects. Results. Whole brain showed a substantial heritability (88%) and lateral ventricles substantial common environmental effects (67%). Whole brain showed a significant genetic correlation with schizophrenia, whereas lateral ventricles showed a significant individual specific correlation with schizophrenia. There were significant familial effects for hippocampus and third ventricle, but the analyses could not resolve whether these were genetic or environmental in origin (around 30% each). Conclusions. Using genetic model fitting on twin and sibling data we have demonstrated differential sources of covariation between schizophrenia and brain volumes, genetic in the case of whole brain volume and individual specific environment in the case of lateral ventricles.
The back and forth nudging algorithm applied to a shallow water model , comparison and hybridization with the 4 D-VAR

We study in this paper a new data assimilation algorithm, called the Back and Forth Nudging (BFN). This scheme has been very recently introduced for simplicity reasons, as it does not require any linearization, or adjoint equation, or minimization process in comparison with variational schemes, but nevertheless it provides a new estimation of the initial condition at each iteration. We study its convergence properties as well as efficiency on a 2D shallow water model. All along the numerical experiments, comparisons with the standard variational algorithm (called 4D-VAR) are performed. Finally, a hybrid method is introduced, by considering a few iterations of the BFN algorithm as a preprocessing tool for the 4D-VAR algorithm. We show that the BFN algorithm is extremely powerful in the very first iterations, and also that the hybrid method can both improve notably the quality of the identified initial condition by the 4D-VAR scheme and reduce the number of iterations needed to achieve convergence. Key-words: Data assimilation, shallow water, back and forth nudging, variational methods, hybrid method, nonlinear dynamics ∗ Institut de Mathématiques de Toulouse, Université Paul Sabatier Toulouse 3, 31062 Toulouse cedex 9, France (auroux@math.univ-toulouse.fr) † INRIA Grenoble Rhône-Alpes, équipe-projet MOISE, France in ria -0 03 29 18 2, v er si on 1 10 O ct 2 00 8 Le nudging direct et rétrograde appliqué à un modèle shallow-water: comparaison et hybridation avec le 4D-VAR Résumé : Dans cet article, nous étudions le nudging direct et rétrograde. Cet algorithme a été récemment introduit pour des raisons de simplicité, comme il ne nécessite ni linéarisation, ni état adjoint, ni minimisation, par rapport aux méthodes variationnelles. Cet algorithme fournit toutefois une nouvelle estimation de la condition initiale à chaque itération. Nous étudions les propriétés de convergence et l’efficacité de cet algorithme sur un modèle shallowwater 2D. Tout au long des expériences numériques, nous effectuons des comparaisons avec le 4D-VAR. Enfin, une méthode hybride est introduite dans cet article, consistant à effectuer quelques itérations de l’algorithme BFN comme préconditionnement de l’algorithme 4D-VAR. Nous montrons que l’algorithme BFN est très performant dans les toutes premières itérations, et la méthode hybride peut non seulement améliorer sensiblement la qualité de la condition initiale identifiée par le 4D-VAR, mais aussi réduire la nombre d’itérations nécessaires pour atteindre la convergence. Mots-clés : Assimilation de données, modèle shallow-water, nudging direct et rétrograde, méthodes variationnelles, hybridation, dynamique non linéaire in ria -0 03 29 18 2, v er si on 1 10 O ct 2 00 8 Back and forth nudging algorithm on a shallow water model 3
The Association between Fatal Coronary Heart Disease and Ambient Particulate Air Pollution: Are Females at Greater Risk?

The purpose of this study was to assess the effect of long-term ambient particulate matter (PM) on risk of fatal coronary heart disease (CHD). A cohort of 3,239 nonsmoking, non-Hispanic white adults was followed for 22 years. Monthly concentrations of ambient air pollutants were obtained from monitoring stations [PM < 10 μm in aerodynamic diameter (PM10), ozone, sulfur dioxide, nitrogen dioxide] or airport visibility data [PM < 2.5 μm in aerodynamic diameter (PM2.5)] and interpolated to ZIP code centroids of work and residence locations. All participants had completed a detailed lifestyle questionnaire at baseline (1976), and follow-up information on environmental tobacco smoke and other personal sources of air pollution were available from four subsequent questionnaires from 1977 through 2000. Persons with prevalent CHD, stroke, or diabetes at baseline (1976) were excluded, and analyses were controlled for a number of potential confounders, including lifestyle. In females, the relative risk (RR) for fatal CHD with each 10-μg/m3 increase in PM2.5 was 1.42 [95% confidence interval (CI), 1.06–1.90] in the single-pollutant model and 2.00 (95% CI, 1.51–2.64) in the two-pollutant model with O3. Corresponding RRs for a 10-μg/m3 increase in PM10-2.5 and PM10 were 1.62 and 1.45, respectively, in all females and 1.85 and 1.52 in postmenopausal females. No associations were found in males. A positive association with fatal CHD was found with all three PM fractions in females but not in males. The risk estimates were strengthened when adjusting for gaseous pollutants, especially O3, and were highest for PM2.5. These findings could have great implications for policy regulations.
Implicit Contracts with Asymmetric Information and Bankruptcy: The Effect of Interest Rates on Layoffs

This paper develops a model in which a firm writes labour contracts with workers and debt contracts with creditors. Firms have more information than do the owners of the factors of production and they are also subject to limited liability. We show that if the limited liability constraint is binding then the employment level is inefficient relative to a situation of symmetric information. The firm is then embedded into a partial equilibrium model in which the real rate of interest is exogenously determined. We show that increases in the real rate of interest increase the inefficiency of the optimal employment contract and lead to layoffs in more states of nature than would occur at lower real interest rates.
Computers, Wages and Working Hours in Italy Computers, Wages and Working Hours in Italy *

This paper provides an estimate of the relationships between wages, working hours and the use of computers at the workplace for the Italian labour market. On the methodological side, we offer a contribution on the appropriate procedure for estimating the above effects: it is shown that the simultaneity between wages and hours must be taken into account when specifying the statistical model for the data and, furthermore, that the interactions between explanatory variables plays a significant role that cannot be neglected. Our empirical findings are also of interest: by controlling for computer skill, workers’ ability and many other covariates, we found that only for higher-level white collars the average wage premium associated with computer usage is in the same order of magnitude as the one estimated for the US, Germany and France, while the effect vanishes for lower qualifications. The use of computers at work increases the number of hours worked, although this effect is small and much lower than that estimated for the US. Moreover, since hourly wages have a negative impact on hours worked, computers seem to exert little, if any, impact on working time. JEL Class. : J31, O33 Indirizzo: Dipartimento di Economia and Dipartimento di Management e Organizzazione Industriale, Università Politecnica delle Marche. Corresponding author: A. Sterlacchini sterla@dea.unian. it Computers, Wages and Working Hours in Italy∗ Riccardo Lucchetti, Stefano Staffolani and Alessandro Sterlacchini
Self-organization of behavioral primitives as multiple attractor dynamics: a robot experiment

I investigated how behavior primitives are self-organized in my previously (Tani, 2001) proposed "forwarding forward model" neural network model in the context of robot imitation learning. The model is characterized with the so-called parametric biases which adaptively modulate for embedding different behavior patterns in a single recurrent neural net in a distributed way. My experiments, using a real robot, showed that a set of end-point and oscillatory behavior patterns are learned as fixed points and limit cycle dynamics respectively with adapting parametric bias for each. Further analysis showed that diverse behavior patterns other than learned patterns were also generated because of self-organization of the nonlinear map between the parametric biases and behavior patterns. It is concluded that such diversity emerges because primitives are represented distributedly in the network.