Miracle-dz/UniFAR-FTUs huggingface dataset:
The effects of collocational strength and contextual predictability in lexical production 1

and hence have a lower information value. 2 A consequence of considering frequency and predictability as probabilities is that they can be unified into a probabilistic model of processing together with other types of probabilistic knowledge, ultimately providing a more complete explanation of language use. Probabilistic models of human language comprehension claim that probabilistic information about words, phrases, and other linguistic structure is represented in the minds of language users and plays a role in language comprehension (Jurafsky 1996, Narayanan & Jurafsky 1998). This paper extends this probabilistic hypothesis to language production, suggesting that speakers use their knowledge of the probability of a word or combinations of words in sentence production. In particular, we present evidence that highly probable (less informative) words are shorter or more reduced in conversational speech. This is true whether the high probability of the word is based on frequency, collocation with neighboring words, repetition of the word in the conversation, or the semantic association of the word with its conversation context. Our results are based on experiments designed to test probabilistic effects on three measures of shortening: deletion, tapping, and durational shortening. The effects of various probabilistic measures were tested on 8,472 word tokens ending in t or d taken from the phonetically transcribed Switchboard corpus of American telephone conversations (Greenberg et al. 1996). In §1 we review the range of probabilistic measures known to affect production and argue that frequency and predictability are probabilistic measures. We describe the methodology of our study in §2, defining the probabilistic measures considered as predictors in §2.3. The results of the models are presented in §3, with a discussion following in §4. In §5, we discuss the implications of our results for probabilistic models of production. 1 Probabilistic measures and production A good deal of support for a probabilistic model of processing comes from studies of comprehension (Ford, Bresnan, & Kaplan 1982, Resnik 1993, MacDonald 1994, Trueswell, Tanenhaus, & Garnsey 1994, Jurafsky 1996, Garnsey, Pearlmutter, Myers, & Lotocky 1997), where a variety of probabilistic measures
A collaborative recommendation framework for ontology evaluation and reuse

Ontology evaluation can be defined as assessing the quality and the adequacy of an ontology for being used in a specific context, for a specific goal. Although ontology reuse is being extensively addressed by the Semantic Web community, the lack of appropriate support tools and automatic techniques for the evaluation of certain ontology features are often a barrier for the implementation of successful ontology reuse methods. In this work, we describe the recommender module of CORE [5], a system for Collaborative Ontology Reuse and Evaluation. This module has been designed to confront the challenge of evaluating those ontology features that depend on human judgements and are by their nature, more difficult for machines to address. Taking advantage of collaborative filtering techniques, the system exploits the ontology ratings and evaluations provided by users to recommend the most suitable ontologies for a given domain. Thus, we claim two main contributions: the introduction of collaborative filtering notion like a new methodology for ontology evaluation and reuse, and a novel recommendation algorithm, which considers specific user requirements and restrictions instead of general user profiles or item-based similarity measures.
The WICS Model of Organizational Leadership

6 96 Leadership is essential to the successful functioning of virtually any organization. Scholars of leadership attempt to understand what leads to success in leadership. Successful leaders need to do two things, among others. First, they need to have a story that followers can understand, accept, and, hopefully, support (see also Gardner, 1995). Second, they need to engage in complex processing that results in the creation, implementation, and monitoring of the story (see also Sternberg, 2003). The WICS model of leadership addresses both aspects of the leadership process. This model synthesizes many aspects of previous models. Thus it draws on much that is old, including trait, situational, behavioral, contingency, and transformational models. What do these models have to say about leadership? First, I present WICS. Then I relate it to past theories. Finally, I draw conclusions. WICS is an acronym that stands for wisdom, intelligence and creativity, synthesized. The model attempts to show how successful leadership involves the synthesis of the three qualities. In the center of the model is intelligence, traditionally defined as the ability to adapt to the environment (Cianciolo & Sternberg, 2004). According to the model used here, successful intelligence is one's ability to attain one's goals in life, given one's sociocultural context, by adapting to, shaping, and selecting environments , through a balance of analytical, creative, and practical skills (Sternberg, 1997). Underlying this ability are fundamental executive processes, or " metacomponents " (Sternberg, 1985): recognizing the existence of a problem, defining and redefining the problem, allocating resources to the solution of the problem, representing the problem mentally, formulating a strategy for solving the problem, monitoring the solution of the problem while problem solving is ongoing, and evaluating the solution to the problem after it has been solved. Analytical intelligence is involved when one applies these processes to fairly abstract problems that nevertheless take a relatively familiar form (e.g., intelligence-test items). Creative intelligence is involved when one applies the processes to relatively novel tasks and situations. Practical intelligence is involved when one applies the processes to everyday problems for purposes of adaptation to, shaping, and selection of environments. The theory of successful intelligence actually involves three subtheories (Sternberg, 1985). The first, com-ponential subtheory, specifies kinds of components—metacomponents (mentioned above), which are used to plan, monitor, and evaluate problem solutions; performance components, used to execute problem solutions; and knowledge-acquisition components, used to learn how to solve the problems …
Texture orientation for sorting photos "at a glance"

Investigates a measure of "dominant perceived orientation" that has been developed to match the output of a human study involving 40 subjects. The results of this measure are compared with humans analyzing seven "teaser" images to test its effectiveness for finding perceptually dominant orientations. The use of low-level orientation is then applied to a "quick search" problem important in image database applications. Since both pigeons and humans are able to perform coarse classification of certain kinds of scenes, e.g., city from country, without taking time or brain-power to solve the image understanding problem, the authors conjecture that the collective behavior of low-level textural features such as orientation may be doing most of the work. The authors demonstrate a simple test of global multiscale orientation for quickly searching a database of vacation photos for likely "city/suburb" shots. The orientation features achieve agreement with human classification in 91 out of 98 of the scenes.
Efficient Probabilistic Parameter Synthesis for Adaptive Systems

Probabilistic modelling has proved useful to analyse performance, reliability and energy usage of distributed or networked systems. We consider parametric probabilistic models, in which probabilities are specified as expressions over a set of parameters, rather than concrete values. We address the parameter synthesis problem for parametric Markov decision processes and parametric Markov reward models, which asks for a valuation for the parameters such that the resulting (concrete) probabilistic model satisfies a given property. To solve parametric probabilistic models for quantitative reachability properties, we propose efficient, robust methods, either based on sampling, for which we provide two algorithms, Markov chain Monte Carlo and the cross entropy algorithm, or on swarm intelligence, for which we adapt the particle swarm algorithm, a nonlinear optimisation method from evolutionary computation. We implement the methods in PRISM and demonstrate the effectiveness of our approach on several case studies, including adaptive systems and online model repair.
Study on eliminating wrong match pairs of SIFT

To eliminate or reduce wrong pairs in SIFT(Scale Invariant Feature Trans for m)feature matching, this paper proposes an error canceling algorithm through computing match-base. First finding three match point pairs by considering minimal Euclidean distance; second take three match point pairs as match-base if these pairs satisfy with criterion, or finding another three match pairs. Finally checking all other match pairs and eliminating wrong match pairs. Experimental results show that the proposed algorithm consumes lower time than RANSAC with inheriting rotation invariance of SIFT. At the same time, it does not exclude the right match pairs, with strong robustness. As a result, precision of image mosaic has been improved.
Polynomial-Time Aggregation of Integer Programming Problems

It ts shown that a set of linear Dtophantme equations m nonnegative variables with nonnegative coefficients can be reduced to a single equation with the same solution set in polynomial time. A weaker verston of the above statement ~s shown to be true when the coefficients are allowed to be negative Besides being polynomial-trine bounded, the present aggregation scheme differs from existing ones in that the final equation is m variables that are not exphcltly bounded Three applications of this aggregation technique are presented: (i) ~t Is proved that a certain type of knapsack problem cannot have a polynomialtune approxtmatlon algorithm unless NP = P; 00 an analog of Farkas' lemma for integer programming is proved; and 0ii) ~t is shown that a decision problem revolving integer variables is NP-complete.
Variant Brain-Derived Neurotrophic Factor Val66Met Polymorphism Alters Vulnerability to Stress and Response to Antidepressants

Brain-derived neurotrophic factor (BDNF) plays important roles in cell survival, neural plasticity, learning, and stress regulation. However, whether the recently found human BDNF Val66Met (BDNFMet) polymorphism could alter stress vulnerability remains controversial. More importantly, the molecular and structural mechanisms underlying the interaction between the BDNFMet polymorphism and stress are unclear. We found that heterozygous BDNF+/Met mice displayed hypothalamic-pituitary-adrenal axis hyperreactivity, increased depressive-like and anxiety-like behaviors, and impaired working memory compared with WT mice after 7 d restraint stress. Moreover, BDNF+/Met mice exhibited more prominent changes in BDNF levels and apical dendritic spine density in the prefrontal cortex and amygdala after stress, which correlated with the impaired working memory and elevated anxiety-like behaviors. Finally, the depressive-like behaviors in BDNF+/Met mice could be selectively rescued by acute administration of desipramine but not fluoxetine. These data indicate selective behavioral, molecular, and structural deficits resulting from the interaction between stress and the human genetic BDNFMet polymorphism. Importantly, desipramine but not fluoxetine has antidepressant effects on BDNF+/Met mice, suggesting that specific classes of antidepressant may be a more effective treatment option for depressive symptoms in humans with this genetic variant BDNF.
Understanding Commodity Cultures: Explorations in Economic Anthropology with Case Studies from Mexico

1. Economic Otherness South of the Border: The Twentieth Century Foundations and Formation of the Economic Anthropology of Mexico 2. Commodity Culture(s), Capitalism, and the Economic Anthropology of Mexico: the Case of B. Travern 3. Re-Reading Penny Capitalism: The Paradox of Poverty in a Land of Enterprise 4. Rereading Canonical Texts and Revisiting the "Great Debate": A Retrospective View from the Trenches through a Twenty-First-Century Lens 5. Commodity Value, Culture, and Economy 6. Understanding Peasants, Commodity Economy, and Change in the Mesoamerican Experience 7. Commodity Culture(s), Livelihood Strategies, and Reproductive Goals: A Critique of Ethnography 8. Social Reproduction of Commodity Value: Mapping Interior and Exterior Connections 9. The U.S-Mexico Borderlands: Commodity Culture(s), Labor, and Capital 10. The New Transborder Space: NAFTAmerica, Migration, and Identity
Dynamic Approach to Space and Habitat Use Based on Biased Random Bridges

Background Although habitat use reflects a dynamic process, most studies assess habitat use statically as if an animal's successively recorded locations reflected a point rather than a movement process. By relying on the activity time between successive locations instead of the local density of individual locations, movement-based methods can substantially improve the biological relevance of utilization distribution (UD) estimates (i.e. the relative frequencies with which an animal uses the various areas of its home range, HR). One such method rests on Brownian bridges (BBs). Its theoretical foundation (purely and constantly diffusive movements) is paradoxically inconsistent with both HR settlement and habitat selection. An alternative involves movement-based kernel density estimation (MKDE) through location interpolation, which may be applied to various movement behaviours but lacks a sound theoretical basis. Methodology/Principal Findings I introduce the concept of a biased random (advective-diffusive) bridge (BRB) and show that the MKDE method is a practical means to estimate UDs based on simplified (isotropically diffusive) BRBs. The equation governing BRBs is constrained by the maximum delay between successive relocations warranting constant within-bridge advection (allowed to vary between bridges) but remains otherwise similar to the BB equation. Despite its theoretical inconsistencies, the BB method can therefore be applied to animals that regularly reorientate within their HRs and adapt their movements to the habitats crossed, provided that they were relocated with a high enough frequency. Conclusions/Significance Biased random walks can approximate various movement types at short times from a given relocation. Their simplified form constitutes an effective trade-off between too simple, unrealistic movement models, such as Brownian motion, and more sophisticated and realistic ones, such as biased correlated random walks (BCRWs), which are too complex to yield functional bridges. Relying on simplified BRBs proves to be the most reliable and easily usable way to estimate UDs from serially correlated relocations and raw activity information.
Combating corruption, encouraging ethics : a practical guide to management ethics

In their second edition of "Combating Corruption, Encouraging Ethics", William L. Richter and Frances Burke update this essential staple to delve deeply into the unique ethical problems of twenty-first century public administration. "Combating Corruption, Encouraging Ethics" offers both the depth demanded by graduate courses in administrative ethics and the accessibility necessary for an undergraduate introduction to public administration.
A Survey and Evaluation of the Existing Tools that Support Adoption of Cloud Computing and Selection of Trustworthy and Transparent Cloud Providers

In spite of the benefits that could flow from its adoption, cloud computing brings new challenges associated with potential lack of transparency, trust, and loss of controls. With a growing number of cloud service providers, potential customers will require methods for selecting trustworthy and appropriate providers. We discuss existing tools, methods and frameworks that promote the adoption of cloud computing models, and the selection of trustworthy cloud service providers. We propose a set of customer's assurance requirements as a basis for comparative evaluation, and is applied to several popular tools (CSA STAR, CloudTrust Protocol, C.A.RE and Cloud Provider Transparency Scorecard). We describe a questionnaire-based survey in which respondents evaluate the extent to which these tools have been used, and assess their usefulness. The majority of respondents agreed on the importance of using the tools to assist migration to the cloud and, although most respondents have not used the tools, those who have used them reported them helpful. It has been noticed that there might be a relationship between a tool's compliance to the proposed requirements and the popularity of using these tools, and these results should encourage cloud providers to address customers' assurance requirements.
ELECTRICAL MODEL OF CARBON NANOTUBE TRANSISTORS

At present, an important issue is to dispose of electrical models describing the interplay between the observed phenomenology in CNT-FETs. These models are intended to serve as guidelines for the design and projection of CNT-FET performances. In this work we propose a physics-based model for CNT-FETs for computing the transfer and output characteristics. The model captures the observed phenomenology of CNT-FETs: (a) thermionic and tunnel emission through a Schottky barrier [1]; (b) ambipolar and bipolar conduction [2,3]; (c) ballistic transport [4]; (d) multimode propagation [5]; and (e) electrostatics dominated by the nanotube capacitance [6]. In the proposed model, the spatial band diagram along the nanotube consists of three parts: two injecting parts at the vicinity of the source and drain metallic contacts, and a midlength region where ballistic transport occurs. There are four operation modes depending on the presence of Schottky barriers for electrons and holes at the injecting parts. The Schottky barrier has been approximated by a triangular barrier, being the height determined by half the nanotube bandgap plus the workfunction difference between the source (drain) contact and the nanotube. The spatial band diagram at low drain-to-source bias in the midlength region is approximated by a plateau, being the position of this plateau essentially determined by the nanotube capacitance, which is supposed to dominate over the insulator capacitance (operation close to the quantum capacitance limit). The width of the Schottky barrier at high drain-to-source bias is calculated self-consistently with the injected carrier charge in the midlength region. The current is obtained by means of the Landauer formula for one-dimensional systems contacted with bulk reservoirs. The key information to compute the current is the transmission over all the energies. We have taken into account that multiple reflections can arise between both Schottky barriers at the interfaces, in the same way as a Fabry-Pérot resonator [7]. The proposed model has been tested against accurate self-consistent quantum mechanical simulations.
Fraud Detection of Credit Card Payment System by Genetic Algorithm

With an increase usage of credit cards for online purchases as well as regular purchases, causes a credit card fraud. In the mode of electronic payment system, fraud transactions are rising on the regular basis. The Modern techniques based on the Data Min- ing, Genetic Programming etc. has used in detecting fraudulent transactions. The technique of finding optimal solution for the problem and implicitly generate the results using genetic algorithm. The aim is to develop a method of generating test data and to detect fraudu- lent transaction with this algorithm. This algorithm is an optimization technique and evolutionary search based on the principles of genetic and natural selection, heuristic used to solve high complexity computational problems. This paper presents to find the detec- tion of credit card fraud mechanism and examines the result based on the principles of this algorithm. The benefit of detecting fraud is to clear for both credit card companies and their clients. The fraudulent transactions are not prevented from being cleared; the compa- ny must accept the financial cost of that transaction. This reduces the cost associated with higher interest rates, and its charges.
Augmented multi-user communication system

This paper presents improvements carried out to enhance the visual interaction of computer users in existing communication systems. It includes the usage of augmented reality techniques and the modification of a method for user model reconstruction according to particular requirements of such applications. Promised achievement is to prepare the background for further development of multi-user interface, videoconference or collaborative workspace.The aim of our research is replacing the standard computer interface components by equipment used in augmented reality and so immerse the user into augmented environment. Such approach allows to user positioning virtual objects in his workspace. One of possible techniques for precise virtual object pose evaluation widely used in augmented reality applications is to employ special tracking markers.Traditionally, communication systems of videoconference type represent a remote user using his sprite (plain, billboard-like) model. The lack of realistic appearance, when the participant is displayed as a sprite model, can be eliminated by its artificial reconstruction. The method gain depth information from knowledge of human anatomy and hence it is able to create the artificial relief model of the remote user.
Images and Spectra from the Interior of a Relativistic Fireball

The power-law decay of gamma-ray burst (GRB) afterglow can be well described by synchrotron emission from a relativistic spherical blast wave, driven by an expanding fireball. We calculate the spectrum and the light curve expected from an adiabatic blast wave which is described by the Blandford-McKee self-similar solution. These calculations include emission from the whole blast wave and not just from the shock front. We provide numerical corrections that can be used to modify simple analytic estimates of such emission. We find that the expected light curve and spectra are flat near the peak. This rules out the interpretation of the sharp optical peak observed in GRB 970508 as the peak of the light curve. We also calculate the observed image of an afterglow. This image could be resolved in future VLBI observations, and its structure could influence microlensing and scintillation. The observed image is ringlike: brighter near the edge and dimmer at the center. The image depends on the observed frequency. The contrast between the edge and the center increases and the ring becomes narrower at higher frequencies.
ROBUST GENERATION OF HIGH DYNAMIC RANGE IMAGES

High dynamic range images may be created by capturing multiple images of a scene with varying exposures. Images created in this manner are prone to ghosting artifacts, which appear if there is movement in the scene at the time of capture. This paper describes a novel approach to removing ghosting artifacts from high dynamic range images, without the need for explicit object detection and motion estimation. Weights are computed iteratively and then applied to pixels to determine their contribution to the final image. We use a non-parametric model for the static part of the scene, and a pixel’s membership in this model determines its weight. In contrast to previous approaches, our technique does not rely on explicit object detection, tracking, or pixelwise motion estimates. Ghost-free images of different scenes demonstrate the effectiveness of our technique.