Miracle-dz/UniFAR-FTUs huggingface dataset:
Developing the Construct of General Self-Efficacy1

The theory of general self-efficacy is still in the early stages of development. There are few scales designed to measure increments of general self-efficacy, and the research on these scales and general self-efficacy is only slowly increasing. The challenge of general self-efficacy theory is that the construct is global unlike Bandura's 1977 theory of specific self-efficacy. Self-efficacy began as a domain-rooted construct and was easily operationalized and studied. General self-efficacy is less developed and its potential has yet to be fully realized. The purpose of this article was to summarize the literature on self-efficacy, both in its specific form and in its general form. The definitions of specific and general self-efficacy are made clear as well as their conceptualized relationship.
Ommeren Non-parametric Smoothing Improving Adaptive Importance Sampling Simulation of Markovian Queueing Models using

Previous work on state-dependent adaptive importance sampling techniques for the simulation of rare events in Markovian queueing models used either no smoothing or a parametric smoothing technique, which was known to be non-optimal. In this paper, we introduce the use of kernel smoothing in this context. We derive expressions for the smoothed transition probabilities, compare several variations of the technique, and explore the choice of kernel width. We provide some examples, demonstrating that the technique significantly improves convergence and estimator variance.
Pilotless Frame Synchronization for LDPC-Coded Transmission Systems

We present a pilotless frame synchronization approach that exploits feedback from a low-density parity-check (LDPC) code decoder. The synchronizer is based on syndrome checks using hard decisions from the channel observations. The bandwidth overhead associated with pilot symbols in conventional receiver architectures is eliminated while providing sufficient synchronization performance. An LDPC decoder coupled with our synchronizer exhibits negligible frame error rate degradation over a system with perfect synchronization. The complexity of the frame synchronizer is kept relatively low due to its XOR-based approach.
What or Who is Multilingual Watson?

IBM Watson is an intelligent open-domain question answering system capable of answering questions posed in natural language. However, the system originally developed to compete against human players on Jeopardy! is heavily reliant on English language components, such as the English Slot Grammar parser, which impacts multilingual extensibility and scalability. This paper presents a working prototype for a multilingual Watson, introducing the major challenges encountered and their proposed solutions.
Structural Change and the Kaldor Facts of Economic Growth

We present a model in which two of the most important features of the long-run growth process are reconciled: the massive changes in the structure of production and employment; and the Kaldor facts of economic growth. We assume that households expand their consumption along a hierarchy of needs and firms continuously introduce new products. In equilibrium industries with an expanding and those with a declining employment share co-exist, and each such industry goes (or has already gone) through a cycle of take-off, maturity, and stagnation. Nonetheless macroeconomic aggregates grow pari passu at a constant rate.
Wave propagation and sampling theory—Part II: Sampling theory and complex waves

Morlet et al (1982, this issue) showed the advantages of using complex values for both waves and characteristics of the media. We simulated the theoretical tools we present here, using the Goupillaud-Kunetz algorithm. Now we present sampling methods for complex signals or traces corresponding to received waves, and sampling methods for complex characterization of multilayered or heterogeneous media. Regarding the complex signals, we present a twodimecsional(2-D) method of sampling in the time-frequency domain using a special or “extended” Gabor expansion on a set of basic wavelets adapted to phase preservation. Such a 2-D expansion permits us to handle in a proper manner instantaneous frequency spectra. We show the differences between “wavelet resolution” and “sampling grid resolution. ” We also show the importance of phase preservation in high-resolution seismic. Regarding the media, we show how analytical studies of wave propagation in periodic structured layers could help when trying to characterize the physical properties of the layers and their large scale granularity as a result of complex deconvolution. Analytical studies of wave propagation in periodic structures are well known in solid state physics, and lead to the so-called “Bloch waves. ” The introduction of complex waves leads to replacing the classical wave equation by a Schriidinger equation. Finally, we show that complex wave equations, Gabor expansion, and Bloch waves are three different ways of ‘introducing the tools of quantum mechanics in highresolution seismic (Gabor, 1946; Kittel, 1976, Morlet, 1975). And conversely, the Goupillaud-Kunetz algorithm and an extended Gabor expansion may be of some use in solid state physics.
An Artificial Behavioral Immune System for cognitive robotics

The paper proposes the implementation of an artificial behavioral immune system (ABIS) that could be integrated on a robotic platform. The ultimate goal is to have a form of perceptual processing to create the sensation of disgust (on more in general of discomfort) that may influence the behavior that is determined by the cognitive modules. The present work, being oriented to human-robot interaction, is focused on perceptual processing of facial expression, and speech recognition. As regards the first aspect, the human face closer to the robot is detected, then facial features are extracted, and finally a vector of data which has an emotional valence linked to expression is determined. The speech is processed to recognize the individual words and the moods using a ”sentiment analysis” technique. An artificial immune system is used to recognize positive and negative ”feelings” that cames from interactions and generate the signal of discomfort. For training and validation we used a few human subjects and sequences of a fairy tale.
Airport Mobile Information Access with Spoken Query over Wireless Networks

The today's mobile communication networks and modern end-user devices provide an access to the Internet while on the move. The paper builds a model of airport mobile information service accessibility with spoken query. A system is developed and tested through the prototype that applies state-of-the-art Speech Recognition with robust feature extraction and knowledge-based Information Retrieval processing for spoken query. The model adopts a traditional Client-Server architecture. For the Server part, a speak recognizer system is implemented on the basis of ETSI standard DSR front-end with cepstral mean subtraction (CMS) method combined with CW and cepstral derivatives; and a knowledge-based Information extraction solution is developed for fast retrieval of the most relevant documents. For the Client part, a Graphical User Interface (GUI) is designed to show the focused part of the query result. The two parts are integrated into a full spoken query system. The system has the flexibility for being ported to any airport.
Milestone Age Affects the Role of Health and Emotions in Life Satisfaction: A Preliminary Inquiry

Jill turns 40. Should this change how she evaluates her life, and would a similar change occur when she turns 41? Milestone age (e.g., 30, 40, 50)—a naturally occurring feature in personal timelines—has received much attention is popular culture, but little attention in academic inquiry. This study examines whether milestone birthdays change the way people evaluate their life. We show that life outlook is impacted by this temporal landmark, which appears to punctuate people’s mental maps of their life cycle. At these milestone junctures, people take stock of where they stand and have a more evaluative perspective towards their lives when making life satisfaction judgments. Correspondingly, they place less emphasis on daily emotional experiences. We find that milestone agers (vs. other individuals) place greater weight on health satisfaction and BMI and lesser weight on daily positive emotions in their overall life satisfaction judgments, whereas negative emotions remain influential.
Multifunctional approach of L-Dopa induced dyskinesia pathophysiology in Parkinson’s disease : from the striatum to the whole brain

The gold standard treatment for Parkinson’s disease (PD) remains the dopamine precursor L- 3,4-dihydroxyphenylalanine (L-Dopa). Long-term L-Dopa treatment systematically leads to abnormal involuntary movements (AIMs) called L-Dopa-induced dyskinesia (LID). These manifestations first led to investigate the neuronal dysfunctions in the motor regions of thebasal ganglia and unravelled an overexpression of ΔFosB, ARC, Zif268 and FRA2 immediate-early genes (IEG) in the dopamine-depleted striatum of dyskinetic rats. However, other several dopaminoceptive structures, likely affected by the exogenously produced dopamine, have been neglected although they might play a key role in mediating LID. Hence, we assessed the expression of ΔFosB, ARC, FRA2 and Zif268 IEGs in the whole brain of dyskinetic rats compared to non-dyskinetic ones. Such approach shed light notably upon 9 structures located outside of the basal ganglia displaying an IEG overexpression. Among them, the dorsolateral bed nucleus of the stria terminalis (dlBST) and the lateralhabenula (LHb) displayed a significant correlation between ΔFosB expression and LID severity. We therefore postulated that these structures might play a role in LID manifestation. Therefore, to assess dlBST and LHb causal roles upon LID severity, we inhibited the electrical activity of FosB/ΔFosB-expressing neurons using the selective Daun02/β- galactosidase inactivation method that we previously validated in a well known structure involve in LID: the striatum. Interestingly, the inactivation of dlBST and LHb ΔfosBexpressing neurons alleviated LID severity and increased the beneficial effect of L-Dopa in dyskinetic rats. Remarkably, BST involvement in LID was confirmed in the gold standard model of LID, the dyskinetic MPTP-lesioned macaque. Altogether, our results highlight for the first time the functional involvement of 2 structures.
Detection of Cross-Channel Anomalies from Multiple Data Channels

We identify and formulate a novel problem: cross channel anomaly detection from multiple data channels. Cross channel anomalies are common amongst the individual channel anomalies, and are often portent of significant events. Using spectral approaches, we propose a two-stage detection method: anomaly detection at a single-channel level, followed by the detection of cross-channel anomalies from the amalgamation of single channel anomalies. Our mathematical analysis shows that our method is likely to reduce the false alarm rate. We demonstrate our method in two applications: document understanding with multiple text corpora, and detection of repeated anomalies in video surveillance. The experimental results consistently demonstrate the superior performance of our method compared with related state-of-art methods, including the one-class SVM and principal component pursuit. In addition, our framework can be deployed in a decentralized manner, lending itself for large scale data stream analysis.
Simulation of 3G DCHs supporting TCP traffic: design, experiments and insights on parameter tuning

This paper describes a simulator of dedicated channels in 3G radio access networks, with TCP traffic. The design principles of this simulator and the experiments performed in it are explained in depth. We provide specific implementation details of RLC functions in OMNeT++. The main objective of the simulator is RLC parameter configuration. Although many previous works have addressed this issue, our approach is different and more general: we investigate how the conditions of the environment (channel data rate, frame error ratio, Doppler frequency, etc) affect the proper adjustment of each parameter. We disclose the interactions between these conditions and the functionalities of RLC, achieving a methodology for robust RLC configuration in terms of suitable operation under changes in the environment.
Automatic Error Detection concerning the Definite and Indefinite Conjugation in the HunLearner Corpus

In this paper we present the results of automatic error detection, concerning the definite and indefinite conjugation in the extended version of the HunLearner corpus, the learners corpus of the Hungarian language. We present the most typical structures that trigger definite or indefinite conjugation in Hungarian and we also discuss the most frequent types of errors made by language learners in the corpus texts. We also illustrate the error types with sentences taken from the corpus. Our results highlight grammatical structures that might pose problems for learners of Hungarian, which can be fruitfully applied in the teaching and practicing of such constructions from the language teachers or learners point of view. On the other hand, these results may be exploited in extending the functionalities of a grammar checker, concerning the definiteness of the verb. Our automatic system was able to achieve perfect recall, i.e. it could find all the mismatches between the type of the object and the conjugation of the verb, which is promising for future studies in this area.
Feature Extraction and Detection of Simple Objects Using Particle Swarm Optimisation

The purpose of this paper is to demonstrate the application of particle swarm optimisation to the detection of simple objects. The paper’s new contribution to object detection is application of particle swarm optimisation for extraction of geometric properties of an object in an image for accurate recognition especially in noisy environments. In this approach, the edges and the corners of an object are detected by particle swarm optimisation algorithm and then the object is classified based on number of the corners and attributes of the edges by a simple fuzzy rule-based classifier. Several simple geometric objects in different aspects have been used in the variety of noise levels for testing of the system. This system can categorise images containing these simple objects even with high noise levels more accurately in contrast to other approaches proposed in the last literature.
The hidden treasure in your data: phasing with unexpected weak anomalous scatterers from routine data sets

Single wavelength anomalous dispersion (SAD) utilizing anomalous signal from native sulfurs, or other atoms with Z≤20, generally requires highly redundant data collected with relatively long wavelength X-rays. Here we present experiences with two proteins, where anomalous signal from serendipitously acquired surface bound calcium atoms with data redundancy as low as 10 was utilized to drive de novo structure determination. In both the cases, the calcium atoms were acquired from the crystallization solution, and data collection strategy was not optimized for exploiting the anomalous signal from these scatterers. The X-ray data were collected at 0. 98Å in one case and at 1. 74Å in the other (wavelength optimized for sulfur but anomalous signal from Ca was exploited for structure solution). Similarly, using a test case, we show that the data collected at ~1. 0Å wavelength, where the f" value for sulfur is 0.28e, is sufficient for structure determination using intrinsic sulfur atoms from a strongly diffracting crystal. Interestingly, it was also observed that SHELXD was capable of generating a substructure solution from high-exposure data with a completeness of 70% for low-resolution reflections extending to 3. 5Å, with relatively low redundancy (i.e., 6.0 fold). Considering the fact that many crystallization conditions contain anomalous scatterers such as Cl, Ca, Mn etc., it appears that the data from well diffracting crystals should be processed, with anomalous pairs kept separate, so as to detect any fortuitous signal that might be present, which could prove useful in either solving the structure de novo or in accurately assigning surface bound atoms.
Well-Behaved Model Transformations with Model Subtyping

In model-driven engineering, models abstract the relevant features of software artefacts and model transformations act on them automating complex tasks of the development process. It is, thus, crucially important to provide pragmatic, reliable methods to verify that model transformations guarantee the correctness of generated models in order to ensure the quality of the final end product. In this paper, we build on an object-oriented algebraic encoding of metamodels and models as defined in the standard Meta-Object Facility and in tools, such as the Eclipse Modeling Framework, to specify a domain-specific language for representing the action part of model transformations. We introduce the big-step operational structural semantics of this language and its type system, which includes a notion of polymorphic model subtyping, showing that well-typed model transformations are well behaved. That is, that metamodel-conformant model transformations never go wrong.
Porting an Open Information Extraction System from English to German

Many downstream NLP tasks can benefit from Open Information Extraction (Open IE) as a semantic representation. While Open IE systems are available for English, many other languages lack such tools. In this paper, we present a straightforward approach for adapting PropS, a rule-based predicate-argument analysis for English, to a new language, German. With this approach, we quickly obtain an Open IE system for German covering 89% of the English rule set. It yields 1.6 extractions per sentence with 60% precision, making it readily usable in downstream applications.
A probabilistic definition of item similarity

In item-based collaborative filtering, a critical intermediate step to personalized recommendations is the definition of an item-similarity metric. Existing algorithms compute the item-similarity using the user-to-item ratings (cosine, Pearson, Jaccard, etc.). When computing the similarity between two items A and B many of these algorithms divide the actual number of co-occurring users by some "difficulty" of co-occurrence. We refine this approach by defining item similarity as the ratio of the actual number of co-occurrences to the number of co-occurrences that would be expected if user choices were random. In the final step of our method to compute personalized recommendations we apply the usage history of a user to the item similarity matrix. The well defined probabilistic meaning of our similarities allows us to further improve this final step. We measured the quality of our algorithm on a large real-world data-set. As part of Comcast's efforts to improve its personalized recommendations of movies and TV shows, several top recommender companies were invited to apply their algorithms to one year of Video-on-Demand usage data. Our algorithm tied for first place. This paper includes a MapReduce pseudo code implementation of our algorithm.
Behavioral Biases in Interpersonal Contexts

markdownabstractThis thesis presents evidence suggesting that the same types of biases in individual decision making under uncertainty pertain in interpersonal contexts. The chapters above demonstrate in specific contexts how specific interpersonal factors attenuate, amplify, or replicate these biases. One of the most natural interpersonal contexts is group decision making. The group effects on decisions consist of aggregation and communication, and disentangling these could help us improve our understanding of the group decision making process and make better predictions. Because the two measures of rationality applied in Chapter 2, namely stochastic dominance and EU-compliance, are both dichotomous, we use the simulated decisions from pure voting as benchmarks to isolate the communication effects. Chapter 3 describes how simple pieces of information were provided to individuals, with the aim of helping them evaluate the quality of the estimates they received in interpersonal communication. Chapter 4 extends Yaari's definition of comparative risk aversion to enable comparisons between people holding different beliefs. The last chapter presents evidence that the mere presentation with cash could make a substantial psychological impact on people's risk attitudes by changing their likelihood insensitivity in probability weighting. The cash effects that lower valuations could potentially come from a buyer's evolutionary instinct in bargaining triggered by cash. Testing the existence of such instincts and, if they exist, finding what triggers them could be complementary to the current study.
A New Fast and Robust Method Based on Head Detection for People-Flow Counting System

This paper presents an implementation method for the people counting system which detects and tracks moving people using a fixed single camera. The main contribution of this paper is the novel head detection method based on body's geometry. A novel body descriptor is proposed for finding people's head which is defined as Body Feature Rectangle (BFR). First, a vertical projection method is used to get the line which divides touching persons into individuals. Second, a special inscribed rectangle is found to locate the neck position which describes the torso area. Third, locations of people's heads can be got according to its neck-positions. Last, a robust counting method named MEA is proposed to get the real counts of walking people flows. The proposed method can divide the multiple-people image into individuals whatever people merge with each other or not. Moreover, the passing people can be counted accurately under the influence of wearing hats. Experimental results show that our proposed method can nearly reach to an accuracy of 100% if the number of a people-merging pattern is less than six. Keywords-People Counting; Head Detection; BFR; People-flow Tracking
Galaxy distribution and evolution around a sample of 2dF groups

Context. We study galaxy evolution and spatial patterns in the surroundings of a sample of 2dF groups. Aims. Our aim is to find evidence of galaxy evolution and clustering out to 10 times the virial radius of the groups and so redefine their properties according to the spatial patterns in the fields and relate them to galaxy evolution. Methods. Group members and interlopers were redefined after the identification of gaps in the redshift distribution. We then used exploratory spatial statistics based on the the second moment of the Ripley function to probe the anisotropy in the galaxy distribution around the groups. Results. We found an important anticorrelation between anisotropy around groups and the fraction of early-type galaxies in these fields. Our results illustrate how the dynamical state of galaxy groups can be ascertained by the systematic study of their neighborhoods. This is an important achievement, since the correct estimate of the extent to which galaxies are affected by the group environment and follow large-scale filamentary structure is relevant to understanding the process of galaxy clustering and evolution in the Universe.