Miracle-dz/UniFAR-FTUs huggingface dataset:
Chern-Simons Theory with Sources and Dynamical Quantum Groups I: Canonical Analysis and Algebraic Structures.

We study the quantization of Chern-Simons theory with group G coupled to dynamical sources. We first study the dynamics of Chern-Simons sources in the Hamiltonian framework. The gauge group of this system is reduced to the Cartan subgroup of G. We show that the Dirac bracket between the basic dynamical variables can be expressed in term of dynamical r matrix of rational type. We then couple minimally these sources to Chern-Simons theory with the use of a regularisation at the location of the sources. In this case, the gauge symmetries of this theory split in two classes, the bulk gauge transformation associated to the group G and world lines gauge transformations associated to the Cartan subgroup of G. We give a complete hamiltonian analysis of this system and analyze in detail the Poisson algebras of functions invariant under the action of bulk gauge transformations. This algebra is larger than the algebra of Dirac observables because it contains in particular functions which are not invariant under reparametrization of the world line of the sources. We show that the elements of this Poisson algebra have Poisson brackets expressed in term of dynamical r matrix of trigonometric type. This algebra is a dynamical generalization of Fock-Rosly structure. We analyze the quantization of these structures and describe different star structures on these algebras, with a special care to the case where G = SL(2, R) and G = SL(2, C)R, having in mind to apply these results to the study of the quantization of massive spinning point particles coupled to gravity with a cosmological constant in 2+1 dimensions.
Multiple targets’ detection in terms of Keystone transform at the low SNR level

In pulse Doppler (PD) radar, a novel motion compensation method based on keystone transform is proposed for handling with the data of a low signal-to-noise ratio (SNR). The keystone transform is used to correct the linear range migration which results from the radial velocity of targets. The SNR is improved through coherently accumulating all pulses. The simulation results show that the performance of the method based on keystone transform is better than that of the conventional coherent integration method using fast Fourier transform (FFT).
A Discriminative Model for Learning Semantic and Geometric Interactions in Indoor Scenes

Visual scene understanding is a difficult problem, interleaving object detection, geometric reasoning and scene classification. Consider the scene in Fig. 1. (a). A scene classifier will tell you, with some uncertainty, that this is a dining room [6, 3]. A layout estimator [5, 7] will tell you, with different uncertainty, how to fit a box to the room. An object detector [8, 4] will tell you, with large uncertainty, that there is a dining table and four chairs. Each algorithm provides important but uncertain and incomplete piece of information. This is because the scene is cluttered with objects which tend to occlude each other: the dining table occludes the chairs, the chairs occlude the dining table; all of these occlude the room layout components (i.e. the walls and floor).
Production and perception of emotional prosody : the case of autism and Parkinson's disease

The current study aims to investigate the acoustic correlates of the production and perception in emotional and attitudinal prosody of Taiwan Mandarin-speaking adolescents with autism (ASD) and Parkinson’s disease (PD) patients. It has been widely accepted among speech therapists that, although from very different aetiologies, individuals with ASD or PD speak with deviant prosodic patterns, monopitch, wrong stress, and greater difficulties in expressing emotions through prosody, while their perception of emotion and attitude is also jeopardised. However, when comparing their performance with their respective peers, results from previews studies have been far from consistent, ranging from significantly poorer to similar performance level. This disparity in findings may emerge from disease severity, task type, and research method. Therefore, in the present study, these issues were systematically controlled. Only individuals with mild to moderate ASD or PD were included in the experimental groups. Synthetic speech was used to generate auditory stimuli for the perceptual tasks, allowing precise manipulations of acoustic parameters. The use of designed sentences to elicit speech provided better comparison across speakers. The major innovation of this study is the use of bio-informational dimension (BID) theory as the theoretical framework. BID dimensions include body-size projection, dynamicity, audibility and association. Body-size projection associates high pitch with submissiveness, friendliness, politeness, vulnerability, and low pitch with dominance, confidence, protection, aggressiveness. This research paradigm has been proven to be effective in several studies examining the perception of emotional prosody. The hypotheses of the present study were made based on body-size projection. The main findings of this study include 1) adolescents with ASD and PD patients performed poorer than their controls in the perceptual judgement of emotional and attitudinal prosody; 2) only their expressive skills in emotional prosody was comparable to their controls; 3) their expressive skills in attitudinal prosody was worse than their controls.
Performance analysis of single Bluetooth piconet in error-prone environments

This paper analyzes the performance of a Bluetooth piconet in error-prone environments. A statistical characterization of a waiting time, an end-to-end delay, and a goodput are derived analytically in terms of the arrival rates, the number of slaves, and the packet error rate (PER). For simplicity, half-symmetric piconet is assumed in this analysis. Both exhaustive and limited scheduling are considered. The analytic results are validated by simulations.
Fast motion deblurring

This paper presents a fast deblurring method that produces a deblurring result from a single image of moderate size in a few seconds. We accelerate both latent image estimation and kernel estimation in an iterative deblurring process by introducing a novel prediction step and working with image derivatives rather than pixel values. In the prediction step, we use simple image processing techniques to predict strong edges from an estimated latent image, which will be solely used for kernel estimation. With this approach, a computationally efficient Gaussian prior becomes sufficient for deconvolution to estimate the latent image, as small deconvolution artifacts can be suppressed in the prediction. For kernel estimation, we formulate the optimization function using image derivatives, and accelerate the numerical process by reducing the number of Fourier transforms needed for a conjugate gradient method. We also show that the formulation results in a smaller condition number of the numerical system than the use of pixel values, which gives faster convergence. Experimental results demonstrate that our method runs an order of magnitude faster than previous work, while the deblurring quality is comparable. GPU implementation facilitates further speed-up, making our method fast enough for practical use.
Performance-Aware Workflow Management for Grid Computing

Grid middleware development has advanced rapidly over the past few years to support component-based programming models and service-oriented architectures. This is most evident with the forthcoming release of the Globus toolkit (GT4), which represents a convergence of concepts (and standards) from both the grid and web-services communities. Grid applications are increasingly modular, composed of workflow descriptions that feature both resource and application dynamism. Understanding the performance implications of scheduling grid workflows is critical in providing effective resource management and reliable service quality to users. This paper describes a series of extensions to an existing performance-aware grid management system (TITAN). These extensions provide additional support for workflow prediction and scheduling using a multi-domain performance management infrastructure.
Selection and Monetary Non-Neutrality in Time-Dependent Pricing Models

For a given frequency of price adjustment, monetary non-neutrality is smaller if older prices are disproportionately more likely to change. Selection for the age of prices provides a complete characterization of price-setting frictions in time-dependent models. Selection for older prices is weaker and non-neutralities are larger if the hazard function of price adjustment is less strongly increasing. Selection is weaker if there is heterogeneity in price stickiness. Finally, selection is weaker if durations of price spells are more variable. In particular, the Taylor (1979) model exhibits maximal selection for older prices, whereas the Calvo (1983) model exhibits no selection.
Using genetically optimized artificial intelligence to improve gameplaying fun for strategical games

Fun in computer games depends on many factors. While some factors like uniqueness and humor can only be measured by human subjects, in a strategical game, the rule system is an important and measurable factor. Classics like chess and GO have a millennia-old story of success, based on clever rule design. They only have a few rules, are relatively easy to understand, but still they have myriads of possibilities. Testing the deepness of a rule-set is very hard, especially for a rule system as complex as in a classic strategic computer game. It is necessary, though, to ensure prolonged gaming fun. In our approach, we use artificial intelligence (AI) to simulate hours of beta-testing the given rules, tweaking the rules to provide more game-playing fun and deepness. To avoid making the AI a mirror of its programmer's gaming preferences, we not only evolved the AI with a genetic algorithm, but also used three fundamentally different AI paradigms to find boring loopholes, inefficient game mechanisms and, last but not least, complex erroneous behavior.
Hybrid models for future event prediction

We present a hybrid method to turn off-the-shelf information retrieval (IR) systems into future event predictors. Given a query, a time series model is trained on the publication dates of the retrieved documents to capture trends and periodicity of the associated events. The periodicity of historic data is used to estimate a probabilistic model to predict future bursts. Finally, a hybrid model is obtained by intertwining the probabilistic and the time-series model. Our empirical results on the New York Times corpus show that autocorrelation functions of time-series suffice to classify queries accurately and that our hybrid models lead to more accurate future event predictions than baseline competitors.
P rogrammable Floating Gate Transistor Operating as a Resistor for Analog Applications

Th is paper presents a programmable resistor using two-input floating gate MOS transistor (FGMOST). One of the two-input gates is connected to the drain and the other is connected to a tuned voltage to control the floatin g gate transistor resistance. A wide range of the programmable resistance is achieved by controlling the tuned voltage. The resistance is changed by 33% by varying the tuned voltage by 0.4 V. Three applicat ions based on FGMOST operated as a resistor are proposed. These are tunable filter, tunable triangular oscillator and tunable amp lifier. The cut-off frequency of the low-pass filter is tuned fro m 21.4 kHz to 32.1 kHz by controlling the tuned voltage by 0.4 V. The oscillation frequency of the triangular oscillator is varied fro m 336.18 kHz to 540.2 kHz by varying the tuned voltage by 0.4. A lso, the gain of the amplifier is changed by 50% by changing the tuned voltage by 0.4 V.
Functional implication of BAFF synthesis and release in gangliosides‐stimulated microglia

BAFF is a recently identified member of the TNF ligand superfamily that plays a critical role in B cell differentiation, survival, and regulation of Ig production. In the present study, we examined whether BAFF is expressed in microglia, and the expression and release of BAFF are regulated by gangliosides. The results showed that BAFF was expressed and released in rat primary microglia as well as in BV‐2 cells. Furthermore, its expression and release were increased by gangliosides stimulation and regulated by JAK‐STAT, especially the STAT1‐ and STAT3‐dependent signaling pathways. It was of particular interest to observe that SP600125 and SB203580, specific inhibitors of JNK and p38, did not inhibit BAFF synthesis but inhibited the release of sBAFF in gangliosides‐treated cells by regulating furin expression, suggesting that the JNK and p38 signaling pathways regulate the release but not the synthesis of BAFF. Moreover, BV‐2 cells expressed BAFF‐R on their cell surface, and rat primary microglia expressed BAFF‐R and TACI on their cell surface. rBAFF increased the release of cytokines, especially IL‐6, TNF‐α, and IL‐10, in rat primary microglia as well as in BV‐2 cells. These findings imply that BAFF secreted by microglia may play important roles in CNS inflammation by regulating microglia as well as infiltrated B cells.
Atomic Congestion Games on Graphs and Their Applications in Networking

In this paper, we introduce and analyze the properties of a class of games, the atomic congestion games on graphs (ACGGs), which is a generalization of the classical congestion games. In particular, an ACGG captures the spatial information that is often ignored in a classical congestion game. This is useful in many networking problems, e.g., wireless networks where interference among the users heavily depends on the spatial information. In an ACGG, a player's payoff for using a resource is a function of the number of players who interact with it and use the same resource. Such spatial information can be captured by a graph. We study fundamental properties of the ACGGs: under what conditions these games possess a pure strategy Nash equilibrium (PNE), or the finite improvement property (FIP), which is sufficient for the existence of a PNE. We show that a PNE may not exist in general, but that it does exist in many important special cases including tree, loop, or regular bipartite networks. The FIP holds for important special cases including systems with two resources or identical payoff functions for each resource. Finally, we present two wireless network applications of ACGGs: power control and channel contention under IEEE 802.11.
Towards Privacy in a Context-Aware Social Network Based Recommendation System

Previous work has reported on `Instant Knowledge', a context-aware social networking based recommendation system for enterprise. This paper outlines a hierarchical privacy architecture, to provide anonymity, unlink ability, unobservability and pseudonymity to IK users. Users are grouped according to `proportional distance reservation', which indicates how likely users are willing to share private information. The protection of private information is stronger when queries are made by `distant' users, and weaker for fellow group members.
Quantitative T2 Magnetic Resonance Imaging Compared to Morphological Grading of the Early Cervical Intervertebral Disc Degeneration: An Evaluation Approach in Asymptomatic Young Adults

Objective The objective of this study was to evaluate the efficacy of quantitative T2 magnetic resonance imaging (MRI) for quantifying early cervical intervertebral disc (IVD) degeneration in asymptomatic young adults by correlating the T2 value with Pfirrmann grade, sex, and anatomic level. Methods Seventy asymptomatic young subjects (34 men and 36 women; mean age, 22.80±2.11 yr; range, 18–25 years) underwent 3.0-T MRI to obtain morphological data (one T1-fast spin echo (FSE) and three-plane T2-FSE, used to assign a Pfirrmann grade (I–V)) and for T2 mapping (multi-echo spin echo). T2 values in the nucleus pulposus (NP, n = 350) and anulus fibrosus (AF, n = 700) were obtained. Differences in T2 values between sexes and anatomic level were evaluated, and linear correlation analysis of T2 values versus degenerative grade was conducted. Findings Cervical IVDs of healthy young adults were commonly determined to be at Pfirrmann grades I and II. T2 values of NPs were significantly higher than those of AF at all anatomic levels (P<0.000). The NP, anterior AF and posterior AF values did not differ significantly between genders at the same anatomic level (P>0.05). T2 values decreased linearly with degenerative grade. Linear correlation analysis revealed a strong negative association between the Pfirrmann grade and the T2 values of the NP (P = 0.000) but not the T2 values of the AF (P = 0.854). However, non-degenerated discs (Pfirrmann grades I and II) showed a wide range of T2 relaxation time. T2 values according to disc degeneration level classification were as follows: grade I (>62.03 ms), grade II (54.60–62.03 ms), grade III (<54.60 ms). Conclusions T2 quantitation provides a more sensitive and robust approach for detecting and characterizing the early stage of cervical IVD degeneration and to create a reliable quantitative in healthy young adults.
Uniform Sampling for Matrix Approximation

Random sampling has become a critical tool in solving massive matrix problems. For linear regression, a small, manageable set of data rows can be randomly selected to approximate a tall, skinny data matrix, improving processing time significantly. For theoretical performance guarantees, each row must be sampled with probability proportional to its statistical leverage score. Unfortunately, leverage scores are difficult to compute. A simple alternative is to sample rows uniformly at random. While this often works, uniform sampling will eliminate critical row information for many natural instances. We take a fresh look at uniform sampling by examining what information it does preserve. Specifically, we show that uniform sampling yields a matrix that, in some sense, well approximates a large fraction of the original. While this weak form of approximation is not enough for solving linear regression directly, it is enough to compute a better approximation. This observation leads to simple iterative row sampling algorithms for matrix approximation that run in input-sparsity time and preserve row structure and sparsity at all intermediate steps. In addition to an improved understanding of uniform sampling, our main proof introduces a structural result of independent interest: we show that every matrix can be made to have low coherence by reweighting a small subset of its rows.
Alleviating the Impact of Coincidental Correctness on the Effectiveness of SFL by Clustering Test Cases

Spectrum-based fault localization techniques leverage coverage information to identify the faulty elements of the program via passed and failed runs. However, the effectiveness of these techniques can be affected adversely by coincidental correctness, which occurs when faulty elements are executed, but the program produces the correct output. This paper proposes a clustering-based strategy to improve the effectiveness of spectrum-based fault localization. The basis of this strategy is that test cases in the same cluster have similar behaviors. Our experimental results show that, the percentage of clusters that contain coincidentally correct test cases in clusters which do not contain failed test cases, is usually smaller than the percentage of coincidentally correct test cases in passed test cases. By clustering test cases and reconstructing the coverage matrix, our extensive experiments demonstrated that the fault-localization accuracy of Spectrum-based fault localization techniques can be effectively improved.
Exploring the sensitivity of current and future experiments to

The first results from the KamLAND experiment in conjunction with the global solar neutrino data has demonstrated striking ability to constrain them 2 (�m 2 ) very pre- cisely. However the allowed range of �� (�12) did not change much with the inclusion of the KamLAND results. In this paper we probe if future data from KamLAND can increase the accuracy of the allowed range in �� and conclude that even after 3 kton-year of statistics and most optimistic error estimates, KamLAND may find it hard to significantly improve the bounds on the mixing angle obtained from the solar neutrino data. We discuss the �12 sensitivity of the survival probabilities in matter (vacuum) as is relevant for the solar (Kam- LAND) experiments. We find that the presence of matter effects in the survival probabilities for 8 B neutrinos give the solar neutrino experiments SK and SNO an edge over KamLAND, as far as �12 sensitivity is concerned, particularly near maximal mixing. Among solar neu- trino experiments we identify SNO as the most promising candidate for constraining �12 and make a projected sensitivity test for the mixing angle by reducing the error in the neutral current measurement at SNO. Finally we argue that the most accurate bounds on �12 can be achieved in a reactor experiment, if the corresponding baseline and energy can be tuned to a minimum in the survival probability. We propose a new reactor experiment which can give the value of tan 2 �12 to within 14%. We also discuss the future Borexino and LowNu experiments.
Learning probabilistic classifiers under computational resource constraints

In many online applications of machine learning, the computational resources available will vary from time-to-time. Surprisingly, existing techniques are designed to accommodate the minimum expected resources, and fail to utilize further resources when they are available. This paper presents an analysis of the relevant categories of computational resource involved, and presents an algorithm that starts with the classification time and accuracy of naive Bayes and can utilize increasing amounts of time to increase classification accuracy.
Modal logic as a design notation

A notation to describe software system designs is given, together with the means to verify properties over them. Designs are considered as models of a modal logic. The procedure to derive the modal model associated to a design, the algorithm to check properties over a model, the method to define new relations and the method of model filtration are presented. The proposed logic (KPI, a poly-modal logic with inverse operators) is used as a property specification language verified through a model checking algorithm. The methods provided proved to be effective and simple to implement. A prototype tool has been developed in SML-NJ covering all functionalities described.
Entities, Topics and Events in Community Memories (cid:63)

This paper brieﬂy describes the components of the ARCOMEM architecture concerned with the extraction, enrichment, consolidation and dynamics analysis of entities, topics and events, deploying text mining, NLP, and semantic data integration technologies. In particular, we focus on four main areas relevant to support the ARCOMEM requirements and use cases: (a) entity and event extraction from text; (b) entity and event enrichment and consolidation; (c) topic detection and dynamics; and (d) temporal aspects and dynamics detection in Web language and online social networks.