Miracle-dz/UniFAR-FTUs huggingface dataset:
Front Vehicle Detection and Distance Estimation Using Single-Lens Video Camera

This paper is dedicated to the front vehicle detection and its distance estimation using one single-lens car video camera on the urban & suburb road roads. The proposed method mainly consists of road area detection and the front vehicle detection & distance calculation. Firstly, Hough transform is used to detect lines in which the appropriate straight lines are selected and their intersection points are exploited for obtaining the vanishing point. Then, both strong right and left edges are extracted and connected to the vanishing point for segmenting the road area, and on such area the bottom shadow of the front vehicle is utilized to locate the vehicle's position. Finally, the distance between the host vehicle and the front vehicle is calculated based on the position of a vehicle and the vanishing point. Experimental results show that the proposed technique can moderately detect the front vehicles on the urban & suburb roads with detection rate of 78% at least.
Large Time Behavior of Solutions to SemiLinear Equations with Quadratic Growth in the Gradient

This paper studies the large time behavior of solutions to semilinear Cauchy problems with quadratic nonlinearity in gradients. The Cauchy problem considered has a general state space and may degenerate on the boundary of the state space. Two types of large time behavior are obtained: (i) pointwise convergence of the solution and its gradient and (ii) convergence of solutions to associated backward stochastic differential equations. When the state space is $\mathbb{R}^d$ or the space of positive definite matrices, both types of convergence are obtained under growth conditions on coefficients. These large time convergence results have direct applications in risk-sensitive control and long-term portfolio choice problems.
A Neural Probabilistic Structured-Prediction Method for Transition-Based Natural Language Processing

We propose a neural probabilistic structured-prediction method for transition-based natural language processing, which integrates beam search and contrastive learning. The method uses a global optimization model, which can leverage arbitrary features over non-local context. Beam search is used for efficient heuristic decoding, and contrastive learning is performed for adjusting the model according to search errors. When evaluated on both chunking and dependency parsing tasks, the proposed method achieves significant accuracy improvements over the locally normalized greedy baseline on the two tasks, respectively.
Relation Theoretic Common Fixed Point Results for Generalized Weak Nonlinear Contractions with an Application

In this paper, by introducing the concept of generalized Ćirić-type weak ( ϕ g , R ) -contraction, we prove some common fixed point results in partial metric spaces endowed with binary relation R . We also deduce some useful consequences showing the usability of our results. Finally, we present an application to establish the solution of a system of integral equations.
Relations between invasion percolation and critical percolation in two dimensions.

We study invasion percolation in two dimensions. We compare connectivity properties of the origin’s invaded region to those of (a) the critical percolation cluster of the origin and (b) the incipient infinite cluster. To exhibit similarities, we show that for any k ≥ 1, the k-point function of the first socalled pond has the same asymptotic behavior as the probability that k points are in the critical cluster of the origin. More prominent, though, are the differences. We show that there are infinitely many ponds that contain many large disjoint pc-open clusters. Further, for k> 1, we compute the exact decay rate of the distribution of the radius of the kth pond and see that it differs from that of the radius of the critical cluster of the origin. We finish by showing that the invasion percolation measure and the incipient infinite cluster measure are mutually singular.
A Sampling-Based Heuristic for Tree Search Applied to Grammar Induction

In the field of Operation Research and Artificial Intelligence, several stochastic search algorithms have been designed based on the theory of global random search (Zhigljavsky 1991). Basically, those techniques iteratively sample the search space with respect to a probability, distribution which is updated according to the result of previous samples and some predefined strategy. Genetic Algorithms (GAs) (Goldberg 1989) or Greedy Randomized Adaptive Search Procedures (GRASP) (Feo & Resende 1995) are two particular instances of this paradigm. In this paper, we present SAGE, a search algorithm based on the same fundamental mechanisms as those techniques. However, it addresses a class of problems for which it is difficult to design transformation operators to perform local search because of intrinsic constraints in the definition of the problem itself. For those problems, a procedural approach is the natural way to construct solutions, resulting in a state space represented as a tree or a DAG. The aim of this paper is to describe the underlying heuristics used by SAGE to address problems belonging to that class. The performance of SAGE is analyzed on the problem of grammar induction and its successful application to problems from the recent Abbadingo DFA learning competition is presented.
Emotion and Attention Effects: Is It All a Matter of Timing? Not Yet

Controversy surrounds the relationship between emotion and attention in brain and behavior. Two recent studies acquired millisecond-level data to investigate the timing of emotion and attention effects in the amygdala (Luo et al., 2010; Pourtois et al., 2010). Both studies argued that the effects of emotional content temporally precede those of attention and that prior discrepancies in the literature may stem from the temporal characteristics of the functional MRI (fMRI) signal. Although both studies provide important insights about the temporal unfolding of affective responses in the brain, several issues are discussed here that qualify their results. Accordingly, it may not be yet time to accept the conclusion that “automaticity is a matter of timing”. Indeed, emotion and attention may be more closely linked than suggested in the two studies discussed here.
Dynamic load-balancing via a genetic algorithm

We produce a genetic algorithm (GA) scheduling routine, which with often relatively low cost finds well-balanced schedules. Incoming tasks (of varying durations) accumulate, then are periodically scheduled, in small batches, to the available processors. Two important priorities for our scheduling work are that loads on the processors are well balanced, and that scheduling per se remains cheap in comparison to the actual productive work of the processors. We also include experimental results, exploring a variety of distributions of task durations, which show that our scheduler consistently produces well-balanced schedules, and quite often does so at relatively low cost.
Leveraging Position Bias to Improve Peer Recommendation

With the advent of social media and peer production, the amount of new online content has grown dramatically. To identify interesting items in the vast stream of new content, providers must rely on peer recommendation to aggregate opinions of their many users. Due to human cognitive biases, the presentation order strongly affects how people allocate attention to the available content. Moreover, we can manipulate attention through the presentation order of items to change the way peer recommendation works. We experimentally evaluate this effect using Amazon Mechanical Turk. We find that different policies for ordering content can steer user attention so as to improve the outcomes of peer recommendation.
Learning Abstract Concept Embeddings from Multi-Modal Data: Since You Probably Can’t See What I Mean

Models that acquire semantic representations from both linguistic and perceptual input are of interest to researchers in NLP because of the obvious parallels with human language learning. Performance advantages of the multi-modal approach over language-only models have been clearly established when models are required to learn concrete noun concepts. However, such concepts are comparatively rare in everyday language. In this work, we present a new means of extending the scope of multi-modal models to more commonly-occurring abstract lexical concepts via an approach that learns multimodal embeddings. Our architecture outperforms previous approaches in combining input from distinct modalities, and propagates perceptual information on concrete concepts to abstract concepts more effectively than alternatives. We discuss the implications of our results both for optimizing the performance of multi-modal models and for theories of abstract conceptual representation.
Sound Field Reproduction Using Planar and Linear Arrays of Loudspeakers

In this paper, we consider physical reproduction of sound fields via planar and linear distributions of secondary sources (i.e., loudspeakers). The presented approach employs a formulation of the reproduction equation in spatial frequency domain which is explicitly solved for the secondary source driving signals. Wave field synthesis (WFS), the alternative formulation, can be shown to be equivalent under equal assumptions. Unlike the WFS formulation, the presented approach does not employ a far-field approximation when linear secondary source distributions are considered but provides exact results. We focus on the investigation of the spatial truncation and discretization of the secondary source distribution occurring in real-world implementations and present a rigorous analysis of evanescent and propagating components in the reproduced sound field.
Polyphenols are responsible for the proapoptotic properties of pomegranate juice on leukemia cell lines

Pomegranates have shown great promise as anti-cancer agents in a number of cancers including clinical trials in prostate cancer. We have previously shown pomegranate juice (PGJ) induced apoptosis and preferentially alters the cell cycle in leukemia cell lines compared with nontumor control cells. However, the agents responsible have not yet been fully elucidated. Treatment of four leukemia cell lines with five fractions obtained from PGJ by solid phase extraction demonstrated that only the acetonitrile fractions decreased adenosine triphosphate (ATP) levels in all leukemia cell lines. Acetonitrile fractions also significantly activated caspase-3 and induced nuclear morphology characteristic of apoptosis. S phase arrest was induced by acetonitrile fractions which matched S phase arrest seen previously following whole PGJ treatments. The acetonitrile fractions contained higher phenol content than whole PGJ whereas only low levels of phenols were seen in any other fraction. Liquid chromatography mass spectrometry (LC–MS) analysis demonstrated that acetonitrile fractions were enriched in ellagitannins, ellagic acid, and hydroxycinnamic acid derivatives but depleted in anthocyanins. Individual treatments with identified compounds demonstrated that the ellagitannin: punicalagin was the most active and mimicked the responses seen following acetonitrile fraction treatment. Bioactive components within pomegranate were confined to the acetonitrile fraction of PGJ. The enrichment in ellagitannins and hydroxycinnamic acids suggest these may provide the majority of the bioactivities of PGJ. Individual treatments with compounds identified demonstrated that the ellagitannin: punicalagin was the most active agent, highlighting this compound as a key bioactive agent in PGJ.
Stochastic reaction-diffusion simulation with MesoRD

UNLABELLED MesoRD is a tool for stochastic simulation of chemical reactions and diffusion. In particular, it is an implementation of the next subvolume method, which is an exact method to simulate the Markov process corresponding to the reaction-diffusion master equation. AVAILABILITY MesoRD is free software, written in C++ and licensed under the GNU general public license (GPL). MesoRD runs on Linux, Mac OS X, NetBSD, Solaris and Windows XP. It can be downloaded from http://mesord.sourceforge. net. CONTACT johan.elf@icm.uu. se; johan.hattne@embl-hamburg.de SUPPLEMENTARY INFORMATION 'MesoRD User's Guide' and other documents are available at http://mesord.sourceforge. net.
Interaction in Quantum Communication Complexity

One of the most intriguing facts about communication using quantum states is that these states cannot be used to transmit more classical bits than the number of qubits used, yet there are ways of conveying information with exponentially fewer qubits than possible classically. Moreover, these methods have a very simple structure---they involve little interaction between the communicating parties. We look more closely at the ways in which information encoded in quantum states may be manipulated, and consider the question as to whether every classical protocol may be transformed to a ``simpler'' quantum protocol of similar efficiency. By a simpler protocol, we mean a protocol that uses fewer message exchanges. We show that for any constant k, there is a problem such that its k+1 message classical communication complexity is exponentially smaller than its k message quantum communication complexity, thus answering the above question in the negative. Our result builds on two primitives, local transitions in bi-partite states (based on previous work) and average encoding which may be of significance in other applications as well.
NON-PARAMETRIC METHODS IN ANALYSIS OF EXPERIMENTAL DATA

1. Introduction In conventional setup the analysis of experimental data is based on the assumptions like normality, independence and constant variance of the observations. However, there may arise experimental situations where these assumptions, particularly the assumption of normality, may not be satisfied. In such situations non-parametric test procedures may become quite useful. A lot of attention is being made to develop non-parametric tests for analysis of experimental data. Most of these non-parametric test procedures are based on rank statistic. The rank statistic has been used in development of these tests as the statistic based on ranks is 1. distribution free 2. easy to calculate and 3. simple to explain and understand. The another reason of use of the rank statistic is due to the well known result that the average rank approaches normality quickly as n (number of observations) increases, under the rather general conditions, while the same might not be true for the original data {see e.g. Conover and Iman (1976)}. The non-parametric test procedures available in literature cover completely randomized designs, randomized complete block designs, balanced incomplete block designs, design for bioassays, split plot designs, cross-over designs and so on. For excellent and elaborate discussions on non-parametric tests in the analysis of experimental data, one may refer In the present talk we shall concentrate on the non-parametric test procedure for analysis of one-way and two-way classified data. Some of these procedures are: 1. In the sequel we describe each of these tests in brief. 2. Non-parametric Procedures for the Analysis of Experimental Data In this section, we shall describe the non-parametric tests for analysis of experimental data generated through completely randomized designs (CRD) and block designs. We begin with the test procedure for the experimental data generated through CRD
Sensorimotor Coarticulation in the Execution and Recognition of Intentional Actions

Humans excel at recognizing (or inferring) another's distal intentions, and recent experiments suggest that this may be possible using only subtle kinematic cues elicited during early phases of movement. Still, the cognitive and computational mechanisms underlying the recognition of intentional (sequential) actions are incompletely known and it is unclear whether kinematic cues alone are sufficient for this task, or if it instead requires additional mechanisms (e.g., prior information) that may be more difficult to fully characterize in empirical studies. Here we present a computationally-guided analysis of the execution and recognition of intentional actions that is rooted in theories of motor control and the coarticulation of sequential actions. In our simulations, when a performer agent coarticulates two successive actions in an action sequence (e.g., “reach-to-grasp” a bottle and “grasp-to-pour”), he automatically produces kinematic cues that an observer agent can reliably use to recognize the performer's intention early on, during the execution of the first part of the sequence. This analysis lends computational-level support for the idea that kinematic cues may be sufficiently informative for early intention recognition. Furthermore, it suggests that the social benefits of coarticulation may be a byproduct of a fundamental imperative to optimize sequential actions. Finally, we discuss possible ways a performer agent may combine automatic (coarticulation) and strategic (signaling) ways to facilitate, or hinder, an observer's action recognition processes.
Towards Pharmacological Treatment of Cystic Fibrosis

The importance of chloride channels for the cell is demonstrated by a number of serious human diseases that are due to mutations in chloride channels. The most well-known of these diseases is cystic fibrosis. Investigations into the mechanisms of the disease and possible treatments require the study of chloride fluxes at the level of individual cells. The present study compares two methods for studies of chloride transport: X-ray microanalysis and MQAE fluorescence with image analysis. As an experimental system, the cAMP-activated chloride channel in cultured respiratory epithelial cells was chosen. Both methods showed that stimulation with the cAMP-elevating agents forskolin and IBMX decreased the chloride content of the cells by about 20-27%. Inducing a driving force for chloride by replacing extracellular chloride by nitrate resulted in a chloride efflux that was significantly increased in the presence of forskolin and IBMX. This study shows that X-ray microanalysis and MQAE fluorescence are adequate and comparable methods for measuring cAMP-dependent chloride transport in individual cells.
Elaborating Software Test Processes and Strategies

This paper introduces the research topic of “Elaborating Software Test Processes and Strategies”, in which I with assistance from our research group conducted a qualitative study on software producing organization’s test processes. My goal is to develop a reference model for organizations to enhance and develop their test processes based on the upcoming ISO/IEC 29119 software testing standard by interviewing professional software developers from different phases of software process. The study focuses on the aspects that compose testing strategy; human resources, test tools, test case selection, testing methods and the role of the management in the test process to name few of the major components. Based on the preliminary results, there exists room for improvements in testability of the software products and focusing the available test resources, problems which could be addressed by means of systematic process improvement and defining test strategy for the organization.
Gesture and the process of speech production: We think, therefore we gesture

At what point in the process of speech production is gesture involved? According to the Lexical Retrieval Hypothesis, gesture is involved in generating the surface forms of utterances. Specifically, gesture facilitates access to items in the mental lexicon. According to the Information Packaging Hypothesis, gesture is involved in the conceptual planning of messages. Specifically, gesture helps speakers to ''package'' spatial information into verbalisable units. We tested these hypotheses in 5-year-old children, using two tasks that required comparable lexical access, but different information packaging. In the explanation task, children explained why two items did or did not have the same quantity (Piagetian conservation). In the description task, children described how two items looked different. Children provided comparable verbal responses across tasks; thus, lexical access was comparable. However, the demands for information packaging differed. Participants' gestures also differed across the tasks. In the explanation task, children produced more gestures that conveyed perceptual dimensions of the objects, and more gestures that conveyed information that differed from the accompanying speech. The results suggest that gesture is involved in the conceptual planning of speech.
Tax Evasion, Income Inequality and Opportunity Costs of Compliance

This paper argues that widening income inequality contributes to the propensity to evade by both reducing the probability of detection and increasing compliance opportunity costs. Lower detection probability occurs as rising inequality gradually alters the composition of income from being employment-based (i.e., matchable) to investment-based (i.e., non-matchable). Greater economic polarization also increases the financial strain on many former middle-class taxpayers, thus raising their opportunity cost of compliance. In addition, the compliance opportunity costs for wealthy taxpayers also could increase if they perceive a growing exchange inequity between their tax burdens and public sector benefits. This paper tests the hypothesis that rising income inequality contributes to tax evasion in the United States. Empirical analysis for the period 1947-2000 finds a positive correlation between the underreporting rate for wage and salary income and the top decile wage share. This finding suggests that enforcement policies aimed at reducing income tax evasion may lose some effectiveness in an environment of increasing inequality.
English language teaching in Thailand: Filipino teachers' experiences and perspectives

English language teaching and learning is vital for the development of the country and its people. In Thailand, English language teaching has become one of the most popular jobs both for native and non-native English speaker-teachers. However, only a few studies have been conducted to identify and describe English language education in the Thailand. This study presents the experiences of 9 Filipino university and college English teachers and their perceptions on the teaching of English as a foreign language in Thailand. The method used was in-depth individual interviews. Findings reveal that although Filipino teachers were positive about teaching English to Thai students, they perceived that English language teaching in the country is a challenging task because of students' lack of interest in the English language; lack of exposure to and support for an English speaking environment; unclear and unsuitable English language curriculum; and lack of teacher professional development. Implications are discussed and suggestions for future studies are offered.