Miracle-dz/UniFAR-FTUs huggingface dataset:
Real-Time Robust Tracking with Sparse Representation

Real-Time Robust Tracking with Sparse Representation Visual object tracking plays a critical role in many computer vision applications including visual surveillance, transportation monitoring system etc. A main goal of visual object tracking is to estimate the location of specified object in consecutive frames. For these applications, we need a real time tracker that is robust to various challenges such as illumination change, pose change, noise and partial occlusion. Hence continues to be an acive research area in computer vision community. In our project, we have proposed real time trackers which can handle many of these challenges and track the object in real time using sparse representaion framework. In the first approach, we have used Three Step Search(TSS) procedure to rapidly sample the candidate space instead of computationally expensive particle filter. In the second approach, the object motion is estimated by matching the target and candidate fragments in l1 minimization framework. In the third approach we have represented the object as a collection of interest points. Here, the tracking is accomplished by establishing the correspondence between the target and candidate interest points via sparse representation. The object and candidate dictionaries are created by a small vectorized image patch surrounding each interest point. The RGB color values are considered while building the dictionary, which improves the robustness of the tracker. A robust matching criteria, which checks for mutual matching between target and candidate interest points, has been proposed for pruning the noisy matches and improve the robustness. The performance of the proposed tracker is bench-marked with various publicly available challenging video sequences and found to be fast and robust compared to the state of the art trackers. keywords: Visual Tracking, Sparse representation, Three Step Search, Harris corner detector, interest points, l1 minimization.
Gaussian Approximation for LDPC Codes

Today, LDPC codes have become one of the hottest topics in coding theory. Unlike many other classes of cods LDPC codes are already equipped with very fast (probabilistic) encoding and decoding algorithm. The decoding of LDPC codes are implemented through message-passing algorithm. Passed messages can be modeled as Gaussian variables. In this paper, the new approximate method for calculation of statistical parameters of these Gaussian variables is proposed. Based on proposed method, we can be able to estimate the threshold level of noise of regular LDPC codes over AWGN channels.
Utility of Surgeon-Performed Ultrasound Assessment of the Lateral Neck for Metastatic Papillary Thyroid Cancer

Ultrasound is the recommended staging modality for papillary thyroid cancer. Surgeons proficient in US assessment of the neck and experienced in the management of papillary thyroid cancer (PTC) appear uniquely qualified to assess the lateral cervical lymph nodes for metastatic disease. Of 310 patients treated for PTC between 2000 and 2008, 109 underwent surgeon-performed ultrasound (SUS) of the lateral neck preoperatively. Fine needle aspiration was performed on suspicious lateral lymph nodes. SUS findings were compared with FNA cytology and results of postoperative imaging studies. The sensitivity and negative predictive value of SUS were 88% and 97%, respectively. Four patients were found to have missed metastatic disease within 6 months. No patient underwent a nontherapeutic neck dissection. SUS combined with US-guided FNA of suspicious lymph nodes can accurately stage PTC to reliably direct surgical management.
Sorting Texts by Readability

This article presents a novel approach for readability assessment through sorting. A comparator that judges the relative readability between two texts is generated through machine learning, and a given set of texts is sorted by this comparator. Our proposal is advantageous because it solves the problem of a lack of training data, because the construction of the comparator only requires training data annotated with two reading levels. The proposed method is compared with regression methods and a state-of-the art classification method. Moreover, we present our application, called Terrace, which retrieves texts with readability similar to that of a given input text.
On the Complexity of Gene Expression Classification Data Sets

One of the main kinds of computational tasks regarding gene expression data is the construction of classifiers (models), often via some machine learning (ML) technique and given data sets, to automatically discriminate expression patterns from cancer (tumor) and normal tissues or from subtypes of cancers. A very distinctive characteristic of these data sets is its high dimensionality and the fewer number of data items. Such a characteristic makes the induction of accurate ML models difficult (e.g., it could lead to model overfitting). In this context, we present an empirical study on the complexity of the classification task of gene expression data sets, related to cancer, used for classification purposes. In order to do so, we measure the complexity of the ML models used to perform the tumors' classification. The results indicate that most of these data sets can be effectively discriminated by a simple linear function.
Luzp4 defines a new mRNA export pathway in cancer cells

Cancer testis antigens (CTAs) represented a poorly characterized group of proteins whose expression is normally restricted to testis but are frequently up-regulated in cancer cells. Here we show that one CTA, Luzp4, is an mRNA export adaptor. It associates with the TREX mRNA export complex subunit Uap56 and harbours a Uap56 binding motif, conserved in other mRNA export adaptors. Luzp4 binds the principal mRNA export receptor Nxf1, enhances its RNA binding activity and complements Alyref knockdown in vivo. Whilst Luzp4 is up-regulated in a range of tumours, it appears preferentially expressed in melanoma cells where it is required for growth.
Behavior of a second class particle and its dual in Hammersley ’ s process

In the case of a rarefaction fan in a non-stationary Hammersley process, we explicitly calculate the asymptotic behavior of the process as we move out along a ray, and the asymptotic distribution of the angle within the rarefaction fan of a second class particle and a dual second class particle. Furthermore, we show that a second class particle and a dual second class particle touch with probability one, and we give some information on the area enclosed by the two trajectories, up until the first intersection point. The concept of a dual second class particle is natural within a Hammersley process, but we have not encountered it, or problems related to it, in the literature on discrete interacting particle processes.
An invariant action for noncommutative gravity in four dimensions

Two main problems face the construction of noncommutative actions for gravity with star products: the complex metric and finding an invariant measure. The only gauge groups that could be used with star products are the unitary groups. I propose an invariant gravitational action in D=4 dimensions based on the constrained gauge group U(2,2) broken to U(1,1)×U(1,1). No metric is used, thus giving a naturally invariant measure. This action is generalized to the noncommutative case by replacing ordinary products with star products. The four-dimensional noncommutative action is studied and the deformed action to first order in deformation parameter is computed.
cis-Golgi proteins accumulate near the ER exit sites and act as the scaffold for Golgi regeneration after brefeldin A treatment in tobacco BY-2 cells

Particular cis-Golgi proteins accumulate in novel punctate structures close to ERES by BFA treatment in tobacco BY-2 cells. These structures reassemble first to form cis-Golgi after BFA removal, and the Golgi stacks regenerate in the cis-to-trans order. This indicates that the punctate structures act as the scaffold for Golgi regeneration.
Restricted Epidemic Routing in Multi-Community Delay Tolerant Networks

In some specific applicable scenarios, nodes are placed in some geographical areas and limited to move in their own community. We investigate the tradeoff between the delivery delay and the number of transmissions in the above multi-community delay tolerant networks by propagating a data packet in a carefully chosen segment of community. First, three restricted epidemic routings are proposed: the shortest community-hop path scheme, the rectangle scheme, and the parallelogram scheme. Second, the ratios of the average number of communities that can propagate the data packet in the proposed schemes to those that can propagate in the epidemic routing are analyzed. The ratios are found to be small and to decrease with the increase in the number of communities. The tail distribution of the inter-meeting time of any two nodes in the neighboring communities is then demonstrated to be exponential. Third, the delivery delay of the proposed schemes is analyzed by Markovian chain tool. The experiments show that the theoretical model proposed here is reliable, and that the proposed schemes can significantly decrease the number of transmissions, even if these schemes increase the delivery delay to some extent.
Density control through random sampling: an architectural perspective

Information visualisation systems often have to cope with presenting large amounts of data. In this paper we look at the problem of reducing the display density through the use of random sampling. We review some of the uses of sampling and examine density reduction techniques currently used in visualisation. We then look at a proposed novel visualisation that utilises sampling and discuss many issues that arise. Furthermore, we propose the /spl zeta/DB sampling database architecture and demonstrate how this can be used to enhance current visualisation applications. Finally, we describe the architecture of a sampling aware application and illustrate its advantages.
Financial characteristics of high-income families

Robert B. Avery and Gregory E. Elliehausen of the Board’s Division of Research and Statistics prepared this article with the assistance of Glenn B. Canner, Thomas A. Gustafson, Julia Springer, and members of the Board’s Flow of Funds Section. Special thanks are due Richard T. Curtin of the Survey Research Center of the University of Michigan, who supervised the design of the survey and its implementation. This is the last in a series of three reports on the I983 Survey of Consumer Finances. The first report appeared in the September 1984 issue, and the second appeared in the December 1984 issue. Footnotes appear at the end of the article.
PARAMETER ESTIMATION IN EPIDEMIC MODELS : SIMPLIFIED FORMULAS

We consider the problem of identifying the time-dependent transmission rate from incidence data and from prevalence data in epidemic SIR, SIRS, and SEIRS models. We show closed representation formulas avoiding the computation of higher derivatives of the data or solving differential equations. We exhibit the connections between the formulas given in several recent papers. In particular we explain the difficulties to estimate the initial number of susceptible or, equivalently, the initial transmission rate.
Modified Subspace Algorithms for DoA Estimation With Large Arrays

This paper proposes the use of a new generalized asymptotic paradigm in order to analyze the performance of subspace-based direction-of-arrival (DoA) estimation in array signal processing applications. Instead of assuming that the number of samples is high whereas the number of sensors/antennas remains fixed, the asymptotic situation analyzed herein assumes that both quantities tend to infinity at the same rate. This asymptotic situation provides a more accurate description of a potential situation where these two quantities are finite and hence comparable in magnitude. It is first shown that both MUSIC and SSMUSIC are inconsistent when the number of antennas/sensors increases without bound at the same rate as the sample size. This is done by analyzing and deriving closed-form expressions for the two corresponding asymptotic cost functions. By examining these asymptotic cost functions, one can establish the minimum number of samples per antenna needed to resolve closely spaced sources in this asymptotic regime. Next, two alternative estimators are constructed, that are strongly consistent in the new asymptotic situation, i.e., they provide consistent DoA estimates, not only when the number of snapshots goes to infinity, but also when the number of sensors/antennas increases without bound at the same rate. These estimators are inspired by the theory of G-estimation and are therefore referred to as G-MUSIC and G-SSMUSIC, respectively. Simulations show that the proposed algorithms outperform their traditional counterparts in finite sample-size situations, although they still present certain limitations.
Democracy's Infrastructure: The Role of Procedural Fairness in Fostering Consent

Several strands of democracy theory posit that citizens ought to consent to political institutions only under the condition that those institutions adhere to fair procedures of decisions making. While this theory linking citizens' consent to the design of decision-making processes may be normatively compelling, our current knowledge of this link in real political life remains incomplete. Which approaches to decision making do citizens view as more, or less, procedurally fair? To what extent do citizens' evaluations of decision-making processes actually affect their willingness to defer to political institutions and to political decisions? Public opinion research has documented a long term decline in citizens' confidence in government in established democratic nations. In addition, citizens are increasingly inclined, and equipped, to contest political decisions. These trends suggest a growing reluctance to consent to political authority. Attempts to explain and interpret these trends abound, yet the theory of procedural fairness remains empirically under explored. The theory of procedural fairness postulates that citizens evaluate decision-making processes, and that these evaluations in turn can either engender or undermine consent to the decision-making authority. Democracy's Infrastructure employs two attitudes as indicators of consent: willingness to accept decisions, and trust for political institutions. The study considers citizens' assessments of decision-making processes along two different conceptualizations of procedural fairness. The first relates to citizens' satisfaction with their own ability to exert influence in the decision-making process. The second draws on a theme in deliberative democracy theory, which suggests that political decision makers should engage in dialogue with constituents, show a willingness to receive and address input from citizens, and provide clear explication of the various alternatives considered and selected. The empirical analyses examine citizens' assessments of seven decision-making processes in a single political issue, the construction of a double-tracked railway along Sweden's west coast. This comparison sheds light on what approaches to decision making citizens evaluate more favorably or critically. Panel data gathered through two mail surveys enable an examination of the causal order in perceived procedural fairness and indicators of consent. The results show that authorities perceived to employ a more deliberative approach are regarded as much more trustworthy and also, though to a lesser extent, are more able to induce citizens to accept the final decision outcome. Citizens' satisfaction with their own influence in the issue also fosters consent, though to a lesser extent. Furthermore, citizens' assessments of their own influence in the issue seem to reflect personal attributes more than the actual availability of opportunities to exert influence.
Bracken: Estimating species abundance in metagenomics data

We describe a new, highly accurate statistical method that computes the abundance of species in DNA sequences from a metagenomics sample. Bracken (Bayesian Reestimation of Abundance after Classification with KrakEN) uses the taxonomy labels assigned by Kraken, a highly accurate metagenomics classification algorithm, to estimate the number of reads originating from each species present in a sample. Kraken classifies reads to the best matching location in the taxonomic tree, but does not estimate abundances of species. We use the Kraken database itself to derive probabilities that describe how much sequence from each genome is shared with other genomes in the database, and combine this information with the assignments for a particular sample to estimate abundance at the species level, the genus level, or above. Combined with the Kraken classifier, Bracken produces accurate species-and genus-level abundance estimates even when a sample contains multiple near-identical species.
Texture Variations Suppress Suprathreshold Brightness and Colour Variations

Discriminating material changes from illumination changes is a key function of early vision. Luminance cues are ambiguous in this regard, but can be disambiguated by co-incident changes in colour and texture. Thus, colour and texture are likely to be given greater prominence than luminance for object segmentation, and better segmentation should in turn produce stronger grouping. We sought to measure the relative strengths of combined luminance, colour and texture contrast using a suprathreshhold, psychophysical grouping task. Stimuli comprised diagonal grids of circular patches bordered by a thin black line and contained combinations of luminance decrements with either violet, red, or texture increments. There were two tasks. In the Separate task the different cues were presented separately in a two-interval design, and participants indicated which interval contained the stronger orientation structure. In the Combined task the cues were combined to produce competing orientation structure in a single image. Participants had to indicate which orientation, and therefore which cue was dominant. Thus we established the relative grouping strength of each cue pair presented separately, and compared this to their relative grouping strength when combined. In this way we observed suprathreshold interactions between cues and were able to assess cue dominance at ecologically relevant signal levels. Participants required significantly more luminance and colour compared to texture contrast in the Combined compared to Separate conditions (contrast ratios differed by about 0.1 log units), showing that suprathreshold texture dominates colour and luminance when the different cues are presented in combination.
Digital youth in digital schools: Literacy, learning and all that noise

Educational researchers, practitioners, and policymakers face increasing pressure to determine the role of new media in America's schools. Despite widespread agreement that digital media are transforming how young people learn and communicate, little evidence exists that digital media have markedly changed how we "do school. " In the last decade, extensive research focused on increasing access to and integrating technology in schools, suggesting that digital media support new contexts for knowledge development. Yet little empirical research examined how adolescents actually engage digital media in their everyday lives in schools. In a two-year study in a Philadelphia public high school, I researched what it means for literacy learning when youth attend a digitally comprehensive school, and what happens when we shift our focus away from new media as discrete tools, and instead consider them as part of the social and cultural fabric of "doing school. " I followed and learned from tenth-graders in English and History classes taught by the same teacher. Through the theoretical frames of socio-cultural constructions of literacy, youth culture, and media ecologies, I examine three interrelated dimensions significant to adolescents' experiences as students in what I call a new culture of literacy learning: (1) Noise, (2) Navigation, and (3) Negotiation. Noise refers to the intense, multilayered, and highly saturated nature of this context. Navigation represents the range of moves, tools, and roles that adolescents engaged to accomplish their intellectual work in these classrooms. Negotiation illustrates how adolescents leveraged digital media to participate with others. The findings can support the work of teachers to redesign classrooms that harness digital media to cultivate adolescents' literacies and foster meaningful participation. This study raises questions for educators, researchers, and policymakers about how to assess literacies that are multimodal, fluid, and collaborative. My results also can contribute to conversations about designing new ways to study adolescents' literacies within and across the dynamic contexts associated with digital media. Finally, this study suggests that we will need new theoretical frameworks to understand adolescents' literacy work in schools. Degree Type Dissertation Degree Name Doctor of Philosophy (PhD) Graduate Group Education First Advisor Susan L. Lytle
Performance assessment of JPEG 2000 based MCTF and H.264 FRExt for Digital Cinema compression

In this paper we present a comparison between JPEG 2000-based Motion Compensated Temporal Filtering (MCTF) and H.264 Fidelity Range Extension (FRExt) High Profile (HP) codecs, used for the compression of video streams for Digital Cinema (DC) applications. Existing MCTF techniques have been extended and adapted to the particular characteristics of DC images, and they have been compared with state-of-the-art compression methods. The results show that H.264 generally achieves the best objective results, with MCTF very close or better at low bit rates: in this case, the existing JPEG 2000 decompression hardware may profitably exploit MCTF.
The exact solution of the Riemann problem with non-zero tangential velocities in relativistic hydrodynamics

We have generalized the exact solution of the Riemann problem in special relativistic hydrodynamics (Martí & Müller 1994) for arbitrary tangential flow velocities. The solution is obtained by solving the jump conditions across shocks plus an ordinary differential equation arising from the self-similarity condition along rarefaction waves, in a similar way as in purely normal flow. The dependence of the solution on the tangential velocities is analysed, and the impact of this result on the development of multi-dimensional relativistic hydrodynamic codes (of Godunov type) is discussed.
Human capital and SME internationalization: Empirical evidence from Belgium

This article explores the role of firm-level human capital for the internationalization of small and medium-sized enterprises (SMEs). Building on the resource-based view of the firm and theories of SME internationalization, we hypothesize that the level of human capital will vary with SME internationalization strategy and will be of considerable importance for firms that follow a strategy of accelerated internationalization. At the same time, we suggest a threshold point, after which additional firm endowments of human capital become less productive. We test our ideas using a unique dataset of all manufacturing SMEs in Belgium which internationalized between 1998 and 2005. Findings indicate a significant curvilinear (inverted U) association between the level of human capital and the firm’s export intensity when firms choose a strategy of accelerated internationalization.