Miracle-dz/UniFAR-FTUs huggingface dataset:
The Sparse Matrix Transform for Covariance Estimation and Analysis of High Dimensional Signals

Covariance estimation for high dimensional signals is a classically difficult problem in statistical signal analysis and machine learning. In this paper, we propose a maximum likelihood (ML) approach to covariance estimation, which employs a novel non-linear sparsity constraint. More specifically, the covariance is constrained to have an eigen decomposition which can be represented as a sparse matrix transform (SMT). The SMT is formed by a product of pairwise coordinate rotations known as Givens rotations. Using this framework, the covariance can be efficiently estimated using greedy optimization of the log-likelihood function, and the number of Givens rotations can be efficiently computed using a cross-validation procedure. The resulting estimator is generally positive definite and well-conditioned, even when the sample size is limited. Experiments on a combination of simulated data, standard hyperspectral data, and face image sets show that the SMT-based covariance estimates are consistently more accurate than both traditional shrinkage estimates and recently proposed graphical lasso estimates for a variety of different classes and sample sizes. An important property of the new covariance estimate is that it naturally yields a fast implementation of the estimated eigen-transformation using the SMT representation. In fact, the SMT can be viewed as a generalization of the classical fast Fourier transform (FFT) in that it uses “butterflies” to represent an orthonormal transform. However, unlike the FFT, the SMT can be used for fast eigen-signal analysis of general non-stationary signals.
Kinematic Modeling and Analysis of Skid-Steered Mobile Robots With Applications to Low-Cost Inertial-Measurement-Unit-Based Motion Estimation

Skid-steered mobile robots are widely used because of their simple mechanism and high reliability. Understanding the kinematics and dynamics of such a robotic platform is, however, challenging due to the complex wheel/ground interactions and kinematic constraints. In this paper, we develop a kinematic modeling scheme to analyze the skid-steered mobile robot. Based on the analysis of the kinematics of the skid-steered mobile robot, we reveal the underlying geometric and kinematic relationships between the wheel slips and locations of the instantaneous rotation centers. As an application example, we also present how to utilize the modeling and analysis for robot positioning and wheel slip estimation using only low-cost strapdown inertial measurement units. The robot positioning and wheel slip-estimation scheme is based on an extended Kalman filter (EKF) design that incorporates the kinematic constraints for accuracy enhancement. The performance of the EKF-based positioning and wheel slip-estimation scheme are also presented. The estimation methodology is tested and validated experimentally on a robotic test bed.
The MetaCrawler architecture for resource aggregation on the Web

The paper discusses the MetaCrawler Softbot parallel Web search service that has been available at the University of Washington since June 1995. It provides users with a single interface for querying popular general-purpose Web search services, such as Lycos and AltaVista, and has some sophisticated features that allow it to obtain results of much higher quality than simply regurgitating the output from each search service.
Blind source separation of convolved sources by joint approximate diagonalization of cross-spectral density matrices

We present a new method for separating non-stationary sources from their convolutive mixtures based on approximate joint diagonalization of the observed signals' cross-spectral density matrices. Several blind source separation (BSS) algorithms have been proposed which use approximate joint diagonalization of a set of scalar matrices to estimate the instantaneous mixing matrix. We extend the concept of approximate joint diagonalization to estimate MIMO FIR channels. Based on this estimate we then design a separating network which will recover the original sources up to only a permutation and scaling ambiguity for minimum phase channels. We eliminate the commonly experienced problem of arbitrary scaling and permutation at each frequency bin, by optimizing the cost function directly with respect to the time-domain channel variables. We demonstrate the performance of the algorithm by computer simulations using real speech data.
Analyzing data-centric applications: Why, what-if, and how-to

We consider in this paper the analysis of complex applications that query and update an underlying database in their operation. We focus on three classes of analytical questions that are important for application owners and users alike: Why was a result generated? What would be the result if the application logic or database is modified in a particular way? How can one interact with the application to achieve a particular goal? Answering these questions efficiently is a fundamental step towards optimizing the application and its use. Noting that provenance was a key component in answering similar questions in the context of database queries, we develop a provenance-based model and efficient algorithms for these problems in the context of data-centric applications. Novel challenges here include the dynamic update of data, combined with the possibly complex workflows allowed by applications. We nevertheless achieve theoretical guarantees for the algorithms performance, and experimentally show their efficiency and usefulness, even in presence of complex applications and large-scale data.
QoE-aware Media Streaming in Technology and Cost Heterogeneous Networks

We present a framework for studying the problem of media streaming in technology and cost heterogeneous environments. We first address the problem of efficient streaming in a technologyheterogeneous setting. We employ random linear network coding to simplify the packet selection strategies and alleviate issues such as duplicate packet re ception. Then, we study the problem of media streaming from multiple cost-heterogeneous access networks. Our objective is to characterize analytically the trade-off between access cost and user experience. We model the Quality of user Experience (QoE) as the probability of interruption in playback as well as the in itial waiting time. We design and characterize various control policies, and formulate the optimal contro l problem using a Markov Decision Process (MDP) with a probabilistic constraint. We present a characterization of the optimal policy using the Hamilton-Jacobi-Bellman (HJB) equation. For a fluid approx imation model, we provide an exact and explicit characterization of a threshold policy and prove i ts optimality using the HJB equation. Our simulation results show that under properly designed control policy, the existence of alternative access technology as a complement for a primary access network can significantly improve the user experience without any bandwidth over-provisioning.
Managing Frequent Updates in R-Trees for Update-Intensive Applications

Managing frequent updates is greatly important in many update-intensive applications, such as location-aware services, sensor networks, and stream databases. In this paper, we present an R-tree-based index structure (called Rsb-tree, R-tree with semibulk loading) for efficiently managing frequent updates from massive moving objects. The concept of semibulk loading is exploiting a small in-memory buffer to defer, buffer, and group the incoming updates and bulk-insert these updates simultaneously. With a reasonable memory overhead (typically only 1 percent of the whole data set), the proposed approach far outperforms the previous works in terms of update and query performance as well in a realistic environment. In order to further increase buffer hit ratio for the proposed approach, a new page-replacement policy that exploits the level of buffered node is proposed. Furthermore, we introduce the concept of deferring threshold ratio (dtr) that simply enables deferring CPU- and I/O-intensive operations such as node splits and removals. Extensive experimental evaluation reveals that the proposed approach is far more efficient than previous approaches for managing frequent updates under various settings.
Do Subsidies Increase Charitable Giving in the Long Run? Matching Donations in a Field Experiment

Subsidizing charitable givingâ€”for example, for victims of natural disastersâ€”is very popular, not only with governments but also with private organizations. Many companies match their employees' charitable contributions, hoping that this will foster the willingness to contribute. However, systematic analyses of the effect of such a matching mechanism are still lacking.This article tests the effect of matching charitable giving in a randomized field experiment in the short and the long run. The donations of a randomly selected group were matched by contributions from an anonymous donor. The results support the hypothesis that a matching mechanism increases contributions to a public good. However, in the periods after the experiment, when matching donations have been stopped, the contribution rate declines for the treatment group. The matching mechanism leads to a negative net effect on the participation rate. The field experiment therefore provides evidence suggesting that the willingness to contribute may be undermined by a matching mechanism in the long run. (JEL: C93, D64, H00) (c) 2007 by the European Economic Association.
Immunomodulation of Nasal Epithelial Cells by Staphylococcus aureus-Derived Serine Proteases1

The impact of Staphylococcus aureus in the pathogenesis of chronic rhinosinusitis is not well understood. Therefore, we investigated primary human nasal epithelial cell cultures for their ability to produce IL-8, growth-related oncogene-α, and IL-6 via stimulation with trypsin and culture supernatants of different S. aureus strains and phenotypes. Inhibition of cytokine synthesis was performed using a glucocorticoid, a serine protease inhibitor, and a cysteine protease inhibitor. Finally, signal transduction pathways were analyzed by quantifying phosphorylated forms of MAPKs (PI3K, ERK, and p38) and DNA-binding assays that quantified NF-κB and its inhibition using BAY11-7085. In vitro studies showed that the induction of IL-8, growth-related oncogene-α, and IL-6 by S. aureus culture supernatants was significantly inhibited by the serine protease inhibitor. In contrast, steroids and the cysteine protease inhibitor had little effect. Activation of NF-κB was observed after cell treatment with trypsin and bacterial supernatants, and was inhibited by BAY11-7085 and the serine protease inhibitor. S. aureus serine proteases were identified to modulate chemokine synthesis and activate NF-κB in nasal epithelial cells, and may therefore be relevant for the pathophysiology of chronic rhinosinusitis.
The evaluation of multicast routing algorithms with delay constraints in mesh networks

Wireless mesh networks are playing an important role in extending the implementation of traditional wireless infrastructure (cellular networks, wireless LAN, etc). Routing design in mesh networks is a challenge because of limited node resources. Thus efficient data transmission techniques like multicasting regarding quality of service requirements are under scrutiny. The article analyzes and explores the performance of multicast heuristic algorithms and quality of multicast trees in mesh networks.
An Overview of the PKCS Standards

This note gives an overview of the PKCS family of standards for public-key cryptography. These standards cover RSA encryption, Diffie-Hellman key agreement, password-based encryption, extended-certificate syntax, cryptographic message syntax, private-key information syntax, and certification request syntax, as well as selected attributes. The note gives the motivation for the standards and discusses their relationship to other standards or agreements on public-key cryptography.
Socioeconomic Inequalities in Body Mass Index across Adulthood: Coordinated Analyses of Individual Participant Data from Three British Birth Cohort Studies Initiated in 1946, 1958 and 1970

Background High body mass index (BMI) is an important contributor to the global burden of ill-health and health inequality. Lower socioeconomic position (SEP) in both childhood and adulthood is associated with higher adult BMI, but how these associations have changed across time is poorly understood. We used longitudinal data to examine how childhood and adult SEP relates to BMI across adulthood in three national British birth cohorts. Methods and Findings The sample comprised up to 22,810 participants with 77,115 BMI observations in the 1946 MRC National Survey of Health and Development (ages 20 to 60–64), the 1958 National Child Development Study (ages 23 to 50), and the 1970 British Cohort Study (ages 26 to 42). Harmonized social class-based SEP data (Registrar General’s Social Class) was ascertained in childhood (father’s class at 10/11 y) and adulthood (42/43 years), and BMI repeatedly across adulthood, spanning 1966 to 2012. Associations between SEP and BMI were examined using linear regression and multilevel models. Lower childhood SEP was associated with higher adult BMI in both genders, and differences were typically larger at older ages and similar in magnitude in each cohort. The strength of association between adult SEP and BMI did not vary with age in any consistent pattern in these cohorts, but were more evident in women than men, and inequalities were larger among women in the 1970 cohort compared with earlier-born cohorts. For example, mean differences in BMI at 42/43 y amongst women in the lowest compared with highest social class were 2.0 kg/m2 (95% CI: −0.1, 4.0) in the 1946 NSHD, 2.3 kg/m2 (1.1, 3.4) in the 1958 NCDS, and 3.9 kg/m2 (2.3, 5.4) the in the 1970 BCS; mean (SD) BMI in the highest and lowest social classes were as follows: 24.9 (0.8) versus 26.8 (0.7) in the 1946 NSHD, 24.2 (0.4) versus 26.5 (0.4) in the 1958 NCDS, and 24.2 (0.3) versus 28.1 (0.8) in the 1970 BCS. Findings did not differ whether using overweight or obesity as an outcome. Limitations of this work include the use of social class as the sole indicator of SEP—while it was available in each cohort in both childhood and adulthood, trends in BMI inequalities may differ according to other dimensions of SEP such as education or income. Although harmonized data were used to aid inferences about birth cohort differences in BMI inequality, differences in other factors may have also contributed to findings—for example, differences in missing data. Conclusions Given these persisting inequalities and their public health implications, new and effective policies to reduce inequalities in adult BMI that tackle inequality with respect to both childhood and adult SEP are urgently required
Validation of finite element model of transcranial electrical stimulation using scalp potentials: implications for clinical dose

Objective. During transcranial electrical stimulation, current passage across the scalp generates voltage across the scalp surface. The goal was to characterize these scalp voltages for the purpose of validating subject-specific finite element method (FEM) models of current flow. Approach. Using a recording electrode array, we mapped skin voltages resulting from low-intensity transcranial electrical stimulation. These voltage recordings were used to compare the predictions obtained from the high-resolution model based on the subject undergoing transcranial stimulation. Main results. Each of the four stimulation electrode configurations tested resulted in a distinct distribution of scalp voltages; these spatial maps were linear with applied current amplitude (0.1 to 1 mA) over low frequencies (1 to 10 Hz). The FEM model accurately predicted the distinct voltage distributions and correlated the induced scalp voltages with current flow through cortex. Significance. Our results provide the first direct model validation for these subject-specific modeling approaches. In addition, the monitoring of scalp voltages may be used to verify electrode placement to increase transcranial electrical stimulation safety and reproducibility.
On algebraic multilevel methods for non-symmetric systems - convergence results.

We analyze algebraic multilevel methods applied to non-symmetric M -matrices. Two types of multilevel approximate block factorizations are consider ed. The first one is related to the AMLI method. The second method is the multiplicative counterpart of the AMLI approach which we call the multiplicative algebraic multilevel (MAMLI) method. The MAMLI method is closely related to certain geometric and algebraic multigrid methods, such as the AMGr method. Although these multilevel methods work very well in practice for many problems, not much is known about theoretical convergence properties for non-symmetric problems. Here, we establish convergence results and comparison results betw een AMLI and MAMLI multilevel methods applied to non-symmetric M -matrices.
Visual Recommendations for Network Navigation

Understanding large, complex networks is important for many critical tasks, including decision making, process optimization, and threat detection. Existing network analysis tools often lack intuitive interfaces to support the exploration of large scale data. We present a visual recommendation system to help guide users during navigation of network data. Collaborative filtering, similarity metrics, and relative importance are used to generate recommendations of potentially significant nodes for users to explore. In addition, graph layout and node visibility are adjusted in real‐time to accommodate recommendation display and to reduce visual clutter. Case studies are presented to show how our design can improve network exploration.
Towards a Domain-Referenced System for Classifying Composition Assignments.

Recently there has been growing awareness that the way in which a writing assignment is worded may greatly influence the nature of the writing process and product. For this reason a domain-referenced system intended to both describe and classify current writing assignments and to create composition assignments was developed for an international study of written composition. The system consists of fifteen dimensions: instruction, stimulus, cognitive demand, purpose, role, audience, content, rhetorical specification, tone/style, advance preparation, length, format, time, draft, and criteria. Writing assignments from a number of countries are cited to illustrate the use of the system. It appears to have some promise as a tool in instruction (increasing awareness of the complexity of writing assignments) as well as in assessments and research (insuring coverage of the domain and comparability of assignments across assessments and research studies). // the teacher is, then, to choose the subject for the student, it is desirable to consider next the principles upon which his choice shall be made. These may be briefly stated as follows: (1) The subject chosen must be one that is interesting to the teacher. (2) The subject chosen must be one that is interesting, or that can be made interesting to the students. (Carpenter, Baker, & Scott, 1903, p. 322) The assessment of writing skills through direct writing samples, rather than through various indirect measures, has become an important issue in the past five years or so. Large-scale assessment programs have been carried out in several countries (including England, Scotland, and the United States) and are beginning in the Netherlands. There are several stages in a writing assessment project, all of which have a number of problems associated with them. Assignment development, development of the scoring system, scorer training, scoring, data analysis, and reporting all involve problems and issues (cf. Meredith & Williams, 1984). We will address the first stage in any assessment, the development of the tasks that are presented to students. Much research in the area of written composition has foundered on the assignment issue, and much evaluation of written composition has been challenged on the basis of the assignments used to assess writing. In general Research in the Teaching of English, Vol. 18, No. 4, December 1984
Pose Estimation and Object Identiication Using Complex Algebraic Representations Pose Estimation and Object Identiication Using Complex Algebraic Representations

The comparison and alignment of two similar objects is a fundamental problem in pattern recognition and computer vision that has been considered using various approaches. In this work, we employ a complex representation for an algebraic curve, and illustrate how the algebraic transformation which relates two Euclidean equivalent curves can be determined using this representation. The idea is based on a complex representation of 2D points expressed in terms of the orthogonal x and y variables, with rotations of the complex numbers described using Euler's identity. We develop a simple formula for integer multiples of the rotation angle of the Euclidean transformation in terms of the real coeecients of implicit polynomial equations that are used to model 2D free-form objects. When there is a translation, it can be determined using some new results on the conic-line factors of implicit polynomial curves. Experimental results are presented for data sets characterized by both noisy and missing data points to illustrate and validate our procedures.
PrintScreen: fabricating highly customizable thin-film touch-displays

PrintScreen is an enabling technology for digital fabrication of customized flexible displays using thin-film electroluminescence (TFEL). It enables inexpensive and rapid fabrication of highly customized displays in low volume, in a simple lab environment, print shop or even at home. We show how to print ultra-thin (120 µm) segmented and passive matrix displays in greyscale or multi-color on a variety of deformable and rigid substrate materials, including PET film, office paper, leather, metal, stone, and wood. The displays can have custom, unconventional 2D shapes and can be bent, rolled and folded to create 3D shapes. We contribute a systematic overview of graphical display primitives for customized displays and show how to integrate them with static print and printed electronics. Furthermore, we contribute a sensing framework, which leverages the display itself for touch sensing. To demonstrate the wide applicability of PrintScreen, we present application examples from ubiquitous, mobile and wearable computing.
Does Empathy Beget Guile?

Some theories about the positive impact of markets on morality suggest that competition increases empathy, not between competitors, but between them and third parties. However, empathy may be a necessary evolutionary antecedent to guile, which is when someone knows what the other person wants and intentionally deceives him or her, and deception may have evolved as a means of exploiting empathy. This paper examines how individuals primed for empathy behave towards third parties in a simple economic game of deception. It reports the results of a data entry experiment in an online labor market. Individuals enter data randomized to be a prime for empathy, for guile, or a control. Empathy is then measured using a Reading the Mind in the Eyes Test and guile is measured using a simple economic game. Individuals primed for empathy become less deceptive towards third parties. Individuals primed for guile become less likely to perceive that deceiving an individual is unfair in a vignette. These results are robust to a variety of controls and to restricting to workers who entered the prime accurately. These findings are inconsistent with the hypothesis that empathy causes guile and suggests that empathy may cause those who are making judgements to become less deceptive.