Miracle-dz/UniFAR-FTUs huggingface dataset:
Colored noise and computational inference in neurophysiological (fMRI) time series analysis: Resampling methods in time and wavelet domains

Even in the absence of an experimental effect, functional magnetic resonance imaging (fMRI) time series generally demonstrate serial dependence. This colored noise or endogenous autocorrelation typically has disproportionate spectral power at low frequencies, i.e., its spectrum is f–1 ‐like. Various pre‐whitening and pre‐coloring strategies have been proposed to make valid inference on standardised test statistics estimated by time series regression in this context of residually autocorrelated errors. Here we introduce a new method based on random permutation after orthogonal transformation of the observed time series to the wavelet domain. This scheme exploits the general whitening or decorrelating property of the discrete wavelet transform and is implemented using a Daubechies wavelet with four vanishing moments to ensure exchangeability of wavelet coefficients within each scale of decomposition. For f–1 ‐like or fractal noises, e.g., realisations of fractional Brownian motion (fBm) parameterised by Hurst exponent 0 < H < 1, this resampling algorithm exactly preserves wavelet‐based estimates of the second order stochastic properties of the (possibly nonstationary) time series. Performance of the method is assessed empirically using f–1 ‐like noise simulated by multiple physical relaxation processes, and experimental fMRI data. Nominal type 1 error control in brain activation mapping is demonstrated by analysis of 13 images acquired under null or resting conditions. Compared to autoregressive pre‐whitening methods for computational inference, a key advantage of wavelet resampling seems to be its robustness in activation mapping of experimental fMRI data acquired at 3 Tesla field strength. We conclude that wavelet resampling may be a generally useful method for inference on naturally complex time series. Hum. Brain Mapping 12:61–78, 2001. © 2001 Wiley‐Liss, Inc.
Toward a Monopoly Botnet Market

ABSTRACT Economics play an increasingly important role in fighting cyber crimes. While the arms race against botnet problems has achieved limited success, we propose an approach attacking botnets through affecting a botnet market structure. The characteristics of the present underground botnet market suggest that it functions effectively as perfectly competitive. Competitive markets are usually efficient. We argue that less competition in the botnet market is actually preferred. Our economic analysis suggests that monopoly reduces the overall market output of botnets. Using a model of market structure evolution, we identify key forces that affect the botnet market structure and propose possible ways such as defaming botnet entrants to reduce competition, which ultimately reduce the size and output of the botnet market. The analysis provides useful insight to botnet defenders as a guidance on an efficient allocation of defending resources by attacking more on new entrants to the botnet market relative to the existing botmasters.
An Approach for Intrusion Detection of IPv6 Network Based on LS-SVM Algorithm

IPv6 has enough IP addresses to solve the problem of lack of IP address space. However, there are many security problems to be concerned. The detection ability of current intrusion detection system is poor when given less priori knowledge. In this paper, we analyze the Least Squares Support Vector Machine (LS-SVM) algorithm and the working process of snort intrusion detection system. And then we study the methods of intrusion detection in IPv6, and use LS-SVM to optimize snort intrusion detection system. Simulation results show that intrusion detection system with LS-SVM has a robust performance and has high detection efficiency
Phonetically-constrained PLDA modeling for text-dependent speaker verification with multiple short utterances

The importance of phonetic variability for short duration speaker verification is widely acknowledged. This paper assesses the performance of Probabilistic Linear Discriminant Analysis (PLDA) and i-vector normalization for a text-dependent verification task. We show that using a class definition based on both speaker and phonetic content significantly improves the performance of a state-of-the-art system. We also compare four models for computing the verification scores using multiple enrollment utterances and show that using PLDA intrinsic scoring obtains the best performance in this context. This study suggests that such scoring regime remains to be optimized.
The Krakatoa Chronicle: An Interactive Personalized Newspaper on the Web

This paper describes The Krakatoa Chronicle, a highly interactive, personalized newspaper on the World Wide Web (WWW). It is intended for Java-savvy WWW browsers such as HotJava, and is architecturally quite different from conventional Web-based newspapers. Its high interactivity and powerful personalization are the result of sending an interactive agent along with the text of the newspaper to operate within the user's Web-browser. The agent keeps a network connection open to the WWW server site to fetch resources dynamically, and for updating the user's personal profile as it garners relevance feedback. Users are provided a variety of article browsing options such as scrolling, maximizing, resizing, and the ability to "peek. " These operations not only enhance the reading experience in ways conventional newspapers cannot, but also transparently provide information to our agent about the user's locus of interest. Ours is the first Web newspaper to attempt a realistic rendering of a newspaper, with a multicolumn format and embedded custom widgets for easy browsing. We provide dynamic layout control mechanisms that let the user specify how personal and community interests should be interpreted by the agent in designing the layout.
MultiKulti Algorithm: Migrating the Most Different Genotypes in an Island Model

Migration policies in distributed evolutionary algorithms has not been an active research area until recently. However, in the same way as operators have an impact on performance, the choice of migrants is due to have an impact too. In this paper we propose a new policy (named multikulti) for choosing the individuals that are going to be sent to other nodes, based on multiculturality: the individual sent should be as different as possible to the receiving population. We have checked this policy on different discrete optimization problems, and found that, in average or in median, this policy outperforms classical ones like sending the best or a random individual.
A scenario for symmetry breaking in Caffarelli–Kohn–Nirenberg inequalities

Abstract -The purpose of this paper is to explain the phenomenon of symmetry breaking for optimal functions in functional inequalities by the numerical computations of some well chosen solutions of the corresponding Euler-Lagrange equations. For many of those inequalities it was believed that the only source of symmetry breaking would be the instability of the symmetric optimizer in the class of all admissible functions. But recently, it was shown by an indirect argument that for some Caffarelli-Kohn-Nirenberg inequalities this conjecture was not true. In order to understand this new symmetry breaking mechanism we have computed the branch of minimal solutions for a simple problem. A reparametrization of this branch allows us to build a scenario for the new phenomenon of symmetry breaking. The computations have been performed using freefem++.
Conditional cash transfer programs: A "magic bullet" for reducing poverty?

In 1997, the government of Mexico introduced a conditional cash transfer (CCT) program called Programa de Educación, Salud, y Alimentación (PROGRESA) to provide assistance to about 300,000 extremely poor households. The essential premise of a CCT program is a cash transfer to households conditioned on their participation in health, nutrition, and education services. Ten years later, PROGRESA, now Oportunidades, covers more than 5 million households in all 31 Mexican states. Approximately 20 countries have adopted a pilot or full-scale CCT program, and another 20 countries have expressed interest in starting one. Most current programs are in Latin America, but others can be found in Asia, Africa, and the Caribbean, and interest is increasing among African countries struggling with extreme poverty and low human capital. CCT programs are increasingly perceived as being “a magic bullet in development. ” Are they? This chapter presents a review of the rationale for and operation of CCT programs, an assessment of their effectiveness, and a discussion of key issues facing countries considering these interventions or reforming existing programs.
Progressive 3 D mesh compression : A B-Spline approach

This paper proposes a new approach for efficient progressive compression of dense and smooth 3D meshes. Based on a multi-patch B-Spline representation, the proposed compression scheme includes three stages: mesh segmentation into patches, parameterization, and B-Spline fitting. The geometry images of the B-Splines control points are compressed with optimized still image encoders, while the mesh connectivity is lossless encoded by applying the Touma and Gotsman (TG) algorithm. The experimental evaluation, carried out on a corpus of meshes from the Stanford and Cyberware repositories, shows that the proposed compression scheme achieves significant gains (30% on average) when compared to the spectral compression (SC) approach and outperforms both MPEG-4 and TG encoding schemes, particularly at low bitrates of less than 8 bits per vertex. Key-Words: 3D mesh compression, geometry images, B-Spline, parameterization.
Presentation sensei: a presentation training system using speech and image processing

In this paper we present a presentation training system that observes a presentation rehearsal and provides the speaker with recommendations for improving the delivery of the presentation, such as to speak more slowly and to look at the audience. Our system "Presentation Sensei" is equipped with a microphone and camera to analyze a presentation by combining speech and image processing techniques. Based on the results of the analysis, the system gives the speaker instant feedback with respect to the speaking rate, eye contact with the audience, and timing. It also alerts the speaker when some of these indices exceed predefined warning thresholds. After the presentation, the system generates visual summaries of the analysis results for the speaker's self-examinations. Our goal is not to improve the content on a semantic level, but to improve the delivery of it by reducing inappropriate basic behavior patterns. We asked a few test users to try the system and they found it very useful for improving their presentations. We also compared the system's output with the observations of a human evaluator. The result shows that the system successfully detected some inappropriate behavior. The contribution of this work is to introduce a practical recognition-based human training system and to show its feasibility despite the limitations of state-of-the-art speech and video recognition technologies.
Scintillation-induced variability in radio absorption spectra against extragalactic sources

Spectral features absorbed against some radio quasars exhibit similar to 50 mJy variations, with the lines varying both relative to the continuum and, when several lines are present, even relative to one another. We point out that such variability can be expected as a consequence of refractive scintillation caused by the interstellar medium of our Galaxy. Scintillation can cause independent variations between closely-spaced spectral lines, and can even alter the line profile. The background source need not be compact to exhibit spectral variability. The variability can be used to infer the parsec to sub-parsec scale structure of the intervening absorbing material. We discuss the importance of scintillation relative to other possible origins of spectral variability. The present theory is applied to account for the variations observed in the HI-absorbed quasar PKS1127-145.
Distributed transmit beamforming with one bit feedback revisited: How noise limits scaling

Distributed transmit beamforming with N cooperating nodes, each with fixed transmit power, provides a received power scaling with N2, corresponding to a “power pooling” gain of N and a beamforming gain of N. Prior work has shown that the optimal beamforming solution can be attained using a decentralized, iterative algorithm based on one bit (per iteration) feedback broadcast from the receiver to the transmitters. The algorithm is provably convergent in a noiseless setting, and is the basis for several successful prototypes. In this paper, we develop a framework for providing analytical insight into the effect of receiver noise, with the following key question in mind: can we bootstrap the algorithm from the incoherent power-pooled solution to operate in a regime in which the received SNR per node can be made arbitrarily small as we scale up the number of nodes N? Our analytical computations, validated by simulations, yield a somewhat negative answer: while the power-pooling gain guarantees a linear increase in received power with N, the per-node SNR cannot be scaled down with N if we wish to attain a quadratic increase in received power. Specifically, the fraction of the ideal beamforming gain attained using the one-bit algorithm is asymptotically independent of N, and depends only on the per-node SNR. However, the one-bit algorithm provides significant performance gains in practical regimes with a moderate number of cooperating nodes: the per-node SNR required for attaining a substantial fraction of the beamforming gain is low enough (e.g., - 5dB for 65% of the beamforming gain) to provide significant extension in operation regimes, while providing aggregate SNRs which permit reliable communication at high spectral efficiency: for example, starting from -5 dB per-node SNR, we obtain about 11 dB aggregate SNR with 10 cooperating nodes, and 17 dB SNR with 20 cooperating nodes.
A Refinement Calculus for Communicating Processes with State

A uniform treatment is presented of specifications, programs, and programming for communicating processes with machine state. The treatment is based on addition of a specification statement to a CSP-like language. The extended language is viewed as a specification language in which programs are identified with a subclass of specifications. A semantics is provided and here a selection of sound refinement laws is given to support the development of programs from specifications. The result is a homogeneous framework for the specification and development of parallel programs which, as usual, guarantees functional correctness of an implementation as a consequence of development using its laws. An example is given to demonstrate use of the method.
Diversity of Anaplasma phagocytophilum Strains, USA

We analyzed the structure of the expression site encoding the immunoprotective protein MSP2/P44 from multiple Anaplasma phagocytophilum strains in the United States. The sequence of p44ESup1 had diverged in Ap-variant 1 strains infecting ruminants. In contrast, no differences were detected between A. phagocytophilum strains infecting humans and domestic dogs.
Method of Extracting Is-A and Part-Of Relations Using Pattern Pairs in Mass Corpus

This paper proposes a method that extracts term pairs satisfying is-a relations or part-of relations from a mass corpus using pairs of patterns sharing a term. We extracted reliable single patterns and pattern pairs using some term pairs that satisfy the target relation, and extracted reliable term pairs using these patterns. The extracted term pairs were used to extract new single patterns and pattern pairs, and we repeated these steps several times. The proposed method achieved 71.5% accuracy in detecting is-a relations and 88% accuracy in detecting part-of relations, and extracted 144 new is-a relations and 85 new part-of relations which could not be extracted using single patterns. These results are useful in constructing an ontology and a thesaurus because these language knowledge bases consist mainly of is-a relations and part-of relations.
Practical Aspects of the Moreau-Yosida Regularization: Theoretical Preliminaries

When computing the infimal convolution of a convex function f with the squared norm, the so-called Moreau--Yosida regularization of f is obtained. Among other things, this function has a Lipschitzian gradient. We investigate some more of its properties, relevant for optimization. The most important part of our study concerns second-order differentiability: existence of a second-order development of $f$ implies that its regularization has a Hessian. For the converse, we disclose the importance of the decomposition of ${\Bbb R}^N$ along $\cal U$ (the subspace where f is "smooth") and $\cal V$ (the subspace parallel to the subdifferential of f).
Digit ratio (2D:4D) predicts pro-social behavior in economic games only for unsatisfied individuals

Prenatal exposure to hormones, and to sex hormones in particular, exerts organizational effects on the brain and these have observable behavioral correlates in adult life. There are reasons to expect that social behaviors—which are fundamental for the evolutionary success of humans—might be related to biological factors such as prenatal sex hormone exposure. Nevertheless, the existing literature is inconclusive as to whether and how prenatal exposure to testosterone and estrogen, proxied by the second-to-fourth digit ratio (2D:4D), may predict non-selfish behavior. Here, we investigate this question using economic experiments with real monetary stakes and analyzing five different dimensions of social behavior in a comparatively large sample of Caucasian participants (n=560). For both males and females, our results show no robust association between right- or left-hand 2D:4D and generosity, bargaining, or trust-related behaviors. Since 2D:4D is thought to be a marker for status, we set-up and test the hypothesis that 2D:4D explains prosocial behavior only for people with low subjective wellbeing who are in need for status. Using two different measures of subjective wellbeing, we find considerable support for our hypothesis, especially among males. These results contribute to the debate regarding the context-dependent interpretation of the effect of prenatal hormone exposure on behavior by suggesting that important moderating factors may explain the differing results in the literature. In particular, we uncover the importance of accounting for the subjective nature of need for status, which has been largely overlooked in previous work.
Emotional intelligence and its relationship with sales success

Emotional intelligence is a theoretical framework that organizes and integrates empirical research regarding emotions. Personal selling is the most effective marketing communication vehicle available to organizations because of its ability to adapt to specific customer needs. While two bodies of research have evolved regarding emotional intelligence theory and sales success predictors, little research has been carried out to link these two concepts together. This exploratory study tested a model of emotional intelligence and a measure of sales performance. The participants for the investigation were sales representatives in the personal home products industry. One hundred twenty-eight adult sales professionals completed a measure of emotional intelligence and sales performance data. Overall, the results supported the main hypothesis, which was that emotional intelligence positively related to sales performance. Moreover, the findings showed that the emotional intelligence of high performing sales professionals was significantly different from the emotional intelligence of low performing sales professionals. Age, formal education, professional experience, and ethnicity did not moderate the relationship between emotional intelligence and sales performance. The findings suggest that emotional intelligence, when viewed from a global perspective, provides a valuable link with existing theories regarding sales success. Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. TABLE OF CONTENTS Signatory Page List of Tables List of Figures Acknowledgements CHAPTER
Adolescent Depressive Symptoms and Substance Use : The Mediating Influence of Health Service Utilization

A large number of American adolescents suffer from depression and the consequences have been shown to be detrimental to their well-being. Adolescent substance use is also an increasing social problem due to the high usage rates and negative lifelong consequences for users. This paper explores the relationships between victimization, substance use, psychological health service utilization, and depressive symptoms in a sample of 4,757 adolescents. Using two waves of data from the National Longitudinal Study of Adolescent Health (Add Health), the results revealed a positive relationship between victimization and adolescent depressive symptoms, even after controlling for several demographic variables and previous depressive symptoms. However, victimization was only moderately associated with depressive symptoms, indirectly through cigarette or marijuana use. Moreover, psychological health service utilization partially mediated the significant association between adolescent substance use (cigarette or marijuana) and adolescent depressive symptoms. In conclusion, adolescents who experience higher levels of victimization may be more likely to use cigarettes or marijuana, which is positively associated with utilizing psychological health services, thereby elevating the risk of adolescent depressive symptoms. Intervention to reduce adolescent substance use may reduce vulnerability to adolescent depressive symptoms. iii AUTHOR'S ACKNOWLEDGMENTS I would first like to thank all of the members of my thesis committee at the Christina Falci. Since the beginning of my graduate studies, they have generously provided their time and support which have been invaluable to my progress and accomplishments thus far. I would especially like to thank my academic advisor and thesis chair, Dr. Kimberly A. Tyler, for her continual guidance and thoughtful comments throughout my time in the program and while conducting research. Not only did she read and edit countless drafts of this work and provide exceptional feedback, but she was a constant source of support and motivation. I cannot thank her enough for all of her advice. I would also like to thank the Sociology Department at the University of Nebraska –Lincoln for accepting me into their graduate program and for encouraging my growth as an academic in the field. I will be forever grateful for all of the opportunities that have been offered to me so far and for the many opportunities that will arise in my future because of the thoughtful professors, friends, and colleagues in the Sociology Department. Among the major psychiatric disorders, depression is one of the most common to occur and frequently begins during adolescence (Hankin 2006). Depression has been …
Receiver design for binary timing-based molecular communication

Molecular communication has been a promising approach to interconnect the nano-machines, which can perform basic calculation and some simple communication functions. In this paper, the receiver design for timing modulated molecular communication system is studied. In order to reduce the complexity of the receiver, several simplified detection algorithms are studied, and especially an order statistic based detection method is proposed to simplify the receiver. Performances of proposed detection algorithms are discussed. It is shown that the simplified receiver can achieve near optimal performance in symbol error probability.