Miracle-dz/UniFAR-FTUs huggingface dataset:
A Stochastic Model for Non-Stationary Outdoor K-Factor Variation

A dense urban cellular environment contains many different locations where a line-of-sight or specular signal component from the base station is present. The small scale fading at these locations is best characterized using the Ricean distribution. However, the K-factor of that distribution will vary from one location to the next. This paper presents a statistical model for dense urban vehicular non-stationary Ricean fading where K- factor changes gradually due to movement through changing surroundings. Using analysis of empirical radio channel measurements, a model is developed to represent K-factor variation as a stochastic process. An auto-regressive (AR) model is used to ensure the autocorrelation of the simulated K-factor process matches the empirical data. The model is verified by using it to simulate a non-stationary Ricean small scale fading envelope and comparing it to the fading envelope seen in the measurements.
AN ARTIFICIAL VISCOSITY APPROACH TO QUASISTATIC CRACK GROWTH

We introduce a new model of irreversible quasistatic crack growth in which the evolution of cracks is the limit of a suitably modified "-gradient flow of the energy functional, as the "viscosity" parameter " tends to zero. In this paper we consider the crack growth in brittle materials in the particular case of a preassigned crack path . We assume that is a regular arc with one endpoint on the boundary of the reference configuration , that there exists an initial connected crack starting from the boundary point, and that the crack remains connected during the evolution. Hence, such a crack will be completely determined by its length σ. The evolution is assumed to be irreversible, so that the length of the crack will be increasing in time, and quasistatic, i.e. at each time the configuration describing the body is in equilibrium. By configuration we mean a pair (u, σ) where u represents the displacement, and σ the length of the crack. The main new feature of this model is that it is based on a local stability criterion for the energy functional rather than on a global one. The choice of the total energy E(t)(u, σ), of a configuration (u, σ) at time t, is inspired by Griffith's idea (11) that the evolution of cracks in brittle materials is the result of the competition between the elastic energy of the body and the energy needed to extend the crack. For simplicity of exposition, we detail our study in the case of antiplane shears and therefore, u is a scalar function representing the displacement orthogonal to the plane of and the bulk part of the energy is given by the square of the L 2 -norm of the gradient of u. We consider the case of a homogeneous isotropic material and, according to Griffith's theory (11), we assume the surface energy to be proportional to the length σ of the crack, the constant of proportionality being given by the toughness of the material. The evolution is driven by time-dependent imposed boundary displacements ψ(t) on a part ∂D of the boundary, and applied boundary forces g(t) on the remaining part ∂N. The total energy, E(t)(u, σ), is the sum of the bulk energy and the surface energy minus the work of the applied forces g(t). Let AD(ψ(t), σ) denote the set of admissible displacements, i.e. displacements with finite bulk energy, compatible with the imposed boundary displacement ψ(t) and with the crack length σ. Let us recall that the functional E(t)(u, σ) is not differentiable, nor convex. It depends on σ both through the surface energy term and through the constraint on the set of admissible displacements. Note that, given t and σ, there exists a unique minimizer ut,σ of the energy E(t)(u, σ) in AD(ψ(t), σ). Then let us consider the minimal energy corresponding to the boundary data ψ(t) and to the
Antigenic and Genetic Characteristics of Swine-Origin 2009 A(H1N1) Influenza Viruses Circulating in Humans

Generation of Swine Flu As the newly emerged influenza virus starts its journey to infect the world's human population, the genetic secrets of the 2009 outbreak of swine influenza A(H1N1) are being revealed. In extensive phylogenetic analyses, Garten et al. (p. 197, published online 22 May) confirm that of the eight elements of the virus, the basic components encoded by the hemagglutinin, nucleoprotein, and nonstructural genes originated in birds and transferred to pigs in 1918. Subsequently, these formed a triple reassortant with the RNA polymerase PB1 that transferred from birds in 1968 to humans and then to pigs in 1998, coupled with RNA polymerases PA and PB2 that transferred from birds to pigs in 1998. The neuraminidase and matrix protein genes that complete the virus came from birds and entered pigs in 1979. The analysis offers insights into drug susceptibility and virulence, as well as raising the possibility of hitherto unknown factors determining host specificity. A significant question is, what is the potential for the H1 component of the current seasonal flu vaccine to act as a booster? Apart from the need for ongoing sequencing to monitor for the emergence of new reassortants, future pig populations need to be closely monitored for emerging influenza viruses. Evolutionary analysis suggests a triple reassortant avian-to-pig origin for the 2009 influenza A(H1N1) outbreak. Since its identification in April 2009, an A(H1N1) virus containing a unique combination of gene segments from both North American and Eurasian swine lineages has continued to circulate in humans. The lack of similarity between the 2009 A(H1N1) virus and its nearest relatives indicates that its gene segments have been circulating undetected for an extended period. Its low genetic diversity suggests that the introduction into humans was a single event or multiple events of similar viruses. Molecular markers predictive of adaptation to humans are not currently present in 2009 A(H1N1) viruses, suggesting that previously unrecognized molecular determinants could be responsible for the transmission among humans. Antigenically the viruses are homogeneous and similar to North American swine A(H1N1) viruses but distinct from seasonal human A(H1N1).
Compression-Based Compressed Sensing

Modern compression codes exploit signals’ complex structures to encode them very efficiently. On the other hand, compressed sensing algorithms recover “structured” signals from their under-determined set of linear measurements. Currently, there is a noticeable gap between the types of structures used in the area of compressed sensing and those employed by state-of-the-art compression codes. Recent results in the literature on deterministic signals aim at bridging this gap through devising compressed sensing decoders that employ compression codes. This paper focuses on structured stochastic processes and studies application of lossy compression codes to compressed sensing of such signals. The performance of the formerly proposed compressible signal pursuit (CSP) optimization is studied in this stochastic setting. It is proved that in the low-distortion regime, as the blocklength grows to infinity, the CSP optimization reliably and robustly recovers <inline-formula> <tex-math notation="LaTeX">$n$ </tex-math></inline-formula> instances of a stationary process from its random linear measurements as long as <inline-formula> <tex-math notation="LaTeX">$n$ </tex-math></inline-formula> is slightly more than <inline-formula> <tex-math notation="LaTeX">$n$ </tex-math></inline-formula> times the rate-distortion dimension (RDD) of the source. It is also shown that under some regularity conditions, the RDD of a stationary process is equal to its information dimension. This connection establishes the optimality of CSP at least for memoryless stationary sources, which have known fundamental limits. Finally, it is shown that CSP combined by a family of universal variable-length fixed-distortion compression codes yields a family of universal compressed sensing recovery algorithms.
Balanced energy and coverage guaranteed protocol for wireless sensor networks

Wireless platforms are becoming less expensive and more powerful, enabling the promise of widespread use, everything from health monitoring to military sensing. In large scale applications like military surveillance, sensing coverage is essential for target detection and optimization of power consumption is important for lifetime extension of the network. Coverage and long lifetime network are two important factors and challenges for sensor networks. In this paper, we propose a new scheme, named as BECG, which remains the best coverage of the sensing area and energy balanced scheduling for all sensors. It allows nodes to determine when they can switch to sleep mode during operation. The energy efficiency of the proposed scheme is shown by intelligent decisions making. Each node in the network takes decision to turn on or turn off in a distributed manner that results a set of small number of active nodes throughout the lifetime of the network and covers sensing area of interest for target detection. It reduces redundancy, power consumption and increase the lifetime of a network. At first we applied our algorithm for a random topology and then we evaluate the performance of the network by simulation.
A flow-based optimization model for throughput-oriented relay node placement in wireless sensor networks

This work addresses the relay node placement problem in wireless sensor networks. We consider a scenario in which all sensor nodes stream data towards sink nodes. Additional relay nodes can be placed with the aim of optimizing overall network performance in terms of data throughput. We formalize the problem with a linear, mixed integer mathematical programming model. We include a number of constraints and penalties to closely model the wireless environment. When relay nodes can be placed anywhere, we define their possible locations using a discrete grid. Model solutions specify both where to place the relays and the paths for routing. Through extensive simulation experiments, we compare model solutions against a state-of-the-art dynamic routing protocol to assess the quality of the routes, and against a relay node placement heuristic to evaluate relay positioning. To tackle the computational complexity, we also propose and study the effect of different strategies for determining the grid resolution. Additionally, an experimental validation carried out in a real testbed shows that the computed solutions clearly increase network performance by enabling the reception of larger number of data packets at the sinks and determining a fair QoS distribution among the nodes. Finally, we propose an on-line application, in which the model is built and solved on-demand, to adapt to changes in traffic patterns induced by external events, and the results are rapidly spread throughout the network and used to modify relay node positioning and routing paths.
Architecture for Automated Tagging and Clustering of Song Files According to Mood

Music is one of the basic human needs for recreation and entertainment. As song files are digitalized now a days, and digital libraries are expanding continuously, which makes it difficult to recall a song. Thus need of a new classification system other than genre is very obvious and mood based classification system serves the purpose very well. In this paper we will present a well-defined architecture to classify songs into different mood-based categories, using audio content analysis, affective value of song lyrics to map a song onto a psychological-based emotion space and information from online sources. In audio content analysis we will use music features such as intensity, timbre and rhythm including their subfeatures to map music in a 2-Dimensional emotional space. In lyric based classification 1-Dimensional emotional space is used. Both the results are merged onto a 2-Dimensional emotional space, which will classify song into a particular mood category. Finally clusters of mood based song files are formed and arranged according to data acquired from various Internet sources.
Reliability and Validity of the Online Continuous Performance Test Among Young Adults

Continuous Performance Tests (CPTs) are used in research and clinical contexts to measure sustained attention and response inhibition. Reliability and validity of a new Online Continuous Performance Test (OCPT) was assessed. The OCPT is designed for delivery over the Internet, thereby opening new opportunities for research and clinical application in naturalistic settings. In Study 1, participants completed the OCPT twice over a 1-week period. One test was taken at home and one in the laboratory. Construct validity was assessed against a gold standard CPT measure. Results indicate acceptable reliability between the home- and laboratory-administered tests. Modest to high correlations were observed between the OCPT scales and the corresponding scales of the gold standard CPT. Study 2 examined whether the OCPT may discriminate participants with attention deficit hyperactivity disorder from healthy controls. Results revealed significantly higher rates of omission and commission errors and greater response time variability in participants with attention deficit hyperactivity disorder relative to healthy controls. These results support the reliability and validity of the OCPT and suggest that it may serve as an effective tool for the assessment of attention function in naturalistic settings.
Prediction based Lossless compression scheme for Bayer color filter array image

In most digital cameras Bayer color filter array images captured and demosaicing is generally carried out before compression. Recently it was compression first scheme o u t perform the conventional demosaicing first schemes in terms o f output image quality. An e f f i c i e n t prediction based lossless compression scheme for Bayer filter color images proposed
Introducing a New Classification of Early Childhood Disorders: DC:0-5™.

ZERO TO THREE • JANUARY 2017 ZERO TO THREE published DC:0–5TM: Diagnostic Classification of Mental Health and Developmental Disorders of Infancy and Early Childhood in December 2016. This article is a brief guide to DC:0–5, designed both for readers who are familiar with DC:0–3R and the original DC:0–3 and those for whom DC:0–5 is their introduction to this diagnostic classification system. The authors are members of the Diagnostic Classification Revision Task Force who completed the update and revision. Abstract This article introduces the revised and updated DC:0–5TM: Diagnostic Classification of Mental Health and Developmental Disorders of Infancy and Early Childhood. The authors describe the past and current efforts to create a developmentally based classification system for very young children. DC:0–3, published in 1994 by ZERO TO THREE, was created to address the significant need for a systematic, developmentally based approach to the classification of mental health and developmental difficulties in the first 4 years of life (i.e., birth through 3 years old). Based on advances in knowledge, ZERO TO THREE decided to revise DC:0–3 and published DC:0–3R in 2005. The current revision, DC:0–5, was substantial, expanding the age range from 3 years old to 5 years old and expanding the number of diagnostic categories and clinical disorders from previous versions. The authors describe the new features of DC:0–5, detail three levels of the training model, highlight other DC:0–5 resources, and discuss the future of DC:0–5.
A decision-based approach to econometric modelling

In many applications it is necessary to use a simple and therefore highly misspecified econometric model as the basis for decision-making. We propose an approach to developing a possibly misspecified econometric model that will be used as the beliefs of an expected utility maximiser. An objective function that measures the value of predictive distributions in decision-making is introduced and used in estimation, selection and evaluation of parametric or semiparametric models. The methods proposed also provide an econometric approach for developing arbitrary parametric action rules such as technical trading rules. The approach is compared in detail with existing methods and is applied in the context of a CARA investor’s decision problem where analytical, simulation and empirical results suggest it is very effective.
A Criterion for the Complete Deposition of Magnetic Beads on the Walls of Microchannels

This paper analyzes numerical simulations of the trajectories of magnetic beads in a microchannel, with a nearby permanent cubical magnet, under different flow and magnetic conditions. Analytically derived local fluid velocities and local magnetic forces have been used to track the particles. A centered position and a lateral position of the magnet above the microchannel are considered. The computed fractions of deposited particles on the walls are compared successfully with a new theoretically derived criterion that imposes a relation between the sizes of the magnet and the microchannel and the particle Stokes and Alfvén numbers to obtain the complete deposition of the flowing particles on the wall. In the cases in which all the particles, initially distributed uniformly across the section of the microchannel, are deposited on the walls, the simulations predict the accumulation of the major part of particles on the wall closest to the magnet and near the first half of the streamwise length of the magnet.
Time reversal DORT and MUSIC methods for extended targets detection and imaging

In this paper, the imaging methods with transmitting-mode electromagnetic DORT and TR-MUSIC for extended targets applications are proposed. The full-wave analysis of the multiple scattering models is carried out, and its eigenvalue system and pesudospectrum definition are discussed in detail. Compared with the echo-mode cases, the superiority is realized as follows. Firstly, it leads to more accurate location and higher imaging resolution because the noncoincident arrays actually increase the effective aperture of the array; secondly, the proposed algorithms are proved to be more flexible and practical; furthermore, it enlarges the coverage area of the detection system due to the reciprocal mapping between the transmitter and receiver spaces. Therefore, it suggests the great potential in the areas of extended targets detection, through-wall radar imaging and medical examinations.
Correlation inequalities: a useful tool in the theory of LDPC codes

It is shown that a correlation inequality of statistical mechanics can be applied to low-density parity-check codes. Thanks to this tool we prove that the growth rate of regular LDPC codes, can be exactly calculated by iterative methods, at least on the interval where it is a concave function of the relative weight of code words. We also consider communication over a binary input additive white Gaussian noise channel with a Poisson LDPC code and prove that (at least part of) the GEXIT curve (associated to MAP decoding) can also be computed exactly by the belief propagation decoder. In both problems, the correlation inequality yields sharp lower bounds. We also use a non trivial extension of the interpolation techniques that have recently led to rigorous results in spin glass theory and in the SAT problem
CONIC: Content-Oriented Network with Indexed Caching

In this paper, we present Content-Oriented Network with Indexed Caching (CONIC), a deployable and self-scaling architecture to exploit spare storage and bandwidth from end-systems to eliminate redundant traffic and enable efficient and fast access to content. Our trace-driven simulation indicates that CONIC can reduce 25% to 50% traffic volume and can cumulatively halve the latency of content access in the real-world network environment. Also, our prototype implementation verifies the deployability of the CONIC architecture.
Child Maltreatment, Delinquent Behavior, and School Factors as Predictors of Depressive Symptoms from Adolescence to Adulthood: A Growth Mixture Model

Previous methodological approaches have not been flexible enough to model the heterogeneity of depressive symptoms or to identify variations between prototypical trajectories conditional on risk and protective factors. The current study examined latent class trajectories of depressive symptoms using data from 3,819 respondents of the Adolescent Health Survey. Four trajectory profiles of depressive symptoms were identified: low-stable, high-decreasing, low-increasing, and moderate-decreasing. A broad array of risk factors were included into the modeling procedure to identify predictors of group membership. Relative to the low-stable group, membership in one of the three symptomatic groups (i.e., heightened depressive symptoms) was predicted by poverty, low self-esteem, gender, drinking frequency, poor academic outcomes, delinquency, and child maltreatment type. This study contributes to our understanding about the longitudinal manifestations of depression and identifies a broad array of factors significantly related to pathways of resilience.
A Methodological Survey and Proposed Algorithm on Image Segmentation using Genetic Algorithm

literature review attempts to provide a brief overview of some of the most common image segmentation techniques. It discusses Edge detection technique, Thresholding technique, Region growing based technique, Watershed technique, Compression based method, Histogram based segmentation and Graph partitioning method. With the growing research on image segmentation, it has become important to categorise the research outcomes and provide readers with an overview of the existing segmentation techniques in each category. In this paper different method of implementing genetic algorithm has been reviewed. Finally, summaries and review of research work on wrapper approach for image segmentation techniques has been represented. General Terms Image processing, image segmentation, image classification, genetic algorithm, wrapper approach, object detection. Keywordsimage, Genetic algorithm, segmentation techniques, wrapper approach.
Break Out the Tissues : Automatic Detection of Sadness in Film Audio

Classification of emotion in visual and audio media continue s to be a difficult task for computers. In this work, we propose a system that cla ssifies scenes from popular movies as sad or not sad by examining the audio conten t of the scene. We consider that audio content in movies contains noisy spee ch and noisy music, adopting techniques from both speech and music analysis for classification. Features used for this task include Mel-Frequency Cepstral Coe fficients and statistics about the fundamental frequency, f0. We investigate classi fying clips using both sets of features and three classification algorithms: K-Nea rest Neighbors, a clustering algorithm called Lump, and Support Vector Machines. We achieve 79% accuracy using the derivative of f0 and a K-Nearest Neighbor s classifier.
Authentication in a Multi-access IMS Environment

The standard ISIM-based authentication mechanism of IMS is only intended for mobile phones and cannot be used for fixed IMS clients on stationary devices without SIM cards. This paper presents the authentication schemes dedicated for fixed IMS clients. Such schemes are necessary in order to extend the usage of IMS to fixed environments. Authentication solutions for other applications than the IMS client are also described. These applications are assumed to be located on the same stationary device as the IMS client, and might for example be browsers, contact lists and email clients. Finally, a single-sign-on mechanism is proposed. It is designed to simplify the authentication process without compromising the security.