Miracle-dz/UniFAR-FTUs huggingface dataset:
Collaborative Cyclostationary Spectrum Sensing for Cognitive Radio Systems

This paper proposes an energy efficient collaborative cyclostationary spectrum sensing approach for cognitive radio systems. An existing statistical hypothesis test for the presence of cyclostationarity is extended to multiple cyclic frequencies and its asymptotic distributions are established. Collaborative test statistics are proposed for the fusion of local test statistics of the secondary users, and a censoring technique in which only informative test statistics are transmitted to the fusion center (FC) during the collaborative detection is further proposed for improving energy efficiency in mobile applications. Moreover, a technique for numerical approximation of the asymptotic distribution of the censored FC test statistic is proposed. The proposed tests are nonparametric in the sense that no assumptions on data or noise distributions are required. In addition, the tests allow dichotomizing between the desired signal and interference. Simulation experiments are provided that show the benefits of the proposed cyclostationary approach compared to energy detection, the importance of collaboration among spatially displaced secondary users for overcoming shadowing and fading effects, as well as the reliable performance of the proposed algorithms even in very low signal-to-noise ratio (SNR) regimes and under strict communication rate constraints for collaboration overhead.
Feature Trees over Arbitrary Structures

This paper presents a family of rst order feature tree theories, indexed by the theory of the feature labels used to build the trees. A given feature label theory, which is required to carry an appropriate notion of sets, is conservatively extended to a theory of feature trees with the predicates xt]y (feature t leads from the root of tree x to the tree y), where we have to require t to be a ground term, and xt# (feature t is deened at the root of tree x). In the latter case, t might be a variable. Together with the notion of sets provided by the feature label theory, this yields a rst-class status of arities. We present a quantiier elimination procedure to reduce any sentence of the feature tree theory to an equivalent sentence of the feature label theory. Hence, if the feature label theory is decidable, the feature tree theory is too. If the feature label theory is the theory of innnitely many constants and nite sets over innnitely many constants, we obtain an extension of the feature theory CFT, giving rst-class status to arities. As an another application, we obtain decidability of the theory of feature trees, where the feature labels are words, and where the language includes the successor function on words, lexical comparison of words and rst-class status of arities.
AYP Status, Urbanicity, and Sector: School-to-School Variation in Instruction

This study investigates whether adequate yearly progress (AYP) status, locale, and sector—common variables used to judge the quality of schools—accurately signal true differences in instructional practices in high school mathematics and science. Using data from the High School Longitudinal Study (HSLS), we find the school-to-school variation in instructional practices to be minimal. Controlling for a variety of school and teacher characteristics, we find that there is no difference in the use of developmental instruction between schools that make AYP and schools that do not, urban and nonurban schools, and public and private schools.
Implementation of a real-time object detection system on a TI TMS320DM6437 DSP

This paper describes the realization of visual object detection system on a DSP. It proposes several approaches, which can speed-up the detection system program to be run in a real-time on a Texas Instruments TMS320DM6437 DSP. Validity of the proposed techniques confirmed during experimental approbation on the real hardware.
A Novel Particle Swarm Optimization Based on the Self-Adaptation Strategy of Acceleration Coefficients

Based on a new self-adaptation strategy for acceleration coefficients ($ACs$), a novel particle swarm optimization ($PSO$)algorithm is presented in this paper. In the newly proposed algorithm, each particle has different $ACs$ which is on-line updated according to its current search state. Numerical experiments on several typical global optimization problems show that the improvements brought about by the algorithm in this paper is greater than that of the canonical $PSO$ ($CPSO$) in terms of effectiveness.
Solid-organ transplantation in HIV-infected patients.

Many centers do not consider asymptomatic HIV-positive patients to be candidates for solid-organ transplantation, although there are no data to indicate that the outcome of transplantation is worse among these patients than among other transplant recipients. This Sounding Board reviews the ethical arguments for considering tranplantatation in patients with HIV infection as similar to transplantation in patients with other chronic illnesses.
Qigong, singing, and health: A possible composition?

This study aimed to search evidence available in literature on the effects of qigong as a breathing relaxation technique to reduce music performance anxiety, as well as its effects on singers’ health and wellbeing. Integrative literature review was selected as the method of research. The inclusion criteria were: (1) publications in English, Spanish, and Portuguese from January 2000 to December 2010; (2) publications with abstracts available at and indexed in PubMed, Web of Science, PsycINFO, and LILACS. Twenty-two articles met the inclusion criteria. The results provided interesting tools for performers to integrate emotional, mental, and physical skills to efficiently and effectively improve their performance. Applied research through cross-disciplinary collaboration and innovative methods, such as qigong, may offer new possibilities to meet these challenges.
Universit a Degli Studi Design and Maintenance of Data-intensive W Eb Sites

Many Web sites include signi cant and substantial pieces of information, in a way that is often di cult to share, correlate and maintain. In many cases the management of a Web site can greatly bene t from the adoption of methods and techniques borrowed from the database eld. This paper introduces a methodology for designing and maintaining large Web sites based on the assumption that data to be published in the site are managed using a DBMS. We see the process of designing the site as the result of two intertwined activities: the database design and the hypertext design. Each of these is further divided in a conceptual design phase and a logical design phase, based on speci c data models. A new logical data model, called adm, is used to describe the structure of a Web hypertext. It is page-oriented, in the sense that the main construct is the one of page-scheme, providing an intensional description of a class of pages in the site. Based on the adm scheme of the site, we introduce a language, called Penelope, that allows to automatically generate HTML pages starting from the database content. Penelope is also able to correlate di erent pages in a complex hypertext using a suitable URL invention mechanism to guarantee reference integrity. adm and Penelope strongly support site maintenance: the rst provides a concise description of the site structure; it allows to reason about the overall organization of pages in the site, in order to evaluate the e ectiveness and e ciency of the chosen structure, and possibly to restructure it; at the same time, Penelope alleviates the burden of managing HTML les by hand, and guarantees link consistency in presence of updates and reorganizations.
Compared study of the analyzing methods for EEG data

There are large numbers of physiologic and diseased information in electroencephalogram (EEG) signals. It can provide clinical diagnosis information for doctors by the effective processing of EEG data. Therefore, the analyzing methods of EEG are the key technology of the brain-computer interface. Based on wavelet transform, short-time Fourier transform, spectrum analysis and the Wigner distribution, some methods were used to analyze the EEG signals collected from drinking testers and no-drinking testers. Experimental results showed that there were relevant effects of the chronic alcohol's stimulation on the nervous system in a certain extent. In the drinking tester's EEG data, transient pulse signals appeared in the nearby of 0.6s, the energy of EEG power spectrum concentrated obviously in the low frequency. It is clear that the methods presented in this paper could extract the feature effectively.
Exploiting harmonic periods to improve linearly approximated response-time upper bounds

Hard real-time embedded systems need to guarantee that tasks always meet their deadlines. Exact schedulability tests can guarantee this for fixed-priority, preemptively scheduled systems even under the tightest resource constraints. However, these tests are pseudo-polynomial in complexity. This can become a limiting factor in open systems where it might be necessary to have run-time admission tests. A linear-time sufficient test [1] has therefore been developed to estimate response-time upper bounds. In line with utilization-based sufficient tests, we propose to improve this test for task sets with harmonically related task periods. Moreover, we make it possible to reuse this test in the context of hierarchically scheduled (partitioned) resources. In such systems several applications are given a virtual share (budget) of the processor. By modeling the unavailability of processor resources to an application as two fictive tasks, we can also use a budget's period to improve response-time bounds1.
Using Krylov subspace and spectral methods for solving complementarity problems in many‐body contact dynamics simulation

Many‐body dynamics problems are expected to handle millions of unknowns when, for instance, investigating the three‐dimensional flow of granular material. Unfortunately, the size of the problems tractable by existing numerical solution techniques is severely limited on convergence grounds. This is typically the case when the equations of motion embed a differential variational inequality problem that captures contact and possibly frictional interactions between rigid and/or flexible bodies. As the size of the physical system increases, the speed and/or the quality of the numerical solution decreases. This paper describes three methods – the gradient projected minimum residual method, the preconditioned spectral projected gradient with fallback method, and the modified proportioning with reduced gradient projection method – that demonstrate better scalability than the projected Jacobi and Gauss–Seidel methods commonly used to solve contact problems that draw on a differential‐variational‐inequality‐based modeling approach. Copyright © 2013 John Wiley & Sons, Ltd.
Filtering noise in color images using adaptive-neighborhood statistics

Various nonlinear, fixed-neighborhood techniques based on local statistics have been proposed in the literature for filtering noise in color images. We present adaptive-neighborhood filtering (ANF) techniques for noise removal in color images. The main idea is to find for each pixel (called the ‘‘seed’’ when being processed) a variable-shaped, variable-sized neighborhood that contains only pixels that are similar to the seed. Then, statistics computed within the adaptive neighborhood are used to derive the filter output. Results of the ANF techniques are compared with those given by a few multivariate fixed-neighborhood filters: the double-window modified trimmed-mean filter, the generalized vector directional filter— double-window—? -trimmed mean filter, the adaptive hybrid multivariate filter, and the adaptive nonparametric filter with Gaussian kernel. It is shown that the ANF techniques provide better visual results, effectively suppressing noise while not blurring the edges; the results are also better in terms of objective measures (such as normalized mean-squared error and normalized color difference) than the results of the other methods.
Unravelling the Myth/Metaphor Layer in Causal Layered Analysis

This paper investigates how the myth/metaphor layer of Inayatullah's Causal Layered Analysis is formed, using an embodied cognitive approach. The very way we experience the world, move in it, interact within it and orient our body to our environment generates patterns and concepts that form as metaphors. Language is saturated in metaphor. As we interact together shared metaphors connect together to emerge and take shape as myths. These are the building blocks of Inayatullah's worldview layer. The worldview that emerges from social interactions of a group of people form a particular arrangement of interlinking elements from the myth/metaphor layer. The worldview informs the systemic layer, which in turn informs the litany of everyday life. Any particular worldview is therefore only ever one within many possible ways of interlinking the mythic and epistemic elements. It is easy to fall into the trap of assuming our particular worldview is the best, or even the only true worldview. CLA helps us to avoid this problem as it problematises the present and find new metaphors to enable us to envision alternative and preferred futures.
Note atlab-based tool for ECG and HRV analysis

Delivery of electroporation pulses in electroporation-based treatments could potentially induce heartrelated effects. The objective of our work was to develop a software tool for electrocardiogram (ECG) analysis to facilitate detection of such effects in pre-selected ECGor heart rate variability (HRV) parameters. Our software tool consists of five distinct modules for: (i) preprocessing; (ii) learning; (iii) detection and classification; (iv) selection and verification; and (v) ECG and HRV analysis. Its key features are: automated selection of ECG segments from ECG signal according to specific user-defined requirements (e.g., selection of relatively noise-free ECG segments); automated detection of prominent heartbeat features, such as Q, R and T wave peak; automated classification of individual heartbeat as normal or abnormal; displaying of heartbeat annotations; quick manual screening of analyzed ECG signal; and manual correction of annotation and classification errors. The performance of the detection and classification module was evaluated on 19 two-hour-long ECG records from Long-Term ST database. On average, the QRS detection algorithm had high sensitivity (99.78%), high positive predictivity (99.98%) and low detection error rate (0.35%). The classification algorithm correctly classified 99.45% of all normal QRS complexes. For normal heartbeats, the positive predictivity of 99.99% and classification error rate of 0.01% were achieved. The software tool provides for reliable and effective detection and classification of heartbeats and for calculation of ECG and HRV parameters. It will be used to clarify the issues concerning patient safety during the electroporation-based treatments used in clinical practice. Preventing the electroporation pulses from interfering with the heart is becoming increasingly important because new applications of electroporation-based treatments are being developed which are using endoscopic, percutaneous or surgical means to access internal tumors or tissues and in which the target tissue can be located in immediate vicinity to the heart.
Ambiguity Management in Natural Language Generation

In natural language generation (NLG) it can be desirable to preserve some ambiguities rather than try to eliminate them. The question is, which ones are so liable to misinterpretation that they should be removed, and which can be allowed to remain. Our approach to the problem is to notify the user of an NLG system of ambiguities that might be present in generated text, and to advise him/her as to how serious these might be for readers of the text. The degree to which each ambiguity is considered serious is adjusted by the responses of users upon seeing instances of that ambiguity. The system learns from these interactions, and an ambiguity tolerance level is thereby established. The ultimate goal of this research is to build an adaptive ambiguity notification tool that incorporates these features and can be used with an NLG system.
An Adaptive Restart Implementation of DIRECT

This paper is concerned with the algorithmic behavior of the DIRECT (DIviding RECTangles) algorithm. We show that DIRECT is sensitive to additive scaling, and this sensitivity can affect convergence. We present a modified version of the algorithm, and illustrate the effectiveness of our modification with numerical results. DIRECT (DIviding RECTangles) (16) is an optimization algorithm de- signed to aggressively search for global minima of a real valued objective function over a bound-constrained domain. The algorithm does not use derivative information in its search; instead, it relies on the iteration history to determine future sample locations. The strength of DIRECT is the balanced global and local search it performs. This article describes conditions under which the balance of the algorithm becomes skewed. We observe that DIRECT is sensitive to additive scaling, and has slow asymptotic convergence. We suggest a modification to the algorithm, and present test results that illustrate the effectiveness of our modification. For this paper, we are concerned with a bound constrained opti- mization problem: (P) min x2­ f(x), where f : R n ! R, (1) with ­ = {x 2 R n : li · xi · ui, i = 1.n}, and l,u 2 R n given. We
Small disks and semiclassical resonances

We study the effect on quantum spectra of the existence of small circular disks in a billiard system. In the limit where the disk radii vanish there is no effect, however this limit is approached very slowly so that even very small radii have comparatively large effects. We include diffractive orbits which scatter off the small disks in the periodic orbit expansion. This situation is formally similar to edge diffraction except that the disk radii introduce a length scale in the problem such that for wavelengths smaller than the order of the disk radius we recover the usual semiclassical approximation; however, for wavelengths larger than the order of the disk radius there is a qualitatively different behaviour. We test the theory by successfully estimating the positions of scattering resonances in geometries consisting of three and four small disks.
Distance metric between 3D models and 2D images for recognition and classification

A transformation metric to measure the similarity between 3-D models and 2-D images is proposed. The transformation metric measures the amount of affine deformation applied to the object to produce the given image. A simple, closed-form solution for this metric is presented. This solution is optimal in transformation space, and it is used to bound the image metric from both above and below. The transformation metric can be used in several different ways in recognition and classification tasks. <<ETX>>
HLTC-HKUST: A Neural Network Paraphrase Classifier using Translation Metrics, Semantic Roles and Lexical Similarity Features

This paper describes the system developed by our team (HLTC-HKUST) for task 1 of SemEval 2015 workshop about paraphrase classification and semantic similarity in Twitter. We trained a neural network classifier over a range of features that includes translation metrics, lexical and syntactic similarity score and semantic features based on semantic roles. The neural network was trained taking into consideration in the objective function the six different similarity levels provided in the corpus, in order to give as output a more fine-grained estimation of the similarity level of the two sentences, as required by subtask 2. With an F-score of 0.651 in the binary paraphrase classification subtask 1, and a Pearson coefficient of 0.697 for the sentence similarity subtask 2, we achieved respectively the 6th place and the 3rd place, above the average of what obtained by the other contestants.
Structured language modeling

This paper presents an attempt at using the syntactic structure in natural language for improved language models for speech recognition. The structured language model merges techniques in automatic parsing and language modeling using an original probabilistic parameterization of a shift-reduce parser. A maximum likelihood re-estimation procedure belonging to the class of expectation-maximization algorithms is employed for training the model. Experiments on the Wall Street Journal and Switchboard corpora show improvement in both perplexity and word error rate? word lattice rescoring? over the standard 3-gram language model.
Bone morphogenetic protein 4 modulates c-Kit expression and differentiation potential in murine embryonic aorta-gonad-mesonephros haematopoiesis in vitro

The transforming growth factor‐β‐related factor bone morphogenetic protein 4 (BMP4) is expressed in the human embryonic aorta‐gonad‐mesonephros (AGM) coincident with the emergence of haematopoietic cells and influences postnatal mammalian haematopoietic stem cells in vitro. To investigate the role of BMP4 in mammalian embryonic haematopoiesis, cells were isolated from murine AGM and two populations of CD34+ cells with different levels of c‐Kit expression and multipotency were identified. CD34+/c‐Kithigh cells express CD45 and are haematopoietic‐restricted progenitors. In contrast, CD34+/c‐Kitlow cells are Flk1+/CD45neg and generate adherent colonies in ex vivo culture that resemble haemangioblast colonies identified in other systems. The addition of BMP4 to AGM cells resulted in expansion of the CD34+/c‐Kitlow cell pool within 48 h, via a combination of down modulation of the c‐Kit receptor in CD34+/c‐Kithigh cells and proliferation. In long‐term culture, BMP4 increased the growth/survival of CD34+/c‐Kithigh haematopoietic progenitors, effects that were blocked by BMP inhibitors. CD34+/c‐Kithigh progenitors cultured with BMP4 also generated adherent colonies typical of c‐Kitlow cells. These results suggest that BMP4 regulates c‐Kit expression and differentiation potential in CD34+ AGM cells and supports a role for BMP signalling in the maintenance of multipotency during embryonic haematopoiesis, providing an insight into stem cell homeostasis within the mammalian haematopoietic niche.
Ad hoc networks security

Countermeasures against node misbehavior and selfishness are mandatory requirements in mobile ad hoc networks. Selfishness that causes lack of node activity cannot be solved by classical security means that aim at verifying the correctness and integrity of an operation. In this paper we outline an original security mechanism (CORE) based on reputation that is used to enforce cooperation among the nodes of a MANET. We then investigate on its robustness using an original approach: we use game theory to model the interactions between the nodes of the ad hoc network and we focus on the strategy that a node can adopt during the network operation. As a first result, we obtained the guidelines that should be adopted when designing a cooperative security mechanism that enforces mobile nodes cooperation. Furthermore, we were able to show that when no countermeasures are taken against misbehaving nodes, network operation can be heavily jeopardized. We then showed that the CORE mechanism is compliant with guidelines provided by the game theoretic model and that, under certain conditions, it assures the cooperation of at least half of the nodes of a MANET.
Coercions in a polymorphic type system

We incorporate the idea of coercive subtyping, a theory of abbreviation for dependent type theories, into the polymorphic type system in functional programming languages. The traditional type system with let-polymorphism is extended with argument coercions and function coercions, and a corresponding type inference algorithm is presented and proved to be sound and complete.