Miracle-dz/UniFAR-FTUs huggingface dataset:
Data Communications Using Guided Elastic Waves by Time Reversal Pulse Position Modulation: Experimental Study

In this paper, we present and demonstrate a low complexity elastic wave signaling and reception method to achieve high data rate communication on dispersive solid elastic media, such as metal pipes, using piezoelectric transducers of PZT (lead zirconate titanate). Data communication is realized using pulse position modulation (PPM) as the signaling method and the elastic medium as the communication channel. The communication system first transmits a small number of training pulses to probe the dispersive medium. The time-reversed probe signals are then utilized as the information carrying waveforms. Rapid timing acquisition of transmitted waveforms for demodulation over elastic medium is made possible by exploring the reciprocity property of guided elastic waves. The experimental tests were conducted using a National Instrument PXI system for waveform excitation and data acquisition. Data telemetry bit rates of 10 kbps, 20 kbps, 50 kbps and 100 kbps with the average bit error rates of 0, 5.75 x 10-4, 1.09 x 10-2 and 5.01 x 10-2, respectively, out of a total of 40, 000 transmitted bits were obtained when transmitting at the center frequency of 250 kHz and a 500 kHz bandwidth on steel pipe specimens. To emphasize the influence of time reversal, no complex processing techniques, such as adaptive channel equalization or error correction coding, were employed.
Adaptive Volterra Filters With Evolutionary Quadratic Kernels Using a Combination Scheme for Memory Control

This paper proposes a new paradigm for adaptive Volterra filtering using a time-variant size of the quadratic kernel memory in order to optimally identify any unknown transversal second-order nonlinear system. To this end, competing Volterra structures of different sizes are employed in a hierarchical combination scheme so as to find the best configuration of the second-order kernel memory, using the already known diagonal-coordinate representation. The length and number of required quadratic kernel diagonals can be concurrently estimated by monitoring the combination performance. Subsequently, the memory size of the involved models is dynamically increased or decreased, following a set of intuitive rules. Since this automatic memory adaptation is performed along with the coefficient updates, an efficient Volterra filter is realized, offering great flexibility and minimizing the risk of under- or overmodeling any given quadratic nonlinearity. Besides the straightforward scheme, a simplified version is presented, greatly reducing the algorithmic demands. This efficient version is based on a virtualization of the competing Volterra filters by jointly using common coefficients and hence exhibits a computational complexity suitable for practical implementations. The robust estimation performance of the approach is demonstrated by various examples for a nonlinear acoustic echo cancellation scenario, involving stationary noise, real speech signals and realistic Volterra kernels.
Using SMS text messaging to assess moderators of smoking reduction: Validating a new tool for ecological measurement of health behaviors.

OBJECTIVE Understanding the psychological processes that contribute to smoking reduction will yield population health benefits. Negative mood may moderate smoking lapse during cessation, but this relationship has been difficult to measure in ongoing daily experience. We used a novel form of ecological momentary assessment to test a self-control model of negative mood and craving leading to smoking lapse. DESIGN We validated short message service (SMS) text as a user-friendly and low-cost option for ecologically measuring real-time health behaviors. We sent text messages to cigarette smokers attempting to quit eight times daily for the first 21 days of cessation (N-obs = 3,811). MAIN OUTCOME MEASURES Approximately every two hours, we assessed cigarette count, mood, and cravings, and examined between- and within-day patterns and time-lagged relationships among these variables. Exhaled carbon monoxide was assessed pre- and posttreatment. RESULTS Negative mood and craving predicted smoking two hours later, but craving mediated the mood-smoking relationship. Also, this mediation relationship predicted smoking over the next two, but not four, hours. CONCLUSION Results clarify conflicting previous findings on the relation between affect and smoking, validate a new low-cost and user-friendly method for collecting fine-grained health behavior assessments, and emphasize the importance of rapid, real-time measurement of smoking moderators.
Self-localization capable mobile sensor nodes

Position sensing systems for indoor environments have one common problem: The setup effort of the whole system. GPS-supported localization is simple and fast to implement and the reference grid is ubiquitous. However, in locations where the signals of GPS are not available, e.g. indoor, or where the technique is not accurate enough, other position sensing systems have to be used. Usually, a reference grid will be provided by an administrator: Reference points must be deployed and programmed with the correct location information. Especially for temporary installations and dynamic surroundings the setup costs are very high. In our work, we developed a robotic platform, which is capable of deploying itself autonomously and which can operate as a mobile reference point equipped with ultra sound transmitters. Relying on a combination of two controllers and an odometry system, the platform is able to drive on a complex spline-like trace using only a few supporting points. We also investigated the problem for the localization system itself. The detection field of our ultra sound based system is a full hemisphere. Within this domain, we can measure the distances between nodes exploiting the time of flight technique as well as the angle of arrival. Finally, the system can also be used as a sonar system for passive obstacles detection.
A Practical Approach To The Modelling, Visualising And Executing Of Reactive Systems

Reliability (like recoverability and fault tolerance) has often been considered as a crucial quality aspect of the reactive system. In this way, the designer can put great attention and effort into increasing their reliability level. On the other hand, the growing popularity and massive usage these systems on various domains could be noticed. This phenomenon force activities that lead to the improvement of other aspects of this widely understood quality, such as functionality or usability, which are especially important for end users. More engagement and early feedback from the stakeholder is required. For rapid prototyping, testing and evaluation of the system, a new technique based on basic UML models and the Java Real Time platform is proposed
An Intelligent Agent That Autonomously Learns How to Translate

We describe the design of an autonomous agent that can teach itself how to translate from a foreign language, by first assembling its own training set, then using it to improve its vocabulary and language model. The key idea is that a Statistical Machine Translation package can be used for the Cross-Language Retrieval Task of assembling a training set from a vast amount of available text (e.g. a large multilingual corpus, or the Web) and then train on that data, repeating that process several times. The stability issues related to such a feedback loop are addressed by a mathematical model, connecting statistical and control-theoretic aspects of the system. We test it on real-world tasks, showing that indeed this agent can improve its translation performance autonomously and in a stable fashion, when seeded with a very small initial training set. The modelling approach we develop for this agent is general, and we believe will be useful for an entire class of self-learning autonomous agents working on the Web.
The Planck oscillator model

We consider oscillators at the Planck scale in the background dark energy. Starting from a coherent array of such oscillators it is possible to get a description from elementary particles to Black Holes including the usual Hawking-Beckenstein theory. There is also a description of Gravitation in the above model: It is an artifact of the background dark energy and the existence of the minimum spacetime scale. This points to a unified description with electromagnetism.
Predicting Time-Varying Musical Emotion Distributions from Multi-Track Audio

Music exists primarily as a medium for the expression of emotions, but quantifying such emotional content empirically proves a very dicult task. Myriad features comprise emotion, and as such mu- sic theory provides no rigorous foundation for analysis (e.g. key, mode, tempo, harmony, timbre, and loudness all play some roll), and the weight of individual musical features may vary due to the expressiveness of dif- ferent performers. In previous work, we have shown that the ambiguities of emotions make the determination of a single, unequivocal response label for the mood of a piece of music unrealistic, and we have instead chosen to model human response labels to music in the arousal-valence (A-V) representation of aect as a stochastic distribution. Using multi- track sources, we seek to better understand these distributions by ana- lyzing our content at the performer level for dierent instruments, thus allowing the use of instrument-level features and the ability to isolate af- fect as a result of dierent performers. Following from the time-varying nature of music, we analyze 30-second clips on one-second intervals, in- vestigating several regression techniques for the automatic parameteriza- tion of emotion-space distributions from acoustic data. We compare the results of the individual instruments to the predictions from the entire instrument mixture as well as ensemble methods used to combine the individual regressors from the separate instruments.
Influence of Apo E Polymorphism on Coronary Artery Disease

The ε4 allele of the ε2, ε3 and ε4 protein isoform polymorphism in the gene encoding apolipoprotein E (Apo E) has previously been associated with increased cardiac artery disease (CAD); therefore to investigate the significance of this polymorphism in pathogenesis of CAD in Iranian patients with stenosis and control subjects. To investigate the association between Apo E polymorphism and coronary artery disease we performed a comparative case control study of the frequency of Apo E polymorphism in One hundred CAD patients with stenosis who underwent coronary angiography (>50% stenosis) and 100 control subjects (<10% stenosis). The Apo E alleles and genotypes were determined by polymerase chain reaction (PCR) and restriction fragment length polymorphism (RFLP). We observed an association between the Apo E polymorphism and CAD in this study. These data suggest that the Apo ε4 and ε2 alleles increase the risk for CAD in Iranian population (χ =4.26, p= 0.05, OR=2 and χ =0.38, p=0.53, OR=1.2). These results suggest that ε4 and ε2 alleles are risk factors for stenosis. Keywords—Arterial blood vessels, atherosclerosis, cholesterol.
Integration of Multiple Sensors using Binary Features in a Bernoulli Mixture Model

This article reports on the use of a Bernoulli mixture model to integrate features extracted independently from two or more distinct sensors. Local image features (SIFT) and multiple types of features from a 2D laser range scan are all converted into Binary form and integrated into a single binary feature incidence matrix (FIM). The correlation between the different features is captured by modeling the resultant FIM in terms of a Bernoulli mixture model. The integration of binary features from different sensors allows for good place recognition. The use of binary features also promises a much simpler integration of features from dissimilar sensors
The Impact of Beamwidth on Temporal Channel Variation in Vehicular Channels and Its Implications

Millimeter wave (mmWave) has great potential in realizing high data rates, thanks to the large spectral channels. It is considered as a key technology for fifth-generation (5G) wireless networks and is already used in wireless LAN (e.g., IEEE 802.11ad). Using mmWave for vehicular communications, however, is often viewed with some skepticism due to a misconception that the Doppler spread would become too large at these high frequencies. This is not necessarily true when directional beams are employed. In this paper, closed-form expressions relating the channel coherence time and beamwidth are derived. Unlike prior work that assumed perfect beam pointing, the pointing error due to the receiver motion is incorporated to show that there exists a nonzero optimal beamwidth that maximizes the coherence time. We define a novel concept of beam coherence time, which is an effective measure of beam alignment frequency. Using the derived correlation function, the channel coherence time, and the beam coherence time, an overall performance metric considering both the channel time variation and the beam alignment overhead is derived. Using this metric, it is shown that beam realignment in every beam coherence time performs better than beam realignment in every channel coherence time.
Research and Realization for Simulation System of Rock-Fill Dams Based on Service-Oriented-Architecture

The background is to build a simulation system for rock-fill dams based on service-oriented architecture (SOA) structure, Web Services technology and . NET platform. The principles of SOA are analyzed. It describes Web Services which is the implementation of the SOA. The key technologies of Web Services are also discussed. The modeling which is simulation system for rock-fill dams based on SOA structure is analyzed, and the process for layer design of simulation system is given, including the presentation layer, the appearance of the business layer, the business layer, data access layer and data layer, and so on. Finally, the actual works carry out case studies. A case shows that the simulation system of the rock-fill dam based on SOA is effective and feasible.
The effect of primordial non-Gaussianity on the topology of large-scale structure

We study the effect of primordial non-Gaussianity on the development of large-scale cosmic structure using high-resolution N-body simulations. In particular, we focus on the topological properties of the ‘cosmic web’, quantitatively characterized by the Minkowski functionals (MFs), for models with quadratic non-linearities with different values of the usual non-Gaussianity parameter fNL. In the weakly non-linear regime (the amplitude of mass density fluctuations σ0 < 0.1), we find that analytic formulae derived from perturbation theory agree with the numerical results within a few per cent of the amplitude of each MF when |fNL| < 1000. In the non-linear regime, the detailed behaviour of the MFs as functions of threshold density deviates more strongly from the analytical curves, while the overall amplitude of the primordial non-Gaussian effect remains comparable to the perturbative prediction. When smaller-scale information is included, the influence of primordial non-Gaussianity becomes increasingly significant statistically due to decreasing sample variance. We find that the effect of the primordial non-Gaussianity with |fNL| = 50 is comparable to the sample variance of mass density fields with a volume of 0.125(h−1 Gpc)3 when they are smoothed by Gaussian filter at a scale of 5 h−1 Mpc. The detectability of this effect in actual galaxy surveys will strongly depend on residual uncertainties in cosmological parameters and galaxy biasing
On Unitary Cayley Graphs

AgsrRAcr. We deal with a family of undirected Cayley graphs X* which are unions of disjoint Hamilton cycles, and some of their properties, where n runs over the positive integers. It is proved that X* is a bipartite graph when n is even. If n is a"n odd number, we count the number of different colored triangles in X.
A simplified model of planar snake robot locomotion

This paper presents a model of the kinematics and dynamics of a planar, wheelless snake robot aimed at control design and stability analysis purposes. The proposed model is significantly less complex than existing models of planar snake robot locomotion. The paper presents an analysis of an existing complex snake robot model which reveals a set of essential properties that characterize the overall motion of a planar snake robot. The proposed model is developed to capture only these essential properties of snake locomotion, thereby significantly reducing the complexity compared to the original model used in the analysis. The paper presents simulation results that indicate that the qualitative behaviour of the proposed model and the original complex model are similar, and that a quantitative similarity is achieved with a proper choice of numerical values of the friction coefficients in the two models.
Downlink cell association for large-scale MIMO HetNets employing small cell wireless backhaul

Downlink cell association (CA) is studied for cellular heterogeneous networks (HetNets) where large-scale antenna array is implemented at the macro base station (BS), while the opportunistically deployed small cells are single-antenna nodes, and they rely on over-the-air links to the macro base station for backhaul. The coupling constraint due to in-band wireless backhaul becomes another key criterion for cell association. A duplex and spectrum sharing scheme based on reverse timedivision duplex (TDD) is considered for interference management in the HetNet under the wireless backhaul constraint. A sum logarithmic-throughput maximization problem is formulated to balance throughput and fairness. By relaxing the binary cell association indicator variables, the optimization problem is shown to be a convex problem. Dual decomposition for relaxed optimization is employed to solve the integer nonlinear CA problem, which results in a distributed CA algorithm. Improved performance and fairness are achieved with the proposed algorithm under the wireless backhaul constraint, and more small cells implemented within the macro cell range achieves better load balancing. As no additional radio frequency hardware is required by the proposed scheme, it allows low-cost and fast implementation of wireless backhaul enabled cellular HetNets.
Relationship between respiratory syncytial virus bronchiolitis and future obstructive airway diseases

Evidence from a large number of prospective case-control studies shows that respiratory syncytial virus (RSV) bronchiolitis in infancy is often associated with recurrent wheezing and asthma during subsequent years. However, wheezing tends to diminish and most studies show no significant increase in wheezing compared to controls by school age or adolescence. An unresolved question is whether severe RSV infection during infancy causes the respiratory sequelae or inherent abnormalities predispose an infant to develop severe respiratory infection and sequelae, i.e. RSV is associated with the development of pulmonary sequelae. Studies on long-term outcome of RSV bronchiolitis are reviewed from an evidence-based perspective. The majority of prospective placebo-controlled studies do not show any long-term beneficial effects of corticosteroid treatment, i.e. the risk of subsequent wheezing is not diminished by the treatment. The evidence for an increased risk of allergic sensitization after RSV bronchiolitis is not nearly as strong as the evidence for an increased risk of subsequent wheezing. In fact, most studies do not show any significant increase in atopy after RSV bronchiolitis. This suggests that the increased risk of wheezing after RSV is not linked to an increased risk of atopy. There are some indications that infants who develop severe RSV and subsequent wheezing may have aberrations that predate the RSV infection. To decide whether respiratory syncytial virus bronchiolitis causes, or is associated with the respiratory sequelae (or with subsequent allergy), it will be necessary to conduct prospective, randomized studies, where the cytokine profile prior to bronchiolitis onset is known. Such studies should preferably include some form of intervention against respiratory syncytial virus. A more complete understanding of the risk factors for severe respiratory syncytial virus infection and the role of respiratory syncytial virus infection in the initiation of asthma is needed as a basis for large-scale and cost-effective programmes to prevent respiratory syncytial virus-related morbidity.
Parallelism and Implementation Technology for Logic Programming Languages

Logic programming provides a high-level view of programming where programs are fundamentally seen as a collection of statements that define a model of the intended problem. Logic programming has been successfully applied to a vast number of applications, and has been shown to be a good match for parallel computers. This survey discusses the major issues on the implementation of logic programming systems. We first survey the evolution of sequential implementations, since the original Marseille Prolog implementation. Focus is then given to the WAM based techniques that are the basis for most Prolog systems. More recent developments are presented, such as compilation to native code. We next survey the main issues of parallel logic programming, since the original proposals for And/Or parallel systems. The article describes the major techniques used for the shared memory systems that implement only Or-parallelism and only And-parallelism, such as Aurora, Muse, &-Prolog, DDAS, &-ACE, PARLOG and KLIC. Last, the survey discusses recent work on combining several forms of parallelism, as in the Andorra based languages such as Andorra-I or Penny, or in the Independent-And plus Or models, such as the PBA, SBA, ACE, or Fire.
Predicting time sequences in gene expression using dynamic neuro-fuzzy networks

Gene regulation at the cellular level is a dynamic process; and neural networks with the capability of being trained and regulated based on training data, and fuzzy systems with their interpretability, are suitable algorithms for this type of computations. In this research, methods based on neuro-fuzzy networks were employed for predicting the complicated relationships that exist among genes. In the proposed method, genes that have the greatest effect on each other are found and considered as regulatory genes. Then the types of their relationships including those with inhibitory, activating, and neutralizing effects are determined, and the gene regulatory network is mapped. The standard microarray dataset related to 12 typical genes that influence the germination cycle of the yeast species Saccharomyces cerevisiae was used for training. Obtained results were validated using previous biological laboratory results. It was found that the proposed method reduced the number of extracted rules for input-output space fragmentation by 15%, which substantially reduced the required computations, while the sum square error of the algorithm declined by -0.3 compared to the method that resembled the proposed algorithm the most.
A novel objective no-reference metric for digital video quality assessment

A novel objective no-reference metric is proposed for video quality assessment of digitally coded videos containing natural scenes. Taking account of the temporal dependency between adjacent images of the videos and characteristics of the human visual system, the spatial distortion of an image is predicted using the differences between the corresponding translational regions of high spatial complexity in two adjacent images, which are weighted according to temporal activities of the video. The overall video quality is measured by pooling the spatial distortions of all images in the video. Experiments using reconstructed video sequences indicate that the objective scores obtained by the proposed metric agree well with the subjective assessment scores.