Miracle-dz/UniFAR-FTUs huggingface dataset:
Development and Analysis of Convolutional Neural Network based Accurate Speech Emotion Recognition Models

Automatic speech recognition is a major topic in artificial intelligence and machine learning, with the intent of developing machines that can communicate with humans through speech. Recently, with the emergence of the deep-learning paradigm, end to-end models that extract features and train directly from the raw speech signal have been developed. With the goal of more precisely classifying emotions from speech, this paper presents a comparative analysis on two deep-learning architectures that improves on the models available in the literature in terms of accuracy. Using a combined CNN-LSTM architecture and a CNN-Transformer encoder architecture, this work analyses the complete deep learning strategy for extracting distinct spatial and temporal features and classifying the emotions from speech. Experiments are carried out on the RAVDESS dataset. The CNN-Transformer encoder network achieves high accuracy 82% in these networks, while the CNN-LSTM network achieves 74%.
Use of the Kalman filters for the analysis of the mechanical properties of human skin in vivo

In this article, we present an inverse method for the identification of the mechanical properties of human skin, a complex multi-layered organ which has been studied in vivo using a suction deformation technique. To identify the required properties, experimental results were compared to finite element solutions of the test, with the assumption that skin behaves as a single isotropic hyperelastic layer. The inverse method used in this article is based on that of the extended Kalman filters principle, with two modifications of this standard formulation for use in skin analysis. The modified formulation was then tested using Finite Element Method (FEM) simulated mechanical data and also with a study of linear and nonlinear theoretical problems. The results of the new formulation were also compared with the Gauss–Newton, recursive least square and Kalman smoother approaches. Finally, the reliability of the method was tested on a case study.
A Constrained Graph Coloring Solver Based on Ising Machines

Optimum or quasi-optimum solutions of combinatorial optimization problems can be efficiently found by using Ising machines. The graph coloring problem (GCP) is known as a difficult combinatorial problem. Given a graph, each vertex should be assigned a color and any two vertices connected by an edge must not be colored the same. Although methods to map the GCP onto the Ising model are proposed, none of them considers minimizing the number of colors. In this paper, we propose a mapping method of the GCP including minimizing the number of colors and additional constraints to the QUBO (Quadratic Unconstrained Binary Optimization) model. As well as the constraint terms for the GCP, we firstly propose an objective function term that can minimize the number of colors so that the number of used spins cannot increase exponentially. Secondly, we propose two more additional terms so that our proposed method can be applicable to practical consumer applications. The experimental evaluations on an Ising machine showed that the proposed method reduces the number of used colors by up to 75.1% on average compared with the existing baseline method. Considering the additional constraints, the proposed method can effectively find feasible solutions satisfying all the constraints.
Modeling and Simulation of Pulmonary Acoustic Signal and Imaging for Lung Function Assessment

Structural airway changes can be related to acoustic airflow resistance in various chronic lung disorders. However, acoustic imaging for pulmonary diagnosis has been challenging. This paper presents a study on lung function assessment with acoustic imaging through respiratory modeling and simulation and correlates acoustic lung images with pathologic alterations. The method combines wall thickness, inner radius, airway length, and tissue structure into mathematical modeling for pressure, wall elasticity, and airflow at each airway level. By modifying the airway wall thickness (AWT), we have demonstrated the airway resistance of healthy lungs and lungs with respiratory diseases. In addition, the correlation between increasing AWT and mean acoustic image intensity is established for characterizing the severity of the respiratory disease. Furthermore, a structural similarity index of 0.8762 was achieved between our model impedance acoustic image and reference lung sound acoustic image. This work can potentially be used for optimizing the number of acoustic sensors and their placement to obtain an accurate and frequent respiratory assessment.
Robust nonnegative stabilization of interval discrete systems

The authors consider the class of nonnegative discrete-time systems and analyze the matrix theoretical results involving nonnegative maintainability with respect to the problem of robust stabilization of interval discrete systems. Using state feedback, a controller which may include an observer such that the closed-loop interval system is robustly stabilized and at the same time becomes nonnegative is designed. The procedure is to characterize the set of robust controllers by means of matrix inequalities, and to choose a suitable controller by solving an optimization algorithm. <<ETX>>
STABILITY OF REGIME SWITCHING ERROR CORRECTION MODELS UNDER LINEAR COINTEGRATION

The paper obtains conditions that ensure stationarity of linear long-run equilibrium relations and differenced observations in vector autoregressive error correction models with nonlinear short-run dynamics. The considered models include various threshold error correction models and their smooth transition counterparts. These models assume that the form of the short-run dynamics depends on values of observable transition functions that determine the regime in which the considered process evolves. In related models studied in the paper the transition functions are unobservable. These models are obtained by making the transition functions of threshold error correction models dependent on an unobservable random term. Previous stationarity conditions obtained for these kinds of regime switching error correction models are extended by using recent developments on nonlinear autoregressive models based on the theory of Markov chains and the concept of joint spectral radius of a set of square matrices. In addition to stationarity, existence of second-order moments and beta mixing is also established. The results of the paper enhance the understanding of the considered nonlinear error correction models and pave the way for the development of their asymptotic estimation and testing theory.Financial support from the Research Unit of Economic Structures and Growth (RUESG) in the University of Helsinki and the Yrjö Jahnsson Foundation is gratefully acknowledged. The author thanks Anders Rahbek for stimulating discussions on the topic of this paper and Helmut Lütkepohl and an anonymous referee for useful comments.
Analysis of Integrated Water Resources Scheduling System in the Yellow River Basin Based on Fuzzy Cluster Cyclic Iteration Algorithm

Combining with the economic development, ecological environment condition and water resources development and utilization status of the Yellow River, the paper established comprehensive evaluation index system of the economic development-ecological environment-water resources scheduling of the Yellow River basin in 2019. Using fuzzy cluster cyclic iteration algorithm, the coordinated development of integrated water resources system in the Yellow River basin was evaluated. The method could be used to rank the evaluation results and get different coordination degree classification of the Yellow River basin, which could evaluate the degree of water resources optimal allocation.
A Multi-Scale Residual Neural Network for ECG Based Person Identification

The electrocardiogram (ECG) signal is unique for each person. Due to the physiological and geometrical differences of the heart, the morphological shape of the ECG signal changes for different persons. In this work, we have proposed a multiscale residual neural network (MS-ResNet) architecture to exploit the morphological shape of the ECG waveforms and their inter-relationship for biometric application. The proposed neural network model utilises three parallel convolutional branches with dilated kernels for capturing the multi-scale representation of the ECG signal. The proposed MS-ResNet model is evaluated using two publicly available ECG datasets, i.e., the UofTDB dataset and CYBHi dataset. The proposed model gives an identification accuracy of 87.98% and 94.18% for the UofTDB and CYBHi datasets, respectively.
Symbolic Execution of Floating-point Programs: How far are we?

Floating-point programs are challenging for symbolic execution due to the constraint solving problem. To investigate the effectiveness and limitations of the existing methods, we conduct the first empirical study in this paper on five existing symbolic execution methods for floating-point programs. We have implemented the existing methods on the state-of-the-art symbolic execution KLEE and use the real-world representative floatingpoint programs as the benchmarks, which are used to evaluate the existing methods with respect to code coverage and bug finding. The results indicate that the existing methods complement each other in bug finding. Based on the findings of the experimental results, we propose synergizing the existing methods to improve symbolic execution‘s effectiveness. The experimental results demonstrate that our synergic method can detect more bugs.
Whole Heliosphere Interval: Overview of JD16

Abstract The Whole Heliosphere Interval is an international observing and modeling effort to characterize the three-dimensional interconnected solar-heliospheric-planetary system, i.e., the “heliophysical” system. WHI was part of the International Heliophysical Year, on the 50th anniversary of the International Geophysical Year, and benefited from hundreds of observatories and instruments participating in IHY activities. WHI describes the 3-D heliosphere originating from solar Carrington Rotation 2068, March 20–April 16, 2008. The focus of IAU JD16 was on analyses of observations obtained during WHI, and simulations and modeling involving those data and that period. Consideration of the WHI interval in the context of surrounding solar rotations and/or compared to last solar minimum was also encouraged. Our goal was to identify connections and commonalities between the various regions of the heliosphere.
A General Framework for Testing a Null Hypothesis in a “Mixed” Form

A general framework for asymptotic tests is proposed. The framework contains as particular cases tests based on various estimation techniques: maximum likelihood methods, pseudo-maximum likelihood (PML) methods and quasi-generalized PML methods, m-estimation methods, moments or generalized moments method, and asymptotic least squares. Moreover the null hypothesis has a general mixed form, including the usual implicit and explicit form.
The dynamics of helical decaying turbulence

The dynamics of helical decaying homogeneous turbulence is investigated in direct numerical simulations at moderate Reynolds numbers. A new initialization procedure is presented that allows one to control both the energy and the helicity spectral density of the initial flow field. It is observed that large initial helicity impedes the transfer of energy toward smaller scales, inhibits the buildup of enstrophy, and reduces dissipation for several turnover times. Also, the skewness and flatness of the velocity derivatives reach values typical of turbulence much later than in comparable flows without helicity. However, these effects are significant only if the helicity of the flow is quite high. In simulations with small or vanishing initial helicity it is found that the fluctuations of the average helicity and the helicity spectral density lie within the range suggested by a quasi‐Gaussian approximation. This suggests that at moderate Reynolds number spontaneous fluctuations of helicity are not large enough.
Resonator fiber optic gyroscope with digital serrodyne scheme using a digital controller

To get rid of the complex analogue control loops that are traditionally used in resonator fiber optic gyroscope (R-FOG) and to meet the requirements of high accuracy as well as small-size and light-weight in Inertial Navigation Systems (INSs), a digital controller is developed and demonstrated experimentally to control the R-FOG with the digital serrodyne modulation. The digital controller is designed to implement the function of tracking the laser diode frequency drift and to compensate for the imperfect 2π modulation voltage of the phase modulator for the serrodyne modulation. To acquire the resonant frequency, the digital serrodyne modulation with symmetric frequency shift is adopted as a counter-measure for Rayleigh backscattering noise. The optimal serrodyne modulation generated frequency shift is decided to be in the range of 100~120 kHz according to the numerical calculation. The successful demonstration of the open loop operation with the digital controller is deemed as the basis for the digitalized closed-loop experiment in future.
The impact of atmospheric aerosols on precipitation from deep organized convection: A prescribed‐flow model study using double‐moment bulk microphysics

This note discusses the results of numerical simulations in which a prescribed‐flow model is merged with a double‐moment warm‐rain and ice microphysics scheme to investigate the impact of microphysical processes on precipitation from deep organized convection. The prescribed two‐dimensional flow mimics an idealized squall line, with a narrow region of strong convective updraft and much wider region of weak stratiform updraft overlaying a stratiform downdraft. To cover the broad range of conditions that are possible for a squall line as well as to explore precipitation dependence on different parameters, 25 pairs of simulations are performed. Simulated cases differ in the dynamics (e.g. changing the updraft strength or large‐scale shear), thermodynamics (e.g. changing the inflow sounding) or microphysics (e.g. changing the collision efficiencies). Each pair features cloud condensation nuclei (CCN) in either a pristine or polluted environment. Total surface precipitation and partitioning between convective and stratiform precipitation in each pair appears to be almost the same, with the difference being typically a few tenths of 1%. However, the dynamical and thermodynamical parameters do affect the precipitation significantly. It follows that the surface precipitation from organized convection can differ between pristine and polluted environments only through the feedback of CCN on cloud dynamics. In this feedback, small differences in the latent heating for the same flow pattern lead to different flow patterns in subsequent squall‐line evolution. Details of this feedback need to be investigated using a dynamical model. Copyright © 2009 Royal Meteorological Society
On the relationship of magnetocrystalline anisotropy and stoichiometry in epitaxial L10 CoPt (001) and FePt (001) thin films

Two series of epitaxial CoPt and FePt films, with nominal thicknesses of 42 or 50 nm, were prepared by sputtering onto single-crystal MgO(001) substrates in order to investigate the chemical ordering and the resultant magnetic properties as a function of alloy composition. In the first series, the film composition was kept constant, while the substrate temperature was increased from 144 to 704 °C. In the second series the substrate temperature was kept constant at 704 °C for CoPt and 620 °C for FePt, while the alloy stoichiometry was varied in the nominal range of 40–60-at. % Co(Fe). Film compositions and thicknesses were measured via Rutherford backscattering spectrometry. The lattice and long-range order parameter for the L10 phase were obtained for both sets of films using x-ray diffraction. The room-temperature magnetocrystalline anisotropy constants were determined for a subset of the films using torque magnetometry. The order parameter was found to increase with increasing temperature, with ordering.
Emotional Intelligence on Organizational Performance with the Moderating Effect of Organizational Culture in the Banking Sector in Sri Lanka: A Systematic Review

This is a conceptual paper based on a systematic literature review. For many years, the topic of emotional intelligence and organizational performance has caught the interest of researchers and practitioners. Much of the interest in these two areas is motivated by explicit and implicit assumptions that both the emotional intelligence of individuals and organizational culture are associated with organizational performance. While the associations between emotional intelligence and organizational performance and organizational culture have been studied independently, few studies have examined the relationship between the three variables. This paper aims to advance understanding of the effects of emotional intelligence on organizational performance with the moderating role of organizational culture by reviewing the literature of previous studies. This study reviewed fifty-two (52) journal articles from the Scopus database and other sources. The study culminates with the development of a conceptual framework that can be used in future empirical studies.
Generalized Normal Derivatives and Their Applications in DDMs with Nonmatching Grids and DG Methods

A class of normal-like derivatives for functions with low regularity defined on Lipschitz domains are introduced and studied. It is shown that the new normal-like derivatives, which are called the generalized normal derivatives, preserve the major prop- erties of the existing standard normal derivatives. The generalized normal derivatives are then applied to analyze the convergence of domain decomposition methods (DDMs) with nonmatching grids and discontinuous Galerkin (DG) methods for second-order el- liptic problems. The approximate solutions generated by these methods still possess the optimal energy-norm error estimates, even if the exact solutions to the underlying elliptic problems admit very low regularities. AMS subject classifications: 46E35, 65M15, 65M55, 65M60
Ultrasound-guided erector spinae plane block for postoperative short-term outcomes in lumbar spine surgery: A meta-analysis and systematic review

Background: Patients undergoing lumbar spine surgery usually suffer from moderate to severe acute pain. Erector spinae plane block (ESPB) has been applied to relieve acute pain in various surgeries and improve postoperative outcomes. This study aimed to further identify the efficacy and safety of erector spinae plane block in patients undergoing lumbar spine surgery. This study also evaluates the outcomes of the erector spinae plane block compared with other regional blocks. Methods: We searched PubMed, Web of Science, Cochrane library, Embase, and CINAHL databases to identify all randomized controlled trials evaluating the effects of ESPB on postoperative pain after lumbar spine surgery. The primary outcome is postoperative total opioid consumption in 24 hours. The secondary outcomes are postoperative pain scores, intraoperative opioid consumption, time to first rescue analgesia, number of patients requiring rescue analgesia, first time to ambulation after surgery, length of hospital stay, patients’ satisfaction score, and postoperative side effects such as postoperative nausea and vomiting, itching. Results: A total of 19 randomized controlled trials are included in the final analysis. Compared with no/sham block, ultrasound-guided erector spinae plane block can decrease perioperative opioid consumption including intraoperative opioid consumption: standardized mean difference (SMD) = −3.04, 95% confidence interval (CI) (−3.99, −2.09), P < . 01, and opioid consumption postoperatively: (SMD = −2.80, 95% CI [−3.61, −2.00], P < .01); reduce postoperative pain at 2, 6, 12, 24, and 48 hours both at rest and movement; meanwhile shorten time to hospital length of stay: (SMD = −1.01, 95% CI [−1.72, 0.30], P = .006), decrease postoperative nausea and vomiting (RR = 0.35, 95% CI [0.27, 0.46], P < .00001), and improve patient satisfaction (SMD = −2.03, 95% CI [−0.96, 3.11], P = .0002). But ultrasound-guided ESPB doesn’t shorten the time to ambulation after surgery (SMD = −0.56, 95% CI [−1.21, 0.08], P = .09). Additionally, ESPB is not superior to other regional blocks (e.g., thoracolumbar interfascial plane/midtransverse process to pleura block). Conclusion: This meta-analysis demonstrates that ultrasound-guided ESPB can provide effective postoperative analgesia in patients undergoing lumbar spine surgery and improve postoperative outcomes, and it deserves to be recommended as an analgesic adjunct in patients undergoing lumbar spine surgeries.
Simple prism pyramids: a new light trapping texture for silicon solar cells

A new light trapping front surface geometry for solar cells, the simple prism pyramid (SPP) texture, is introduced and numerically analyzed with the newly developed ray tracing program SUNRAYS. The SPP texture is applicable to polycrystalline cells because it can be prepared by mechanical grooving. The SPP texture achieves the maximum average path length of rays that is theoretically possible under isotropic illumination. Encapsulated, 300 /spl mu/m thick silicon solar cells with a grooving period of 100 /spl mu/m and a flat aluminum back surface reflector are considered. The light trapping properties of symmetric upright grooves and pyramids are studied systematically as a function of facet orientation. The SPP texture is superior to both symmetric upright grooves and pyramids. <<ETX>>
Examining Trends in Satellite-Detected Tropical Overshooting Tops as a Potential Predictor of Tropical Cyclone Rapid Intensification

AbstractA geostationary satellite–derived cloud product that is based on a tropical-overshooting-top (TOT) detection algorithm is described for applications over tropical oceans. TOTs are identified using a modified version of a midlatitude overshooting-top detection algorithm developed for severe-weather applications. The algorithm is applied to identify TOT activity associated with Atlantic Ocean tropical cyclones (TCs). The detected TOTs can serve as a proxy for “hot towers,” which represent intense convection with possible links to TC rapid intensification (RI). The purpose of this study is to describe the adaptation of the midlatitude overshooting-top detection algorithm to the tropics and to provide an initial exploration of possible correlations between TOT trends in developing TCs and subsequent RI. This is followed by a cursory examination of the TOT parameter’s potential as a predictor of RI both on its own and in multiparameter RI forecast schemes. RI forecast skill potential is investigated by.
Spectral representation of local semigroups associated with Klein-Landau systems

In their paper [5], Klein and Landau prove that given a symmetric ‘local semigroup’ of unbounded operators {T(t); t ≥ 0} on a Hilbert space, there exists a unique selfadjoint operator T such that T(t) is a restriction of e−tT, for each t ≥ 0. A similar representation theorem was proved earlier by Nussbaum [8]. The result of Klein and Landau was recently extended to the setting of reflexive Banach spaces by Kantorovitz ([4], theorem 2–3). More precisely, Kantorovitz presented necessary and sufficient conditions for a local semigroup of unbounded operators {T(t); t ≥ 0} to consist of restrictions of e−tT, t ≥ 0, for some unbounded spectral operator of scalar-type T with real spectrum (cf. [1] for the terminology).