Miracle-dz/UniFAR-FTUs huggingface dataset:
The relative accuracy of ( x + y ) ∗ ( x − y )

We consider the relative accuracy of evaluating ( x + y )( x − y ) in IEEE ﬂoating-point arithmetic, when x,y are two ﬂoating-point numbers and rounding is to nearest. This expression can be used, for example, as an eﬃcient cancellation-free alternative to x 2 − y 2 and (at least in the absence of underﬂow and overﬂow) is well known to have low relative error, namely, at most about 3 u with u denoting the unit roundoﬀ. In this paper we propose to complement this traditional analysis with a ﬁner-grained one, aimed at improving and assessing the quality of that bound. Speciﬁcally, we show that if the tie-breaking rule is to away then the bound 3 u is asymptotically optimal (as the precision tends to ∞ ). In contrast, if the tie-breaking rule is to even , we show that asymptotically optimal bounds are now 2 . 25 u for base two and 2 u for larger bases, such as base ten. In each case, asymptotic optimality is obtained by the explicit construction of a certiﬁcate, that is, some ﬂoating- point input ( x,y ) parametrized by u and such that the error of the associated result is equivalent to the error bound as u tends to zero. We conclude with comments on how ( x + y )( x − y ) compares with x 2 in the presence of ﬂoating-point arithmetic, in particular showing cases where the computed value of ( x + y )( x − y ) exceeds that of x 2 .
Implementation of the blade element momentum model on a polar grid and its aeroelastic load impact

Abstract. We show that the upscaling of wind turbines from rotor diameters of 15–20 m to presently large rotors of 150–200 m has changed the requirements for the aerodynamic blade element momentum (BEM) models in the aeroelastic codes. This is because the typical scales in the inflow turbulence are now comparable with the rotor diameter of the large turbines. Therefore, the spectrum of the incoming turbulence relative to the rotating blade has increased energy content on 1P, 2P, …, nP, and the annular mean induction approach in a classical BEM implementation might no longer be a good approximation for large rotors. We present a complete BEM implementation on a polar grid that models the induction response to the considerable 1P, 2P, …, nP inflow variations, including models for yawed inflow, dynamic inflow and radial induction. At each time step, in an aeroelastic simulation, the induction derived from a local BEM approach is updated at all the stationary grid points covering the swept area so the model can be characterized as an engineering actuator disk (AD) solution. The induction at each grid point varies slowly in time due to the dynamic inflow filter but the rotating blade now samples the induction field; as a result, the induction seen from the blade is highly unsteady and has a spectrum with distinct 1P, 2P, …, nP peaks. The load impact mechanism from this unsteady induction is analyzed and it is found that the load impact strongly depends on the turbine design and operating conditions. For operation at low to medium thrust coefficients (conventional turbines at above rated wind speed or low induction turbines in the whole operating range), it is found that the grid BEM gives typically 8 %–10 % lower 1 Hz blade root flapwise fatigue loads than the classical annular mean BEM approach. At high thrust coefficients that can occur at low wind speeds, the grid BEM can give slightly increased fatigue loads. In the paper, the implementation of the grid-based BEM is described in detail, and finally several validation cases are presented. Comparisons with blade loads from full rotor CFD, wind tunnel experiments and a field experiment show that the model can predict the aerodynamic forces in half-wake, yawed flow, dynamic inflow and turbulent inflow conditions.
Lack-of-fit Testing for Polynomial Regression Models Without Replications

Parametric and non-parametric approaches are developed to test the adequacy of the polynomial model Y=β°+j=1pβjXj+ε when there is no replication in the values of the independent variable. The proposed tests avoid partitioning of the sample space of the continuous covariate. This paper suggests three tests based on the following concept: if the model is appropriate for a selected application, then the error component ε1,ε2,…,εn is a random sample with zero mean and constant variance. Simulation results are provided to illustrate the power and size of the proposed tests. An example is used to illustrate the methodologies. These tests are also compared with the classical lack-of-fit test to demonstrate their advantage.
Comparison of the GPM DPR Single- and Double-Frequency Products Over the Mediterranean Area

The NASA/JAXA Global Precipitation Measurement (GPM) Core Observatory (CO) carries, for the first time, a dual-frequency precipitation radar (DPR) designed to provide insights into the 3-D structure of precipitating clouds and rain intensity by using its Ka- and Ku-band frequencies. Single-frequency (SF) (both Ku- and Ka-only) and double-frequency (DF) based products provide particle-size distribution (PSD) parameters, as well as precipitation rates. Background surface type, precipitation type and phase, and vertical extension of the storm are also provided. In this paper, an intercomparison between the SF and DF DPR outputs over the Mediterranean area during rainfall events in the first four years of GPM-CO mission is carried out. The goal is to investigate the reliability of SF-based products by assessing their quality compared to the DF-based ones, treated as a reference. The vertical profiles and the near-surface values of the corrected reflectivity of the PSD parameters (mean mass-weighted diameter and normalized intercept) and of the rainfall rate have been analyzed. The data have been categorized for surface type (land and sea) and precipitation type (stratiform and convective). The results show a more marked difference between the DF and SF Ka-only based products than between DF and SF Ku-only based products. The feature is confirmed by the analysis of vertical profiles of the SF- and DF-based retrieved parameters. The statistical scores do not differ significantly between land and sea while they differ noticeably between stratiform and convective precipitation.
Reshaping the urban hierarchy: patterns of information diffusion on social media

ABSTRACT The spatial diffusion of information is a process governed by the flow of interpersonal communication. The emergence of the Internet and especially social media platforms has reshaped this process and previous research has studied how online social networks contribute to the diffusion of information. Understanding such processes can help devise methods to maximize or control the reach of information or even identify upcoming events and social movements. Yet activities in cyberspace are still confined to physical locations and this geographic connection tends to be overlooked. In this research, we focus on geographic regions instead of individuals and study how the underlying hierarchical structure of regions relates to their response to the information. We examined the top 30 populated cities and metropolitan areas in the U.S. and retrieved Twitter data related to two selected topics from these regions, the 2015 Nepal Earthquake and the #JesuisCharlie hashtag in response to the Paris attacks on the Charlie Hebdo offices. We analyzed the similarity among regions of their response using multiple statistical methods and three urban classifications. Our results indicate that the diffusion of information is impacted by the hierarchy of urban regions and that the Twitter responses act more similar when the populated regions are positioned at the same level in the urban hierarchy.
Unified Parameterization of Convective Boundary Layer Transport and Clouds With the Thermal Plume Model

The representation of stratocumulus clouds, and of the stratocumulus to cumulus transitions which are ubiquitous features of marine boundary layer clouds, remains a challenge for climate models. We show how a mass flux representation of boundary layer convective structures combined with an eddy diffusivity scheme, the “thermal plume model,” first developed to represent cumulus clouds, can also adequately simulate stratocumulus and the stratocumulus to cumulus transition in a climate model. To achieve this, the detrainment formulation, in which detrainment increases for increasing negative buoyancy, has to be slightly modified: the buoyancy of a thermal plume parcel of air is computed by comparing the virtual potential temperature θv,th of the parcel with that of the surrounding environment θv,env at a given distance above instead of at the same level. This is consistent with the picture of detrained air parcels that experience some overshoot and reach a final destination at a level lower than the one at which they effectively leave the cloud or organized convective plume. The impacts of this modification are documented both for selected cases of stratocumulus, in comparison with large‐eddy simulations, and in full 3‐D climate simulations, in comparison with satellite observations of cloud cover. The modified scheme provides a uniform treatment of the dry convective boundary layer, of cumulus clouds, of stratocumulus, and of the transition from stratocumulus to cumulus. It is included in the most recent version of the LMDZ atmospheric general circulation model.
Optimal Control on Finite-Time Consensus of the Leader-Following Stochastic Multiagent System With Heuristic Method

In this paper, the optimization of the finite-time consensus of a multiagent system is studied when the leader is disturbed by white noise. Different from the consensus problem itself, this paper is devoted to optimizing the performance of the consensus and the constructive method and martingale method are used to guarantee the effectiveness of the optimization. Another contribution is that the problem of the optimal control with the piecewise constant controller gains under a stochastic environment is solved, and the reformed dynamic principle and the reformed Hamilton–Jacobi–Bellman (HJB) partial differential equations (PDEs) are proposed by using the splitting method and Feynman–Kac formula. Furthermore, since the multiagent system often runs on a high-dimensional space, a heuristic method is proposed based on the derivation of the reformed HJB PDEs and the scalar of the computational complexity of the PDEs is equivalent to that of a system of ordinary differential equations with the same dimensions when the multiagent system can be described as a piecewise linear system. Finally, the heuristic method is compared with usual filtering methods for solving engineering problems by a numerical example and it is found that the heuristic method achieves higher precision in finite time.
Concurrent fault diagnosis of modular multilevel converter with Kalman filter and optimized support vector machine

ABSTRACT In this paper, concurrent fault diagnosis problem of modular multilevel converter (MMC) with Kalman filter and optimized support vector machine (SVM) is investigated. The state space model by synthesizing the circulating current and the output current is first established. Recurring to the Kalman filtering theory, the estimation on circulating and output current is realized, the residual is achieved by using the innovation which involved the predicted and measured current. Based on the obtained residual, the residual evaluation function and its threshold are constructed. Then, the fault can be detected according to the proposed fault detection strategy. Once the fault is detected, the fault localization unit is triggered and the residual data is adopted as data set. By employing the optimized SVM with genetic algorithm, the concurrent and intermittent fault localization of MMC can be accomplished. Finally, an 11-level MMC simulation systems with concurrent fault and intermittent fault are set up in MATLAB/Simulink, and the effectiveness of the proposed fault detection and localization method is verified.
Stock Management Problem: Adaptive Fixed-Time Convergent Continuous Controller Design

This paper presents an adaptive fixed-time convergent continuous controller designed to solve a stock management problem with the objective to drive stock and supply chain levels at the reference values, subject to loss rate disturbances whose bounds are unknown. The only measurable state of the supply chain is the inventory retailer stock level, whereas the supply line inventory level should be estimated. The designed controller includes a fixed-time convergent differentiator, an adaptive fixed-time convergent disturbance observer, and a fixed-time convergent regulator. The adaptive fixed-time convergent observer is used to estimate a disturbance without excessively increasing the controller gains. The controller design is validated in a case study of stock management. The calculated upper estimate for the total settling (convergence) time and the obtained simulation results confirm the fixed-time convergence and the robustness of the designed controller.
Facial Expression Recognition Method Based on Improved VGG Convolutional Neural Network

Because the shallow neural network has limited ability to represent complex functions with limited samples and calculation units, its generalization ability will be limited when it comes to complex classification problems. The essence of deep learning is to learn a nonlinear network structure, to represent input data distributed representation and demonstrate a powerful ability to learn deeper features of data from a small set of samples. In order to realize the accurate classification of expression images under normal conditions, this paper proposes an expression recognition model of improved Visual Geometry Group (VGG) deep convolutional neural network (CNN). Based on the VGG-19, the model optimizes network structure and network parameters. Most expression databases are unable to train the entire network from the start due to lack of sufficient data. This paper uses migration learning techniques to overcome the shortage of image training samples. Shallow CNN, Alex-Net and improved VGG-19 deep CNN are used to train and analyze the facial expression data on the Extended Cohn–Kanade expression database, and compare the experimental results obtained. The experimental results indicate that the improved VGG-19 network model can achieve 96% accuracy in facial expression recognition, which is obviously superior to the results of other network models.
Near-IR wide-field-of-view Huygens metalens for outdoor imaging applications

Abstract The ongoing effort to implement compact and cheap optical systems is the main driving force for the recent flourishing research in the field of optical metalenses. Metalenses are a type of metasurface, used for focusing and imaging applications, and are implemented based on the nanopatterning of an optical surface. The challenge faced by metalens research is to reach high levels of performance using simple fabrication methods suitable for mass production. In this paper, we present a Huygens nanoantenna-based metalens, designed for outdoor photographic/surveillance applications in the near infrared. We show that good imaging quality can be obtained over a field of view as large as ±15°. This first successful implementation of metalenses for outdoor imaging applications is expected to provide insight and inspiration for future metalens imaging applications.
Convergence of binomial tree methods to Black Scholes model on determining stock option prices

There are many alternative investment tools that can be used to be the choice of investors. One of them is a derivative product. Derivative products that are more widely known and traded on financial markets are options. Option is a contract or agreement between two parties to buy or sell an instrument. To minimize risk, it is necessary to determine the option price by determining the fair price of the option. This option pricing can be done by using the Binomial Tree method and the Black Scholes method. Some factors that influence options are stock prices, strike prices, maturity, volatility, and interest rates. This paper discusses the European option pricing call on the shares of Bank Central Asia (BCA) with the Binomial Tree method and the Black Scholes Method. From the results of the research, it is found that the Binomial Tree method will converge to the Black Scholes method if the time partition increases.
Convergence study on the logarithmic-quadratic proximal regularization of strictly contractive Peaceman–Rachford splitting method with larger step-size

Recently, a strictly contractive Peaceman–Rachford splitting method with logarithmic-quadratic proximal regularization (SPRSM-LQP) was proposed for solving two-block separable convex minimization model. In practical applications, however, the smaller step-size should be strongly avoided. So we actually have the desire of seeking larger step-size whenever possible in order to accelerate the numerical performance. In this paper, we combine Fortin and Glowinski's accelerating techniques with the SPRSM-LQP. Thus a new algorithm with larger step-size is proposed. Under the same assumptions as the SPRSM-LQP, we establish the global convergence of its larger step-size counterpart. Moreover, preliminary numerical results show that the proposed method on a traffic network equilibrium problem is reliable and more efficient with larger step-size.
Microseisms of the “Voice of the Sea”

Results of registration by a coastal laser strainmeter of the microseismic oscillations, caused by signals of range of the “voice of the sea” (5–10 Hz), connected with the movement of typhoons are discussed. For the first time in the world, it is shown that the time of occurrence of microseisms of the “voice of the sea” coincides with the time of arrival of primary microseisms, generated by progressive sea waves in the observation site.
Tidal response of rocky and ice-rich exoplanets

The amount of detected planets with sizes comparable to that of the Earth is increasing drastically. Most of the Earth-size planet candidates orbit at close distances from their central star, and therefore are subjected to large tidal forces. Accurate determination of the tidal parameters of exoplanets taking into account their interior structure and rheology is essential to better constrain their rotational and orbital history, and hence their impact on climate stability and planetary habitability. In the present study, we compute the tidal response of rocky and ice-rich solid exoplanets for masses ranging between 0.1 and 10 Earth masses using a multilayer approach and an Andrade rheology. We show that the amplitude of tidal response, characterized by the gravitational Love number, k2, is mostly controlled by self-gravitation and increases as a function of planet mass. For rocky planets, k2 depends mostly on the relative size of the iron core, and hence on the bulk iron fraction. For ice-rich planets, the presence of outer ice layers reduces the amplitude of tidal response compared to ice-free rocky planets of similar masses. For both types of planet (rocky and ice-rich), we propose relatively simple scaling laws to predict the potential Love number value as a function of radius, planet mass and composition. For the dissipation rate, characterized by the Q−1 factor, we did not find any direct control by the planet mass. The dissipation rate is mostly sensitive to the forcing frequency and to the internal viscosity, which depends on the thermal evolution of the planet, which is in turn controlled by the planet mass and composition. The methodology described in the present study can be applied to any kind of solid planet and can be easily implemented into any thermal and orbital evolution code.
Privacy-Preserving Energy Trading Using Consortium Blockchain in Smart Grid

Implementing blockchain techniques has enabled secure smart trading in many realms, e.g. neighboring energy trading. However, trading information recorded on the blockchain also brings privacy concerns. Attackers can utilize data mining algorithms to obtain users’ privacy, specially, when the user group is located in nearby geographic positions. In this paper, we present a consortium blockchain-oriented approach to solve the problem of privacy leakage without restricting trading functions. The proposed approach mainly addresses energy trading users’ privacy in smart grid and screens the distribution of energy sale of sellers deriving from the fact that various energy trading volumes can be mined to detect its relationships with other information, such as physical location and energy usage. Experiment evaluations have demonstrated the effectiveness of the proposed approach.
ANALISIS FAKTOR-FAKTOR YANG MEMPENGARUHI PENGHENTIAN PREMATUR ATAS PROSEDUR AUDIT

ANALISIS FAKTOR-FAKTOR YANG MEMPENGARUHI PENGHENTIAN PREMATUR ATAS PROSEDUR AUDIT - Penghentian prematur atas prosedur audit (premature sign-off of audit procedures), time pressure, risiko audit, kompetensi auditor, auditee pressure, prosedur review dan quality control.
Exact solutions for laminated composite beams using a unified state space formulation

Abstract The variationally consistent methodology for generating state space models of 1D composite beams is evolved systematically and used to establish such models corresponding to different composite higher order beam theories. The state space form always yields the state vector in terms of generalized displacements and its associated generalized forces. It can handle arbitrary material coupling in a general manner and satisfy all the boundary conditions simultaneously. Numerical results of generally laminated beams under transverse loading using four warping functions of the normal and shear deformation theories for different boundary conditions are provided and compared with previous studies from the literature.
Superconductivity in the doped Hubbard model and its interplay with charge stripes and next-nearest hopping $t^{\prime}$

We report a large-scale density-matrix renormalization group study of the lightly doped Hubbard model on 4-leg cylinders at hole doping concentration $\delta=12.5\%$. By keeping a large number of states for long system sizes, we are able to reveal a delicate interplay between superconductivity and charge and spin density wave orders tunable via next-nearest neighbor hopping $t^{\prime}$. For finite $t^\prime$, the ground state is consistent with that of a Luther-Emery liquid, having `half-filled' charge stripes with power-law superconducting and charge-density-wave correlations of wave-length $\lambda=1/2\delta$, but short-range spin correlations. This is in direct contrast to the case with $t^{\prime}=0$, where superconducting correlations fall off exponentially while charge- and spin-density modulations are dominant. Our results indicate that a route to robust long-range superconductivity involves destabilizing insulating charge stripes in the doped Hubbard model.
Magneto-optical Stern-Gerlach forces and nonreciprocal torques on small particles

This research was supported by the Spanish MICINN and European Regional Development Fund (ERDF) through Projects No. FIS2015-69295-C3-1-P, No. FIS2015-69295-C3-3-P, No. PGC2018-095777-B-C21, No. PGC2018-095777-B-C22, the Basque Departamento de Educacion through Project No. PI-2016-1-0041, and the Maria de Maeztu Program No. MDM-2014-0377