Miracle-dz/UniFAR-FTUs huggingface dataset:
Data Mining Approach for the Identification of the Intelligent Gear Decision Strategy for the Stepped Automatic Transmission

The primary goal of automatic transmission vehicle design and optimization is to ensure that drivers can operate automatic transmission vehicles with the same driving experience as skilled drivers driving manual transmission vehicles. However, the existing gear decision strategies of stepped automatic transmission vehicles have poor adaptability to different driving intentions and complex driving environments. When operating manual transmission vehicles, skilled drivers can make intelligent gear decision to satisfy their driving intentions and adapt to different driving environments. Therefore, this study's objective is to establish the design and formulation process for the identification of the intelligent gear decision strategy for the stepped automatic transmission that adapts to different driving intentions and complex driving environments. This is achieved using the data mining method to identify skilled drivers’ gear decision strategy from their driving data. To this end, the driving data of skilled drivers operating manual transmission vehicles are collected. The shift boundary points of each gear under the target driving condition are obtained through data preprocessing, data cleaning, outlier processing, and boundary points extraction. Thereafter, the gear decision strategy of skilled drivers is established by fitting the shift boundary points. Taking the flat-straight road condition as an example, the gear decision strategy is established and experimental comparisons are made to verify the effectiveness of proposed gear decision design method.
Non-Bianisotropic Complementary Split Ring Resonator Metamaterial Bandstop Filter Using Cylindrical Metal Vias

This brief presents a bandstop filter using the Non-bianisotropic Complementary Split Ring Resonator (NBCSRR) and cylindrical metal vias, which exhibits electromagnetic bandgap behavior. A compact bandstop filter structure is achieved using NBCSRR sub-wavelength operation. The filter prototype is fabricated and tested, and the measured results agree well with the simulated results. The filter has higher bandstop rejection levels in the X band, which ranges from 8.8GHz to 9.3GHz.
Measures of the full Hausdorff dimension for a general Sierpiński carpet

The measure of the full dimension for a general Sierpinski carpet is studied. In the first part of this study, we give a criterion for the measure of the full Hausdorff dimension of a Sierpinski carpet. Meanwhile, it is the conditional equilibrium measure of zero potential with respect to some Gibbs measure $\nu_{\alpha}$ of matrix-valued potential $\alpha\mathbf{N}$ (defined later). On one hand, this investigation extends the result of [17] without condition \textbf{(H)}. On the other hand, it provides a checkable condition to ensure the existence and uniqueness of the measure of the full Hausdorff dimension for a general Sierpinski carpet. In the second part of this paper we give a criterion for the Markov projection measure and estimate its number of steps by means of the induced matrix-valued potential. The results enable us to answer some questions which arise from [1] and [4] on the projection measure and factors.
Universal deformation formula, formality and actions

In this paper we provide a quantization via formality of Poisson actions of a triangular Lie algebra $(\mathfrak g,r)$ on a smooth manifold $M$. Using the formality of polydifferential operators on Lie algebroids we obtain a deformation quantization of $M$ together with a quantum group $\mathscr{U}_\hbar(\mathfrak{g})$ and a map of associated DGLA's. This motivates a definition of quantum action in terms of $L_\infty$-morphisms which generalizes the one given by Drinfeld.
A Generic Framework for Deploying Video Analytic Services on the Edge

This article introduces a novel distributed model for handling in real-time, edge-based Artificial Intelligence analytics, such as the ones required for smart video surveillance. The novelty of the model relies on decoupling and distributing the services into several decomposed functions which are linked together, creating virtual function chains (<inline-formula><tex-math notation="LaTeX">$VFC$</tex-math><alternatives><mml:math><mml:mrow><mml:mi>V</mml:mi><mml:mi>F</mml:mi><mml:mi>C</mml:mi></mml:mrow></mml:math><inline-graphic xlink:href="tsakanikas-ieq1-3218813.gif"/></alternatives></inline-formula> model). The model considers both computational and communication constraints. Theoretical, simulation and experimental results have shown that the <inline-formula><tex-math notation="LaTeX">$VFC$</tex-math><alternatives><mml:math><mml:mrow><mml:mi>V</mml:mi><mml:mi>F</mml:mi><mml:mi>C</mml:mi></mml:mrow></mml:math><inline-graphic xlink:href="tsakanikas-ieq2-3218813.gif"/></alternatives></inline-formula> model can enable the support of heavy-load services to an edge environment while improving the footprint of the service compared to state-of-the art frameworks. In detail, results on the <inline-formula><tex-math notation="LaTeX">$VFC$</tex-math><alternatives><mml:math><mml:mrow><mml:mi>V</mml:mi><mml:mi>F</mml:mi><mml:mi>C</mml:mi></mml:mrow></mml:math><inline-graphic xlink:href="tsakanikas-ieq3-3218813.gif"/></alternatives></inline-formula> model have shown that it can reduce the total edge cost, compared with a Monolithic and a Simple Frame Distribution models. For experimenting on a real-case scenario, a testbed edge environment has been developed, where the aforementioned models, as well as a general distribution framework (Spark ©) and an edge-deployement framework (Kubernetes©), have been deployed. A cloud service has also been considered. Experiments have shown that <inline-formula><tex-math notation="LaTeX">$VFC$</tex-math><alternatives><mml:math><mml:mrow><mml:mi>V</mml:mi><mml:mi>F</mml:mi><mml:mi>C</mml:mi></mml:mrow></mml:math><inline-graphic xlink:href="tsakanikas-ieq4-3218813.gif"/></alternatives></inline-formula> can outperform all alternative approaches, by reducing operational cost and improving the QoS. Finally, a caching and a QoS monitoring service based on Long-Term-Short-Term models are introduced and evaluated.
Sea Clutter Feature Prediction and Parameters Inversion Using Deep Learning Model

The characteristics of sea clutter in real marine environments in different sea areas play a vital role in military industry, such as radar detection, remote sensing, SAR imaging, and situational awareness. In this article, a deep neural network (DNN) sea clutter model is proposed based on the sea clutter big data under the real marine environment to study the characteristics of sea clutter and parameter inversion. Based on the ERA-Interim reanalysis (2015–2017), a database of marine environmental elements in China's offshore waters was established, and a spatiotemporal prediction model for marine environmental elements was proposed to improve missing values. Considering the scattering mechanism of sea surface at different scales comprehensively, a large database of sea clutter time series of multiscale real surface is established and comparison with the experimental data. Aiming at the coastal waters of China, the long short-term memory model and DNN are used to establish the correlation model between marine environmental elements and sea clutter characteristics, and the prediction and parameter inversion of sea clutter characteristics based on sea clutter big data are studied. The results show that the coefficients of determination of the predicted fitted curves for the HH and VV polarization amplitudes reach 0.9249 and 0.8872, respectively. The inversion of wave heights in different sea areas is the lowest in the South China Sea (accuracy rate of 78%) and the highest in the East China Sea (accuracy rate is 90%). The results of this article can help improve the ability of sea surface remote sensing and sea clutter suppression.
ON QUASIHYPERBOLIC GEODESICS IN BANACH SPACES

We study properties of quasihyperbolic geodesics on Banach spaces. For example, we show that in a strictly convex Banach space with the Radon-Nikodym property, the quasihy- perbolic geodesics are unique. We also give an example of a convex domain in a Banach space such that there is no geodesic between any given pair of points x,y ∈ . In addition, we prove that if X is a uniformly convex Banach space and its modulus of convexity is of a power type, then every geodesic of the quasihyperbolic metric, defined on a proper subdomain of X, is smooth.
A TM11 High-Order Mode Leaky Wave Antenna

A novel leaky-wave antenna (LWA), which operates at the <inline-formula> <tex-math notation="LaTeX">$TM_{11}$ </tex-math></inline-formula> high-order mode, is proposed. This LWA achieves a 4.6 times higher gain than the traditional TE10-based LWAs. An analytical formulation is derived, which shows that a <inline-formula> <tex-math notation="LaTeX">$TM_{11}$ </tex-math></inline-formula>-based LWA couples more energy to free space through an appropriately designed slot than traditional TE10-based LWAs. Simulations are used to compare the performance of our proposed <inline-formula> <tex-math notation="LaTeX">$TM_{11}$ </tex-math></inline-formula>-based LWA with a similar LWA that operates at its fundamental TE10 mode. Specifically, it is shown that our <inline-formula> <tex-math notation="LaTeX">$TM_{11}$ </tex-math></inline-formula> high-order mode LWA achieves 6.67 dB higher gain than a TE10-mode LWA that operates at the same frequency. Also, a <inline-formula> <tex-math notation="LaTeX">$TM_{11}$ </tex-math></inline-formula>-mode LWA is designed to mitigate the open-stopband (OSB) problem. This design achieves a fan beam with a maximum gain of 15.4 dBi and a scanning elevation range of 18° (through the broadside direction) in a bandwidth of 2 GHz. Prototypes of our LWA designs are manufactured using a cost-effective additive manufacturing method (i.e., selective laser melting), and their performance is measured. The measurements exhibit good agreement with simulations, thereby validating the proposed designs.
Unveiling the Capacity Drop Phenomenon Through Traffic Microsimulation: Modeling, Calibration, and Sensitivity Analysis

The Capacity Drop (CD) is a sustained drop in a freeway bottleneck outflow when its upstream section becomes congested. Understanding how to replicate CD with microscopic models can help us to better understand its properties and mechanism. However, there is no published study replicating an observed occurrence of CD using microscopic models. In this study, we combine a lane-changing model with two widely known car-following models and calibrate the combined model parameters against field data, to replicate the CD in a merge bottleneck. We confirm that both car-following models can reproduce the CD. Moreover, we show that including the cooperative lane-changing behavior in the model is critical for the replication success. Further, we perform a sensitivity analysis with respect to the ramp demand and maximum acceleration parameters, showing: (i) slower acceleration rate leads to a lower bottleneck throughput, and (ii) higher ramp demand leads to decreased bottleneck throughput.
Fair Energy-Efficient Resource Optimization for Multi-UAV Enabled Internet of Things

Unmanned aerial vehicle (UAV) enabled Internet of Things (IoT) can keep network connectivity when the ground infrastructures are paralyzed. However, its transmission perform will be restricted due to the limited energy of the UAV. In this paper, a multi-UAV enabled IoT is proposed, where the UAVs as base stations send information to the ground IoT nodes via downlink within the flight time. And a fair energy-efficient resource optimization scheme for the IoT is studied to ensure fair energy consumption of multiple UAVs. The optimization problem seeks to maximize the minimum energy efficiency of each UAV by jointly optimizing communication scheduling, power allocations and trajectories of the UAVs. We decompose the non-convex optimization problem into three sub-optimization problems and solve them by Dlinkelbach method and successive convex approximation (SCA). Then a joint optimization algorithm is put forward to obtain the global optimal solutions by iteratively optimizing the three sub-optimization problems. The simulations results show that the multi-UAV enabled IoT can achieve significant performance improvement, and the energy efficiency between UAVs can achieve relative fairness by the fair resource optimization.
Recovery-Based Error Estimators for Diffusion Problems: Explicit Formulas

We introduced and analyzed robust recovery-based a posteriori error estimators for various lower order finite element approximations to interface problems in [9, 10], where the recoveries of the flux and/or gradient are implicit (i.e., requiring solutions of global problems with mass matrices). In this paper, we develop fully explicit recovery-based error estimators for lower order conforming, mixed, and non- conforming finite element approximations to diffusion problems with full coefficient tensor. When the diffusion coefficient is piecewise constant scalar and its distribution is local quasi-monotone, it is shown theoretically that the estimators developed in this paper are robust with respect to the size of jumps. Numerical experiments are also performed to support the theoretical results.
DIFFERENCE ALGEBRAIC RELATIONS AMONG SOLUTIONS OF LINEAR DIFFERENTIAL EQUATIONS

We extend and apply the Galois theory of linear differential equations equipped with the action of an endomorphism. The Galois groups in this Galois theory are difference algebraic groups, and we use structure theorems for these groups to characterize the possible difference algebraic relations among solutions of linear differential equations. This yields tools to show that certain special functions are difference transcendent. One of our main results is a characterization of discrete integrability of linear differential equations with almost simple usual Galois group, based on a structure theorem for the Zariski dense difference algebraic subgroups of almost simple algebraic groups, which is a schematic version, in characteristic zero, of a result due to Z. Chatzidakis, E. Hrushovski, and Y. Peterzil.
On Demazure and local Weyl modules for affine hyperalgebras

We establish the existence of Demazure flags for graded local Weyl modules for hyper current algebras in positive characteristic. If the underlying simple Lie algebra is simply laced, the flag has length one, i.e., the graded local Weyl modules are isomorphic to Demazure modules. This extends to the positive characteristic setting results of Fourier-Littelmann and Naoi for current algebras in characteristic zero. Using this result, we prove that the character of local Weyl modules for hyper loop algebras depend only on the highest weight, but not on the (algebraically closed) ground field, and deduce a tensor product factorization for them.
Estimating Worldwide Impact of Low Physical Activity on Risk of Developing Ischemic Heart Disease-Related Disability: An Updated Search in the 2019 Global Health Data Exchange (GHDx)

We provide here updated analysis of the impact of physical inactivity on risk of developing ischemic heart disease (IHD)-related disability along with the latest 10-year progression. We collected data through an electronic search in the 2019 Global Health Data Exchange (GHDx) database using the keywords “low physical activity”, complemented with the additional epidemiologic variables “disability-adjusted life years” (DALYs; number); “ischemic heart disease”; “socio-demographic index” (SDI); “age”; “sex” and “year”, for calculating volume of DALYs lost due to physical activity (PA)-related disability after IHD (LPA-IHD impairment). Based on this search, the overall LPA-IHD impairment was estimated at 7.6 million DALYs in 2019 (3.9 and 3.7 million DALYs in males and females, respectively), thus representing nearly 50% of all PA-related disabilities. The highest impact of LPA-IHD impairment was observed in middle SDI countries, being the lowest in low SDI countries. The LPA-IHD DALYs increased by 17.5% in both sexes during the past 10 years (19.2% in males, and 15.8% in females, respectively), though this trend was dissimilar among different SDI areas, especially during the past two years. In high and high–middle SDI countries, the LPA-IHD grew during the past 2 years, whilst the trend remained stable or declined in other regions. In conclusion, LPA-IHD impairment remains substantial worldwide, leading the way to reinforce current policies aimed at increasing PA volume in the population.
Comprehensive Analysis and Gain Derivation of Phase-Shifted Dual-Input LLC Converter

This paper presents a comprehensive time-domain analysis of the dual-input LLC converter. By utilizing PSM and FSM, the converter power stage interfaces two photovoltaic (PV) panels to achieve maximum power point tracking (MPPT). The detailed mode-by-mode operation and steady-state analysis are derived using three parameters: the switching frequency, phase shift, and load weight. Furthermore, the DC gain equations of each PV panel and their characteristic curves are derived. In addition, the waveform boundaries and ZVS analysis are discussed as well. Moreover, an extended perturbation & observation (P&O) algorithm that guarantees achieving MPPT for each panel is proposed. Finally, the theoretical analysis has been tested and verified by a 450-W prototype of dual-input LLC converter.
TestAXE: Automatically Refactoring Test Smells Using JUnit 5 Features

Test smells have been proven to deteriorate the quality of the test suite of a system, to the point where several different tools have been devised with the objective of detecting or sometimes even fixing these smells. Have been extensively studied in more recent years, these smells have been cataloged and researchers have proposed a series of source code transformations capable of eliminating these smells. Our goal in this paper is to present TESTAXE, a tool to refactor test smells using the latest features of JUnit 5. We present an empirical assessment of TESTAXE accuracy and highlight its current limitations.
Analysis of radix selection on Markov sources

The complexity of the algorithm Radix Selection is considered for independent data generated from a Markov source. The complexity is measured by the number of bucket operations required and studied as a stochastic process indexed by the ranks; also the case of a uniformly chosen rank is considered. The orders of mean and variance of the complexity and limit theorems are derived. We find weak convergence of the appropriately normalized complexity towards a Gaussian process with explicit ∞ �
Investigation of a Novel Biperiodic Reltron for High-Power Microwave Generation

A novel configuration of a reltron, referred to as the biperiodic reltron, has been proposed to generate gigawatts-level RF radiation. It uses a modified modulation cavity, in which double-side coupled modulation cavities are biperiodically associated instead of a single-side coupled modulation cavity as in the conventional case. All three feasible resonating modes, i.e., 0, <inline-formula> <tex-math notation="LaTeX">$\pi $ </tex-math></inline-formula>/2, and <inline-formula> <tex-math notation="LaTeX">$\pi $ </tex-math></inline-formula> modes, generated concurrently at the two different resonant frequencies provided a good field stability against unwanted perturbations. With the input beam current and voltage of ~53 kA and 400 kV, respectively, the proposed biperiodic reltron has predicted ~12-GW RF power generation with ~57% efficiency using particle-in-cell (PIC) simulation.
The equivariant Cuntz semigroup

We introduce an equivariant version of the Cuntz semigroup that takes an action of a compact group into account. The equivariant Cuntz semigroup is naturally a semimodule over the representation semiring of the given group. Moreover, this semimodule satisfies a number of additional structural properties. We show that the equivariant Cuntz semigroup, as a functor, is continuous and stable. Moreover, cocycle conjugate actions have isomorphic associated equivariant Cuntz semigroups. One of our main results is an analog of Julg's theorem: the equivariant Cuntz semigroup is canonically isomorphic to the Cuntz semigroup of the crossed product. We compute the induced semimodule structure on the crossed product, which in the abelian case is given by the dual action. As an application of our results, we show that freeness of a compact Lie group action on a compact Hausdorff space can be characterized in terms of a canonically defined map into the equivariant Cuntz semigroup, extending results of Atiyah and Segal for equivariant K ‐theory. Finally, we use the equivariant Cuntz semigroup to classify locally representable actions on direct limits of one‐dimensional NCCW‐complexes, generalizing work of Handelman and Rossmann.
Liftings of finite linearly reductive torsors of curves in positive characteristic

Let $U$ be a smooth curve over a complete discrete valuation ring $R$ with algebraically closed residue field $k$ of characteristic $p>0$ together with a smooth compactification $X$ with $D=X\setminus U$ etale over $R$. Let $U_0$ denote its special fiber. Grothendieck's specialization theorem for the prime-to-$p$ etale fundamental group includes the fact that any prime-to-$p$ Galois covering of $U_0$ can be uniquely lifted to a prime-to-$p$ covering of $U$. In this paper, we will ask such a lifting problem for finite linearly reductive torsors and prove that the existence of a lifting is true if one allows a finite extension of $R$. We will also observe that the unicity of a lifting cannot be valid in general even in the equal characteristic case and discuss on a moduli-dependency of the corresponding fundamental group scheme as a related topic.
Localizing virtual fundamental cycles for semi-perfect obstruction theories

Recently H. -L. Chang and J. Li generalized the theory of virtual fundamental class to the setting of semi-perfect obstruction theory. A semi-perfect obstruction theory requires only the local existence of a perfect obstruction theory with compatibility conditions. In this paper, we generalize the torus localization, the cosection localization and their combination, to the setting of semi-perfect obstruction theory. As an application, we show that the Jiang-Thomas theory of virtual signed Euler characteristic works without the technical quasi-smoothness assumption from derived algebraic geometry.
Hastening Stream Offloading of Inference via Multi-Exit DNNs in Mobile Edge Computing

As the primary driver of intelligent mobile applications, deep neural networks (DNNs) have gradually deployed to millions of mobile devices, producing massive latency-sensitive and computation-intensive tasks daily. Mobile edge computing facilitates the deployment of computing resources at the edge, which enables fine-grained offloading of DNN inference tasks from mobile devices to edge nodes. However, most existing studies have not systematically considered three crucial performance aspects: scheduling multiple streams of DNN inference tasks, leveraging multi-exit models to hasten task processing, and partitioning inference models for partial offloading. To this end, this paper proposes an adaptive inference framework in mobile edge computing, which can dynamically select the exit point and partition point for multiple inference task streams. We design a dynamic programming algorithm to obtain an efficient solution under the ideal condition that task arrival information is known. Further, we design a learning-based algorithm for online scheduling, whose training efficiency is improved based on historical experience initialization and priority experience replay. Experimental results show that compared with the Greedy algorithm, the online algorithm improves the performance on two environmental parameters by an average of 5.9% and 32%, respectively.