Miracle-dz/UniFAR-FTUs huggingface dataset:
A quantum inspired differential evolution algorithm with multiple mutation strategies

The advent of the digital age and the internet has recently seen a corresponding increase in security concerns. Intrusion detection systems are one of the crucial factors to consider in today’s digital world. This paper proposes a metaheuristic algorithm based on quantum differential evolution with multiple strategies. This algorithm proposes a new differential mutation strategy approach to improve the search capability and convergence speed. Then, a quantum rotation gate is used to perform the secondary evolution of the population. Finally, various benchmark functions are chosen to demonstrate the optimization ability of the algorithm. The experimental results show that the model outperforms differential evolution and quantum differential evolution. And has better optimization capability, efficiency and stability. This evolutionary technique plays an important role in identifying network intrusions and security attacks.
Vortex Generators in a Two-Dimensional External-Compression Supersonic Inlet

Vortex generators within a two-dimensional external-compression supersonic inlet for Mach 1.6 were investigated to determine their ability to increase total-pressure recovery, reduce total-pressure distortion, and improve the boundary layer. The vortex generators studied included vanes and ramps. The geometric factors of the vortex generators studied included height, length, spacing, and positions upstream and downstream of the inlet terminal shock. The flow through the inlet was simulated through the computational solution of the steady-state Reynolds-averaged Navier–Stokes equations on multiblock structured grids. The vortex generators were simulated by either gridding the geometry of the vortex generators or modeling the vortices generated by the vortex generators. The inlet performance was characterized by the inlet total-pressure recovery, total-pressure distortion, and incompressible shape factor of the boundary layer at the engine face. The results suggested that ramps were not effective, and only .
A Design of Honeycomb-shape Coil for Wireless Charging of Leadless Cardiac Pacemaker

In this paper, a novel transmitting coil for magnetic resonance wireless power transfer is designed, which is called honeycomb-shape coil. It surrounds the human body and can form a stronger magnetic field than the traditional coil. Take the leadless cardiac pacemaker as an example, suppose it is on the left side of the heart and design the LCC-C compensation topology circuit to build an energy transmission system working at 13.56MHz, the simulation results show that the transmission efficiency is approximately 0.9%. When the received power is 1mW, the maximum average specific absorption rate (SAR) of the system is 0.240W/kg, which accords with the EN62209-1 human electromagnetic radiation standard.
A free-Lagrange augmented Godunov method for the simulation of elastic-plastic solids

A Lagrangian finite-volume Godunov scheme is extended to simulate two-dimensional solids in planar geometry. The scheme employs an elastic-perfectly plastic material model, implemented using the method of radial return, and either the 'stiffened' gas or Osborne equation of state to describe the material. The problem of mesh entanglement, common to conventional two-dimensional Lagrangian schemes, is avoided by utilising the free-Lagrange Method. The Lagrangian formulation enables features convecting at the local velocity, such as material interfaces, to be resolved with minimal numerical dissipation. The governing equations are split into separate subproblems and solved sequentially in time using a time-operator split procedure. Local Riemann problems are solved using a two-shock approximate Riemann solver, and piecewise-linear data reconstruction is employed using a MUSCL-based approach to improve spatial accuracy. To illustrate the effectiveness of the technique, numerical simulations are presented and compared with results from commercial fixed-connectivity Lagrangian and smooth particle hydrodynamics solvers (AUTODYN-2D). The simulations comprise the low-velocity impact of an aluminium projectile on a semi-infinite target, the collapse of a thick-walled beryllium cylinder, and the high-velocity impact of cylindrical aluminium and steel projectiles on a thin aluminium target. The analytical solution for the collapse of a thick-walled cylinder is also presented for comparison.
An Improved Multiscale Patch-Based Contrast Measure for Small Infrared Target Detection

Aiming at the problems of insufficient background suppression and weak multi-target detection abilities of existing infrared small target detection methods, which lead to high false alarm rate and high omission factor of infrared search and track system, an infrared small target detection method fusing modified anisotropic diffusion coefficients with multiscale patch-based contrast measure (ADMPCM) was proposed. The local contrast values of four different directions in the local area are applied into the modified anisotropic diffusion coefficient equation, and the final filtering result is the minimum function value of the four equations. Extraordinary experimental results revealed that, in average, background suppression factor increased 2.95 times, signal-to-clutter ratio gain increased 6.17 times on single-target detection task and 10.49 times on multi-target detection task, respectively, compared with similar detection methods.
Condition parameter degradation assessment and prediction for hydropower units using Shepard surface and ITD

A condition parameter degradation assessment and prediction model was developed to evaluate and forecast hydropower units based on the Shepard surface, intrinsic time-scale decomposition (ITD), a radial basis function (RBF) artificial neural network and grey theory. The model includes the effect of the active power and the working head on the hydropower unit’s condition. The condition parameter degradation time series is decomposed into a finite number of proper rotation components and an approximate component using the ITD method. The GM(1,1) model (a first-order one-variable grey model) is then used to predict the approximate component time series. The proper rotation component time series are then predicted separately by building different RBF neural networks. Finally, the original condition parameter degradation time series is found by adding these results. Real condition monitoring data from a pumped storage power station in China is used to verify the method. The results show that this method accurately reflects the condition parameter degradation for the hydropower unit.
Optimal weighting design for distributed parameter systems estimation

This paper presents a method which aims at improving parameter estimation in dynamical systems. The general principle of the method is based on a modification of the least‐squares objective function by means of a weighting operator, in view to improve the conditioning of the identification problem. First we recall a previous work using variational calculus in order to obtain the weighting operators through a linear equation. Then we propose a new approach which consists of determining the weights by formulating an optimization problem including positive semidefinite constraints (linear matrix inequalities, LMI). Copyright © 2001 John Wiley & Sons, Ltd.
Lower-Height-Oriented Magnetic Integration Design for Onboard Power Converter of Electric Vehicles

With the development of electric vehicles (EVs), EV onboard power converters are expected to pursue higher power density and lower height. Compared with active power devices, passive magnetics seems to be the main restriction for higher efficiency and power density. In the power distribution system, two-stage configurations of Buck + LLC converter are widely employed in various electronic equipment, which requires multiple magnetics. On this basis, the integration of two Buck + LLC converters has been studied to reduce the overall cost and improve the power density. First, the two buck converters are interleaved and operate in critical mode (CRM) to reduce current ripple and realize soft switching. Hence, the two buck inductors can be text negative-coupled with each other and integrated into one magnetic core to achieve lower switching frequency and smaller volume. In addition, the two LLC dc transformers are also integrated with only one switching leg and one magnetic core. By extending the effective area and canceling the text high-frequency magnetic flux, the loss and volume of both the integrated buck inductors and integrated LLC transformers are reduced significantly. Detailed integration methods and parameter design processes are presented. A 700-W, 150–350-V to 12-V dual-output text dc–dc converter with 500 W/in3 three power density is demonstrated to verify the effectiveness and feasibility of the proposed methods.
Coverage Reliability of IoT Intrusion Detection System based on Attack-Defense Game Design

The emergence of new applications of Internet of Things (IoT) makes its security and reliability become one of the most concerning issues and requires more breakthroughs. To ensure reliable operation of IoT, network reliability measures are essential for quantifying the performance of such networks. In this paper, we focus on the problem of coverage reliability of IoT intrusion detection systems based on Attack-Defense Game Design. A comprehensive coverage reliability algorithm is proposed based on Monte Carlo simulations. The algorithm employs Byzantine attack and defense ideas to determine network node attributes and uses confident information model to calculate the network coverage area. Furthermore, we propose a system reliability metric based on the analytic hierarchy process method, which takes advantage of node attributes, network coverage and connectivity. The metric is used to compare algorithms in simulated experiments, and a series of simulation comparisons illustrate the superiority and usability of the proposed approach.
Multi-source Data Fusion Base on Block-Term Decomposition in Federated Learning

With the development of the Internet of Things technology and the popularization of artificial intelligence, the number of edge devices in the network is growing exponentially. These devices are generating a large amount of data all the time. However, the traditional methods of centralized processing of these data usually require huge storage space and cause high computation burden. In addition, massive data is generally diversified, making the unified processing of these heterogeneous data more complicated, and the utilization of data is low. In this paper, we propose a Block-Term Decomposition (BTD) based algorithm in federated learning to make a fully utilization of multi-source data on edges. For the fusion problem of heteroge-neous data without interaction in Federated Learning (FL), the proposed algorithm introduces BTD method to capture the multi-dimensional characteristics of heterogeneous data by constructing high-order tensors. Experimental results on IEMOCAP dataset show that the proposed algorithm improve calculation accuracy in a single node and under FL framework.
Enhanced strength and toughness of polylactic acid by blending with modified natural rubber having acetate pendant group

Among biobased and biodegradable polymers, polylactic acid (PLA) is most widely used one. However, its poor mechanical properties need to be enhanced. In this study, PLA blend film with improved mechanical properties were developed without compromising any bio-content. For this, natural rubber derivative with acetate pendant group (ANR) and PLA blend films were prepared. First, natural rubber was epoxidized, and then partial acetylation was achieved by the ring-opening reaction of the epoxy groups. The epoxidation and the acetylation were examined by FTIR analysis. 1H-NMR spectrum revealed a 29% epoxidation and 8.25% acetylation degree. The Tg of natural rubber (−66°C) increased to −41°C and −31°C after epoxidation and acetylation, respectively. The compatibility of ENR and ANR with PLA was evident from the DSC results and Molau test. The morphology of PLA blend film containing 25 wt% of ANR (ANR25) was observed as well-dispersed fine droplets by SEM images. The tensile strength, elastic modulus, and yield strength of ANR25 were measured as 11.6 MPa, 397.3 MPa, and 6.9 MPa, respectively. These values are considerably higher than neat PLA film. Compared to reported studies on PLA toughening so far, increments in both the strength and elongation of ANR25 were observed by tensile tests. Moreover, highest toughness among all samples was determined as 18.8 MJm−3 for ANR25, which is 1.8 times higher than neat PLA. Thus, a strong and tough bio-based PLA blend was developed for film application such as packaging and sheeting.
Challenges of E-Learning: Behavioral Intention of Academicians to Use E-Learning during COVID-19 Crisis

The COVID-19 crisis demanded that all educational activities should be performed virtually to follow social distancing guidelines. Therefore, there was a need to perform a research study to assess the effects of external factors on the perceived usefulness, ease of use of e-learning, and the further effect of these perceptions on attitude and intent to use e-learning by using the technology acceptance model (TAM) among academicians at higher education institutions in the Kingdom of Saudi Arabia. Methods: A cross-sectional study was conducted, and data were collected from 263 academicians across Saudi Arabia through an online survey questionnaire using a non-probability purposive sampling technique and analyzed and tested using the SPSS and Smart PLS software. Results: This study found that self-efficacy was positively associated with perceived usefulness at β = 0.143 and p < 0.05, but it had no association with perceived ease of use at β = 0.057 at p > 0.05. System accessibility had a significant and positive relationship with perceived usefulness and perceived ease of use at β = 0.283, β = 0.247, and p < 0.01, respectively. Self-efficacy had a positive effect on perceived usefulness, whereas the subjective norm had no relationship with perceived usefulness and perceived ease of use at β = −0.065 and β = −0.012 at p > 0.05, respectively. Perceived ease of use and perceived usefulness were positively related to attitude towards use, which has a significant influence on intention to use e-learning. Conclusion: Perceived ease of application is the most significant factor (β = 0.556) in developing the attitude among academicians to practice e-learning, followed by perceived usefulness (β = 0.262). Moreover, it can be concluded that system accessibility has a stronger influence on developing perception among academicians about the expediency and ease of application of e-learning than self-efficacy.
Image segmentation algorithm based on the improved watershed algorithm

An improved watershed image segmentation algorithm based on particle swarm and region growing was proposed to solve the problems of noisesensitivity and over-segmentation.The improved algorithm,combining region growing with the classical watershed algorithm,was established by constructing an objective function based on Shannon entropy to determine the parameter of the region growing.The regional disparity degree was calculated by the gray mean,and the smaller region was merged with the neighbor region with a minimal disparity degree.The particle swarm optimization algorithm was employed to search the global optimization of the objective function.Experimental results show that this improved algorithm is better than other image segmentation methods,and can solve effectively the problem of over-segmentation that existed with the watershed algorithm.The segmentation results conform to the visual characteristics of the human eye,so this algorithm is therefore an effective,accurate,and practical image segmentation method.
Efficient SM2 Hardware Design for Digital Signature of Internet of Vehicles

The rapid development of the Internet of Vehicles (IoV) provides a strong technical guarantee for intelligent transportation, greatly facilitating people's daily travel. At the same time, its security problems are becoming increasingly prominent. Fortunately, the cryptographic integrated circuits (ICs) provide a security guarantee for the IoV access authentication, traffic management, data communication, etc., which is the core and cornerstone of the IoV cryptographic technology. However, the IoV has high requirements for timeliness, and its communication resources are precious, so its necessary to ensure that the overhead of the cryptographic module is small and the delay is low. In this paper, we adopt SM2 Elliptic Curve Public Key Digital Signature Algorithm-with fast operation speed and short signature data to implement cryptographic ICs. We design and optimize its hardware design to balance overhead and efficiency. Based on the Montgomery point multiplication algorithm in Lopez-Dahab (LD) projection coordinates, we have researched the core point multiplication operation in SM2 and optimized the time-consuming operation in finite fields, which improved the computational efficiency of SM2. Finally, we completed the hardware design of SM2 on GF(2233) domain and verified it on a Xilinx Kintex-7 FPGA development board. The experiment results show that the design occupies a total of 77,665 Slice LUTs and merely takes 2.57 μs to complete a signature verification. The signature verification rate is 389,105 times/s. Compared with traditional solutions, our proposed method achieves less overhead and little latency.
Engineering IoT-Based Open MAS for Large-Scale V2G/G2V

In this paper, we aimed to demonstrate how to engineer Internet of Things (IoT)-based open multiagent systems (MASs). Specifically, we put forward an IoT/MAS architectural framework, along with a case study within the important and challenging-to-engineer vehicle-to-grid (V2G) and grid-to-vehicle (G2V) energy transfer problem domain. The proposed solution addresses the important non-functional requirement of scalability. To this end, we employed an open multiagent systems architecture, arranging agents as modular microservices that were interconnected via a multi-protocol Internet of Things platform. Our approach allows agents to view, offer, interconnect, and re-use their various strategies, mechanisms, or other algorithms as modular smart grid services, thus enabling their seamless integration into our MAS architecture, and enabling the solution of the challenging V2G/G2V problem. At the same time, our IoT-based implementation offers both direct applicability in real-world settings and advanced analytics capabilities via enabling digital twin models for smart grid ecosystems. We have described our MAS/IoT-based architecture in detail; validated its applicability via simulation experiments involving large numbers of heterogeneous agents, operating and interacting towards effective V2G/G2V; and studied the performance of various electric vehicle charging scheduling and V2G/G2V-incentivising electricity pricing algorithms. To engineer our solution, we used ASEME, a state-of-the-art methodology for multiagent systems using the Internet of Things. Our solution can be employed for the implementation of real-world prototypes to deliver large-scale V2G/G2V services, as well as for the testing of various schemes in simulation mode.
A necessary and sufficient condition for Riemann's singularity theorem to hold on a Prym theta divisor

Let $(P,\Xi)$ be the naturally polarized model of the Prym variety associated to the étale double cover $\pi : \tilde C\rightarrow C$ of smooth connected curves defined over an algebraically closed field k of characteristic $\ne 2$, where genus(C) = $g \ge 3$, Pic$^{(2g-2)}(\tilde C) \supset P = \{\mathcal L \in {\rm Pic}^{(2g-2)}(\tilde C) : {\rm Nm}(\mathcal L) = \omega_C$ and $h^0(\tilde C,\mathcal L)$ is even\} is the Prym variety, and $P \supset \Xi = \{\mathcal L \in P: h^0(\tilde C,\mathcal L) >0 \}$ is the Prym theta divisor with its reduced scheme structure. If $\mathcal L$ is any point on $\Xi$, we prove that ‘Riemann's singularity theorem holds at $\mathcal L$’, i.e. mult$_{\mathcal L}(\Xi) = (1/2)h^0(\tilde C,\mathcal L)$, if and only if $\mathcal L$ cannot be expressed as $\pi^*(\mathcal M)(B)$ where $B \ge 0$ is an effective divisor on $\tilde C$, and $\mathcal M$ is a line bundle on C with $h^0(C,\mathcal M) >(1/2)h^0(\tilde C,\mathcal L)$. This completely characterizes points of $\Xi$ where the tangent cone is the set theoretic restriction of the tangent cone of $\tilde {\Theta}$, hence also those points on $\Xi$ where Mumford's Pfaffian equation defines the tangent cone to $\Xi$.
Forecasting Technological Substitutions with Concurrent Short Time Series

Abstract It has been shown in the literature that the data of technological substitutions exhibit a strong correlation across different time periods, that is, a strong serial correlation. Significant improvement in predicting such substitutions has been achieved by incorporating serial correlation and power transformation parameters into four growth curve models. The modified models, or data-based transformed models, however, break down when the number of time points is small. This article proposes a generalized growth curve model for forecasting technological substitutions with concurrent short time series. The model combines the concepts of power transformations and repeated measurements with a common serial covariance structure. Concurrent time series for several cases provide the repeated measurement requirement of the model. Improvement in forecasting accuracy by using this model is demonstrated with a set of telephone switching data.
Analysis of Cattaneo–Christov heat flux and thermal radiation on Darcy–Forchheimer flow of Reiner–Philippoff fluid

The non-Newtonian liquid scheme is created to address the limitations of the classical (Newtonian) scheme in terms of accurately reflecting real-world fluid flow behavior in industrial applications and improving operational efficiency. The Reiner–Philippoff model, one of the many extant models, modeling non-Newtonian fluids, is of concern because it only captures a few features in some circumstances. Thus, this study aims to investigate the theoretical aspects of Cattaneo–Christov for heat diffusion fusion of Reiner–Philippoff liquid stream in the presence of Darcy–Forchheimer media. Furthermore, the procedure of heat transport is taken out in the occurrence of nonlinear heat radiative, viscous dissipation and Ohmic heating. The partial derivatives of nonlinear differential equations are changed into similarity equations of a certain form by using appropriate similarity transformations. Furthermore, the Runge–Kutta–Fehlberg method with shooting approach is utilized to solve the dimensionless model. The influence of pertinent fluid flow parameters is illustrated graphically. The further engineering curiosity of a local Nusselt number is illustrated and analyzed. It is found that velocity curve is boosted with the augmenting scales of Reiner–Philippoff liquid parameter and Forchheimer number. Further, it is analyzed that increasing the thermal relaxation parameter and Eckert number reduces the heat transport rate at the surface.