Miracle-dz/UniFAR-FTUs huggingface dataset:
The Impact of Shareholding Structure on Enterprise Performance under Different Types of Placards

From 2013 to 2017, the wave of insurance placards surged from an overwhelming tide to disappearance, but the influence of placards continued in the follow-up period. This paper studies the performance's changes of listed companies before and after the placards year and explores the correlation between ownership structure and firm performance. The result shows that the performance falls significantly in the takeover year, the relation between it and the first big shareholder's ratio is the inverted "U" type in insurance sample, while it is the "U" type in non-insurance sample. What's more, the manager shareholding ratio, the ownership concentration and equity separation all play different roles in the insurance and non-insurance sample. The above study not only reveals how to improve the companies' shareholding structure and avoid malicious acquisitions but also gives suggestions on how to deal with the subsequent influence brought by the placards in today's environment, revealing what factors contribute to the improvement of performance.
Design and Development of Revolved 5G Core Networks Based on Lower-Layer Software-Defined and Upper-Layer Virtualized Approaches

5G EPC over Network Functions Virtualization (NFV) complemented with Software Defined Networking (SDN) framework is envisioned to be a novel paradigm of network architecture that supports a variety of access technologies and solves growth challenges and requirements such as seamless mobility management. Using cloud and virtualization, it manages and orchestrates the execution of mobile core servers on virtual machines. SDN can be used to segregate the network allowing multiple virtual mobile networks to co-exist on a physical datacenter network. This design is free of redundant functionality and inter-node interfaces that increase costs and reduce performance in hardware-based packet cores. With proposed vEPC (Virtualized Evolved Packet Core) framework we could construct a network of any-size with linear performance scaling on general-purpose servers for cost-effective business growth.
AgileSAR: Achieving Wide-Swath Spaceborne SAR Based on Time-Space Sampling

High resolution and wide swath, which are related to imaging quality and observation efficiency, are the key specifications for spaceborne synthetic aperture radar (SAR). Owing to the restrictions of the Nyquist sampling theorem, it is difficult to improve both specifications simultaneously. The increase of the swath width often leads to the decrease of the spatial resolution, e.g., in scanning SAR and terrain observation with progressive scan SAR. For a sparse scene, an image containing only a few targets has massive data but little useful information. This paper proposes a novel SAR observation mode, AgileSAR, which is based on the time–space sampling method and can overcome the limitations of the Nyquist theorem. It also increases the swath width while preserving the resolution of the sparse scene. AgileSAR steers the antenna beam towards a different sub-swath, generally after one or two pulse intervals, and the average pulse repetition rate corresponding to every sub-swath is much lower than that determined by the Nyquist theorem. Compared with Sentinel-1, which can achieve 5-m resolution and 80-km swath, a single azimuth-channel AgileSAR system can achieve 5-m resolution and 300-km swath for a sparse scene, once the corresponding system parameters are designed. The $\text{l}_{1}$ relaxation method is used to reconstruct sparse SAR images, and the reconstruction performance is quantitatively analyzed based on the estimation error. The simulation results validating the proposed method with sub-Nyquist samples can achieve approximately similar performance as conventional SAR with Nyquist samples.
Fast Frequency-Domain Compressed Sensing Analysis for High-Density Super-Resolution Imaging Using Orthogonal Matching Pursuit

Single-molecule localization methods play a vital role in a localization-based super-resolution fluorescence microscopy. However, it is difficult for conventional localization schemes based on the Gaussian fitting to locate overlapped high-density fluorescent emitters. Currently, in the spatial domain, the compressive-sensing-based algorithm (CSSTORM) can localize high-emitter-density images. However, the computational cost of this approach is extremely high, which limits its practical application. Here, we propose an alternative frequency-domain compressed sensing (FD-CS) technique for fast super-resolution imaging. Unlike the CSSTORM method, which is a measurement matrix based on the point spread function, a Fourier dictionary designed in the frequency domain and orthogonal matching pursuit is used to reliably recover the original signal. The simulation and experimental results prove that the FD-CS is 1000 times faster than CSSTORM with CVX and ten times faster than that with L1-Homotopy with almost the same localization accuracy and recall rate. This drastic reduction in computational time should allow the compressed sensing approach to be routinely applied to a super-resolution image analysis.
Analysis and Design of High-Efficiency Hybrid High Step-Up DC–DC Converter for Distributed PV Generation Systems

High step-up converters are required for distributed photovoltaic generation systems, due to the low voltage of the photovoltaic source. In this paper, a new hybrid high voltage gain dc–dc converter is created by merging the standard boost converter with a coupled inductor and different switched-capacitor techniques. With a single switch and no requirement of higher duty cycle values, the proposed converter achieves a high voltage gain and high efficiency, in addition to lowered voltage and current stresses of the components. A 200-W prototype was implemented experimentally to evaluate the converter, which reached a maximum efficiency of 97.6%.
A Fast Weighted SVT Algorithm

Singular value thresholding (SVT) plays an important role in the well-known robust principal component analysis (RPCA) algorithms which have many applications in machine learning, pattern recognition, and computer vision. There are many versions of generalized SVT proposed by researchers to achieve improvement in speed or performance. In this paper, we propose a fast algorithm to solve aweighted singular value thresholding (WSVT) problem as formulated in [1], which uses a combination of the nuclear norm and a weighted Frobenius norm and has shown to be comparable with RPCA method in some real world applications.
A novel algorithm for performance improvement of solar photovoltaics under partial shading conditions

The conventional sources of energy, widely used for generating electricity is depleting and there is rapid growth in electricity demand. Solar energy for electricity generation is popular and widespread as it is clean and abundantly found in nature. Partial shading on solar photovoltaics directly affects performance by reducing the power output of the system. As a contribution to further developments in photovoltaic technologies, factors that affect the performance of photovoltaics, under partial shading conditions were studied to improve the technology. Currently available strategies include the use of bypass diodes, Centralized Maximum Power Point Tracking, Distributed Maximum Power Point Tracking as solutions. Comparison of these methods were done and observed that Distributed Maximum Power Point Tracking gave the optimum solution. A DC-DC converter along with a Maximum Power Point Tracker was interfaced at each PV module which enabled the Maximum Power Point to be tracked. In this paper, a novel algorithm is proposed for optimal configuration of solar panels under partial shading conditions. The simulations were done in Matlab/Simulink.
Modified Wang Shaped Ultra-Wideband (UWB) Fractal Patch Antenna for Millimetre-Wave Applications

In this work, a microstrip line fed ultra-wideband (UWB) modified Wang shaped fractal patch (MWFP) antenna has been proposed. The parameters of the MWFP antenna such as operational bandwidth, efficiency, gain, and radiation pattern have been examined numerically. Four bands, 14.8-16.3 GHz, 19.6-21.5 GHz, 32.65-36.1 GHz and 40–160 GHz, are achieved. The operational bandwidth of the fourth band is from 40–160 GHz (U, V, E, W, F & D bands) which shows the fractional bandwidth as 120%, stable gain around 9.81 dB, efficiency of 80% and VSWR less than 1.8. The examined characteristics show that the proposed antenna is a good candidate for the applications of millimetre-wave.
Compression embarquée temps réel pour caméras rapides

Les cameras rapides sont de puissants outils pour etudier, par exemple, la dynamique des fluides ou le deplacement des pieces mecaniques lors d'un processus de fabrication. Nous decrivons dans ce papier, un nouveau type de camera rapide possedant un fonctionnement original. En effet, outre le fait qu'elle utilise comme d'autres cameras, la grande flexibilite des capteurs CMOS en termes d'acquisition (ROI), elle est novatrice au niveau du transfert des donnees. Celles-ci pouvant etre a la fois traitees et/ou compressees en temps reel au sein meme de la camera. Le transfert peut s'effectuer alors a l'aide d'une simple connection serie de type USB 2.0. On realise ainsi l'economie d'une memoire embarquee, les donnees etant directement stockees sur la memoire d'un PC standard, ce qui permet d'utiliser l'integralite de ses capacites (grande taille memoire, evolution constante). En parallele au developpement materielle de la camera, nous presenterons les algorithmes de compression integres au sein de la camera, notamment un algorithme nous permettant d'utiliser la camera a sa plus grande resolution (1280 x 1024 pixels) et avec une frequence image de 500 par seconde. Son taux de compression est de 20, avec un PSNR superieur `a 30.
An Improved Radar Anti-jamming Method

When the interference enters from the main lobe direction of the radar, the adaptive side-lobe cancellation algorithm will lead to beam distortion, main lobe pointing offset, and affect the detection of the target. This paper proposes a phase-coded signal system. Anti-jamming method, according to the characteristics of the transmitted signal, to construct a matched filter and blocking filter, the received signal through the two filters to get two signals, and then use the side lobe cancellation algorithm to filter out the interference of the auxiliary channel. However, this method will cause the sidelobe of the target Doppler cell to rise. For this problem, we propose to remove the Doppler trespass element from the target and then perform sidelobe cancellation. The algorithm is found through simulation. The interference from the main lobe can be effectively suppressed, and the distance sidelobes of the target Doppler unit are reduced, which verifies the effectiveness of the algorithm.
Nanomechanical Disk Resonator-on-Membrane with Pico-Meter Deflection Resolution

This paper reports on fabrication of nano mechanical disk resonators on micro-thick membranes and characterization of their resonance frequency shift due to air-pressure induced membrane deflection. Finite element analysis (FEM) has been used to show the estimate deflection at the center of the membrane. For the $20\mu \mathbf{m}$ thick, 2mm diameter membrane in this work, 1mPa of pressure change corresponds to 2pm of deflection (shear stress of 12Pa at the center of the membrane). Measurements show highest resonator sensitivity of 0.5Hz per pico-meter of deflection at the membrane center. In addition, it is shown that as the dimension of disks decreases from $20\mu \mathbf{m}$ to $5\mu \mathbf{m}$, the resonator sensitivity increases by about 8 times.
Emulating Wireless Networks with High Fidelity RF Interference Modeling

Wireless tactical data links such as Link-16 can experience a wide variety of interference from both allied communications and hostile jammers. This paper proposes a method to implement high-fidelity RF interference modeling in an emulated network using the open source CORE and EMANE software. A look up based statistical approach to define the RF interference in a pairwise RX/TX representation is inserted into the emulator at the physical (PHY) layer. This adjusts the reception in real time in order to analyze a network's performance in the presence of specific interference such as a jammer or another network using the same waveform. The comparative study conducted shows a percent error more than 95% for the base EMANE processing, in network packet loss, in our test setup with little degradation in emulation performance. Our algorithm reduces this error to almost zero.
Doppler Radar Vital Sign Detection Based on Complex Continuous Basis Pursuit Algorithm

The Doppler radar-based technique for noncontact vital sign detection has drawn increasing interest in recent years. In this paper, the signal model of human micro-motion is established and the Complex Continuous Basis Pursuit (CCBP)based vital sign detection algorithm for extracting the frequencies of human respiration and heartbeat signal is proposed. By exploiting the sparsity property of the established signal model, the proposed CCBP algorithm can extract the vital signal information by using the polar interpolation and the convex optimization problem solving technique. Simulation experiment results have verified the effectiveness and correctness of the proposed algorithm in the vital sign detection.
Finite-Time Adaptive Fuzzy Output Feedback Dynamic Surface Control for MIMO Nonstrict Feedback Systems

This paper investigates the finite-time adaptive fuzzy control problem for a class of multi-input and multi-output (MIMO) nonlinear nonstrict feedback systems. During the control design process, fuzzy logic systems (FLSs) are utilized to approximate the unknown nonlinear functions, and fuzzy state observer is constructed to estimate the unmeasured states. By combining adaptive backstepping with the dynamic surface control (DSC) technique, a finite-time fuzzy adaptive control scheme is presented to overcome the “explosion of complexity” problem. The stability of the close-loop systems can be proved based on the finite-time Lyapunov stability theory. The presented control scheme demonstrates that the closed-loop systems are semiglobal practical finite-time stability, and tracking errors converge to a small neighborhood of the origin in a finite time. Finally, two simulation examples are provided to show the effectiveness of the presented control method.
Entity Alignment Across Knowledge Graphs Based on Representative Relations Selection

Entity alignment across knowledge graphs is an important task in web mining. The aligned entities can be used for transferring knowledge across knowledge graphs and benefit several tasks such as cross-lingual knowledge graph construction and knowledge reasoning. This paper propose a representation learning based algorithm for embedding knowledge graph and aligning entities. In particular, considering the multi-type relations in knowledge graph, we select the alignment-task driven representative relations based on the pre-aligned entity pairs. With the help of selected relations, we embed the entities across networks into a common space by modeling entities’ head/tail are with corresponding context vectors. For entity alignment task, pre-aligned entities are adopted to facilitate the transfer of context information across the knowledges graphs. Through this way, the problem of entity embedding and alignment can be solved simultaneously under a unified framework. Extensive experiments on two multi-lingual knowledge graphs demonstrate the effectiveness of the proposed model comparing with several state-of-the-art models.
The Challenges in Development of Internet of Things Based Smart Power Distribution System

The traditional aging power grid is on the verge of revamp into the smart grid in which all stakeholders will have active participation. Internet of Things (IoT) will play a major role in the development of smart grid. The most of the countries giving thrust in incorporating the renewable generation for the purpose of getting clean energy. Mostly, the renewable generations are penetrating the low voltage side of the power system. This penetration is making the power distribution system a complex one. The power distribution system embedded with IoT can provide a solution to this complexity. But embedding the IoT into the power distribution system poses new challenges. This paper identifies these challenges in various interdisciplinary domains of the IoT power distribution system while surveying different latest literatures.
Effects of Span Length and Radar Polarimetry on the Backscattering Characteristics of Ultra-High Voltage Power Transmission Line in TerraSAR-X Images

With the continuous improvement of the spatial resolution of spaceborne synthetic aperture radar (SAR), detection of ultra-high voltage (UHV) power transmission line in high-resolution SAR images has become possible. However, the backscattering characteristics of UHV power transmission line in a SAR image are significantly influenced by several factors including the span length and the radar polarimetry. In this paper, the effects of span length and radar polarimetry on the backscattering characteristics of UHV power transmission line are analyzed by using the high-resolution TerraSAR-X images. We first give a brief introduction to the imaging geometry of UHV power transmission line. Subsequently, for different angles between the satellite ground track and the extend direction of power transmission line, the effect of span length on the scattering characteristics of power transmission line is described. In addition, the intensity and pixel size of scattering spots, which are formed by the power transmission line in the co-polarized SAR images, are analyzed. The analysis results show that the span length mainly influences the distance between the scattering spot and the perpendicular bisector of the power transmission lines. Moreover, the backscattering from the power transmission line can be found to be much stronger in the HH polarized SAR images compared with the VV polarized ones.
Metasurface Spectroscopic Analyzers

Diversity in design is a feature in metasurfaces. Spectroscopic responses by meta-surfaces significantly vary with depending on the structural details. However, the potential has not been well explored so far. In this paper, we report a non-empirical, large-scale numerical structural search for dielectric metasurfaces. As a result, we found new metasurfaces of narrow high-reflection windows. The metasurfaces are able to serve as spectroscopic analyzing elements in their zeroth-order reflection, in contrast to conventional diffraction gratings that exhibit spectra-analyzing functions in their first-order reflection or transmission. The metasurface spectroscopic analyzers make spectroscopic analyses simpler and more efficient, enabling to produce miniature spectroscopic devices.
Effects of Ionosphere Polarimetric Dispersion on Lower-Frequency Spaceborne SAR

Spaceborne synthetic aperture radar (SAR) systems, especially operating at lower-frequency, such as L-band and P-band, are significantly affected by ionosphere effects, therein, Faraday Rotation (FR) is the rotation of the polarization plane of the radar signal and reduces the accuracy of the polarization scattering matrix. Models of FR effects have already been proposed, but most of which ignore the polarimetric dispersion (PD) caused by FR for its high disturbance over the range bandwidth. A novel model of PD based on frequency domain range pulse compression is proposed in this paper, and simulation results show that PD has little effect on L-band systems and P-band-narrower-bandwidth SAR systems, but will introduce some serious effects on P-band-wider-bandwidth SAR systems.
The Load Balancing of Optimizing LEACH Clustering Algorithm with Mobile Sink and Rendezvous Nodes

This paper proposes a load balancing technique in optimizing LEACH clustering algorithm with mobile sink and Rendezvous nodes (RNs). The proposed paper focuses on network reliability, stability, lifetime and synchronous consumption of energy in the network. In this approach, the nodes which are outside the rendezvous region follow the clustering phenomenon. On the other hand, some nodes inside the rendezvous region are selected as RNs which are closest to their cluster heads and rest are treated as normal nodes which can transmit its data directly to the mobile sink. The simulation results verified that the performance of the proposed scheme is better than the optimizing LEACH.
Formation control of multiple UAV’s via decentralized control approach

In this article simultaneous arrival of multiple unmanned aerial vehicle (UAV) at a common point was studied in a fixed network hierarchy is used. By considering the model of fixed wing UAV the decentralized based control algorithm is developed for the formation control of all UAV’s. The tree based networked geometry is developed for the formation control of multiple UAV’s with respect to the leader. Whereas, UAV’s agent or (leader / follower) are autonomously connected with each other. Formation of flight via decentralized control structure which contains two parts, one is to achieve the arrival of expected meet-point for the formation geometry and other is to maintain the synchronization of all UAV’s. Moreover, the leader is supposed and able to regulate the speed or velocity of UAV’s. Simulated results showed that arrival of multiple UAV’s at a common point for the formation is achieved successfully and the above designed control algorithm has good robustness and flexible.
Toward an Adaptive Fair GPU Sharing Scheme in Container-Based Clusters

Virtualization is an innovative technology that accelerates software development by providing portability and maintainability of applications. However, it often leads underperformance especially caused by overheads from managing virtual machines. To address the limitation of virtual machines, container technology has emerged to deploy and operate distributed applications without launching entire virtual machines. Unfortunately, resources contention issues in container-based clusters, bringing substantial performance loss are still challenging. This paper proposes an adaptive fair-share method to share effectively in container-based virtualization environment. In particular, we focus on enabling GPU sharing between multiple concurrent containers without lack of GPU memory. We demonstrate that our approach contributes to overall performance improvement as well as higher resource utilization compared to default and static fair-share methods with homogeneous and heterogeneous workloads. Compared to two other conditions, their results show that the proposed method reduces by 16.37%, 15.61% in average execution time and boosts approximately by 52.46%, 10.3% in average GPU memory utilization, respectively.