Miracle-dz/UniFAR-FTUs huggingface dataset:
A Simulation of an IoT-based Solution Using LoRaWAN for Remote Stations of Peruvian Navy

Peruvian Navy uses a Supervisory Control and Data Acquisition (SCADA) system to monitor and control its remote meteorological and luminous stations which are out of town and powered by photovoltaic systems. They use cellular gateways with high energy consumption to transmit data to a control center using the services of a mobile service provider. The storage of the obtained information and system management is done in a single location. This paper focuses on the design of an IoT-based solution using LoRaWAN technology and a cloud IoT platform to replace the current system and give mobility, redundancy and efficiency characteristics. The path loss and coverage for the farthest remote station is calculated using the Okumura-Hata propagation model and two radio propagation simulators. A LoRaWAN end-node with meteorological sensors is simulated and a web page is developed to show the information to the users.
Sparse Online Portfolio Selection Based on Proximal Gradient

To improve existing online portfolio selection strategies when the number of assets is large, we propose an online portfolio selection strategy based on the proximal gradient projection (PGP). This paper first applies the L_1 norm of portfolio weights to portfolio construction and gains the sparse rebalance rule. PGP strategy is backtested on the four datasets. The empirical results show that the PGP strategy outperforms almost all the latest portfolio selection strategies in most cases. In addition to its superior performance, the PGP algorithm needs to be linear with the product of the number of stocks and trading days. It runs fast in backtests and thus is very suitable for large scale or high frequency online trading applications. Moreover, the SGP strategy can sustain reasonable transaction costs.
A Voronoi Diagram-Based Grouping Test Localization Scheme in Wireless Sensor Networks

With the rapid development and wide application of wireless sensor networks (WSNs), localization, as one of key technologies, has also received more and more attention. In this paper, we present a novel range-free localization scheme for WSNs which use the region test and Centroid algorithm to estimate the position. Considering environmental interference and irregular propagation of signals, a reliable method is proposed to find overlapping regions by Voronoi diagram of grouping anchor nodes. We use the grid scan method to simplify the Centroid calculation. Furthermore, we compare VTL algorithm with other two range-free algorithms by simulation experiments which show that VTL algorithm performs well in localization accuracy and estimation percentage.
Wavelet Transform-Based One Dimensional Manifold Embedding For Hyperspectral Image Classification

Traditional wavelet transform-based methods process decompose coefficient in high-dimensional, which makes computational complicated. In order to address this problem, in this paper, a novel approach named wavelet transform-based one dimensional manifold embedding (WT1DME) is proposed for HSI classification. In the proposed approach, firstly, using wavelet transform decomposes the input signal into an approximate coefficients (ACs). Then, smooth ordering is applied to the ACs which maps the coefficients into one-dimensional (1-D) space. Finally, since the coefficients in the 1-D space, hence, 1-D signal processing tools can be applied to build final classifier(we utilize interpolation in this paper). Our proposed methods can be used to process the decompose coefficients in 1-D space, which can perform efficiently. The proposed scheme is experimentally demonstrated by two HSI data sets: IndianPines, University of Pavia has the state-of-the-art performance of results.
Beam-Superposition-Based Multi-beam RSMA for Hybrid mmWave Systems

In this paper, a beam-superposition based multi-beam rate splitting multiple accesses (RSMA) transmission scheme is proposed for hybrid mmWave system. Firstly, multiple initial single-beam analog precoders are designed according to the users’ angle-of-departure (AoD). Then multiple initial single-beam analog precoding vectors of the same non-orthogonal multiple access (NOMA) group are superimposed. Applying constant modulus constraints on the newly generated precoding vectors, the beam-superposition based multi-beam precoding vector can be obtained. In this way, the entire antenna array can be applied to generate multiple analog beams at the same time. Furthermore, due to the higher adaptability of RSMA than NOMA to the distinction of channel gain and orthogonality between beams, the RSMA technology is applied to the beam-superposition based multi-beam scheme, which is proved by simulations that the use of RSMA achieves a higher system sum-rate than the use of the NOMA scheme and time division multiple access (TDMA) scheme.
E-Band RF MEMS Differential Reflection-Type Phase Shifter

A systematic approach in the design methodology, leading to the optimization of a differential reflection-type phase shifter (RTPS), is presented. The key parameters of the quadrature coupler and the reflective loads are analyzed for optimum RTPS performance, showing that: 1) equality between the coupling and through transmission coefficients provides the best return and insertion loss; 2) a minimized coupler reflection coefficient with negative phase optimizes the return loss and the phase performance; and 3) a wide tunable reflective load with minimized resistance assures lower insertion loss and larger phase range. The even–odd mode analysis leads to the coupler miniaturization. The differential microstrip line dimensions are determined by the minimum feature size of our fabrication process. By choosing the separation between the coupled lines, the even- and odd-mode characteristic impedances satisfy the derived design equations for equalized quadrature outputs and provide the matching capacitance. By exploiting the virtual ground of the differential structure, a novel RF MEMS reconfigurable short circuit is introduced for the reflective loads aiming at 180° phase shift range and low insertion loss. Over the 70–86-GHz range, the measurements show good agreement with the simulations. The measured RTPS achieves a 195.6° phase shift range with a phase error less than 8.6° and insertion loss error less than 0.7 dB. For all phase states, the reflection coefficients are below −18 dB, and at 74 GHz, the insertion loss is 4.4 ± 0.5 dB.
Trajectory tracking for vessels with the kinematic model using complex networks

In this work, the trajectory synchronization in ship networks is proposed applying the theory of complex dynamic networks. The network nodes were modeled by the kinematic equation in the horizontal plane, without considering environmental disturbances. To solve the trajectory synchronization problem, the error synchronization is calculated as the difference between the ships trajectories, and then this error must be converged to zero. The error convergence is proven by the Lyapunov analysis proposed in the present work. The control law design for this method is determined by the structural properties of the network, as well as the dynamic characteristics in the nodes, and the simple choice of a coupling constant. To keep the separation distance between the ships trajectories a repulsion coefficient is added into the control law. Numerical simulations were carried out using Matlab, showing a fast error convergence for network synchronization. The obtained results in this work suggest the use of this method to solve the trajectory tracking problem in coordinated motion between ships, where the nodes in the network include the dynamic equation for ships.
Strategic Analysis of User Association Based on Power-Domain Non-Orthogonal Multiple Access in Visible Light Communication Multi-cell Networks

Multi-cell visible light communication (VLC) network with non-orthogonal multiple access (NOMA) has its own challenges, such as inter-cell interference (ICI) and poor edge-user experience. As user association is an important base for network management, this paper focuses on the strategic analysis of user association and reveals the characteristics of user association principles in multi-cell NOMA-VLC networks. First, we establish a system model including interference of NOMA in multiple cells. Second, we present the violation of the principle of proximity access and derive a closed-form sufficient condition for edge users based on visible light channels. Third, we evaluate the cell deployment of NOMA-VLC involved with the strategic analysis of user association. Finally, simulation results indicate that the violation of the principle of proximity access achieves better data rate performance than the traditional one based on the sufficient condition. Furthermore, Monte Carlo simulations show that the numerical results are supported by the analytic derivation.
A Proposed Method to Improve Higway Construction Quality Using Machine Learning

The US government spends billions of dollars every year for repair and rehabilitation of structures. The objective of this research is to present a model that would help civil engineers predict the overall construction quality of highways and avoid premature failures. Advanced Machine Learning techniques are developed and implemented on simulated datasets as well as field data. The dataset for this paper contains data elements, which describe the quality of construction materials and the quality of various layers of the road foundation. An Artificial Neural Network is built and trained to perform supervised learning on the dataset resulting in a predictive model to predict the overall construction quality from the selected features.
A Formation Maintenance and Reconstruction Method of UAV Swarm based on Distributed Control with Obstacle Avoidance

This paper studies the problem of formation maintenance and reconstruction of UAV swarm with obstacle avoidance. Firstly, a collision prediction mechanism is introduced to determine whether each UAV needs to avoid obstacles or not. Secondly, by designing the position and speed consistency control law between UAVs, each UAV and the virtual leader, combined with the obstacle avoidance mechanism based on the artificial potential field method, the swarm formation control and maintenance algorithm with obstacle avoidance is realized. Finally, the formation transformation is realized by changing the relative positional relationship between each UAV and the virtual leader. The simulation results show that the UAV swarm can generate, maintain and reconstruct the expected formation in a real-time distributed manner while avoiding obstacles.
A Novel Family of Parallel Mechanisms With Synchronous Telescopic Parallelograms

A novel synchronous telescopic parallelogram mechanism with movement realized by a belt drive is proposed, from which a compound kinematic limb is derived. According to the configuration derivation, a class of two-translation (2T), three-translation (3T) and three-translation-one-rotation (3T1R) parallel mechanisms is obtained by assembling the above kinematic limbs. Since the motion of these limbs in the parallelogram mechanism are dependent, screw theory is applied to illustrate the mobility of the obtained lower mobility parallel mechanisms. Moreover, through the simplified kinematic equations for these mechanisms, their position, velocity and singularity are analyzed and their workspaces are calculated. Finally, the prototype of the 2T parallel mechanism is manufactured and experimented to validate mobility and motion feasibility.
A Low Latency Clustering Method for Large-Scale Drone Swarms

Large-scale drone swarms are expected to play an important role in information acquisition, rescue search and joint fire strikes. These swarms usually adopt a clustering structure to control formation flight for fast and stable communication. Effective clustering can improve the transmission efficiency and task execution ability of the network. On the basis of uniform clustering, we establish a model with the number of unmanned aerial vehicles (UAVs) and the number of cluster heads (CHs) as variables to minimize the communication latency. Using conditional criteria, the communication delay is minimized to solve the relationship between the number of drones and the number of CHs, and this model is for clustering. A simulation platform is built with OPNET to evaluate the impact of different numbers of CHs on the network performance. According to the proposed scheme, the optimal number of CHs for 500, 300, 100 UAVs is 31, 24, 14, respectively. In the case of specific simulation parameters, these optimal numbers of CHs can achieve excellent performance in terms of delay and packet loss rate. This result has value in drone swarms clustering applications.
Secure Telemedicine System

Telemedicine (Telehealth) means the use of medical information that is exchanged from one site to another through electronic communication to improve patients’ health status. In 2016, the Department of Health and Human Services estimated that more than 60% of all health care institutions and 40 to 50% of all hospitals in the United States currently use some form of telemedicine. Recently, privacy and personal information have become a big issue again due to the enforcement of General Data Protection Regulation (GDPR) of EU, while healthcare/medical area is ranked the first with 34.5% for data leakage accidents according to the Identity Theft Resource Center of USA. One of the most important problems is that the information of telemedicine is mostly sensitive things related to the patients. Therefore, in this paper, we list security risks of telemedicine system and propose the secure telemedicine system STS with the countermeasures.
Plate-like Metal Oxide Nanostructure for Detection of Small Metabolites by Mass Spectrometry

Novel plate-like metal oxide nanostructure was demonstrated for analysis of small metabolites by laser desorption/ionization mass spectrometry (LDI MS). We prepared the nanoplates using hydrothermal method. Owing to the unique nanostructure and physicochemical properties, our method displayed high sensitivity and high accuracy towards the analysis of standard molecules and metabolites of serum samples. The nanomaterials also indicated great salt tolerance and protein endurance in complex biosamples in LDI MS. This work provided an innovative matrix for metabolic analysis and clinical diagnose in LDI MS.
FPowerTool: A Function-Level Power Profiling Tool

This paper presents the design and implementation of FPowerTool, a lightweight function-level profiling tool for measuring the energy consumption of program code. Based on the trace of energy usage and the timestamps of programs execution events, FPowerTool monitors and analyzes the power consumption of a program at runtime. Two issues have been addressed: associating the power consumption data with the individual function code segments and reducing the overhead of power profiling. FPowerTool adopts an approach which takes advantage of both sampling and dynamic instrumentation to address those issues. The energy consumed by code at the granularity of function is measured by sampling the energy usage hardware counters built in the CPU and the sampled value is associated to the corresponding code segments by offline analysis. Experiment results show that this approach significantly reduces the overhead of the program power profiling without significant interference to the timing of the original program execution.
Extraction of the 4H-SiC/SiO2 Barrier Height Over Temperature

The behavior of the barrier height of the SiC/SiO2 interface has been investigated over a wide temperature range, from 173 K to 523 K. These data complement the literature, providing a better knowledge of this parameter, which was studied only over a more restricted temperature range, and never before for low temperatures. It is highlighted that the measured samples exhibit a barrier height temperature dependence very near to the theoretical one (≈−0.7 meVK−1). Beyond 473 K, the barrier height seems to drop faster for some samples, reaching ≈−1.4 meVK−1. If this faster decreasing rate is maintained for higher temperatures, it could limit 4H-SiC MOSFETs performances or reliability for high-temperature applications. It is expected that the data provided here will allow for more accurate modeling of the gate current and the charge injection in the oxide layer of power MOSFETs, leading to more reliable predictions of the oxide lifetime for 4H-SiC MOSFETs.
An Overview of Atmospheric Correction for GB-SAR

Ground-based synthetic aperture radar (GB-SAR) has been developed rapidly in ground deformation measurement technology and its accuracy has been improved gradually. However, atmospheric effects greatly affect the accuracy of its deformation measurement. That how to effectively reduce the impact of the atmosphere on deformation measurement results has become an important research direction. This paper firstly introduces that how atmosphere affects the GB-SAR deformation measurement. Then, some common atmospheric correction methods, based on the physical characteristic of the atmosphere and the internal characteristics of radar images, are summarized. Further, we present some improved methods, which overcome shortcomings of common methods. Specifically, we hope that we can bring some new ideas for atmospheric correction. Finally, the application examples in the meteorological data correction and the permanent scatterer correction are presented.
Run-Time Safety Monitoring Framework for AI-Based Systems: Automated Driving Cases

Intelligent systems based on artificial intelligence techniques are increasing and are recently being accepted in the automotive domain. In the competition of automobile makers to provide fully automated vehicles, it is perceived that artificial intelligence will profoundly influence the automotive electric and electronic architecture in the future. However, while such systems provide highly advanced functions, safety risk increases as AI-based systems may produce uncertain output and behaviour. In this paper, we devise a run-time safety monitoring framework for AI-based intelligence systems focusing on autonomous driving functions. In detail, this paper describes (i) the characteristics of a safety monitoring framework; (ii) the safety monitoring framework itself, and (iii) we develop a prototype and implement the framework for two critical driving functions: Lane detection and object detection. Through an implementation of the framework to a prototypic control environment, we show the possibility of this framework in the real context. Finally, we discuss the techniques used in developing the safety monitoring framework and describes the encountered challenges.
Optimal Design of Subconnected Hybrid Structure for mmWave Massive MIMO Systems

Millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) systems typically employ hybrid beamforming architectures to reduce the number of radio-frequency (RF) chains, thereby the cost and power consumption is decreased. Compared with fully connected architectures, subconnected architectures provide greater energy efficiency in general. In this paper, we devote to find the optimal subconnected hybrid structure. We first proposed a novel model to describe the connections between antennas and RF chains, based on which the optimal problem is formulated and solved by considering the channel characteristics. Meanwhile, the factors affecting the spectral efficiency of diverse subconnected hybrid structures are analysed. Simulation results show that the spectral efficiency is related to the inter antenna spacing. When the inter antenna spacing equals half wavelength, the optimal interleaved scheme is given in closed form.
A Novel Control Method to Improve Current Regulation and Harmonics in Navigation Dimming Power Supply

Regulating the output current and reducing the harmonic distortion are key control problems in the airport navigation dimming power supply (DPS). In this study, a new method which could dynamically adjust P and I gains is presented for the DPS based on the radial basis function (RBF) neural networks combined with the gradient descent method. To implement the proposed method, the key factors which influence the performance of DPS are revealed by analyzing the dynamic response of the control system. The controller design process is presented in detail along with a system stability analysis. The correctness of theoretical derivation is examined through extensive digital computer simulation analyses in MATLAB while the comparative analysis is carried out under different operation conditions through experiments in a 30kW experimental prototype. The results indicate that the DPS adopting the method proposed in this paper could obtain better dynamic response and less harmonic content in various complex working conditions.
Oblique Projection Polarization Filter-Based Self-Interference Cancellation Scheme in In-Band Full-Duplex Systems

In this paper, a self-interference cancellation scheme is designed by the oblique projection polarization filter (OPPF) in an in-band full-duplex (IBFD) system. We apply two different polarization states (PSs) for the transmitter and receiver by the virtual polarization (VP) technique, which can be generated by orthogonal dual-polarization antennas (ODPAs). The local receiver implements the OPPF to cancel the local transmitter's strong co-frequency interference. In addition, depolarization is considered, and a pre-compensation method is designed to mitigate the in fluence of the depolarization. Finally, simulation results by the performance of OPPF are given to prove the effectiveness of the proposed methods and show the key parameters.
MBS Price Decision and Internal Relationship with CPR

As one of the earliest products of asset securitization, MBS has played an important role in promoting the development of the subsequent financial derivatives. The determination of its price is influenced by several economic factors such as market interest rates and trading frequencies. Thus, our study accurately discusses the calculation the MBS price with multiple steps. Furthermore, we analyze the internal relationship between CPR and MBS price through Newton method. The results show that the movement trends CPR and MBS price are probably in the opposite directions, which is quite consistent with the realistic economy.
Dynamic Scenario Adaption for Simulation Training

Human behavior models support simulation-based training, experimentation, and mission rehearsal. However, these models are often brittle when used outside of their original development context, resulting in diminished effectiveness of simulation. This paper describes the Scenario Director, a software component developed for an operational simulation system, that enables scenario designers and operators to use pre-existing behavior models in new and different usage contexts than the ones anticipated when the models were developed. The Scenario Director leverages methods and algorithms from intelligent tutoring systems, supervisory control, and computational cognitive modeling. The paper outlines the motivations and requirements for scenario adaptation, overviews the solution, and outlines multiple evaluations of the technology. The Scenario Director is now integrated in a deployed simulation system and is being used to deliver operational training.