Miracle-dz/UniFAR-FTUs huggingface dataset:
Steering Feel Design for Steer-by-Wire System on Electric Vehicles

In this paper, the problem of hand-wheel force feedback to obtain the tire-to-ground contact information for steer-by-wire (SBW) system is studied. The torque generated by the upper motor is composed of road-to-tire contact torque, known as self-aligning torque (SAT), returnability torque and inherent system torque. The terminal sliding mode control (TSMC) is designed to guarantee the hand-wheel angle converges to the reference angle in finite time when the vehicle is static. Furthermore, a steering feel model including damping, inertia and SAT are proposed to model the actual lower part feedback force while the vehicle is under verified road condition. Simulation results verify the effectiveness and good performance of the proposed method.
Novel Microfluidic Perfusion Bioreactor for Vascularized Organ-on-a-Chip

By combining advanced microfluidic techniques, the perfusion-based bioreactor plays a critical role in 3D cell/tissue culture, especially for the construction of organ-on-a-chip models. This paper reports a novel microfluidic perfusion bioreactor design by separating microfluidic channels and tissue culture chambers into two separate layers, which can be applied to different applications by designing arbitrary structure with versatile flow profiles. As a proof of concept we have created a novel bioreactor design with more uniform line-to-line flow profiles and higher interstitial flow velocity compared to the conventional communication pore design with point-to-point flow profiles on the same layer. In addition, the microfluidic channel design perpendicular to the gel loading direction was implemented to realize either independent or interconnected horizontal flow pattern rather than the vertical one appeared in most conventional designs. The effectiveness of this novel bioreactor design is validated by using an in vitro vascularized organ-on-a-chip model.
Integration of SMT-based Scheduling with RC Network Calculus Analysis in TTEthernet Networks

In mixed-criticality Ethernet-based time-triggered networks, like TTEthernet, time-triggered communication (TT) coexists with rate-constrained (RC) and best-effort (BE) traffic. A global communication scheme, i.e., a schedule, establishes contention-free transmission times for TT flows ensuring guaranteed low latency and minimal jitter. Current approaches use Satisfiability Modulo Theories (SMT) to formulate the scheduling constraints and solve the resulting problem. However, these approaches do not take into consideration the impact of the TT schedule on RC traffic. Hence, the resulting TT schedule may cause the worst-case latency requirements of RC traffic not to be fulfilled anymore.In this paper, we present a novel method for including an RC analysis in state-of-the-art SMT-based schedule synthesis algorithms via a feedback loop in order to maintain the optimality properties of the SMT-based approaches while also being able to improve the RC traffic delays. Our method is designed in such a way that it can be readily integrated into existing SMT- or MiP-based solutions. We evaluate our approach using variants derived from a realistic use-case and present methods to further improve the efficiency of our feedback-based approach.
Experimental observation of Arnold tongues in the analysis of the signal from contour of the autonomous regulation of heart rate and respiration

We proposed a method of experimental observation of the Arnold tongues in the study of the synchronization of the contours of autonomic regulation of the heart rate with a characteristic frequency of about 0.1 Hz and respiration. The formulation of a special active experiment made it possible to determine the boundaries of synchronization tongues in 3 subjects. The method allows noninvasive research. The basic idea is to influence the contours of heart rate regulation with a respiratory signal, which has respiratory frequency varying linearly about 0.1 Hz according to the sound signal generated by a special device. The amplitude of the breath is changed by the subjects at the command of the researcher. The study is important for understanding the features of complex multichannel systems of biological nature and their mathematical modeling.
Current Sharing Approach for DC Microgird Based on Superimposed Frequency Droop Control

Accurate current sharing between micro-sources is an important control objective in DC microgrid. The traditional droop control based on virtual resistance is difficult to meet the requirements of sharing accuracy and stability at the same time because of the differential line impedances and low-speed communication. A new current sharing approach for paralleled micro-sources based on superimposed frequency droop control is proposed in this paper. A small ac voltage with low frequency and low amplitude is superimposed onto the output dc voltage of each converter. Therefore, dc converters can be coordinated together with the frequency of the small ac voltage, without any communication. Utilizing the droop characteristic between superimposed frequency and output DC current, reactive circulating power would be generated between converters and then be used to regulate the output DC voltage of each converter. Then, the accurate current sharing can be achieved. On this basis, a reactive power limiter is proposed to compensate the voltage drop, so as to make the bus voltage operating within the specified range. Small signal analysis is used to verify the system stability and select proper parameters. Finally, the feasibility and effectiveness of the proposed control strategy are validated by the results obtained from simulations.
Modeling and analysis of cascading failures considering risk awareness

Cascading failures triggered by a node failure in networks are common phenomena, and the failure of nodes will cause the panic in other nodes as the rumor and information spread in the network. In this paper, a new cascading failures model considering risk awareness is proposed, where the panic brought by the warning is expressed as disturbance of noise. We find that the risk awareness aggravates the cascading failures, and the risk awareness increases the critical threshold. However, as the heterogeneity of loads redistribution enhances, the impact of risk awareness is not evident. With the help of simulations and theoretical analysis, the proposed model has been verified.
Multi-strategy based exploration for 3D mapping in unknown environments using a mobile robot

In this paper, a multi-strategy based exploration approach is proposed, enabling a mobile robot to autonomously explore unknown environments and construct 3D maps of the world. The approach combines information-gain based local exploration strategy and global exploration strategy. Firstly, the information-gain based decision model for exploration is formulated and an information gain calculation method which can be applied to evaluate the utility of exploration trajectory over multiple time steps is designed. Then a model-predictive based trajectory generation method is used to generate a set of candidate trajectories for local exploration. The best local exploration trajectory is obtained based on the information-gain evaluation criterion. When this strategy gets to a local minima, a complementary global strategy is executed. Specifically, a set of viewpoints that map to sightings of frontier regions is generated. Then a graph search method is used to search exploration path to the candidate viewpoints. The best global exploration path is also obtained based on the information-gain evaluation criterion. Finally, real-world experiment is conducted to accomplish the exploration and 3D mapping task on a mobile robot in indoor unknown environments. Experimental results show that the proposed multi-strategy based exploration method performs fast exploration in 3D unknown environment, meanwhile, it ensures the completeness of the obtained map.
Bipolar Micro Electret Power Generator

Inspired by electromagnetic hydropower station that contains reverse polarized magnet, this paper reports a novel micro electrostatic rotary energy harvester (e-REH) that integrates both positive and negative charged electrets into single rotational energy conversion system. It is the first time successfully demonstrating the feasibility and viability of micro-patterning bipolar charge into single electret sheet for boosting rotary energy harvesting effectiveness. Selectively localized corona charging method with rotational shadow mask is invented to pattern the predefined area with microscale opposite types of charges. With the fabricated prototype, the experimental results show the superior performance of the proposed bipolar e-REH: the output voltage increases over 200% compared to the positive alone and negative alone configurations.
The Industrie 4.0 Asset Administration Shell as Information Source for Security Analysis

One of the essential concepts of the Reference Architecture Model Industrie 4.0 (RAMI4.0) is the uniform modelling of assets by means of a common meta-data model called the Asset Administration Shell (AAS). However, important practical experience with this concept is still missing, as not many use cases for the AAS have yet been implemented. Thus, practical issues within the AAS concept and respective solutions are hard to identify. In this paper, presents our experience with the implementation of an AAS use case. The AAS is used as information source to create an ontology, which is then used for security analysis. The paper discusses the use-case-specific modelling language selection and provides a practical examination of several of our implementations that use OWL and OPC UA together. Furthermore, it provides recommendations for the implementation of Asset Administration Shells for this and similar use cases.
Enhanced Low-Complexity Matrix Inversion Method for Massive MIMO Systems

Massive multiuser multi-input-multi-output (MU-MIMO) is a key enabling technology for increasing the spectral efficiency in wireless communication networks. Due to the fact that green communication, low power and hardware costs are key demands for network operators this paper aims at solving efficiently the problem of low complexity matrix inversion for downlink precoding. Unlike different variants of approximate matrix inversion methods presented in literature that minimize the approximation error to the exact inversion case, it is proposed here to find the approximation maximizing the resulting achieved signal to interference noise ratio (SINR) assuming zero-forcing precoding (ZF). Simulation results show that the proposed precoding method is more efficient in terms of the achieved sum rate, yet with comparable computational complexity to other methods in literature. The performance gain is more significant especially for the case of high system loading and/or high correlation which both are considered inevitable in future wireless systems.
The Exploration of Silicon Nanowires as a Stationary Phase Support for Micro Gas Chromatographic Columns

In this paper, silicon nanowires were innovatively used as a stationary phase support for micro-fabricated gas chromatographic column ($\mu \mathrm{GC}$ colunm). The silicon nanowires were grown in-situ in the high aspect ratio microchannels of the $\mu \mathrm{GC}$ colunm, and polydimethylsiloxane (OV-101) was used as the stationary phase. It was demonstrated that the alkane mixture of C6-C10 was well separated by using the $2\ \mathrm{m}\ \mu \mathrm{GC}$ colunm. The separation efficiency of the $\mu \mathrm{GC}$ colunm was as high as 23647 plates/m, which could be attributed to the large surface area of the silicon nanowires.
Interlaboratory Comparison of Radiated Immunity in Automotive EMC

Interlaboratory comparisons are performed for two reasons: to ensure repeatability of testing amongst EMC laboratories worldwide concerning specific test methods and for evaluating the testing capabilities of these laboratories. The purpose of this paper is to present application of an interlaboratory comparison method for radiated immunity (RI) testing involving 4 laboratories. An E-field probe is used as a Sample, which is moved from one laboratory to another in order to obtain the raw data for the final assessment. The statistical analysis based on the z performance criterion is applied.
A Submap per Perspective - Selecting Subsets for SuPer Mapping that Afford Superior Localization Quality

This paper targets high-precision robot localization. We address a general problem for voxel-based map representations that the expressiveness of the map is fundamentally limited by the resolution since integration of measurements taken from different perspectives introduces imprecisions, and thus reduces localization accuracy. We propose SuPer maps that contain one Submap per Perspective representing a particular view of the environment. For localization, a robot then selects the submap that best explains the environment from its perspective. Our methods serves as an offline refinement step between initial SLAM and deploying autonomous robots for navigation. We evaluate the proposed method on simulated and real-world data that represent an important use case of an industrial scenario with high accuracy requirements in an repetitive environment. Our results demonstrate a significantly improved localization accuracy, up to 46% better compared to localization in global maps, and up to 25% better compared to alternative submapping approaches.
Composite fault detection and diagnosis for IGBT and current sensor in CRH2 through modified EEMD and KPCA methods

This study proposes a diagnosis method for IGBT open circuit fault and sensor drift fault in CRH2 through ensemble empirical mode decomposition (EEMD) and an improved kernel principal component analysis (KPCA) way. EEMD is modified to reduce noise in the current and voltage signals. Subsequently, an improved KPCA method using weight matrix to highlighting fault information is developed to detect and diagnose the composite fault. Then the three-phase current averaging method is applied to perform fault location. Numerical simulation results verify the validity and availability of the composite fault detection method.
Simulation Investigation of S/Ku dual-band magnetically insulated line Oscillator

A dual-band Magnetically insulated line oscillator (MILO) generating RF in S-band and Ku-band has been presented. The standard device design methodology has been followed for design and validated through simulation. The dispersion diagram for both S-band and Ku -band calculated through EIGEN mode simulation. For the PIC simulation of the device, typically selected beam parameters: diode voltage of 610 kV and diode current of 58 kA, generates the RF of 3.1 GW at frequency 14.1 GHz and RF of 1.2 GW at frequency 2.1 GHz. The overall efficiency of ~12.1 % has been achieved through the device with frequency difference of 8.4 dB.
AEx: Automated Customization of Exposed Datapath Soft-Cores

High-level synthesis tools aim to produce hardware designs out of software descriptions with a goal to lower the bar in FPGA usage for software engineers. Despite their recent progress, however, HLS tools still require FPGA target specific pragmas and other modifications to the originally processor-targeting source code descriptions. Customized soft core based overlay architectures provide a software programmable layer on top of the FPGA fabric. The benefit of this approach is that a platform independent compiler target is presented to the programs, which lowers the porting burden, and online repurposing the same configuration is natural by just switching the executed program. The main drawback, like with any overlay architecture, are the additional implementation overheads the overlay imposes to the resource consumption and the maximum operating frequency. In this paper we show how by utilizing the efficient structure of Transport-Triggered Architectures (TTA), soft-cores can be customized automatically to benefit from the flexible FPGA fabric while still presenting a comfortable software layer to the users. The results compared to previously published non-specialized TTA soft cores indicate equal or better execution times, while the program image size is reduced by up to 49%, and overall resource utilization improved from 10% to 60%.
Modeling and Nonlinear Coordination Control of a Dual Drones Lifting System

In recent years, it has become increasingly popular to lift relief supplies by using drones. Restricted by the material technology and the power system, the lifting capacity of a single drone is not enough for some specific tasks. Therefore, the lifting capacity will be improved by utilizing the dual drones cooperative lifting system, and the attitude of the load can be fully considered. However, this cooperative lifting system has not received sufficient attention, and most results of relevant research have remained at the theoretical stage. This paper uses the Lagrange modeling method to establish an accurate model for the whole dual drones lifting system. On this basis, it uses Lyapunov techniques and LaSalle’s invariance theorem to ensure the stability of the equilibrium point. Finally, the feasibility and the effectiveness of the proposed method are guaranteed by software simulation experiments.
A Comprehensive Review of Flux Barriers in Interior Permanent Magnet Synchronous Machines

Interior permanent magnet synchronous machines (IPMSMs) are commonly utilized in many applications where high-torque density and low torque ripple are required. Flux barriers inside the rotor have a great impact on the electromagnetic performance and thus considered as an effective design parameter. This paper provides a comprehensive review of the function and design methodologies of flux barriers in IPMSMs. Both symmetric and asymmetric flux barriers that improve the torque capability and decrease torque ripples are discussed. The paper also investigates different flux barrier designs to reduce the stator and rotor iron losses to enhance the motor efficiency. The optimization of the shape of the flux barriers to mitigate irreversible demagnetization of the rotor magnets is also presented. It is concluded that a good design of flux barriers can significantly improve the motor’s electromagnetic performance while reducing the manufacturing costs.
Therapeutics of Alzheimer’s Disease

Alzheimer’s disease (AD) is the most common age-related neurodegenerative disorder, its prevalence is increasing along with population longevity and there is no cure for this disease so far, despite of the amount of information research has provided. This leads us to seek for better treatments able to improve the patient’s and caregivers’ quality of life. In this chapter we will review some of the main aspects of those proteins playing a key role in the pathological processes of Alzheimer’s disease, as well as the therapeutic strategies currently in use and those that have been developing in the last few years for the treatment of this disease. We will take a look on the processes of formation of the characteristic lesions of the Alzheimer’s brain and sum up some of the properties of the main proteins involved in such processes leading to neuronal damage and death and the resulting cognitive decline. We will also have an overview of the current drugs of choice for Alzheimer’s treatment and discuss about the latest therapies research has been developing to treat AD in its different stages, such as a therapy of our own proposal for the repair of neuronal membranes prior to initiate a conventional drug treatment and the advantages these strategies would provide combined on patients with a mild to moderate neuronal damage. At last we will focus on the importance of an integral care of Alzheimer’s patients.
Deep Recurrent Electricity Theft Detection in AMI Networks with Evolutionary Hyper-Parameter Tuning

Despite its prominent role in future smart power grid for monitoring and billing purposes, advanced metering infrastructure (AMI) opens the door wide for serious cyber-security threats. This paper investigates an electricity theft cyber-attack scenario where malicious customers hack their smart meters and manipulate the energy consumption readings in order to reduce their electricity bills. In this context, machine learning techniques offer an attractive means to efficiently detect such cyber-attacks. The contributions of this work are two-fold: 1) Unlike the existing works that rely on shallow and static machine learning techniques, we propose a detection mechanism based on deep recurrent neural networks that exploit the time-series nature of the energy consumption readings to improve the detection performance, and 2) While the existing works did not consider fine-tuning of the detector's hyper-parameters, we employ a multi-objective evolutionary (Non-dominated Sorting Genetic Algorithm)-based optimization approach to fine-tune the detector's hyper-parameters to further improve the detection performance. Real energy consumption data is utilized to test the proposed detection mechanism, which demonstrates a superior detection performance compared with a state-of-the-art (static and shallow) detector.
Optimal Blood Glucose Prediction based on Intermittent Data from Wearable Glucose Monitoring Sensors

Blood glucose prediction is to predict the glucose trend over time based on historical glucose data, and it plays a crucial role in the closed-loop control of artificial pancreas, which can reduce the risk of complications by regulating insulin dose and injection time. This paper proposes a Kalman-filter-based glucose prediction method through minimizing the mean square prediction error, which assumes that the data is sampled every 15 min from a wearable flash glucose monitoring sensor. This method calculates glucose estimates every 5 min and provides glucose predictions for the next 30 min. The method is evaluated on in-silico data generated from the 10-adult cohort of the US FDA-accepted UVA/Padova T1DM simulator. The predicted results are compared with CGM data with 5-min sample-period through multiple metrics, including the mean square prediction error and the mean absolute relative deviation. The results show that the performance of the proposed approach with slow-rate glucose data (15 min) is close to that obtained based on fast-rate data (5 min).
Single-Sideband Hybrid Opto-Electronic Oscillator

Opto-electronic oscillators (OEO) are important building blocks in microwave photonics systems, allowing to obtain low-phase noise optically-carried radiofrequency signals. We have recently demonstrated an OEO scheme based on a monolithic dual-frequency source [1], whose beatnote is self-stabilized using frequency-shifted optical feedback, and a delay line [2]. The main interest of such a setup is that it allows the generation of single-sideband signals, which are thus insensitive to dispersion fading when propagating in optical fibers. The scheme presented in [2] offered good short-term performances. However, it could be affected by mode-hopping due to both the resonant modes of the optical feedback loop, and to those of the optoelectronic loop including the delay line. In the present work, we present significant improvements, namely the complete suppression of mode-hopping, and a significant reduction of the spurs in the phase noise spectrum. This has been obtained by (i) the introduction of a RF interferometer thanks to the use of two delay lines, and (ii) a significant shortening of the optical feedback loop (see Fig. 1(a)) [3].