Miracle-dz/UniFAR-FTUs huggingface dataset:
Energy-efficient trajectory planning for high-speed trains via an mixed integer linear programming approach

This paper proposes an energy-efficient trajectory planning approach for high speed trains to reduce the traction energy consumption. Firstly, an optimization model is developed by defining the objective function as a weighted sum of the traction energy consumption and passengers’ riding comfort. Besides the constraints in the classic optimal train control problem (such as the trip time, running resistance, speed limit, and the train characteristics), the discrete throttles, split phase zone, and the sectionalized tunnel resistance are introduced in this paper. Then, all the nonlinear constraints are approximated through the piecewise affine function and the energy-efficient trajectory planning problem is turned into an mixed integer linear programming (MILP) problem. The MILP problem can be solved by existing solvers CPLEX and YALMIP. Finally, some cases are conducted to illustrate the effectiveness of the proposed approach. The result shows that the traction energy consumption is increased by 4.5% when the ridding comfort is taken into consideration.
Converter-fed Induction Motor Efficiency Measurement under Variable Frequency/Load Points: An Extension of the IEC/TS 60034-2-3

As Variable Frequency Drives (VFDs) continue to dominate industrial process control, there is a need for stakeholders to quantify the converter-fed motor losses over a wide range of operating frequency and loading conditions. Although there is an increase in legislative activities, particularly in Europe, towards the classification and improvement of energy efficiency in electric drive systems, the handful of available standards for quantifying the harmonic losses are still undergoing validation. With regards to the IEC/TS 60034-2-3, which has been lauded as a step in the right direction, its limitation to rated motor frequency has been identified as one of its main weaknesses. Therefore, this study demonstrates how the IEC/TS 60034-2-3 methodology at norminal frequency can be extended over the constant-torque region of an induction motor (IM). The results presented in this paper provide good feedback to the relevant IEC standards committee as well as guidance to stakeholders.
Theory of 3-D Superjunction MOSFET

The state-of-the-art superjunction (SJ) MOSFETs are based on the p-n pillar structures, arranged in a 2-D stripe geometry. This arrangement uses the superposition of the electric field components at the p-n junctions to create an enhanced depletion volume for higher breakdown capability. In this article, we will discuss structures, which additionally use the component of the electric field in the third dimension, to further enhance the depletion space. This allows higher doping concentrations in the pillars, which result in a better tradeoff between the breakdown voltage and the ON-state resistance, when compared with the 2-D structures. Specifically, we present a core–shell cylindrical SJ structure, and using the radial Poisson equation, we explain the electric field distribution within the SJ. We further discuss which geometry (core or shell) gives the best performance tradeoff. This is followed by the development of an analytical model, for the ON-state resistance in a 3-D SJ. Finally, we derive a specific figure of merit for the 3-D SJs and compare it with that of the equivalent 2-D structures.
A System for Image-Based Non-Line-Of-Sight Detection Using Convolutional Neural Networks

The ERSAT GGC project introduces the concept of virtual balises for train localization, which avoids investment and maintenance costs of physical balises. Since this concept relies on the matching of train positions to balise positions stored in a database, it is dependent on placing virtual balises in track areas with unimpeded GNSS reception. One factor majorly contributing to the distortion of GNSS signals is the non-line-of-sight (NLOS) scenario where the direct path between a satellite and the receiver on the train is blocked. As these NLOS situations result in deflections or the total absence of GNSS signals, this paper proposes a system to identify obstacles occluding the visibility of satellites above the tracks traversed by a train. This is achieved by video recording the sky from the roof of the train and segmenting the images into sky and non-sky regions. The line-of-sight status of individual satellites is found through projecting the known satellite locations into the segmented images. Consequently, the information whether a satellite is located in a sky or non-sky segment of the image allows for a determination of the GNSS performance at any observed track area.
Can a Single Model Deep Learning Approach Enhance Classification Accuracy of an EEG-based Brain-Computer Interface?

Convolutional Neural Network (CNN) has outperformed many traditional linear and polynomial classifiers in various domains. CNN and other deep learning methods have gained attention in the Brain-Computer Interface (BCI) domain also. Here, we investigate a CNN-based model with two different optimizers for reducing error of classification of brain states using EEG motor imagery data. Two different optimizers namely stochastic gradient descent (SGD) and adaptive momentum (Adam) are investigated for increasing classification accuracy using the well-known BCI competition IV 2b dataset. The study was conducted to investigate the feasibility of a single deep learning model for all subjects without compromising on information decoding rate for any of the BCI participants. Using two different models, mean cross-validation accuracy of 80.32% (±2.2) was achieved across participants, which is significantly higher (p<0.05) compared to a state-of-the-art deep learning approach.
MRI detected prevalence of abnormalities in patients of knee pain

Background: In patients of knee pain diagnosis has utmost important for treatment and to avoid unnecessary surgery. MRI is a non-invasive procedure in evaluation of knee joint. So this study was planned find out the prevalence of abnormalities detected by MRI in patients of knee pain. Methods: Fifty patient of knee pain were examined after taking permission from institutional ethics committee by using Siemens Avanto MR machine with a superconducting magnet and field strength of 1.5 tesla using dedicated knee coil (Flex), which were referred from department of Orthopedics & Rheumatology. Results: In this present study 72% patients were males and 28% patients females and their ages ranging from (11-80) years. Knee pain was found common in age group 31-40 years. Menisci lesions (44%) were more common as compared to ligament lesions (14%) in patients of knee pain. Osteoarthritis was found in 40 % of patients of knee pain. Joint effusion and marrow edema was found with incidence of 74% and 62% respectively. 4% patients were suffering from intraarticular tumors. Conclusions: Knee pain can occur at any stage of life due to various causative factors. MRI can demonstrate the exact nature and extent of bony as well as soft tissue abnormality. This has increase the use of MRI in evaluation of patients of knee pain.
Two Selective Harmonic Control Techniques Applied in 10kV Grid with Three-Level NPC Inverter

In high-power applications, bulky and expensive filtering elements or systems are commonly used, since the commutation of high-voltage and high-current rated semiconductors will impact the thermal losses of power systems, which will further lead to distorted output waveforms. In the meantime, due to the non-uniform regulations in the area of power quality and more new and strict grid codes, the harmonic control of power converters' output signal is becoming greatly important. By taking this situation into account, comparisons between selective harmonic elimination pulse width modulation (SHEPWM) and selective harmonic mitigation pulse width modulation (SHMPWM) techniques are proposed in this paper, based on the requirements of two well-known grid codes EN 50160 and CIGRE WG 36–05. In the presented simulation model, a switching frequency that is equal to 750 Hz is considered, and the harmonics up to the 49th are considered and the total harmonic distortion (THD) obtained considering up to the 40th and 50th. The obtained results show that, under the same switching frequency condition, only the SHMPWM technique can satisfy the requirements of the above-mentioned two grid codes, compared with the SHEPWM technique. This fact implies that the SHMPWM technique is more suitable for high-power applications, especially for reducing or removing the additional filtering elements or systems.
Breakdown Enhancement and Current Collapse Suppression in AlGaN/GaN HEMT by NiOX/SiNX and Al2O3/SiNX as Gate Dielectric Layer and Passivation Layer

We propose two kinds of stacked materials that effectively yield low drain off-state leakage current, high off-state breakdown voltage and low current collapse simultaneously in AlGaN/GaN HEMT. The two kinds of stacked materials, which is NiO<sub>X</sub>/SiN<sub>X</sub> and Al<sub>2</sub>O<sub>3</sub>/SiN<sub>X</sub> respectively, act as gate dielectric layer and passivation layer for the devices. The NiO<sub>X</sub> and Al<sub>2</sub>O<sub>3</sub> are prepared through depositing Ni and Al thin film by electron beam evaporation and then annealing in O<sub>2</sub> ambient by rapid thermal processing. The SiN<sub>X</sub> is deposited by plasma-enhanced chemical vapor deposition. Compared to the single SiN<sub>X</sub> layer, the NiO<sub>X</sub>/SiN<sub>X</sub> stack layer and Al<sub>2</sub>O<sub>3</sub>/SiN<sub>X</sub> stack layer can distinctly reduce the drain off-state leakage current of devices. Meanwhile, high off-state breakdown voltage is also achieved. The off-state breakdown voltage in the devices with NiO<sub>X</sub>/SiN<sub>X</sub> stack layer and Al<sub>2</sub>O<sub>3</sub>/SiN<sub>X</sub> stack layer are 52% and 36% higher than that of the devices with single SiN<sub>X</sub> layer respectively. Especially, the current collapse under 200 V stress bias is reduced by 90% and 58% in the devices with NiO<sub>X</sub>/SiN<sub>X</sub> stack layer and Al<sub>2</sub>O<sub>3</sub>/SiN<sub>X</sub> stack layer compare to the devices with single SiN<sub>X</sub> layer respectively.
Development and Hybrid Control of an Electrically Actuated Lower Limb Exoskeleton for Motion Assistance

This paper describes a system design and hybrid control algorithm of an electrically actuated lower limb exoskeleton (LLE). The system design mainly includes three parts: mechanical structure design, actuation system design and sensor system design. According to the initial state of the joint angle, LLE can be divided into Non-anthropomorphic state (NAS) and anthropomorphic state (AS). The human motion intention (HMI) estimation can be divided into gait phase classification and reference trajectory estimation. The fuzzy logic is used to detect different phases in the gait phase classification. In the reference trajectory estimation, the kinematic model of the LLE is utilized to obtain a continuous joint trajectory, which is used as input of the control law. To make the LLE accurately follow the movement of people and remain stable, a hybrid dual-mode control strategy is proposed in this paper, i.e., the adaptive impedance control (AIC) method is used to improve the stability and resistance to shock in stance phase, and the active disturbance rejection control with the fast terminal sliding mode control (ADRC-FTSMC) method is employed to improve the response speed and the tracking precision in swing phase. Furthermore, in order to solve the torque discontinuity in the switching process, a smoothing method is proposed during the transition. Finally, the prototype experiments were set up to verify the tracking performance and power-assisted effect of the proposed exoskeleton. The experiments results show the LLE can achieve excellent tracking performance and power-assisted effect based on the proposed HMI methodology and hybrid dual-mode control strategy.
A Single-Phase dc-ac Dual-Active-Bridge Based Resonant Converter For Grid-Connected Photovoltaic (PV) Applications

This paper presents the topology, modelling and control strategy for a single-phase grid-connected converter for photovoltaic (PV) applications based on the series-resonant dual active bridge (DAB). A state-space large-signal model is derived for phase-shift based modulations, and a linearized model is presented for control design. A multi-loop control strategy is presented where a current-control loop regulates the current that the converter injects in-phase with the grid voltage, while a slower loop regulates the PV array voltage for MPPT. To verify the model and control strategy, simulation and experimental results are presented
An Automated Text Mining Approach for Classifying Mental-Ill Health Incidents from Police Incident Logs for Data-Driven Intelligence

Data-driven intelligence can play a pivotal role in enhancing the effectiveness and efficiency of police service provision. Despite of police organizations being a rich source of qualitative data (present in less formally structured formats, such as the text logs), little work has been done in automating steps to allow this data to feed into intelligence-led policing tasks, such as demand analysis/prediction. This paper examines the use of police incident logs to better estimate the demand of officers across all incidents, with particular respect to the cases where mental-ill health played a primary part. Persons suffering from mental-ill health are significantly more likely to come into contact with the police, but statistics relating to how much actual police time is spent dealing with this type of incident are highly variable and often subjective. We present a novel deep learning based text mining approach, which allows accurate extraction of mental-ill health related incidents from police incident logs. The data gained from these automated analyses can enable both strategic and operational planning within police forces, allowing policy makers to develop long term strategies to tackle this issue, and to better plan for day-today demand on services. The proposed model has demonstrated the cross-validated classification accuracy of 89.5% on the real dataset.
Small Signal Dynamic Model and Stability Analysis of a Self-Synchronizing Grid-Tied Current Regulated Inverter

Self-synchronising grid-tied inverters use the internal dynamic states of their current regulator to estimate the voltage at the point-of-common-coupling (PCC), and then synchronise to this voltage estimate using a phase-locked-loop (PLL). This approach offers several benefits including a reduction in the required sensor count and improved harmonic attenuation. However, a self-synchronising control system is non-linear because the current regulator and PLL interact dynamically, which makes the analysis of the controller stability and sensitivity more difficult to quantify. This paper presents a linearized small signal model for a self-synchronising inverter that fully accounts for the current regulator and PLL dynamic interactions. This allows the stability of the inverter control loop to be assessed across a wide range of operating conditions. The model has been validated using detailed switched simulations of a three-phase grid-tied inverter, and tests conducted on a matching experimental inverter.
Spatial Analysis of Taxi Speeding Event Using GPS Trajectory Data *

GPS-equipped taxis can generate large-scale trajectory data which enables scholars to uncover taxi abnormal behaviors, such as speeding. Hence, this study intends to disclose the characteristics of taxi speeding event (SE), identify the spatial factors impacting the frequency of taxi SE, using 5,757 taxis’ GPS trajectory data in a part of the central area of Chengdu city from November 1 to November 30, 2016, along with speed limit data, electronic map data, etc. By comparing the calculated travel speeds with speed limits, taxi SEs were identified and categorized into five groups: SE (<10%), SE (10-20%), SE (20-50%), SE (50-70%), and SE (≥70%). Firstly, spatial autocorrelations of five types of taxi SE were verified by employing global and local Moran’s I, respectively. Secondly, a spatial error model was developed to investigate the influences of spatial factors on the frequency of five types of taxi SE. The results showed that there existed a global and local spatial autocorrelation and hotspots for five types of taxi SE in the metropolis. The number, length of roads and average speed limit within a grid significantly impact the frequency of various taxi SEs. The findings of this study and corresponding implications were further discussed.
Molecular Diagnosis of Mycoplasma pneumoniae in Synovial Fluid of Rheumatoid Arthritis Patients

1. Department of Medical Microbiology, Faculty of Medicine, Baqiyatallah University of Medical Sciences, Tehran, Iran. 2. Health Research Center, Baqiyatallah University of Medical Sciences, Tehran, Iran. 3. Department of Rheumatology, Faculty of Medicine, Baqiyatallah University of Medical Sciences, Tehran, Iran. 4. Molecular Biology Research Center, Baqiyatallah University of Medical Sciences, Tehran, Iran. 5. Applied Virological Research, Faculty of Medicine, Baqiyatallah University of Medical Sciences, Tehran, Iran.
Performance Study of LoRaWAN for Smart-City Applications

One of the verticals that will be more benefited with the arrival of upcoming 5G deployments are smart-cities. Under this umbrella, different applications for end-users will be developed in two principal scenarios in the city, namely, under mobility conditions or in static situations. In order to provide ubiquitous connectivity in these scenarios, the Low Power-Wide Area Network (LP-WAN) technologies have emerged, hence enabling the development of novel Internet of Things (IoT) services. In this line, LoRaWAN is one of the most prominent LP-WAN alternatives that is considered to be integrated within the 5G ecosystem. In this work, we focus on evaluating the performance of this technology under different working conditions. A comparison between two commercial LoRaWAN gateways is presented and the attained results in both deployments are compared and discussed. The outcomes place LoRaWAN as an outstanding solution to be adopted in smart-city deployments for supporting certain IoT applications.
Topical Androgen Treatment for ACNE a Review

Acne results from the increased production of sebum and the accumulation of sebum in the sebaceous duct. Androgens have a direct influence on this condition as they stimulate both the formation of sebum and the hyperkeratinisation of the upper part of the duct which leads eventually to its obstruction. Clinical tests have demonstrated that most acne patients do not have an increased level of androgen in the blood. They do, however, show an increased conversion of testosterone to 5-alpha-dihy-drotestosterone (5-alpha-DHT) in the skin. This latter hormone is responsible for the stimulation of the sebaceous gland. The enzymic conversion of testosterone to 5-alpha-DHT can be inhibited by progesterone. Progesterone, when applied topically in an alcohol/water solution, is 80 percent metabolized in the skin and is not converted into androgens in the body. It may therefore be expected that the topical application of progesterone will not give rise to side effects in either men or women. Preliminary trials are in agreement with this expectation. Extensive clinical investigations of an alcohol/ water solution of progesterone are therefore recommended, as this may be the first clinically useful, locally active, antiandrogen to be effective in the treatment of acne.
Effect of OFF-State Stress on Gate-Induced Drain Leakage by Interface Traps in Buried-Gate FETs

The gate-induced drain leakage (GIDL) current is one of the major leakage sources in a dynamic random-access memory (DRAM) cell transistor. In addition to band-to-band tunneling (BTBT), which causes GIDL in the gate-to-drain overlap region, the generation of interface traps in the gate dielectric increases the GIDL current by trap-assisted two-step tunneling (TATT). In this article, the influence of OFF-state stress on the generation of the interface traps, which deteriorates GIDL, was quantitatively analyzed with charge pumping (CP) characterization method in buried-channel array transistors (BCATs) for DRAM cells. The applied stress increased the GIDL current while simultaneously degrading device performance including such as transconductance (<inline-formula> <tex-math notation="LaTeX">$\text{g}_{\text {m}}$ </tex-math></inline-formula>) and ON-state current (<inline-formula> <tex-math notation="LaTeX">${I}_{ \mathrm{\scriptscriptstyle ON}}$ </tex-math></inline-formula>), due to the generation of the interface traps. By using the CP characterization, the interface traps were spatially profiled along the gate-to-drain overlap region in the junction. Trap distribution inside the energy bandgap was also characterized.
Enhanced Resource Scheduling for Platooning in 5G V2X Systems

Vehicular platooning with short inter-vehicular distances promises to achieve better road traffic efficiency and high fuel savings. Manoeuvring and maintaining such Platoons is very challenging and requires mutual awareness and coordination between the vehicles through a highly reliable and low latency communication mechanism. Thus, cellular vehicle-to-vehicle communication is a key enabler of High Density Platooning. However, detrimental effects of cell borders have up to now not been sufficiently considered. This paper addresses 3GPP V2X radio and mobility management of Platoons in a multi-cell system. The challenges related to Sidelink resource scheduling for Platooning are studied in a realistic multi-cell V2X deployment. Our comprehensive system simulations show that current LTE mobility and resource management, where Platoon Members are scheduled individually, cannot support the required performance. To address the identified challenges, a group scheduling mechanism is proposed, which involves the Platoon Leader taking charge of the whole Platoon. The Sidelink resources required for the whole Platoon is granted by the network to the Platoon Leader while entering a cell, which distributes the scheduling information to other Platoon Members. The proposed solution considerably outperforms the baseline LTE system and largely overcomes the cell border issues. These improvements and further enhancements are candidate features for 3GPP NR-V2X in Rel. 16 and Rel. 17.
Preventing Freeway Capacity Drop via MTFC and Ramp Metering

Capacity drop at congested freeway bottlenecks is well known with a lot of field observations and accounts for severe performance degradation of road infrastructure. This paper addresses freeway ramp metering and mainstream traffic flow control (MTFC) at active bottlenecks, with an aim of avoiding capacity drop. A special attention was paid to the effects of capacity drop on the performance of control measures. Via mathematical analyses, it was first shown that the significance and usefulness of the control measures are justified by the presence of capacity drop in field. This was then verified via macroscopic simulation studies, with ramp metering, MTFC, and their integration formulated in a framework of coordinated and integrated optimal control. It was also demonstrated that an appropriate usage of the control measures can effectively prevent the activation of potential bottlenecks on freeways and hence avoid capacity drop there.