Miracle-dz/UniFAR-FTUs huggingface dataset:
Congestion dispatching of distribution network guided by electric vehicle charging service fee

With the large-scale popularization of electric vehicles, its unconstrained or unguided charging behavior may cause the distribution network to block. The owners can choose the charging time and charging place flexibly, which makes the charging of electric vehicles(EV) have the dual uncertainty of time and space. Based on the actual situation of China's electric power market, a spatial-temporal dispatching model guided by charging and changing service fees for EV is put forward to solve the problem of distribution network congestion. In this model, a set of optimal real-time charging service fee pricing scheme that can influence the charging behavior of car owners is designed based on the elasticity coefficient relation between charging service fee change rate and charging amount change rate, taking into account the different degree of attraction of charging price to car owners at different charging stations at different moments. The example shows that the proposed blocking scheduling strategy can effectively guide the owners to make a reasonable charging plan, solve the possible congestion problems in the distribution network, and enhance the economy and safety of the grid operation while taking into account the benefits of the charging and changing facility operators, the charging cost and the satisfaction of the owners with the electricity usage.
Design and Analysis of a Compact Dual-Band Patch Antenna for 5G mmW Application

This paper presents a novel slotted rectangular dual-band (28/42GHz) patch antenna for fifth generation (5G) network applications. A simple microstrip patch antenna of the size 8×8×0.8 mm3has been proposed having impedance bandwidth of 2/9.2 GHz for 28/42 GHz transmission frequency, to resolve the issues of the required compactness, high gain and improved efficiency of the 5G wireless applications. Rogers RO4350 (lossy) is used as a substrate material having dielectric constant and thickness of εr=3.66 and 0.8 mm, respectively. For the resonant frequencies of 28.2 GHz and 42 GHz, the gain of 6.2 dB is achieved for the entire considered bandwidth and a directional radiation pattern is achieved for millimeter-wave transmission. A defected ground structure (DGS) is formed by placing a rectangular slot under the ground, underneath the feed line of a microstrip patch antenna (MSA) which results in improving of the gain. The comparison of the DGS, full ground, and the effect of the slot technique are shown in detail with simulation results in CST. The results for return loss, VSWR, gain, efficiency, directivity, and current distributions shows that the proposed antenna is well suited for the 5G applications in the millimeter-wave region.
Cooperative Control for Stochastic Upper-Triangular Nonlinear Systems with Time-Varying Delay

This paper studies cooperative control problem for upper-triangular nonlinear multi-agent systems (MASs) with time delay. We first introduce a coordinate transformation so that we get a MASs with a low-gain. Then, we build a distributed controller for nominal system of the MASs with a low-gain. With the help of the distributed controller, we choose the appropriate Lyapunov function and use stochastic analysis tool to solve the control problem.
Recent Advances on Linear Low-Dropout Regulators

This brief revises the recent design trends of linear low-dropout regulators. The design issues and advantages of analog LDOs (ALDO) are discussed. High-performance operation and high rejection to supply noise when delivering large current values is a major advantage of the ALDO, but transient response when transitioning from standby operation to full load is a major issue; the main limitation is the slow charging/discharging of the large gate’s capacitor of the pass transistor. This issue is more critical when designing full-on chip ALDOs, where large load capacitors are not available. Digital LDOs (DLDO) employ digital controllers that drive the segmented pass transistor, in most of the cases operate in triode region. The digital nature of the DLDO scales with the technology, but its rejection to supply noise is limited. Mixed-mode LDOs take advantage of the properties of both ALDO and DLDOs. Transient is managed by the agile DLDO and steady state operation is mainly handled by the clock glitch free ALDO. In this brief, all three architectures are revisited.
Classification of Personality Type Based on Twitter Data Using Machine Learning Techniques

In the world of education, knowing about the personality of students can help education providers to determine the development of students. If a person's personality is known, of course we can identify the characteristics, thought patterns, feelings, and behaviors of a person that make them unique. However, conventional personality assessment requires several resources, such as interpreters, space, and time which tends to be long. A person's personality is certainly related to and will affect several linguistic aspects that he uses, including word choice and word placement. Twitter is an internet-based social networking service that allows its users to use its linguistic aspects in sending and reading short messages. This study provides solutions to problems in implementing conventional personality assessments, especially the DISC personality type, by using Twitter media to form a predictive model that applies the naïve bayes classifier method to classify the DISC personality types of Twitter users. We used 9,044 tweets from 70 Twitter accounts as training data to build a predictive model. Before forming and evaluating a model, tweets must go through a series of preprocessing stages. The evaluation of the model was carried out by comparing the classification results of the expert and the classification results of the model, so that the data prediction accuracy rate was 76.19%.
Effect of temperature on crystal growth and crystal properties of paracetamol

The crystal growth kinetics of paracetamol have been investigated at different temperatures and the crystals obtained have been analysed for their mechanical properties. Variations in the crystal habit and crystal quality can be explained by different growth activation energies for the most important crystallographic faces, {001} and {110}. The magnitude of these energies corresponds to the anisotropy of the intermolecular bonds in the crystal lattice. The crystallization temperature strongly influences the thermodynamic and mechanical properties of paracetamol crystals.
Robot Auxiliary Suspension and Control Feedback System

With the gradual rise of the robot industry, the corresponding robot auxiliary system came into being, the object of this study is the robot auxiliary feedback system, can realize the protection of humanoid robots in motion and the corresponding auxiliary control, permanent magnet synchronous motor (PMSM) was manufactured in the middle of the last cent ury, with the development and use of the information industry,the permanent magnetic synchronous motor with its small size, high conversion efficiency High-precision control, and a close d-loop control follow-up system, the function is to enable the up-position command to achieve rapid and precise speed and position response. The Field-oriented Control (FOC) system is a permanent magnet synchronous motor that can be used in the no-position control sensor detection method, and the use of current ring control to achieve the force control of the robot auxiliary. The adaptive control of the robot-assisted force is realized by controlling the output current of the inverter, using the control of PI control ,and the prediction of the current loop.
Magical attention

Cowan postulates that the capacity of short-term memory is limited to the number of items to which attention can be simultaneously directed. Unfortunately, he endows attention with unexplained properties, such as being able to locate the most recent inputs to short-term memory, so his theory does little more than restate the data.
DFNet: Deep Fusion Network for 3D Shape Classification and Retrieval

3D shape classification and retrieval are the primary tasks in computer vision with great application value. Recent researches have benefited a lot from deep learning methods, mainly around point-based and view-based methods. The former lacks robustness under different perspectives, while the latter lacks the ability to capture global features of 3D objects. Inspired by the way humans perceive a 3D object, first to receive its 3D global characteristics and then learn more details from multiple perspectives, we design a Deep Fusion Network (DFNet) that combines a point-based network (PointNet) which reflects intrinsic properties of 3D shape from the point cloud and a view-based network (ViewNet) which captures spatio-temporal features from shape's sequential projections through the combination of CNNs and LSTM. A high-level 3D shape feature descriptor, combining the advantages of the two features merits, is finally obtained by FusionNet. Experimental results show that our proposed DFNet which fuses point-based and view-based features achieves better performance than only one feature based network. And comparison with other excellent methods shows that DFNet outperforms under two large-scale 3D shape benchmarks.
MEMTV: a Research on Multi-level Edge Computing Model for Traffic Video Processing

Real-time traffic video data analysis and processing technology is an important part of intelligent urban transportation, real-time urban traffic planning, reducing urban traffic congestion, has certain application value. Aiming at the problem that network transmission link resources are limited and it is difficult to meet the real-time analysis and processing of massive video data uploading to the cloud. In this paper, we propose MEMTV, a multi-level edge computing model based on big data machine. The model obtains scene semantic information by processing traffic video data at the edge intelligent terminal, and uploads the scene semantic information as textual metadata to the edge server for analysis, while the edge server only does the inference of the model, and the update training of the model is performed in the cloud, which does not affect the edge data processing while ensuring the high reliability of the prediction model. The experimental results show that the MEMTV can effectively process traffic video stream data.
Research of Fault Feature Extraction and Analysis Method Based on Aeroengine Fault Data

Research of engine fault diagnosis is an effective way to ensure the safety of aviation aircraft. The original gas path fault information of turboshaft engines and turboprop engines often introduces a lot of noise during the collection process, which interferes with the extraction of fault features. Therefore, it is necessary to develop fault feature extraction algorithms adapted to the needs of big data processing to solve such problems. In this paper, the C-MAPSS turbofan engine degradation simulation data set is used as the research object. After using Principal components analysis (PCA) for data dimensionality reduction, two algorithms of k-means clustering and DBSCAN clustering are used to extract fault features of the data. The Silhouette Coefficients and DBI internal evaluation indicators of the two methods are analyzed. In order to improve the effect of clustering, a fault feature extraction algorithm with better performance is proposed: DBSCAN k-means Mixing (DKMM) algorithm improves the accuracy of the clustering algorithm. Finally, the fault feature extraction software for turboshaft engines and turboprop engines was developed. The research results of this paper can provide theoretical support for the development of the two-machine special health management system.
Formation Control with Obstacle Avoidance via Complex Laplacian

This article handles the obstacle avoidance problem of formation using the complex Laplacian. We assume that only two agents named leaders can obtain information from the target due to the particularity of formation control via complex Laplacian. A strategy is proposed to handle the problem of obstacle avoidance, this control strategy consists of three parts: formation control, track control and obstacle avoidance. The formation is completed by complex Laplacian in which the final formation is determined by the two leaders with consistent speed. However, the speed of the leaders will definitely be affected by obstacles. we choose a target curve for leaders to track so that they can eventually reach the same velocity after avoiding obstacles. The problem of obstacle avoidance is completed by the artificial potential field (APF) method. The simulation results verify the effectiveness of multi-agent obstacle avoidance and formation under the proposed control protocol.
A New Short-Circuit Protection Scheme for Boost Converter

Protections of converters are a challenging task to avoid the damage of the converter and minimize operational efficiency. In this paper, a new dc short-circuit (SC) protection approach with boost converter is implemented to protect the dc bus, load, and converter’s component from the SC fault current. If a SC fault occurs in the dc bus or load side, the proposed protection scheme isolates the power supply from the converter and reconfigures the converter for damping the SC current. The SC current circulates through the damping resistance thus, damps gradually to zero. The significant key point of the proposed scheme infers that the detection of a short-circuit fault is done by the voltage control loop. Other key points are low component count and fast isolation. The fast isolation is achieved even in case of lower SC resistance. The presented fault protection scheme integrated with the converter is useful in its application at load or source side in the dc microgrids. The detailed analysis, working principle, and simulation results are presented in this paper. The proposed protection scheme is verified using the SPICE model of the circuit components on the “LTspice” simulator using Modified Trapezoidal Integration solver.
A lightweight soft exoskeleton in lower limb assistance

The soft exoskeleton is a wearable robot which is functioned to improve the capacity of human walking or loading. The metabolic of human is increase with the additional load, one integrated design method is used to reduce this effect in this paper. Meanwhile, in order to enhance the convenience and decrease the disturbance to wearer, the wireless module is used to replace the signal line. The nonlinear characteristics and uncertainty of flexible material make the control of soft exoskeleton system be a challenge, a switching controller is proposed to deal with this problem in this paper. It consists of Iterative learning control (ILC) based stable controller and admittance control based unstable controller, functioned with wearers walking stable and not. An experiment of force tracking is conducted to verify the controller performance in this paper, and the result demonstrate that the tracking is well after 20 iteration. In order to evaluate the performance of assistance of soft exoskeleton, five health adult male take part in metabolic experiment By compare the metabolic rate between the wear soft exoskeleton and not wear, the metabolic rate are decrease 7.33%, 14.56% and 10.45% with the walking speed of 3km/h, 5km/h and 7km/h, which are corresponding absolute values decrease of 0.46W/kg, 1.60W/kg and 1.21W/kg respectively.
Community midwives’ and health visitors’ experiences of research recruitment: a qualitative exploration using the Theoretical Domains Framework

Abstract Background: Successful research is frequently hampered by poor study recruitment, especially in community settings and with participants who are women and their children. Health visitors (HVs) and community midwives (CMs) are well placed to invite young families, and pregnant and postnatal women to take part in such research, but little is known about how best to support these health professionals to do this effectively. Aim: This study uses the Theoretical Domains Framework (TDF) to explore the factors that influence whether HVs and CMs invite eligible patients to take part in research opportunities. Method: HVs (n = 39) and CMs (n = 22) working in four NHS Trusts and one community partnership in England completed an anonymous, online survey with open-ended questions about their experiences of asking eligible patients to take part in the research. Qualitative data were analysed using directed content analysis and inductive coding to identify specific barriers and enablers to patient recruitment within each of the 14 theoretical domains. Findings: Six key TDF domains accounted for 81% of all coded responses. These were (a) environmental context and resources; (b) beliefs about capabilities; (c) social/professional role and identity; (d) social influences; (e) goals; (f) knowledge. Key barriers to approaching patients to participate in the research were time and resource constraints, perceived role conflict, conflicting priorities, and particularly for HVs, negative social influences from patients and researchers. Enablers included feeling confident to approach patients, positive influence from peers, managers and researchers, beliefs in the relevance of this behaviour to health care and practice and good knowledge about the study procedures, its rationale and the research topic. The findings suggest that to improve research recruitment involving HVs and CMs, a package of interventions is needed to address the barriers and leverage the enablers to participant approach.
Quadrotor UAV Trajectory Tracking Control based on ASMC and Improved ARDC

In this paper, a new double closed-loop control method for trajectory tracking of quadrotor unmanned aerial vehicles (UAV) is proposed to attenuate wind gusts disturbance and effects of parameter uncertainties. The dynamics and kinematics equations of the quadrotor UAV are established by the Euler and Newton theorem. In the outer loop subsystem, the adaptive sliding mode control (ASMC) algorithm is proposed to estimate the payload variation and air disturbance, and it can realize the stable tracking of the target position. For the inner loop subsystem, this paper designs an improved active disturbance rejection control (ADRC), which replaces the extended state observer with a higher-order sliding modes observer, and improves nonlinear state error feedback by a new nonlinear functions. Simulation experiments are given to evaluate the robustness and effectiveness of the designed controller algorithm.
Adapting Tellegen’s Theorem for Synchrophasor-Assisted Fault Identification in Active Distribution Networks - An Illustration

The integration of distributed generations at distribution level makes the traditional fault location schemes inappropriate, owing to bidirectional power flows and other challenges. It therefore becomes imperative to develop new and reliable fault identification methods in Active Distribution Network (ADN) in order to automatically isolate and restore the end-user services in a short space of time. To this end, this paper presents a synchrophasor-assisted Tellegen’s theorem based fault identification method in ADNs. At first, the two adjoints of the original network are created and their phasor information is stored offline. Next, it is assumed that the distribution-level Phasor Measurement Units (PMUs) aka $\mu$PMUs are located at the extreme buses of the actual network that provides the real-time data, and finally, both the off-line and real-time information is utilized to detect the open or short circuit fault in the network. The proposed fault identification method is demonstrated in detail on a simple system, keeping in view the typical ADN characteristics.
Fixed-Time Synchronization of Fifth-Order Memristor Chaotic Systems

Based on the classical Chua’s circuit, a chaotic circuit is constructed including double magnetron memristors. To study the fixed-time synchronization problem about the fifth-order memristor chaotic systems, a sliding-mode surface is proposed firstly. Then, a suitable controller is devised by using the sliding-mode control method. The sliding-mode surface is reached, then the stability on the surface also can be achieved within a fixed time thereafter. Moreover, the settling time for system synchronization is estimated, and numerical simulations confirm the correctness of the theory.
Flexibility analysis of nondispersive solvent extraction plant

The objective of this work is to analyze the behavior of a nondispersive solvent extraction plant in the uncertain space of concentration and flow rate of the feed stream. To carry out this task, a superstructure with a maximum number of 64 modules distributed in 8 parallel lines of 8 modules in series for both extraction and stripping subprocesses is developed. A flexibility analysis on the optimal design obtained with this superstructure is implemented using the equation-oriented flowsheeting package speedup (Aspen Technology, Inc). Further studies of the flexibility index for different overdesigns are done in order to obtain a deeper insight of the operability characteristics of the system. The results show that the optimal nondispersive solvent extraction processes for the case of removal and concentration of Cr(VI) with Aliquat 336 present low flexibility indices.
Robots Learn to Write via Human–Robot Interaction

Human–Robot Interaction (HRI) has been extensively investigated in academia, industries, and technology companies. How to teach a robot to write is recognized as a difficult task, involving perception, learning and control of the overall robotic system. This paper develops a robotic handwriting system on a NAO robot by using HRI and Q-learning. In the simulator setup, the human demonstrator first writes to form a desired writing content, with the coordinates of each stroke writing saved; then, by applying the Q-learning algorithm, the virtual NAO automatically learns to find the correct writing order and to optimize the strokes. With the learned knowledge, the real NAO uses its inverse kinematics for generating the joint values from the stroke trajectories, and thus can quickly replicate the letters or words written by the human demonstrator. It is shown that by using the proposed HRI-based handwriting system, the human can naturally and conveniently teach NAO to write many characters and NAO can also have an acceptable writing quality close to the human.
Evaluation of Time Delay Intervals in the Wide-Area Damping Controller Design

Synchronized electrical measurements acquired with high sampling rates by Synchronized Phase Measurement Units (PMUs) from different locations in the Wide-Area Measurement Systems has shown promise in the design of central controllers or Wide-Area Damping Controller (WADC) whose purpose is to increase the damping rates of electromechanical modes. However, due to the different locations of the PMUs, different time delays may be present in the WADC communication channels. Motivated by this, this article proposes to evaluate how different time delay intervals interfere in the design of central damping controllers. Using an evolutionary approach called Marine Predators Algorithm, a statistical evaluation will be made in order to assess which time delay intervals provided the highest damping rates of the cyber-physical control system. A detailed case study procedure will be formulated and applied in the following system: IEEE 68-bus 5-area power system.