Miracle-dz/UniFAR-FTUs huggingface dataset:
Landslide Detection Based on Improved YOLOv4

Landslides are a common and highly hazardous geological hazard, causing serious damage to human safety, property economy and surface environment worldwide. Starting from a deep learning data source, we use remote sensing images of landslides as the base data and perform multiple data-strength processing. A landslide hazard detection model is proposed. The study proposes a landslide detection model based on the one-stage object detection model YOLOv4 (You Only Look Once) and reconstructs the model framework using phantom convolution module, group convolution and attention mechanism. The model addresses the problems of slow detection speed of two-stage model and low detection accuracy of one-stage detection model, and greatly reduces the number of parameters of the model with high detection accuracy while maintaining the model with high detection speed.
Short-term Wind Power Prediction Method Based on GCN-LSTM

Led by the strategic goal of "carbon peaking and carbon neutral", the development of new energy, especially wind power, will occupy an important position in the power grid. The current wind power prediction has a large error, which has a serious impact on the safe and economic operation of the grid. In this paper, a combined prediction model combining graph convolutional network (GCN) and long short-term memory network (LSTM) is proposed for short-term wind power prediction by combining deep learning. The method firstly uses graph convolutional network to extract spatial relationship features of wind power historical data; secondly, it uses long and short-term memory network model to extract and predict the temporal features of wind power. According to the experimental results, the method has less error and higher accuracy than the single-model method in prediction results.
Monte Carlo Modelling of mmWave 6G Systems for Shared Spectrum Deployments

The evolving 6G systems will push the mobile spectrum frontier well into the mmWave and THz bands, i.e., from 24 GHz to 275 GHz. This calls for a better understanding of future spectrum sharing and co-existence scenarios that involve mobile systems in those frequency ranges. The European regulatory establishment has started to address such studies with an initial focus on 5G mobile systems sharing in 26 GHz band. This paper takes a further step by modelling the evolving 6G systems across a wider mmWave range of 26-71 GHz. The paper discusses radio wave propagation prediction in mmWave bands and uses Monte Carlo simulations to estimate the probability of interference between mobile and fixed systems under different assumptions. In particular, the paper shows the importance of terrain elevation modelling in spectrum sharing studies of future 6G systems.
Hybrid Pulse Width Modulation with Current Derivative Measurement for PMSM Sensorless Control

This paper proposes a position sensorless control method of permanent magnet synchronous motor (PMSM) using the current derivative measurement with the hybrid pulse width modulation (PWM). Ensuring a sufficient duration of the voltage vector for the current derivative measurement is a main issue in fundamental PWM excitation-based (FPE) sensorless control method. The proposed method overcomes this issue by extracting the position error from the phase voltage and current in only one voltage vector. Then, the hybrid PWM method is introduced to enhance the accuracy of the position estimation regardless of the modulation index (MI). In addition, the current derivative is accurately measured using the multi-point current sampling (MPCS) and the least square curve fitting (LSCF). To improve the performance of the sensorless control, the time delay compensation and average current calculation methods are presented. As a result, the proposed method enables a full-region sensorless control of PMSM without any voltage injection or phase shifting, which deteriorates the field-oriented control (FOC). The effectiveness of the proposed method is verified by a 1kW PMSM drive system in various driving conditions.
Multi-Scale Temporal Adaptive Convolution for Gait Recognition

Gait recognition is one of the most promising biometric technologies which widely used in video security. The spatio-temporal features contained in gait sequences provide rich discriminative information for individual recognition. However, most existing gait recognition methods pay more attention to spatial features and ignore temporal information. To address this issue, we design a multi-scale temporal adaptive convolution module (MTAC) in the proposed framework. Specifically, we introduce the adaptive temporal modeling strategy to generate convolution kernel based on specific videos, and combine the adaptive temporal kernel with multi-scale dilated convolutions to extract more robust gait temporal information. We conduct experiments on the CASIA-B dataset. The proposed method achieved recognition accuracies of 97.2%, 93.5% and 83.9% under three conditions, namely normal walking and walking with a backpack or coat, respectively, showing the effectiveness and advancement of the propose method.
A Multi-Band Antenna with an Aesthetic Design for Ambient RF Energy Harvesting

This paper presents a novel multi-band patch antenna with an aesthetic design for ambient RF energy harvesting applications. A new approach is applied to create antenna elements with unique shapes on a 3D-printed substrate for easy antenna integration into different objects. The measured results show that the proposed antenna provides three frequency ranges over which the reflection coefficient magnitude is below -10 dB of 1.71-1.80 GHz, 2.33–2.60 GHz, and 3.3-3.6 GHz. The antenna radiation patterns show that the antenna enables multi-direction harvesting from unknown RF sources. Moreover, the proposed antenna has been embedded in a 3D-printed flower pot. The results show that the embedded antenna has a robust input impedance when a flower is placed in the flower pot close to the antenna ground plane. These demonstrated properties of the proposed novel antenna with an aesthetic design make it an appropriate candidate for incorporation into next-generation IoT self-powered devices.
Three-Phase LLC DC/DC Converter in Stack Configuration: A Topology for High-Voltage Conversion Ratio Applications

Those applications with a very high step-down voltage such as in aircrafts, being able to obtain high power density and high efficiency is crucial. Gallium Nitride transistors have been enabling the downsize of magnetic components due to their low capacitance. Due to the scaling of switching losses as the frequency increases, lower efficiency is obtained. LLC converters are a classic soft-switching topology able to push the magnetic component design to their limits. Wisely choosing the topology in this situation is not only desirable but essential to take maximum advantage out of it, for that, a new cell stack configuration is proposed, promising high integration and thus, high power density. In this paper, a detailed analysis for the design of a Three-Phase LLC converter in stack configuration is exposed. The challenging specifications of the application include a wide input voltage range (235-285 V), a large step-down to 12 V in a half-brick form factor (47 cm3) for a nominal output power of 1 kW leading to a power density of 10 kW/L.
A Tourist Online Consumption Data Analysis Platform Based on Real-time Satellite Positioning Equipment

With the rapid development of communication technology and computer application, satellite navigation system has become an important part of the city, and its positioning service function is one of the key contents of the national security monitoring agency. This paper builds an online consumption data analysis platform for tourists based on real-time tracking and positioning as the main research object. First, it introduces the relevant concepts and basic knowledge of tourists’ travel path query, and then preprocesses the original data to obtain the user’s current location information, and uses the target axis to provide the destination information and historical trend and other parameters as prediction features to achieve automatic matching. After that, the software simulation test was used to test the function of the platform. The test results showed that the positioning time and payment module of the online consumer travel platform based on real-time positioning technology were maintained at about 5 seconds, and the efficiency of the information communication module and location positioning were both above 90%, which indicated that the platform could meet the needs of users.
Fault Location Method of Power Line Based on Real-Time Parameter Estimation

In order to accurately determine the location of the short-circuit fault point of the distribution power line, this paper first proposes a method for estimating the line parameters of the distribution network based on multi-source data and multi-time sections from the micro-synchronous phasor measurement unit (μPMU) which can be deployed on a large scale. It not only uses the sampling rapidity of μPMU to fuse the measurement data of multi-time sections, but also uses the precise time scale of μPMU to align the data on the same time section, and establishes a typical trunk/branch connection mode of the distribution network to construct a parameter estimation model for real-time estimation of the line parameters. On this basis, the mathematical model of distribution line parameter identification and fault location is established, and the simulation analysis is carried out based on PSCAD/EMTDC. The error of parameter identification and its influence on the final location are studied, and the influence of different line types, short circuit fault types, transition resistance and fault initial angle on the algorithm is analyzed and compared with the traditional algorithm. The results show that the proposed method in this paper has high location accuracy.
Comparative Validation of SRAM Cells Based on Decoupled Read Technique using 45nm CMOS

The modern era expects great computing power, portability, and minimal power consumption from all electronic devices. SRAM is widely valued in the consumer electronics sector because it can match the criteria for high processing speed and memory density. In this paper, a detailed analysis and comparison among Asymmetric-Read-Decoupled10T (ASRD10T) SRAM, PPN-Read-Decoupled-10T (PPNRD10T) SRAM and Conventiona1-6T (C6T) SRAM is presented. The results show that the read delay of ASRD10T and PPNRD10T is improved with a factor of 1.13× in comparison to C6T. The write delay of PPNRD10T is improved with a factor of 0.989× and 0.936× in comparison to C6T and ASRD10T. The hold stability and read stability of ASRD10T and PPNRD10T is higher in comparison to C6T improved with a factor of 1.117× and the write margin is improved with a factor of 1.13× and 1.38×, in comparison to PPNRD10T and C6T. This is due to the separate read mechanism because of the read decoupled circuit, the read stability is acting as hold stability. The Electrical quality metric (EQM) calculation shows the better performance of PPNRD10T circuit in comparison with C6T and ASRD10T. All the comparisons were performed using a supply voltage ranging from 0. 5V to 1V.
Dynamic Level Shift Control Scheme for Power Loss Reduction in T-type Traction

A Dynamic Level Shift Control Scheme (DLSC) is proposed to improve the efficiency by reducing the losses in the switching devices. In this scheme, a hysteresis comparator is used to compare the instantaneous loading with the loading threshold set by the user. This threshold is decided based on the power loss such that, when the operating conditions cause more losses, a three level-inverter Space Vector Control (SVPWM) is implemented while when the losses are less than desired threshold, the control switches to two-level control, hence reducing the losses in the neutral legs. The proposed control has been implemented in a GaN based T-type traction inverter. The simulation results verify the proposed control. Further, the block diagram used to design the control scheme has also been presented.
DDoS Vulnerabilities Analysis in SDN Controllers: Understanding the Attacking Strategies

Modern technologies like 5G, IoT, and Cloud Computing are all adopting Software-Defined Networking (SDN) as a standard approach. The reason behind its widespread acceptance is its innovative design principle of decoupling the network's control logic from its data-forwarding hardware. SDN controller is the core of the network which manages the network traffic flows therefore the most important task in SDN is to provide security to the controller. Distributed Denial of Service attacks are types of attacks that slow down the performance of SDN where malicious users send a large volume of fake packets to the controller in an attempt to use up all of its resources. In this study, we analyze the vulnerability of DDoS attacks in different SDN controllers like POX, Ryu, Floodlight, and OpenDayLight through a comprehensive experimental study. From this study, it has been observed that said controllers are affected differently in terms of the CPU and memory utilization due to their routing policies. This study will help a network administrator to choose the right solution against DDoS attacks in SDN controllers.
Controller Design and Phase Current Balancing for Fast Dynamic Performance in Voltage Mode Controlled Multiphase Buck Converters

With the growing computational requirement in powerful digital processors in modern smartphone and automotive applications, multiphase buck converters remain an attractive power management solution to achieve higher efficiency over a wide load current range with better thermal distribution and faster load as well as DVS transient performance with the reduced output capacitor. Also, a high switching frequency is desirable for a smaller form factor, which makes it difficult to sense fast-changing phase currents. Fixed frequency voltage mode control (VMC) remains a cost-effective solution in terms of phase shifting and phase shading; however, the challenges remain in achieving fast transient performance and accurate phase current balancing. This paper considers a VMC multiphase buck converter and proposes a novel current balancing method and controller tuning algorithm to achieve fast transient with accurate phase current balancing for master-master VMC configuration. Small-signal-based PID and type-III compensator design methods are considered for the controller design. Finally, a large-signal based PID controller is computed, which can significantly improve the transient performance and is demonstrated using simulation results. A four-phase buck converter prototype is fabricated, and a few experimental results are presented.
A Batteryless Full Energy Harvesting System for Inside-Engine Temperature Sensors

This paper presents a full energy harvesting system for harvesting mechanical energy from internal combustion engines to power low power autonomous sensor systems inside of the engine to record and wirelessly transmit the piston temperatures. Due to the reciprocating movement of the pistons, sensors cannot be connected to the cars electrical system by wires and thus are usually powered by batteries. Changing those batteries is a time consuming process since large parts of the engine needs to be taken apart to get to the pistons. This is the reason why we present a system that uses a piezoelectric nano generator (PENG) based on flexible PVDF to convert a small amount of the mechanical energy of the pistons to electrical energy. A power management system (PMS) including a maximum power point (MPP) circuit maximizes the power output of the harvester and supplies a regulated dc voltage to the sensor. The MPP circuit used in this design has a very few components, thus keeping its own power consumption low. It requires a minimum input voltage of 3V and a minimum power of 1. 4µW during operation. During startup, a power of 4µW is required for a short time until the input capacitor of thre PMS is charged to 1.8V. Measurements show an increase of up to 44% of harvested power while also allowing higher output voltages compared to the same power management system without an MPP circuit. A prototype to emulate the movement of the pistons was built and tested with the PENG and PMS. At 600rpm, data transmission is possible every 90 seconds with 3. 5µW harvested power.
Millimeter-Wave Switched-Beam Grid-Array Antenna

An electronic switched-beam grid-array antenna (GAA) at 28.0 GHz is investigated. The proposed antenna panel includes of a sixteen-port GAA integrated with RF switching circuit that consists of five RF switches and a separate control panel. The sixteen beams can be electronically switched/steered with a beam coverage of ±22° and measured antenna gain of >14.0 dBi at 28.0 GHz.
A Two-Phase Hybrid Switched Capacitors Converter with Interleaving Control Scheme for Flying Capacitors Self-Balancing

This paper presents a dual-path power stage with an interleaving control scheme in a two-phase hybrid switched capacitor converter. In a conventional three-level converter, the flying capacitor voltage is not self-balanced and thus extra calibration is required to overcome parameter and timing mismatches, parasitic capacitors, etc. The proposed converter obtains a self-balanced flying capacitor voltage with an interleaving control scheme. And then, the non-ideal effects are also calibrated without an additional cost. In addition, there are two series power switches in the discharge path in the three-level converter. But in the proposed power stage, there is only one power switch. Therefore, the conduction loss is reduced dramatically in each de-energizing phase. The converter is implemented with a conversion from 12.0 V to 1.0 V at a 1-MHz switching frequency, based on a $0.15-\mu\mathrm{m}$ highvoltage BCD process. The simulation shows that the flying capacitor voltages are self-balanced within only one switching cycle. The peak efficiency of 89.8% is achieved by this converter under a 3-A current load.
Some dynamical properties of continuous maps on the k-Warsaw circle.

Some dynamical properties of continuous maps on the \%k\%\|Warsaw circle are studied, show that: a \%k\%\|Warsaw circle need not be a Sarkovskii space; it has the \%PR\%\|property; for the self\|map on a \%k\%\|Warsaw circle, isolated chain recurrent points are eventually periodic; the depth of the center is not greater than 4; the topological entropy is zero provided that the periods of periodic points are the powers of 2; and transitive maps are equivalent to the chaos in the sense of Devaney.
Noisy Phoneme Recognition Using 2D Convolution Neural Network

Speech is one of the most important parts of everyday life, thus it has been investigated from various standpoints, however, there is still room for exploration within noisy speech signals. This study examines how speech signals are recognized in the presence of noise by conducting a recognition process using both clean speech and speech data with additive noise. Spectrograms and Mel Spectrograms have been extracted and tested using a Convolutional Neural Network. Training on noise-free data and on mixed data which has been composed of clean and noisy phoneme signals has been considered. The experimental results showed that model trained with set which includes noisy samples gives better results when classifying signals with noise present compared to noise-free trained model. It was also revealed that Mel Spectrograms represent noisy signals better than Spectrograms.
Shielding Technique of Planar Transformers to Suppress Common-Mode EMI Noise for LLC Converter with Full Bridge Rectifier

The planar transformer shows excellent benefits when applied in a high efficiency and high power density LLC converter with increased common-mode (CM) noise caused by the large interwinding capacitances. For the shielding design of a half-bridge (HB) LLC converter with a full-bridge rectifier(FBR), it is essential to find the static-electric-potential (SEP) point in the physical primary or secondary windings. With the proper design of the ground connection of shielding winding, the voltage potential difference between shielding winding and primary/secondary windings is minimized, and the net displacement CM current diminishes. In this paper, the analysis of the SEP point of different transformers for the HBLLC converter with a FBR was discussed, and the net CM current under different ground connection strategies of shielding winding was compared. The CM noises of different strategies are measured based on a 1.5kW HBLLC converter with FBR hardware platform. The EMI measurement results show that it can attenuate the CM noise by 20 dB or more with proper shielding design.
Mini-LEGO: A 1.5-MHz 240-A 48-V-to-1-V CPU VRM with 8.4-mm Height for Vertical Power Delivery

This paper presents the design and optimization of a miniaturized 48-V-to-l-V 240-A linear-extendable group oper- ated point-of-load (LEGO-PoL) CPU voltage regulation module (VRM) − Mini-LEGO - with 336 mm2 area and 8.4 mm height for vertical power delivery. The Mini-LEGO features compact device implementation, simplified gate drive circuitry, optimized magnetics, and switches at 1.5 MHz. The overall converter area, including all power stage and gate drive circuitry, is 336 mm 2 with 0.71 A/mm2 current area density. The vertical coupled inductor delivers 80 A with a thickness of 2.5 mm. It achieves a peak efficiency of 87.1 %, a full load efficiency of 84.1 %, and a power density of 1,390 W/in3 with the maximum device junction temperature maintained below 100°C after five minutes of full- load operation.
C-Band Two-Dimensional Dynamic Metasurface Antenna for Through-the-Wall Computational Imaging

This contribution presents the design of a two-dimensional (2D) dynamic metasurface antenna (DMA) for a through-the-wall computational imaging system. The use of C-band is intended to achieve enough penetration capabilities to image different types of wall. The 2D DMA comprises a set of randomly distributed dynamically tunable unit cells which can be activated and deactivated by switching off and on PIN diodes. This reconfigurability enables to generate quasiorthogonal radiation patterns, or measurement modes, to encode the information of the area under inspection and compress it into a reduced number of channels. The imaging performance of the proposed imaging system was validated through electromagnetic simulations considering two metallic patches placed in front of the DMA panels as test targets and a scenario with and without a wall. Results show that, even when a significantly reduced number of radiation patterns is considered, targets concealed behind a simple wall can be accurately imaged.
CNN Framework for Accurate Brain Tumour Segmentation from Enhanced MRI Slices

The brain tumor (BT) is a severe condition caused by abnormal cell growth. If left untreated, the BT may result in a variety of harsh conditions, including death. As a consequence of the significance of automatic BT detection, several schemes have been developed and implemented in the literature to accurately assess the BT. We propose a method for accurately segmenting brain images from MRI slices in this study. This proposal includes a number of phases, including; (i) collecting and resizing images, (ii) enhancing the image using a selected scheme, (iii) segmenting using ResUnet, and (iv) evaluating and validating the performance. This study examines several brain MRi slices with or without the skull region, and the results are evaluated separately. Based on these outcomes, it is concluded that the proposed ResUnet together with CLAHE provides a significant improvement over other methods concerning Jaccard (>92%), Dice (>95%), and accuracy (>98%).