Miracle-dz/UniFAR-FTUs huggingface dataset:
An Electromagnetic Compatibility Design for Optical Channel of Optoelectronic System

This article presents an electromagnetic compatibility design of optical channel in optoelectronic system based on high impedance surface. Using the characteristics of high impedance surface wave suppression, it is attached to the side wall of the optical channel to achieve the electromagnetic compatibility function with high optical signal transmittance. By changing the arrangement of the protection unit array, the appropriate anti-electromagnetic interference ability and frequency band are designed. In the simulation results, the resisting electromagnetic interference reaches 10 dB in the 1.64 −1.74 GHz and 1.84-2.51 GHz bands. The 10 dB bandwidth reaches 0.77 GHz.
Evaluating Demand Response Potential of Air Conditioners in Residential Sector: A Data-Driven Approach Estimating Room Temperature

With the rapid spread of renewable energy, the utilizing residential air conditioners (AC) for demand response (DR) is gaining importance. As resource aggregators seek to manage the flexibility offered by a large number of AC units, accurately estimating the DR potential of ACs is essential for successful bidding in the balancing market. This study introduced a data-driven method that leverages measured electricity data from residential ACs to evaluate the DR potential and estimate the room temperature without the complex model of thermal conduction. The proposed method comprises three components: estimating the AC turn-on/off states, calculating time-dependent parameters for room temperature estimation, and determining the room temperature and AC electricity consumption after DR implementation. A case study was conducted using data from 479 dwellings in Osaka, Japan, to assess the downward DR potential during the cooling season. Results indicate a median DR potential ranging from 9.2% to 18.7% of total AC electricity consumption. This study provides valuable insights into leveraging residential ACs as flexible resources for demand response, empowering resource aggregators to make informed decisions in a balanced market.
A High-Linearity, Energy-Efficient Switched-Capacitor Computing Circuit for Edge Applications

This paper presents a passive switched-capacitor multiplication circuit for deep neural network computing in edge applications. A novel capacitor switching scheme is proposed to eliminate the computation error caused by non-binary-weighted parasitic capacitance, and dramatically increase the computing accuracy. It also simplifies the switching sequences to five phases to reduce the computation latency and improve the energy efficiency. Additionally, a mixed-signal multiply-add computing array is built with nine proposed switched-capacitor circuits and a SAR ADC. The simulation results in 28-nm technology show that the proposed array can achieve an energy efficiency of 11.94 TOPS/W and an average absolute computation error of 0.25 LSB, resulting in a classification accuracy of 98.43% when used for a 3-layer neural network on the MNIST dataset. As compared to the state-of-art mixed-signal computing circuit, the proposed circuit can enhance 1.19× energy efficiency and reduce 74% average absolute computation error.
Thermal Performance Comparisons of Different Spacer Structures in Double-Sided Cooling Power Modules

The thermal performance of double-sided cooling (DSC) power module is influenced by different spacer structures. In this paper, thermal performance improvement principles of different kinds of spacer structures are described qualitatively and thermal performance of these structures are analyzed by finite element method (FEM) quantitatively. Both Expanding spacer area and connecting low temperature areas to high-temperature areas by thermal conductor are effective methods to improve overall thermal performance. Structure with spacer under the bare die have the best thermal performance among these structures due to larger heat conduction area. Furtherly, transient dual interface method is utilized to measure the thermal resistance of different structures. The body diode electrical characteristic is chosen as the temperature sensitive electrical parameter.
Packet-Level Intrusion Detection Using LSTM Focusing on Personal Information and Payloads

In recent years, network-based intrusion detection systems (NIDS) based on advanced neural network (NN) technologies have emerged. In the previous study (Hwang et al. 2019), higher classification accuracy than conventional NIDS models was achieved by an NN-based NIDS using features from strings contained in the header information of communication packets. It used LSTM to learn the time series extracted from the packets. However, the data used for training contained information about the attacker’s devices, which we could not utilize in real situations. Therefore, in this study, we conducted experiments using the LSTM model to hide the MAC addresses, IP addresses, and port numbers from the headers, which are the attacker’s personal information. The results show that the accuracy of packet classification was significantly degraded, confirming that the classification results in the previous study depended on the attacker’s personal information. In addition, our experiment, in which personal information was removed and payload information was added to the classification, achieved an F1-Score of 99.0%. The result is comparable to that of the previous study.
An Accurate Deep Learning-Based Thermal Reconstruction Technique for Microprocessors Using Embedded Sensors

This paper proposes a deep learning-based thermal reconstruction technique to accurately recover a microprocessor's full thermal maps with a limited number of sensors. A neural network model derived from U-Net is improved to infer comprehensive thermal profiles using limited sensor readings. An integrated thermal simulation framework combining Gem5, McPAt and HotSpot generates training data, and evaluates the technique on a microprocessor running real applications. Results demonstrate that the proposed technique can accurately reconstruct thermal maps and outperform prior methods.
A Novel High Voltage Gain Nonisolated Bidirectional DC-DC Converter for Hybrid Energy Storage System

T In this paper, a novel non-isolated bidirectional dc-dc converter (BDC) with high voltage conversion ratio has been proposed for hybrid energy storage system (HESS). The converter presented combines the advantages of simple structure, high voltage gain, wide voltage gain range and low stresses across the power semiconductors. A broad analysis of the operation principle and the characteristics analysis of the converter in a continuous conduction mode are presented in detail. This paper also develop a 1 kW experimental prototype, which validates the effectiveness and feasibility of the proposed BDC.
A Three-Phase Soft-Switched AC/DC Active Front End Converter for Solid-State Transformer Applications

In a number of applications, including data centers, on-board chargers (OBCs), solid-state transformers (SSTs), etc. AC/DC PWM converters are typically used for active power factor correction. Conventional AC/DC converters are hard-switched, which results in lower switching frequencies to achieve good efficiencies which results in the increased size of magnetic components. In a bid to improve the performance of AC/DC converter systems in terms of efficiency and power density, soft-switched converters are imperative. In this paper, an integrated Triangular Current Mode (iTCM) operation of a three-phase converter system is introduced. The iTCM approach achieves soft-switching over the entire line cycle without the use of any additional active devices but uses passive LC branches connected to the midpoint of the phase legs. The LC circuit carries high-frequency triangular currents, which enables the soft-switching of all the devices. The operation of the three-phase converter is introduced for the first time in literature, and the design procedure for each of the components is provided. The effect of various modulation strategies is analyzed, and the discontinuous PWM method is chosen based on its inherent advantages. Experimental results on a 11 kW three-phase converter system, demonstrating the feasibility of the converter design and operational ability in an inverter mode of operation are shown. These converters can be helpful in validating the effectiveness of soft-switched converters based on the operating principles, efficiencies and power density in various application areas.
Load Characterization Tuning Strategy to Reduce Switching Losses in Power Quality Compensators

Literature on capacitorless power quality compensators (C-PQC) was shown to increase the converter service life and increase the reliability of the power system. This paper improves the C-PQC by achieving longer converter service life through reducing switching losses. While finite control set model predictive control (MPC) achieves high fidelity tracking for multi-objective cost functions, it results in high switching frequency, which increases losses and device stresses, and reduces the overall converter reliability. Additionally, cost function weight factors assignment is not an entirely solved issue, as it is mostly based on trial-and-error and little expertise in the system. This paper develops an auto-tuning approach for the MPC weighting factors that minimizes the switching frequency within IEEE harmonics standards, hence reduces switching stresses. The significance of the developed approach is its use of the load characterization of the system bus, to auto-tune the MPC weighting factors during operation.
A Generalized Modulation Method for Capacitive AC-Link Universal Converter with Wide Reactive Power Range

This paper proposes a generalized structure with extended modulation scheme for capacitive AC-Link universal converters. Capacitive AC-Link universal converters use a small capacitor for transferring power from any type of source to any type of load. They offer numerous advantages, including high reliability, due to eliminating the need for large electrolytic capacitors, as well as high power density, due to using small capacitors and the possibility of using compact high-frequency transformers. There are still some analytical gaps in the earlier studies on this converter. Firstly, the switching pattern is power-direction dependent, and asymmetrically defined for input/output ports. Secondly, with the previously proposed modulation scheme, the power factor is limited to 0.866 lead/lag. In this paper, a generalized modulation scheme is introduced that is independent of the port type (DC or AC) or the power direction (input or output). Moreover, the proposed approach mitigates the problem of limited power factor in earlier studies and extends it to a full range operation by defining 12 new operating zones. The effectiveness of the presented modulation scheme in this work is verified through simulation and experiment.
GaN-HEMT Power Module Structure with Single-sided and Double-sided Aluminum-Clad Printed-Circuit Boards for Small Power Loop Inductance and High Cooling Performance

Gallium nitride high electron mobility transistor (GaN-HEMT) is attractive for fast switching capability and small on-resistance, which motivates researchers to adopt GaN-HEMT for high-power applications. High-power application of GaN-HEMT requires small power loop inductance to suppress switching surge under fast switching but also requires a large power module size for sufficient cooling performance by heat spreading, which results in large wire length and increases the power loop inductance. This paper addresses this problem by proposing a module structure with small power loop inductance and high cooling capability. The proposed module structure incorporates double-sided and single-sided aluminum-clad printed-circuit boards (PCBs) that sandwich the switching devices. These PCBs offer double-sided cooling and small power loop inductance owing to the eddy current generation inside the aluminum clad. A 3kw half-bridge prototype module was constructed to test the proposed structure in comparison with the preceding module structure, which incorporates the double-sided FR4 PCB for the power circuit and the single-sided aluminum-clad PCB for heat spreading. The result successfully revealed that the proposed structure exhibited a small power loop inductance of 1.4nH and a small thermal resistance of 0.72℃/W, which indicates the reduction in power loop inductance by 53% and in thermal resistance by 20%.
Achieving Low Thermal Stress in a PCB/AMB Hybrid SiC Power Module Using Fluidic Connections Based on Liquid Metal

Due to the mismatch of coefficient of thermal expansion (CTE) among different material layers, power modules are usually under substantial thermomechanical stress during operation. This problem becomes more significant for silicon carbide (SiC) power modules because the Young’s Modulus of SiC crystal is very high. To tackle this problem, this paper utilizes liquid metal (LM) as the interface material inside a PCB/AMB hybrid SiC power module. The LM layer not only acts as a thermal interface material, but can also conduct the drain current of the device. Compared with solder which is a rigid connection, LM is a fluidic material that can decouple the strain between the die and the AMB substrate while maintaining the thermal and electrical connection. FEA simulations show that the thermal stress caused by the mismatch of the CTE is reduced by 83%. Sample modules are fabricated and tested, revealing that the LM connection can provide the same electrical and thermal performance as solder. This article reveals the potential of using fluidic interconnection inside SiC power modules, providing a new solution to improve their reliability without adding complexity and cost.
Battery Charging Strategy of Electric Vehicles

With the rising popularity of portable electronic gadgets, electric vehicles, and renewable energy storage applications, there is a greater need for efficient and dependable battery charging solutions. This paper discusses a method for designing battery charging systems, with an emphasis on enhancing charging effectiveness and overall performance. To optimize the charging process, the suggested system combines cutting-edge technology such as power electronics and control schemes. Focus areas include battery longevity, charging time, safety, and compatibility with different battery chemistries. To reduce charging time while maintaining battery health, charging algorithm using Arduino is also used to dynamically modify charging parameters while taking into account battery characteristics, state of charge (SoC), and temperature.
Fault Diagnosis and Current Estimation of Current Sensors for Asynchronous Motors Based on Student’s T Distribution

The asynchronous motor system performance will deteriorate significantly when the current sensor is faulty. And because the asynchronous motor has the characteristics of nonlinearity and high coupling in practical application, the system noise is generally non-Gaussian noise. So, it is of good meaning to discuss the current sensor fault diagnosis and correction problem of the asynchronous motor in the case of non-Gaussian noise. Firstly, coordinate transformation is used to determine whether the current sensor is breakdown. When both two-phase current sensors are faulty, a new kind of current estimation method is designed, for the asynchronous motor system with the noise satisfying the Student’s t distribution. A non-Gaussian current sensor correction method is given to obtain the state estimate of phase current and replace the measurement of the current sensor affected by the fault. The given method is compared with the pre-existing Luenberger observer. Simulation results indicate that the designed method has the advantage over the Luenberger observer.
Distributed Control Strategy Based on Line Impedance Identification for Reactive Power Sharing in Microgrid

In microgrids (MGs), general distributed control schemes cannot achieve both accurate power sharing and voltage recovery under the unknown and difference of line impedances. To solve this problem, a new two-level scheme based on line impedance identifications and distributed communication is proposed for AC microgrids with any line impedances. Firstly, a distributed estimator is designed to identify the bus voltage and line impedance parameters. Secondly, a unified droop control based on line impedance estimation is proposed to achieve reactive power sharing without considering line impedances mismatching. Finally, a distributed compensation protocol based on bus voltage identification is presented, and accurate voltage recovery and reactive power sharing for AC microgrids are obtained. Small signal stability analysis and simulation results verify the effectiveness of the proposed strategy.
Enhanced Precision in Frequency and Phase Spectrum in Optical Frequency Domain Reflectometry Using Zoom-FFT Based Spectrum Refinement

We present optical frequency domain reflectometry relying on frequency spectrum refinement based on zoom fast Fourier transform. Without posing sacrifices in the processing consumption, this frequency domain processing allows improving the precision in the frequency and in particular, phase spectrum. Both numerical and experimental demonstration have been carried out, testifying the estimation of frequency, amplitude, and phase with an improved error performance.
Design of a Compact Line-of-Sight Rectenna for Wireless Power Transfer Systems

This paper presents the design of a compact line-of-sight rectenna system for wireless power transfer and energy harvesting applications. The proposed rectenna consists of a highly-directive Vivaldi microstrip antenna and a voltage doubler rectifier circuit assembled in the same double-sided copper fiberglass substrate. To achieve the established requirements for the antenna, a mixed optimization process is proposed by using alternately two techniques: Particle Swarm and Covariance Matrix Adaptation Evolution Strategy. In addition, to limit the rectifier output current, a buffer circuit is proposed to interface the rectifier output and the load. Finally, the proposed methodology and the designed rectenna are numerically and experimentally characterized, and the obtained results confirm the system’s capacity to power low-consumption loads.
A Dual Power Path DC-DC Step Up/Down Partial Power Converter for Electric Vehicle Fast Charging

In this paper, a new DC-DC step up/down partial power converter (SUD-PPC) topology is proposed for fast charging of electric vehicles (EVs). A fast charging (FC) architecture with a variable DC-link voltage is considered to overcome the mode transition challenges in SUD-PPC. The proposed DC-DC topology consists of a three-winding high frequency transformer (HFT), two MOSFET full bridges, one diode full bridge rectifier, and two series LC resonant tanks. The proposed circuit has two operating modes, namely, step-up (SU) and step-down (SD) modes. These modes are achieved through two decoupled power flow paths. The operation of proposed SUD-PPC topology and design method are discussed in detail. A simulation model of the proposed SUD-PPC with the variable DC-link FC architecture is studied for charging a 750 V EV battery at a constant charging current of 100 A. The simulation results are also discussed in detail and the converter performance is validated.
Facial expression recognition using LBP and CNN networks integrating attention mechanism

In order to improve the accuracy of facial expression recognition, a novel method integrating attention mechanism on LBP and CNN networks is proposed, and verified on public datasets. The self-built attention mechanism can help the model automatically select and focus attention on the most informative areas in the image, so as to improve the recognition performance of the model for key areas, and then improve the accuracy of recognition. Firstly, the public dataset is preprocessed. Local Binary Pattern (LBP) is used to obtain local texture features. The resulting dataset of LBP features is randomly scrambled multiple times. The attention mechanism is embedded in the CNN, and the Adam optimizer is used to train and verify the scrambled dataset every time. The FER2013 dataset, CK dataset and JAFFE dataset are experimentally evaluated and the recognition rates of 71.29%, 99.48% and 90.70% are obtained, respectively. Comparative experiments show that the method based on attention mechanism has high recognition accuracy and robustness in facial expression recognition tasks. It has obvious advantages over traditional facial expression recognition methods. The results of this research are expected to have important application value in the fields of affective computing and human-computer interaction.
Design and Implementation of Free-Eye of Flexible Underactuated Rope-Driven Manipulator for Line-Tracking Vehicle

With the rapid development of subway construction, different forms and different degrees of tunnel and underground engineering disasters occur every year, such as collapse, water inrush, rock burst and gas leakage, contact line failure, etc. Therefore, the robot arm Free-eye that can carry a camera for flexible observation can be realized through a smaller weight and simple mechanical structure, which is of great significance for the realization of the patrol intelligent vehicle and the replacement of the patrol intelligent vehicle for the detection of the contact net, the rail bed and the tunnel lining of the subway tunnel. In this paper, a flexible underactuated rope-driven manipulator free eye is proposed, which consists of multiple manipulator nodes, a flexible shaft, and a camera, and is controlled by four wire ropes and four stepper motors. The main work of this paper is as follows: 1) Design a flexible underactuated rope-driven manipulator free eye. 2) Use Solidworks to complete the 3D modeling and physical construction of the manipulator. 3) The kinematic space mapping method is used to model the motion and control of the manipulator. 4) The driving test, control test and photo test were carried out respectively. The position of the flexible underactuated rope driven manipulator can be controlled with an error of less than 10 degrees when the bending Angle is less than 100 degrees, and the accurate photo can be completed.
Parametric Vector Fitting Applied to the Analysis of Arbitrary field-to-line coupling

In this paper, parametric vector fitting is applied to solve the coupling between arbitrary plane wave and circuit. The calculation results from full wave and parametric vector fitting on linear and nonlinear loads are compared. The validity of parametric vector fitting is verified by solving the response of an active circuit exposed to the irradiation of plane waves from different directions
A Universal Modeling Framework for Real and Virtual Energy Storage

Energy storage equivalent circuit models are commonly used in design as they represent various physics or chemistries in a way familiar to power system engineers. However, the wide variety of employed circuits makes it challenging to identify the capability and transient response of energy storage and convolutes the comparison of storage options. Virtual energy storage, an aggregation of controllable loads, also currently lacks a modeling approach analogous to real storage. This paper proposes a universal energy storage model that represents both real and virtual storage—abstracting away the virtual storage power electronics while maintaining the system dynamics. This work demonstrates how the universal model can represent virtual energy storage and how existing battery and supercapacitor models can convert into the universal model. A comparison to switching models demonstrates the efficacy of the proposed universal model.