Miracle-dz/UniFAR-FTUs huggingface dataset:
AttenTPU: Tensor Processor for Attention Mechanism with Fine-Grained Padding

Transformer-based models have achieved state-of-the art performance in many Artificial Intelligence (AI) tasks. The core component of the transformer is the attention mechanism, which includes computation-intensive operators-such as MatMul and Linear-raising demand for hardware support. Many Institute, and researchers have proposed their hardware acceleration methods in recent years. However, most of these works mainly focus on algorithm optimization and hardware performance. Little attention has been paid to the variable sequence lengths in the attention mechanism. In the hardware design, the variability of sequence length brings a challenge to the load-store unit and on-chip data movement. In this work, we first propose a hardware-friendly fine-grained padding method aiming to handle the variability of sequence length in scaled dot-product attention. Then, a hardware architecture named AttenTPU is proposed using the padding method. The experimental results indicate that compared to the CPU and GPU platform, our accelerator achieves speed-ups of $3.43\times$ and $1.41\times$, respectively.
Adaptive Ambiance Mode For Noise Cancelling Headphones

This paper introduces a novel and robust model for ambiance mode in noise-canceling headphones. Prior to this study, the focus in this domain has primarily been on Active Noise Cancellation as a comprehensive solution to eliminate unwanted sounds. However, the ambient mode has traditionally been regarded as a conduit through which most surrounding noises pass through. Although a few techniques, such as Transparent mode, Voice pass, and sound control, exist for ambient modes, these approaches mainly aim to modify the level of noise cancellation and not the type of noise that a user must hear. To address these limitations, the present study proposes an Adaptive Ambiance Mode that leverages deep learning to classify audio signals and, based on the context, turns the Active Noise Cancellation on or off for a particular interval of time. In this regard, the paper categorizes ambient modes into three categories: Street Ambiance, Workspace Ambiance, and General Ambiance. A neural network is employed to classify the sound signals into three groups, yielding an accuracy of 93%. The Active Noise Cancellation component is implemented using the Least-Mean-Squared algorithm, which is highly effective, achieving a Karl Pearson's coefficient of correlation of 96.51%.
Comparative Study of Designing Compensators using Auto Tuning and Manual Pole Placement Techniques for Switch Mode Power Converters

DC-DC converters play a vital role in the electric vehicle (EV) industry in terms of delivering power at high efficiency. Preferably, these Switch Mode Power Converters (SMPCs) are operated in a closed loop for maintaining fixed output voltage irrespective of changes in the input voltage and output current. In this paper, a simple boost converter operating in continuous conduction mode (CCM) is designed to operate in a closed loop. The voltage controller for the closed-loop control is modeled and simulated using two methods viz; bode plot and auto-tuning techniques (build-it library in MATLAB / Simulink software). The compensator obtained using the bode plot technique is observed to be more realistic and reliable compared to that using an auto-tuned controller. The auto-tuned controller generates parameters (Kp and Ki) by choosing a region where the Phase Margin (PM) is highly positive, thereby decreasing the bandwidth (BW) of the system. This in turn results inlow cross-over frequency (fc), an increase in settling time, and overshoot.
Four-Port Converter Interfacing Two PV Panels, Load, and Bidirectional Battery

In this paper, a four-port converter (FPC) is introduced, which integrates a storage unit to improve power flow management in dual-input LLC converters. The proposed FPC topology and used modulation techniques are presented, demonstrating their effectiveness in enhancing power flow control. The performance of the FPC and its capacity to adjust to changing input sources and load demands are evaluated using a steady-state analysis that takes into account all potential power flow scenarios. The proposed FPC design’s validity and its ability to effectively manage power flow are supported by simulation results obtained using the PSIM software.
Functional Programming for the Internet of Things: A LoRa-MQTT Gateway written in Elixir

Networks for the Internet of Things typically use a gateway to provide connectivity between a low bit rate, low capability sensor network and the broader Internet. The gateway can be subject to very high traffic loads, many concurrent processes and needs to be highly reliable. Functional programming languages such as Erlang and Elixir have proven to be an effective programming paradigm for such scenarios, notably in large scale telecommunications switches. In this paper we report on our experiences of developing a gateway between a LoRa network and an MQTT broker using the functional programming language Elixir. Our experience suggests that the discipline imposed by functional programming results in a system that is more compact, supports concurrent processes well and is more reliable than similar systems developed using conventional languages. However, we also note that subsystems to support the development of such systems are primitive and that functional programming has a considerably steep learning curve. Nevertheless we conclude that functional programming has considerable potential for the Internet of Things and plan to continue research in this area.
A Decentralized Control for a Triple Active Bridge Converter Integrating PV and ESS

This paper introduces a decentralized control strategy for an isolated Triple Active Bridge (TAB) bidirectional converter integrating Photovoltaic (PV) and Energy Storage Systems (ESS). The proposed control method ensures a well-regulated DC bus voltage and is implemented using a decoupled control approach. The methodology considers variations in solar irradiation for PV and the State-of-Charge (SOC) of the ESS. In the proposed approach, when the ESS SOC is less than 100%, the PV output is maximized by operating it in maximum power point (MPP) mode and the ESS is charged or discharged based on load conditions. However, when ESS is fully charged, the control strategy switches PV operation to non-MPP mode, ensuring a well-regulated DC bus voltage. Switching simulations demonstrate the efficacy of the proposed method across a wide range of operating conditions for a TAB integrated into a DC microgrid (MG). Hardware experimental results further validate the performance and effectiveness of the decentralized control approach.
Ship Object Detection and Classification Based on Improved YOLOv5

In recent years, with the rapid development of the marine economy, maritime transportation industry has also steadily strengthened, leading to an increasing number of ships at sea. However, this growth has also raised safety risks for maritime vessels, making accurate and effective maritime vessel recognition technology essential for improving navigational safety. Presently, most target detection algorithms focus solely on improving model accuracy while neglecting the computational and parameter overheads resulting from the complexity of the models. To address this issue, this paper proposes an improved YOLOv5 object detection algorithm, utilizing MobileN et V3 for lightweight enhancements to minimize model size and computational demands. Additionally, to ensure model precision, Hybrid Channel Attention Mechanism (CBAM) is introduced. Experiments were conducted on the Seaships dataset, comparing the proposed improved YOLOv5 algorithm with YOLOv5 and Faster R-CNN algorithms. The experimental results demonstrate that the enhanced YOLOv5 detection network achieves accuracy of 99.1 % and mean average precision of 99.5%. Compared to other algorithms, it exhibits excellent detection performance.
A Power and Area Efficient Approximate Matrix Vector Multiplier using Stochastic Computing

This paper presents a modification of the existing stochastic computing based approximate multiplier using a different stochastically generated bit stream, which results in architectural level improvements and reduced power and area consumption while maintaining computation accuracy. The power and area efficiency of different approximated multipliers (AM) and their performances are compared with those of the existing works. Later the power consumption, hardware area requirements and performance of the proposed AM based matrix vector multiplication unit is also illustrated.
Efficient Implementation of Peak Detection Algorithm for X-Ray Fluorescence Systems

X-ray fluorescence (XRF) is the emission of characteristic “secondary” X-rays from a material that has been excited by high-energy X-rays. X-ray fluorescence systems are widely used for elemental and chemical analyses. In XRF systems, various techniques have been developed for the synthesis of pulse shapes using digital methods instead of traditional analog methods. The accuracy of XRF spectrometers can be improved using an appropriate trapezoidal pulse shaping method. In this paper, an efficient trapezoidal filter architecture is presented. In addition, we present a hardware-efficient peak value detection algorithm. By using the proposed algorithm, the peak value detection error is decreased up to 53.1% compared with the conventional algorithm. The proposed design was implemented on Altera Cyclone IV FPGA and successfully operated.
A Double-side Hybrid Control of Constant Voltage and Maximum Efficiency Tracking for Wireless Charging of EVS

For wireless charging of electric vehicles (EVS), the load resistance of the battery changes continuously during the whole charging process. While the system efficiency and charging voltage are highly dependent on the load conditions. Meanwhile, achieving maximum efficiency tracking (MET) and constant voltage (CV) output is difficult under variable loads and coil offsets. This paper proposes a double-side LCC-S system containing the primary side full bridge inverter and the secondary side semi-active rectifier (SAR) to ensure CV output and MET. Specifically, CV output and MET are realized simultaneously via SAR phase shift angle θ2 and high-frequency inverter shift angle θ1. After theoretical analysis, the LCC-S topology can realize MET when the formula partial ∂(sin(θ1/2)) /∂(sin(θ2/2)) is equal to σ/M. Finally, the proposed method is verified by constructing an experimental prototype of a 50V input and 68V output LCC-S system under the load resistance of 10-50Ω and the mutual inductance of 6-12μH. The results show that by adjusting θ1 to 60.31° and θ2 to 50.7 °, the system efficiency can reach a maximum efficiency point of 93.1929%, which is 6.8298% higher than without MET. The system can maintain CV output regardless of load changes and tolerate coil misalignment within a certain range.
A Decentralized Secondary Frequency Control Method Based on High-Frequency Small-AC-Signal Injection for Parallel Droop-Controlled Inverters

In an islanded microgrid composed of parallel droop-controlled inverters, the secondary frequency control without communication is important for mitigating frequency deviation. To achieve fundamental frequency restoration and power sharing among inverters, a low frequency small-AC-signal injection-based secondary frequency control (LF-SACS-SFC) method has been explored in existing works. However, some factors such as nonlinear load, the inverter dead time, asymmetric transformer current, etc., could produce lots of low-frequency harmonics. When the harmonic frequency is very close to the small-AC-signal frequency, the secondary frequency control performance would become worse. To avoid the interference introduced by the low-frequency harmonics, this paper proposes a high-frequency small-AC-signal injection-based secondary frequency control (HF-SACS-SFC) method, in which the frequency of the SACS is increased obviously to be much higher than the dominate harmonics. The HF-SACS-SFC can achieve power sharing and fundamental frequency restoration when low-frequency harmonics exist in the parallel inverters system. Furthermore, the operation principle of HF-SACS-SFC is analyzed, and the comparison between HF-SACS-SFC and LF-SACS-SFC is conducted. Finally, the simulation results demonstrate the effectiveness of HF-SACS-SFC.
Electromagnetic Transient Simulation Research on UHVDC Based on Synchronous Condenser

This paper builds an electromagnetic transient model of the UHVDC including synchronous condenser system in PSCAD. Due to its excellent dynamic reactive power compensation capability, Synchronous condenser technology has been widely applied in the East China Power Grid. The model is helpful for further study of the system voltage regulation and dynamic stabilization effects. The operation results show that the model reflects truly the actual situation and provide platform for further research on commutation failure and suppression measures.
Modeling and optimization of local oscillation signals for Nyquist Folding Receiver

Sensing broadband spectrum using a low-speed analog-to-digital converter is a challenge for reconnaissance receivers. Nyquist Folding Receiver (NYFR) proposed by Fudge's team, as one of the effective sub-Nyquist sampling schemes exhibits a lower system working frequency than most other schemes. NYFR relies on a local oscillation signal(LOS) to generate periodic non-uniform sampling pulses. The design of the LOS directly affects the system's overall performance, yet few studies are currently available. In this paper, we study the working model of the LOS, analyze several elements that affect the sampling performance, and optimize the LOS by taking the performance indexes as constraints. Theoretical derivations and simulation experiments show that the optimized LOS in this paper can produce better NYFR sampling waveforms with strong broadband signal processing capability and system robustness.
A Drone-Based 0.7-4.7 GHz FMCW Radar System for High-Resolution Exploration of Subsurface Glacier Structures

A majority of the studies on subglacial structure mapping and imaging have relied on low-frequency ground penetrating radar (GPR) systems. In particular, mapping alpine glaciers using surface-based high-resolution radar sensors poses a considerable threat to the operators due to crevasses or avalanches; this can be avoided by deploying an unpiloted aerial vehicle (UAV)-based radar sensor. Herein, we present an ultrawideband (UWB) bistatic frequency-modulated continuous-wave (FMCW) GPR for operation on a UAV. By using a UAV equipped with ultrawideband and extremely lightweight additively manufactured horn antennas at a bandwidth of 4GHz between 0.7 GHz and 4.7 GHz we acquired ultra-high-resolution images of the upper firn layers of an alpine glacier. The acquired measurements at the Jungfraufirn, Switzerland illustrate the out-standing performance of the overall system and its applicability in glaciological research.
Reinforcement Learning-Based Market Game Model Considering Virtual Power Plants

Virtual power plant (VPP) gathers various types of resources and is a new participant in the power market. The research on the market equilibrium state based on VPPs is helpful to analyze the problems existing in the construction of open power market. Based on the analysis of game behavior in power market, this paper constructs the decision-making models of VPPs and traditional power plants, and discusses the applicability of reinforcement learning in the bidding strategy of power producers. Based on this, a bi-level game model with VPPs is proposed. The model is solved iteratively based on the multi-agent reinforcement learning (MARL) method combining win or learn fast and policy hill-climbing algorithm, and the state space is compressed to improve the solution speed. Finally, through the example analysis, the results show that the proposed model and algorithm can effectively solve the optimal bidding strategy of VPPs and obtain the market equilibrium results. In the power market with constant total demand, VPPs have better resource integration and profitability than traditional power plants, and have higher adaptability to different power trading mechanisms.
Detecting Infectious Disease-Causing Bacteria from Gram Stained Smears Images

In this paper, we detect 13 kinds of infectious disease-causing bacteria from Gram stained smears images. As detectors, we adopt YOLOv5 and YOLOv7, and their improvements to changing an activation function from Swish to Mish and to add a “Squeeze-and-Excitation” block in front of the output layer. Then, we give experimental results of detecting them in Gram stained smears images and evaluate the results.
Load Commutation Switch for a Hybrid DC Circuit Breaker in Cryogenic Environment

Electric aircraft could significantly reduce carbon dioxide emission and achieve ecological and sustainable development objectives. Cryogenic and superconducting technologies have the potential to boost the development of electrical propulsion aircraft. However, the low impedance of DC networks could result in extremely fast rising DC fault current, which poses a substantial challenge for DC fault protection. Furthermore, the design of components capable of operating at cryogenic temperatures is another challenging task. This paper, for the first time, presents the design and experimental performance of a load communication switch (LCS) as key integral part of a high-current hybrid DC circuit breaker at cryogenic temperatures. A low-voltage silicon metal-oxide-semiconductor field-effect transistor (Si-MOSFET)-based load commutation switch has been built and experimentally tested in both room temperature and liquid nitrogen (LN2) bath. The experimental results show that the on-state resistance of LCS submerged in liquid nitrogen bath is as low as 23 μΩ, comparable with contact resistance of mechanical switches. Correspondingly, the conduction loss of the prototype LCS in LN2 is as low as 64 W at 1700 A, which is only 23% of power loss at room temperature. Meanwhile, the fast current commutation driven by the LCS from the mechanical switch to the main breaker during the fault current interruption has been successfully verified.
Advanced Primary-side Load Monitoring Schemes for Inductive Power Transfer Systems with Enhanced Nonlinear Rectifier Load Models

This paper is related to a general method to monitor the load conditions of direct inductive power transfer (IPT) systems at transmitter sides without any communications between the transmitters and receivers. The proposed method is established based on the analysis of IPT systems with full consideration of odd-order harmonics. Based on the derived enhanced nonlinear rectifier load model, the proposed load monitoring method performs superior accuracy than conventional load monitoring methods for IPT systems with light load conditions. Both simulations and experiments have been conducted to verify the effectiveness of the proposed primary-side load monitoring scheme. The results demonstrate that the proposed scheme significantly improves the estimation accuracy across a wide range of load resistances, from 10 Ω to 70 Ω.
Ground-based Surveillance and Classification Radar for Wildlife Protection

Wildlife poaching has become an increasingly large problem over the last decade in southern Africa. There have consequently been worrying declines in rhinoceros population levels. As part of a multi-year effort to investigate and develop technology to aid in the prevention of poaching activities, a C-band phased array radar, with integrated ground target classification capability, has been produced. In a field trial that took place in the Kruger National Park Game Reserve in South Africa, it successfully detected and classified human and animal movement at ranges of up to 10 km. The misclassification rate of humans was less than 7%, and non-human movement, predominantly from animals and vehicles, was incorrectly classified as human 3.8% of the time. This shows that modern radar, without assistance from other sensors, has great potential to contribute towards the preservation of scarce wildlife resources.
A Cable-Free Ironless Linear Motor with Power Provisioning Capability to the Payload

Cables typically connect to the movers of linear motors for power and communication, which can lead to additional drag, friction, vibration, maintenance, and limited working distances. By integrating wireless power transfer and linear motors, the latter can eliminate the need for cables or energy chains, thereby enhancing performance, allowing unlimited working distance, and reducing mover mass. The mutual inductance of transmitting and receiving windings plays a vital role in wireless power transfer systems. To maintain stable motion and electrical operation, the mutual inductance should not fluctuate excessively along the rail. Mathematical derivations for numerical evaluations have been derived to calculate the self and mutual inductances of rail transmitter and mover receiver rectangular windings and to model power performances. A prototype motor has been constructed to confirm the feasibility of this combination.
Comparison of Frequency Spectra for Micotremors, After Shocks (M=2.5-4.7) and the Main Shock of the Spitak Earthquake Obtained on Massive Lake-River Formations in the Region of Giumry (Armenia)

On December 7, 1988 a disastrous earthquake with magnitude M=7.0 took place in the northern part of Armenia, during which in Giumry (former Leninakan) large-scale destruction of standardized buildings with epicentral distance 35 km was observed. This forced us to set a task: to find connection between large-scale destruction and some dynamic peculiarities of grounds on the territory of the city. The present article makes an attempt to explain the significance of the upper engineering-geological stratum (20-30 m) and that of the lower massive lake-river formations. Basing ourselves on a great number of instrumental observations we tried to compare prevailing periods of ground microthremors with frequency spectra ofthe Spitak earthquake main shock and its aftershocks and to reveal connection between them in order to ascertain the significance of own prevailing periods of grounds on the territory of Giumry in the large-scale destruction during the main shock as well as to prove that they didn’t manifest themselves during the event. The obtained results can be applied to drawing up of new seismic microzonation maps not only for Giumry, but for an territories of other cities as well, which are situated on massive lake-river formations. Besides the results can benefit creators of normative documents on seismostable building.
A 16.5 mW 4.0 GHz Bandwidth VGA Based on Capacitance Neutralization Technique in 65 nm CMOS

This paper presents a wideband variable gain amplifier (VGA) based on capacitance neutralization technique for high-speed communications and high-resolution radar systems. The negative capacitance path proposed in this paper effectively compensates the output capacitance of the VGA, thus achieving the bandwidth extension. Furthermore, it ensures a flat gain over a wide bandwidth at different gain settings. The VGA is designed in a standard 65nm CMOS process. The simulation results demonstrate that the VGA achieves a -3dB bandwidth of more than 4.0 GHz with a wide gain range from -2.8 to 49.4 dB. Moreover, it consumes 16.5 mW at a supply voltage of 1 V and has a core circuit area of 0.006mm2.