Miracle-dz/UniFAR-FTUs huggingface dataset:
Identifying Regions-of-Interest and Extracting Gold from PCBs Using MHz HIFU

Increased digitalization and technological development raises the demand for rare and precious metals (RPM). Due to their rarity, mining RPMs from the earth is becoming increasingly difficult. Traditional urban mining methods to recover RPMs from printed circuit boards (PCB) need to separate the RPMs from non-metallic substances, e.g. plastic. This separation requires toxic substances and causes unwanted and toxic by-products and emissions. The ability to identify regions-of-interest on PCBs, i.e. the gold pads, and to extract RPMs from only the desired areas would reduce the need for toxic substances. In this study, a single 12 MHz high-intensity focused-ultrasound transducer was used to 1) image a PCB to locate the gold pads, and 2) to subsequently induce inertial cavitation to remove gold from three extraction areas on the selected gold pad. The sonication was performed in water without additional chemicals. Gold removal was verified by imaging the pad with a coded-excitation scanning acoustic microscope ($f_{c} = 375$ MHz). Average areas and volumes of the three extraction regions were $A= (12.2 \pm 0.5). 10^{3}$ µm2 and $V=(18 \pm 2). 10^{3}$ µm3, respectively. The total amount of removed gold and nickel (from beneath the gold plating) from all three extraction areas was estimated to $m_{Au, tot}= (570 \pm 20)$ ng and $m_{Ni, tot}= (440 \pm 30)$ ng. This study constitutes a first step towards more environmentally friendly, non-toxic urban mining of RPMs.
Parameter Design Optimization for DC-DC Power Converters with Deep Reinforcement Learning

The deep deterministic policy gradient (DDPG) algorithm, a reinforcement learning (RL) technique which trains an agent to achieve the maximal reward by interacting with the environment, is applied for parameters optimization for a DC-DC power converter. A model for evaluating the efficiency of both semiconductor and magnetic components is developed. An artificial neural network (ANN) is trained by data from Spice simulation to establish a fast and accurate model for semiconductor losses. In the meantime, magnetic design is conducted by considering various core shapes, materials, winding turns, and airgaps. Finally, DDPG is trained by the combined efficiency evaluation model. The results indicate that the ANN model for semiconductor losses is accurate and the optimal design is obtained quickly by the trained DDPG algorithm.
The Impact of Operating Conditions on the Maintenance Interval of Trucks Equipped with a Computerized Maintenance Management System

In modern conditions, an increasing number of trucks and special construction and agricultural equipment manufacturers are using new computerized maintenance management system (CMMS) instead of maintenance system with rigidly set intervals for mileage or equipment operation in hours. The latter allow use of individually adjustable maintenance systems for equipment that determine maintenance intervals depending on actual load on equipment and its operating conditions. From point of view of work practice, there is currently insufficient information on the final results of these systems operation, depending on changes in operating conditions and modes of equipment use. The article analyzes data on 22 units of Mercedes-Benz Arocs and Mercedes-Benz Actros trucks for 180-250 ths.km. mileage and service maintenance on them, service intervals are shown, influence of operating conditions on them is analyzed, and mathematical models for assigning maintenance intervals are built.
Compact Tri-Band Two-Element MIMO Slot Antenna for 5G Sub-6 GHz Frequency Bands

in this paper, a compact two-element triple band, multiple-input multiple-output antenna for fifth-generation (5G) New Radio (NR) sub-6 GHz is presented and discussed. The single-element antenna consists of a $50 \Omega$ microstrip feed line where three open-ended slots are etched on the ground plane (DGS). The proposed 2-elements MIMO antenna has dimensions of $34 \times 32.5 \times 1.57$ mm3. A wide slot is cut off between the two ports to reduce the mutual coupling in the structure. Operating bands of the proposed MIMO structure are obtained from 2.23 to 2.50 GHz, 3.53 to 3.71 GHz and 5.46 to 5.84 GHz with relative bandwidths of 11.42 %, 4.97 % and 6.7 %, respectively. The minimum isolation for the entire frequency operating band is greater than 18 dB. Diversity performance (ECC, DG, etc.) is calculated and analyzed from the simulated and measured S-parameters. The obtained results are compared with other works published recently.
A 22.8 GHz to 32.8 GHz Compact Power Amplifier with a 15 dBm Output P1dB and 36.5% Peak PAE in 65-nm CMOS

A CMOS broadband millimeter-wave power amplifier (PA) based on a Sandwiched Transformer (ST) output matching network is presented in this paper. The ST output matching network with a three-layer structure providing a larger coupling coefficient (k) than the traditional two-layer stack structure is proposed for PA's output matching network. The layout of the transistors is optimized to improve the PA's performance. Fabricated in 65-nm CMOS process, the PA has achieved 15 dBm OP1dBand 36.5% peak power added efficiency (PAE). The 3-dB bandwidth of the PA is from 22.8 GHz to 32.8 GHz.
Rule-based Logical Reasoning Knowledge Extraction of Chinese Legislative Text

The Chinese legislative text contains a lot of legal logical reasoning knowledge to describe the code of conduct and the conditions for driving it. The development of the legal logical reasoning Knowledge Base is helpful to the legal knowledge consultation, and the prediction of the legal consequences caused by the behavior. In this study, we use the Civil Code of the People's Republic of China (CCPRC) as the main corpus to analyze the conditional logical reasoning relations and the characteristics of its trigger words and generate rules for extracting conditional logical reasoning knowledge. Finally, we verify the effectiveness of the rules in the Chinese legislative text.
Optical polarimetry and photometry of young sun-like star LO Peg

Abstract We have carried out the B,V and R-band polarimetric and V-band photometric study of the star LO Peg. Our analysis reveal that LO Peg is highly polarized among the sun-like stars. The degree of polarization and polarization position angle are found to be rotationally modulated. The levels of polarization observed in LO Peg could be the result of scattering of an anisotropic stellar radiation field by an optically thin circumstellar envelope or scattering of the stellar radiation by prominence-like structures. The long term photometric observations of LO Peg indicate three independent groups of spots are present on the surface of LO Peg.
Deep Learning on Energy Harvesting IoT Devices: Survey and Future Challenges

Internet-of-Things (IoT) devices are becoming both intelligent and green. On the one hand, Deep Neural Network (DNN) compression techniques make it possible to run deep learning applications on devices equipped with low-end microcontrollers (MCUs). By performing deep learning on IoT devices, in-situ decision-making can be made, which can improve the responsiveness of such devices to the environment and reduce data uploading to edge servers or clouds to save valuable network bandwidth. On the other hand, many IoT devices in the future will be powered by energy harvesters instead of batteries to reduce environmental pollution and achieve permanent service free of battery maintenance. As the energy output of energy harvesters is tiny and unstable, energy harvesting IoT (EH-IoT) devices will experience frequent power failures during their execution, making the software task hard to progress. The deep learning tasks running on such devices must face this challenge and, at the same time, ensure satisfactory execution efficiency. We believe deploying deep learning on EH-IoT devices that execute intermittently will be a challenging yet promising research direction. To motivate research in this direction, this paper summarizes existing solutions and provides an in-depth discussion of future challenges that deserve further investigation. With IoT devices becoming more intelligent and green, DNN inference on EH-IoT devices will generate a much more significant impact in the future in academia and industry.
High performance large-area polymeric PMUT phased arrays in air

Airborne ultrasound applications such as mid-air vibro-tactile haptic feedback, acoustic tweezers, and touchless gesture recognition require high pressures at low ultrasonic frequencies. Current solutions for such applications include large standard bulk piezoelectric and relatively expensive and small silicon-based micromachined transducer arrays. In this study, we demonstrate the capability of flat-panel display compatible large-area thin-film polymeric PMUTs for the purposes of air-coupled high fill-factor ultrasound transducer arrays. Annular PMUT array designs were optimized via simulations and fabricated on glass wafer substrates. An optical microphone was used to perform high resolution measurements of generated acoustic focal and trap fields. Focal pressures of up to 1.1 kPa (at 30 mm) and 1.6 kPa (at 20 mm) were generated in air at 229 kHz and 390 kHz respectively demonstrating the capability of using large-area PMUTs for practical airborne applications.
Multi-objective Optimization Hardening Design for Multiplier Circuit

Soft error has been a major reliability issue in advanced technology nodes. Mitigating soft error rate (SER) will bring great area and power overhead inevitably. This paper makes several improvements to a multi-objective optimization framework based on Bayesian optimization. A scheme incorporating Affinity Propagation (AP) and a novel sorting algorithm is proposed to cluster and sort the flip-flops (FFs), which ensures that the framework is suitable for large-scale circuit design. Results show that the scheme proposed in this paper performs better than the reference work. By employing the framework on multiplier hardening designs, a 78.3% reduction in SER is achieved with an acceptable increase in area and power consumption.
Probabilistic Capacity Planning Framework for Electric Vehicle Charging Stations with Overstay

Public charging stations provide charging services as well as parking for the growing population of electric vehicles (EVs). Effective management of these facilities is becoming crucial, with a significant proportion of drivers remaining parked even after the services are completed. This phenomenon, known as overstay, results in an underutilization of station resources and becomes a barrier to other electric vehicle drivers seeking charging services. To that end, this article presents (i) stochastic modelling of charging stations with overstaying customers, and (ii) a methodology to calculate station capacities with respect to a performance metric probability of loss of load that represents the percentage of unsatisfied demand. The station model is constructed using a two-dimensional Markov chain reflecting interactions among the “idle”, “charging”, and “overstaying” customers. Initially, a generalized small-scale charging station model is studied to investigate the behavior of the station parameters. Then, the general model is extended using the statistical large deviation theory to cover the case of large-scale charging stations. Effective demand, a deterministic quantity, for each charger is calculated, and station capacity is calculated in terms of the abovementioned performance metric. The case studies demonstrate that calculating effective demand-based capacity leads to substantial savings when provisioning station resources. However, a significant proportion of these savings diminish with increasing rate of overstay customers and durations.
Hybrid Optimization Method for WSN Data Collection using Mobile Sink based on TSP Approach

The path chosen by the mobile sink for data collection in a wireless sensor network must be the shortest possible path to reduce the data collection delay and data loss through buffer overflow. Finding the shortest path is a typical traveling salesman problem (TSP), which is a NP-hard combinatorial optimization problem. This work proposes the HWOAGWO algorithm which is a hybrid form of whale optimization algorithm (WOA) and the grey wolf optimization (GWO) algorithm to solve the TSP problem efficiently. Dimension learning based hunting strategy is used to avoid the algorithm getting trapped in local optima and slow convergence. Finally, simulation is used to prove that the proposed HWOAGWO algorithm is better at obtaining the best pathway over the other state-of-the-art algorithms. The algorithm is also tested in a real-time outdoor environment to prove its reliability.
Analysis of the Refrigeration Performance of the Refrigerated Warehouse with Ice Thermal Energy Storage Driven Directly by Variable Photovoltaic Capacity

An independent solar photovoltaic (PV) refrigerated warehouse system with ice thermal energy storage is constructed in this paper. In this system, the vapour compression refrigeration cycle is directly driven by a PV array, and the frequency of the compressor varies with the solar radiation intensity. The refrigeration performance and the matching characteristics of the system driven by different PV capacities are studied. The results show that the intensity of solar radiation required for the compressor to work at the same frequency decreases by approximately 7.8% when the ratio of PV capacity to compressor-rated power increases by 10%, and the time required for the temperature in the refrigerated warehouse to drop from ambient temperature to 0°C is reduced by 32 min on average. The energy efficiency ratio of the vapour compression refrigeration subsystem and the coefficient of performance (COP) of the refrigerated warehouse system increase with the ratio of PV capacity to compressor-rated power α. When α increases from 1 to 1.3, the growth rate of the COP is very slow. For the PV direct-drive refrigerated warehouse system with a compressor-rated power of 4.4 kW, the suitable ratio of PV capacity to compressor-rated power α is about 1.3. When the refrigerated warehouse system is driven directly by a 5.4 kW PV array, the overall COP is approximately 0.19. In the cycle mode of refrigeration and cold energy storage during the day and cold energy release at night, the stored cold energy can still meet the refrigeration required by the load for 48 hours after eight days of continuous operation. According to the current market price of cold storage, during the service life of the system, the income per unit volume of cold storage is about 2.2 times the investment.
Stability Assessment Study for a Triple-Stage Three-Phase Solid-State Transformer

This paper proposes an accurate stability and performance analysis for a triple-stage three-phase modular solid-state transformer (SST), based on the cascaded H-bridge (CHB) and on the dual active bridge (DAB) topologies. The control strategy of this system consists of a complex multi-layer structure, mainly because of the need to balance the various dc-links of the converter. Such a complex system is highly prone to instability, both for the cascaded topology and for the control structure. In this paper, the small-signal modelling approach and the Middlebrook's criterion are used to address the stability issues of the converter. For this purpose, the small signal model for each converter stage is developed and through those the SST impedance transfer functions are derived. To validate the theoretical impedance equations, a numerical simulation has been carried out in order to map the frequency response of the converter stages. Then, the stability of the whole system is discussed, pointing out what parameters may cause instability in the analyzed SST system. Four relevant case studies corresponding to four different operating modes are assessed and verified via Simulink simulations.
Analyzing the 2nd Harmonic Emissions of a BAW Resonator Undergoing Lateral Mode Excitation

For the first time of which we are aware, high frequency resolution phase and magnitude measurements of the 2nd harmonic (H2) emissions response of a BAW resonator are recorded and analyzed. A circular resonator exhibiting distinct lateral modes and H2 emissions rattles is analyzed in a variety of ways: First using a nonlinear extended BVD model to relate both the phase and magnitude of H2 emissions to its linear S11 response, then via an analytical model of H2 emissions, and finally via a nonlinear 2D FEM model. The H2 phasor emissions of a resonator having a practical shape, and thus exhibiting complex lateral mode and H2 rattle behavior is measured. A measurement-based H2 model is constructed, and then is used to model the H2 emissions response of an anti-series resonator pair.
Production and beaming of pulsar gamma-ray emission

There are now known to be four pulsars that emit pulsed . gamma. -rays in addition to the usual radio emission. Of these four, two are normal radio pulsars with periods on the order of 0.5 s. The other two are the Crab and Vela pulsars with very short periods. For one of the ''normal'' radio pulsars, PSR 1747--46, and for the Vela pulsar, the . gamma. -ray pulse lags the radio pulse. The . gamma. -ray pulse precedes the radio pulse for the other ''normal'' radio pulsar, PSR 1818--04. At low energies the . gamma. -ray emission from the Crab pulsar is in phase with the radio and optical emission and appears to be an extension of the pulsed X-ray spectrum. However, at high energies, above 10/sup 11/ eV, there is evidence for pulsed emission with variable phase but lagging the main optical pulse. It is shown that the observed . gamma. -ray emission can originate at or near the pulsar's surface and that radio emission should originate at some distance above the surface. The phase difference between radio and . gamma. -ray pulses can be understood as resulting from magnetic field configuration and aberration effects. It is also shown that the high-energy . gamma. -ray emission from the Crab pulsar cannot bemore » produced in this fashion, but is probably due to emission from high-energy particles at the light cylinder. « less
Optimal Scheduling of on-Street EV Charging Stations

The uncoordinated charging of Electric Vehicles (EVs) into the grid increases the stochastic rebound peak on the grid. These charging demands can strain grid equipment at the street charging points in an area. In this study, a smart coordination approach is proposed for charging process management by considering the parking times of EVs. EV types with different characteristics are used in the smart coordination approach. This approach limits the charging powers to the minimum value between the charging point and the EV maximum power ratio. Also, the approach using quadratic programming (QP) for charge scheduling of 20 EV minimizes the cost of daily charging via the Generic Algebraic Modeling System (GAMS). The results show that EV charges occur within the maximum allowable grid limits, reducing the cost of charging. Additionally, the proposed smart coordination prevented the occurrence of daily on-grid rebound peaks at street charging points in the area.
Optimizing microstrip antennas and antenna arrays using evolutionary algorithms

This paper uses a genetic algorithm to present the mechatronics engineering approach challenges of a 5.1 GHz linear array patch microstrip antenna (PMA). The PMAs are critical elements of the sensor and communication devices of the Cyber-Physical Systems (CPS). To find the optimum among differently oriented CPS antenna pattern requirements such as antenna beam control of physical radar emissions and receives in complex environmental conditions or interference mitigation can be found effectively using evolutionary algorithms. The presented method investigates, produces, and breeds PMA layouts for expected antenna performance while keeping the complexity of the code as low as possible and ensuring ease of manufacture. Furthermore, the unique PMA layout provides a direct insight into the workings of the optimization process, which shows added educational potential.
5 GHz Lamb wave Wi-Fi channel filters

Lamb-wave resonators offer the possibility to adjust their resonance frequency by varying the period of their inter-digitated electrodes. Leveraging the high frequency operation of the first antisymmetric mode in thin film lithium niobate membranes, this opens perspectives towards the cointegration of several filters operating in the 4–7 GHz range on the same die. To demonstrate this, we designed and fabricated a set of channel filters for the 5 GHz Wi-Fi standard. Resonators exhibit frequencies varying from 5.1 to 5.6 GHz and electromechanical coupling ranging from 5.5 to 9% for electrodes pitches varying from 1.1 µm to 800 nm, with quality factors in the 400–600 range. 3 and 5-resonator ladder filters exhibit insertion losses close to 2 (resp. 4) dB and rejection of 20 (resp. 30) dB, mostly limited by the frequency positionning of the resonators and feedthrough capacitances.
Optimisation Techniques for Load Frequency Control

Stability is a crucial part when discussing power systems. It is the ability of a system to return to an equilibrium state after being subjected to a certain load perturbation. In this paper, the focus is on frequency stability, also known as Load Frequency Control (LFC). For this instance, two different power systems, namely a single source two area system and a multi-source power system were used. The aim is to design and apply three different control algorithms namely Equilibrium optimisation (EO), Grey Wolf optimisation (GWO) and Whale optimisation (WOA) to the two mentioned power systems and determine the most suitable one for LFC. The results obtained showed that all three algorithms were successful in improving the uncompensated response. Further in-depth analysis which was related to the fitness function found that the Equilibrium optimisation was the best among the three techniques due to its superior explorative behaviour.
Modified Hybrid Modulation Technique for Cascaded H-Bridge Converter with DC Bus Oscillation

Cascaded H-bridge converter (CHBC) has emerged as a popular multi-level converter (MLC) topology for interfacing a utility scale battery energy storage (BES) with the medium/high voltage grid. Conventionally, interface has been implemented by connecting battery packs (BP) to Single-Phase H-Bridge through bidirectional dc-dc converter (BDC) to form a battery module (BM) which then connected in series to form a leg of CHBC. This single-phase H-bridge interface employed in CHBC draws the ripple power from DC bus at twice the mains frequency. It results in oscillation on the DC bus voltage which adversely affects the quality of the output voltage. Another challenge with the grid connected BES control is the state of charge (SoC) balancing among the BP. To address either or both of this issue, additional intermediate converter interface is needed which affects overall system cost, efficiency, and reliability. This paper proposes volt-second (V-s) balance-based modified hybrid modulation technique (HMT) for CHBC that achieves both SoC balancing and reduction in harmonic from the output voltage despite the oscillations in the DC bus voltage of individual BMs. Proposed methodology works with existing CHBC based system and sensors with reduced dc bus capacitor. The proposed modulation technique is validated on 5-level CHBC on the Typhoon Real Time Simulator.