Miracle-dz/UniFAR-FTUs huggingface dataset:
Remote Sensing Based Crop Type Classification Via Deep Transfer Learning

Machine learning methods using aerial imagery (satellite and unmanned-aerial-vehicles-based imagery) have been extensively used for crop classification. Traditionally, per-pixel-based, object-based, and patch-based methods have been used for classifying crops worldwide. Recently, aided by the increased availability of powerful computing architectures such as graphical processing units, deep learning-based systems have become popular in other domains such as natural images. However, building complex deep neural networks for aerial imagery from scratch is a challenging affair, owing to the limited labeled data in the remote sensing domain and the multitemporal (phenology) and geographic variability associated with agricultural data. In this article, we discuss these challenges in detail. We then discuss various transfer learning methodologies that help overcome these challenges. Finally, we evaluate whether a transfer learning strategy of using pretrained networks from a different domain helps improve remote sensing image classification performance on a benchmark dataset. Our findings indicate that deep neural networks pretrained on a different domain dataset cannot be used as off-the-shelf feature extractors. However, using the pretrained network weights as initial weights for training on the remote sensing dataset or freezing the early layers of the pretrained network improves the performance compared to training the network from scratch.
Measurement-Based Multi-link Massive MIMO Channel Characterization at Millimeter-Wave Bands

This paper presents a multi-user channel measurement campaign using a recently developed VNA-based multi-link channel sounder in an indoor hall scenario. The channel sounder architecture and comparison with the conventional multi-link channel sounder are firstly demonstrated, with a focus on the cost-effectiveness of the developed channel sounder. The two multi-user location combinations are considered in these channel measurements. The empirical channel data for the multi-user is then processed using the calibration procedure. By using the classical beamforming algorithm, the power-angle-delay-profiles (PADPs) are obtained from the calibrated channel response. The channel characteristics of the two links, i.e., PADP, delay and angular spread, are analyzed and compared.
Effects of an IC Chip on an Antenna-IC Transition at 100 GHz

This paper investigates the challenges and limitations an IC chip places for modeling a mm-wave antenna system. A compact differential antenna-IC transition suitable for antenna array applications at 100 GHz is presented. Challenges related to including the chip in the antenna design process are evaluated by analyzing the transition through EM simulations. The importance of the correct excitation method in the simulations is discussed, and different excitation port types and their locations are compared. Additionally, the effects of differently modeled IC chips, for example a simple silicon slab or partially metallic chip, are studied. Finally, recommendations for the combined antenna and IC chip simulations are given.
A Robust Voltage Sensor-Less Control for SiC Grid-Tied Inverter With Zero-Voltage Ride-Through

In this paper, a deadbeat control is proposed for a SiC grid-tied inverter to achieve voltage sensor-less, PLL-less and Zero-Voltage Ride-Through (ZVRT). In addition, an improved grid voltage prediction technology is introduced to enhance the robustness of the proposed deadbeat control which allows the voltage sensor-less PLL-less inverter to be operated under different grid impedance conditions. The operation principles of the proposed robust voltage sensor-less and PLL-less deadbeat control method are presented with the Lyapunov-based stability analysis. The proposed robust deadbeat control method has been implemented and verified on a 50kHz switching frequency SiC grid-tied inverter. The simulation and experimental results include low-voltage ride-through (LVRT) under large grid inductance are presented to verify its validity and advantages.
Cognitive Solution for NextGen Networks

In the era of Industry 4.0, business applications are becoming complex, and hosting platforms are becoming hybrid to achieve agility and cost optimization. Moreover, end-users are demanding secure connectivity with greater speed, intelligence and enhanced experience irrespective of their physical locations. Traditional networks are also transforming from one-to-many or many-to-one, to many-to-many form of connectivity, termed hyperconnectivity. To cater to the needs of end-users and business organizations, we propose ‘Hyper Connected Networks’. It is a complete horizontal solution framework applicable across various business verticals. The entire solution comprises three unique assets -Unified Network Service Platform which brings co-existence of legacy with the NextGen networks, Security Orchestrator which brings multiple vendor platforms under one umbrella, and a Cognitive Platform which brings vendor-agnostic and application-aware networking for Wi-Fi 5/6, 5G and beyond. These assets are designed using a microservices framework and hence can be easily extended to create on-demand solutions in future.
Discrete Turbulent Spectrum Modelling for 2D Split-Step Electromagnetic Propagation Schemes

The multiple phase screen method is widely used for modelling the electromagnetic propagation in a turbulent medium. In this technique, the turbulent phase screens are classically generated from a continuous Von-Karman Kolmogorov scintillation spectrum. Recent works led to the development of an auto-coherent split-step wavelet propagation method based on a discrete formulation of the parabolic wave equation. In this configuration, the use of continuous spectra is no more suitable. In this paper, we propose an auto-coherent generation method of the turbulent phase screens. To do so, a discrete formulation of the classical Von-Karman Kolmogorov spectrum is introduced. The impact of the modelled turbulence is finally discussed through the computation of the log-amplitude variance to validate this approach.
Indirect Detection of Gravitational Waves Method Validation Using an Analogue Electromagnetic Spacetime Modulated Medium

This manuscript studies the interaction between Gravitational Plane Waves and Electromagnetic Plane Waves by means of an analogous electromagnetic model of gravity, where the electromagnetic properties codify the variations in the metric tensor produced by the Gravitational Plane Wave. A space-time modulation of the electromagnetic properties of the medium is generated and analyzed via the Finite-Difference Time-Domain method. We find that, when a Gravitational Plane Wave interacts with a monochromatic Electromagnetic Plane Wave, it is triggered a multiple scattering of photons by gravitons resulting in the apparition of an infinite number of electromagnetic sidebands, equally separated between themselves by the Gravitational Plane Wave frequency. We numerically prove in this paper a totally novel effect that might be used in the detection of gravitational waves.
Research on Power Balancing Control Method of Distribution Network Considering the Integration of Distributed Photovoltaic

With the global transformation to clean energy, low-carbon and sustainable development, and the gradual reduction of the cost of distributed clean energy power generation represented by photovoltaic, the penetration ratio of distributed generation (DG) sustains to raise in the power distribution network. DG has strong intermittent, volatility and other characteristics, and it brings great challenges to the operation of smart grid. A distributed photovoltaic optimal scheduling method with equal reserve rate constraints is proposed. Taking the maximum distributed photovoltaic output, the minimum node voltage deviation, and the minimum line loss of network as the objective functions, taking into account the constraints such as power flow related equality and inequality constraints, photovoltaic output regulation constraints, and photovoltaic reserve rate constraints, a distributed photovoltaic scheduling optimization model for distribution networks is established. The model is solved relying on the improved Wolf Colony algorithm. Numerical results on IEEE 33-bus proved that the proposed method is fast and effective.
Surface Damage Detection for Bridge Cables Based on YOLOv7

There is a growing demand for automatic bridge cable inspection using intelligent detection technologies to replace manual inspection. However, the application of intelligent inspection systems is hindered due to the lack of effective cable damage detection methods. To resolve this issue, this paper proposes a surface damage detection method for bridge cables based on YOLOv7, a powerful real-time object detector. We introduce the basic algorithm of YOLOv7, and elaborate its training, transfer, and deployment methods for cable damage detection. A dataset is built containing 7548 cable damage images collected from real bridge cables. The results show that this method can effectively detect common bridge cable defects, including scratches, dirt, and abrasions. The proposed method achieved an F1 score of 0.75 and an mAP score of 0.799 on the test set. The incorrect predictions are mainly caused by slight and vague defects that can be either labeled or not labeled. The inference efficiency of the proposed method reaches 20.5 FPS for images with resolution of 640×640 when deployed with NVIDIA Triton. Considering the diversity of bridge cables in real-world scenarios, we have also conducted model transfer analysis to discover how much additional data is needed to transfer a pre-trained model for a new bridge, which provides a valuable reference for applying transfer learning technology on bridge cable inspection. The proposed approach is practically useful for assisting humans in data processing, reducing labor input significantly, and improving the objectivity and consistency of cable inspection.
Compressor using Cadence 180nm for Image Processing Applications

Magnetic Compressors play major role in image processing and microwave applications. AND-OR complex compound gates and XOR-XNOR modules are used to design compressor to achieve low power consumption and less hardware complexity using cadence 180nm technology. The waveforms of the compressor are analyzed for its better logical performance over conventional compressors.
Mutual Coupling Reductions of Dielectric Resonator Antennas without Extra Circuits

This paper describes an effective strategy to reduce the mutual couplings of dielectric resonator antennas without using extra circuits. The strategy is enabled by etching an elliptical cylinder in a cube-shaped dielectric resonator along its diagonal direction. By optimizing the dimension and location of the elliptical cylinder, the mutual coupling of the orthogonal polarizations of the dielectric resonator antenna can be effectively reduced. For demonstration, a cube-shaped dielectric resonator antenna operating at 5.8 GHz is configured with a proper elliptical cylinder drilled in the right position. The simulated results demonstrate the mutual couplings of the orthogonal polarizations can be reduced to -25 dB from 5.6 to 5.95 GHz, where an average of 8 dB mutual coupling reduction can be obtained compared to the one without the ellipse cylinder drilled. The radiation patterns, realized gains, and total efficiencies of the dielectric resonator antenna with the elliptical cylinder drilled can still be maintained, verifying the effectiveness of the proposed strategy to reduce the mutual coupling.
Robust Unity-Gain Transmitter-side Operation Mode in IPT Systems for Low Power Applications

Wireless power transfer has become a highly valued feature for users of portable electronic devices, which has contributed to a breakthrough in the improvement of this technology. In this paper, it is shown the analysis and implementation of two stable operation modes applied to low power inductive power transfer (IPT) systems. These operation modes do not require feedback from the receiver side because considers some parameters, such as the peak voltage across the compensation transmitter capacitor, to estimate the current through the resonant tank. The objective is to simplify the electronics required in IPT systems and to achieve proper operation, because this can be reflected in easy control, less time spent on designing with lower costs and shorter manufacturing time. In addition to the simplicity of the proposed systems, the build prototypes show high robustness to load variations thanks to the stability of the system when working at unity gain frequency.
Pesticide Maximum Residue Classification Prediction Based on Transformer

We propose a Transformer-based MRL classification prediction model to achieve an exploration of the relationship between MRL (maximum pesticide residue level) and agricultural and pesticide attributes from the data level. The model consists of a feature pre-processing module, an encoder and decoder module, and a multi-level classification module. We also constructed a dataset of MRL on pesticide and agricultural attributes. To address the problem of data category imbalance in the dataset, we mitigate the impact of data category imbalance through loss function focal loss and upsampling. Our proposed model achieves 75.13% accuracy on MRL data, which proves the value of our exploration of the relationship between MRL and agricultural and pesticide attributes.
Grasp Detection for Assembly Robots Using High-fidelity Synthetic Data

Artificial intelligence-driven collaborative robots (cobots) have attracted significant interest. Object perception is one of the important capabilities for robotic grasping in complex environments. Vision-based methods in the main perception tasks of robotic systems mostly require large pre-labeled training datasets. Building large-scale datasets that satisfy the conditions has always been a challenge in this field. In this work, we propose a robot vision system for robotic grasping tasks. The proposed system's primary design goal is to minimize the cost of human annotation during system setup. Moreover, since it is difficult to collect sufficient labeled training data, the existing methods are typically trained on real data that are highly correlated with test data. The system we presented includes a one-shot deep neural network trained with high-fidelity synthetic data based entirely on domain randomization to avoid collecting large amounts of human-annotated data and inaccurate annotation data in real world. At last, we build the vision system in the real environment and simulation with the robot operating system (ROS).
Group-Consensus of Hierarchical Containment Control for Linear Multi-Agent Systems

The existing containment control has been widely developed for several years, but ignores the case for large-scale cooperation. The strong coupling of large-scale networks will increase the costs of system detection and maintenance. Therefore, this paper is concerned with an extensional containment control issue, hierarchical containment control. It aims to enable a multitude of followers achieving a novel cooperation in the convex hull shaped by multiple leaders. Firstly, by constructing the three-layer topology, large-scale networks are decoupled. Then, under the condition of directed spanning group-tree, a class of dynamic hierarchical containment control protocol is designed such that the novel group-consensus behavior in the convex hull can be realized. Moreover, the definitions of coupling strength coefficients and the group-consensus parameter in the proposed dynamic hierarchical control protocol enhance the adjustability of systems. Compared with the existing containment control strategy, the proposed hierarchical containment control strategy improves dynamic control performance. Finally, numerical simulations are presented to demonstrate the effectiveness of the proposed hierarchical control protocol.
Fully Compensated Self-Resonant Coil with Low E-field and Low Profile for Consumer Electronics Wireless Charging

This paper details a fully compensated self-resonant coil (FSRC) with series LC resonance and reduced surface electric field for application in wireless power transfer for consumer electronics. By having a repeated series LC connection along the entire coil trace, the proposed series resonant structure achieves high-Q, low E-field, and thin profile simultaneously. The impact of ferrite shielding is also studied. Different E-field compensation coil geometries are studied, and a systematic design method is presented for optimal coil performance. Experimental tests verify the coil function, modeling, and design.
Quasi-Omnidirectional Millimetre Wave 5G Handset Antenna

This paper presents a handset antenna array operating within approved millimetre-wave 5G (mmWave) 3GPP n257 band 26.5-29.5 GHz and providing quasi-omnidirectional radiation characteristics. A 4 x 1 linear antenna array is placed into 3 distinct locations within a handset for testing against a numerical hand model which allows simulation of the effects of a user in a specific handset holding scenario. Blockages can cause significant degradation of the performance of the antenna, however, the optimized antenna locations presented achieved 52% coverage for gain values greater than 0 dBi, achieved using a 3bit phase shifter. Single 4x1 array characteristics were confirmed by far-field measurements. Beam steering characteristics are thoroughly investigated, showcasing how signal coverage can be improved in the event of a blockage. Study was also carried out into the effectiveness of increasing the size of multi-bit phase shifters and it is shown how improvement is negligible beyond a certain point.
Miniaturized UWB FSS for Space Shuttle Communication

An Ultra-wideband (UWB) Frequency selective surface (FSS) is proposed for Ku band space shuttle applications. A combination of circular loop (CL) on top layer and miniaturized square loop (MSL) on bottom layer of the substrate formed the proposed FSS. The FSS unit cell size is 5 mm x 5mm, which is designed on Fire-Retardant 4 (FR4) substrate with the thickness of 1.6 mm. The proposed FSS covers broad bandwidth range from 11.76GHz to 20.93GHz stop band frequency response. The FSS exhibits good angle of incidence and polarisation stability up to 60 degrees. The designed FSS is having a large fractional bandwidth of 9.17GHZ at -10 dB reference. We provide theoretical findings for both transverse Electric (TE) and transverse Magnetic (TM) polarisation at both normal and oblique incidence angles. For both straight-on and off-axis angles of incidence, theoretical results for TE and TM polarisation are presented.
Digital-Assisted Analog In-Memory Computing with RRAM Devices

In-memory computing (IMC) has been proposed as a solution to accelerate deep neural networks (DNNs) and other machine learning algorithms. RRAM-based IMC accelerators combine memory access and computation into the same array structure, saving a significant amount of chip area. However, the output from RRAM crossbar array requires an analog-to-digital converter (ADC) for further processing which causes the accuracy drop, extra power dissipation, and area overhead. In addition, the RRAM device also suffers from several nonidealities that degrade the accuracy. In this work, we propose a digital-assisted analog IMC architecture that combines analog RRAM-based IMC with the digital SRAM macro, using a programmable shifter, to compensate for the accuracy loss from ADC and the RRAM variations. By adding the precise output from the digital SRAM macro, the non-ideal output from the RRAM macro will be compensated. In this way, we achieve digital-assisted analog in-memory computing. We also designed a silicon prototype of the proposed hybrid IMC architecture in the 65nm CMOS process to demonstrate its efficacy. Our hybrid IMC architecture, evaluated through simulation on ResNet-20 with CIFAR-10, achieves a post-mapping testing accuracy to 91.15%, higher to that of the RRAM macro with 3-bit ADC, while requiring 1.19× smaller area and 1.90× less average power.
Beam-shaping of Wired Antennas through Huygens’ Metasurface Coatings

In this contribution, we discuss the possibility to exploit functionalized metasurface coatings wrapping wired antennas for manipulating their radiation pattern. Through a proper design of a cylindrical Huygens metasurface coat, the quasi-cylindrical wavefront of the field radiated by the antenna is locally transformed into a plane wave, leading to the generation of either multiple or single radiating beams from the original omnidirectional pattern. The semi-analytical model of the device is presented, and some relevant examples are provided. Finally, a realistic configuration of the device enabling reconfigurability of the antenna's radiation pattern is discussed.
A Self-Balancing Topology of Vienna Rectifier Based on PD Modulation

Vienna rectifier is widely used in high-voltage and high-power applications that do not require bidirectional power flow. As a three-level converter, the neutral point potential of Vienna rectifier inevitably needs to be controlled. In this paper, a neutral point potential self-balancing topology of Vienna rectifier is proposed. By connecting a small resonant capacitor in series with the neutral point of the filter capacitors, a series resonance at a specific frequency is formed. Combining the switching of traditional control strategies, the switches act to inject the DC zero-sequence component into the neutral point of the DC side capacitors. The existence of the DC zero-sequence component will cause the neutral point potential offset to tend to zero, so that the DC side capacitor voltages can be quickly evenly divided, and the neutral point potential can be self-balanced. The effectiveness of the proposed self-balancing Vienna rectifier topology is verified by simulation.
Compact End-Fire Arrays: from Theory to Directivity and Gain Maximization

End-fire arrays are among the best candidate for high directivity and compact dimensions. Several solutions for the synthesis of superdirective arrays have been proposed in the literature. However, what is called a "superdirective" array suffers inevitably from high losses and very poor radiation efficiency. More appealing is the joint optimization of directivity and efficiency, or the intrinsic gain, of the antennas. This paper set side by side the directivity and gain optimization methods based on the Spherical Wave Expansion (SWE) theory. The synthesis of superdirective and supergain end-fire arrays is proposed when Huygens sources, which attain the highest level of directivity, or simple bent dipoles are selected as elements of the array. On behalf of the spherical modal expansions, the results obtained for different optimizations of the two arrays are examined.
ZVS Clamp-Switch Quasi Z-Source dc/dc Boost Converters

This article proposes several modified quasi Z-source dc/dc boost converters. These can achieve soft-switching by using a clamp-switch network comprised of an active switch and a diode in parallel with a capacitor connected across one of the inductors of the Z-source network. In this way, ringing at the transistor switching node is mitigated, and the voltage at the turn-on of the transistor is reduced. Even a zero voltage switching (ZVS) of the main transistor is possible if the capacitor in the clamp-switch network is adequately chosen. The proposed circuit structure and operating mode are described and validated through simulations and measurements on a low-power prototype.