Miracle-dz/UniFAR-FTUs huggingface dataset:
Implementation of Tiny Machine Learning (TinyML) as Pre-distorter for High Power Amplifier (HPA)Linearization of SDR-based MIMO-OFDM

This paper implements a new pre-distorter (PD) scheme using Tiny Machine Learning (TinyML) to compensate for the non-linear High-Power Amplifier (HPA) in the Software Defined Radio (SDR)-based Multiple-Input Multiple-Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM). TinyML is used because there are weaknesses in the PD neural network (NN), which has a large model size and high computational costs. Some research uses PDNN because it has flexible advantages and can provide the inverse characteristics of sophisticated PA modelling. Using PDNN in the SDR-based MIMO-OFDM will cause system degradation because the SDR device has low computational memory. The system degraded because the execution time of the transmitter was high, which affected the latency of the communication system. TinyML will reduce the complexity of the NN model, resulting in a smaller model size and a lower computational cost. The implementation of PD TinyML in SDR-based MIMO-OFDM can improve the execution time by 40% compared to the use of PDNN. Even though it has a lower execution time, TinyML can compensate for HPA and perform similarly to PDNN. The maximum SNR value of PD TinyML is only 2.07 dB, lower than the maximum SNR value of PDNN. In addition, the BER graph of PDTinyML’s SNR to achieve a minimum BER is 1.37 dB higher than PDNN. From this, the performance decrease in PDTinyML is not too significant.
Marine Jurassic pelecypods from central and southern Utah

_ __-_--___-___-_. Introduction. _____-_-_. __Biologic analysis___ ________ Stratigraphic considerations. Ages and correlations___ _. Carmel Formation. Arapien Shale. _______. Cl 1 1 2 3 3 5 Faunal associations and comparisons. Geographic distribution__ _ _ _______ Summary of results. _______________ Systematic descriptions. ____________ Literature eited____________________ Index. ___________________________ Page 06 8 22 23 38 41
Circular Ring Fractal UWB Antenna for Microwave Imaging Applications

In this work, an ultra-wideband (UWB) planar antenna design is presented that is suitable for microwave imaging applications. The radiating element is comprised of three connected rings connected through thin metallic strips that correspond to fractal geometry. The antenna’s bottom side utilizes a stair-shaped slot-based partial ground plane to achieve UWB response. The use of a stair-shaped slot also helps in achieving good impedance matching in the UWB frequency range. The proposed antenna design exhibits a total dimension of 18×20 mm2. An impedance bandwidth of ≈31.68 GHz is observed within the frequency range of 3.32 GHz ≈ to beyond 35 GHz. Furthermore, the proposed UWB antenna shows a fractional bandwidth (FBW) of 165.35% and a peak gain of ≈8.5 dBi within the desired operating range. It is evident from the results that the proposed antenna exhibits exceptional low-dispersive characteristics across a broad frequency spectrum, which makes it highly suitable for microwave imaging applications.
Improving The Performance of Cascade Vapor Refrigeration System by Using Al2O3 Nanoparticles

The utilization of cascade refrigeration systems in the frozen food industry has proven advantageous, as they offer improved reliability compared to two-stage refrigeration systems. This study focuses on inspecting the application of nanoparticles in cascade refrigeration system. This research is done to assess the impact of nanoparticles on refrigeration capacity, compressor power, and coefficient of performance (COP). Al2O3 nanoparticles with mass concentration of 0.1% and 0.2%. The system employed by R-134a and R-410a in the high and low circuits respectively. The system analysis was conducted with varying concentrations of nanoparticles Al2O3 in the R134a circuit. The presence of nanoparticles in the system led to increased refrigeration capacity, significant decrease on compressor powers and the system COP improved by 40.7%.
Wideband 5-bit Vector-sum Phase Shifter for 5G Millimeter-wave Applications

This paper presents a wideband 5-bit vector-sum phase shifter implemented in a low-cost 90-nm CMOS process. The proposed vector-sum phase shifter consists of a wideband quadrature generator with low amplitude/phase imbalance and a wideband, low-phase variation variable-gain amplifier integrated with 0/π phase shifter to satisfy most of the operation frequency bands of the 5G millimeter-wave communications. From 25 to 43 GHz, the proposed 5-bit phase shifter demonstrates the RMS amplitude/phase errors of better than 1.4 dB/4.8°, and the insertion losses of all states are lower than 6.4 dB from 25 to 43 GHz.
Institutional Alterations and Economic Growth --Focus on Hangzhou’s household (Hukou) registration system

In the recent three decades, the great development of China’s economy cannot separate from its institutional alterations. Hukou system, an institution with Chinese feature, is a kind of “passport” that admitted in the country. This thesis aims to investigate the Hukou system and its impact on labor migration, and more specifically, how Hangzhou’s Hukou system impacts local economic growth. The result shows that Hukou system manages the labor migration between rural-urban areas and inter-cities. Hangzhou’s slack Hukou system significantly and positively influences the Hangzhou’s labor mobility and economic growth.
Accurate Measurement and Control Sytem for RF Broadband Power Amplifier

A new measurement system has been developed for broadband RF power amplifiers dedicated to EMC applications. The system allows the power output of the amplifier to be measured while correcting the variations of broadband coupler’s frequency response. This is achieved by measuring, simultaneously, the power and the frequency of the RF signal. These measurements are made using a developed broadband RF frequency meter and a power detector. Tests are presented and carried out using industrial amplifiers to evaluate the proposed solution. Measuring the RF signal frequency passing through the amplifier is an additional information that allows more accurate power level measurement and improves the monitoring of the amplifier.
A PEEC-informed Deep Learning Approach for Inverse Electromagnetic Problem in Heterogeneous Integrations

In this paper, a partial element equivalent circuit (PEEC) informed deep learning approach is proposed for inverse electromagnetic scattering problems involving finite-sized dielectrics. To balance the enormous learning space and limited computation resources, a partial-relative-permittivity (PRP) model is proposed based on the compact PEEC model, which is capable to reveal the electromagnetic (EM) behavior of three-dimensional (3-D) heterogeneous structures by a 2.5-dimensional (2.5-D) representation. A tailored generative adversarial network (GAN) is developed to learn the intrinsic relation between the PRP model and the near-field information. To imitate the real-world phenomenon with adequate and accurate data, a dedicated training dataset is built numerically. With the GAN model, a PRP model can be interpreted from the measured phaseless magnetic fields at a single frequency, resulting in a broad-band c-PEEC model that is especially useful in power integrity and radiated emission analysis.
Design and Development of Wideband 2-Way Power Divider for Space Application

A compact and wideband two-way equal Wilkinson power divider with operating frequency range of 3 to 6 GHz for space applications using microstrip structure is presented in this paper. Compared with conventional microstrip power dividers, this power divider utilizes only single section and optimum impedance transforming network to achieve wide bandwidth. The limiting effect of isolation resistor pads is analyzed and the parasitic pad capacitances are compensated by the proposed structure. The power divider is realized on 25mil alumina substrate in small size of 12.5mm X 12.5mm. Broadband characteristic of the proposed power divider is verified by experimental results. Measurements of the fabricated divider showed input and output return losses better than 13dB with low insertion loss of 0.35-0.55dB and typical isolation better than 14dB over the design bandwidth.
Towards Surgical Skill Modeling in Cardiac Ablation Using Deep Learning

The most widely practised method for treating cardiovascular problems is minimally invasive surgery (MIS). The rising interest in surgical robots and simulations has led to a greater demand for more objective methods of skill evaluation. Traditionally, the performance of novices is evaluated using surgeons’ skills through a specific and streamlined ablation task. To this end, an experimental setup was proposed to provide a simulated ablation procedure through a mechanical system. It is equipped with the synthetic heartbeat mechanism of the heart with the capability of measuring the contact forces between a catheter’s tip and a force sensor. Using a commercially available catheter for ablation, the task was to maintain the force within a safe range while the tip of the catheter is touching the surface of the sensor. Accomplishing multiple experiments by novices and experts, a deep recurrent neural network was considered to extract the model of skills by solving a binary classification problem. The results of the trained model showed that the proposed pipeline was able to properly distinguish the novices’ from experts’ maneuvers with 95% accuracy.
Novel Two-Stage AC-DC Power Converter with Partial Single-Stage Power Processing

AC-DC power conversion is typically implemented with two converter stages: an AC-DC boost converter stage followed by a zero-voltage switching (ZVS) pulse-width modulated (PWM) full-bridge converter stage. An active auxiliary circuit is often used to reduce switching losses in the first-stage converter. The use of such a circuit to transfer a portion of the input power directly to the output of a two-stage AC-DC converter is investigated in the paper. Such direct power transfer (DPT) allows a portion of the power from the input to be processed only once, instead of twice, thus reducing the losses and the current stresses of the second-stage DC-DC converter. In this paper, the basic operating principles of the converter are explained, the features of the first-stage AC-DC boost converter are stated, and a set of guidelines for the design of the converter are given. The feasibility of the proposed converter is confirmed with experimental results.
Wideband Vertically Polarized Magnetic Dipole Antenna for MIMO Applications

In this paper, a mode-superposed wideband vertically polarized(VP) half-mode substrate integrated waveguide (HMSIW) antenna with a double-layered structure is proposed. The conventional HMSIW antenna can be considered as a magnetic dipole antenna. It is constructed with the help of a three-sided closed cavity and opened at one side, yielding a very low impedance bandwidth (IBW) (below 5%) for the profile below 0.038 λ0 (λ0 is the free space wavelength at the centre frequency). In order to enhance the IBW of the HMSIW antenna, a double-layered structure with an air gap has been incorporated. The half-TE110 and half-TE310 are the two adjacent modes of the HMSIW. So, in this manuscript by combining these two adjacent modes by placing the two pairs of slots at the null position of half-TE310, the IBW of VP magnetic dipole is further increased. The proposed structure provides 26.40% of impedance bandwidth and 3.8 dBi as a peak endfire realized gain with the dimension as 1. 259λL× 0. 363λL× 0.038λL. In order to design a four-port multi-input multi-output (MIMO) antenna, the proposed structure is arranged orthogonally. The proposed wideband VP MIMO antenna exhibit very good isolation, along with the MIMO parameters.
GAU-Net: U-Net Variant for Segmentation of Skin Lesion

Image segmentation of skin lesions is a critical component in the auxiliary diagnosis of medical-related diseases. However, traditional U-Net network methods struggle to achieve accurate segmentation results when presented with high-resolution skin lesion images, especially under small batch size training conditions. In this study, we propose a novel GAU-Net network that leverages the attention mechanism of mobile networks. Based on U-Net, the method employs Group Normalization and LeakyReLU activation functions in the convolution block to obtain normalized and reliable features, thereby enhancing the network’s ability to represent high-level semantic information. Additionally, the proposed method introduces Coordinate Attention to embed effective position information into the channel Attention, further improving the model’s segmentation results. We evaluated the segmentation performance of GAU-Net on the ISIC2016 skin disease dataset, showing that it outperformed traditional segmentation indicators such as mIoU and mAP. These results demonstrate the superiority of GAU-Net as an effective solution for skin lesion image segmentation.
PINNs for Sound Propagation and Sound Speed Field Estimation Simultaneously

Ocean dynamics phenomena can induce structural changes in sound speed, which, in turn, affect sound propagation in both depth and range directions. Typical methods for estimating underwater wavefields rely on traditional models or numerical solvers, which require complete sound speed information that is difficult to obtain. Recently, Physics-informed Neural Networks (PINNs) have emerged as a promising approach for solving physical problems, they have been applied to various problems but nothing about 2D underwater sound propagation. In this study, we propose a PINNs model composed of two independent networks to simultaneously estimate the sound propagation and sound speed field. Through simulations, we have demonstrated that PINNs can yield excellent results and tackle problems that traditional methods cannot solve. The estimated sound speed field can be utilized to model disturbances and gain insight into spatial changes in the ocean, which has practical application value and exciting prospects.
Navigation, Guidance and Control of a catamaran robust to external disturbances

This paper includes the implementation of navigation, guidance, and control algorithms for the catamaran-shaped autonomous surface vehicle (ASV) with a thruster configuration that includes 4 smaller thrusters in x-configuration and one larger thruster for the surge motion. The algorithms are described with emphasis on the allocator algorithms for which customizations were made to improve maneuverability. An experiment was conducted to show better energy optimization after a bigger thruster was included for surge motion. Two different experiments were made in s Marine Robotics Unity Simulator (MARUS) to show maneuverability improvement and test the full path following setup.
Roof Wind Pressure Reconstruction Method based on NMF and LSF

For the problems of high cost, large amount of data and poor real time of roof health monitoring, this paper proposes a method of roof wind pressure reconstruction based on non-negative matrix factroization and least squares fit. The method combines the field measurement method with the numerical wind tunnel simulation method to obtain the real-time wind pressure distribution of the whole roof by a small amount of sensor data. The proposed method is also validated using Fluent software. The reconstructed error of the obtained results is less than 5%. It is demonstrated that this method can reconstruct the roof wind pressure quickly and accurately, reduce the measurement cost, and facilitate the wind pressure monitoring for more roofs.
Improving the Scalability of Automated Planning-based Vehicle Routing via Smart Routes Identification

Due to growing urbanisation, traffic infrastructures have to accommodate increasing demands of traffic volume. One promising way for supporting a better exploitation of traffic networks is vehicle routing, that can distribute traffic from congested links to under utilised ones. Automated Planning techniques, a research field of Artificial Intelligence, have demonstrated to be a suitable approach for performing effective centralised traffic distribution. However, a main weakness of this class of approaches is the limited scalability to large and complex networks.In this paper, we aim to improve the scalability of automated planning techniques for urban traffic distribution by introducing an approach for the identification of routes to be considered. The proposed technique can significantly improve the planning capabilities by simplifying the complexity of the urban network to be considered, as demonstrated by our extensive experimental analysis performed on realistic traffic data on part of the New York and Sydney urban areas.
High Gain Low Axial-Ratio Circularly Polarized Dual-PRS Fabry-Perot Cavity Antenna at S-Band

A high-gain all-metallic dual-PRS Cross-dipole fed Circularly Polarized Fabry-Perot Cavity Antenna (CP-FPCA) with low axial-ratio and symmetric radiation pattern is presented in this paper. Cavity-backed ground plane and cross-dipole elements are optimally configured with dual-layer PRS of the FPC to simultaneously achieve high performance including gain of 17.0-18.5dBi, axial-ratio < 1.5dB and Return-loss < -15dB over 2.56-2.68GHz S-band transmit-receive frequency band.
Quadruped robot target following based on a gimbal mechanism

Human-robot collaboration is gradually becoming the way of life and production in the future. In this work, we focus on promoting the application scenarios of robots that can autonomously follow users, and propose a quadruped robot that can achieve autonomous following in complex environments. To address the problem that traditional quadruped robots using fixed visual sensors easily lose track of the target, we propose a method of using a gimbal mechanism equipped with a visual sensor for visual servoing tracking. By combining the chassis direction to plan the target servo strategy and controlling the gimbal rotation, we can achieve visual target following. On this basis, this paper controls the foot trajectory by using the cubic spline interpolation method, so that the robot can walk along various expected trajectories to achieve target following. This paper uses a field-of-view evaluation index to evaluate the tracking performance of this method and proves the effectiveness of the proposed target following method through experiments.
NISAR S-SAR Multichannel Receive chain ground characterization

ISRO and JPL(NASA) are developing a synthetic aperture radar (SAR) mission to map Earth's surface every 12 days, known as NASA-ISRO SAR (NISAR). NISAR is based on novel SweepSAR concept to provide wider swath along with high spatial resolution [6] & [7]. It uses a large deployable reflector antenna with a phased array antenna feed. To illuminate wider swath during transmit, all feed elements are excited to sub-illuminate reflector. While on receive, a much smaller portion of phased array antenna is used to collect the return echo. As per the joint agreement, JPL (NASA) is developing the L-Band SAR and ISRO is developing the S-Band SAR [6]. S-SAR employs scan on receive with digital beamforming (DBF) and has 48 receiver chains (24H+24V Pol). In this paper, end to end characterization of integrated receive chain is presented. The paper focuses on measurement techniques, challenges and test methodologies used to characterize the multiple receiver chains. The measurement results and their compliance with payload performance specifications has been discussed.
Image-based Visual Servo Control for UUV Recovery System under Field of View Constraints

Visual-based unmanned underwater vehicle (UUV) recovery is popular due to its high speed and positioning accuracy. This paper focuses on the image-based visual servo (IBVS) control for the UUV recovery system subject to the field of view (FOV). A new UUV relative kinetic model is presented based on the image plane features and the designed path planner with FOA constraints. Moreover, this paper addresses an IBVS controller and its stability is analyzed. Finally, a numerical example illustrates the effectiveness of the proposed theoretical results to evaluate the visibility of the marker.
A Monocular Biological Simultaneous Localization and Mapping Method Based on a Bionic Vision Model

Animals can navigate robustly through large unknown environments, utilizing inaccurate sensor and egomotion cues. Inspired by the mechanism of the human visual system, this paper presents a biological simultaneous localization and mapping (SLAM) system based on a monocular vision sensor to perform navigation tasks in complex environments. Specifically, our contributions are two folds: an improved monocular visual odometry with a scale recovery algorithm to calibrate the estimated robot pose, and a bionic vision model based on image enhancement algorithm and feature extraction approach to detect closed-loop. Experiments on public datasets demonstrate that our proposed method performs competitively in illumination-varying scenarios indoors and outdoors, which achieve a trade-off to maintain performances in terms of accuracy, execution time, and robustness.
DE ECONOMÍA

This study has two aims. First, to establish the main features of labor mobility; and second, to analyze the determinants of the main transitions between states of occupation. In order to achieve the first objective, we utilize transition matrices, on the basis of which different indicators are calculated that allow the characterization of the dynamics of labor markets in Peru. These calculations, in addition to the results of previous works, enable us to establish a number of stylized facts about labor mobility. Regarding the second objective
Development of Compact Unequal Power Divider Based on Wilkinson Topology for Indoor Navigation System

This paper presents the development of Wilkinson topology-based compact unequal power divider implemented for indoor navigation system. The proposed unequal power divider which is designed to have a power ratio of 1:2.2 aims to operate at the frequency of 2.4 GHz satisfying the IEEE 802.11b/g protocol standard of wireless communication. A 1.6 mm thick flame-retardant 4 (FR4) epoxy dielectric substrate with the size of 41.2 mm by 32.8 mm is used for the design and realization. A surface mount technology (SMT) resistor type with the value of 110 Ω is employed to fulfill the design. From the characterization results, the measured reflection coefficients at the input port and two output ports, as well as the transmission coefficients, show good achievements which are comparable to the simulated ones. Furthermore, at the frequency of 2.4 GHz the realized unequal power divider achieves a –20.49 dB isolation coefficient.
Underwater acoustic target identification via Siamese network

Underwater acoustic target identification is a task in which two acoustic samples are determined whether they belong to the same target, which is helpful for downstream tasks such as target recognition or target tracking. In this paper, we propose a method base on the Siamese network for underwater acoustic target identification. Compared with the traditional classification-based method, our method reduces the impact of data scarcity. It is more robust in the case of unseen target categories, which is more suitable for practical applications. We test the system performance on two publicly available datasets: Deepship and ShipsEar. The accuracy of our system can achieve 88.22% when the data are from the same source; when the data are from different sources, the identification accuracy can reach 77.34%. Experimental results show that our proposed method has both high accuracy and good generalization performance.