Miracle-dz/UniFAR-FTUs huggingface dataset:
Research on adaptive crawling of underwater hexapod robot on complex seabed

In this paper, the research on underwater adaptive walking planning of underwater hexapod robot is carried out aiming at the research goal of safe and stable seabed climbing behavior of underwater hexapod robot. Aiming at the unknown complex terrain on the seabed, an innovative method based on five-point gait is proposed to perceive the unknown terrain through the position of the foot tip. On the one hand, five-point gait can meet the high stability of underwater hexapod robot, on the other hand, it can avoid the problem of asynchronous landing of legs under other gait. The method of evaluating unknown terrain by foot position can reduce the number of sensors carried by the body on the one hand, and reduce the complexity of the overall planning method on the other hand. Finally, the paper will verify the correctness of the theory through the simulation method, and provide theoretical support for the underwater hexapod robot to crawl on the seabed.
medSafe- A Blockchain based Electronic Health Record Application

For a long time, the medical business was the only one that accepted new technologies first. As a result, they now accept cloud computing to store patient records in the cloud, which they refer to as an "Electronic Health Record. " They went to the cloud for a variety of reasons, including the inability to retain a traditional base of servers within them. Cloud computing is more secure and responsive. Their security is sometimes compromised. Blockchain is currently an interesting research topic, and the benefits it provides have been used by a range of applications. Blockchain will substantially improve the healthcare sector if it is connected with its means because to its robust nature in privacy and data protection. It is also a network-based technology that is decentralized. Each node will contain a duplicate of the data. Furthermore, EHR systems require a system with strong data security, integrity, and management challenges. Blockchain is made up of blocks that contain data. With an address, each block in the blockchain points to the next block. To put it simply, if someone tampers with the data in the block, the hash of the block changes, and every block in the blockchain becomes invalid. The purpose of this study is to demonstrate how blockchain can be connected with HER systems.
Data Structures Analysis for Text Processing in the Framework of NLP Classification in Polish

Natural language processing (NLP) involves au-tomating the analysis, understanding, generation, and translation of the content of written statements. It is done in order to develop appropriate tools and techniques. One of the most important things on software engineering is the proper selection of the data structure for the task. The paper presents the set of requirements for creating an ideal data structure in the context of text classification in Polish and the review of existing data structures that are useful for text processing, in particular classification, comparing them with each other. Created set of requirements specific to natural language processing in Polish enabled effective comparison of data structures with the ultimate text processing task in mind.
Design of High-Bandwidth, High-DC Gain Single-Stage Amplifier for High-Speed ADCs

Many modern, high-speed, high-performance applications require analog-to-digital converters (ADCs) that operate in high frequency. This paper presents the design and simulation of a high gain bandwidth (GBW), high gain, high-power-bandwidth efficiency fully differential single-stage operational amplifier (Opamp) implemented in 65nm CMOS technology. The Opamp was designed suitable for high-speed pipeline ADC building blocks such as the sample-and-hold (S/H) stage, a multiplying digital-to-analog converter (MDAC). The proposed topology uses a single-stage folded-cascode with Nauta transconductor assisted gain boosting to simultaneously achieve independent DC gain and GBW boosting. The PVT variations from the inverter-based Nauta transconductor are compensated using a process compensated biasing architecture to stabilize the regulated cascode loop gain and GBW under different process corners. The simulated Opamp achieves a DC gain of 75 dB, unity-gain bandwidth of 1.5 GHz under 4pF load, and a phase margin of SO degrees. The settling time is 5.5 ns, and the Opamp consumes power of 6 mW with a supply voltage of 1.2 V.
DICOF: A Distributed and Collaborative Framework for Hybrid DDoS Attack Detection

Hybrid distributed denial-of-service (DDoS) attack, which utilizes multiple types of DDoS attack to launch one attack event, has become more rampant. However, existing researches for DDoS attack detection mainly focus on the single attack scene and ignore the hybrid attack incident. To deal with the hybrid DDoS attack detect problem, we propose a distributed and collaborative DDoS detection framework(DICOF) to detect and classify multiple DDoS attack simultaneously. Firstly, we propose an entropy-based method to quickly identify the DDoS attack events by measuring the distribution of the total length of inbound and outbound packets for network traffics. Then, we adopt a GRU(Gated Recurrent Unit) based classification method to distinguish the type of different DDoS attacks contained in one attack event. Experiment results show that the DICOF is able to detect hybrid DDoS attack events at millisecond level and classify different DDoS attacks precisely.
AI-based Traffic Forecasting in 5G network

Forecasting of the telecommunication traffic is the foundation for enabling intelligent management features as cellular technologies evolve toward fifth-generation (5G) technology. In this work, a deep-learning based analysis of a traffic dataset was conducted. For this purpose, several neural network-based models are utilized. The paper explores the forecasting performance of the fully connected sequential network (FCSN). Specifically, one-dimensional convolutional neural network (1D-CNN), single shot learning LSTM (SS-LSTM), and autoregressive LSTM (AR-LSTM) models have been evaluated. In addition, the baseline model was developed to assess the performance of the aforementioned models. The results reveal that FCSN and 1D-CNN have comparable performance. However, 1D-CNN is a smaller network with less number of parameters. One of the other benefits of the proposed 1D-CNN is having less complexity and faster execution time for predicting the next 24-hour traffic.
A Low-Leakage, Low-Loss Magnetic Transformer Structure for High-Frequency Applications

Energy-storage transformers, such as transformers for flyback or LLC converters, have different design constraints than typical transformers. Since primary and secondary currents are not in phase, interleaving does not necessarily reduce high-frequency losses. Such transformers often must be designed with low leakage as well. In this work, we propose design guidelines for a transformer structure that uses field shaping to achieve current conduction along most of the skin of the conductors (double-sided conduction), equal current sharing between paralleled turns, even for out-of-phase currents, and near zero MMF drop across the leakage reluctance paths. The transformer therefore has low leakage inductance and low conduction loss without the use of litz wire and can be used effectively at frequencies beyond a few megahertz. Step-by-step design guidelines are proposed and a prototype transformer is built which achieves a leakage to magnetizing ratio of 1.12%, a power loss 14–17% of a traditional lumped-gap transformer, and current sharing variation less than 1.5% between paralleled turns.
Common-Mode EMI Noise Modeling of Three-Level T-Type Inverter for Adjustable Speed Drive Systems

This article studies the EMI noise modeling of a three-level T-type inverter (3LT2I) for adjustable speed drive (ASD) systems. A methodology to generate the common-mode (CM) voltages in the time-domain is proposed based on SiC MOSFETs switching behavior, such as the variable rise and fall times. The frequency spectrums of the time-domain voltages are used with the CM noise paths to predict the CM current of the 3LT2I. The CM noise model of the 3LT2I consists mainly of two CM noise sources. The effect of these noise sources on the CM current is investigated. The proposed EMI noise prediction method is validated by the comparison between the simulation and experimental results of the CM voltage and CM current spectrums.
Towards Consistent Visual-Inertial Navigation for Unmanned Aerial Vehicles using Depth Information

This paper proposes a new filtering-based depth enhanced visual inertial navigation system (DE-VINS) for quadrotor unmanned aerial vehicles (UAV). This filter addresses the drifting and degraded performance of a class of conventional monocular VINS filters at hovering conditions. A theoretical nonlinear observability analysis is performed to verify the filter design. The performance of the proposed DE-VINS is numerically evaluated using a Matlab simulator and then compared against the conventional VINS filter proposed in literature. The results show improved performance of the DE-VINS in terms of estimation accuracy and consistency at zero-velocity flight conditions.
Blind single-input multi-output (SIMO) channel identification with application to time delay estimation

A cumulant based single-input multi-output (SIMO) blind channel estimation (BCE) algorithm, with a given set of non-Gaussian measurements, is proposed. It uses the multi-input multi-output (MIMO) inverse filter criteria (blind deconvolution criteria using higher-order cumulants) proposed by J.K. Tugnait (see IEEE Trans. Sig. Proc., vol.SP-41, p.549-58, 1993) and C. -Y. Chi and C. -H. Chen (see IEEE Trans. Sig. Proc., 2001). Then a time delay estimation (TDE) algorithm is proposed that estimates P-1 time delays from the phase information of the estimated single-input P-output (P/spl ges/2) system obtained by the proposed SIMO BCE algorithm. Some simulation results are presented to support the efficacy of the proposed SIMO BCE and TDE algorithms.
Learning Rat-Like Behavioral Interaction Using a Small-Scale Robotic Rat

In this paper, we propose a novel method for emulating rat-like behavioral interactions in robots using reinforcement learning. Specifically, we develop a state decision method to optimize the interaction process among 6 known behavior types that have been identified in previous research on rat interactions. The novelty of our method lies in using the temporal difference (TD) algorithm to optimize the state decision process, which enables the robots to make informed decisions about their behavior choices. To assess the similarity between robot and rat behavior, we use Pearson correlation. We then use TD-λ to update the state value function and make state decisions based on probability. The robots execute these decisions using our dynamics-based controller. Our results demonstrate that our method can generate rat-like behaviors on both short- and long-term timescales, with interaction information entropy comparable to that between real rats. Overall, our approach shows promise for controlling robots in robot–rat interactions and highlights the potential of using reinforcement learning to develop more sophisticated robotic systems.
On the optimization of Grounding Design of Rods Covered by Low Resistivity Materials

Reducing the grounding resistance using low resistivity materials (LRM) is a widely used technique to improve the grounding system performance, especially under high resistivity conditions. In this light, the present paper deals with cost-effective design of a typical configuration of grounding systems with LRM coverings. Indeed, optimization problems are proposed and resolved using particle swarm optimisation. Considering vertical ground electrodes partially and fully covered by LRM, the objective is devoted to obtain the geometrical configuration that gives simultaneously an economical and safe grounding design. Each step in the optimization is discussed to help generalise the technique for more complex grounding designs. The results show that soil treatment can significantly reduce the grounding resistance by more than 50% compared to identical systems without LRM coverings. Moreover, the optimal geometrical parameters are senssitive to the variation of the soil resistivity as well as the maximum tolerable limits.
Fixed Beamformer Design Using Polynomial Eigenvalue Decomposition

Array processing is widely used in many speech applications involving multiple microphones. These applications include automatic speech recognition, robot audition, telecommunications, and hearing aids. A spatio-temporal filter for the array allows signals from different microphones to be combined desirably to improve the application performance. This paper will analyze and visually interpret the eigenvector beamformers designed by the polynomial eigenvalue decomposition (PEVD) algorithm, which are suited for arbitrary arrays. The proposed fixed PEVD beamformers are lightweight, with an average filter length of 114 and perform comparably to classical data-dependent minimum variance distortionless response (MVDR) and linearly constrained minimum variance (LCMV) beamformers for the separation of sources closely spaced by 5 degrees.
PLASMA INSTABILITIES IN THE CONTEXT OF CURRENT HELIUM SEDIMENTATION MODELS: DYNAMICAL IMPLICATIONS FOR THE ICM IN GALAXY CLUSTERS

Understanding whether Helium can sediment to the core of galaxy clusters is important for a number of problems in cosmology and astrophysics. All current models addressing this question are one-dimensional and do not account for the fact that magnetic fields can effectively channel ions and electrons, leading to anisotropic transport of momentum, heat, and particle diffusion in the weakly collisional intracluster medium (ICM). This anisotropy can lead to a wide variety of instabilities, which could be relevant for understanding the dynamics of heterogeneous media. In this paper, we consider the radial temperature and composition profiles as obtained from a state-of-the-art Helium sedimentation model and analyze its stability properties. We find that the associated radial profiles are unstable to different kinds of instabilities depending on the magnetic field orientation at all radii. The fastest growing modes are usually related to generalizations of the magnetothermal instability (MTI) and the heat-flux-driven buoyancy instability which operate in heterogeneous media. We find that the effect of sedimentation is to increase (decrease) the predicted growth rates in the inner (outer) cluster region. The unstable modes grow quickly compared to the sedimentation timescale. This suggests that the composition gradients as inferred from sedimentation models, which do not fully account for the anisotropic character of the weakly collisional environment, might not be very robust. Our results emphasize the subtleties involved in understanding the gas dynamics of the ICM and argue for the need of a comprehensive approach to address the issue of Helium sedimentation beyond current models.
Control and Integration of a multiphase Brushless Wounded Synchronous Motor Drive

This paper presents a fully integrated seven-phase Brushless Wounded Rotor Synchronous Motor BWRSM machine drive and its control. A direct integration strategy of the power electronics on the motor case is performed. Advanced PCB integration with embedded die are used for low profile rotary transformer. For the control side, the machine was modelled by Finite Element Method (FEM) in order to extract the flux tables. These tables were then used to improve the precision of analytic simulation model. By using so obtained analytic simulation with integrated flux tables designed field-oriented control was verified. Details on design and the model are presented in the paper. Finally, the controller's efficiency and the power electronics of the motor drive are confirmed with experiments on described prototype machine.
Carrier Frequency Offset-Based OFDM Synchronization Technology

To meet the demand of high speed and reliability, the key performance of mobile communication has higher requirements for different application scenarios. According to the 3rd Generation Partnership Project protocol, the 5th generation (5G) mobile communication technology still adopts Orthogonal Frequency Division Multiplexing (OFDM) technology in spectrum transmission. The wireless channel fading, noise interference and Doppler effect will cause data loss in signal transmission, so the research of synchronization technology has more practical significance for signal transmission in complex environment and limited bandwidth resources. This paper investigates Carrier Frequency Offset (CFO) synchronization technology in OFDM, analyzes CFO from time domain and frequency domain, and simulates CFO synchronization technology based on OFDM with MATLAB. The simulation results show that the received signals’ signal noise ratio (SNR) of increases, the mean square error (MSE) estimated by CFO decreases, and the MSE estimated by CFO is also different when the phase difference between the two repeat leads is changed.
Frequency and Modulation Index Related Effects in Continuous and Discontinuous Modulated Y-Inverter for Motor-Drive Applications

The effect of the pulse-width modulation scheme on the efficiency of a three-phase Y-inverter with a wide range of output voltages and currents is investigated experimentally in this paper. The efficiency measurements obtained while conducting experiments on a GaN-based Y-inverter prototype indicate that no pulse-width modulation scheme results in higher efficiency of the Y-inverter over the entire range of motor operation. In other words, depending on the operating conditions, a discontinuous PWM results in a higher or lower efficiency than a continuous sinusoidal PWM. As a result, there is a chance that using a hybrid modulation strategy will improve the efficiency of the Y-inverter. Furthermore, the distortion effect caused by inappropriate inductor and capacitor value selection is highlighted.
Fast Quadratic Sensing Via Nonconvex Optimization

This paper concerns the problem of recovering an unknown but rank-r signal from quadratic measurements. We formulate the recovery problem as two-stage nonconvex optimization approach where an efficient adaptive accelerated gradient-like iterative refinement starting from a careful initialization. Moreover, an efficient initial scheme is proposed for this problem. The average relative error of our initialization estimator reduces exponentially as the oversampling ratio grows, which can also boost the performance of existing two-stage approach for rank-$-r$ matrix recovery from vector measurements. Experimental results not only clearly demonstrate the superiority of introduced initialization estimator but also show the advantages of our adaptive accelerated gradient-like approach in terms of both sample complexity and computational complexity.
A three-finger dexterous hand with suction cups integrated on fingertips

This study introduces a three-finger dexterous hand with integrated suction cups on the fingertips. The dexterous hand has 8 degrees of freedom and is driven by rigid linkage. The movement and arrangement of the fingers refer to human hand. Each fingertip integrates a suction cup and is cast in silicone. This design expands the grasping ability of the dexterous hand and simplifies the grasping action. We make a physical prototype of this dexterous hand and perform grasping experiment. Results of the experiments prove the effectiveness and practicality of this design.
A Compact Tri-band Single Circularly Polarized Antenna

A tri-band antenna is designed by using the coplanar waveguide feeding method. In order to reduce the size of the antenna, a hollow rectangular stepped structure is constructed. The three operating frequencies are 2.9 GHz, 3.3 GHz and 4.1 GHz respectively, which meet the requirements of 5G (5th Generation) communication and radio navigation frequency bands respectively. And the circular polarization is realized at the resonance frequency of 4.1 GHz. The size of the antenna is only 40×40 mm2, and it has the advantages of simple structure, wide coverage frequency band, and good radiation performance.
Dual-Compression Neural Network with Optimized Output Weighting For Improved Single-Channel Speech Enhancement

Approaches to the problem of single-channel spectral speech enhancement comprise either model-based signal processing or neural networks (NNs) or a combination thereof. Diverse compression functions of input features (noisy spectral magnitudes) and targets (clean speech magnitudes) have been proposed in the NN domain, most commonly the linear and logarithmic compression that will favor speech intelligibility and noise reduction, respectively. An average of a linear and a logarithmic NN prediction (averaged on the same decibel scale) has been proposed recently to benefit from both compression characteristics. In this contribution, we propose an optimized time- and frequency-dependent weighting of linear and logarithmic NN outputs by an additional computationally-light NN stage. This structure is termed dual-compression NN with optimized output (DuCO) weighting. It shows improved performance over NNs with either linear or logarithmic compression, over post-processing by output averaging, and over state-of-the-art model-based processing in terms of objective PESQ, STOI, and segmental SNR.
Experimental Evaluation on Observer-Based Delay-Compensating Active Damping for LC-Filters

This work presents experimental results of a discrete-time observer-based delay-compensating active damping technique for LC filters. This method is state-feedback-based and consequently very robust regarding the system parameter such as the grid impedance. Nonetheless, the limits of this strategy are discussed. The experimental setup is a low voltage representation of a 5 MW wind converter. Much know-how was invested in transferring the electrical conditions from high to low power. Particular mention should be made of the adaptation concerning the naturally slower switches in the high voltage and the compensation of the higher damping of the passive components in the low voltage class.
Torch: Software Package For The Search Of Linear Binary Codes

We describe a software package created by the authors that can be used to search for linear binary codes with almost arbitrary conditions. The package is easily extensible and reconfigurable to suit the specific needs of the search. The main function can be used to search for currently unknown linear codes, or to quickly generate examples of known codes.
Proximity-based anomaly detection in Securing Water Treatment

Industrial Control Systems (ICSs) utilize different sensors and various embedded systems to operate. Devices often communicate using protocols like Siemens Step 7 and Modbus, which were designed for use in closed networks many years ago and are vulnerable to attacks. The goal of this study is to detect anomalies in industrial control systems using a proximity-based approach on the Securing Water Treatment (SWaT) dataset. We encoded categorical data using one hot encoding and normalized numerical data using min max scaling. The experiment shown that by adopting a proximity-based approach, we can obtain state-of-the-art 99% precision and 98% recall and able to identify 35 out of 37 attack points, indicating that the suggested methodology is suitable for usage in industrial control system scenarios.
Method to analyze the influence of switching behavior in hard switching half bridge topologies for traction application

The current harmonics feed back (interference current) of railway traction inverter towards the grid has to be limited. The goal of this paper is to present a method which allows to model harmonics caused by switching behavior and turn on delay. Since simulation is limited by numerical errors due to the step size of the numerical solvers and also takes much time, an analytical method is chosen.