bluuebunny/crossref_metadata_2025 huggingface dataset:
Generalization of the Landau–Lifshitz–Gilbert equation by multi-body contributions to Gilbert damping for non-collinear magnets
Authors: Brinker Sascha , dos Santos Dias Manuel , Lounis Samir
Published: April 2022

We propose a systematic and sequential expansion of the Landau–Lifshitz–Gilbert equation utilizing the dependence of the Gilbert damping tensor on the angle between magnetic moments, which arises from multi-body scattering processes. The tensor consists of a damping-like term and a correction to the gyromagnetic ratio. Based on electronic structure theory, both terms are shown to depend on e.g. the scalar, anisotropic, vector-chiral and scalar-chiral products of magnetic moments: e

i
⋅ e

j
, (n

ij
⋅ e

i
)(n

ij
⋅ e

j
), n

ij
⋅ (e

i
× e

j
),

(

e

i

⋅

e

j

)

2

, e

i
⋅ (e

j
× e

k
) …, where some terms are subjected to the spin–orbit field n

ij
in first and second order. We explore the magnitude of the different contributions using both the Alexander–Anderson model and time-dependent density functional theory in magnetic adatoms and dimers deposited on Au(111) surface.
Advances in phosphor two-color ratio method thermography for full-field surface temperature measurements
Authors: Jones E M C , Jones A R , Hoffmeister K N G , Winters C
Published: April 2022

Thermographic phosphors can be employed for optical sensing of surface, gas phase, and bulk material temperatures through different strategies including the time-decay method, time-integrated method, and frequency-domain method. We focus on the time-integrated method, also known as the ratio method, as it can be more practical in many situations. This work advances the ratio method using two machine vision cameras with CMOS detectors for full-field temperature measurements of a solid surface. A phosphor calibration coupon is fabricated using aerosol deposition and employed for in situ determination of the temperature-versus-intensity ratio relationship. Algorithms from digital image correlation are employed to determine the stereoscopic imaging system intrinsic and extrinsic parameters, and accurately register material points on the sample to subpixel locations in each image with 0.07 px or better accuracy. Detector nonlinearity is carefully characterized and corrected. Temperature-dependent, spatial non-uniformity of the full-field intensity ratio—posited to be caused by a blue-shift effect of the bandpass filter for non-collimated light and/or a wavelength-dependent transmission efficiency of the lens—is assessed and treated for cases where a standard flat-field correction fails to correct the non-uniformity. In sum, pixel-wise calibration curves relating the computed intensity ratio to temperature in the range of T = 300–430 K are generated, with an embedded error of less than 3 K. This work offers a full calibration methodology and several improvements on two-color phosphor thermography, opening the door for full-field temperature measurements in dynamic tests with deforming test articles.
Lead-doped scintillator dosimeters for detection of ultrahigh dose-rate x-rays
Authors: Hart Alexander , Cecchi Daniel , Giguère Cloé , Larose Frédérique , Therriault-Proulx François , Esplen Nolan , Beaulieu Luc , Bazalova-Carter Magdalena
Published: April 2022

Objective. Lead-doped scintillator dosimeters may be well suited for the dosimetry of FLASH-capable x-ray radiotherapy beams. Our study explores the dose rate dependence and temporal resolution of scintillators that makes them promising in the accurate detection of ultrahigh dose-rate (UHDR) x-rays. Approach. We investigated the response of scintillators with four material compositions to UHDR x-rays produced by a conventional x-ray tube. Scintillator output was measured using the HYPERSCINT-RP100 dosimetry research platform. Measurements were acquired at high frame rates (400 fps) which allowed for accurate dose measurements of sub-second radiation exposures from 1 to 100 ms. Dose-rate dependence was assessed by scaling tube current of the x-ray tube. Scintillator measurements were validated against Monte Carlo simulations of the probe geometries and UHDR x-ray system. Calibration factors converting dose-to-medium to dose-to-water were obtained from simulation data of plastic and lead-doped scintillator materials. Main Results. The results of this work suggest that lead-doped scintillators were dose-rate independent for UHDR x-rays from 1.1 to 40.1 Gy s−1 and capable of measuring conventional radiotherapy dose-rates (0.1 Gy s−1) at extended distance from the x-ray focal spot. Dose-to-water measured with a 5% lead-doped scintillator detector agreed with simulations within 0.6%. Significance. Lead-doped scintillators may be a valuable tool for the accurate real-time dosimetry of FLASH-capable UHDR x-ray beams.
NiTi shape memory alloy pipe couplers for ultra-high vacuum systems: development and implementation
Authors: Niccoli F , Giovinco V , Garion C , Maletta C , Chiggiato P
Published: April 2022

Novel Nickel–Titanium (NiTi)-based shape memory alloy (SMA) pipe couplers were designed and developed. They are suitable for room-temperature ultrahigh vacuum (UHV) systems and provide a quick and compact solution at reasonable cost. Their use is particularly interesting for restricted-access areas of particle accelerators as their installation/dismounting can be performed remotely by temperature variations. A NiTi SMA with suitable composition was selected. NiTi couplers with different diameters in the range 30–135 mm were manufactured and thermo-mechanically trained to exhibit a proper two-way shape memory behaviour which comply with the strict operative constraints for coupling applications in room temperature vacuum sectors. The connectors are easily implementable as they were designed to be compatible with commercially available flanges (DN16, DN25, DN100) used worldwide in vacuum systems. The effect of the SMA joint geometry on the thermo-mechanical response and vacuum performance was investigated by numerical studies and experimental analyses such as strain-gauge, extensometer and leak-tightness tests performed under different operating conditions including static axial loads and multiple thermal cycles. It was demonstrated that NiTi-based connectors can be thermally mounted upon heating and can guarantee the leak tightness of the vacuum pipe within a suitable temperature window. The thermal dismounting was also verified by cooling the couplers down to subzero temperatures (lower than −40 °C). Possible use of these connections at European Organization for Nuclear Research (CERN) is foreseen in vacuum assemblies installed in high radioactive areas, like those nearby particle collision points and beam collimators. Thanks to their compactness, SMA couplers are also of great interest for connecting beam pipes with small aperture such as those studied for the electron–positron future circular collider (FCC-ee) and next-generation synchrotron light facilities.
Comprehensive review on topological superconducting materials and interfaces
Authors: Sharma M M , Sharma Prince , Karn N K , Awana V P S
Published: April 2022

Superconductivity in topological materials has drawn significant interest from the scientific community as these materials provide a hint of the existence of Majorana fermions conceived from the quantized thermal conductivity, a zero-biased conduction peak and the anomalous Josephson effect. In this review, we make a systematic study of recent advances in the field of topological superconductivity. The article comprises of both bulk systems as well as heterostructures. A brief description of Majorana fermions and their relationship with topological superconductors and heterostructures is also carried out. This review also consists of details of key experimental techniques to characterize candidates for topological superconductivity. Moreover, we summarize the potential material candidate that may demonstrate topological superconductivity. We also consider some intrinsic odd-parity superconductors, non-centrosymmetric, centrosymmetric superconductors, doped topological insulators, doped topological crystalline insulators and some other materials that are expected to show superconductivity along with topological non-trivial states in bulk form. The effects of pressure, emergence of superconductivity in topological materials and muon spin rotation studies are also summarized in this article.
Spin Hall conductivity and anomalous Hall conductivity in full Heusler compounds
Authors: Ji Yimin , Zhang Wenxu , Zhang Hongbin , Zhang Wanli
Published: April 2022

The spin Hall conductivity (SHC) and anomalous Hall conductivity (AHC) in about 120 full Heusler compounds are calculated using the density functional theory in a high-throughput way. The electronic structures are mapped to the Wannier basis and the linear response theory is used to get the conductivity. Our results show that the mechanism under the SHC or AHC cannot be simply related to the valence electron numbers or atomic weights. It is related to the very details of the electronic structures, which can only be obtained by calculations. A high-throughput calculation is efficient to screen out the desired materials. According to our present results, Rh2MnAl and Cu2CoSn, as well as Co2MnAl and Co2MnGa are candidates in spintronic materials regarding their high SHC and AHC values, which can benefit the spin-torque-driven nanodevices.
Conserved charges in Chern-Simons modified theory and memory effects
Authors: Hou Shaoqi , Zhu Tao , Zhu Zong-Hong
Published: April 2022

In this work, conserved charges and fluxes at the future null infinity are determined in the asymptotically flat spacetime for Chern-Simons modified gravity.
The flux-balance laws are used to constrain the memory effects.
For tensor memories, the Penrose's conformal completion method is used to analyze the asymptotic structures and asymptotic symmetries, and then, conserved charges for the Bondi-Metzner-Sachs algebra are constructed with the Wald-Zoupas formalism.
These charges take very similar forms to those in Brans-Dicke theory. For the scalar memory, Chern-Simons modified gravity is rewritten in the first-order formalism, and the scalar field is replaced by a 2-form field dual to it. With this dual formalism, the scalar memory is described by the vacuum transition induced by the large gauge transformation of the 2-form field.
The Integrated Sachs Wolfe effect: unWISE and Planck constraints on dynamical dark energy
Authors: Krolewski Alex , Ferraro Simone
Published: April 2022

CMB photons redshift and blueshift
as they move through gravitational potentials Φ
while propagating across the Universe. If the potential is not constant in time, the photons will pick up a net redshift or blueshift, known as the Integrated Sachs-Wolfe (ISW) effect.
In the z ≪ 1000 universe, Φ̇ is nonzero on large scales when the Universe transitions from matter to dark energy domination. This effect is only detectable in cross-correlation with large-scale structure at z ∼ 1. In this paper we present a 3.2σ detection of the ISW effect using cross-correlations between unWISE infrared galaxies and Planck CMB temperature maps. We use 3 tomographic galaxy samples spanning 0 < z < 2, allowing us to fully probe the dark energy domination era and the transition into matter domination. This measurement is consistent with ΛCDM (AISW = 0.96 ± 0.30).
We study constraints on a particular class of dynamical dark energy models
(where the dark energy equation of state is different in matter and dark energy domination),
finding that unWISE-ISW improves constraints
from type Ia supernovae due to improved constraints on the time evolution of dark energy. When combining with BAO measurements, we obtain the tightest constraints on specific dynamical dark energy models. In the context of a phenomenological model for freezing quintessence, the Mocker model, we constrain the dark energy density within 10% at z < 2 using ISW, BAO and supernovae. Moreover, the ISW measurement itself provides an important independent check when relaxing assumptions about the theory of gravity, as it is sensitive to the gravitational potential rather than the expansion history.
Learning Reaching Tasks Using an Arm Robot Equipped with MACMSA
Authors: Akikawa Motohiro , Yamamura Masayuki
Published: April 2022

In recent years, models that integrate multimodal information to control robots have been actively developed. Memorizing and Associating Converted Multimodal Signal Architecture (MACMSA) was proposed to integrate multimodal information obtained from robots with Hopfield networks as associators and independent feed-forward neural networks as encoders and decoders. The performance of MACMSA has thus far been investigated only using pseudo-data. Notably, MACMSA exhibits high resistance to noise. However, it cannot generate signals for robot control. The purpose of this study was to improve MACMSA to generate signals for robot control and optimize it using real data on reaching tasks. The results of the generated control signals on a real machine are presented to demonstrate that the improved model can be effectively used in a real environment. The results also show that the proposed model can perform well with real data.
Defect detection in the textile industry using image-based machine learning methods: a brief review
Authors: Shahrabadi Somayeh , Castilla Yusbel , Guevara Miguel , Magalhães Luís G. , Gonzalez Dibet , Adão Telmo
Published: April 2022

Traditionally, computer vision solutions for detecting elements of interest (e.g., defects) are based on strict context-sensitive implementations to address contained problems with a set of well-defined conditions. On the other hand, several machine learning approaches have proven their generalization capacity, not only to improve classification continuously, but also to learn from new examples, based on a fundamental aspect: the separation of data from the algorithmic setup. The findings regarding backward-propagation and the progresses built upon graphical cards technologies boost the advances in machine learning towards a subfield known as deep learning that is becoming very popular among many industrial areas, due to its even greater robustness and flexibility to map and deal knowledge that is typically handled by humans, with, also, incredible scalability proneness. Fabric defect detection is one of the manual processes that has been progressively automatized resorting to the aforementioned approaches, as it is an essential process for quality control. The goal is manifold: reduce human error, fatigue, ergonomic issues and associated costs, while simultaneously improving the expeditiousness and preciseness of the involved tasks, with a direct impact on profit. Following such research line with a specific focus in the textile industry, this work aims to constitute a brief review of both defect types and Automated Optical Inspection (AOI) mostly based on machine learning techniques, which have been proving their effectiveness in identifying anomalies within the context of textile material analysis. The inclusion of Convolutional Neural Network (CNN) based on known architectures such as AlexNet or Visual Geometry Group (VGG16) on computerized defect analysis allowed to reach accuracies over 98%. A short discussion is also provided along with an analysis of the current state characterizing this field of intervention, as well as some future challenges.
Anomaly Detection and Analysis Based on Deep Autoencoder for the Storage Tank Liquid Level of Oil Depot
Authors: Cheng Long , Dong Guishan , Ren Linlin , Yang Ruirui , Liu Bo , Rong Yan , Li Dayong
Published: April 2022

In the industrial control system of oil depot, the change of storage tank liquid level is closely related to the transportation process and site management of oil depot. It is of great significance to detect the abnormality of storage tank liquid level data for the safe and stable production of oil depot. A data-driven anomaly detection strategy is proposed by analyzing the non-periodic time series data of the oil storage tank liquid level. Based on the convolutional autoencoder algorithm to learn the features and patterns of a large number of samples, the strategy is carried out by reconstructing the samples and calculating the reconstruction error, which not only does not rely on the labeled samples, but also improves the detection precision. This paper chooses three algorithms of convolutional autoencoder, RNN (Recurrent Neural Network) autoencoder and LSTM (Long Short-Term memory) autoencoder for experimental analysis. Experiments were carried out on the oil tank historical data set and NAB (Numenta Anomaly Benchmark) simulation data set respectively. The results show that the accuracy of convolutional autoencoder is 98% and the F1 score is 82%, which is more practical for the scenes with real-time requirements.
An Intelligent Dosing Algorithm Model for Wastewater Treatment Plant
Authors: Fang Xusheng , Zhai Zhengang , Zang Jian , Zhu Yunya
Published: April 2022

The precise coagulation add-in in the wastewater process treatment is key for efficient contamination removal. However, the complexity of the coagulant chemical theory and affected by many factors (turbidity, pH, conductivity, flow rate, etc.) that it is difficult to determine the optimal dosage. The traditional method in the production process, such as PID controller had a bad adaptability on the complex systems and high performance required systems due to its inefficient parameter coordination, and it has a large time delay, difficult to achieve precise control. Excessive dosage will lead to waste and cost-waste, insufficient dosage could not guarantee the quality of effluent water. In this research study, we proposed an intelligent precisely dosing prediction algorithm based on LightGBM, using the characteristics of the influent water quality parameters PH, turbidity, electrical conductivity and flow rate to predict the dosage of coagulant. Perform experiments based on the actual data collected from the sewage treatment plant. Compared to experimental results with the optimal dosage solution, it demonstrated that the proposed approach could predict the dosage more accurate, resulting in intelligent and precise dosing add-in in water treatment process.
Marking and Cutting of Non-metallic Products with CO2 Laser
Authors: Dolchinkov Nikolay Todorov
Published: April 2022

Since the discovery of the laser more than 60 years ago, research has begun on its application in various fields of technology. One of the most commonly used applications of laser technology is the cutting and marking of various materials. And while the use of different metals has been studied and used much better, the use of lasers in non-metallic materials has been studied much less. Research has been conducted with a CO2 laser on various materials -various types of textiles, felt, transparent and opaque Plexiglas and other materials that have wide application in technology and economics. The optimal parameters for performing various operations on this type of materials have been found and are shown in tabular and graphical form. Studies with different power and speed of the laser beam have been made. Based on the obtained results, the relevant conclusions are shown. These materials are widely used in industry, the manufacture of automobiles, aircraft, ships and other vehicles and machinery and the results prove the effectiveness of laser cutting and marking compared to the methods used so far to perform these operations.
Nonlinear Inverse Heat Transfer Problem
Authors: Rysbaiuly Bolatbek , Alpar Sultan
Published: April 2022

In this work, a method for finding nonlinear heat-conducting characteristics of soil is developed. Two-layer complexes of containers were created, the side faces of which are thermally insulated, so the 1D thermal conductivity equation is used. A temperature sensor is placed at the junction of the two media, and a mixed boundary value problem is solved in each area. In order to provide the inverse coefficient problem with initial data, two temperature sensors are used: one sensor was placed at the open border of the container and recorded the soil temperature at this border, and the second sensor was placed at a short distance from the border, which recorded the air temperature. The measurements were carried out in the time interval (0,4t
max
). First, the initial-boundary value problem of thermal conductivity with nonlinear coefficients is investigated by the finite difference method. Two types of difference schemes are constructed: linearized and nonlinear. The linearized difference scheme is implemented numerically by the scalar Thomas method, and the nonlinear difference problem is solved by the Newton method. The solution of the linearized difference problem was taken as the initial approximation of the Newton method. To find the thermophysical parameters, the corresponding functional is minimized using the gradient descent method. In addition, all thermophysical characteristics (8 coefficients) were found for a two-layer container with sand and chernozem.
Safety Analysis of Secondary Cable in Substation during Power Frequency Short Circuit
Authors: Liu Shengjun , Yin Yanzeng , Qi Hongbin , Wang Xuejia
Published: April 2022

In order to study the safy of secondary cables in substation, the influences of soil resistivity, short circuit current, distance, grounding grid parameters and cable parameter on the core-to-sheath potential difference and shielding layer current are investigated. It is shown that the core-to-sheath potential difference and shielding layer current change little with soil resistivity, and increase linearly with the increase of short-circuit current, and decrease with the increase of distance. The core-to-sheath potential difference increases with the increase of side length of grounding grid and cable length.
Design and Implementation of Remote Monitoring System for Rare Trees Based on LoRa Communication
Authors: Xu Chen , Xiaoyue Zheng , Quou Ge , Tao Xu , Xiushan Wu
Published: April 2022

In recent years, rare plants on the earth have gradually disappeared, so it is urgent to inspect and protect their health. A rare tree monitoring system compatible with NB-IOT (Narrow Band Internet of Things) is designed based on the low-power data transmission technology of LoRa (Long Range Radio). The system takes stm32f103c8t6 as the core of the controller, collects information through temperature and humidity sensor, attitude sensor, infrared pyroelectric sensor and sound sensor, builds a server to store the information and data back to the server, uses the terminal to access the server, and reminds the operator when the amount of information exceeds a certain threshold, Finally, the real-time monitoring of rare trees in the field is realized.
Reliability Analysis and Modelling of Containment Spray System Based on Petri Net
Authors: Zhang Ziben , Zhang Dongliang
Published: April 2022

Reliability modelling for digital instrumentation and control systems in nuclear power plants is one of the new trends. The containment spray system in the digital I&C system of nuclear power plant is selected, and the generalized stochastic Petri net model is used to model the reliability of the containment spray system. A single-cycle simulation of the generalized stochastic Petri net model is carried out under consideration of a variety of dynamic events, and the probability of system start-up failure is obtained. The results show that the generalized stochastic Petri net model can well reflect the impact of various dynamic events on system security. Therefore, the generalized stochastic Petri net model is suitable for reliability modelling of I&C systems in nuclear power plants.
An English Pronunciation Quality Evaluation Model Based on Multi-dimensional Features
Authors: Li Yiqun , Huang Guimin
Published: April 2022

As a universal language, English has been paid more and more attention, among which oral English learning is very important. In this paper, the two key technologies of pronunciation error detection and quality evaluation are studied, both of them are effectively integrated, aiming to build a model for L2 learners’ English pronunciation quality evaluation. This paper mainly studies two different methods of pronunciation error detection. Based on the speech recognition framework, the standard score is compared with the threshold to judge the correctness of phoneme pronunciation, and the phoneme-dependent threshold is set to improve the maximum Precision to 0.44. By judging the correct pronunciation and confusing phoneme, the accuracy of pronunciation error detection is improved to 81.26%. This paper proposes the fusion algorithm from multi-dimensions of speech fluency and intonation respectively, and a newly designed feature called word duration ratio, which significantly improve the correlation of pronunciation quality evaluation to 0.746.
Discussion on Zero-dimension Model and Designed Hydrological Conditions in Calculation of Water Pollution Capacity
Authors: Chen Juan , Wang Sen
Published: April 2022

In order to implement the strictest water resource management system and ensure the sustainable utilization of water resources, it is necessary to carry out the work of limiting pollution in water function area. The calculation of water pollution capacity is the basis of pollution limitation in water function area. Code of practice for computation on allowable permitted assimilative capacity of water bodies (GB/T25173-2010) is the main reference basis for the calculation of water pollution capacity. There are some limitations in the practical application. In this paper, the zero-dimensional model is modified based on the current code of pollutant carrying capacity. And the determination of designed hydrological conditions was discussed. This would give reference for the calculation of water pollution capacity.
Experimental Bulging and Buckling of Bi-segmented Cylinders
Authors: Wang Feng , Zhang Jian , Zuo Xinlong , Tang Wenxian , Zhao Tan
Published: April 2022

This paper studies the experimental free bulging and buckling of bi-segmented cylinders. Two cylindrical shells are manufactured using argon-arc welding and analyzed for manufacturing errors. Next, free bulging tests and hydrostatic pressure tests are conducted to verify the feasibility of the free bulging technique and to confirm the destruction form of the bulged bi-segmented barrel. At the same time, the reasonableness of the circular thick plate is examined, which is determined according to the deformation consistency. The results show that the bi-segmented cylindrical preforms exhibit good welding quality by TIG welding technology. It has the same critical pressure load as a single cylindrical preform. Nevertheless, the bi-segmented cylindrical preforms have larger internal volume and better buoyancy capability than the single cylindrical preform. The free bulging bi-segmented shell has good symmetry along the axial direction. It has larger internal volume and higher critical buckle capacities than the non-bulging one.
Security Assessment of the MQTT-SN Protocol for the Internet of Things
Authors: Roldán-Gómez José , Carrillo-Mondéjar Javier , Castelo Gómez Juan Manuel , Martínez José Luis Martínez
Published: April 2022

The Internet of Things (IoT) is growing globally at a fast pace. However, the expansion of the IoT paradigm has brought with it the challenge of promptly detecting and evaluating attacks against these systems. The Message Queuing Telemetry Transport (MQTT) protocol is one of the most used protocols in the IoT scenario due to its lightness. The MQTT-SN protocol, which is an even lighter version of MQTT, is specially designed for embedded devices on non-TCP/IP networks. This paper presents an exhaustive assessment of the MQTT-SN protocol and describes its shortcomings, which can allow an attacker to compromise the security of the entire IoT infrastructure. We have designed 3 different attacks in order to allow us to evaluate the different security impacts on a real MQTT-SN network. All the attacks were implemented and tested, and we show how they work and their impact on performance. Furthermore, a non-attacked scenario was also implemented to allow us to compare the performance of an attacked system with that of system without attacks.
Study on a Compatible Model Combining Point Cloud Model and Digital Elevation Model
Authors: Guo Wenbo , Zhao Jun
Published: April 2022

DEM is an important data source to describe the surface morphology, but it is not a real 3D model, which can not meet the requirements of true 3D description under the ground. LIDAR point cloud data is a new true 3D data with high precision and high density. Based on the analysis of the differences between DEM and point cloud data in acquisition method, data structure and model construction, this paper proposes a 3D point set data model based on regular grid 2D data field, as well as the idea of regional modeling, and tests the feasibility of the data model through the upper and lower boundary modeling method. The experiments show that: (1) the 3D point set data model based on regular grid 2D data field is compatible with complete DEM data and simplified point cloud data, and has good expansibility; (2) the newly-built data model can complete the true 3D modeling of simple underground entity with high efficiency when the amount of data is only doubled; (3) The new data model can be generated by inputting DEM data, point cloud data and simplified algorithm of point cloud data under the same coordinate system. It has the potential of large-scale, multi-scale and automatic output processing, and has a good prospect of popularization.
Resource Allocation Algorithm Based on Modeling of Ubiquitous Network Node Capability
Authors: Song Dai , Chen Xushan , Rui Lanlan , Li Wenjing , Du Zongpeng , Li Zhiqiang , Lu Lu
Published: April 2022

With the continuous development and progress of the Internet, computing power is gradually moving from the center to the edge. In order to perceive, measure, schedule and manage the distributed computing resources, it is necessary to model and evaluate the node capability. Based on the development trend of network computing convergence and the demand of network computing service scheduling, this paper studies the unified measurement model and resource allocation algorithm for the integration of network computing and heterogeneous resources. The node resources are divided into four dimensions: computing, communication, memory and storage, and on this basis, the comprehensive ability evaluation index is proposed. Through simulation analysis, the effectiveness of the resource allocation algorithm based on node capability modeling is verified.
Control Analysis of Propagation Dynamics on Networks
Authors: Zhu Zhiqiang
Published: April 2022

It is generally the dynamic behavior of multiple information in the network. Based on the principle of propagation dynamics and mathematical model, this paper simulates the dynamic process of information in the network, and analyzes the influence of network structure and propagation dynamics on the dynamic behavior of information in the network through the simulation results. By simulating the dynamic process of communication, we find that the location and release time of intervention information in the network will have an impact, and we can control the dynamic behavior of information in the network by controlling the location and release time of intervention information.
Stable Reverse Driving of a Tractor with Multiple Trailers
Authors: Jelenc Blaž
Published: April 2022

We address the problem of the stable reverse driving of a vehicle with multiple trailers. By itself, the reverse driving of a multiple trailer vehicle is highly unstable, so a proper steering control is needed. First, the straight reverse driving is analysed and a stable solution to the problem is explicitly calculated. The solution depends on the specific geometry of the vehicle, namely on the lengths of the tractor and the trailers, and on the set of parameters that determine the rate of convergence of the reverse driving towards the straight reverse driving. We describe two different approaches towards the derivation of the solution of the stable reverse driving. We show that the solution to the problem is uniquely determined and finally we show that the proposed solution can be easily applied to the reverse driving of the tractor along an arbitrary, gently curved, path.
Active Obstacle Avoidance Control Strategy Based on Four-Wheel Steering
Authors: Li Haiqing , Li Sijun , Xia Fuhao
Published: April 2022

Active obstacle avoidance control strategy is the main question of intelligent vehicles, and active four-wheel steering is gradually used in the intelligent control system. Considering both tracking performance and driving characters, an active controller with four-wheel steering (4WS) and active rear steering (ARS) based on adaptive model predictive theory (AMPC) is designed. The control architecture is composed a supervisor and an AMPC controller. The supervisor is used to select the appropriate control mode and the AMPC is used to calculate the expected steering angle when the stability indexes over the safety threshold. Finally, the proposed control strategy is simulated via Carsim-Simulink co-simulation. The results show that the integrated controller can track the obstacle avoidance path and has good driving performance.
Class Specific Dictionary Learning with the Independence Between-class and Dependence Intra-class Coefficient’s Constraint
Authors: Du Yu , Lu Yonggang , Zhao Ligang
Published: April 2022

In the field of image classification, deep learning has become the focus of research. But when the number of training samples is small, especially when there are a large number of intra-class variations in the small samples, the performance of deep learning is often not satisfactory. To deal with the problem, a new dictionary learning method based on sparse representation and an improved coefficient’s constraint is proposed. A general dictionary is learned to eliminate noise signal, and then based on the general dictionary, a class specific dictionary is learned by an improved coefficient’s constraint which maintaining the independence of the dictionary atoms between-classes, while allowing the dependence of the dictionary atoms intra- class. The class specific dictionary combined with the general dictionary is used for the image recognition. Experimental results show that, compared with the state-of-the-art dictionary learning methods, the proposed method usually shows better performance on image classification with small data sets.
Backstepping Adaptive Trajectory Tracking Control of Manipulator with Uncertainties of Model and State
Authors: Liu Yuhang , Zhang Lei , Zhou Jiaxin , Wang Xiaohua , Wang Wenjie
Published: April 2022

In this paper, a backstepping adaptive control method based on Kalman data fusion (KDF-BAC) is proposed to solve parametric and non-parametric as well as state variables in manipulator dynamics model. Firstly, the non-parametric uncertainties are regarded as internal disturbances to simplify the dynamics model of the manipulator. Secondly the backstepping control law is derived using the idea of recursive design, and the adaptive method is used to identify the uncertain parameters to provide the estimated value of unknown parameters for the backstepping control law. Finally, the Kalman data fusion method is used to reduce the uncertainty of the velocity information, and the most reliable estimate value is obtained, which is fed back to the controller. The simulation results show that the proposed KDF-BAC can reduce the influence of manipulator uncertainties on trajectory tracking performance, and has better control effect than adaptive control and backstepping control.
Modelling a Swarm of Delivery Drones for Disaster Relief Utilizing an Organization Approach
Authors: Kolesnikov Valeriy
Published: April 2022

This paper describes an organization-based approach to modelling an autonomous distributed system. This approach simplifies design of such systems and allows for a better understanding of the system overall. Such an approach is applicable for modelling a variety of distributed systems. We demonstrated it for a swarm system of autonomous drones used for disaster relief aid delivery.
Decision-Making Support Software Tools Based on Original Authoring Bayesian Probabilistic Models
Authors: Kozhomberdieva G I , Burakov D P , Khamchichev G A
Published: April 2022

The article presents programs that implement original approaches to group expert rating estimation and fuzzy inference. They implement probabilistic models based on Bayes’ Formula, previously proposed and published in the works of the authors. In these models, the estimated input data are interpreted as evidence in favor of one or another hypothesis from the set of possible ones, determined by the specifics of the model. All the evidence obtained is, in one way or another, transformed into a set of Bayesian conditional probabilities calculated under the assumption that the corresponding hypothesis is true, and the posterior probability distribution on the set of these hypotheses is used as the output. This distribution is used either directly as a result for decision making, or as a basis for calculating the final result. The features of the software implementation of models on the Java platform are discussed, the advantages of the models, confirmed or identified in the process of software implementation, are noted. The developed programs have a convenient graphical user interface and can be used as decision-making support tools to solve applied problems in the field of expert rating estimation and fuzzy inference.
Heart Rate Estimation Algorithm Based on Normalized Least Mean Square combining Complete Ensemble Empirical Mode Decomposition with Adaptive Noise
Authors: Cheng Jie , Yu Chengbo
Published: April 2022

Aiming at the difficulty of extracting heart rate due to the relative movement between human body and acquisition equipment, this paper proposes a Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDA) based on Normalized Least Mean Square (NLMS) adaptive filtering combined with fully adaptive noise sets for heart rate estimation. Firstly, an adaptive filter was used to filter the motion artifacts in the original signal by taking the triaxial acceleration signal as the reference signal. Then, the PPG signal was decomposed by CEEMDAN to obtain a series of Intrinsic Modal Functions (IMF) from high to low frequency. The Permutation Entropy (PE) criterion was used to determine the threshold range of the signal, so as to filter out the high-frequency noise and baseline drift. The results show that the Pearson correlation coefficient between the computed heart rate of PPG signal after noise reduction and the standard heart rate based on ECG signal is 0.742, and the average absolute error percentage is 6.08%, which indicates that the proposed method can accurately calculate the heart rate in the exercise state, and is beneficial to human physiological monitoring under the exercise state.
Study on the Methods to Estimate the Bed Shear Stresses in Yangtze Estuary
Authors: Gu Fengfeng , Lu Hanfang , Wan Yuanyang , Shen Qi , Wang Yuanye
Published: April 2022

High spatial and temporal current resolution velocities were measured by use of an acoustic Doppler velocimeter (ADV) in the tidal bottom layer of North Passage Deep water Navigational Channel (DNC) of Yangtze Estuary in China. And the vertical profiles of mean velocity were measured by using a pulse-coherent acoustic Doppler profiler (PC-ADP). The measured data show the vertical profiles of mean velocity are almost logarithmic. For discussing, the turbulent kinetic energy (TKE) method based on the velocity for ADVs-based is chosen and a new logarithmic profile (LP) method ignoring the influence of complex variation of the parameter Z
0 is suggested to estimate the bed shear stresses respectively. The calculated results show that the bed shear stresses estimated by LP method are larger than the ones estimated by TKE method mostly in Yangtze estuary. At the moment of ebb peak, the maximum error can be about twice occurring and the error of ebb tide is almost greater than the one of flood tide. These phenomena are explained in this study by the deduction of formula for steady and unsteady flow. It is concluded that the vertical logarithmic profile of velocities will be influenced by unsteady flow and there is not the same bed shear stress even if there is the same logarithmic velocity profile in vertical. Generally, this has led to a necessary adjustment of the drag coefficient Cd
of steady flow in flow model to avoid overestimating the bed stress for unsteady flow in estuary based on the observed data.
Active Power Joint Control Strategy for Hydro-wind-solar-storage Multi-energy Complementary Power Supply
Authors: Hu Lin , Shen Jianjian , Wang Yue
Published: April 2022

Compared with a single type of power supply, hydro-wind-solar-storage multi energy complementary system has obvious advantages in active power regulation performance. However, there are also many new problems in terms of coordinated control of multiple types of power supplies and giving full play to the performance advantages of various power supplies. Considering the regulation characteristics of different power supplies and the requirements of shallow charging and shallow discharging of energy storage battery, this study proposes a joint active power control strategy of multi-energy complementary power supply systematically. The basic regulation of hydropower is used to supplement the output of wind and solar power plants, while the compensation regulation of energy storage power supply is used to improve the stability of total output. Additionally, hydropower is used to charge and discharge the energy storage battery. The simulation results show that the proposed strategy can effectively give play to the regulation advantages of different power supplies, and meet the requirements of shallow charge and introduction.
JWST retrieval simulation of super-Earth
Authors: Barbier H , Lopez Izurieta E D , Manzaba Vélez A , Herrería Hoyos D A
Published: April 2022

The James Webb Telescope (JWST), launched at the end of 2021, will permit the study of exoplanets’ atmospheres with an accuracy never obtained before. One of the most keenly anticipated science themes with JSWT data is the study of super-Earth type planets. There exist many questions about their interior and atmospheric composition as well as their evolution and possible migrations.

In this work, we simulated transmission spectra of super-Earth type systems with the petitRADTRANS code and emission spectra of a M-type star with PySynphot. The primary transit observation is simulated with the MIRISim simulator working in the MIRI LRS-Slitless mode. We then obtained the transmission spectra of the planet using a code that we developed ourselves. Finally, we carried out the retrieval: first, in order to check the retrieval tool included in the petitRADTRANS code, we treated the original transmission spectrum. Second, the code is used with the spectrum obtained from the telescope simulator.

The results found encourage us to compare them to results found when using other tools, with the hope of gaining precision in those results, in addition to working in a wider range of wavelengths.
Ionospheric total electron content (TEC) above Ecuador
Authors: Lopez Izurieta E D , Toapanta Guamanarca E , Barbier H
Published: April 2022

The equatorial ionosphere over the Ecuadorian territory has not been previously studied, although there are some studies in other equatorial geographical positions, local research is required to characterize the ionospheric magnetoactive plasma in this region.

In this study, for the first time in Ecuador, using pseudophase and pseudorange data from the satellite signals of the GPS system, detected at the Riobamba-Ecuador (RIOP) station, the Total Electronic Content (TEC) is estimated in the period between the years 1999 and 2019. The TEC values and their daily, weekly, monthly and annual variation are calculated and compared with the observed data of the IGS network (International GNSS Service). The fit of the observed series with the series of the dispersive model has a goodness of fit of 0.88, which is quite acceptable. The adjustment can be improved by incorporating data from new local stations, as well as instrumental errors and delays and in the received signals, all of which were not considered in the present work.
Research on Degradation Characteristics of GaN-based LD
Authors: Zhang Chengwei , Liao Wenyuan , Wang Hongran , Lai Canxiong , lu Guoguang , Wei Zhipeng , Yang Shaohua
Published: April 2022

In recent years, GaN-based semiconductor laser diode(LD) have become an ideal light source for laser display, because of their high power and unique luminous wavelength. However, there is a challenge about reliability of GaN-based LD in industrial application. In this paper, an accelerated aging test is conducted on the same group of GaN-based LD at a high current of 4.1A. The degradation rate of GaN-based LD is obtained by least square method. Besides, the optical characteristics and low frequency electrical noise of LD are analysed after degradation. The results show that the lasing wavelength and low frequency electrical noise of GaN-based LD will increase after degradation. This helps to provide experimental reference for degradtion research of GaN-based LD.
Analysis on the Electrostatic Doping and Several Alternative Devices
Authors: Yu Chenxi
Published: April 2022

With the development of semiconductor technology, the size of precision instruments is becoming more and more stringent. The purpose of electrostatic doping is to provide a possibility on nanoscale semiconductor devices and to replace chemical doping, it also replaces donor/receptor doping with Gate-Induced free electron/hole charges in ultra-thin MOS (Metal-Oxide-Semiconductor) structures, and provide some areas with high electron/hole density in semiconductor devices. This paper introduces Electrostatic Doping methods and Several Alternative Devices, emphasizing the functions of metal and semiconductor operation functions, energy band gaps and applied electric fields, and their interaction in induced ED. In addition, this paper discusses the advantages of ED devices and the major potential obstacles to future CMOs, and the modeling and experimental implementation of this approach will help to implement and evaluate the possibility of replacing traditional doping methods for innovative devices for future CMOs.
Simulation Design of 3dB Orthogonal Directional Coupler
Authors: Jin Qi
Published: April 2022

Directional couplers can isolate, mix, and orient signals, and play an important role in RF circuits. In this paper, the quadrature coupler is firstly analyzed theoretically. According to the results of the theoretical analysis, a microstrip 3dB quadrature directional coupler with a new structure based on 2.2GHz is designed using ADS after the design objective is given. After repeated simulation optimization, the coupling degree is optimal.