bluuebunny/crossref_metadata_2025_split huggingface dataset:
PD-Based Control of Cart-Pole System on Inclined Plane with Variable Slope
Authors: Wang Yifan 
Published: April 2022

Abstract
For control research, the cart-pole system is one of the basic models. Various controllers for controlling under-actuated systems in unstable postures are available, according to the literature. In this paper, an off-line management of a variable slope cart-pole system is proposed. The system moves on a circular arc surface with a certain radius. The dynamic pattern of the cart-pole system is obtained by Euler-Lagrangian formulation, and the controllability analysis is considered. Initially, a Python model of the proposed system was created, which was then simulated with a PD controller. Based on the required joint angle, we can calculate the required control parameter distribution. By studying the differences in the stability time and steady-state error of the system under different parameters, the efficacy of the suggested method is proved, and the possibility of further parameter optimization is proposed. For the future study, the simulation of a more irregular trajectory would be inspired by this model and control of the cart-pole system on a non-linear trajectory.
Asymmetric Dilation Residual Distillation Network with Lightweight Image Super-Resolution
Authors: Hong Kai , Fan Kefeng , Li Fei 
Published: April 2022

Abstract
Deep learning approaches have achieved remarkable performances in single image super-resolution (SISR) while the heavy memory consumption and computational complexity hinder their applications in real-world devices. We design a lightweight asymmetric dilation distillation network (ADDN) that cascades asymmetric dilation distillation modules (ADDMs) as feature extraction blocks to efficiently refine hierarchical features. In our design, asymmetric dilation residual block (ADRB) is connected by the ADDM in an information distillation manner. Specifically, the ADRB regulates the dilation factors to expand different multiples of receptive fields and substantially reduces the number of parameters simultaneously. Compared with the existing methods quantitatively and qualitatively, the proposed ADDN can achieve superior performance on four available benchmark datasets with much fewer parameters and memory storage.
Improved Routing Protocol Algorithm Based on Hierarchical Clustering*
Authors: Wang Gaiyun , Liu Jianbin , Shen Jintao , Zhang Bin , Sun Chuanfeng , Guo Zhichao 
Published: April 2022

Abstract
In order to allocate network energy consumption more scientifically and save the cost of the system, an improved wireless sensor networks algorithm is proposed. The algorithm uses hierarchical clustering, using the Chaos algorithm and evaluation function to optimize the cluster head selection. Simulation results show that compared with LEACH and JC-LEACH, the algorithm has a longer system life cycle, better energy-saving effect, and a more balanced energy consumption mode.
A composite image recognition based approach for spontaneous combustion point detection and positioning in coal piles
Authors: Wu Fuhui , Zhou Zhihao , He Xingwei , Wang Zhan , Li Junhai , Ruan Yaliang , Lei Hao 
Published: April 2022

Abstract
The phenomenon of spontaneous combustion of coal piles often occurs in closed coal yards of power plants, automatic fire-fighting equipments are generally used to detect and locate the spontaneous combustion point. However, their performance (false alarm rate) are largely limited due to the complicated environment of the coal yard. To deal with this problem, this paper proposes a composite image recognition based method for detecting and positioning the spontaneous combustion point (SCP) in coal yard. Yolov5s is trained to efficiently detect SCPs and infrared information is fused to distinguish the realiability of SCP detection result via composite image registration method. In addition, an angle compensation algorithm is proposed to adjust the spray angle of the equipment for positioning the cooling area. The experimental results show that after integrating the above related technologies, the false alarm rate of the spontaneous combustion point in the scene is greatly reduced, and the work efficiency is effectively improved.
Multiple Granularity Person Re-identification Network Based on Representation Learning and Metric Learning
Authors: Liu Panting , Du Haishun , Sha Junpeng 
Published: April 2022

Abstract
Powerful local features can be extracted from multiple body regions of a pedestrian. Early person re-identification research has focused on extracting local features by locating regions with specific pre-defined semantics, which is not effective and increases the complexity of the network. In this paper, we propose a multiple granularity person re-identification network based on representation learning and metric learning for learning discriminative representations of pedestrian images. Multiple granularity person re-identification network consists of a multiple granularity feature extraction part and a combined loss part. In particular, the multiple granularity feature extraction part extracts global features and local features of different granularities from the feature maps of Conv4 and Conv5 of the ResNet50 backbone network, respectively, the extracted feature information is more comprehensive and discriminative. The combined loss part employs a joint representation learning and metric learning approach for supervised learning, which enables the model to learn more optimal parameters. The experimental results show that the Rank-1 accuracy of the multiple granularity person re-identification network reaches 95.2% and 88.2% on the Market1501 dataset and DukeMTMC-reID dataset, respectively, which illustrates the effectiveness of the model.
Application of Dunkl Wavelets to solve the Integral Equations
Authors: Dixit M M , Pandey C P , Pandey Abhishek Kumar , Phukan Pranami 
Published: April 2022

Abstract
The Integral Equation appears in different fields of science and engineering mathematics, for example image processing and the concept of electromagnetic. The technique of wavelet transform to find the solution of integral equations allows creating an algorithm after comparing with known algorithms. This paper is about the uses of the Dunkl Wavelet transforms and associated convolution to establish some suppositions for solution of these equations on distribution spaces. This work defined the method to solve various integral equations by using the Dunkl wavelet transforms.
Improvement of Starting Point Selection of Data Field Clustering Algorithm
Authors: Wang Lei , Li Tianyu , Xu Huiqi , Zhang Zhiyong 
Published: April 2022

Abstract
Since it does not depend on the starting point selection, data field clustering can perform unsupervised clustering according to the data distribution characteristics. However, due to its drawback of high computational complexity caused by iterative updates, it is not suitable for the scenarios with high real-time requirements such as radar signal sorting. In this paper, an improved method of starting point selection is proposed to address the problems of low timeliness and poor interference immunity of data field clustering in radar signal sorting. The performance of the improved algorithm is simulated and verified in a complex electromagnetic environment, and the results show that the improvement of the data field clustering in this paper improves the performance of the algorithm.
Research on Missile Firing Practice Evaluation Method of Online and Offline Integration
Authors: Zhong Zhitong , Zhang Lin , Huyan Xiaoyang 
Published: April 2022

Abstract
This paper is meant to test the missile combat capability and operators practical operating standard, in view of the fire training effect and after-fire analysis and research under the background of practical combat. The research is realistic &honest in evaluation and assessing exercises, training,practices that lead to better fire result. Combined with the practical needs of man-in-the-loop missile fire training evaluation, the paper advances the on-line evaluation with off-line review evaluation concept, which has been applied to missile fire training evaluation for many a times, and the close analysis and synthesis of relevant case studies provides a great help to the military field training.
Development of a Geometric Cutting Aided System for Tin-sprayed Steel Mesh
Authors: Luo Ming , Li Gui , Ding Zixi 
Published: April 2022

Abstract
The design of tin-sprayed steel mesh is particularly important in the production of tin-sprayed steel mesh, which is the key to ensuring the function and quality of the tin-sprayed steel mesh. At present, the tin-sprayed steel mesh is still manually designed, and the design process is error-prone and inefficient. Therefore, a geometric cutting assistance system for tin-sprayed steel mesh of the combiner based on AutoCAD and ObjectARX was developed. The system adopts a parameterized design to realize the automatic operation of the steel mesh cutting process. First introduced the system development environment and composition architecture, and briefly explained the system interaction interface. Then it explains two key methods in the software system design and development process, including cutting quality control and finding the intersection of line segments. Finally, the actual case proves that the system greatly improves the efficiency and quality of steel mesh cutting.
Towards Speech Recognition and Training Utilization in the Nuclear Power Main Control Room
Authors: Wang Zhiminxing , Deng Shiguang , Duan Pengfei , Xu Yunlong , Li Wanting 
Published: April 2022

Abstract
Speech, as the material shell of language, is the external form of language, and is the symbol system that most directly records people’s thinking activities. As a means of interaction, it has the characteristics of simplicity and speed. For a long time, due to insufficient recognition accuracy, it cannot be applied in industry. However, with the rapid development of big data and machine learning technology, the training effect of speech model has greatly increased, and the reliability of speech recognition has been greatly improved. The application of speech interaction in nuclear power plants with extremely high safety requirements brings feasibility. The purpose of this system is to establish an intelligent speech control system and its related speech model training system, and use Kaldi and Python scripts as model training scripts to train the corpus. And designed experiments to verify that after using speech recognition, it can effectively reduce the operation time by about 45%, and the overall task execution efficiency has been significantly improved. Therefore, the use of speech recognition can significantly reduce the operator’s task load and reduce the probability of human error.
Numerical Analysis of Mechanical Response Characteristics of Jointed Tunnel Surrounding Rock under Dynamic Loading
Authors: Li Chao , Shi Zhongqi , Li Jinhui , Xiang Yanting 
Published: April 2022

Abstract
The jointed rock mass is widely distributed in nature, which has certain impact on the stability of the underground tunnel. In order to study the response characteristics of jointed tunnel surrounding rock mass under dynamic loading such as earthquake and explosion, the tunnel surrounding rocks with different distributed joints are simulated and studied by RFPA numerical analysis method, and the failure process of tunnel surrounding rock is obtained. The numerical results show that under the action of dynamic loading, the tunnel surface reflects the stress wave and form a tensile failure zone, resulting in serious instability and failure in the zone; The stability of tunnel surrounding rock is closely related to the distribution of joints; The interaction between tunnels increases the failure of surrounding rock mass, so a safe distance should be maintained between tunnels. The research results of this paper provide guidance for tunnel route selection and surrounding rock reinforcement design.
High Level Integrated System of Space Detector Network Integration
Authors: Zhang Ying , Ma Zheng , Niu Zhichao , Feng Li 
Published: April 2022

Abstract
In order to meet the requirements of high reliability and low power consumption during the operation of aircraft, this paper adopts the high-level synthesis method to map the high-level language into RTL level code that can run directly on FPGA, and proposes an intelligent integration system for aircraft based on high-level synthesis. The input of aircraft system is image radar sensor data, visible image data and infrared image output. The output of the aircraft system is target identification. Including convolutional IP core, pooled IP core and fully connected IP core. The whole system uses 7-layer deep learning neural network structure, which is convolution IP core, pooled IP core, convolution IP core, pooled IP core, fully connected IP core, fully connected IP core, fully connected IP core.
Harmonics Current Detection in Three-phase Circuit using Neural Network
Authors: Liang Jian , Zhang Shuang , Ren Yong , Cheng Yuanchu 
Published: April 2022

Abstract
Harmonics seriously affect the safety and economy of power system. In order to control harmonics effectively, harmonic current and harmonic power must be detected quickly. Based on the analysis of the components of three-phase nonlinear current, a neural network detection method of fundamental and harmonic current in three-phase circuit is proposed. The method uses a neural network instead of the low-pass filter in the instantaneous reactive power theory. The example results show that the proposed method has the advantages of less computation, better real-time performance and high detection accuracy. The method can be used to detect the positive-sequence (negative-sequence) fundamental active current, positive-sequence (negative-sequence) fundamental reactive current, harmonic, distortion current and harmonic power.
Analysis of Image Restoration Based on EM Algorithm
Authors: Lu Yujie 
Published: April 2022

Abstract
Image noise is mainly introduced in the process of image imaging. Different imaging mechanisms lead to different distribution characteristics of image noise. The maximum likelihood method is a commonly used parameter estimation method, which can obtain a good estimation effect for Gaussian distribution, but it has the disadvantage of relatively complicated calculation when it is used for parameter estimation of mixed Gaussian distribution. However, it has the disadvantage of relatively complicated calculation when it is used for parameter estimation of mixed Gaussian distribution. The EMs of this paper flexibly bring their blurring effects. The solution of the maximum likelihood equation is simplified by introducing potential variables, which has the advantages of smooth implementation of equations, stable numerical calculation, and guaranteed convergence to a stable point to make up for the deficiency of the maximum likelihood method
Onchip digital calibrated 2 mW 12-bit 25 MS/s SAR ADC with reduced input capacitance
Authors: Hernandez Herrera H.D. , Bregant M. , Sanchez B. , Van Noije W. 
Published: April 2022

Abstract
We present a 12-bits asynchronous SAR ADC with a low complexity digital on-chip calibration and just 2 pF of total array capacitance. The ADC architecture utilizes a redundant weighting switching of 2 fF MOM capacitors consuming 14 clock-cycles to complete the conversion. Taking advantage of redundancy, the weights of the MSB capacitors are estimated using the LSB array, thus it is possible to digitally compensate for the mismatch non-linearity directly over the ADC output. The circuit consumes 2 mW at 25 MS/s on a core area of 300 μm × 500 μm in 180 nm CMOS technology. ENOB improvements of 0.85 bits were post-layout simulated after calibration. Sample characterization is ongoing.
Beam diagnostics for linear accelerator of SKIF synchrotron light source
Authors: Xiaochao M. , Maltseva Yu.I. , Meshkov O.I. , Arsentyeva M.V. , Bekhtenev E.V. , Cheskidov V.G. , Borin V.M. , Karpov G.N. , Nikiforov D.A. , Pavlov O.A. , Volkov V.N. 
Published: April 2022

Abstract
As the injector of the new fourth-generation SKIF
synchrotron light source at the BINP SB RAS (Novosibirsk, Russia),
the linear accelerator will provide a 200 MeV electron beam. A
precise measurement of the beam is very important for the control of
the linac and even the entire light source. A set of diagnostic
instruments for tuning the linac and measuring the beam parameters
starting from the electron RF gun to the output of accelerator has
been designed. The instrumentation should cover the dynamic
diagnostic range of 0.6 to 200 MeV and a beam duration from the
initial 100 ps to 3 ps at the output of the accelerator. The set
includes eight fluorescent screens to measure beam transverse size,
two Cherenkov probes and RF-cavity sensors to record beam duration,
a dipole magnetic spectrometer to measure energy and energy spread,
a Faraday cup (FC) and fast current transformers (FCTs) to measure
beam charge current, and beam position monitors (BPMs) to check the
beam position. This paper aims to give an overview of the beam
instrumentation and briefly describes the design and parameters of
each diagnostic system. The results of numerical and dynamics
simulations of some of the instruments are briefed. Possible
scenarios of linac tuning are discussed.
Impermanence and failure: the legacy of conservation-based payments in Sumatra, Indonesia
Authors: Erbaugh James T 
Published: April 2022

Abstract
Projects that pay communities or individuals to conserve natural areas rarely continue indefinitely. When payments cease, the behaviors they motivate can change. Previous research on conservation-based payments recognizes the impermanence of conservation success, but it does not consider the legacy of payments that failed to effect change. This research assesses impermanence and failure by investigating the legacy of village-level conservation payments made through one of the largest Integrated Conservation and Development Projects in Indonesia. The Kerinci-Seblat Integrated Conservation and Development Project aimed to conserve forest area and promote local development through voluntary conservation agreements (VCAs) that provided payments for pro-conservation pledges and activities from 2000 through 2003. Project documentation and previous research find that payments failed to incentivize additional forest conservation, producing nonsignificant differences in forest-cover change during the project period. To examine the legacy of these payments in the post-project period, this research uses matched difference-in-differences and triple differences models to analyze forest cover change in villages (n = 263) from 2000 through 2016 as well as matched binary logistic regression models to assess enduring differences in household (n = 1303) livelihood strategies within VCA villages in 2016. The analysis finds that VCA villages contained significantly more forest loss than the most similar non-VCA villages outside the national park, and greater payments predict increased forest loss in the post-project period. In addition, farming high-value tree crops and cultivating private land were the most important attributes for modeling VCA affiliation among randomly selected households. These results demonstrate that, after payments ceased, project failures increased in severity over time.Those who design and implement conservation-based payments bear great responsibility to ensure their projects are informed by local voice, align with community preferences, and provide sufficient benefits, lest they result in a conservation legacy of increased failure.
Study on epoxy resin modified by hyperbranched polysiloxane containing active amino group and its properties
Authors: Xiao Mengting , Cai Haopeng 
Published: April 2022

Abstract
A novel phosphorous/silicon hybrid containing active amino was synthesized by bisphenol F epoxy resin modified by 0-(2,5-Dihydroxyphenyl)−10-hydro-9-oxa-10-phosphaphenanthrene-10-oxide (ODOPB) and hyperbranched polysiloxane (APTMS-HPSi). At first, APTMS-HPSi was synthesized by a simple reaction among aminoethylamino propyltrimethoxy silane (APTMS) and tripropylene glycol (TPG). ODOPB was used to modify bisphenol F epoxy resin. Then add different content of APTMS-HPSi to the phosphorus-containing modified epoxy resin (P-EP). Fourier Transform Infrared (FTIR) Spectroscopy was used to characterized the chemical structure of APTMS-HPSi. The effects of APTMS-HPSi content on key properties was systemically investigated. Results showed that the addition of APTMS-HPSi and ODOPB effectively improve the toughness and liquid oxygen compatibility. With the increase content of APTMS-HPSi, char yield and limited oxygen index (LOI) value of the cured resin increased, and the liquid oxygen sensitivity coefficient (IRS) decreased. The elongation at break was increased 45.32% by only 6wt% loading with APTMS-HPSi in epoxy resin, and at the same time the IRS of the modified resin was reduced from 7% to 0%. When the addition amount was 6wt%, the fracture elongation, impact strength and fracture toughness KIC were increased by 52.1%, 81.8% and 54.3% respectively. Therefore, adding phosphorus and hyperbranched polysiloxane to the resin can improve the liquid oxygen compatibility and toughness of the epoxy resin at the same time.
Micro-impulse and plasma plume produced by irradiating aluminum target with nanosecond laser pulses in double-pulse scheme
Authors: YU Chenghao , YE Jifei , ZHOU Weijing , CHANG Hao , GUO Wei 
Published: April 2022

Abstract
The micro-impulse generated by ablating an aluminum target in double-pulse laser bursts with different interpulse delays was investigated using a torsion pendulum. The plasma plume was simultaneously visualized using high-speed photography to analyze the coupling mechanism of the ablation impulse. The experiment was carried out using a pulsed laser with a pulse width of 8 ns and a wavelength of 1064 nm. The experimental results show that an impulse with an interpulse delay of 60 ns is roughly 60% higher than that with no delay between the two pulses, when the energy of both laser pulses is 50 mJ. Therefore, double-pulse schemes could enhance the ablation impulse under certain conditions. This is because the ablation of the first laser pulse changes the optical properties of the aluminum target surface, increasing the absorptivity. However, the ablation impulse is reduced with a time delay of 20 ns when the energy of both laser pulses is 100 mJ or 150 mJ. It can be concluded that the plasma produced by ablating the aluminum with the first pulse shields the second laser pulse. To summarize, the experimental results show that different delay times in a double-pulse scheme have a significant effect on the ablation impulse. The study provides a reference for the optimization of the parameters when laser ablation propulsion with a double-pulse scheme is applied in the fields of space debris removal, laser ablation thrusters, and so on.