bluuebunny/crossref_metadata_2025_split huggingface dataset:
Research on AdHoc network routing algorithm for link stability prediction
Authors: Xu Xiaoling , Cui Wei 
Published: August 2024

Abstract
This study aims to improve network communication efficiency and reliability by researching routing algorithms for predicting link stability in AdHo networks. AdHoc network is a self-organizing, decentralized network structure in which nodes establish temporary connections through wireless communication, making the network resilient and flexible. However, due to the continuous changes in network topology and the instability of wireless links, routing problems in AdHoc networks have become particularly complex. This article proposes a backup path routing algorithm LS-BPR based on link stability prediction. This mechanism takes the path with the minimum delay as the main path, uses the cost function as the standard for selecting backup paths, and then uses the ARIMA model to predict links with good link stability as backup paths. We simulate and compare LS-BPRAODV and AODV protocols using the QualNet simulation platform. The simulation results show that the LS-BPRAODV, with the addition of a prediction mechanism, improves network performance, reduces the number of source node routing discoveries, reduces the number of route breaks, significantly reduces the packet loss rate and information reception delay in the network, and improves the average throughput of the network. This study provides new theoretical and empirical support for the routing algorithm for link stability prediction in AdHo networks, which is of great significance for promoting the development of wireless self-organizing networks.
A stable satellite routing algorithm based on a-star algorithm in dynamic networks
Authors: Sun Xiaohui , Shen Yuefeng , Zhang Huibin 
Published: August 2024

Abstract
This paper focuses on solving the routing optimization problem under the dynamic topology of the satellite communication network. With the rapid development of low-earth-orbit (LEO) satellite network communication technology, the dynamically changing topology of satellite networks has brought about frequent link switching and triggered a large number of routing updates. This paper proposes an improved routing algorithm named the Stable A-Star Routing (SASR) algorithm. The SASR algorithm is based on the A-star algorithm and aims to reduce path-switching frequency and enhance path stability by optimizing the path selection strategy. Through detailed simulation experiments and performance evaluation, we verified the performance advantages of the SASR algorithm in terms of the number of path switches, the number of path hops, the route convergence time, and the occurrences of congestion in business under different business volumes, and conducted comparative studies with classic algorithms. The results show that the SASR algorithm offers obvious advantages in key performance indicators. Compared with the Dijkstra algorithm and the A-star algorithm, the average number of path switches can be reduced by 22% and 10%, respectively. It shows more prominent advantages under a larger business volume, providing an efficient and reliable solution for routing optimization under the dynamic topology of satellite communication networks.
Application of an improved simulated annealing algorithm in satellite network routing
Authors: Liu Haojiang , Zhang Huibin 
Published: August 2024

Abstract
Satellite communication is integral to modern communication systems, yet navigating the intricacies of routing in networks characterized by high loads and dynamic evolution poses a significant challenge. This research is dedicated to enhancing satellite communication routing algorithms, with the goal of bolstering network efficiency and amplifying the success rate of business transmissions. Our approach introduces an improved simulated annealing algorithm incorporating adaptive temperature control and innovative path neighborhood exploration strategies. This novel algorithm is adept at adjusting to ever-shifting network topologies and meeting various business requirements. Our simulation results reveal that this refined algorithm outperforms traditional annealing methods in several critical aspects. It elevates the success rate of business transmissions, reduces the average number of forwardings by 6.546% across various load scenarios, and diminishes system response time by 15.05%, thereby marking a substantial improvement in network performance.
Dual-Branch feature fusion residual neural network for individual radar signal recognition in low SNR environments
Authors: Jing Zehuan , Li Peng , Yan Erxing , Chen Yingchao , Zhang Jiamiao , Wu Bin , Gao Youbing 
Published: August 2024

Abstract
To address the challenge of radar emitter signal individual recognition, where single-dimensional radar fingerprint features are susceptible to noise interference and neural networks exhibit low recognition accuracy in low signal-to-noise ratio (SNR) environments, this study introduces a residual neural network predicated on a two-branch feature fusion. This approach amalgamates two-dimensional time-frequency domain features with one-dimensional intermediate-frequency signal features. Unlike existing algorithms, our proposed method integrates the knowledge gleaned from features learned across different dimensions. This integration enables the neural network to utilize features from multiple dimensions for recognition, thereby mitigating the impact of noise on a single feature. Experimental results demonstrate that our proposed algorithm outperforms others under various low SNRs, achieving an average recognition rate of 88.39%.
FPGA-based tiling scheme and on-chip memory scheduling scheme for multi-branch semantic segmentation neural network accelerator
Authors: Li Hui , He Pengyu , Lu Shengli 
Published: August 2024

Abstract
According to the characteristics of a multi-branch semantic segmentation neural network with a large amount of intermediate data during the inference process, we reduce the requirement of off-chip memory access and the redundant calculation due to tiling through better blocking scheme, better on-chip memory partitioning scheme, and on-chip memory scheduling scheme, improving the energy efficiency to 77.4 GOPS/W.
Implementation of turbo decoding for VDES signal data segments
Authors: Zhang Haotian , Wang Jianxin 
Published: August 2024

Abstract
The International Telecommunication Union (ITU) mandates the use of turbo coding for VDES signal data segments. Previous studies primarily focused on turbo decoding for a specific link in VDES, often neglecting its applicability to all links. This paper proposes an FPGA-based implementation method for turbo code decoding, aiming to achieve fast and accurate turbo decoding of VDES signal data segments, while also ensuring compatibility with different links. The resulting turbo decoder can adapt to the different code rates and data segment lengths specified in the VDES. A comparison of the decoding speeds between DSP and FPGA confirms that the parallel computing capability of FPGA can significantly improve the decoding speed. Finally, the main onboard resources required for FPGA implementation of turbo decoding were provided.
Research on signal equalization technology based on visible light communication
Authors: Wang Hetao , Weng Qing , Liu Hao 
Published: August 2024

Abstract
Visible Light Communication (VLC) transmits signals through visible light and realizes the two functions of lighting and communication at the same time without the need for other hardware equipment. There are still some shortcomings in the visible light communication system. The optical signal propagated indoors is affected by inter-symbol interference (ISI) and external light noise at the receiving end. The signal will be severely distorted. These factors will significantly reduce the accuracy of the received signal decision, thereby seriously affecting the performance of the visible light communication system. Given the problems of intersymbol interference and optical noise in indoor visible light systems, this article studies adaptive equalization technology and modulation and demodulation technology suitable for visible light communication systems and improves the signal-receiving end equalization. Based on the existing equalizer structure, we combined the advantages of two different equalizers and optimized their combined structure parameters. On this basis, we added the MAP algorithm and proposed a hyperbolic tangent function to improve the traditional error function. The defects speed up the convergence speed without changing the mean square error. Experimental results show that the algorithm has improved in convergence performance. The algorithm’s convergence speed is 53.6% higher than the traditional algorithm, the steady-state error is reduced by about 6 dB, and the steady-state error of the algorithm is reduced by about 5 dB respectively.
Design and Analysis of Gas Cyclone with Arc-Shaped Cone Using Bézier Curve for Improved Performance
Authors: Abdo Toka A , Elnady Abdelrady O , Elsayed Khairy , El-shaer Yasser I 
Published: August 2024

Abstract
The research investigates novel gas cyclone separators with curved conical sections, comparing eight configurations with varying curvature sizes. Gas cyclones are traditionally used as particle separators to remove dust from gas streams, aiming to achieve a dust-free gas flow at the exit pipe while recovering particles to the dust outlet. Computational fluid dynamics (CFD) was employed to model the gas cyclone using the Reynolds stress turbulence model (RSM); the study examines flow fields and pressure losses. It finds that increased curvature correlates with reduced pressure drop. The curved profile is derived from the Bézier curve, characterized by a set of control points determining its shape. This study examines eight cyclone configurations with the intermediate point placed at varying fractions of the main radius: 1/8, 1/4, 3/8, 1/2, 5/8, 3/4, 7/8, and the main radius itself. The investigation focuses on the impact of different conical segment shapes on cyclone performance, highlighting how convex variants outperform others at higher flow rates while concave variants exhibit higher pressure drop. The pressure drop in the convex variant with an intermediate point position equal to the main radius decreased by 50%. These findings suggest the potential of the convex variant in certain operating conditions over traditional designs with improved particle capture efficiency.
Modelling stress-strain curves and forming limit curves using deep learning
Authors: Eldin Salem Hossam , Elatriby Sherif A. , Mohamed Mohamed 
Published: August 2024

Abstract
The sheet metal forming process stands one of the most principal applications in production engineering with the goal of producing defect free products possessing the mechanical properties that met the working conditions requirements. The efficient metal forming process relies on a deep understanding of the material behaviour during the forming process. To achieve this, feasibility studies for new incoming components helps determine if a part is feasible for manufacturing or if design modifications are required. This simulation requires an accurate material card to replicate the real material behaviour, requiring extensive material testing data such as stress-strain curves and forming limit curves (FLC). Artificial intelligence, specifically deep learning, is a promising tool to overcome such challenges. In this study, one of the deep learning algorithms, the artificial neural network (ANN), is utilized to create material testing data for building the material cards for feasibility simulation.
A developed products’ families commonality Index based on variants’ similarity.
Authors: Hesham Fatma , Zamzam N. , Shedid GE , El-Kharbotly A.K. 
Published: August 2024

Abstract
Commonality indices used to assess the shared features of product families are crucial tools for benchmarking and redesigning these families. They also play a significant role in optimizing manufacturing systems by adding or removing components/modules to product platforms during delayed customization stages. Although several indices have been developed by researchers to measure commonality across product family variants, these indices are often only suitable for specific applications with specific configurations. In the present research, a new commonality index has been developed based on the similarity features of each pair of variants within a product family. The developed index is useful for clustering family variants into subfamilies, each with high components’ sharing ratio, facilitating the design of necessary product platform/s for delayed customization manufacturing systems. The results of applying this developed index to determine commonality across product family variants were compared with those obtained from several known commonality indices. The new index proved to be effective and sensitive in distinguishing between the commonalities of different product families. Additionally, the index was found to be effective in categorizing products into homogeneous families, grouping variants that share certain similarities and commonality features.
Virtual power plant optimization with demand response and multi-complementary energy planning
Authors: Jia Dongsheng , Bai Di 
Published: August 2024

Abstract
To effectively address the increasing complexity of system operation optimization and resource allocation caused by the continuous enrichment of supply-side resources and the flexible variability of demand-side loads in the energy system, a robust optimization model for virtual power plants considering demand response and multi-energy complementarity is proposed. Handling renewable energy and load uncertainty in virtual power plants by building a two-stage robust optimisation model. The introduction of robust coefficients allows for flexible adjustment of the conservatism of the optimized scheduling. Results indicate that considering demand response and multi-energy complementarity can effectively enhance the system’s robustness and flexibility.
Research on a transmission line defect identification method based on voiceprint recognition
Authors: Cheng Qi , Du Jikuan , Gao Yinghong , Li Lin , Li Junming , Yu Xin 
Published: August 2024

Abstract
With the continuous development and improvement of China’s power system, the length and coverage of transmission lines are getting larger and larger, making it inevitable that transmission lines will pass through areas with harsh environments and complex geographical environments. If defects are not discovered and handled properly, over time, serious losses will be caused. Traditional manual inspections can no longer meet actual requirements due to low efficiency. This paper proposes a transmission line defect identification method based on voiceprint recognition. First, the sound signal collected by the sensor is divided into frames and windowed for preprocessing. Then, feature extraction is performed based on the Mel frequency cepstral coefficient. Finally, the extracted vector is used to train the nearest neighbor classifier, and the trained classifier can identify defects in transmission lines.
Unified monitoring and online maintenance technology of substation secondary equipment
Authors: Su Faliang , Zheng Suisheng , Ji Rongrong , Ma Wei , Chai Changqing 
Published: August 2024

Abstract
To meet the needs of the promotion of “equipment ownership” and the implementation of a centralized monitoring mode in substations, a technical scheme of unified monitoring, online operation, and maintenance for secondary equipment in substations is proposed, considering the monitoring, operation, and maintenance requirements of secondary equipment such as protection devices and automation devices. A secondary equipment monitoring real-time gateway is arranged in Security Zone I. The comprehensive operation status data of various secondary equipment is collected, analyzed, processed, diagnosed, and applied through various apps, to realize heterogeneous access, on-demand deployment, and flexible expansion. The master station is designed with functions such as human-machine interaction and remote analysis for secondary device monitoring and operation. GSP, MQTT, and other service-oriented and message mechanism communication protocols are adopted between the substation and the master station to meet the diversified and easily expandable information exchange requirements. Through the factory test, it is verified that the scheme can realize the panoramic perception of the operation state of the secondary system and effectively improve the ability of abnormality diagnosis and processing.
An intelligent analysis method for power flow of bulk power grid based on fusion of indicator system feature and image feature
Authors: Cao Hongbo , Liu Jun , Ren Bixing , Chen Xinglei , Li Qiang 
Published: August 2024

Abstract
At present, the adjustment of power flow non-convergence in large power grid is still mostly based on manual trial and error, which relies heavily on expert experience and is inefficient. Therefore, an intelligent power flow analysis method based on index system and image feature fusion is proposed. Firstly, the power flow index system is constructed according to the actual demand, which can provide data support for the following power flow convergence judgment problems. Secondly, taking into account the constraints of similarity and ternary loss, the image feature information is used to guide the output of the information feature representation and to realize the organic interaction of the two modal features. On this basis, the calculation result of the index is correlated with the actual state of power flow to judge the convergence of power flow. Finally, the proposed method is verified on the CEPRI36 nodes system and a large power grid in China. The simulation results show that the accuracy of power flow convergence judgment is 100% for CEPRI36 nodes system and 99.83% for some domestic large power grid. It can effectively predict the convergence of the power flow before the calculation of the power flow required by the project and can provide the basis and theoretical support for the power flow optimization adjustment based on the indicator data.
On the contact of an absolutely rigid stamp with a half-plane taking into account static friction
Authors: Hakobyan V N , Amirjanyan H A , Grigoryan A H 
Published: August 2024

Abstract
The plane deformable state of an elastic half-plane into which an absolutely rigid stamp is pressed with friction is considered. It is assumed that the tangential stresses acting in the contact zone are related to normal pressure by the law of dry friction, the coefficient of which is a linear function of the coordinate of the contacting points of the contacting bodies. A determining singular integral equation for the stated problem is obtained, the solution of which is constructed in closed form. Numerical analysis is conducted, and regularities in the variation of contact stresses are determined depending on the ratios of horizontal and normal loads applied to the stamp.
Mechanical behavior of GFRP-Polymer sandwich composites with montmorillonite nanoclay
Authors: Sharma A P , Purusothaman M , Mohan T P , Kanny K , Velmurugan R 
Published: August 2024

Abstract
A sandwich composite consists of high stiffness and high strength outer layers called face sheets and low-density inner layers called core. In the present study, the sandwich composites comprising glass fabric/epoxy face sheets and epoxy modified with montmorillonite (MMT) nanoclay core are fabricated by a co-curing method. The sandwich panels show higher static tensile and three-point flexural properties such as ultimate strength, elastic modulus, and failure strain on adding up to 3 wt.% of MMT nanoclay contents than pristine sample. The former properties reduce at 4 and 5 wt.% of nanoclay contents owing to the formation of clustering of clay particles within the matrix. The stress-strain behavior of sandwich panels with 0–5 wt.% of MMT nanoclays obtained by laminated plate model follows experiments. The maximum lateral deflection of sandwich panels with nanoclays predicted by assuming them to be a simply supported beam is in-line with experimental results. For low-velocity single impact perforation load, the maximum force of sandwich panels improves on the infusion of up to 3 wt.% of clay while maximum displacement decreases. The ballistic limit velocity and energy absorption of panels improve on adding up to 3 wt.% of clay. Beyond the ballistic limit at different initial velocities, the residual velocity of sandwich panels decreases on addition of up to 3 wt.% of clay and energy absorption increases.
Dynamics of two cylinders in a cavity filled with liquid under modulated rotation
Authors: Vlasova O A 
Published: August 2024

Abstract
The dynamics of cylindrical bodies in a rotating horizontal cylinder filled with a high-viscosity fluid is experimentally studied. The cylinder rotation rate is modulated. When the cylinder rotates uniformly, the bodies are located near the cylindrical wall and rotate together with the cylinder. The dynamics of bodies depending on the amplitude and frequency of modulation of the cylinder rotation rate is studied in detail. It is found that the cylindrical bodies undergo azimuthal and rotational oscillations. When the critical amplitude of modulation is reached, the bodies repel from the wall and obtain a steady state position at some distance from the wall.
Response of the first POLAR-2 prototype to polarized beams
Authors: Kole Merlin , Angelis Nicolas De , Bacelj Ana , Cadoux Franck , Elwertowska Agnieszka , Hulsman Johannes , Li Hancheng , Łubian Grzegorz , Kowalski Tomasz , Koziol Gilles , Pollo Agnieszka , Produit Nicolas , Rybka Dominik , Stil Adrien , Sun Jianchao , Wu Xin , Zezuliński Kacper , Zhang Shuang-Nan 
Published: August 2024

Abstract
POLAR-2 is a dedicated gamma-ray polarimeter currently
foreseen to be launched towards the China Space Station around
2027. The design of the detector is based on the legacy of its
predecessor mission POLAR which was launched in 2016. POLAR-2 aims
to measure the polarization of the Gamma-ray Burst prompt emission
within the 30–800 keV energy range. Thanks to
its high sensitivity to gamma-ray polarization, as well as its large
effective area, POLAR-2 will provide the most precise measurements
of this type to date. Such measurements are key to improve our
understanding of the astrophysical processes responsible for
Gamma-Ray Bursts. The detector consists of a segmented array of
plastic scintillator bars, each one of which is read out by a
Silicon PhotoMultiplier channel. The flight model of POLAR-2 will
contain a total of 6400 scintillators. These are divided into 100
groups of 64 bars each, in so-called polarimeter modules. In recent
years, the collaboration has designed and produced the first
prototypes of these polarimeter modules and subjected these to space
qualification tests. In addition, in April 2023, the first of these
modules were calibrated using fully polarized gamma-ray beams at the
European Synchrotron Radiation Facility (ESRF) in France. In this
work, we will present the results of this calibration campaign and
compare these to the simulated performance of the POLAR-2
modules. Potential improvements to the design are also
discussed. Finally, the measurements are used, in combination with
the verified simulation framework, to estimate the scientific
performance of the full POLAR-2 detector and compare it to its
predecessor.