bluuebunny/crossref_metadata_2025 huggingface dataset:
Quantum Monte Carlo simulations for estimating FOREX markets: a speculative attacks experience
Authors: Alaminos David , Salas M. Belén , Fernández-Gámez Manuel Á.
Published: June 2023

The foreign exchange markets, renowned as the largest financial markets globally, also stand out as one of the most intricate due to their substantial volatility, nonlinearity, and irregular nature. Owing to these challenging attributes, various research endeavors have been undertaken to effectively forecast future currency prices in foreign exchange with precision. The studies performed have built models utilizing statistical methods, being the Monte Carlo algorithm the most popular. In this study, we propose to apply Auxiliary-Field Quantum Monte Carlo to increase the precision of the FOREX markets models from different sample sizes to test simulations in different stress contexts. Our findings reveal that the implementation of Auxiliary-Field Quantum Monte Carlo significantly enhances the accuracy of these models, as evidenced by the minimal error and consistent estimations achieved in the FOREX market. This research holds valuable implications for both the general public and financial institutions, empowering them to effectively anticipate significant volatility in exchange rate trends and the associated risks. These insights provide crucial guidance for future decision-making processes.
Strategies to enhance the performance of thermoelectric materials: A review
Authors: Bugalia Anita , Gupta Vivek , Thakur Nagesh
Published: June 2023

Various techniques to enhance the performance of thermoelectric materials have been reviewed in an unified way. The influence of synthesis techniques, post-synthesis treatment, microstructure, nanostructure, doping, and interface on thermoelectric materials' transport properties has been discussed. The research ideas given by researchers are presented in tabular forms so that young researchers and engineers can find the potential research gaps and best practices in this field. Conclusions drawn from this review would give research directions to the new researchers working in thermoelectric materials.
Solvothermal vapor annealing setup for thin film treatment: A compact design with in situ solvent vapor concentration probe
Authors: Ariaee Sina , Jakobsen Bo , Pedersen Ib Høst , Rasmussen Torben Steen , Posselt Dorthe
Published: June 2023

A compact setup for in situ solvothermal vapor annealing of thin polymer films in the temperature range from room temperature to 70 °C is presented. The design is optimized to avoid solvent condensation in tubes and other components. The setup consists of a chamber, a gas delivery system, a commercial film-thickness measuring device, and a solvent vapor concentration sensor. The chamber is equipped with heaters and thermometers and is thermally insulated. It has windows to allow for penetration of xrays together with a sample table with a gas distributer to ensure homogeneous swelling of the polymer film. The computer-controlled gas delivery system has two different components, which can be used separately or in parallel (for mixed gas solvent annealing): (a) mass flow controllers and a bubbler system and (b) a commercial “controlled evaporation and mixing” system. The film-swelling ratio is determined in situ using optical reflectometry, and the solvent concentration in the exhaust gas is continuously monitored by UV-absorption. Test results are presented where the setup is used for swelling of ∼100 nm thick polystyrene and polyisoprene homopolymer films with toluene and acetone, respectively.
The Rho guanine dissociation inhibitor α inhibits skeletal muscle Rac1 activity and insulin action
Authors: Møller Lisbeth L. V. , Ali Mona S. , Davey Jonathan , Raun Steffen H. , Andersen Nicoline R. , Long Jonathan Z. , Qian Hongwei , Jeppesen Jacob F. , Henriquez-Olguin Carlos , Frank Emma , Jensen Thomas E. , Højlund Kurt , Wojtaszewski Jørgen F. P. , Nielsen Joachim , Chiu Tim T. , Jedrychowski Mark P. , Gregorevic Paul , Klip Amira , Richter Erik A. , Sylow Lykke
Published: June 2023

The molecular events governing skeletal muscle glucose uptake have pharmacological potential for managing insulin resistance in conditions such as obesity, diabetes, and cancer. With no current pharmacological treatments to target skeletal muscle insulin sensitivity, there is an unmet need to identify the molecular mechanisms that control insulin sensitivity in skeletal muscle. Here, the Rho guanine dissociation inhibitor α (RhoGDIα) is identified as a point of control in the regulation of insulin sensitivity. In skeletal muscle cells, RhoGDIα interacted with, and thereby inhibited, the Rho GTPase Rac1. In response to insulin, RhoGDIα was phosphorylated at S101 and Rac1 dissociated from RhoGDIα to facilitate skeletal muscle GLUT4 translocation. Accordingly, siRNA-mediated RhoGDIα depletion increased Rac1 activity and elevated GLUT4 translocation. Consistent with RhoGDIα’s inhibitory effect, rAAV-mediated RhoGDIα overexpression in mouse muscle decreased insulin-stimulated glucose uptake and was detrimental to whole-body glucose tolerance. Aligning with RhoGDIα’s negative role in insulin sensitivity, RhoGDIα protein content was elevated in skeletal muscle from insulin-resistant patients with type 2 diabetes. These data identify RhoGDIα as a clinically relevant controller of skeletal muscle insulin sensitivity and whole-body glucose homeostasis, mechanistically by modulating Rac1 activity.
Endothermic physiology of extinct megatooth sharks
Authors: Griffiths Michael L. , Eagle Robert A. , Kim Sora L. , Flores Randon J. , Becker Martin A. , Maisch Harry M. , Trayler Robin B. , Chan Rachel L. , McCormack Jeremy , Akhtar Alliya A. , Tripati Aradhna K. , Shimada Kenshu
Published: June 2023

The evolution of the extinct megatooth shark,
Otodus megalodon
, and its close phylogenetic relatives remains enigmatic. A central question persists regarding the thermophysiological origins of these large predatory sharks through geologic time, including whether
O. megalodon
was ectothermic or endothermic (including regional endothermy), and whether its thermophysiology could help to explain the iconic shark’s gigantism and eventual demise during the Pliocene. To address these uncertainties, we present unique geochemical evidence for thermoregulation in
O. megalodon
from both clumped isotope paleothermometry and phosphate oxygen isotopes. Our results show that
O. megalodon
had an overall warmer body temperature compared with its ambient environment and other coexisting shark species, providing quantitative and experimental support for recent biophysical modeling studies that suggest endothermy was one of the key drivers for gigantism in
O. megalodon
and other lamniform sharks. The gigantic body size with high metabolic costs of having high body temperatures may have contributed to the vulnerability of
Otodus
species to extinction when compared to other sympatric sharks that survived the Pliocene epoch.
De novo designed ice-binding proteins from twist-constrained helices
Authors: de Haas Robbert J. , Tas Roderick P. , van den Broek Daniëlle , Zheng Chuanbao , Nguyen Hannah , Kang Alex , Bera Asim K. , King Neil P. , Voets Ilja K. , de Vries Renko
Published: June 2023

Attaining molecular-level control over solidification processes is a crucial aspect of materials science. To control ice formation, organisms have evolved bewildering arrays of ice-binding proteins (IBPs), but these have poorly understood structure–activity relationships. We propose that reverse engineering using de novo computational protein design can shed light on structure–activity relationships of IBPs. We hypothesized that the model alpha-helical winter flounder antifreeze protein uses an unusual undertwisting of its alpha-helix to align its putative ice-binding threonine residues in exactly the same direction. We test this hypothesis by designing a series of straight three-helix bundles with an ice-binding helix projecting threonines and two supporting helices constraining the twist of the ice-binding helix. Our findings show that ice-recrystallization inhibition by the designed proteins increases with the degree of designed undertwisting, thus validating our hypothesis, and opening up avenues for the computational design of IBPs.
Tunable three-dimensional architecture of nematic disclination lines
Authors: Modin Alvin , Ash Biswarup , Ishimoto Kelsey , Leheny Robert L. , Serra Francesca , Aharoni Hillel
Published: June 2023

Disclination lines play a key role in many physical processes, from the fracture of materials to the formation of the early universe. Achieving versatile control over disclinations is key to developing novel electro-optical devices, programmable origami, directed colloidal assembly, and controlling active matter. Here, we introduce a theoretical framework to tailor three-dimensional disclination architecture in nematic liquid crystals experimentally. We produce quantitative predictions for the connectivity and shape of disclination lines found in nematics confined between two thinly spaced glass substrates with strong patterned planar anchoring. By drawing an analogy between nematic liquid crystals and magnetostatics, we find that i) disclination lines connect defects with the same topological charge on opposite surfaces and ii) disclination lines are attracted to regions of the highest twist. Using polarized light to pattern the in-plane alignment of liquid crystal molecules, we test these predictions experimentally and identify critical parameters that tune the disclination lines’ curvature. We verify our predictions with computer simulations and find nondimensional parameters enabling us to match experiments and simulations at different length scales. Our work provides a powerful method to understand and practically control defect lines in nematic liquid crystals.
Unveiling the catalytic mechanism of GTP hydrolysis in microtubules
Authors: Beckett Daniel , Voth Gregory A.
Published: June 2023

Microtubules (MTs) are large cytoskeletal polymers, composed of αβ-tubulin heterodimers, capable of stochastically converting from polymerizing to depolymerizing states and vice versa. Depolymerization is coupled with hydrolysis of guanosine triphosphate (GTP) within β-tubulin. Hydrolysis is favored in the MT lattice compared to a free heterodimer with an experimentally observed rate increase of 500- to 700-fold, corresponding to an energetic barrier lowering of 3.8 to 4.0 kcal/mol. Mutagenesis studies have implicated α-tubulin residues, α:E254 and α:D251, as catalytic residues completing the β-tubulin active site of the lower heterodimer in the MT lattice. The mechanism for GTP hydrolysis in the free heterodimer, however, is not understood. Additionally, there has been debate concerning whether the GTP-state lattice is expanded or compacted relative to the GDP state and whether a “compacted” GDP-state lattice is required for hydrolysis. In this work, extensive quantum mechanics/molecular mechanics simulations with transition-tempered metadynamics free-energy sampling of compacted and expanded interdimer complexes, as well as a free heterodimer, have been carried out to provide clear insight into the GTP hydrolysis mechanism. α:E254 was found to be the catalytic residue in a compacted lattice, while in the expanded lattice, disruption of a key salt bridge interaction renders α:E254 less effective. The simulations reveal a barrier decrease of 3.8 ± 0.5 kcal/mol for the compacted lattice compared to a free heterodimer, in good agreement with experimental kinetic measurements. Additionally, the expanded lattice barrier was found to be 6.3 ± 0.5 kcal/mol higher than compacted, demonstrating that GTP hydrolysis is variable with lattice state and slower at the MT tip.
Mutation pressure, drift, and the pace of molecular coevolution
Authors: Lynch Michael
Published: June 2023

Most aspects of the molecular biology of cells involve tightly coordinated intermolecular interactions requiring specific recognition at the nucleotide and/or amino acid levels. This has led to long-standing interest in the degree to which constraints on interacting molecules result in conserved vs. accelerated rates of sequence evolution, with arguments commonly being made that molecular coevolution can proceed at rates exceeding the neutral expectation. Here, a fairly general model is introduced to evaluate the degree to which the rate of evolution at functionally interacting sites is influenced by effective population sizes (
N

e

), mutation rates, strength of selection, and the magnitude of recombination between sites. This theory is of particular relevance to matters associated with interactions between organelle- and nuclear-encoded proteins, as the two genomic environments often exhibit dramatic differences in the power of mutation and drift. Although genes within low
N

e

environments can drive the rate of evolution of partner genes experiencing higher
N

e

, rates exceeding the neutral expectation require that the former also have an elevated mutation rate. Testable predictions, some counterintuitive, are presented on how patterns of coevolutionary rates should depend on the relative intensities of drift, selection, and mutation.
On sequential warped product manifolds admitting gradient Ricci-harmonic solitons
Authors: Karaca Fatma , Özgür Cihan
Published: June 2023

We consider sequential warped product manifolds admitting gradient Ricci-harmonic solitons. We give the main relations for a gradient Ricci-harmonic soliton on sequential warped product manifolds. As physical applications, we consider gradient Ricci-harmonic solitons on sequential generalized Robertson-Walker space-times and sequential standard static space-times.
The role of a highly optimized approach with superior transparent conductive oxide anode towards efficient organic solar cell
Authors: Gogoi Dipankar , Das T D
Published: June 2023

The effort emphasizes the numerical analysis of different transparent conducting oxides (TCOs) perspectives, which include ITO, FTO, AZO, and IZO anode-based organic solar cells (OSCs) with the drift-diffusion approach. The prior selection of aluminum-doped zinc oxide (AZO) as TCO is feasible for more extended transparency and antireflection due to a tailored absorption wavelength of <380 nm and the factors of higher mechanical flexibility, low-cost processing, and realistic performance at lower temperatures. To confirm the stability and reproducibility of the design OSC, the contribution of each interfacial layer thickness, i.e., AZO as TCOs, P3HT: PC61BM as an organic absorbing layer (OAL), Spiro-OMeTAD (SOT) as a hole-transport layer (HTL), and ZnO as an electron-transport layer (ETL), is also investigated. Furthermore, functions of optimum trap-state densities (

N

t

) and charge carrier mobility (

μ

n
,
p

) in OAL have been performed to aid in increasing the diffusion length of excitons carriers (

L

n
,
p

). These properties led to better photogeneration and transport of charge carriers, decreasing the series resistance (RS), leading to lower bimolecular recombination, a long carrier lifetime (

τ

n
,
p

), and consequently higher power conversion efficiency (PCE). The findings revealed that the proposed OSC structure achieves an excellent PCE of 10.28% for AZO as TCO with an 850 nm ultra-thick OAL under AM 1.5 G light irradiation. Hence, a better fabrication process for efficient OSC could also be improved by the optimization of all these critical factors for future research.
Low-temperature enhanced figure of merit of ThSixP1-x and prospects for thermoelectric energy performance
Authors: Bashir Azmat Iqbal , Irfan Muhammad , Azam Sikander , Siddique Muhammad
Published: June 2023

Rare Earth metals and actinides-based materials gained immense attention of scientists and technologists owing to their fascinating fundamental and applied prospects. These are large density, neutron abundance, enhanced melting temperature and thermal stability which enhance their thermal performance. Herein, we report on the low temperature-enhanced thermoelectric performance of ThP through silicon substitution via ThSixP1-x (x = 0, 0.25, 0.5, 0.75, 1). For the density functional theory-based quantum computation analysis on the Si substitution-assisted properties of ThP, we utilize all-electron full-potential with linearized augmented plane wave. For the theoretical characterization of the compounds for the desired properties, we treat the exchange-correlation density functional within TB-mBJ approximation. The computed thermoelectric properties via Boltzmann theory as implemented in BoltzTrap computer code are Seebeck coefficient (

S

), electrical (

σ

) and thermal conductivity (

k

), power factor (PF) (

S

2

σ

), and figure of merit (

ZT

). The substitution of Si into ThP renders a considerable enhancement of thermoelectric and transport performance of the ThSixP1-x samples with enhanced

σ
,

PF, and ZT of orders 3.0 × 1020

Ω
.
s
.
cm

−
1

,

2.5 × 1012 Wm−1K−2s−1 and 1.6 at 50 K, respectively. To our knowledge, this is the highest low-temperature thermal efficiency achieved for the metallic thorium silicides. As such, the reported results hold great promise for fundamental prospects and technological interest such as thermoelectricity and fertile materials as nuclear fuel for clean nuclear energy technology.
Einstein–Podolsky–Rosen steering and coherence in structured environments
Authors: Berrada K , Eleuch H
Published: June 2023

We examine the quantum steering and coherence for two qubits that are immersed in an isotropic (I) and anisotropic (A) photonic band-gab (PBG) crystal. We show how the steerability and coherence of the qubits’ state depends on the essential parameters of the model and initial state setting of the qubits. We find that the prevention of the amount of quantum steering and coherence can be achieved in the presence of PBG materials by a considerable choice of the system parameters. Furthermore, we show that the quantum steering and coherence can resist the degradation during the dynamics in IPBG more than in APBG according to the same physical conditions. Finally, we illustrate the relationship between the quantum steering and coherence with respect to the system parameters under the decoherence effect. These obtained results reveal that quantum systems in PBG materials are very useful to implement diverse applications of quantum technology with optimal performance.
Performance Analysis and Optimization of a Modified Stewart Platform for the Qitai Radio Telescope
Authors: Kazezkhan Guljaina , Xu Qian , Wang Na , Xue Fei , Wang Hui
Published: June 2023

This paper presents a modified Stewart platform that enables precise adjustment of the sub-reflector for the Qitai Radio Telescope (QTT). QTT demands a parallel platform capable of carrying a heavy load (≥4000 kg), and moving in elevation from 5° to 88° together with the primary reflector while precisely adjusting the sub-reflector’s position in five degrees of freedom. To meet these requirements, a modified Stewart platform with two separated actuators is proposed, and the comprehensive performance is analyzed and optimized for practical application. The performance of the modified platform is compared to that of the traditional Stewart platform, and the results demonstrate that the modified platform has superior load-bearing capacity and stiffness over the entire elevation angle with more uniform actuator load and stiffness distributions. These results indicate that the modified Stewart platform is well-suited for practical application in QTT.
Target-driven multi-input mapless robot navigation with deep reinforcement learning
Authors: Xing Hua , Yu Longfeng
Published: June 2023

Collision-free navigation without pre-built maps is a promising and challenging problem. To make full use of the information in the environment, we propose a multi-input mapless navigation framework that combines both vision-based and ranging-based approaches. It takes the position and orientation of the robot relative to the target as the reference, incorporating RGB-D images and distance measurements as state inputs to the deep reinforcement learning model. In the framework, Dual-VAE is designed to encode RGB images and depth images simultaneously, in order to effectively mine the intrinsic information of RGB-D images. Moreover, we engineer a special reward function that enables the robot to navigate with a smooth trajectory and leave redundant space with obstacles for other tasks. Target-driven multi-input mapless navigation framework has been experimentally proven to achieve satisfactory performance in simulation environments. Our source code and simulation environments are released at https://github.com/YosephYu/MultiInput-Mapless-Navigation.
Smooth Clip Advantage PPO in Reinforcement Learning
Authors: Wang Junwei , Zeng Zilin , Shang Peng
Published: June 2023

Deep reinforcement learning outperforms traditional methods in some domains. In this paper, we propose a novel reinforcement learning on policy (RL) algorithm, the Smoothing Clip Advantage Proximal Policy optimization Algorithm (SCAPPO), which extends the classical PPO algorithm where we exploit the smoothing properties of the sigmoid function to make full use of useful gradients. In addition, we provide more efficient gradients for policy networks effective gradients, aiming to solve the overfitting problem caused by the coupling of strategy and value functions. SCAPPO outperforms currently popular reinforcement learning algorithms in performance tasks in the Open AI Gym.
Multi-objective Optimal Motion Planning of Heavy-duty Assembly Robot for Large Spacecraft Entering Cabin
Authors: Zhang Chengli , Meng Shaohua , Liu Tonghui , Li Haiyue , Zhao Jinlong , Wang Pengfei , Xing Shuai , Hu Ruiqin
Published: June 2023

The space inside the space capsule such as the space station sky and the core module is narrow, the size of the depth is large, and the bearing points are scattered and weak, there are some difficulties in loading, large size, different shape, complicated interface, scattered position, difficult position and pose adjustment, high assembly risk, etc.. To solve these problems, a six-DOF heavy-duty assembly robot is proposed in this paper. The robot adopts the combination of linear drive and rotating joint to increase the working space and bearing capacity of the robot. The kinematics and dynamics analysis model of the robot is established, and the path planning is carried out by means of quintic non-uniform B-spline interpolation method, considering fully the space constraints of the assembled equipment, a multi-objective trajectory optimization model based on NSGA2 algorithm is established to obtain the Pareto optimal solution set with time, impact and energy consumption as optimization objectives, prove that the equipment can be efficient and smooth. Reliable installation, with less impact and less power consumption under multi-objective optimization analysis.
An anchor-free detector designed for dense small water object detection
Authors: Wei Tao , Li Zi-Xin , Wang Yu-Long
Published: June 2023

The detection of dense small objects on the water surface is one of the hot topics in object detection. In this paper, a one-to-many label assignment strategy based on the OTA algorithm, which is applied to anchor-free detector, is proposed to improve the detection accuracy of dense small objects on water surface. To be specific, one-to-many label assignment means that a ground truth (GT) corresponding to multiple prediction boxes is conducted globally. The cost function used by OTA algorithm is improved to make the distribution of positive and negative samples more reasonable. Meanwhile, an efficient training strategy is designed to accelerate network convergence by adding L1 loss in the last stage of training. The results show that the proposed strategies achieve 87.9% average precision (AP). Compared to the original algorithm, we achieve 3.3% relative improvement for the detection precision of dense small objects.
Moving Path Planning and Motion Coordination for Carrier-Borne Aircraft on Deck
Authors: Zhao H D , Liu G , Zhou L H
Published: June 2023

This paper mainly discusses the planning method of shipboard transportation scheduling process on aircraft carrier from two aspects of deck moving path planning and motion coordination method for carrier-borne aircraft in deck. Two kinds of moving path planning algorithms between deck carrier aircraft stations based on standard motion pattern were proposed firstly. And the evaluation criteria of the planned moving paths were discussed. Then, basing on the network of deck moving paths generated by previous path planning algorithm, we developed a motion coordination method of deck carrier-borne aircraft basing on mixed integer programming formulations which can be used to solve the problems of coordination and collision in the transportation scheduling process of multiple carrier-borne aircraft effectively.
Displacement reconstruction based on Kalman smoothing in multi-rate suspension health monitoring systems
Authors: Wang Ying , Zheng Xueke , Wang Le , Lu Gavin , Jia Yixing , Li Mian
Published: June 2023

Suspension displacements and wheel center accelerations are important signals for suspension health monitoring systems to improve vehicle reliability and safety. The current way to obtain these signals is to install sensors on vehicles to conduct direct measurements. Usually, displacements are sampled at a slower rate than accelerations due to technical or economic limitations in real scenarios. This paper introduces a method for displacement reconstruction with low-sampling-rate displacement and high-sampling-rate acceleration measurements by formulating the reconstruction problem as a state estimation problem. A state-space model is established by identifying two data-driven models: a time-series Auto-Regressive model and a Finite Impulse Response model. Then, Kalman smoothing is used to estimate the displacement. A series of experiments have been done to show that the estimates from Kalman smoother coincide with the measurements.
Research on the Evaluation Technology of UAV Pilot Training Action Quality based on Entropy Weight-TOPSIS Method
Authors: An Ran , Yin Wenqiang
Published: June 2023

The system composition and usage of UAVs are different from those of manned aircraft, and a large number of flight training sessions for UAV pilots can gradually make them understand and be familiar with the characteristics of UAV. In this paper, the quality evaluation indexes of UAV pilot training actions are sorted out and an evaluation model is constructed based on the Entropy Weight-TOPSIS method. Through application verification, the evaluation results of the model are consistent with the subjective evaluation results of flight instructors. The model can be applied to the evaluation of UAV pilot training actions quality, and at the same time has high evaluation efficiency.
Short-term Metallurgical Load Forecasting Based on Adaptive Ensemble Learning
Authors: Pengyu Ma , Weijian Kong , Zhiyong Su
Published: June 2023

Accuracy and rapidity are the primary objectives of load forecasting, and also the necessary conditions for ensuring power supply and production schedule. However, in actual production, due to the variability of operating modes and the interference of production environment, the difficulties such as non-stable and high fluctuation are in the power load prediction. In light of this, we propose an adaptive hybrid prediction model based on Discrete Wavelet decomposition(DWT). It is well known that DWT can show local features such as mutation and fluctuation in the sequence, and has excellent multi-scale analysis ability. Adopt energy entropy evaluate the aggregation of wavelet coefficients in order to obtain the subsequence with the highest degree of preserving the main frequency of the original signal. Random Forest (RF) and Long Short-Term Memory (LSTM) were used to track low-frequency profile and high-frequency detail fluctuations respectively. Further, parameters of the heterogeneou models are optimized using the Particle Swarm Optimization(PSO) to improve the adaptability of hybrid models to different frequency components. Compared with other excellent metallurgical load forecasting techniques, the effectiveness and superiority of the proposed model are verified by experiments on the actual industrial data set of an electrical smelting furnaces for magnesia.
Fast response flight multi-service nodes prediction based on one hidden layer neural network
Authors: Li Baiqiang , yang Xiaoming , Tang Zhengjiang , Peng Wentao , Zhou Yang , Liao Fangmin , Tan Jing , Lin Xuan
Published: June 2023

Airport scene multi-service process(ASMP) state prediction is one of the important links to optimize airport ground resource allocation, improve collaborative release scheduling, and improve airport operation efficiency. In order to solve the problem of the slow response of existing prediction models, a Gaussian kernel probability density model of multi-service nodes in airport scenes is established. Then the one hidden layer neural network(OHLNN) is used to predict the nodes of ASMP. A study on the data of more than 20,000 flights at a large airport in China shows that: The mean absolute error (MAE) of the mixed flight prediction result is only 2.62911min, the mean root mean square error (RMSE) is only 3.24564min, and the response speed of the prediction model in the verification set is about 0.48s. When the results of MAE and RMSE are good, the response speed of the prediction model is greatly improved.
Research on Image Fusion in UAV Visual Navigation
Authors: Li Dongtao , Shao Yuanzheng , Yu Yao , Feng Zhifang , Wen Jiaolong
Published: June 2023

The accuracy of multi-sensor image fusion is the key to improve the accuracy of UAV visual navigation. In this paper, a two-step registration method combining region registration and feature registration is proposed. First, rough image registration is carried out based on improved Hough transform and Fourier-Mellin transform, and image precise registration is implemented based on Harris corner feature and cross-correlation function. Finally, wavelet transform is applied to image fusion and image edge enhancement to realize the coarse to accurate registration of SAR images.
Research on Automatic Design of Substation Secondary Circuit Based on Improved SPCD Model and Knowledge Graph
Authors: Xia Guoqiang , Zhu Xiaotong , Jun Xie , Xinghua Li
Published: June 2023

In view of the lack of automatic design research of the physical circuit of the substation secondary system, and the digital design and handover level that the substation urgently needs to improve, this paper proposes the following solutions. First of all, an improvement plan is proposed for the existing SPCD model, adding all design related information such as external function grouping and logical interface of the panel cabinet. Secondly, extract the function group elements and secondary cabinet elements of the improved SPCD model as knowledge graph nodes, and abstract the relationship between function group’s interfaces as knowledge graph relationships. Based on the Neo4j graph database, a typical bay knowledge graph for secondary design is conFstructed. Furthermore, the electric power secondary field data set is mined, the Word2vec model is trained by the secondary field data set, and the text similarity algorithm model in the secondary design field is established. Finally, based on the above research, a method for automatic design of substation secondary physical circuits and automatic generation of SPCD model file based on word2vec text similarity is proposed.
A Personalized Alarm Distribution Approach Based on Collaborative Filtering in New-type Power System
Authors: Zhang Jiafa , Wang Yiyun , Wu Hao , Lai Yuyang , Wang Xiaoyi
Published: June 2023

Due to the complexity and heterogeneous characteristics of the information system architecture of the new-type power system, once a fault occurs during operation, a large number of alarm information will be generated. In order to improve the efficiency of operation and maintenance (O&M) personnel and minimize the loss caused by failures, a collaborative filtering algorithm is introduced to provide personalized alarm information distribution. Each alarm is preferentially assigned to O&M personnel with high processing probability, so that O&M personnel can receive alarm information they can handle. In addition, the minimum distribution number is limited to ensure that each alarm can be received by enough O&M personnel. Finally, experiments show that the proposed method can effectively improve the O&M efficiency and improve the fault recovery capability of the new-type power system.
Multivariate Time Series Clustering based on Graph Convolutional Network
Authors: Zhu Chuanze , Zhong Xu , Lin Zhenjie , Wang Liming , Li Wenzhong , Lu Sanglu
Published: June 2023

Multivariable time series (MTS) clustering is an important topic in time series data mining. The major challenge of MTS clustering is to capture the temporal correlations and the dependencies between multiple variables. In this paper, we propose a novel MTS clustering approach based on graph convolutional network (GCN), which is a powerful feature extractor for graph structure data. We regard each variable in MTS as a node in the graph and construct edges through the correlation between variables. Furthermore, GCN and deep learning back-ropagation technology are used to continuously learn the relationship between multiple variables. Combining the learned variables with the characteristics of the time dimensions, the comprehensive features can be fused to form effective representation for MTS clustering task. We carry out extensive experimental analysis on four open time series data sets and six benchmark algorithms, which shows the superiority of the proposed method.
Reliability Analysis for Programs with Redundancy Computation for Soft Errors
Authors: Meng Xiankai , Zhang Zhuo , Xue Jianxin , Chen Fangshu , Wang Jiahui
Published: June 2023

Soft error is one of the factors which may affect the reliability of computer programs. A common method to alleviate the impact of soft errors is redundancy computation, a classical data flow error detection mechanism. However, a program with redundancy computation may still have some vulnerable spots, which might be caused by the flaw during implementation or the instruction reordering given by compiler optimization. Finding the vulnerable spots of a program with redundancy computation is of great significance to evaluate the capability of the error detection mechanism. There are some conventional methods to analyze the reliability of a program under soft errors, such as the irradiation experiment, fault injection, and modeling analysis. However, the irradiation experiment is expensive, fault injection is very time-consuming, and the existing modeling analysis methods have not considered the error detection mechanism. This paper proposes a novel method of reliability analysis for programs with redundancy computation by analyzing the dynamic instruction sequence. Experimental results show that our approach has fairly high accuracy and a false negative rate of about 0.0545.
A Multi-channel System Architecture Design for Myocardial Infarction Prediction
Authors: Li Qiuping , Li Xueqing , Wang Xin’an , Zhang Xing , Yang Jie , Wu Fangke
Published: June 2023

Cardiac and cerebral infarctions represent the most perilous pathologies within the spectrum of cardiovascular and cerebrovascular diseases, with grave consequences following their onset. However, prompt diagnosis and treatment can substantially enhance the chances of successful rescue and avert severe outcomes. Therefore, the development of a non-invasive, low-cost, and easy-to-use cardiac and cerebral infarction prediction system for home and personal use bears considerable social and economic significance.

The electrocardiogram (ECG), acupoint electrical signals, and pulse, as physiological signals, contain abundant information on human health status. Integrating the information from these three signals can offer a more comprehensive and accurate risk prediction of cardiovascular and cerebrovascular diseases in patients. This approach represents a promising avenue for advancing the field of healthcare and disease management.

Firstly, we analyzed the myocardial infarction and cerebral infarction prediction system requirements. The research determines four pulse collection points, two ECG, and ten acupoint electricity collection points. Then, we completed the cardiovascular and cerebrovascular disease risk warning system’s overall architecture design and front-end scheme design of ECG, acupoint electricit and pulse wave acquisition. The system successfully collects data from the test subjects by connecting to the computer.
A Research on Operator Design Method for Health Detection SoC
Authors: Li Qiuping , Wu Fangke , Zhang Xing , Wang Xin’an , Ma Jieru , Li Xueqing
Published: June 2023

Improving the efficiency of System-on-Chip(SoC) design has always been a hot topic in SoC design methods. The quality of SoC architecture design directly affects the core elements of SoC performance and cost. However, architecture design usually requires highly experienced and skilled personnel, which are scarce resources. Operators in SoC, like instructions in a CPU, are extracted from algorithms and are both universal and flexible. SoC can be designed based on operators, and algorithmic functions can be implemented through operators’ interconnection. In this paper, we propose an operator design method to improve the efficiency of SoC design. Additionally, we design algorithmic operators using pulse signal processing as an example to enhance the efficiency of designing health detection SoCs.
Knowledge graph based AR content adaptive generation for 5G communication network maintenance services
Authors: Ming Wei , wang Li , xiangyu Hu , jiwei Hu , junfeng Wang , tao Peng , chong Zhang , jian Zhang
Published: June 2023

5G technology puts forward new requirements for communication network human maintenance services. However, with the complexity of 5G maintenance knowledge and the diversification of maintenance scenarios, the ability of maintenance engineer cannot be greatly improved in a short time. This paper proposed a knowledge graph (KG) based augmented reality (AR) content adaptive generation method for 5G communication network maintenance services. The KG and AR technology are used to reduce the cognitive burden of manual maintenance and improve the efficiency of communication network maintenance.
Design Scheme of Distributed Energy Resources Interconnection Oriented the VPP System
Authors: Suo Siliang , Che Xiangbei , Xu Aidong , Huang Yingqi , Chen Liming , Cao Yang , Zhong Han
Published: June 2023

At present, the virtual power plant is still in the stage of theoretical research and early pilot development. It has not yet formed a systematic and comprehensive Distributed Energy Resource (DER) modeling, market participation mechanism, operational risk management, operational optimization decision-making method, and systematic operating platform. Given the massive DERs interconnection requirements of the virtual power plant system, this paper proposes a design scheme for the DER interconnection protocol, which solves the problems of the existing application layer protocol, such as high overhead, poor security, and low efficiency of massive interconnection, and supports the safe and stable operation of power grid enterprises and virtual power plant systems.
Research on Multi-objective Optimal Configuration of Distributed Energy Storage System
Authors: Cao Yuanzheng , Zhang Lei
Published: June 2023

The purpose is to improve the absorption capacity of new energy generation added to the power system, the distributed energy storage system (ESS) is introduced. Considering the new energy generation as the main distributed power supply is united to the power grid, the mathematical model of wind-photoelectric-energy storage system is constructed. Taking active power loss, voltage offset and comprehensive cost as objectives, a multi-objective internal and external layer optimization energy storage device configuration model is established. The outer layer uses branch and bound method to locate the location of energy storage. In the inner layer, NSGA-II algorithm is used to optimize the capacity and the situation of storing or releasing power. Eventually, the IEEE 30 node test system with distributed power supply is used for simulation, and the optimal location, capacity and charging/discharging strategy of the ESS in the grid topology are obtained. The results verify the rationality of the configured energy storage, and show that system can absorb distributed energy to a certain extent.
Optimal Dispatching Method of Urban Comprehensive Energy System Based on Multi-energy Complementarity
Authors: Liu Hengmen , Liu Zhong , Ye Zhelin , Chen Ying
Published: June 2023

Considering the complexity of the multi-microgrid system and the diversity of internally distributed power sources, it is challenging for the centralized control scheduling mode to deal with new microgrid systems. Hierarchical management and distributed control strategy can adapt to the power grid management system. In this paper, considering the source-load uncertainty of multi-energy complementary power grid operation, the influence of the multi-energy output distribution model on the supply-demand balance of power grid regulation is constructed, and the probability balance model of power grid regulation capacity is built. To minimize the cost of cooperative operation between multi-energy microgrids and energy storage power stations and maximize the flexibility of regulation, the multi-objective particle swarm optimization (PSO) algorithm is used to constrain the deterministic equivalence of the regulation power probability balance constraint. The effectiveness of the proposed model in describing uncertain factors, reducing operating costs, and improving the regulation capacity of multi-energy microgrids and energy storage power stations is verified through an example analysis.
A Method for Optimal Allocation of Distributed PV and Energy Storage Based on High Reliability of Distribution Network
Authors: Shao Jingwei , Zhou Weidong , Xu Jun , Sun Ran , Hua Ke
Published: June 2023

In the context of the current widespread application of distributed PV, the energy storage system has bi-directional power characteristics and flexible regulation capability, and the reasonable joint planning of the two can enhance the safe and reliable operation of the system. In order to maximize long-term economic benefits, this paper proposes an optimal allocation method of distributed PV and energy storage based on high reliability of distribution network. Considering both normal operation and disaster scenarios for distributed photovoltaic storage planning, firstly, the investment and operation cost of distributed energy storage system is the target, and the storage planning model under normal operation scenario is established by considering the storage access location, configuration capacity, load state and grid operation state as constraints; then, the distributed photovoltaic storage optimal configuration model under disaster scenario is established by taking grid economy as the objective function. In summary, a two-layer planning model is established, with the upper layer using genetic algorithm to optimize the location, power and capacity of energy storage configuration, and the lower layer using particle swarm algorithm combined with tide calculation tool to optimize the intra-day operation strategy of energy storage; finally, the feasibility and effectiveness of the optimal configuration method are verified.
Design and Key Technology of Energy Management System Based on Wind Storage System
Authors: Guo Jihong , Liu Runbiao , Jing Zhe
Published: June 2023

With the goal of “carbon peaking and carbon neutrality” and the proposal of building a new power system, more and more research and applications of wind power supporting energy storage have been conducted in scientific and technological research and engineering construction. The energy management system technology of wind storage system plays a key role in improving system operation efficiency, improving grid security and wind power utilization, and reducing the cost of the whole life cycle. This paper sorts out the development trend of energy management systems, introduces the management objects, system architecture, network architecture, and functional architecture of the wind storage system energy management system, and finally expounds on the key technologies of the wind storage energy management system.
Regulation Cost Forecasting Model for Systems with High Renewable Energy Penetration Based on Stochastic Distribution of Net Load Modeling
Authors: Li Sitao , Yuan Bo , Dong Li , Gao Xiao , You Peipei
Published: June 2023

With the increasing installed capacity of wind power and PV, the strong randomness of power generation makes the requirements of power systems for regulation and other ancillary services increase. However, the traditional regulation requirement prediction method cannot meet the problem of randomness on both sides of the plant and the user well. Therefore, this paper designs a regulation requirement forecasting method based on netload random distribution modeling. Combined with the hypothetical typical operation scenario of the Chinese power system in 2025, the total cost of regulation is predicted. The results show that China’s total cost of regulation can reach 10.62 billion yuan in 2025. And the sensitivity test results show that the total cost of regulation increases with the decrease of sub-period and with the increase of coverage of random fluctuation of net load.
Multi-operating state traction control of the regionally integrated energy system
Authors: Chen Yansen , Wang Pengyu , Wan Siyang , Pan Jiajing , Yang Ping , Lin Zhenfu , Zhang Zihao , Ge Jun , Yao Senjing
Published: June 2023

The regionally integrated energy system consists of multi-type energy production units, energy conversion units, and energy consumption units. This form is of great importance in the area of regenerative energy consumption and multi-type energy optimization. The optimal regulation of the regionally integrated energy system with a high percentage of regenerative energy is the key to the consumption of regenerative energy and the optimal utilization of multi-type energy. The paper presents a method which adopts multi-operating state traction control and considers both system-level and unit-level. Firstly, according to the function of each equipment, the system is classified as various units. Then the state of each unit and the system are determined by the operation data of each unit. The system allocates the unbalanced power regulation task according to the regulation ability of each unit. Finally, each unit completes the traction control according to its control parameters. In the example, the particle swarm optimization computation algorithm is applied to solve the above multi-operating state model. The results indicates that for the regionally integrated energy system, the optimal regulation can achieve the regulation effect of promoting regenerative energy consumption and reducing operation costs.