bluuebunny/crossref_metadata_2025 huggingface dataset:
Research on Regional Energy System Planning Considering Flexible Access of Electric Vehicles
Authors: Zhang Chongbiao , Qian Chenwen , Yu Hongyan , Peng Yanling , Chen Jinwei
Published: March 2024

The high proportion of renewable energy sources and intermittent loads pose challenges to the flexible operation of regional energy systems. To improve the flexible operation level of regional energy system, this paper considers the uncertainty of energy storage charging and discharging, demand-side management, and V2G of electric vehicles, and establishes a flexible resource supply capacity and cost model. With the goal of minimum flexibility demand and economic optimization, the implementation of flexible supply and demand balance constraints is added. The advantages and disadvantages of the traditional resource scheduling scheme and the unified flexible resource scheduling method are compared from the net load volatility, the maximum operating volatility and the whole time scale flexible supply and demand balance index. The algorithm analysis proves the advantages of the proposed scheduling scheme in improving the flexibility of the regional energy system, which can describe the flexibility of the regional energy system well and can be quantitatively characterized.
Study On Marine Boundary Layer Aerosol Structure based on Satellite Observations
Authors: Deng Shumei , Yi Mingjian , Zhao Qiang , Liu Changyu
Published: March 2024

The aerosol vertical distribution in the boundary layer is heavily influenced by the boundary layer thermal structure. This paper studied on marine boundary layer (MBL) aerosol and its structure by using satellite lidar measurements. The lidar methodology was improved and applied to the 3-year satellite MBL aerosol observations over Oceans, and a new global ocean dataset was built. The global MBL structure were examined and discussed with the new dataset. Results showed that the BLH generally increases and MLH generally decreases when away from the coast. Further analyze shows that the MBL tends to be more well-mixed with lower BLH, and the aerosol loading shows weaker relationships with U10m under overcast conditions than partly cloudy conditions.  This study demonstrated that satellite lidar measurements have the great potential in evaluating and constraining both modeled MBL aerosol optical properties and modeled MBL structure.
Inversion of Ocean Wave Spectrum from the Multi-frequency HF Radar Sea Echoes with Wind and Swell Coexisting
Authors: Liu Han , Liu Zhen , Wang Suyue
Published: March 2024

Recently, the multi-frequency HF radar has attracted much attention. However, only a few works focus on the method of obtaining wave information directly. In this work, a wave spectrum inversion method for multi-frequency HF radar in complex sea conditions is proposed. This method considers the swell component in the ocean, and uses multiple HF radars of different frequencies to obtain the echo Doppler spectra from complex sea conditions with wind and swell coexisting. And then the wave spectrum is derived from the high-energy outer second-order spectra and the corresponding first-order peak of the Doppler spectra. In addition, the proposed method is applied to the simulated sea echo data and the result indicates that the method is effective.
Overview and Energy Power Analysis of Composite Solar Unmanned Aerial Vehicles
Authors: Wu Zhengan
Published: March 2024

In this paper, based on the existing research progress and challenges in unmanned aerial vehicles (UAVs), efforts are made to enhance the performance of UAVs in terms of endurance and range by optimizing the energy and power systems. We propose the concept of a composite UAV and further introduce the concept of a solar-powered UAV. The paper outlines the project's design philosophy and innovative aspects, followed by an exploration of potential applications. Energy control calculations are then conducted, leading to the proposal of a gravity energy storage strategy. Then a preliminary flight control scheme is presented. This paper concludes with a conclusion and prospects for future work.
An Intelligent Health Monitoring System for Buildings Based on IoT Technology
Authors: Zhu Feiyue , He Yuli , Qiu Haifeng
Published: March 2024

This paper presents the design and development of an intelligent health monitoring system for buildings, utilizing IoT (Internet of Things) technology. In addressing a prevailing issue in current building stress monitoring methods, which often overlooks point cloud data preprocessing, we propose a method that focuses on monitoring vertical stress points in concrete structures and aligning the collected data with finite element analysis models. Subsequently, harnessing the potential of IoT technology, we design a Zigbee-based scheme for collecting environmental data within the building. This scheme incorporates a diverse array of sensors and encompasses the construction of a comprehensive software and hardware system alongside a monitoring platform. The resulting system is adept at real-time monitoring and data collection across various facets of the building, ensuring alignment with actual conditions. It demonstrates significant practical value, offering user-friendly operation, robust stability, and excellent performance in the realm of building monitoring.
N- or S-doped porous carbon-based metal catalysts for hydrogenation of CO2 to formic acid
Authors: Xu Yuankang , Zhang Jianchao , Zhu Linqing , Xu Ruiqin , Pan Baizhen , Liu Lianwei , Zhang Guangquan , Sun Rui , Wang Lin , Fan Zhuangjun
Published: March 2024

Hydrogenation of CO2 to formic acid (FA) is a promising method to meet the increasing energy demand and reduce CO2 emissions. In this work, efficient catalyst was successfully designed and synthesized by loading uniformly dispersed Ir nanoparticles on N- or S-doped carbon materials, catalyzing the hydrogenation of CO2 to FA. The experimental results showed that the catalytic performance of N-doped Ir/NC catalyst was much higher than that of S-doped Ir/SN catalyst. Ir/NC catalyst exhibited a high catalytic performance under the reaction conditions of 120℃, 8 h and 6 MPa with a turnover number (TON) of 987. Moreover, a high TON of 3901 was achieved after 48h, thus indicating the good stability of the obtained catalyst.
Double Restriction of Bismuth Nanoparticles by Carbon Matrixes for Ultralong−lifespan Sodium Storage
Authors: Huang Fuchao , Liu Zheng , Cao Ke , Fan Zhuangjun
Published: March 2024

Alloying-type bismuth (Bi) anodes show a high theoretical capacity for sodium-ion batteries (SIB), yet their huge volume expansion and electrode pulverization resulted in poor electrochemical stability. Herein, we proposed a feasible strategy for the preparation of carbon/Bi composite material in which the Bi nanoparticles are uniformly dispersed in the double-layered carbon matrix. Benefiting from the synergistic confinement of the external coating of graphene and the internal layer of MOF-derived carbon, the volumetric expansion and large chemo-mechanical stress of Bi nanoparticles are effectively buffered. Therefore, the GAB@GO-800 anode exhibits a dramatically reversible capacity of 328 mA h g−1 at 0.1 A g−1, exceptional rate capability (299 mA h g−1 at 5 A g−1), and ultrahigh stability of 255 mA h g−1 at 2 A g−1 over 2000 cycles. Such hybrid carbon confinemental strategy via a combination of graphene coating and MOF-derived carbon is expected to be a promising method for the alloying-type anodes of SIBs.
Modification 1T-MoS2 with surface ions towards electrocatalytic hydrogen evolution reaction
Authors: Chen Lulu , Huang Yichao , Wang Limin , Huang Sixuan , Fan Zhuangjun
Published: March 2024

Molybdenum disulfide (MoS2) is considered as a thriving and cost-efficient electrocatalyst for hydrogen evolution reaction (HER). Unfortunately, the semiconductor phase of 2H-MoS2 itself has a conservative electronic intrinsic transport rate and the restricted active sites to edge regions, leading to unsatisfactory electrocatalytic performance of HER. Here, we have fabricated highly conductive metal phase 1T-MoS2 nanosheets by a hydrothermal method and introduced a series of transition metal ions on their surfaces by an in-situ reduction strategy to achieve MoS2 surface modification. It was found that the metals Ni and Co not only enhanced the intrinsic conductivity of 1T-MoS2, but also significantly increased the number of active sites in the catalyst, which resulted in the catalyst exhibiting excellent HER activity. Ni@1T-MoS2 exhibits fast reaction kinetics (86 mV·dec-1), good mechanical stability (~28 h) and low energy consumption in 1.0 M KOH medium, as well as an over-potential of only 187 mV at 50 mA·cm-2.
Fatigue Fracture Behavior of TA15 Alloy after Laser Marking
Authors: Qian Kun , Yang Linqing , Jiang Yunlong , An Jinlan , Hui Li
Published: March 2024

In order to study the effect of laser marking on the fatigue properties of TA15 titanium alloy, the alloy was marked at two depths respectively, and the low-cycle fatigue properties and fracture mechanism of TA15 titanium alloy after marking were analyzed and discussed. The results show that different degrees of marking pits appear on the surface of the alloy after laser marking, which is easy to cause local stress concentration. With the increase of power, the cross section shape of the bottom end of laser marking changes from a semi-arc shape to a sharp cone shape, resulting in high stress concentration phenomenon. The low cycle fatigue life of laser shallow marking specimens decreases by 62.7%, and that of laser deep marking specimens decreases by 86.4%. With the increase of the marking depth, the fatigue source area gradually becomes rough from smooth at the beginning, the divergence degree of cracks increases, the spacing of each crack in the initiation area increases, and the morphology becomes rough. The deeper the marking area is, the more driving force is provided for the initiation of cracks, and finally the fatigue performance deteriorates significantly.
Analysis of the effectiveness of landslide stabilization in a near-dam reservoir area
Authors: Wang Zhiquan , Wu Jian , Ye Shuaihua , Yang Dong , Gao Fengfeng
Published: March 2024

The geological conditions of the landslide area in a near-dam reservoir area of a water conservancy hub project are complicated, and the stability problem of the landslide body is prominent, which is not only directly related to the safety of the adjacent office building and highway, but also poses a threat to the normal operation of the water conservancy hub. According to the latest geological data of the landslide area, the results of the stability calculation of the landslide body are analyzed, and the reinforcement design scheme of circular chair type anti-slide piles & prestressed anchor cables is proposed for the landslide body to solve the problem of anti-slide stability of the landslide body. Numerical analysis results show that: the safety factor under each working condition after reinforcement is within the permissible range and meets the relevant normative requirements, the landslide body has good control effect on deformation after reinforcement, and the reinforcement measures can provide certain reference value for the design and construction of similar projects.
Residual strength of a casing with corrosion semi-ellipsoid defect in high-sulfur gas wells
Authors: Wang Yang , Yi Xiang , Zhang Xuelun , Liu Siyan , Jing Jiajia , Yang Wenwu , Yang Liuchuan
Published: March 2024

There are few studies on the residual strength of semi-ellipsoid defect casing considering the bending moment load in high sulfur gas well. In this paper, a numerical model of a casing with corrosion defects exposed to bending moment is proposed. The effect of the defect positions along the circumference on the residual strength of the casing with bending moment is investigated. Parametric studies highlight that defect size have significant effect on the residual strength of the casing, and the circumferential defect and the axial defect can change the critical internal pressure and the critical axial load. This finding has a significant guidance for residual intensity evaluation of a casing with defect.
Intelligent Technology Assessment of High-Speed Railway Based on Knowledge Graphs
Authors: Liu Chenchen , Wang Hongwei , Wang Lin
Published: March 2024

This paper introduces an intelligent technology assessment framework for high-speed railways based on a knowledge graph approach. We employ rule-based knowledge extraction algorithms and a Bert-BiLSTM-CRF model for entity extraction from technical texts. Subsequently, we establish relationships among various entities, constructing a knowledge graph specific to high-peed railways. The knowledge graph is stored in a Neo4j graph database in triple format. Furthermore, we establish a comprehensive evaluation metric system, integrating knowledge graph insights to assess the utility of enabling technologies. We employ the CRITIC weighting method to calculate the value assessment results for target technologies. Simulation results indicate that the training results for word segmentation and sentence splitting are favorable, and the Bert-BiLSTM-CRF model achieves convergence in accuracy, recall, and F1 score after 30 iterations. The technical assessment results in this paper align closely with the actual technological value assessment.
Risk prediction of water inrush in karst tunnels and analysis of surrounding rock stability
Authors: Tian Yujiang , Liu Bin , Hu Baoming , Yuan Chen , Wang Jin , Liu Chao
Published: March 2024

Karst tunnel construction has always been an important and difficult point in tunnel engineering. Based on the Yilai Expressway Wantan Tunnel Project, this paper analyzes the water-bearing lithofacies of the surrounding rock of the Wantan Tunnel and the karst hydrogeological conditions of the tunnel site area, and predicts the risk of tunnel water inrush disaster. Through monitoring and measurement, the existing construction technology was analyzed and the following conclusions were drawn: The surrounding rock of the Wantan Tunnel is a typical carbonate phase stratum, with a large amount of water inflow during the rainy season. There are local caves and karst pipes, and the comprehensive water inrush assessment level is III (medium risk); According to the monitoring, the displacement and deformation of each monitoring section in the tunnel changes normally, and the cumulative deformation value is less than 1/3 of the limit value. The stability of the surrounding rock is good, and the construction safety is high.
Analysis of deformation law of an airport foundation pit monitoring in loess area
Authors: Guo Shuli , Wei Kongfeng , Wu Weiqiang
Published: March 2024

This paper takes an airport foundation pit project in northwest loess area as the research object, and introduces the key method technology of support, construction and monitoring of this foundation pit project. The scope of this foundation pit project is widely distributed, there are no buildings in the surrounding area, and there is less restriction on the construction space, so the GRF01 green assembled support method of Slope release with soil nail wall is adopted, which controls the deformation of the foundation pit well and at the same time, plays the role of green environmental protection and reduces the cost. The analysis of the pit monitoring data shows that the pit engineering support design scheme effectively controls the deformation of the pit, and all monitoring data did not reach the alarm value, which ensures the safety of pit excavation and in-pit operation, and achieves the dual goals of economy and environmental protection. It can provide reference for the design and construction of similar large-scale foundation pit excavation and support in loess area.
Design and application of VRGIS 3D simulation system for power grid soil and water conservation
Authors: Yu Lei , Zhang Songyang , Shang Jinjin , Su Gaofeng , Sun Zhen
Published: March 2024

Under the development trend of economic globalization, the rapid development of social economy and science and technology provides a new direction for the research of soil and water conservation technology in power grid. As an organic combination of geographic information system and virtual reality technology, VRGIS not only continues the basic functions of traditional spatial data storage and processing, but also has the unreal interface of virtual reality technology, building a new platform for the construction and management of smart grid in the new era. Therefore, after understanding the research status of smart grid construction, this paper mainly studies the design and application measures of 3D simulation system for water and soil conservation of power grid according to the application advantages of VRGIS technology in smart grid management, so as to provide an effective basis for the development of smart grid.
Research on Wear Damage of Anchor Chain under Different Load Modes
Authors: Li Yugang , Chen Jingjie , Li Jiachen , Wang Bin , Ten Bo
Published: March 2024

In the marine environment, mooring anchor chains bear complex loads such as axial tension and out of plane bending. These loads cause wear and corrosion damage to the anchor chain, reducing its fatigue strength, and even leading to fatigue fracture. The inspection load applied to the anchor chain before leaving the factory will generate residual stress, which will affect the stress characteristics and fatigue life of the anchor chain during service. This article aims to obtain the residual stress generated by the test load on the anchor chain through numerical simulation, and explore the impact of the test load residual stress on the stress characteristics and wear performance of the anchor chain; Analyze the stress and contact characteristics of anchor chains under different bending angles and wear depths, and obtain the locations where fatigue damage is prone to occur in the later stage of anchor chain wear.
Research on Measurement Technology of Coefficient of Thermal Expansion of Honeycomb Structure
Authors: Tang Xiaojun , Liu Lixia , Dai Guobao , Sun Zijie , Yang Yaodong , Li Ao
Published: March 2024

Honeycomb structure is widely used as the main sandwich layer of load-bearing structure in aviation, aerospace and other fields because of its light weight and high strength. Under some service conditions, the deformation of the honeycomb structure affected by high and low temperature will affect the overall mechanical performance of the structure. Therefore, accurate evaluation of the thermal expansion performance of the honeycomb structure becomes the key to structural design. However, the existing measurement methods of thermal expansion coefficient mainly have problems such as the hollow structure cannot be effectively contacted, the area of the grid optical target is limited and difficult to detect. In view of the above conditions, in this paper, a method for measuring the thermal expansion coefficient of honeycomb structure is proposed, and the measurement system is built, and the thermal expansion performance of honeycomb structure is effectively obtained by testing the honeycomb structure. At the same time, the measurement accuracy of the system is verified by using standard test pieces. The experimental results show that the method has high measurement accuracy.
Effect of Multi-rough Element Combination on Hypersonic Boundary Layer
Authors: Zhao Zhiyi , Zhu Dalei , Yang Yaodong , Tang Xiaojun , Xin Liang , Dai Guobao , Li Ao
Published: March 2024

In this paper, the influence of multi-rough element combination controlled by cubic polynomial on the flow field of hypersonic blunt wedge is studied by direct numerical simulation. The influence mechanism of six continuous rough element combinations on the flow parameters in the boundary layer is analyzed in depth, and compared with the influence of double rough elements. It is concluded that the first rough element of the continuous rough element combination has a great influence on the flow field pressure, and the influence of the latter rough element decreases in turn. The combination of six continuous rough elements on the wall can better suppress the incoming flow heating and reduce the wall friction compared with the double rough elements. Compared with smooth wall, wall friction and incoming flow heating are reduced by 25.23 % and 2.69 %, respectively.
Research on Singularity in Calculation of Induced Electric Field in Pointed Conductors
Authors: Li Kejie , Sun Dian
Published: March 2024

In the electric field environment of thunderstorm, the tip of a grounded object at a high place is more likely to produce corona discharge and finally cause lightning flash. Therefore, the study of the surface electric field of the grounded object tip in the electric field environment has important theoretical value and practical significance for the analysis of the characteristics of the head-on discharge. Due to the strong singularity of the tip structure, the traditional numerical analysis method cannot accurately calculate its surface electric field. Therefore, the traditional literature usually chamfers the conductor tip, but in lightning physics, researchers are most concerned about the maximum field strength in the local area. In order to study the electric field distribution on the tip conductor surface, a semi-analytical boundary element method is proposed to calculate the tip structure directly. Firstly, the analytical formula of the electric field on the tip conductor surface and the boundary element semi-analytical common method are derived, and the tip conductor model is established to calculate the tip electric field excited by the external electric field using the analytical solution and the semi-analytical method. The correctness of the semi-analytical method is verified by calculating the L2 loss function of the two, and the influence of the tip angle on the semi-analytical calculation results is studied. The results show that for the three-dimensional cone model, the L2 loss function is 10-5, which meets the calculation accuracy. The special treatment of the semi-analytical method at the strong singular integral makes the calculation accuracy much higher than that of the Gaussian integral, where the L2 loss function is greatly reduced. Further, based on the change of tip angle, as the conductor tip becomes sharper, the greater the electric field distortion is, and the greater the L2 loss function is. The research results provide a method reference for the calculation of the electric field on the tip conductor surface.
Multi-objective Agent Model for XGBoost Controlled VFTO Simulator Based on Bayesian Optimization Algorithm
Authors: Li Kejie , Li Longlong
Published: March 2024

VFTO generated from GIS may cause interference and damage to terminal equipment on the primary and secondary sides, but experimental measures to evaluate the affected equipment and electromagnetic effects of the equipment through actual measurements are quite limited, so it is desired to build a VFTO simulator in the laboratory for experimental research and laboratory testing. Most of the current researches are conducted by building a true-type experimental platform for VFTO simulation, but this method has the disadvantages of large footprint, high cost and the scope of application can only simulate VFTO in a certain situation. Therefore, this paper establishes a broadband circuit model considering the pulse generator and the frequency domain equivalent transmission line model, and introduces the machine learning algorithm XGBoost to fit the agent model of the functional relationship between the design target and the structural parameters by establishing the sample data of the input circuit parameters and the output frequency waveform characteristics of the simulator, which is capable of dynamically adjusting the input parameters based on the waveform characteristics according to the changes of the target waveform, and ensures that a controllable waveform is obtained accurately in the laboratory the accuracy of obtaining controllable waveforms, thus realizing the output of controllable analog VFTO waveforms by changing the parameters of circuit components. Finally, the Bayesian optimization process is used for the hyper-parameter optimization of the XGBoost model, which has a fast convergence speed, and the characteristics of the output model are compared and analyzed, which verifies the feasibility and superiority of the proposed agent model as well as the multi-objective optimization method.
Experimental study on the bond-slip behaviour between corroded bars and concrete
Authors: Zhao Chenxu , Ying Zongquan , Du Chengbin , Yang Shuai
Published: March 2024

Pull-out tests were conducted to investigate the effects of corrosion of the both longitudinal bar on the bond-slip behaviour of reinforced concrete specimens. The main experimental variables include concrete strength (26.7 MPa, 37.7 MPa, 45.2 MPa) and expected corrosion rate (0%, 4%, 8%, 12%), with a total of 36 specimens fabricated. The results show that the relative bonding strength of specimens under different concrete strengths gradually decreases with increasing corrosion rate, but the higher the concrete strength is, the faster its degradation rate. Based on the experimental results of this work and the achievements of other scholars, a modified relative bonding strength degradation model is presented by accounting for the influence coefficient of concrete strength.
Calculation Method of Flange Bolt Preload Based on Finite Element
Authors: Wang Ziqiang , Yang Zhonggui , Zhao Zhilei , Liu Zhenqiang , Wen Jiahao , Li Menghan
Published: March 2024

Flange bolt connection is one of the most important connection modes in bolt connection at present. In this paper, the finite element model of the bolt between the shell and the head flange is established to analyze the influence of different initial preload on the bolt stress state under external load. The results show that according to the bolt stress state, the range of initial preload is divided into the influence area of the external load, the influence area of the resultant force and the influence area of the initial preload. In the influence area of external load, the bending moment exerted on the bolt dominates the stress state of the bolt, and the stress state of the bolt is poor, which is not the safe value area of the initial preload；in the influence area of the initial preload, initial preloads dominates the stress state of the bolt, the average stress of the bolt section is larger, and the bolt safety is smaller, which is not the safe value area of initial preloads; in the influence area of the resultant force, the bolt has better stress state and higher safety coefficient, which is the safety value area of initial preload. The initial preload corresponding to the boundary point between the influence area of the resultant force and the influence area of the external load and the influence area of the external load is the limit of the safe value range of the bolt preload.
Study on Bond-slip Behavior between Non-uniformly Corroded Reinforcement and Concrete
Authors: Wu Songtao , Ying Zongquan , Du Chengbin , Yang Shuai
Published: March 2024

In order to improve the stress concentration in concrete at steel nodes caused by zero thickness springs, the improved Spring2 nonlinear spring model from ABAQUS is used to simulate the bond-slip behavior between non-uniformly corroded reinforcement and concrete. Based on the collected test results with different stirrup spacing, fitting the influence coefficients of bond stress under stirrup corrosion. With the combination of a non-uniformly corroded rebar distribution model, the refined numerical simulation of the drawing process of reinforced concrete specimens was carried out using ABAQUS. The study shows that the improved nonlinear spring model is better than the zero thickness spring model in terms of computational accuracy and efficiency. The stirrup correction coefficient is approximately linear with the stirrup spacing; the bond-slip relationship considering the effect of stirrup spacing, has a better consistency with the relevant tests in the simulation of the pullout test. Weibull distribution for the fitting of non-uniform corrosion of reinforcement is more reasonable than Gumbel distribution.
Balancing Performance Trade-offs in Modern Sorting Methodologies
Authors: Li Muyang
Published: March 2024

The study of sorting algorithms has always been a key topic. This paper thoroughly explains and investigates the time complexity of six classic sorting algorithms through theoretical analysis and experimental comparison. We implemented insertion sort, selection sort, bubble sort, shell sort, quicksort, and heapsort. By controlling data scale and distribution, we systematically tested the performance of different algorithms under various scenarios. The results show that there are significant efficiency differences between algorithms on small-scale data, and the advantages of quicksort and heapsort become more obvious as data size increases. Through extensive comparative experiments, this paper identifies the application scenarios of each algorithm, providing a theoretical basis for algorithm design and selection.
Graph Neural Networks for Skeleton-based action recognition
Authors: Chen Kairen , Yang Zihao , Yang Zhenyu
Published: March 2024

One of the important directions of the application of artificial intelligence based on human bone behavior recognition is also a research hotspot in the field of computer vision in recent years. Human image video not only contains complex backgrounds, but also uncertain factors such as changes in illumination and changes in the appearance of the human body, which makes behavior recognition based on image videos have certain limitations. Compared with image video, human skeleton video can well overcome the influence of these uncertain factors, so be- havior recognition based on human skeleton has received more and more attention. The human skeleton sequence not only contains the tempo- ral features, but also the spatial structure features of the human body. How to effectively extract the discriminative spatial and temporal fea- tures from the human skeleton sequence is a problem to be solved. In recent years, many methods have been applied to bone-based behavior recognition, such as Recurrent Neural Network (RNN), Convolutional Neural Network (CNN) and Graph Neural Network (GCN). This article will introduce the content and characteristics of these three methods one by one. , And conduct a comparative analysis on it.
Large-Scale Data Processing and Machine Learning Analysis Model Based on Distributed Algorithm
Authors: Lo Manfei
Published: March 2024

The model of large-scale data processing and ML(machine learning) analysis based on DA(distributed algorithm) is a powerful computing method, which aims at processing huge data sets and performing efficient ML analysis. In this paper, a cluster topology driver module based on gradient switching and aggregate communication is designed, and its core goal is to adapt the distributed system to various underlying network topologies. By designing decentralized gradient exchange algorithm and aggregate communication framework, the parallel transmission ability of multi-interface network can be fully exerted, thus improving the model synchronization efficiency of ML task. The experimental results show that the cluster topology driver module can provide better performance than the existing methods in terms of training convergence, cluster scalability and communication overhead. Large-scale data processing and ML analysis model based on DA is widely used in processing massive data and realizing complex analysis tasks.
Convenient Synthesis and Characterization of Novel 4-[2-Ethoxy-5-(4-Methyl-1-Piperazinesulphonyl)Benzamido]-3-Isobutyl-1-Methyl-1H-Pyrazole-5-Carboxamide: Key Precursor for Isobutyl Sildenafil
Authors: Sun Jiali , Guo Zheng , Qi Shengxuan , Zhang Yan
Published: March 2024

This work presents a rational synthesis of 4-[2-Ethoxy-5-(4-Methyl-1-Piperazinesulphonyl)benzamido]-3-Isobutyl-1-Methyl-1H-Pyrazole-5-Carboxamide (13) by condensation of 4-amino-3-isobutyl-1-methyl-1H-pyrazole-5-carboxamide (8) with 2-ethoxy-5-(4-methyl-1-piperazinesulphonyl)benzoyl chloride (12) with an overall yield of 37.4 %. The preparative details of all intermediates and Isobutyl Sildenafil were discussed step by step. The structures of key intermediate 13 and Sildenafil impurity A were characterized by 1H NMR, 13C NMR and HR-MS analysis. It provides a convenient approach in good yield for Sildenafil impurity A in a convergent way with easy manipulations and scale up.
A review of recent advances in fault diagnosis based on deep neural networks
Authors: Li Rongyu
Published: March 2024

Bearings are essential components in mechanical systems, supporting the rotation of various machine parts in motors, wind turbines, vehicles, and industrial robots, making their health critical for system performance and reliability. Traditional diagnosis methods, such as vibration and acoustic analysis, along with temperature monitoring, often demand expertise and may struggle to detect early faults. However, the introduction of deep learning technology has created new opportunities for more effective bearing fault diagnosis. The application of deep learning-based bearing fault diagnosis in the industrial sector has gained significant attention and multiple types of deep learning networks have already been successfully implemented. This paper aims to provide a clear review of bearing fault diagnosis based on deep learning algorithms. This essay focuses on two of the most popular deep learning networks, Autoencoder and Convolutional Neural Networks. Their mechanism and applications are analyzed based on essays and research paper related to the field of bearing fault diagnosis. Finally, conclusions are presented to summarize the current development and point out faced challenges and future trends of these deep learning networks. It is also expected that this narrative not only serves as a cogent overview of the contemporary fault diagnosis technologies but also provides convenience and inspiration for further study in this field.
A survey on common biostatistics tools in neuroscience: Machine learning and Bayesian modeling
Authors: Xue Ziyi
Published: March 2024

Machine learning was characterized by building models and finding correlations between data features, while logistic regression, decision trees, support vector machines (SVM), random forest (RF) and neural networks were recognized as common ML approaches. Bayesian modeling model uncertainty, which can estimate the features from the dataset directly instead of from sampling distribution. Their roles were extremely useful for the detection and progression for diseases in neuroscience. This review summarize different approaches in various diseases, hoping to introduce the potential roles of biostatistics tools in neuroscience.
Miniaturized detection devices powered by various heaters: A quick review under the background of water-borne disease epidemics
Authors: Zhang Chuanhao
Published: March 2024

With the progress of society and the development of productivity, the problem of water pollution and water shortage caused by water pollution is becoming more and more serious. Water-borne diseases caused by pathogenic microorganisms also bring great harm to human beings and other life forms. These microorganisms include bacteria, viruses, protozoa, and parasitic pathogens. Traditional detection methods are time-consuming and costly, and can’t meet the needs of water resource detection. Therefore, there is an urgent need for accurate, rapid, specific, and portable detection equipment for detecting pathogenic microorganisms in water. We analyzed and sorted out the detection methods and detection equipment for detecting pathogenic microorganisms that cause water-borne diseases, summarized these detection methods and detection equipment, and analyzed the advantages and disadvantages of these detection methods. We reasonably concluded that a good detection method for pathogenic microorganisms in water should have the advantages of low cost, low energy consumption, simple operation, strong specificity, and high portability, which can more easily meet the needs of the water quality detection field. Multifunctional small nucleic acid detection devices have been reported for decades, which reduce the reaction time of nucleic acid amplification from hours to minutes, and these miniaturized devices based on nucleic acid amplification are not only highly specific but also low cost, which is very suitable for resource-limited environments.
Analysis of overvoltage impact on shell-type on-board traction transformer by multi-physics field simulation
Authors: Zhang Ziyue , Wang Zijing , Xiao Song
Published: March 2024

With the rapid development and increasing demands for the high-speed railway in China, it is of great significance to examine the defects of the high-speed train and ensure the safety of the operating railway. In the actual operation of the high-speed train, there is a split-phase section to transit the train to the next substation power supply arm. In this particular stage, operational overvoltage would occur as the VCB and the pantograph switch on and off, which threatens the safety of the operation of high-speed trains and contributes to the breakdown of transformer windings, which is indispensable in transformer operation. In this work, a finite element model of shell type on board traction transformer is constructed and multi-physics field simulation results, including electromagnetic field, temperature field, and flow velocity field, are analyzed to investigate the potential risky spots in the practical operation of high-speed train under overvoltage impulse, which could be supportive in maintaining the devices and detecting the winding defects.
A novel decomposition-based ensemble broad learning system for short-term load forecasting
Authors: Tian Yihan
Published: March 2024

Load forecasting of the power system plays a key role in the production planning and actual operation scheduling of power systems. However, as the power system becomes larger and more complex, it is very important to propose a forecasting model with high accuracy and low computational cost. In this paper, a novel short-term load forecasting model is proposed, which combines the empirical wavelet transform (EWT) and the broad learning system (BLS). The advantage of EWT is that it can decompose the signal into multiple local frequency bands, select the local wavelet function adaptively, and overcome the modal mixing problem caused by the discontinuity of the signal time-frequency scale. While, the advantage of BLS is that it allows the model to learn more by stretching the width, and uses ridge regression to make it less time consuming and faster. To verify the effectiveness, the model is compared with some other state-of-the-art methods, and several performance estimations indicate that the model has high accuracy and low computational cost.
Research on the application of big data mining technology based on neural network
Authors: Wang Xiangchao
Published: March 2024

In the development of social construction, all walks of life have the application of data mining technology, with the continuous development of science and technology, data mining technology can not only use the hidden law to solve the problem of time, but also can grasp more valuable data in the increasingly competitive social environment. Originally, after understanding the application research status of big data mining technology, based on the application of big data mining technology with neural network as the core, empirical analysis was carried out with Guanhealth big data intelligent analysis system as an example, in order to verify the unique value of data mining technology.
Optimal Operation Model of Ecological Flow of Hydropower Station Based on Genetic Algorithm and Neural Network
Authors: Wang Qiyou , Chen Jiping , Cui Liang
Published: March 2024

In view of the contradiction between the ecological flow regulation of the reservoir River and the power generation flow regulation of the reservoir with the largest power generation, this paper takes the maximum power generation and the maximum average ecological protection degree as the objective function, and uses the genetic algorithm back propagation neural networks (GA-BP) algorithm to establish the reservoir flow regulation model under the constraints of water balance, reservoir capacity, unit output and unit overflow, The optimal solution of the dispatching scheme is carried out, and the Shulehe hydropower station is taken as an example to verify the optimal scheme. The results show that the optimized dispatching model can ensure the demand of ecological flow, increase 32680 kW·h power generation and 23.85% power generation benefit, so as to provide scientific reference for the rational planning, dispatching and utilization of reservoir water resources.
Preparation and Properties of Graphene Flexible Membrane
Authors: Yao Yao , Han Chao , Guo Zijun , Dai Jinzhou , Zhou Bichen
Published: March 2024

Graphene material has excellent electrical, thermal and mechanical properties, and the flexible film prepared by it can be widely used in intelligent wearables, industrial temperature control, biomedicine, home heating and other fields. In this paper, graphene paste was used to prepare textile substrate and non-substrate graphene flexible film, and its tensile strength, elongation at break, resistivity, hardness, modulus and other parameters were tested. The results show that the graphene flexible film has smooth appearance, good electrical conductivity and good mechanical strength, and is a good choice for smart wear and industrial parts gasket applications.
Topology-based Resilience Assessment of Port Multimodal Transport Networks: A Case Study of Shanghai Port
Authors: Dong Xi , Min Junyi , Xi Yiheng , Jiang Chenming
Published: March 2024

As transit nodes in the field of international trade, ports are of critical importance for establishing and maintaining the effectiveness of the trade supply chain. However, the system performance of ports is vulnerable to disruptions caused by unexpected events such as natural disasters, accidental catastrophes, and public health emergency. These disruptive events will have serious negative impacts on the normal operation performance of ports and international trade among countries. This paper is to propose a comprehensive assessment framework of the system resilience of the port multimodal transport networks before and after the occurrence of disruption events, which can effectively improve its ability to deal with emergencies, minimize losses, and enhance the system performance levels. This paper also establishes several simulation experiments focusing on the full lifecycle of resilience based on topology of the transport networks, and simulates a variety of scenarios regarding different damage and recovery modes, such as deliberate attack, random attack, planned recovery, and random recovery, in the assessment process. Then the actual transport situation of Shanghai port is taken as a case study, and three multimodal transport networks including the sea-rail network, the sea-road network, and the sea-road-rail network under different disruption scenarios are compared，and evaluate the evolutions of the network resilience of the multimodal transport networks of Shanghai port stage by stage. In addition, managerial suggestions are also proposed based on the resilience assessments of different disruption scenarios to maximize the resilience of multimodal transport networks of Shanghai port.
Efficiency Optimization Strategies for Wind-Solar Driven Hydrogen Energy Storage Systems
Authors: Zhou Xiaokai , Yin Dai
Published: March 2024

This research focuses on optimizing wind-solar driven hydrogen energy storage systems. It addresses efficiency challenges through mathematical modeling and optimization. The study establishes mathematical representations, including probability distribution models for energy inputs, and defines output efficiency linked to electrolysis and fuel cell processes. Various optimization strategies, such as linear programming, nonlinear programming, and genetic algorithms, are explored. Case analysis and numerical simulations demonstrate the strategy's effectiveness. The study concludes by highlighting its practical implications and the promising future of wind-solar driven hydrogen energy storage systems.
An Exploration of Customer Segmentation Methods Based on Clustering Algorithm in the Context of Big Data
Authors: Zhao Wenbo
Published: March 2024

Accompanied by the continuous development of big data technology, various industries are well aware of the advantages of big data, which are widely used in customer service work, especially in the support of customer segmentation work, and have achieved good results. In this paper, for the problems of large fluctuation of clustering results and low clustering purity in the traditional data mining process, the big data precision mining technology with improved clustering algorithm is proposed. And it is applied in the field of customer segmentation, and the experimental results show that the improved clustering algorithm is applied in customer segmentation, the result curve fluctuation amplitude is small, and the clustering purity is significantly higher than the traditional algorithm.
Study On The Improvement Of Precise Transfer Process For Critically Ill Neonates
Authors: Wang Xin , Guo Chaoxue , Li Zhiyi , Liu Yuchi , Wang Linlin , Gao Yuxian
Published: March 2024

Objective To improve the nursing strategy of critically ill neonatal transport and provide guidance for neonatal transport nursing through the study of critically ill neonatal transport. Methods From January 2020 to July 2023, according to the specific requirements and management regulations of epidemic prevention and control, our hospital established a strict and standardized transport plan, carried out transport tasks for 472 newborns who met the transport indications, and organization and management in the transport process; full security protection policy ;the improvement of transport quality and psychological support of family members were studied and analyzed. Results All 472 neonates arrived at the transport hospital safely, their condition did not worsen, their vital signs were stable, and the accompanying medical personnel and drivers did not have infection symptoms. Conclusion This study concluded that in the process of critically ill neonatal transport, the corresponding quality improvement was made in all aspects, which significantly improved the safety of transport during the epidemic period, met the needs of primary hospitals, ensured the life treatment of critically ill children, and maintained the integrity of the medical system.
Application of AES and 3DES Hybrid Encryption Algorithm Based on Optimized S Box in the Data Transmission of Human Resources and Social Security Informatization
Authors: Hua Lei
Published: March 2024

In this paper, a hybrid encryption algorithm based on AES and 3DES is proposed to improve the security of data transmission in human resources and social security informatization. We first analyze the advantages and disadvantages of AES and 3DES, and then elaborate on why the two algorithms are used in combination. Then, this paper discusses the implementation process and mathematical principle of the hybrid algorithm. Finally, we implement the hybrid algorithm in the C + + language and present an application example.