Research on static characteristic of double redundance double nozzle flapper valve based on AMESim

The feedback spring rod of the armature assembly is cancelled in the double redundance double nozzle flapper valve(DRDNFV),and the difficulty of valve core displacement control is increased.Therefore,this paper intends to study the static characteristic of DRDNFV through the AMESet and AMESim simulation.It is explored under the circumstance of the fixed orifices being clogged and experimentally verified on the test bench.The results show that the pressure gain increases and the flow gain decreases with the increasing clogged degree of the fixed orifices on both sides.The zero bias increases synchronously with the increasing clogged degree of the unilateral fixed orifice.The experimental results are basically consistent with the theoretical curves and the theoretical correctness of the simulation model is effectively verified.The results can provide the theoretical reference for design,debugging,maintenance and fault diagnosis of DRDNFV.

Performance analysis of the tight combination of GPS, BDS, GALILEO, and QzsS mixed frequencies signals

With the gradual development and modernization of satellite navigation systems,using observation information from multi-GNss has become one of the hot-spot issues in recent years.Multi-system loose combinations form double-difference observation equations within their respective systems,and the positioning effect is improved.However,the interchangeability and compatible interoperability between global navigation satellite systems(GNSS)cannot be truly realized.At the same time,when the number of visible satellites decreases abruptly,the positioning performance deteriorates sharply.This paper focuses on the GNsS multi-system tight combination relative positioning technique,gives a mathe-matical model of multi-system tight combination relative positioning considering differential inter-system bias(DISB),and analyzes the time-varying characteristics of DISB at overlapping and non-overlapping frequencies among GPS/Galileo,GPS/BDS,and GPS/QZSS in terms of receiver brand,tem-perature,and receiver restart.The GNsS tight combination relative positioning performance is verified by static data from Curtin University and dynamic data measured at Taiyuan University of Technology.The results show that compared with loose combination,the ambiguity-fixed rate increases from 62.18%to 97.60%for static data and from 74.97%to 99.53%for dynamic data when the elevation mask angle is 50°,resulting in a significant improvement in positioning performance.

A redundant subspace weighting procedure for clock ensemble

A redundant-subspace-weighting(RSW)-based approach is proposed to enhance the frequency stability on a time scale of a clock ensemble.In this method,multiple overlapping subspaces are constructed in the clock ensemble,and the weight of each clock in this ensemble is defined by using the spatial covariance matrix.The superimposition average of covariances in different subspaces reduces the correlations between clocks in the same laboratory to some extent.After optimizing the parameters of this weighting procedure,the frequency stabilities of virtual clock ensembles are significantly improved in most cases.

Redundant Data Detection and Deletion to Meet Privacy Protection Requirements in Blockchain-Based Edge Computing Environment

With the rapid development of information technology,IoT devices play a huge role in physiological health data detection.The exponential growth of medical data requires us to reasonably allocate storage space for cloud servers and edge nodes.The storage capacity of edge nodes close to users is limited.We should store hotspot data in edge nodes as much as possible,so as to ensure response timeliness and access hit rate;However,the current scheme cannot guarantee that every sub-message in a complete data stored by the edge node meets the requirements of hot data;How to complete the detection and deletion of redundant data in edge nodes under the premise of protecting user privacy and data dynamic integrity has become a challenging problem.Our paper proposes a redundant data detection method that meets the privacy protection requirements.By scanning the cipher text,it is determined whether each sub-message of the data in the edge node meets the requirements of the hot data.It has the same effect as zero-knowledge proof,and it will not reveal the privacy of users.In addition,for redundant sub-data that does not meet the requirements of hot data,our paper proposes a redundant data deletion scheme that meets the dynamic integrity of the data.We use Content Extraction Signature(CES)to generate the remaining hot data signature after the redundant data is deleted.The feasibility of the scheme is proved through safety analysis and efficiency analysis.

Intelligent Dynamic Heterogeneous Redundancy Architecture for IoT Systems

The conventional dynamic heterogeneous redundancy(DHR)architecture suffers from the security threats caused by the stability differences and similar vulnerabilities among the executors.To overcome these challenges,we propose an intelligent DHR architecture,which is more feasible by intelligently combining the random distribution based dynamic scheduling algorithm(RD-DS)and information weight and heterogeneity based arbitrament(IWHA)algorithm.In the proposed architecture,the random distribution function and information weight are employed to achieve the optimal selection of executors in the process of RD-DS,which avoids the case that some executors fail to be selected due to their stability difference in the conventional DHR architecture.Then,through introducing the heterogeneity to restrict the information weights in the procedure of the IWHA,the proposed architecture solves the common mode escape issue caused by the existence of multiple identical error output results of similar vulnerabilities.The experimental results characterize that the proposed architecture outperforms in heterogeneity,scheduling times,security,and stability over the conventional DHR architecture under the same conditions.

Multi-Label Feature Selection Based on Improved Ant Colony Optimization Algorithm with Dynamic Redundancy and Label Dependence

The world produces vast quantities of high-dimensional multi-semantic data.However,extracting valuable information from such a large amount of high-dimensional and multi-label data is undoubtedly arduous and challenging.Feature selection aims to mitigate the adverse impacts of high dimensionality in multi-label data by eliminating redundant and irrelevant features.The ant colony optimization algorithm has demonstrated encouraging outcomes in multi-label feature selection,because of its simplicity,efficiency,and similarity to reinforcement learning.Nevertheless,existing methods do not consider crucial correlation information,such as dynamic redundancy and label correlation.To tackle these concerns,the paper proposes a multi-label feature selection technique based on ant colony optimization algorithm(MFACO),focusing on dynamic redundancy and label correlation.Initially,the dynamic redundancy is assessed between the selected feature subset and potential features.Meanwhile,the ant colony optimization algorithm extracts label correlation from the label set,which is then combined into the heuristic factor as label weights.Experimental results demonstrate that our proposed strategies can effectively enhance the optimal search ability of ant colony,outperforming the other algorithms involved in the paper.

A framework for dynamic modelling of railway track switches considering the switch blades,actuators and control systems

The main contribution of this paper is the development and demonstration of a novel methodology that can be followed to develop a simulation twin of a railway track switch system to test the functionality in a digital environment.This is important because,globally,railway track switches are used to allow trains to change routes;they are a key part of all railway networks.However,because track switches are single points of failure and safety-critical,their inability to operate correctly can cause significant delays and concomitant costs.In order to better understand the dynamic behaviour of switches during operation,this paper has developed a full simulation twin of a complete track switch system.The approach fuses finite element for the rail bending and motion,with physics-based models of the electromechanical actuator system and the control system.Hence,it provides researchers and engineers the opportunity to explore and understand the design space around the dynamic operation of new switches and switch machines before they are built.This is useful for looking at the modification or monitoring of existing switches,and it becomes even more important when new switch concepts are being considered and evaluated.The simulation is capable of running in real time or faster meaning designs can be iterated and checked interactively.The paper describes the modelling approach,demonstrates the methodology by developing the system model for a novel“REPOINT”switch system,and evaluates the system level performance against the dynamic performance requirements for the switch.In the context of that case study,it is found that the proposed new actuation system as designed can meet(and exceed)the system performance requirements,and that the fault tolerance built into the actuation ensures continued operation after a single actuator failure.

A new technique of monsplasty as an adjunctive procedure in cases of abdominoplasty:A prospective clinical trial

Background:No standard monsplasty technique has existed until now.Although various monsplasty methods have been described,they exhibit high complication rates with sparse postoperative data.Studies that used pubic suspension techniques did not describe exact anatomical landmarks for the mons pexy.This study aimed to improve the aesthetic and functional appearance of the pubic region with long-term results for all grades of pubic ptosis or bulging with abdominoplasty and provide exact anatomical points to anchor the mons to the rectus sheath.Methods:This non-randomized prospective clinical trial included 30 patients with various degrees of abdominal wall laxity between December 2017 and September 2019.The surgical procedure was performed for female patients with pendulous abdomen,pubic ptosis or bulging,body mass index≤35 kg/m^(2),and age 18–60 years.All patients were followed for up to one year;patient satisfaction was assessed before and after surgery regarding aesthetic results and impact on outfits,hygiene,and sexual activity.Results:The marginal homogeneity test revealed a statistically significant patient satisfaction rate regarding outfits,sexual function,hygiene,and aesthetics.Regarding postoperative complications,seroma(one case)was managed by aspiration,and one case of wound dehiscence was managed conservatively with dressings.Conclusion:This study recommends a quick and reproducible monsplasty technique with a low complication rate,a technique that helps determine specific anatomical landmarks for anchoring the mons to the rectus sheath.Combining this technique with abdominal contouring is advisable for optimal aesthetic results and maintained lymphatic drainage in the pubic region.

Analysis of wheel-rail adhesion redundancy considering the thirdbody medium on the rail surface

Purpose–In response to the problem of insufficient traction/braking adhesion force caused by the existence of the third-body medium on the rail surface,this study aims to analyze the utilization of wheel-rail adhesion coefficient under different medium conditions and propose relevant measures for reasonable and optimized utilization of adhesion to ensure the traction/braking performance and operation safety of trains.Design/methodology/approach–Based on the PLS-160 wheel-rail adhesion simulation test rig,the study investigates the variation patterns of maximum utilized adhesion characteristics on the rail surface under different conditions of small creepage and large slip.Through statistical analysis of multiple sets of experimental data,the statistical distribution patterns of maximum utilized adhesion on the rail surface are obtained,and a method for analyzing wheel-rail adhesion redundancy based on normal distribution is proposed.The study analyzes the utilization of traction/braking adhesion,as well as adhesion redundancy,for different medium under small creepage and large slip conditions.Based on these findings,relevant measures for the reasonable and optimized utilization of adhesion are derived.Findings–When the third-body medium exists on the rail surface,the train should adopt the low-level service braking to avoid the braking skidding by extending the braking distance.Compared with the current adhesion control strategy of small creepage,adopting appropriate strategies to control the train’s adhesion coefficient near the second peak point of the adhesion coefficient-slip ratio curve in large slip can effectively improve the traction/braking adhesion redundancy and the upper limit of adhesion utilization,thereby ensuring the traction/braking performance and operation safety of the train.Originality/value–Most existing studies focus on the wheel-rail adhesion coefficient values and variation patterns under different medium conditions,without considering whether the rail surface with different medium can provide sufficient traction/braking utilized adhesion coefficient for the train.Therefore,there is a risk of traction overspeeding/braking skidding.This study analyzes whether the rail surface with different medium can provide sufficient traction/braking utilized adhesion coefficient for the train and whether there is redundancy.Based on these findings,relevant measures for the reasonable and optimized utilization of adhesion are derived to further ensure operation safety of the train.

Quantitative Comparative Study of the Performance of Lossless Compression Methods Based on a Text Data Model

Data compression plays a key role in optimizing the use of memory storage space and also reducing latency in data transmission. In this paper, we are interested in lossless compression techniques because their performance is exploited with lossy compression techniques for images and videos generally using a mixed approach. To achieve our intended objective, which is to study the performance of lossless compression methods, we first carried out a literature review, a summary of which enabled us to select the most relevant, namely the following: arithmetic coding, LZW, Tunstall’s algorithm, RLE, BWT, Huffman coding and Shannon-Fano. Secondly, we designed a purposive text dataset with a repeating pattern in order to test the behavior and effectiveness of the selected compression techniques. Thirdly, we designed the compression algorithms and developed the programs (scripts) in Matlab in order to test their performance. Finally, following the tests conducted on relevant data that we constructed according to a deliberate model, the results show that these methods presented in order of performance are very satisfactory:- LZW- Arithmetic coding- Tunstall algorithm- BWT + RLELikewise, it appears that on the one hand, the performance of certain techniques relative to others is strongly linked to the sequencing and/or recurrence of symbols that make up the message, and on the other hand, to the cumulative time of encoding and decoding.

Beyond Defense: Proactive Approaches to Disaster Recovery and Threat Intelligence in Modern Enterprises

As cyber threats keep changing and business environments adapt, a comprehensive approach to disaster recovery involves more than just defensive measures. This research delves deep into the strategies required to respond to threats and anticipate and mitigate them proactively. Beginning with understanding the critical need for a layered defense and the intricacies of the attacker’s journey, the research offers insights into specialized defense techniques, emphasizing the importance of timely and strategic responses during incidents. Risk management is brought to the forefront, underscoring businesses’ need to adopt mature risk assessment practices and understand the potential risk impact areas. Additionally, the value of threat intelligence is explored, shedding light on the importance of active engagement within sharing communities and the vigilant observation of adversary motivations. “Beyond Defense: Proactive Approaches to Disaster Recovery and Threat Intelligence in Modern Enterprises” is a comprehensive guide for organizations aiming to fortify their cybersecurity posture, marrying best practices in proactive and reactive measures in the ever-challenging digital realm.

拉林河浮游植物三种功能群分布特征及其与环境因子的关系

浮游植物是河流生态系统能量流动与信息传递的关键环节。浮游植物及其功能性状对于水体水文条件、理化特征及气候变化敏感,因此被广泛应用于水体环境监测。拉林河流域是我国北方重要稻米基地和商品粮基地,受农业面源污染严重。然而,拉林河流域浮游植物群落演替规律尚不明确,基于不同生态属性的功能群对拉林河环境的指示意义仍不清晰。于2021年春季和夏季在拉林河流域设置23个采样点对浮游植物群落进行定性定量分析。基于浮游植物功能群(functional group,FG)、生态功能群(morpho-functional group,MFG)和形态功能群(morphology-based functional group,MBFG)分析浮游植物群落演替特征。通过冗余分析(redundancy analysis,RDA)揭示驱动浮游植物群落演替的关键环境因子。结果显示,研究期间拉林河流域浮游植物群落演替明显,划分FG功能群25个,MFG功能群24个,MBFG功能群7个。FG、MFG和MBFG功能群的演替受多种环境因素共同影响,其中水温(water temperature,WT)和总氮(total nitrogen,TN)与功能群演替关系密切。经研究表明FG功能群能更好的响应拉林河流域水环境的时空异质性。相较于传统的林奈分类法,FG功能群提供了高效、简便且能反映生态信息的划分方式。在未来对于拉林河流域水生生物多样性保护及环境监测研究中,FG功能群是可靠的研究手段。

Modern pollen assemblages and their relationships with vegetation and climate on the northern slopes of the Tianshan Mountains, Xinjiang, China

The reconstruction of paleovegetation and paleoclimate requires an understanding of the relationships between surface pollen assemblages and modern vegetation and climate.Here,we analyzed the characteristics of surface pollen assemblages across different vegetation zones in the Tianshan Mountains.Using surface pollen analysis and vegetation sample surveys at 75 sites on the northern slopes of the Tianshan Mountains,we determined the correlation between the percentage of dominant pollen types and the corresponding vegetation cover.Redundancy analysis was used to investigate the relationships between surface pollen assemblages and environmental factors.Our results show that the Tianshan Mountains contain several distinct ecological regions,which can be divided into five main vegetation zones from low to high altitudes:mountain desert zone(Hutubi County(HTB):500-1300 m;Qitai County(QT):1000-1600 m),mountain steppe zone(HTB:1400-1600 m;QT:1650-1800 m),mountain forest zone(HTB:1650-2525 m;QT:1850-2450 m),subalpine meadow zone(HTB:2550-2600 m;QT:2500-2600 m),and alpine mat vegetation zone(HTB:2625-2700 m;QT:2625-2750 m).The surface pollen assemblages of different vegetation zones can accurately reflect the characteristics of the mountainous vegetation patterns on the northern slopes of the Tianshan Mountains when excluding the widespread occurrence of Chenopodiaceae,Artemisia,and Picea pollen.Both average annual precipitation(P_(ann))and annual average temperature(T_(ann))affect the distribution of surface pollen assemblages.Moreover,P_(ann) is the primary environmental factor affecting surface pollen assemblages in this region.A significant correlation exists between the pollen percentage and vegetation cover of Picea,Chenopodiaceae,Artemisia,and Asteraceae.Moreover,Picea,Chenopodiaceae,and Artemisia pollen are over-represented compared with their corresponding vegetation cover.The Asteraceae pollen percentage roughly reflects the distribution of a species within the local vegetation.These results have important implications for enhancing our understanding of the relationship between surface pollen assemblages and modern vegetation and climate.

Wavelet Denoising Applied to Hardware Redundant Systems for Rolling Element Bearing Fault Detection

This work presents a novel wavelet-based denoising technique for improving the signal-to-noise ratio(SNR)of nonsteady vibration signals in hardware redundant systems.The proposed method utilizes the relationship between redundant hardware components to effectively separate fault-related components from the vibration signature,thus enhancing fault detection accuracy.The study evaluates the proposed technique on two mechanically identical subsystems that are simultaneously controlled under the same speed and load inputs,with and without the proposed denoising step.The results demonstrate an increase in detection accuracy when incorporating the proposed denoising method into a fault detection system designed for hardware redundant machinery.This work is original in its application of a new method for improving performance when using residual analysis for fault detection in hardware redundant machinery configurations.Moreover,the proposed methodology is applicable to nonstationary equipment that experiences changes in both speed and load.

Microcontroller Design Based on Dynamic Heterogeneous Redundancy Architecture

Redundancy control can effectively enhance the stability and robustness of a system.Based on the conventional redundancy control switchover and majority arbitration strategy,this paper introduces the concept of heterogeneity and dynamics,constructs a dynamic heterogeneous redundancy-based microcontroller architecture DHR-MCU,and designs a fixed-leader distributed consensus algorithm that satisfies the program running state control of this architecture.The theoretical analysis and actual measurement of the prototype system prove that this architecture has good anti-attack and self-recovery capabilities under normal functions and performances and meets the general robust features in terms of safety and security.

Multi-Objective Redundancy Optimization of Continuous-Point Robot Milling Path in Shipbuilding

The 6-DOF manipulator provides a new option for traditional shipbuilding for its advantages of vast working space,low power consumption,and excellent flexibility.However,the rotation of the end effector along the tool axis is functionally redundant when using a robotic arm for five-axis machining.In the process of ship construction,the performance of the parts’protective coating needs to bemachined tomeet the Performance Standard of Protective Coatings(PSPC).The arbitrary redundancy configuration in path planning will result in drastic fluctuations in the robot joint angle,greatly reducing machining quality and efficiency.There have been some studies on singleobjective optimization of redundant variables,However,the quality and efficiency of milling are not affected by a single factor,it is usually influenced by several factors,such as the manipulator stiffness,the joint motion smoothness,and the energy consumption.To solve this problem,this paper proposed a new path optimization method for the industrial robot when it is used for five-axis machining.The path smoothness performance index and the energy consumption index are established based on the joint acceleration and the joint velocity,respectively.The path planning issue is formulated as a constrained multi-objective optimization problem by taking into account the constraints of joint limits and singularity avoidance.Then,the path is split into multiple segments for optimization to avoid the slow convergence rate caused by the high dimension.An algorithm combining the non-dominated sorting genetic algorithm(NSGA-II)and the differential evolution(DE)algorithm is employed to solve the above optimization problem.The simulations validate the effectiveness of the algorithm,showing the improvement of smoothness and the reduction of energy consumption.

Novel Double Modular Redundancy Based Fault-Tolerant FIR Filter for Image Denoising

In signal processing and communication systems,digital filters are widely employed.In some circumstances,the reliability of those systems is crucial,necessitating the use of fault tolerant filter implementations.Many strategies have been presented throughout the years to achieve fault tolerance by utilising the structure and properties of the filters.As technology advances,more complicated systems with several filters become possible.Some of the filters in those complicated systems frequently function in parallel,for example,by applying the same filter to various input signals.Recently,a simple strategy for achieving fault tolerance that takes advantage of the availability of parallel filters was given.Many fault-tolerant ways that take advantage of the filter’s structure and properties have been proposed throughout the years.The primary idea is to use structured authentication scan chains to study the internal states of finite impulse response(FIR)components in order to detect and recover the exact state of faulty modules through the state of non-faulty modules.Finally,a simple solution of Double modular redundancy(DMR)based fault tolerance was developed that takes advantage of the availability of parallel filters for image denoising.This approach is expanded in this short to display how parallel filters can be protected using error correction codes(ECCs)in which each filter is comparable to a bit in a standard ECC.“Advanced error recovery for parallel systems,”the suggested technique,can find and eliminate hidden defects in FIR modules,and also restore the system from multiple failures impacting two FIR modules.From the implementation,Xilinx ISE 14.7 was found to have given significant error reduction capability in the fault calculations and reduction in the area which reduces the cost of implementation.Faults were introduced in all the outputs of the functional filters and found that the fault in every output is corrected.

Fault-tolerant FADS system development for a hypersonic vehicle via neural network algorithms

Hypersonic vehicles suffer from extreme aerodynamic heating during flights, especially around the area of leading edge due to its small curvature. Therefore, flush air data sensing(FADS) system has been developed to perform accurate measurement of the air data parameters. In the present study, the method to develop the FADS algorithms with fail-operational capability for a sharp-nosed hypersonic vehicle is provided. To be specific, the FADS system implemented with 16 airframe-integrated pressure ports is used as a case study. Numerical simulations of different freestream conditions have been conducted to generate the database for the FADS targeting in 2 ≤ Ma ≤ 5 and 0 km ≤ H ≤ 30 km. Four groups of neural network algorithms have been developed based on four different pressure port configurations, and the accuracy has been validated by 280 groups of simulations. Particularly, the algorithms based on the 16-port configuration show an excellent ability to serve as the main solver of the FADS, where 99. 5% of the angle-of-attack estimations are within the error band ±0. 2°. The accuracy of the algorithms is discussed in terms of port configuration. Furthermore, diagnosis of the system health is present in the paper. A fault-tolerant FADS system architecture has been designed, which is capable of continuously sensing the air data in the case that multi-port failure occurs, with a reduction in the system accuracy.

Reliability-based selective maintenance for redundant systems with dependent performance characteristics of components

The reliability-based selective maintenance(RSM)decision problem of systems with components that have multiple dependent performance characteristics(PCs)reflecting degradation states is addressed in this paper.A vine-Copulabased reliability evaluation method is proposed to estimate the reliability of system components with multiple PCs.Specifically,the marginal degradation reliability of each PC is built by using the Wiener stochastic process based on the PC’s degradation mechanism.The joint degradation reliability of the component with multiple PCs is established by connecting the marginal reliability of PCs using D-vine.In addition,two RSM decision models are developed to ensure the system accomplishes the next mission.The genetic algorithm(GA)is used to solve the constraint optimization problem of the models.A numerical example illustrates the application of the proposed RSM method.

Redundant Transmission Control Algorithm for Information-Centric Vehicular IoT Networks

Vehicular Adhoc Networks(VANETs)enable vehicles to act as mobile nodes that can fetch,share,and disseminate information about vehicle safety,emergency events,warning messages,and passenger infotainment.However,the continuous dissemination of information fromvehicles and their one-hop neighbor nodes,Road Side Units(RSUs),and VANET infrastructures can lead to performance degradation of VANETs in the existing hostcentric IP-based network.Therefore,Information Centric Networks(ICN)are being explored as an alternative architecture for vehicular communication to achieve robust content distribution in highly mobile,dynamic,and errorprone domains.In ICN-based Vehicular-IoT networks,consumer mobility is implicitly supported,but producer mobility may result in redundant data transmission and caching inefficiency at intermediate vehicular nodes.This paper proposes an efficient redundant transmission control algorithm based on network coding to reduce data redundancy and accelerate the efficiency of information dissemination.The proposed protocol,called Network Cording Multiple Solutions Scheduling(NCMSS),is receiver-driven collaborative scheduling between requesters and information sources that uses a global parameter expectation deadline to effectively manage the transmission of encoded data packets and control the selection of information sources.Experimental results for the proposed NCMSS protocol is demonstrated to analyze the performance of ICN-vehicular-IoT networks in terms of caching,data retrieval delay,and end-to-end application throughput.The end-to-end throughput in proposed NCMSS is 22%higher(for 1024 byte data)than existing solutions whereas delay in NCMSS is reduced by 5%in comparison with existing solutions.