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The high-efficient processing of mass data is a primary issue in building and maintaining security video surveillance system. This paper aims to focus on the architecture of security video surveillance system, which was based on Hadoop parallel processing technology in big data environment.

A hardware framework of security video surveillance network cascaded system (SVSNCS) was constructed on the basis of Internet of Things, network cascade technology and Hadoop platform. Then, the architecture model of SVSNCS was proposed using the Hadoop and big data processing platform.

Finally, we suggested the procedure of video processing according to the cascade network characteristics.

Our paper, which focused on the architecture of security video surveillance system in big data environment on the basis of Hadoop parallel processing technology, provided high-quality video surveillance services for security area.

This article has been withdrawn as it was published elsewhere and accidentally duplicated. The original article can be seen here: 10.1108/17488840610639681. When citing the article, please cite: Xiujie Jiang, Huixian Sun, Xiaomin Chen, Zhihua Wang, Li Zhang, Daxing Wang, (2006), “Utilization of a COTS component in temperature measurement system for microgravity fluid experiment on SZ-4 spaceship”, Aircraft Engineering and Aerospace Technology, Vol. 78 Iss: 1, pp. 45 - 49.

This paper aims to convict the offender of real concurrence offenses of the most severe offense and applying the most severe penalty will result in no distinction between the perpetrator who conducted more than one act and the one who conducted only one act. This approach deviates from the purpose of criminal law. The real concurrence of offenses means several offenses, the perpetrator’s dangerousness and culpability are much higher than the perpetrator who commits just one crime, so combined punishments for several offenses should be applied to the real concurrence of offenses.

If the depositors are acquaintances or relatives and friends, the relationship can be explained by “personality trust.” If the depositors are strangers, but they have complied with their duties of care, the deposit relationship can be explained by “system trust.”

The real concurrence of offenses means several offenses, the perpetrator’s dangerousness and culpability are much higher than the perpetrator who commits just one crime, so combined punishments for several offenses should be applied to the real concurrence of offenses.

The principle of choosing the most severe punishment applied to the real concurrence of offense should be abolished. As the perpetrator separately conducts two acts at different times, these acts infringe on different legal interests. Although these acts exist closely, the authors cannot deny that these acts constitute more than one offense.

In this paper, considering a tradeoff between consumers comfort and energy efficiency, a multi-period joint energy scheduling algorithm (MPJ-ESA) based on prediction of residents energy consumption is proposed, which includes long-period preliminary sch eduling, short-period preliminary scheduling, and real-time fine-tuning scheduling. First, by analyzing historical data of energy consumption, preferred usage profile of consumers is inferred, and the dynamic comfort level is presented. Then the paper uses the wavelet neural networks (WNNs) prediction algorithm to predict the operation of the appliances which are classified into appliances with unschedulable mode and schedulable mode. Based on the energy consumption prediction and dynamic comfort level, home appliances running state are scheduled according to the prediction of renewable energy available amount and real-time pricing (RTP). The simulation results show that scheduling algorithm effectively improves the energy efficiency and enhances user satisfaction with the operation of scheduled appliances and let the consumers comfort and energy efficiency achieve a better tradeoff.

The purpose of this paper is to address the problem of control in a typical chaotic power system. Chaotic oscillations cannot only extremely endanger the stabilization of the power system but they can also not be controlled by adding the traditional controllers. So, the sliding mode control based on a fuzzy supervisor can sufficiently ensure perfect tracking and controlling in the presence of uncertainties. Closed-loop stability is proved using the Lyapunov stability theory. The simulation results show the effectiveness of the proposed method in damping chaotic oscillations of the power system, eliminating control signal chattering and also show less control effort in comparison with the methods considered in previous literatures.

The sliding mode control based on a fuzzy supervisor can sufficiently ensure perfect tracking and controlling in the presence of uncertainties. Closed-loop stability is proved using the Lyapunov stability theory.

Closed-loop stability is proved using the Lyapunov stability theory. The simulation results show the effectiveness of the proposed method in damping chaotic oscillations of power system, eliminating control signal chattering and also less control effort in comparison with the methods considered in previous literatures.

Main contributions of the paper are as follows: the chaotic behavior of power systems with two uncertainty parameters and tracking reference signal for the control of generator angle and the controller signal are discussed; designing sliding mode control based on a fuzzy supervisor in order to practically implement for the first time; while the generator speed is constant, the proposed controller will enable the power system to go in any desired trajectory for generator angle at first time; stability of the closed-loop sliding mode control based on the fuzzy supervisor system is proved using the Lyapunov stability theory; simulation of the proposed controller shows that the chattering is low control signal.

This paper aims to focus on the spatial docking task of unmanned vehicles under ground conditions. The docking task of military unmanned vehicle application scenarios has strict requirements. Therefore, how to design a docking robot mechanism to achieve accurate docking between vehicles has become a challenge.

In this paper, first, the docking mechanism system is described, and the inverse kinematics model of the docking robot based on Stewart is established. Second, the genetic algorithm-based optimization method for multiobjective parameters of parallel mechanisms including workspace volume and mechanism flexibility is proposed to solve the problem of multiparameter optimization of parallel mechanism and realize the docking of unmanned vehicle space flexibility. The optimization results verify that the structural parameters meet the design requirements. Besides, the static and dynamic finite element analysis are carried out to verify the structural strength and dynamic performance of the docking robot according to the stiffness, strength, dead load and dynamic performance of the docking robot. Finally, taking the docking robot as the experimental platform, experiments are carried out under different working conditions, and the experimental results verify that the docking robot can achieve accurate docking tasks.

Experiments on the docking robot that the proposed design and optimization method has a good effect on structural strength and control accuracy. The experimental results verify that the docking robot mechanism can achieve accurate docking tasks, which is expected to provide technical guidance and reference for unmanned vehicles docking technology.

This research can provide technical guidance and reference for spatial docking task of unmanned vehicles under the ground conditions. It can also provide ideas for space docking missions, such as space simulator docking.

This study aims to address the issue of random movement and non coordination between docking mechanisms and locking mechanisms, and proposes a comprehensive dynamic docking control architecture that integrates perception, planning, and motion control.

Firstly, the proposed dynamic docking control architecture uses laser sensors and a charge-coupled device camera to perceive the pose of the target. The sensor data are mapped to a high-dimensional potential field space and fused to reduce interference caused by detection noise. Next, a new potential function based on multi-dimensional space is developed for docking path planning, which enables the docking mechanism based on Stewart platform to rapidly converge to the target axis of the locking mechanism, which improves the adaptability and terminal docking accuracy of the docking state. Finally, to achieve precise tracking and flexible docking in the final stage, the system combines a self-impedance controller and an impedance control algorithm based on the planned trajectory.

Extensive simulations and experiments have been conducted to validate the effectiveness of the dynamic docking system and its control architecture. The results indicate that even if the target moves randomly, the system can successfully achieve accurate, stable and flexible dynamic docking.

This research can provide technical guidance and reference for docking task of unmanned vehicles under the ground conditions. It can also provide ideas for space docking missions, such as space simulator docking.

This study aims to investigate the sealing performance of a novel ribbed oil-slinging ring composite seal (ROSRCS) for the axle end of train gearboxes. The ROSRCS design incorporates added ribs and an inclined outer edge to enhance the sealing mechanism and reduce oil leakage.

Computational fluid dynamics simulations were used to analyze the leakage characteristics of ROSRCS under varying angles, outer edge inclinations and rib numbers and heights. The sealing performance was compared to a traditional oil-slinging ring composite seal (OSRCS). Key parameters such as oil leakage rate, turbulence dissipation intensity and jet strength were evaluated.

Results indicate that ROSRCS reduces the oil leakage rate by 5.7% compared to OSRCS. At a slinger ring inclination of 35°, the turbulence dissipation center in the ROSRCS flow field shifts toward the inlet, increasing the maximum turbulence dissipation intensity by 22.56%. A proper outer edge inclination enhances jet intensity, strengthening turbulence dissipation by up to 9.21%. While adding ribs may generate negative pressure zones, strategic rib configurations improve axle-end sealing performance by modifying the number, position and intensity of vortices.

This research presents a refined composite seal design that enhances the sealing efficiency of train gearbox axle ends, demonstrating improved oil retention through innovative geometric modifications. The findings contribute to the development of more efficient sealing technologies in high-speed train applications.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-10-2024-0370/

The purpose of this paper is to investigate the relationships between supply chain quality management (SCQM) and firm performance (including quality safety performance and sales performance) leveraging social co-regulation as a moderator.

Using survey data collected from 203 food manufacturers in China, a series of hierarchical linear modeling analyses were conducted to test hypotheses on the relationships between SCQM and firm performance.

The findings are threefold. First, all three dimensions of food SCQM practices, i.e., supplier quality management, internal quality management, and customer quality management, have significant positive effects on an enterprise's quality safety performance and sales performance. Second, SCQM practices can also increase sales performance indirectly through quality safety performance as a mediator. Third, while social co-regulation has no significant effect on the relationship between supplier quality management and quality safety performance, it has a significant moderating effect on the relationship between internal quality management and quality safety performance, customer quality management and quality safety performance.

This study not only integrates SCQM with social co-regulation but also explores the regulating effect of social co-regulation through empirical analysis, thereby providing a theoretical base for future research. However, this research is confined to China and so the results are not necessarily generalizable to other countries.

The findings inform managers of the importance in enhancing awareness of food quality and safety as well as in improving their sensitivity to salient quality demands of external stakeholders in order to achieve better SCQM practices. The findings can also inform policymakers of the significance in designing a systematic multi-agent cooperation mechanism for food SCQM as well as to build an effective information sharing mechanism for social co-regulation of food safety.

This study contributes to knowledge by empirically examining the relationships of SCQM practices with firm performance. It also expands the scope of SCQM research by incorporating social co-regulation in the study framework.

Hexahedral meshing is one of the most important steps in performing an accurate simulation using the finite element analysis (FEA). However, the current hexahedral meshing method in the industry is a nonautomatic and inefficient method, i.e. manually decomposing the model into suitable blocks and obtaining the hexahedral mesh from these blocks by mapping or sweeping algorithms. The purpose of this paper is to propose an almost automatic decomposition algorithm based on the 3D frame field and model features to replace the traditional time-consuming and laborious manual decomposition method.

The proposed algorithm is based on the 3D frame field and features, where features are used to construct feature-cutting surfaces and the 3D frame field is used to construct singular-cutting surfaces. The feature-cutting surfaces constructed from concave features first reduce the complexity of the model and decompose it into some coarse blocks. Then, an improved 3D frame field algorithm is performed on these coarse blocks to extract the singular structure and construct singular-cutting surfaces to further decompose the coarse blocks. In most modeling examples, the proposed algorithm uses both types of cutting surfaces to decompose models fully automatically. In a few examples with special requirements for hexahedral meshes, the algorithm requires manual input of some user-defined cutting surfaces and constructs different singular-cutting surfaces to ensure the effectiveness of the decomposition.

Benefiting from the feature decomposition and the 3D frame field algorithm, the output blocks of the proposed algorithm have no inner singular structure and are suitable for the mapping or sweeping algorithm. The introduction of internal constraints makes 3D frame field generation more robust in this paper, and it can automatically correct some invalid 3–5 singular structures. In a few examples with special requirements, the proposed algorithm successfully generates valid blocks even though the singular structure of the model is modified by user-defined cutting surfaces.

The proposed algorithm takes the advantage of feature decomposition and the 3D frame field to generate suitable blocks for a mapping or sweeping algorithm, which saves a lot of simulation time and requires less experience. The user-defined cutting surfaces enable the creation of special hexahedral meshes, which was difficult with previous algorithms. An improved 3D frame field generation method is proposed to correct some invalid singular structures and improve the robustness of the previous methods.