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Computer‐integrated manufacturing (CIM) has been paid serious attention in most of the industrialized countries. Shenyang Blower Works (SBW), the largest enterprise developing, designing and fabricating turbine compressors, blowers and large fans in China, made its production plan according to orders due to its single or small batch production mode. For this SBW decided to adopt the CIM philosophy and build CIM systems (CIMS) to increase the enterprise’s market competitiveness. SBW has begun to develop CIMS going through the steps of feasibility study, primary design, detailed design and a partial implementation‐breakthrough project since 1990. A relatively perfect computer support environment for the computer‐integrated manufacturing system in Shenyang Blower Works (SB‐CIMS), especially for the primary integrated application software systems, has been completed. This accounted for various economic benefits.

This paper aims to provide an overview of current and historical arcjet development. The reviewed arcjets are considered with respect to both design and thruster relevant parameters. Correspondingly, the paper enables the identification of adequate design criteria and of the probable thruster parameters.

The approach consists of a database for thruster relevant parameters in conjunction with relevant operational requirements (such as type of propellant) and specific design criteria (such as e.g. propellant injection systems).

The synopsis of both operational parameter and respectively assigned design allows for the derivation of development approaches for arcjets under given high level requirements such as power regime.

The paper is a general review. However, its strength is in the synthesis of the arcjet classification, the functional evidence of design criteria and the application scenario.

Not only basic but also specific design criteria are analyzed and evaluated leading to a recommendation feature of the paper with respect to the overall design of adequate arcjets.

Within the scope of the Clean Space initiative, new applications and scenarios from the operation of arcjets arise enabling EOL phases of spacecraft that fulfill respective levels of debris mitigation and, in addition, the requirements concerning the adequately adapted re-entry of spacecrafts that are at end of life.

The paper is a general review. However, its strength is in the synthesis of the arcjet classification, the functional evidence of design criteria and the application scenario.

The purpose of this paper is to propose an improved optimization method for image matching problem, which is based on multi-scale Gaussian mutation pigeon-inspired optimization (MGMPIO) algorithm, with the objective of accomplishing the complicated image matching quickly.

The hybrid model of multi-scale Gaussian mutation (MGM) mechanism and pigeon-inspired optimization (PIO) algorithm is established for image matching problem. The MGM mechanism is a nonlinear model, which can adjust the position of pigeons by mutation operation. In addition, the variable parameter (VP) mechanism is exploited to adjust the map and compass factor of the original PIO. Low-cost quadrotor, a type of electric multiple rotorcraft, is used as a carrier of binocular camera to obtain the images.

This work improved the PIO algorithm by modifying the search strategy and adding some limits, so that it can have better performance when applied to the image matching problem. Experimental results show that the proposed method demonstrates satisfying performance in convergence speed, robustness and stability.

The proposed MGMPIO algorithm can be easily applied to solve practical problems and accelerate convergence speed of the original PIO, and thus enhancing the speed of matching process, which will considerably increase the effectiveness of algorithm.

A hybrid model of the MGM mechanism and PIO algorithm is proposed for image matching problem. The VP mechanism and low-cost quadrotor is also utilized in image matching problem.

The purpose of this paper is to propose a novel target automatic recognition method for unmanned aerial vehicle (UAV), which is based on backpropagation – artificial neural network (BP-ANN) algorithm, with the objective of optimizing the structure of backpropagation network, to increase the efficiency and decrease the recognition time. A hardware-in-the-loop system for UAV target automatic recognition is also developed.

The hybrid model of BP-ANN structure is established for aircraft automatic target recognition. This proposed method identifies controller parameters and reduces the computational complexity. Approaching speed of the network is faster and recognition accuracy is higher. This kind of network combines or better fuses the advantages of backpropagation artificial neural algorithm and Hu moment. with advantages of two networks and improves the speed and accuracy of identification. Finally, a hardware-in-the-loop system for UAV target automatic recognition is also developed.

The double hidden level backpropagation artificial neural can easily increase the speed of recognition process and get a good performance for recognition accuracy.

The proposed backpropagation artificial neural algorithm can be ANN easily applied to practice and can help the design of the aircraft automatic target recognition system. The standard backpropagation algorithm has some obvious drawbacks, namely, converging slowly and falling into the local minimum point easily. In this paper, an improved algorithm based on the standard backpropagation algorithm is constructed to make the aircraft target recognition more practicable.

A double hidden levels backpropagation artificial neural algorithm is presented for automatic target recognition system of UAV.

The purpose of this paper is to present a neural network approach to control performance assessment.

The performance index under study is based on the minimum variance control benchmark, a radial basis function network (RBFN) is used as the pre‐whitening filter to estimate the white noise sequence, and a stable filtering and correlation analysis method is adopted to calculate the performance index by estimating innovations sequence using the RBFN pre‐whitening filter. The new approach is compared with the auto‐regressive moving average model and the Laguerre model methods, for both linear and nonlinear cases.

Simulation results show that the RBFN approach works satisfactorily for both linear and nonlinear examples. In particular, the proposed scheme shows merits in assessing controller performance for nonlinear systems and surpasses the Laguerre model method in parameter selection.

A RBFN approach is proposed for control performance assessment. This new approach, in comparison with some well‐known methods, provides satisfactory performance and potentials for both linear and nonlinear cases.

The purpose of this paper is to improve the generation efficiency of singlet oxygen of methylene blue molecules through finely controlling their aggregation states in drug carriers.

As a photosensitiser in photodynamic therapy, methylene blue (MB) was loaded on citrate-modified hydroxyapatite (HAp) through an electrostatic interaction and followed by encapsulation of coordination complexes of tannic acid (TA) and Fe(III) ions. Ultraviolet-visible absorption spectrum of the supernatant after incubation of samples was recorded at certain time interval to investigate the release behaviour of MB. Photodynamic activity of MB was determined by the oxidation reaction of uric acid by singlet oxygen generated by MB under illumination.

Almost all MB molecules were immediately released from HAp-MB, whilst an initial burst release of MB from HAp-MB@TA was followed by a sustainable and pH-sensitised release. In comparison with HAp-MB, photocatalystic reduction of HAp-MB@TA by titanium dioxide hardly occurred under illumination, indicating the stability against reduction to leukomethylene blue in vitro. Generation efficiency of singlet oxygen by MB released from HAp-MB@TA was significantly higher than that from HAp-MB because of the control of TA and Fe(III) ions complexes on molecular structures of released MB.

A facile method was herein demonstrated to optimise the generation efficiency of singlet oxygen by controlling aggregation states of PS molecules and improve PDT efficiency to damage tumour tissues.

Keeping satellite position within close tolerances is key for the utilization of satellite formations for space missions. The presence of perturbation forces makes control inevitable if such mission objective is to be realised. Various approaches have been used to obtain feedback controller parameters for satellites in a formation; this paper aims to approach the problem of estimating the optimal feedback parameter for a leader–follower pair of satellites in a small eccentric orbit using nature-based search algorithms.

The chaotic artificial bee colony algorithm is a variant of the basic artificial bee colony algorithm. The algorithm mimics the behaviour of bees in their search for food sources. This paper uses the algorithm in optimizing feedback controller parameters for a satellite formation control problem. The problem is formulated to optimize the controller parameters while minimizing a fuel- and state-dependent cost function. The dynamical model of the satellite is based on Gauss variational equations with J2 perturbation. Detailed implementation of the procedure is provided, and experimental results of using the algorithm are also presented to show feasibility of the method.

The experimental results indicate the feasibility of this approach, clearly showing the effective control of the transients that arise because of J2 perturbation.

This paper applied a swarm intelligence approach to the problem of estimating optimal feedback control parameter for a pair of satellites in a formation.

The idea of relating health, education and other social sector variables with growth and development, or trying to find any convergence among similar countries with respect to such macroeconomic indicators is the basic idea of this chapter, which explores the concept of enhancing welfare through a subjective route, specifically by way of expenditure in health care. By way of testing σ- and β-convergence of current healthcare expenditure per capita of the BRICS countries for the period 2006–2018, it has been found that these countries catch up with significant convergence. It has also been obtained through panel data analysis that such convergence is significantly explained by gross domestic product (GDP) per capita, life expectancy at birth, elderly ratio, CO₂ emissions and prevalence of undernourishment, all of which are in accordance with conventional hypotheses. This chapter claims that, by way of convergence, the BRICS nations may emerge as a new economic power, and expenditure on health care is one of the major areas, among other social sector variables that will play an important role.

The purpose of this paper is to examine a new idea of vibration control which minimizes joint‐torques and suppresses vibration of the flexible redundant manipulator.

Using the kinematics redundancy feature of the flexible redundant manipulator, the self‐motion in the joint space can be properly chosen to both suppress vibration and minimize joint‐torques.

The study shows that the flexible redundant manipulator still has the second optimization feature on the premise of vibration suppression. The second optimization feature can be used to minimize joint‐torques on the premise of vibration suppression.

To a flexible redundant manipulator, its joint‐torques and vibration can be reduced simultaneously via its kinematics redundancy feature.

The method and algorithm discussed in the paper can be used to minimize joint‐torques and suppress vibration for the flexible redundant manipulator.

The paper contributes to the study on improving dynamic performance of the flexible redundant manipulator via its kinematics redundancy feature. The second optimization capability of the flexible redundant manipulator is discovered and used to both minimize joint‐torques and suppress vibration.

The purpose of this paper is to propose a novel method to prepare pure Ti powder for 3D printing with tailorable particle size distribution.

The main procedures of the present method consist of gas state reaction to synthesize TiH₂ nanoparticles, agglomeration to obtain micronscale powder particles by spray drying, and densification of particle interior by heat treatment.

The prepared Ti powder has a specific bimodal particle size distribution in a range of small sizes, good sphericity and high flowability. Particularly, this new technique is capable of controlling powder purity and adjusting particle size.

To the best knowledge of the authors, the approach for preparing 3D printing metallic powders from nanoparticles has not been reported in the literature so far. This work provides a novel method that is particularly applicable to prepare 3D printing metallic powders which have small initial particle sizes and high reactivity in the air.