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The purpose of this paper is to justify the algorithm optimization based on a consideration of its accuracy characteristics in a pure coning motion, which is widely used in optimizing strapdown attitude algorithms to describe the special angular motion of a vehicle.

Two more general angular motions of a vehicle were given: generalized vibration describing periodical motions and benign dynamic describing aperiodical motions. The algorithm performances were evaluated in these two motions.

The theoretical analysis and numerical results show that errors of the algorithm optimized in pure coning motion are null or neglectable in these two motions, and performance of the optimized algorithm in a pure coning motion is superior to that of the non-optimized algorithm.

The value of the paper lies in that the authors justify the concept optimizing strapdown attitude algorithms in a pure coning motion.

The aim of this paper is to propose a new coning correction algorithm, based on the singular perturbation technique, for the attitude update computation with non‐ideal angular rate information.

Unlike conventional coning correction algorithms, the new method uses angular rate two‐time scale model to construct the coning correction term of attitude update. In order to achieve balanced real/pseudo coning correction performance, the selection guidelines of the new algorithm parameters are established.

Performance of the new algorithm is evaluated by comparison with the conventional algorithm in no ideal sensors undergoing stochastic coning environments. The accuracy of attitude update can be improved effectively with reduced computational workload by using this new coning algorithm as compared with conventional ones.

The proposed coning correction algorithm can be implemented with angular rate sensors in UAV (unmanned aerial vehicle) and other aircrafts attitude estimation for navigation and control applications.

Singular perturbation is an effective method for structuring coning correction algorithm with filtered angular rate outputs in stochastic coning environments. The improved coning correction algorithm based on singular perturbations reduces the real and pseudo coning effects effectively as compared with conventional ones. It is proved to be valid for improvement of accuracy with reduced computations of the attitude update.

The purpose of this paper is to investigate the performance of cultural algorithms (CAs) over a complete range of optimization problem complexities, from fixed to chaotic and specifically observing whether there is a given homogeneous agent topology within a culture which can dominate across all complexities.

In order to apply the CA overall complexity classes it was necessary to generalize on its co‐evolutionary nature to keep the variation in the population across all complexities. First, previous CA approaches were reviewed. Based on this the existing implementation was extended to produce a more general one that could be applied across all complexity classes. As a result a new version of the cultural algorithms toolkit, CAT 2.0, was produced, which supported a variety of co‐evolutionary features at both the knowledge and population levels. The system was applied to the solution of a 150 randomly generated problems ranging from simple to chaotic complexity classes.

No homogeneous social fabric tested was dominant over all categories of problem complexity; as the complexity of problems increased so did the complexity of the social fabric that was need to deal with it efficiently. A social fabric that was good for fixed problems might be less adequate for periodic problems, and chaotic ones.

The paper presents experimental evidence that social structure of a cultural system can be related to the frequency and complexity type of the problems that presented to a cultural system.

The purpose of this paper is to design a solar sail heliocentric transfer orbit which can meet the requirements of control system and capture orbit, and to provide the change of angles for attitude control system.

Aiming at the problem of solar sail heliocentric transfer orbits design, this paper addresses the derivation of analytical optimal control law. The control laws can realize the combination of the control of each orbit element, but they can only give local optimal solution to meet the practical needs of mission. In order to solve this problem and meet the capture orbit and the attitude control system requirements, the modified genetic algorithm based on the analytical control law is introduced.

The algorithm addressed by this paper includes results closer to the global optimization, and also can meet the engineering constraints.

The analytical optimal control law can be applied to the future onboard sail control systems. The blending optimal algorithm is demonstrated to be suitable as a method of preliminary design for solar sail deep space exploration mission.

A blending optimal algorithm combining the analytical control law and genetic algorithm is proposed; the algorithm can search for global optimization based on the local optimal results of analytical control law.

The purpose of this paper is to explore the possibility of combining additive manufacturing (AM) with topology optimization to generate support structures for addressing the challenging overhang problem. The overhang problem is considered as a constraint, and a novel algorithm based on continuum topology optimization is proposed.

A mathematical model is formulated, and the overhang constraint is embedded implicitly through a Heaviside function projection. The algorithm is based on the Solid Isotropic Material Penalization (SIMP) method, and the optimization problem is solved through sensitivity analysis.

The overhang problem of the support structures is fixed. The optimal topology of the support structures is developed from a mechanical perspective and remains stable as the material volume of support structures changes, which allows engineers to adjust the material volume to save cost and printing time and meanwhile ensure sufficient stiffness of the support structures. Three types of load conditions for practical application are considered. By discussing the uniform distributive load condition, a compromise result is achieved. By discussing the point load condition, the removal work of support structures after printing is alleviated. By discussing the most unfavorable load condition, the worst collapse situation of the printing model during printing process is sufficiently considered. Numerical examples show feasibility and effectiveness of the algorithm.

The proposed algorithm involves time-consuming finite element analysis and iterative solution, which increase the computation burden. Only the overhang constraint and the minimum compliance problem are discussed, while other constraints and objective functions may be of interest.

Compared with most of the existing heuristic or geometry-based support-generating algorithms, the proposed algorithm develops support structures for AM from a mechanical perspective, which is necessary for support structures particularly used in AM for mega-scale construction such as architectures and sculptures to ensure printing success and accuracy of the printed model.

With the rapid development of AM, complicated structures result from topology optimization are available for fabrication. The present paper demonstrates a combination of AM and topology optimization, which is the trend of fabricating manner in the future.

This paper remarks the first of attempts to use continuum topology optimization method to generate support structures for AM. The methodology used in this work is theoretically meaningful and conclusions drawn in this paper can be of important instruction value and practical significance.

Additive manufactured (AM) skull models are increasingly used to plan complex surgical cases and design custom implants. The accuracy of such constructs depends on the standard tessellation language (STL) model, which is commonly obtained from computed tomography (CT) data. The aims of this study were to assess the image quality and the accuracy of STL models acquired using different CT scanners and acquisition parameters.

Images of three dry human skulls were acquired using two multi-detector row computed tomography (MDCT) scanners, a dual energy computed tomography (DECT) scanner and one cone beam computed tomography (CBCT) scanner. Different scanning protocols were used on each scanner. All images were ranked according to their image quality and converted into STL models. The STL models were compared to gold standard models.

Image quality differed between the MDCT, DECT and CBCT scanners. Images acquired using low-dose MDCT protocols were preferred over images acquired using routine protocols. All CT-based STL models demonstrated non-uniform geometrical deviations of up to +0.9 mm. The largest deviations were observed in CBCT-derived STL models.

While patient-specific AM constructs can be fabricated with great accuracy using AM technologies, their design is more challenging because it is dictated by the correctness of the STL model. Inaccurate STL models can lead to ill-fitting implants that can cause complications after surgery.

This paper suggests that CT imaging technologies and their acquisition parameters affect the accuracy of medical AM constructs.

The purpose of this paper is to conduct a review of types of tomographic systems that have been widely researched within the past 10 years. Decades of research on non-invasively and non-intrusively visualizing and monitoring gas-liquid multi-phase flow in process plants in making sure that the industrial system has high quality control. Process tomography is a developing measurement technology for industrial flow visualization.

A review of types of tomographic systems that have been widely researched especially in the application of gas-liquid flow within the past 10 years was conducted. The sensor system operating fundamentals and assessment of each tomography technology are discussed and explained in detail.

Potential future research on gas-liquid flow in a conducting vessel using ultrasonic tomography sensor system is addressed.

The authors would like to undertake that the above-mentioned manuscript is original, has not been published elsewhere, accepted for publication elsewhere or under editorial review for publication elsewhere and that my Institute’s Universiti Teknologi Malaysia representative is fully aware of this submission.

The purpose of this paper is to extend a methodology for solving multi‐objective linear programming (MOLP) problems, when the objective functions and constraints coefficients are stated as interval numbers.

The approach proposed in this paper for the considered problem is based on the maximization of the sum of membership degrees which are defined for each objective of multi objective problem. These membership degrees are constructed based on the deviation from optimal solutions of individual objectives. Then, the final model based on membership degrees is itself an interval linear programming which can be solved by current methods.

The efficiency of the solutions obtained by the proposed method is proved. It is shown that the obtained solution by the proposed method for an interval multi objective problem is Pareto optimal.

The proposed method can be used in modeling and analyzing of uncertain systems which are modeled in the context of multi objective problems and in which required information is ill defined.

The paper proposed a novel and well‐defined algorithm to solve the considered problem.

The issues of radiating sources in the existence of smooth convex matters by such objects are of huge significance in the modeling of antennas on structures. Conformal antenna arrays are necessary when an antenna has to match to certain platforms. A fundamental problem in the design is that the possible surfaces for a conformal antenna are infinite in number. Furthermore, if there is no symmetry, each element will see a different environment, and this complicates the mathematics. As a consequence, the element factor cannot be factored out from the array factor.

This paper intends to enhance the design of the conformal antenna. Here, the main objective of this task is to maximize the antenna gain and directivity from the first-side lobe and other side-lobes in the two way radiation pattern. Thus the adopted model is designed as a multiobjective concern. In order to attain this multiobjective function, both the element spacing and the radius of each antenna element should be optimized based on the probability of the Crow Search Algorithm (CSA). Thus the proposed method is named Probability Improved CSA (PI-CSA). Here, the First Null Beam Width (FNBW) and Side-Lobe Level (SLL) are minimized. Moreover, the adopted scheme is compared with conventional algorithms, and the results are attained.

From the analysis, the gain of the presented PI-CSA scheme in terms of best performance was 52.68% superior to ABC, 25.11% superior to PSO, 13.38% superior to FF and 3.21% superior to CS algorithms. Moreover, the mean performance of the adopted model was 62.94% better than ABC, 13.06% better than PSO, 24.34% better than FF and 10.05% better than CS algorithms. By maximizing the gain and directivity, FNBW and SLL were decreased. Thus, the optimal design of the conformal antenna has been attained by the proposed PI-CSA algorithm in an effective way.

This paper presents a technique for enhancing the design of the conformal antenna using the PI-CSA algorithm. This is the first work that utilizes PI-CSA-based optimization for improving the design of the conformal antenna.

To paint large workpieces automatically, painting manipulators with hollow wrists must be transported by mobile platforms to different positions because of their limited workspaces. This paper aims to provide a visualization method for finding appropriate base positions (BPs) and maximum painting areas for manipulators.

This paper begins by analyzing the motion characteristics of manipulators possessing a spherical wrist and summarizing them into three constraints – positioning, orientation and singularity avoidance. The hollow wrist is simplified and considered as spherical by introducing the concepts of an inner wrist center and an outer wrist center. Taking the three constraints into consideration, the boundaries of the manipulating space are formulated analytically. Finally, to verify the method, the space obtained is applied to determine the maximum painting areas for flat, cylindrical and conical surfaces. Experiments of robotic painting were used to confirm the results.

Compared with previous studies, the maximum areas obtained using the proposed method increased by 17-131 per cent with an algorithm of lower complexity, and the process remained visually intuitive, thereby demonstrating that the method of manipulating space is more effective.

Such a method allows individuals to visualize the entire painting area at the current BP, thereby maximizing painting areas or optimizing BPs. It opens a black box that is the relationship between BPs and blocks. The method can also be used to choose the best configuration for painting manipulators, select the end-effector structure parameters, split surfaces into blocks, etc.