Summary In this article, a new quantum social spider optimization (QSSO) algorithm is proposed. In the QSSO algorithm, we introduce an encoding approach based on bits described on social spider optimization (SSO) and serves as the evolution method of the population space. For the encoding of individuals, the probability amplitude expression of quantum bit is applied to describe the position of individuals, by which one individual's position can be expressed as the superposition of multistates. In such a way, the population diversity and the global searching capability of the SSO algorithm are enhanced. The QSSO algorithm was used to optimize the hydropower station dispatch, and the calculation results show that QSSO algorithm has fast convergence, small number of tuning parameters, high calculation accuracy, stability, simple, and is easy to be implemented with strong global search capability.

Abstract Salp swarm algorithm (SSA) is one of the efficient recent meta‐heuristic optimization algorithms, where it has been successfully utilized in a wide range of optimization problems in different fields. In the research process, it is found that it is very difficult to maintain the balance between the exploration and exploitation capabilities of a certain algorithm. Therefore, one of the main purposes of this article is to provide an algorithm that can intelligently balance between exploration and exploitation, so that it can balance exploration and exploitation capabilities. Later, in the research process, it was found that the sine and cosine function and the salp foraging trajectory have a high mathematical similarity, which greatly improves the optimization ability of the algorithm. In addition, the variable neighbourhood strategy can appropriately expand the optimization range of the algorithm. So in this paper, a novel golden sine cosine salp swarm algorithm with variable neighbourhood search scheme (GSCSSA‐VNS) is proposed, the another objective of proposing this algorithm is as a new optimization method for shape matching. As a relatively new branch, atomic potential matching (APM) model is inspired by potential field attractions. Compared to the conventional edge potential function (EPF) model, APM has been verified to be less sensitive to intricate backgrounds in the test image and far more cost effective in the computation process. Experimental results of four realistic examples show that GSCSSA‐VNS is able to provide very competitive results and outperforms the other algorithms.

Jumping with controllable elevation is significant for insect-scale robots to improve terrain adaptability and to escape from risks. However, jumping robots based on soft materials with low stiffness cannot transmit displacement precisely, exhibiting poor control of jumping. Here, we propose a modified two-bars catapult mechanism combined with an asynchronous sequential releasing strategy to realize elevation controllable jumping. In this work, an 80 mg prototype robot, 56 (long) × 29 mm (wide) × 3 mm (high) mm in size, is designed with the controllable elevation range from 63° to 112°. The soft robot is mainly composed of a shape memory alloy actuator and four electrostatic pads acting as the lock/release structures. Elevation control is realized by asynchronously releasing the electrostatic pads in a small time interval (about 10 ms). A maximum jump height of 62 mm and a maximum half-distance of 41 mm are also achieved.

In real-time rendering transparency is an important multi-fragment effect to visualize the structure of three-dimensional models. The per-pixel transmittance implicitly describes how the light is attenuated by traveling through several transparent fragments. We present a hybrid approach to fit the transmittance using the Heaviside step function and the trigonometric function. The k fragments with the largest contribution are exactly composited and the remaining ones are accurately compressed in an unified formulation. With a single geometry pass, fragments are sorted into a fixed-size array and overflowing ones are expanded by a truncated Fourier series. Then the transmittance is reconstructed on the fly to modulate the surface color in another geometry pass. Our approach favors high scene complexity but operates in bounded memory without losing noticeable high-frequency detail. We demonstrate that it is able to closely match the image quality at competitive frame rate, comparing to a realtime A-buffer implementation and other approximate transparency techniques.