Material selection is a fundamental step in mechanical design that has to meet all the functional requirements of the component. Multiple-attributed decision-making (MADM) processes are already well established to choose the preeminent alternative from the finite set of alternatives, but there is some lack of geometrical evidence if the alternatives are considered as multi-dimensional points. In this paper, a fresh spatial approach is proposed based on nearest neighbor search (NNS) in which the nearness parameter is considered as a Manhattan norm (Taxicab geometry) in turn which is a function of the Euclidean norm and cosine similarity to raise a preeminent alternative under the MADM framework. Cryogenic storage tank and flywheel are considered as two case studies to check the validity of the proposed spatial approach based on NNS in material selection. The result shows the right choice for the cryogenic storage tank is the austenitic steel (SS 301 FH), and for the flywheel, it is a composite material (Kevler 49-epoxy FRP) those are consistent with the real-world practice and the results are compared with other MADM methods of previous works.

This paper investigates how we infer the status of others from their social relationships. In a series of experimental studies, we test the effects of a social relationship's type and direction on the status judgments of others. We demonstrate empirically, possibly for the first time, a widely-assumed connection between network structure and perceptions of status; that is, that observers do infer the status positions of group members from their relationships. Moreover, we find that observers' status judgments vary with the direction and type of social relationship. We theorize that underlying this variance in status judgments are two relational schemas which differentially influence the processing of the observed social ties. Our finding that only the linear-ordering schema leads to status inferences provides an important scope condition to prior research on network cognition, and specifically on the perceptions of social status.

With origins in post-war development thinking, the core–periphery concept has spread across the social and, increasingly, the natural sciences. Initially reflecting divergent socioeconomic properties of geographical regions, its relational connotations rapidly led to more topological interpretations. In today's network science, the standard core–periphery model consists of a cohesive set of core actors and a peripheral set of internally disconnected actors. Exploring the classical core–periphery literature, this paper finds conceptual support for the characteristic intra-categorical density differential. However, this literature also lends support to the notions of peripheral dependency and core dominance, power-relational aspects that existing approaches do not capture. To capture such power-relations, this paper suggests extensions to the correlation-based core–periphery metric of Borgatti and Everett (2000). Capturing peripheral dependency and, optionally, core dominance, these extensions allow for either measuring the degree of such power-relational features in given core–periphery partitions, or as part of a criteria function to search for power-relational core–periphery structures. Applied to the binary and valued citation data in Borgatti and Everett (2000), the proposed extensions seemingly capture dependency and dominance features of core–periphery structures. This is particularly evident when, circling back to the original domains of the concept, examining the network of European commodity trade in 2010.

A Pneumatic Muscle Actuator (PMA) is a new pneumatic component sharing similar characteristics with biological muscles, and the flexible manipulator actuated by PMAs can better reflect the flexibility of the mechanism. First and foremost, based on the study of the characteristics of human shoulder joints, the configuration design of the flexible manipulator is analyzed, and its kinematics and dynamics models are established. Furthermore, with regard to the nonlinearity, time-invariance and uncertainty of the control system, three aspects of improvement are proposed, which are based on the Radial Basis Function (RBF) network torque control algorithm. The Genetic Algorithm is used to optimize the initial values of RBF network parameters; RBF network parameters are adjusted dynamically by using the additional momentum method; the Levenberg--Marquardt (LM) algorithm, instead of the gradient descent method, is adopted to adjust Proportion Integration Differentiation (PID) parameters online in real time. At last, to test the effects that the improved algorithm exerts on the flexible manipulator control system, some physical platform experiments are carried out. It turns out that the control accuracy and robustness of the improved algorithm are well improved, and the mechanism can be controlled better to track the circular arc trajectory. It lays fundamental importance to the practical application for the working environment.