The recalibrational theory: Anger as a bargaining emotion

This chapter uses the adaptationist program (Williams, 1966) - to predict and explain the major features of anger. According to this approach, anger evolved by natural selection to bargain for better treatment. Thus, the major triggers of anger (e.g. cost impositions, cues of disrespect) all indicate an increased willingness (on the part of the offender) to impose costs on the angry individual. Once triggered, the anger system bargains using the two primary incentives that humans have available to modify others’ behavior in favor of the focal individual: the imposition of costs and the denial of benefits. This simple functional sketch of anger is then supplemented with additional considerations needed to address the resultant selection pressures created by bargaining. This process offers functionally sound and theoretically justified explanations for: anger in aggressive and cooperative contexts, the role of apologies and their sincerity, the content of sex-specific insults, the computational structure of “intentionality” in the context of anger, and the origin of the implicit rules of combat.

A highly efficient approach for bi-level programming problems based on dominance determination

Bi-level programming, where one objective is nested within the other, is widely used in engineering design, e.g., structural optimization and electronic system design. One major issue of current solvers for these bi-level problems is their low computational efficiency, especially for complex nonlinear problems. To solve this issue, a new method based on bi-level grey wolf optimizer is proposed in this paper. The basic idea is to drop the time-consuming nested computational structure commonly used by existing methods and instead use a simultaneous computational structure built on top of a dominance determination process for the grey wolf optimizer. The effectiveness of this new method has been validated with ten benchmark functions and two engineering design examples, as well as comparisons with three important existing methods in the bi-level programming domain.

Fluid-Structure Interaction Simulations of Parachute Deployment and Inflation

The numerical simulation of the parachute deployment/inflation process involves fluid structure interaction problems, the inherent complexities in the fluid structure interaction have been posing several computational challenges. In this paper a high fidelity Eulerian computational approach is proposed for the simulation of parachute deployment/inflation. Unlike the arbitrary Eulerian Lagrangian (ALE) method widely employed in this area, the Eulerian computational approach is established on three computational techniques: computational fluid dynamics, computational structure dynamics and computational moving boundary. A set of stationary, non-deforming Cartesian grids is adopted in our computational fluid dynamics, our computational structure dynamics is enhanced by non-linear finite element method and membrane wrinkling algorithm, instead of conventional computational mesh dynamics, an immersed boundary method is employed to avoid insurmountable poor grid quality brought in by moving mesh approaches. To validate the proposed numerical approach the deployment/inflation of C-9 parachute is simulated using our approach and the results show similar characteristics compared with experimental results and previous literature. The computed results have demonstrated the proposed method to be a useful tool for analyzing dynamic parachute deployment and subsequent inflation.

Formation of Hybrid Computational Structure for the Analysis of Critical Control Scenarios in Biocybernetics

We have considered methods of computational modeling of rapid processes in ecosystems and events of changes with extreme amplitude of abundance. For biocybernetics, the phenomena of degradation of the commercial population in the form of a sudden collapse for specialists and an explosive increase in the number of a new species after invasion — outbreaks are of the type predicted with difficulties. We have developed and ecologically substantiated a method for modeling a group of rapid phenomena, including the calculation of threshold states and transient modes. Algorithmically implemented computational structure, which describes spontaneous modes of rapid transformations in ecodynamics based on the internal properties of biosystems. New model is based on the formalization of threshold effects in regulation of reproduction, included as additional functionals in the basic hybrid structure for research in scenario experiments. Computational scenario is obtained for a generalized description of the extreme population process. We have considered the situation of the collapse of the commercial population with a quota-regulated harvest on the example of the king crab Paralithodes camtschaticus near the coast of Alaska. In the simulation scenario of the crab collapse, we took into account the logic of expert management of the level of exploitation of biological resources. The resulting control scenarios using the iterative model use bifurcations and the loss of the invariance property by the attractor. Modeling with the expert logic of fishery management revealed the characteristic signs of the dynamics of crab collapse and predicted important stages in the process of degradation of exploited biological resources.

THE PARALLEL-PIPELINED IMPLEMENTATION OF THE FRACTAL IMAGE COMPRESSION FOR RECONFIGURABLE COMPUTING SYSTEMS

The developed fractal image compression method, implemented for reconfigurable computing systems is described. The main idea parallel fractal image compression based on parallel execution pairwise comparison of domain and rank blocks. Achievement high performance occurs at the expense of simultaneously comparing maximum number of pairs. Implementation fractal image compression for reconfigurable computing systems has two critical resources, as number of input channels and FPGA Look-up Table (LUT). The main critical resource for fractal image compression is data channels, and implementation this task for reconfigurable computing systems requires parallel-pipeline computations organization replace parallel, preliminarily produced performance reduction parallel computational structure. The main critical resource for fractal image compression is data channels, and implementation this task for reconfigurable computing systems requires parallel-pipeline computations organization replace parallel computations organiation. For using parallel-pipeline computations organization, preliminarily have produce performance reduction parallel computational structure. Each operator has routed to computational structure sequentially (bit by bit) to save computational resources and reduces equipment downtime. Storing iterated functions system coefficients for image encoding has been introduced in data structure, which correlates between corresponding parameters the numbers of rank and domain blocks. Applying this approach for parallel-pipeline programs allows scaling computing structure to plurality programmable logic arrays (FPGAs). Task implementation on the reconfigurable computer system Tertius-2 containing eight FPGAs 15 000 times provides performed acceleration relatively with universal multi-core processor, and 18 – 25 times whit to existing solutions for FPGAs.