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This paper presents a model to design, describe and analyze the human machine system of systems (SoS) for decision makings involving predictions, particularly about future. The hypernetwork model is used, which is suitable to describe and analyze systems consisting of humans and machines, because the model allows simultaneous representations of multiple viewpoints, dynamic hierarchical structure and variable boundaries.

This paper proposes a model to design, describe and analyze the human machine system, treating it as a system of systems (SoS). The hypernetwork model is suitable to describe and analyze systems consisting of humans and machines, because the model allows simultaneous representations of multiple viewpoints, dynamic hierarchical structure and variable boundaries.

We propose a mechanism to alleviate the aggression on Computer Mediated Communications. A title that supposedly reflects the aggressivity of comments posted by the user is displayed on screen. The effects of the proposed mechanism are verified with laboratory experiment, where participants post comments after reading the topics of discussion and other participants' comments. The results indicate that users choose less aggressive comments, besides that the time duration to select comments becomes shorter.

Cu wires patterning by direct etch methods is investigated at 300mm wafer level. Cross-sectional sidewall profiles with tapering angles around 74.5° are obtained with a mid-line width of 44 nm, which paves the way to further scaling of this technique. Lower resistivity is demonstrated with respect to conventional Cu damascene process, with low leakage current between adjacent Cu lines. An in-situ 10nm SiN cap is deposited as a passivation to enable electrical and reliability tests. The electromigration (EM) characterization shows promising reliability performance of the direct etched Cu wires.

The feeding mechanism of Mammalians other than Homo sapiens is relatively well understood at the molecular level. However, the feeding mechanism of Homo sapiens involves independent control mechanisms that are difficult to be described using conventional models. Furthermore, with the advance of high throughput experiment techniques, an important but unsolved problem is to integrate data of different substance classes. This paper presents a model to describe these phenomena.

In this paper, we present an adaptive observer for nonlinear systems using a genetic algorithm (GA). It is considered that the GA has a superior performance for solution searching of multivariable systems. We utilize the GA searching ability to determine unobtainable variables in the control system. We extended the role of the GA observer to that of a parameter estimator for unknown systems and constructed an adaptive GA observer. The adaptive GA observer has a searching ability to estimate unobtainable variables and parameters simultaneously. In this paper, we use the estimated values of the system variables and parameters to design a neurocontroller (NC) using a GA. We applied the adaptive GA observer and NC design method to the backward movement control of a trailer truck. A simulation shows the effectiveness of the proposed method.

Analyzes the concept of the robustness and changeability related to the ability of evolutionary systems to follow environmental variations. We employ a genetic code for the analysis, because the robustness and changeability are defined quantitatively as the intrinsic properties of the structure of genetic codes. Specifically, we study the relationship between the variability of the fitness landscape and the robustness and changeability of genetic codes. A genetic algorithm was applied to obtain genetic codes suitable for a given variability of fitness landscapes, where a multimodal function defines a dynamic fitness landscape, varying constantly the number and the height of peaks. For higher variable fitness landscapes, genetic codes with lower robustness are obtained. The dynamic control of the robustness and changeability of genetic codes is also discussed.