A polynomial fuzzy neural network for modeling and control

This paper introduces a novel neurofuzzy system based on polynomial fuzzy neural network (PFNN) architecture. A PFNN consists of a set of if-then rules with appropriate membership functions (MFs) whose parameters are optimized via a hybrid genetic algorithm. A polynomial neural network is employed in the defuzzification scheme to improve output performance and to select appropriate rules. A performance criterion for model selection is defined to overcome the overfitting problem in the modeling procedure. For a performance assessment of the PFNN inference system, two well-known problems are employed for a comparison with other methods. The results of these comparisons show that the PFNN inference system out-performs the other methods and exhibits robustness characteristics. This work was presented in part at the Fourth International Symposium on Artificial Life and Robotics, Oita, Japan, January 19–22, 1999     

The role of self-construal in consumers’ electronic word of mouth (eWOM) in social networking sites: A social cognitive approach

The current study reconceptualized self-construal as a social cognitive indicator of self-observation that individuals employ for developing and maintaining social relationship with others. From the social cognitive perspective, this study investigated how consumers’ self-construal can affect consumers’ electronic word of mouth (eWOM) behavior through two cognitive factors (online community engagement self-efficacy and social outcome expectations) in the context of a social networking site. This study conducted an online experiment that directed 160 participants to visit a newly created online community. The results demonstrated that consumers’ relational view became salient when the consumers’ self-construal was primed to be interdependent rather than independent. Further, the results showed that such interdependent self-construal positively influenced consumers’ eWOM behavioral intentions through their community engagement self-efficacy and their social outcome expectations.     

A task‐based and resource‐aware approach to dynamically generate optimal software architecture for intelligent service robots

Intelligent service robots provide various services to users by understanding the context and goals of a user task. In order to provide more reliable services, intelligent service robots need to consider various factors, such as their surrounding environments, users' changing needs, and constrained resources. To handle these factors, most of the intelligent service robots are controlled by a task‐based control system, which generates a task plan that represents a sequence of actions, and executes those actions by invoking the corresponding functions. However, the traditional task‐based control systems lack the consideration of resource factors even though intelligent service robots have limited resources (limited computational power, memory space, and network bandwidth). Moreover, system‐specific concerns such as the relationships among functional modules are not considered during the task generation phase. Without considering both the resource conditions and interdependencies among software modules as a whole, it will be difficult to efficiently manage the functionalities that are essential to provide core services to users. In this paper, we propose a mechanism for intelligent service robots to efficiently use their resources on‐demand by separating system‐specific information from task generation. We have defined a sub‐architecture that corresponds to each action of a task plan, and provides a way of using the limited resources by minimizing redundant software components and maintaining essential components for the current action. To support the optimization of resource consumption, we have developed a two‐phase optimization process, which is composed of the topological and temporal optimization steps. We have conducted an experiment with these mechanisms for an infotainment robot, and simulated the optimization process. Results show that our approach contributed to increase the utilization rate by 20% of the robot resources. Copyright © 2011 John Wiley & Sons, Ltd.     

Numerical analysis of coronary artery bypass grafts: An over view

Arterial bypass grafts tend to fail after some years due to the development of intimal thickening (restenosis). Non-uniform hemodynamics following a bypass operation contributes to restenosis and bypass failure can occur due to the focal development of anastomotic intimal hyperplasia. Additionally, surgical injury aggravated by compliance mismatch between the graft and artery has been suggested as an initiating factor for progress of wall thickening along the suture line Vascular grafts that are small in diameter tend to occlude rapidly. Computational fluid dynamics (CFD) methods have been effectively used to simulate the physical and geometrical parameters characterizing the hemodynamics of various arteries and bypass configurations. The effects of such changes on the pressure and flow characteristics as well as the wall shear stress during a cardiac cycle can be simulated. Recently, utilization of fluid and structure interactions have been used to determine fluid flow parameters and structure forces including stress and strains relationships under steady and transient conditions. In parallel to this, experimental diagnostics techniques such as Laser Doppler Anemometry, Particle Image Velocimetry, Doppler Guide wire and Magnetic Resonance Imaging have been used to provide essential information and to validate the numerical results. Moreover, clinical imaging techniques such as magnetic resonance or computed tomography have assisted considerably in gaining a detailed patient-specific picture of the blood flow and structure dynamics. This paper gives a review of recent numerical investigations of various configurations of coronary artery bypass grafts (CABG). In addition, the paper ends with a summary of the findings and the future directions.     

Modeling and experimental investigation for electrolytic corrosion prevention in high frequency micro EDM using deionized water

The characteristics of the prevention of electrolytic corrosion during micro electrical discharge machining (EDM) using deionized water and high frequency bipolar pulse were investigated. Electrolytic corrosion during micro EDM using deionized water was analyzed using an equivalent electrical circuit based on the electrical double layer theory. Based on the analysis and experimental verification, a narrow positive pulse duration should be provided to the workpiece to prevent corrosion. A negative voltage with zero average applied voltage (V_{avg, app}) is also essential for this purpose. If V_{avg, app} is positive or negative, electrolytic corrosion occurs on the workpiece or tool, respectively. Micro holes and 3D structures without corrosion were successfully fabricated using a high frequency bipolar pulse with a pulse duration of 0.2?μs and a period of 1?μs, as well as V_{avg, app}?=?0?V.     

Testing digital safety system software with a testability measure based on a software fault tree

Using predeveloped software, a digital safety system is designed that meets the quality standards of a safety system. To demonstrate the quality, the design process and operating history of the product are reviewed along with configuration management practices. The application software of the safety system is developed in accordance with the planned life cycle. Testing, which is a major phase that takes a significant time in the overall life cycle, can be optimized if the testability of the software can be evaluated. The proposed testability measure of the software is based on the entropy of the importance of basic statements and the failure probability from a software fault tree. To calculate testability, a fault tree is used in the analysis of a source code. With a quantitative measure of testability, testing can be optimized. The proposed testability can also be used to demonstrate whether the test cases based on uniform partitions, such as branch coverage criteria, result in homogeneous partitions that is known to be more effective than random testing. In this paper, the testability measure is calculated for the modules of a nuclear power plant's safety software. The module testing with branch coverage criteria required fewer test cases if the module has higher testability. The result shows that the testability measure can be used to evaluate whether partitions have homogeneous characteristics.     

Scalable Model of On-Wafer Interconnects for High-Speed CMOS ICs

This paper describes the development of an equivalent circuit model of on-wafer interconnects for high-speed CMOS integrated circuits. By strategically cascading two-pi blocks together, the lumped model can characterize the distributed effects. Besides, the elaborately proposed model characterizes the frequency-variant characteristics with frequency-independent components. Thus, the model can be easily plugged into commercial computer-aided design tools. By adopting a newly invented optimization algorithm, namely, particle swarm optimization (PSO), the model parameters are extracted and formulated as empirical expressions. Therein, with each set of the geometrical parameters, the interconnect behaviors can be accurately predicted. The accuracy of the model is validated by comparisons with the on-wafer measurements up to 30 GHz. Moreover, the scalability of the proposed model is also discussed     

Effect of Hot Band Annealing on Magnetic Properties in 3% Si Grain‐oriented Electrical Steels

Hot band annealing is known to be a prerequisite for good magnetic properties irrespective of manufacturing methods in grain‐oriented Fe‐3 wt.% Si electrical steels. In this study, the effects of hot band annealing on magnetic properties were investigated in 3% grain‐oriented electrical steels of low soluble AI contents and one‐stage cold rolling. Microstructure and precipitate distribution were compared with hot band annealing conditions. Secondary recrystallization behaviour with hot band annealing condition was also discussed.     

Database summarization using fuzzy ISA hierarchies

Summary discovery is one of the major components of knowledge discovery in databases, which provides the user with comprehensive information for grasping the essence from a large amount of information in a database. We propose an interactive top down summary discovery process which utilizes fuzzy ISA hierarchies as domain knowledge. We define a generalized tuple as a representational form of a database summary including fuzzy concepts. By virtue of fuzzy ISA hierarchies where fuzzy ISA relationships common in actual domains are naturally expressed, the discovery process comes up with more accurate database summaries. We also present an informativeness measure for distinguishing generalized tuples that delivers much information to users, based on C. Shannon's (1948) information theory.