Specification and validation of dynamic systems using temporal logic
A specification and validation technique for dynamic systems is proposed. In particular, a new temporal logic called HDTL, is presented and the tableau method revised for automatic analysis. Using a freeze quantifier, HDTL with the revised tableau method makes it possible to specify the correctness requirements of dynamic systems and validate them. The proposed logic is rather generic, i.e. it has only a few assumptions on operational language. The authors introduce a simple dynamic modelling language and illustrate its experiment. The experiment shows that HDTL is suitable for specifying dynamic properties and the analysis technique is promising.

title: Co-Validation Environment for Memory Card.

title: Extending the SCR Method for Real-Time Systems
abstract: Wepropose timed SCR specifications, which are a generalizationof SCR specifications, intended to specify quantitative timingproperties of real-time systems. We extend the tabular notationof the SCR method to deal with sporadic and periodic timing constraints.We present a formal semantics for timed SCR specifications bytranslating them into timed transition systems. A shutdown systemin Korean nuclear power plants is used as a case study to illustratetimed SCR specifications.

title: Evolutionary Learning of Modular Neural Networks with Genetic Programming
abstract: Evolutionary design of neural networks has shown a great potential as a powerful optimization tool. However, most evolutionary neural networks have not taken advantage of the fact that they can evolve from modules. This paper presents a hybrid method of modular neural networks and genetic programming as a promising model for evolutionary learning. This paper describes the concepts and methodologies for the evolvable model of modular neural networks, which might not only develop new functionality spontaneously, but also grow and evolve its own structure autonomously. We show the potential of the method by applying an evolved modular network to a visual categorization task with handwritten digits. Sophisticated network architectures as well as functional subsystems emerge from an initial set of randomly-connected networks. Moreover, the evolved neural network has reproduced some of the characteristics of natural visual system, such as the organization of coarse and fine processing of stimuli in separate pathways.

title: A Data-Driven Statistical Approach to Analyzing Process Variation in 65nm SOI Technology
abstract: This paper presents a simple yet effective method to analyze process variations using statistics on manufacturing in-line data without assuming any explicit underlying model for process variations. Our method is based on a variant of principal component analysis and is able to reveal systematic variation patterns existing on a die-to-die and wafer-to-wafer level individually. The separation of die variation from wafer variation can enhance the understanding of a nature of the process uncertainty. Our case study based on the proposed decomposition method shows that the dominating die-to-die variation and wafer-to-wafer variation represent 31% and 25% of the total variance of a large set of in-line parameters in 65nm SOI CMOS technology

title: Modular neural networks evolved by genetic programming
abstract: We present an evolvable model of modular neural networks which are rich in autonomy and creativity. In order to build an artificial neural network which is rich in autonomy and creativity, we have adopted the ideas and methodologies of artificial life. The paper describes the concepts and methodologies for the evolvable model of modular neural networks, which will be able not only to develop new functionality spontaneously but also to grow and evolve its own structure autonomously. Although the ultimate goal of this model is to design the control system for such behavior based robots as Khepera, we have attempted to apply the mechanism to a visual categorization task with handwritten digits. The evolutionary mechanism has shown a strong possibility to generate useful network architectures from an initial set of randomly connected networks.

title: TCP Performance Improvement with ACK Pacing in Wireless Data Networks
abstract: Wireless data services are fundamental in ubiquitous networks. In wireless data networks, the TCP congestion mechanism can mistake a wireless channel error or blackout for congestion on the route. Several wireless TCP protocols have been proposed considering TCP performance degradation in wireless systems. However, these protocols are too complex to deploy in wireless systems. In this paper, we propose the ACK Pacing algorithm for long lasting loss periods like a hand-off or a blackout. By pacing ACK packets sending, we prevent bursty data delivery to the old path and a spurious timeout occurrence. Also, paced ACK packets trigger the route update to the new path faster. The proposed algorithm can be implemented in the wireless-node-side which is easily applicable to wireless systems. From simulation results, ACK Pacing improves TCP performance compared with many TCP variations. The ACK Pacing algorithm shows good performance during a long lasting loss period.

title: Aggregated Aggressiveness Control on Groups of TCP Flows
abstract: The use of multiple concurrent parallel TCP flows is an easy way to achieve higher speed reliable data transfers. However, parallel TCP flows are inherently unfair with respect to single TCP flows. We suggest a new scheme called TCP-P, which controls aggressiveness of a group of parallel TCP flows by regulating their total aggressiveness (or unfairness) to be comparable to a single TCP flow, or any multiple thereof. TCP-P makes a group of N parallel TCP flows appear to other flows like k separable TCP flows – i.e., have strength k – through appropriate manipulations of increase and decrease behavior of the congestion windows of the TCP flows in the group. We implemented our scheme as part of Linux and experimental results show that the proposed scheme effectively controls aggressiveness of parallel TCP flows.