We thank Kamata et al. (2023) [1] for their interest in our work [2], and for providing an explanation of the quasi-linear kernel from a viewpoint of multiple kernel learning. In this letter, we first give a summary of the quasi-linear SVM. Then we provide a discussion on the novelty of quasi-linear kernels against multiple kernel learning. Finally, we explain the contributions of our work [2].

In this letter, we establish a model of a digital clock synchronization method for power packet dispatching. The first-order control is carried out to a specified model to achieve the clock synchronization. From the experimental results, it is confirmed that power packets were recognized under autonomous synchronization.

The market growths of smart-phones and thin clients have been significantly increasing communication traffic in mobile networks. To handle the increased traffic, network operators should consider how to leverage distributed wireless resources such as distributed spots of wireless local access networks. In this paper, we consider the system where multiple moving users share distributed wireless access points on their traveling routes between their start and goal points and formulate as an optimization problem. Then, we come up with three algorithms as a solution for the problem. The key idea here is 'longcut route instruction', in which users are instructed to choose a traveling route where less congested access points are available; even if the moving distance increases, the throughput for users in the system would improve. In this paper, we define the gain function. Moreover, we analyze the basic characteristics of the system using as a simple model as possible.

Conventional system models such as the finite impulse response (FIR) model, autoregressive external input (ARX) model, time delay neural network (TDNN), and recurrent neural network (RNN) depend on short-term memory when modeling a discrete time system. However, short-term memory can be inefficient with a varying appearance speed of I/O data. This inefficiency is referred to herein as the Varying Appearance Speed Problem (VASP) and demonstrated by analyzing impulse and frequency responses. Simulation results indicate that the varying appearance speed leads to asymmetrical cycles. Unable to prevent the memory effect from extensively disturbing the next output cycle, conventional models simulate the systems inaccurately. A solution using rate independent memory is then proposed. Only concerned with the previous extreme inputs, rate independent memory differs from short-term memory and potentially prevents a system model from the impact of varying appearance speeds. To demonstrate the VASP and verify the proposed model, this study conducts three experiments, i.e. (a) learning random step trajectories of circular and trefoil shapes, (b) modeling the relationship between the economic leading and coincident indexes, (c) simulating the connection between the ground-water level and land subsidence. In contrast to conventional models, the model presented here performs better in terms of mean square errors.

A new approach for generating a system model from its input-output data is presented. The model is approximated as a linear combination of simple basis functions. The number of basis functions is kept as small as possible to prevent over-fitting and to make the model efficiently computable. Based on these conditions, genetic programming is employed for the generation and selection of the appropriate basis. Since the obtained model can be expressed in simple mathematical expressions, it is suitable for using the model as a macro or behavior model in system level simulation. Experimental results are shown.

This paper focuses on methodology underlying the application to fault tolerant computer systems with "no down communication" capability of stochastic Petri nets with general firing times. Based on a formal specification of the stochastic Petri net, we provide criteria for the marking process to be a regenerative process in continuous time with finite cycle-length moments. These results lead to strongly consistent point estimates and asymptotic confidence intervals for limiting system availability indices. We also show how the building blocks of stochastic Petri nets with general firing times facilitate the modeling of non-deterministic transition firing and illustrate the use of "interrupter input places" for graphical representation of transition interruptions.

The pursuit of higher availability has resulted in the development of fault tolerant systems for many industries. However, system characteristics that can be perceived by the customer have never been diagnosed quantitatively. This paper considers the application of stochastic Petri nets with general firing times to modeling of a fault tolerant system and the use of discrete-event simulation methods for stochastic Petri nets to study the behavior of the system. The stochastic Petri net model incorporates factors that compose the system as well as those that accompany it, including RAS characteristics of products, personnel arrangements, and system management. By modeling the behavioral aspect of each factor, it is possible to diagnose a fault tolerant system quantitatively on the basis of customer impact.