In an amusement park, an attraction-visiting route considering the waiting time and traveling time improves visitors' satisfaction and experience. We focus on Ising machines to solve the problem, which are recently expected to solve combinatorial optimization problems at high speed by mapping the problems to Ising models or quadratic unconstrained binary optimization (QUBO) models. We propose a mapping of the visiting-route recommendation problem in amusement parks to a QUBO model for solving it using Ising machines. By using an actual Ising machine, we could obtain feasible solutions one order of magnitude faster with almost the same accuracy as the simulated annealing method for the visiting-route recommendation problem.

Multi-Mouse Quiz (MMQ) is a quiz application based on the Single Display Groupware (SDG)[1] concept through which several users can answer quizzes by sharing a computer to take the quiz in a classroom or any other learning environment. We conducted a practice, where we used the MMQ to support collaborative learning, which was combined with a museum visit. In the previous research, we found that the 3rd-grade children were able to operate the MMQ without any special assistance from the researchers, and that their use of the MMQ was characterized by high engagement[2]. In this study, we also conducted qualitative evaluation in the form of observation data and a free description of the questionnaire; we found that, compared to previous studies, which used MMQ with 6th-grade children, the 3rd-grade were more willing to use body language to express their emotions, and this tendency made the whole class more active. Furthermore, MMQ quiz learning inspired children with reflection perspectives to participate in the museum activity and activities in the computer room.

This paper proposes an adaptive microphone array using blind deconvolution. The method realizes an signal enhancement based on the combination of blind deconvolution, synchronized summation and DSA (Delay-and-Sum Array) method. The proposed method improves performance of estimation by the iterative operation of blind deconvolution using a cost-function based on the coherency function.

Development of low power MUSE (Multiple Sub-Nyquist Sampling Encoding) chip set through reduction in operating voltage (from 5 V to 3.7 V) is described. This leads to great cost reduction since the chips could be mounted on low cost plastic packages and the necessity for cooling fans to dissipate heat was obviated. To maintain compatibility with standard 5 V analog and digital peripherals such as 4 Mbit DRAMs and an A/D converter, a special voltage-level converter was also developed.