With the growing global demand for seafood, sustainable aquaculture is attracting more attention than conventional natural fishing, which causes overfishing and damage to the marine environment. However, a major problem facing the aquaculture industry is the cost of feeding, which accounts for about 60% of a fishing expenditure. Excessive feeding increases costs, and the accumulation of residual feed on the seabed negatively impacts the quality of water environments (e.g., causing red tides). Therefore, the importance of raising fishes efficiently with less food by optimizing the timing and quantity of feeding becomes more evident. Thus, we developed a system to quantitate the amount of fish activity for the optimal feeding time and feed quantity based on the images taken. For quantitation, optical flow that is a method for tracking individual objects was used. However, it is difficult to track individual fish and quantitate their activity in the presence of many fishes. Therefore, all fish in the filmed screen were considered as a single school and the amount of change in an entire screen was used as the amount of the school activity. We divided specifically the entire image into fixed regions and quantitated by vectorizing the amount of change in each region using optical flow. A vector represents the moving distance and direction. We used the numerical data of a histogram as the indicator for the amount of fish activity by dividing them into classes and recording the number of occurrences in each class. We verified the effectiveness of the indicator by quantitating the eating and not eating movements during feeding. We evaluated the performance of the quantified indicators by the support vector classification, which is a form of machine learning. We confirmed that the two activities can be correctly classified.

Recent studies investigating the Internet topology reported that inter Autonomous System (AS) topology exhibits a power-law degree distribution which is known as the scale-free property. Although there are many models to generate scale-free topologies, no game theoretic approaches have been proposed yet. In this paper, we propose the new dynamic game theoretic model for the AS level Internet topology formation. Through numerical simulations, we show our process tends to give emergence of the topologies which have the scale-free property especially in the case of large decay parameters and large random link costs. The significance of our study is summarized as following three topics. Firstly, we show that scale-free topologies can also emerge from the game theoretic model. Secondly, we propose the new dynamic process of the network formation game for modeling a process of AS topology formation, and show that our model is appropriate in the micro and macro senses. In the micro sense, our topology formation process is appropriate because this represents competitive and distributed situation observed in the real AS level Internet topology formation process. In the macro sense, some of statistical properties of emergent topologies from our process are similar to those of which also observed in the real AS level Internet topology. Finally, we demonstrate the numerical simulations of our process which is deterministic variation of dynamic process of network formation game with transfers. This is also the new result in the field of the game theory.

In order to operate an ambulance efficiently, we developed a Smart Ambulance Approach Alarm System using smartphone, by notifying the approach of an ambulance to other vehicles on public roads. The position information of ambulances has not been opened in view of development costs and privacy protection. Therefore, our study opens the position information inexpensively by loading commodity smartphones, not special devices, into ambulances. The position information is made to be open as minimum necessary information by our developed cloud server application, considering dynamic state of other vehicles on public roads and privacy of ambulance service users. We tested the functional efficiency of this system by the demonstration experiment on public roads.