A new paradigm of mechanism design, called mechanism design over social networks, investigates agents’ incentives to diffuse the information of mechanisms to their followers over social networks. In this paper we consider it for two-sided matching, where the agents on one side, say students, are distributed over social networks and thus are not fully observable to the mechanism designer, while the agents on the other side, say colleges, are known a priori. The main purpose of this paper is to clarify the existence of mechanisms that satisfy several properties that are classified into four criteria: incentive constraints, efficiency constraints, stability constraints, and fairness constraints. We proposed three mechanisms and showed that no mechanism is better than these mechanisms, i.e., they are in the Pareto frontier according to the set of properties defined in this paper.

Underwater object detection and tracking are of considerable interest in offshore defense. Recently, a new method that takes advantage of direct-current resistivity survey techniques has been introduced as a complement to the conventional detection method for use in acoustically noisy conditions. However, dedicated rapid target localization methods are required to enable real-time tracking in this detection method. Therefore, in this paper, we propose a real-time localization method using grid-based template matching. The main features of our method are as follows: 1) measurement data sets from two separate detection lines are used; 2) template matching based on correlation is used; 3) the templates are precalculated by numerical modeling; and 4) real-time localization processing is implemented by efficient calculations. To verify our method, we first performed experiments for stationary target object positions under a water tank condition: template versus numerical modeling data and template versus physical modeling data. Next, real-time localization experiments for a moving target in the water tank were conducted using the real-time data at 3-Hz refresh rate. In the real-time experiments, we confirmed that the estimated positions could keep track of the actual target positions continuously. We expect that this paper will contribute positively to offshore defense and surveillance.

A new real-time underwater object detection method adopting geophysical direct-current resistivity techniques is proposed. Our final goals are real-time detection and tracking of small submarines in water depths less than 100 m, under acoustically noisy conditions. The main features of our method are as follows: a detection line, several kilometers long and semipermanently buried in the seabed, consisting of two current electrodes and multiple potential electrodes; fixed current electrode configurations for high-speed real-time detection of the target object; measurement of extremely low-level electric field signals, made possible by the shielding effect of the conductive seawater overburden; and signals from a moving object such as a submarine are extracted by differential data analysis because the target object passes through the detection area for only a short time compared with the long-term drift change of the electrical properties of seawater. We verify our method and confirm real-time detection feasibility through numerical and physical scale experiments. For this purpose, a dedicated instrument and a background data update algorithm are developed, and a differential data analysis method is used. The background data update algorithm is used for counteracting the time-varying electrical characteristics of seawater. The differential data analysis method is exploited to extract disturbed signals by objects from complex background data. Through numerical experiments, we find that the x-coordinate value of a target object corresponds to the position of a peak data point, and this result is consistent with 1:200 downscaled water tank experiments. We also confirm real-time detection feasibility using our instrument through an offshore experiment. We expect that our proposed method will complement conventional detection methods for harbor defense and surveillance systems in acoustically noisy environments.