In this paper, an analytical design of a complex coefficient transfer function with flat passband characteristics and finite transmission zeros at two frequencies is proposed. The transfer function obtained from the proposed method has multiple finite transmission zeros at D. C. and another frequency. A transfer function obtained through the conventional method can also be obtained by using the proposed method. In other words, the proposed method includes the conventional method when the complex transfer function with flat passband characteristics is designed. The transfer function obtained from the special case of the proposed squared characteristic function can be realized as complex RⁱCR filters. The validity of the proposed method is confirmed through computer simulation.

In this study, visual working memory was assessed using nonverbal “accuracy,” in contrast to typical memory research, which is usually based on “right/wrong” answers. We analyzed the relationship between dynamic control of pen-use and pointing accuracy using a tablet liquid crystal device (LCD). Healthy participants held a pen equipped with a triaxial accelerometer in each hand. Using the dominant hand, they targeted a point at the center of a “diamond” formed by the intersection of two 4×1 cm rectangles tilted 45° to the left and right, respectively. The rectangles were quasi-randomly displayed at various locations on the LCD with time lags. The working memory accuracy was defined as the standard deviation of the distance between the absolute and surmised centers. The evident result indicated that the pen-dynamics (4-100 Hz) of the dominant hand started to increase for action readiness then decayed for the last 3 s during a 4-s interval (waiting period). Furthermore, the ability to sustain power for 100-200 Hz correlated with decrease of pointing deviation (i.e., increased working memory accuracy). We also discuss the relationship between our results and other memory theories, including those derived from rodent studies.

Control valves are used in many applications such as air conditioning systems. From the practical points of view, it is important to maintain desirable properties of such systems while it is also important to save cost which are required for the effective maintenance. To realize these purposes, we utilize FRIT, which is one of the controller parameter tuning methods with only one-shot experimental data, to update of controller parameters which are involved in the control valves.

In recent years, application of multiple robots system for a large scale system, such as a smart factory, is expected. A system consisting of heterogeneous robots can select the function by switching a combination of the robots according to a purpose. Therefore, the system is more versatile than a single robot on which multiple functions are installed. When the system is controlled by distributed system management, it is an essential technique that the robots communicate with each other. We have developed spatially seamless local communication system in order to exchange information between the robots without convergences. This system ensures spatially seamless communicable area towards robot's surroundings by rotating a transmitter and a receiver. However, a bit rate of communication using the system is insufficient. Although the system has redundant frame structure to detect interference between signals from different transmitters, it causes decrease of the bit rate. In this paper, we aim to improve the bit rate by reducing frame length of transmission pulse while retaining the interference detection function.

We conducted an auditory experiment assuming a natural disaster situation, where local governments issue prompt evacuation orders. Our key interest here is to assess the viability of using imperative forms and simple sentences to enhance listeners' sense of urgency, intelligibility, and credibility of evacuation orders. Supporting our preceding theoretical considerations, our experiment in this paper proved the statistical validity in such linguistic alterations. This will contribute to local governments prescribing evacuation call sentences.

There is a need for methods to recognize night pedestrian to reduce pedestrian traffic accidents at night. In this paper, we proposed the method that converts images using continuous nighttime images from in-vehicle camera. The proposed method performs feature extraction that doesn't depend on own vehicle speed because inputting continuous nighttime images, and the function of convolution layer that performs dimensionality reduction. In order to confirm the effectiveness of the proposed method, we prepared the images of simulation and camera. The nighttime images were conversed with the proposed method. After conversion, we calculated the recognition performance by applying object detection which is an object recognition method. We showed the proposed method is more robust against the own vehicle speed change.

This research investigates the effects of comparative information interventions on electric consumption behaviors and intention to use renewable energy. We surveyed 48 households by a web monitoring system to obtain energy consumption data and a questionnaire to measure awareness of renewable energy use. As a result, the information of electricity consumption of neighboring residents promoted energy saving behaviors, and it also stimulated personal norm and coping self-efficacy. On the other hand, the same information did not promote behaviors of renewable energy use. Therefore, different intervention methods will be expected to promote the behaviors of renewable energy use.

Design of IIR filters using PSO (Particle Swarm Optimization) has been proposed. However, an objective function of the design problem has a shape like a saddle point under the min-max criterion, and it causes one of the factors of the stagnation. In this paper, a design method IIR filters using CSO (Cat Swarm Optimization) is proposed for a succesive search. The design examples are shown to present the effectiveness of the proposed method.

Automatic classification of fundus blood vessels into artery and vein is one of the important topics in fundus image analysis. The conventional method, which employs pixel-wise training data, takes high costs for creating the training data. In this paper, we propose a very simple method to create as many training data as possible enough for deep learning, which only needs clipping an image of small size from the whole blood vessel image without any experts knowledge. The effectiveness of the proposed method has been confirmed.