In this paper, we propose a method of surveillance of the plant growth using image processing. This method is able to observe the condition of raising the plant in the greenhouse by detecting small insects. Experts can classify small insects, but many general people cannot classify small insects. Therefore we propose a method of classifying small insects by using image processing. The plate is prepared for extracting small insect. The image is obtained by an image scanner. In first process, each region of small insects is extracted from the image scanner image by using color information. In next process, some features are detected from the region of small insects. In last process, small insects are classified using above features. The experiments using the experimental system are performed to demonstrate the efficacy of this method and the experimental results are shown.
In this paper, we propose a method to create a 3-dimensional model of space using 3-d Rotation Invariant Phase Only Correlation (RIPOC). RIPOC is the applications of Phase Only Correlation (POC). The RIPOC can correlate two data even though there is rotation between two data. In this paper, we extend the RIPOC to 3-dimensional. It estimates the rotation angle between two 3-d information. We create a 3-d model using the estimated results. And it shows the ability of the proposed method.
In design process, miscellaneous knowledge is required for achieving desirable goal. Collaboration is a crucial method that contributes designers to create prime solutions by sharing their knowledge within a team. During a collaboration, valuable novel knowledge that is not held by the members could emerge due to synergistic effect. However, the way to generate such new knowledge is implicit. In this paper, a new model for collaborative design mechanism is proposed to investigate process of generating such knowledge. Effect of a collaboration can be visualized by using the proposed model. To show the usefulness of the model, a calculation tool has been developed based on the proposed model.
Aiming to help persons with mental health problems identify their own mental state and control it, not by visiting specialists passively but by proactively confronting their symptoms, this paper proposes an indirect biofeedback system that externalizes and objectifies the physiological state of users to allow them to self-control their inner state but also to control their physiological state. In the proposed system that we have developed, based on a display representation of physiological information with colors and shapes, the users can grasp their inner state and control it by different methods of breathing that help control their autonomic nervous system. Also, this paper clarifies the usefulness of the proposed system, showing the experimental results in comparison with the conventional direct feedback waveform display system.
Inpatients of circulatory system disease must manage their urine volume every day since they have low ability to control fluid balance inside their bodies. In most hospitals, measuring cups are used which lead to nosocomial infection. Our study propose a new method of urine volume estimation without using a cup. We propose multiple cylindrical model to estimate the amount of liquid volume from images taken by a monocular camera. This model is based on the idea of calculating the total volume of cylinder extracted from each image. First, images of liquid simulating male urination are binarized to derive features for the model. Each volume of cylinder is calculated by the initial velocity and diameter of liquid in each image. We conducted experiments to evaluate the model. As a result, we suggest that this model could be a new way of urine volume management for inpatients.
Q-learning is learning the optimal policy by updating in action-state value function(Q-value) to maximize a expectation reward by a trial and error search. However, there is major issues slowness of learning speed. Therefore, we added technique agent memorize environmental information and useing with update of the Q-value in many states. By updating the Q-value in the number of conditions to give a lot of information to the agent, be able to reduce learning time. Further, by incorporating the stored environmental information into action selection method, and the action selection to avoid the failure behavior, such as learning to stagnation, improved the learning speed of learning the initial stage. In addition, we design a new action area value function, in order to search for much more statas from the learning initial. Finally, numerical examples which solved maze problem showed the usefulness of the proposed method.
Cloud services like web-based e-mail or hosted office suites are becoming widespread. With these services, PC users are likely to use several services and to visit several sites at once, e.g. document preparation with looking in a net dictionary, or Internet surfing with watching movie. As a result, several windows appear on the desktop, and their overlapping complicates access to hidden windows. In this study, the authors propose a window manager running on the browser. The proposed window manager employs a tiling style in order to improve the usability of multiple cloud services at the same time. It also employs a window placement method implemented by drawing frame edges, and a window replacement method using drag and drop. The authors developed essential functions as a window manager and as a browser, and evaluated by a desktop experiment and a trial experiment in a college class of dozens students. The desktop experiment showed that the proposed window manager was effective in reducing the number of operations for window placement or replacement. The trial experiment showed that it improved efficiency and it was user-friendly compared with other window managers.