We are studying with the aim of practical application of spelling type brain-computer interface (BCI) as intention transmission means of amyotrophic lateral sclerosis (ALS). There is a problem that the character input time per character is long in the character input BCI. In our previous study they needed more than 60 (sec/char). Therefore, such as a decrease in concentration ability and fatigue of eye movements, they are burdensome. Thus, the present, we propose a character estimation method to shorten spelling time by using the feature of discriminant score. This proposed method can extract intention from electroencephalogram with minimum stimulation. We investigated the purpose of improving character input speed while maintaining character input accuracy of character input type BCI by proposed method. As a result, the effectiveness of the proposed method is higher than that of the conventional method (averaging method). In addition, character input speed in ALS patients was shortened from 81.6 (sec/char) to 21.1 (sec/char).

We aim to develop earphone type wearable devices for measuring occlusal force. In this paper, we investigated the correlation between occlusal force and the movement of the ear canal as a basic study to estimate the occlusion force. The proposed estimation method uses the least squares method and the weighted average. We developed an experimental device for simultaneously measuring occlusal force and the movement of the ear canal. This device primarily consists of an occlusal force sensor and a wearable ear sensor, and converts analog signals from both sensors into digital signals using an analog-to-digital (AD) converter, then records the data as signals associated with measurement time. The experiment involved six subjects, who performed chewing of the occlusal force sensor five times, for 2 seconds. The occlusal force sensor was placed at the right second molar, with the wearable ear sensor placed on the right ear. Through the experiment, the occlusion and the ear canal movement were found to have a strong correlation. The average correlation coefficients consistently exceeded 0.89 for all subjects.

Establishment of real-time monitoring technique for blood viscosity during extracorporeal treatment is strongly desired. We have demonstrated that the red blood cell aggregation degree, which highly correlates with the blood viscosity, can be estimated by the microscopic observation of the red blood cell over a transparent blood circuit tube and the two dimensional correlation process executed between time different images. In this paper, for estimation precision improvement, a maximum likelihood design of correlation region based on calculation of local flow vector has been attempted.

Stroke Impairment Analysis Set (SIAS) is a set of evaluation methods of the hemiplegia body caused by stroke. The score of the test is made by visual examiners. However, the decisions are often different between them. Thus, the purpose of this study is to make an automatic evaluation system for the SIAS by using depth sensors. Kinect and Leap Motion are used to evaluate the proximal and distal upper extremity tests and the proximal lower extremity test in SIAS. The evaluation of these tests are based on the time difference of left and right cases, and the smoothness. If both of left and right motions are roughly the same and the motion is smooth enough, the score is 5, otherwise the score is decreased to between 4 and 0. The perfect match ratio between the system output and therapist judged is 65～75% and it can be higher than this if similar judgements are partially added to the score. In experimental results, this system has been shown to yield reasonable scores for the knee-mouth test, the finger test and the hip flexion test in motor function of SIAS.

In hospitals, in order to prevent a patient from falling and fall accidents, there is an increasing demand to detect a lifting movement and a leaving-off movement of a patient with a camera installed in a hospital room. As a measure for efficiently detecting these operations, a process of specifying a bed position which is an occurrence position of an action is effective. We propose a method to detect bed position from image of monocular camera, using image features and framework of machine learning. By generating a viewpoint conversion image for an input image, a uniform bed shape is acquired even for images at different camera positions. Evaluation was made with 2160 still images and 3888 scene moving images to confirm the usefulness of the method.

This paper proposes a new design concept of active integrated array antennas having oscillation and modulation functions for spatial modulation wireless communication systems. Several configurations of the active integrated array antennas are proposed and discussed. The proposed active integrated antennas provide polarization modulated radio waves with a simple structure. A polarization switchable ring-slot active integrated antenna employing Gunn oscillators is designed and experimentally demonstrated as an example of the proposed concept. The prototype active integrated antenna successfully switched its polarization angle between ±45 degrees. The proposed active integrated antenna concept was found to be feasible.

The use of Internet and Mobile Broadband Network are spreading in the field of Remote Monitoring Systems for facilities located in buildings and factories. These best effort services experience large packet transmission delay, random and frequent packet loss, etc. It has been a technical issue to achieve guarantee for the maximum delay of the O&M sensor data, and high average throughput including the other data. In this paper, a new method for QoS control is proposed. It achieves delay guarantee and high throughput at the same time, controlling transmission speed of TX data in accordance with the estimated bandwidth of the network. Performance of the proposed method is evaluated using a commercial cellular network. It was shown that the proposed method can achieve both delay guarantee and high throughput, while the measurement with no control could only achieve high throughput.

This paper proposed a precise time synchronization method between schedulers of real-time operating systems by communicating timestamps over a network. An NTP based communication protocol was used to measure the time offset between nodes. To minimize the measurement error, a light-weight network stack called RT-Messenger was used instead of common TCP/IP stack. Also, a Kalman filter was introduced to eliminate such error and to estimate time offset and drift. Furthermore, a real-time scheduler in RTAI/Linux was modified to compensate the time difference using the estimated offset and drift. The time compensation of a scheduler clock affects the next resume times for real-time tasks. Therefore, a re-calculation process of next resume times for all real-time tasks and a re-ordering process of reak-time task queue were added into the real-time scheduler. To validate the proposed method, time differences of resume times for two real-time tasks on different nodes were measured under various experimental conditions. The results confirm that the resume time differences were successfully kept lower than 400ns with 300ns standard deviation under the condition of observation period at 1s and correction period at 10s.

Regarding the T-S fuzzy model as a mathematical model of the plant to be controlled, the model is widely used in the fuzzy control systems for the purpose of designing controller. In this paper, the so-called lumped disturbance is considered in the T-S fuzzy model in an effort to cover the modeling error including the external disturbance, unmodeled dynamics and parameter perturbations. Following a design of the disturbance observer as well state observer in case the control state is unavailable, the existence conditions for the aforementioned observers are discussed. Finally, a design of T-S fuzzy controller based on the state and disturbance observers is developed. Also, simulations are provided to demonstrate the effectiveness of the approaches proposed.

In recent years, the manufacturing industry has seen a shift of the domain of competition from “performance” which can easily be expressed numerically to “design” which is hard to be expressed numerically. The rise of companies that focus on design, such as Apple, Samsung and IKEA, is remarkable. However, design presents two challenges for the manufacturing industry. The first one is sensory. It is very difficult to quantitatively evaluate, and unified evaluation indicators are not yet defined. The second one is confidentiality of product design. Design is in the position of top secret in companies, so large customer survey has high hurdles. The above two problems increase the influence of the evaluator’s experience and cause a situation that it is difficult to truly create a design desired by the customer. Therefore, the purpose of this research is to quantitatively and confidentially and inexpensively enable the evaluation of the sensitivity for automobile exterior design from the accumulated design and customer’s voice without surveying of target products.

Inverse Reinforcement Learning (IRL) is a promising framework for estimating a reward function under given behaviors of the expert. However, the IRL problem is ill-posed in that several reward functions that can reproduce expert's behavior will be available. The previous studies of IRL have just focused on the reproduction rate of original behavior of expert's to select the most appropriate reward function. This evaluation measure seems not enough to shape the candidate of reward functions. To select the most appropriate one from the alternative reward functions, we introduce another objective function into the existing IRL algorithms of Ng et al. Specifically, we focus on the learning efficiency as an additional objective function to make the faster convergence of RL via introducing Genetic Algorithm. Consequently, our proposed IRL algorithm guarantees to output the reward function by which agent acquires both effective and optimal policy. We show the effectiveness of our approach by comparing the performance of the proposed method to those of the previous algorithms.

We propose server and storage resource partition method for mission critical system consolidation to prevent performance interference in cloud computing environment. We made experiments to allocate dedicated CPU core and SSD to a virtual machine. As a result of running a standard online transaction processing benchmark on 3 virtual machines, transaction performance decrease by 65% with the existing method and by only 9% with the proposed method.

In recent years, food waste disposal, food loss has become a social problem. Among them, attention is focused on reducing food loss. Food loss refers to the disposal of parts that were originally available for eating during food disposal. Food losses are targeted for residues left behind, excessive removal, expiration of expiration dates and the like in the home. On the other hand, disposal due to expiration of expiration dates at retail stores is treated as food disposal. We made proposals for pricing by smartphone application to reduce food loss. The penetration rate of smartphones has become about 65%, and in the age of 20 to 50 years it is high as around 80%, so it can appeal to many consumers. In this paper, we verify that price presentation considering consumer's purchasing behavior by smartphone application is effective.

In IoT (Internet of Things) systems, sensors and actuators placed in the data generation site are connected to the cloud via a network, and operations such as data transmission, analysis, and feedback are handled without human intervention. IoT systems have a wide range of technology, so that it takes a long time to commercialize it. However, by creating a prototype system and verifying the degree of achievement of the main specifications at an early point in time, it will become possible to predict what should be done before completing the product, and get the reaction of the limited user market. In this paper, we propose a method of verification from third party view for IoT prototype system. This method has features of extracting verification items for prototype, measuring distances between prototype and product, and verifying the degree of the hazard prevention function. We applied this method to two prototypes of hydroponic cultivation and UAV (unmanned aerial vehicle) to harmful birds, and evaluated the method.

Since solar power generation has increased rapidly, balancing function, especially in the form of increasing demand, is becoming needed. We propose technique of demand response in which an aggregator dispatches home appliances expected to be IoT-ready in the near future in order to consume the surplus deriving from over-generation of solar energy.

In this study, assuming that such an aggregator could be an energy retailer as well, this demand dispatch is provided to customers as an energy service and also offered to the power system operator as a balancing function. An experimental demand dispatch system is implemented, and challenges are pointed out such as an error between target demand value to be increased and actually dispatched demand value.

A compact rat-race circuit consisting of planar circuits is presented in this paper. The prototype is fabricated at 1GHz, and the propagation characteristics and reflection characteristics of each port are measured. The measurement results agreed well with those of the theory. The dimensions of the circuit are approximately 21mm×25mm.