Electronics and Communications in Japan最新文献

Femtosecond double optical pulse experiments with nanosecond time delay were conducted in air. Terahertz pulses were generated from laser plasmas produced by the irradiation with the main pulses on shockwave excited by the pre-pulse illumination. Intensity of the terahertz pulses depends on the time difference Δt and relative position Δy between the pre- and main pulses. We found a characteristic dependence of the intensity of the terahertz pulses on Δy at a longer time delay, Δt = 14.7 ns, which has two maxima while only one maximum was observed when delay times were at and shorter than 9.7 ns. The results are discussed taking into account air density distribution of the shockwave. The terahertz emission spectroscopy shown here can be a useful technique for investigating density structure and its time variation of shockwave with high temporal resolution.

In the fields of medical and sports science, it is required to evaluate muscle activity qualitatively and quantitatively. Currently, mechanomyogram (MMG) that can reflect the mechanical activity of muscle fibers is attracting attention. The purpose of this study is to develop a sensor that can measure MMG during exercise. In this study, a small and flexible MMG sensor using P(VDF/TrFE), which is a piezoelectric polymer material, spun into nanofibers by the electrospinning method has been fabricated and evaluated. By the fabricated electrospinning equipment and the obtained fabrication conditions of the nanofibers MMG sensor has been fabricated by using piezoelectric polymer fibers. By using nanofiber nonwoven fabric for the sensor element, the flexible sensor has been realized. In a sound wave reception experiment assuming MMG measurement, the P(VDF/TrFE) nonwoven fabric element showed that the element detected the sound pressure. Additionally, MMG during isometric contraction and pedaling motion has been measured using the fabricated sensor. The results show that the proposed sensor is effective for measuring MMG during exercise.

We propose a modeling framework for automating batch processes operation. Batch processes are often controlled by PID controllers, where engineers manually regulate their parameters and temporal patterns of reference signals. Therefore, it takes a long time for optimizing these parameters and temporal patterns. A possible solution for this is to apply so-called Model Predictive Control (MPC) technology to the tuning. Here, batch process dynamics depend on the types of products and of equipment, thereby forcing engineers to construct and maintain multiple models that correspond to the number of combinations of product types and equipment types. Thus, batch process modeling is a time-consuming and complicated task. To solve this problem, we propose a modeling framework; about a modeling target, the part applying commonly and parameters can be decided in advance are constructed by mathematical models, and the part that required experimentation for designing or tuning are constructed by machine learning models. We expect this framework can improve estimation accuracy and suppressing the number of model construction by separating model construction and combining the mathematical and machine learning models. In our simulation, we confirmed that our proposed model can suppress prediction error (RMSE) of reactor temperature under 1 K. Furthermore, an optimization algorithm with our model can find a temporal pattern of a reference signal so as to reduce control error of reactor temperature under 1.99 K.

To properly maintain and manage track surfaces, the amount of collapsed settlement of a ballast bed must be determined. However, high maintenance costs make it difficult for railway operators to fully maintain and manage track surfaces. Therefore, we propose a method of estimating the shape of the ballast bed using Dense Inverse Search (DIS) optical flow in images captured using a camcorder, which is inexpensive. This paper describes the outline of the method, an evaluation of its accuracy through simulation and model experiments, and the results of applying the method to actual images captured.

Respiratory rate (RR) is known to be a more accurate predictor of clinical deterioration than other vital signs. However, there were few respiration measurement devices certified as medical devices that could be used in daily clinical settings. Therefore, using a bult-in microcontroller (72×57×12 mm) instead of a personal computer, we developed a portable stand-alone respiration measurement device with minimum workload in computing that can be used for non-contact measurement in 30 s using a Doppler radar. In this study, the problems of respiration measurement using a Doppler radar, such as miscounting of respiratory peaks were clarified, and proposed device with respiratory peaks miscount prevention algorithm achieved high accuracy RR measurement. Clinical testing was conducted on pediatric outpatients of Children's Medical Center, Showa University Koto Toyosu Hospital. The measurement accuracy of the system was confirmed to be comparable to the respiration measurement accuracy of stationary certified medical devices used in hospital, such as capnometers and the chest wall impedance method used in bedside monitors.

The purpose of this study is to realize a grasp force measurement of forceps for robotic surgery systems. Generally, surgical robot forceps is actuated by traction wire, and we have suggested a newly force sensing system by measuring the wire expansion utilizing micro displacement sensors. For measuring the elongation of the wire, the white-light interference principle has been utilized on sensor system, and the sensor consists of a tip-tilted optical fiber, a Fizeau interferometer and a sensor holder. In this report, displacement sensor has been successfully fabricated and mounted onto the wire to measure the elongation of the wire under tension and discussed the experimental results.

This study deals with the task of segmentation of SEM images of fine ceramics sintered bodies by using deep neural network (DNN). In particular, we focus on misclassification caused by the blurriness of grain boundaries(boundaries between particles). Therefore, we utilize the frequency distribution of brightness gradient of grain boundaries and give higher weights to pixels with lower gradient values. Experiments confirmed that the model trained with proposed loss function gave the best prediction results.

Text input, which is essential for a variety of applications, is one of the most difficult operations for older people. So, we propose a prototype to automatically detect and input text from a natural image taken from a user's smartphone. For the evaluation of the system, 232 photo data taken by the actual people were prepared. When all data was processed on the server, the average processing time was less than 10 seconds, and the overall recognition rate was over 94%. For user study, 20 healthy older people aged 65 years or older were collected. And, after conducting a simulation with the conventional typing system, the prototype in this proposal was asked to be used. The time required to complete each work was recorded, and the usability was evaluated using System Usability Scale (SUS).

As a result, both the healthy older group and the MCI older group tended to shorten the task execution times and increase their SUS scores by using our application, compared to the conventional method. Also, comparing the SUS score with other Web applications, it is considered that usability is high as a prototype.

There is a growing interest to introduce energy-saving algorithms which balance energy efficiency with residents’ comfortability into a building energy management system (BEMS). However, the following issues hinder penetration of the energy-saving algorithms into markets: difficulties both in embedding the algorithms into the BEMS, and in turning the algorithms suitably to fit varieties of installed equipment in each building. In this paper, A BEMS on micro-service architecture, and software service modules for the BEMS, were proposed. The micro-services architecture improves flexibility to introduce newly developed energy-saving algorithms into the BEMS and software service modules manipulate whole roles (modeling, planning, doing, and action) required for tuning the algorithms on-line to fit the algorithms to each building. Each software service module was implemented and integrated as elements of BEMS on micro-service architecture. The BEMS on micro-service architecture was applied to an actual building for evaluation, and its availability was confirmed through the field test.

In this study, we measured the enzymatic activity of acetylcholinesterase (AChE) using the Light Addressable Amperometric Sensor (LAAS), an electrochemical sensor that can easily measure redox current values of multiple samples. Acetylthiocholine (ATCh) was used as a substrate. ATCh is hydrolyzed by AChE and releases electrons, making it possible to measure current values in accordance with the amount of substrate using LAAS. When KCl solution was used as the supporting electrolyte and an Ag/AgCl reference electrode as the counter electrode, a correlation between substrate concentration and reaction was confirmed in the range of 1 μM–10 mM. Malathion was then used as an inhibitor of AChE. Malathion phosphorylates and inactivates AChE, which prevents substrate hydrolysis and is expected to decrease the current value. Experimental results showed a decrease in sensor response correlated with inhibitor concentration.