ABSTRACT This paper addresses the short battery lifespan of wireless mouse rings by introducing the picoRing mouse . We develop a near‐field sensitive inductive telemetry, which allows a ring coil to send its data to a nearby wristband coil in an ultra‐low‐power way. This approach drastically extends the ring's operation time from a few hours to over 200 h on a 27 mAh battery.
ABSTRACT In the field of Technology and Home Economics (Technology Area) in Japanese lower secondary schools, there is growing demand to enhance educational practices through the integration of ICT. Instruction in the use of hand tools is often based on the experience and intuition of teachers, while students are expected to acquire skills through trial and error. Consequently, the visualization and objective assessment of technical skills remain limited in practice. This study hypothesizes that by visualizing how force is applied during tool use, learners can reflect on and adjust their actions, thereby promoting the improvement of technical skills. To address this issue, a measurement device was developed to capture the thrust force and torque generated during drilling operations using a gimlet.
Remote control and tele-operation are employed across a wide range of applications. However, one challenge with these technologies is the lack of an established method for evaluating the workload they impose. Visually Induced Motion Sickness (VIMS) is an issue that can occur during remote control and tele-operation. Although both objective physiological indicators and subjective assessments are used to evaluate VIMS, each approach requires improvement. One issue that needs to be addressed in terms of objective evaluation criteria for VIMS is the burden associated with measurement. The use of gaze data is being considered as an objective evaluation index for VIMS with low burden. This study aims to develop evaluation indicators for VIMS by remote control and tele-operation. The result, the effectiveness of quantitative indicators such as total locus length, area of gaze and sparse density calculated from gaze data was demonstrated in the evaluation of VIMS associated with remote control and tele-operation. It was suggested that gaze data while staring videos could be used as an evaluation indicator. Future works include the development of evaluation indicators for video staring, the need to examine the relationship between VIMS and extraocular muscles, as well as exploring new analytical methods.
The principle of direct-current (DC) induction acceleration was numerically demonstrated using a three dimensional electromagnetic field simulator and a circuit simulator. Induction acceleration cells designed for DC acceleration accompanying with a racetrack-shaped beam duct were modeled to investigate the electromagnetic field induced during beam acceleration and resetting of ferromagnetic cores. The simulation showed that leakage electric field induced in the beam duct during resetting was largely suppressed owing to the induced current flowing in the beam duct although it is not perfectly negligible. The equivalent circuit simulation using linear and nonlinear transformer models revealed also that the continuous operation time of the DC induction accelerator would be limited by the magnetic saturation of the ferromagnetic core of a magnetic flux storage placed along the beam duct to ensure the resetting of the induction cells.
In this study, nondestructive evaluations of the setting and hardening process of cementitious materials were performed using a quartz-crystal-based complex capacitance sensor. The timing of setting and the process of hardening can be determined from the change in the frequency change. First, nondestructive measurements of the setting and hardening process of mortar were carried out and a combined evaluation was successfully carried out at two frequencies to evaluate the setting and hardening process. The weathering and cement material type dependence of the setting and hardening process was also evaluated, and differences in the reaction mechanism due to the properties of each compound were successfully detected. This research is expected to contribute to the streamlining of construction planning in the construction and civil engineering fields, the prolongation of the service life of infrastructure facilities, and the field of cement science.
Rapid technological developments are driving the digitalization of buildings. However, turning existing buildings into smart buildings requires the placement of many sensors. This involves extensive electrical work, making implementation difficult. However, by using wireless power supply, it is possible to supply power to the sensor module through the glass without the need for wiring or electrical work. In addition, because the power supply does not include batteries, after installation, it can operate for long periods of time without additional maintenance.
We quantitatively investigated the spatial distribution of fusion reactions under various discharge conditions in a linear inertial electrostatic confinement fusion (IECF) neutron source. A comparison between spectroscopic measurements and a one-dimensional Monte-Carlo simulation of collisional reactions in the plasma revealed that the spatial distribution of fusion reactions between ions and background deuterium molecules follows a Gaussian profile with a FWHM of 100 mm, while that of fusion reactions between fast neutral particles and background deuterium gas molecules appears to be uniform. Furthermore, a comparison between the angular distribution of neutron flux measured in the experiment and particle and heavy ion transport code system (PHITS) calculations reproducing the experimental conditions indicates that these fusion reactions contribute approximately 80% of the total fusion reactions at a discharge current of 10 mA and a discharge voltage of 40 kV, increasing to as much as 96% at 30 mA and 60 kV.
We are developing and operating the laser hammering system (LHS) that is non-destructive remote sensing device for concrete infrastructures. LHS can digitize the hammering test which is current mainstream of the inspection of concrete by using an impact laser (short-pulse laser), laser Doppler vibrometer, scanning system and camera. In this study, long-range LHS (applicable distance of 30 m) and small LHS (160 kg weight, for use on aerial work platforms) are developed for the bridge inspection. Long-range system succeeded on measurement of the concrete specimens of class 2 and 3 defect which were identified by active inspectors, and real defect of class 2 on bridge on use at the distance of 30 m. Small LHS succeeded on generation the surface vibration of the concrete specimens of class 2 and 3 defect which were identified by active inspectors. It indicates Long-range LHS and small LHS satisfied the inspection requirement as the support tool of hammering test prescribed by Japanese government. These devices are available for support to inspectors and digitalization of concrete sound status to achieve smart infra-maintenance.
Capacitive-type MEMS microphone with an amorphous solid structure membrane of PdCuSi metallic glass has been developed to suppress crack propagation and fracture against applied impact of air burst/air blow which was an issue with conventional poly-Si thin membranes. High fracture toughness, low LFRO (low-frequency roll-off), and high SNR characteristics were simultaneously confirmed for the prototype, showing the air burst resistance of more than twice that of conventional poly-Si membrane at the measurement limit of 0.97 MPa or more, the LFRO of 10 Hz or less, and the SNR of 69 dBV.
Soil in Sub-Saharan Africa has a low pH and high aluminum levels, which hinder agricultural productivity. In this study, WE1 aimed to develop a simple and efficient method for aluminum measurement in soil with minimal pretreatment. To achieve this, WE1 designed a potentiometric sensor for the detection of aluminum ions (Al3+). The sensor showed a range of detection for Al3+ (10(-5) - 10(-3) M) with a sensitivity of 17.40 mV/decade under pH 4.0 conditions. Furthermore, it exhibited high selectivity for Al3+ over possible ions. These results suggest that the proposed sensor could serve as a useful tool for soil monitoring and contribute to improved crop productivity.
There is a lot of previous research on smart agriculture. In this research, crop rotation is studied in smart agriculture. In some previous research on crop rotation, the expected profit of finite periods is maximized considering the fluctuating crop price. The previous method cannot maximize the expected profit after the finite periods. In this research, the expected profit of infinite periods is maximized considering the fluctuating crop price. In this research, the crop rotation problem is modeled by Markov decision processes. The expected profit is maximized by value iteration algorithm in the proposed method. The effectiveness of the proposed method is shown by some computational examples. The expected profit of the proposed method is greater than that of the comparison target. In the results of the proposed method, the adaptive crop selections according to the fluctuating crop price are confirmed. The proposed method is expected to contribute to the automation of decision making in smart agriculture.
This article describes a method for measuring the diameter of fruits with a near spherical shape using an RGB-D camera in order to investigate fruit enlargement at different times of the year. In general, depth-based measurement methods, when considering the diameter of an object with a near-spherical shape, the diameter can be calculated by obtaining the Euclidean distance from the coordinates of the object's sides or by using the depth at the center of the object and the size of the object on the RGB image. However, it is difficult to accurately determine the diameter of an object because of errors in the calculated results due to the perspective projection of a general camera. Therefore, this study proposes a method to measure the diameter of fruits that have a shape similar to a sphere. Although this study focuses on young apple fruits, the proposed method can be applied to other agricultural crops, as well as to objects that are similar to spheres. In addition, we have also studied a correction that takes into account the rotation of the object so that the method can be applied to objects with circular cross-sections.
The rapid penetration of renewable energy resources has introduced significant uncertainty into modern power systems, necessitating accurate pre-assessment to ensure secure operation. Probabilistic power flow (PPF) analysis is a powerful technique for quantifying such uncertainty, but its reliance on repeated AC power-flow solutions makes it computationally prohibitive. This study proposes a fast PPF framework that couples the linear DC power flow (DC method) model with an Extreme Learning Machine (ELM) surrogate. By augmenting ELM inputs with DC-PF results and employing Latin Hypercube Sampling, the method achieves both high speed and high accuracy. Numerical experiments on benchmark IEEE systems confirm that the proposed approach preserves the precision of conventional Monte-Carlo-based PPF while reducing total computation time by approximately 140 times
Under lighting using RGB (red, green and blue) color LEDs, retina images become sharper. Under lighting light with the same illuminance and chromaticity, the near point distance, which is extended by presbyopia was reduced by 12%. Also visual acuity was improved by 11%. However, further improvements are desired to commercialize RGB color LED lighting. The sharpness of the boundaries of retinal images is thought to be due to the chromatic aberration of each color of light. The near point distance and visual acuity were thought that they could be further improved by lengthening the dominant wavelength of the red LED and shortening the dominant wavelength of the blue LED. Therefore, the authors analyzed chromatic aberration and manufactured a lighting, in which the dominant wavelength of the red LED was lengthened to 660 nm from 625 nm, and the dominant wavelength of the blue LED was shortened to 425 nm from 470 nm, as long as the luminous efficiency can be maintained. We repeated measure the near point distance and visual acuity using the manufactured lighting. As a result, the near point distance was shortened by 9% to 13% and visual acuity was improved by 11% to 22%.
Blood viscosity, which is an important index during the extracorporeal treatment, is one of the determinants of red blood cell aggregation in the blood. In this paper, we propose an optical detection method for red blood cell aggregations by using object detection algorithms, assuming that they will be incorporated into the flow path of an extracorporeal circulation device. By performing detection from a single image, it is a method that can detect aggregations without being affected by rotation, scaling, or the attachment and detachment of red blood cells. In the simulated red blood cell sample, the detectability of aggregations was shown not only at the focus site but also at the defocus site.
Eddy current sensor (EC sensor) is a non-destructive and non-contact method to measure the thickness of metal coatings in real time. However, it is known that the distance between the EC sensor and the object to be measured (lift-off) leads to thickness measurement errors in metal coating thickness measurement using the EC sensor. In this paper, we propose a simple method to measure the thickness of non-magnetic metal thin films formed on ferromagnetic metal substrates using EC sensor in the sub-micron order and to solve the lift-off problem. Specifically, based on Dodd's theory, the measurement principle of the EC sensor is modeled theoretically, and the verification is conducted using an EC sensor designed based on the model and its driving circuit. According to the proposed method, the EC sensor shows high sensitivity in the range of Cu film thickness from 0.1 & micro;m to 1.0 & micro;m, which is about 400 to 500 times higher than the sensitivity due to lift-off. This indicates that the effect of lift-off can be minimized. A method for measuring the thickness of Cu films on the sub-micron order at arbitrary lift-off is also shown.
In this research, we examined the differences between different gazing positions during training. We used multiple electrodes and focused on the amplitude and conduction velocity of the measured conducting waves, which enabled a detailed examination of the muscle contraction mechanism. In this experiment, the test muscle was the biceps brachii muscle, which was trained under three separate conditions to investigate differences in conducting wave characteristics depending on gazing position. As a result, no differences were found in the relative frequency distribution or in the percentage of the frequency of the occurrence of the antiphase conducting wave pairs due to the difference in the gazing position. However, it was shown that the ratio of the frequency of the occurrence of the antiphase conducting wave pairs could be used as an indicator of the training effect.
In this study, we attempted to estimate heart rate and blood pressure using an electret capacitor sensor (ECS) that measures pulse waves with high resolution. The ECS was attached to multiple areas of the body, and plethysmogram and mechanomyogram (pulse wave and muscle sound) were measured while blood pressure and pulse rate were measured. The results showed that the ECS had a signal-to-noise ratio more than 20 dB higher than that of the accelerometer (ACS), especially in the low-frequency range. In pulse wave measurements, peaks derived from the first and second heart sound were identified; multiple regression analysis of the 6-50 Hz component of the peak of the first sound showed that correlations with R 2 values of 0.6 or higher were observed in systolic blood pressure (SBP), diastolic blood pressure (DBP), and pulse rate, even when a single first sound peak was used. In addition, ECS was able to detect muscle sounds during loading with a higher signal-to-noise ratio than ACS. Based on these results, it is expected that ECS is a sensor that can measure pulse wave and muscle sound with broadband frequency components and has the potential to estimate blood pressure and pulse rate from pulse wave in a short time.
Atherosclerosis is a key factor in lifestyle-related diseases, characterized by near-irreversible arterial thickening and hardening. Early detection is crucial for effective intervention, however current wearable technology lacks noninvasive arterial stiffness assessment capabilities. This study explores the feasibility of using Photoplethysmogram (PPG) at the radial artery for arterial stiffness evaluation, focusing on green-light PPG. PPG signals were collected from 18 healthy young participants (9 males: 23.3 +/- 3.7 years; 9 females: 24.7 +/- 7.3 years) at the fingertip and wrist. The second derivative PPG (SDPPG) obtained from fingertip with green and near-infrared light and that from radial artery with green light was analyzed. Preliminary results showed that SDPPG aging indices obtained from fingertip with green and near-infrared light were highly correlated in 4 participants, suggesting its feasibility for vascular age estimation. However, at the radial artery, individualized vascular age estimation models may be required. Further studies are needed to validate this approach and establish standardized evaluation criteria.
Reservoir computing (RC) has attracted much attention in recent years as a model suitable for machine learning of time series information and requiring low computational resources. Among these, physical reservoir computing (PRC), in which RC is implemented in hardware devices, has been actively studied using various devices as it is applicable to edge computing. In this article, we construct a RC system using Pulse-type Hardware Chaotic Neuron Model (P-HCNM), which can be implemented in integrated circuits, and perform a benchmark task. A second order Nonlinear Auto Regressive Moving Average (NARMA) task, which is widely used as a benchmark task for RC, is evaluated using Normalized-Mean-Square-Error (NMSE), and the result is 0.0456. The score is comparable to other PRCs in previous studies. In the Delay task that evaluates short-term memory, the recall results of the RC showed a forgetting curve. The result indicates that RCs have short-term memory, which is a necessary component for RCs. Using these benchmark tasks, we suggest that a P-HCNM-implemented neural network can be the hardware basis for a neuromorphic reservoir computing system.
