Daido University

Plasma nitriding of JIS SKD61 tool steel was performed by open-air type atmospheric-pressure plasma jet. The results of our experiments show that the surface hardness of tool steel work pieces was increased by more than two times that of the core material after within 30 min of treatment time.

Until now, authors have considered the Balancing Domain Decomposition DIAGonal scaling (BDD-DIAG) preconditioner as a preconditioner of non-overlapping domain decomposition analysis of 3-dimensional magnetostatic problems taking the magnetic vector potential as an unknown function. One interesting fact is that the direct solver without pivoting can be used in many cases for solving the coarse problem in BDD-DIAG. In this paper, they show a sufficient condition for positive-definiteness of the Schur complement matrix of the original magnetostatic problem in which the coefficient matrix of the finite element approximation is a well-known singular one. Authors only considered a well-known perturbed problem previously. But, in this paper, they consider the original magnetostatic problem. Furthermore, with a numerical example, they notice that the BDD-DIAG preconditioner includes the DIAGonal scaling (diag) preconditioner as its special case.

We have been conducting research and development of training devices of adjustability for grasping force and verified. Based on these knowledges, we have developed the Touch Wakka, a hand-finger tactile stimulation device that presents the reaction force. The subject grasps the Touch Wakka and deforms it to feel the reaction force of the leaf spring in the Touch Wakka while evaluating or training grasping ability, and there are a motor and a wind up mechanism in the Touch Wakka, so that the reaction force presented to the subject can be adjusted by the motor. In this paper, performances of the Touch Wakka was evaluated. The results showed that the amount of deformation of the Touch Wakka was proportional to the reaction force when the motor was not driven. Furthermore, the frequency response of the reaction force adjustment was measured. From this result, the Touch Wakka have a response above 85Hz.

In structural design, RC shear wall boundary beams are commonly modeled as rigid, including in multi-story seismic wall structures with a soft-first story, and thus the verification (warranty design) of the boundary beams directly above a soft-first story is not commonly performed. However, the boundary beam of the shear wall above the soft-first story may not constrain the shear wall due to the beam deflection. Therefore, the possible failure should be considered in the structural design. This study conducted a finite element analysis on the previous test specimen to investigate the stress levels in the boundary beam of the shear wall above the soft-first story. The analytical results adequately captured the experimental results on load-deformation relationship and failure; therefore, the analytical model used in this research is validated, and additionally, insights were gained into the distribution of axial forces/bending moments acting on the boundary beams, which can be applied to structural design considerations.

Hands-free control of shower settings, such as temperature, is highly desirable, enhancing user convenience when both hands are occupied or eyes are closed. In this paper, we propose a speaker-dependent, template-based isolated word recognition system using pre-trained large speech models (LSMs) to realize voice-activated shower control with a single microphone. Specifically, we examine the performance of 3 LSMs (wav2vec2.0, HuBERT, WavLM) as well as conventional MFCC as features. Additionally, we investigate speech enhancement using a Convolutional Recurrent Neural Network (CRN) to improve robustness against shower noise. Our experiments for recognizing 30 words with SNRs ranging from-5 dB to 20 dB demonstrate that HuBERT achieves the highest recognition accuracy (77.8 to 95.6%). CRN, on the other hand, improved recognition accuracy only under-5 dB conditions, but its accuracy was only 80.8%.

Recent advances in AI technology have brought not only many benefits but also considerable risks due to malicious use of the technology. One key example is spoofing through speech synthesis and voice conversion technologies against speaker verification system. To tackle this challenge, we proposed a two-step matching method as a robust speaker verification , in which a user specifies an emotion to a system in advance, and the user is accepted only when the user speaks with the specified emotion. This previous method reduced the false acceptance rate. However, the false rejection rate increased. To overcome this problem, we propose a novel method that integrates speaker and emotion verification scores in this work. Experiments revealed that the proposed method can reduce the equal error rate compared with that of the conventional method to assign the optimal weight to the speaker and emotional information contained in the speech.

To enhance speaker verification for short utterances, we have developed a Same Speaker Identification Deep Neural Network (SSI-DNN). This network identifies whether two utterances are uttered by the same speaker with greater accuracy by focusing on the same texts. In this paper, we extend the detection target of the SSI-DNN from monosyllabic utterances to word utterances to improve the speaker recognition performance. Experimental results showed that the SSI-DNN trained on word utterances achieved an EER of 0.1% to 2.8%. These results indicated that the SSI-DNN outperformed the x-vector-based speaker verification method, which is a representative speaker verification method.

This study presents the development of a small electric vehicle (EV) traction drive motor using Fe‐based amorphous laminated cores that can be mass produced. The following innovative technologies are developed to realize the amorphous laminated core: (1) production technology for thicker amorphous alloy foils to reduce the number of machining operations and (2) punching press technology for amorphous alloy foils that improves the usability of the tool life and maintains quality. The interior permanent magnet synchronous motor (IPMSM) using the amorphous laminated core is designed to be compatible with a 4.5‐kW‐class small EV traction drive with high efficiency while satisfying the required torque characteristics. A prototype of the designed IPMSM was manufactured and evaluated. The test machine achieves a maximum efficiency of 98.7% and a wide range of efficiencies exceeding 97%. Additionally, the prototype motor exhibit improved efficiency in all operating points compared with a prototype manufactured using an electrical steel sheet.

In this study, according to AIJES, the odor standard value of sidestream smoke of cigarettes and other than mainstream aerosol of heated tobacco products (HTPs) was examined. The acceptability of each odor sample was examined by 60 panels who passed the selection test, and the odor concentration of the unacceptable rate of 15%, 20%, and 30% was indicated. The results showed that the standard values of other than mainstream aerosol of HTPs were 1.2～1.5 times higher than standard values of AIJES, and indicating that HTPs was more acceptable at higher concentrations than cigarettes.

The oppressive or vibratory sensation caused by low-frequency sound is a widely known sensation inherent to that type of sound. In previous studies using one-third octave band noise as stimuli, the frequency region that causes the oppressive or vibratory sensation was felt before other sensations such as loudness and noisiness (here, called the peculiar region). However, it has been suggested that level fluctuations of one-third octave band noise affect the oppressive or vibratory sensation. Furthermore, few studies have investigated the threshold of these sensations. In the present study, we conducted laboratory experiments to investigate the peculiar region from 10 to 160 Hz as well as the sensation threshold by using low-frequency pure tones. The peculiar region in which the oppressive or vibratory sensation became dominant was generally consistent with the findings of previous studies. However, differences were found in relatively higher frequencies such as 80 and 160 Hz. In addition, the median threshold value was lower than the lowest level of the peculiar region. The threshold differed greatly among the participants, and the higher the frequency, the more pronounced the difference. Multiple regression analysis suggested that these individual differences might be related to noise sensitivity.

A socio-acoustic survey was conducted among residents living along major arterial roads in Kanagawa Prefecture, Japan, to examine the occurrence of sleep disturbances due to road traffic noise. Lnight noise maps was introduced for estimating ranges from 30 dB to 80 dB. We asked the frequency of "difficulty falling asleep," "nocturnal awakenings," "early morning awakenings", "feeling unrefreshed in the morning",and "daytime sleepiness" due to road traffic noise. Cases experiencing any of these items more than three times a week were defined as "highly sleep disturbed (HSD)", and that one or twice a week were defined as "sleep disturbed (SD)", respectively. The exposure response relationships between those and Lnight were examined with the independent variables of noise sensitivity, gender, and age. The results of multiple logistic regression analysis revealed that Lnight, and noise sensitivity had a significant effect on SD, while noise sensitivity significantly affected HSD. We show the results of this study in comparison with previous surveys on sleep disturbances conducted in Japan and other regions.

To conduct detailed studies on aircraft noise and manage noise maps around airports, it is necessary to measure aircraft noise under various conditions. In such measurements, it is necessary to obtain not only the noise signals but also information that identifies the noise, such as the type of aircraft and flight mode, and so on. To automate this measurement, we have been developing a technique for identifying aircraft noise using machine learning based on measured acoustic information. To enhance the generalizability of this technique, it is necessary to create an integrated model by accumulating aircraft noise data measured by various organizations. However, this type of information is subject to strict security and involves a large amount of data. To solve this problem, we applied Swarm learning, which accumulates only the weight information learned by machine learning in each organization, to create an integrated model. We compared the accuracy of models within each organization, models trained with the accumulated data from all organizations, and models that integrated only the weights extracted from each organization's model using Swarm learning. As a result, the models using accumulated data and those using Swarm learning had almost the same accuracy.

This study explores the intriguing phenomenon of positive participant responses amidst sustained high noise levels in a follow-up survey conducted in the previous year (2023) at Military Hospital 175. Building upon the initial 2022 survey, our investigation reveals a noteworthy continuity of positive responses from participants, despite the persistent influence of high noise levels on both staff and patients. This study, expanding its focus to include road traffic noise surrounding the hospital, highlights the resilience demonstrated by individuals within the hospital environment. The results suggest a complex interplay between perception and adaptation to noise, emphasizing the need for a nuanced understanding of the psychological and physiological responses to sustained high noise levels. This study contributes valuable insights for future interventions and strategies aimed at promoting well-being in healthcare settings with persistent noise challenges.

This paper reviews studies on the prediction of ductile fracture during metal forming using an ellipsoidal void model and some other models proposed by the author and some relevant studies. Section 2 discusses the research on the theory of voids for predicting ductile fracture during metal forming. Section 3 summarizes the simulation method for predicting ductile fracture during metal forming using the ellipsoidal void model, and Section 4 summarizes the simulation result on the ductile fracture prediction during metal forming using the ellipsoidal void model. Section 5 shows the applicability of the ellipsoidal void model and the simulation result on the ductile fracture prediction during metal forming using some other models.

The body diode characteristics at high di/dt (approximately 2000 A/µs) were evaluated for four power devices with a breakdown voltage of 650 V: (1) GaN-FET (cascode), (2) SiC-MOSFET, (3) Si-SJ-MOSFET, and (4) Si-RC-IGBT. The Qrr of the GaN-FET and SiC-MOSFET were approximately 6.3% and 4.5% of that of the SJ-MOSFET, respectively. The GaN-FET has a cascode-connected Si-MOSFET body diode. The accumulation of minority carriers in this diode was small, and the main component of the recovery current was due to the parasitic capacitance of the device. In addition, in the IGBT, a dynamic avalanche occurred and a second peak appeared in the recovery current.

This paper presents an analysis of sleep patterns and environmental noise levels recorded from 21 participants wearing smartwatches and 5 participants using ECG devices in patient rooms (A3) and outdoor areas on the 4th floor of an inpatient ward. Sleep data revealed variations in sleep stages among participants, with an average distribution of 60% wake, 10% REM, 22% light, and 8% deep sleep. Environmental noise levels were measured at different times of day, showing higher levels during the day and lower levels at night, with an average LAeq of 53.4 dB for 24 hours. Comparisons between indoor and outdoor areas and different times of day indicate fluctuations in noise levels, with outdoor areas generally exhibiting higher noise levels. These findings contribute to understanding sleep patterns and noise exposure in healthcare settings, highlighting the need for further research to explore the impact of environmental factors on sleep quality and patient well-being.

This paper reviews studies on the prediction of ductile fracture during metal forming using an ellipsoidal void model and some other models proposed by the author and some relevant studies. Section 2 discusses the research on the theory of voids for predicting ductile fracture during metal forming. Section 3 summarizes the simulation method for predicting ductile fracture during metal forming using the ellipsoidal void model, and Section 4 summarizes the simulation result on the ductile fracture prediction during metal forming using the ellipsoidal void model. Section 5 shows the applicability of the ellipsoidal void model and the simulation result on the ductile fracture prediction during metal forming using some other models.

Binaural and transaural systems are well-known methods of sound field reproduction. However, each system has its own problems such as in-head localization and narrow control points. Therefore, this study aims to design a sound field reproduction system using shoulder-mounted wearable-speakers that can solve these problems. The system is expected to sustain the effect of sound field reproduction even while moving and is expected to be applied in the field of entertainment. This paper shows the head transfer function of the wearable loudspeaker and designs an inverse filter, which is indispensable for the sound field reproduction system, using H∞ control theory.