13197 research outputs found
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Augmented Reality Visual Effects for Mitigating Anxiety of In-person Communication for Individuals with Social Anxiety Disorder
No full textIndividuals with social anxiety disorder (SAD) experience heightened anxiety in in-person communication, particularly when they perceive negative evaluations from their conversation partner based on eye gaze and facial expressions. To address this issue, this study developed an augmented reality (AR) system for in-person conversations, capable of concealing the presence and masking the facial emotions of the conversation partner. An online survey was conducted using Amazon Mechanical Turk (n = 130) to examine the visual effects that individuals with SAD find anxiety-inducing during in-person conversations. 91 out of them have a tendency for SAD. For the aspect of "ease to talk", individuals with SAD achieved significantly higher scores for the visual effects involving a smiley face or anime avatar overlaid onto the conversation partner, as opposed to the remaining visual effects (p < .05). Based on these findings, we developed two prototypes wherein an AR head-mounted display (HMD) overlays either a smiley face or an anime avatar onto the conversation partner during an in-person conversation. A small-scale user study was conducted to investigate participant’s ability to interact with a conversation partner, using these visual effects, as well as their subjective experiences. The results were further analyzed through user interviews. The social
anxiety levels of participants were measured using the Liebowitz Social Anxiety Scale. Participants with SAD exhibited a preference for communicating with an anime avatar rather than real individuals, while participants without SAD preferred real-person interactions. These findings inform future research, wherein the objective (heart rate, eye tracking, self-disclosure) and quantitative data (questionnaires) will be utilized to evaluate anxiety levels during in-person conversations.conference pape
Jamming Gripper-Inspired Soft Jig for Perceptive Parts Fixing
No full textTo achieve precise and time-efficient operation to ensure stable and reliable product assembly, custom-made jigs have been developed for each assembly part. However, designing these jigs is a time-consuming task. Therefore, this study proposes a jamming gripper-inspired flexible jig using a soft membrane consisting of transparent beads and oil with an adjusted refractive index. The proposed jig is equipped with a hydraulic drive system with visual control of the amount of transparent oil inside the jig. The proposed system enables parts fixing by creating a jammed state while maintaining optical transparency, thereby facilitating the visual sensing of the jig’s membrane from camera sensors embedded in the jig. Furthermore, a sensing method was developed to perform a precise assembly without external sensors to estimate the pose of an object based on the proposed point-to-function iterative closest point. The results show that the proposed system successfully estimates the orientation at a root mean square error of less than ang 4 when the position is varied from 0mm to 20mm and the angle is varied from ang 0 to ang 20. Furthermore, it can repeatedly fix the object in any orientation from ang 0 to ang 20 at a position of less than 0.5mm and an angle of less than ang 1.1.journal articl
Oblivious Statistic Collection With Local Differential Privacy in Mutual Distrust
No full textLocation data is valuable for various applications such as epidemiology, natural disasters, and urban planning but causes exposure of sensitive information, e.g., home or work place, from collected data in a datastore. Local Differential Privacy (LDP)-based data collection is a promising technology to protect sensitive information. A mobile device modify data to make each piece of data indistinguishable from others but keep its intrinsic value for statistical characteristics in data. Although LDP fundamentally protects the privacy exposure from a data store, a datastore suffer a shortcomings on it; as a datastore can never validate the modified data due to concealed raw data, that allows anyone to tamper with one’s data or inject any amount of data, and thus manipulate the statistics of the whole data in a datastore, called data poisoning attack. As a device does not disclose raw data and a datastore cannot collaborate to validate data with a device who may be an adversary on this mutual distrust relationship, data collection needs an ability to avoid the effect of data poisoning.. The cause of data poisoning is the direct relationship between data volume and statistic; the more data a device sends gives more statistical changes on merged data in a datastore. In this paper, we propose to decouple statistical characteristics from data volumes on LDP-based data collection process to minimize the effect of poisoned data on a datastore. We utilize Oblivious Transfer (OT) protocol to retrieve only statistic characteristics of receiving data at a datastore. As OT protocol inevitably strengthen privacy protection on LDP-based data collection and accordingly drops statistic characteristics of data, We adjust LDP processing to collaboratively work with OT protocol. The proposed adjustment method adapts the protection strength of LDP to OT protocol behavior so that a data store receives data containing sufficient statistical characteristics. We conduct qualitative and experimental overhead analysis and show that our method decouples the relationship between statistical characteristics from data volume. Our experimental result also prove that the overhead can be acceptable on devices such as smartphones and IoT.journal articl
Experimental Survey on Bridging the Digital Divide Through Daily Text Chat Communication with Virtual Agents
Get PDFTo bridge the digital divide, this study investigates the current state of smartphone use and work to improve smartphone skills by using both online support and on-site support approaches in collaboration with industry, academia, and government. The proposed method aims to improve the frequency of smartphone use and smartphone skills through daily interaction with a virtual agent “Goodchan” using the SNS (LINE) text chat function as online support, as well as to eliminate concerns about smartphone use and improve motivation by conducting on-site smartphone consultation as on-site support. In this effort for dialogue chat, we use the Wizard of Oz method, in which the operator acts as Goodchan, and conducts dialogue chats with the participants. In addition, we proposed a smartphone skill evaluation sheet called SmaSki 2022 to quantitatively evaluate smartphone skills and surveyed changes in the smartphone skills of the participants. As a result, we confirmed that approximately 30% of the 46 elderly participants improved their smartphone skills during the six-month demonstration experiment at Shij$014Dnawate-city in Japan.conference pape
Development of 4-μm-pixel Pitch NIR Multispectral Imaging Sensor and Its Application to Glare-free NIR Color Fundus Camera
No full textIn this study, we describe the development of a compact NIR multispectral imaging sensor for use in glare-free NIR color fundus cameras. Integrating NIR technology into a fundus camera offers significant advantages over conventional RGB imaging using visible illumination, as it enables the glare-free capture of fundus images with minimal patient discomfort. The specifications necessary for a glare-free NIR color fundus camera were evaluated on the basis of factors such as pixel pitch size, pixel array layout, and multilayer interference filter design, in accordance with the camera’s intended purpose. While multilayer interference filters were deposited on a glass substrate and bonded with the sensor chip in a 7.5 μm pixel pitch in a previous study, we propose an NIR multispectral imaging sensor directly depositing the interference filters on the wafer in a narrower 4 μm pixel pitch. In addition, the fabrication process for directly depositing NIR multispectral filters on the sensor wafer was proposed. The fabricated NIR multispectral imaging sensor was analyzed against the intended design. Finally, an NIR multispectral imaging sensor was installed on a glare-free NIR color fundus camera, and it was confirmed that the resulting camera is capable of providing medically relevant and meaningful information.research repor
Adaptation of yeast Saccharomyces cerevisiae to grape-skin environment
No full textSaccharomyces cerevisiae, an essential player in alcoholic fermentation during winemaking, is rarely found in intact grapes. Although grape-skin environment is unsuitable for S. cerevisiae’s stable residence, Saccharomycetaceae-family fermentative yeasts can increase population on grape berries after colonization during raisin production. Here, we addressed adaptation of S. cerevisiae to grape-skin ecosystem. The yeast-like fungus Aureobasidium pullulans, a major grape-skin resident, exhibited broad spectrum assimilation of plant-derived carbon sources, including ω-hydroxy fatty acid, arising from degradation of plant cuticles. In fact, A. pullulans encoded and secreted possible cutinase-like esterase for cuticle degradation. When intact grape berries were used as a sole carbon source, such grape-skin associated fungi increased the accessibility to fermentable sugars by degrading and assimilating the plant cell wall and cuticle compounds. Their ability seems also helpful for S. cerevisiae to obtain energy through alcoholic fermentation. Thus, degradation and utilization of grape-skin materials by resident microbiota may account for their residence on grape-skin and S. cerevisiae’s possible commensal behaviors. Conclusively, this study focused on the symbiosis between grape-skin microbiota and S. cerevisiae from the perspective of winemaking origin. Such plant$2013microbe symbiotic interaction may be a prerequisite for triggering spontaneous food fermentation.journal articl
Heat illness detection with heart rate variability analysis and anomaly detection algorithm
No full textObjective:
Incidence of heat illness has been increasing dramatically due to the progression of global warming. Preventing severe heat illness, called heatstroke, is crucial because it can lead to long-term multiple organ damage, including the brain, and results in more than 600 deaths per year in the United States. It has been reported that heat stress affects heart rate variability (HRV), which is the fluctuations of the R-R interval (RRI) on an electrocardiogram (ECG). We propose a method for detecting symptoms of heat illness based on HRV analysis in order to prevent exacerbation of heat illness.
Methods:
In the proposed method, monitoring abnormal changes in HRV caused by heat stress is monitored. Multivariate statistical process control (MSPC), a commonly used anomaly detection method in machine learning, is adopted for training the heat illness detection method. To validate the proposed method, we recruited 103 healthy volunteers with risks of heat illness development: employees working in hot environments, athletes, and amateur marathon runners. Data collection was performed using our wearable heart rate sensor and smartphone app.
Results:
The result of applying the proposed method showed that a sensitivity of 75% (21 out of 28 cases) and a false-positive rate of 1.02 times per hour were achieved.
Conclusion:
The proposed heat illness detection method will be used in daily life because RRI data can be easily measured by a wearable sensor.
Significance:
The proposed method will contribute to receiving appropriate treatment for heat illness before exacerbation, which contributes to protecting people’s health.journal articl
Movement recognition via channel-activation-wise sEMG attention
No full textContext: Surface electromyography (sEMG) signals contain rich information recorded from muscle movements and therefore reflect the user's intention. sEMG has seen dominant applications in rehabilitation, clinical diagnosis as well as human engineering, etc. However, current feature extraction methods for sEMG signals have been seriously limited by their stochasticity, transiency, and non-stationarity.
Objective: Our objective is to combat the difficulties induced by the aforementioned downsides of sEMG and thereby extract representative features for various downstream movement recognition.
Method: We propose a novel 3-axis view of sEMG features composed of temporal, spatial, and channel-wise summary. We leverage the state-of-the-art architecture Transformer to enforce efficient parallel search and to get rid of limitations imposed by previous work in gesture classification. The transformer model is designed on top of an attention-based module, which allows for the extraction of global contextual relevance among channels and the use of this relevance for sEMG recognition.
Results: We compared the proposed method against existing methods on two Ninapro datasets consisting of data from both healthy people and amputees. Experimental results show the proposed method attains the state-of-the-art (SOTA) accuracy on both datasets. We further show that the proposed method enjoys strong generalization ability: a new SOTA is achieved by pretraining the model on a different dataset followed by fine-tuning it on the target dataset.journal articl
Composition Regulation by Flow Copolymerization of Methyl Methacrylate and Glycidyl Methacrylate with Free Radical Method
No full textIt is important to match the feeding ratio of comonomers to the composition ratio in the resulting copolymers as closely as possible in industrial production, where the goal is often to produce more a homogeneous composition in copolymers. In this study, a flow copolymerization system with a conventionally initiated free radical method, together with randomly selected polymerization conditions is investigated. It is succeeded in achieving a closer match between the composition ratio and feeding ratio than previously reported in the copolymerization of styrene with methyl methacrylate and of glycidyl methacrylate with methyl methacrylate, which will widen the range of applications, by precisely controlling the mixing and heating in a flow polymerization apparatus. This is confirmed by the fact that the estimated values of reactivity ratios, r1 and r2, which are used in the reaction kinetics of copolymerization, are close to 1.journal articl