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Parkinson disease is characterized by dopaminergic cell loss in the substantia nigra of the midbrain. There are various imaging markers for Parkinson disease. Recent advances in MRI have enabled elucidation of the underlying pathophysiologic changes in the nigral structure. This has contributed to accurate and early diagnosis and has improved disease progression monitoring. This article aims to review...
In this paper, we employ a dynamics modeling method for investigating a multi-body dynamics system consisting of an unmanned surface vehicle (USV), an umbilical cable (UC), and an autonomous underwater vehicle (ROV). The ROV, which is towed by a UC for the purposes of exploration or mine hunting, is modeled with a Six-Degree-of-Freedom (6-DOF) equation of motion that reflects its hydrodynamics characteristics...
There is a possibility that vast amounts of undersea resources are buried beneath Japanese territorial sea. In order to find these undersea resources, a detailed topography including specific objects and events of seabed should be carefully surveyed. One of effective methods for this is to use seabed visualization technologies, which are applied to an autonomous underwater vehicle (AUV). Therefore,...
The underwater vehicle-manipulator system (UVMS) generally has more degrees of freedom than those required to perform a given task. Because of these extra of degrees of freedom, UVMS has infinite combinations of joint velocities. In this paper, in order to generate the joint angle trajectories of the manipulator, a redundancy resolution is performed to minimize the distance between the position of...
To enhance the safety of various marine operations in many coastal regions, ocean weather monitoring and prediction systems are playing an increasingly important role over the last couple of decades. To provide marine forecasts in Cook Inlet, Alaska, which has extremely complex geometry and the largest tidal fluctuations has in the U.S., a wave forecasting system is developed. High-resolution 36-hour...
Brain-computer interface (BCI) has been used as a communication tool to enable paralyzed people to interact with the world. Its application has been extended to other non-medical areas like self-regulation, marketing, games and entertainment. Conventionally, BCI largely relies on the visual perception channel to provide users with cues or stimuli for the generation of appropriate brain signals that...
Motor imagery (MI) based on brain computer interfaces (BCIs) have been widely applied for upper limb motor rehabilitation. Due to the fact that a large number of disabled people need to restore or improve walking ability, it is also important to investigate the use of MI-based BCIs for lower limb motor rehabilitation. The brain activity of lower limb MI is more difficult to detect because of low reliability...
This paper presents a study that evaluates the performance of multi-view human activity recognition with videos having degraded quality. For the activity recognition models, a support vector machine-based approach using spatiotemporal features and a deep learning-based approach using convolutional and recurrent layers are built. We investigate the recognition performance of the two models with respect...
Three-dimensional (3D) ultrasound is extensively used in obstetrics and gynecology, and realistic rendering results can both enhance the accuracy of diagnosis and facilitate communication between obstetricians and pregnant women. This paper proposes an interactive and realistic rendering method using global illumination effects for 3D ultrasound images with low signal-to-noise-ratio (SNR) values....
This work presents an ultra-low phase noise and all-digital frequency generator, providing multiple output-frequencies. In a time-interleaved fashion, the proposed calibrator can continue to correct the multiple output-frequencies of injection-locked DCOs, which can change independently between 0.9 and 1.2GHz. Due to the time-interleaved calibrator, operating continuously in the background, each injection-locked...
High-level synthesis (HLS) tools have vastly increased the productivity of field-programmable gate array (FPGA) programmers with design automation and abstraction. However, the side effect is that many architectural details are hidden from the programmers. As a result, programmers who wish to improve the performance of their design often have difficulty identifying the performance bottleneck. It is...
Quadrotor unmanned aerial vehicles (UAVs) have seen a surge of use in various applications due to its structural simplicity and high maneuverability. However, conventional control methods using joysticks prohibit novices from getting used to maneuvering quadrotors in short time. In this paper, we suggest the use of a wearable device, such as a smart watch, as a new remote-controller for a quadrotor...
This paper presents a connectivity control algorithm of a multi-agent system. The connectivity of the multi-agent system can be represented by the second smallest eigenvalue λ2 of the Laplacian matrix LG and it is also referred to as algebraic connectivity. Unlike many of the existing connectivity control algorithms which adapt convex optimization technique to maximize algebraic connectivity, we first...
Hand gesture recognition is one of the secure natural user interface (NUI) mechanisms on wearable devices since it does not reveal user's intention in public domain unlike the speech recognition. However, its energy dissipation is very demanding as it requires compute-intensive machine vision processing. Recently, wake-up detectors have been proposed to improve the energy-efficiency of always-on sensing...
A robust enterprise SSD design should provide scalable throughput and storage capacity by integrating (up to thousands) flash chips in a scale-out fashion. However, the current "channel-based" SSD architecture is not a scalable design choice to allow such a dense integration. Motivated by the inherent architectural scalability of PCIe, we propose UT-SSD, a novel enterprise-scale scale-out...
IoT smart energy management is to maximize energy efficiency through energy information collection, energy DR management and energy sharing/trading by developing IoT-based smart energy platform technology. IoT smart energy management services provide energy efficiency enhancement, energy sharing and trading services through interconnection and integration of energy supply-transfer-utilization energy...
The present paper allows to hybrid energy management for community energy system facilities. Energy management system is enabled cost savings through efficient use of energy. Active initiatives for energy management begin from the baseline of energy use. Given the vast amount of data and comparable systematized information gathered from greenhouse gas and energy IT systems, it is possible to reduce...
This paper presents an efficient unipolar stochastic computing hardware for convolutional neural networks (CNNs). It includes stochastic ReLU and optimized max function, which are key components in a CNN. To avoid the range limitation problem of stochastic numbers and increase the signal-to-noise ratio, we perform weight normalization and upscaling. In addition, to reduce the overhead of binary-to-stochastic...
This research presents a scheme for explainable sleep quality evaluation utilizing the heart rate based sleep index. In the proposed model, the global covering rule induction of LERS (Learning from Examples based on Rough Sets) is used to generate rules associated with sleep quality status, such as ‘Bad,’ ‘Normal,’ and ‘Good.’ These rules are used to interpret the three sleep statuses. To show the...
Purpose of this study was to develop a fall prediction model based on various variables with linear and nonlinear analysis using postural sway. The included variables in the regression model were Sample Entropy, Largest Lyapunov exponent and Hurst exponent in anterior-posterior direction, which are nonlinear variables. Accuracy of this regression model for fall prediction was 81.9%.
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