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This paper presents a multi-physics analysis coupling the electrical and thermal properties of a power module. As power modules have multi-physical behaviors, it is important to simulate their multi-physical characteristics. Simulations of these characteristics have been separately conducted using specific software; however, as these characteristics are often coupled, it is difficult to fully understand the multi-physical nature of power modules. This paper proposes a method to analyze the coupled characteristics of a power module in an iterative manner. The analyzed module is designed for an automotive electric power steering (EPS) system. We fabricated the EPS module and measured its electrical and thermal characteristics, which were used for reference. For the coupled simulation, we employed ANSYS Icepak and Q3D Extractor for thermal and electrical simulations, respectively, linked them to the ANSYS workbench environment, and conducted an iterative feedback simulation until the simulated results converged. The coupled simulation demonstrated that the parasitic resistance and volume loss density of the power module are increased by ~50% compared to the those obtained from a separately conducted electrical simulation due to the impact of the linked thermal simulation. As a result, the simulated thermal resistance increased to 0.26 K/W, which is almost identical to the measured value of ~0.27 K/W. Therefore, our iterative electrical–thermal coupled simulation exhibits more accurate results than the conventional separate simulations.

Automotive Lidar sensors are highly susceptible to their environment. One of its major limitations results from the effects of rain environments, which should be seriously considered while designing a Lidar system. This study addresses the impact of rain on the Lidar system by considering the raindrop distributions of different regions. The regional distributions are derived from the rainfall data of three locations, which were reported by previous works, and converted using the constrained-gamma model. The regional distribution reveals different characteristics of raindrops, such as sizes, shapes, and numbers. The derived raindrop distributions are imported to a custom-built Lidar model, providing three models representing the three regions. The simulation results demonstrate that the signal power received by a Lidar attenuates, which is modeled using Mie scattering theory, and the amount of attenuation clearly differs in the regional models. Therefore, the attenuation characteristics change according to the regions; consequently, their effect on the Lidar sensor performances are quantitatively evaluated. In addition, the custom-built Lidar model is mounted on a virtual vehicle, which is simulated using a commercial automobile testing software, PreScan. The driving simulation also demonstrates similar conclusion that the regional raindrop distribution is critical in determining the Lidar performances.

This study employs a dual deep neural network (D-DNN) to accurately estimate the absolute longitudinal speed of a vehicle. Accuracy in speed estimation is crucial for vehicle safety, because longitudinal speed is a common parameter employed as a state variable in active safety systems such as anti-lock braking system and traction control system. In this study, DNNs are applied to determine the gain of an adaptive filter to estimate vehicle speed. The used data consists of longitudinal acceleration, wheel speed, filter gain, and estimated vehicle speed. The data generated from Carsim software are collected and preprocessed using a Simulink model. To acquire data with numerous wheel slip patterns, various acceleration and deceleration conditions are applied to four different road conditions. Though, it is challenging to achieve a single DNN model that is optimally cope with the various driving situations. Thus, we adopt two DNN models that were individually trained in low and high acceleration regions. The dual DNN model results in error reductions of 74% and 65%, compared with a single DNN and classical adaptive Kalman filter approaches, respectively.

Background/Aims There is insufficient quality data to recommend the use of herbs for the treatment of acute bronchitis. Small number of randomized trials of plant extracts for this purpose were determined to be low quality and there are concerns for the safety. HL301 is a combined product of seven medicinal plants. In the present study, we tried to evaluate the efficacy and safety of HL301 for the treatment of acute bronchitis with a randomized, double-blind, placebo-controlled, multicenter trial design. Methods A total of 166 patients with acute bronchitis were randomized to receive placebo or HL301 (600 mg/day) for 7 days. The primary endpoint was change in bronchitis severity score (BSS) from baseline visit (visit 2) to the end of treatment (visit 3). Other efficacy variables were the change of each component of the BSS (cough, sputum, dyspnea, chest pain, and crackle) with treatment, response rate, improvement rate, satisfaction rate and number of rescue medications taken. Results Changes in the BSS from visit 2 to visit 3 were higher in the HL301 group than in the placebo group both in the full analysis set (4.57 ± 1.82 vs. 3.15 ± 3.08, p < 0.01) and in the per protocol set (4.62 ± 1.81 vs. 3.30 ± 3.03, p < 0.01). Four BSS components (cough, sputum, dyspnea, and chest pain) improved more with HL301 treatment than with placebo treatment. Participants treated with HL301 showed higher response, improvement, and satisfaction rates and less use of rescue medication than the placebo group. Conclusions HL301 (600 mg/day) was effective and safe for symptomatic treatment of acute bronchitis.

Objective: Studies have reported several treatment modalities for patients with lumbosacral radicular pain. However, the available evidence is not robust to establish definitive conclusions. The goal of this study was to evaluate the clinical efficacy of pulsed radiofrequency (PRF) treatment in patients with lumbosacral radicular pain. Methods: We have retrospectively reviewed and analyzed lumbosacral radicular pain in 34 patients who underwent PRF treatment at our institute. Diagnostic selective nerve root block was performed and patients who experienced more than 50% pain reduction were exposed to PRF. Pain relief was evaluated based on visual analog scale (VAS) scores at pre-treatment, 2 weeks, 3 and 6 months post-treatment. A success group and outcome were defined by more than 50% reduction in VAS scores at 6 months. Results: Successful outcome was achieved in 47% of patients. None of the patients had any side effects or procedure-related complications during the follow-up. Sex, number of lesions of treatment and pre-treatment VAS score showed no statistically significant differences between success and failure groups. The age of success group (52.9 ± 17.30 years) was significantly (P

Background The 2016 Society of Critical Care Medicine (SCCM)/European Society of Intensive Care Medicine (ESICM) task force for Sepsis-3 devised new definitions for sepsis, sepsis with organ dysfunction and septic shock. Although Sepsis-3 was data-driven, evidence-based approach, East Asian descents comprised minor portions of the project population. Methods We selected Korean participants from the fever and antipyretics in critically ill patients evaluation (FACE) study, a joint study between Korea and Japan. We calculated the concordance rates for sepsis diagnosis between Sepsis-2 and Sepsis-3 criteria and evaluated mortality rates of sepsis, sepsis with organ dysfunction, and septic shock by Sepsis-3 criteria using the selected data. Results Korean participants of the FACE study were 913 (383 with sepsis and 530 without sepsis by Sepsis-2 criteria). The concordance rate for sepsis diagnosis between Sepsis-2 and Sepsis-3 criteria was 55.4%. The intensive care unit (ICU) and 28-day mortality rates of sepsis, sepsis with organ dysfunction, and septic shock patients according to Sepsis-3 criteria were 26.2% and 31.0%, 27.5% and 32.5%, and 40.8% and 43.4%, respectively. The quick Sequential Organ Failure Assessment (qSOFA) was inferior not only to SOFA but also to systemic inflammatory response syndrome (SIRS) for predicting ICU and 28-day mortality. Conclusions The concordance rates for sepsis diagnosis between Sepsis-2 and Sepsis-3 criteria were low. Mortality rate for septic shock in Koreans was consistent with estimates made by the 2016 SCCM/ESICM task force. SOFA and SIRS were better than qSOFA for predicting ICU and 28-day mortality in Korean ICU patients.

Faults in vehicle sensor connectors are crucial to the safety of a vehicle. Once the connector is loosened according to the reduction of its contact forces, its electrical contact resistance may be increased, causing unexpected errors in sensor systems. However, such error mechanisms have enormously diverse causes that have not yet been identified. This study proposes a process to analyze the causes influencing the connector contact force and resistance by employing a combination of numerical and experimental methods. Specifically, the causes of variation of contact force are numerically analyzed and their influence on the electrical contact resistance is experimentally studied. Precise 3D models of a commercial vehicle sensor connector are developed based on a 3D tomography, and a 3D finite element (FE) simulation is employed to estimate the connector contact force, considering plastic deformation. After classifying potential causes into three categories, two major factors are selected: manufacturing tolerance occurring during the connector manufacturing process and plastic deformation occurring during the vehicle maintenance process. The factors are observed to substantially reduce the contact force (by ~14.6 or 19%). The impact of the reduced contact force is validated in sequential experiments, and exhibits a nonlinear relationship between the contact force and corresponding contact resistance. In addition, the experiments also consider simulated manufacturing and maintenance factors, and demonstrate an increased contact resistance by the functions of the decreased contact force with minor measurement errors (

Objectives Regenerative treatment using stem cells may serve as treatment option for empty nose syndrome (ENS), which is caused by the lack of turbinate tissue and deranged nervous system in the nasal cavity. We aimed to assess the efficacy and safety of the autologous stromal vascular fraction (SVF) in the treatment of ENS. Methods In this prospective observational clinical study, we enrolled 10 ENS patients who volunteered to undergo treatment of ENS through the injection of autologous SVF. Data, including demographic data, pre- and postoperative Sino-Nasal Outcome Test-25 (SNOT-25) scores, overall patient satisfaction, and postoperative complications, were prospectively collected. Nasal secretion was assessed using the polyurethane foam absorption method, and the levels of biological markers were analyzed in both ENS group and control group using enzyme-linked immunosorbent assay. The SVF extracted from abdominal fat was diluted and injected into both inferior turbinates. Results Among the 10 initial patients, one was excluded from the study. Subjective satisfaction was rated as “much improved” in two and “no change” in seven. Among the improved patients, the mean preinjection SNOT-25 score was 55.0 and the score at 6 months after injection was 19.5. However, the average SNOT-25 score of nine participants at 6 months after injection (mean±standard deviation, 62.4±35.8) did not differ significantly from the baseline SNOT25 score (70.1±24.7, P>0.05, respectively). Among the various inflammatory markers assessed, the levels of interleukin (IL)-1β, IL-8, and calcitonin gene-related peptide were significantly higher in ENS patients. Compared with preinjection secretion level, the nasal secretions from SVF-treated patients showed decreased expressions of IL-1β and IL-8 after injection. Conclusion Although SVF treatment appears to decrease the inflammatory cytokine levels in the nasal mucosa, a single SVF injection was not effective in terms of symptom improvement and patient satisfaction. Further trials are needed to identify a more practical and useful regenerative treatment modality for patients with ENS.

In this paper, we propose an automatic cell counting framework for stimulated Raman scattering (SRS) images, which can assist tumor tissue characteristic analysis, cancer diagnosis, and surgery planning processes. SRS microscopy has promoted tumor diagnosis and surgery by mapping lipids and proteins from fresh specimens and conducting a fast disclose of fundamental diagnostic hallmarks of tumors with a high resolution. However, cell counting from label-free SRS images has been challenging due to the limited contrast of cells and tissue, along with the heterogeneity of tissue morphology and biochemical compositions. To this end, a deep learning-based cell counting scheme is proposed by modifying and applying U-Net, an effective medical image semantic segmentation model that uses a small number of training samples. The distance transform and watershed segmentation algorithms are also implemented to yield the cell instance segmentation and cell counting results. By performing cell counting on SRS images of real human brain tumor specimens, promising cell counting results are obtained with > 98% of area under the curve (AUC) and R = 0.97 in terms of cell counting correlation between SRS and histological images with hematoxylin and eosin (H&E) staining. The proposed cell counting scheme illustrates the possibility and potential of performing cell counting automatically in near real time and encourages the study of applying deep learning techniques in biomedical and pathological image analyses.

BACKGROUND:Severe centrum semiovale perivascular spaces (CSO-PVSs) are associated with the onset of brain atrophy and dementia. This study explored the relationship between severity of CSO-PVS and development of subdural fluid (SDF) in patients with mild traumatic brain injury (TBI), with the aim of investigating independent radiological risk factors for development of SDF. METHODS:The study cohort comprised 222 patients with a mean age of 51 years (64.0% men) who presented with mild TBI from January 2013 to November 2016. In this study, mild TBI was defined as a Glasgow Coma Scale (GCS) of ≥ 13, Post-Traumatic Amnesia (PTA) of

In this paper, an approach to determine the thermal impedance of a multi-chip silicon carbide (SiC) power module is proposed, by fusing optical measurement and multi-physics simulations. The tested power module consists of four parallel SiC metal-oxide semiconductor field-effect transistors (MOSFETs) and four parallel SiC Schottky barrier diodes. This study mainly relies on junction temperature measurements performed using fiber optic temperature sensors instead of temperature-sensitive electrical parameters (TESPs). However, the fiber optics provide a relatively slow response compared to other available TSEP measurement methods and cannot detect fast responses. Therefore, the region corresponding to undetected signals is estimated via multi-physics simulations of the power module. This method provides a compensated cooling curve. We analyze the thermal resistance using network identification by deconvolution (NID). The estimated thermal resistance is compared to that obtained via a conventional method, and the difference is 3.8%. The proposed fusion method is accurate and reliable and does not require additional circuits or calibrations.

Human hand gestures are a widely accepted form of real-time input for devices providing a human-machine interface. However, hand gestures have limitations in terms of effectively conveying the complexity and diversity of human intentions. This study attempted to address these limitations by proposing a multi-modal input device, based on the observation that each application program requires different user intentions (and demanding functions) and the machine already acknowledges the running application. When the running application changes, the same gesture now offers a new function required in the new application, and thus, we can greatly reduce the number and complexity of required hand gestures. As a simple wearable sensor, we employ one miniature wireless three-axis gyroscope, the data of which are processed by correlation analysis with normalized covariance for continuous gesture recognition. Recognition accuracy is improved by considering both gesture patterns and signal strength and by incorporating a learning mode. In our system, six unit hand gestures successfully provide most functions offered by multiple input devices. The characteristics of our approach are automatically adjusted by acknowledging the application programs or learning user preferences. In three application programs, the approach shows good accuracy (90−96%), which is very promising in terms of designing a unified solution. Furthermore, the accuracy reaches 100% as the users become more familiar with the system.

ObjectivesIn the present study, we investigated whether speech-related cognitive function and speech recognition ability under background noise in adults with hearing impairment are improved with the use of hearing aids.MethodsParticipants were recruited from the ENT Department of Eulji Hospital from September 2008 to July 2009. The study group comprised 18 participants (mean age, 69.5±8.3 years) with sensorineural hearing loss who were fitted with hearing aids, and the control group comprised 11 participants of equivalent age (mean age, 63.1±11.8 years) who were not fitted with hearing aids. All participants were assessed using the computerized Korean visual verbal learning test (VVLT) and words-in-noise (WIN) test prior to fitting of hearing aids for the study group and initially for the control group. Both groups were reassessed in both tests after 6 months. For each group, differences in the results between the two assessments were compared using the Friedman test.ResultsThere was no difference in mean age between the study group and control group. In the study group, total VVLT score (reflecting short-term memory) was significantly improved from before hearing aid use to 6 months after hearing aid use (P0.05).ConclusionThe speech-related cognitive function of individuals with hearing impairment improved after using hearing aids. This finding indicates that hearing aids may induce acclimatization of the central auditory system.

ObjectivesTo evaluate that the cross-sectional area of the air space in the Eustachian tube (ET) on computed tomography (CT) images could be useful for predicting the postoperative aeration of the middle ear.MethodsThe patient group consisted of 80 patients (80 ears) with chronic otitis media and who underwent middle ear surgery from 2006-2007 and who were followed up for more than 1 yr. The control group consisted of 100 ears of 50 individuals with normal tympanic membranes and who underwent CT for other causes (such as tinnitus or hearing loss). The largest cross-sectional areas of the aerated ET were measured on the coronal images of the temporal bone CT by a single otologist using the computer-based "Region of Interest" picture archiving and communications system. The patient group was divided into two subgroups, 1) those with good postoperative aeration and 2) those with poor postoperative aeration. The largest cross-sectional areas of the aerated ETs were compared between the patients and the controls, and between the patients with good aeration and the patients with poor aeration.ResultsThe mean cross-sectional areas significantly differed between the patient group and the control group, and between the good and poor aeration subgroups (P

ObjectivesTo compare tinnitus patients who have normal hearing between 250 Hz and 8 kHz with normal controls with regard to the ability of each group to hear extended high-frequency pure tone thresholds.MethodsWe enrolled 18 tinnitus patients, each of whom had a threshold of HL