• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.459-464
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• 2024

The purpose of this study is to design a toilet lifting seat to prevent falls accidents in the elderly while using the toilet. Prior to design, laws and national standards related to restroom use were investigated and the available space for the assistive devices to be installed was determined. In additions, considering the body size and operating range of the elderly, the optimal final position of the toilet seat is set so that users can use it more safely and conveniently without external help. Moreover, in order to provide an effective standing assistance function, a complex 4-bar link structure was applied to enable simultaneous seat elevation and angle adjustment when operating the device, and the appropriate link shape and dimensions were determined using a linkage program and UG NX. FEA analysis using ANSYS Workbench is performed to ensure the robustness of the stretched linkage and the feasibility of the lifting seat is verified through fabrication.

• Progress in Medical Physics
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• v.14 no.3
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• pp.151-160
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• 2003

The application of more complex radiotherapy techniques using multileaf collimation (MLC), such as 3D conformal radiation therapy and intensity-modulated radiation therapy (IMRT), has increased the significance of verifying leaf position and motion. Due to thier reliability and empirical robustness, quality assurance (QA) of MLC. However easy use and the ability to provide digital data of electronic portal imaging devices (EPIDs) have attracted attention to portal films as an alternatives to films for routine qualify assurance, despite concerns about their clinical feasibility, efficacy, and the cost to benefit ratio. In this study, we developed method for daily QA of MLC using electronic portal images (EPIs). EPID availability for routine QA was verified by comparing of the portal films, which were simultaneously obtained when radiation was delivered and known prescription input to MLC controller. Specially designed two-test patterns of dynamic MLC were applied for image acquisition. Quantitative off-line analysis using an edge detection algorithm enhanced the verification procedure as well as on-line qualitative visual assessment. In conclusion, the availability of EPI was enough for daily QA of MLC leaf position with the accuracy of portal films.

• Journal of Satellite, Information and Communications
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• v.7 no.3
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• pp.99-104
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• 2012

The United States will proceed with the effort to modernize the GPS system, and one of its main content is to provide L5 signal. L5 will be transmitted in a radio band reserved exclusively for aviation safety services. And, L5, in combination with L1, will improve the position accuracy via ionospheric correction and robustness via signal redundancy. However, The acquisition processing time of L5 takes longer than that of L1 as the code length of L5 is 10 times longer than that of L1. To reduce this acquisition processing time, a higher number of correlators in the aquisition module should be used. However, there is a problem that this causes increase in the complexity of the correlator configuration and the computation power. So, in this paper, we propose L5 signal tracking scheme using tracking results in the GPS L1/L5 receiver. The proposed scheme could reduce the hardware complexity as the GPS L5 signal acquisition module is not needed, and provide fast and stable tracking of L5 signal by aiding L1 tracking results such as PRN, the code phase synchronization, and the Doppler frequency. The feasibility of the proposed scheme is demonstrated through simulation results.

• The Journal of the Acoustical Society of Korea
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• v.35 no.1
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• pp.74-82
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• 2016

In this paper, a new automatic speech recognition (ASR) was proposed where ultrasonic doppler signals were used, instead of conventional speech signals. The proposed method has the advantages over the conventional speech/non-speech-based ASR including robustness against acoustic noises and user comfortability associated with usage of the non-contact sensor. In the method proposed herein, 40 kHz ultrasonic signal was radiated toward to the mouth and the reflected ultrasonic signals were then received. Frequency shift caused by the doppler effects was used to implement ASR. The proposed method employed multi-channel ultrasonic signals acquired from the various locations, which is different from the previous method where single channel ultrasonic signal was employed. The PCA(Principal Component Analysis) coefficients were used as the features of ASR in which hidden markov model (HMM) with left-right model was adopted. To verify the feasibility of the proposed ASR, the speech recognition experiment was carried out the 60 Korean isolated words obtained from the six speakers. Moreover, the experiment results showed that the overall word recognition rates were comparable with the conventional speech-based ASR methods and the performance of the proposed method was superior to the conventional signal channel ASR method. Especially, the average recognition rate of 90 % was maintained under the noise environments.

• Journal of Biosystems Engineering
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• v.26 no.1
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• pp.21-28
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• 2001

Major deficiencies of current automation scheme including various robots for bioproduction include the lack of task adaptability and real time processing, low job performance for diverse tasks, and the lack of robustness of take results, high system cost, failure of the credit from the operator, and so on. This paper proposed a scheme that could solve the current limitation of task abilities of conventional computer controlled automatic system. The proposed scheme is the man-machine hybrid automation via tele-operation which can handle various bioproduction processes. And it was classified into two categories. One category was the efficient task sharing between operator and CCM(computer controlled machine). The other was the efficient interface between operator and CCM. To realize the proposed concept, task of the object identification and extraction of 3D coordinate of an object was selected. 3D coordinate information was obtained from camera calibration using camera as a measurement device. Two stereo images were obtained by moving a camera certain distance in horizontal direction normal to focal axis and by acquiring two images at different locations. Transformation matrix for camera calibration was obtained via least square error approach using specified 6 known pairs of data points in 2D image and 3D world space. 3D world coordinate was obtained from two sets of image pixel coordinates of both camera images with calibrated transformation matrix. As an interface system between operator and CCM, a touch pad screen mounted on the monitor and remotely captured imaging system were used. Object indication was done by the operator’s finger touch to the captured image using the touch pad screen. A certain size of local image processing area was specified after the touch was made. And image processing was performed with the specified local area to extract desired features of the object. An MS Windows based interface software was developed using Visual C++6.0. The software was developed with four modules such as remote image acquisiton module, task command module, local image processing module and 3D coordinate extraction module. Proposed scheme shoed the feasibility of real time processing, robust and precise object identification, and adaptability of various job and environments though selected sample tasks.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.5
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• pp.503-514
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• 2016

Delineation of accurate object boundaries is crucial to provide reliable spatial information products such as digital topographic maps, building models, and spatial database. In LiDAR(Light Detection and Ranging) data, real boundaries of the buildings exist somewhere between outer-most points on the roofs and the closest points to the buildings among points on the ground. In most cases, areas of the building footprints represented by LiDAR points are smaller than actual size of the buildings because LiDAR points are located inside of the physical boundaries. Therefore, building boundaries determined by points on the roofs do not coincide with the actual footprints. This paper aims to estimate accurate boundaries that are close to the physical boundaries using airborne LiDAR data. The accurate boundaries are determined from the non-gridded original LiDAR data using initial boundaries extracted from the gridded data. The similar method implemented in this paper is also found in demarcation of the maritime boundary between two territories. The proposed method consists of determining initial boundaries with segmented LiDAR data, estimating accurate boundaries, and accuracy evaluation. In addition, extremely low density data was also utilized for verifying robustness of the method. Both simulation and real LiDAR data were used to demonstrate feasibility of the method. The results show that the proposed method is effective even though further refinement and improvement process could be required.

• Korean Journal of Radiology
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• v.21 no.7
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• pp.869-879
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• 2020

Objective: To evaluate the performance of a convolutional neural network (CNN) model that can automatically detect and classify rib fractures, and output structured reports from computed tomography (CT) images. Materials and Methods: This study included 1079 patients (median age, 55 years; men, 718) from three hospitals, between January 2011 and January 2019, who were divided into a monocentric training set (n = 876; median age, 55 years; men, 582), five multicenter/multiparameter validation sets (n = 173; median age, 59 years; men, 118) with different slice thicknesses and image pixels, and a normal control set (n = 30; median age, 53 years; men, 18). Three classifications (fresh, healing, and old fracture) combined with fracture location (corresponding CT layers) were detected automatically and delivered in a structured report. Precision, recall, and F1-score were selected as metrics to measure the optimum CNN model. Detection/diagnosis time, precision, and sensitivity were employed to compare the diagnostic efficiency of the structured report and that of experienced radiologists. Results: A total of 25054 annotations (fresh fracture, 10089; healing fracture, 10922; old fracture, 4043) were labelled for training (18584) and validation (6470). The detection efficiency was higher for fresh fractures and healing fractures than for old fractures (F1-scores, 0.849, 0.856, 0.770, respectively, p = 0.023 for each), and the robustness of the model was good in the five multicenter/multiparameter validation sets (all mean F1-scores > 0.8 except validation set 5 [512 x 512 pixels; F1-score = 0.757]). The precision of the five radiologists improved from 80.3% to 91.1%, and the sensitivity increased from 62.4% to 86.3% with artificial intelligence-assisted diagnosis. On average, the diagnosis time of the radiologists was reduced by 73.9 seconds. Conclusion: Our CNN model for automatic rib fracture detection could assist radiologists in improving diagnostic efficiency, reducing diagnosis time and radiologists' workload.

• Microbiology and Biotechnology Letters
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• v.37 no.4
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• pp.377-382
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• 2009

Viral safety is an important prerequisite for clinical preparations of all biopharmaceuticals derived from plasma, cell lines, or tissues of human or animal origin. To ensure the safety, implementation of multiple viral clearance (inactivation and/or removal) steps has been highly recommended for manufacturing of biopharmaceuticals. Of the possible viral clearance strategies, Ultraviolet-C (UVC) irradiation has been known as an effective viral inactivating method. However it has been dismissed by biopharmaceutical industry as a result of the potential for protein damage and the difficulty in delivering uniform doses. Recently a continuous flow UVC reactor (UVivatec) was developed to provide highly efficient mixing and maximize virus exposure to the UV light. In order to investigate the effectiveness of UVivatec to inactivate viruses without causing significant protein damage, the feasibility of the UVC irradiation process was studied with a commercial therapeutic protein. Recovery yield in the optimized condition of $3,000\;J/m^2$ irradiation was more than 98%. The efficacy and robustness of the UVC reactor was evaluated with regard to the inactivation of human immunodeficiency virus (HIV), hepatitis A virus (HAV), bovine herpes virus (BHV), bovine viral diarrhea virus (BVDV), porcine parvovirus (PPV), bovine parvovirus (BPV), minute virus of mice (MVM), reovirus type 3 (REO), and bovine parainfluenza virus type 3 (BPIV). Non enveloped viruses (HAV, PPV, BPV, MVM, and REO) were completely inactivated to undetectable levels by $3,000\;J/m^2$ irradiation. Enveloped viruses such as HIV, BVDV, and BPIV were completely inactivated to undetectable levels. However BHV was incompletely inactivated with slight residual infectivity remaining even after $3,000\;J/m^2$ irradiation. The log reduction factors achieved by UVC irradiation were ${\geq}3.89$ for HIV, ${\geq}5.27$ for HAV, 5.29 for BHV, ${\geq}5.96$ for BVDV, ${\geq}4.37$ for PPV, ${\geq}3.55$ for BPV, ${\geq}3.51$ for MVM, ${\geq}4.20$ for REO, and ${\geq}4.15$ for BPIV. These results indicate that UVC irradiation using UVivatec was very effective and robust in inactivating all the viruses tested.