• The Journal of the Institute of Internet, Broadcasting and Communication
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• 제15권6호
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• pp.187-193
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• 2015

The ICT healing platform sets a couple of goals including preventing chronic diseases and sending out early disease warnings based on personal information such as bio-signals and life habits. The 2-step open system(TOS) had a relay designed between the healing platform and the storage of personal health data. It also took into account a publish/subscribe(pub/sub) service based on large-scale connections to transmit(monitor) the data processing process in real time. In the early design of TOS pub/sub, however, the same buffers were allocated regardless of connection idling and type of message in order to encode connection messages into a deflate algorithm. Proposed in this study, the dynamic buffer allocation was performed as follows: the message transmission type of each connection was first put to queuing; each queue was extracted for its feature, computed, and converted into vector through tf-idf, then being entered into a k-means cluster and forming a cluster; connections categorized under a certain cluster would re-allocate the resources according to the resource table of the cluster; the centroid of each cluster would select a queuing pattern to represent the cluster in advance and present it as a resource reference table(encoding efficiency by the buffer sizes); and the proposed design would perform trade-off between the calculation resources and the network bandwidth for cluster and feature calculations to efficiently allocate the encoding buffer resources of TOS to the network connections, thus contributing to the increased tps(number of real-time data processing and monitoring connections per unit hour) of TOS.

• Journal of the Institute of Electronics and Information Engineers
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• 제51권11호
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• pp.11-18
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• 2014

Most of the energy efficient MAC protocols for wireless sensor networks (WSNs) are based on duty cycling in a single channel and show competitive performances in a small number of traffic flows; however, under concurrent multiple flows, they result in significant performance degradation due to contention and collision. We propose a multi-channel pipelining (MCP) method for convergecast WSN in order to address these problems. In MCP, a staggered dynamic phase shift (SDPS) algorithms devised to minimize end-to-end latency by dynamically staggering wake-up schedule of nodes on a multi-hop path. Also, a phase-locking identification (PLI) algorithm is proposed to optimize energy efficiency. Based on these algorithms, multiple flows can be dynamically pipelined in one of multiple channels and successively handled by sink switched to each channel. We present an analytical model to compute the duty cycle and the latency of MCP and validate the model by simulation. Simulation evaluation shows that our proposal is superior to existing protocols: X-MAC and DPS-MAC in terms of duty cycle, end-to-end latency, delivery ratio, and aggregate throughput.

• Journal of Cadastre & Land InformatiX
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• 제51권1호
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• pp.97-110
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• 2021

This study estimated the delay factor, which is the ratio of travel time at the speed limit and travel time at the actual speed using real-time traffic information in Seoul. The actual travel speed on the road was lower than the maximum speed of the road and the travel speed was the slowest during the rush hour. As a result of accessibility analysis based on travel speed during the rush hour, the travel time at the actual speed was 37.49 minutes on average. However, the travel time at the speed limit was 15.70 minutes on average. This result indicated that the travel time at the actual speed is 2.4 times longer than that at the speed limit. In addition, this study proposedly defined the delay factor as the ratio of accessibility by the speed limit and accessibility to actual travel speed. As a result of delay factor analysis, the delay factor of Seoul was 2.44. The results by the administrative district showed that the delay factor in the north part areas of the Han River is higher than her south part areas. Analysis results after applying the relationship between road density and traffic volume showed that as the traffic volume with road density increased, the delay factor decreased. These results indicated that it could not be said that heavy traffic caused longer travel time. Therefore, follow-up research is needed based on more detailed information such as road system shape, road width, and signal system for finding the exact cause of increased travel time.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• 제6권9호
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• pp.59-70
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• 2016

The rapid development of the Chinese version of Twitter, the groom Weibo has become an important communication means for Chinese SNS users to obtain and share information. As a result, in China, the phenomenon of the power shift has emerged from the traditional opinion leaders to SNS opinion leasers. The relationship analysis of demographic variables of the Chinese SNS users and their Information on the relationship between keywords was made by utilizing the centrality analysis using Social Network Program NetMiner. China's SNS opinion leaders have general interest in daily activities with their families or friends rather than in social issues. And in case of SNS opinion leaders of high betweenness centrality, it was analyzed that general users was a key mediator role that organically out lead to the adjacent information. These properties are not independent of demographic variables, such as professional, therefore, the demographic characteristics of SNS opinion leaders showed a significant effect on the parameters of betweenness centrality. This study analyzed the characteristics of SNS users, especially opinion leaders in China by looking at the aspects of Chinese social phenomenon in terms of information. Through this study, we expect to provide basic information about the social characteristics of China through collective communication.

• Korean Journal of Radiology
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• 제22권2호
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• pp.168-178
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• 2021

Objective: To provide an automatic method for segmentation and diameter measurement of type B aortic dissection (TBAD). Materials and Methods: Aortic computed tomography angiographic images from 139 patients with TBAD were consecutively collected. We implemented a deep learning method based on a three-dimensional (3D) deep convolutional neural (CNN) network, which realizes automatic segmentation and measurement of the entire aorta (EA), true lumen (TL), and false lumen (FL). The accuracy, stability, and measurement time were compared between deep learning and manual methods. The intra- and inter-observer reproducibility of the manual method was also evaluated. Results: The mean dice coefficient scores were 0.958, 0.961, and 0.932 for EA, TL, and FL, respectively. There was a linear relationship between the reference standard and measurement by the manual and deep learning method (r = 0.964 and 0.991, respectively). The average measurement error of the deep learning method was less than that of the manual method (EA, 1.64% vs. 4.13%; TL, 2.46% vs. 11.67%; FL, 2.50% vs. 8.02%). Bland-Altman plots revealed that the deviations of the diameters between the deep learning method and the reference standard were -0.042 mm (-3.412 to 3.330 mm), -0.376 mm (-3.328 to 2.577 mm), and 0.026 mm (-3.040 to 3.092 mm) for EA, TL, and FL, respectively. For the manual method, the corresponding deviations were -0.166 mm (-1.419 to 1.086 mm), -0.050 mm (-0.970 to 1.070 mm), and -0.085 mm (-1.010 to 0.084 mm). Intra- and inter-observer differences were found in measurements with the manual method, but not with the deep learning method. The measurement time with the deep learning method was markedly shorter than with the manual method (21.7 ± 1.1 vs. 82.5 ± 16.1 minutes, p < 0.001). Conclusion: The performance of efficient segmentation and diameter measurement of TBADs based on the 3D deep CNN was both accurate and stable. This method is promising for evaluating aortic morphology automatically and alleviating the workload of radiologists in the near future.

• Korean Journal of Radiology
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• 제21권7호
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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.

• Journal of Photoscience
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• 제9권2호
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• pp.311-313
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• 2002

X-ray structures of pharaonis phoborhodopsin (ppR) show the different direction of the side chain of Arg72 from that of the corresponding residue (Arg82) of bacteriorhodopsin, BR. For BR, this residue is considered to play an important role in the proton pumping. In order to investigate the role of Arg72 in ppR, we constructed Arg72 mutants of R72A, R72K and R72Q, and measured the photocycle and proton pumping activities. The pH-titration curves on the absorption maximum of the mutants were shifted to alkaline in comparison of that of the wild-type. This may imply the increase of pKa of D75, suggesting the presence of the (probably electric) interaction between D75 and Arg72. Rate constants of the M-decay were 3-7 times faster than that of the wild-type, and the time for the completion of the photocycling was also reduced. Using Sn0$_2$ electrode, the rate of transmembrane proton transport was measured upon illumination. The photo-induced proton pumping activities were estimated after the corrections that are the percentages of the associated form of D75 (which has no pumping activity) and the photocycling rates. R72A and R72Q showed the reduced activity while R72K did not reduce the activity.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• 제24권12호
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• pp.955-961
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• 2011

We investigated the physical properties of stoichiometric and non-stoichiometric oxide doped complex perovskite, $Ba(Zn_{1/3}Ta_{2/3})O_3$ ceramics and their impacts on the microwave dielectric performances using various characterization techniques such as X-ray diffraction, scanning electron microscopy, transmission electron microscopy, and network analyzer. According to the measurement of lattice constant changes, anomalous lattice volume contraction of $ZrO_2$ doped $Ba(Zn_{1/3}Ta_{2/3})O_3$ sample only showed the dielectric quality factor enhancements, which was due to the lattice volume contraction as well as the 1:2 B-site cation ordering. In addition, NiO doping was useful to the stabilization of temperature coefficient of resonance frequency.

• 한국HCI학회:학술대회논문집
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• 한국HCI학회 2006년도 학술대회 1부
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• pp.1093-1098
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• 2006

VR 엔진은 일부 입력장치에 대해서만 제한적으로 지원하기 때문에, 개발자가 원하는 입력장치를 사용하지 못하는 경우가 있으며, 가격 또한 고가이기 때문에 특수한 입력장치를 사용하기 위해, 다른 VR 엔진이나 별도의 옵션을 구매하기에는 경제적인 부담이 많이 든다. 이러한 문제를 해결하기 위해 본 논문에서는 개발자가 사용하고자 하는 입력장치와 VR 엔진의 호환을 위한 랩퍼 클래스를 제안한다. 개발한 랩퍼 클래스는 VR 엔진에서 조이스틱을 제어할 수 있는 조이스틱 클래스와 USB 캠을 통하여 영상을 획득하기 위한 USB 캠 클래스이다. 조이스틱 클래스는 입력장치 클래스를 상속받은 후 DirectX 를 이용하여 입력장치를 셋업 하고, 입력장치의 데이터 값을 처리한 후 VR 엔진의 API 로 값을 넘겨주기 전에 후킹하여 조이스틱을 제어할 수 있다. USB 캠 클래스는 VFW(Video for Window)를 사용하여 캠의 영상을 획득하여 버퍼에 저장한 후 VR 엔진의 디스플레이 버퍼에 값을 넘겨서 캠의 영상을 VR 엔진에서 디스플레이 할 수 있다. 이러한 방법을 통해 조이스틱, USB 캠 같은 입력장치를 VR 엔진과 호환할 수 있으며, 다른 종류의 입력장치에 대하여서도 본 연구에서 개발한 랩퍼 클래스를 상속받아 사용할 수 있다. 본 논문에서 사용한 VR 엔진은 Vega Prime 엔진이며, Vega Prime 엔진의 API 에 개발한 랩퍼 클래스를 추가하여 드라이빙, 영상인식 시뮬레이터를 개발한 결과, 효과적이고 경제적으로 입력장치의 연동이 가능함을 확인할 수 있었다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.132-137
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• 2004

On-Board Diagnostic(OBD) systems are in most cars and light trucks on the load today. During the 1970's and early 1980's manufacturers started using electronic means to control engine functions and diagnose engine problems. The CARB's diagnostic requirements to meet EPA emission standards have been designated as OBD with a goal of monitoring all of the emissions-related components, as well as the chassis, body, accessory devices and the diagnostic control network of the vehicle for proper operation. In this paper, we present a remote measurement system for the wireless monitoring of diagnosis signal and sensors output signals of ECU adopted KWP2000, united the OBD communication protocol, on OBD-compliant vehicle using the wirless communication technique of Bluetooth. In order to measure the ECU signals, the interface circuit is designed to communicate ECU and designed terminal wirelessly according to the ISO, SAE regulation of communication protocol standard. A microprocessor S3C3410X is used for communicating ECU signals. The embedded system's software is programmed to measure the ECU signals using the ARM compiler and ANCI C based on MicroC/OS kernel to communicate between bluetooth modules using bluetooth stack. The diagnostic system is developed using Visual C++ MFC and protocol stack of bluetooth for Windows environment. The self-diagnosis and sensor output signals of ECU is able to monitor using PC with bluetooth board connected in serial port of PC. The algorithms for measuring the ECU sensor output and self-diagnostic signals are verified to monitor ECU state. At the same time, the information to fix the vehicle's problem can be shown on the developed monitoring software. The possibility for remote measurement of self-diagnosis and sensor signals of ECU adopted KWP2000 in embedded system verified through the developed systems and algorithms.