• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권8호
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• pp.1805-1824
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• 2013

Recently, the use of wireless body area networks (WBAN) has been increasing rapidly in medical healthcare applications. WBANs consist of smart nodes that can be used to sense and transmit vital data such as heart rate, temperature and ECG from a human body to a medical centre. WBANs depend on limited resources such as energy and bandwidth. In order to utilise these resources efficiently, a very well organized medium access control (MAC) protocol must be considered. In this paper, a new, adaptive and energy-efficient MAC protocol, entitled isMAC, is proposed for WBANs. The proposed MAC is based on multi-channel communication and aims to prolong the network lifetime by effectively employing (i) a collision prevention mechanism, (ii) a coordinator node (WCN) selection algorithm and (iii) a transmission power adjustment approach. The isMAC protocol has been developed and modelled, by using OPNET Modeler simulation software. It is based on a networking scenario that requires especially high data rates such as ECG, for performance evaluation purposes. Packet delay, network throughput and energy consumption have been chosen as performance metrics. The comparison between the simulation results of isMAC and classical IEEE 802.15.4 (ZigBee) protocol shows that isMAC significantly outperforms IEEE 802.15.4 in terms of packet delay, throughput and energy consumption.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권11호
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• pp.4395-4412
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• 2020

The multisource image fusion has become an active topic in the last few years owing to its higher segmentation rate. To enhance the accuracy of multimodal pig-body feature segmentation, a multisource image fusion method was employed. Nevertheless, the conventional multisource image fusion methods can not extract superior contrast and abundant details of fused image. To superior segment shape feature and detect temperature feature, a new multisource image fusion method was presented and entitled as NSST-GF-IPCNN. Firstly, the multisource images were resolved into a range of multiscale and multidirectional subbands by Nonsubsampled Shearlet Transform (NSST). Then, to superior describe fine-scale texture and edge information, even-symmetrical Gabor filter and Improved Pulse Coupled Neural Network (IPCNN) were used to fuse low and high-frequency subbands, respectively. Next, the fused coefficients were reconstructed into a fusion image using inverse NSST. Finally, the shape feature was extracted using automatic threshold algorithm and optimized using morphological operation. Nevertheless, the highest temperature of pig-body was gained in view of segmentation results. Experiments revealed that the presented fusion algorithm was able to realize 2.102-4.066% higher average accuracy rate than the traditional algorithms and also enhanced efficiency.

• International journal of advanced smart convergence
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• 제10권1호
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• pp.151-158
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• 2021

The main cause of ulcer is pressure, which starts to develop when the critical body pressure (32mmHg) is exceeded, and when the critical time elapses, ulcer occurs. In this study, the keyboard mechanism of the medical bed with 4 bar links was adopted, and each key can be controlled vertically. A key has one servo drive and one sensor controller which hasseveral body pressure sensors. The sensor controllers and the servo drives are connected to the main controller by two CAN (Car Are Network) in series, respectively. By reading the maximum body pressure value of each keyboard sensor, and by calculating the error value based on the critical body pressure, the fuzzy controller moves each key so that the total error becomes zero. If the fuzzy controller fails, then it prevents ulcer by lifting and lowering the keys of the bed alternatively within a short time. Thus, the controller operates in two-stage. The validity and effectiveness of the proposed approach have been verified through experiments.

• 한국항행학회논문지
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• 제13권2호
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• pp.224-230
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• 2009

최근, Medical Body Area Networks (MBAN)는 사람의 인체를 진단하기 위한 새로운 기술로서 주목받고 있다. MBAN은 소형, 저 전력, 단거리 무선통신 기술을 의료(medical)분야에 적용한 의료 네트워크 이다. 본 논문은 MBAN에서 긴급 메시지 전송시 패킷 간 충돌과 IEEE 802.15.3이 가지는 전송대기 시간에 의해 발생하는 전송지연을 개선하기 위해 Carrier Sense Multiple Access/Time Division Multiple Access를 이용한 프로토콜을 제안하였다. 제안하는 프로토콜은 전력의 효율성 및 신뢰성을 개선하기 위해, IEEE 802.15.3의 MCTA를 MBAN에서 적용 가능한 SR-MCTA로 변형하여 전송의 신뢰성 및 전력 사용의 효율성을 높였다. 제안하는 프로토콜에서 SR-MCTA 슬롯은 단말 디바이스의 요청에 의해 MBAN 코디네이터가 할당하며, 할당하는 방법은 현재 슬롯에서 긴급 패킷이 발생할 때 임의의 충돌 패킷을 발생시켜 패킷을 획득하는 방법을 사용한다. 제안하는 프로토콜의 성능을 평가하기 위해 전송대기 시간을 평가할 수 있는 수식을 유도하고, 또한 이러한 결과를 이용하여 시뮬레이션 하였다. 시뮬레이션의 결과는 우리가 제안하는 프로토콜에서는 전송지연이 개선됨을 보였다.

• 한국통신학회논문지
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• 제36권10C호
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• pp.597-604
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• 2011

본 논문에서는 의료용 in-body WBAN (Wireless Body Area Network) 시스템을 위한 GM (Group Manchester code) 변조 방식을 제안한다. 현재 IEEE에서는 WBAN 시스템을 802.15. TG (Task Group) 6로 지정하고 이에 관한 표준화를 진행하고 있다. 높은 전력 효율이 요구되는 WBAN 시스템을 위해 최근 표준화 그룹에서는 PPM(Pulse Position Modulation) 신호 간의 grouping을 통하여 전송률 이득을 얻을 수 있는 GPPM (Group Pulse Position Modulation) 변조 방식이 제안된 바 있으나, 기존 GPPM 방식은 복조 과정의 SNR 손실 및 gray coding의 부재로 인한 BER 성능 열화가 나타나는 단점이 존재한다. 따라서 본 논문에서는 PPM 보다 잡음 성능이 우수한 Manchester code를 기반으로, GM 방식의 BER 성능 최대화를 위한 복조 방식 및 turbo coded GM을 위한 LLR (Log Likelihood Ratio) 판정 방식을 제안하였으며, 다양한 성능 2 분석을 통해 제안된 방식의 우수성을 입증하였다.

• 한국ITS학회 논문지
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• 제8권6호
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• pp.88-97
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• 2009

WBAN은 인체 내부 혹은 인체로부터 3미터 이내의 주변에서 일어나는 근거리 무선 통신을 목적으로 하는 네트워크이며 운전자의 생체 정보를 분석하여 보다 안전한 차량 운전이 가능하도록 하는 차량 산업에 적용할 수 있다. 본 논문에서는 고속 WBAN 시스템의 요구 조건을 만족하기 위한 UWB 기술과 다중 안테나 기법에 대해 논하고 Noncoherent UWB 수신기를 이용한 수신 안테나 선택 기법을 제안한다. 제안된 방식은 Noncoherent 수신기를 이용하여 BPPM 구간의 에너지 비율을 비교하여 수신 신호를 선택하는 기법으로 2~4개의 수신 안테나 환경에서의 성능을 비교 하였고, 시스템의 요구조건인 10-3 BER을 만족하는 경우에는 수신 신호의 에너지 크기를 비교하여 안테나를 선택하는 방식에 비해 4dB 이상의 성능 향상을 보였다.

• 한국해양공학회지
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• 제29권3호
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• pp.270-282
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• 2015

A submerged body moving near the free surface needs to maintain its attitude and position to accomplish missions. It is necessary to validate the performance of a designed controller before a sea trial. The hydrodynamic coefficients of maneuvering are generally obtained by experiments or computational fluid dynamics, but these coefficients have uncertainty. Environmental loads such as the wave exciting force and suction force act on the submerged body when it moves near the free surface. Thus, a controller for the submerged body should be robust to parameter uncertainty and environmental loads. In this paper, the six-degree-of-freedom equations of motions for the submerged body are constructed. The suction force is calculated using the double Rankine body method. An adaptive control method based on an artificial neural network and proportional-integral-derivative control are used for the depth controller. Simulations are performed under various depth and speed conditions, and the results show the effectiveness of the designed controller.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.184-184
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• 2000

The new-type measuring modules for unmanned remote supervisory system using mobile communication network have been designed in this study. Measuring modules consist of temperature measuring module, humidity measuring module and human body sensing module. And we will design a main part to collect and process informations of each modules, evaluate reliability of combined total system.

• 대한기계학회논문집A
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• 제26권5호
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• pp.969-975
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• 2002

Visual effects are important cues for providing occupants with virtual reality in a vehicle simulator which imitates real driving. The viewpoint of an occupant is sensitively dependent upon the occupant's posture, therefore, the total human body motion must be considered in a graphic simulator. A real-time simulation is required for the dynamic analysis of complex human body motion. This study attempts to apply a neural network to the motion analysis in various driving situations. A full car of medium-sized vehicles was selected and modeled, and then analyzed using ADAMS in such driving conditions as bump-pass and lane-change for acquiring the accelerations of chassis of the vehicle model. A hybrid III 50%ile adult male dummy model was selected and modeled in an ellipsoid model. Multibody system analysis software, MADYMO, was used in the motion analysis of an occupant model in the seated position under the acceleration field of the vehicle model. Acceleration data of the head were collected as inputs to the viewpoint movement. Based on these data, a back-propagation neural network was composed to perform the real-time analysis of occupant motions under specified driving conditions and validated output of the composed neural network with MADYMO result in arbitrary driving scenario.

• 한국세라믹학회지
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• 제43권4호
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• pp.199-202
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• 2006

In this study, SiC whiskers were grown on a porous SiC diesel particulate filter for nanoparticle filtering. To grow the whiskers at the inner pore without closing the pores, we used chemical vapor infiltration with a solution source and a dilute. As the deposition time increased, the whiskers grew and formed a network structure. After 180 min of deposition, the mean diameter of the whiskers was 174 nm and the compressive strength was 58.4 MPa. The pores shrank from $10{\mu}m\;to\;0.4{\mu}m$ and, because the whiskers filed the inner pores, the gradient of permeability decreased as the deposition time increased. However, by using the network structure of whiskers deposited for 120 min and 180 min, we obtained a diesel particulate filter with pores of $0.98{\mu}m\;and\;0.4{\mu}m$, respectively. Furthermore, the filter shows better permeability than a porous body with pores of $1{\mu}m$. In short, by filtering the nanoparticulate materials, the network structure of whiskers improves the strength, reduces the pore size and minimizes the permeability drop.