• Journal of Biomedical Engineering Research
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• v.43 no.4
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• pp.280-289
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• 2022

In this paper, we present a QRS-complex detection algorithm to calculate an accurate heartbeat and clearly recognize irregular rhythm from ECG signals. The conventional Pan-Tompkins algorithm brings false QRS detection in the derivative when QRS and noise signals have similar instant variation. The proposed algorithm uses amplitude differences in 7 adjacent samples to detect QRS-complex which has the highest amplitude variation. The calculated amplitude is cubed to dominate QRS-complex and the moving average method is applied to diminish the noise signal's amplitude. Finally, a decision rule with a threshold value is applied to detect accurate QRS-complex. The calculated signals with Pan-Tompkins and proposed algorithms were compared by signal-to-noise ratio to evaluate the noise reduction degree. QRS-complex detection performance was confirmed by sensitivity and the positive predictive value(PPV). Normal ECG, muscle noise ECG, PVC, and atrial fibrillation signals were achieved which were measured from an ECG simulator. The signal-to-noise ratio difference between Pan-Tompkins and the proposed algorithm were 8.1, 8.5, 9.6, and 4.7, respectively. All ratio of the proposed algorithm is higher than the Pan-Tompkins values. It indicates that the proposed algorithm is more robust to noise than the Pan-Tompkins algorithm. The Pan-Tompkins algorithm and the proposed algorithm showed similar sensitivity and PPV at most waveforms. However, with a noisy atrial fibrillation signal, the PPV for QRS-complex has different values, 42% for the Pan-Tompkins algorithm and 100% for the proposed algorithm. It means that the proposed algorithm has superiority for QRS-complex detection in a noisy environment.

• Journal of IKEEE
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• v.26 no.1
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• pp.43-49
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• 2022

This paper compares the sensorless control performance according to the applied voltage waveform by injecting sinusoidal, triangular, and square waveform in the harmonic injection sensorless control method. By injecting various voltage shape waveform with a frequency of 1kHz, the error amount of the estimated angle for each waveform is compared and analyzed. For the experiment, the HILS(hardware in the loop simulation) system was used. The hardware is the control board, and the inverter and motor models implemented in Simulik are located in the real-time simulator. The control algorithm is implemented by the FPGA control board, which includes a PWM interrupt service routine with a frequency of 10 kHz, harmonic injection and position detection sensorless algorithm.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.189-192
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• 2021

This study applies a deep learning-based long short-term memory(LSTM) model to track tracking technology. In the case of existing track tracking technology, the weight of constant velocity, constant acceleration, stiff turn, and circular(3D) flight is automatically changed when tracking track in real time using LMIPDA based on Kalman filter according to flight characteristics of an aircraft such as constant velocity, constant acceleration, stiff turn, and circular(3D) flight. In this process, it is necessary to improve performance of changing flight characteristic weight, because changing flight characteristics such as stiff turn flight during constant velocity flight could incur the loss of track and decreasing of the tracking performance. This study is for improving track tracking performance by predicting the change of flight characteristics in advance and changing flight characteristic weigh rapidly. To get this result, this study makes deep learning-based Long Short-Term Memory(LSTM) model study the plot and target of simulator applied with radar error model, and compares the flight tracking results of using Kalman filter with those of deep learning-based Long Short-Term memory(LSTM) model.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.255-257
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• 2021

During the winter season, when electricity usage increases rapidly every year, fires are frequent due to short circuits in aging electrical facilities in multi-use facilities such as traditional markets and jjimjilbangs, apartments, and multi-family houses. Most of the causes of such fires are caused by excessive loads applied to aging wires, causing the wire covering to melt and being transferred to surrounding ignition materials. In this study, we implement a system that measures the overload and overheating of the wire through a composite sensor, detects the toxic gas generated there, and logs it to the server through the gateway. Based on this, we will develop a platform that can predict, alarm and block electric fires in real time through big data analysis, and a simulator that can simulate fire occurrence experiments.

• Journal of Advanced Marine Engineering and Technology
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• v.39 no.7
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• pp.760-764
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• 2015

Wireless sensors, installed on machinery, and Time Division Multiple Access (TDMA) transmission make an ideal system for monitoring machine conditions in industrial plants because there is no need for electronic wiring. However, there has not yet been a successful field application of such a system, capable of continuously transmitting data at sample rates greater than 100 Hz. In this research, a TDMA network protocol capable of acquiring data from multiple sensors at sample rates greater than 100 Hz was developed for field application. The protocol was implemented in a single cluster-star topology network, and the system was evaluated based on the node number and transmission distance. Network simulator 2 (ns-2) was used for a real field simulation. Non-TDMA and TDMA protocol cases were compared using four sensor nodes. In the cases of 20-s and 40-s transmission times, there was little difference between the reception rates of the non-TDMA and TDMA systems. However, the difference was much greater when using a 60-s transmission time.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.9 no.4
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• pp.1-12
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• 2010

This paper deals with the transmission interval of vehicle data in smart highway where WAVE (Wireless Access for Vehicular Environments) systems have been installed for advanced road infrastructure. The vehicle data could be collected at every second, which is containing location information of the vehicle as well the vehicle speed, RPM, fuel consuming and safety data. The safety data such as DTC code, can be collected through OBD-II. These vehicle data can be used for valuable contents for processing and providing traffic information. In this paper, we propose a model to decide the collection interval of vehicle information in real time environment. This model can change the transmission interval along with special and time-variant traffic condition based on the 32 scenarios using microscopic traffic simulator, VISSIM. We have reviewed the transmission interval, communication transmission quantity and communication interval, tried to confirm about communication possibility and BPS, etc for each scenario. As results, in 2-lane from 1km highway segment, most appropriate transmission interval is 2 times over spatial basic segment considering to communication specification. In the future, if a variety of wireless technologies on the road is introduced, this paper considering not only traffic condition but also wireless network specification will be utilized the high value.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.4
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• pp.54-62
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• 2018

As a part of realization of artificial intelligence signal(AI Signal), this study proposed an actuated signal algorithm based on vehicle queue length that estimates in real time by deep learning. In order to implement the algorithm, we built an API(COM Interface) to control the micro traffic simulator Vissim in the tensorflow that implements the deep learning model. In Vissim, when the link travel time and the traffic volume collected by signal cycle are transferred to the tensorflow, the vehicle queue length is estimated by the deep learning model. The signal time is calculated based on the vehicle queue length, and the simulation is performed by adjusting the signaling inside Vissim. The algorithm developed in this study is analyzed that the vehicle delay is reduced by about 5% compared to the current TOD mode. It is applied to only one intersection in the network and its effect is limited. Future study is proposed to expand the space such as corridor control or network control using this algorithm.

• Journal of Korean Society of Transportation
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• v.26 no.4
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• pp.251-264
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• 2008

One of the crucial elements to fully facilitate the various benefits of intelligent transportation systems (ITS) is to obtain more reliable traffic monitoring in real time. To date, point and section-based traffic measurements have been available through existing surveillance technologies, such as loops and automatic vehicle identification (AVI) systems. However, seamless and more reliable traffic data are required for more effective traffic information provision and operations. Technology advancements including vehicle tracking and wireless communication enable the acceleration of the availability of individual vehicle travel information. This study presents a UBIquitous PRObe vehicle Surveillance System (UBIPROSS) using vehicle-to-vehicle (V2V) wireless communications. Seamless vehicle travel information, including origin-destination information, speed, travel times, and other data, can be obtained by the proposed UBIPROSS. A set of parameters associated with functional requirements of the UBIPROSS, which include the market penetration rate (MPR) of equipped vehicles, V2V communication range, and travel time update interval, are investigated by a Monte Carlo simulation- (MCS) based evaluation framework. In addition, this paper describes prototypical implementation. Field test results and identified technical issues are also discussed. It is expected that the proposed system would be an invaluable precursor to develop a next-generation traffic surveillance system.

• Journal of Biomedical Engineering Research
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• v.19 no.1
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• pp.25-32
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• 1998

This paper is based on the design and analysis computing model of oxygen saturation with the pulse oximeter using the integral ratio of pulsating components. In our proposed algorithm. we modeled the transmitted optical signal in fingertip or earlobe to DC component $A_{dc}$ pulsating component $A_a\;Sinwt$, noise component $A_{noise}$ and etc.. To separate the pulsating components and DC components efficiently, we defined the signal average to DC components. Also we presented the way to eliminate the noise using integral ratio. To acquire a linearity of correlation graph for pulsating components ratios and non invasive oxygen saturation. we intensively observed on the oxygen saturations in the range of 75-100% in consideration of the error range of simulator. Also, for real time processing we experimented on changing the period of area calculating cycle from 1 to 6. The functional evaluation of the algorithm is compared with the method using the amplitude ratio of pulsating components frequently seen with pulse oximeter. The result was that our algorithm with 4 cycles of area calculating cycle which considered to be best fit by 1% to the existing method. Moreover r , the decision coefficient showing the correlation of regression graph with real data, proved better result of 0.985 than 0.970.

• The Journal of the Korea Contents Association
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• v.9 no.8
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• pp.73-83
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• 2009

TCP(Transmission Control Protocol) is currently used connection-oriented protocol as a typical transport layer protocol in the Internet. However, it has deficiency not be able to communicate with other TCP entities when any link included in the path is down because of single-homing on single path. SCTP(Stream Control Transmission Protocol) suggested as the new transport layer protocol supports multi-homing feature, which provides several paths between source and destination. It can communicate with other SCTP entities using alternate path even when any link on the primary path is down. This paper aims to measure and analyze the multi-homing effect of SCTP over TCP in case of link-down using NS-2 simulator. We classify SCTP into $SCTP_{single-homing}$ and $SCTP_{multi-homing}$ because SCTP with single-homing can also be used like TCP. We measured throughput and bandwidth utilization varying link-down duration, bandwidth, and RTT(round trip time), Simulation results show that throughput of $SCTP_{multi-homing}$ is more than that of TCP by 18 % on average. It is also shown that $SCTP_{multi-homing}$ on varying RTT and bandwidth increases the throughput of TCP by 'l7% and 9% on average, respectively in the link-down environment. In above cases, more or less difference between $SCTP_{single-homing}$ and TCP on throughput and bandwidth utilization was found To summarize, multi-homing effect of SCTP over TCP on throughput is about 18 % on average in the link-down environment This experimental result can be used as the benchmark in order to estimate the multi-homing effect of SCTP over TCP when the link-down happens in the real Internet.