• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.2
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• pp.129-134
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• 2010

Diseases such as cardiovascular illnesses, according to the National Statistical Office opened reveals that 600-800 people were killed, blood pressure, arteriosclerosis, heart disease, stroke, etc. will be a flow of blood disorders that occur in cardiovascular illnesses today are fulfilling the Master / Slave samangryulin disease appears high. Died of cardiovascular disease also told them the correct first aid survival when patients are accounted for approximately 40% of emergency rapid response is required. Therefore, this paper, the weak classifier in the AdaBoost algorithm to generate a strong classifier by combining effects throughout the analysis to measure the ECG, and cardiovascular disease that occurred to you as soon as the emergency management system that can deliver on the proposed Desk was. The electrocardiogram data measured by the ZigBee-based sensors, communication devices and emergency transport for emergency alarms in the determination and monitoring of the management desk by providing health services to enable the delivery was fast.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.4
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• pp.129-135
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• 2017

Recently, with the development of IoT technology, there has been an increase in interest in the power consumption of the devices used by the internal devices. Especially, the standby power consumption during the main function of the devices is about 11% of the power energy and the problem of standby power interruption is suggested. However, there is a problem that the plug must be unplugged in order to substantially shut off standby power. Therefore, in this paper, we design and implement a standby power cutoff algorithm that can automatically control and manage users' participation in order to solve there problems. As a result of evaluating the implemented system, it was confirmed that the standby power interruption rate improved by about 5.89Wh on average compared to the existing system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.4
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• pp.846-854
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• 2017

In this paper, we proposed a method to reduce the error of compass by combining the ceiling technique used in the past with modern IT technology. We combined an encoder and the Azimuth Circle for applying an algorithm. The algorithm is able to calculate the true north by using astronomical observation. Finally, we implemented the embedded system possible to indicate various situations and perform calculations. As a result, it isn't only able to calculate the true north with an error of about $0.2^{\circ}$ but also takes less than 5 seconds. Originally, using astronomical observation requires more than 5minutes. So it is analyzed as convenient by solving the problem of taking lots of time. Especially, we present the tolerance less than $0.5^{\circ}$ by the analysis of the existing gyrocompass and the bearing standard of IMO. In conclusion, we clearly confirm that the results of this paper are possible to reduce the error of various compasses in a real world.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.8A
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• pp.575-582
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• 2009

The localization algorithm(LAtu) using the IDentification Code($C_{ID}$) is suggested in RSS(Received Signal Strength) based Wireless Sensor Network(WSN), and the localization system using the suggested algorithm is designed and implemented in this paper. In addition to this, the performance of ranging correction quality and localization error of the localization system(System(LAtu)) that is developed using the LAtu is analyzed and compared with that of the localization system(System(LAieee)) using the channel model of IEEE 802.15.4 standard(LAieee) by the actual experimentation. From the experimentation, the ranging correction quality is analyzed that the LAtu is highly better than the channel model of LAieee about 34% under the distance between the moving module and the beacon module($D_{MM-BM}$) is 2m, and is also a few better than that of the LAieee about average 5% under the $D_{MM-BM}$ is above 5m. The localization error quality of the System(LAtu) is lower than that of the System(LAieee)) about 1cm under the lecture room and 4cm in the large lecture room.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.4A
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• pp.434-439
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• 2008

This paper proposes an efficient coarse frequency synchronizer for digital video broadcasting - second generation (DVB-S2). The input signal requirement of acquisition range for coarse frequency estimator in the DVB-S2 is around ${\pm}1.5625Mhz$, which corresponds to 6.25% of the symbol rate at 25Mbaud. At the process of analyzing the robust algorithm among data-aided approaches, we find that the Luise & Reggiannini (L&R) algorithm is the most promising one for coarse frequency estimation with respect to estimation performance and complexity. However, it requires many multipliers and adders to compute output values of correlators. We propose an efficient architecture identifying the serial correlator with the buffer and multiplexers. The proposed coarse frequency synchronizer can reduce the hardware complexity about 92% of the direct implementation. The proposed architecture has been implemented and verified on the Xilinx Virtex II FPGA.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.1 s.307
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• pp.101-108
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• 2006

In this paper, an efficient butterfly structure for Radix-4 FFT algorithm using DA(Distributed Arithmetic) is proposed. It is shown that DA can be efficiently used in twiddle factor calculation of the Radix-4 FFT algorithm. The Verilog-HDL coding results for the proposed DA butterfly structure show $61.02\%$ cell area reduction comparison with those of the conventional multiplier butterfly structure. furthermore, the 64-point Radix-4 pipeline structure using the proposed butterfly and delay commutators is compared with other conventional structures. Implementation coding results show $46.1\%$ cell area reduction. Due to its efficient processing scheme, the proposed FFT structure can be widely used in large size of FFT like OFDM Modem.

• Spatial Information Research
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• v.16 no.4
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• pp.455-465
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• 2008

Augmented reality (AR) has tremendous potential in visualizing geospatial information, especially on the actual physical scenes. However, to utilize augmented reality in mobile system, many researches have undergone with GPS or ubiquitous marker based approaches. Although there are several papers written with vision based markerless tracking, previous approaches provide fairly good results only in largely under "controlled environments." Localization and tracking of current position become more complex problem when it is used in indoor environments. Many proposed Radio Frequency (RF) based tracking and localization. However, it does cause deployment problems of large RF-based sensors and readers. In this paper, we present a noble markerless AR approach for indoor (possible outdoor, too) navigation system only using monoSLAM (Monocular Simultaneous Localization and Map building) algorithm to full-fill our grand effort to develop mobile seamless indoor/outdoor u-GIS system. The paper briefly explains the basic SLAM algorithm, then the implementation of our system.

• Journal of Broadcast Engineering
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• v.20 no.3
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• pp.421-429
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• 2015

This paper is about an approach for pedestrian detection and tracking with infrared imagery. We used the CUDA(Computer Unified Device Architecture) that is a parallel processing language in order to improve the speed of video-based pedestrian detection and tracking. The detection phase is performed by Adaboost algorithm based on Haar-like features. Adaboost classifier is trained with datasets generated from infrared images. After detecting the pedestrian with the Adaboost classifier, we proposed a particle filter tracking strategies on HSV histogram feature that exploit adaptively at the same time. The proposed approach is implemented on an NVIDIA Jetson TK1 developer board that is full-featured device ideal for software development within the Linux environment. In this paper, we presented the results of parallel processing with the NVIDIA GPU on the CUDA development environment for detection and tracking of pedestrians. We compared the object detection and tracking processing time for night-time images on both GPU and CPU. The result showed that the detection and tracking speed of the pedestrian with GPU is approximately 6 times faster than that for CPU.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.3
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• pp.93-98
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• 2017

This paper relates with the robustness performance improvement of QE-MMA (Quantized Error-MMA) adaptive equalization algorithm based on the dithering in order to reduce the intersymbol interference by nonlinear distortion occurs at channel. The QE-MMA was appeared for the easiness of H/W implementation in place of multiplication to shifting in the tap coefficient updates applying the power-of-two operation to the magnitude of error signal in currently SE-MMA, it's performance were degraded by this. For improving it's performance, the proposed DQE-MMA adds the dither signal which has constant statistical characteristics in the prestage of power-of-two operation. It was confirmed by simulation that the DQE-MMA gives better robustness performance than current QE-MMA in the same channel and signal to noise ratio.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.2
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• pp.102-108
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• 2011

The existing vessels lighting control system has several problems, which are complexity of construction and high cost of establishment and maintenance. In this paper, We designed low cost and high performance lighting control system at digital vessel environment. We proposed a system which recognize the user's emotions after obtaining the biological informations about user's bio information(pulse sensor, blood pressure sensor, blood sugar sensor etc) through wireless sensors controls the LED Lights. This system classified emotions using backpropagation algorithm. We chose 3,000 data sets to train the backpropagation algorithm. As a result, obtained about 88.7% accuracy. And the classified emotions find the most appropriate point in the method of controlling the waves or frequencies to the red, green, blue LED Lamp comparing with the 20-color-emotion models in the HP's 'The meaning of color' and control the brightness or contrast of the LED Lamp. In this method, the system saved about 20% of the electricity consumed.