• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.23 no.4
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• pp.491-498
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• 2012

Recently, many papers have been proposed in order to improve the OFDM system performance in T-DMB DOCR (Digital On Channel Repeater), by using removing the feedback signal so that the transmitter power can be increased or by using the equalizer to remove ICI. Despite these efforts, however, signal quality at the receiving terminal has not been improved because of constellation smearing in T-DMB DOCR. In this paper, in order to suppress constellation smearing, we propose an effective equalizer algorithm that can improve system performance. We perform adaptive channel estimation and non-coherent decision directed noise cancellation method that can estimate the channel subsequently during data symbols period in the frequency domain. So we can obtain better quality of the signal at the receiving terminal. In order to secure QoS(Quality of Service) required in T-DMB handsets, we evaluate SNR and BER in T-DMB DOCR(Digital On Channel Repeater) and verified by simulation. In this simulation results, this system is satisfied the performance of BER=$10^{-5}$ at less than SNR=14 dB at the receiver after compensation of phase noise -18 dBc.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.05a
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• pp.678-681
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• 2003

In this paper, we aims to develop a microcontroll er-based portable pulse oximeter using Compact Flash Interface. First, portable pulse oxineter system is designed to record 2 channel of biosignals simultaneously, including 1 channel of SpO$_2$ and 1 channel of pulse rate. It is very small and portable. Besides, the system makes it possible to measure a patients condition without an additional medical equipment. We tried to solve the problems generated by a patient's motion. That is, we added an analog circuit to a traditional pulse oximeter in order to eliminate the change of the base line. And we used 2D sector algorithm. As present, SpO$_2$ modules are completed. But there are still many further development needed in order to enhance the function. Especially, compact flash interface remains the most to complete. Second, ECG monitoring system uses almost same as present 3-lead ECG system. But we focus on the analog part, especially in filter. The proposed filter is composed of two parts. One is a filter to remove the power-line interface. The other is a filter to remove the baseline drift. A filter to remove the power-line and the baseline drift is necessarily used in the ECG system. The implemented filter have three features; minimizing the distortion in DC component, removing the harmonic component of power-line frequency. Using compact flash interface, we can easily transfer a patient's personal information and the measured signal data to a network based server environment. That means, it is possible to implement a patient's monitoring system with low cost.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.6
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• pp.1060-1067
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• 2004

In a CDMA system, the rapacity is variable and mainly depends on multiple access interference. The multiple access interference has a deep relationship with transmitted or received power. The capacity of CDMA2000 1x system is considered to be limited by the forward link capacity. In this paper, we show that the transmitted power can represent the total cell load and we propose a load control scheme for CDMA2000 1x system. CDMA2000 1x system has fast power control scheme and we can measure forward link cell load by using total transmitted power. In the proposed algorithm, by monitoring the total transmit power, we can simply adjust data rate to channel conditions and efficiently use radio resources. The proposed algorithm is practical algorithm to implement in the power controlled CDMA systems and enhances the system throughput and quality of service(QoS)

• International conference on construction engineering and project management
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• 2020.12a
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• pp.463-481
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• 2020

Cutter suction dredgers (CSDs) are widely used in various dredging constructions such as channel excavation, wharf construction, and reef construction. During a CSD construction, the main operation is to control the swing speed of cutter to keep the slurry concentration in a proper range. However, the slurry concentration cannot be monitored in real-time, i.e., there is a "time-lag effect" in the log of slurry concentration, making it difficult for operators to make the optimal decision on controlling. Concerning this issue, a solution scheme that using real-time monitored indicators to predict current slurry concentration is proposed in this research. The characteristics of the CSD monitoring data are first studied, and a set of preprocessing methods are presented. Then we put forward the concept of "index class" to select the important indices. Finally, an ensemble learning algorithm is set up to fit the relationship between the slurry concentration and the indices of the index classes. In the experiment, log data over seven days of a practical dredging construction is collected. For comparison, the Deep Neural Network (DNN), Long Short Time Memory (LSTM), Support Vector Machine (SVM), Random Forest (RF), Gradient Boosting Decision Tree (GBDT), and the Bayesian Ridge algorithm are tried. The results show that our method has the best performance with an R² of 0.886 and a mean square error (MSE) of 5.538. This research provides an effective way for real-time predicting the slurry concentration of CSDs and can help to improve the stationarity and production efficiency of dredging construction.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.5
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• pp.168-176
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• 2014

Detecting moving objects from a video sequence is a fundamental and critical task in video surveillance, traffic monitoring and analysis, and human detection and tracking. It is very difficult to detect moving objects in a video sequence degraded by the environmental factor such as fog. In particular, the color of an object become similar to the neighbor and it reduces the saturation, thus making it very difficult to distinguish the object from the background. For such a reason, it is shown that the performance and reliability of object detection and tracking are poor in the foggy weather. In this paper, we propose a novel method to improve the performance of object detection, combining a haze removal algorithm and a local histogram-based object tracking method. For the quantitative evaluation of the proposed system, information retrieval measurements, recall and precision, are used to quantify how well the performance is improved before and after the haze removal. As a result, the visibility of the image is enhanced and the performance of objects detection is improved.

• Journal of Advanced Navigation Technology
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• v.21 no.5
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• pp.485-490
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• 2017

In this paper, we propose a technique for high speed removal of sea-fog using a graphic processor. This technique uses a host processor(CPU) and several graphics processors(GPU) capable of parallel processing to remove sea-fog from the input image. In the process of removing sea-fog, the dark channel extraction, the maximum brightness channel extraction, and the calculation of the transmission are performed by the host processor, and the process of refining the transmission by applying the bidirectional filter is performed in parallel through the graphic processor. To verify the proposed parallel processing method, three NVIDIA GTX 1070 GPUs were used to construct the verification environment. As a result, it takes about 140ms when implemented with one graphics processor, and 26ms when implemented using OpenMP and multiple GPGPUs. The proposed a parallel processing algorithm based on the graphics processor unit can be used for safe navigation, port control and monitoring system.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.2
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• pp.70-78
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• 1998

Spike detection in long-term EEG monitoring forepilepsy by wavelet transform(WT), artificial neural network(ANN) and the expert system is presented. First, a small set of wavelet coefficients is used to represent the characteristics of a singlechannel epileptic spikes and normal activities. In this stage, two parameters are also extracted from the relation between EEG activities before the spike event and EEG activities with the spike. then, three-layer feed-forward network employing the error back propagation algorithm is trained and tested using parameters obtained from the first stage. Spikes are identified in individual EEG channels by 16 identical neural networks. Finally, 16-channel expert system based on the context information of adjacent channels is introducedto yield more reliable results and reject artifacts. In this study, epileptic spikes and normal activities are selected from 32 patient's EEG in consensus among experts. The result showed that the WT reduced data input size and the preprocessed ANN had more accuracy than that of ANN with the same input size of raw data. Ina clinical test, our expert rule system was capable of rejecting artifacts commonly found in EEG recodings.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.817-818
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• 2006

In Magnetic Resonance Imaging(MRI), the QRS complex of ECG is used as a trigger signal for MRI scan. But, gradient and RF(radio frequency) artifacts which are caused to static and dynamic field in MRI scanner cause interference in the ECG. Also, the signal shape of theses artifacts can be similar to the QRS-complex, causing possible misinterpretation during patient monitoring and false gating of the MRI. In case of using general FIR or IIR band-pass filters for minimizing the artifacts, artifact-reduction-ratio is not excellent. So, an adaptive real-time digital filter is proposed for reduction of noise by gradient and RF(radio frequency) artifacts. The proposed filter for MRI-Gating is based on the noise-canceller with NLMS(Normalized Least Mean Square) algorithm. The reference signals of the adaptive noise canceller are a combination of the noisy three channel ECG signals. In conclusions, the proposed method showed the acceptable quality of ECG signal with sufficient SNR for gating the MRI and possibility of real time implementation.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.2 s.344
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• pp.27-38
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• 2006

When an RFID reader attempts to read tags, interference might occur if the neighboring readers also attempt to communicate with the same tag at the same time or the neighboring readers use the same frequency at the same time. These interferences cause the RFID reader collision. When the RFID reader collision occirs, either the command from the reader can not be transmitted to the tags or the response from the tags can not be received by the reader correctly. RFID reader anti-collision algorithms have been developed to reduce it. One of the best blown reader anti-collision algorithms is the Colorwave algorithm proposed by MIT. The Colorwave algorithm reduces the reader collisions by having the readers operate at different times. In Colorwave the time is divided into frames and a frame is divided into a number of slots. Each reader can access the tags using the slot time assigned to it. Depending on the probability of the interference, the colorwave adjusts the frame size to improve the efficiency. In this paper, we analyze the operations and the performance of the Colorwave algorithm and identify the problems of the algorithm. We also show that by adding some modifications to the algorithm the performance can be improved significantly.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.4
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• pp.1-14
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• 2012

A river is defined as the watercourse flowing through its channel, and the mapping tasks of a river plays an important role for the research on the topographic changes in the riparian zones and the research on the monitoring of flooding in its floodplain. However, the utilization of the ground surveying technologies is not efficient for the mapping tasks of a river due to the irregular surfaces of the riparian zones and the dynamic changes of water level of a river. Recently, the spatial information data sets are widely used for the coastal mapping tasks due to the acquisition of the topographic information without human accessibility. In this research, we tried to extract a river from the RapidEye imagery by using the ISODATA(Iterative Self_Organizing Data Analysis) classification algorithm with the two different parameters(NIR (Near Infra-Red) band and NDVI(Normalized Difference Vegetation Index)). First, the two different images(the NIR band image and the NDVI image) were generated from the RapidEye imagery. Second, the ISODATA algorithm were applied to each image and each river was generated in each image through the post-processing steps. River boundaries were also extracted from each classified image using the Sobel edge detection algorithm. Ground truths determined by the experienced expert are used for the assessment of the accuracy of an each generated river. Statistical results show that the extracted river using the NIR band has higher accuracies than the extracted river using the NDVI.