• Journal of KIISE:Databases
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• v.29 no.3
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• pp.193-206
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• 2002

In this paper, we design and implement an efficient bulk-loading algorithm for CIR-Tree. Bulk-loading techniques increase node utilization, improve query performance and reduce index construction time. The CIR-tree has variable size of internal node entries since it only maintains minimal dimensions to decriminate child nodes. This property increases fan-out of internal nodes and improves search performance. Even though several bulk-loading algorithms for multi/high-dimensional index structures have been proposed, we cannot apple them to CIR-tree because of the variable size of internal node entries. In this paper, we propose an efficient bulk- loading algorithm for CIR-tree that improves the existing bulk-loading algorithm and accomodates the property of CIR-tree. We also implement it on a storage system MiDAS-III and show superiority of our algorithm through various experiments.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.2 no.1
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• pp.45-51
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• 1998

In the realization of a high speed digital transmission over several tens kbps in mobile communications, it follow delay distortion on a count of transmission path variation by multipath interference waves. Therefore it is inevitably necessary to establish the techniques overcoming the frequency selective fading. In this paper, a feedback running RLS algorithm which is improved the RLS algorithm using exponential weighting factor, is proposed for the control algorithm of DFE and by the computer simulation method, and the performance characteristics of DFE is analyzed for the one-ray and two-ray waves model under the random Gaussian noise. The computer simulation results of proposed RLS algorithm for the $\pi$/4QPSK signal with one symbol time delayed interference signal of S/I = 20［dB］, under the S/N = 10［dB］ with $\lambda$= 0.9 showed excellent following characteristics and equalization characteristics.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.10
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• pp.1247-1255
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• 2016

The safety and autonomous flight function of micro UAV or drones is crucial to its commercial application. The requirement of own building stable drones is still a non-trivial obstacle for researchers that want to focus on the intelligence function, such vision and navigation algorithm. The paper present a GCS using commercial drone and hardware platforms, and open source software. The system follows modular architecture and now composed of the communication, UI, image processing. Especially, lane-keeping algorithm. are designed and verified through testing at a sports stadium. The designed lane-keeping algorithm estimates drone position and heading in the lane using Hough transform for line detection, RANSAC-vanishing point algorithm for selecting the desired lines, and tracking algorithm for stability of lines. The flight of drone is controlled by 'forward', 'stop', 'clock-rotate', and 'counter-clock rotate' commands. The present implemented system can fly straight and mild curve lane at 2-3 m/s.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.3
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• pp.423-431
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• 2022

The UPS(Uninterruptible Power Supply) system operates in the battery charging mode when the grid is normal, and in the UPS mode, which is the battery discharge mode when a grid error occurs. Since the UPS must supply the same voltage as the grid to the load within 4 [ms] in case of a grid error, the switching time and power recovery time should be short when controlling the output voltage and current of the UPS, and the power failure detection time is also important. The power outage detection algorithm using DFT(Discrete Fourier Transform) proposed in this paper compares the grid voltage waveform with the voltage waveform including the 9th harmonic generated through DFT using Schmitt trigger to detect power outage faster than the existing power outage monitoring algorithm. There are advantages. Therefore, it is possible to supply instant and stable power when switching modes in the UPS system. The multi-power-applied UPS system proposed in this paper uses DFT, which is faster than the conventional blackout monitoring algorithm in detecting power failure, to provide stable power to the load in a shorter time than the existing power outage monitoring algorithm when a system error occurs. The detection method was applied. The changeover time of mode switching was set to less than 4 [ms], which is 1/4 of the system cycle, in accordance with KSC 4310 regulation, which was established by the Industrial Standards Council on the regulation of uninterruptible power supply. A 10 [kW] UPS system in which commercial voltage, vehicle generator, and auxiliary diesel generator can be connected to each of the proposed transfer devices was constructed and the feasibility was verified by conducting an experiment.

• IEMEK Journal of Embedded Systems and Applications
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• v.19 no.3
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• pp.151-158
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• 2024

Although on-device artificial intelligence (AI) has gained attention to diagnosing machine faults in real time, most previous studies did not consider the model retraining and redeployment processes that must be performed in real-world industrial environments. Our study addresses this challenge by proposing an on-device AI-based real-time machine fault diagnosis system that utilizes continual learning. Our proposed system includes a lightweight convolutional neural network (CNN) model, a continual learning algorithm, and a real-time monitoring service. First, we developed a lightweight 1D CNN model to reduce the cost of model deployment and enable real-time inference on the target edge device with limited computing resources. We then compared the performance of five continual learning algorithms with three public bearing fault datasets and selected the most effective algorithm for our system. Finally, we implemented a real-time monitoring service using an open-source data visualization framework. In the performance comparison results between continual learning algorithms, we found that the replay-based algorithms outperformed the regularization-based algorithms, and the experience replay (ER) algorithm had the best diagnostic accuracy. We further tuned the number and length of data samples used for a memory buffer of the ER algorithm to maximize its performance. We confirmed that the performance of the ER algorithm becomes higher when a longer data length is used. Consequently, the proposed system showed an accuracy of 98.7%, while only 16.5% of the previous data was stored in memory buffer. Our lightweight CNN model was also able to diagnose a fault type of one data sample within 3.76 ms on the Raspberry Pi 4B device.

• Journal of Navigation and Port Research
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• v.38 no.4
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• pp.349-356
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• 2014

In the underwater communication, the performance of system is reduced because of the inter-symbol interference occur by the multi-path. In the recent years, to deal with poor channel environment and improve the throughput, the efficient concatenated structure of equalization, channel codes and Space Time Codes has been studied as MIMO system in the underwater communication. Space Time Codes include Space Time Block Codes and Space Time Trellis Codes in underwater communication. Space Time Trellis Codes are optimum for equalization and channel codes among the Space Time Codes to apply in the MIMO environment. Therefore, in this paper, turbo pi codes are used for the outer code to efficiently transmit in the multi-path channel environment. The inner codes consist of Space Time Trellis Codes with transmission diversity and coding gain in the MIMO system. And Zero Forcing method is used to remove inter-symbol interference. Finally, the performance of this model is simulated in the underwater channel.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.6
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• pp.57-65
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• 2007

This paper presents the design of single phase PFC(Power Factor Correction) using a DSP(TMS320F2812). In order to realize the proposed boost PFC converter in average current mode control, the DSP requires the A/D sampling values for a line input voltage, a inductor current, and the output voltage of the converter. Because of a FET switching noise, these sampling values contain a high frequency noise and switching ripple. The solution of A/D sampling keeps away from the switching point. Because the PWM duty is changed from 5% to 95%, we can#t decide a fixed sampling time. In this paper, the three A/D converters of the DSP are started using the prediction algorithm for the FET ON/OFF time at every sampling cycle(40 KHz). Implemented A/D sampling algorithm with only one timer of the DSP is very simple and gives the autostart of these A/D converters. From the experimental result, it was shown that the power factor was about 0.99 at wide input voltage, and the output ripple voltage was smaller than 5 Vpp at 80 Vdc output. Finally the parameters and gains of PI controllers are controlled by serial communication with Windows Xp based PC. Also it was shown that the implemented PFC converter can achieve the feasibility and the usefulness.

• Journal of Korea Society of Industrial Information Systems
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• v.20 no.5
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• pp.61-69
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• 2015

We are in overload status of information not just in a flood of information due to the data pouring from various kinds of mobile devices, online and Social Network Service(SNS) every day. While there are many existing information already created, lots of new information has been created from moment to moment. Linkage analysis has the shortcoming in that it is difficult to find the information we want since the number of rules increases geometrically as the number of item increases with the method of finding out frequent item set where the frequency of item is bigger than minimum support in this information. In this regard, this thesis proposes WT-algorithm that represents the transaction data set as Boolean variable item and grants weight to each item by making algorithm with Quine-McKluskey used to simplify the logical function. The proposed algorithm can improve efficiency of data mining by reducing the unnecessary rules due to the advantage of simplification regardless of number of items.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.6_2
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• pp.1071-1081
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• 2022

As the demand for high-rise buildings increases, the demand for high-speed elevators is also increasing. In order to make a high-speed elevator, a method is needed to reduce the weight of the elevator's components, which is a constraint on the increase in speed. As a measure to reduce the weight, it is possible to remove the traveling cable for power and signal supply. Since the weight of the traveling cable varies depending on the position of the carriage, it is difficult to compensate the weight using the counter weight. The power supply is a structure in which a brush-rail type power input terminal is installed in the elevator hoistway to receive power in a contact-type manner while the carriage is moving. If a small-capacity ESS is installed in a passenger car, power can be supplied uninterruptedly inside the passenger car. A small-capacity ESS charging system to be applied to such an elevator system is required to perform several functions. First, the passenger Car must be able to charge as much as possible even during high-speed operation. A control algorithm with high responsiveness is required because charging starts and ends repeatedly by the partially installed input power stage. In addition, if the input-side line impedance is large due to the structure of the system and the response characteristic is increased, the stability of the system may be lowered. Accordingly, in this paper, we propose a control algorithm that has a stable steady-state output while having a fast response in a transient state. To verify the proposed control algorithm, simulation was conducted using PSIM, and the performance of the controller was verified by manufacturing a prototype buck conveter charger.

• Geomechanics and Engineering
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• v.36 no.3
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• pp.259-276
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• 2024

The undrained shear strength is widely acknowledged as a fundamental mechanical property of soil and is considered a critical engineering parameter. In recent years, researchers have employed various methodologies to evaluate the shear strength of soil under undrained conditions. These methods encompass both numerical analyses and empirical techniques, such as the cone penetration test (CPT), to gain insights into the properties and behavior of soil. However, several of these methods rely on correlation assumptions, which can lead to inconsistent accuracy and precision. The study involved the development of innovative methods using extreme gradient boosting (XGB) to predict the pile set-up component "A" based on two distinct data sets. The first data set includes average modified cone point bearing capacity (q_t), average wall friction (f_s), and effective vertical stress (σ_vo), while the second data set comprises plasticity index (PI), soil undrained shear cohesion (S_u), and the over consolidation ratio (OCR). These data sets were utilized to develop XGBoost-based methods for predicting the pile set-up component "A". To optimize the internal hyperparameters of the XGBoost model, four optimization algorithms were employed: Particle Swarm Optimization (PSO), Social Spider Optimization (SSO), Arithmetic Optimization Algorithm (AOA), and Sine Cosine Optimization Algorithm (SCOA). The results from the first data set indicate that the XGBoost model optimized using the Arithmetic Optimization Algorithm (XGB - AOA) achieved the highest accuracy, with R2 values of 0.9962 for the training part and 0.9807 for the testing part. The performance of the developed models was further evaluated using the RMSE, MAE, and VAF indices. The results revealed that the XGBoost model optimized using XGBoost - AOA outperformed other models in terms of accuracy, with RMSE, MAE, and VAF values of 0.0078, 0.0015, and 99.6189 for the training part and 0.0141, 0.0112, and 98.0394 for the testing part, respectively. These findings suggest that XGBoost - AOA is the most accurate model for predicting the pile set-up component.