• The Transactions of the Korean Institute of Power Electronics
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• v.24 no.2
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• pp.111-119
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• 2019

In this study, constant power generation (CPG) algorithms are introduced for whole range power point tracking in photovoltaic systems. Currently, maximum power point tracking (MPPT) algorithm is widely used for high-power photovoltaic systems. However, MPPT algorithm cannot flexibly control such systems according to changing grid conditions. Maintaining grid stability has become important as the capacity of grid-connected photovoltaic systems is increased. CPG algorithms are required to generate the desired power depending on grid conditions. A grid-connected photovoltaic system is configured, and CPG algorithms are implemented. The performances of the implemented algorithms are compared and analyzed by experimental results.

• The Transactions of the Korean Institute of Power Electronics
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• v.27 no.1
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• pp.18-25
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• 2022

The cold staring issue of permanent magnet synchronous motors (PMSM) is a chronic problem in the field of PMSM sensorless drives. A traditional starting method, called the I-F method, is widely adopted because of its simple structure. However, when using this method, the pre-defined magnitude and frequency of the starting current should be changed according to the condition of the load and machine inertia. In this paper, a smart and simple algorithm for the cold starting of PMSM is proposed. In the proposed method, an integrated control angle from the estimated electrical rotor speed is used for vector control such as the indirect vector control of the induction machine. Thus, very stable cold starting is performed regardless of the machine load condition or inertia changing.

• International journal of advanced smart convergence
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• v.12 no.4
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• pp.111-118
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• 2023

In the ever-changing landscape of finance, the fusion of artificial intelligence (AI)and pair trading strategies has captured the interest of investors and institutions alike. In the context of supervised machine learning, crafting precise and accurate labels is crucial, as it remains a top priority to empower AI models to surpass traditional pair trading methods. However, prevailing labeling techniques in the financial sector predominantly concentrate on individual assets, posing a challenge in aligning with pair trading strategies. To address this issue, we propose an inventive approach that melds the Triple Barrier Labeling technique with pair trading, optimizing the resultant labels through genetic algorithms. Rigorous backtesting on cryptocurrency datasets illustrates that our proposed labeling method excels over traditional pair trading methods and corresponding buy-and-hold strategies in both profitability and risk control. This pioneering method offers a novel perspective on trading strategies and risk management within the financial domain, laying a robust groundwork for further enhancing the precision and reliability of pair trading strategies utilizing AI models.

• Wind and Structures
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• v.39 no.2
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• pp.101-110
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• 2024

Tall buildings are distinguished by their slenderness, making them sensitive to wind loads. A huge amount of resources is typically dedicated to controlling loads and vibrations caused by wind. Enhancing tall buildings' aerodynamic performance can save a large portion of these expenses. This enhancement can be achieved through aerodynamic optimization that can be tackled either by altering the outer shape of the building locally through modifying the corners (e.g., corner chamfering) or globally through changing the whole form of the building (e.g., twisting). In this paper, a newly developed aerodynamic optimization procedure (AOP) is adopted to enhance tall buildings' aerodynamic performance. This procedure is a combination of computational fluid dynamics (CFD), Artificial Neural Networks (ANN) and Genetic algorithm (GA). An ANN-based surrogate model is used to evaluate the aerodynamic parameters through the optimization procedure to reach a reliable aerodynamic shape. Helical twisting and corner modifications of the buildings are used to reduce the along-wind base moment.

• Journal of Korea Multimedia Society
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• v.22 no.12
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• pp.1415-1429
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• 2019

Nowadays object tracking process becoming one of the most challenging task in Computer Vision filed. A CSR-DCF (channel spatial reliability-discriminative correlation filter) tracking algorithm have been proposed on recent tracking benchmark that could achieve stat-of-the-art performance where channel spatial reliability concepts to DCF tracking and provide a novel learning algorithm for its efficient and seamless integration in the filter update and the tracking process with only two simple standard features, HoGs and Color names. However, there are some cases where this method cannot track properly, like overlapping, occlusions, motion blur, changing appearance, environmental variations and so on. To overcome that kind of complications a new modified version of CSR-DCF algorithm has been proposed by integrating deep learning based object detection and CSRT tracker which implemented in OpenCV library. As an object detection model, according to the comparable result of object detection methods and by reason of high efficiency and celerity of Faster RCNN (Region-based Convolutional Neural Network) has been used, and combined with CSRT tracker, which demonstrated outstanding real-time detection and tracking performance. The results indicate that the trained object detection model integration with tracking algorithm gives better outcomes rather than using tracking algorithm or filter itself.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.12
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• pp.3675-3681
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• 2009

One of the most important factors in the lifetime of WSN(Wireless Sensor Network) is the limited resources and static control problem of the sensor nodes. In order to achieve energy efficiency and network utilities, sensor nodes can be well organized into one cluster and selected head node and normal node by dynamic conditions. Various clustering algorithms have been proposed as an efficient way to organize method based on LEACH algorithm. In this paper, we propose an efficient clustering algorithm using information entropy theory based on LEACH algorithm, which is able to recognize environmental differences according to changes from data of sensor nodes. To measure and analyze the changes of clusters, we simply compute the entropy of sensor data and applied it to probability based clustering algorithm. In experiments, we simulate the proposed method and LEACH algorithm. We have shown that our data balanced and energy efficient scheme, has high energy efficiency and network lifetime in two conditions.

• Journal of Welding and Joining
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• v.31 no.5
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• pp.35-40
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• 2013

In this paper, we propose the Tangible Virtual Reality Representation Method to using haptic device and feature to morphology of created bead from Flux Cored Arc Welding. The virtual reality was started to rising for reduce to consumable materials and welding training risk. And, we will expected maximize virtual reality from virtual welding training. In this paper proposed method is get the database to changing the input factor such as work angle, travelling angle, speed, CTWD. And, it is visualization to bead from extract to optimal morphological feature information to using the Neural Network algorithm. The database was building without error to extract data from automatic robot welder. Also, the Neural Network algorithm was set a dataset of the highest accuracy from verification process in many times. The bead was created in virtual reality from extract to morphological feature information. We were implementation to final shape of bead and overlapped in process by time to using bead generation algorithm and calibration algorithm for generate to same bead shape to real database in process of generating bead. The best advantage of virtual welding training, it can be get the many data to training evaluation. In this paper, we were representation bead to similar shape from generated bead to Flux Cored Arc Welding. Therefore, we were reduce the gap to virtual welding training and real welding training. In addition, we were confirmed be able to maximize the performance of education from more effective evaluation system.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.2
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• pp.60-67
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• 2017

A baggage handling system (BHS) in airport is an unified system for moving the passengers' baggage in designated time. Input baggage from the check-in counter travels to the baggage claim area or cargo handling terminal through this system. In particular, entryway BHS consists of conveyors, X-ray and sorters such as tilt-tray to send the baggage to departing airplane and it could have various problems for handling certain amount of baggage in restricted time such as baggage jamming at certain merge point. This causes systemic error such as delay of the time, omissions of the baggage and even breakdown of the equipment and inefficiency. Also the increasing maximum time of the baggage passing through the BHS could delay the flight schedule and finally decrease the service level. Thus, the algorithm for controlling the flow of the merge is essential to the system. The window reservation algorithm is the one of the most frequently used methods to control the merge configuration. Above all, the reserve location, so called reserve ahead point, that allocates the window is important for the performance of the algorithm. We propose the modified window reservation algorithm and the best reserve locations by changing the reserve ahead point in the induction conveyors. The effect of various reserve ahead points such as the capacity and utility of the system were analyzed and the most effective reserve ahead point combination was found. The total baggage processing time and the utilization of the tilt-tray are properly considered when choosing the optimal Reserve ahead point combination. In the layout of this study, the configuration of four conveyors merged into one tilt-tray is studied and simulation analysis is done by AutoMod(R), 3D simulation software. Through the simulation, the window reservation algorithm is effectively operated with the best combination of reserve ahead point which reduces the maximum baggage travel time.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.2B
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• pp.178-187
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• 2009

Cognitive radio (CR) technology is to maximize the spectrum utilization by allocating the unused spectrums to the unlicensed users. In CR environment, it is strictly required for the unlicensed users not to interference with the licensed users. Thus, it is essential to rely on the scheduling algorithm to avoid the interference when utilizing spectrum holes that are changing in time and frequency. However, the existing scheduling algorithms that are applied for the wireless communication environment considering the licensed users only is not appropriate for CR environment. In this paper, we propose downlink scheduling algorithm based on probability of incumbent user presence for cognitive radio networks. With computer simulations, it is shown that the proposed scheduling algorithm outperforms the conventional scheduling algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.1
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• pp.28-35
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• 2014

Surveillance cameras in national border and coastline area often occur the video distortion because of rapidly changing weather and light environments. It is positively necessary to enhance the distorted video quality for keeping surveillance. In this paper, we propose an adaptive video enhancement algorithm in the various environment changes. To solve an unstable performance problem of the existing method, the proposed method is based on Retinex algorithm and uses enhanced curves which is adapted in foggy and low-light conditions. In addition, we mixture the weighted HSV color model to keep color constancy and reduce noise to obtain clear images. As a results, the proposed algorithm improves the performance of well-balanced contrast enhancement and effective color restoration without any quality loss compared with the existing algorithm. We expect that this method will be used in surveillance camera systems and offer help of national defence with reliability.