• International Journal of Computer Science & Network Security
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• v.23 no.4
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• pp.166-171
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• 2023

The Stock price analysis is an increasing concern in a financial time series. The purpose of the study is to analyze the price parameters of date, high, low, and news feed about the stock exchange price. Long short term memory (LSTM) is a cutting-edge technology used for predicting the data based on time series. LSTM performs well in executing large sequence of data. This paper presents the Long Short Term Memory Model has used to analyze the stock price ranges of 10 days and 20 days by exponential moving average. The proposed approach gives better performance using technical indicators of stock price with an accuracy of 82.6% and cross entropy of 71%.

• The KIPS Transactions:PartD
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• v.16D no.3
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• pp.317-326
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• 2009

Recently, there have been many research efforts proposed on trajectory information. Most of them mainly focus their attention on those objects moving in Euclidean space. Many real-world applications such as telematics, however, deal with objects that move only over road networks, which are highly restricted for movement. Thus, the existing methods targeting Euclidean space cannot be directly applied to the road network space. This paper proposes a new clustering scheme for a large volume of trajectory information of objects moving over road networks. To the end, we first define a trajectory on a road network as a sequence of road segments a moving object has passed by. Next, we propose a similarity measurement scheme that judges the degree of similarity by considering the total length of matched road segments. Based on such similarity measurement, we propose a new clustering algorithm for trajectories by modifying and adjusting the FastMap and hierarchical clustering schemes. To evaluate the performance of the proposed clustering scheme, we also develop a trajectory generator considering the observation that most objects tend to move from the starting point to the destination point along their shortest path, and perform a variety of experiments using the trajectories thus generated. The performance result shows that our scheme has the accuracy of over 95% in comparison with that judged by human beings.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2004.11a
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• pp.273-280
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• 2004

Intra-block remarshalling is the task of rearranging into some target bays those containers whim are scattered around the block, so that the containers can be loaded onto the ship ffficiently. Howeuer, if we rearrange the containers without considering the container larding sequence, too mud! rehandling work will be required at the time rf larding to fetch the right containers whim are stacked under the wrong ones. Therefore, the remarshalling should be done by moving the relevant containers in an appropriate order. This paper presents an efficient heuristic search technique for finding an appropriate container moving order during remarshalling to avoid rehandling at the time of larding. Simulation experiments have shown that the proposed method can generate rehandling-free solutions in a real time.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.43 no.3 s.309
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• pp.31-40
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• 2006

Many researches on path planning and obstacle avoidance for the fundamentals of mobile robot have been done. Informations from various sensors can find obstacles and make path. In spite of many solutions of finding optimal path, each can be applied to only a constrained condition. This means that it is difficult to find a universal algorithm. A optimal path with a complicated computation generates a time delay which cannot avoid moving obstacles. In this paper, we propose the algorithm of path planning and obstacle avoidance for mobile robot. We call the proposed method Random Access Sequence(RAS) method. In the proposed method, a small region is set first and numbers are assigned to its neighbors, then the path is selected using these numbers. It has an advantage of fast planning and simple operation. This means that new path selection may be possible within short time and that helps a robot to avoid obstacle in any direction. When a robot meets moving obstacles, it avoids obstacles in a random direction. RAS method using obstacle information from variable sensors is useful to get minimum path length to goal.

• Journal of the Korea Society of Computer and Information
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• v.11 no.6 s.44
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• pp.279-287
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• 2006

This paper proposes a method to detect fall action by using stereo images to recognize emergency situation. It uses 3D information to extract the visual information for learning and testing. It uses HMM(Hidden Markov Model) as a recognition algorithm. The proposed system extracts background images from two camera images. It extracts a moving object from input video sequence by using the difference between input image and background image. After that, it finds the bounding rectangle of the moving object and extracts 3D information by using calibration data of the two cameras. We experimented to the recognition rate of fall action with the variation of rectangle width and height and that of 3D location of the rectangle center point. Experimental results show that the variation of 3D location of the center point achieves the higher recognition rate than the variation of width and height.

• The Journal of the Acoustical Society of Korea
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• v.16 no.5
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• pp.26-35
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• 1997

This paper deals with establishing correspondent points of feature pints and sampling period when we estimate object motion parameters from image information of freely moving objects in space of gravity-free state. Replacing the inertial coordinate system with the camera coordinate system which is equipped within a space robot, it is investigated to be able to analyze a problem of correspond points from image information, and to obtain sequence of angular velocity $\omega$ which determine a motion of object by means of computer simulation. And if a sampling period ${\Delta}t$ is shortened, the relative errors of angular velocity are increased because the relative errors against moving distance of feature points are increased by quantization. In reverse, if a sampling period ${\Delta}t$ is lengthened too much, the relative error are likewise increased because a sampling period is long for angular velocity to be approximated, and we confirmed the precision that grows according to ascending of resolution.

• Journal of Navigation and Port Research
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• v.29 no.1 s.97
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• pp.83-90
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• 2005

Intra-block remarshalling is the task of rearranging into some target bays those containers which are scattered around within the block, so that the containers can be loaded onto the ship efficiently. However, if we rearrange the containers without considering the container loading sequence, excessive rehandling work will be required at the time of loading because the containers to be fetched are often stacked under other containers. Therefore, the remarshalling should be done by moving the relevant containers in an appropriate order. This paper presents an efficient heuristic search technique for finding an appropriate container moving order during remarshalling to avoid rehandling at the time of loading. Simulation experiments have shown that the proposed method can generate rehandling-free solutions in real time.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.8
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• pp.1537-1545
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• 2016

In real time video sequence, object segmentation and tracking method are actively applied in various application tasks, such as surveillance system, mobile robots, augmented reality. This paper propose a robust object tracking method. The background models are constructed by learning the initial part of each video sequences. After that, the moving objects are detected via object segmentation by using background subtraction method. The region of detected objects are continuously tracked by using the HSV color histogram with particle filter. The proposed segmentation method is superior to average background model in term of moving object detection. In addition, the proposed tracking method provide a continuous tracking result even in the case that multiple objects are existed with similar color, and severe occlusion are occurred with multiple objects. The experiment results provided with 85.9 % of average object overlapping rate and 96.3% of average object tracking rate using two video sequences.

• Journal of Power Electronics
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• v.16 no.5
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• pp.1904-1917
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• 2016

The moving average filter (MAF) is widely utilized to improve the disturbance rejection capability of phase-locked loops (PLLs). This is of vital significance for the grid-integration and stable operation of power electronic converters to electric power systems. However, the open-loop bandwidth is drastically reduced after incorporating a MAF into the PLL structure, which makes the dynamic response sluggish. To overcome this shortcoming, some new techniques have recently been proposed to improve the transient response of MAF-based PLLs. In this paper, a comprehensive performance comparison of advanced MAF-based PLL algorithms is presented. This comparison includes HPLL, MPLC-PLL, QT1-PLL, and DMAF-PLL. Various disturbances, such as grid voltage sag, voltage flicker, harmonics distortion, phase-angle and frequency jumps, DC offsets and noise, are considered to experimentally test the dynamic performances of these PLL algorithms. Finally, an improved positive sequence extraction method for a HPLL under the frequency jumps scenario is presented to compensate for the steady-state error caused by non-frequency adaptive DSC, and a satisfactory performance has been achieved.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.2
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• pp.281-288
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• 2016

The natural moving objects are the most non-rigid shapes with randomly time-varying deformation, and its types also very diverse. Methods of non-rigid shape reconstruction have widely applied in field of movie or game industry in recent years. However, a realistic approach requires moving object to stick many beacon sets. To resolve this drawback, non-rigid shape reconstruction researches from input video without beacon sets are investigated in multimedia application fields. In this regard, our paper propose novel CPSRF(Chained Partial Stereo Rigid Factorization) algorithm that can reconstruct a non-rigid 3D shape. Our method is focused on the real-time reconstruction of non-rigid 3D shape and motion from stereo 2D video sequences per frame. And we do not constrain that the deformation of the time-varying non-rigid shape is limited by a Gaussian distribution. The experimental results show that the 3D reconstruction performance of the proposed CPSRF method is superior to that of the previous method which does not consider the random deformation of shape.