• International Journal of Computer Science & Network Security
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• v.21 no.8
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• pp.127-136
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• 2021

Real-time human recognition is a challenging task, as the images are captured in an unconstrained environment with different poses, makeups, and styles. This limitation is addressed by generating several facial images with poses, makeup, and styles with a single reference image of a person using Generative Adversarial Networks (GAN). In this paper, we propose deep learning-based human recognition using integration of GAN and Spatial Domain Techniques. A novel concept of human recognition based on face depiction approach by generating several dissimilar face images from single reference face image using Domain Transfer Generative Adversarial Networks (DT-GAN) combined with feature extraction techniques such as Local Binary Pattern (LBP) and Histogram is deliberated. The Euclidean Distance (ED) is used in the matching section for comparison of features to test the performance of the method. A database of millions of people with a single reference face image per person, instead of multiple reference face images, is created and saved on the centralized server, which helps to reduce memory load on the centralized server. It is noticed that the recognition accuracy is 100% for smaller size datasets and a little less accuracy for larger size datasets and also, results are compared with present methods to show the superiority of proposed method.

• Journal of KIISE:Computer Systems and Theory
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• v.29 no.7
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• pp.369-376
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• 2002

Although LRU is not adequate for database that has non-uniform reference pattern, it has been adopted in most database systems due to the absence of the proper alternative. We analyze database block reference pattern with the realistic database trace. Based on this analysis, we propose a new cache replacement policy. Trace analysis shows that extremely non-popular blocks take up about 70 % of the entire blocks. The influence of recency on blocks' re-reference likelihood is at first strong due to temporal locality, however, it rapidly decreases and eventually becomes negligible as stack distance increases. Based on this observation, RCB(Reference Characteristic Based) cache replacement policy, which we propose in this paper, classifies the entire blocks into four block groups by blocks' recency and re-reference likelihood, and operates different priority evaluation methods for each block group. RCB policy evicts non-popular blocks more quickly than the others and evaluates the priority of the block by frequency that has not been referenced for a long time. In a trace-driven simulation, RCB delivers a better performance than the existing polices(LRU, 2Q, LRU-K, LRFU). Especially compared to LRU. It reduces miss count by 5~l2.7%. Time complexity of RCB is O(1), which is the same with LRU and 2Q and superior to LRU-K(O(log$_2$N)) and LRFU(O(l) ~ O(log$_2$N)).

• The Journal of the Acoustical Society of Korea
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• v.10 no.2
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• pp.23-28
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• 1991

This paper is a study on isolated word recognition by independent speaker, we propose DTW speech recognition system by modified dynamic averaging method as reference pattern. 57 city names are selected as recognition vocabulary and 2th LPC cepstrum coefficients are used as the feature parameter. In this paper, besides recognition experiment using modified dynamic averaging method as reference pattern, we perform recognition experiments using causal method, dynamic averaging method, linear averaging method and clustering method with the same data in the same conditions for comparison with it. Through the experiment result, it is proved that recogntion rate by DTW using modified dynamic averaging method is the best as 97.6 percent.

• IEIE Transactions on Smart Processing and Computing
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• v.4 no.1
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• pp.1-9
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• 2015

Template matching is used for many applications in image processing. One of the most researched topics is object tracking. Normalized Cross Correlation (NCC) is the basic statistical approach to match images. NCC is used for template matching or pattern recognition. A template can be considered from a reference image, and an image from a scene can be considered as a source image. The objective is to establish the correspondence between the reference and source images. The matching gives a measure of the degree of similarity between the image and the template. A problem with NCC is its high computational cost and occasional mismatching. To deal with this problem, this paper presents an algorithm based on the Sum of Squared Difference (SSD) and an adaptive template matching to enhance the quality of the template matching in object tracking. The SSD provides low computational cost, while the adaptive template matching increases the accuracy matching. The experimental results showed that the proposed algorithm is quite efficient for image matching. The effectiveness of this method is demonstrated by several situations in the results section.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.399-399
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• 2000

In this paper, path generation using the sensor platform is proposed. The sensor platform is composed two electric motors which make panning and tilting motions. An algorithm fur a real path form and an obstacle length is realized using a scanning algorithm to rotating the sensors on the sensor platform. An ARV (Autonomous Robot Vehicle) is able to recognize the given path by adapting this algorithm. In order for the ARV to navigate the path flexibly, a kinematic model needed to be constructed. The kinematic model of the ARV was reformed around its body center through a relative velocity relationship to controllability, which derives from the nonholonomic characteristics. The optimal controller that is based on tile kinematic model is operated purposefully to track a reference vehicle's path. The path generation algorithm is composed of two parks. On e part is the generating path pattern, and the other is used to avoid an obstacle. The optimal controller is used for tracking the reference path which is generated by recognizing the path pattern. Results of simulation show that this algorithm for an ARV is sufficient for path generation by small number of sensors and for low cost controller.

• The Journal of the Acoustical Society of Korea
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• v.15 no.2E
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• pp.60-68
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• 1996

In this paper, we implement the door lock system based on pattern matching technique for speaker recognition using DTW. In this study, major features of our system are summarized as follows:(1) Make the average reference pattern using DTW. This method keeps the high recognition rate compared with the other systems whose performances degrade rapidly as time goes on. (2) Use F-ratio values of the cepstral coefficients. We find that the weighted cepstral reveals an effect on intensifying the difference between th customer and the imposter. The system hardware is composed of two parts : the door lock part and the speaker recognition processing part. We use an 8051 microprocessor in the door lock park for serial communication with host processor to open or close the lock. Using our system, we obtain speaker recognition rate of about 99.5%.

• Journal of Electrical Engineering and Technology
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• v.10 no.6
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• pp.2368-2375
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• 2015

To accommodate various navigational commands, a humanoid should be able to change its walking motion in real time. Using the modifiable walking pattern generation (MWPG) algorithm, a humanoid can handle dynamic walking commands by changing its walking period, step length, and direction independently. If the humanoid is given a command to perform an infeasible movement, the algorithm substitutes the infeasible command with a feasible one using binary search. The feasible navigational command is subsequently translated into the desired center-of-mass (CM) state. Every sample time CM reference is generated using a zero-moment-point (ZMP) variation scheme. Based on this algorithm, various complex walking patterns can be generated, including backward and sideways walking, without detailed consideration of the feasibility of the navigational commands. In a previous study, the effectiveness of the MWPG algorithm was verified by dynamic simulation. This paper presents experimental results obtained using the small-sized humanoid robot platform DARwIn-OP.

• Journal of Information Technology Services
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• v.11 no.3
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• pp.89-101
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• 2012

The study investigated if IT investment in Korean financial markets for the past 18 years has grown following the s-curve pattern based on Nolan's growth model in order to find the correlation between IT investment and management performance in the financial industry. According to the research finding it can be said that the overall financial markets maintain s-curve pattern, and IT investment is related to management performance, particularly increase in total assets and net profit. However, each sector has defining features of growth patterns. The banking industry has grown similarly to the s-curve, and the insurance industry also shows the s-curve but it looks more like linear pattern. In terms of securities industry, its growth patterns can hardly be considered s-curve due to the irregular changes. his research outcome illustrates the analysis of IT growth patterns in the financial industry and thus, it is expected to be a useful reference when deciding the appropriate time for IT investment in the financial industry.

• Journal of Electrical Engineering and Technology
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• v.11 no.3
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• pp.751-758
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• 2016

The modifiable walking pattern generation (MWPG) algorithm can handle dynamic walking commands by changing the walking period, step length, and direction independently. When an infeasible command is given, the algorithm changes the command to a feasible one. After the feasibility of the navigational command is checked, it is translated into the desired center of mass (CM) state. To achieve the desired CM state, a reference CM trajectory is generated using predefined zero moment point (ZMP) functions. Based on the proposed algorithm, various complex walking patterns were generated, including backward and sideways walking. The effectiveness of the patterns was verified in dynamic simulations using the Webots simulator.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2016.05a
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• pp.156-157
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• 2016

Construction projects have shown a dramatic increase in size and complexity during the recent years that precise management has been recognized as one of key factors leading the project to success. It has been investigated that management in construction sites is generally done based on the experience of site engineers. Such experience based decision making lacks reliability that could bring disastrous results such as delay and cost overruns. The purpose of this study is to suggest a process progress pattern analysis method that is expected to be used as an objective reference for site managers to aid the decision making done regarding process progress management.