• Smart Media Journal
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• v.7 no.4
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• pp.90-98
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• 2018

A Multilinear LDA Method of Tensor Representation for ECG Signal Based Individual Identification Electrocardiogram signals, included in the cardiac electrical activity, are often analyzed and used for various purposes such as heart rate measurement, heartbeat rhythm test, heart abnormality diagnosis, emotion recognition and biometrics. The objective of this paper is to perform individual identification operation based on Multilinear Linear Discriminant Analysis (MLDA) with the tensor feature. The MLDA can solve dimensional aspects of classification problems in high-dimensional tensor, and correlated subspaces can be used to distinguish between different classes. In order to evaluate the performance, we used MPhysionet's MIT-BIH database. The experimental results on this database showed that the individual identification by MLDA outperformed that by PCA and LDA.

• Journal of the Korea Society of Computer and Information
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• v.23 no.11
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• pp.51-57
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• 2018

In this paper, we studied about the extraction of the parameter and implementation of speechreading system to recognize the Korean 8 vowel. Face features are detected by amplifying, reducing the image value and making a comparison between the image value which is represented for various value in various color space. The eyes position, the nose position, the inner boundary of lip, the outer boundary of upper lip and the outer line of the tooth is found to the feature and using the analysis the area of inner lip, the hight and width of inner lip, the outer line length of the tooth rate about a inner mouth area and the distance between the nose and outer boundary of upper lip are used for the parameter. 2400 data are gathered and analyzed. Based on this analysis, the neural net is constructed and the recognition experiments are performed. In the experiment, 5 normal persons were sampled. The observational error between samples was corrected using normalization method. The experiment show very encouraging result about the usefulness of the parameter.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.1
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• pp.213-218
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• 2019

In this paper, we study autonomous navigation system for path guide system by using RFID that is enable to navigate and load in hotel. In case of a mobile robot used in a general autonomous navigation guidance system, a large amount of sensors are added to the system in order to improve the accuracy, resulting in cost problems. Therefore, to reduce the number of sensors, and to increase the accuracy and recognition rate, an autonomous driving guidance system was implemented using one of the inexpensive small micro controller units (MCU) such as Raspberry Pi3.

• Journal of Korea Multimedia Society
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• v.22 no.2
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• pp.186-193
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• 2019

Visible light communication technology is being studied and developed in various ways due to advantages such as high transmission speed, excellent positioning and higher security. However, existing visible light communication systems have difficulties in entering the market because they use special transmitters and receivers. We will overcome the difficulty if we develope a VLC system that uses a conventional LED light as a transmitter and a smartphone camera as a receiver. What matters is that LED lights include a scatter filter to prevent glareness for human eyes, but the existing VLC(Visual Light Communication) method can not be applied. In this paper, we propose a method to encode data with On / Off patterns of LEDs in the lighting with $M{\times}N$ LEDs. We defined parameters like L-off-able and K-seperated to facilitate the recognition of On / Off patterns in the diffused Lights. We conducted experiments using an LED lighting and smart phones to determine the parameter values. Also, the maximum transmission rate of our encoding technique is mathematically presented. Our encoding scheme can be applied to indoor and outdoor positioning applications or settlement of commercial transactions.

• Journal of the Korea Society of Computer and Information
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• v.23 no.12
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• pp.43-48
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• 2018

In this paper, more efficient classification result could be obtained by applying the combination of the Hidden Markov Model and SVM Model to HMSV algorithm gene expression data which simulated the stochastic flow of gene data and clustering it. In this paper, we verified the HMSV algorithm that combines independently learned algorithms. To prove that this paper is superior to other papers, we tested the sensitivity and specificity of the most commonly used classification criteria. As a result, the K-means is 71% and the SOM is 68%. The proposed HMSV algorithm is 85%. These results are stable and high. It can be seen that this is better classified than using a general classification algorithm. The algorithm proposed in this paper is a stochastic modeling of the generation process of the characteristics included in the signal, and a good recognition rate can be obtained with a small amount of calculation, so it will be useful to study the relationship with diseases by showing fast and effective performance improvement with an algorithm that clusters nodes by simulating the stochastic flow of Gene Data through data mining of BigData.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.4
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• pp.781-786
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• 2019

We should give a realistic value on the large amounts of relevant data obtained from these studies to achieve effective objectives of the disease study which is dealing with various vital phenomenon today. In this paper, the proposed MKSV algorithm is estimated by optimal probability distribution, and the input pattern is determined. After classifying it into data mining, it is possible to obtain efficient computational quantity and recognition rate. MKSV algorithm is useful for studying the relationship between disease and gene in the present society by simulating the probabilistic flow of gene data and showing fast and effective performance improvement to classify data through the data mining process of big data.

• Journal of Korea Game Society
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• v.19 no.4
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• pp.97-108
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• 2019

Recently interests in voice game commands have been increasing due to the diversity and convenience of the input method, but also by the distance between commands. The command distance is the phonetic difference between command utterances, and as such distance increases, the recognition rate improves. In this paper, we propose an IP(Integer Programming) modeling of the problem which is to select a combination of commands from given candidate commands for maximizing the average distance. We also propose a SA(Simulated Annealing)-based algorithm for solving the problem. We analyze the characteristics of our method using experiments under various conditions such as the number of commands, allowable command length, and so on.

• Microbiology and Biotechnology Letters
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• v.49 no.3
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• pp.425-431
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• 2021

The use of big data may facilitate the recognition and interpretation of causal relationships between disease occurrence and climatic variables. Considering the immense contribution of rhinoviruses in causing respiratory infections, in this study, we examined the effects of various climatic variables on the seasonal epidemiology of rhinovirus infections in the temperate climate of Cheonan, Korea. Trends in rhinovirus detection were analyzed based on 9,010 tests performed between January 1, 2012, and December 31, 2018, at Dankook University Hospital, Cheonan, Korea. Seasonal patterns of rhinovirus detection frequency were compared with the local climatic variables for the same period. Rhinovirus infection was the highest in children under 10 years of age, and climatic variables influenced the infection rate. Temperature, wind chill temperature, humidity, and particulate matter significantly affected rhinovirus detection. Temperature and wind chill temperature were higher on days on which rhinovirus infection was detected than on which it was not. Conversely, particulate matter was lower on days on which rhinovirus was detected. Atmospheric pressure and particulate matter showed a negative relationship with rhinovirus detection, whereas temperature, wind chill temperature, and humidity showed a positive relationship. Rhinovirus infection was significantly related to climatic factors such as temperature, wind chill temperature, atmospheric pressure, humidity, and particulate matter. To the best of our knowledge, this is the first study to find a relationship between daily temperatures/wind chill temperatures and rhinovirus infection over an extended period.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.4
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• pp.549-557
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• 2021

In this research, we will use the existing OID sensor environment for smart robots, which are a type of educational robot, but we would like to propose that the problem of running be handled by a program. Maybe you have driving information We are building a driving test environment focusing on environment, position recognition, route planning, obstacle avoidance and path reset, and it is not the average final error rate, but the time when the error increases The experiment was conducted by a household that catches the moment of recalibration. Through the process, stable running results were obtained compared to the previous experiment. In this research, I think that it will be a development method that can improve the running performance of educational robots equipped with low-cost sensors currently on the market.

• Annual Conference of KIPS
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• 2013.11a
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• pp.389-391
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• 2013

실내공간에서 사용자 재실인원수를 파악하기 위한 일반적인 방법으로는 출입구의 내 외부 벽면에 인체감지용 센서를 두 개 이상 설치하여 센서 ID별로 감지되는 순서에 따라 사용자의 입 퇴실 상황을 판별하는 것이다. 기존에 사용되고 있는 대부분의 인체 감지용 센서시스템은 동일한 종류의 센서를 조합한 형태로서 각 센서의 종류에 따른 동작방식 및 하드웨어적 특징에 따라 빛이나 온도 등의 주변 환경 요소와 장애물 등에 의해 오작동하는 문제점을 가지고 있다. 이에 본 논문에서는 적외선, 초음파, 마이크로웨이브 등 세 가지 인체감지용 센서를 다양하게 조합할 수 있는 하이브리드 센서 모듈을 이용하여 사용자의 입 퇴실 상황과 공간 내 재실인원수를 정확하게 인식하기 위한 최적의 센서 조합을 파악한다. 실험 결과, 내부/외부 모두 적외선 센서 또는 마이크로웨이브 센서를 조합하거나 내부/외부에 적외선 및 마이크로웨이브 센서를 조합한 시스템이 타 센서를 조합한 시스템에 비해 우수한 성능을 보였다.