• Journal of the Institute of Electronics Engineers of Korea SD
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• v.37 no.8
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• pp.76-85
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• 2000

Effects of the random fluctuation in grating half-period have been studied by an effective index transfer matrix method in DFB lasers. The laser facets are assumed to be perfectly antireflection coated, and the period fluctuation is modeled as a Gaussian random variable. The random fluctuation breaks spectral symmetry in both uniform-grating and quarter-wavelength -shifted(QWS) DFB lasers, and decreases the effective coupling coefficient. This leads to increased average mirror loss of ${\pm}$1 modes and reduced stopband width in uniform grating DFB lasers, and degradation in the wavelength accuracy and the single mode stability in QWS-DFB lasers. Threshold gain difference decreases with increasing period fluctuation irrespective of grating coupling coefficient in QWS-DFB lasers, while spatial hole-burning effect is exacerbated or alleviated when the normalized coupling coefficient is lower and higher than 1.5, respectively.

• The KIPS Transactions:PartD
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• v.15D no.4
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• pp.531-540
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• 2008

An Adaptive Random Testing(ART) is one of test case generation algorithms, which was designed to get better performance in terms of fault-detection capability than that of Random Testing(RT) algorithm by locating test cases in evenly spreaded area. Two ART algorithms, such as Distance-based ART(D-ART) and Restricted Random Testing(RRT), had been indicated that they have significant drawbacks in computations, i.e., consuming quadratic order of runtime. To reduce the amount of computations of D-ART and RRT, iterative partitioning of input domain strategy was proposed. They achieved, to some extent, the moderate computation cost with relatively high performance of fault detection. Those algorithms, however, have yet the patterns of non-uniform distribution in test cases, which obstructs the scalability. In this paper we analyze the distribution of test cases in an iterative partitioning strategy, and propose a new method of input domain enlargement which makes the test cases get much evenly distributed. The simulation results show that the proposed one has about 3 percent of improvement in terms of mean relative F-measure for 2-dimension input domain, and shows 10 percent improvement for 3-dimension space.

• Proceedings of the Korea Society for Simulation Conference
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• 2001.05a
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• pp.132-132
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• 2001

본 논문에서는 혼합예약요청(hybrid reservation request) 알고리즘을 적용한 새로운 동적 예약 TDMA 프로토콜을 제안한다. 제안된 혼합 예약 요청 알고리즘은 기존의 랜덤접속방식과 기지국의 중재 없이 단말간 직접 신호교환을 통하여 이웃 단말의 새로운 예약 요청을 대신 전송하는 방식을 혼합해서 사용하는 방법이다. 이 알고리즘은 기존 slotted-ALOHA 방식을 이용한 예약 요청의 비효율성을 개선하여 새로운 단말의 예약 요청실패로 인한 셀 전송지연 및 호 봉쇄 확률(call blocking probability)을 줄이기 위한 목적으로 제안되었다. 제안한 알고리즘은 새로 전송할 데이터를 가진 단말이 많은 경우에 특히 효율적이다. 본 논문에서 제안하는 프로토콜은 모든 종류의 트래픽이 예약을 통한 전송방식으로 전송된다. 즉, 단말들로부터의 예약 요청을 바탕으로, 기지국이 스케줄링을 하여 트래픽 별로 접근 슬랏을 할당해 주는 방식이다. 이 경우, 예약 요청을 하는 방법은 새로 전송을 개시하는 단말과 이미 전송중인 단말의 경우가 다른데, 새로운 전송을 위한 예약이 필요한 단말은 제안하는 알고리즘을 이용하며, 이미 예약에 성공한 단말은 기존에 사용하던 자신의 버스트헤더(burst header)에 피기백(piggybacking)하는 방법을 이용한다. 제안한 알고리즘에 따라, 새로 접속하는 단말이나 새로운 예약 요청이 필요한 단말은 두 단계로 요청을 전송할 수 있다. 첫 번째 단계는 이미 예약에 성공하여 전송중인 이웃단말에게 전송요청신호를 보내 간접적으로 기지국에게 예약을 요청하는 방법이며, 두 번째 단계는 첫 번째 방법이 실패했을 경우 기존의 랜덤접속방법에 참가하는 것이다 먼저 첫 번째 방법에서는 단말이 랜덤접근 구간의 예약요청구간(resonation request)중 하나의 미니 슬랏을 선택해 이웃 단말들에게 한번 방송(broadcast) 한다 이후 ACK 응답구간(ACK receive)에서 응답을 받으면 예약요청성공이라 간주하고, 그렇지 않으면 실패로 판단, 뒤이어 오는 랜덤접근구간(normal random access period)에 참가하여 기지국에게 직접 예약 요청을 한다. 시뮬레이션은 기존 slotted-ALOHA방식으로 랜덤 접속을 할 경우와 제안한 방식과의 성공률을 비교해 제안한 방식의 call blocking probability가 낮음을 보였다.

• Journal of Digital Convergence
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• v.18 no.4
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• pp.243-250
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• 2020

Systematic farming can be planned and managed if long-term agricultural weather information of the plantation is available. Because the greatest risk factor for crop cultivation is the weather. In this study, a method for long-term predicting of agricultural weather using the GloSea5 and machine learning is presented for the cultivation of Chinese cabbage. The GloSea5 is a long-term weather forecast that is available up to 240 days. The deep neural networks and the spatial randomforest were considered as the method of machine learning. The longterm prediction performance of the deep neural networks was slightly better than the spatial randomforest in the sense of root mean squared error and mean absolute error. However, the spatial randomforest has the advantage of predicting temperatures with a global model, which reduces the computation time.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.6
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• pp.100-105
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• 2017

This work presents an ECG biometric recognition system for the purpose of biometric authentication. ECG biometric approaches are divided into two major categories, fiducial-based and non-fiducial-based methods. This paper proposes a new non-fiducial framework using discrete cosine transform and a Random Forest classifier. When using DCT, most of the signal information tends to be concentrated in a few low-frequency components. In order to apply feature vector of Random Forest, DCT feature vectors of ECG heartbeats are constructed by using the first 40 DCT coefficients. RF is based on the computation of a large number of decision trees. It is relatively fast, robust and inherently suitable for multi-class problems. Furthermore, it trade-off threshold between admission and rejection of ID inside RF classifier. As a result, proposed method offers 99.9% recognition rates when tested on MIT-BIH NSRDB.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.9
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• pp.2014-2021
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• 2015

Opportunistic interference alignment (OIA) has been proposed for multi-cell random access networks (RAN), which minimizes the generating interference to neighboring RANs and yields better performance compared with the conventional techniques. The OIA for RANs considers both physical (PHY) and medium access control (MAC) layers. In this paper, we introduce a protocol of which each user maximizes the transmit signal regardless of the generating interference to neighboring RANs, contrary to the OIA technique. In addition, we compare the performance of the signal-maximization technique with the OIA technique.

• Smart Media Journal
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• v.5 no.1
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• pp.38-43
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• 2016

As smart environment is spread out in our living environments, the needs of an approach related to Human Computer Interaction(HCI) is increases. One of them is head pose estimation. it related to gaze direction estimation, since head has a close relationship to eyes by the body structure. It's a key factor in identifying person's intention or the target of interest, hence it is an essential research in HCI. In this paper, we propose an approach for head pose estimation with pre-defined several directions by random forest classifier. We use canny edge detector to extract feature of the different facial image which is obtained between input image and averaged frontal facial image for extraction of rotation information of input image. From that, we obtain the binary edge image, and make two accumulated histograms which are obtained by counting the number of pixel which has non-zero value along each of the axes. This two accumulated histograms are used to feature of the facial image. We use CAS-PEAL-R1 Dataset for training and testing to random forest classifier, and obtained 80.6% accuracy.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.5
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• pp.1001-1008
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• 2019

A high-quality pseudorandom sequence generation is an important part of many cryptographic applications, including encryption protocols. Therefore, a pseudorandom number generator (PRNG) is an essential element for generating key sequences in a cryptosystem. A PRNG must effectively generate a large, high-quality random data stream. It is well known that the bitstreams output by the CA-based PRNG are more random than the bitstreams output by the LFSR-based PRNG. In this paper, we prove that the complemented CA derived from 90/150 maximum length cellular automata(MLCA) is a MLCA to design a PRNG that can generate more secure bitstreams and extend the key space in a secret key cryptosystem. Also we give a method for calculating the cell positions outputting a nonlinear sequence with maximum period in complemented MLCA derived from a 90/150 MLCA and a complement vector.

• Journal of the Korean Society for information Management
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• v.36 no.2
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• pp.57-77
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• 2019

Random Forest (RF), a representative ensemble technique, was applied to automatic classification of journal articles in the field of library and information science. Especially, I performed various experiments on the main factors such as tree number, feature selection, and learning set size in terms of classification performance that automatically assigns class labels to domestic journals. Through this, I explored ways to optimize the performance of random forests (RF) for imbalanced datasets in real environments. Consequently, for the automatic classification of domestic journal articles, Random Forest (RF) can be expected to have the best classification performance when using tree number interval 100~1000(C), small feature set (10%) based on chi-square statistic (CHI), and most learning sets (9-10 years).

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.7
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• pp.875-880
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• 2019

A RC4 stream cipher is widely used for security applications such as IEEE 802.11 WEP, IEEE 802.11i TKIP and so on, because it can be simply implemented to dedicated circuits and achieve a high-speed encryption. RC4 is also used for systems with limited resources like IoT, but there are performance limitations. RC4 consists of two stages, KSA and PRGA. KSA performs initialization and randomization of S-box and K-box and PRGA produces cipher texts using the randomized S-box. In this paper, we initialize the S-box and K-box in the randomization of the KSA stage to reduce the initialization delay. In the randomization, we use clusters to process swap operation between elements of S-box in parallel and can generate two cipher texts per clock. The proposed RC4 cipher hardware can initialize S-box and K-box without any delay and achieves about 2 times to 6 times improvement in KSA randomization and key stream generation.