• Journal of Biosystems Engineering
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• 제40권4호
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• pp.417-427
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• 2015

Purpose: This study investigated different band selection methods to classify spectrally similar data - obtained from aerial images of healthy citrus canopies and citrus greening disease (Huanglongbing or HLB) infected canopies - using small differences without unmixing endmember components and therefore without the need for an endmember library. However, large number of hyperspectral bands has high redundancy which had to be reduced through band selection. The objective, therefore, was to first select the best set of bands and then detect citrus Huanglongbing infected canopies using these bands in aerial hyperspectral images. Methods: The forward feature selection algorithm (FFSA) was chosen for band selection. The selected bands were used for identifying HLB infected pixels using various classifiers such as K nearest neighbor (KNN), support vector machine (SVM), naïve Bayesian classifier (NBC), and generalized local discriminant bases (LDB). All bands were also utilized to compare results. Results: It was determined that a few well-chosen bands yielded much better results than when all bands were chosen, and brought the classification results on par with standard hyperspectral classification techniques such as spectral angle mapper (SAM) and mixture tuned matched filtering (MTMF). Median detection accuracies ranged from 66-80%, which showed great potential toward rapid detection of the disease. Conclusions: Among the methods investigated, a support vector machine classifier combined with the forward feature selection algorithm yielded the best results.

• Journal of Communications and Networks
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• 제16권5호
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• pp.502-511
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• 2014

In this paper, we evaluate performance of a hybrid decode-amplify-forward relaying protocol in underlay cognitive radio. In the proposed protocol, a secondary relay which is chosen by partial relay selection method helps a transmission between a secondary source and a secondary destination. In particular, if the chosen relay decodes the secondary source's signal successfully, it will forward the decoded signal to the secondary destination. Otherwise, it will amplify the signal received from the secondary source and will forward the amplified signal to the secondary destination. We evaluate the performance of our scheme via theory and simulation. Results show that the proposed protocol outperforms the amplify-and-forward and decode-and-forward protocols in terms of outage probability.

• Journal of Communications and Networks
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• 제12권6호
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• pp.616-623
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• 2010

In this paper, exact closed-form expressions for outage probability and bit error probability (BEP) are presented for multi-hop decode-and-forward (DF) relaying schemes in conjunction with cooperative diversity, in which selection combining technique is employed at each node. We have shown that the proposed protocol offers remarkable diversity advantage over direct transmission as well as the conventional DF relaying schemes with the same combining technique. We then investigate the system performance when different diversity schemes are employed. It has been observed that the system performance loss due to selection combining relative to maximal ratio combining is not significant. Simulations are performed to confirm our theoretical analysis.

• 한국멀티미디어학회논문지
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• 제14권12호
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• pp.1544-1548
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• 2011

A process of choosing a subset of original features, so called feature selection, is considered as a crucial preprocessing step to image processing applications. There are already large pools of techniques developed for machine learning and data mining fields. In this paper, basically two methods, non-feature selection and feature selection, are investigated to compare their predictive effectiveness of classification. Color co-occurrence feature is used for defining image features. Standard Sequential Forward Selection algorithm are used for feature selection to identify relevant features and redundancy among relevant features. Four color spaces, RGB, YCbCr, HSV, and Gaussian space are considered for computing color co-occurrence features. Gray-level image feature is also considered for the performance comparison reasons. The experimental results are presented.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권11호
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• pp.4623-4643
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• 2015

This paper considers physical-layer security protocols in multicast cognitive radio (CR) networks. In particular, we propose dual-hop cooperative decode-and-forward (DF) and randomize-and-forward (RF) schemes using partial relay selection method to enhance secrecy performance for secondary networks. In the DF protocol, the secondary relay would use same codebook with the secondary source to forward the source's signals to the secondary destination. Hence, the secondary eavesdropper can employ either maximal-ratio combining (MRC) or selection combining (SC) to combine signals received from the source and the selected relay. In RF protocol, different codebooks are used by the source and the relay to forward the source message secretly. For each scheme, we derive exact and asymptotic closed-form expressions of secrecy outage probability (SOP), non-zero secrecy capacity probability (NzSCP) in both independent and identically distributed (i.i.d.) and independent but non-identically distributed (i.n.i.d.) networks. Moreover, we also give a unified formula in an integral form for average secrecy capacity (ASC). Finally, our derivations are then validated by Monte-Carlo simulations.

• 한국통신학회논문지
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• 제35권1A호
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• pp.1-9
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• 2010

본 논문을 통해 i.n.d 레일리 패이딩 체널에서 서로 다른 변조/복조 기법을 사용하는 중계기들로 구성된 선택적 복호 후 재전송 네트워크의 성능평가를 보여준다. 본 논문은 i.i.d와 i.n.d 레일리 패이딩 채널 모두에서 선택적 복호 후 전송 프로토콜이 최대 다이버시티를 얻을 수 있다는 것을 보여준다. 또한 SC(selection combining)기법을 사용하는 시스템과 MRC(maximal ratio combining)기법을 사용하는 시스템의 성능을 비교하여 결합기술의 효과를 연구하였다. 높은 SNR에서 시뮬레이션 결과와 수식적 분석 결과가 정확하게 일치하는 것을 보여준다.

• 대한전자공학회논문지SP
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• 제41권3호
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• pp.83-92
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• 2004

유전 발현 데이터는 생명체의 특정 조직에서 채취한 샘플을 마이크로어레이상에서 측정한 것으로, 유전자들의 발현 정도가 수치로 나타난 데이터이다. 일반적으로 정상조직과 이상조직에서 관련 유전자들의 발현 정도는 차이를 보이기 때문에 유전 발현 데이터를 통하여 암을 분류할 수 있다. 그러나 분류에 모든 유전자가 관여하지는 않으므로 효율적인 암의 분류를 위해서는 관련성 있는 소수의 유전자만을 선별해내는 작업인 특징선택 방법이 필요하다. 본 논문에서는 회귀분석의 변수선택방법중 하나인 전진 선택법(forward selection method)을 사용하여 유전자들을 선하고 분류하는 방법을 제안한다. 이 방법은 선택되는 유전자들의 중복된 정보를 최소화시켜 암의 분류에 있어 보다 효과적인 유전자 선택을 한다. 실험데이터는 대장암 데이터(Colon cancer dataset)를 사용하였고, 분류기는 k-최근접 이웃(KNN)을 사용하였다. 이 방법과 상관계수를 이용한 특징 선택방법인 피어슨 상관계수와 스피어맨 상관계수방법과 비교해본 결과 전진 선택법에 의한 특징선택 방법이 암의 분류에 있어서 더 효과적인 유전자 선택을 한다는 사실을 확인하였다. 실험결과 90.3%의 높은 인식률을 보였다. 추가적으로 림프종 데이터에 대한 실험을 하였고, 그 결과 전진 선택법의 유용성을 확인할 수 있었다.

• 한국ITS학회 논문지
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• 제12권3호
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• pp.87-95
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• 2013

본 논문에서는 다중 홉 시스템에서 하나의 홉에 대한 채널 정보만을 이용하는 효율적인 부분 중계 노드 선택(efficient partial relay selection, EPRS) 기법에 대한 아웃티지 확률을 레일레이 페이딩 채널에서 분석한다. 특히, 디코딩 후 전달 중계 기반의 EPRS 기법에 대한 정확한 아웃티지 확률의 식을 유도한다. 또한, 다중 홉 시스템에서 EPRS 기법의 실효성을 확인하기 위하여, 임의의 중계 경로에서 종단간 신호 대 잡음비와 각 홉의 신호 대 잡음비의 상관관계를 분석한다. 그리고, 수치적 결과를 통해 EPRS 기법과 모든 채널 정보를 이용하는 중계 노드 선택 기법의 아웃티지 성능을 비교한다.

• 한국컴퓨터정보학회논문지
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• 제22권2호
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• pp.81-87
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• 2017

Nowadays wine is increasingly enjoyed by a wider range of consumers, and wine certification and quality assessment are key elements in supporting the wine industry to develop new technologies for both wine making and selling processes. There have been many attempts to construct a more methodical approach to the assessment of wines, but most of them rely on objective decision rather than subjective judgement. In this paper, we propose a data mining approach to predict human wine taste preferences that is based on easily available analytical tests at the certification step. We used sequential forward selection and decision tree for this purpose. Experiments with the wine quality dataset from the UC Irvine Machine Learning Repository demonstrate the accuracies of 76.7% and 78.7% for red and white wines respectively.

• Journal of Communications and Networks
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• 제11권5호
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• pp.480-488
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• 2009

Cooperative transmission is an effective solution to improve the performance of wireless communications over fading channels without the need for physical co-located antenna arrays. In this paper, selection combining is used at the destination instead of maximal ratio combing to optimize the structure of destination and to reduce power consumption in selective decode-and-forward relaying networks. For an arbitrary number of relays, an exact and closed-form expression of the bit error rate (BER) is derived for M-PAM, M-QAM, and M-PSK, respectively, in both independent identically distributed and independent but not identically distributed Rayleigh fading channels. A variety of simulations are performed and show that they match exactly with analytic ones. In addition, our results show that the optimum number of relays depend not only on channel conditions (operating SNRs) but also on modulation schemes which to be used.