• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권4호
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• pp.1961-1974
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• 2019

In this letter, a harmonic-mean-based dual-antenna selection scheme at relay node is proposed in two-way relaying networks (TWRNs). With well-designed distributed orthogonal concatenated Alamouti space-time block code (STBC), a dual-antenna selection problem based on the instantaneous achievable sum-rate criterion is formulated. We propose a low-complexity selection algorithm based on the harmonic-mean criterion with linearly complexity $O(N_R)$ rather than the directly exhaustive search with complexity $O(N^2_R)$. From the analysis of network outage performance, we show that the asymptotic diversity gain function of the proposed scheme achieves as $1/{\rho}{^{N_R-1}}$, which demonstrates one degree loss of diversity order compared with the full diversity. This slight performance gap is mainly caused by sacrificing some dual-antenna selection freedom to reduce the algorithm complexity. In addition, our proposed scheme can obtain an extra coding gain because of the combination of the well-designed orthogonal concatenated Alamouti STBC and the corresponding dual-antenna selection algorithm. Compared with the common-used selection algorithms in the state of the art, the proposed scheme can achieve the best performance, which is validated by numerical simulations.

• Journal of information and communication convergence engineering
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• 제13권2호
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• pp.113-122
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• 2015

Feature subset selection is as a pre-processing step in learning algorithms. In this paper, we propose an efficient algorithm, ModifiedFAST, for feature subset selection. This algorithm is suitable for text datasets, and uses the concept of information gain to remove irrelevant and redundant features. A new optimal value of the threshold for symmetric uncertainty, used to identify relevant features, is found. The thresholds used by previous feature selection algorithms such as FAST, Relief, and CFS were not optimal. It has been proven that the threshold value greatly affects the percentage of selected features and the classification accuracy. A new performance unified metric that combines accuracy and the number of features selected has been proposed and applied in the proposed algorithm. It was experimentally shown that the percentage of selected features obtained by the proposed algorithm was lower than that obtained using existing algorithms in most of the datasets. The effectiveness of our algorithm on the optimal threshold was statistically validated with other algorithms.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 2011년도 하계학술대회
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• pp.310-313
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• 2011

Broadcasting nature of wireless communications makes it possible to apply opportunistic network coding (OPNC) by overhearing transmitted packets from a source to sink nodes. However, it is difficult to apply network coding to the topology of multiple relay and sink nodes. We propose to use relay node selection, which finds a proper node for network coding since the OPNC alone in the topology of multiple relays and sink nodes cannot guarantee network coding gain. The proposed system is a novel combination of wireless network coding and relay selection, which is a key contribution of this paper. In this paper, with the consideration of channel state and potential network coding gain, we propose relay node selection techniques, and show performance gain over the conventional OPNC and a channel-based selection algorithm in terms of average system throughput.

• Journal of Information Technology Applications and Management
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• 제26권3호
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• pp.19-27
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• 2019

In this study, we propose a methodology for predicting the movie audience based on movie information that can be easily acquired before opening and effectively distinguishing qualitative variables. In addition, we constructed a model to estimate the number of movie audiences at the time of data acquisition through the configured variables. Another purpose of this study is to provide a criterion for categorizing success of movies with qualitative characteristics. As an evaluation criterion, we used information gain ratio which is the node selection criterion of C4.5 algorithm. Through the procedure we have selected 416 movie data features. As a result of the multiple linear regression model, the performance of the regression model using the variables selection method based on the information gain ratio was excellent.

• 한국통신학회논문지
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• 제31권10A호
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• pp.943-951
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• 2006

MIMO(Multiple Input Multiple Output) 시스템에서 성능 향상을 위해 안테나의 수를 증가시킬 수 있으나 RF체인의 증가와 하드웨어의 복잡도에 의해 제한될 수 있다. 이때, RF 체인의 수를 고정시키고 그보다 많은 수의 안테나를 채용한 후, 승)수신 양단에서 채널 상태에 따라 동적으로 안테나를 선택함으로써 이와 같은 문제를 완화할 수 있다. 본 논문에서는 전체 $M_R{\times}M_T$채널 이득 행렬에서 가장 큰 채널 이득을 갖는 송신 안테나와 수신안테나를 교차적으로 선택하여 Frobenius norm을 최대화하는 $M_R{\times}M_T$ 채널 행렬을 결정함으로써 송/수신 양단에서 안테나 선택을 동시에 수행하는 송/수신안테나 선택 알고리즘(joint Tx/Rx antenna selection algorithm)을 제안하며, exhaustive search를 통한 최적 방식과 비교할 때 현저하게 계산량을 줄일 수 있어 구현의 복잡도가 매우 낮은 것이 특징이다. $8{\times}8$ 안테나에서 $4{\times}4$ 안테나를 선택하는 경우 성능면에 있어서는 기존의 최적 방식인 exhaustive search 방식에 비해 $0.5{\sim}2dB$가량의 성능 열화가 있으나, 계산량에서는 약 1/10,000 단위로 복잡도를 감소시킬 수 있음을 예시한다.

• 한국통신학회논문지
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• 제37권8B호
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• pp.657-667
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• 2012

본 논문에서는 OLSR의 MPR 선택방법을 개선함으로써 애드혹(ad hoc) 네트워크의 처리율(throughput), 지연 시간(delay) 등의 성능을 향상시킬 수 있는 S-MPR 선택 방법을 제안한다. OLSR의 MPR 선택 방법은 각 노드가 독립적으로 MPR을 선택하기 때문에 대부분의 노드가 MPR로 선택되는 문제가 있다. 이러한 문제를 해결하기 위해 기존에 제안되었던 MPR 후보(candidate) 선택 방법은 MPR의 수는 감소시킬 수 있지만 그로 인해 경로의 효율성과 네트워크의 연결성(connectivity)이 저하되는 문제를 갖고 있다. 본 논문에서 제안하는 S-MPR 방법은 이러한 문제를 해결하기 위해 각 노드 입장에서 가장 중요한 노드를 S-MPR로 선택하고 나머지 MPR은 MPR 후보를 이용하여 선택하는 방법을 사용한다. 따라서 제안 방법은 경로 효율성의 저하를 최소화하면서 MPR로 선택되는 노드의 수를 줄임으로써 TC 메시지로 인한 오버헤드를 최소화하고 MPR간의 충돌을 감소시킴으로써 처리율, 지연 시간 성능을 향상시킬 수 있다. 본 논문에서 제안한 S-MPR의 성능을 알아보기 위해 OPNET을 활용하여 시뮬레이션을 수행하고 제안 S-MPR의 성능이 가장 우수함을 보인다.

• ETRI Journal
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• 제41권3호
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• pp.358-370
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• 2019

The main aim of this study is to select the optimal set of genes from microarray cancer datasets that contribute to the prediction of specific cancer types. This study proposes the enhancement of the feature selection filter algorithm based on Joe's normalized mutual information and its use for gene selection. The proposed algorithm is implemented and evaluated on seven benchmark microarray cancer datasets, namely, central nervous system, leukemia (binary), leukemia (3 class), leukemia (4 class), lymphoma, mixed lineage leukemia, and small round blue cell tumor, using five well-known classifiers, including the naive Bayes, radial basis function network, instance-based classifier, decision-based table, and decision tree. An average increase in the prediction accuracy of 5.1% is observed on all seven datasets averaged over all five classifiers. The average reduction in training time is 2.86 seconds. The performance of the proposed method is also compared with those of three other popular mutual information-based feature selection filters, namely, information gain, gain ratio, and symmetric uncertainty. The results are impressive when all five classifiers are used on all the datasets.

• 디지털산업정보학회논문지
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• 제4권1호
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• pp.9-16
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• 2008

This paper presents a frequency selection algorithm for minimization power consumption of processor in Mobile System. The proposed algorithm has processor designed low power processor using clock gating method. Clock gating method has improved the power dissipation by control main clock through the bus which is embedded clock block applying the method of clock gating. Proposed method has compared power consumption considered the dynamic power for processor, selected frequency has considered energy gain and energy consumption for designed processor. Or reduced power consumption with decreased processor speed using slack time. This technique has improved the life time of the mobile systems by clock gating method, considered energy and using slack time. As an results, the proposed algorithm reduce average power saving up to 4% comparing to not apply processor in mobile system.

• 전기전자학회논문지
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• 제24권1호
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• pp.106-119
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• 2020

본 논문에서는 극 배치 기법을 활용하여 쿼드로터 시스템의 제어기법을 제안한다. 일반적으로 상태 궤환 제어기를 사용하여 제어된 시스템 성능을 개선하기 위해서는 많은 제어 이득 값 선정에서의 시행착오가 필요하다. 이러한 복잡성을 완화시키고, 체계적인 제어 이득 선정을 위해 쿼드로터의 폐루프 시스템을 분석한다. 시스템 성능을 개선시키기 위해 극 배치 기법을 활용한 제어 이득 결정 알고리즘을 제안한다. 제안된 제어기법은 실제 시스템인 쿼드로터에 적용하여 유효성을 입증한다.

• International Journal of Computer Science & Network Security
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• 제22권1호
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• pp.167-174
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• 2022

In metaheuristic algorithms such as Genetic Algorithm (GA), initial population has a significant impact as it affects the time such algorithm takes to obtain an optimal solution to the given problem. In addition, it may influence the quality of the solution obtained. In the machine learning field, feature selection is an important process to attaining a good performance model; Genetic algorithm has been utilized for this purpose by scientists. However, the characteristics of Genetic algorithm, namely random initial population generation from a vector of feature elements, may influence solution and execution time. In this paper, the use of a statistical algorithm has been introduced (Chi2) for feature relevant checks where p-values of conditional independence were considered. Features with low p-values were discarded and subject relevant subset of features to Genetic Algorithm. This is to gain a level of certainty of the fitness of features randomly selected. An ensembled-based learning model for Hepatitis has been developed for Hepatitis C stage classification. 1385 samples were used using Egyptian-dataset obtained from UCI repository. The comparative evaluation confirms decreased in execution time and an increase in model performance accuracy from 56% to 63%.