• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.12
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• pp.5820-5834
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• 2017

This paper investigates the channel selection problem with dynamic users and the asymmetric interference relation in distributed opportunistic spectrum access systems. Since users transmitting data are based on their traffic demands, they dynamically compete for the channel occupation. Moreover, the heterogeneous interference range leads to asymmetric interference relation. The dynamic users and asymmetric interference relation bring about new challenges such as dynamic random systems and poor fairness. In this article, we will focus on maximizing the tradeoff between the achievable utility and access cost of each user, formulate the channel selection problem as a directional graphical game and prove it as an exact potential game presenting at least one pure Nash equilibrium point. We show that the best NE point maximizes both the personal and system utility, and employ the stochastic learning approach algorithm for achieving the best NE point. Simulation results show that the algorithm converges, presents near-optimal performance and good fairness, and the directional graphical model improves the systems throughput performance in different asymmetric level systems.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2012.04a
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• pp.734-738
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• 2012

A comprehensive vibration assessment program for the Advanced Power Reactor 1400 reactor vessel internals is established in accordance with the United States Nuclear Regulatory Commission Regulatory Guide 1.20 Revision 3. This paper is related to instruments and measurement locations based on the vibration and stress response analysis results at the inner barrel assembly top plate in the reactor. The analysis results of the inner barrel assembly top plate in the reactor show that the deterministic stress and deformation due to the reactor coolant pump induced pressure pulsations are larger than the random stress and deformation induced by the flow turbulence. The selection of the instruments and measurement locations at Inner barrel assembly top plate in the reactor is essential requirements and very important study process for the vibration and stress measurement program in comprehensive vibration assessment program for the Advanced Power Reactor 1400 reactor vessel internals.

• Journal of Plant Biotechnology
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• v.30 no.3
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• pp.227-232
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• 2003

Radiation technique has been used to develope mutant rice. Suwon 345 rice seeds were irradiated with 250 Gy gamma ray. Morphological characteristics of the variants in M$_{8}$ generation were observed and random amplified polymorphic DNA(RAPD) analysis was carried out. Plant height, panicle length, 1,000 grain weight and lodging were very different in mutants compared with donor cultivar. RAPD analysis showed that polymorphic bands were presented in several primers of the mutants. In comparison with original variety, variants were classified into four group through UPGMA analysis. A group has mutation trait in panicle length, B group in plant height and C group in 1,000 grain weight. Among mutants, no. 46 and 147 was ranked as salt tolerance and the malonaldehyde content of these mutants was more increased than that of original variety. Valuable mutants obtained will be useful for developing new cultivars and for studing gene function in molecular level.l.

• Journal of Information Processing Systems
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• v.16 no.2
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• pp.435-446
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• 2020

With the ability to learn rules from training data, the machine learning model can classify unknown objects. At the same time, the dimension of hyperspectral data is usually large, which may cause an over-fitting problem. In this research, an identification methodology of tea diseases was proposed based on spectral reflectance and machine learning, including the feature selector based on the decision tree and the tea disease recognizer based on random forest. The proposed identification methodology was evaluated through experiments. The experimental results showed that the recall rate and the F1 score were significantly improved by the proposed methodology in the identification accuracy of tea disease, with average values of 15%, 7%, and 11%, respectively. Therefore, the proposed identification methodology could make relatively better feature selection and learn from high dimensional data so as to achieve the non-destructive and efficient identification of different tea diseases. This research provides a new idea for the feature selection of high dimensional data and the non-destructive identification of crop diseases.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.8
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• pp.4021-4037
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• 2018

In network intrusion detection research, two characteristics are generally considered vital to building efficient intrusion detection systems (IDSs): an optimal feature selection technique and robust classification schemes. However, the emergence of sophisticated network attacks and the advent of big data concepts in intrusion detection domains require two more significant aspects to be addressed: employing an appropriate big data computing framework and utilizing a contemporary dataset to deal with ongoing advancements. As such, we present a comprehensive approach to building an efficient IDS with the aim of strengthening academic anomaly detection research in real-world operational environments. The proposed system has the following four characteristics: (i) it performs optimal feature selection using information gain and branch-and-bound algorithms; (ii) it employs machine learning techniques for classification, namely, Logistic Regression, Naïve Bayes, and Random Forest; (iii) it introduces bulk synchronous parallel processing to handle the computational requirements of large-scale networks; and (iv) it utilizes a real-time contemporary dataset generated by the Information Security Centre of Excellence at the University of Brunswick (ISCX-UNB) to validate its efficacy. Experimental analysis shows the effectiveness of the proposed framework, which is able to achieve high accuracy, low computational cost, and reduced false alarms.

• Communications for Statistical Applications and Methods
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• v.24 no.2
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• pp.143-154
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• 2017

A variable selection method based on probabilistic principal component analysis (PCA) using penalized likelihood method is proposed. The proposed method is a two-step variable reduction method. The first step is based on the probabilistic principal component idea to identify principle components. The penalty function is used to identify important variables in each component. We then build a model on the original data space instead of building on the rotated data space through latent variables (principal components) because the proposed method achieves the goal of dimension reduction through identifying important observed variables. Consequently, the proposed method is of more practical use. The proposed estimators perform as the oracle procedure and are root-n consistent with a proper choice of regularization parameters. The proposed method can be successfully applied to high-dimensional PCA problems with a relatively large portion of irrelevant variables included in the data set. It is straightforward to extend our likelihood method in handling problems with missing observations using EM algorithms. Further, it could be effectively applied in cases where some data vectors exhibit one or more missing values at random.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.2
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• pp.105-116
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• 2018

In this study, we consider the assembly line balancing (ALB) problem which is known as an very important decision dealing with the optimal design of assembly lines. We consider ALB problems with soft constraints which are expected to be fulfilled, however they are not necessarily to be satisfied always and they are difficult to be presented in exact quantitative forms. In previous studies, most researches have dealt with hard constraints which should be satisfied at all time in ALB problems. In this study, we modify the mixed integer programming model of the problem introduced in the existing study where the problem was first considered. Based on the modified model, we propose a new algorithm using the genetic algorithm (GA). In the algorithm, new features like, a mixed initial population selection method composed of the random selection method and the elite solutions of the simple ALB problem, a fitness evaluation method based on achievement ratio are applied. In addition, we select the genetic operators and parameters which are appropriate for the soft assignment constraints through the preliminary tests. From the results of the computational experiments, it is shown that the proposed algorithm generated the solutions with the high achievement ratio of the soft constraints.

• Journal of Communications and Networks
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• v.12 no.3
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• pp.222-230
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• 2010

In this paper, we present a closed-form approximation of the average sum rate of zero-forcing (ZF) beamforming (BF) with semi-orthogonal user selection (SUS). We first derive the survival probability associated with the SUS that absolute square of the channel correlation between two users is less than the orthogonalization level threshold (OLT).With this result, each distribution for the number of surviving users at each iteration of the SUS and the number of streams for transmission is calculated. Secondly, the received signal power of ZF-BF is represented as a function of the elements of the upper triangular matrix from QR decomposition of the channel matrix. Thirdly, we approximate the received signal power of ZF-BF with the SUS as the maximum of scaled chisquare random variables where the scaling factor is approximated as a function of both OLT and the number of users in the system. Putting all the above derivations and order statistics together, the approximated ergodic sum rate of ZF-BF with the SUS is shown in a closed form. The simulation results verify that the approximation tightly matches with the sample average for any OLT and even for a small number of users.

• ETRI Journal
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• v.42 no.6
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• pp.872-885
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• 2020

Distributed consensus requires the consent of more than half of the congress to produce irreversible results, and the performance of the consensus algorithm deteriorates with the increase in the number of nodes. This problem can be addressed by delegating the agreement to a few selected nodes. Since the selected nodes must comply with the Byzantine node ratio criteria required by the algorithm, the result selected by any decentralized node cannot be trusted. However, some trusted nodes monopolize the consensus node selection process, thereby breaking decentralization and causing a trilemma. Therefore, a consensus node selection algorithm is required that can construct a congress that can withstand Byzantine faults with the decentralized method. In this paper, an algorithm based on the Byzantine agreement among decentralized agents to facilitate agreement between decentralization nodes is proposed. It selects a group of random consensus nodes per block by applying the proposed proof of nonce algorithm. By controlling the percentage of Byzantine included in the selected nodes, it solves the trilemma when an arbitrary node selects the consensus nodes.

• Asian Journal of Innovation and Policy
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• v.9 no.3
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• pp.281-307
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• 2020

A variety of approaches are being applied to improve the existing ex-ante evaluation by expert panels in publicly funded R&D. While the objective evaluation criteria are constantly being improved to screen and select the superior projects, alternative approaches such as random prioritization and logical modeling are also underway to overcome the conservative bias of reviewers and to secure disruptive innovation. This study intends to find critical implications for ex-ante evaluation of public R&D system from the comparison of Indonesia and Korea. For the comparative analysis, literature review and expert in-depth interviews are conducted on the national R&D system and the selection evaluation process. In Korea, the selection criteria of projects are legally promulgated for establishing an objective evaluation system, and at the program level, the major considerations in the planning process are specified by Presidential Decree. On the other hand, while Indonesia conducts R&D in 47 strategic fields largely by public research institutes (PRI) based on the non-competitive government contributions. This study draws out implications of institutionalizing the planning process at the level of program, and of increasing the ratio of contract-based competitive funding at the level of project in the national R&D portfolio.