• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.9
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• pp.1299-1307
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• 1989

A Korean syllable is regarded as a random variable according to its probabilistic property in occurrence. A Korean syllable is divided into a 'choseong', a 'jungseong', and a 'jongseong' which are regarded as random variables. From the cumulative freaquency of a Korean syllable all possible joint probabilities and conditional probabilities are computed for the three ramdom variables. From the joint probabilities and the conditional probabilities all possible joint entropies and conditional entropies are computed for the three random varibles. Also all possible average mutual informations are calculated for the three random variables. Average mutual informatin between two random variables hss its biggest value between choseong and jungseong. Average mutual information between a random variable and other two random variables has its biggest value between jungseong and choseong-jongseong.

• Proceedings of the Korean Society for Language and Information Conference
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• 1998.02a
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• pp.195-205
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• 1998

• ETRI Journal
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• v.41 no.3
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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.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.23 no.6
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• pp.669-681
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• 2012

In this paper, analytical calculations using a novel mutual inductance formula for a resonant wireless power transmission system using helical coils. The look-up table of critical variables during the mutual inductance calculation process was formulated. The calculation results for resonant frequency and insertion loss were compared with experimental results when the distance between the two helical coils in a structure where the transmission and reception is symmetrical was varied with 10 mm increments from 53 mm to 500 mm. On average, the resonant frequency showed a difference of 5.63 % between the experimental results and the calculation results. The insertion loss had an average difference 2.25 dB where the smallest difference of 0.33 dB occurred with 290 mm. It was found that the experimental results without using a balun were in greater agreement with the calculation results.

• Journal of Information Processing Systems
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• v.10 no.1
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• pp.36-54
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• 2014

Resource sharing is a major advantage of distributed computing. However, a distributed computing system may have some physical or virtual resource that may be accessible by a single process at a time. The mutual exclusion issue is to ensure that no more than one process at a time is allowed to access some shared resource. The article proposes a token-based mutual exclusion algorithm for the clustered mobile ad hoc networks (MANETs). The mechanism that is adapted to handle token passing at the inter-cluster level is different from that at the intra-cluster level. It makes our algorithm message efficient and thus suitable for MANETs. In the interest of efficiency, we implemented a centralized token passing scheme at the intra-cluster level. The centralized schemes are inherently failure prone. Thus, we have presented an intra-cluster token passing scheme that is able to tolerate a failure. In order to enhance reliability, we applied a distributed token circulation scheme at the inter-cluster level. More importantly, the message complexity of the proposed algorithm is independent of N, which is the total number of nodes in the system. Also, under a heavy load, it turns out to be inversely proportional to n, which is the (average) number of nodes per each cluster. We substantiated our claim with the correctness proof, complexity analysis, and simulation results. In the end, we present a simple approach to make our protocol fault tolerant.

• International Journal of Control, Automation, and Systems
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• v.6 no.4
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• pp.620-625
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• 2008

The $H_{\infty}$ entropy in $H_{\infty}$ control theory is discussed based on investigating information transmission in continuous-time linear stochastic systems. It is proved that the stabilizing feedback does not change the time-average information transmission between system input and output, and the $H_{\infty}$ entropies of open- and closed-loop stable transfer functions are bounded by mutual information rate between input and output in the open-loop system. Furthermore, a new $H_2$ upper bound for $H_{\infty}$ entropy is introduced with a numerical example. Thus the $H_{\infty}$ entropy of a stable transfer function is sandwiched between $H_2$ norms of the original system and a static feedback system.

• Genomics & Informatics
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• v.19 no.3
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• pp.26.1-26.3
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• 2021

Previous approaches to create a controlled vocabulary for Japanese have resorted to existing bilingual dictionary and transformation rules to allow such mappings. However, given the possible new terms introduced due to coronavirus disease 2019 (COVID-19) and the emphasis on respiratory and infection-related terms, coverage might not be guaranteed. We propose creating a Japanese bilingual controlled vocabulary based on MeSH terms assigned to COVID-19 related publications in this work. For such, we resorted to manual curation of several bilingual dictionaries and a computational approach based on machine translation of sentences containing such terms and the ranking of possible translations for the individual terms by mutual information. Our results show that we achieved nearly 99% occurrence coverage in LitCovid, while our computational approach presented average accuracy of 63.33% for all terms, and 84.51% for drugs and chemicals.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.2
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• pp.40-49
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• 2015

PicoCast is a recently proposed short-range wireless communications technology that supports both low rate sensor/control data and high speed data such as voice and video traffic in the personal space, defined by the user-centric space of radius tens of meters, with one unified protocol. When the users are in the same area, personal spaces defined by each user may overlap. Since these PicoCast piconets may simultaneously operate, mutual interference is unavoidable. It is necessary to investigate the effect of mutual interference on data transmission and to conduct research on minimizing the interference among PicoCast devices. In this paper we analyze the effect of mutual interference between PicoCast piconets based on data throughput using OPNET network simulator. We have implemented the PicoCast protocol and measured the average throughput and packet loss rate.

• Journal of Korea Multimedia Society
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• v.19 no.8
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• pp.1530-1537
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• 2016

Recently, solar power generation shows the significant growth in the renewable energy field. Using the short-term prediction, it is possible to control the electric power demand and the power generation plan of the auxiliary device. However, a short-term prediction can be used when you know the weather forecast. If it is not possible to use the weather forecast information because of disconnection of network at the island and the mountains or for security reasons, the accuracy of prediction is not good. Therefore, in this paper, we proposed a system capable of short-term prediction of solar power generation amount by using only the weather information that has been collected by oneself. We used temperature, humidity and insolation as weather information. We have applied a moving average to each information because they had a characteristic of time series. It was composed of min, max and average of each information, differences of mutual information and gradient of it. An artificial neural network, SVM and RBF Network model was used for the prediction algorithm and they were combined by Ensemble method. The results of this suggest that using a moving average during pre-processing and ensemble prediction models will maximize prediction accuracy.

• The Transactions of the Korea Information Processing Society
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• v.3 no.5
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• pp.1207-1214
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• 1996

We present an efficient decentralized, symmetric mutual exclusion algorithm for the hypercube architecture. The algorithm is based on the technique which embeds a mesh into a hypercube. We compare the performance of our algorithm with that of Gupta et al.'s algorithm. As a result of performance comparison, the minimum round-trip delay is equal to that of Gupta et al.'s algorithm, the average blocking delay is a little longer than that of Gupta et al.'s algorithm, and the number of messages per access to critical resource is fewer than that of Gupla et al.'s algorithm.