• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.6
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• pp.275-282
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• 2011

Current service discovery protocols such as UPnP, Jini, SLP provide the basic function which is message exchange pattern, service representation and description, in service discovery. They does not guarantee service interoperability among service discovery. Therefore, in this paper, we design and implement CLAM (Component-based Autonomic Layered Middleware) agent platform to enable an efficient service discovery through extension of DF agent function in FIPA-compliant specification. Also, we propose an efficient service discovery mechanism using DHT-Chord algorithm to guarantee scalability and interoperability in DF agent.

• Journal of the Ergonomics Society of Korea
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• v.22 no.2
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• pp.57-69
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• 2003

This study was performed to investigate the isometric endurance time as percentages of maximum voluntary contraction. Electromyogram(EMG) and Borg's CR-I0 value were measured by push-pull-up-down tasks for 10 healthy males. The normalized EMG value and the MPF(mean power frequency) were used to estimate the muscle recruitment pattern and the development of muscle fatigue. The subjects exerted and maintained 5 levels of %MVC(maximum voluntary contraction) in $90^{\circ}$ shoulder flexion/ 180oelbow extension at sitting posture. The up-task showed the lower endurance time and higher Borg's CR-I0 value than the other task types. Comparing Rohmert's curve with the endurance time of task types. Rohmert's curve overestimated the endurance time of up-task and underestimated the endurance time of push-pull-down tasks. The normalized EMG value showed that muscles recruitment patterns were different from task types. The 4 muscles(biceps brachii muscle, tricep brachii muscle. middle deltoid muscle. trapezius muscle) recruitment patterns of up-task were higher than those of other tasks. The MPF value decreased with the endurance time, and the shift of MPF at up-task was larger than that of the other task types.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.54 no.3
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• pp.332-338
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• 2009

Rapid extension of genomic database leads to the remarkable advance of functional genomics. This study proposes a novel methodology of functional analysis using 5-methyltrytophan (5 MT) mutant together with their 2-DE analysis and public microarray database. A total of 24 proteins was changed in 5 MT mutant and four remarkably different expressed proteins were identified. Among them, three spots were converted to Affymetrix probe. A total of 155 microarray samples from Gene Expression Omnibus (GEO) in NCBI was retrieved and followed by constructing gene co-expression networks over a broad range of biological issues through Self-Organising Tree Algorithm. Three co-expressing gene clusters were retrieved and each functional categorization with differential expression pattern was exhibited from 5 MT resistance mutant rice. It was indicated new co-expression networks in the mutant. This study suggests that on investigating possibility which correspond 2-DE to microarray database with their full potential.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.5
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• pp.497-501
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• 2008

In this paper we present a method for continuous EEG classification, where we employ nonnegative tensor factorization (NTF) to determine discriminative spectral features and use the Viterbi algorithm to continuously classily multiple mental tasks. This is an extension of our previous work on the use of nonnegative matrix factorization (NMF) for EEG classification. Numerical experiments with two data sets in BCI competition, confirm the useful behavior of the method for continuous EEG classification.

• The Journal of Korean Physical Therapy
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• v.22 no.6
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• pp.43-51
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• 2010

Purpose: This study examined the influence of visuomotor congruency on learning a relative phase relationship between a single joint movement and an external signal. Methods: Participants (N=5) were required to rhythmically coordinate elbow flexion-extension movements with a continuous sinusoidal wave (0.375 Hz) at a $90^{\circ}$ relative phase relationship. The congruent group was provided online feedback in which the elbow angle decreased (corresponding to elbow flexion) as the angle trajectory was movingup, and vice versa. The incongruent group was provided online feedback in which the elbow angle decreased as the angle trajectory was moving down, and vice versa. There were two practice sessions (day 1 and 2) and each session consisted of 6 trials per block (5 blocks per session). Retention tests were performed 24 hours after session 2, and only the external sinusoidal wave was provided. Repeated ANOVAs were used for statistical analysis. Results: During practice, the congruent group was significantly less variable than the incongruent group. Phase variability in the incongruent group did not significantly change across blocks, while variability decreased significantly in the congruent group. In retention, the congruent group produced the required $90^{\circ}$ relative phase pattern with significantly less phase variability than the incongruent group. Conclusions: Congruent visual feedback facilitates learning. Moreover, the deprivation of online feedback does not affect the congruent group but does affect the incongruent group in retention.

• Communications for Statistical Applications and Methods
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• v.25 no.5
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• pp.501-512
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• 2018

We propose Sequential Patient Recruitment Monitoring (SPRM), a new monitoring procedure for patient recruitment in a clinical trial. Based on the sequential probability ratio test using improved stopping boundaries by Woodroofe, the method allows for continuous monitoring of the rate of enrollment. It gives an early warning when the recruitment is unlikely to achieve the target enrollment. The packet data approach combined with the Central Limit Theorem makes the method robust to the distribution of the recruitment entry pattern. A straightforward application of the counting process framework can be used to estimate the probability to achieve the target enrollment under the assumption that the current trend continues. The required extension of the recruitment period can also be derived for a given confidence level. SPRM is a new, continuous patient recruitment monitoring tool that provides an opportunity for corrective action in a timely manner. It is suitable for the modern, centralized data management environment and requires minimal effort to maintain. We illustrate this method using real data from two well-known, multicenter, phase III clinical trials.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.5
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• pp.2523-2538
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• 2017

In most of the existing literature, the definition of the class label has the following characteristics. First, the class label of the samples from the same object has an absolutely fixed value. Second, the difference between class labels of the samples from different objects should be maximized. However, the appearance of a face varies greatly due to the variations of the illumination, pose, and expression. Therefore, the previous definition of class label is not quite reasonable. Inspired by discriminative least squares regression algorithm (DLSR), a noisy label based discriminative least squares regression algorithm (NLDLSR) is presented in this paper. In our algorithm, the maximization difference between the class labels of the samples from different objects should be satisfied. Meanwhile, the class label of the different samples from the same object is allowed to have small difference, which is consistent with the fact that the different samples from the same object have some differences. In addition, the proposed NLDLSR is expanded to the kernel space, and we further propose a novel kernel noisy label based discriminative least squares regression algorithm (KNLDLSR). A large number of experiments show that our proposed algorithms can achieve very good performance.

• Journal of Korea Water Resources Association
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• v.31 no.6
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• pp.741-755
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• 1998

An extension of TOPMODEL was developed for rainfall-runoff simulation in agricultural watersheds equipped with tile drains. Tile drain functions are incorporated into the framework of TOPMODEL. Nine possible flow generation scenarios are suggested for tile drained watershed and applied in the modeling procedure. In the model development process, the traditional physically based storage approach and a new approach using a transfer function for the simulation of the flow in the unsaturated zone were compared. In order to provide better insight into the simulation process, a regionalized sensitivity analysis was performed to test the performance of the model and to compare the behavior of the transfer function to that of the simple storage related formulation. The results of analysis show good performance of the transfer function approach. Since the rainfall-runoff response pattern tends to vary seasonally, seven events distributed throughout a year were used in the sensitivity analysis to investigate the seasonal variation of the hydrologic characteristics. It is found that the sensitivity of each parameter described by the model are varied seasonally.

• Journal of the Korea institute for structural maintenance and inspection
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• v.9 no.1
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• pp.243-250
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• 2005

In elevated irrigation aquaducts, one can observe a common damage pattern. That is, cracks, and crushing of concrete are usually repeated at a certain interval even if no faults are found in the design and construction of the structures. To investigate the causes of this damage, longitudinal deformations of several aquaducts have been measured. The analysis of the measured data suggests that the damages are mainly caused by cumulative repetition of extension and contraction due to temperature changes.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.3
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• pp.316-321
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• 2003

Recently, support vector learning attracts great interests in the areas of pattern classification, function approximation, and abnormality detection. It is well-known that among the various support vector learning methods, the so-called no-versions are particularly useful in cases that we need to control the total number of support vectors. In this paper, we consider the problem of function approximation utilizing both predetermined basis functions and a no-version support vector learning called $\nu-SVR$. After reviewing $\varepsilon-SVR$, $\nu-SVR$, and a semi-parametric approach, this paper presents an extension of the conventional $\nu-SVR$ method toward the direction that can utilize Predetermined basis functions. Moreover, the applicability of the presented method is illustrated via an example.