• The KIPS Transactions:PartC
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• v.16C no.6
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• pp.773-782
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• 2009

A DHT(Distributed Hash Table) based P2P is a method to overcome disadvantages of the existing unstructured P2P method. If a DHT algorithm is used, it can do a fast data search and maintain search efficiency independent of the number of peer. The peers in the DHT method send messages periodically to keep the routing table updated. In a mobile environment, the peers in the DHT method should send messages more frequently to keep the routing table updated and reduce the failure of a request. Therefore, this results in increase of network traffic. In our previous research, we proposed a method to reduce the update load of the routing table in the existing Chord by updating it in a reactive way, but the reactive method had a disadvantage to generate more traffic than the existing Chord if the number of requests per second becomes large. In this paper, we propose an adaptive method of routing table update to reduce the network traffic. In the proposed method, we apply different routing table update method according to the number of request message per second. If the number of request message per second is smaller than some threshold, we apply the reactive method. Otherwsie, we apply the existing Chord method. We perform experiments using Chord simulator (I3) made by UC Berkeley. The experimental results show the performance improvement of the proposed method compared to the existing methods.

• The KIPS Transactions:PartC
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• v.16C no.6
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• pp.761-772
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• 2009

A DHT(Distributed Hash Table) based P2P is a method to overcome disadvantages of the existing unstructured P2P method. If a DHT algorithm is used, it can do a fast data search and maintain search efficiency independent of the number of peer. The peers in the DHT method send messages periodically to keep the routing table updated. In a mobile environment, the peers in the DHT method should send messages more frequently to keep the routing table updated and reduce the failure of a request. Therefore, this results in increase of network traffic. In our previous research, we proposed a method to reduce the update load of the routing table in the existing Chord by updating it in a reactive way, but the reactive method had a disadvantage to generate more traffic than the existing Chord if the number of requests per second becomes large. In this paper, we propose an adaptive method of routing table update to reduce the network traffic. In the proposed method, we apply different routing table update method according to the number of request message per second. If the number of request message per second is smaller than some threshold, we apply the reactive method. Otherwsie, we apply the existing Chord method. We perform experiments using Chord simulator (I3) made by UC Berkeley. The experimental results show the performance improvement of the proposed method compared to the existing methods.

• The Transactions of the Korea Information Processing Society
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• v.1 no.2
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• pp.225-236
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• 1994

Many research result conducted by neural network researchers claimed that the degree of generalization of the neural network system is higher or at least equal to that of statistical methods. However, those successful results could be brought only if the neural network was trained by appropriately sound data, having a little of noisy data and being large enough to control noisy data. Real data used in a lot of fields, especially business fields, were not so sound that the network have frequently failed to obtain satisfactory prediction accuracy, the degree of generalization. Enhancing the degree of generalization with noisy data is discussed in this study. The suggestion, which was obtained through a series of experiments, to enhance the degree of generalization is to remove inconsistent data by checking overlapping and inconsistencies. Furthermore, the previous conclusion by other reports is also confirmed that the learning mechanism of neural network takes average value of two inconsistent data included in training set［2］. The interim results of on-going research project are reported in this paper These are ann architecture of the neural network adopted in this project and the whole idea of developing on-line credit evaluation system,being intergration of the expert(resoning)system and the neural network(learning system.Another definite result is corroborated through this study that quickprop,being agopted as a learing algorithm, also has more speedy learning process than does back propagation even in very noisy environment.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.11A
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• pp.878-891
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• 2011

We consider the throughput-maximization problem for both the up- and downlink in a wireless network with interference channels. For this purpose, we design an iterative and distributive uplink algorithm based on Lagrangian relaxation. Using the uplink power prices and network duality, we achieve throughput-maximization in the dual downlink that has a symmetric channel and an equal power budget compared to the uplink. The network duality we prove here is a generalized version of previous research [10], [11]. Computational tests show that the performance of the up- and downlink throughput for our algorithms is close to the optimal value for the channel orthogonality factor, ${\theta}{\in}$(0.5, 1]. On the other hand, when the channels are slightly orthogonal (${\theta}{\in}$(0, 0.5]), we observe some throughput degradation in the downlink. We have extended our analysis to the real downlink that has a nonsymmetric channel and an unequal power budget compared to the uplink. It is shown that the modified duality-based approach is thoroughly applied to the real downlink. Considering the complexity of the algorithms in [6] and [18], we conclude that these results are quite encouraging in terms of both performance and practical applicability of the generalized duality theorem.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.2
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• pp.16-27
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• 2011

Embryo is a very early stage of the development of multicellular organism such as animals and plants. It is an important research target for studying ontogeny because the fundamental body system of multicellular organism is determined during an embryo state. Researchers in the developmental biology have a large volume of embryo image databases for studying embryos and they frequently search for an embryo image efficiently from those databases. Thus, it is crucial to organize databases for their efficient search. Hierarchical clustering methods have been widely used for database organization. However, most of previous algorithms tend to produce a highly skewed tree as a result of clustering because they do not simultaneously consider both the size of a cluster and the number of objects within the cluster. The skewed tree requires much time to be traversed in users' search process. In this paper, we propose a method that effectively organizes a large volume of embryo image data in a balanced tree structure. We first represent embryo image data as a similarity-based graph. Next, we identify clusters by performing a graph partitioning algorithm repeatedly. We check constantly the size of a cluster and the number of objects, and partition clusters whose size is too large or whose number of objects is too high, which prevents clusters from growing too large or having too many objects. We show the superiority of the proposed method by extensive experiments. Moreover, we implement the visualization tool to help users quickly and easily navigate the embryo image database.

• Korean Journal of Construction Engineering and Management
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• v.13 no.6
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• pp.84-93
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• 2012

The information generated from large and complex construction projects transfer and evolve in long-term business cycle. Therefore, while there is any problem, such as delay, the cause of the problem might relate to the previous business process rather than where it arises. However, for complex project players and business relationships, it is unsuitable to search an information flow using traditional retrieval methods. This research addresses a relationship-based information search system to analyze the information flow in large-scale and complex construction projects. First, we identified the components of the information retrieval system customizing for a large-scale complex construction projects, and then developed the inference algorithm which define the relationship between business processes. For the validation, we applied the system on a business information system of urban regeneration projects and suggested some application using information flow retrieval system for project players and project managers. Using the system, players are easy to prepare for their work process and managers can define the causal flow of the problem.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.44 no.12
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• pp.54-60
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• 2007

This paper proposes a built-in-self-repair (BISR) structure using 2-dimensional spare memory to effectively self-repair faults of an embedded memory. In case of multiple faults in the same row (column) of an embedded memory, the previous method using 1-D spare column (row) memory needs the same number of spare memory columns (rows) as the number of faults to self-repair them. while the new method using 2-D spare memory needs only one spare row (column) to self-repair them. Also, the virtual divided memory is adopted to be able to self-repair using not a full spare column memory but the only partial spare column memory corresponding to the faults. A self-repair circuit with $64\times1-bit$ core memory and $2\times8$ 2-D spare memory is designed. And the circuit includes a built-in-self-test block using the 13N March algorithm. The circuit has been implemented using the $0.25{\mu}m$ MagnaChip CMOS process and has $1.1\times0.7mm^2$ chip area with 10,658 transistors.

• Asian-Australasian Journal of Animal Sciences
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• v.31 no.5
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• pp.738-747
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• 2018

Objective: In a previous study, analysis of Illumina sequenced metagenomic DNA data of bacteria in Vietnamese goats' rumen showed a high diversity of putative lignocellulolytic genes. In this study, taxonomy speculation of microbial community and lignocellulolytic bacteria population in the rumen was conducted to elucidate a role of bacterial structure for effective degradation of plant materials. Methods: The metagenomic data had been subjected into Basic Local Alignment Search Tool (BLASTX) algorithm and the National Center for Biotechnology Information non-redundant sequence database. Here the BLASTX hits were further processed by the Metagenome Analyzer program to statistically analyze the abundance of taxa. Results: Microbial community in the rumen is defined by dominance of Bacteroidetes compared to Firmicutes. The ratio of Firmicutes versus Bacteroidetes was 0.36:1. An abundance of Synergistetes was uniquely identified in the goat microbiome may be formed by host genotype. With regard to bacterial lignocellulose degraders, the ratio of lignocellulolytic genes affiliated with Firmicutes compared to the genes linked to Bacteroidetes was 0.11:1, in which the genes encoding putative hemicellulases, carbohydrate esterases, polysaccharide lyases originated from Bacteroidetes were 14 to 20 times higher than from Firmicutes. Firmicutes seem to possess more cellulose hydrolysis capacity showing a Firmicutes/Bacteroidetes ratio of 0.35:1. Analysis of lignocellulolytic potential degraders shows that four species belonged to Bacteroidetes phylum, while two species belonged to Firmicutes phylum harbouring at least 12 different catalytic domains for all lignocellulose pretreatment, cellulose, as well as hemicellulose saccharification. Conclusion: Based on these findings, we speculate that increasing the members of Bacteroidetes to keep a low ratio of Firmicutes versus Bacteroidetes in goat rumen has resulted most likely in an increased lignocellulose digestion.

• Science of Emotion and Sensibility
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• v.20 no.3
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• pp.13-22
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• 2017

Emotion has a direct influence such as decision-making, perception, etc. and plays an important role in human life. For the convenient and accurate recognition of high-arousal negative emotion, the purpose of this paper is to design an algorithm for analysis using the bio-signal. In this study, after two emotional induction using the 'normal' / 'fear' emotion types of videos, we measured the Galvanic Skin Response (GSR) signal which is the simple of bio-signals. Then, by decomposing Tonic component and Phasic component in the measured GSR and decomposing Skin Conductance Very Slow Response (SCVSR) and Skin Conductance Slow Response (SCSR) in the Phasic component associated with emotional stimulation, extracting the major features of the components for an accurate analysis, we used a discrete wavelet transform with excellent time-frequency localization characteristics, not the method used previously. The extracted features are maximum value of Phasic component, amplitude of Phasic component, zero crossing rate of SCVSR and zero crossing rate of SCSR for distinguishing high-arousal negative emotion. As results, the case of high-arousal negative emotion exhibited higher value than the case of low-arousal normal emotion in all 4 of the features, and the more significant difference between the two emotion was found statistically than the previous analysis method. Accordingly, the results of this study indicate that the GSR may be a useful indicator for a high-arousal negative emotion measurement and contribute to the development of the emotional real-time rating system using the GSR.

• Journal of the Korean association of regional geographers
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• v.22 no.3
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• pp.681-702
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• 2016

Two different modelling approaches to dune dynamics have been established thus far; continuous models that emphasize the precise representation of wind field, and feedback-based models that focus on the interactions between dunes, rather than aerodynamics. Though feedback-based models have proven their capability to capture the essence of dune dynamics, the compatibility issues on these models have less been addressed. This research investigated, mostly from the theoretical point of view, the algorithmic compatibility of three feedback-based dune models: sand slab models, Nishimori model, and de Castro model. Major findings are as follows. First, sand slab models and de Castro model are both compatible in terms of flux perspectives, whereas Nishimori model needs a tuning factor. Second, the algorithm of avalanching can be easily implemented via repetitive spatial smoothing, showing high compatibility between models. Finally, the wind shadow rule might not be a necessary component to reproduce dune patterns unlike the interpretation or assumption of previous studies. The wind shadow rule, rather, might be more important in understanding bedform-level interactions. Overall, three models show high compatibility between them, or seem to require relatively small modification, though more thorough investigation is needed.