• Communications of the Korean Institute of Information Scientists and Engineers
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• v.5 no.2
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• pp.85-89
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• 1987

The large sparse matrix problems arise in many applications areas, such as structural analysis, network analysis. In dealing with such sparse systems proper preprogramming techniques such as permuting rows and columns simultaneously, will be needed in order to reduce the number of arithmetic operations and storage spaces.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.10A
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• pp.1604-1612
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• 2000

This paper proposes a simultaneous hardware resource allocation and binding algorithm for VLSI design. The proposed algorithm works on scheduled input graph and simultaneously allocates binds functional units, interconnections and registers by considering interdependency between operations and storage elements in each control step, in order to share registers and interconnections connected to functional units, as much as possible. Also, the register allocation is especially executes the allocation optima us-ing graph coloring techniques. Therefore the overall resource is reduced. This paper shows the effectiveness of the proposed algorithm by comparing experiments to determine number of functional unit in advance or to separate executing allocation and binding of existing system.

• The Journal of the Korea Contents Association
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• v.16 no.2
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• pp.374-386
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• 2016

Provenance means the meta data that represents the history or lineage of a data in collaboration storage environments. Therefore, as provenance has been accruing over time, it takes several ten times as large as the original data. The schemes for effciently compressing huge amounts of provenance are required. In this paper, we propose a provenance compression scheme considering the RDF graph patterns. The proposed scheme represents provenance based on a standard PROV model and encodes provenance in numeric data through the text encoding. We compress provenance and RDF data using the graph patterns. Unlike conventional provenance compression techniques, we compress provenance by considering RDF documents on the semantic web. In order to show the superiority of the proposed scheme, we compare it with the existing scheme in terms of compression ratio and the processing time.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.49 no.2
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• pp.134-142
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• 2012

This paper analyze an LDPC code replication method suitable for cloud computing. First, we determine the number of blocks suitable for cloud computing through analysis of the performance for the file availability and storage overhead. Also we determine the type of LDPC code appropriate for cloud computing through the performance for three types of LDPC codes. Finally we present the graph random generation method and the comparing method of each generated LDPC code's performance by the iterative decoding process. By the simulation, we confirmed the best graph's regularity is left-regular or least left-regular. Also, we confirmed the best graph's total number of edges are minimum value or near the minimum value.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.571-572
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• 2017

The blockchain technology that implements electronic money uses decentralized computing and all transactions in a blockchain are open to everyone. This technique seems to guarantee anonymity by performing the transaction on the address instead of the user, but by using direction acyclic graph based on the transaction graph, the privacy problem is caused by tracking the addresses. In this paper, we analyze various techniques for centralized processing which makes it difficult to find the relevance on the graph in order to protect the privacy in the block chain technology. We also analyze the techniques of anonymizing in a distributed way to enhance privacy. Using the zero knowledge proof scheme guarantees full distributed anonymity but requires more computation and storage space, and various techniques to make this efficient are proposed. In this paper, we propose a privacy protection scheme of blockchain technology to integrate existing privacy protection techniques into a blockchain technology and perform it more efficiently with a centralized or decentralized technique.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.5
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• pp.462-468
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• 2017

In this paper IoT/WSN(Internet of Things/Wireless Sensor Network) has been modeled with a random geometric graph. And a performance of the decentralized code for the efficient storage of data which is generated from WSN has been analyzed. WSN with n=100 or 200 has been modeled as a random geometric graph and has been simulated for their performance analysis. When the number of the total nodes of WSN is n=100 or 200, the successful decoding probability as decoding ratio ${\eta}$ depends more on the number of source nodes k rather than the number of nodes n. Especially, from the simulation results we can see that the successful decoding rate depends greatly on k value than n value and the successful decoding rate was above 70% when $${\eta}{\leq_-}2.0$$. We showed that the number of operations of BP(belief propagation) decoding scheme increased exponentially with k value from the simulation of the number of operations as a ${\eta}$. This is probably because the length of the LT code becomes longer as the number of source nodes increases and thus the decoding computation amount increases greatly.

• The Korean Journal of Food And Nutrition
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• v.13 no.5
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• pp.403-410
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• 2000

This study was carried out to understand the effect of addition of potato search on the frozen dough. The characteristics of frozen dough were measured by the farinogram, the extensogram and the amylogram. The results of these measurements show that the dough added with starch has higher stability than the control. The physical and chemical change of the dough were measured in accordance with the period of the frozen storage. The dough added with starch showed smaller physical and chemical change than control, which means that the starch prevents the frozen dough from the deterioration during the frozen storage. It is supposed from this result that the starch protects the activity of yeast and the structure of gluten matrices from frozen damage. It is understood from this study that addition of potato starch into frozen dough improve the stability of the frozen dough.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.2 no.4
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• pp.33-38
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• 1982

A successful operation of underground oil storage cavern depends on water-tightness around cavern by groundwater. If water-tightness is not secured, gas bubbles would leak out and oil would migrate to an adjacent empty cavern. In this research an electrical analogy method was employed to study the influence of shape of cavern on gas leakage and the required natural groundwater level, relative oil level in two neighboring caverns and cavern spacing to prevent oil migration. The results show that gas leakage is prevented from a cavern with a ceiling of large curvature. The required values of factors to curtail the migration of oil are given on a graph.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.1
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• pp.109-116
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• 2021

Since RDF (Resource Description Framework) triples are modeled as graph, we cannot directly adopt existing solutions in relational databases and XML technology. In order to store, index, and query Linked Data more efficiently, we propose a convergence indexing method combined R*-tree and K-dimensional trees. This method uses a hybrid storage system based on HDD (Hard Disk Drive) and SSD (Solid State Drive) devices, and a separated filter and refinement index structure to filter unnecessary data and further refine the immediate result. We perform performance comparisons based on three standard join retrieval algorithms. The experimental results demonstrate that our method has achieved remarkable performance compared to other existing methods such as Quad and Darq.

• ETRI Journal
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• v.45 no.4
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• pp.650-665
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• 2023

A novel smart metering technique capable of anomaly detection was proposed for real-time home power management system. Smart meter data generated in real-time were obtained from 900 households of single apartments. To detect outliers and missing values in smart meter data, a deep learning model, the autoencoder, consisting of a graph convolutional network and bidirectional long short-term memory network, was applied to the smart metering technique. Power management based on the smart metering technique was executed by multi-objective optimization in the presence of a battery storage system and an electric vehicle. The results of the power management employing the proposed smart metering technique indicate a reduction in electricity cost and amount of power supplied by the grid compared to the results of power management without anomaly detection.