• Proceedings of the Korea Information Processing Society Conference
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• 2005.11a
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• pp.27-30
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• 2005

XML(Extensible Markup Language)이 데이터 표현(data representation)과 문서 교환(data exchange)의 표준으로 지정됨에 따라 데이터베이스(database, DB)에 XML 문서를 저장하고 질의하기 위한 연구가 활발히 진행되고 있다. 특히, 현재 주류를 이루고 있는 관계형 DB 에 저장하기 위한 XML 인덱싱(indexing) 기법에 대한 연구도 다양하게 진행되고 있다. 본 논문에서는 XML 문서를 관계형 DB 에 효율적으로 저장하고 질의하기 위한 방법으로서 기존의 트리(tree) 구조의 데이터를 관계형 DB 에 Nested Interval 인덱싱 기법을 적용하여 XML 문서를 저장하는 방법에 대해 연구한다. 기존의 저장 기법들의 경우 XML 문서를 효율적으로 질의하기 위한 인덱싱을 수행하기 때문에 입력 후 추가되는 노드(node), 혹은 노드 집합의 입력 시에는 전체 혹은 일부분의 XML 문서를 재-인덱싱 해야 하는 비효율이 있다. 그러나, Nested Interval 의 경우에는 재-인덱싱이 불필요하다. 본 논문에서는 기존의 트리 구조 데이터의 인덱싱 기법들에 대한 비교와 함께 Nested Interval 을 이용한 XML 문서의 인덱싱 기법에 대해 기술한다.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.6
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• pp.767-772
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• 2018

Recently, some meta-heuristic algorithms, such as GA(Genetic Algorithm) and GP(Genetic Programming), have been used to optimize CNN(Convolutional Neural Network). The CNN, which is one of the deep learning models, has seen much success in a variety of computer vision tasks. However, designing CNN architectures still requires expert knowledge and a lot of trial and error. In this paper, the recent attempts to automatically construct CNN architectures are investigated and analyzed. First, two GA based methods are summarized. One is the optimization of CNN structures with the number and size of filters, connection between consecutive layers, and activation functions of each layer. The other is an new encoding method to represent complex convolutional layers in a fixed-length binary string, Second, CGP(Cartesian Genetic Programming) based method is surveyed for CNN structure optimization with highly functional modules, such as convolutional blocks and tensor concatenation, as the node functions in CGP. The comparison for three approaches is analysed and the outlook for the potential next steps is suggested.

• Proceedings of the Korean Information Science Society Conference
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• 2004.10a
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• pp.559-561
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• 2004

임베디드 시스템은 정해진 하드웨어 환경에서 특정 어플리케이션이 돌아가는 형태로 존재한다. 코드 압축은 이러한 임베디드 시스템환경에서 메모리와 프로세서간의 소모되는 전력을 줄이는 가장 효과적인 방법으로 잘 알려져 있다. 본 논문에서는 기존과는 다른 접근방법을 통해 이 문제를 정의하고, 압축되는 명령어들의 이진코드를 결정하는 방법을 제시하고자 한다. 압축될 명령어들에 적절한 이진코드를 할당한다면 상당한 에너지를 절약할 수 있다. 이는 명령어 접근 때 발생하는 스위칭 활동이 이진코드할당에 큰 영향을 받기 때문이다. 전력 절감을 위해 이 문제를 그래프 최적화 문제로 전환을 하고, 점진적인 노드 커버링 테크닉(incremental node covering technique)을 사용하여 부분적으로는 효율적이면서도 전체적으로는 효과적인 방법으로 해결하고자 한다.

• Journal of IKEEE
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• v.23 no.2
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• pp.710-715
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• 2019

We consider parameter estimation in distributed systems in which measurements at local nodes are quantized in a non-regular manner, where multiple codewords are mapped into a single local measurement. For the system with non-regular quantization, to ensure a perfect independent encoding at local nodes, a local measurement can be encoded into a set of a great number of codewords which are transmitted to a fusion node where estimation is conducted with enormous computational cost due to the large cardinality of the sets. In this paper, we propose an efficient estimation technique that can handle the non-regular quantized data by efficiently finding the feasible combination of codewords without searching all of the possible combinations. We conduct experiments to show that the proposed estimation performs well with respect to previous novel techniques with a reasonable complexity.

• Smart Media Journal
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• v.12 no.1
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• pp.9-16
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• 2023

Recently, a convolutional neural network (CNN) based system is being developed to overcome the limitations of human resources in the apple quality classification of farmhouse. However, since convolutional neural networks receive only images of the same size, preprocessing such as sampling may be required, and in the case of oversampling, information loss of the original image such as image quality degradation and blurring occurs. In this paper, in order to minimize the above problem, to generate a image patch based graph of an original image and propose a random walk-based positional encoding method to apply the graph transformer model. The above method continuously learns the position embedding information of patches which don't have a positional information based on the random walk algorithm, and finds the optimal graph structure by aggregating useful node information through the self-attention technique of graph transformer model. Therefore, it is robust and shows good performance even in a new graph structure of random node order and an arbitrary graph structure according to the location of an object in an image. As a result, when experimented with 5 apple quality datasets, the learning accuracy was higher than other GNN models by a minimum of 1.3% to a maximum of 4.7%, and the number of parameters was 3.59M, which was about 15% less than the 23.52M of the ResNet18 model. Therefore, it shows fast reasoning speed according to the reduction of the amount of computation and proves the effect.

• Journal of Broadcast Engineering
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• v.13 no.6
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• pp.951-961
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• 2008

Cooperative diversity is a cooperative technique which exploits user diversity by decoding the combined signal of the relayed signal and the direct signal in wireless multi-hop networks. Using the cooperation, the performance of the network system can be improved because cooperative diversity which is very strong against the fading channels can be achieved. In this paper, we propose the technique that provides the enhanced visual quality of the reconstructed video using the cooperative diversity with the FMO which is the error resilience tool of H.264/AVC standardization over wireless networks. The eye-tracker can detect the gaze point of user and transmit the gaze information to the nodes. After receiving the gaze information of user, each node performs ROI encoding according to the received gaze information. After encoding, video sources are divided into ROI and Non-ROI. Through the simulation results, the better visual quality of the reconstructed video is achieved when ROI and Non-ROI are transmitted through different channels.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.3
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• pp.1510-1532
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• 2017

In smart grid, privacy implications to individuals and their families are an important issue because of the fine-grained usage data collection. Wireless communications are utilized by many utility companies to obtain information. Network coding is exploited in smart grids, to enhance network performance in terms of throughput, delay, robustness, and energy consumption. However, random linear network coding introduces a new challenge for privacy preserving due to the encoding of data and updating of coefficients in forwarder nodes. We propose a distributed privacy preserving scheme for random linear network coding in smart grid that considers the converged flows character of the smart grid and exploits a homomorphic encryption function to decrease the complexities in the forwarder node. It offers a data confidentiality privacy preserving feature, which can efficiently thwart traffic analysis. The data of the packet is encrypted and the tag of the packet is encrypted by a homomorphic encryption function. The forwarder node random linearly codes the encrypted data and directly processes the cryptotext tags based on the homomorphism feature. Extensive security analysis and performance evaluations demonstrate the validity and efficiency of the proposed scheme.

• Journal of Microbiology and Biotechnology
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• v.26 no.2
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• pp.326-336
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• 2016

Saccharomyces cerevisiae is one of the most employed cell factories for the production of bioproducts. Although monomeric hexose sugars constitute the preferential carbon source, this yeast can grow on a wide variety of nitrogen sources that are catabolized through central nitrogen metabolism (CNM). To evaluate the effects of internal perturbations on nitrogen utilization, we characterized strains deleted or overexpressed in GLT1, encoding for one of the key enzymes of the CNM node, the glutamate synthase. These strains, together with the parental strain as control, have been cultivated in minimal medium formulated with ammonium sulfate, glutamate, or glutamine as nitrogen source. Growth kinetics, together with the determination of protein content, viability, and reactive oxygen species (ROS) accumulation at the single cell level, revealed that GLT1 modulations do not significantly influence the cellular physiology, whereas the nitrogen source does. As important exceptions, GLT1 deletion negatively affected the scavenging activity of glutamate against ROS accumulation, when cells were treated with H₂O₂, whereas Glt1p overproduction led to lower viability in glutamine medium. Overall, this confirms the robustness of the CNM node against internal perturbations, but, at the same time, highlights its plasticity in respect to the environment. Considering that side-stream protein-rich waste materials are emerging as substrates to be used in an integrated biorefinery, these results underline the importance of preliminarily evaluating the best nitrogen source not only for media formulation, but also for the overall economics of the process.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.7
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• pp.3494-3510
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• 2019

Wireless sensor networks encounter energy saving as a major issue as the sensor nodes having no rechargeable batteries and also the resources are limited. Clustering of sensors play a pivotal role in energy saving of the deployed sensor nodes. However, in the cluster based wireless sensor network, the cluster heads tend to consume more energy for additional functions such as reception of data, aggregation and transmission of the received data to the base station. So, careful selection of cluster head and formation of cluster plays vital role in energy conservation and enhancement of lifetime of the wireless sensor networks. This study proposes a new mutation chemical reaction optimization (MCRO) which is an algorithm based energy efficient clustering protocol termed as MCRO-ECP, for wireless sensor networks. The proposed protocol is extensively developed with effective methods such as potential energy function and molecular structure encoding for cluster head selection and cluster formation. While developing potential functions for energy conservation, the following parameters are taken into account: neighbor node distance, base station distance, ratio of energy, intra-cluster distance, and CH node degree to make the MCRO-ECP protocol to be potential energy conserver. The proposed protocol is studied extensively and tested elaborately on NS2.35 Simulator under various senarios like varying the number of sensor nodes and CHs. A comparative study between the simulation results derived from the proposed MCRO-ECP protocol and the results of the already existing protocol, shows that MCRO-ECP protocol produces significantly better results in energy conservation, increase network life time, packets received by the BS and the convergence rate.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.1C
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• pp.14-19
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• 2006

The high encoding complexity of LDPC codes can be solved by designing structured parity-check matrix. If the parity-check matrix of LDPC codes is composed of same type of blocks, decoder implementation can be simple, this structure allow structured decoding and required memory for storing the parity-check matrix can be reduced largely. In this parer, we propose a construction algorithm for short block length structured LDPC codes based on girth condition, PEG algorithm and variable node connectivity. The code designed by this algorithm shows similar performance to other codes without structured constraint in low SNR and better performance in high SNR than those by simulation