• Journal of KIISE:Databases
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• v.32 no.2
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• pp.193-203
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• 2005

XML (extensible Markup Language) is recognized as a standard of data representation and transmission on Internet. XPath is a standard for specifying parts of XML documents anda suitable language for both query processing and access control of XML. In this paper, we use the XPath expression for representing user queries and access control for XML. And we propose an access control method for XML, where we control accesses to XML documents by filtering query XPath expressions through access control XPath expressions. In the proposed method, we directly search XACT (XML Access Control Tree) for a query XPath expression and extract the access-granted parts. The XACT is our proposedstructure, where the edges are structural summary of XML elements and the nodes contain access-control information. We show the query XPath expressions are successfully filtered through the XACT by our proposed method, and also show the performance improvement by comparing the proposed method with the previous work.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.11
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• pp.1071-1075
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• 2010

Because a sensor node in wireless sensor networks(WSNs) has limited resources, such as battery capacity and memory, data aggregation techniques have been studied to manage the limited resources efficiently. Because sensor network uses wireless communication, a data can be disclosed by attacker. Thus, the study on data protection schemes for data aggregation is essential in WSNs. But the existing data aggregation methods require both a large number of computation and communication, in case of network construction and data aggregation processing. To solve the problem, we propose a data protection scheme based on Hilbert-curve for data aggregation. Our scheme can minimizes communications among neighboring sensor nodes by using tree-based routing. Moreover, it can protect the data from attacker by doing encryption through a Hilbert-curve technique based on a private seed, Finally, we show that our scheme outperforms the existing methods in terms of message transmission and average sensor node lifetime.

• The Plant Pathology Journal
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• v.31 no.4
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• pp.371-378
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• 2015

Surveys of yellowing viruses in plastic tunnels and in open field crops of melon (Cucumis melo cultivar catalupo), oriental melon (C. melo cultivar oriental melon), and cucumber (C. sativus) were carried out in two melon-growing areas in 2014, Korea. Severe yellowing symptoms on older leaves of melon and chlorotic spots on younger leaves of melon were observed in the plastic tunnels. The symptoms were widespread and included initial chlorotic lesions followed by yellowing of whole leaves and thickening of older leaves. RT-PCR analysis using total RNA extracted from diseased leaves did not show any synthesized products for four cucurbit-infecting viruses; Beet pseudo-yellows virus, Cucumber mosaic virus, Cucurbit yellows stunting disorder virus, and Melon necrotic spot virus. Virus identification using RT-PCR showed Cucurbit aphid-borne yellows Virus (CABYV) was largely distributed in melon, oriental melon and cucumber. This result was verified by aphid (Aphis gossypii) transmission of CABYV. The complete coat protein (CP) gene amplified from melon was cloned and sequenced. The CP gene nucleotide and the deduced amino acid sequence comparisons as well as phylogenetic tree analysis of CABYV CPs showed that the CABYV isolates were undivided into subgroups. Although the low incidence of CABYV in infections to cucurbit crops in this survey, CABYV may become an important treat for cucurbit crops in many different regions in Korea, suggesting that CABYV should be taken into account in disease control of cucurbit crops in Korea.

• Genomics & Informatics
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• v.19 no.1
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• pp.11.1-11.8
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• 2021

For the novel coronavirus disease 2019 (COVID-19), predictive modeling, in the literature, uses broadly susceptible exposed infected recoverd (SEIR)/SIR, agent-based, curve-fitting models. Governments and legislative bodies rely on insights from prediction models to suggest new policies and to assess the effectiveness of enforced policies. Therefore, access to accurate outbreak prediction models is essential to obtain insights into the likely spread and consequences of infectious diseases. The objective of this study is to predict the future COVID-19 situation of Korea. Here, we employed 5 models for this analysis; SEIR, local linear regression (LLR), negative binomial (NB) regression, segment Poisson, deep-learning based long short-term memory models (LSTM) and tree based gradient boosting machine (GBM). After prediction, model performance comparison was evelauated using relative mean squared errors (RMSE) for two sets of train (January 20, 2020-December 31, 2020 and January 20, 2020-January 31, 2021) and testing data (January 1, 2021-February 28, 2021 and February 1, 2021-February 28, 2021) . Except for segmented Poisson model, the other models predicted a decline in the daily confirmed cases in the country for the coming future. RMSE values' comparison showed that LLR, GBM, SEIR, NB, and LSTM respectively, performed well in the forecasting of the pandemic situation of the country. A good understanding of the epidemic dynamics would greatly enhance the control and prevention of COVID-19 and other infectious diseases. Therefore, with increasing daily confirmed cases since this year, these results could help in the pandemic response by informing decisions about planning, resource allocation, and decision concerning social distancing policies.

• Journal of Conservation Science
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• v.37 no.3
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• pp.220-231
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• 2021

The use of digital copies of film-based analog images and the introduction of digital radiographic imaging systems using image plates gradually replace the non-destructive radiationirradiation method of Cultural Heritage. The quality of images obtained from this technique is affected by conditions such as tube voltage, tube current, and exposure time, type of image acquisition medium, distance of the artifacts from the image acquisition medium, and thickness of artifacts. In this study, we evaluated the grayscale image obtained using GE's Computed Radiograhpy (CR) imaging system, the transmission characteristics of the X-ray source for each tree type (pine, chestnut, sawtooth oak, ginkgo) used in wooden Cultural Heritage, and the signal-to-noise ratio (SNR) and contrast. The GE's CR imaging were analyzed using the Duplex wire image quality indicator, line-pair gauges.

• Journal of the Korea Society of Computer and Information
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• v.27 no.7
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• pp.101-108
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• 2022

We propose an intrusion detection model that detects denial-of-service(DoS) and distributed reflection denial-of-service(DRDoS) attacks, based on the empirical data of each internet of things(IoT) device by training system and network metrics that can be commonly collected from various IoT devices. First, we collect 37 system and network metrics from each IoT device considering IoT attack scenarios; further, we train them using six types of machine learning models to identify the most effective machine learning models as well as important metrics in detecting and distinguishing IoT attacks. Our experimental results show that the Random Forest model has the best performance with accuracy of over 96%, followed by the K-Nearest Neighbor model and Decision Tree model. Of the 37 metrics, we identified five types of CPU, memory, and network metrics that best imply the characteristics of the attacks in all the experimental scenarios. Furthermore, we found out that packets with higher transmission speeds than larger size packets represent the characteristics of DoS and DRDoS attacks more clearly in IoT networks.

• ALGAE
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• v.36 no.4
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• pp.241-261
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• 2021

Amphidinium species are amongst the most abundant benthic dinoflagellates in marine intertidal sandy ecosystems. Some of them produce a variety of bioactive compounds that have both harmful effects and pharmaceutical potential. In this study, Amphidinium cells were isolated from intertidal sand collected from the East China Sea. The two strains established were subjected to detailed examination by light, and scanning and transmission electron microscopy. The vegetative cells had a minute, irregular, and triangular-shaped epicone deflected to the left, thus fitting the description of Amphidinium sensu stricto. These strains are distinguished from other Amphidinium species by combination characteristics: (1) longitudinal flagellum inserted in the lower third of the cell; (2) icicle-shaped scales, 276 ± 17 nm in length, on the cell body surface; (3) asymmetrical hypocone with the left side longer than the right; and (4) presence of immotile cells. Therefore, they are described here as Amphidinium stirisquamtum sp. nov. The molecular tree inferred from small subunit rRNA, large subunit rRNA, and internal transcribed spacer-5.8S sequences revealed that A. stirisquamtum is grouped together with the type species of Amphidinium, A. operculatum, in a fully supported clade, but is distantly related to other Amphidinium species bearing body scale. Live A.stirisquamtum cells greatly affected the survival of rotifers and brine shrimp, their primary grazers, making them more susceptible to predation by the higher tropic level consumers in the food web. This will increase the risk of introducing toxicity, and consequently, the bioaccumulation of toxins through marine food webs.

• Advances in nano research
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• v.13 no.4
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• pp.325-339
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• 2022

Endophytes ascertain a symbiotic relationship with plants as promoters of growth, defense mechanism etc. This study is a first report to screen the endophytic population in Waltheria indica, a tropical medicinal plant. 5 bacterial and 3 fungal strains in leaves, 3 bacterial and 1 yeast species in stems were differentiated morphologically and identified by biochemical and molecular methods. The phylogenetic tree of the isolated endophytes was constructed using MEGA X. Silver nanoparticles were biosynthesized from a rare endophytic bacterium Cupriavidus metallidurans isolated from the leaf of W. indica. The formation of silver nanoparticles was confirmed by UV-Visible spectrophotometer that evidenced a strong absorption band at 408.5 nm of UV-Visible range with crystalline nature and average particle size of 16.4 nm by Particle size analyzer. The Fourier Transform Infra-Red spectrum displayed the presence of various functional groups that stabilized the nanoparticles. X-ray diffraction peaks were conferred to face centered cubic structure. Transmission Electron Microscope and Scanning Electron Microscope revealed the spherical-shaped, polycrystalline nature with the presence of elemental silver analyzed by Energy Dispersive of X-Ray spectrum. Selected area electron diffraction also confirmed the orientation of AgNPs at 111, 200, 220, 311 planes similar to X-ray diffraction analysis. The synthesized nanoparticles are evaluated for antimicrobial activity against 7 bacterial and 3 fungal pathogens. A good zone of inhibition was observed against pathogenic bacteria than fungal pathogens. Thus the study could hold a key aspect in drug discovery research and other pharmacological conducts of human clinical conditions.

• Proceedings of the Korea Information Processing Society Conference
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• 2008.11a
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• pp.1348-1351
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• 2008

최근 인터넷 사용자들의 요구는 멀티미디어로 집중되고 있으며 그중 라이브 미디어 스트리밍 서비스에 대한 요구가 증가하고 있다. 라이브 서비스에서는 적절한 시간에 사용자에게 데이터가 도착하는 것이 중요하다. 따라서 라이브의 시간적절성을 충족시켜 줄 효율적이고 신속한 데이터 전달구조와 전송기법이 요구된다. 이에 본 논문에서는 트리와 메시 구조를 혼합한 하이브리드 방식으로 네트워크 자원을 효율적으로 사용하면서 빠른 데이터 전송으로 라이브의 시간적절성을 충족시킬 수 있는 데이터 분할 전송 방식의 P2P(Peer-to-Peer) 오버레이 구조를 제안한다. 제안하는 ToG(Tree of Groups)는 n개의 피어들이 메시로 그룹을 형성하고, 그렇게 형성된 그룹들이 트리를 이루는 구조이다. ToG에서 그룹 내의 각 피어들은 상위그룹의 피어 한 개와 부모-자식으로 연결되어 있어서 그룹 사이에 여러 개의 연결이 존재하게 된다. 따라서 그룹 내에서 어느 한 피어가 그룹을 빠져 나가더라도 상위그룹과의 여러 연결에 의해서 서비스 지속성을 보장 할 수 있다. ToG는 그룹단위로 트리가 형성되기 때문에 피어의 개수가 같을 때 피어단위로 트리를 형성하는 구조보다 트리의 깊이가 줄어든다. 그에 따라 말단에 있는 피어들에게까지 빠른 시간에 데이터가 전달 될 수 있다. ToG의 데이터 전달은 소스로부터 세그먼트가 일정한 값 n으로 나뉘어져 각 피어들에게 전달된다. 세그먼트 조각은 소스로부터 나뉘어져 전송 될 때 책임적으로 전달해야할 피어와 전달 순서가 정해져있고, 데이터 전송 스케줄링을 위한 버퍼 맵 교환은 필요하지 않다.

• Spatial Information Research
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• v.19 no.3
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• pp.95-106
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• 2011

Recently as efficient processing of aggregate queries for fetching desired data from sensors has been recognized as a crucial part, in-network aggregate query processing techniques are studied intensively in wireless sensor networks. Existing representative in-network aggregate query processing techniques propose routing algorithms and data structures for processing aggregate queries. However, these aggregate query processing techniques have problems such as high energy consumption in sensor nodes, low accuracy of query processing results, and long query processing time. In order to solve these problems and to enhance the efficiency of aggregate query processing in wireless sensor networks, this paper proposes Bucket-based Parallel Aggregation(BPA). BPA divides a query region into several cells according to the distribution of sensor nodes and builds a Quad-tree, and then processes aggregate queries in parallel for each cell region according to routing. And it sends data in duplicate by removing redundant data, which, in turn, enhances the accuracy of query processing results. Also, BPA uses a bucket-based data structure in aggregate query processing, and divides and conquers the bucket data structure adaptively according to the number of data in the bucket. In addition, BPA compresses data in order to reduce the size of data in the bucket and performs data transmission filtering when each sensor node sends data. Finally, in this paper, we prove its superiority through various experiments using sensor data.