• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.2
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• pp.178-188
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• 2016

The traffic in the wired and wireless networks has increased exponentially because of increase of smart phone and improvement of PC performance. Multimedia services and file transmission such as Facebook, Youtube occupy a large part of the traffic. CDN is a technique that duplicates the contents on a remote web server of content provider to local CDN servers near clients and chooses the optimal CDN server for providing the content to the client in the event of a content request. In this paper, the content request message between CDN servers and the client used the SCRP algorithm utilizing the MST algorithm and the traffic throughput was optimized. The average response time for the content request is reduced by employing HC_LRU cache algorithm that improves the cache hit ratio. The proposed SCRP and HC_LRU algorithm may build a scalable content delivery network system that efficiently utilizes network resources, achieves traffic localization and prevents bottlenecks.

• The KIPS Transactions:PartB
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• v.12B no.7 s.103
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• pp.783-788
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• 2005

Recently researches that apply P2P networks to VOD streaming have been actively published In the previous works on VOD streaming, they aimed at achieving two major goals, which are zero-delay transmission and minimization of service rejection ratio. This paper proposes a new method, called ForwardCast, for VOD streaming based on a P2P-based multicasting tree in order to achieve theses two goals. In this method,- basically a new client selects one of the preceding clients and starts receiving a whole video from the selected one without any delay. In some situation, two preceding clients are selected to transfer the ending part of the video and its the remaining part simultaneously. In our experiment, ForwardCast can reduce the rejection ratio compared to previous works without increasing server stress.

• The KIPS Transactions:PartC
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• v.10C no.6
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• pp.809-814
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• 2003

The multicast transmitting the real-time data to groups may easily have many attacks from abnormal attacks because it has many links as compared to the unicast. The existing group key management architectures for preventing these problems are designed for protocols suitable for a large scale. Thus these architectures applied to a small scale routing protocols may have many overheads with key distribution and a constant core tree. Therefore this paper proposes a groups key management protocol for a secure multicast in PIM-SM multicast group communication. The proposed method divide multicast groups with RO(Rendezvous-Point), and subgroup key managers are established in each RP and can be transmitted groups keys between senders and receivers, so the security cannel is set up for secure data transfer, And this does not have needs of the data translation for group keys and the new key distribution for path change. As a result of this, the data transmission time can be reduced.

• 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.