• The KIPS Transactions:PartC
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• v.18C no.5
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• pp.303-316
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• 2011

Data aggregation is important in wireless sensor networks. However, it also introduces many security problems, one of which is that a compromised node may inject false data or drop a message during data aggregation. Most existing solutions rely on encryption, which however requires high computation and communication cost. But they can only detect the occurrence of an attack without finding the attacking node. This makes sensor nodes waste their energy in sending false data if attacks occur repeatedly. Even an existing work can identify the location of a false data injection attack but it has a limitation that at most 50% of total sensor nodes can participate in data transmission. Therefore, a novel approach is required such that it can identify an attacker and also increase the number of nodes which participate in data transmission. In this paper, we propose a monitoring-based secure data aggregation protocol to prevent against a compromised aggregator which injects false data or drops a message. The proposed protocol consists of aggregation tree construction and secure data aggregation. In secure data aggregation, we use integration of abnormal data detection with monitoring and a minimal cryptographic technique. The simulation results show the proposed protocol increases the number of participating nodes in data transmission to 95% of the total nodes. The proposed protocol also can identify the location of a compromised node which injects false data or drops a message. A communication overhead for tracing back a location of a compromised node is O(n) where n is the total number of nodes and the cost is the same or better than other existing solutions.

• Microbiology and Biotechnology Letters
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• v.47 no.1
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• pp.20-24
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• 2019

Moringa oleifera Lam (MOL) has been used as a traditional medicine to treat various cancers and inflammation. Whereas the bioactivities of the MOL leaf and seed are well reported, the study of the root is still rudimentary. In this study, the ethanol extract of MOL (EEMOL) and its subsequent organic solvent fractions were prepared and their anticoagulation activity in vitro and platelet aggregation inhibitory activity were evaluated. The EEMOL had negligible anticoagulation and strong platelet aggregation activities. However, the hexane and ethyl acetate fractions of EEMOL showed significant inhibition against thrombin, prothrombin, coagulation factors, and platelet aggregation, without hemolytic activity up to 1.0 mg/ml. Our results suggest that the active fractions of MOL root have potential as new anti-thrombosis agents.

• Journal of KIISE:Databases
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• v.36 no.3
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• pp.226-234
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• 2009

A data stream is a massive unbounded sequence of data elements continuously generated at a rapid rate. Due to the characteristics of a data stream, it is impossible to save all the data elements of a data stream. Therefore it is necessary to define a new synopsis structure to store the summary information of a data stream. For this purpose, this paper proposes a cuboid prefix tree that can be effectively employed in evaluating an iceberg query over data streams. A cuboid prefix tree only stores those itemsets that consist of grouping attributes used in GROUP BY query. In addition, a cuboid prefix tree can compute multiple iceberg queries simultaneously by sharing their common sub-expressions. A cuboid prefix tree evaluates an iceberg query over an infinitely generated data stream while efficiently reducing memory usage and processing time, which is verified by a series of experiments.

• Proceedings of the Korean Information Science Society Conference
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• 2003.10b
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• pp.46-48
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• 2003

최근 시공간 데이타에 대한 OLAP연산 효율을 증가시키기 위한 여러 가지 연구들이 행하여지고 있다. 이들 연구의 대부분은 다중트리구조에 기반하고 있다. 다중트리구조는 공간차원을 색인하기 위한 하나의 R-tree와 시간차원을 색인하기 위한 다수의 B-tree로 이루어져 있다. 하지만, 이러한 다중트리구조는 높은 유지비용과 불충분한 질의 처리 효율로 인해 현실적으로 시공간 OLAP연산에 적용하기에는 어려운 점이 있다. 본 논문에서는 이러한 문제를 근본적으로 개선하기 위한 접근 방법으로서 힐버트큐브(Hilbert Cube, H-Cube)를 제안하고 있다. H-Cube는 집계질의(aggregation query) 처리 효율을 높이기 위해 힐버트 곡선을 이용하여 셀들에게 완전순서(total-order)를 부여하고 있으며, 아울러 전통적인 누적합(prefix-sum) 기법을 함께 적용하고 있다. H-Cube는 적응적이며, 완전순서화되어 있으며, 또한 누적합을 이용한 셀 기반의 색인구조이다. 본 논문에서는 H-Cube의 성능 평가를 위해서 다양한 실험을 하였으며, 그 결과로서 유지비용과 질의 처리 효율성면 모두에서 다중트리구조보다 높은 성능 향상이 있음을 보인다.

• The Korean Journal of Ecology
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• v.2 no.1
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• pp.1-8
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• 1978

Epiphytic lichens were sampled quantitatively on the cherry trees (Prunus serrulata) at Jeonju and Hadong along both north and south exposures of tat trees. Coverage of lichens was determinated for each species by 10*20cm quadrat. Lichen species diversities such as total diversity (D), mean diversity (D), Shannon diversity (D') and redundancy (R) were estimated according to Brillouin and Shannon equation. The importance value of lichen species was meassured by niche preemption model, The importance value transformed into some fraction k of the niche space. The value of k was compared with aggregation of lichens communities in to areas. The ten most important awariensis, Parmelia incurva, Parmelia crinita, Dirinaria applanta, Parmelia wallichiana, Parmelia austrosinensis and Cetraria platyphylla. The mean coverage epiphytic lichens on north side of tree was higher than of south side in two areas. The species diversities of epiphytic lichen of two areas shows that a change in the value of D' along vertical was not paralled with the D and R. In Kumsan-sa, D, D and D' increased upward along the tree of north exposure, but did not follow this trend in south, However in Sangge-sa, D, D and D' of both sides increased.

• Journal of Ecology and Environment
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• v.35 no.4
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• pp.359-365
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• 2012

We investigated leaf disease intensity of Kalopanax septemlobus (prickly castor oil tree) caused by the parasitic fungus Mycosphaerella acanthopanacis, in thirty natural host populations in the Japanese Archipelago. The disease intensity observed for individual trees were analyzed using a generalized additive model as a function of tree size, tree density, climatic terms and spatial trend surface. Individual tree size and conspecific tree density were shown to have significant negative and positive effects on disease intensity, respectively. The findings suggest that the probability of disease infection is partly determined by dispersal of infection agents (ascospores) from the fallen leaves on the ground, which can be enhanced by aggregation of host trees in a forest stand. Regional-scale spatial bias was also present in disease intensity; the populations in northern Japan and southern Kyushu were more severely infected by the fungus than those in southwestern Honshu and Shikoku. Regional variation of disease intensity was explained by both climatic factors and a trend surface term, with a latitudinal cline detected, which increases towards the north. Further research should be conducted in order to understand all of the factors generating the latitudinal cline detected in this study.

• The KIPS Transactions:PartC
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• v.17C no.1
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• pp.69-80
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• 2010

Wireless sensor networks (WSN) consisting of a large number of sensors aim to gather data in a variety of environments and are being used and applied to many different fields. The sensor nodes composing a sensor network operate on battery of limited power and as a result, high energy efficiency and long network lifetime are major goals of research in the WSN. In this paper we propose a novel tree-based clustering approach for energy efficient wireless sensor networks. The proposed scheme forms the cluster and the nodes in a cluster construct a tree with the root of the cluster-head., The height of the tree is the distance of the member nodes to the cluster-head. Computer simulation shows that the proposed scheme enhances energy efficiency and balances the energy consumption among the nodes, and thus significantly extends the network lifetime compared to the existing schemes such as LEACH, PEGASIS, and TREEPSI.

• Journal of Ecology and Environment
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• v.29 no.1
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• pp.17-22
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• 2006

Since the demands not only for value-added timber but the environmental functions of forests had been increased, native tree species has been, and is rapidly being replaced by foreign tree species in many parts of the world. However, the studies on population structure and regeneration characteristics of native tree species were not conducted enough. Regeneration of Kalopanax septemlobus growing among other hardwoods in natural forests is very difficult because of its low seed viability and germination rate. The study examined the distribution of mature trees of K. septemlobus and their regeneration pattern at the 1.12 ha study plot in natural deciduous broad-leaved forest of Mt. Jeombong. The density and mean DBH of K. septemlobus was 97 trees per ha and 32 cm, respectively. The spatial distribution of K. septemlobus showed a random pattern (aggregation index is 0.935) in the 1.12 ha study plot. The age of 90 trees among 99 sample trees of K. septemlobus ranged from 90 to 110 years and represented a single cohort, thus suggesting that K. septemlobus in advance regeneration has regenerated as a result of disturbances such as canopy opening.

• The KIPS Transactions:PartD
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• v.13D no.1 s.104
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• pp.23-28
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• 2006

In this paper, a power-aware query processing using optimized distributed R-tree in a sensor network is proposed. The proposed technique is a new approach for processing range queries that uses spatial indexing. Range queries are most often encountered under sensor networks for computing aggregation values. The previous work just addressed the importance but didn't provide any efficient technique for processing range queries. A query processing scheme is thus designed for efficiently processing them. Each node in the sensor network has the MBR of the region where its children nodes and the node itself are located. The range query is evaluated over the region which intersects the geographic location of sensors. It ensures the maximum power savings by avoiding the communication of nodes not participating over the evaluation of the query.

• Journal of Korea Multimedia Society
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• v.9 no.11
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• pp.1381-1394
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• 2006

Generation methods of data cube have been studied for many years in data warehouse which supports decision making using stored data. There are two previous studies, one is multi-way array algorithm and the other is H-cubing algorithm which is based on the hyper-tree. The multi-way array algorithm stores all aggregation data in arrays, so if the base data is increased, the size of memory is also grow. The H-cubing algorithm which is based on the hyper-tree stores all tuples in one tree so the construction cost is increased. In this paper, we present an efficient data cube generation method based on hash table using weight mapping table and record hash table. Because the proposed method uses a hash table, the generation cost of data cube is decreased and the memory usage is also decreased. In the performance study, we shows that the proposed method provides faster search operation time and make data cube generation operate more efficiently.