• The Korean Journal of Pesticide Science
• /
• v.6 no.1
• /
• pp.16-24
• /
• 2002

Research trends in the measurement of foliar uptake of pesticides and the recently proposed action mechanism of the surfactant-induced uptake of pesticides were reviewed with the related reports and studies. Major techniques used in those fields are bioassay, radiotracer techniques with leaves or cuticular membrane. Recently, a new method using Congo Red as a tracer was proposed. The limiting factor in the pesticides uptake into leaves is the waxy layer which consists of the epicuticular and cuticular wax. Physico-chemical parameters such as molar volume, water solubility and partition coefficient of pesticides have limited influences on the pesticide uptake into leaves. Polydisperse ethoxylated fatty alcohol surfactants are well known as the good activator for many pesticides. It is now generally agreed that uptake activation is not related to the intrinsic surface active properties of surfactants such as surface activity, solvent property, humectancy and critical micelle concentration. Recent studies using ESR-spectroscopy revealed that the surfactants have an unspecific plasticising effect on the molecular structure of the wax and cuticular matrix, leading to increased mobilities of pesticides. Penetration of surfactants into waxy layer altered the pesticide mobility in wax and the partition coefficient of pesticide, and then the pesticides penetration into leaves was enhanced temporally. The enhancing effect of surfactant could be significantly different depending on the carbon number of aliphatic moiety and the number of ethoxy group in polyoxyethylene chain of surfactants. It is suggested that the rate of penetration of surfactants should have a significant relationship with the rate of penetration of pesticides.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.48 no.2
• /
• pp.16-27
• /
• 2011

Embryo is a very early stage of the development of multicellular organism such as animals and plants. It is an important research target for studying ontogeny because the fundamental body system of multicellular organism is determined during an embryo state. Researchers in the developmental biology have a large volume of embryo image databases for studying embryos and they frequently search for an embryo image efficiently from those databases. Thus, it is crucial to organize databases for their efficient search. Hierarchical clustering methods have been widely used for database organization. However, most of previous algorithms tend to produce a highly skewed tree as a result of clustering because they do not simultaneously consider both the size of a cluster and the number of objects within the cluster. The skewed tree requires much time to be traversed in users' search process. In this paper, we propose a method that effectively organizes a large volume of embryo image data in a balanced tree structure. We first represent embryo image data as a similarity-based graph. Next, we identify clusters by performing a graph partitioning algorithm repeatedly. We check constantly the size of a cluster and the number of objects, and partition clusters whose size is too large or whose number of objects is too high, which prevents clusters from growing too large or having too many objects. We show the superiority of the proposed method by extensive experiments. Moreover, we implement the visualization tool to help users quickly and easily navigate the embryo image database.

• The Journal of the Korea Contents Association
• /
• v.16 no.10
• /
• pp.477-482
• /
• 2016

This paper presents a new method of parity storing for ECC(error correcting code) in SSD (solid-state drive) and suitable structure of the controller. In general usage of NAND flash memory, we partition a page into data and spare area. ECC parity is stored in the spare area. The method has overhead on area and timing due to access of the page memory discontinuously. This paper proposes a new parity policy storing method that reduces overhead and R(read)/W(write) timing by using whole page area continuously without partitioning. We analyzed overhead and R/W timing. As a result, the proposed parity storing has 13.6% less read access time than the conventional parity policy with 16KB page size. For 4GB video file transfer, it has about a minute less than the conventional parity policy. It will enhance the system performance because the read operation is key function in SSD.

• YAKHAK HOEJI
• /
• v.48 no.6
• /
• pp.328-334
• /
• 2004

Cervical cancer is one of the leading causes of female death. Viral oncoproteins E6 and E7 are selectively retained and expressed in carcinoma cells infected with HPV (Human pa pilloma virus) type 16 and cooperated in immotalization and transformation of primary keratinocyte. E6 and E7 oncoproteins interfere the functions of tumor suppressor proteins p53 and retinoblasoma protein (pRb), respectively. Among a lots of natural products, Mentha arvensis Linne var.piperascens have inhibitory effects on bindings between E6 oncoprotein and tumor suppressor p53, E3 ubiqutin- protein ligase (E6AP). HPV oncoprotein inhibitors from Mentha piperita L. were isolated by solvent partition and column chromatography (Silica gel, RP-18) and inhibitory compounds were finally purified by HPLC using an ELISA screening system based on binding between E6 and E6AP. The aim of this study is to identify the structure of inhibitory compounds and to investigate whether these compounds have inhibitory effects on functions of E6 oncoprotein. We investigated whether caffeic acid methyl ester (CAM) extracted from Mentha piperita L. could inhibit the function of E6 oncoprotein. CAM inhibited the in vitro binding of E6 and E6AP which are essential for the binding and degradation of the tumor suppressor p53 and also inhibited the proliferation of human cervical cancer cell lines (SiHa and CaSKi) in a dose response manner. These results suggest that CAM inhibited the function of E6 oncoprotein, suggesting that it can be used as a potential drug for the treatment of cervical cancers infected with HPV.

• Journal of KIISE:Databases
• /
• v.29 no.3
• /
• pp.180-192
• /
• 2002

We investigate the effect of the data skew of join attributes on the performance of a pipelined multi-way hash join method, and propose two new harsh join methods in the shared-nothing multiprocessor environment. The first proposed method allocates buckets statically by round-robin fashion, and the second one allocates buckets dynamically via a frequency distribution. Using harsh-based joins, multiple joins can be pipelined to that the early results from a join, before the whole join is completed, are sent to the next join processing without staying in disks. Shared nothing multiprocessor architecture is known to be more scalable to support very large databases. However, this hardware structure is very sensitive to the data skew. Unless the pipelining execution of multiple hash joins includes some dynamic load balancing mechanism, the skew effect can severely deteriorate the system performance. In this parer, we derive an execution model of the pipeline segment and a cost model, and develop a simulator for the study. As shown by our simulation with a wide range of parameters, join selectivities and sizes of relations deteriorate the system performance as the degree of data skew is larger. But the proposed method using a large number of buckets and a tuning technique can offer substantial robustness against a wide range of skew conditions.

• Proceedings of the Ginseng society Conference
• /
• 1988.08a
• /
• pp.122-128
• /
• 1988

Several major polyacetylene compounds were isolated from the petroleum-ether fraction of fresh Korean ginseng roots through solvent fractionation. partition and silica gel column chromatography. Further separation of acetylenic compounds was accomplished by bonded normal phase HPLC utilizing a moderately nonpolar microparticulate column. The preparative separation for the various spectral measurements was carried out by low pressure preparative liquid chromatography. The chemical structure of these polyacetylenes separated was determined by UV. IR/FTIR. $^{1}H$ NMR. mass spectral and elemental analysis. These are identified to be heptadeca-1-en-4.6-diyn-3.9.l0.-triol [1] heptadeca-1.9-dien-4.6-diyn-3-ol. heptadeca-1.8-dien-4.6-diyn-3.10-diol and the 4th was denatured polyacetylene. heptadeca-1.4-dien-6.8-diyn-3.10-diol. Two different p-substituted benzoates of panaxynol were synthesized for the determination of exciton chirality. The circular dichroism spectra in the UV region show that panaxynol p-bromobenzoate and p-dimethyl-aminobenzoate constitute negative exciton chirality [2]. Isolated major polyacetylene compounds were irradiated in aerated solution with 300 nm UV light to obtain the oxidized product at the allylic alcohol center to corresponding carbonyl compounds such as heptadeca-1-en-4.6-diyn-9.10-diol-3-one and heptadeca-1.9-dien-4.6-diyn-3-one. These photooxidation compounds have en-on-diyne chromophore and undergo nucleophilic addition reaction with methanol to yield ${\beta}-methoxy$ carbonyl compounds such as heptadeca-9-en-4.6-diyn-1-methoxy-3-one and heptadeca-4.6-diyn-1-methoxy-9.10-diol-3-one.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.60 no.3
• /
• pp.639-647
• /
• 2011

In this paper, we introduce a design methodology of data-centroid Radial Basis Function neural networks with extended polynomial function. The two underlying design mechanisms of such networks involve K-means clustering method and Particle Swarm Optimization(PSO). The proposed algorithm is based on K-means clustering method for efficient processing of data and the optimization of model was carried out using PSO. In this paper, as the connection weight of RBF neural networks, we are able to use four types of polynomials such as simplified, linear, quadratic, and modified quadratic. Using K-means clustering, the center values of Gaussian function as activation function are selected. And the PSO-based RBF neural networks results in a structurally optimized structure and comes with a higher level of flexibility than the one encountered in the conventional RBF neural networks. The PSO-based design procedure being applied at each node of RBF neural networks leads to the selection of preferred parameters with specific local characteristics (such as the number of input variables, a specific set of input variables, and the distribution constant value in activation function) available within the RBF neural networks. To evaluate the performance of the proposed data-centroid RBF neural network with extended polynomial function, the model is experimented with using the nonlinear process data(2-Dimensional synthetic data and Mackey-Glass time series process data) and the Machine Learning dataset(NOx emission process data in gas turbine plant, Automobile Miles per Gallon(MPG) data, and Boston housing data). For the characteristic analysis of the given entire dataset with non-linearity as well as the efficient construction and evaluation of the dynamic network model, the partition of the given entire dataset distinguishes between two cases of Division I(training dataset and testing dataset) and Division II(training dataset, validation dataset, and testing dataset). A comparative analysis shows that the proposed RBF neural networks produces model with higher accuracy as well as more superb predictive capability than other intelligent models presented previously.

• Journal of KIISE:Information Networking
• /
• v.33 no.1
• /
• pp.76-90
• /
• 2006

Sensor network consists of a large number of sensor nodes that are densely deployed either inside the phenomenon or very close to it. The life time of each node in the sensor network significantly affects the life time of whole sensor network. A node which drained out its battery may incur the partition of whole network in some network topology The life time of each node depends on the battery capacity of each node. Therefore if all sensor nodes in the network live evenly long, the life time of the network will be longer. In this paper, we propose Cluster-Based Power-Efficient Routing (CBPER) Protocol which provides scalable and efficient data delivery to multiple mobile sinks. Previous r(luting protocols, such as Directed Diffusion and TTDD, need to flood many control packets to support multiple mobile sinks and many sources, causing nodes to consume their battery. In CBPER, we use the fact that sensor nodes are stationary and location-aware to construct and maintain the permanent grid structure, which makes nodes live longer by reducing the number of the flooding control packets. We have evaluated CBPER performance with TTDD. Our results show that CBPER is more power-efficient routing protocol than TTDD.

• Journal of the Korean Society of Radiology
• /
• v.17 no.2
• /
• pp.201-206
• /
• 2023

In order to improve the spatial resolution of the gamma camera, the size of the hole in the collimator must be reduced, so the sensitivity is reduced. In order to improve the sensitivity, the size of the hole must be increased, and thus the spatial resolution is reduced. In other words, spatial resolution and sensitivity show opposite characteristics. In this study, a gamma camera was designed to improve both spatial resolution and sensitivity. In order to obtain higher sensitivity in gamma cameras with the same spatial resolution, the structure of the scintillator was designed differently from the existing system. A scintillation pixel was used, and a partition wall was placed between the scintillation pixels to prevent incident gamma rays from being transmitted to other scintillation pixels to interact. Geant4 Application for Tomographic Emission (GATE) simulation was performed to evaluate the performance of the designed gamma camera. When the same sensitivity as the block-type scintillator was obtained, the spatial resolution increased by 16.5%, and when the same spatial resolution was obtained, the sensitivity increased by 61.5%. It is considered that the use of the gamma camera designed in this study can improve the sensitivity compared to the existing system while securing excellent spatial resolution.

• Korean Chemical Engineering Research
• /
• v.54 no.5
• /
• pp.621-629
• /
• 2016

Recently, the researches on quantitative structure activity relationship (QSAR) for describing toxicities or activities of chemicals based on chemical structural characteristics have been widely carried out in order to estimate the toxicity of chemicals in multiuse facilities. Because the toxicity of chemicals are explained by various kinds of molecular descriptors, an important step for QSAR model development is how to select significant molecular descriptors. This research proposes a statistical selection of significant molecular descriptors and a new QSAR model based on partial least square (PLS). The proposed QSAR model is applied to estimate the logarithm of partition coefficients (log P) of 130 polychlorinated biphenyls (PCBs) and lethal concentration ($LC_{50}$) of 14 PCBs, where the prediction accuracies of the proposed QSAR model are compared to a conventional QSAR model provided by OECD QSAR toolbox. For the selection of significant molecular descriptors that have high correlation with molecular descriptors and activity information of the chemicals of interest, correlation coefficient (r) and variable importance of projection (VIP) are applied and then PLS model of the selected molecular descriptors and activity information is used to predict toxicities and activity information of chemicals. In the prediction results of coefficient of regression ($R^2$) and prediction residual error sum of square (PRESS), the proposed QSAR model showed improved prediction performances of log P and $LC_{50}$ by 26% and 91% than the conventional QSAR model, respectively. The proposed QSAR method based on computational toxicology can improve the prediction performance of the toxicities and the activity information of chemicals, which can contribute to the health and environmental risk assessment of toxic chemicals.