• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.2
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• pp.54-64
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• 2010

Localization is the most important feature in the sensor network environment because it is a basic element enabling people and things to aware the circumference environment. Existing localization methods can be categorized as either range-based or range-free. While range-based is known to be not suitable because of the irregularity of radio propagation and the additional device requirement. range-free is much appropriated for the resource constrained sensor network because it can actively locate by means of the communication radio. But its location accuracy is just depended on the density of circumference nodes; it is very low in low-density sensor network environment. This paper proposes a mobile object tracking method, named DRTS(Distributed Range-hybrid Tracking Scheme), with combining range-based and range-free. It is optimally making use of the location, communication range, and received signal strength from circumference nodes. Especially, it can greatly improve the mobile tracking accuracy by adapting a new prediction method, named EGP(Estimative Gird Points) into the proposed location estimation method. The simulation results show that our method outperforms the other localization and tracking methods in the tracking accuracy point of view.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.35C no.3
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• pp.79-89
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• 1998

The Error Back-Propagation(EBP) algorithm is widely applied to train a multi-layer perceptron, which is a neural network model frequently used to solve complex problems such as pattern recognition, adaptive control, and global optimization. However, the EBP is basically a gradient descent method, which may get stuck in a local minimum, leading to failure in finding the globally optimal solution. Moreover, a multi-layer perceptron suffers from locking a systematic determination of the network structure appropriate for a given problem. It is usually the case to determine the number of hidden nodes by trial and error. In this paper, we propose a new algorithm to efficiently train a multi-layer perceptron. OUr algorithm uses stochastic perturbation in the weight space to effectively escape from local minima in multi-layer perceptron learning. Stochastic perturbation probabilistically re-initializes weights associated with hidden nodes to escape a local minimum if the probabilistically re-initializes weights associated with hidden nodes to escape a local minimum if the EGP learning gets stuck to it. Addition of new hidden nodes also can be viewed asa special case of stochastic perturbation. Using stochastic perturbation we can solve the local minima problem and the network structure design in a unified way. The results of our experiments with several benchmark test problems including theparity problem, the two-spirals problem, andthe credit-screening data show that our algorithm is very efficient.

• Nuclear Engineering and Technology
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• v.51 no.4
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• pp.1176-1179
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• 2019

Measurements of activity concentrations of radionuclides in atmospheric releases were performed in 2017-2018 at vent stacks of seven Russian nuclear power plants. The selected instruments and research methods, with detection limits significantly lower than the existing detection limit of Russian NPPs routine control, allowed to reliably determine up to 26 radionuclides. Analysis of experimental data allows to determine the list of radionuclides for calculation the effective dose rates to public and the permissible annual discharge levels for each Russian NPP. Radiocarbon is determined as major contributor for the dose from the atmospheric releases of LWGR reactors - up to 98% for EGP-6 and RBMK-1000 (Smolensk NPP) reactors. For PWR reactors (VVER) radionuclides contribution to the annual dose from atmospheric releases is more complicated, but, in general, dose is formed by tritium, $^{14}C$ and noble gases. The special monitoring results with ranking of measured radionuclides according to their contribution to the effective dose makes it possible to optimize the list of controlled radionuclides in airborne releases of Russian NPPs from 94 to 8-16 for different NPPs.

• The Plant Pathology Journal
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• v.35 no.4
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• pp.287-300
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• 2019

Spot blotch caused by Bipolaris sorokiniana has spread to more than 9 million ha of wheat in the warm, humid areas of the Eastern Gangetic Plains (EGP) of South Asia and is a disease of major concern in other similar wheat growing regions worldwide. Differential lignin content in resistant and susceptible genotypes and its association with free radicals such as hydrogen peroxide ($H_2O_2$), superoxide ($O_2{^-}$) and hydroxyl radical ($OH^-$) were studied after inoculation under field conditions for two consecutive years. $H_2O_2$ significantly influenced lignin content in flag leaves, whereas there was a negative correlation among lignin and $H_2O_2$ to the Area Under Disease Progress Curve (AUDPC). The production of $H_2O_2$ was higher in the resistant genotypes than susceptible ones. The $O_2{^-}$ and $OH^-$ positively correlated with AUDPC but negatively with lignin content. This study illustrates that $H_2O_2$ has a vital role in prompting lignification and thereby resistance to spot blotch in wheat. We used cluster analysis to separate the resistant and susceptible genotypes by phenotypic and biochemical traits. $H_2O_2$ associated lignin production significantly reduced the number of appressoria and penetration pegs. We visualized the effect of lignin in disease resistance using differential histochemical staining of tissue from resistant and susceptible genotypes, which shows the variable accumulation of hydrogen peroxide and lignin around penetration sites.

• Journal of Chest Surgery
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• v.30 no.9
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• pp.854-861
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• 1997

CYPRA 21-1 is known to be a cytokeratin 19 fragment, and it can be detected by using two specific monoclonal antibodies (KS 19-1 and BM 19-21) and can be clinically applied as a useful circulating tumor marker The epidermal growth factor receptor (EGF-R) expression was evaluated and characterized by its tyrosine protein kinase activity and by its ligand-stimulated autophosphorylation, a property shared with other peptide growth factor receptors. Autocrine or para'urine action was initiated by a growth factor, or by a transforming growth factor o, which had an extensive homology with EGP and which also stimulated tyrosine kinase activity on the EGF-R. The CYFRA 21-1 and the EGF-R levels in 30 patients with primary lung tumors were investigated. There were 24 patients with squamous cell carcinomas and 6 patients with adenocarcinomas. Specimen 5 mm3 in size were sampled at three different locations ; the main lesion, the boundary between the lesion and the unaffected tissue, and the unaffected tissue of the patients. The results were as follows 1. The CYPRA 21-1 concentration in the cancer boundary, the most malignant region,(348.6 : 89.9 ng/ml) was the lowest value. The CYFRA 21-1 concentration in unaffected tissue,(718.4$\pm$77.8 ng/ml) was higher than that in the main lesion. which had intact cellularity. 2. The EGF-R concentration in the main lesion was higher than that in the unaffected tissue, and the EGF-R concentration in a squamous cell cacinoma was higher than that in an adenocarcinoma. also, the EGF-R concentration in the cancer b undary was highest at stage 1, ll. The EGF-R concentration was higher in the main cancer lesion that in the unaffected tissue at stage 111, IV. 3. The CYFRA 21-1 was a cytoplasmic skeleton and the EGF-R was a cell-wall component; there was no correlation. In conclusion, CYFRA 21-1 was abundant in the cytoplasm but had a higher concentration in the unaffected tissue than in the main cancer lesion. The CYFRA 21-1 concentration of the tissue did not reflect the amount of cancer activity, the EGP-R was located in the cell membrane, the level of tissue that reflects cancer activity, so the main cancer lesion had a higher concentration than the unaffected tissue. CYFRA 21-1 is not a useful tumor maker at the tissue level. Because the EGF-R concentration re(looted the cancer activity, its a useful tumor marker for lung cancer.