• Journal of Animal Science and Technology
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• v.51 no.4
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• pp.337-342
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• 2009

The feasibility of reutilization of magnesium ammonium phosphate (MAP) or struvite slurry recovered from the process through microwave irradiation was studied in this experiment. For this purpose, 4 different operations were performed with or without Mg source addition and different levels of MAP recycled in a batch reactor. Dissolution rate of MAP, ${NH_4}^+$ elimination pattern and physicochemical changes of MAP during microwave irradiation were also studied. The result showed that only 33% orthophosphate ($PO_4-P$) and 27% $NH_4-N$ removal occurred without adding any external Mg source (run A), whereas 87% $PO_4-P$ and 40% $NH_4-N$ removed when 1.0 M ratio of $MgCl_2$ (run B) was added based on $PO_4-P$ in influent. Although the addition of 1.0 molar ratio of microwave irradiated MAP (Run C) removed lower $PO_4-P$ and $NH_4-N$ than 1.0 M $MgCl_2$ (run B), $PO_4-P$ removal was double when compared with no Mg addition (run A). Addition of half MAP and half $MgCl_2$ (run D) showed the similar removal efficiency (88% $PO_4-P$ and 35% $NH_4-N$) with sole $MgCl_2$ addition (run B). Based on these results, the reutilization of MAP irradiated by microwave would be a feasible way to enhance the removal efficiencies of N and P, as well as curtail the Mg chemical usage. Track study showed that $NH_4-N$ gradually increased at initial stage of microwave irradiation of MAP, and then started eliminating from liquor as temperature increased over $45^{\circ}C$. Dissolution rate of ${PO_4}^{-3}$ during microwave irradiation was proportional to the initial MAP concentration, having $0.0091x^{0.6373}$ mg/sec. It was found from the scanning electron microscope (SEM) study that physical structure of MAP crystal started breaking down into small cube granules within very short time by electromagnetic vibration force during microwave irradiation and then gradually melted down into solution.

• Journal of Life Science
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• v.21 no.1
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• pp.119-126
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• 2011

There is a growing recognition of the significance of $H_2S$ as a biological signaling molecule involved in vascular and nervous system functions. In mammals, two enzymes in the transsulfuration pathway, cystathionine ${\beta}$-synthase (CBS) and cystathionine ${\gamma}$-lyase (CGL), are believed to be chiefly responsible for $H_2S$ biogenesis. Genetic inborn error of CGL leads to human genetic disease, cystathioninuria, by accumulating cystathionine in the body. This disease is secondarily associated with a wide range of diseases including diabetes insipidus and Down's syndrome. Although the human CGL (hCGL) overexpression is essential for the investigation of its function, structure, reaction specificity, substrate specificity, and protein-protein interactions, there is no clear report concerning optimum overexpression conditions. In this study, we report a detailed analysis of the overexpression conditions of the hCGL using a bacterial system. Maximum overexpression was obtained in conditions of low culture temperature after inducer addition, performing low aeration during overexpression, and using a low concentration inducer (0.1 mM, IPTG) for induction. Expressed hCGL was purified by His-tag affinity column chromatography and confirmed by Western blot using hCGL antibody and enzyme activity analysis. We also report that the His tag with TEV site attached protein exhibits 76% activity for ${\alpha}-{\gamma}$ elimination reaction with L-cystathionine and 88% for ${\alpha}-{\beta}$ elimination reaction with L-cysteine compared to those of wild type hCGL, respectively. His tag with TEV site attached protein also exhibits a 420 nm absorption maximum, which is attributed to the binding cofactor, pyridoxal 5'-phosphate (PLP).

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.105-122
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• 2019

Dimensionality reduction is one of the methods to handle big data in text mining. For dimensionality reduction, we should consider the density of data, which has a significant influence on the performance of sentence classification. It requires lots of computations for data of higher dimensions. Eventually, it can cause lots of computational cost and overfitting in the model. Thus, the dimension reduction process is necessary to improve the performance of the model. Diverse methods have been proposed from only lessening the noise of data like misspelling or informal text to including semantic and syntactic information. On top of it, the expression and selection of the text features have impacts on the performance of the classifier for sentence classification, which is one of the fields of Natural Language Processing. The common goal of dimension reduction is to find latent space that is representative of raw data from observation space. Existing methods utilize various algorithms for dimensionality reduction, such as feature extraction and feature selection. In addition to these algorithms, word embeddings, learning low-dimensional vector space representations of words, that can capture semantic and syntactic information from data are also utilized. For improving performance, recent studies have suggested methods that the word dictionary is modified according to the positive and negative score of pre-defined words. The basic idea of this study is that similar words have similar vector representations. Once the feature selection algorithm selects the words that are not important, we thought the words that are similar to the selected words also have no impacts on sentence classification. This study proposes two ways to achieve more accurate classification that conduct selective word elimination under specific regulations and construct word embedding based on Word2Vec embedding. To select words having low importance from the text, we use information gain algorithm to measure the importance and cosine similarity to search for similar words. First, we eliminate words that have comparatively low information gain values from the raw text and form word embedding. Second, we select words additionally that are similar to the words that have a low level of information gain values and make word embedding. In the end, these filtered text and word embedding apply to the deep learning models; Convolutional Neural Network and Attention-Based Bidirectional LSTM. This study uses customer reviews on Kindle in Amazon.com, IMDB, and Yelp as datasets, and classify each data using the deep learning models. The reviews got more than five helpful votes, and the ratio of helpful votes was over 70% classified as helpful reviews. Also, Yelp only shows the number of helpful votes. We extracted 100,000 reviews which got more than five helpful votes using a random sampling method among 750,000 reviews. The minimal preprocessing was executed to each dataset, such as removing numbers and special characters from text data. To evaluate the proposed methods, we compared the performances of Word2Vec and GloVe word embeddings, which used all the words. We showed that one of the proposed methods is better than the embeddings with all the words. By removing unimportant words, we can get better performance. However, if we removed too many words, it showed that the performance was lowered. For future research, it is required to consider diverse ways of preprocessing and the in-depth analysis for the co-occurrence of words to measure similarity values among words. Also, we only applied the proposed method with Word2Vec. Other embedding methods such as GloVe, fastText, ELMo can be applied with the proposed methods, and it is possible to identify the possible combinations between word embedding methods and elimination methods.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.29 no.1
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• pp.14-27
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• 2024

Unlike the shelf sand ridges moribund in motion, nearshore sand ridges are highly mobile, sensitive to changes in ocean environments, thereby becoming of particular interest with respect to morphological changes. About 5 km off the Daesan port, the Jangan Sand Ridge has been undergoing severe subsea morphological change over the past two decades. Understanding the nature of sand ridges is critical to elucidate the causes of morphological changes. In this context, this study aims at understanding the characteristics and distribution patterns of surface sediments of the ridge and its vicinity. For this purpose, 227 sediment samples were acquired using a grab-sampler, the grain sizes being analysed by the sieve-pipette method. In addition, comparison of grain sizes in sediments between 1997 and 2021 was made in order to investigate the 25-years change in sediment composition. Surface sediments along the ridge axis are fine to medium sands with 2-3 phi in mean grain size, whereas, in the trough of ridge, the sediments are composed of gravels and muddy sandy gravels with mean sizes of -2 to -6 phi. Sediments in the crest of the ridge are well-sorted with normal distribution, on the other hand, the basal sediments are poorly-sorted and positively skewed. Along the ridge crest, the sediments are negatively skewed. From 1997 to 2021, the ridge sediments became largely coarser about 0.5 phi. Such coarsening trend in mean grain size can be explained either by elimination of fine sediments during high waves in winter or elimination of fines suspended during sand mining activities in the past. Spatial distribution pattern of surface sediments shows that ca. 30 m thick of the sand ridge itself overlies the thin relict gravels. The strong asymmetry of sand ridge, the exposure of ridge base, and reworked gravel lags suggest that Jangan sand ridge is probably sediment-deficit and hence erosive in nature at present.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.173-198
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• 2020

For a long time, many studies have been conducted on predicting the success of campaigns for customers in academia, and prediction models applying various techniques are still being studied. Recently, as campaign channels have been expanded in various ways due to the rapid revitalization of online, various types of campaigns are being carried out by companies at a level that cannot be compared to the past. However, customers tend to perceive it as spam as the fatigue of campaigns due to duplicate exposure increases. Also, from a corporate standpoint, there is a problem that the effectiveness of the campaign itself is decreasing, such as increasing the cost of investing in the campaign, which leads to the low actual campaign success rate. Accordingly, various studies are ongoing to improve the effectiveness of the campaign in practice. This campaign system has the ultimate purpose to increase the success rate of various campaigns by collecting and analyzing various data related to customers and using them for campaigns. In particular, recent attempts to make various predictions related to the response of campaigns using machine learning have been made. It is very important to select appropriate features due to the various features of campaign data. If all of the input data are used in the process of classifying a large amount of data, it takes a lot of learning time as the classification class expands, so the minimum input data set must be extracted and used from the entire data. In addition, when a trained model is generated by using too many features, prediction accuracy may be degraded due to overfitting or correlation between features. Therefore, in order to improve accuracy, a feature selection technique that removes features close to noise should be applied, and feature selection is a necessary process in order to analyze a high-dimensional data set. Among the greedy algorithms, SFS (Sequential Forward Selection), SBS (Sequential Backward Selection), SFFS (Sequential Floating Forward Selection), etc. are widely used as traditional feature selection techniques. It is also true that if there are many risks and many features, there is a limitation in that the performance for classification prediction is poor and it takes a lot of learning time. Therefore, in this study, we propose an improved feature selection algorithm to enhance the effectiveness of the existing campaign. The purpose of this study is to improve the existing SFFS sequential method in the process of searching for feature subsets that are the basis for improving machine learning model performance using statistical characteristics of the data to be processed in the campaign system. Through this, features that have a lot of influence on performance are first derived, features that have a negative effect are removed, and then the sequential method is applied to increase the efficiency for search performance and to apply an improved algorithm to enable generalized prediction. Through this, it was confirmed that the proposed model showed better search and prediction performance than the traditional greed algorithm. Compared with the original data set, greed algorithm, genetic algorithm (GA), and recursive feature elimination (RFE), the campaign success prediction was higher. In addition, when performing campaign success prediction, the improved feature selection algorithm was found to be helpful in analyzing and interpreting the prediction results by providing the importance of the derived features. This is important features such as age, customer rating, and sales, which were previously known statistically. Unlike the previous campaign planners, features such as the combined product name, average 3-month data consumption rate, and the last 3-month wireless data usage were unexpectedly selected as important features for the campaign response, which they rarely used to select campaign targets. It was confirmed that base attributes can also be very important features depending on the type of campaign. Through this, it is possible to analyze and understand the important characteristics of each campaign type.

• Resources Recycling
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• v.28 no.6
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• pp.3-8
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• 2019

Recently, plastic waste in Korea has been recognized as a critical issue due to an increase in massive production of plastics, difficulty in disposal of waste plastics, and public recognition of toxicity in micro-plastics, etc. To resolve those problems, the regulation to reduce plastics consumption may be primarily considered but, in this case, clarification should be made on the rationales and the action plans in the regulation for individual waste plastic items. Another problem is the small capital sizes of domestic recycling companies, which leads to poor R&D capacity, low recycling yields and thus lowering values of recycling items. This adversely affects consumers' perception. The R&D toward recycling technical progress should take into account the environmental friendliness and recyclability from the early product design stages. Certainly, this should be supported in governmental policy and public action plans. In addition, by referring to advanced policies of i.e. European Union, the recycling industry should be recognized as an opportunity toward new investment & employment. If necessary, the regulation of plastic consumption through a formal evaluation process such as Life Cycle Assessment (LCA) will also be helpful. The values of recycled plastics should be improved through the identification and elimination of harmful chemical substances potentially contained in the products.

• The Korean Journal of Physiology and Pharmacology
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• v.1 no.6
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• pp.717-730
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• 1997

$Mg^{2+}$ is the fourth most abundant cation in cellular organisms. Although the biological chemistry and the physiological roles of the magnesium ion were well known, the regulation of intracellular $Mg^{2+}$ in mammalian cells is not fully understood. More recently, however, the mechanism of $Mg^{2+}$ mobilization by hormonal stimulation has been investigated in hearts and in myocytes. In this work we have investigated the regulation mechanism responsible for the $Mg^{2+}$ mobilization induced by ${\alpha}1-adrenoceptor$ stimulation in perfused guinea pig hearts or isolated myocytes. The $Mg^{2+}$ content of the perfusate or the supernatant was measured by atomic absorbance spectrophotometry. The elimination of $Mg^{2+}$ in the medium increased the force of contraction of right ventricular papillary muscles. Phenylephrine also enhanced the force of contraction in the presence of $Mg^{2+}$-free medium. ${\alpha}1-Agonists$ such as phenylephrine were found to induce $Mg^{2+}$ efflux in both perfused hearts or myocytes. This was blocked by prazosin, a ${\alpha}1-adrenoceptor$ antagonist. $Mg^{2+}$ efflux by phenylephrine was amplified by $Na^+$ channel blockers, an increase in extracellular $Ca^{2+}$ or a decrease in extracellular $Na^+$. By contrast, the $Mg^{2+}$ influx was induced by verapamil, nifedipine, ryanodine, lidocaine or tetrodotoxin in perfused hearts, but not in myocytes. $W_7$, a $Ca^{2+}/calmodulin$ antagonist, completely blocked the pheylephrine-, A23187-, veratridine-, $Ca^{2+}-induced$ $Mg^{2+}$ efflux in perfused hearts or isolated myocytes. In addition, $Mg^{2+}$ efflux was induced by $W_7$ in myocytes but not in perfused heart. In conclusion, An increase in $Mg^{2+}$ efflux by ${\alpha}1-adrenoceptor$ stimulation in hearts can be through $IP_3$ and $Ca^{2+}-calmodulin$ dependent mechanism.

• Journal of radiological science and technology
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• v.30 no.1
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• pp.1-6
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• 2007

This study is to decrease compound noise in x-ray films. This study compared Signal to noise ratio(SNR), Peak signal to noise ratio(PSNR), Mean square error(MSE) to surface of the earth. In addition, we evaluated noise elimination effect according to the kernel size of Median filter. This experiments show that some filters are useful by finding image that is near in circle image comparing circle picture with each processed picture. In noise power value, when cutoff frequency was compared with other filters of cutoff frequency. Cutoff frequency of $2/3\pi{\sim}3/4\pi$ is good and it shows good SNR and PSNR. Therefore, it can display high filter effect. As Median Filter's Kernel size grows SNR value gets bigger, which shows better filter effect. Most pictures are distorted after filter application in medical treatment image. It is important to keep spatial resolution in most medical images. Visual estimation as well as quantitative indicators should be necessary for a better image.

• Applied Biological Chemistry
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• v.40 no.1
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• pp.53-57
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• 1997

The rate of hydrolysis of insecticidal 1-(6-chloro-3-pyridylmethyl) -2-nitro-iminoimidazolidine (common name; imidacloprid) have been investigated in 15%(v/v) aqueous dioxane at $45^{\circ}C$. From the kinetics and non-kinetics data such as pH-effect, solvent effect(m=0.04, n=0.30 IT m<${\Delta}H^{\neq}=16.14kcal{\cdot}mol^{-1}\;&\;{\Delta}S^{\neq}=-0.03e.u.$), rate equation ($k_{obs.}=4.56{\times}10^{-3}[OH^-]$) and analysis of hydrolysis product, 1-(6-chloro-3-pyridylmethyl-2)-imidazolidinon, the hydrolysis mechanism of imidacloprid is proposed that the specific base catalyzed hydrolysis($K_{OH^-}$) through nucleophilic addition-elimination ($Ad_N-E$) mechanism proceed via intermediate, 1-(6-chloro-3- pyridylmethyl)-2-hydroxy-2-imidazolidinylisonitraminate (I) and ${\beta}$-3-(6-chloro-3-pyridylmethyl)aminoethyl-1-nitrourea(III). And the half-life(t1/2) of hydrolytic degradation at pH 8.0 and $45^{\circ}C$ was about 4.5 months.

• Journal of Korean Academy of Nursing
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• v.25 no.1
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• pp.45-60
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• 1995

This study investigated the effects of education program conducted through individual home visit by CHPs, which was developed ,by the operational re-search technique for families of dementia patients. (Yeo Shin Hong et at,1994) The study was conducted in the form of a primary experimental design with 43 people as subjects, including dementia patients and family member in several Myon areas of Chungcheong Namdo between June 10 and August 20, 1994. The data was collected by questionnaires through the home visit by the CHPs. The results of study are as follows. 1. There is no difference in the quality of life between before and after the education program. 2. Role stress 'before the education program' was significantly different than 'after the education program'. 3. There was no difference in the feeling of burden between before and after the education program. 4. There was a significant difference in the abnormal behaviors of patients between before and after the education program. 5. The knowledge of dementia by the patient's family increased significantly after the education program, compared to that of 'before the education program'. 6. There was a significant difference in the attitude of family members toward the education program on dementia between before and after the education program. 7. The results of analysis on the coefficient relationship of various variables showed that the age of patients and family members have a significant correlation with role stress(p=.01). 8. In the subjective evaluation of family members on changes in actual nursing actions and the improvement of knowledge and technique in terms of daily living, (including abnormal behavior of patients, adjustment of environment for patients, activity programs for patients, communication technique with patients, ensuring the safety of patients, clothing, meals and elimination, 60-65% of family members responded that their knowledge had increased. As for improvement in techniques for each item, the technique for communication with patients showed the greatest improvement while the action program method for patients showed the least change. As for the nursing service provided to patients, most respondents showed a positive change. The specific items for which more than 80% respondents answered positively were as follows : recognizing the demand of patients, getting patients to do simple house works, talking softly and gently, removing dangerous things, preparing comfortable clothes that are easy to put on and take off, and limiting water consumption at night. As a result of study, the following suggestions can be made. The purpose of the study was to examine the effect of an education program developed and applied for dementia patients and family members in the community. This needs to be compared with a similar study conducted in the urban setting. In addition, a community service program (ex : nursing hem and shelter) including the application of the education program should be developed and the study done to investigate its effect.