• Journal of Korean Society of Environmental Engineers
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• v.32 no.1
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• pp.33-46
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• 2010

We investigated and estimated at the characteristics of decomposition and by-products of N-Nitrosodimethylamine (NDMA) using a design of experiment (DOE) based on the Box-Behken design in an UV process, and also the main factors (variables) with UV intensity($X_2$) (range: $1.5{\sim}4.5\;mW/cm^2$), NDMA concentration ($X_2$) (range: 100~300 uM) and pH ($X_2$) (rang: 3~9) which consisted of 3 levels in each factor and 4 responses ($Y_1$ (% of NDMA removal), $Y_2$ (dimethylamine (DMA) reformation (uM)), $Y_3$ (dimethylformamide (DMF) reformation (uM), $Y_4$ ($NO_2$-N reformation (uM)) were set up to estimate the prediction model and the optimization conditions. The results of prediction model and optimization point using the canonical analysis in order to obtain the optimal operation conditions were $Y_1$ [% of NDMA removal] = $117+21X_1-0.3X_2-17.2X_3+{2.43X_1}^2+{0.001X_2}^2+{3.2X_3}^2-0.08X_1X_2-1.6X_1X_3-0.05X_2X_3$ ($R^2$= 96%, Adjusted $R^2$ = 88%) and 99.3% ($X_1:\;4.5\;mW/cm^2$, $X_2:\;190\;uM$, $X_3:\;3.2$), $Y_2$ [DMA conc] = $-101+18.5X_1+0.4X_2+21X_3-{3.3X_1}^2-{0.01X_2}^2-{1.5X_3}^2-0.01X_1X_2+0.07X_1X_3-0.01X_2X_3$ ($R^2$= 99.4%, 수정 $R^2$ = 95.7%) and 35.2 uM ($X_1$: 3 $mW/cm^2$, $X_2$: 220 uM, $X_3$: 6.3), $Y_3$ [DMF conc] = $-6.2+0.2X_1+0.02X_2+2X_3-0.26X_1^2-0.01X_2^2-0.2X_3^2-0.004X_1X_2+0.1X_1X_3-0.02X_2X_3$ ($R^2$= 98%, Adjusted $R^2$ = 94.4%) and 3.7 uM ($X_1:\;4.5\;$mW/cm^2$, $X_2:\;290\;uM$, $X_3:\;6.2$) and $Y_4$ [$NO_2$-N conc] = $-25+12.2X_1+0.15X_2+7.8X_3+{1.1X_1}^2+{0.001X_2}^2-{0.34X_3}^2+0.01X_1X_2+0.08X_1X_3-3.4X_2X_3$ ($R^2$= 98.5%, Adjusted $R^2$ = 95.7%) and 74.5 uM ($X_1:\;4.5\;mW/cm^2$, $X_2:\;220\;uM$, $X_3:\;3.1$). This study has demonstrated that the response surface methodology and the Box-Behnken statistical experiment design can provide statistically reliable results for decomposition and by-products of NDMA by the UV photolysis and also for determination of optimum conditions. Predictions obtained from the response functions were in good agreement with the experimental results indicating the reliability of the methodology used.

• Journal of Periodontal and Implant Science
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• v.24 no.3
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• pp.581-596
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• 1994

This in vitro study was undertaken to obtain optimal tetracycline concentration that aids proliferation and spreading of human periodontal ligament cells, for clinical application in root surfaces of periodontally diseased teeth. Periodontal ligament cells used in this study were obtained from explants of periodontal ligament of 1st premolar teeth which were extracted for the purpose of orthodontic treatment. The cells were cultured in Dulbecco's Modified Eagle Medium(DMEM) supplemented with 100 U/ml penicillin, $100\;{\mu}g/ml$ streptomycin and 10% FBS at $37^{\circ}C$, 100% humidity, 5% $CO_2-95%$ air. Cells were used between the third to 4th passage. After root planing of periodontally extracted teeth, the root slabs were cut with carborundum disk. In the cell proliferation experiment, experimental groups were root planing only group, immersed groups in 25, 50, 75, 100, 150mg/ml aqueous solution of Tetracycline HCl followed by a vigorous rinse in PBS. Human PDL cells at concentration of $1{\times}10^5\;cells/ml$ were seeded in each culture well which contained root slabs and incubated for 6 hours. Then, all of the root slabs were moved into new 24 culture well and incubated 24, 48 and 72 hours. The cell counting was done by inverted phase contrast microscope after trypsinization. The following results were obtained. The cell number was increased in order root planing only group, 25, 150, 50, 75, 100mg/ml of Tetracycline HCl treated group in 24, 48 and 72 hours. The maximal cell number was obtained when the root slabs were immersed in solution with 100mg/ml of Tetracycline HCl. There were statistically significant between the root planing only group and 75, 100 mg/ml of Tetracycline HCl treated group in 24 hours, between the root planing only group and 100mg/ml of Tetracycline HCl treated group in 48 hours, between the root planing only group and 50, 75, 100mg/ml of Tetracycline HCl treated group, between 25 and 100mg/ml of Tetracycline HCl treated group in 72 hours(p<0.05). In the cell spreading experiment, after 30 minutes of incubated, in the root planing only group, the cells were generally round in shape. The cell surface was mostly covered with blebs. The cells started to attach to root surface by cytoplasmic extension in 50, 100mg/ml of Tetracycline HCl treated groups, more numerous cells attached to root surface than root planing only group. Many orifices of dentinal tubule were exposed, cells showed radially spreaded cytoplasm and unspreaded central region of the cell was covered with blebs. After 6 hours of incubation, in the root planing only group, cells showed radially spreaded cytoplasm and were attached flat appearance. In 50, 100mg/ml of Tetracycline HCl treated groups, cellular margin was concaved and cytoplasm showed elongated appearance with polarity. After 24 hours of incubation, in the root planing group, cells showed characteristic polarity. In 50, 100mg/ml of Tetracycline HCl treated groups, cells showed more elongated and spindle - like appearance.

• Radiation Oncology Journal
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• v.20 no.4
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• pp.323-327
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• 2002

Purpose : To evaluate the outcome of early stage non-small cell lung cancer patients who were treated with radiation therapy alone and define the optimal radiotherapeutic regimen for these patients. Materials and Methods : A retrospective review was peformed on patients with sage I or II non-small cell carcinoma of the lung that were treated at our institution between June, 1987 and May, 2000. A total of 21 patients treated definitively with radiation therapy alone were included in this study. The age of the patients ranged from 53 to 81 years with a median of 66 years. All the patients were male. The medical reasons for inoperability were lack of pulmonary reserve, cardiovascular disease, poor performance status, old age, and patient refusal in the decreasing order. Pathological evidence was not adequate to characterize the non-small cell subtype in two patients. Of the remaining 19 patients, 16 had squamous cell carcinoma and 3 had adenocarcinoma. Treatment was given with conventional fractionation, once a day, five times a week. The doses to the primary site ranged from 56 Gy to 59 Gy. No patients were lost to follow-up. Results : The overall survival rates for the entire group at 2, 3 and 5 years were 41, 30 and $21\%$, respectively. The cause specific survivals at 2, 3 and 5 years were 55, 36 and $25\%$, respectively. An intercurrent disease was the cause of death in two patients. The cumulative local failure rate at 5 years was $43\%$. Nine of the 21 patients had treatment failures after the curative radiotherapy was attempted. Local recurrences as the first site of failure were documented in 7 patients. Therefore, local failure alone represented $78\%$ of the total failures. Those patients whose tumor sizes were less than 4 cm had a significantly better 5 year disease free survival than those with tumors greater than 4 cm $(0\%\;vs\;36\%)$. Those patients with a Karnofsky performance status less than 70 did not differ significantly with respect to actuarial survival when compared to those with a status greater than 70 $(25\%\;vs\;26\%,\;p>0.05)$. Conclusion : Radiation therapy 리one is an effective and safe treatment for early stage non-small ceil lung cancer patients who are medically inoperable or refuse surgery. Also we believe that a higher radiation dose to the primary site could improve the local control rate, and ultimately the overall survival rate.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.185-202
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• 2012

.Since the value of information has been realized in the information society, the usage and collection of information has become important. A facial expression that contains thousands of information as an artistic painting can be described in thousands of words. Followed by the idea, there has recently been a number of attempts to provide customers and companies with an intelligent service, which enables the perception of human emotions through one's facial expressions. For example, MIT Media Lab, the leading organization in this research area, has developed the human emotion prediction model, and has applied their studies to the commercial business. In the academic area, a number of the conventional methods such as Multiple Regression Analysis (MRA) or Artificial Neural Networks (ANN) have been applied to predict human emotion in prior studies. However, MRA is generally criticized because of its low prediction accuracy. This is inevitable since MRA can only explain the linear relationship between the dependent variables and the independent variable. To mitigate the limitations of MRA, some studies like Jung and Kim (2012) have used ANN as the alternative, and they reported that ANN generated more accurate prediction than the statistical methods like MRA. However, it has also been criticized due to over fitting and the difficulty of the network design (e.g. setting the number of the layers and the number of the nodes in the hidden layers). Under this background, we propose a novel model using Support Vector Regression (SVR) in order to increase the prediction accuracy. SVR is an extensive version of Support Vector Machine (SVM) designated to solve the regression problems. The model produced by SVR only depends on a subset of the training data, because the cost function for building the model ignores any training data that is close (within a threshold ${\varepsilon}$) to the model prediction. Using SVR, we tried to build a model that can measure the level of arousal and valence from the facial features. To validate the usefulness of the proposed model, we collected the data of facial reactions when providing appropriate visual stimulating contents, and extracted the features from the data. Next, the steps of the preprocessing were taken to choose statistically significant variables. In total, 297 cases were used for the experiment. As the comparative models, we also applied MRA and ANN to the same data set. For SVR, we adopted '${\varepsilon}$-insensitive loss function', and 'grid search' technique to find the optimal values of the parameters like C, d, ${\sigma}^2$, and ${\varepsilon}$. In the case of ANN, we adopted a standard three-layer backpropagation network, which has a single hidden layer. The learning rate and momentum rate of ANN were set to 10%, and we used sigmoid function as the transfer function of hidden and output nodes. We performed the experiments repeatedly by varying the number of nodes in the hidden layer to n/2, n, 3n/2, and 2n, where n is the number of the input variables. The stopping condition for ANN was set to 50,000 learning events. And, we used MAE (Mean Absolute Error) as the measure for performance comparison. From the experiment, we found that SVR achieved the highest prediction accuracy for the hold-out data set compared to MRA and ANN. Regardless of the target variables (the level of arousal, or the level of positive / negative valence), SVR showed the best performance for the hold-out data set. ANN also outperformed MRA, however, it showed the considerably lower prediction accuracy than SVR for both target variables. The findings of our research are expected to be useful to the researchers or practitioners who are willing to build the models for recognizing human emotions.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.35 no.2
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• pp.91-101
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• 2009

in the cosmetics and medical supply field as a antioxidant material. The stable nano particle emulsion of skin toner type containing VEA was prepared. To evaluate the skin permeation, experiments on VEA permeation to the skin of the ICR outbred albino mice (12 weeks, about 50 g, female) and on differences of solubility as a function of receptor formulations was performed. The analysis of nano-emulsions containing VEA 0.07 % showed that the higher ethanol contents the larger emulsions were formed, while the higher surfactant contents the size became smaller.In this study, vitamin E acetate (VEA, tocopheryl acetate), a lipid-soluble vitamin which is widely used A certain contents of ethanol in receptor phase increased VEA solubility on the nano-emulsion. When the ethanol contents were 10.0 % and 20.0 %, the VEA solubility was higher than 5.0 % and 40.0 %, respectively. The type of surfactant in receptor solution influenced to VEA solubility. The comparison between three kind surfactants whose chemical structures and HLB values are different, showed that solubility of VEA was increased as order of sorbitan sesquioleate (Arlacel 83; HLB 3.7) > POE (10) hydrogenated castor oil (HCO-10; HLB 6.5) > sorbitan monostearate (Arlacel 60; HLB 4.7). VEA solubility was also shown to be different according to the type of antioxidant. In early time, the solubility of the sample including ascorbic acid was similar to those of other samples including other types of antioxidants. However, the solubility of the sample including ascorbic acid was 2 times higher than others after 24 h. Franz diffusion cell experiment using mouse skin was performed with four nano-emulsion samples which have different VEA contents. The emulsion of 10 wt% ethanol was shown to be the most permeable at the amount of 128.8 ${\mu}g/cm^2$. When the result of 10 % ethanol content was compared with initial input of 220.057 ${\mu}g/cm^2$, the permeated amount was 58.53 % and the permeated amount at 10 % ethanol was higher 45.0 % and 15.0 % than the other results which ethanol contents were 1.0 and 20.0 wt%, respectively. Emulsion particle size used 0.5 % surfactant (HCO-60) was 26.0 nm that is one twentieth time smaller than the size of 0.007 % surfactant (HCO-60) at the same ethanol content. Transepidermal permeation of VEA was 54.848 ${\mu}g/cm^2$ which is smaller than that of particlesize 590.7 nm. Skin permeation of nano-emulsion containing VEA and difference of VEA solubility as a function of receptor phase formulation were determined from the results. Using these results, optimal conditions of transepidermal permeation with VEA were considered to be set up.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.141-154
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• 2019

Rapid growth of internet technology and social media is progressing. Data mining technology has evolved to enable unstructured document representations in a variety of applications. Sentiment analysis is an important technology that can distinguish poor or high-quality content through text data of products, and it has proliferated during text mining. Sentiment analysis mainly analyzes people's opinions in text data by assigning predefined data categories as positive and negative. This has been studied in various directions in terms of accuracy from simple rule-based to dictionary-based approaches using predefined labels. In fact, sentiment analysis is one of the most active researches in natural language processing and is widely studied in text mining. When real online reviews aren't available for others, it's not only easy to openly collect information, but it also affects your business. In marketing, real-world information from customers is gathered on websites, not surveys. Depending on whether the website's posts are positive or negative, the customer response is reflected in the sales and tries to identify the information. However, many reviews on a website are not always good, and difficult to identify. The earlier studies in this research area used the reviews data of the Amazon.com shopping mal, but the research data used in the recent studies uses the data for stock market trends, blogs, news articles, weather forecasts, IMDB, and facebook etc. However, the lack of accuracy is recognized because sentiment calculations are changed according to the subject, paragraph, sentiment lexicon direction, and sentence strength. This study aims to classify the polarity analysis of sentiment analysis into positive and negative categories and increase the prediction accuracy of the polarity analysis using the pretrained IMDB review data set. First, the text classification algorithm related to sentiment analysis adopts the popular machine learning algorithms such as NB (naive bayes), SVM (support vector machines), XGboost, RF (random forests), and Gradient Boost as comparative models. Second, deep learning has demonstrated discriminative features that can extract complex features of data. Representative algorithms are CNN (convolution neural networks), RNN (recurrent neural networks), LSTM (long-short term memory). CNN can be used similarly to BoW when processing a sentence in vector format, but does not consider sequential data attributes. RNN can handle well in order because it takes into account the time information of the data, but there is a long-term dependency on memory. To solve the problem of long-term dependence, LSTM is used. For the comparison, CNN and LSTM were chosen as simple deep learning models. In addition to classical machine learning algorithms, CNN, LSTM, and the integrated models were analyzed. Although there are many parameters for the algorithms, we examined the relationship between numerical value and precision to find the optimal combination. And, we tried to figure out how the models work well for sentiment analysis and how these models work. This study proposes integrated CNN and LSTM algorithms to extract the positive and negative features of text analysis. The reasons for mixing these two algorithms are as follows. CNN can extract features for the classification automatically by applying convolution layer and massively parallel processing. LSTM is not capable of highly parallel processing. Like faucets, the LSTM has input, output, and forget gates that can be moved and controlled at a desired time. These gates have the advantage of placing memory blocks on hidden nodes. The memory block of the LSTM may not store all the data, but it can solve the CNN's long-term dependency problem. Furthermore, when LSTM is used in CNN's pooling layer, it has an end-to-end structure, so that spatial and temporal features can be designed simultaneously. In combination with CNN-LSTM, 90.33% accuracy was measured. This is slower than CNN, but faster than LSTM. The presented model was more accurate than other models. In addition, each word embedding layer can be improved when training the kernel step by step. CNN-LSTM can improve the weakness of each model, and there is an advantage of improving the learning by layer using the end-to-end structure of LSTM. Based on these reasons, this study tries to enhance the classification accuracy of movie reviews using the integrated CNN-LSTM model.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.23 no.4
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• pp.153-178
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• 2018

Most operational uses of wind speed data require measurements at, or estimates generated for, the reference height of 10 m above mean sea level (AMSL). On the Ieodo Ocean Research Station (IORS), wind speed is measured by instruments installed on the lighthouse tower of the roof deck at 42.3 m AMSL. This preliminary study indicates how these data can best be converted into synthetic 10 m wind speed data for operational uses via the Korea Hydrographic and Oceanographic Agency (KHOA) website. We tested three well-known conventional empirical neutral wind profile formulas (a power law (PL); a drag coefficient based logarithmic law (DCLL); and a roughness height based logarithmic law (RHLL)), and compared their results to those generated using a well-known, highly tested and validated logarithmic model (LMS) with a stability function (${\psi}_{\nu}$), to assess the potential use of each method for accurately synthesizing reference level wind speeds. From these experiments, we conclude that the reliable LMS technique and the RHLL technique are both useful for generating reference wind speed data from IORS observations, since these methods produced very similar results: comparisons between the RHLL and the LMS results showed relatively small bias values ($-0.001m\;s^{-1}$) and Root Mean Square Deviations (RMSD, $0.122m\;s^{-1}$). We also compared the synthetic wind speed data generated using each of the four neutral wind profile formulas under examination with Advanced SCATterometer (ASCAT) data. Comparisons revealed that the 'LMS without ${\psi}_{\nu}^{\prime}$ produced the best results, with only $0.191m\;s^{-1}$ of bias and $1.111m\;s^{-1}$ of RMSD. As well as comparing these four different approaches, we also explored potential refinements that could be applied within or through each approach. Firstly, we tested the effect of tidal variations in sea level height on wind speed calculations, through comparison of results generated with and without the adjustment of sea level heights for tidal effects. Tidal adjustment of the sea levels used in reference wind speed calculations resulted in remarkably small bias (<$0.0001m\;s^{-1}$) and RMSD (<$0.012m\;s^{-1}$) values when compared to calculations performed without adjustment, indicating that this tidal effect can be ignored for the purposes of IORS reference wind speed estimates. We also estimated surface roughness heights ($z_0$) based on RHLL and LMS calculations in order to explore the best parameterization of this factor, with results leading to our recommendation of a new $z_0$ parameterization derived from observed wind speed data. Lastly, we suggest the necessity of including a suitable, experimentally derived, surface drag coefficient and $z_0$ formulas within conventional wind profile formulas for situations characterized by strong wind (${\geq}33m\;s^{-1}$) conditions, since without this inclusion the wind adjustment approaches used in this study are only optimal for wind speeds ${\leq}25m\;s^{-1}$.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.191-207
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• 2021

Up to this day, mobile communications have evolved rapidly over the decades, mainly focusing on speed-up to meet the growing data demands of 2G to 5G. And with the start of the 5G era, efforts are being made to provide such various services to customers, as IoT, V2X, robots, artificial intelligence, augmented virtual reality, and smart cities, which are expected to change the environment of our lives and industries as a whole. In a bid to provide those services, on top of high speed data, reduced latency and reliability are critical for real-time services. Thus, 5G has paved the way for service delivery through maximum speed of 20Gbps, a delay of 1ms, and a connecting device of 106/㎢ In particular, in intelligent traffic control systems and services using various vehicle-based Vehicle to X (V2X), such as traffic control, in addition to high-speed data speed, reduction of delay and reliability for real-time services are very important. 5G communication uses high frequencies of 3.5Ghz and 28Ghz. These high-frequency waves can go with high-speed thanks to their straightness while their short wavelength and small diffraction angle limit their reach to distance and prevent them from penetrating walls, causing restrictions on their use indoors. Therefore, under existing networks it's difficult to overcome these constraints. The underlying centralized SDN also has a limited capability in offering delay-sensitive services because communication with many nodes creates overload in its processing. Basically, SDN, which means a structure that separates signals from the control plane from packets in the data plane, requires control of the delay-related tree structure available in the event of an emergency during autonomous driving. In these scenarios, the network architecture that handles in-vehicle information is a major variable of delay. Since SDNs in general centralized structures are difficult to meet the desired delay level, studies on the optimal size of SDNs for information processing should be conducted. Thus, SDNs need to be separated on a certain scale and construct a new type of network, which can efficiently respond to dynamically changing traffic and provide high-quality, flexible services. Moreover, the structure of these networks is closely related to ultra-low latency, high confidence, and hyper-connectivity and should be based on a new form of split SDN rather than an existing centralized SDN structure, even in the case of the worst condition. And in these SDN structural networks, where automobiles pass through small 5G cells very quickly, the information change cycle, round trip delay (RTD), and the data processing time of SDN are highly correlated with the delay. Of these, RDT is not a significant factor because it has sufficient speed and less than 1 ms of delay, but the information change cycle and data processing time of SDN are factors that greatly affect the delay. Especially, in an emergency of self-driving environment linked to an ITS(Intelligent Traffic System) that requires low latency and high reliability, information should be transmitted and processed very quickly. That is a case in point where delay plays a very sensitive role. In this paper, we study the SDN architecture in emergencies during autonomous driving and conduct analysis through simulation of the correlation with the cell layer in which the vehicle should request relevant information according to the information flow. For simulation: As the Data Rate of 5G is high enough, we can assume the information for neighbor vehicle support to the car without errors. Furthermore, we assumed 5G small cells within 50 ~ 250 m in cell radius, and the maximum speed of the vehicle was considered as a 30km ~ 200 km/hour in order to examine the network architecture to minimize the delay.

• Journal of Preventive Medicine and Public Health
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• v.7 no.1
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• pp.1-28
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• 1974

The writers have conducted the investigation to assess the nutritional status of young rural Korean children aged from 0 to 4 years old in August 1971. The survey areas were Kaejong-myon. Daeya-myon, Okku-gun, Jeonra-bukdo, Korea. These survey areas were typical agricultural plain areas. The total numbers of children examined were 2,706 comprising 1,394 male and 1,312 female. The weight, height, and chest circumference of children were measured and means and standard deviations. were calculated for each measurement. In addition, the nutritional status of each child was classified by the four levels of malnutrition and the Gomez classification, The examination of red blood cell count, haematocrit value, and intestinal parasite infection were carried out at the same time. In general, recent work tend to suggest that environmental influences, especially nutrition, are of great importance than genetic background or other biological factors for physical growth and development. Certainly the physical dimensions of the body are much influenced by nutrition, particularly in the rapidly growing period of early childhood. Selected body measurements can therefore give valuable information concerning protein-calory malnutrition. Growth can also be affected by bacterial, viral, and parasitic infection. For the field workers in a developing country, therefore, nutritional anthropometry appears to be of greatest value in the assessment of growth failure and undernutrition, principally from lack of protein and calories. In order to compare and evaluate the data obtained, the optimal data of growth from the off-spring of the true well-fed, medically and socially protected are needed. So-called 'Standards' that have been compiled for preschool children in Korea, however, are based on measurement of children from middle or lower socio-economic groups, who are, in fact, usually undernourished from six months of age onwards and continuously exposed to a succession of infective and parasitic diseases. So that, the Harvard Standards which is one of the international reference standards was used as the reference standards in this study. Findings of the survey were as follows: A. Anthropometric data: 1) Comparing the mean values for body weight obtained with the Korean standard weight of the same age, the rural Korean children were slightly haevier than the Korean standard values in both sexes. Comparing with the Japanese children values, the rural Korean children were slightly haevier in male and in the infant period of female but lighter in female of the period of 1 to 4 years old than Japanese children. 2) Comparing the mean values for height obtained with the Korean standard height of the same age, the rural Korean children were taller than the Korean standard values except the second half of infatn period in both sexes. Comparing with the Japanese children, the rural Korean children were slightly smaller than Japanese children except the first half of infant peroid in both sexes. 3) Mear values of chest circumference of rural Korean children obtained were less than the Korean standard values of the same ages in both sexes. B. Prevalence of Protein-Calory Malnutrition: Children examined were devided into two groups, i. e., infant(up to the first birthday) and toddler (1 to 4 fears old). 1) Percentages of four levels of malnutrition: a) When the nutrtional status of each child was classified (1) by body weight value, the percentages for male and female of children attained standard growth were 52.8%(infant 83.3%, toddler 44.4%) and 39.7% (infant 74.5%. toddler 30.5%), the first level of malnutrition were 31.9%(infant 13.7%, toddler 36.9%) and 31.7%(infant 15.3%, toddler 36,0%), the second level of malnutrition were 12.3%(infant 1.7%, toddler 15.3%) and 23.3% (infant 7.7%, fodder 27.5%), the third level of malnutrition were 2.7%(infant 0.7%, toddler 3.2%) and 4.6%(infant 1.8%, toddler 5.3%) the fourth level of malnutrition were 0.3% (infant 0.7%, toddler 0.2%) and 0.7% (0.7% for infant and toddler) respectively. (2) by height value, the percentages for male and female of children attained standard growth were 80.3% (infant 97.3%, toddler 75.6%) and 75.1% (infant 96.4%, toddler 69.5), the first level of malnutrition were 17.9% (infant 2.0%, toddler 22.3%) and 23.6% (infants 3.6%, toddler 28.8%), the second level of malnutrition were 1.2% (infant 0.3%, toddler 1.5%) and 1.1% (infant 0%, toddler 1.4%), the third level of malnutrition were 0.4%(infant 0.3%, toddler 0.5%) and 0.2%(infant 0%, toddler 0.3%), the fourth level of malnutrition were 0.1%(infant 0%, toddler 0.1%) and 0% respectively. (3) by body weight in relation to height, the percentages for male and female of children attained standard growth were 87.9% (infant 77.6%, toddler 87.9%) and 78.2% (infant 77.4%, toddler 78.2%), the first level of malnutrition were 12.2% (infant 18.4%, toddler 10.6%) and 18.2% (infant 17.9%, toddler 18.3%), the second level of malnutrition were 1.9%(infant 3.3%, toddler 1.5%) and 3.0%(infant 3.3%, toddler 2.9%), the third level of malnutrition were 0.1%(infant 0%. toddler 0.1%) and 0.5% (infant 0%, toddler 0.6%), the fourth level of malnutrition were 0.1%(infant 0.7%, toddler 0%) and 0.3% (infant 1.5%, toddler 0%) respectively. b) When the nutritional status of each child according to the mother's age at perturition, i. e., young aged mother (up to 30 years old), middle aged mother (31 to 40 years old) and old aged mother (41 years or above) was classified (1) by body weight, among infants and toddlers, at each year of age, with increasing the mother's age, there was an increase in percentage of subjects underweight. This tendency of increasing percentage of underweight was more significant in the infant period than the toddler period. (2) by height value, no significant differences between each mother's age group were found. c) When the nutritional status of each child according to the birth rank, i. e., lower birth rank (first to third) and higher birth rank (fourth or above) was classified (1) by weight value, children of higher birth rank were slightly more often underweight than those of lower birth rank, but not significant. (2) by height value, no differences were found between children of lower and higher birth rank. 2) Gomez Classification: When the nutritional status of each child was classified a) by body weight value, the percentages for male and female of children. attained standard growth were 53.1% (infant 82.6%, toddler 44.9%) and 39.2% (infant 73.4%, toddler 30.1%), the first degree of malnutrition were 39.4% (infant 14.7%, toddler 46.2%) and 47.1% (infant 21.9%, toddler 53.8%), the second degree of malnutrition were 7.3%(infant 2.3%, toddler 8.6%) and 12.9% (infant 4.0%, toddler 15.2%). and the third degree of malnutrition were 0.2%. (infant 0.3%, toddler 0.2%) and 0.8% (infant 0.7%, toddler 0.9%) respectively. b) by height value, the percentages for male and female of children attained standard growth were 80.8% (infant 97.0%, toddler 76.3%) and 73.8%(infant 95.6%, toddler 68.0%), the first degree of malnutrition were 18.5% (infant 2.7%, toddler 22.9%) and 24.6% (infant 4.4%, toddler 30.0%), the second degree of malnutrition were 0.6%(infant 0.3%, toddler 0.7%) and 0.5% (infant 0.1%, toddler 0.7%), and the third degree of malnutrition were 0.1%(infant 0%, toddler 0.1%) and 1.1% (infant 0%, toddler 1.3%) respectively. C. Results of clinical laboratory examination: 1) Red blood cells: The ranges of mean red blood cell counts for male and female were $3,538,000/mm^3\;to\;4,403,000/mm^3\;and\;3,576,000/mm^3\;to\;4,483,000/mm^3$ respectively. The lowest red cell counts were seen at the age of 0-3 months for male and 1-2 months for female. 2) Haematocrit value : The ranges of haematocrit value of male and female were 35.1% to 38.8% and 34.7% to 38.8% respectively. The lowest haematocrit values were seen at the age of 2-3 months for male and 1-2, months for female. 3) The prevalence rates of intestinal parasites for male and female children with Ascaris lumbricoides were 34.1% (infant 18.8%, toddler 38.1%) and 36.0%(infant 18.4%, toddler 40.7%), with Trichocephalus trichiuris were 6.8% (infant 2.9%, toddler 7.9%) and 9.0% (infant 3.0%, toddler 10.6%), with Hookworm were 0.3% (infant 0.5%, toddler 0.2%) and 0.3% (infant 0.5%, toddler 0.3%), with Clonorchis sinensis were 0.4%(infant 0%, toddler 0.5%) and 0.1%(infant 0%, toddler 0.1%) respectively.

• Journal of Internet Computing and Services
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• v.14 no.6
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• pp.71-84
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• 2013

Log data, which record the multitude of information created when operating computer systems, are utilized in many processes, from carrying out computer system inspection and process optimization to providing customized user optimization. In this paper, we propose a MongoDB-based unstructured log processing system in a cloud environment for processing the massive amount of log data of banks. Most of the log data generated during banking operations come from handling a client's business. Therefore, in order to gather, store, categorize, and analyze the log data generated while processing the client's business, a separate log data processing system needs to be established. However, the realization of flexible storage expansion functions for processing a massive amount of unstructured log data and executing a considerable number of functions to categorize and analyze the stored unstructured log data is difficult in existing computer environments. Thus, in this study, we use cloud computing technology to realize a cloud-based log data processing system for processing unstructured log data that are difficult to process using the existing computing infrastructure's analysis tools and management system. The proposed system uses the IaaS (Infrastructure as a Service) cloud environment to provide a flexible expansion of computing resources and includes the ability to flexibly expand resources such as storage space and memory under conditions such as extended storage or rapid increase in log data. Moreover, to overcome the processing limits of the existing analysis tool when a real-time analysis of the aggregated unstructured log data is required, the proposed system includes a Hadoop-based analysis module for quick and reliable parallel-distributed processing of the massive amount of log data. Furthermore, because the HDFS (Hadoop Distributed File System) stores data by generating copies of the block units of the aggregated log data, the proposed system offers automatic restore functions for the system to continually operate after it recovers from a malfunction. Finally, by establishing a distributed database using the NoSQL-based Mongo DB, the proposed system provides methods of effectively processing unstructured log data. Relational databases such as the MySQL databases have complex schemas that are inappropriate for processing unstructured log data. Further, strict schemas like those of relational databases cannot expand nodes in the case wherein the stored data are distributed to various nodes when the amount of data rapidly increases. NoSQL does not provide the complex computations that relational databases may provide but can easily expand the database through node dispersion when the amount of data increases rapidly; it is a non-relational database with an appropriate structure for processing unstructured data. The data models of the NoSQL are usually classified as Key-Value, column-oriented, and document-oriented types. Of these, the representative document-oriented data model, MongoDB, which has a free schema structure, is used in the proposed system. MongoDB is introduced to the proposed system because it makes it easy to process unstructured log data through a flexible schema structure, facilitates flexible node expansion when the amount of data is rapidly increasing, and provides an Auto-Sharding function that automatically expands storage. The proposed system is composed of a log collector module, a log graph generator module, a MongoDB module, a Hadoop-based analysis module, and a MySQL module. When the log data generated over the entire client business process of each bank are sent to the cloud server, the log collector module collects and classifies data according to the type of log data and distributes it to the MongoDB module and the MySQL module. The log graph generator module generates the results of the log analysis of the MongoDB module, Hadoop-based analysis module, and the MySQL module per analysis time and type of the aggregated log data, and provides them to the user through a web interface. Log data that require a real-time log data analysis are stored in the MySQL module and provided real-time by the log graph generator module. The aggregated log data per unit time are stored in the MongoDB module and plotted in a graph according to the user's various analysis conditions. The aggregated log data in the MongoDB module are parallel-distributed and processed by the Hadoop-based analysis module. A comparative evaluation is carried out against a log data processing system that uses only MySQL for inserting log data and estimating query performance; this evaluation proves the proposed system's superiority. Moreover, an optimal chunk size is confirmed through the log data insert performance evaluation of MongoDB for various chunk sizes.