• Journal of The Korean Association For Science Education
• /
• v.32 no.1
• /
• pp.95-112
• /
• 2012

The research evaluated the effects of the improvements in scientific inquiry for elementary school students and focused on the development and application of the explicit and reflective learning strategy through observation and classification. The explicit and reflective learning strategy was modified and completed with the review of the experts after the development of the draft based on the theoretical approach. The students were evaluated for their academic achievements in scientific inquiry skills before and after taking the course. The results were as follows: First, the steps of the developed learning strategy (1) to motivate, (2) to explore reflectively, (3) to guide explicitly, (4) to inquire explicitly, and (5) to verify reflectively were set to reflect the verification. Second, the results of applying the developed model to the lessons based on the quantitative analysis was effective for observation and classification skills in the quest for improved performance of the whole (the sum of observation and classification, inquiry skills) and the observed features, but there was no effect on classification. Also, the lessons applied the developed teaching strategy and showed effectiveness in improving academic achievement. Particularly in analyzing the relationship between the academic achievement and exploration capabilities, in order to improve academic achievement, the importance of improving inquiry skills was found. Third, the qualitative analysis of teaching and learning strategy developed by applying the lessons of this teacher guide and small group activities through the explicit and reflective observation and classification of the student learning activities showed the significant improvement of ability of the scientific inquiry skills. In addition to the improvement in the abilities of the classification showed after the formation of the most basic observation skills of the scientific inquiry.

• Strategy21
• /
• s.32
• /
• pp.123-159
• /
• 2013

The purpose of this research paper is to re-valuate the factors that affected the Royal Navy's rearmament and preparation for war by conducting analysis on the discussion held in the Britain on the strategic priorities and Navy's coping measures adopted during the interwar period. After the end of the WWI, each of the military arms of the Britain faced significant difficulty in securing budget and increasing their military power all throughout the interwar period, and the Navy was not an exception. The WWII that got started on September 1939 was the turning point in which this difficulty led to full-fledged crisis. Immensely many criticisms followed after the war and problems were identified when it comes to the Royal Navy's performance during the war. This type of effort to identify problem led to the attempt to analyze whether Royal Navy's preparation for war and rearmament policy during interwar period were adequate, and to identify the root causes of failure. Existing studies sought to find the root cause of failed rearmament from external factors such as the deterioration of the Britain itself or pressure from the Treasury Department to cut the budget for national defense, or sought to detect problems from the development of wrong strategies by the Navy. However, Royal Navy's failed preparation for the war during interwar period is not the result of one or two separate factors. Instead, it resulted due to the diverse factors and situations that the Britain was facing at the time, and due to intricate and complex interaction of these factors. Meanwhile, this research paper focused on the context characterized by 'strategic selection and setting up of priorities' among the various factors to conduct analysis on the Navy's rearmament by linking it with the discussion held at the time on setting up strategic priorities, and sought to demonstrate that the Navy Department's inadequate counter-measures developed during this process waned Royal Navy's position. After the end of WWI, each of the military arms continued to compete for the limited resources and budget all throughout the interwar period, and this type of competition amidst the situation in which the economic situation of Britain was still unstable, made prioritization when it comes to the allocation of resources and setting up of the priorities when it comes to the military power build-up, inevitable. Amidst this situation, the RAF was able to secure resources first and foremost, encouraged by the conviction of some politicians who were affected by the 'theory of aerial threat' and who believed that curtailing potential attack with the Air Force would be means to secure national security at comparatively lower cost. In response, Navy successfully defended the need for the existence of Navy despite the advancement of the aerial power, by emphasizing that the Britain's livelihood depends on trade and on the maintenance of maritime traffic. Despite this counter-measuring logic, however, Navy's role was still limited to the defense of overseas territory and to the fleet run-off instead of sea traffic route production when it comes to the specific power build-up plan, and did not understand the situation in which financial and economic factors gained greater importance when it comes to the setting up of strategic priorities. As a result, Navy's plan to build its powers was met with continual resistance of the Treasury Department, and lost the opportunity to re-gain the status of 'senior service' that it had enjoyed in the past during the competition for strategic prioritization. Given that the strategic and economic situation that Korea faces today is not very different from that of the Britain during the interwar period, our Navy too should leverage the lessons learned from the Royal Navy to make the effort to secure viable position when it comes to the setting of priorities in case of national defense strategy by presenting the basis on why maritime coping should be prioritized among the numerous other threats, and by developing the measures for securing the powers needed effectively amidst the limited resources.

• Analytical Science and Technology
• /
• v.23 no.1
• /
• pp.1-14
• /
• 2010

It is of importance that all countries in worldwide, including EU and China, have adopted the Restrictions on the use of certain Hazardous Substances (RoHS) for all electronics. IEC62321 document, which was published by the International Electronics Committee (IEC) can have conflicts with the standards in the market. On the contrary Publicly Accessible Specification (PAS) for sampling published by IEC TC111 can be adopted for complementary application. In this work, we tried to find a route to disassemble and disjoint cellular phone sample, based on PAS and compare the screening methods available in the market. For this work, the cellular phone produced in 2001, before the regulation was born, was chosen for better detection. Although X-ray Fluorescence (XRF) showed excellent performance for screening, fast and easy handling, it can give information on the surface, not the bulk, and have some limitations due to significant matrix interference and lack of variety of standards for quantification. It means that screening with XRF sometimes requires supplementary tool. There are several techniques available in the market of analytical instruments. Laser ablation (LA) ICP-MS, energy dispersive (ED) XRF and scanning electron microscope (SEM)-energy dispersive X-ray (EDX) were demonstrated for screening a cellular phone. For quantitative determination, graphite furnace atomic absorption spectrometry (GF-AAS) was employed. Experimental results for Pb in a battery showed large difference in analytical results in between XRF and GF-AAS, i.e., 0.92% and 5.67%, respectively. In addition, the standard deviation of XRF was extremely large in the range of 23-168%, compared with that in the range of 1.9-92.3% for LA-ICP-MS. In conclusion, GF-AAS was required for quantitative analysis although EDX was used for screening. In this work, it was proved that LA-ICP-MS can be used as a screening method for fast analysis to determine hazardous elements in electrical products.

• Journal of the Korean Institute of Landscape Architecture
• /
• v.45 no.3
• /
• pp.54-65
• /
• 2017

The purpose of this study is to investigate the perception of landscape law and institutions and to provide basic data for improvement of landscape systems. Specifically, we analyzed the importance and achievement of various landscape systems, and examined the understanding and perception of government officers in landscape plan, landscape project, landscape agreement, landscape reviews and landscape committees, landscape ordinance, and landscape administration. The main results of the study are summarized as follows. 1. Overall, the landscape administration system was highly interested, and it was also positive about the utility of the landscape law and the landscape charter. As a result of analysis of the IPA, the landscape plan and the landscape policy plan need to be intensively improved. 2. The landscape plan is mostly used for the purpose of responding to the scenery review or complaint request, but about 10.8% of respondents said that they did not refer it at all, so it is urgent to make the contents of the landscape plan real and improve the performance. Although many officers thought that less than 18 months would be quite enough for landscape plans, but it is necessary to change this duration issue. 3. In order to improve landscape projects and landscape agreements, it seems that budget securing, experts, and promotional organizations should be improved first. 4. It is urgently necessary to enhance the understanding about overall landscape law and systems of landscape review committee in order to supplement the landscape review and the landscape committee. 5. Administrative support such as personnel recruitment is required for landscape ordinance and landscape administration, and it is also found that many officers also have a great burden in making subjective judgment as the person in charge. There could be a positive bias in the results of the study, because the survey was conducted only for public officials who participated in the education. But the result will be helpful to look at the overall tendency of the landscape system. I hope that it will help improve the landscape system in the future much more realistic.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
• /
• v.14 no.1
• /
• pp.48-55
• /
• 2009

Seasonal variations of microalgal biomass and community composition in both the sediment and the seawater were investigated by HPLC pigment analysis in an estuarine muddy sandflat of Gwangyang Bay from January to November 2002. Based on the photosynthetic pigments, fucoxanthin, diadinoxanthin, and diatoxanthin were the most dominant pigments all the year round, indicating that diatoms were the predominant algal groups of both the sediment and the seawater in Gwangyang Bay. The other algal pigments except the diatom-marker pigments showed relatively low concentrations. Microphytobenthic chlorophyll ${\alpha}$ concentrations in the upper layer (0.5 cm) of sediments ranged from 3.44 (March at the middle site of the tidal flat) to 169 (July at the upper site) mg $m^{-2}$, with the annual mean concentrations of $68.4{\pm}45.5,\;21.3{\pm}14.3,\;22.9{\pm}15.6mg\;m^{-2}$ at the upper, middle, and lower tidal sites, respectively. Depth-integrated chlorophyll ${\alpha}$ concentrations in the overlying water column ranged from 1.66 (November) to 11.7 (July) mg $m^{-2}$, with an annual mean of $6.96{\pm}3.04mg\;m^{-2}$. Microphytobenthic biomasses were about 3${\sim}$10 times higher than depth-integrated phytoplankton biomass in the overlying water column. The physical characteristics of this shallow estuarine tidal flat, similarity in taxonomic composition of the phytoplankton and microphytobenthos, and similar seasonal patterns in their biomasses suggest that resuspended microphytobenthos are an important component of phytoplankton biomass in Gwangyang Bay. Therefore, considering the importance of microphytobenthos as possible food source for the estuarine benthic and pelagic consumers, a consistent monitoring work on the behavior of microphytobenthos is needed in the tidal flat ecosystems.

• Journal of Intelligence and Information Systems
• /
• v.22 no.4
• /
• pp.247-264
• /
• 2016

With the rapid acceleration of low-birth rate and population aging, the employment of the neglected groups of people including the middle aged class is a crucial issue in South Korea. In particular, in the 2010s, the number of the middle aged who want to find a new job after retirement age is significantly increasing with the arrival of the retirement time of the baby boom generation (born 1955-1963). Despite the importance of matching jobs to this emerging middle aged class, private job portals as well as the Korean government do not provide any online job service tailored for them. A gigantic amount of job information is available online; however, the current recruiting systems do not meet the demand of the middle aged class as their primary targets are young workers. We are in dire need of a specially designed recruiting system for the middle aged. Meanwhile, when users are searching the desired occupations on the Worknet website, provided by the Korean Ministry of Employment and Labor, users are experiencing discomfort to search for similar jobs because Worknet is providing filtered search results on the basis of exact matches of a preferred job code. Besides, according to our Worknet data analysis, only about 24% of job seekers had landed on a job position consistent with their initial preferred job code while the rest had landed on a position different from their initial preference. To improve the situation, particularly for the middle aged class, we investigate a soft job matching technique by performing the following: 1) we review a user behavior logs of Worknet, which is a public job recruiting system set up by the Korean government and point out key system design implications for the middle aged. Specifically, we analyze the job postings that include preferential tags for the middle aged in order to disclose what types of jobs are in favor of the middle aged; 2) we develope a new occupation classification scheme for the middle aged, Korea Occupation Classification for the Middle-aged (KOCM), based on the similarity between jobs by reorganizing and modifying a general occupation classification scheme. When viewed from the perspective of job placement, an occupation classification scheme is a way to connect the enterprises and job seekers and a basic mechanism for job placement. The key features of KOCM include establishing the Simple Labor category, which is the most requested category by enterprises; and 3) we design MOMA (Middle-aged Occupation Matching Algorithm), which is a hybrid job matching algorithm comprising constraint-based reasoning and case-based reasoning. MOMA incorporates KOCM to expand query to search similar jobs in the database. MOMA utilizes cosine similarity between user requirement and job posting to rank a set of postings in terms of preferred job code, salary, distance, and job type. The developed system using MOMA demonstrates about 20 times of improvement over the hard matching performance. In implementing the algorithm for a web-based application of recruiting system for the middle aged, we also considered the usability issue of making the system easier to use, which is especially important for this particular class of users. That is, we wanted to improve the usability of the system during the job search process for the middle aged users by asking to enter only a few simple and core pieces of information such as preferred job (job code), salary, and (allowable) distance to the working place, enabling the middle aged to find a job suitable to their needs efficiently. The Web site implemented with MOMA should be able to contribute to improving job search of the middle aged class. We also expect the overall approach to be applicable to other groups of people for the improvement of job matching results.

• Proceedings of the Korean Vacuum Society Conference
• /
• 2013.08a
• /
• pp.88-89
• /
• 2013

A variety of influenza A viruses from animal hosts are continuously prevalent throughout the world which cause human epidemics resulting millions of human infections and enormous industrial and economic damages. Thus, early diagnosis of such pathogen is of paramount importance for biomedical examination and public healthcare screening. To approach this issue, here we propose a fully integrated Rotary genetic analysis system, called Rotary Genetic Analyzer, for on-site detection of influenza A viruses with high speed. The Rotary Genetic Analyzer is made up of four parts including a disposable microchip, a servo motor for precise and high rate spinning of the chip, thermal blocks for temperature control, and a miniaturized optical fluorescence detector as shown Fig. 1. A thermal block made from duralumin is integrated with a film heater at the bottom and a resistance temperature detector (RTD) in the middle. For the efficient performance of RT-PCR, three thermal blocks are placed on the Rotary stage and the temperature of each block is corresponded to the thermal cycling, namely $95^{\circ}C$ (denature), $58^{\circ}C$ (annealing), and $72^{\circ}C$ (extension). Rotary RT-PCR was performed to amplify the target gene which was monitored by an optical fluorescent detector above the extension block. A disposable microdevice (10 cm diameter) consists of a solid-phase extraction based sample pretreatment unit, bead chamber, and 4 ${\mu}L$ of the PCR chamber as shown Fig. 2. The microchip is fabricated using a patterned polycarbonate (PC) sheet with 1 mm thickness and a PC film with 130 ${\mu}m$ thickness, which layers are thermally bonded at $138^{\circ}C$ using acetone vapour. Silicatreated microglass beads with 150~212 ${\mu}L$ diameter are introduced into the sample pretreatment chambers and held in place by weir structure for construction of solid-phase extraction system. Fig. 3 shows strobed images of sequential loading of three samples. Three samples were loaded into the reservoir simultaneously (Fig. 3A), then the influenza A H3N2 viral RNA sample was loaded at 5000 RPM for 10 sec (Fig. 3B). Washing buffer was followed at 5000 RPM for 5 min (Fig. 3C), and angular frequency was decreased to 100 RPM for siphon priming of PCR cocktail to the channel as shown in Figure 3D. Finally the PCR cocktail was loaded to the bead chamber at 2000 RPM for 10 sec, and then RPM was increased up to 5000 RPM for 1 min to obtain the as much as PCR cocktail containing the RNA template (Fig. 3E). In this system, the wastes from RNA samples and washing buffer were transported to the waste chamber, which is fully filled to the chamber with precise optimization. Then, the PCR cocktail was able to transport to the PCR chamber. Fig. 3F shows the final image of the sample pretreatment. PCR cocktail containing RNA template is successfully isolated from waste. To detect the influenza A H3N2 virus, the purified RNA with PCR cocktail in the PCR chamber was amplified by using performed the RNA capture on the proposed microdevice. The fluorescence images were described in Figure 4A at the 0, 40 cycles. The fluorescence signal (40 cycle) was drastically increased confirming the influenza A H3N2 virus. The real-time profiles were successfully obtained using the optical fluorescence detector as shown in Figure 4B. The Rotary PCR and off-chip PCR were compared with same amount of influenza A H3N2 virus. The Ct value of Rotary PCR was smaller than the off-chip PCR without contamination. The whole process of the sample pretreatment and RT-PCR could be accomplished in 30 min on the fully integrated Rotary Genetic Analyzer system. We have demonstrated a fully integrated and portable Rotary Genetic Analyzer for detection of the gene expression of influenza A virus, which has 'Sample-in-answer-out' capability including sample pretreatment, rotary amplification, and optical detection. Target gene amplification was real-time monitored using the integrated Rotary Genetic Analyzer system.

• The Korean Journal of Archival Studies
• /
• no.47
• /
• pp.95-130
• /
• 2016

The job satisfaction of records managers is of importance because it affects their work performance and retention. The purpose of this study is to investigate records managers' job satisfaction and to identify factors affecting records manager's job satisfaction to find the way to improve their job satisfaction. Specific questions of the study are as follows: 1) What is the job satisfaction of records managers? 2) Are factors affecting job satisfaction different depending on record managers' personal characteristics? 3) What are the most influential factors on job satisfaction? To do that, questionnaires were used to gather data from 60 domestic records managers working in different types of records centers. Data analyses included descriptive statistics, one-way ANOVA, independent t-test, and multiple-regression analysis. Additionally, interviews with 2 record managers were conducted to collect opinions on factors affecting job dissatisfaction and recommendations for improving their job satisfaction. Important findings of the study are as follows: First, the respondents are moderately satisfied with their jobs (3.2 out of 5 points). The level of job satisfaction is different depending on years of career, years of employment, number of personnel the respondent is working with in the records center, and etc. The number of personnel the respondent is working with was found to be the most influential factor. Second, multiple-regression analysis result shows that motivation factors(satisfaction factors) are more influential than hygiene factors (dissatisfaction factors) on the respondents' job satisfaction, which confirms Herzberg's two factor theory. More specifically, 'work ethic,' one of motivator factors, has the greatest influence, followed by 'procedural impartiality', 'communication', 'job characteristic', 'distributive justice', and 'working conditions.' Based on the results, this study suggests several ways to improve record managers' job satisfaction level. First, the awareness of records management should be increased. The respondents indicated that their job dissatisfaction is usually derived from a lack of the awareness of records management. Therefore, every chief of organizations, National Archives of Korea, and records managers themselves should try to raise the awareness of records management. Especially, records managers should make stronger efforts to attract the office's attention. Second, records managers ought to establish their identity as records management profession. Also, they should participate in various activities of the archival community to overcome the limitation of individuals.

• Journal of Intelligence and Information Systems
• /
• v.23 no.2
• /
• pp.123-138
• /
• 2017

Since the stock market is driven by the expectation of traders, studies have been conducted to predict stock price movements through analysis of various sources of text data. In order to predict stock price movements, research has been conducted not only on the relationship between text data and fluctuations in stock prices, but also on the trading stocks based on news articles and social media responses. Studies that predict the movements of stock prices have also applied classification algorithms with constructing term-document matrix in the same way as other text mining approaches. Because the document contains a lot of words, it is better to select words that contribute more for building a term-document matrix. Based on the frequency of words, words that show too little frequency or importance are removed. It also selects words according to their contribution by measuring the degree to which a word contributes to correctly classifying a document. The basic idea of constructing a term-document matrix was to collect all the documents to be analyzed and to select and use the words that have an influence on the classification. In this study, we analyze the documents for each individual item and select the words that are irrelevant for all categories as neutral words. We extract the words around the selected neutral word and use it to generate the term-document matrix. The neutral word itself starts with the idea that the stock movement is less related to the existence of the neutral words, and that the surrounding words of the neutral word are more likely to affect the stock price movements. And apply it to the algorithm that classifies the stock price fluctuations with the generated term-document matrix. In this study, we firstly removed stop words and selected neutral words for each stock. And we used a method to exclude words that are included in news articles for other stocks among the selected words. Through the online news portal, we collected four months of news articles on the top 10 market cap stocks. We split the news articles into 3 month news data as training data and apply the remaining one month news articles to the model to predict the stock price movements of the next day. We used SVM, Boosting and Random Forest for building models and predicting the movements of stock prices. The stock market opened for four months (2016/02/01 ~ 2016/05/31) for a total of 80 days, using the initial 60 days as a training set and the remaining 20 days as a test set. The proposed word - based algorithm in this study showed better classification performance than the word selection method based on sparsity. This study predicted stock price volatility by collecting and analyzing news articles of the top 10 stocks in market cap. We used the term - document matrix based classification model to estimate the stock price fluctuations and compared the performance of the existing sparse - based word extraction method and the suggested method of removing words from the term - document matrix. The suggested method differs from the word extraction method in that it uses not only the news articles for the corresponding stock but also other news items to determine the words to extract. In other words, it removed not only the words that appeared in all the increase and decrease but also the words that appeared common in the news for other stocks. When the prediction accuracy was compared, the suggested method showed higher accuracy. The limitation of this study is that the stock price prediction was set up to classify the rise and fall, and the experiment was conducted only for the top ten stocks. The 10 stocks used in the experiment do not represent the entire stock market. In addition, it is difficult to show the investment performance because stock price fluctuation and profit rate may be different. Therefore, it is necessary to study the research using more stocks and the yield prediction through trading simulation.

• Journal of Intelligence and Information Systems
• /
• v.24 no.2
• /
• pp.111-124
• /
• 2018

This study aims to develop a classification model for predicting the occurrence of hyperlipidemia, one of the chronic diseases. Prior studies applying data mining techniques for predicting disease can be classified into a model design study for predicting cardiovascular disease and a study comparing disease prediction research results. In the case of foreign literatures, studies predicting cardiovascular disease were predominant in predicting disease using data mining techniques. Although domestic studies were not much different from those of foreign countries, studies focusing on hypertension and diabetes were mainly conducted. Since hypertension and diabetes as well as chronic diseases, hyperlipidemia, are also of high importance, this study selected hyperlipidemia as the disease to be analyzed. We also developed a model for predicting hyperlipidemia using SVM and meta learning algorithms, which are already known to have excellent predictive power. In order to achieve the purpose of this study, we used data set from Korea Health Panel 2012. The Korean Health Panel produces basic data on the level of health expenditure, health level and health behavior, and has conducted an annual survey since 2008. In this study, 1,088 patients with hyperlipidemia were randomly selected from the hospitalized, outpatient, emergency, and chronic disease data of the Korean Health Panel in 2012, and 1,088 nonpatients were also randomly extracted. A total of 2,176 people were selected for the study. Three methods were used to select input variables for predicting hyperlipidemia. First, stepwise method was performed using logistic regression. Among the 17 variables, the categorical variables(except for length of smoking) are expressed as dummy variables, which are assumed to be separate variables on the basis of the reference group, and these variables were analyzed. Six variables (age, BMI, education level, marital status, smoking status, gender) excluding income level and smoking period were selected based on significance level 0.1. Second, C4.5 as a decision tree algorithm is used. The significant input variables were age, smoking status, and education level. Finally, C4.5 as a decision tree algorithm is used. In SVM, the input variables selected by genetic algorithms consisted of 6 variables such as age, marital status, education level, economic activity, smoking period, and physical activity status, and the input variables selected by genetic algorithms in artificial neural network consist of 3 variables such as age, marital status, and education level. Based on the selected parameters, we compared SVM, meta learning algorithm and other prediction models for hyperlipidemia patients, and compared the classification performances using TP rate and precision. The main results of the analysis are as follows. First, the accuracy of the SVM was 88.4% and the accuracy of the artificial neural network was 86.7%. Second, the accuracy of classification models using the selected input variables through stepwise method was slightly higher than that of classification models using the whole variables. Third, the precision of artificial neural network was higher than that of SVM when only three variables as input variables were selected by decision trees. As a result of classification models based on the input variables selected through the genetic algorithm, classification accuracy of SVM was 88.5% and that of artificial neural network was 87.9%. Finally, this study indicated that stacking as the meta learning algorithm proposed in this study, has the best performance when it uses the predicted outputs of SVM and MLP as input variables of SVM, which is a meta classifier. The purpose of this study was to predict hyperlipidemia, one of the representative chronic diseases. To do this, we used SVM and meta-learning algorithms, which is known to have high accuracy. As a result, the accuracy of classification of hyperlipidemia in the stacking as a meta learner was higher than other meta-learning algorithms. However, the predictive performance of the meta-learning algorithm proposed in this study is the same as that of SVM with the best performance (88.6%) among the single models. The limitations of this study are as follows. First, various variable selection methods were tried, but most variables used in the study were categorical dummy variables. In the case with a large number of categorical variables, the results may be different if continuous variables are used because the model can be better suited to categorical variables such as decision trees than general models such as neural networks. Despite these limitations, this study has significance in predicting hyperlipidemia with hybrid models such as met learning algorithms which have not been studied previously. It can be said that the result of improving the model accuracy by applying various variable selection techniques is meaningful. In addition, it is expected that our proposed model will be effective for the prevention and management of hyperlipidemia.