• Journal of The Korean Association For Science Education
• /
• v.44 no.1
• /
• pp.11-27
• /
• 2024

This study aimed to investigate the role of scientific empathy in influencing students' productive disciplinary engagement in scientific activities and analyze the key factors of scientific empathy that manifest during this process. Twelve fifth-grade students were divided into three subgroups based on their general empathic abilities. Lessons promoting productive disciplinary engagement, integrating design thinking processes, were conducted. Subgroup discourse analysis during idea generation and prototype stages, two of five problem-solving steps, enabled observation of scientific empathy and practice aspects. The results showed that applying scientific empathy effectively through design thinking facilitated students' productive disciplinary engagement in science. In the idea generation stage, we observed an initial increase followed by a decrease in scientific empathy and practice utterances, while during the prototyping stage, utterance frequency increased, particularly in the later part. However, subgroups with lower empathic abilities displayed decreased discourse frequency in scientific empathy and practice during the prototype stage due to a lack of collaborative communication. Across all empathic ability levels, the students articulated all five key factors of scientific empathy through their utterances in situations involving productive science engagement. In the high empathic ability subgroup, empathic understanding and concern were emphasized, whereas in the low empathic ability subgroup, sensitivity, scientific imagination, and situational interest, factors of empathizing with the research object, were prominent. These results indicate that experiences of scientific empathy with research objects, beyond general empathetic abilities, serve as a distinct and crucial factor in stimulating diverse participation and sustaining students' productive engagement in scientific activities during science classes. By suggesting the potential multidimensional impact of scientific empathy on productive disciplinary engagement, this study contributes to discussions on the theoretical structure and stability of scientific empathy in science education.

• Journal of Energy Engineering
• /
• v.29 no.2
• /
• pp.68-78
• /
• 2020

According to the new climate change agreement, technology development to reduce greenhouse gases is actively conducted worldwide, and research on energy efficiency improvement in the field of power generation and transmission and distribution is underway [1,2]. Economic analysis of the operation method of storing and supplying surplus electricity using energy storage devices, and using energy storage devices as a frequency adjustment reserve power in regional cogeneration plants has been reported as the most profitable operation method [3-7]. Therefore, this study conducted an economic analysis for the installation of energy storage devices in the combined heat and power plant in the Czech Republic. The most important factor in evaluating the economics of battery energy storage devices is the lifespan, and the warranty life is generally 10 to 15 years, based on charging and discharging once a day. For the simulation, the ratio of battery and PCS was designed as 1: 1 and 1: 2. In general, the primary frequency control is designed as 1: 4, but considering the characteristics of the cogeneration plant, it is set at a ratio of up to 1: 2, and the capacity is simulated at 1MW to 10MW and 2MWh to 20MWh according to each ratio. Therefore, life was evaluated based on the number of cycles per year. In the case of installing a battery energy storage system in a combined heat and power plant in the Czech Republic, the payback period of 3MW / 3MWh is more favorable than 5MW / 5MWh, considering the local infrastructure and power market. It is estimated to be about 3 years or 5 years from the simple payback period considering the estimated purchase price without subsidies. If you lower the purchase price by 50%, the purchase cost is an important part of the cost for the entire lifetime, so the payback period is about half as short. It can be, but it is impossible to secure profitability through the economy at the scale of 3MWh and 5MWh. If the price of the electricity market falls by 50%, the payback period will be three years longer in P1 mode and two years longer in P2 and P3 modes.

• The Korean Journal of Ecology
• /
• v.17 no.3
• /
• pp.299-310
• /
• 1994

Intraspecific clonal interactions have important influences on a population structure of the cellular slime mold (CSM). This study was to investigate whether or not evolutionary change in a population could be induced by clonal competition, and to elucidate how various clones in a population evolve in a homogeneous environment of laboratory culture. The characteristic clones of Polysphondylium pallidum which had different resource consumption rates (RCR) and mating types I and II were selected for study. Investigation was conducted for 4 experimental time interval $(T_0-T_4)$; one experimental time interval took almost 10-14 days from inoculation to havest of fruiting bodies. Two sets of 50 clones were cultured from 50 clones at To, and RCR variations of the population were compared between $(T_0\;and\;T_4)$ for each set of clones. Each clone of the CSM had a diverse resource consumption rate, or growth rate, in a homogeneous and limited Cerophyl agar plate despite the passage of 48-56 generations from the beginning of the experiment. Diverse clones with different growth rate could coexist in one site of the homogeneous agar plate as well as heterogeneous soil microenvironment. When there was high clonal diversity of RCR, a clone in a population had high chances to encounter other clones with resultant increased clonal competition. In one set, 26 of 37 clones of mating type I were changed to mating type Il for the 4 experimental time intervals, which indicated that the rate of competitive exclusion among clones during total experiment from $(T_0\;to\;T_4)$ was 0.703. In another set, 31 of 37 clones of mating type I were changed to mating type II , having the rate of competitive exclusion 0.838. The frequency of each of mat~ng types changed by 0.93-1.29% in each successive generation. The competitive exclusion among clones occurred by 1.26-1.75% when approximately $2.6{\times}10^8$ bacterial cells were provided as food and thereafter one generation of myxamoebae of CSM elapsed at room temperature. This finding implicated that in the vegetative state of P, pallidurn there was 1.26-1.75% probabil~ty of evolutionary change per generation changing from one clone to another clone.

• Tuberculosis and Respiratory Diseases
• /
• v.41 no.5
• /
• pp.537-545
• /
• 1994

Background: In 1987, the British Thoracic Society (BTS) subjected an extensive list of patient variables to statistical analysis in a prospective study of prognosis in 453 adults with community-acquired pneumonia and, subsequently published guidelines for management of severe community acquired pneumonia. It was hoped that those at risk of dying from community acquired pneumonia could be easily identified and treated appropriately, thereby reducing mortality. To date, severe community acquired pneumonia has not been well studied in Korea. Therefore, we studied retrospectively 10 patients dying of severe community acquired pneumonia in Dongsan Hospital to see clinical manifestations of dying of severe community-acquired pneumonia. Methods: Between July 1987 and july 1993, 498 patients were admitted to Keimyung University Dongsan Hospital with community acquired pneumonia, and 77 of them received intensive care. Of the 77 patients, 10 patients died. We reviewed medical records of these patients. Results: 1) The mean age of the patients was 56.2 years(range, 25 to 75 years). There were 7 men and 3 women. Seven patients(70%) were older than 60years of age. 2) The clinical features on admission were as follows: tachypnca, hypoxemia, mental change, cyanosis, leukopenia, leukocytosis, azotemia, hypotension, hypoalbuminemia in order of frequency. Three patients had one abnormal physical finding, 3 patients had 2, 2 patients had 3, and 2 patients had none of these abnormal physical findings. All patients had at least one of the abnormal laboratory findings. 3) A potential bacterial pathogen was isolated in sputum culture from 2 patients. One was E.coli, the other Enterobacter species. Sputum stain were positive in eight cases (G(+)cocci in six, G(+) cocci and G(-)bacilli in two). 4) Features of respiratory failure were the main reasons for ICU transfer, but two patients were transferred only following a cardiac or respiratory arrest in the general ward. 5) The mean of 2.7 different antibiotics were given to the patients. The aminoglycoside and first generation cephalosporin were the most frequently prescribed antibiotics, followed by the third generation cephalosporin and vancomycin. The most frequently prescribed antibiotics combination was a 1st generation cephalosporin plus an aminoglycoside. 6) Seven patients death(70%) occured after admission within the first five days, and a mean duration of hospitaliztion was 11.2 days. Conclusion: As the results show most death occured within the first five days after admission and aged patients; consequently, an aggressive intensive treatment should be provided early to the patients with severe community acquired pneumonia, and we should pay more attention to the aged patients.

• Journal of the Korean earth science society
• /
• v.38 no.1
• /
• pp.24-34
• /
• 2017

The westerly waves generation is described in the advanced earth science textbook used at high school as follows: as westerly wind approaches and blows over large mountains, the air flow shows wave motions in downwind side, which can be explained by the conservation of potential vorticity. However, there has been no case study showing the phenomena of the mesoscale westerly waves with observational data in the area of small mountains in Korea. And thus the wind speed and time persistency of westerly winds along with the width and length of mountains have never been studied to explain the generation of the westerly waves. As a first step, we assured the westerly waves generated in the downwind side of Sobaek mountains based on surface station wind data nearby. Furthermore, the critical or minimum wind velocity of the westerly wind over Sobaek mountains to generate the downwind wave were derived and calcuated tobe about $0.6m\;s^{-1}$ for Sobaek mountains, which means that the westerly waves could be generated in most cases of westerly blowing over the mountains. Using surface station data and 4-dimensional assimilation data of RDAPS (Regional Data Assimilation and Prediction System) provided by Korea Meteorological Agency, we also analyzed cases of westerly waves occurrence and life cycle in the downwind side of Sobaek mountains for a year of 2014. The westerly waves occurred in meso-${\beta}$ or -${\gamma}$ scales. The westerly waves generated by the mountains disappeared gradually with wind speed decreasing. The occurrence frequency of the vorticity with meso-${\beta}$ scale got to be higher when the stronger westerly wind blew. When we extended the spatial range of the analysis, phenomena of westerly waves were also observed in the downwind side of Yensan mountains in Northeastern China. Our current work will be a study material to help students understand the atmospheric phenomena perturbed by mountains.

• Journal of Life Science
• /
• v.28 no.11
• /
• pp.1255-1261
• /
• 2018

Whole genome analysis have been made possible with the development of DNA sequencing technologies and discovery of many single nucleotide polymorphisms (SNPs). Large number of SNP can be analyzed with SNP chips, since SNPs of human as well as livestock genomes are available. Among the various missing nucleotide imputation programs, Minimac3 software is suggested to be highly accurate, with a simplified workflow and relatively fast. In the present study, we used Minimac3 program to perform genomic missing value substitution 1,226 animals 770K SNP chip and imputing missing SNPs with next generation sequencing data from 311 animals. The accuracy on each chromosome was about 94~96%, and individual sample accuracy was about 92~98%. After imputation of the genotypes, SNPs with R Square ($R^2$) values for three conditions were 0.4, 0.6, and 0.8 and the percentage of SNPs were 91%, 84%, and 70% respectively. The differences in the Minor Allele Frequency gave $R^2$ values corresponding to seven intervals (0, 0.025), (0.025, 0.05), (0.05, 0.1), (0.1, 0.2), (0.2, 0.3). (0.3, 0.4) and (0.4, 0.5) of 64~88%. The total analysis time was about 12 hr. In future SNP chip studies, as the size and complexity of the genomic datasets increase, we expect that genomic imputation using Minimac3 can improve the reliability of chip data for Hanwoo discrimination.

• Journal of Intelligence and Information Systems
• /
• v.25 no.2
• /
• pp.141-166
• /
• 2019

Recently, channels like social media and SNS create enormous amount of data. In all kinds of data, portions of unstructured data which represented as text data has increased geometrically. But there are some difficulties to check all text data, so it is important to access those data rapidly and grasp key points of text. Due to needs of efficient understanding, many studies about text summarization for handling and using tremendous amounts of text data have been proposed. Especially, a lot of summarization methods using machine learning and artificial intelligence algorithms have been proposed lately to generate summary objectively and effectively which called "automatic summarization". However almost text summarization methods proposed up to date construct summary focused on frequency of contents in original documents. Those summaries have a limitation for contain small-weight subjects that mentioned less in original text. If summaries include contents with only major subject, bias occurs and it causes loss of information so that it is hard to ascertain every subject documents have. To avoid those bias, it is possible to summarize in point of balance between topics document have so all subject in document can be ascertained, but still unbalance of distribution between those subjects remains. To retain balance of subjects in summary, it is necessary to consider proportion of every subject documents originally have and also allocate the portion of subjects equally so that even sentences of minor subjects can be included in summary sufficiently. In this study, we propose "subject-balanced" text summarization method that procure balance between all subjects and minimize omission of low-frequency subjects. For subject-balanced summary, we use two concept of summary evaluation metrics "completeness" and "succinctness". Completeness is the feature that summary should include contents of original documents fully and succinctness means summary has minimum duplication with contents in itself. Proposed method has 3-phases for summarization. First phase is constructing subject term dictionaries. Topic modeling is used for calculating topic-term weight which indicates degrees that each terms are related to each topic. From derived weight, it is possible to figure out highly related terms for every topic and subjects of documents can be found from various topic composed similar meaning terms. And then, few terms are selected which represent subject well. In this method, it is called "seed terms". However, those terms are too small to explain each subject enough, so sufficient similar terms with seed terms are needed for well-constructed subject dictionary. Word2Vec is used for word expansion, finds similar terms with seed terms. Word vectors are created after Word2Vec modeling, and from those vectors, similarity between all terms can be derived by using cosine-similarity. Higher cosine similarity between two terms calculated, higher relationship between two terms defined. So terms that have high similarity values with seed terms for each subjects are selected and filtering those expanded terms subject dictionary is finally constructed. Next phase is allocating subjects to every sentences which original documents have. To grasp contents of all sentences first, frequency analysis is conducted with specific terms that subject dictionaries compose. TF-IDF weight of each subjects are calculated after frequency analysis, and it is possible to figure out how much sentences are explaining about each subjects. However, TF-IDF weight has limitation that the weight can be increased infinitely, so by normalizing TF-IDF weights for every subject sentences have, all values are changed to 0 to 1 values. Then allocating subject for every sentences with maximum TF-IDF weight between all subjects, sentence group are constructed for each subjects finally. Last phase is summary generation parts. Sen2Vec is used to figure out similarity between subject-sentences, and similarity matrix can be formed. By repetitive sentences selecting, it is possible to generate summary that include contents of original documents fully and minimize duplication in summary itself. For evaluation of proposed method, 50,000 reviews of TripAdvisor are used for constructing subject dictionaries and 23,087 reviews are used for generating summary. Also comparison between proposed method summary and frequency-based summary is performed and as a result, it is verified that summary from proposed method can retain balance of all subject more which documents originally have.

• Pediatric Infection and Vaccine
• /
• v.19 no.1
• /
• pp.12-18
• /
• 2012

Purpose : This study attempted to investigate the frequency, duration, and risk factors of antibiotic-associated diarrhea (AAD) in infants hospitalized due to febrile urinary tract infection (UTI). This is a basic research on the probiotics used in the prevention and treatment of AAD in infants. Methods : Medical records of the infants aged 3-6 months hospitalized in Gachon University Gil Hospital from January 2008 to September 2010 due to the febrile UTI were retrospectively reviewed. The episodes of loose or watery stool were investigated for frequency, onset, and duration. Those who had AAD and those who did not (non-AAD) were compared. The antibiotic regimens and the episodes of diarrhea were investigated in AAD group. Result : Total 147 infants were included. Fifty-four (36.7%) showed AAD. Intravenous third-generation cephalosporin ($3^{rd}$ CS) single therapy was used for 102 patients (69.4%), the $3^{rd}$ CS and non-$3^{rd}$ CS combination therapy for 24 (16.3%), and non-$3^{rd}$ CS combination therapy for 21 (14.3%). There was no significant difference in the dose of cefotaxime between AAD and non-AAD group (P=0.601). According to the antibiotic therapies above, in AAD group, there was no significant difference in the onset and duration of diarrhea respectively (P=0.717, P=0.830). Although the frequency of diarrhea was higher for the $3^{rd}$ CS and non-$3^{rd}$ CS combination therapy subgroup with $9.25{\pm}5.30$ times/day than the other two subgroups ($7.58{\pm}2.97$ times/day in $3^{rd}$ CS single therapy subgroup, $6.75{\pm}4.40$ times/day in non-$3^{rd}$ CS combination therapy subgroup), there was no statistical significance (P=0.078). Conclusion : AAD seems common to the infants aged 3-6 months with febrile UTI, regardless of regimen and amount of antibiotics in usual dosage. Further research on the effects of probiotics used in the prevention and treatment of AAD in infants is warranted.

• Journal of the Korean Electrochemical Society
• /
• v.4 no.2
• /
• pp.58-64
• /
• 2001

YSZ ($8mol\%$ yttria-stabilized zirconia)-modified LSM $(La_{0.85}Sr_{0.15}MnO_3)$ composite cathodes were fabricated by formation of YSZ film on triple phase boundary (TPB) of LSM/YSZ/gas. The YSZ coating film greatly enlarged electrochemical reaction sites from the increase of additional TPB. The composite cathode was formed on thin YSZ electrolyte (about 30 Um thickness) supported on an anode and then I-V characterization and AC impedance analyses were performed at temperature between $700^{\circ}C\;and\;800^{\circ}C$. As results of the impedance analysis on the cell at $800^{\circ}C$ with humidified hydrogen as the fuel and air as the oxidant, R1 around the frequency of 1000 Hz represents the anode Polarization. R2 around the frequency of 100Hz indicates the cathode polarization, and R3 below the frequency of 10 Hz is the resistance of gas phase diffusion through the anode. The cell with the composite cathode produced power density of $0.55\;W/cm^2\;and\;1W/cm^2$ at air and oxygen atmosphere, respectively. The I-V curve could be divided into two parts showing distinctive behavior. At low current density region (part I) the performance decreased steeply and at high current density region (part II) the performance decreased gradually. At the part I the performance decrease was especially resulted from the large cathode polarization, while at the part H the performance decrease related to the electrolyte polarization.

• Journal of Intelligence and Information Systems
• /
• v.25 no.2
• /
• pp.25-38
• /
• 2019

Selecting high-quality information that meets the interests and needs of users among the overflowing contents is becoming more important as the generation continues. In the flood of information, efforts to reflect the intention of the user in the search result better are being tried, rather than recognizing the information request as a simple string. Also, large IT companies such as Google and Microsoft focus on developing knowledge-based technologies including search engines which provide users with satisfaction and convenience. Especially, the finance is one of the fields expected to have the usefulness and potential of text data analysis because it's constantly generating new information, and the earlier the information is, the more valuable it is. Automatic knowledge extraction can be effective in areas where information flow is vast, such as financial sector, and new information continues to emerge. However, there are several practical difficulties faced by automatic knowledge extraction. First, there are difficulties in making corpus from different fields with same algorithm, and it is difficult to extract good quality triple. Second, it becomes more difficult to produce labeled text data by people if the extent and scope of knowledge increases and patterns are constantly updated. Third, performance evaluation is difficult due to the characteristics of unsupervised learning. Finally, problem definition for automatic knowledge extraction is not easy because of ambiguous conceptual characteristics of knowledge. So, in order to overcome limits described above and improve the semantic performance of stock-related information searching, this study attempts to extract the knowledge entity by using neural tensor network and evaluate the performance of them. Different from other references, the purpose of this study is to extract knowledge entity which is related to individual stock items. Various but relatively simple data processing methods are applied in the presented model to solve the problems of previous researches and to enhance the effectiveness of the model. From these processes, this study has the following three significances. First, A practical and simple automatic knowledge extraction method that can be applied. Second, the possibility of performance evaluation is presented through simple problem definition. Finally, the expressiveness of the knowledge increased by generating input data on a sentence basis without complex morphological analysis. The results of the empirical analysis and objective performance evaluation method are also presented. The empirical study to confirm the usefulness of the presented model, experts' reports about individual 30 stocks which are top 30 items based on frequency of publication from May 30, 2017 to May 21, 2018 are used. the total number of reports are 5,600, and 3,074 reports, which accounts about 55% of the total, is designated as a training set, and other 45% of reports are designated as a testing set. Before constructing the model, all reports of a training set are classified by stocks, and their entities are extracted using named entity recognition tool which is the KKMA. for each stocks, top 100 entities based on appearance frequency are selected, and become vectorized using one-hot encoding. After that, by using neural tensor network, the same number of score functions as stocks are trained. Thus, if a new entity from a testing set appears, we can try to calculate the score by putting it into every single score function, and the stock of the function with the highest score is predicted as the related item with the entity. To evaluate presented models, we confirm prediction power and determining whether the score functions are well constructed by calculating hit ratio for all reports of testing set. As a result of the empirical study, the presented model shows 69.3% hit accuracy for testing set which consists of 2,526 reports. this hit ratio is meaningfully high despite of some constraints for conducting research. Looking at the prediction performance of the model for each stocks, only 3 stocks, which are LG ELECTRONICS, KiaMtr, and Mando, show extremely low performance than average. this result maybe due to the interference effect with other similar items and generation of new knowledge. In this paper, we propose a methodology to find out key entities or their combinations which are necessary to search related information in accordance with the user's investment intention. Graph data is generated by using only the named entity recognition tool and applied to the neural tensor network without learning corpus or word vectors for the field. From the empirical test, we confirm the effectiveness of the presented model as described above. However, there also exist some limits and things to complement. Representatively, the phenomenon that the model performance is especially bad for only some stocks shows the need for further researches. Finally, through the empirical study, we confirmed that the learning method presented in this study can be used for the purpose of matching the new text information semantically with the related stocks.