• Education of Primary School Mathematics
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• v.10 no.1 s.19
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• pp.41-56
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• 2007

Related with the mathematics gifted children the situation of different case studies is the research which is limited in mathematics problem solving process of the most mathematics gifted children. The research which it sees hereupon observes from the scope which is wider the quality of the mathematics gifted children, before the hazard mathematics gifted children whom it sees enter into the mathematics gifted children education center unit life and life after studying living and dismissal of a class from the general school, namely for their general life it leads compared to attitude it observes the reporter it does a quality. For a what kind of interest in the mathematics gifted children, the research leads the family or general class, from the gifted children education center it has it considers encouragement, map and to give a help to good mathematics gifted children education activation, it does. It will reach and to respect with afterwards it set a same three research problem. First, before entering into the mathematics gifted children education center, are the mathematics gifted children what kind of quality? Second, Are the mathematics gifted children what kind of quality for general school hour? Third, Are the mathematics gifted children what kind of quality after dismissal of a class after hour? Being selected in the hazard gifted children education center which solves an up research problem, simple characteristic and approach ease characteristic, by the condition of the permission possibility back it selected 2 person gifted children school boxes which are coming and going. And, before entering into these mathematics gifted children education center, studying life from the general school, life after dismissal of a class it will extend at 1 years, various recording it will ask and it collected direct observation and interview it led against their quality it analyzed. It shared the result which it analyzes with emotional quality, studying conduct qualities, general qualities of the mathematics gifted children and qualities of mathematics gifted children parents. Studies level of the mathematics gifted children parents high facility when them are young from, the interest and helping out which it has were considerable, to advance with the direction where in order for always with great disaster them are proper the map it did. In general quality of the mathematics gifted children from young age the ability which finds a language and a possibility concept superiorly the ability which expresses the thought of oneself logically was superior, the competitive spirit was high, it liked it came reading, a leader role, to reveal a deepening school with the fact that it comes and goes. Also it will burn with their studying conduct quality and it will roll and it did deeply and it arranged knot eagerly, accomplishing which is superior from the field which is various it showed, the originality was superior, the subject attachment power was high quite, oneself it studies it has a devotion the possibility of knowing it was. And, the social characteristic of the friends and is good with their emotional quality and it does there is own reflection and an encouragement at any time and also a confidence, but just as good as the stress also it receives the possibility of knowing it was to him.

• Journal of The Korean Association For Science Education
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• v.34 no.2
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• pp.63-78
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• 2014

Integrative STEM education is an engineering design-based learning approach that purposefully integrates the content and process of STEM disciplines and can extend its concept to integration with other school subjects. This study was part of fundamental research to develop an integrative STEM education program based on the science inquiry process. The specific objectives of this study were to review relevant literature related to STEM education, analyze the key elements and value of STEM education, develop an integrative STEM education model based on the science inquiry process, and suggest an exemplary program. This study conducted a systematic literature review to confirm key elements for integrative STEM education and finally constructed the integrative STEM education model through analyzing key inquiry processes extracted from prior studies. This model turned out to be valid because the average CVR value obtained from expert group was 0.78. The integrative STEM education model based on the science inquiry process consisted of two perspectives of the content and inquiry process. The content can contain science, technology, engineering, and liberal arts/artistic topics that students can learn in a real world context/problem. Also, the inquiry process is a problem-solving process that contains design and construction and is based on the science inquiry. It could integrate the technological/engineering problem solving process and/or mathematical problem solving process. Students can improve their interest in STEM subjects by analyzing real world problems, designing possible solutions, and implementing the best design as well as acquire knowledge, inquiry methods, and skills systematically. In addition, the developed programs could be utilized in schools to enhance students' understanding of STEM disciplines and interest in mathematics and science. The programs could be used as a basis for fostering convergence literacy and cultivating integrated and design-based problem-solving ability.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.1-17
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• 2017

The deep learning framework is software designed to help develop deep learning models. Some of its important functions include "automatic differentiation" and "utilization of GPU". The list of popular deep learning framework includes Caffe (BVLC) and Theano (University of Montreal). And recently, Microsoft's deep learning framework, Microsoft Cognitive Toolkit, was released as open-source license, following Google's Tensorflow a year earlier. The early deep learning frameworks have been developed mainly for research at universities. Beginning with the inception of Tensorflow, however, it seems that companies such as Microsoft and Facebook have started to join the competition of framework development. Given the trend, Google and other companies are expected to continue investing in the deep learning framework to bring forward the initiative in the artificial intelligence business. From this point of view, we think it is a good time to compare some of deep learning frameworks. So we compare three deep learning frameworks which can be used as a Python library. Those are Google's Tensorflow, Microsoft's CNTK, and Theano which is sort of a predecessor of the preceding two. The most common and important function of deep learning frameworks is the ability to perform automatic differentiation. Basically all the mathematical expressions of deep learning models can be represented as computational graphs, which consist of nodes and edges. Partial derivatives on each edge of a computational graph can then be obtained. With the partial derivatives, we can let software compute differentiation of any node with respect to any variable by utilizing chain rule of Calculus. First of all, the convenience of coding is in the order of CNTK, Tensorflow, and Theano. The criterion is simply based on the lengths of the codes and the learning curve and the ease of coding are not the main concern. According to the criteria, Theano was the most difficult to implement with, and CNTK and Tensorflow were somewhat easier. With Tensorflow, we need to define weight variables and biases explicitly. The reason that CNTK and Tensorflow are easier to implement with is that those frameworks provide us with more abstraction than Theano. We, however, need to mention that low-level coding is not always bad. It gives us flexibility of coding. With the low-level coding such as in Theano, we can implement and test any new deep learning models or any new search methods that we can think of. The assessment of the execution speed of each framework is that there is not meaningful difference. According to the experiment, execution speeds of Theano and Tensorflow are very similar, although the experiment was limited to a CNN model. In the case of CNTK, the experimental environment was not maintained as the same. The code written in CNTK has to be run in PC environment without GPU where codes execute as much as 50 times slower than with GPU. But we concluded that the difference of execution speed was within the range of variation caused by the different hardware setup. In this study, we compared three types of deep learning framework: Theano, Tensorflow, and CNTK. According to Wikipedia, there are 12 available deep learning frameworks. And 15 different attributes differentiate each framework. Some of the important attributes would include interface language (Python, C ++, Java, etc.) and the availability of libraries on various deep learning models such as CNN, RNN, DBN, and etc. And if a user implements a large scale deep learning model, it will also be important to support multiple GPU or multiple servers. Also, if you are learning the deep learning model, it would also be important if there are enough examples and references.

• Microbiology and Biotechnology Letters
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• v.26 no.6
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• pp.537-544
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• 1998

The cultivation conditions of transformant Alcaligenes eutrophus AER5 harboring cloned phbC gene for mass production of poly (3-hydroxybutyrate-3-hydroxyvalerate)[P(3HB-3HV)] containing high molar fraction of 3-hydroxyvalerate (3-HV) were investigated. In two-stage batch cultivation, transformant accumulated P(3HB-3HV) containing 52.2 mol% of 3HV compared to 30 mol% of parent strain A. eutrophus H16. The increased 3-HV molar fraction was due to the amplified activity of PHB synthase participating in condensation of 3-HB and 3-HV. To increase efficiency of P(3HB-3HV) accumulation, fructose was added along with precursor compound valerate, and total cell mass and P(3HB-3HV) concentrations remarkably increased, but not 3-HV molar fraction. The effect of magnesium ion showed that P(3HB-3HV) concentration and 3-HV molar fraction were significantly increased upto 6.1 g/L and 71.3 mol% at 0.01 g/L of MgSO$_4$, respectively. The efficiency of several pH adjuster, NaOH, NaOH and (NH$_4$)$_2$SO$_4$, and NH$_4$OH, on total cell mass, p(3HB-3HV) concentration, and 3-HV molar fraction was also compared. To overcome the disadvantage of two-stage cultivation, one-stage intermittent fed-batch cultivation was attempted, such a way 10.0 g/L of fructose was supplied for cell growth at initial 36 hr and then 10.0 g/L of valerate and 5.0 g/L of fructose were applied to induce the accumulation of P(3HB-3HV), consequently, 10.4 g/L of P(3HB-3HV) with 38 mol% of 3-HV fraction could be obtained after 72 hr. These results can be used for elucidating cultivation strategy for mass production of P(3HB-3HV) containing high 3-HV molar fraction using transformant A. eutrophus AER5 harboring cloned phbC gene.

• Investigative Magnetic Resonance Imaging
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• v.10 no.2
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• pp.98-107
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• 2006

Magnetization Transfer (MT) imaging generates contrast dependent on the phenomenon of magnetization exchange between free water proton and restricted proton in macromolecules. In biological materials in knee, MT or cross-relaxation is commonly modeled using two spin pools identified by their different T2 relaxation times. Two models for cross-relaxation emphasize the role of proton chemical exchange between protons of water and exchangeable protons on macromolecules, as well as through dipole-dipole interaction between the water and macromolecule protons. The most essential tool in medical image manipulation is the ability to adjust the contrast and intensity. Thus, it is desirable to adjust the contrast and intensity of an image interactively in the real time. The proton density (PD) and T2-weighted SE MR images allow the depiction of knee structures and can demonstrate defects and gross morphologic changes. The PD- and T2-weighted images also show the cartilage internal pathology due to the more intermediate signal of the knee joint in these sequences. Suppression of fat extends the dynamic range of tissue contrast, removes chemical shift artifacts, and decreases motion-related ghost artifacts. Like fat saturation, phase sensitive methods are also based on the difference in precession frequencies of water and fat. In this study, phase sensitive methods look at the phase difference that is accumulated in time as a result of Larmor frequency differences rather than using this difference directly. Although how MT work was given with clinical evidence that leads to quantitative model for MT in tissues, the mathematical formalism used to describe the MT effect applies to explaining to evaluate knee disorder, such as anterior cruciate ligament (ACL) tear and meniscal tear. Calculation of the effect of the effect of the MT saturation is given in the magnetization transfer ratio (MTR) which is a quantitative measure of the relative decrease in signal intensity due to the MT pulse.

• Asia pacific journal of information systems
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• v.19 no.2
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• pp.157-178
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• 2009

Corporate credit rating is a very important factor in the market for corporate debt. Information concerning corporate operations is often disseminated to market participants through the changes in credit ratings that are published by professional rating agencies, such as Standard and Poor's (S&P) and Moody's Investor Service. Since these agencies generally require a large fee for the service, and the periodically provided ratings sometimes do not reflect the default risk of the company at the time, it may be advantageous for bond-market participants to be able to classify credit ratings before the agencies actually publish them. As a result, it is very important for companies (especially, financial companies) to develop a proper model of credit rating. From a technical perspective, the credit rating constitutes a typical, multiclass, classification problem because rating agencies generally have ten or more categories of ratings. For example, S&P's ratings range from AAA for the highest-quality bonds to D for the lowest-quality bonds. The professional rating agencies emphasize the importance of analysts' subjective judgments in the determination of credit ratings. However, in practice, a mathematical model that uses the financial variables of companies plays an important role in determining credit ratings, since it is convenient to apply and cost efficient. These financial variables include the ratios that represent a company's leverage status, liquidity status, and profitability status. Several statistical and artificial intelligence (AI) techniques have been applied as tools for predicting credit ratings. Among them, artificial neural networks are most prevalent in the area of finance because of their broad applicability to many business problems and their preeminent ability to adapt. However, artificial neural networks also have many defects, including the difficulty in determining the values of the control parameters and the number of processing elements in the layer as well as the risk of over-fitting. Of late, because of their robustness and high accuracy, support vector machines (SVMs) have become popular as a solution for problems with generating accurate prediction. An SVM's solution may be globally optimal because SVMs seek to minimize structural risk. On the other hand, artificial neural network models may tend to find locally optimal solutions because they seek to minimize empirical risk. In addition, no parameters need to be tuned in SVMs, barring the upper bound for non-separable cases in linear SVMs. Since SVMs were originally devised for binary classification, however they are not intrinsically geared for multiclass classifications as in credit ratings. Thus, researchers have tried to extend the original SVM to multiclass classification. Hitherto, a variety of techniques to extend standard SVMs to multiclass SVMs (MSVMs) has been proposed in the literature Only a few types of MSVM are, however, tested using prior studies that apply MSVMs to credit ratings studies. In this study, we examined six different techniques of MSVMs: (1) One-Against-One, (2) One-Against-AIL (3) DAGSVM, (4) ECOC, (5) Method of Weston and Watkins, and (6) Method of Crammer and Singer. In addition, we examined the prediction accuracy of some modified version of conventional MSVM techniques. To find the most appropriate technique of MSVMs for corporate bond rating, we applied all the techniques of MSVMs to a real-world case of credit rating in Korea. The best application is in corporate bond rating, which is the most frequently studied area of credit rating for specific debt issues or other financial obligations. For our study the research data were collected from National Information and Credit Evaluation, Inc., a major bond-rating company in Korea. The data set is comprised of the bond-ratings for the year 2002 and various financial variables for 1,295 companies from the manufacturing industry in Korea. We compared the results of these techniques with one another, and with those of traditional methods for credit ratings, such as multiple discriminant analysis (MDA), multinomial logistic regression (MLOGIT), and artificial neural networks (ANNs). As a result, we found that DAGSVM with an ordered list was the best approach for the prediction of bond rating. In addition, we found that the modified version of ECOC approach can yield higher prediction accuracy for the cases showing clear patterns.

• Journal of the Korean Society of Food Science and Nutrition
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• v.34 no.8
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• pp.1274-1283
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• 2005

The sensory acceptability, texture profile analysis and nutritional evaluation were peformed in Korean traditional mungbean pancake (MPC) and modified MPC containing squid meat and soybean to standardize the recipes for healthy fast food market potentiality. Optimal ingredient formulations were revealed as mung-bean 55$\%$, pork 13$\%$ and vegetables 32$ \%$ for traditional MPC, and pork 3$\%$, squid 42$\%$ and soybean 55$\%$ for modified MPC using response surface methodology. Flavor and hardness correlated highly with overall accept-ability rather than appearance and color of traditional MPC. Higher squid levels raised adhesiveness, springi-ness and resiliences of modified MPC, but soybean decreased these textural attributes. Protein, lipid and total calorie of modified MPC were lower than those of traditional MPC. Computed protein efficiency ratio (C-PER) and degree of gelatinization of modified MPC were superior than traditional MPC.

• International Journal of Computer Science & Network Security
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• v.21 no.12spc
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• pp.664-674
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• 2021

The relevance of this scientific research is determined by the negative impact of the COVID-19 pandemic on the current trends and dynamics of world tourism development. This article aims to identify patterns of development of the modern tourist market, analysis of problems and prospects of development in the context of the COVID-19 pandemic. Materials and methods. General scientific methods and methods of research are used in the work: analysis, synthesis, comparison, analysis of statistical data. The analysis of the viewpoints of foreign and domestic authors on the research of the international tourist market allowed us to substantiate the actual directions of tourism development due to the influence of negative factors connected with the spread of a new coronavirus infection COVID-19. Economic-statistical, abstract-logical, and economic-mathematical methods of research were used during the process of study and data processing. Results. The analysis of the current state of the tourist market by world regions was carried out. It was found that tourism is one of the most affected sectors from COVID-19, as, by the end of 2020, the total number of tourist arrivals in the world decreased by 74% compared to the same period in 2019. The consequence of this decline was a loss of total global tourism revenues by the end of 2020, which equaled $1.3 trillion. 27% of all destinations are completely closed to international tourism. At the end of 2020, the economy of international tourism has shrunk by about 80%. In 2020 the world traveled 98 million fewer people (-83%) relative to the same period last year. Tourism was hit hardest by the pandemic in the Asia-Pacific region, where travel restrictions are as strict as possible. International arrivals in this region fell by 84% (300 million). The Middle East and Africa recorded declines of 75 and 70 percent. Despite a small and short-lived recovery in the summer of 2020, Europe lost 71% of the tourist flow, with the European continent recording the largest drop in absolute terms compared with 2019, 500 million. In North and South America, foreign arrivals declined. It is revealed that a significant decrease in tourist flows leads to a massive loss of jobs, a sharp decline in foreign exchange earnings and taxes, which limits the ability of states to support the tourism industry. Three possible scenarios of exit of the tourist industry from the crisis, reflecting the most probable changes of monthly tourist flows, are considered. The characteristics of respondents from Ukraine, Germany, and the USA and their attitude to travel depending on gender, age, education level, professional status, and monthly income are presented. About 57% of respondents from Ukraine, Poland, and the United States were planning a tourist trip in 2021. Note that people with higher or secondary education were more willing to plan such a trip. The results of the empirical study confirm that interest in domestic tourism has increased significantly in 2021. The regression model of dependence of the number of domestic tourist trips on the example of Ukraine with time tendency (t) and seasonal variations (Turˆt = 7288,498 - 20,58t - 410,88∑5) it forecast for 2020, which allows stabilizing the process of tourist trips after the pandemic to use this model to forecast for any country. Discussion. We should emphasize the seriousness of the COVID-19 pandemic and the fact that many experts and scientists believe in the long-term recovery of the tourism industry. In our opinion, the governments of the countries need to refocus on domestic tourism and deal with infrastructure development, search for new niches, formats, formation of new package deals in new - domestic - segment (new products' development (tourist routes, exhibitions, sightseeing programs, special rehabilitation programs after COVID) -19 in sanatoriums, etc.); creation of individual offers for different target audiences). Conclusions. Thus, the identified trends are associated with a decrease in the number of tourist flows, the negative impact of the pandemic on employment and income from tourism activities. International tourism needs two to four years before it returns to the level of 2019.

• Journal of Korean Elementary Science Education
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• v.41 no.4
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• pp.658-672
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• 2022

The unique teaching and learning difficulties of speed-related units in elementary school science are mainly due to the student's lack of mathematical thinking ability and procedural knowledge on speed measurement, and curriculums and textbooks must be constructed with these in mind. To identify the implications of composing a new science curriculum and relevant textbooks, this study reviewed the structure and contents of the speed-related units of three curriculums from the 2007 revised curriculum to the 2015 revised curriculum and the resulting textbooks and examined their relevance in light of the literature. Results showed that the current content carries the risk of making students calculate only the speed of an object through a mechanical algorithm by memorization rather than grasp the multifaceted relation between traveled distance, duration time, and speed. Findings also highlighted the need to reorganize the curriculum and textbooks to offer students the opportunity to learn the meaning of speed step-by-step by visualizing materials such as double number lines and dealing with simple numbers that are easy to calculate and understand intuitively. In addition, this paper discussed the urgency of improving inquiry performance such as process skills by observing and measuring an actual object's movement, displaying it as a graph, and interpreting it rather than conducting data interpretation through investigation. Lastly, although the current curriculum and textbooks emphasize the connection with daily life in their application aspects, they also deal with dynamics-related content somewhat differently from kinematics, which is the main learning content of the unit. Hence, it is necessary to reorganize the contents focusing on cases related to speed so that students can grasp the concept of speed and use it in their everyday lives. With regard to the new curriculum and textbooks, this study proposes that students be provided the opportunity to systematically and deeply study core topics rather than exclude content that is difficult to learn and challenging to teach so that students realize the value of science and enjoy learning it.