• Journal of the Korean School Mathematics Society
• /
• v.18 no.3
• /
• pp.241-258
• /
• 2015

The purpose of this paper is to examine the students' mathematics problem solving process in the intuitive stages. For this, researcher developed the questionnaire which consisted of problems in relation to intuitive and algorithmic problem solving. 73 fifth grade and 66 sixth grade elementary students participated in this study. I got the conclusion as follows: Elementary students' intuitive problem solving ability is very low. The rate of algorithmic problem solving is higher than that of intuitive problem solving in number and operation areas. The rate of intuitive problem solving is higher in figure and measurement areas. Students inclined to solve the problem intuitively in that case there is no clue for algorithmic solution. So, I suggest the development of problems which can be solved in the intuitive stage and the preparation of the methods to experience the insight and intuition.

• Journal of The Korean Association For Science Education
• /
• v.18 no.3
• /
• pp.337-345
• /
• 1998

This study examined the influences of computer-assisted instruction(CAl) upon high school students' conceptual understanding, algorithmic problem solving ability, learning motivation, and attitudes toward chemistry instruction. CAl programs were designed to supply animated molecular motions for emphasizing the particulate dynamic nature of matter and immediate feedbacks according to students' response types at each stage of four stage problem-solving strategy(understanding, planning, solving, and reviewing). The CAl and control groups (2 classes) were selected from a girls high school in Seoul, and taught about gas law for four class hours. Data analysis indicated that the students at the CAl group scored significantly higher than those at the control group in the tests on conceptual understanding and algorithmic problem solving ability. In addition, the students at the CAl group performed significantly better in the tests on the learning motivation and attitudes toward chemistry instruction.

• Journal of KIISE:Software and Applications
• /
• v.29 no.12
• /
• pp.873-882
• /
• 2002

Estimation of development cost, effort and time is difficult and a key problem of software engineering in the early stage of software development. These are estimated by using the function point which is measured from a requirement specification. However, it is often a serious Question of the staffing level required for the software development. The purpose of this paper is to show us the model which can be used to estimate a size of development team. Three hundred one software projects have been analyzed and studied for the model. First, an analysis was conducted for statistical algorithmic model. After various data transformation and regression analysis, it was concluded that no good model was available. Therefore, non-algorithmic model was suggested for analysis, which has random distribution of residuals and makes good performance using RBF (Radial Basis Function) network. Since the model provides a standard to determine the required size of development team, it ran be used as management information.

• The Journal of Industrial Distribution & Business
• /
• v.10 no.11
• /
• pp.71-80
• /
• 2019

Purpose: The purpose of this study is to design the curriculum of Basic College Software Programming to develop creative and logical-thinking. This course is guided by algorithmic thinking and logical thinking that can be solved by computing for problem-solving, and it helps to develop by software through basic programming education. Through the stage of problem analysis, abstraction, algorithm, data structure, and algorithm implementation, the curriculum is designed to help learners experience algorithm problem-solving in various areas to develop diffusion thinking. For Learners aim to achieve the balanced development of divergent and convergent-thinking needed in their creative problem-solving skills. Research design, data and methodology: This study is to design a basic software education for improving algorithm-thinking for non-major. The curriculum designed in this paper is necessary to non-majors students who have completed the 'Creative Thinking and Coding Course' Design Thinking based are targeted. For this, contents were extracted through advanced research analysis at home and abroad, and experts in computer education, computer engineering, SW education, and education were surveyed in the form of quasi-openness. Results: In this study, based on ADD Thinking's algorithm thinking, we divided the unit college majors into five groups so that students of each major could accomplish the goal of "the ability to internalize their own ideas into computing," and extracted and designed different content areas, content elements and sub-components from each group. Through three expert surveys, we established a strategy for characterization by demand analysis and major/textbook category and verified the appropriateness of the design direction to ensure that the subjects and contents of the curriculum are appropriate for each family in order to improve algorithm-thinking. Conclusions: This study helps develop software by enhancing the ability of students who practice various subjects and exercises to explore creative expressions in various areas, such as 'how to think like a computer' that can implement and execute their ideas in computing. And it helps increase the ability to think logical and algorithmic computing based on creative solutions, improving problem-solving ability based on computing thinking and fundamental understanding of computer coding and development of logical thinking ability through programming.

• International Journal of Computer Science & Network Security
• /
• v.22 no.1
• /
• pp.105-112
• /
• 2022

The development and spread of IT-technologies has raised interest in teaching programming pupils. The article deals with problems related to programming and ways to overcome them. The importance of programming skills is emphasized, as this process promotes the formation of algorithmic thinking of pupils. The authors determined the level of pupils' interest to programing learning depending on the age. The analysis has showed that the natural interest of younger pupils in programming is decreasing over the years and in the most productive period of its study is minimized. It is revealed that senior school pupils are characterized by low level of interest in the study of programming; lack of motivation; the presence of psychological blocks on their own abilities in the context of programming; law level of computer science understanding. To overcome these problems, we conducted the second stage of the experiment, which was based on a change in the approach to programing learning, which involved pupils of non-specialized classes of senior school (experimental group). During the study of programming, special attention was paid to the motivational and psychological component, as well as the use of game technologies and teamwork of pupils. The results of the pedagogical experiment on studying the effectiveness of teaching programming for pupils of nonspecialized classes are presented. Improvement of the results provided the use of social and cognitive motives; application of verbal and non-verbal, external and internal means; communicative attacks; stimulation and psychological setting; game techniques, independent work and reflection, teamwork. The positive effect of the implemented methods is shown by the results verified by the methods of mathematical statistics in the experimental and control groups of pupils.

• 제어로봇시스템학회:학술대회논문집
• /
• 1990.10b
• /
• pp.1259-1264
• /
• 1990

During the past two decades, a lot of researches have been done on the synthesis of grassroot heat exchanger networks(HEN). However, few have been dedicated to retrofit of existing heat exchanger networks, which usually use more amount of utilities (i.e. steam and/or cooling water) than the minimum requirements. This excess gives motivation of trades-off between energy saving and rearranging investment. In this paper, an algorithmic-evolutionary synthesis procedure for retrofitting heat exchanger networks is proposed. It consists of two stages. First, after the amount of maximum energy recovery(MER) is computed, a grass-root network featuring minimum number of units(MNU) is synthesized. In this stage, a systematic procedure of synthesizing MNU networks is presented. It is based upon the concept of pinch, from which networks are synthesized in a logical way by the heuristics verified by the pinch technology. In the second stage, since an initial feasible network is synthesized based on the pre-analysis result of MER and must-matches, an assignment problem between new and existing units is solved to minimize total required additional areas. After the existing units are assigned, the network can be improved by switching some units. For this purpose, an improvement problem is formulated and solved to utilize the areas of existing units as much as possible. An example is used to demonstrate the effectiveness of the proposed method.

• Journal of Science and Technology Studies
• /
• v.18 no.3
• /
• pp.153-216
• /
• 2018

The contemporary practices of Big-Data based automated decision making algorithms are widely deployed not just because we expect algorithmic decision making might distribute social resources in a more efficient way but also because we hope algorithms might make fairer decisions than the ones humans make with their prejudice, bias, and arbitrary judgment. However, there are increasingly more claims that algorithmic decision making does not do justice to those who are affected by the outcome. These unfair examples bring about new important questions such as how decision making was translated into processes and which factors should be considered to constitute to fair decision making. This paper attempts to delve into a bunch of research which addressed three areas of algorithmic application: criminal justice, law enforcement, and national security. By doing so, it will address some questions about whether artificial intelligence algorithm discriminates certain groups of humans and what are the criteria of a fair decision making process. Prior to the review, factors in each stage of data mining that could, either deliberately or unintentionally, lead to discriminatory results will be discussed. This paper will conclude with implications of this theoretical and practical analysis for the contemporary Korean society.

• IE interfaces
• /
• v.13 no.3
• /
• pp.320-327
• /
• 2000

In this research report, we consider multi stage supply chain optimization modeling techniques, and propose a new integrated model. The stages that are normally associated with a supply chain include procurement, production and distribution. In general, there are two distinct set of approaches which manage whole supply chain. One approach is the plant decision and subsequently distribution and inventory decision while the second approach is to address all decisions simultaneously through the integrated model. First, we present a survey of existing models that are treated by independently. And then, we propose an integrated model that is in a moderate size and easy to implement in practice. Finally, we address possible solution methodologies and present some computational test results using CPLEX to see the computational burden from which new algorithmic insight might be come up.

• Childhood Kidney Diseases
• /
• v.21 no.2
• /
• pp.53-60
• /
• 2017

Proteinuria is common in pediatric and adolescent patients. Proteinuria is defined as urinary protein excretion at levels higher than $100-150mg/m^2/day$ in children. It can be indicative of normal or benign conditions as well as numerous types of severe underlying renal or systemic disease. The school urine screening program has been conducted in Korea since 1998. Since then, numerous patients with normal or benign proteinuria as well as early stage renal diseases have been referred to the hospital. Benign proteinuria includes orthostatic proteinuria and transient proteinuria. Most causes of proteinuria can be categorized into 3 types: 1) overflow, 2) tubular, and 3) glomerular. Although treatment should be directed at the underlying cause of the proteinuria, prompt evaluation, diagnosis, and long-term monitoring of these pediatric patients can prevent potential progression of the underlying disease process. This article provides an overview of proteinuria: its causes, methods of assessment, and algorithmic suggestions to differentiate benign from pathologic renal disease.

• Journal of the Korea Society of Computer and Information
• /
• v.22 no.3
• /
• pp.81-88
• /
• 2017

In this paper, we classified the weaknesses of C/C++ programs listed in CWE based on the diagnostic information produced at each stage of program compilation. Our classification identifies which stages should be responsible for analyzing the weaknesses. We also present algorithmic frameworks for detecting typical weaknesses belonging to the classes to demonstrate validness of our scheme. For the weaknesses that cannot be analyzed by using the diagnostic information, we separated them as a group that are often detectable by the analyses that simulate program execution, for instance, symbolic execution and abstract interpretation. We expect that classification of weaknesses, and diagnostic information accordingly, would contribute to systematic development of static analyzers that minimizes false positives and negatives.