• Journal of Information Technology Services
• /
• v.20 no.5
• /
• pp.147-158
• /
• 2021

The digital transformation and COVID-19 are also causing major changes in teaching-learning methods. The biggest change is the spread of remote training and the emergence of various innovative learning platforms. Distance education has been criticized for not meeting technology trends and field demands..However, the problem of distance education is being solved through a system that supports various interactions and collaborations and supports customized learning paths. The researcher conducted a case study on domestic and foreign learning platforms that provide non-face-to-face ICT education. Based on the case study results, the researcher presented the functional characteristics of a learning platform that effectively supports non-face-to-face learning. In common, these sites faithfully supported the basic functions of the information system. In addition to learning progress check and learning guidance, some innovative learning platforms were providing differentiated functions in practice support, performance management, mentoring, learning data analysis, curation provision, and CDP support. Most learning platforms supported one-way, superficial interaction. If the platform effectively supports a variety of learning experiences and provides an integrated learning experience thanks to the development of IT technology, user satisfaction with the learning platform, intention to continue learning, and achievement will increase.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.19 no.2
• /
• pp.135-141
• /
• 2019

Recently, there has been active researches about building an artificial intelligence agent that can learn how to play a game by using re-enforcement learning. The performance of the learning can be diverse according to what kinds of deep learning activation functions they used when they train the agent. This paper compares the activation functions when we train our agent for learning how to play a 2D shooting game by using re-enforcement learning. We defined performance metrics to analyze the results and plotted them along a training time. As a result, we found ELU (Exponential Linear Unit) with a parameter 1.0 achieved best rewards than other activation functions. There was 23.6% gap between the best activation function and the worst activation function.

• Journal of Korean Institute of Industrial Engineers
• /
• v.32 no.2
• /
• pp.74-81
• /
• 2006

In this paper, we deal with the separation of data by concurrently determined, piecewise nonlinear discriminant functions. Toward the end, we develop a new $l_1$-distance norm error metric and cast the problem as a mixed 0-1 integer and linear programming (MILP) model. Given a finite number of discriminant functions as an input, the proposed model considers the synergy as well as the individual role of the functions involved and implements a simplest nonlinear decision surface that best separates the data on hand. Hence, exploiting powerful MILP solvers, the model efficiently analyzes any given data set for its piecewise nonlinear separability. The classification of four sets of artificial data demonstrates the aforementioned strength of the proposed model. Classification results on five machine learning benchmark databases prove that the data separation via the proposed MILP model is an effective supervised learning methodology that compares quite favorably to well-established learning methodologies.

• 제어로봇시스템학회:학술대회논문집
• /
• 2001.10a
• /
• pp.157.6-157
• /
• 2001

We estimated various neuron functions to construct of engineering neurons, which are the combination of sigmoid, linear, sine, quadric, double/single bended, soft max/minimum functions. These combinations are estimated by the property on the potential surface between the learning points, calculation speed, and learning convergence; because the surface depends on the inference ability of a neuron system; and speed and convergence are depend on the efficiency on the points of engineering applications. After the evaluating discussions, we can select more appropriate combination than original sigmoid function´s, which is single bended function and linear one. The combination ...

• East Asian mathematical journal
• /
• v.38 no.2
• /
• pp.187-214
• /
• 2022

This study compares the functions of the Learning Management Systems (LMS) in three widely used Edu-Tech platforms, that support students' individualized learning by using the learning characteristics of the students. The rapid advances in artificial intelligence (AI) are broadening their impacts in the education industry, and play a broad role in supporting student learning. In many countries, online classes have become a norm due to the COVID-19 crisis, and the demand for Edu-Tech in classes has increased rapidly. As a result, many countries, including South Korea, are now preparing and implementing various policy measures to adopt Edu-Tech in the class setting. Therefore, in this study, we analyze and compare the structures and characteristics of the three widely used Edu-Tech platforms that support individualized mathematics learning. In particular, we compare the LMSs of the three platforms by considering the elements such as learning design, learning management, learner analysis, learning result analysis, and student management functions. The results of this study give implications in the future directions to take on how to build Edu-Tech platform models that promote students' individualized mathematics learning in public education.

• Journal of Fisheries and Marine Sciences Education
• /
• v.21 no.2
• /
• pp.278-290
• /
• 2009

The purpose of this study is to investigate the relationship between learning skills and cognitive functions on elementary school students. In this study CAS and Learning Skills Test(LST) were administered with 3 to 6 grade, 60 students from 5 elementary schools. The data were analyzed according to Pearson's correlation and Stepwise Multiple Regression Analysis. The results are as follows. Firstly, girls and older students showed significantly higher ability than boys and younger students on the learning skills. And girls significantly outperformed boys on the planning function and attention function and on the simultaneous cognitive function was the other way round. Secondly, learning skills were explained 41% by two variables that the planning function and the successive function which are sub factors of the cognitive function. And then, planning and successive processing effected to self-management, attention and planning to test-taking skills, successive processing and attention to class-participation skills, and successive processing to information processing.

• 제어로봇시스템학회:학술대회논문집
• /
• 2000.10a
• /
• pp.489-489
• /
• 2000

Recently, Reinforcement Learning(RL) methods have been used far teaming problems in Partially Observable Markov Decision Process(POMDP) environments. Conventional RL-methods, however, have limited applicability to POMDP To overcome the partial observability, several algorithms were proposed [5], [7]. The aim of this paper is to extend our previous algorithm for POMDP, called Labeling Q-learning(LQ-learning), which reinforces incomplete information of perception with labeling. Namely, in the LQ-learning, the agent percepts the current states by pair of observation and its label, and the agent can distinguish states, which look as same, more exactly. Labeling is carried out by a hash-like function, which we call Labeling Function(LF). Numerous labeling functions can be considered, but in this paper, we will introduce several labeling functions based on only 2 or 3 immediate past sequential observations. We introduce the basic idea of LQ-learning briefly, apply it to maze problems, simple POMDP environments, and show its availability with empirical results, look better than conventional RL algorithms.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.5 no.6
• /
• pp.69-78
• /
• 1982

Traditional CVP (Cost-Volume-Profit) analysis employs linear cost and revenue functions within some specified time period and range of operations. Therefore CVP analysis is assumption of constant labor productivity. The use of linear cost functions implicity assumes, among other things, that firm's labor force is either a homogenous group or a collection homogenous subgroups in a constant mix, and that total production changes in a linear fashion through appropriate increase or decrease of seemingly interchangeable labor unit. But productivity rates in many firms are known to change with additional manufacturing experience in employee skill. Learning curve is intended to subsume the effects of all these resources of productivity. This learning phenomenon is quantifiable in the form of a learning curve, or manufacturing progress function. The purpose d this study is to show how alternative assumptions regarding a firm's labor force may be utilize by integrating conventional CVP analysis with learning curve theory, Explicit consideration of the effect of learning should substantially enrich CVP analysis and improve its use as a tool for planning and control of industry.

• East Asian mathematical journal
• /
• v.37 no.2
• /
• pp.265-288
• /
• 2021

In the 2015 revised mathematics curriculum, the system of equations is first introduced in 'Variables and Expressions' of [Middle School Grades 1-3]. Then, It is constructed that after learning the linear function in 'Functions', the relationship between the graphs of two linear functions and the systems of linear equations are learned so that students could improve the geometric representation of the systems of equations. However, in of Elective-Centered Curriculum Common Courses, Instruction is limited to algebraic manipulation when teaching and learning systems of quadratic equations. This paper presented the teaching and learning method that can improve students' mathematical connection through various representations by providing geometric representations in parallel using GeoGebra, a mathematics learning software, with algebraic solutions in the teaching and learning situation of simultaneous quadratic equations.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.23 no.4
• /
• pp.79-84
• /
• 2023

Apache Spark, which provides the fastest processing speed among recent distributed and parallel processing technologies, provides real-time functions and machine learning functions. Although official documentation guides for these functions are provided, a method for fusion of functions to predict a specific value in real time is not provided. Therefore, in this paper, we conducted a study to predict the value of data in real time by fusion of these functions. The overall configuration is collected by downloading stock price data provided by the Python programming language. And it creates a model of regression analysis through the machine learning function, and predicts the adjusted closing price among the stock price data in real time by fusing the real-time streaming function with the machine learning function.