• Journal of Computing Science and Engineering
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• 제1권2호
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• pp.162-176
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• 2007

Machine Learning (ML) has become very popular within Data Mining (KDD) and Artificial Intelligence (AI) research and their applications. In the ML and KDD contexts, two main approaches can be used for inducing a Bayesian Network (BN) from data, namely, Conditional Independence (CI) and the Heuristic Search (HS). When a BN is induced for classification purposes (Bayesian Classifier - BC), it is possible to impose some specific constraints aiming at increasing the computational efficiency. In this paper a new CI based approach to induce BCs from data is proposed and two algorithms are presented. Such approach is based on the Markov Blanket concept in order to impose some constraints and optimize the traditional PC learning algorithm. Experiments performed with the ALARM, as well as other six UCI and three artificial domains revealed that the proposed approach tends to execute fewer comparison tests than the traditional PC. The experiments also show that the proposed algorithms produce competitive classification rates when compared with both, PC and Naive Bayes.

• 한국컴퓨터정보학회논문지
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• 제6권3호
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• pp.17-22
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• 2001

전통적인 교육방식에서는 학생이 교육과정에서 정해진 과정을 그대로 이수하고 있다. 일부 유사과목들은 유사한 내용을 서로 다른 과목에서 동일하게 다루고 있는 문제점이 있다. 따라서 본 논문에서는 인터넷 기반의 원격교육을 수행함에 있어서 자기주도형 학습자를 위한 교과목 구성을 위해 모듈별로 세분하는 가상교육시스템을 제안하였다. 기존의 두 과목의 수업내용을 비교 분석하여 기존방식에 비해 제안한 방식이 약 9.4％의 시간을 절감할 수 있었다.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2019년도 춘계학술대회
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• pp.155-156
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• 2019

Classification and Regression Tree (CART), SVM (Support Vector Machine) 및 k-nearest neighbor classification (kNN)과 같은 기존 기계 학습 기반 감정 분석 방법은 정확성이 떨어졌습니다. 본 논문에서는 개선 된 kNN 분류 방법을 제안한다. 개선 된 방법 및 데이터 정규화를 통해 정확성 향상의 목적이 달성됩니다. 그 후, 3 가지 분류 알고리즘과 개선 된 알고리즘을 실험 데이터에 기초하여 비교 하였다.

• Journal of information and communication convergence engineering
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• 제20권2호
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• pp.96-102
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• 2022

We aim to build predictive models for Airbnb's prices using a GPU-accelerated RAPIDS in a big data cluster. The Airbnb Listings datasets are used for the predictive analysis. Several machine-learning algorithms have been adopted to build models that predict the price of Airbnb listings. We compare the results of traditional and big data approaches to machine learning for price prediction and discuss the performance of the models. We built big data models using Databricks Spark Cluster, a distributed parallel computing system. Furthermore, we implemented models using multiple GPUs using RAPIDS in the spark cluster. The model was developed using the XGBoost algorithm, whereas other models were developed using traditional central processing unit (CPU)-based algorithms. This study compared all models in terms of accuracy metrics and computing time. We observed that the XGBoost model with RAPIDS using GPUs had the highest accuracy and computing time.

• 대한수학교육학회지:수학교육학연구
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• 제10권2호
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• pp.229-246
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• 2000

The purpose of this paper is to compare and analyze the two different teaching methods of elementary mathematics in the traditional method and in the constructive view. To do so, the actual class in the constructive view has been made for about four months using a class of 45 students in the second grade of an elementary school. After the class was finished, we collected diverse data from the class, such as the responses from the children(self-evaluation, mathematics diary, observation by the investigator, daily report), class evaluation report by other teacher and so on. The results of this research are as follows: First, the traditional class reaches at the goal of learning in a unit time because the class is guided by the teacher but the class in the constructive view is a little flexible because it is contextual. Second, in the constructive process of mathematical knowledge we knew that small group activities or discussion without intervention of teacher was often ended in exhaustive argument without arriving at valid social consensus. Third, the attitude in mathematics was changed from the passive one to the self-regulated ones. Fourth, the class in the constructive view could extend not only the ability of mathematical communication but also the ability of self-directed learning of children. Fifth, it was a considerable change the role of teacher, that is, guide of instruction instead of unique specialist in the classroom. Sixth, finally, the evaluation was made after finishing a unit class in the traditional instruction but it was integrated in a class in a constructive view.

• The Korean Journal of Physiology and Pharmacology
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• 제23권5호
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• pp.305-310
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• 2019

The physiomic approach is now widely used in the diagnosis of cardiovascular diseases. There are two possible methods for cardiovascular physiome: the traditional mathematical model and the machine learning (ML) algorithm. ML is used in almost every area of society for various tasks formerly performed by humans. Specifically, various ML techniques in cardiovascular medicine are being developed and improved at unprecedented speed. The benefits of using ML for various tasks is that the inner working mechanism of the system does not need to be known, which can prove convenient in situations where determining the inner workings of the system can be difficult. The computation speed is also often higher than that of the traditional mathematical models. The limitations with ML are that it inherently leads to an approximation, and special care must be taken in cases where a high accuracy is required. Traditional mathematical models are, however, constructed based on underlying laws either proven or assumed. The results from the mathematical models are accurate as long as the model is. Combining the advantages of both the mathematical models and ML would increase both the accuracy and efficiency of the simulation for many problems. In this review, examples of cardiovascular physiome where approaches of mathematical modeling and ML can be combined are introduced.

• International Journal of Advanced Culture Technology
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• 제10권1호
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• pp.1-9
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• 2022

The notion of outcome-based educational paradigm and its adaptability for higher education has become a recent growing and quite stirring trend. In the year 2017-18, this educational philosophy has been embraced by some of the higher educational institutions in Pakistan as well. This research attempts to investigate OBE and non-OBE systems in the context of students learning outcomes and academic attainment levels in engineering education in Pakistan. The study has been conducted on undergraduate students of MUET, Jamshoro, Sindh Pakistan. The students of the software engineering department are taken as the sample. Student cohorts are formed i.e., OBE and non-OBE (traditional/teacher-centered approach) cohorts. The summative assessments of semester exams are used for data analysis descriptive statistics and independent samples t-test is performed to set up the group statistic. The findings of this study show that, in terms of students' performance, the OBE system outperforms the traditional system and this transition in engineering institutions might be beneficial in the future.

• 한국게임학회 논문지
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• 제15권1호
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• pp.125-134
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• 2015

본 논문은 학습자가 효과적인 게임프로그래밍을 학습하도록 피어튜터모형(TGF: Tutoring Game program in Flipped learning)을 설계하고, 수업에 적용한 학습경험을 교수와 피어튜터 및 학습자의 관점에서 제시하고, 학습 성과를 설문조사를 통해 분석하여 플립드 러닝 환경에서의 TGF가 전통적인 수업방식에 비해 게임프로그래밍 수업에서 학습목표를 달성하는데 더욱 효과적임을 보였다.

• 수산해양교육연구
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• 제13권2호
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• pp.194-211
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• 2001

This study was conducted to investigate the effects of cooperative learning applying Jigsaw II on learner's self-regulated learning ability, achievements, self-esteem & cooperation. 12 graders were assigned to experimental group(applying Jigsaw II treatment) & control group(applying traditional instructional treatment). Experimental group was trained to ask comprehension & thought-provoking questions on the material when in tutor role & to explain material to group members when acting as tutee. Tutorial sessions followed over 8-week treatment. As a results, Experimental group outperformed control group on ability to construct learner's self-regulated learning ability, achievements, self-esteem & cooperation both during their tutorial interaction & on written measures.

• 컴퓨터교육학회논문지
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• 제11권6호
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• pp.95-102
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• 2008

본 연구에서 SDG를 사용한 교육 퍼즐구현을 통하여 협동학습을 컴퓨터교육에 적용하였다. SDG란 하나의 컴퓨터 디스플레이에 다중 입력장치로 협동적인 작업을 할 수 있는 시스템을 말한다. SDG 기반의 협동학습을 통해 학습자들은 협동 학습을 수행하게 된다. SDG를 이용한 협동학습이 단일 디바이스를 이용한 개별 학습보다 우월하다는 기존의 연구가 있다. 이를 바탕으로 협동학습을 이용한 퍼즐게임을 구현하였다.