• IEIE Transactions on Smart Processing and Computing
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• 제3권6호
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• pp.366-371
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• 2014

This paper reports a machine learning approach for image object detection. Object detection and localization in a wild image, such as a STL-10 image dataset, is very difficult to implement using the traditional computer vision method. A convolutional neural network is a good approach for such wild image object detection. This paper presents an object detection application using a convolutional neural network with pretrained feature vector. This is a very simple and well organized hierarchical object abstraction model.

• 한국식생활문화학회지
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• 제25권6호
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• pp.661-670
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• 2010

Although many studies have suggested that introducing the distance learning method, including Web-based learning, to a practice class is effective, studies applying the distance learning method to subjects who are practicing cooking are rare. The purpose of this study was to determine the perception of the distance learning method, the degree of computer use, and the use of distance learning by college students with cuisine-related majors to practice cooking. The results showed that most students used the distance learning method, and that the method was positively perceived, as it was a great aid in learning. Most of the cooking information was obtained through the internet, and the most effective learning media for practicing cooking was "e-learning" using a computer. The most effective learning method for those who were practicing cooking was a "face-to-face learning method", because face-to-face type of teaching and learning was most universally recognized. Most of the students surveyed responded that using the distance learning method was a positive experience, indicating that cyber lectures could be applied at more universities for subjects practicing cooking.

• International Journal of Computer Science & Network Security
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• 제24권4호
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• pp.67-76
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• 2024

Diabetic retinopathy is a threatening complication of diabetes, caused by damaged blood vessels of light sensitive areas of retina. DR leads to total or partial blindness if left untreated. DR does not give any symptoms at early stages so earlier detection of DR is a big challenge for proper treatment of diseases. With advancement of technology various computer-aided diagnostic programs using image processing and machine learning approaches are designed for early detection of DR so that proper treatment can be provided to the patients for preventing its harmful effects. Now a day machine learning techniques are widely applied for image processing. These techniques also provide amazing result in this field also. In this paper we discuss various machine learning and deep learning based techniques developed for automatic detection of Diabetic Retinopathy.

• International Journal of Computer Science & Network Security
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• 제22권11호
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• pp.265-271
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• 2022

Social media is a form of communication based on the internet to share information through content and images. Their choice of profile images and type of image they post can be closely connected to their personality. The user posted images are designated as personality traits. The objective of this study is to predict five factor model personality dimensions from profile images by using deep learning and neural networks. Developed a deep learning framework-based neural network for personality prediction. The personality types of the Big Five Factor model can be quantified from user profile images. To measure the effectiveness, proposed two models using convolution Neural Networks to classify each personality of the user. Done performance analysis among two different models for efficiently predict personality traits from profile image. It was found that VGG-69 CNN models are best performing models for producing the classification accuracy of 91% to predict user personality traits.

• 한국컴퓨터정보학회논문지
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• 제28권5호
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• pp.189-196
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• 2023

본 연구는 정보통신기술(IT)의 발전으로 외국어 교육과 학습에서 기존의 전통적인 '훈련과 연습(drill and practice)'의 방법에서 벗어난 '컴퓨터 보조언어학습(Computer-assisted learning: CALL)'과 '모바일 지원 언어학습(Mobile-based Language Learning: MALL)'이 실제로 어학 교육에 미치는 영향을 분석한다. 연구 대상은 비교적 영어 능력이 상대적으로 우수하지 않고, 또한 영어학습에 대한 동기부여를 충분히 느끼지 못하는 전문대학 1학년 학생들을 대상으로 진행하였다. 연구 방법은 멀티미디어 저작 도구를 이용하여 디지털 콘텐츠를 제작하여 이러닝(e-learning) 시스템에 등재하여 교육보조재료로 한 학기 동안 활용한다. 동영상 콘텐츠는 컴퓨터, 스마트폰, 테블릿, 노트북 등 다양한 매체로 접근하여 활용할 수 있도록 구성한다. 동영상 콘텐츠에 대한 설문조사를 통하여 콘텐츠의 구성, 학습에 도움 여부, 보완해야 할 부분, 콘텐츠 접근 빈도, 학습경로 등을 분석한다. 분석의 결과를 통하여 정보통신기술을 활용한 어학 학습의 효과, 교육용 콘텐츠의 개선해야 할 부분 및 교육에 어떻게 활용해야 하는지에 대해 제언한다. 궁극적으로는 '플립러닝((Flipped Learning)'을 위한 컴퓨터 및 모바일 매체에 대한 효용성 분석과 활용방안을 제언한다.

• International Journal of Computer Science & Network Security
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• 제21권6호
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• pp.77-88
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• 2021

Heart Failure represents a critical pathological case that is challenging to predict and discover at an early age, with a notable increase in morbidity and mortality. Machine Learning and Neural Network techniques play a crucial role in predicting heart attacks, diseases and more. These techniques give valuable perspectives for clinicians who may then adjust their diagnosis for each individual patient. This paper evaluated neural network models for heart attacks predictions. Several online learning methods were investigated to automatically and accurately predict heart attacks. The UCI dataset was used in this work to train and evaluate First Order and Second Order Online Learning methods; namely Backpropagation, Delta bar Delta, Levenberg Marquardt and QuickProp learning methods. An optimizer technique was also used to minimize the random noise in the database. A regularization concept was employed to further improve the generalization of the model. Results show that a three layers' NN model with a Backpropagation algorithm and Nadam optimizer achieved a promising accuracy for the heart attach prediction tasks.

• Journal of information and communication convergence engineering
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• 제14권2호
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• pp.97-105
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• 2016

With the increasing demand for interoperability among existing learning resource systems in order to enable the sharing of learning resources, such resources need to be annotated with ontologies that use different metadata standards. These different ontologies must be reconciled through ontology mediation, so as to cope with information heterogeneity problems, such as semantic and structural conflicts. In this paper, we propose an ontology-mapping technique using Semantic Web Rule Language (SWRL) to generate semantic mapping rules that integrate learning resources from different systems and that cope with semantic and structural conflicts. Reasoning rules are defined to support a semantic search for heterogeneous learning resources, which are deduced by rule-based inference. Experimental results demonstrate that the proposed approach enables the integration of learning resources originating from multiple sources and helps users to search across heterogeneous learning resource systems.

• 한국학교수학회논문집
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• 제2권1호
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• pp.231-242
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• 1999

The focus of this development program is to input multimedia materials into learning according to the trend of recent social changes and to maximize the learning effect for improving problem-solving by offering familiar teaching materials. The expecting effects of this study are as follows: 1. This program helps students acquire mathematical concepts and principles about circular equation through concrete examples using a variety of media - text, voice, sound, and animation and so on - , makes it possible individual learning which was difficult for students to expect at the existing multitude class as progressing learning each unit on the screen and the perfect learning by offering FEED BACK 2. This program varied the difficulty of learning contents to learn according to learning abilities of learners by using animation and making the most of merits of computer and was able to improve learning effect by studying in a mutual way with managing learning procedure nonsuccessively. 3. Class using CAI program about developed circular equation unit has a positive effect on improving problem-solving by becoming from teacher centered class to student centered one. 4. This program makes students understand the contents of auxiliary learning in multimedia computer more efficiently, and cultivate abilities to adopt in accordance with changes in the future society by forming familiar computer mind.

• ETRI Journal
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• 제44권2호
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• pp.232-243
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• 2022

Changes in household composition and the residential environment have had a considerable impact on the features of postal delivery regions in recent years, resulting in a large increase in the overall workload of domestic postal delivery services. In this paper, we provide complex analysis results for postal delivery areas using various unsupervised learning approaches. First, we extract highly influential features using several feature-engineering methods. Then, using quantitative and qualitative cluster analyses, we find the distinctive traits and semantics of postal delivery zones. Unsupervised learning approaches are useful for successfully grouping postal service zones, according to our findings. Furthermore, by comparing a postal delivery region to other areas in the same group, workload balancing was achieved.

• 한국인터넷방송통신학회논문지
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• 제10권6호
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• pp.287-292
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• 2010

시대의 흐름이 점차 정보화 시대로 변함에 따라 정보화 시대를 대표하는 컴퓨터와 통신기술의 발달에 대한 가치가 매우 중요시하게 되었다. 이중 컴퓨터 통신의 사용에서 가장 많은 사용 비중을 차지하는 것은 인터넷이고 이런 인터넷의 발전은 정보가 상호 작용하는 수단으로 자리매김하였다. 논문은 웹 기반교육이 학습자에게 효과적인 교육 시스템으로서의 역할을 하기 위해 기존의 학습시스템 문제점을 찾아내어 개선하고, 시간과 공간의 제약을 받지 않고 양방향의 상호 작용이 가능하도록 웹 기반학습을 사용하여 컴퓨터 구조론의 학습이 가능 하도록 하였다. 웹 기반학습을 이용한 컴퓨터 구조론 학습 방법은 학습자가 시간과 장소의 제한을 받지 않고 인터넷의 브라우저를 통해 실시간 학습과 평가를 가능하게 하며 학습자 개개인에게 알맞은 교수-학습 과정으로 연계하여 학습자 개인별 자기 주도 학습이 가능하도록 하는 역할을 담당할 것이다.