• IEIE Transactions on Smart Processing and Computing
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• v.3 no.6
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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.

• Journal of the Korean Society of Food Culture
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• v.25 no.6
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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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• v.24 no.4
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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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• v.22 no.11
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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.

• Journal of the Korea Society of Computer and Information
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• v.28 no.5
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• pp.189-196
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• 2023

This study aims to show that "Computer-assisted language learning (CALL)" and "Mobile-based language learning (MALL)" actually influence education, deviating from the traditional "drill and practice" method in foreign language education and learning due to the development of information and communication technology (IT). Specifically, for first-year college students who have relatively poor English skills and do not feel enough motivation for English learning, I will produce educational video content using multimedia authoring tools and upload it to the e-learning system. Video content is configured to be accessed and utilized through various media such as computers, smartphones, tablets, laptops, etc. Ultimately, an exploration of educational value behind the utilization of IT devices in English language Teaching(ELT) and the Second Language Acquisition (SLA) theory behind effective instructional use of such technology are presented. That is to say, the effectiveness of language learning using information and communication technology (IT) is introduced. The article closes by suggesting how to use computers and mobile media for 'Flipped Learning'.

• International Journal of Computer Science & Network Security
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• v.21 no.6
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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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• v.14 no.2
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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.

• Journal of the Korean School Mathematics Society
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• v.2 no.1
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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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• v.44 no.2
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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.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.6
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• pp.287-292
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• 2010

The flow gradually into the Information age to the Information age has changed, leading to the development of computer and communication technology was very important for the value. Of these the most used in computer communication using the Internet, and this proportion accounts for the development of the Internet, the information was established as a means of interaction. In this paper, to improve these problems without the constraints of time and space to allow two-way interactions using web based learning system to enable Computer Architecture were learning. Learn how Computer Architecture using Camtasia the learner, without limitation of time and place of the browser through the Internet to enable real-time learning and assessment appropriate to individual learners and teaching - learning process in conjunction with individual learners can be self-directed learning will play a role in that.