• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.9
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• pp.1210-1215
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• 2018

Recently, as the IoT(Internet of Things) and AI(Artificial Intelligence) technologies have developed, smart toys that can understand and act on the language of human beings are being studied. In this paper, we study voice learning using CNN(Convolutional Neural Network) by applying artificial intelligence based voice secretary technology to smart toy. When a human voice command gives, Smart Toy recognizes human voice, converts it into text, analyzes the morpheme, and conducts tagging and voice learning. As a result of test for the simulator program implemented using Python, no malfunction occurred in a single command. And satisfactory results were obtained within the selected simulation condition range.

• International Journal of Computer Science & Network Security
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• v.22 no.5
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• pp.135-142
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• 2022

Despite global medical advancements, many patients are misdiagnosed, and more people are dying as a result. We must now develop techniques that provide the most accurate diagnosis of heart disease based on recorded data. To help immediate and accurate diagnose of heart disease, several data mining methods are accustomed to anticipating the disease. A large amount of clinical information offered data mining strategies to uncover the hidden pattern. This paper presents, comparison between different classification techniques, we applied on the same dataset to see what is the best. In the end, we found that the Random Forest algorithm had the best results.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.3
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• pp.203-210
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• 2023

In this paper, we develope a stock trading system that automatically buy and sell stocks in Kiwoom Securities' HTS system. The system is made by using Kiwoom Open API+ with the Python programming language. A trading strategy is based on an enhanced system query method called a Condition-Search. The Condition-Search script is edited in Kiwoom Hero 4 HTS and the script is stored in the Kiwoom server. The Condition-Search script has the advantage of being easy to change the trading strategy because it can be modified and changed as needed. In the HTS system, up to ten Condition-Search scripts are supported, so it is possible to apply various trading methods. But there are some restrictions on transactions and Condition-Search in Kiwoom Open API+. To avoid one problem that has transaction number and frequency are restricted, a method of adjusting the time interval between transactions is applied and the other problem that do not support a threading technique is solved by an IPC(Inter-Process Communication) with multiple login IDs.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.368-368
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• 2022

The Soil and Water Assessment Tool (SWAT) has been widely used to simulate the long-term hydrological conditions of a catchment. Two output variables, outflow and sediment yield have been widely investigated in the field of water resources management, especially in determining the conditions of ungauged subbasins. The presence of missing data in weather input data can cause poor representation of the climate conditions in a catchment especially for large or mountainous catchments. Therefore, in this study, a custom module was developed and evaluated to determine the efficiency of utilizing basic spatial interpolation methods in the estimation of weather input data. The module has been written in Python language and can be considered as a pre-processing module prior to using the SWAT model. The results of this study suggests that the utilization of the proposed pre-processing module can improve the simulation results for both outflow and sediment yield in a catchment, even in the presence of missing data.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.07a
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• pp.321-322
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• 2022

스마트폰 사용자가 늘어남에 따라 갖춰줘야 할 보안성이 취약하여, 다양한 바이러스 및 악성코드 위험에 노출되어 있다. 안드로이드는 운영체제 중 가장 많이 사용되는 운영체제로, 개방성이 높으며 수많은 악성 앱 및 바이러스가 마켓에 존재하여 위험에 쉽게 노출된다. 2년 넘게 이어진 코로나 바이러스(Covid-19)으로 인해 꾸준히 위험도가 높아진 피싱공격(Phshing attack)은 현재 최고의 스마트폰 보안 위협 Top10에 위치한다. 본 논문에서는 딥러닝 기반 자연어처리 기술을 통해 피싱 공격 대응 방법 제안 및 실험 결과를 도출하고, 또한 향후 제안 방법을 보완하여 피싱 공격 및 다양한 모바일 보안 위협에 대응할 수 있는 앱을 설계할 것이다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.07a
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• pp.93-94
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• 2023

본 논문에서는 Azure 플랫폼 기반의 ChatBot을 활용한 한국어 학습 챗봇 애플리케이션을 설계하고 구현한다. C# ChatBot Server를 통해 챗봇 메뉴 버튼에 대한 네비게이션을 구현하며, Python 기반의 웹 프레임워크 Django를 활용하여 단어 퀴즈에 필요한 대화 처리를 구현한다. 단어 퀴즈를 통해 언어학습에 대한 흥미를 유발하고 학습 효율을 높일 수 있도록 구현한다.

• Journal of Engineering Education Research
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• v.26 no.6
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• pp.71-78
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• 2023

ChatGPT significantly broadens the application of artificial intelligence (AI) services across various domains, with one of its primary functions being assistance in programming and coding. Nevertheless, due to the short history of ChatGPT, there have been few studies analyzing its coding capabilities in Korean higher education. In this paper, we evaluate it using exam questions from three foundational programming courses at S University. According to the experimental results, ChatGPT successfully generated Python, C, and JAVA programs, and the code quality is on par with that of high-achieving students. The powerful coding capabilities of ChatGPT imply the need for a strict prohibition of its usage in coding tests; however, it also suggests significant potential for enhancing practical exercises in the educational aspect.

• Proceedings of the Korean Society of Computer Information Conference
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• 2024.01a
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• pp.13-16
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• 2024

온라인상에 인간의 감성을 담은 리뷰 데이터가 꾸준히 축적되어왔다. 이 텍스트 데이터를 분석하고 활용하는 일은 마케팅에 있어서 중요한 자산이 될 것이다. 이와 관련된 Aspect-Based Sentiment Analysis(ABSA) 연구는 한글에 있어서는 데이터 부족을 이유로 거의 선행연구가 없는 실정이다. 본 연구에서는 최근 공개된 데이터 셋을 바탕으로 하여 화장품 도메인에 대한 소비자들의 리뷰 텍스트와 사전 라벨링 된 속성, 감성 극성을 기반으로 ABSA를 진행한다. Klue RoBERTa base 모델을 활용하여 데이터를 학습시키고, Python Kiwipiepy 등으로 전처리한 결과를 대시보드로 시각화하여 분석하기 쉬운 환경을 마련하는 방법을 제시한다.

• ETRI Journal
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• v.46 no.3
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• pp.473-484
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• 2024

We introduce a machine learning-based web application to help travel agents plan a package tour schedule. K-nearest neighbor (KNN) classification predicts the optimal tourists' dwelling time based on a variety of information to automatically generate a convenient tour schedule. A database collected in collaboration with an established travel agency is fed into the KNN algorithm implemented in the Python language, and the predicted dwelling times are sent to the web application via a RESTful application programming interface provided by the Flask framework. The web application displays a page in which the agents can configure the initial data and predict the optimal dwelling time and automatically update the tour schedule. After conducting a performance evaluation by simulating a scenario on a computer running the Windows operating system, the average response time was 1.762 s, and the prediction consistency was 100% over 100 iterations.

• Journal of Korean Tunnelling and Underground Space Association
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• v.18 no.6
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• pp.545-556
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• 2016

If a back analysis is used in various measurement information for the estimation of an operating subsea tunnel safety, it is possible to obtain the results within efficient error rate. With such a commercial geotechnical analysis program as FLAC3D, back analysis is performed with a DEA which was validated in previous studies. However, there is a problem that is relatively a time-consuming analysis. For this reason, beam-spring model-based FEM solver which takes shorter relative analysis time, was developed by Python language, and then combined with the built-DEA. In order to consider the assessment of safety of an operation tunnel near real-time, a program for longitudinal direction tunnel was developed due to its relative easy development for analysis solver engine.