• Annual Conference of KIPS
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• 2023.11a
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• pp.820-821
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• 2023

본 프로젝트는 Azure OpenAI Service (large language models and generative AI) 를 이용하여 IT 기술 및 현황을 생성형 AI (GPT-4)를 활용한 IT 카드 뉴스 서비스로서 업계 현직자들에게 정보를 제공하는 시스템을 구현하였다. IT 카드 뉴스 서비스의 부재와 뉴스 제작의 비용 및 시간 소요의 문제를 해결하기 위해 생성형 AI 시스템을 고안하였다. 해당 서비스를 통해 IT 업계에 관심이 많은 사용자에게 정리된 뉴스를 한 번에 제공하는 효과를 가져올 것으로 예상한다.

• Review of KIISC
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• v.34 no.2
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• pp.21-27
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• 2024

양자컴퓨터는 매우 많은 경우의 수를 탐색하고 연산하는 데에 있어 이점을 가지며, 이는 소인수분해와 같은 작업에서 기존 컴퓨팅을 능가할 수 있다. 이러한 능력으로 인해 양자컴퓨터는 현재 사용되는 암호체계를 위협할 수 있다. 또한, 화학, 머신러닝 등 다양한 분야에서 혁신을 가져올 수 있는 차세대 컴퓨팅 환경으로 주목받고 있다. 현재 IBM, Google, Amazon 등의 세계적인 IT 기업들이 이 분야의 연구 및 개발에 적극적으로 투자하고 있으며 본고에서는 양자컴퓨터의 최근 개발현황과 양자컴퓨팅을 위한 플랫폼인 IBM Qiskit, Google Cirq, ProjectQ, Amazon Braket, Microsoft Azure Quantum, Intel Quantum SDK, Pennylane에 대해 알아보고자 한다.

• Journal of Korean Society for Geospatial Information Science
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• v.22 no.4
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• pp.175-181
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• 2014

Korean government proposed a new initiative 'government 3.0' with which the administration will open its dataset to the public before requests. City of Seoul is the front runner in disclosure of government data. If we know what kind of attributes are governing factors for any given segmentation, these outcomes can be applied to real world problems of marketing and business strategy, and administrative decision makings. However, with respect to city of Seoul, selection of optimal variables from the open dataset up to several thousands of attributes would require a humongous amount of computation time because it might require a combinatorial optimization while maximizing dissimilarity measures between clusters. In this study, we acquired 718 attribute dataset from Statistics Korea and conducted an analysis to select the most suitable variables, which differentiate Gangnam from other districts, using the Genetic algorithm and Dunn's index. Also, we utilized the Microsoft Azure cloud computing system to speed up the process time. As the result, the optimal 28 variables were finally selected, and the validation result showed that those 28 variables effectively group the Gangnam from other districts using the Ward's minimum variance and K-means algorithm.

• Applied Microscopy
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• v.38 no.3
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• pp.213-219
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• 2008

The plasticity of nervous system is generated not only due to changes in neurons but also due to changes in neuroglial cells. Astrocyte is important for maintaining the normal brain function and controlling the neuronal functions. The amygdala receives an array of important sensory information of danger signals. This information is further transduced and integrated to produce the highly adaptive emotion, fear. In this study, morphometric changes in the cell bodies of astrocytes in the amygdala, induced by prenatal stress and restraint stress were examined. For this purpose. rats were classified into 4 groups; control group (CON), only restraint-stressed (starting on P90 for 3 days) group (CONR), prenatally-stressed group (PNS), and prenatally and restraint (on P90 for 3 days) stressed group (PNSR). Astrocytes were verified with anti-GFAP immunohistochemistry, counter stained with methylene blue/azure II and were examined using the Neurolucida. Results showed that astrocytes in the amygdala of PNS rats had significantly larger cell bodies than did CON rats and this was enhanced further by restraint stress. Thus this data showed that hypertrophy of the astrocytic cell bodies of amygdala complex is induced by prenatal and restraint stress.

• The Journal of the Convergence on Culture Technology
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• v.6 no.2
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• pp.561-566
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• 2020

We propose to design and to implement a recreational and end - of - play robot for symptom relief in patients with depression. The main symptom of depression is the loss of interest and interest in life. The depression diagnosis patient confirms the emotional analysis revealed by his / her robot through the robot, and performs the greeting or ending play. After analyzing the emotions in the expressions after the play, the function of the embodying robot is confirmed by receiving the report. A simple play can not completely cure a patient with a diagnosis of depression, but it can contribute to symptom relief through gradual use. The design of the play-by-play robot is using Q.bo One, an open-source robot that can interact with Thecorpora. Q.bo One's system captures a user's face, takes a picture, passes the value to the Azure server, and checks the emotional analysis before and after the play with the accumulated data.Play is implemented in Rasubian, the OS of Q.bo One, using the programming language Python and interacting with external sensors. The purpose of this paper is to help the symptom relief of depressive patients in a relatively short time with a play robot.

• Journal of Korea Multimedia Society
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• v.20 no.8
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• pp.1456-1463
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• 2017

In recent times, IaaS (Infrastructure as a Services) have been rapidly evolving to allow developers to easily and efficiently access work in the server and network areas for development of a web of App based on cloud computing. In this study, we developed the collaborative image editing tool App based on Cloud-computing, by adopting AWS of representative company that develops IaaS. First, it is crucial to understand various situation conditions for representative infrastructure services: AWS, Azure and Google (GCP). This may have the effect of reducing manpower and development time, but as each company has different policy and technical support, we need a new study every time the environment changes of infrastructure services. We tried to develop a hybrid-App so that users with various devices can collaborate work each other by utilizing the infrastructure service AWS through the process of developing the image editing authoring tool based on the cloud computing. The future studies should continue about compatibility issues and support issues in order to minimize the problems of overseas infrastructure services, but we think that domestic cloud computing policies and developments should be urgently considered.

• Korean Journal of Artificial Intelligence
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• v.6 no.2
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• pp.23-27
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• 2018

Korea has a high proportion of self-employment. Many of them start the food business since it does not require high-techs and it is possible to start the business relatively easily compared to many others in business categories. However, the closure rate of the business is also high due to excessive competition and market saturation. Cafés and restaurants are examples of food business where the business analysis is highly important. However, for most of the people who want to start their own business, it is difficult to conduct systematic business analysis such as trade area analysis or to find information for business analysis. Therefore, in this paper, we predicted business status with simple information using Microsoft Azure Machine Learning Studio program. Experimental results showed higher performance than the number of attributes, and it is expected that this artificial intelligence model will be helpful to those who are self-employed because it can easily predict the business status. The results showed that the overall accuracy was over 60 % and the performance was high compared to the number of attributes. If this model is used, those who prepare for self-employment who are not experts in the business analysis will be able to predict the business status of stores in Seoul with simple attributes.

• Journal of Microbiology and Biotechnology
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• v.11 no.5
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• pp.863-869
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• 2001

A systematic study of microbial fuel cells comprised of alkalophilic Bacillus sp. B-31 has been carried out under various operating conditions. A significant amount of electricity was generated when redox mediators were used. Among the phenothiazine-type redox dyes tested, azure A was found to be the most effective both in maintaining a high cell voltage and for the long-term operation. The maximum efficiency was and for the long-term operation. The maximum efficiency was obtained at ca. $50^{\circ}C$ giving an open circuit voltage of 0.7V. A small change in temperature did not significantly affect the cell performance, but a rapid decrease in performance was observed below $20^{\circ}C$ and above $70^{\circ}C$. It was noticeable that fuel cell efficiency and discharge pattern depended strongly on the carbon source used in the initial culture medium. Regardless of the initial carbon sources, only glucose and trehalose were utilized as substrates. Galactose, however, was not substantially utilized except when galactose was used in the initial medium. Glucose, in particular, showed $87\%$ coulombic efficiency, which was the highest value ever reported, when Bacillus sp. was cultured in a maltose-containing medium. This study demonstrates that highly efficient microbial fuel cells can be constructed with alkalophilic microorganisms by fine-tuning the operating conditions and by carefully selecting carbon sources in the initial culture medium.

• Korean Journal of Artificial Intelligence
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• v.7 no.2
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• pp.19-24
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• 2019

Lung cancer is a chronic disease which ranks fourth in cancer incidence with 11 percent of the total cancer incidence in Korea. To deal with such issues, there is an active study on the usefulness and utilization of the Clinical Decision Support System (CDSS) which utilizes machine learning. Thus, this study reviews existing studies on artificial intelligence technology that can be used in determining the lung cancer, and conducted a study on the applicability of machine learning in determination of the lung cancer by comparison and analysis using Azure ML provided by Microsoft. The results of this study show different predictions yielded by three algorithms: Support Vector Machine (SVM), Two-Class Support Decision Jungle and Multiclass Decision Jungle. This study has its limitations in the size of the Big data used in Machine Learning. Although the data provided by Kaggle is the most suitable one for this study, it is assumed that there is a limit in learning the data fully due to the lack of absolute figures. Therefore, it is claimed that if the agency's cooperation in the subsequent research is used to compare and analyze various kinds of algorithms other than those used in this study, a more accurate screening machine for lung cancer could be created.

• Annual Conference of KIPS
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• 2019.10a
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• pp.354-357
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• 2019

최근 맞벌이 가정이 많아지면서 베이비 시터를 고용해 영아를 양육하는 경우가 많아지고 있는 추세이다. 본 논문에서는 영유아 상태분석에 따른 인공지능 베이비시터 시스템에 대하여 기술하였다. 보다 상세하게는 얼굴인식을 위한 Opencv 영상처리 기법, MS(azure)API 를 이용한 머신러닝 기반의 감정분석과 악취 센서(MQ-135 Sensor)를 이용하여 영유아의 상태를 파악한다. 파악한 영유아의 상태를 바탕으로 스스로 학습하여 요람을 제어하고 어플리케이션을 통해 원격제어를 할 수 있도록 제작한 스마트 베이비시터 시스템에 관한 것이다. 이에 따라 양육에 대한 부담감이 줄어들 것으로 기대하고 양육에 대한 부담감을 조금이나마 경감 시켜 주어 저출산과 양육 지출 비용 절약으로 사회적 측면, 경제적 측면 모두에 기여할 것을 기대한다.