• 한국컴퓨터정보학회논문지
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• 제23권1호
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• pp.111-116
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• 2018

Recently, IoT and Big Data dealing with voluminous and complex sensitive information is one of the key issues in the era of the 4th industrial revolution. There have been a lot of studies to store the collected and processed sensitive information safely in storage data. Especially biometric information, if it is leaked and becomes identity theft, is hard to be corrected and results in serious event. To fix the problem, methods such as FIDO or KFTC have been proposed. In this paper, we propose a modified method of TTAK.KO-12.0098 according to the environment of this paper and propose a method of safely storing the generated disposable template in a block chain. We show that our method is better by comparing the existing method and the security analysis.

• 천문학회보
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• 제44권1호
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• pp.79.1-79.1
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• 2019

We present an algorithm for the fast computation of the general N-point spatial correlation functions of any discrete point set embedded within an Euclidean space of ${\mathbb{R}}n$. Utilizing the concepts of kd-trees and graph databases, we describe how to count all possible N-tuples in binned configurations within a given length scale, e.g. all pairs of points or all triplets of points with side lengths < rmax. Through benchmarking we show the computational advantage of our new graph-based algorithm over more traditional methods. We show that all 3-point configurations up to and beyond the Baryon Acoustic Oscillation scale (~200 Mpc in physical units) can be performed on current Sloan Digital Sky Survey (SDSS) data in reasonable time. Finally we present the first measurements of the 4-point correlation function of ~0.5 million SDSS galaxies over the redshift range 0.43< z <0.7. We present the publicly available code GRAMSCI (GRAph Made Statistics for Cosmological Information; bitbucket.org/csabiu/gramsci), under a GNU General Public License.

• Communications for Statistical Applications and Methods
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• 제28권3호
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• pp.267-279
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• 2021

A regression with multi-dimensional responses is quite common nowadays in the so-called big data era. In such regression, to relieve the curse of dimension due to high-dimension of responses, the dimension reduction of predictors is essential in analysis. Sufficient dimension reduction provides effective tools for the reduction, but there are few sufficient dimension reduction methodologies for multivariate regression. To fill this gap, we newly propose two fused slice-based inverse regression methods. The proposed approaches are robust to the numbers of clusters or slices and improve the estimation results over existing methods by fusing many kernel matrices. Numerical studies are presented and are compared with existing methods. Real data analysis confirms practical usefulness of the proposed methods.

• International Journal of Computer Science & Network Security
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• 제24권4호
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• pp.1-10
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• 2024

In the era of big data, the growth of e-commerce transactions brings forth both opportunities and risks, including the threat of data theft and fraud. To address these challenges, an automated real-time fraud detection system leveraging machine learning was developed. Four algorithms (Decision Tree, Naïve Bayes, XGBoost, and Neural Network) underwent comparison using a dataset from a clothing website that encompassed both legitimate and fraudulent transactions. The dataset exhibited an imbalance, with 9.3% representing fraud and 90.07% legitimate transactions. Performance evaluation metrics, including Recall, Precision, F1 Score, and AUC ROC, were employed to assess the effectiveness of each algorithm. XGBoost emerged as the top-performing model, achieving an impressive accuracy score of 95.85%. The proposed system proves to be a robust defense mechanism against fraudulent activities in e-commerce, thereby enhancing security and instilling trust in online transactions.

• 한국주거학회논문집
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• 제17권1호
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• pp.59-66
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• 2006

The purpose of this study was analyzing the Transforming Characteristics of the Entrance of Privately-built Apartment housing in Daegu from the 1970s to the 2000s. First of all, this study made an investigation into the general situation of Privately-built Apartment housing and the general idea of the Entrance. Through a field study, This study was analyzing change of an era of entrance of Apartment housing till quite recently existing in Daegu. The results are as the body III follows. Results of the research through change of an era is as follows. The change tendency is not to be big before 2003, but It has under gone change after 2003. Studies show that It is the care for the old and the weak, to take interest in natural lighting, to be going to change from passing the time of space to staying space and more space, to show interest in the preservation of public peace and design. So, The Entrance of Apartment housing has a bias towards more elegant. This research look forward to having an intention of furnishing preliminary data for a residence environment of high quality.

• 한국게임학회 논문지
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• 제20권2호
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• pp.113-122
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• 2020

2016년~2019년까지 지능정보기술 관련 콘텐츠 연구를 메타분석한 결과, 관련 기술이 사회적 화두로 부상한 이후 연구가 유의미하게 증가하였으며, 세부 기술과 관련해서는 가상현실 및 증강현실 기술에 대한 관심이 가장 높았다. 특정한 하나의 기술을 넘어 여러 지능정보기술이 콘텐츠와 어떻게 관련되는지가 탐구되는 경향이었다. 게임의 경우 VR 및 AR기술과 관련하여 연구가 많이 이루어졌고, 빅데이터 기술의 경우 영화 콘텐츠 연구에서 주목하는 경향이었다. 지능정보기술에 대한 기술적 접근을 시도한 연구가 많은 편이었으나, 인공지능 기술과 관련해서는 법적, 제도적으로 주로 조망되는 등 기술별, 콘텐츠 분야별로 차이가 나타났다.

• 한국수학사학회지
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• 제30권6호
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• pp.341-351
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• 2017

In the 21st century, the era of artificial intelligence, it is demanded to make a change of the paradigm of education by the recent impact of the 4th industrial revolution. The education up to now has emphasized knowledge, meanwhile the human resources for the future are required to be armed with four C's: critical thinking, creativity, communication and collaboration capability, rather than being equipped with just knowledge. That is because the future society demands such abilities, especially the creativity of each individual. At this point, we are asked to consider the aim of education and teaching methods. In school education, students are to be respected and considered able to develop their potentials by themselves. They shouldn't be estimated by tests in the process of learning as they are now. We reconsider the aim of education here by taking a look at Whitehead's opinions and the present educational situations.

• 한국컴퓨터정보학회논문지
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• 제26권3호
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• pp.29-34
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• 2021

4차 산업혁명 시대의 도래와 함께 IT기술은 기존의 다양한 산업과 분야에 융합되어 기존에 없던 새로운 서비스들을 만들어내고 있다. 특히 인공지능 분야의 챗봇과 최신 기술은 자연어처리 기술의 발전과 함께 그 성능이 비약적으로 발전하여 다양한 업무처리를 챗봇을 통해 처리하고 있다. 본 연구는 슬롯필링(Slot Filling) 기반의 챗봇 기술을 통해서 법률 질의에 대한 구조적인 폼(Structual Form)을 만들고 정해진 형태의 질문을 입력하여 사용자가 찾고자 하는 질문에 근접한 답변을 제공하는 시스템에 대한 연구이다. 제안 시스템을 이용하여 텍스트 형태의 비정형 데이터인 법률 정보를 보다 구조화된 형태로 질의응답 데이터를 구축할 수 있다. 또 축적된 질의응답 데이터를 하이브(Apache Hive)와 같은 빅데이터 저장 시스템을 통해 관리하여 학습에 데이터를 재활용하는 것으로 응답의 신뢰성을 지속적 향상을 기대할 수 있다.

• 한국전자거래학회지
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• 제27권2호
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• pp.1-20
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• 2022

4차 산업혁명으로 글로벌 비즈니스 환경이 빠르게 변화함에 따라 기존에는 없던 새로운 직종들이 등장하고 있다. 새롭게 등장한 직종 중에 최근에 기업들이 가장 많은 관심을 가지고 있는 직종은 '데이터 과학자 (Data Scientist)'일 것이다. 인터넷과 같은 정보통신 기술이 우리들의 생활에서 차지하는 비중이 커지면서 온라인에서의 활동 뿐만 아니라 오프라인 상에서의 활동에 대한 데이터가 매시간 컴퓨터에 저장되어 빅데이터를 생성하고 있다. 기업들은 이런 빅데이터로부터 새로운 기회를 창출하기 위하여 많은 노력을 기울이고 있다. 이런 기업의 노력과 함께 새롭게 등장한 직종이 바로 '데이터 과학자'이다. 빅데이터 시대를 이끌어갈 유망 직업인 데이터 과학자에 대한 수요는 끊임없이 증가되고 있지만 공급은 여전히 부족한 현황이다. 분석과 관련된 기술과 도구들이 새롭게 개발되고 있음에도 불구하고 기업은 여전히 이러한 기술을 목적에 맞게 활용할 수 있는 전문가를 찾는데 있어서 많은 어려움을 겪고 있다. 데이터 과학자 부족 문제를 심각하게 만드는 주요 이유 중 하나는 데이터 과학자 직무에 대한 이해가 부족하다는 점에서 찾을 수 있을 것이다. 이에 본 연구에서는 기업에서 필요로 하는 데이터 과학자의 역량을 기업의 실제 채용정보를 정성적으로 분석하여 보았다. 연구 결과, 과거 소프트웨어 엔지니어나 시스템 분석가들에게 요구되었던 Technical Skill과 System Skill 뿐만 아니라 비즈니스 컨설턴트나 Project Manager에게 요구되었던 비즈니스 관련 스킬이나 효율적인 팀워크를 위한 대인관련 스킬도 광범위하게 요구됨을 발견하였다. 본 연구결과를 통하여 데이터 과학자란 직업에 관심을 가지고 있는 사람들과 데이터 과학자를 채용하기를 원하는 기업에게 가이드라인을 제공하여 줄 것으로 기대하고 있다.

• 전자통신동향분석
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• 제34권5호
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• pp.14-25
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• 2019

As the Internet of Things, artificial intelligence and big data have received a lot of attention as key growth engines in the era of the fourth industrial revolution, data acquisition and utilization in mobile, automotive, robotics, manufacturing, agriculture, health care and national defense are becoming more important. Due to numerous data-based industrial changes, demand for sensor technologies is exploding, especially for intelligent sensor technologies that combine control, judgement, storage and communication functions with the sensors's own functions. Intelligent sensor technology can be defined as a convergence component technology that combines intelligent sensor units, intelligent algorithms, modules with signal processing circuits, and integrated plaform technologies. Intelligent sensor technology, which can be applied to variety of smart IT convergence services such as smart devices, smart homes, smart cars, smart factory, smart cities, and others, is evolving towards intelligent and convergence technologies that produce new high-value information through recognition, reasoning, and judgement based on artificial intelligence. As a result, development of intelligent sensor units is accelerating with strategies for miniaturization, low-power consumption and convergence, new form factor such as flexible and stretchable form, and integration of high-resolution sensor arrays. In the future, these intelligent sensor technologies will lead explosive sensor industries in the era of data-based artificial intelligence and will greatly contribute to enhancing nation's competitiveness in the global sensor market. In this report, we analyze and summarize the recent trends in intelligent sensor technologies, especially those for four core technologies.