• 대한임베디드공학회논문지
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• 제17권4호
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• pp.249-255
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• 2022

The COVID-19 virus appeared in 2019 and is extremely contagious. Because it is very infectious and has a huge impact on people's mobility. In this paper, multiple linear regression and random forest models are used to predict the number of COVID-19 cases using COVID-19 infection status data (open source data provided by the Ministry of health and welfare) and Google Mobility Data, which can check the liquidity of various categories. The data has been divided into two sets. The first dataset is COVID-19 infection status data and all six variables of Google Mobility Data. The second dataset is COVID-19 infection status data and only two variables of Google Mobility Data: (1) Retail stores and leisure facilities (2) Grocery stores and pharmacies. The models' performance has been compared using the mean absolute error indicator. We also a correlation analysis of the random forest model and the multiple linear regression model.

• Geomechanics and Engineering
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• 제13권5호
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• pp.861-879
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• 2017

Coal and gas outburst is a serious dynamic disaster that occurs during coal mining and threatens the lives of coal miners. Currently, coal and gas outburst is commonly predicted using single indicator and its critical value. However, single indicator is unable to fully reflect all of the factors impacting outburst risk and has poor prediction accuracy. Therefore, a more accurate prediction method is necessary. In this work, we first analyzed on-site impacting factors and precursors of coal and gas outburst; then, we constructed a Fisher discriminant analysis (FDA) index system using the gas adsorption index of drilling cutting ${\Delta}h_2$, the drilling cutting weight S, the initial velocity of gas emission from borehole q, the thickness of soft coal h, and the maximum ratio of post-blasting gas emission peak to pre-blasting gas emission $B_{max}$; finally, we studied an FDA-based multiple indicators discriminant model of coal and gas outburst, and applied the discriminant model to predict coal and gas outburst. The results showed that the discriminant model has 100% prediction accuracy, even when some conventional indexes are lower than the warning criteria. The FDA method has a broad application prospects in coal and gas outburst prediction.

• 한국지구과학회지
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• 제23권1호
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• pp.15-29
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• 2002

Bayesian inversion for gravity and resistivity data was performed to investigate the cavity structure appearing as a lava tunnel in Cheju Island, Korea. Dipole-dipole DC resistivity data were proposed for a prior information of gravity data and we applied the geostatistical techniques such as kriging and simulation algorithms to provide a prior model information and covariance matrix in data domain. The inverted resistivity section gave the indicator variogram modeling for each threshold and it provided spatial uncertainty to give a prior PDF by sequential indicator simulations. We also presented a more objective way to make data covariance matrix that reflects the state of the achieved field data by geostatistical technique, cross-validation. Then Gaussian approximation was adopted for the inference of characteristics of the marginal distributions of model parameters and Broyden update for simple calculation of sensitivity matrix and SVD was applied. Generally cavity investigation by geophysical exploration is difficult and success is hard to be achieved. However, this exotic multiple interpretations showed remarkable improvement and stability for interpretation when compared to data-fit alone results, and suggested the possibility of diverse application for Bayesian inversion in geophysical inverse problem.

• 정보처리학회논문지:소프트웨어 및 데이터공학
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• 제7권9호
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• pp.351-360
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• 2018

전통적으로 나태한 학습에 해당하는 국소가중회귀(LWR: Locally Weighted Regression)모델은 입력변수인 질의지점에 따라 예측의 해를 얻기 위해 일정구간 범위내의 학습 데이터를 대상으로 질의지점의 거리에 따라 가중값을 달리 부여하여 학습 한 결과로 얻은 짧은 구간내의 회귀식이다. 본 연구는 메모리 기반학습의 형태에 해당하는 LWR을 위한 점진적 앙상블 학습과정을 제안한다. LWR를 위한 본 연구의 점진적 앙상블 학습법은 유전알고리즘을 이용하여 시간에 따라 LWR모델들을 순차적으로 생성하고 통합하는 것이다. 기존의 LWR 한계는 인디케이터 함수와 학습 데이터의 선택에 따라 다중의 LWR모델이 생성될 수 있으며 이 모델에 따라 예측 해의 질도 달라질 수 있다. 하지만 다중의 LWR 모델의 선택이나 결합의 문제 해결을 위한 연구가 수행되지 않았다. 본 연구에서는 인디케이터 함수와 학습 데이터에 따라 초기 LWR 모델을 생성한 후 진화 학습 과정을 반복하여 적절한 인디케이터 함수를 선택하며 또한 다른 학습 데이터에 적용한 LWR 모델의 평가와 개선을 통하여 학습 데이터로 인한 편향을 극복하고자 한다. 모든 구간에 대해 데이터가 발생 되면 점진적으로 LWR모델을 생성하여 보관하는 열심학습(Eager learning)방식을 취하고 있다. 특정 시점에 예측의 해를 얻기 위해 일정구간 내에 신규로 발생된 데이터들을 기반으로 LWR모델을 생성한 후 유전자 알고리즘을 이용하여 구간 내의 기존 LWR모델들과 결합하는 방식이다. 제안하는 학습방법은 기존 단순평균법을 이용한 다중 LWR모델들의 선택방법 보다 적합도 평가에서 우수한 결과를 보여주고 있다. 특정지역의 시간 별 교통량, 고속도로 휴게소의 시간별 매출액 등의 실제 데이터를 적용하여 본 연구의 LWR에 의한 결과들의 연결된 패턴과 다중회귀분석을 이용한 예측결과를 비교하고 있다.

• 한국통신학회논문지
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• 제41권7호
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• pp.723-731
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• 2016

5G 이동무선통신에서 요구되는 증가된 데이터 속도를 제공하기 위한 핵심적인 기술 축은 대규모 어레이를 활용하는 MIMO 전송을 통한 주파수 효율의 향상이다. MIMO 전송을 위해서는 CSI-RS (channel state information-reference signaling)를 이용하는 채널 추정 및 추정 결과에 적합한 빔포밍이 필요하며, 따라서 빔포밍 벡터를 정의하는 코드북의 설계는 매우 중요한 이슈이다. 본 논문에서는 공간채널모델을 이용하여 생성된 채널의 통계적인 특성을 활용하여 DFT (discrete Fourier transform) 행렬 기반 다중 랭크 코드북의 설계 방안을 제안하였다. 제안 방식은 인접한 안테나 원소 간 위상차의 분포와 전송 레이어 별 선택되는 코드벡터의 특징을 고려하여 PMI (precoding matrix indicator)의 구조 변경을 하였으며, LTE (long-term evolution) 시스템에서 사용 중인 3GPP 표준 코드북과의 성능 비교를 통하여 제안 방식의 이득을 산출하고 검증하였다.

• Journal of Information Technology Applications and Management
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• 제27권3호
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• pp.37-54
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• 2020

In response to the recent decline in the school-age population, universities have made attracting foreign students a major policy task for universities. As a result, the number of foreign students increased rapidly in terms of quantity, but in terms of quality, the risk is inevitable. Accordingly, the government presented education and internationalization competency certification system indicators on the basis of which quality control of students was systematized. Based on the above certification system, this study focused on analyzing the multiple factors that are actually given to the academic adaptation (performance) of the 2200 students who entered a certain university. In addition, factors other than the certification system index were discovered to comprehensively track how they affect the academic performance of students studying abroad. The researcher found the multi-reciprocal model analysis showed that the difference between the learner and the moderator was significant, and whether or not they had the Korean proficiency test (TOPIK) was significant. It also said that it could have a direct impact on Chinese University Entrance Exams (高考) are significant. If a model that is very effective in selecting students is established by each university and used as an indicator through this study, it will serve as a basis for efficient selection of students.

• 센서학회지
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• 제25권6호
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• pp.394-398
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• 2016

In this paper, a fire detection system based on quantitative risk estimation is presented. Multiple sensors are used to build a comprehensive indicator that represents the risk of fire quantitatively. The proposed fire risk estimation method consists of two stages which determines the occurrence of fire and estimates the toxicity of the surveillance area. In the first stage, fire is reliably detected under diverse fire scenarios. The risk of fire is estimated in the second stage. Applying Purser's Fractional Effective Dose (FED) model which quantitates harmfulness of toxic gases, the risk of the surveillance area and evacuation time are calculated. A fire experiment conducted using four different types of combustion materials for the verification of the system resulted in a maximum error rate of 12.5%. By using FED calculation and risk estimation methods, the proposed system can detect various signs of fire faster than conventional systems.

• 한국수학교육학회지시리즈D:수학교육연구
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• 제27권1호
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• pp.129-150
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• 2024

This study utilized South Korean elementary and middle school student data to examine the longitudinal change trajectories of learning motivation types according to the longitudinal change trajectories of mathematics academic achievement. Growth mixture modeling, latent growth model, and multiple indicator latent growth model were used to examine various change trajectories for longitudinal data. As a result of the analysis, it was classified into 4 subgroups with similar longitudinal change trajectories of mathematics academic achievement, and the characteristics of the mathematics subject, which emphasize systematicity, appeared. Furthermore, higher mathematics academic achievement was associated with higher self-determination and higher academic motivation. And as the grade level increases, amotivation increases and self-determination decreases. This study suggests that teaching and learning support using this is necessary because the level of learning motivation according to self-determination is different depending on the level of mathematics academic achievement reflecting the characteristics of the student.

• ETRI Journal
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• 제38권2호
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• pp.280-290
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• 2016

To implement high-order multiuser multiple input and multiple output (MU-MIMO) for massive MIMO systems, there must be a feedback scheme that can warrant its performance with a limited signaling overhead. The interference-to-noise ratio can be a basis for a novel form of Codebook (CB)-based MU-MIMO feedback scheme. The objective of this paper is to verify such a scheme's performance under a practical system configuration with a 3D channel model in various radio environments. We evaluate the performance of various CB-based feedback schemes with different types of overhead reduction approaches, providing an experimental ground with which to optimize a CB-based MU-MIMO feedback scheme while identifying the design constraints for a massive MIMO system.

• Asia pacific journal of information systems
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• 제23권1호
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• pp.65-86
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• 2013

Understanding success factors in electronic banking is important to helping banks succeed. In this study, we extend DeLone and McLean's IS success model to the electronic banking by adding trust as a success variable. We tested the extended model by comparing internet banking and mobile banking in Indonesia. Using a structural equation modelling approach. We found that system quality had positive impacts on perceived usefulness and end-user satisfaction for both internet banking and mobile banking. The development of e-banking (internet banking and mobile banking) in Indonesia is in its initial stage. Finally, although we tested for the common method bias to relieve concern, further research may use multiple methods when collecting the data. This study investigated the role of each dimension of IS success in the electronic banking environment. While the original IS success model emphasizes individual and organizational impacts, we have argued that trust is an important indicator of IS impact on an individual socially in the banking industry. The contribution of our study is two-fold. Conceptually, the study is the first to extend the IS success model to the e-banking context. We provide an extension of the updated IS success model by adding trust as an outcome variable in the research model.