• 한국수소및신에너지학회논문집
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• 제22권4호
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• pp.534-545
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• 2011

This paper describes the evaluation of kinetic parameters for pyrolysis and carbon char oxidation of residual oil. The non-isothermal pyrolysis of residual oil was carried out with TGA (Thermo-Gravimetric Analyzer) at heating rate of 2, 5, 10 and $20^{\circ}C/min$ up to $800^{\circ}C$ under N2 atmosphere. The first order and nth order pyrolysis models were used to fit the experimental data, and the nth order model was turned out to follow the experimental data more precisely than the first order model. For carbon char oxidation experiment, TGA and four heating rates used in pyrolysis experiment were also adapted. The kinetic parameters for the residual carbon char particle were obtained with three char oxidation model, that is, volume reaction, grain and random pore model. Among them, the random pore model described the char oxidation behaviour quite well, compared to other two models. The non-linear regression method was used to obtain kinetic parameters for both pyrolysis and carbon char oxidation of residual oil.

• 해양환경안전학회지
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• 제25권2호
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• pp.244-250
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• 2019

엽상형 해조류의 간접적인 건중량 추정을 위해 구멍갈파래(Ulva australis), 잎파래(Ulva linza), 개도박(Pachymeniopsis lanceolata), 방사무늬김(Pyropia yezoensis)의 형태적 특성과 생체량의 관계를 분석하였다. 시료는 2017년 2월부터 2018년 12월 까지 남해안 6곳에서 채집되었으며, 총 319개체가 분석에 사용되었다. 엽상형 해조류 네 종의 길이와 생체량에 대한 상대성장 지수는 0.28로 일반적인 1/4 (0.25) 지수법칙에 해당하였다. 네 종의 엽체의 표면적과 습중량은 각각 건중량과 유의한 선형관계를 보였으며, 건중량의 94 ~ 99%를 설명할 수 있었다. 이 결과는 엽상형 해조류의 표면적 또는 습중량을 통해 개체의 건중량을 매우 정확하게 추정할 수 있다는 것을 의미한다. 이 방법론은 실험실 연구에서 건중량을 직접 측정할 수 없을 때 쉽고 빠르게 활용할 수 있으며, 추가적으로 소요되는 시간과 비용을 절약할 수 있을 것이다.

• 지역사회간호학회지
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• 제30권2호
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• pp.206-216
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• 2019

Purpose: This study is to investigate the low back pain, social support, impediment in daily living activities and to identify factors affecting impediment in elderly farmer' daily living activities. Methods: The participants were 128 elderly farmers who had received nerve block. Data were collected using a structured questionnaire from February to March, 2018. They were analyzed using t-test, ANOVA, pearson's correlation coefficient, and linear multiple regression. Results: The score of low back pain was $6.27{\pm}1.69$ (10 points), that of social support $2.92{\pm}0.76$ (1~5 points), and that of impediment in activity of daily living $2.01{\pm}0.82$ (0~5 points). Factors affecting impediment in activity of daily living were found to include age (p=.017), daily hours of farm work (p<.001), fear for the nerve block (p<.001), low back pain (p<.001), and social support (p<.001); the explanatory power of these variables was 58.8%. Conclusion: This study has found the controllable factors affecting impediment in activity of daily living among the rural elderly engaging in farm work include low back pain, social support, and daily farming hours. Therefore, to reduce impediment in activity of daily living among them, it is necessary to develop nursing interventions that can improve impediment in activity of daily living through reduction of daily farming hours using local resources. It is also desirable to improve their health status by reducing low back pain, and develop and apply social supports with health education programs that fit the local resources and the needs of the rural elderly.

• Journal of Astronomy and Space Sciences
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• 제39권2호
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• pp.43-50
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• 2022

The unified scheme of Seyfert galaxies hypothesizes that the observed differences between the two categories of Seyfert galaxies, type 1 (Sy1) and type 2 (Sy2) are merely due to the difference in the orientation of the toroidal shape of the obscuring material in the active galactic nuclei. We used in this paper, a sample consisting of 120 Seyfert galaxies at 1.40 × 10⁹ Hz in radio, 2.52 × 10¹⁷ Hz in X-ray and 2.52 × 10²³ Hz in γ-ray luminosities observed by the Fermi Large Area Telescope (Fermi-LAT) in order to test the unified scheme of radio-quiet Seyfert galaxies. Our main results are as follows: (i) We found that the distributions of multiwave luminosities (L_radio, L_X-ray, and L_γ-ray) of Sy1 and Sy2 are completely overlapped with up to a factor of 4. The principal component analysis result reveals that Sy1 and Sy2 also occupy the same parameter spaces, which agrees with the notion that Sy1 and Sy2 are the same class objects. A Kolmogorov-Smirnov test performed on the sub-samples indicates that the null hypothesis (both are from the same population) cannot be rejected with chance probability p ~ 0 and separation distance K = 0.013. This result supports the fact that there is no statistical difference between the properties of Sy1 and Sy2 (ii) We found that the coefficient of the best-fit linear regression equation between the common properties of Sy1 and Sy2 is significant (r > 0.50) which plausibly implies that Sy1 and Sy2 are the same type of objects observed at different viewing angle.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권6호
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• pp.1892-1912
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• 2022

With the massive demand and growth of cloud computing, virtualization plays an important role in providing services to end-users efficiently. However, with the increase in services over Cloud Computing, it is becoming more challenging to manage and run multiple Virtual Machines (VMs) in Cloud Computing because of excessive power consumption. It is thus important to overcome these challenges by adopting an efficient technique to manage and monitor the status of VMs in a cloud environment. Reduction of power/energy consumption can be done by managing VMs more effectively in the datacenters of the cloud environment by switching between the active and inactive states of a VM. As a result, energy consumption reduces carbon emissions, leading to green cloud computing. The proposed Efficient Dynamic VM Scheduling approach minimizes Service Level Agreement (SLA) violations and manages VM migration by lowering the energy consumption effectively along with the balanced load. In the proposed work, VM Scheduling for Efficient Dynamically Migrated VM (VMS-EDMVM) approach first detects the over-utilized host using the Modified Weighted Linear Regression (MWLR) algorithm and along with the dynamic utilization model for an underutilized host. Maximum Power Reduction and Reduced Time (MPRRT) approach has been developed for the VM selection followed by a two-phase Best-Fit CPU, BW (BFCB) VM Scheduling mechanism which is simulated in CloudSim based on the adaptive utilization threshold base. The proposed work achieved a Power consumption of 108.45 kWh, and the total SLA violation was 0.1%. The VM migration count was reduced to 2,202 times, revealing better performance as compared to other methods mentioned in this paper.

• 인간식물환경학회지
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• 제24권6호
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• pp.629-638
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• 2021

Background and objective: This study was conducted to develop diameter growth models for thinned Quercus glauca Thunb. (QGT) stands to inform production goals for treatment and provide the information necessary for the systematic management of this stands. Methods: This study was conducted on QGT stands, of which initial thinning was completed in 2013 to develop a treatment system. To analyze the tree growth and trait response for each thinning treatment, forestry surveys were conducted in 2014 and 2021, and a one-way analysis of variance (ANOVA) was executed. In addition, non-linear least squares regression of the PROC NLIN procedure was used to develop an optimal diameter growth model. Results: Based on growth and trait analyses, the height and height-to-diameter (H/D) ratio were not different according to treatment plot (p > .05). For the diameter of basal height (DBH), the heavy thinning (HT) treatment plot was significantly larger than the control plot (p < .05). As a result of the development of diameter growth models by treatment plot, the mean squared error (MSE) of the Gompertz polymorphic equation (control: 2.2381, light thinning: 0.8478, and heavy thinning: 0.8679) was the lowest in all treatment plots, and the Shapiro-Wilk statistic was found to follow a normal distribution (p > .95), so it was selected as an equation fit for the diameter growth model. Conclusion: The findings of this study provide basic data for the systematic management of Quercus glauca Thunb. stands. It is necessary to construct permanent sample plots (PSP) that consider stand status, location conditions, and climatic environments.

• 한국인공지능학회지
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• 제11권4호
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• pp.9-13
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• 2023

In this study, we explored the potential of integrating interactive AI callbot technology into the medical consultation domain as part of a broader service development initiative. Aimed at enhancing patient satisfaction, the AI callbot was designed to efficiently address queries from hospitals' primary users, especially the elderly and those using phone services. By incorporating an AI-driven callbot into the hospital's customer service center, routine tasks such as appointment modifications and cancellations were efficiently managed by the AI Callbot Agent. On the other hand, tasks requiring more detailed attention or specialization were addressed by Human Agents, ensuring a balanced and collaborative approach. The deep learning model for voice recognition for this study was based on the Transformer model and fine-tuned to fit the medical field using a pre-trained model. Existing recording files were converted into learning data to perform SSL(self-supervised learning) Model was implemented. The ANN (Artificial neural network) neural network model was used to analyze voice signals and interpret them as text, and after actual application, the intent was enriched through reinforcement learning to continuously improve accuracy. In the case of TTS(Text To Speech), the Transformer model was applied to Text Analysis, Acoustic model, and Vocoder, and Google's Natural Language API was applied to recognize intent. As the research progresses, there are challenges to solve, such as interconnection issues between various EMR providers, problems with doctor's time slots, problems with two or more hospital appointments, and problems with patient use. However, there are specialized problems that are easy to make reservations. Implementation of the callbot service in hospitals appears to be applicable immediately.

• 기술혁신학회지
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• 제17권1호
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• pp.45-67
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• 2014

국가혁신역량은 경제성장의 중요한 결정요인으로 이에 대한 측정과 관리는 매우 중요하다. 국가혁신역량을 측정하는 다양한 접근방법 중 복합지표 접근법이 널리 활용되고 있지만, 그 타당성과 신뢰성에 대한 검토는 부족한 실정이다. 따라서 국가혁신역량을 측정하는 가장 대표적인 유럽연합 IUS(Innovation Union Scoreboard)의 최근 3개년 보고서('11년~'13년)를 중심으로 신뢰성과 타당성을 분석하였다. 분석결과 IUS 복합지표 측정모형의 크롬바흐(Chronbach's) ${\alpha}$ 검정 결과 신뢰도는 권고기준을 충족하였다. 하지만 구성타당도와 예측타당도를 분석한 결과, 구성타당도에서는 절대적합지수와 증분적합지수 모두 권고기준을 충족하지 못하였다. 또한 IUS 복합지표의 각 부문과 항목에 대한 패널선형회귀분석 결과, 예측타당도가 매우 낮게 나타났다. 이러한 분석결과를 토대로 복합지표 접근법으로 국가혁신역량을 측정할 때 고려사항과 주요 시사점을 제시하였다.

• 토지주택연구
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• 제12권2호
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• pp.47-59
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• 2021

본 연구에서는 부산시 지역들의 수도권으로 인구유출 현황을 파악하고, 인구·사회, 고용, 주택, 문화, 안전, 의료, 복지, 녹지, 교육 및 보육 등 전통적 인구이동 변수와 삶의 질 변수들을 포괄하여 수도권으로의 인구이동에 영향을 미치는 요인과 인과관계를 규명하고자 한다. 연구의 데이터 구축을 위하여 통계청 마이크로데이터통합서비스(MDIS)에서 제공하는 '국내 인구이동 데이터'를 사용하였으며, 시간적 범위에 맞는 인구이동 데이터(2012-2017년) 총 5,700만 건 가운데 부산시 지역별 유출량 중 수도권 이동량을 추출하였다. 각 독립변수들은 연구의 시간적 공간적 범위에 맞춰 공공데이터에서 추출하였다. 구축한 데이터 세트(Data Set)을 기반으로 선형 다중 회귀분석(Multiple Linear Regression Analysis) 모형을 사용하였으며, 수정 결정계수(Adjusted R2), Durbin-Watson분석, 검정통계량(F-statstics)의 p-value값으로 모형의 적합도를 측정하였다. 분석결과, 부산시에서 수도권으로 인구이동에 유의미한 영향을 미치는 변수는 1인가구 증가율, 고령인구 증가율, 고령자수 비율, 합계출산율, 사업체수 증가율과 종사자수 증가율, 주택매매가지수 증가율, 문화시설 증가율, 교원 1인당 학생수 증가율 변수로 나타났다. 1인가구가 증가하는 지역일수록, 지역의 고령자 비율이 낮을수록, 고령자 비율이 감소할수록, 사업체수가 감소할수록, 종사자수가 증가할수록, 주택매매가지수가 증가할수록, 문화시설수가 감소할수록, 학생수가 감소할수록 수도권 인구이동 비율에 정(+)의 영향을 미치는 것으로 나타났다. 분석 결과를 바탕으로 한 정책적 시사점으로 청년 계층을 부산시에 정착시키고 유인할 수 있는 양질의 일자리, 문화, 복지 등의 제반환경을 제공해야 할 것이다. 일자리와 삶의 질을 높이는 것이 부산시 인구를 수도권으로 유출시키는 현상을 완화할 수 있는 핵심 요인이라고 할 수 있다.

• 한국수자원학회논문집
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• 제55권10호
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• pp.723-736
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• 2022

본 연구에서는 금강권역을 대상으로 최대 12개월까지 선행예측이 가능한 월 강수량 예측모형을 구축하였으며, 예측모형 구축에는 다중회귀분석과 인공신경망의 두 가지 통계적 기법을 적용하였다. 예측인자 후보로 NOAA에서 제공하는 글로벌 기후패턴 39종과 금강권역에 대한 기상인자 8종 등 총 47종의 기후지수를 활용하였다. 예측대상월을 기준으로 과거 40년간의 월 강수량과 기후지수와의 지연상관성 분석을 통해 상관도가 높은 기후지수를 예측인자로 활용하여 다중회귀모형 및 인공신경망 모형을 구축하였다. 1991~2021년에 대해 매월 예측결과의 평균값과 관측값과의 적합도를 분석한 결과, 다중회귀모형은 PBIAS -3.3~-0.1%, NSE 0.45~0.50, r 0.69~0.70으로 분석되었으며, 인공신경망모형은 PBIAS -5.0~+0.5%, NSE 0.35~0.47, r 0.64~0.70로, 다중회귀모형에 의해 도출된 예측치의 평균값이 인공신경망모형보다 관측치에 좀 더 근접한 것으로 나타났다. 각 월의 예측범위 안에 관측치가 포함될 확률을 분석한 결과에서는 다중회귀모형이 57.5~83.6%(평균 72.9%), 인공신경망모형의 경우에는 71.5~88.7%(평균 81.1%)로 인공신경망모형 결과가 우수한 것으로 나타났다. 3분위 예측확률을 비교한 결과는 다중회귀모형의 경우에는 25.9~41.9%(평균 34.6%), 인공신경망모형은 30.3~39.1%(평균 34.7%)로 비슷하며, 두 모형 모두 평균 33.3% 이상으로 월 강수량에 대한 장기예측성을 확인 할 수 있었다. 이상과 같이 두 모형의 예측성 차이는 비교적 크지 않은 것으로 나타났으나, 예측범위에 대한 적중률이나 3분위 예측확률로부터 판단할 때 예측성에 대한 월별 편차는 인공신경망모형의 결과가 상대적으로 작게 나타났다.