• 스마트미디어저널
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• 제13권6호
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• pp.24-34
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• 2024

시계열인 네트워크 트래픽 데이터로부터 미래를 예측할 수 있다면 효율적인 자원 배분, 악성 공격에 대한 예방, 에너지 절감 등의 효과를 거둘 수 있다. 통계 기법과 딥러닝 기법에 기반한 많은 모델이 제안되었는데, 이들 연구 대부분은 모델 구조와 학습 알고리즘을 개선하는 일에 치중하였다. 모델의 예측 성능을 높이는 또 다른 접근방법은 우수한 데이터를 확보하는 것이다. 이 논문은 우수한 데이터를 확보할 목적으로, 시계열 데이터를 증강하는 밀집 샘플링 기법을 네트워크 트래픽 예측 응용에 적용하고 성능 향상을 분석한다. 데이터셋으로는 네트워크 트래픽 분석에 널리 사용되는 UNSW-NB15를 사용한다. RMSE와 MAE, MAPE를 사용하여 성능을 분석한다. 성능 측정의 객관성을 높이기 위해 10번 실험을 수행하고 기존 희소 샘플링과 밀집 샘플링의 성능을 박스플롯으로 비교한다. 윈도우 크기와 수평선 계수를 변화시키며 성능을 비교한 결과 밀집 샘플링이 일관적으로 우수한 성능을 보였다.

• 한국건축시공학회지
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• 제20권1호
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• pp.35-41
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• 2020

외단열 마감 공법에서 사용되는 얇은 바름재는 아크릴 에멀젼을 주 소재로 한 마감재이다. 본 연구에서는 실란 개질 아크릴 에멀젼과 실리카 분산아크릴 에멀젼을 치환하였을때 특성을 평가하였다. 실험결과, 실란 개질 아크릴 에멀젼은 인장강도 개선에는 큰 효과는 없었으나 부착강도, 물흡수계수, 온냉반복저항성의 성능 개선에 효과적인 것으로 나타났다. 실리카 분산 아크릴 에멀젼은 인장강도 개선에 효과적이며, 10%의 치환율에서는 부착강도, 물흡수계수, 온냉반복저항성의 성능 개선에 효과적인 것으로 나타났다. 이를 통해 아크릴 에멀젼의 성능을 향상할 수 있는 복합 에멀젼을 제조할 수 있는 것으로 판단되었다.

• 한국환경복원기술학회지
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• 제23권5호
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• pp.1-14
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• 2020

In order to improve the urban thermal environment, efforts are being made to increase green areas in cities that include park construction, planting, and green roofing. Among these efforts, urban parks play an important role not only in improving the urban thermal environment, but also in terms of ecosystem services (serving as resting places for citizens, providing cleaner air quality, reducing noise, etc.). Therefore, the purpose of this study is to suggest planning and management guidelines for urban parks that are effective in improving the thermal environment, by analyzing the urban surface temperature reduction performance of urban parks. To do this, first, land surface temperature was calculated by using Landsat 8 images. Second, the PCI (Park Cool Island) index was calculated to identify the temperature reduction performance of urban parks. Third, the characteristics of parks (area, shape, vegetation) and the surrounding spatial characteristics (land cover, building-related variables, etc.) were identified. Finally, the relationship between the PCI indices (PCI scale, PCI effect, PCI intensity) and the characteristics of the parks and their surroundings were analyzed. The results revealed that the parks consisting of a larger area, simple shape, and higher tree coverage ratio had increased PCI performance, and were advantageous for improving the urban thermal environment. Meanwhile, PCI performance was found to have decreased in areas with a higher impermeable area ratio and building coverage ratio. The outcomes of this study can be used to identify priority areas for planning and management of urban parks and can also be utilized as planning and management guidelines for improving urban thermal environment.

• 한국항공우주학회지
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• 제46권8호
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• pp.662-670
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• 2018

고도보정 노즐은 모든 고도에서 최적의 성능을 발휘할 수 있도록 고안된 노즐이다. 발사체의 비추력을 향상시키기 위한 방법으로는 연소실만의 특성인 특성배기속도를 향상시키는 방법과 노즐만의 특성인 추력계수를 향상시키는 방법이 있다. 고도보정 노즐은 동일한 연소기에서 노즐의 성능 개선을 통해 발사체의 성능향상을 가능하게 한다. 고도보정 노즐에 대한 연구는 독일 DLR에서 활발하게 진행되고 있으며, 미국, 러시아, 영국, 호주, 일본 등 항공우주선진국에서도 진행되고 있다. 본 논문에서는 고도보정 노즐에 대한 기술 현황 및 특허 동향에 대해 조사하였다. 이를 바탕으로 고도보정 노즐의 기술흐름을 파악하고 발사체 성능향상 연구에 기초자료로 활용하고자 한다.

• 한국전기전자재료학회논문지
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• 제37권3호
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• pp.261-273
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• 2024

This paper is an experimental study on the improvement of smoke and flame detection from different materials with YOLO. For the study, images of fires occurring in various materials were collected through an open dataset, and experiments were conducted by changing the main factors affecting the performance of the fire object detection model, such as the bounding box, polygon, and data augmentation of the collected image open dataset during data preprocessing. To evaluate the model performance, we calculated the values of precision, recall, F1Score, mAP, and FPS for each condition, and compared the performance of each model based on these values. We also analyzed the changes in model performance due to the data preprocessing method to derive the conditions that have the greatest impact on improving the performance of the fire object detection model. The experimental results showed that for the fire object detection model using the YOLOv5s6.0 model, data augmentation that can change the color of the flame, such as saturation, brightness, and exposure, is most effective in improving the performance of the fire object detection model. The real-time fire object detection model developed in this study can be applied to equipment such as existing CCTV, and it is believed that it can contribute to minimizing fire damage by enabling early detection of fires occurring in various materials.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제3권5호
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• pp.461-474
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• 2009

The cognitive radio (CR) technique is a useful tool for improving spectrum utilization by detecting and using the vacant spectrum bands in which cooperative spectrum sensing is a key element, while avoiding interfering with the primary user. In this paper, we propose a novel cluster-based cooperative spectrum sensing scheme in cognitive radio with two solutions for the purpose of improving in sensing performance. First, for the cluster header, we use the double adaptive energy thresholds and a multi-bit quantization with different quantization interval for improving the cluster performance. Second, in the common receiver, the weighed HALF-voting rule will be applied to achieve a better combination of all cluster decisions into a global decision.

• 유통과학연구
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• 제21권4호
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• pp.57-67
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• 2023

Purpose: This study aims to measuring the employee performance distributions of company in using relationship analysis between motivation, organization learning, compensation, and Organizational commitment. Research design and methodology: The study was conducted on 102 employees as a sample. Data were analyzed using Path Analysis in Structural Equation Modeling (SEM) with PLS. Results: the research result has shown that motivation and compensation have a positive significant effect on organizational commitment. While organizational learning has negative and insignificant effect on organizational commitment. Furthermore, motivation, organizational learning and motivation have no significant effect on employee performance distribution and organizational commitment has a positive significant effect on employee performance distribution. Results for mediating effect has obtained where organizational commitment mediates the effect of motivation and compensation on employee performance distribution, but cannot mediate the effect of organizational learning on employee performance distribution. Conclusion: Organizational commitment in this study can make employees feel comfortable and attached to the company so that employees can perform well to achieve company goals. Motivation and compensation are driving factors in improving employee performance distribution and will achieved if employees have good organizational commitment. In this study, organizational learning is not an important factor in improving employee performance distribution.

• 기술혁신학회지
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• 제1권3호
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• pp.299-312
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• 1998

This paper explores the possibility of improving R&D management system through researchers' satisfaction analysis. The relationship between job satisfaction and performance has traditionally been one of the engaging topics in organization psychology. However, the research results of the past showed the relatively low level of correlation between satisfaction and performance at the individual level. In contrast to these past research results, recent research results on this relationship at the organizational level revealed the higher correlation between these two factors, The present study extends this 'satisfaction and performance' hypothesis to the development and improvement of R&D management system. That is, we used the results of researchers' satisfaction analysis to devise appropriate criteria for the design and implementation of more effective R&D management systems. This paper seeks to show that we can make fruitful use of researchers' satisfaction analysis in order to choose a more effective one among alternative R&D management systems.

• ETRI Journal
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• 제45권1호
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• pp.60-74
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• 2023

Integration of the machine learning (ML) technique in all-optical networks can enhance the effectiveness of resource utilization, quality of service assurances, and scalability in optical networks. All-optical multistage interconnection networks (MINs) are implicitly designed to withstand the increasing highvolume traffic demands at data centers. However, the contention resolution mechanism in MINs becomes a bottleneck in handling such data traffic. In this paper, a select list of ML algorithms replaces the traditional electronic signal processing methods used to resolve contention in MIN. The suitability of these algorithms in improving the performance of the entire network is assessed in terms of injection rate, average latency, and latency distribution. Our findings showed that the ML module is recommended for improving the performance of the network. The improved performance and traffic grooming capabilities of the module are also validated by using a hardware testbed.

• 품질경영학회지
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• 제37권1호
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• pp.69-79
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• 2009

Supply Chain Management is the process of planning, implementing and controlling the operations of the supply chain to satisfy customer requirements as efficiently as possible. It spans all movements and storage of raw materials, work-in-process inventory, and finished goods from point-of-origin to point-of-consumption. Korean Standards Association claims the Supply Chain Quality Management(SCQM) as a win-win model of organizations among the supply chains for the best product/service quality to final customers. The SCQM is focused on quality of product/service and will do much for improving manufacturing performance between customer and suppliers. Consulting-teams make every effort to design suitable solution for constructing solutions and improving the performance. This study is to analyze the performance of SCQM consulting, from July of 2007 to June of 2008, and would provide some guidelines to design the optimal consulting models and develop guidebooks.