• ETRI Journal
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• 제37권3호
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• pp.491-501
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• 2015

Spectrum sensing is an elementary function in cognitive radio designed to monitor the existence of a primary user (PU). To achieve a high rate of detection, most techniques rely on knowledge of prior spectrum patterns, with a trade-off between high computational complexity and long sensing time. On the other hand, blind techniques ignore pattern matching processes to reduce processing time, but their accuracy degrades greatly at low signal-to-noise ratios. To achieve both a high rate of detection and short sensing time, we propose fast spectrum sensing with coordinate system (FSC) - a novel technique that decomposes a spectrum with high complexity into a new coordinate system of salient features and that uses these features in its PU detection process. Not only is the space of a buffer that is used to store information about a PU reduced, but also the sensing process is fast. The performance of FSC is evaluated according to its accuracy and sensing time against six other well-known conventional techniques through a wireless microphone signal based on the IEEE 802.22 standard. FSC gives the best performance overall.

• 산업경영시스템학회지
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• 제43권2호
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• pp.120-125
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• 2020

Supply chain managers seek to achieve global optimization by solving problems in the supply chain's business process. However, companies in the supply chain hide the adverse information and inform only the beneficial information, so the information is distorted and cannot be the information that describes the entire supply chain. In this case, supply chain managers can directly collect and analyze supply chain activity data to find and manage the companies described by the data. Therefore, this study proposes a method to collect the order-inventory information from each company in the supply chain and detect the companies whose data characteristics are explained through deep learning. The supply chain consists of Manufacturer, Distributor, Wholesaler, Retailer, and training and testing data uses 600 weeks of time series inventory information. The purpose of the experiment is to improve the detection accuracy by adjusting the parameter values of the deep learning network, and the parameters for comparison are set by learning rate (lr = 0.001, 0.01, 0.1) and batch size (bs = 1, 5). Experimental results show that the detection accuracy is improved by adjusting the values of the parameters, but the values of the parameters depend on data and model characteristics.

• 대한안전경영과학회지
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• 제16권2호
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• pp.147-155
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• 2014

This paper suggests a specific model that could efficiently improve the interaction and the interface between WMS(Warehouse Management System) terminal and PDA terminal through real time processing in manufacturing shop. The proposed model shows that the new method can more efficiently perform to reduce processing time for shipping and receiving, compared with the current approach. As a result of the certain test among the main server, WMS system, and PDA terminal, it is noted in case of the new proposed system that the effects of proposed model are as follows: (a) While the receiving lead time for carrying by the current method was 2 hours, the receiving lead time by the new method was 20 minutes. (b) While the shipping lead time for carrying by the current method was 1 hours, the shipping lead time by the new method was 15 minutes. (c) While the inventory rate of accuracy by the current method was 85%, the inventory rate of accuracy by the new method was 98%.

• 한국자동차공학회논문집
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• 제21권2호
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• pp.98-103
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• 2013

Conventional method to estimate mass of particulate matter accumulated in diesel particulate filter is to use pressure difference between upstream and downstream of the filter. Then measured pressure difference should be compared that of clean condition which is no particulate matter accumulated in DPF. During regeneration soot oxidation is also estimated by same method. This methodology, however, has demerit on accuracy because of pressure difference deviation of clean DPFs and pressure difference caused by non-carbon based PM which is different from that of caused by carbon based PM. This study suggests new methodology to estimate accumulated soot oxidation rate through exhaust gas characteristics during regeneration. Results, more high accuracy of soot oxidation was obtained by analysis of relationship between fuel mass and concentration of carbon dioxide and oxygen.

• 한국정보과학회논문지:시스템및이론
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• 제26권7호
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• pp.788-812
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• 1999

본 논문에서는 범용 워크스테이션 환경하에서 수행되는 멀티미디어 응용프로그램(application)을 지원하기 위한 비례지분 방식의 CPU 스케줄러를 제시한다. 이러한 목적을 위하여 일반적 태스크의 지원을 위해 설계된 스트라이드 스케줄러를 확장한다. 멀티미디어 응용프로그램의 시간 요구사항을 명시하기 위하여 새로운 스케줄링 파라미터들을 도입한다. 비율조정기를 도입한 결과 스케줄링의 정확도의 오차는 O(1)로 감소하였다. 별도의 태스크 그룹을 설정하여 상대적 지분과 절대적 지분을 부여했다. 모의실험을 사용하여 스케줄러의 성능을 평가하였다. 그 결과, 제안된 스케줄러는 증가된 정확도와 적응성 및 유연성을 가짐을 알 수 있었다. Abstract This paper presents a proportional-share CPU scheduler which can support multimedia applications in a general-purpose workstation environment. For this purpose, we have extended the stride scheduler which is designed originally for conventional tasks. New scheduling parameters are introduced to specify timing requirements of multimedia applications. Through the use of the rate regulator, the accuracy error of the scheduling is reduced to O(1). Separate task groups are proposed to represent both relative shares and absolute shares. The proposed scheduler is evaluated using a simulation study. The results show that the proposed scheduler achieves improved accuracy and adaptability as well as flexibility.

• 설비공학논문집
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• 제25권9호
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• pp.493-498
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• 2013

The purpose of this study is to find the infiltration of detached houses, for energy consumption analyses. The pressurization and depressurization method is used to determine infiltration. Blower door tests are expressed in terms of ACH 50, which stands for the hourly air change rate at 50 Pa of fan pressure. The ACH 50 of existing Detached Houses ranges from 5 to 50. Air infiltration is related to construction year and accuracy, maintenance conditions, and so on. When estimating the infiltration of random detached houses, the year used can be the base value of the infiltration rate from 0.25 to 2.0 times/h. The maintenance conditions, construction accuracy and repair affect the air infiltration 0 to 0.5 times/h, 0 to 0.3 times/h, 0 to 1 times/h, respectively.

• 한국정보전자통신기술학회논문지
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• 제11권6호
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• pp.751-756
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• 2018

본 연구는 입력 영상에서 교통 신호등을 검출하고, 신호등의 색상을 인식하며, 신호를 판별하여 무인 자율주행 차량이나 ITS(Intelligent Transportation System)에 적용할 수 있는 신호등 색상 인식 알고리즘을 제안하였다. 제안된 알고리즘은 교통신호등을 검출하기 위해 CEA(Canny Edge Algorithm)를 이용하여 외곽선을 추출하였고, 신호등의 색상을 인식하고 정확도를 높이기 위하여 HCT(Hough Circle Transform)를 적용하였다. 제안된 방법으로 주행도로상에서 획득한 스트림 영상에 적용한 결과, 우수한 신호등 색상 인식률을 확인할 수 있었다. 특히 입력영상에서 신호등이 존재할만한 ROI(Region Of Interest)로 구분하여 연산시간을 줄일 수 있었고, 신호등과 유사한 영역이라도 원이 검출되지 않거나 HSV 공간에서 V값이 낮아 후보영역에서 탈락시킴으로써 인식률의 정확도를 높일 수 있었다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권11호
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• pp.4395-4412
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• 2020

The multisource image fusion has become an active topic in the last few years owing to its higher segmentation rate. To enhance the accuracy of multimodal pig-body feature segmentation, a multisource image fusion method was employed. Nevertheless, the conventional multisource image fusion methods can not extract superior contrast and abundant details of fused image. To superior segment shape feature and detect temperature feature, a new multisource image fusion method was presented and entitled as NSST-GF-IPCNN. Firstly, the multisource images were resolved into a range of multiscale and multidirectional subbands by Nonsubsampled Shearlet Transform (NSST). Then, to superior describe fine-scale texture and edge information, even-symmetrical Gabor filter and Improved Pulse Coupled Neural Network (IPCNN) were used to fuse low and high-frequency subbands, respectively. Next, the fused coefficients were reconstructed into a fusion image using inverse NSST. Finally, the shape feature was extracted using automatic threshold algorithm and optimized using morphological operation. Nevertheless, the highest temperature of pig-body was gained in view of segmentation results. Experiments revealed that the presented fusion algorithm was able to realize 2.102-4.066% higher average accuracy rate than the traditional algorithms and also enhanced efficiency.

• 한국인터넷방송통신학회논문지
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• 제22권5호
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• pp.171-176
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• 2022

최근 딥러닝 기술의 발전과 함께 추천 시스템의 영역도 다양해졌다. 본 논문은 학습률 향상을 위한 알고리즘을 연구하였으며 Word2Vec 모델의 성능 특징과 비교를 통해 단어에 따른 유의어 결과를 연구하였다. 문제 추천 알고리즘은 Word2Vec 모델의 특징인 텍스트 간 의미 반영 및 유사성 테스트를 통해 표현된 값으로 구현됐다. Word2Vec 의 학습 결과를 통해 텍스트 유사도 값을 이용해 문제 추천을 진행하였으며 유사도가 높은 문제를 추천할 수 있다. 실험 과정에서 정량적인 데이터양으로는 정확성이 낮아지는 결과를 보았으며 데이터 셋의 데이터양이 방대할수록 정확성을 높일 수 있음을 확인하였다.

• Computers and Concrete
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• 제29권 6호
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• pp.361-374
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• 2022

On the premise of ensuring that the automatic and quantitative discharging function of concrete conveyors is met, the accuracy of the weight forecast by the mathematical model of the screw conveying volume is improved, and the error of the weight of the concrete parts and the accumulation thickness is reduced. In this paper, the discrete element method (DEM) is used to simulate the macroscopic flow of concrete. Using the concrete discrete element model, the size of the screw conveyor is set, and establish the response model between the influencing factors (process and structure) and the concrete mass flow rate according to the design points of the screw discharging experiment. The nonlinear data fitting method is used to obtain the volumetric efficiency function under the influence of process and structural factors, and the traditional screw conveying volume model is improved. The mass flow rate of concrete predicted by the improved mathematical model of screw conveying volume is consistent with the test results. The model can accurately describe the conveying process of concrete and achieve the purpose of improving the accuracy of forecasting the weight of discharged concrete.