• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2002년도 추계공동학술대회논문집
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• pp.127-132
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• 2002

This paper proposes a sensor-fusion technique where the data sets for the previous moments are properly transformed and fused into the current data sets to enable accurate measurement, such as, distance to an obstacle and location of the service robot itself. In the conventional fusion schemes, the measurement is dependent on the current data sets. As the results, more of sensors are required to measure a certain physical parameter or to improve the accuracy of the measurement. However, in this approach, instead of adding more sensors to the system the temporal sequence of the data sets are stored and utilized for the measurement improvement. Theoretical basis is illustrated by examples and the effectiveness is proved through the simulations. finally, the new space and time sensor fusion (STSF) scheme is applied to the control of a mobile robot in an unstructured environment as well as structured environment.

• 대한전기학회논문지:시스템및제어부문D
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• 제54권3호
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• pp.156-165
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• 2005

Human being recognizes the physical world by integrating a great variety of sensory inputs, the information acquired by their own action, and their knowledge of the world using hierarchically parallel-distributed mechanism. In this paper, authors propose the sensor fusion system that can recognize multiple 3D objects from 2D projection images and tactile informations. The proposed system focuses on improving recognition performance of 3D objects. Unlike the conventional object recognition system that uses image sensor alone, the proposed method uses tactual sensors in addition to visual sensor. Neural network is used to fuse the two sensory signals. Tactual signals are obtained from the reaction force of the pressure sensors at the fingertips when unknown objects are grasped by four-fingered robot hand. The experiment evaluates the recognition rate and the number of learning iterations of various objects. The merits of the proposed systems are not only the high performance of the learning ability but also the reliability of the system with tactual information for recognizing various objects even though the visual sensory signals get defects. The experimental results show that the proposed system can improve recognition rate and reduce teeming time. These results verify the effectiveness of the proposed sensor fusion system as recognition scheme for 3D objects.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제6권1호
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• pp.229-240
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• 2012

Advances in MEMS and CMOS technologies have motivated the development of low cost/power sensors and wireless multimedia sensor networks (WMSN). The WMSNs were created to ubiquitously harvest multimedia content. Such networks have allowed researchers and engineers to glimpse at new Machine-to-Machine (M2M) Systems, such as remote monitoring of biosignals for telemedicine networks. These systems require the acquisition of a large number of data streams that are simultaneously generated by multiple distributed devices. This paradigm of data generation and transmission is known as event-streaming. In order to be useful to the application, the collected data requires a preprocessing called data fusion, which entails the temporal alignment task of multimedia data. A practical way to perform this task is in a centralized manner, assuming that the network nodes only function as collector entities. However, by following this scheme, a considerable amount of redundant information is transmitted to the central entity. To decrease such redundancy, data fusion must be performed in a collaborative way. In this paper, we propose a collaborative data alignment approach for event-streaming. Our approach identifies temporal relationships by translating temporal dependencies based on a timeline to causal dependencies of the media involved.

• 한국통신학회논문지
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• 제35권8C호
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• pp.713-719
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• 2010

협력 스펙트럼 감지 방식은 페이딩이 존재하는 환경에서 1차 사용자의 활동 유무를 알아내는 효과적인 방식으로 알려져 있다. 지금까지 협력 스펙트럼 감지에 관해 이루어진 대부분의 연구는 2차 사용자가 내린 국부 스펙트럼 감지 결정들이 통계적으로 서로 독립이라는 가정에 기초한 것이다. 그러나 실제 환경에서는 이러한 전제가 성립하지 않을 수 있다. 이 논문에서는 지역적으로 이웃한 2차 사용자의 국부 스펙트럼 감지 결정들 사이에 동일한 상관도가 존재하고, 이웃하지 않은 경우에는 통계적으로 독립인 인지 무선 네트워크를 대상으로 하여, AND 규칙과 OR 규칙을 사용하는 협력 스펙트럼 감지 방식의 성능을 분석하였다. 분석 결과, 상관 정도가 강할 때 AND 방식이 OR 방식에 비해 우수한 성능을 나타냄을 확인할 수 있었다.

• 대한원격탐사학회지
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• 제20권4호
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• pp.275-288
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• 2004

이 논문은 다중 센서 원격탐사 화상의 분류를 위해 퍼지 논리 융합과 결합된 relaxation labeling 방법을 제안하였다. 다중 센서 원격탐사 화상의 융합에는 퍼지 논리를, 분광정보와 공간정보의 융합에는 반복적인 relaxation labeling 방법을 적용하였다. 특히 반복적 relaxation labeling 방법은 공간정보의 이용에 따른 분류 화소의 변화양상을 얻을 수 있는 장점이 있다. 토지 피복의 감독 분류를 목적으로 광학 화상과 다중 주파수/편광 SAR 화상에 제안 기법을 적용한 결과, 다중 센서 자료를 이용하고 공간정보를 함께 결합하였을 때 향상된 분류 정확도를 얻을 수 있었다.

• Smart Structures and Systems
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• 제29권1호
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• pp.221-235
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• 2022

Manual inspection of steel box girders on long span bridges is time-consuming and labor-intensive. The quality of inspection relies on the subjective judgements of the inspectors. This study proposes an automated approach to detect and segment cracks in high-resolution images. An end-to-end cascaded framework is proposed to first detect the existence of cracks using a deep convolutional neural network (CNN) and then segment the crack using a modified U-Net encoder-decoder architecture. A Naïve Bayes data fusion scheme is proposed to reduce the false positives and false negatives effectively. To generate the binary crack mask, first, the original images are divided into 448 × 448 overlapping image patches where these image patches are classified as cracks versus non-cracks using a deep CNN. Next, a modified U-Net is trained from scratch using only the crack patches for segmentation. A customized loss function that consists of binary cross entropy loss and the Dice loss is introduced to enhance the segmentation performance. Additionally, a Naïve Bayes fusion strategy is employed to integrate the crack score maps from different overlapping crack patches and to decide whether a pixel is crack or not. Comprehensive experiments have demonstrated that the proposed approach achieves an 81.71% mean intersection over union (mIoU) score across 5 different training/test splits, which is 7.29% higher than the baseline reference implemented with the original U-Net.

• 한국지구과학회지
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• 제44권3호
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• pp.185-195
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• 2023

The prolonged and heavy East Asian summer precipitation in 2020 may have been caused by an enhanced Madden-Julian Oscillation (MJO), which requires evaluation using forecast models. We examined the performance of GloSea6, an operational forecast model, in predicting the East Asian summer precipitation during July 2020, and investigated the role of MJO in the extreme rainfall event. Two experiments, CON and EXP, were conducted using different convection schemes, 6A and 5A, respectively to simulate various aspects of MJO. The EXP runs yielded stronger forecasts of East Asian precipitation for July 2020 than the CON runs, probably due to the prominent MJO realization in the former experiment. The stronger MJO created stronger moist southerly winds associated with the western North Pacific subtropical high, which led to increased precipitation. The strengthening of the MJO was found to improve the prediction accuracy of East Asian summer precipitation. However, it is important to note that this study does not discuss the impact of changes in the convection scheme on the modulation of MJO. Further research is needed to understand other factors that could strengthen the MJO and improve the forecast.

• 한국통신학회논문지
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• 제39A권1호
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• pp.19-27
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• 2014

최근 주파수 자원의 중요성이 부각됨에 따라 이미 할당된 주파수 대역을 재사용하여 주파수 이용 효율을 향상시키는 인지 무선 기술(Cognitive Radio, CR)에 대한 연구가 활발히 이루어지고 있다. CR은 주파수 대역의 사용현황에 따라 기회적으로 사용자가 주파수 대역을 이용하므로 이를 위한 정보를 얻는 센싱 단계가 성능에 중요한 영향을 미친다. 따라서 센싱 성능을 향상시키는 것은 CR에서의 중요 이슈가 되며 이를 위해 다수의 단말이 협력하여 1차 사용자의 스펙트럼 점유 여부를 검출하는 협력 스펙트럼 센싱이 고려되고 있다. 본 논문에서는 협력 스펙트럼 센싱 환경에서 각 사용자의 센싱 정보가 융합 센터(Fusion Center, FC)로 보고되는 채널의 오류 확률을 고려하는 OR 규칙 기반의 협력 스펙트럼 센싱 기법을 제안한다. 제안 기법은 보고 오류 확률을 통해 협력 센싱에 참여하는 사용자 수를 제한함으로써 기존 기법에서 나타나는 오경보 확률의 제한을 완화시킨다.

• 한국통신학회논문지
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• 제34권5A호
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• pp.429-435
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• 2009

협력 스펙트럼 감지(cooperative spectrum sensing)는 CR(cognitive radio) 네트워크를 구성하는 다수의 부 사용자(secondary user)가 서로 협력하여 주 사용자(primary user)의 스펙트럼 사용 여부를 판단하는 기술이다. 이를 수행하는 일반적인 형태는 일차적으로 부 사용자별로 판단을 한 후 이를 종합하여 최종 판단을 내리는 방식이며, 이때 가장 일반적인 융합 규칙(fusion rule)이 k-out-of-n 규칙이다. 이 방식은 n명의 부 사용자 중에 k명 이상이 주 사용자가 해당 스펙트럼을 사용하고 있다는 것에 동의할 때에만 이를 최종 판단으로 확정하는 방식이다. 본 논문에서는 주 사용자의 검파 확률을 일정 수준 이상으로 유지한다는 조건하에서 이 융합 규칙을 사용하는 협력 스펙트럼 감지 방식의 성능 분석 방식을 제시하고, 그 적용 사례로 10명의 부 사용자로 구성된 CR 네트워크에 대한 수치 분석 결과를 제시하고자 한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제8권10호
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• pp.3302-3320
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• 2014

An allocation of sensing and reporting times is proposed to improve the sensing performance by scheduling them in an efficient way for cognitive radio networks with cluster-based cooperative spectrum sensing. In the conventional cooperative sensing scheme, all secondary users (SUs) detect the primary user (PU) signal to check the availability of the spectrum during a fixed sensing time slot. The sensing results from the SUs are reported to cluster heads (CHs) during the reporting time slots of the SUs and the CHs forward them to a fusion center (FC) during the reporting time slots of the CHs through the common control channels for the global decision, respectively. However, the delivery of the local decision from SUs and CHs to a CH and FC requires a time which does not contribute to the performance of spectrum sensing and system throughput. In this paper, a super-allocation technique, which merges reporting time slots of SUs and CHs to sensing time slots of SUs by re-scheduling the reporting time slots, has been proposed to sense the spectrum more accurately. In this regard, SUs in each cluster can obtain a longer sensing duration depending on their reporting order and their clusters except for the first SU belonged to the first cluster. The proposed scheme, therefore, can achieve better sensing performance under -28 dB to -10 dB environments and will thus reduce reporting overhead.