• 대한임베디드공학회논문지
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• 제11권4호
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• pp.243-249
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• 2016

Energy-harvesting nodes in wireless sensor networks(WSNs) can be exhausted due to a heavy workload even though they can harvest energy from their environment. On contrast, they can sometimes fully charged, thus waste the harvested energy due to the limited battery-capacity. In order to utilize the harvested energy efficiently, we introduce a selective data compression and transmission range control scheme for energy-harvesting nodes. In this scheme, if the residual energy of a node is expected to run over the battery capacity, the node spends the surplus energy to exploit the data compression or the transmission range expansion; these operations can reduce the burden of intermediate nodes at the expanse of its own energy. Otherwise, the node performs only basic operations such as sensing or transmitting so as to avoid its blackout time. Simulation result verifies that the proposed scheme gathers more data with fewer number of blackout nodes than other schemes by consuming energy efficiently.

• 한국정보과학회논문지:데이타베이스
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• 제33권2호
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• pp.224-238
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• 2006

XML이 인터넷 상에서 데이타 교환의 표준으로 자리매김하면서 스트리밍 환경의 XML 데이타에 대한 효과적인 조인 질의 처리도 증가하고 있다. 튜플 단위로 처리하는 기존의 데이타베이스 기법을 스트리밍 XML 데이타에 적용했을 때 제한된 메모리 사용에 따른 메모리 한계를 초과하는 문제가 발생한다. 또한 구조적인 특징을 가지는 XML 데이타에 대한 질의 경로 탐색 및 특정 부분 데이타에 대한 접근에 소모되는 처리 비용이 급격히 증가하는 문제가 발생하게 된다. 근본적으로 전체 데이타가 아닌 부분 데이타를 저장하고 질의 처리해야 하는 스트리밍 환경에 적용하기에는 부적절하다. 따라서 스트리밍 XML 데이타에 맞는 저장 기법으로 적은 메모리의 사용을 통해 빠르게 조인 프레디킷을 만족하는 부분 스트리밍 데이타를 검색할 수 있는 새로운 기법이 요구된다. 본 논문에서는 적은 메모리 사용을 위한 저장 기법을 위해 PCDATA와 CDATA에 해당되는 부분만을 추출하여 저장한다. 그리고 빠른 조인 프레디킷(Predicate) 비교를 위해 DTD의 구조정보 중 지시자(Cardinality) "*" 와 "+"를 기초하여 영역 윈도우(Range Window)를 설정하여 질의에 만족하는 윈도우만을 선택적으로 조인하는 기법을 제안하여 문제를 해결한다.

• Journal of Information Processing Systems
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• 제17권5호
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• pp.905-917
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• 2021

In recent years, edge computing technology consists of several Internet of Things (IoT) devices with embedded sensors that have improved significantly for monitoring, detection, and management in an environment where big data is commercialized. The main focus of edge computing is data optimization or task offloading due to data and task-intensive application development. However, existing offloading approaches do not consider correlations and associations between data and tasks involving edge computing. The extent of collaborative offloading segmented without considering the interaction between data and task can lead to data loss and delays when moving from edge to edge. This article proposes a range segmentation of dynamic offloading (RSDO) algorithm that isolates the offload range and collaborative edge node around the edge node function to address the offloading issue.The RSDO algorithm groups highly correlated data and tasks according to the cause of the overload and dynamically distributes offloading ranges according to the state of cooperating nodes. The segmentation improves the overall performance of edge nodes, balances edge computing, and solves data loss and average latency.

• International Journal of Advanced Culture Technology
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• 제6권4호
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• pp.190-194
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• 2018

The runway visual range is one of the important factors that decide the possibility of taking offs and landings of the airplane at local airports. The runway visual range is affected by weather conditions like fog, wind, etc. The pilots and aviation related workers check a local weather forecast such as runway visual range for safe flight. However there are several local airfields at which no other forecasting functions are provided due to realistic problems like the deterioration, breakdown, expensive purchasing cost of the measurement equipment. To this end, this study proposes a prediction model of runway visual range for a local airport by applying convolutional neural network that has been most commonly used for image/video recognition, image classification, natural language processing and so on to the prediction of runway visual range. For constituting the prediction model, we use the previous time series data of wind speed, humidity, temperature and runway visibility. This paper shows the usefulness of the proposed prediction model of runway visual range by comparing with the measured data.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.91.3-91
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• 2001

A sensor fusion scheme for mobile robot environment recognition that incorporates range data and contour data is proposed. Ultrasonic sensor provides coarse spatial description but guarantees open space with no obstacle within sonic cone with relatively high belief. Laser structured light system provides detailed contour description of environment but prone to light noise and is easily affected by surface reflectivity. Overall fusion process is composed of two stages: Noise elimination and belief updates. Dempster Shafer´s evidential reasoning is applied at each stage. Open space estimation from sonar range measurements brings elimination of noisy lines from laser sensor. Comparing actual sonar data to the simulated sonar data enables ...

• 한국지능시스템학회논문지
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• 제23권4호
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• pp.304-309
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• 2013

본 논문은 소나 방정식내의 성능지수를 판단하는 지능형 접근방법을 제안한다. 알 수 없는 수중표적의 거리와 고정적이지 않은 신호초과량은 추적과정에 대해 불확실성을 증가시킨다. 탐지거리와 연관된 신호 초과량의 입력 데이터들을 이용하여, 퍼지집합의 규칙을 세우고, 소나의 수신기로부터 얻어지는 데이터를 퍼지화 된 데이터 집합으로 변화시킨다. 알 수 없는 데이터들에 의해 발생되는 오차값들을 감소시키기 위하여 퍼지 집합으로 변환된 새로운 데이터를 이용한다. 구간별 최소값, 최대값 그리고 평균값이 계산되어, 수중 표적의 거리를 추정하는데 사용된다. 데이터들의 증감에 대한 분석을 통해 표적의 위치와 기동특성을 예측할 수 있다. 제안된 기법의 성능과 효과를 보여주기 위하여 몇 가지 예를 보였다.

• 대한임베디드공학회논문지
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• 제10권3호
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• pp.179-188
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• 2015

We propose obstacle classification method based on 2D LIDAR(Light Detecting and Ranging) database. The existing obstacle classification method based on 2D LIDAR, has an advantage in terms of accuracy and shorter calculation time. However, it was difficult to classifier the type of obstacle and therefore accurate path planning was not possible. In order to overcome this problem, a method of classifying obstacle type based on width data of obstacle was proposed. However, width data was not sufficient to improve accuracy. In this paper, database was established by width, intensity, variance of range, variance of intensity data. The first classification was processed by the width data, and the second classification was processed by the intensity data, and the third classification was processed by the variance of range, intensity data. The classification was processed by comparing to database, and the result of obstacle classification was determined by finding the one with highest similarity values. An experiment using an actual autonomous vehicle under real environment shows that calculation time declined in comparison to 3D LIDAR and it was possible to classify obstacle using single 2D LIDAR.

• 품질경영학회지
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• 제41권1호
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• pp.119-134
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• 2013

Purpose: The purpose of this paper is to show whether the results are changed with respect to the variance of the data, by analysis of data obtained from the Taguchi experimental techniques and general experiment. Because which cannot be prove by mathematical Formula, through experimental examples will show. Methods: Taguchi experiments were carried out with paper Helicopter experiment. Experimental Data are obtained by special designed Drop Test Equipment. While Experimental value arbitrarily changed, we looked at how Significant control Factor of Taguchi Methods and Factor experiments are changed. This process cannot be expressed as a Mathematical formula, but showed as a numerical example. Results: Saw significant changes in the factors when data is outside a certain range of the experimental data. By Test of Equivalence Variance, Experiment data is verified reliability. To find the Control Factor, Taguchi Method is better than the general experiment. Conclusion: We know that a Significant Factor is changed with the range of Variance of Experiment Data. The value of this paper is verified change process with Numerical Data obtained Experiment.

• 한국지능시스템학회논문지
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• 제17권6호
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• pp.744-748
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• 2007

이 논문에서는 다수의 IR 거리센서를 이용한 실내용 이동로봇의 자기위치 추정에 관한 새로운 방법을 제안한다. 각각의 IR 거리센서로부터 획득한 거리데이터를 이용하여 장애물과 벽면의 모서리를 검출한다. 각 센서에서 측정된 데이터를 병합하여 환경지도를 작성한다. 실험을 통하여 얻어진 환경지도와 실제 환경을 비교하고 그 성능을 평가하였다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년도 심포지엄 논문집 정보 및 제어부문
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• pp.339-341
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• 2006

This paper proposes a method of container position measurement using automatic landing system that is estimated by a laser range finder. In the most of container position measurement methods, CCD cameras or laser scanners have been used to get the source data. However those sensors are not only weak for disturbances, for examples, the light, fog, and rain, but also the system cost is high. When the spreader arrives the goal position, it is still swung by inertia or by wind effect. In this paper, the spreader swung data have been used to find the container position. The laser range finder is equipped in the front side of spreader. It can measure distance and relative position between spreader and container. This laser range finder can be rotated as desired by a motor. And a tilt sensor is equipped on the spreader to measure spreader sway. We estimate the relative position information between the spreader and a container using the laser range finder and tilt sensor through the geometrical analysis.