• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권2호
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• pp.520-541
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• 2023

In CRNs, SS is of utmost significance. Every CR user generates a sensing report during the training phase beneath various circumstances, and depending on a collective process, either communicates or remains silent. In the training stage, the fusion centre combines the local judgments made by CR users by a majority vote, and then returns a final conclusion to every CR user. Enough data regarding the environment, including the activity of PU and every CR's response to that activity, is acquired and sensing classes are created during the training stage. Every CR user compares their most recent sensing report to the previous sensing classes during the classification stage, and distance vectors are generated. The posterior probability of every sensing class is derived on the basis of quantitative data, and the sensing report is then classified as either signifying the presence or absence of PU. The ISVM technique is utilized to compute the quantitative variables necessary to compute the posterior probability. Here, the iterations of SVM are tuned by novel GO-PSA by combining GOA and PSO. Novel GO-PSA is developed since it overcomes the problem of computational complexity, returns minimum error, and also saves time when compared with various state-of-the-art algorithms. The dependability of every CR user is taken into consideration as these local choices are then integrated at the fusion centre utilizing an innovative decision combination technique. Depending on the collective choice, the CR users will then communicate or remain silent.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 1999년도 Proceedings of International Symposium on Remote Sensing
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• pp.63-69
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• 1999

The purpose of this study is to develop Water Quality Management System(WQMS), which performs calculating pollutant discharge and forecasting water quality with water pollution model. Operational water quality management requires not only controlling pollutants but acquiring and managing exact information. A GIS software, ArcView was used to enter or edit geographic data and attribute data, and MapObject was used to customize the user interface. PCI, a remote sensing software, was used for deriving land cover classification from 20 m resolution SPOT data by image processing. WQMS has two subsystems, Database Subsystem and Modelling subsystem. Database subsystem consisted of watershed data from digital map, remote sensing data, government reports, census data and so on. Modelling subsystem consisted of NSPLM(NonStorm Pollutant Load Model)-SPLM(Storm Pollutant Load Model). It calculates the amount of pollutant and predicts water quality. This two subsystem was connected through graphic display module. This system has been calibrated and verified by applying to Mokhyun stream watershed.

• 한국항해항만학회지
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• 제27권6호
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• pp.645-652
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• 2003

A virtual vessel traffic control system is introduced to contribute to prevent a marine accident such as collision and stranding from happening. Existing VTS has its limit. The virtual vessel traffic control system consists of both data acquisition by satellite remote sensing and a simulation of traffic environment stress based on the satellite data, remotely sensed data And it could be used to provide timely and detailed information about the marine safety, including the location, speed and direction of ships, and help us operate vessels safely and efficiently. If environmental stress values are simulated for the ship information derived from satellite data, proper actions can be taken to prevent accidents. Since optical sensor has a high spatial resolution, JERS satellite data are used to track ships and extract their information. We present an algorithm of automatic identification of ship size and velocity. It lastly is shown that based on ship information extracted from JERS data, a qualitative evaluation method of environmental stress is introduced.

• Journal of Communications and Networks
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• 제12권4호
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• pp.308-316
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• 2010

The problem of compressed sensing (CS) based multiple access is studied under the assumption of random data traffic. In many multiple access systems, i.e., wireless sensor networks (WSNs), data arrival is random due to the bursty data traffic for every transmitter. Following the recently developed CS methodology, the technique of compressing the transmitter identities into data transmissions is proposed, such that it is unnecessary for a transmitter to inform the base station its identity and its request to transmit. The proposed compressed multiple access scheme identifies transmitters and recovers data symbols jointly. Numerical simulations demonstrate that, compared with traditional multiple access approaches like carrier sense multiple access (CSMA), the proposed CS based scheme achieves better expectation and variance of packet delays when the traffic load is not too small.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
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• pp.136-139
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• 2004

The extraction of 'end-pixels' (i.e. end-members) aims to quantify the abundance of different materials in a single pixel, which becomes popular in the subpixel analysis for hyperspectral dataset. In this paper, we present a new concept called 'End-Pixel of Features (EPF)' to extends the concept of end-pixels for multispectral data and even panchromatic data. The algorithm combines the advantages of previous simplex and clustering methods to search the EPFs in the feature space and reduce the effects of noise. Some experimental results show that, the proposed methodology can be successfully used to hyperspectral data and other remote sensing data.

• 한국컴퓨터정보학회논문지
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• 제22권5호
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• pp.81-88
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• 2017

Solar-powered wireless sensor nodes can use extra energy to obtain additional data to increase the precision. However, if the amount of data sensed is increased indiscriminately, the overhead of relay nodes may increase, and their energy may be exhausted. In this paper, we introduce a sensing and compression rate selection scheme to increase the amount of data obtained while preventing energy exhaustion. In this scheme, the neighbor nodes of the sink node determine the limit of data to be transmitted according to the allocated energy and their descendant nodes, and the other nodes select a compression algorithm appropriate to the allocated energy and the limitation of data to be transmitted. A simulation result verifies that the proposed scheme gathers more data with a lower number of blackout nodes than other schemes. We also found that it adapts better to changes in node density and the amount of energy harvested.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.1171-1173
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• 2003

There are two datasets to estimate the area-mean and time-mean precipitation rate. For one, an array of surface rain gauges represents a series of rods that have to the time axis of the volume. And another data is that of a remote sensing make periodic overpasses at a fixed interval such as radar. The problem of optimally combining data from surface rain gauge data and remote sensed data is considered. In order to combining remote sensed data with Automatic Weather Station (AWS), we use optimal weighting method, which is similar to the method of [2]. They had suggested optimal weights that minimized value of the mean square error. In this paper, optimal weight is evaluated for the cases such as Changma, summer Monsoon, Typhoon and orographic rain.

• 대한원격탐사학회지
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• 제10권2호
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• pp.161-170
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• 1994

The JERS-1 is an Earth Resources Satellite launched by NASDA (Natinal Space Development Agency) of Japan, in February in 1992 and has two sensors; SAR(L-Band Synthetic Aperture Radar) and OPS (SWIR and VNIR radiometers). In this research note, the basic properties and data characteristics of the SAR data are summarized based on the observations made on the data sets received for the Nahanni Canadian test site, Northwest Territories. The JERS-1 SAR data quality. including the spatial resolution of the data, is, in general, excellent for most geological applications.

• Journal of Information Processing Systems
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• 제19권3호
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• pp.377-384
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• 2023

The existence of abnormal breakpoint data leads to poor channel balance in wireless sensor networks (WSN). To enhance the communication quality of WSNs, a method for positioning abnormal breakpoint data in WSNs on the basis of signal reconstruction is studied. The WSN signal is collected using compressed sensing theory; the common part of the associated data set is mined by exchanging common information among the cluster head nodes, and the independent parts are updated within each cluster head node. To solve the non-convergence problem in the distributed computing, the approximate term is introduced into the optimization objective function to make the sub-optimization problem strictly convex. And the decompressed sensing signal reconstruction problem is addressed by the alternating direction multiplier method to realize the distributed signal reconstruction of WSNs. Based on the reconstructed WSN signal, the abnormal breakpoint data is located according to the characteristic information of the cross-power spectrum. The proposed method can accurately acquire and reconstruct the signal, reduce the bit error rate during signal transmission, and enhance the communication quality of the experimental object.

• 정보처리학회논문지:컴퓨터 및 통신 시스템
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• 제8권9호
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• pp.217-224
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• 2019

최근 가정, 교통, 의료, 전력망 등 우리 생활과 밀접한 연관을 가진 여러 분야에서 IoT(Internet of Things) 센서 장치를 활용해 데이터를 수집하는 센서 네트워크를 구축하고 활용하고 있다. 이러한 센서 네트워크에서 센싱 데이터 조작은 재산 상, 안전 상의 심각한 위협이 될 수 있다. 따라서 외부 공격자가 센싱 데이터를 조작하지 못하도록 하는 방법이 필요하다. 본 논문에서는 외부 공격자에 의해 조작된 센싱 데이터를 효과적으로 제거하기 위해 데이터 난독화와 변화량 분석을 활용한 IoT 센싱 데이터 유효성 검증 기법을 제안한다. IoT 센서 장치는 난독화 함수에 따라 센싱 데이터를 변조하여 사용자에게 전송하고, 사용자는 전송받은 값을 원래의 값으로 되돌려 사용한다. 적절한 난독화를 거치지 않은 거짓 데이터는 유효 데이터와 다른 변화 양상을 보이고, 변화량 분석을 통해 거짓 데이터를 탐지할 수 있다. 성능 분석을 위해 데이터 유효성 검증 성능 및 검증 소요시간을 측정하였다. 그 결과, 기존 기법에 비해 최대 1.45배 거짓 데이터 차단율을 향상시키고, 0.1~002.0% 수준의 오검출률을 보였다. 또한 저전력, 저성능 IoT 센서 장치에서 검증 소요시간을 측정 결과, 데이터량 증가에 따라 2.5969초까지 증가되는 RSA 암호화 기법에 비해 제안 기법은 0.0003초로 높은 검증 효율을 확인하였다.