• 제목/요약/키워드: SET K-cover

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A Novel Random Scheduling Algorithm based on Subregions Coverage for SET K-Cover Problem in Wireless Sensor Networks

  • Muhammad, Zahid;Roy, Abhishek;Ahn, Chang Wook;Sachan, Ruchi;Saxena, Navrati
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제12권6호
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    • pp.2658-2679
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    • 2018
  • This paper proposes a novel Random Scheduling Algorithm based on Subregion Coverage (RSASC), to solve the SET K-cover problem (an NP-complete problem). SET K-cover problem distributes the set of sensors into the maximum number of mutually exclusive subsets (MESSs) in such a way that each of them can be scheduled for lifetime extension of WSN. Sensor coverage divides the target region into different subregions. RSASC first sorts the subregions in the ascending order concerning their sensor coverage. Then, it forms the subregion groups according to their similar sensor coverage. Lastly, RSASC ensures the K-coverage of each subregion from every group by randomly scheduling the sensors. We consider the target-coverage and area-coverage applications of WSN to analyze the usefulness of our proposed RSASC algorithm. The distinct quality of RSASC is that it utilizes less number of deployed sensors (33% less) to form the optimum number of MESSs with the higher computational speed (saves more than 93% of the time) as compared to the existing three algorithms.

객체분할과 과거 토지피복 정보를 이용한 토지피복도 갱신 (Updating Land Cover Maps using Object Segmentation and Past Land Cover Information)

  • 곽근호;박소연;유희영;박노욱
    • 대한원격탐사학회지
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    • 제33권6_2호
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    • pp.1089-1100
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    • 2017
  • 이 논문에서는 토지피복도 갱신을 목적으로 영상의 객체분할과 훈련 자료 수집에 과거 토지피복도의 정보를 이용하는 방법을 제안하였다. 제안한 방법에서는 영상의 객체분할 시 명확한 토지피복 경계 분할을 위해 과거 토지피복도의 객체 경계를 이용하였다. 또한 적은 수의 초기 훈련 자료를 이용한 초기 분류 결과로부터 유용한 훈련 자료를 추가로 수집하기 위해 과거 토지피복도의 분류 항목 정보를 이용하였다. 충청남도 태안군 일부 지역을 대상으로 환경부 중분류 토지피복도와 WorldView-2 영상을 이용한 토지피복 갱신 사례 연구를 통해 제안된 토지피복도 갱신 방법론의 적용 가능성을 검토하였다. 사례 연구 결과, 초기 분류 결과에서 나타난 시가지와 나지, 논/밭과 초지의 오분류 양상이 제안 방법론을 통해 완화되었다. 또한 과거 토지피복도의 경계를 이용한 객체분할을 통해 객체의 경계를 명확하게 하고 분류 정확도를 향상시켰다. 따라서, 이 연구에서 제안된 방법이 토지피복도 갱신에 유용하게 적용될 수 있을 것으로 기대된다.

THE DOMINATION COVER PEBBLING NUMBER OF SOME GRAPHS

  • Kim, Ju Young;Kim, Sung Sook
    • 충청수학회지
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    • 제19권4호
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    • pp.403-408
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    • 2006
  • A pebbling move on a connected graph G is taking two pebbles off of one vertex and placing one of them on an adjacent vertex. The domination cover pebbling number ${\psi}(G)$ is the minimum number of pebbles required so that any initial configuration of pebbles can be transformed by a sequence of pebbling moves so that the set of vertices that contain pebbles forms a domination set of G. We determine the domination cover pebbling number for fans, fuses, and pseudo-star.

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Rule set of object-oriented classification using Landsat imagery in Donganh, Hanoi, Vietnam

  • Thu, Trinh Thi Hoai;Lan, Pham Thi;Ai, Tong Thi Huyen
    • 한국측량학회지
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    • 제31권6_2호
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    • pp.521-527
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    • 2013
  • Rule set is an important step which impacts significantly on accuracy of object-oriented classification result. Therefore, this paper proposes a rule set to extract land cover from Landsat Thematic Mapper (TM) imagery acquired in Donganh, Hanoi, Vietnam. The rules were generated to distinguish five classes, namely river, pond, residential areas, vegetation and paddy. These classes were classified not only based on spectral characteristics of features, but also indices of water, soil, vegetation, and urban. The study selected five indices, including largest difference index max.diff; length/width; hue, saturation and intensity (HSI); normalized difference vegetation index (NDVI) and ratio vegetation index (RVI) based on membership functions of objects. Overall accuracy of classification result is 0.84% as the rule set is used in classification process.

MODIS 자료를 이용한 한반도 지면피복 분류 (Classification of Land Cover over the Korean Peninsula using MODIS Data)

  • 강전호;서명석;곽종흠
    • 대기
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    • 제19권2호
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    • pp.169-182
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    • 2009
  • To improve the performance of climate and numerical models, concerns on the land-atmosphere schemes are steadily increased in recent years. For the realistic calculation of land-atmosphere interaction, a land surface information of high quality is strongly required. In this study, a new land cover map over the Korean peninsula was developed using MODIS (MODerate resolution Imaging Spectroradiometer) data. The seven phenological data set (maximum, minimum, amplitude, average, growing period, growing and shedding rate) derived from 15-day normalized difference vegetation index (NDVI) were used as a basic input data. The ISOData (Iterative Self-Organizing Data Analysis), a kind of unsupervised non-hierarchical clustering method, was applied to the seven phenological data set. After the clustering, assignment of land cover type to the each cluster was performed according to the phenological characteristics of each land cover defined by USGS (US. Geological Survey). Most of the Korean peninsula are occupied by deciduous broadleaf forest (46.5%), mixed forest (15.6%), and dryland crop (13%). Whereas, the dominant land cover types are very diverse in South-Korea: evergreen needleleaf forest (29.9%), mixed forest (26.6%), deciduous broadleaf forest (16.2%), irrigated crop (12.6%), and dryland crop (10.7%). The 38 in-situ observation data-base over South-Korea, Environment Geographic Information System and Google-earth are used in the validation of the new land cover map. In general, the new land cover map over the Korean peninsula seems to be better classified compared to the USGS land cover map, especially for the Savanna in the USGS land cover map.

New Blind Steganalysis Framework Combining Image Retrieval and Outlier Detection

  • Wu, Yunda;Zhang, Tao;Hou, Xiaodan;Xu, Chen
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제10권12호
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    • pp.5643-5656
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    • 2016
  • The detection accuracy of steganalysis depends on many factors, including the embedding algorithm, the payload size, the steganalysis feature space and the properties of the cover source. In practice, the cover source mismatch (CSM) problem has been recognized as the single most important factor negatively affecting the performance. To address this problem, we propose a new framework for blind, universal steganalysis which uses traditional steganalyst features. Firstly, cover images with the same statistical properties are searched from a reference image database as aided samples. The test image and its aided samples form a whole test set. Then, by assuming that most of the aided samples are innocent, we conduct outlier detection on the test set to judge the test image as cover or stego. In this way, the framework has removed the need for training. Hence, it does not suffer from cover source mismatch. Because it performs anomaly detection rather than classification, this method is totally unsupervised. The results in our study show that this framework works superior than one-class support vector machine and the outlier detector without considering the image retrieval process.

Set Covering Problem and Reliability of the Covers

  • Liu, Y.-H.;Tzeng, G.-H.;Park, Dong-Ho
    • International Journal of Reliability and Applications
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    • 제5권4호
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    • pp.147-154
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    • 2004
  • This work developed and algorithm for a set covering model when the reliability of covers is a concern. This model extended the usage of the set covering model.

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Lifting 기법을 이용한 Generalized Bilinear Cover Inequality (Generalized Bilinear Cover Inequality via Lifting)

  • 정광헌
    • 한국경영과학회지
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    • 제42권3호
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    • pp.1-12
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    • 2017
  • In this paper, we generalize lifted inequalities to a 0-1 mixed-integer bilinear covering set with linear terms. This work is motivated by the observation that Generalized Bilinear Inequality (GBI) occurs in the Branch and Bound process. We find some conditions and prove the subadditivity of lifting functions for lifting to be sequence-independent. Using the theoretical results, we develop facet-defining inequalities for a GBI-defined set through three steps of lifting.

Conditional Covering : Worst Case Analysis of Greedy Heuristics

  • Moon, I.Douglas
    • 한국경영과학회지
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    • 제15권2호
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    • pp.97-104
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    • 1990
  • The problem is a variation of the weighted set-covering problem (SCP) which requires the minimum-cost cover to be self-covering. It is shown that direct extension of the well-known greedy heuristic for SCP can have an arbitrarily large error in the worst case. It remains an open question whther these exists a greedy heuristic with a finite error bound.

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