• Title/Summary/Keyword: Location정보

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GCP Chip Automatic Extraction of Satellite Imagery Using Interest Point in North Korea (특징점 추출기법을 이용한 접근불능지역의 위성영상 GCP 칩 자동추출)

  • Lee, Kye Dong;Yoon, Jong Seong
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.37 no.4
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    • pp.211-218
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    • 2019
  • The Ministry of Land, Infrastructure and Transport is planning to launch CAS-500 (Compact Advanced Satellite 500) 1 and 2 in 2019 and 2020. Satellite image information collected through CAS-500 can be used in various fields such as global environmental monitoring, topographic map production, analysis for disaster prevention. In order to utilize in various fields like this, it is important to get the location accuracy of the satellite image. In order to establish the precise geometry of the satellite image, it is necessary to establish a precise sensor model using the GCP (Ground Control Point). In order to utilize various fields, step - by - step automation for orthoimage construction is required. To do this, a database of satellite image GCP chip should be structured systematically. Therefore, in this study, we will analyze various techniques for automatic GCP extraction for precise geometry of satellite images.

Developing a decision support system for selecting new crops

  • Jung, Guhyun;Jeon, Myounghee;Lee, Jinhong;Park, Heundong;Lee, Seyong;Kim, Joonyong
    • Agribusiness and Information Management
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    • v.10 no.2
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    • pp.8-17
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    • 2018
  • Due to changes in the agricultural market environment and both overseas and domestic farming conditions, uncertainties in agricultural production and management are becoming greater. Hence, there is a stronger need for farmers to choose crops in the optimal condition. This research aims to introduce the result and process of developing a decision support system for selecting crops, aimed to assist farmers in selecting the optimal crops most suitable in the given situation. There are basically three main factors to consider in the decision-making process for farmers when selecting a crop to introduce to their lands. First of all, one must consider how much profit crop A will produce when it is cultivated. Secondly, one must consider which crop to cultivate in order to earn a certain amount of profit. Thirdly, one must consider what is the best way to maximize Farm A's business profit. For instance, a farm may have land as its resource, and one must research which location, type of crop, level of technology, and so forth, to maximize profit.This research creates a database of the profitability of a total of 180 crop types by analyzing Rural Development Administration's survey of agricultural products income of 115 crop types, small land profitability index survey of 53 crop types, and Statistics Korea's survey of production costs of 12 crop types. Furthermore, this research presents the result and developmental process of a web-based crop introduction decision support system that provides overseas cases of new crop introduction support programs, as well as databases of outstanding business success cases of each crop type researched by agricultural institutions.

Joint Time Delay and Angle Estimation Using the Matrix Pencil Method Based on Information Reconstruction Vector

  • Li, Haiwen;Ren, Xiukun;Bai, Ting;Zhang, Long
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.12
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    • pp.5860-5876
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    • 2018
  • A single snapshot data can only provide limited amount of information so that the rank of covariance matrix is not full, which is not adopted to complete the parameter estimation directly using the traditional super-resolution method. Aiming at solving the problem, a joint time delay and angle estimation using matrix pencil method based on information reconstruction vector for orthogonal frequency division multiplexing (OFDM) signal is proposed. Firstly, according to the channel frequency response vector of each array element, the algorithm reconstructs the vector data with delay and angle parameter information from both frequency and space dimensions. Then the enhanced data matrix for the extended array element is constructed, and the parameter vector of time delay and angle is estimated by the two-dimensional matrix pencil (2D MP) algorithm. Finally, the joint estimation of two-dimensional parameters is accomplished by the parameter pairing. The algorithm does not need a pseudo-spectral peak search, and the location of the target can be determined only by a single receiver, which can reduce the overhead of the positioning system. The theoretical analysis and simulation results show that the estimation accuracy of the proposed method in a single snapshot and low signal-to-noise ratio environment is much higher than that of Root Multiple Signal Classification algorithm (Root-MUSIC), and this method also achieves the higher estimation performance and efficiency with lower complexity cost compared to the one-dimensional matrix pencil algorithm.

Analysis of regional variation in the lifetime physician diagnosis rate of atopic dermatitis (아토피피부염 평생의사진단율의 지역별 변이 분석)

  • Ko, Keum-Bok;Hwang, Ji-Young;Park, Il-Su
    • Journal of Digital Convergence
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    • v.17 no.1
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    • pp.403-412
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    • 2019
  • The purpose of this study is to analyze temporal and spatial variations of atopic dermatitis and to identify major factors. Data utilized in the study were collected by the Community Health Survey, KOSIS and so and on from 2009 to 2013. This study was analyzed using descriptive statistics and Geographically weighted regression model. As a result, regional diagnosis rate of atopic dermatitis was increased by 5 years, and difference related to geographic location was so large. The regional characteristics that contribute to the diagnosis of atopic dermatitis were as follows: older adults population ratio, ratio of basic living security received people, depression experience rate, high risk drinking rate, number of wastewater discharge business, number of tobacco retail business, number of fast food restaurant business. This study is meaningful in that it provided basic data on health policy direction and provided information on prioritization of health business in each region.

A Study on Adaptive Pattern Null Synthesis for Active Phased Array Antenna (능동위상배열안테나의 적응형 패턴 널 형성에 관한 연구)

  • Jung, Jin-Woo;Park, Sung-Il
    • The Journal of the Korea institute of electronic communication sciences
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    • v.16 no.3
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    • pp.407-416
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    • 2021
  • An active phased array antennas can not only electrically steer the beam by controlling the weighting of the excitation signal, but can also form a pattern null in the direction of the interference source. The weight of the excitation signal to steer the main beam can be easily calculated based on the position of the radiating element. In addition, the weight of the excited signal for pattern null formation can also be calculated by setting the required radiation pattern and using WLSM(Weighted Least Squares Method). However, in a general wireless communication network environment, the location of the interference source is unknown. Therefore, an adaptive pattern null synthesis is needed. In this paper, it was confirmed that pattern null synthesis according to the required radiation characteristic was possible. And based on this, adaptive pattern null synthesis into the direction of an interference source was studied using a binary search algorithm based on observation area. As a result of conducting a simulation based on the presented technique, it was confirmed that adaptive pattern null forming into the direction of an interference is possible in efficient way.

Implementation of Smart Companion Dog Lead Line Integration Module using Heterogeneous Sensor Signal Monitoring (이기종 센서 신호 모니터링을 적용한 스마트 반려견 리드줄 통합 모듈 구현)

  • Cho, Joon-Ho;Kim, Bong-Hyun
    • Journal of Digital Convergence
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    • v.17 no.11
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    • pp.183-188
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    • 2019
  • As social perceptions of pets change, cultural attitudes toward pets are becoming more friendly. In particular, dogs have been living familiarly and closely with humans for a long time. In the changing times, various services are being used to improve the understanding of dogs and to prevent companion dogs and increase awareness of respect for life. Therefore, in this paper, we implemented a smart lead line in which IoT service and application technology are linked to the walking dog's automatic lead line. To do this, we developed a smart dog lead line by designing and implementing an integrated module in connection with heterogeneous sensors and linking it with a dog lead line. Finally, a smart dog lead line was used to collect the dog's biological signals in real time, identify the location of the dog, and provide a notification system. Through this, we believe that the culture of dog culture can be further grown.

Atmospheric Pressure Plasma Etching Technology for Forming Circular Holes in Perovskite Semiconductor Materials (페로브스카이트 반도체 물질에 원형 패턴을 형성하기 위한 상압플라즈마 식각 기술)

  • Kim, Moojin
    • Journal of Convergence for Information Technology
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    • v.11 no.2
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    • pp.10-15
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    • 2021
  • In this paper, we formed perovskite (CH3NH3PbI3) thin films on glass with wet coating methods, and used various analytical techniques to discuss film thickness, surface roughness, crystallinity, composition, and optical property. The coated semiconductor material has no defects and is uniform, the surface roughness value is very small, and a high absorption rate has been observed in the visible light area. Next, in order to implement the hole shape in the organic-inorganic layer, Samples in the order of a metal mask with holes at regular intervals, a glass coated with a perovskite material, and a magnet were etched with atmospheric pressure plasma equipment. The shape of the hole formed in the perovskite material was analyzed by changing the time. It can be seen that more etching is performed as the time increases. The sample with the longest processing time was examined in more detail, and it was classified into 7 regions by the difference according to the location of the plasma.

Multi Label Deep Learning classification approach for False Data Injection Attacks in Smart Grid

  • Prasanna Srinivasan, V;Balasubadra, K;Saravanan, K;Arjun, V.S;Malarkodi, S
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.6
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    • pp.2168-2187
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    • 2021
  • The smart grid replaces the traditional power structure with information inventiveness that contributes to a new physical structure. In such a field, malicious information injection can potentially lead to extreme results. Incorrect, FDI attacks will never be identified by typical residual techniques for false data identification. Most of the work on the detection of FDI attacks is based on the linearized power system model DC and does not detect attacks from the AC model. Also, the overwhelming majority of current FDIA recognition approaches focus on FDIA, whilst significant injection location data cannot be achieved. Building on the continuous developments in deep learning, we propose a Deep Learning based Locational Detection technique to continuously recognize the specific areas of FDIA. In the development area solver gap happiness is a False Data Detector (FDD) that incorporates a Convolutional Neural Network (CNN). The FDD is established enough to catch the fake information. As a multi-label classifier, the following CNN is utilized to evaluate the irregularity and cooccurrence dependency of power flow calculations due to the possible attacks. There are no earlier statistical assumptions in the architecture proposed, as they are "model-free." It is also "cost-accommodating" since it does not alter the current FDD framework and it is only several microseconds on a household computer during the identification procedure. We have shown that ANN-MLP, SVM-RBF, and CNN can conduct locational detection under different noise and attack circumstances through broad experience in IEEE 14, 30, 57, and 118 bus systems. Moreover, the multi-name classification method used successfully improves the precision of the present identification.

Dynamic Pricing Based on Reinforcement Learning Reflecting the Relationship between Driver and Passenger Using Matching Matrix (Matching Matrix를 사용하여 운전자와 승객의 관계를 반영한 강화학습 기반 유동적인 가격 책정 체계)

  • Park, Jun Hyung;Lee, Chan Jae;Yoon, Young
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.19 no.6
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    • pp.118-133
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    • 2020
  • Research interest in the Mobility-as-a-Service (MaaS) concept for enhancing users' mobility experience is increasing. In particular, dynamic pricing techniques based on reinforcement learning have emerged since adjusting prices based on the demand is expected to help mobility services, such as taxi and car-sharing services, to gain more profit. This paper provides a simulation framework that considers more practical factors, such as demand density per location, preferred prices, the distance between users and drivers, and distance to the destination that critically affect the probability of matching between the users and the mobility service providers (e.g., drivers). The aforementioned new practical features are reflected on a data structure referred to as the Matching Matrix. Using an efficient algorithm of computing the probability of matching between the users and drivers and given a set of precisely identified high-demand locations using HDBSCAN, this study developed a better reward function that can gear the reinforcement learning process towards finding more realistic dynamic pricing policies.

Resource Allocation for D2D Communication in Cellular Networks Based on Stochastic Geometry and Graph-coloring Theory

  • Xu, Fangmin;Zou, Pengkai;Wang, Haiquan;Cao, Haiyan;Fang, Xin;Hu, Zhirui
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.14 no.12
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    • pp.4946-4960
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    • 2020
  • In a device-to-device (D2D) underlaid cellular network, there exist two types of co-channel interference. One type is inter-layer interference caused by spectrum reuse between D2D transmitters and cellular users (CUEs). Another type is intra-layer interference caused by spectrum sharing among D2D pairs. To mitigate the inter-layer interference, we first derive the interference limited area (ILA) to protect the coverage probability of cellular users by modeling D2D users' location as a Poisson point process, where a D2D transmitter is allowed to reuse the spectrum of the CUE only if the D2D transmitter is outside the ILA of the CUE. To coordinate the intra-layer interference, the spectrum sharing criterion of D2D pairs is derived based on the (signal-to-interference ratio) SIR requirement of D2D communication. Based on this criterion, D2D pairs are allowed to share the spectrum when one D2D pair is far from another sufficiently. Furthermore, to maximize the energy efficiency of the system, a resource allocation scheme is proposed according to weighted graph coloring theory and the proposed ILA restriction. Simulation results show that our proposed scheme provides significant performance gains over the conventional scheme and the random allocation scheme.