• Title/Summary/Keyword: update strategy

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The Pilot Production of Topographic-Cadastral Maps and Its Applications in Korea

  • Park, Yun-Soo;Park, Byung-Uk
    • Korean Journal of Geomatics
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    • v.1 no.1
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    • pp.51-59
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    • 2001
  • The Government confirmed the action planning of digital mapping project for major thematic maps based on ‘Revised Plan for The Development of the National Geographic Information System’(NGIS). Mapping for major thematic maps was begun in 1998 when digital mapping project for topographic maps finished due to the delay of the action planning, and will selectively have produced the essential digital thematic maps according to the frequency of usage. The models of topographic-cadastral maps and administrative boundary maps around Suwon were produced in accordance with the presented draft. We presented specification for production of the most appropriate topographic-cadastral maps and administrative boundary maps through the analysis of the process of production, discussion and error check, and correction of the produced topographic-cadastral maps and administrative boundary maps. And we could make it easier to develop digital mapping project of topographic-cadastral maps and administrative boundary maps effectively by presenting the strategy for data input and maintenance, the cost model for carrying out the digital thematic map production, digital topographic maps, and the supplement of data model and data format. Topographic-cadastral maps has a wide range of usage but a lot of difficulties in the process of production and map update under use. So it seems that the study on users, university, private sector and municipal self-government must follow for promoting the use of topographic-cadastral maps.

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Intelligent Internal Stealthy Attack and its Countermeasure for Multicast Routing Protocol in MANET

  • Arthur, Menaka Pushpa;Kannan, Kathiravan
    • ETRI Journal
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    • v.37 no.6
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    • pp.1108-1119
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    • 2015
  • Multicast communication of mobile ad hoc networks is vulnerable to internal attacks due to its routing structure and high scalability of its participants. Though existing intrusion detection systems (IDSs) act smartly to defend against attack strategies, adversaries also accordingly update their attacking plans intelligently so as to intervene in successful defending schemes. In our work, we present a novel indirect internal stealthy attack on a tree-based multicast routing protocol. Such an indirect stealthy attack intelligently makes neighbor nodes drop their routing-layer unicast control packets instead of processing or forwarding them. The adversary targets the collision avoidance mechanism of the Medium Access Control (MAC) protocol to indirectly affect the routing layer process. Simulation results show the success of this attacking strategy over the existing "stealthy attack in wireless ad hoc networks: detection and countermeasure (SADEC)" detection system. We design a cross-layer automata-based stealthy attack on multicast routing protocols (SAMRP) attacker detection system to identify and isolate the proposed attacker. NS-2 simulation and analytical results show the efficient performance, against an indirect internal stealthy attack, of SAMRP over the existing SADEC and BLM attacker detection systems.

Research of Considerations for Effective Operation of Weapons Data Link (무장데이터링크의 효과적인 운용을 위한 고려사항 고찰)

  • Woo, Sang Hyo;Baek, Inhye;Kwon, Ki-Jeong;Kim, Ki Bum
    • Journal of the Korea Institute of Military Science and Technology
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    • v.21 no.6
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    • pp.886-893
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    • 2018
  • U.S. and the allies attacked chemical weapons sites in Syria in 2018, and verbal battles are carried out about the effectiveness of the air strike. Syria claimed 13 missiles were shot down, and Russia claimed 71 missiles were shot down while the U.S. released pictures of completely destroyed targets, only. It led controversy about the effectiveness of missile defense system. If there is a method to observe mission success rate of the air strike, it can not only improve combat awareness but also can be a good sales strategy in military industry. This paper describes effects and considerations of a Weapon Data Link(WDL) technology which can be used as a smoking gun of effectiveness. The paper describes WDL abilities such as In-Flight Track Update, Loiter, and Bomb Hit Indication etc., and presents examples of expected effectiveness of the WDL. In addition, this paper briefly summarizes operational consideration for better performance.

Visual Tracking Using Improved Multiple Instance Learning with Co-training Framework for Moving Robot

  • Zhou, Zhiyu;Wang, Junjie;Wang, Yaming;Zhu, Zefei;Du, Jiayou;Liu, Xiangqi;Quan, Jiaxin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.11
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    • pp.5496-5521
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    • 2018
  • Object detection and tracking is the basic capability of mobile robots to achieve natural human-robot interaction. In this paper, an object tracking system of mobile robot is designed and validated using improved multiple instance learning algorithm. The improved multiple instance learning algorithm which prevents model drift significantly. Secondly, in order to improve the capability of classifiers, an active sample selection strategy is proposed by optimizing a bag Fisher information function instead of the bag likelihood function, which dynamically chooses most discriminative samples for classifier training. Furthermore, we integrate the co-training criterion into algorithm to update the appearance model accurately and avoid error accumulation. Finally, we evaluate our system on challenging sequences and an indoor environment in a laboratory. And the experiment results demonstrate that the proposed methods can stably and robustly track moving object.

Real-Time Path Planning for Mobile Robots Using Q-Learning (Q-learning을 이용한 이동 로봇의 실시간 경로 계획)

  • Kim, Ho-Won;Lee, Won-Chang
    • Journal of IKEEE
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    • v.24 no.4
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    • pp.991-997
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    • 2020
  • Reinforcement learning has been applied mainly in sequential decision-making problems. Especially in recent years, reinforcement learning combined with neural networks has brought successful results in previously unsolved fields. However, reinforcement learning using deep neural networks has the disadvantage that it is too complex for immediate use in the field. In this paper, we implemented path planning algorithm for mobile robots using Q-learning, one of the easy-to-learn reinforcement learning algorithms. We used real-time Q-learning to update the Q-table in real-time since the Q-learning method of generating Q-tables in advance has obvious limitations. By adjusting the exploration strategy, we were able to obtain the learning speed required for real-time Q-learning. Finally, we compared the performance of real-time Q-learning and DQN.

Adaptive time-step control for modal methods to integrate the neutron diffusion equation

  • Carreno, A.;Vidal-Ferrandiz, A.;Ginestar, D.;Verdu, G.
    • Nuclear Engineering and Technology
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    • v.53 no.2
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    • pp.399-413
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    • 2021
  • The solution of the time-dependent neutron diffusion equation can be approximated using quasi-static methods that factorise the neutronic flux as the product of a time dependent function times a shape function that depends both on space and time. A generalization of this technique is the updated modal method. This strategy assumes that the neutron flux can be decomposed into a sum of amplitudes multiplied by some shape functions. These functions, known as modes, come from the solution of the eigenvalue problems associated with the static neutron diffusion equation that are being updated along the transient. In previous works, the time step used to update the modes is set to a fixed value and this implies the need of using small time-steps to obtain accurate results and, consequently, a high computational cost. In this work, we propose the use of an adaptive control time-step that reduces automatically the time-step when the algorithm detects large errors and increases this value when it is not necessary to use small steps. Several strategies to compute the modes updating time step are proposed and their performance is tested for different transients in benchmark reactors with rectangular and hexagonal geometry.

Therapeutic applications of gene editing in chronic liver diseases: an update

  • Shin, Ji Hyun;Lee, Jinho;Jung, Yun Kyung;Kim, Kyeong Sik;Jeong, Jaemin;Choi, Dongho
    • BMB Reports
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    • v.55 no.6
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    • pp.251-258
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    • 2022
  • Innovative genome editing techniques developed in recent decades have revolutionized the biomedical research field. Liver is the most favored target organ for genome editing owing to its ability to regenerate. The regenerative capacity of the liver enables ex vivo gene editing in which the mutated gene in hepatocytes isolated from the animal model of genetic disease is repaired. The edited hepatocytes are injected back into the animal to mitigate the disease. Furthermore, the liver is considered as the easiest target organ for gene editing as it absorbs almost all foreign molecules. The mRNA vaccines, which have been developed to manage the COVID-19 pandemic, have provided a novel gene editing strategy using Cas mRNA. A single injection of gene editing components with Cas mRNA is reported to be efficient in the treatment of patients with genetic liver diseases. In this review, we first discuss previously reported gene editing tools and cases managed using them, as well as liver diseases caused by genetic mutations. Next, we summarize the recent successes of ex vivo and in vivo gene editing approaches in ameliorating liver diseases in animals and humans.

Inter-Factor Determinants of Return Reversal Effect with Dynamic Bayesian Network Analysis: Empirical Evidence from Pakistan

  • HAQUE, Abdul;RAO, Marriam;QAMAR, Muhammad Ali Jibran
    • The Journal of Asian Finance, Economics and Business
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    • v.9 no.3
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    • pp.203-215
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    • 2022
  • Bayesian Networks are multivariate probabilistic factor graphs that are used to assess underlying factor relationships. From January 2005 to December 2018, the study examines how Dynamic Bayesian Networks can be utilized to estimate portfolio risk and return as well as determine inter-factor relationships among reversal profit-generating components in Pakistan's emerging market (PSX). The goal of this article is to uncover the factors that cause reversal profits in the Pakistani stock market. In visual form, Bayesian networks can generate causal and inferential probabilistic relationships. Investors might update their stock return values in the network simultaneously with fresh market information, resulting in a dynamic shift in portfolio risk distribution across the networks. The findings show that investments in low net profit margin, low investment, and high volatility-based designed portfolios yield the biggest dynamical reversal profits. The main triggering aspects related to generation reversal profits in the Pakistan market, in the long run, are net profit margin, market risk premium, investment, size, and volatility factor. Investors should invest in and build portfolios with small companies that have a low price-to-earnings ratio, small earnings per share, and minimal volatility, according to the most likely explanation.

Development of Drawing Processing Tool Program and Establishment Strategy of 3D Underground Structures based on Standardized Drawings (표준도 기반의 3차원 지하구조물 구축 방안 및 도면가공 툴 프로그램 개발)

  • LEE, Min-Kyu;HAN, Sang-Hoon;KIM, Sung-Su
    • Journal of the Korean Association of Geographic Information Studies
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    • v.24 no.4
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    • pp.1-25
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    • 2021
  • In order to respond and prevent underground safety accidents, the Korean government has been preparing a submitting completion drawing web system project for converting the current manual-based 3D Underground Geospatial Map construction and its update system to an automation-based 3D underground information construction. However, research on standard drawings required for the automatic update of 3D underground structures is insufficient, so detailed research is needed. In this research paper, a standard map-based 3D underground structure construction plan was presented for the six types of underground structures constituting the 3D Underground Geospatial Map, enabling rapid and accurate drawing data creation and systematically 3D underground structure drawing data could be managed. In addition, we developed a 3D construction drawing tool that can be used in underground information practice so that ordinary CAD program users can easily produce processing drawings. The results derived from this paper are expected to be major reference materials for the establishment of standard frameworks and practical application guidelines for the construction of 3D underground structures in the future.

An Optimized Model for the Local Compression Deformation of Soft Tissue

  • Zhang, Xiaorui;Yu, Xuefeng;Sun, Wei;Song, Aiguo
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.14 no.2
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    • pp.671-686
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    • 2020
  • Due to the long training time and high training cost of traditional surgical training methods, the emerging virtual surgical training method has gradually replaced it as the mainstream. However, the virtual surgical system suffers from poor authenticity and high computational cost problems. For overcoming the deficiency of these problems, we propose an optimized model for the local compression deformation of soft tissue. This model uses a simulated annealing algorithm to optimize the parameters of the soft tissue model to improve the authenticity of the simulation. Meanwhile, although the soft tissue deformation is divided into local deformation region and non-deformation region, our proposed model only needs to calculate and update the deformation region, which can improve the simulation real-time performance. Besides, we define a compensation strategy for the "superelastic" effect which often occurs with the mass-spring model. To verify the validity of the model, we carry out a compression simulation experiment of abdomen and human foot and compare it with other models. The experimental results indicate the proposed model is realistic and effective in soft tissue compression simulation, and it outperforms other models in accuracy and real-time performance.