• Title/Summary/Keyword: Space information network

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Learning Less Random to Learn Better in Deep Reinforcement Learning with Noisy Parameters

  • Kim, Chayoung
    • Journal of Advanced Information Technology and Convergence
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    • v.9 no.1
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    • pp.127-134
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    • 2019
  • In terms of deep Reinforcement Learning (RL), exploration can be worked stochastically in the action of a state space. On the other hands, exploitation can be done the proportion of well generalization behaviors. The balance of exploration and exploitation is extremely important for better results. The randomly selected action with ε-greedy for exploration has been regarded as a de facto method. There is an alternative method to add noise parameters into a neural network for richer exploration. However, it is not easy to predict or detect over-fitting with the stochastically exploration in the perturbed neural network. Moreover, the well-trained agents in RL do not necessarily prevent or detect over-fitting in the neural network. Therefore, we suggest a novel design of a deep RL by the balance of the exploration with drop-out to reduce over-fitting in the perturbed neural networks.

Access Control to Objects and their Description in the Future Network of Information

  • Renault, Eric;Ahmad, Ahmad;Abid, Mohamed
    • Journal of Information Processing Systems
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    • v.6 no.3
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    • pp.359-374
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    • 2010
  • The Future Internet that includes Real World Objects and the Internet of Things together with the more classic web pages will move communications from a nodecentric organization to an information-centric network allowing new a paradigm to take place. The 4WARD project initiated some works on the Future Internet. One of them is the creation of a Network of Information designed to enable more powerful semantic searches. In this paper, we propose a security solution for a model of information based on a semantic description and search of objects. The proposed solution takes into account both the access and the management of both objects and their descriptions.

Polynomial Fuzzy Radial Basis Function Neural Network Classifiers Realized with the Aid of Boundary Area Decision

  • Roh, Seok-Beom;Oh, Sung-Kwun
    • Journal of Electrical Engineering and Technology
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    • v.9 no.6
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    • pp.2098-2106
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    • 2014
  • In the area of clustering, there are numerous approaches to construct clusters in the input space. For regression problem, when forming clusters being a part of the overall model, the relationships between the input space and the output space are essential and have to be taken into consideration. Conditional Fuzzy C-Means (c-FCM) clustering offers an opportunity to analyze the structure in the input space with the mechanism of supervision implied by the distribution of data present in the output space. However, like other clustering methods, c-FCM focuses on the distribution of the data. In this paper, we introduce a new method, which by making use of the ambiguity index focuses on the boundaries of the clusters whose determination is essential to the quality of the ensuing classification procedures. The introduced design is illustrated with the aid of numeric examples that provide a detailed insight into the performance of the fuzzy classifiers and quantify several essentials design aspects.

Navigable Space-Relation Model for Indoor Space Analysis (실내 공간 분석을 위한 보행 공간관계 모델)

  • Lee, Seul-Ji;Lee, Ji-Yeong
    • Spatial Information Research
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    • v.19 no.5
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    • pp.75-86
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    • 2011
  • Three-dimensional modeling of cities in the real-world is an essential task for city planning and decision-making. And many three-dimensional city models are being developed with the development of wireless Internet and location-based services that identify the location of users and provide the information increases for consumers. Especially, in case of urban areas of Korea, indoor space modeling as well as outdoor is needed due to the high-rise buildings densities. Also location-based services should be provided through spatial analysis such as the shortest path based on a space model. Many studies of three-dimensional city models are feature models. In a feature model, space is represented by combining primitives, and relationships among spaces are represented only if shared primitives are detected. So relationships between complex three-dimensional objects in space is difficult to be defined through the feature models. In this study, Navigable space-relation model(NSRM) is developed, which is topological data model for efficient representation of spatial relationships between objects based on the network structure.

The application of the ubiquitous system in the interior architectural environment (실내 건축 환경에서 있어서 유비쿼터스의 적용)

  • Chung, Hyo-Kyung
    • Proceedings of the KIEE Conference
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    • 2009.07a
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    • pp.2097_2098
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    • 2009
  • 'Ubiquitous' based on progressive development of IT technology is a new paradigm of the 21th century. In terms of rapid social and technological change, the architectural environment has been changed by computer networking system. According to the condition of the IT business, interior architectural space has been needed to consider applying IT technology for intelligent living environment. To develop the most appropriate architectural interior space applied by home network system, designers need to understand products of the home network system comprised by technical bases and classification of the system. This research is for introducing the information of the recent home network system, products and possible application of ubiquitous system for the future interior architectural space.

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Dynamic Visual Servo Control of Robot Manipulators Using Neural Networks (신경 회로망을 이용한 로보트의 동력학적 시각 서보 제어)

  • 박재석;오세영
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.29B no.10
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    • pp.37-45
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    • 1992
  • For a precise manipulator control in the presence of environmental uncertainties, it has long been recognized that the robot should be controlled in a task-referenced space. In this respect, an effective visual servo control system for robot manipulators based on neural networks is proposed. In the proposed control system, a Backpropagation neural network is used first to learn the mapping relationship between the robot's joint space and the video image space. However, in the real control loop, this network is not used in itself, but its first and second derivatives are used to generate servo commands for the robot. Second, and Adaline neural network is used to identify the approximately linear dynamics of the robot and also to generate the proper joint torque commands. Computer simulation has been performed demonstrating the proposed method's superior performance. Futrhermore, the proposed scheme can be effectively utilized in a robot skill acquisition system where the robot can be taught by watching a human behavioral task.

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Production Equipment Monitoring System Based on Cloud Computing for Machine Manufacturing Tools

  • Kim, Sungun;Yu, Heung-Sik
    • Journal of Korea Multimedia Society
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    • v.25 no.2
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    • pp.197-205
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    • 2022
  • The Cyber Physical System(CPS) is an important concept in achieving SMSs(Smart Manufacturing Systems). Generally, CPS consists of physical and virtual elements. The former involves manufacturing devices in the field space, whereas the latter includes the technologies such as network, data collection and analysis, security, and monitoring and control technologies in the cyber space. Currently, all these elements are being integrated for achieving SMSs in which we can control and analyze various kinds of producing and diagnostic issues in the cyber space without the need for human intervention. In this study, we focus on implementing a production equipment monitoring system related to building a SMS. First, we describe the development of a fog-based gateway system that links physical manufacturing devices with virtual elements. This system also interacts with the cloud server in a multimedia network environment. Second, we explain the proposed network infrastructure to implement a monitoring system operating on a cloud server. Then, we discuss our monitoring applications, and explain the experience of how to apply the ML(Machine Learning) method for predictive diagnostics.

P2P Networking based on CAN for Effective Multimedia Contents Sharing (효율적인 멀티미디어 콘텐츠 공유를 위한 CAN 기반 P2P 네트워킹)

  • 박찬모;김종원
    • Proceedings of the IEEK Conference
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    • 2003.11a
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    • pp.259-262
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    • 2003
  • A efficient P2P (peer to peer) networking for sharing multimedia contents is proposed to overcome the limitations of unstructured approaches. The proposed approach is attempting to organize the participating P2P nodes by modifying a n-dimensional cartesian-coordinate space DHT (distributed hash table), CAN (content addressable network). The network identifiers (e.g., network prefix of IP address) of participating nodes are mapped into the CAN virtual coordinate space (in 2-d) and nodes with similar identifiers are grouped into the same zone. The proposed scheme is expected to show some level of concentration reflecting the network identifiers. Network simulator-based evaluation is performed to verify the effectiveness of the proposed scheme.

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Study on the Method to Create a Pedestrian Network and Path using Navigation Data for Vehicles (차량용 내비게이션 데이터를 이용한 보행 네트워크 및 경로 생성 기법)

  • Ga, Chill-O;Lee, Won-Hee;Yu, Ki-Yun
    • Journal of Korean Society for Geospatial Information Science
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    • v.19 no.3
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    • pp.67-74
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    • 2011
  • In recent years, with increasing utilization of mobile devices such as smartphones, the need for PNS(Pedestrian Navigation Systems) that provide guidance for moving pedestrians is increasing. For the navigation services, road network is the most important component when it comes to creating route and guidance information. In particular, pedestrian network requires modeling methods for more detailed and vast space compared to road network. Therefore, more efficient method is needed to establish pedestrian network that was constructed by existing field survey and manual editing process. This research proposed a pedestrian network creation method appropriate for pedestrians, based on CNS(Car Navigation Systems) data that already has been broadly constructed. Pedestrian network was classified into pedestrian link(sidewalk, side street, walking facility) and openspace link depending on characteristics of walking space, and constructed by applying different methodologies in order to create path that similar to the movements of actual pedestrians. The proposed algorithm is expected to become an alternative for reducing the time and cost of pedestrian network creation.

Extended document format map service for mobile device (바일 기기를 위한 확장 문서 포맷의 맵 서비스)

  • Kim, Jung Sook
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.6 no.4
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    • pp.83-94
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    • 2010
  • Mobile network infrastructure is being completed with the development of hardware and software for mobile devices. Network in mobile devices has evolved for telematics that is expanded much more than its existing concept. Telematics is compound word that is formed from the words "telecommunication" and "informatics". It means that telematics performs control and monitoring service with using mobile device resources. These services provide their services for users' requests through wired or wireless network from mobile devices and server that offers contents and network service collects management information of mobile devices. Map service is one of the preferred services for many telematics users. However, mobile map service has a limit between traffic and information sharing. Therefore it is very important to supply their information for both service provider and terminal user. In this paper, we design a new interactive sketch map using routes and information on the space to be applied effectively, and provide an extended document format that is defined to an extensible and dynamic clustering scheme to have portability map service for mobile device.