• Architectural research
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• v.12 no.2
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• pp.15-22
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• 2010

Our prediction model is based on the development of "Semantic Location Model." It embodies geometrical and topological information which can increase the efficiency in prediction and make it easy to manipulate the prediction model. Data mining is being implemented to extract the inhabitant's location patterns generated day by day. As a result, the self-learning system will be able to semantically predict the inhabitant's location in advance. This context-aware system brings about the key component of the ubiquitous computing environment. First, we explain the semantic location model and data mining methods. Then the location prediction model for the ubiquitous computing system is described in details. Finally, the prototype system is introduced to demonstrate and evaluate our prediction model.

• Journal of Information Technology Services
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• v.10 no.2
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• pp.189-202
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• 2011

It is important issue how to evaluate the economic feasibility of computing factors in the real world when we build ubiquitous spaces. In this paper, we propose a simple model that can evaluate the economic feasibility of mobile RFID-based ubiquitous computing system which enables seamless communication between offline and online via embedded computing factors in the real world. To achieve this, we explore the meaning of mobile RFID system, the difference between our research and extant researches concerning the evaluation of economic feasibility in RFID system, and propose the so-called 'Tag-based Evaluation Model' (TEM) which is an evaluation model to access the economic feasibility of mobile RFID systems. We also analyze the TEM via simulation cases based on proposed model and discuss the future of TEM.

• Proceedings of the KIEE Conference
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• 2005.05a
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• pp.224-226
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• 2005

Grid computing enables the fundamental computing shift from a localized resource computing model to a fully-distributed virtual organization with shared resources. In the grid computing environment, grid users usually get access rights by mapping their credential to local account. The mapped total account is temporally belongs to grid user. So, data on the secondary storage, which is produced by grid operation, can increase the load of system administration or can issue grid user's privacy. In this paper, we design a data management system for grid user to cover these problems. This system implements template account mechanism and manages local grid data.

• International Journal of Internet, Broadcasting and Communication
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• v.9 no.4
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• pp.44-50
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• 2017

To understand whether Falling, which is one of the causes of injuries, occurs, various behavior recognition research is proceeding. However, in most research recognize only the fact that Falling has occurred and provide the service. As well as the occurrence of the Falling, the risk varies greatly based on the type of Falling and the situation before and after the Falling. Therefore, when Falling occurs, it is necessary to infer the user's current situation and provide appropriate services. In this paper, we propose to base on Fog Computing and Cloud Computing to design Context-aware System using analysis of behavior data and process sensor data in real-time. This system solved the problem of increase latency and server overload due to large capacity sensor data.

• Journal of Advanced Navigation Technology
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• v.16 no.2
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• pp.330-339
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• 2012

In this paper, we define and design the Streaming as a Service (StraaS) to support streaming service based on cloud computing. And we describe the various function and security to StraaS service. Specially, we introduce KS-MMA(Key-generation System for Multilateral Matching Authentication) and SIES(Searchable Image Encryption System) as security function for streaming service and cloud computing.

• Agribusiness and Information Management
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• v.8 no.1
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• pp.11-16
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• 2016

This paper presents how Digital Knowledge Ecosystem such as "Govi Nena" (translates as agriculture intelligence) can be used to provide a more effective and practical solution to eliminate the inefficiencies in agricultural markets and achieve higher productivity and price stability. In order to establish the framework to analyze the system, this paper uses a set of hypothetical scenarios faced by value chain actors based on a review of the literature, established knowledge and recent developing country experiences. The scenario analysis reveals that "Govi Nena" enables farmers to make effective production decisions, deepens the level of value chain integration, and enhances the level of welfare for the society as a whole.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2004.11a
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• pp.158-161
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• 2004

In this paper, we propose a level of contexts such as low level and high level contexts, and its criteria of categorization are the existence of interaction and composite process done by the inference mechanism. When there is no matching high level service for the associated high level context, this context is described as meaningless. If the services cannot be provided with the entities by the system, this situational information is of little consequence. To provide services with the entities, we propose "community computing" architectural concept which provide the high level service to a group of agents in a community, and can be managed by the service scenario

• JSTS:Journal of Semiconductor Technology and Science
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• v.10 no.1
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• pp.49-54
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• 2010

This paper describes a fast circuit simulation technique using the latency insertion method (LIM) with a parallel and distributed leapfrog algorithm. The numerical simulation results on the PC cluster system that uses the cloud computing system are shown. As a result, it is confirmed that our method is very useful and practical.

• International Journal of Computer Science & Network Security
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• v.22 no.3
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• pp.95-100
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• 2022

Cloud computing platform is a shared pool of resources and services with various kind of models delivered to the customers through the Internet. The methods include an on-demand dynamically-scalable form charged using a pay-per-use model. The main problem with this model is the allocation of resource in dynamic. In this paper, we have proposed a mechanism to optimize the resource provisioning task by reducing the job completion time while, minimizing the associated cost. We present the Cooperative Agents Dynamic Resource Allocation and Monitoring in Cloud Computing CADRAM system, which includes more than one agent in order to manage and observe resource provided by the service provider while considering the Clients' quality of service (QoS) requirements as defined in the service-level agreement (SLA). Moreover, CADRAM contains a new Virtual Machine (VM) selection algorithm called the Node Failure Discovery (NFD) algorithm. The performance of the CADRAM system is evaluated using the CloudSim tool. The results illustrated that CADRAM system increases resource utilization and decreases power consumption while avoiding SLA violations.

• Electronics and Telecommunications Trends
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• v.35 no.7
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• pp.13-22
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• 2020

There is no denying that computing power has been a crucial driving force behind the development of artificial intelligence today. In addition, artificial intelligence (AI) semiconductors and computing systems are perceived to have promising industrial value in the market along with rapid technological advances. Therefore, success in this field is also meaningful to the nation's growth and competitiveness. In this context, ETRI's AI strategy proposes implementation directions and tasks with the aim of strengthening the technological competitiveness of AI semiconductors and computing systems. The paper contains a brief background of ETRI's AI Strategy #2, research and development trends, and key tasks in four major areas: 1) AI processors, 2) AI computing systems, 3) neuromorphic computing, and 4) quantum computing.