• ETRI Journal
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• v.44 no.6
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• pp.915-924
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• 2022

In this paper, we present a two-stage scalable channel estimator (TSCE), a deep learning (DL)-based scalable, and robust channel estimator for wireless cellular networks, which is made up of two DL networks to efficiently support different resource allocation sizes and reference signal configurations. Both networks use the transformer, one of cutting-edge neural network architecture, as a backbone for accurate estimation. For computation-efficient global feature extractions, we propose using window and window averaging-based self-attentions. Our results show that TSCE learns wireless propagation channels correctly and outperforms both traditional estimators and baseline DL-based estimators. Additionally, scalability and robustness evaluations are performed, revealing that TSCE is more robust in various environments than the baseline DL-based estimators.

• International Journal of Contents
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• v.3 no.1
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• pp.34-38
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• 2007

Load redistribution is a critical resource in computer system. In sender-initiated load redistribution algorithms, the sender continues to send unnecessary request messages for load transfer until a receiver is found while the system load is heavy. These unnecessary request messages result in inefficient communications, low CPU utilization, and low system throughput in distributed systems. To solve these problems, we propose a genetic algorithm based approach for improved sender-initiated load redistribution in distributed systems. Compared with the conventional sender-initiated algorithms, the proposed algorithm decreases the response time and task processing time.

• The Journal of Korea Robotics Society
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• v.3 no.3
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• pp.165-175
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• 2008

For an advanced intelligent service, the need of HRI technology has recently been increasing and the technology has been also improved. However, HRI components have been evaluated under stable and controlled laboratory environments and there are no evaluation results of performance in real environments. Therefore, robot service providers and users have not been getting sufficient information on the level of current HRI technology. In this paper, we provide the evaluation results of the performance of the HRI components on the robot platforms providing actual services in pilot service sites. For the evaluation, we select face detection component, speaker gender classification component and sound localization component as representative HRI components closing to the commercialization. The goal of this paper is to provide valuable information and reference performance on appling the HRI components to real robot environments.

• The Journal of Korea Robotics Society
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• v.4 no.2
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• pp.121-129
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• 2009

This paper presents a goal-directed reactive obstacle avoidance method based on lane method. The reactive collision avoidance is necessarily required for a robot to navigate autonomously in dynamic environments. Many methods are suggested to implement this concept and one of them is the lane method. The lane method divides the environment into lanes and then chooses the best lane to follow. The proposed method does not use the discrete lane but chooses a line closest to the original target line without collision when an obstacle is detected, thus it has a merit in the aspect of running time and it is more proper for narrow corridor environment. If an obstacle disturbs the movement of a robot by blocking a target path, a robot generates a temporary target line, which is parallel to an original target line and tangential to an obstacle circle, to avoid a collision with an obstacle and changes to and follows that line until an obstacle is removed. After an obstacle is clear, a robot returns to an original target line and proceeds to the goal point. Obstacleis recognized by laser range finder sensor and represented by a circle. Our method has been implemented and tested in a corridor environment and experimental results show that our method can work reliably.

• The KIPS Transactions:PartD
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• v.8D no.6
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• pp.681-690
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• 2001

In this paper, we propose a steering concept that considers overall aspects in the CBSD (Component-Based Software Development) environments. While many researches which are concentrated on using components, market promotion and component development itself seem to be insufficient. To overcome this problem, we introduce a brokerage concept called“Value-Added Brokerage Concept”that provides the following three services：1) domain architecture-based component promotion, 2) intelligent component search, and 3) white-box service. Domain architecture-based component promotion facilitates balancing component production and promoting architecture-level large scale reuse. Intelligent component search enables to overcome the long time search and selection problem. Finally, white-box service is for solving maintenance problems, which is one of the most critical problem in the CBSD environments. Especially, we expect this proposed concept would be well adapted to our national environments.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1071-1076
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• 2003

In this work, we propose a new framework of robot control for a variety of applications to our unstructured everyday environments. Programming robots can be a very time-consuming process and seems almost impossible for ordinary end users. To cope with this, this work is to provide a software framework for building robot application programs automatically, where we have robots learn how to accomplish a commanded task from the object. An integrated sensing and computing tag is embedded into every single object in the environment. In the robot controller, only the basic software libraries for low-level robot motion control are provided from the robot manufacturer. The main contributions of this work is to develop a server platform that we call Omniscient Server that generates the application programs and send them to the robot controller through the network. The object-related information from the object server merges into robot control software to generate a detailed application program based on the task commands from the human. We have built a test bed and demonstrated that a robot can perform a common household task within the proposed framework.

• Journal of the Korean Society of Safety
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• v.23 no.6
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• pp.51-56
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• 2008

As RFID/USN technology is used in the latest industry trend, the information analysis paradigm shifts to intelligence service environment. The intelligent service includes autonomic operation, which select activity by defining itself to the status of industry facilities. Furthermore, information analysis based on IT used to frequently data mining for detecting the meaning information and deriving new pattern. This paper suggest self-classifying of context-aware by applying data mining in gas facilities for serving the intelligent gas safety management. We modify data algorithm for fitting the domain of gas safety, construct context-aware model by using the proposed algorithm, and demonstrate our method. As the accuracy of our model is improved over 90%, the our approach can apply to intelligent gas safety management based on RFID/USN environments.

• Journal of Broadcast Engineering
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• v.24 no.3
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• pp.395-400
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• 2019

The CBS and the AEAS functionalities are defined in cellular systems and T-DMB systems, respectively. In the case that communication facilities are disabled in indoor environments, it is impossible for the residents to receive the emergency messages. In this paper, a novel collaborative technology of intelligent mobile robots is proposed, which relies on cooperative communications among the intelligent mobile robots. In order to improve the performance, the intelligent mobile robots exploit their location information. Simulation results confirm that the proposed method is very suitable for reliable emergency alert broadcast.

• Journal of Internet Computing and Services
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• v.20 no.2
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• pp.21-27
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• 2019

The terrestrial ATSC 3.0 broadcasting system, which is capable of converging broadcast and communication services, uses IP based technology for data transmission between broadcasting equipment. In addition, data transmission between broadcasting equipment uses IP-based technology like existing wired communication network, which has advantageous in terms of equipment construction and maintenance In case IP based data transmission technology is used, however, it may inevitably cause an error that a packet is lost during transmission depending on the network environments. In order to cope with a broadcasting accident caused by such a transmission error or a malfunction of a broadcasting apparatus, a broadcasting system is generally configured as a duplication, which can transmit a normal packet when various types of error may occur. By this reason, correction method of error packets and intelligent switching technology are essential. Therefore, in this paper, we propose a design and implementation of intelligent IP switch for Ensuring Reliability of ATSC 3.0 Broadcast Streams. The proposed intelligent IP consists of IP Stream Analysis Module, ALP Stream Analysis Module, STL Stream Analysis Module and SMPTE 2022-1 based FEC Encoding/Decoding Module.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.42 no.3 s.303
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• pp.17-28
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• 2005

Recently intelligent characters in computer games have been an important element more and more because they continually stimulate gamers' interests. As a typical method for implementing such intelligent characters, neural networks have been used for training action patterns of opponent's characters and game rules. However, some of the game rules can be abruptly changed and action properties of garners in on-line game environments are quite different according to gamers. In this paper, we address how a neural network adapts to those environmental changes. Our adaptation solution includes two components: an individual adaptation mechanism and a group adaptation mechanism. With the individual adaptation algorithm, an intelligent character steadily checks its game score, assesses the environmental change with taking into consideration of the lastly earned scores, and initiates a new learning process when a change is detected. In multi-user games, including massively multiple on-line games, intelligent characters confront diverse opponents that have various action patterns and strategies depending on the gamers controlling the opponents. The group adaptation algorithm controls the birth of intelligent characters to conserve an equilibrium state of a game world by using a genetic algorithm. To show the performance of the proposed schemes, we implement a simple fighting action game and experiment on it with changing game rules and opponent characters' action patterns. The experimental results show that the proposed algorithms are able to make intelligent characters adapt themselves to the change.