• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.7
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• pp.2668-2717
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• 2021

Demands for high-speed wireless data services grow rapidly. It is a big challenge to increasing the network capacity operating on licensed spectrum resources. Unlicensed spectrum cellular networks have been proposed as a solution in response to severe spectrum shortage. Licensed Assisted Access (LAA) was standardized by 3GPP, aiming to deliver data services through unlicensed 5 GHz spectrum. Furthermore, the 3GPP proposed 5G New Radio-Unlicensed (NR-U) study item. On the other hand, artificial intelligence (AI) has attracted enormous attention to implement 5G and beyond systems, which is known as Intelligent Radio (IR). To tackle the challenges of unlicensed spectrum networks in 4G/5G/B5G systems, a lot of works have been done, focusing on using Machine Learning (ML) to support resource allocation in LTE-LAA/NR-U and Wi-Fi coexistence environments. Generally speaking, ML techniques are used in IR based on statistical models established for solving specific optimization problems. In this paper, we aim to conduct a comprehensive survey on the recent research efforts related to unlicensed cellular networks and IR technologies, which work jointly to implement 5G and beyond wireless networks. Furthermore, we introduce a positioning assisted LTE-LAA system based on the difference in received signal strength (DRSS) to allocate resources among UEs. We will also discuss some open issues and challenges for future research on the IR applications in unlicensed cellular networks.

• The Journal of Korea Robotics Society
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• v.19 no.2
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• pp.169-175
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• 2024

In this study, we developed control system for stable teleoperation of supermicrosurgical robot platform. The supermicrosurgical robot platform is designed to perform precise anastomosis with micro vessels ranging from 0.3 mm to 0.7 mm. The robotic assistance could help more precise manipulation then manual surgery with the help of motion scaling and tremor filtering. However, since the robotic system could cause several vulnerabilities, control system for stable teleoperation should be preceded. Therefore, we first designed control system including inverse kinematics solver, clutch error interpolator and finite state machine. The inverse kinematics solver was designed to minimized inertial motion of the manipulator and tested by applying orientational motion. To make robot slowly converges to the leader's orientation when orientational error was occurred during clutch, the SLERP was used to interpolate the error. Since synchronized behavior of two manipulators and independent behavior of manipulator both exist, two layered finite state machines were designed. Finally, the control system was evaluated by experiment and showed intended behavior, while maintaining low pose error.

• The KIPS Transactions:PartB
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• v.10B no.7
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• pp.795-802
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• 2003

To live autonomously, intelligent agents such as robots or virtual characters need ability that recognizes given environment, and learns and chooses adaptive actions. So, we propose an action selection/learning mechanism in intelligent agents. The proposed mechanism employs a hybrid system which integrates a behavior-based method using the reinforcement learning and a cognitive-based method using the symbolic learning. The characteristics of our mechanism are as follows. First, because it learns adaptive actions about environment using reinforcement learning, our agents have flexibility about environmental changes. Second, because it learns environmental factors for the agent's goals using inductive machine learning and association rules, the agent learns and selects appropriate actions faster in given surrounding and more efficiently in extended surroundings. Third, in implementing the intelligent agents, we considers only the recognized states which are found by a state detector rather than by all states. Because this method consider only necessary states, we can reduce the space of memory. And because it represents and processes new states dynamically, we can cope with the change of environment spontaneously.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.3
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• pp.307-316
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• 2011

The majority of maritime accidents happened by human factor. For that reason, navigation experts want to an intelligent support system for navigation safety, without officer involvement. The expert system which is one of artificial intelligence skills for navigation support is an important tool that a machine can substitute for an expert through the design of a knowledge base and inference engine using the experience or knowledge of an expert. Further, in the real world, a complex situation requires synthetic estimation with the input of experts in various fields for the correct estimation of the situation, not any one expert. In particular, synthetic estimation is more important for navigation situations than in other cases, because of diverse potential threats. This paper presents the method of knowledge fusion pertaining to navigation safety knowledge from various expert systems, using a blackboard system. Then we will show the validity of the method via a design and implementation of test system effort.

• Convergence Security Journal
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• v.23 no.5
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• pp.117-123
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• 2023

Recently, as the demand for Generative Artificial Intelligence (AI) and artificial intelligence has increased, the seriousness of misuse and abuse has emerged. However, intelligent CCTV, which maximizes detection of abnormal behavior, is of great help to prevent crime in the military and police. AI performs learning as taught by humans and then proceeds with self-learning. Since AI makes judgments according to the learned results, it is necessary to clearly understand the characteristics of learning. However, it is often difficult to visually judge strange and abnormal behaviors that are ambiguous even for humans to judge. It is very difficult to learn this with the eyes of artificial intelligence, and the result of learning is very many False Positive, False Negative, and True Negative. In response, this paper presented standards and methods for clarifying the learning of AI's strange and abnormal behaviors, and presented learning measures to maximize the judgment ability of intelligent CCTV's False Positive, False Negative, and True Negative. Through this paper, it is expected that the artificial intelligence engine performance of intelligent CCTV currently in use can be maximized, and the ratio of False Positive and False Negative can be minimized..

• The Journal of the Korea Contents Association
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• v.9 no.12
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• pp.64-76
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• 2009

Recently, the ubiquitous environment and the practical technology associated with it become more popular topic along with the rapid development of wireless technologies. The necessity of the automated system based on the ubiquitous environment has been increasing when the concept of the ubiquitous is integrated into the fields of existing IT. Also, the necessity of formulating a power-saving plan on large buildings and public institutions is gathering strength because of a raise in exchange rates and high oil prices. In this paper, to efficiently manage the power consumption of the electronic machine such as electric lights, electric heaters, and air conditioners in a building, power-saving manage- ment system using RFID/USN technologies is proposed. Proposed system controls the electric machine and monitor it's condition by RFID and collects the real time information about the surrounding and the power consumption of the electric machine by USN. Especially, proposed system analyzes the real time information and supports the intelligent scheduler with the best power-saving. Finally, this paper shows the difference between proposed system and existing system and establishes thereality of our system through experiments in variety environments.

• Journal of Information Processing Systems
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• v.2 no.1
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• pp.52-57
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• 2006

One of the important functions of an Intelligent Transportation System (ITS) is to classify vehicle types using a vision system. We propose a method using machine-learning algorithms for this classification problem with 3-D object model fitting. It is also necessary to detect road lanes from a fixed traffic surveillance camera in preparation for model fitting. We apply a background mask and line analysis algorithm based on statistical measures to Hough Transform (HT) in order to remove noise and false positive road lanes. The results show that this method is quite efficient in terms of quality.

• Proceedings of the ESK Conference
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• 1998.04a
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• pp.13.1-18
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• 1998

IVNS(In-Vehicle Navigation System) which developed by the advance of technological system including computer, display and communication will procide the important interface functions between the driver and the ITS (Intelligent Transport System). However, hat the human factors engineer can actually offer to the designer is by no means a complete set of design specifications. Therefore, a set of boundary conditions and operational ranges within which the designer can be assured that physical, perceptual and cognitive abilities and limitations of drivers will be accommodated system atically[6]. Also, this will be the considerations to compose the IVNS HMI (Human-Machine Interface) design guidelines and IVNS HMI evaluation system. As the first phase of developing the IVNS HMI evaluation system, this paper describe the architecture and the content of this system.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.10
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• pp.1157-1162
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• 2015

The maintenance function of Solar power plant is configured with Sensor devices, Gateway, and Maintenance Function Platform. In this paper, we designed gateway resource tree and service scenario to fit the Maintenance Function and demonstrated appropriate operation of the maintenance service through intelligent functional modeling.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.05a
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• pp.945-948
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• 2005

Mobile computing devices are becoming increasingly prevalent in a huge range of physical area, offering a considerable market opportunity. The focus of this paper is on the development of a platform of fault diagnosis system integrating with personal digital assistant (PDA). An improvement of induction machine rotor fault diagnosis based on AI algorithms approach is presented. This network system consists of two parts; condition monitoring and fault diagnosis by using Artificial Intelligence algorithm. LabVIEW allows easy interaction between acquisition instrumentation and operators. Also it can easily integrate AI algorithm. This paper presents a development environment fur intelligent application for PDA. The introduced configuration is a LabVIEW application in PDA module toolkit which is LabVIEW software.