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

• Journal of Multimedia Information System
• /
• v.9 no.1
• /
• pp.11-20
• /
• 2022

In this paper, we have recently created self-driving cars and self-parking systems in human-friendly cars that can provide high safety and high convenience functions by recognizing the internal and external situations of automobiles in real time by incorporating next-generation electronics, information communication, and function control technologies. And with the development of connected cars, the ITS (Intelligent Transportation Systems) market is expected to grow rapidly. Intelligent Transportation System (ITS) is an intelligent transportation system that incorporates technologies such as electronics, information, communication, and control into the transportation system, and aims to implement a next-generation transportation system suitable for the information society. By combining the technologies of connected cars and Internet of Things with software features and operating systems, future cars will serve as a service platform to connect the surrounding infrastructure on their own. This study creates a research methodology based on the Enhanced Security Model in Self-Driving Cars model. As for the types of attacks, Availability Attack, Man in the Middle Attack, Imperial Password Use, and Use Inclusive Access Control attack defense methodology are used. Along with the commercialization of 5G, various service models using advanced technologies such as autonomous vehicles, traffic information sharing systems using IoT, and AI-based mobility services are also appearing, and the growth of smart transportation is accelerating. Therefore, research was conducted to defend against hacking based on vulnerabilities of smart cars based on artificial intelligence blockchain.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.16 no.4
• /
• pp.238-245
• /
• 2016

Inverters are considered the basic building blocks of industrial electrical drive systems that are widely used for various applications; however, the failure of electronic switches mainly affects the constancy of these inverters. For safe and reliable operation of an electrical drive system, faults in power electronic switches must be detected by an efficient system that is capable of identifying the type of faults. In this paper, an open switch fault identification technique for a three-phase inverter is presented. Single, double, and triple switching faults can be diagnosed using this method. The detection mechanism is based on stator current analysis. Discrete wavelet transform (DWT) using Daubechies is performed on the Clarke transformed (-) stator current and features are extracted from the wavelets. An artificial neural network is then used for the detection and identification of faults. To prove the feasibility of this method, a Simulink model of the DWT-based feature extraction scheme using a neural network for the proposed fault detection system in a three-phase inverter with an induction motor is briefly discussed with simulation results. The simulation results show that the designed system can detect faults quite efficiently, with the ability to differentiate between single and multiple switching faults.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.16 no.1
• /
• pp.72-78
• /
• 2006

It is essential for robot to have the sensing and communication abilities in the swarm robot system. In general, as the number of robot goes on increasing, the limitation of communication capacity and information overflow occur in global communication system. Therefore a local communication is more effective than global one. In this paper, we propose the novel method for determining the optimal communication radius through the analyzing of the information propagation based on local communication. And we also propose a method of cooperative strategies and group behavior of swarm robot based on artificial immune system.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.16 no.4
• /
• pp.449-453
• /
• 2006

This paper wishes to present way that can take advantage of parts information of image drawing for efficient maintenance management of facilities efficiently. Information for parts that compose facilities to facilities design drawing has been expressed, and legend character has been written to divide each parts. This paper applies Artificial Intelligence techniques for legend character cognition of image drawing. Finally, apply artificial intelligence techniques to drawing management system to evaluate efficiency of method that propose in this paper that see.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.14 no.6
• /
• pp.699-704
• /
• 2004

This paper proposes a Distributed Autonomous Robotic System(DARS) based on an Artificial Immune System(AIS) and a Classifier System(CS). The behaviors of robots in the system are divided into global behaviors and local behaviors. The global behaviors are actions to search tasks in environment. These actions are composed of two types: aggregation and dispersion. AIS decides one among these two actions, which robot should select and act on in the global. The local behaviors are actions to execute searched tasks. The robots learn the cooperative actions in these behaviors by the CS in the local. The proposed system is more adaptive than the existing system at the viewpoint that the robots learn and adapt the changing of tasks.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.16 no.1
• /
• pp.27-35
• /
• 2016

Black-box classifiers, such as artificial neural network and support vector machine, are a popular classifier because of its remarkable performance. They are applied in various fields such as inductive inferences, classifications, or regressions. However, by its characteristics, they cannot provide appropriate explanations how the classification results are derived. Therefore, there are plenty of actively discussed researches about interpreting trained black-box classifiers. In this paper, we propose a method to make a fuzzy logic-based classifier using extracted rules from the artificial neural network and support vector machine in order to interpret internal structures. As an object of classification, an anomalous propagation echo is selected which occurs frequently in radar data and becomes the problem in a precipitation estimation process. After applying a clustering method, learning dataset is generated from clusters. Using the learning dataset, artificial neural network and support vector machine are implemented. After that, decision trees for each classifier are generated. And they are used to implement simplified fuzzy logic-based classifiers by rule extraction and input selection. Finally, we can verify and compare performances. With actual occurrence cased of the anomalous propagation echo, we can determine the inner structures of the black-box classifiers.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.4 no.3
• /
• pp.327-336
• /
• 2004

In distributed autonomous mobile robot system, each robot (predator or prey) must behave by itself according to its states and environments, and if necessary, must cooperate with other robots in order to carry out a given task. Therefore it is essential that each robot have both learning and evolution ability to adapt to dynamic environment. This paper proposes a pursuing system utilizing the artificial life concept where virtual robots emulate social behaviors of animals and insects and realize their group behaviors. Each robot contains sensors to perceive other robots in several directions and decides its behavior based on the information obtained by the sensors. In this paper, a neural network is used for behavior decision controller. The input of the neural network is decided by the existence of other robots and the distance to the other robots. The output determines the directions in which the robot moves. The connection weight values of this neural network are encoded as genes, and the fitness individuals are determined using a genetic algorithm. Here, the fitness values imply how much group behaviors fit adequately to the goal and can express group behaviors. The validity of the system is verified through simulation. Besides, in this paper, we could have observed the robots' emergent behaviors during simulation.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.20 no.4
• /
• pp.489-496
• /
• 2010

In this paper, a self-organization framework for swarm systems in three dimensions is presented. The framework uses artificial potential functions(APFs) to direct the robots toward the goal as well as to keep them in a swarm system. This research extends conventional APFs used for self-organizations in two dimension environment to three dimensions. In three dimension environment, the ground potential for the boundary surfaces that commonly appear in three dimension environments is proposed. Accordingly, the comparison between the paths without and with the ground potentials shows the necessity and effect of ground potentials. Extensive simulations are given to show the effectiveness of the extended potentials and various properties in three dimension environments.

• Journal of Distribution Science
• /
• v.17 no.12
• /
• pp.55-62
• /
• 2019

Purpose: The number intelligent homecare products are focused on the development of technology, resulting in a lack of realistic environments or requirements for consumers. The purpose of this paper is to define the consumer and context for intelligent homecare products and to develop a usability evaluation scale. Research design, data and methodology: For this study, first, consumer and contexts related to intelligent homecare products were analyzed through literature review. Second, the primary usability evaluation factors were derived for intelligent homecare products by collecting the factors related to usability evaluation and conducting in-depth interviews with experts. Third, the second usability evaluation factors were derived through survey and statistical analysis based on the derived usability evaluation factors. Results: As a result, users of intelligent homecare products were classified as primary users and secondary consumers and six related contexts. The usability evaluation scale was established with four factors - Functionality, Error, Convenience, and Emotion - and 13 items. Conclusions: This study can be the basis for developing and distributing products that meet the consumer environment and requirements related to intelligent homecare products that will contribute to securing the competitiveness of companies and developing the technology and service value of related industries.