• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.2
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• pp.279-284
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• 2009

In swarm robot systems, each robot must behaves by itself according to the its states and environments, and if necessary, must cooperates with other robots in order to carry out a given task. Therefore it is essential that each robot has both learning and evolution ability to adapt the dynamic environments. In this paper, reinforcement learning method using many SVM based on structural risk minimization and distributed genetic algorithms is proposed for behavior learning and evolution of collective autonomous mobile robots. By distributed genetic algorithm exchanging the chromosome acquired under different environments by communication each robot can improve its behavior ability. Specially, in order to improve the performance of evolution, selective crossover using the characteristic of reinforcement learning that basis of Cascade SVM is adopted in this paper.

• IEMEK Journal of Embedded Systems and Applications
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• v.4 no.3
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• pp.139-147
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• 2009

This paper proposed the context awareness reasoning system to provide the personalized services dynamically in a ubiquitous mobile environments. The proposed system is designed to provide the personalized services to mobile users and consists of the context aggregator and the knowledge manager. The context aggregator can collect information from networks through Open API Gateway as well as sensors in a various ubiquitous environment. And it can also extract the place types through the geocoding and the social address domain ontology. The knowledge manager is the core component to provide the personalized services, and consists of activity reasoner, user pattern learner and service recommender to provide the services predict by extracting the optimized service from user situations. Activity reasoner uses the ontology reasoning and user pattern learner learns with previous service usage history and contexts. And to design service recommender easy to flexibly apply in dynamic environments, service recommender recommends service in the only use of current accessible contexts. Finally, we evaluate the learner and recommender of proposed system by simulation.

• Advances in Computational Design
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• v.4 no.2
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• pp.141-153
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• 2019

This research is comprised of virtually simulating behavior while experiencing low gravity effects in advance of real world testing in low gravity aboard Zero Gravity Corporation's (Zero-G) research aircraft (727-200F). The experiment simulated a drill rig penetrating a regolith simulant. Regolith is a layer of loose, heterogeneous superficial deposits covering solid rock on surfaces of the Earth' moon, asteroids and Mars. The behavior and propagation of space debris when drilled in low gravity was tested through simulations and visualization in a leading dynamic simulation software as well as discrete element modeling software and in preparation for comparing to real world results from flying the experiment aboard Zero-G. The study of outer space regolith could lead to deeper scientific knowledge of extra-terrestrial surfaces, which could lead us to breakthroughs with respect to space mining or in-situ resource utilization (ISRU). These studies aimed to test and evaluate the drilling process in low to zero gravity environments and to determine static stress analysis on the drill when tested in low gravity environments. These tests and simulations were conducted by a team from Texas A&M University's Department of Construction Science, the United States Air Force Academy's Department of Astronautical Engineering, and Crow Industries

• Journal of the Semiconductor & Display Technology
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• v.22 no.2
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• pp.112-119
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• 2023

In urban environments, signals of Global Positioning System (GPS) can be blocked and reflected by tall buildings, large vehicles, and complex components of road network. Therefore, the performance of the positioning system using the GPS module in urban areas can be degraded due to the loss of GPS signals necessary for the position estimation. To deal with this issue, various localization schemes using inertial measurement unit (IMU) sensors, such as gyroscope and accelerometer, and Bayesian filters, such as Kalman filter (KF) and particle filter (PF), have been designed to enhance the performance of the GPS-based positioning system. Among Bayesian filters, the PF has been widely used for the target tracking and vehicle navigation, since it can provide superior performance in estimating the state of a dynamic system under nonlinear/non-Gaussian circumstance. This paper presents a positioning system that uses the double-stacked particle filter (DSPF) as well as the accelerometer, gyroscope, and GPS receiver on the smartphone to provide higher pedestrian positioning accuracy in urban environments. The DSPF employs a nonparametric technique (Parzen-window) to create the multimodal target distribution that approximates the posterior distribution. Experimental results show that the DSPF-based positioning system can provide the significant improvement of the pedestrian position estimation in urban environments.

• International Journal of Control, Automation, and Systems
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• v.3 no.2
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• pp.173-182
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• 2005

In this paper, a target tracking algorithm for tracking maneuvering vehicles is presented. The overall algorithm belongs to the category of an interacting multiple-model (IMM) algorithm used to detect multiple targets using fused information from multiple sensors. First, two kinematic models are derived: a constant velocity model for linear motions, and a constant-speed turn model for curvilinear motions. Fpr the constant-speed turn model, a nonlinear information filter is used in place of the extended Kalman filter. Being equivalent to the Kalman filter (KF) algebraically, the information filter is extended to N-sensor distributed dynamic systems. The model-matched filter used in multi-sensor environments takes the form of a federated nonlinear information filter. In multi-sensor environments, the information-based filter is easier to decentralize, initialize, and fuse than a KF-based filter. In this paper, the structural features and information sharing principle of the federated information filter are discussed. The performance of the suggested algorithm using a Monte Carlo simulation under the two patterns is evaluated.

• ETRI Journal
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• v.27 no.5
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• pp.595-607
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• 2005

The widespread use of the Internet has led to the problem of intellectual property and copyright infringement. Digital rights management (DRM) technologies have been developed to protect digital content items. Digital content can be classified into static content (for example, text or media files) and dynamic content (for example, VOD or multicast streams). This paper deals with the protection of a multicast stream on set-top boxes connected to an IP network. In this paper, we examine the following design and architectural issues to be considered when applying DRM functions to multicast streaming service environments: transparent streaming service and large-scale user environments. To address the transparency issue, we introduce a 'selective encryption scheme'. To address the second issue, a 'key packet insertion scheme' and 'hierarchical key management scheme' are introduced. Based on the above design and architecture, we developed a prototype of a multicasting DRM system. The analysis of our implementation shows that it supports transparent and scalable DRM multicasting service in a large-scale user environment.

• Journal of Technology Innovation
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• v.8 no.1
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• pp.125-153
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• 2000

This study empirically examined the relationships between the growth stage of ventures and their business characteristics such as KSFs, environmental attributes, CEO roles, and utilization of external resources, based on data from 2,515 Korean ventures. ANOVA results of this study revealed that 1) Key success factors appeared different across the different growth stage of Korean ventures. Financial resources were most critical in the early stage of growth, while the foreign technology licensing appeared to be most important for the success of ventures at later growth stage; 2) As the Korean ventures grew, their environments became more dynamic and hostile; 3) Strategic and external activity roles of top management were critical in younger ventures, while roles for marketing and production were important in older ventures; and 4) Utilization of external resources were more frequent at the later stage of ventures than at the early stage of growth. Based on the research, this study offered several managerial, theoretical, and policy implications.

• The Journal of the Acoustical Society of Korea
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• v.17 no.3E
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• pp.3-11
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• 1998

Zero-crossings with Peak amplitudes (ZCPA) model motivated by human auditory periphery was proposed to extract reliable features form speech signals even in noisy environments for robust speech recognition. In this paper, the performance of the ZCPA model is further improved by incorporating conventional speech processing techniques into the model output. Spectral and cepstral representations of the ZCPA model output are compared, and the incorporation of dynamic features with several different lengths of time-derivative window are evaluated. Also, comparative evaluations with other front-ends in real-world noisy environments are performed, and result in the superiority of the ZCPA model.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.240-243
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• 2003

In this study, as the preliminary step far developing a multi-purpose Autonomous robust carrier mobile robot to transport trolleys or heavy goods and serve as robotic nursing assistant in hospital wards. The aim of this paper is to present the use of multi-sensor data fusion such as sonar, IR sensor for map-building mobile robot to navigate, and presents an experimental mobile robot designed to operate autonomously within both indoor and outdoor environments. Smart sensory systems are crucial for successful autonomous systems. We will give an explanation for the robot system architecture designed and implemented in this study and a short review of existing techniques, since there exist several recent thorough books and review paper on this paper. It is first dealt with the general principle of the navigation and guidance architecture, then the detailed functions recognizing environments updated, obstacle detection and motion assessment, with the first results from the simulations run.

• IEMEK Journal of Embedded Systems and Applications
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• v.15 no.3
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• pp.129-137
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• 2020

Kubernetes is one of the most widely used tool in cloud computing environments. It m anages POD as a basic operational unit, providing a isolated environments through container tech nology. Basically, its scheduler properly allocates POD, considering the utilizations of CPUs, mem ories and volumes on hosts. In our work, we develop a customized scheduling framework additio nally considering network resources. In the framework, we can monitor the dynamic variations of resources and make it possible to utilize the resources for the scheduler. This framework offers not only observing necessary information but also visualizing the data to scheduler for providing convenience.