• Journal of Information Technology Services
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• v.11 no.sup
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• pp.165-176
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• 2012

Context-Awareness system provides an appropriate service to user by recognizing situation from surrounding environment. There are many successful studies on this framework, but still has some limitations. In this paper, we are describing a context-awareness middleware that can enhance the limitation of the previous approaches. We first defined a new concept of context-awareness environment as a social intelligence. This concept implies that intelligent objects can make relationships, can aware of situation from surrounding environment, and can collaborate to accomplish a given task. The significance of the study is as follows. First, the system is capable of multi context-awareness since it is designed with a structure that supports multiple lines of reasoning. Second, the system is capable of context planning by adapting AI planning mechanism. Third, the system is capable of making the intelligent objects as a group for collaboration, and provides adaptive service to user. We have developed a prototype of the system and tested with a virtual scenario.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.1C
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• pp.37-46
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• 2003

As Information Security Technology has become rather transparent, wide, and integrated than in part, exclusive, and separated, A necessity of the study about integrating the separated distributed security systems into one module, has grown However, there is no integrated framework which can manage all separate security systems as one integrated one yet. Accordingly, we propose a new policy based network admirustrative model in this paper which can integrate individual security systems and distributed control way into one effectively.

• International Journal of Automotive Technology
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• v.3 no.3
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• pp.89-94
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• 2002

This paper presents an architecture for distributed control systems and its underlying methodological framework. Ideas and concepts of distributed systems, artificial intelligence, and soft computing are merged into a unique architecture to provide cooperation, flexibility, and adaptability required by knowledge processing in intelligent control systems. The distinguished features of the architecture include a local problem solving capability to handle the specific requirements of each part of the system, an evolutionary case-based mechanism to improve performance and optimize controls, the use of linguistic variables as means for information aggregation, and fuzzy set theory to provide local control. A distributed traffic control system application is discussed to provide the details of the architecture, and to emphasize its usefulness. The performance of the distributed control system is compared with conventional control approaches under a variety of traffic situations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.8
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• pp.2964-2983
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• 2015

As the Android operating system has become a key target for malware authors, Android protection has become a thriving research area. Beside the proved importance of system permissions for malware analysis, there is a lot of overlapping in permissions between malware apps and goodware apps. The exploitation of them effectively in malware detection is still an open issue. In this paper, to investigate the feasibility of neuro-fuzzy techniques to Android protection based on system permissions, we introduce a self-adaptive neuro-fuzzy inference system to classify the Android apps into malware and goodware. According to the framework introduced, the most significant permissions that characterize optimally malware apps are identified using Information Gain Ratio method and encapsulated into patterns of features. The patterns of features data is used to train and test the system using stratified cross-validation methodologies. The experiments conducted conclude that the proposed classifier can be effective in Android protection. The results also underline that the neuro-fuzzy techniques are feasible to employ in the field.

• Journal of Biomedical Engineering Research
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• v.41 no.1
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• pp.28-34
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• 2020

In this paper, we introduce motion artifact reduction algorithm for interleaved MRI using an advanced 3D approximation algorithm. The motion artifact framework of this paper is data corrected by post-processing with a new 3-D approximation algorithm which uses data structure for each voxel. In this study, we simulate and evaluate our algorithm using Shepp-Logan phantom and T1-MRI template for both scattered dataset and uniform dataset. We generated motion artifact using random generated motion parameters for the interleaved MRI. In simulation, we use image coregistration by SPM12 (https://www.fil.ion.ucl.ac.uk/spm/) to estimate the motion parameters. The motion artifact correction is done with using full dataset with estimated motion parameters, as well as use only one half of the full data which is the case when the half volume is corrupted by severe movement. We evaluate using numerical metrics and visualize error images.

• ETRI Journal
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• v.36 no.6
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• pp.953-959
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• 2014

This paper studies the uplink resource allocation for multiple radio access (MRA) in reconfigurable radio systems, where multiple-input and multiple-output (MIMO) multicarrier-code division multiple access (MC-CDMA) and MIMO orthogonal frequency-division multiple access (OFDMA) networks coexist. By assuming multi-radio user equipment with network-guided operation, the optimal resource allocation for MRA is analyzed as a cross-layer optimization framework with and without fairness consideration to maximize the uplink sum-rate capacity. Numerical results reveal that parallel MRA, which uses MC-CDMA and OFDMA networks concurrently, outperforms the performance of each MC-CDMA and OFDMA network by exploiting the multiuser selection diversity.

• Proceedings of the KSME Conference
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• 2001.06b
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• pp.99-104
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• 2001

Discrete-time controller design is proposed using feedback system identification in frequency domain. System Stability imposed by a new controller is checked in the function of a conventional closed-loop system, instead of a poorly modeled plant due to non-linearity and disturbance as well as unstable components, etc. The stability of the system is evaluated in view of Popov criterion. All the equations are formulated in the framework of the discrete-time system. Simulation results are shown on the plant with input saturation components, DC disturbance and a pure integration.

• Proceedings of the KSME Conference
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• 2001.06b
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• pp.664-669
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• 2001

Continuous-time controller design is proposed using feedback system identification in frequency domain. System stability imposed by a new controller is checked in the function of a conventional closed-loop system, instead of a poorly modeled plant due to non-linearity and disturbance as well as unstable components, etc. The stability of the system is evaluated in view of Nyquist stability. All the equations are formulated in the framework of the discrete-time system. Simulation results are shown on the plant with input saturation and DC disturbance.

• ETRI Journal
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• v.33 no.6
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• pp.871-879
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• 2011

Because a wide variety of multimedia services are provided through personal wireless communication devices, the demand for efficient bandwidth utilization becomes stronger. This demand naturally results in the introduction of the variable bitrate speech coding concept. One exemplary work is the selectable mode vocoder (SMV) that supports speech/music classification. However, because it has severe limitations in its classification performance, a couple of works to improve speech/music classification by introducing support vector machines (SVMs) have been proposed. While these approaches significantly improved classification accuracy, they did not consider correlations commonly found in speech and music frames. In this paper, we propose a novel and orthogonal approach to improve the speech/music classification of SMV codec by adaptively tuning SVMs based on interframe correlations. According to the experimental results, the proposed algorithm yields improved results in classifying speech and music within the SMV framework.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.513-518
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• 1998

In this paper, a robust fault-tolerant control scheme for robot manipulators overcoming actuator failures is presented. The joint(or actuator) fault considered in this paper is the free-swinging joint failure and causes the loss of torque on a joint. The presented fault-tolerant control framework includes a normal control with normal(non-failed) operation, a fault detection and a fault-tolerant control to achieve task completion. For both no uncertainty case and uncertainty case, a stable normal con-troller and an on-line fault detection scheme are presented. After the detection and identification of joint failures, the robot manipulator becomes the underactuated robot system with failed actuators. A robust adaptive control scheme of robot manipulators with the detected failed-actuators using the brakes equipped at the failed(passive) joints is proposed in the presence of parametric uncertainty and external disturbances. To illustrate the feasibility and validity of the proposed fault-tolerant control scheme, simulation results for a three-link planar robot arm with a failed joint are presented.