• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.4
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• pp.406-411
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• 2005

In this paper, we present the area-based Q-learning to search a target object using multiple robot. To search the target in Markovian space, the robots should recognize their surrounding at where they are located and generate some rules to act upon by themselves. Under area-based Q-learning, a robot, first of all, obtains 6-distances from itself to environment by infrared sensor which are hexagonally allocated around itself. Second, it calculates 6-areas with those distances then take an action, i.e., turn and move toward where the widest space will be guaranteed. After the action is taken, the value of Q will be updated by relative formula at the state. We set up an experimental environment with five small mobile robots, obstacles, and a target object, and tried to search for a target object while navigating in a unknown hallway where some obstacles were placed. In the end of this paper, we presents the results of three algorithms - a random search, area-based action making (ABAM), and hexagonal area-based Q-teaming.

• Journal of Internet of Things and Convergence
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• v.9 no.1
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• pp.125-129
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• 2023

Age of Information (AoI) has been introduced in wireless networked control systems (WNCSs) to guarantee timely status updates. In addition, as the edge computing (EC) architecture has been deployed in NCS, EC close to sensors can be exploited to collect status updates from sensors and provide control decisions to actuators. However, when lots of sensors simultaneously deliver status updates, EC can be overloaded, which cannot satisfy the AoI requirement. To mitigate this problem, this paper uses actuators with computing capability that can directly receive the status updates from sensors and determine the control decision without the help of EC. To analyze the AoI of the actuation update via EC or directly using actuators, this paper developed an analytic model based on timing diagrams. Extensive simulation results are included to verify the analytic model and to show the AoI with various settings.

• Industry Promotion Research
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• v.9 no.4
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• pp.115-120
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• 2024

This study aims to analyze user reviews of Hyundai Motor Group's 'BlueLink' connected car service to identify key dissatisfaction factors and derive future UX planning directions. To achieve this, review data from the Google Play Store for BlueLink service over one year was collected and classified into satisfaction levels: high, medium, and low. Reviews categorized as medium and low were analyzed to extract key keywords, which were then subjected to social network analysis. Based on the results of the social network analysis, key dissatisfaction factors were classified into three groups with high simultaneous appearance frequencies: 'update-error related dissatisfaction,' 'vehicle-condition related dissatisfaction,' and 'Galaxy-Watch related dissatisfaction.' And I tried to identify key dissatisfaction factors through review data that showed related keywords together. The research results are expected to contribute to improving domestic connected car services by suggesting enhancement strategies, thereby fostering digital innovation in the automotive industry and enhancing user satisfaction.

• Journal of Internet Computing and Services
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• v.9 no.6
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• pp.1-13
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• 2008

Trusted Computing is a hardware-based technology that aims to guarantee security for machines beyond their users' control by providing security on computing hardware and software. TPM(Trusted Platform Module), the trusted platform specified by the Trusted Computing Group, acts as the roots for the trusted data storage and the trusted reporting of platform configuration. Data sealing encrypts secret data with a key and the platform's configuration at the time of encryption. In contrast to the traditional data sealing based on binary hash values of the platform configuration, a new approach called property-based data sealing was recently suggested. In this paper, we propose and analyze a new property-based data sealing protocol using the weakest precondition concept by Dijkstra. The proposed protocol resolves the problem of system updates by allowing sealed data to be unsealed at any configuration providing the required property. It assumes practically implementable trusted third parties only and protects platform's privacy when communicating. We demonstrate the proposed protocol's operability with any TPM chip by implementing and running the protocol on a software TPM emulator by Strasser. The proposed scheme can be deployed in PDAs and smart phones over wireless mobile networks as well as desktop PCs.

• Journal of Internet of Things and Convergence
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• v.8 no.5
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• pp.11-16
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• 2022

As an interest in the development of artificial intelligence(AI) technology in the water supply sector increases, we have developed an AI algorithm that can predict improvement decision-making ratings through repetitive learning using the data of pipe condition evaluation results, and present the most reliable prediction model through a verification process. We have developed the algorithm that can predict pipe ratings by pre-processing 12 indirect evaluation items based on the 2020 Han River Basin's basic plan and applying the AI algorithm to update weighting factors through backpropagation. This method ensured that the concordance rate between the direct evaluation result value and the calculated result value through repetitive learning and verification was more than 90%. As a result of the algorithm accuracy verification process, it was confirmed that all water pipe type data were evenly distributed, and the more learning data, the higher prediction accuracy. If data from all across the country is collected, the reliability of the prediction technique for pipe ratings using AI algorithm will be improved, and therefore, it is expected that the AI algorithm will play a role in supporting decision-making in the objective evaluation of the condition of aging pipes.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.45 no.9
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• pp.724-733
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• 2017

Accidents caused by upset condition leads to fatal damage to both manned and unmanned aircraft. This paper deals with real-time detection of these aircraft upset situations to prevent further severe situations. Firstly, the difference between sensor measurement and predicted measurement from Extended Kalman filter is monitored to determine whether a target aircraft goes into an upset condition or not. In addition, repeating the time update stage of the Extended Kalman filter for a specific length of time can enable future upset situation prediction. The results of aforementioned both the approaches will build a bridge to upset prevention for future generation of manned/unmanned aircraft.

• Journal of Internet Computing and Services
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• v.24 no.6
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• pp.137-144
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• 2023

Cyberattack technology is evolving to an unpredictable degree, and it is a situation that can happen 'at any time' rather than 'someday'. Infrastructure that is becoming hyper-connected and global due to cloud computing and the Internet of Things is an environment where cyberattacks can be more damaging than ever, and cyberattacks are still ongoing. Even if damage occurs due to external influences such as cyberattacks or natural disasters, intelligent self-recovery must evolve from a cyber resilience perspective to minimize downtime of cyber assets (OS, WEB, WAS, DB). In this paper, we propose an intelligent self-recovery technology to ensure sustainable cyber resilience when cyber assets fail to function properly due to a cyberattack. The original and updated history of cyber assets is managed in real-time using timeslot design and snapshot backup technology. It is necessary to secure technology that can automatically detect damage situations in conjunction with a commercialized file integrity monitoring program and minimize downtime of cyber assets by analyzing the correlation of backup data to damaged files on an intelligent basis to self-recover to an optimal state. In the future, we plan to research a pilot system that applies the unique functions of self-recovery technology and an operating model that can learn and analyze self-recovery strategies appropriate for cyber assets in damaged states.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.3
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• pp.593-600
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• 2018

Cellular automata (CA) have been applied to effective cryptographic system design. CA is superior in randomness to LFSR due to the fact that its state is updated simultaneously by local interaction. To apply these CAs to the cryptosystem, a study has been performed how to synthesize CA corresponding to given polynomials. In this paper, we analyze the recurrence relations of the characteristic polynomial of the 90 UCA and the characteristic polynomial of the 90/150 CA whose transition rule is <$00{\cdots}001$>. And we synthesize the 90/150 CA corresponding to the trinomials $x^{2^n}+x+1(n{\geq}2)$ satisfying f(x)=f(x+1) using the 90 UCA transition rule blocks and the special transition rule block. We also analyze the properties of the irreducible factors of trinomials $x^{2^n}+x+1$ and propose a 90/150 CA synthesis algorithm corresponding to $x^{2^n}+x^{2^m}+1(n{\geq}2,n-m{\geq}2)$.

• Composites Research
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• v.14 no.6
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• pp.16-23
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• 2001

Analysis of mechanical behavior for a pultruded-wound hollow rod is presented. For this purpose, the pultruded-wound hollow rod is manufactured by the new winder attached to the conventional pultrusion system. And the conventional pultrusion process is newly altered to manufacture pultruded-wound specimens. A computer program, POST II, is modified to perform this study, In the nonlinear finite element formulation, the updated Lagrangian description method based on the second Piolar-Kirchhoff stress tensor and the Green strain tensor are used. For the finite element modeling of the composite hollow rod, the eight-node degenerated shell element is utilized. In order to estimate the failure, the maximum stress criterion is adopted to the averaged stress in the each layer of the finite elements. As numerical examples, the behavior of glass/up composite hollow rod is investigated from the initial loading to the final collapse. Present finite element results considering stiffness degradation and stress unload due to failure shows excellent agreement with experiments in the ultimate load, failure and deformations.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.6
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• pp.41-47
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• 2011

This paper is concerned with the DW-MCMA(Dual Weight vector Modified Constant Modulus Algorithm) adaptive equalization algorithm using the dual weight vector in order to improve the convergence characteristic and residual inter-symbol interference which are used as the performance index for an adaptive equalizer. The equalizer is used to reduce the distortion caused by the inter-symbol interference on the wireless and the wired band-limited channel that connect the transmitting system and receiving system. The CMA is widely known as the representative algorithm for equalization. In order to transmitting the mass information with a high speed through the channels, a fast convergence speed in the equalizer performance that is able to minimize overhead needed for equalization is acquired. In this paper, By the computer simulation, we confirmed that the proposed DW-MCMA has the faster convergence speed and the smaller residual inter-symbol interference than the conventional CMA and MCMA.