• Journal of the Korea Society for Simulation
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• v.19 no.3
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• pp.45-54
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• 2010

The inherent complexity of semiconductor fabrication processes makes it hard to solve well-known job scheduling problems in analytical ways, which leads us to rely practically on discrete event modeling simulations to learn the effects of changing the system's parameters. Meanwhile, unpredictable disturbances such as machine failures and maintenance diminish the productivity of semiconductor manufacturing processes with fixed scheduling policies; thus, it is necessary to adapt job scheduling policy in a timely manner in reaction to critical environmental changes (disturbances) in order for the fabrication process to perform optimally. This paper proposes an adaptive job control framework for a wafer fabrication process in a control system theoretical approach and implements it based on a DEVS modeling simulation environment. The proposed framework has the advantages in view of the whole systems understanding and flexibility of applying new rules compared to most ad-hoc software approaches in this field. Furthermore, it is flexible enough to incorporate new job scheduling rules into the existing rule set. Experimental results show that this control framework with adaptive rescheduling outperforms fixed job scheduling algorithms.

• Journal of Korea Society of Digital Industry and Information Management
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• v.5 no.3
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• pp.99-105
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• 2009

This paper suggests novel signal processing methods for optimal beamforming of smart antenna system in CDMA2000 mobile communication environments. This method utilize characteristics of the reverse pilot channel of CDMA2000 mobile communication systems, and applies them to improve the performance of an adaptive algorithm, which is used to a smart antenna system for beamforming. To perform the best beamforming, it is important to get an exact beamforming algorithm. This paper proposed an algorithm based on Laglange multiplier which has such an adaptive process, and also proposed the method to demodulate the received signal through array antenna using pilot channel in CDMA2000 environment. This paper analysed the enhanced performance of proposed algorithm in various signal environment through signal modeling of physical layer in CDMA2000 reverse link.

• Journal of the Korea Society of Computer and Information
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• v.23 no.4
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• pp.65-70
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• 2018

This paper describes a effective information compressor algorithm for the fourth industrial technology. One of the difficult problems for outdoor is to obtain effective updating process of background images. Because input images generally contain the shadows of buildings, trees, moving clouds and other objects, they are changed by lapse of time and variation of illumination. They provide the lowering of performance for surveillance system under outdoor. In this paper, a effective information algorithm for variable environment variable under outdoor is proposed, which apply the Kalman Estimation Modeling and adaptive threshold on pixel level to separate foreground and background images from current input image. In results, the better SNR of about 3dB~5dB and about 10%~25% noise distribution rate in the proposed method. Furthermore, it was showed that the moving objects can be detected on various shadows under outdoor and better result Information.

• Proceedings of the Korea Information Processing Society Conference
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• 2007.05a
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• pp.1107-1109
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• 2007

Context-based access control is an emerging approach for modeling adaptive solution, making access control management more flexible and powerful. However, these strategies are inadequate for the increased flexibility and performance that ubiquitous computing environment requires because such systems can not utilize effectively all benefit from this environment. In this paper, we propose a solution based on risk to make use of many context parameters in order to provide good decisions for a safety environment. We design a new model for risk assessment in ubiquitous computing environment and use risk as a key component in decision-making process in our access control model.

• The KIPS Transactions:PartD
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• v.15D no.3
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• pp.361-374
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• 2008

In the latest intelligent computing environments, the self-adaptive software, as new software paradigm, which modifies its own behavior in response to changes in its operating environment is needed. To develop the self-adaptive software, it is necessary to analyze and design the context of software as well as the structure and the behavior of software. We need more efforts for self-adaptive software development than for traditional software development because we need more activities and technologies like context modeling and adaptation to develop the self-adaptive software. In this paper, we present the product line architecture for self-adaptive software and templates of artifacts to improve the efficiency of development through a reuse methodology. The artifacts of the architecture support the systematic reuse activities of core assets by expressing the commonality and variability of product line.

• Journal of the Korea Institute of Military Science and Technology
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• v.11 no.3
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• pp.19-29
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• 2008

Underwater acoustic(UWA) communication is one of the most difficult field in terms of severe channel environments such as multipath propagation, high temporal and spatial variability of channel conditions. Therefore, it is important to model and analyze the characteristics of underwater acoustic channel such as multipath propagation, transmission loss, reverberation, and ambient noise. In this paper, UWA communication channel is modeled with a ray tracing method and applied to image transmission. Quadrature phase shift keying(QPSK) and multichannel decision feedback equalizer(DFE) are utilized as phase-coherent modulation method and equalization technique, respectively. The objective is to improve the performance of the image transmission using vertical sensor array instead of single sensor in the viewpoint of bit error rate(BER), constellation diagram, and received image quality.

• Journal of KIISE
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• v.42 no.11
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• pp.1339-1348
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• 2015

In a distributed system environment based on a service-oriented architecture, separate systems collaborate to achieve the goals of the entire system by using services provided other systems. A service quality violation from using one service can cause runtime system failure in the environment. The existing self-adaptation methods follow fault tolerance mechanism that responds to a failure after a service quality violation. In other words, these methods are limited to responsive action. Therefore, a service-dependability-case based self-adaptation mechanism is necessary to preserve the dependability of the self-adaptive system. This paper demonstrates that the service-dependability-case based self-adaptation mechanism is better than QoS(quality of service)-based self-adaptation with fault tolerance to preserve the dependability of the self-adaptive system. Additionally, this paper suggests a method to present and analyze service dependability by using GSN(Goal Structuring Notation) which is the existing modeling method for the presentation of assurance cases, an action mechanism adapted using an analysis result of service-dependability-cases, a methods of leveraging the service-dependability-case based self-adaptation mechanism by following the service's life cycle, and the framework architecture including the major components and the interactions between the components in the control loop of the self-adaptation process.

• 한국HCI학회:학술대회논문집
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• 2006.02a
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• pp.519-525
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• 2006

Advances in information and telecommunication technology increasingly reveal the potential of computer supported education. However, most computer supported learning systems until recently did not pay much attention to different characteristics of individual learners. Intelligent learning environments adaptive to learner's preferences and tasks are desired. Each learner has different preferences and needs, so it is very crucial to provide the different styles of learners with different learning environments that are more preferred and more efficient to them. This paper reports a study of the intelligent learning environment where the learner's preferences are diagnosed using learner models, and then user interfaces are customized in an adaptive manner to accommodate the preferences. In this research, the learning user interfaces were designed based on a learning-style model by Felder & Silverman, so that different learner preferences are revealed through user interactions with the system. Then, a learning style modeling is done from learner behavior patterns using Decision Tree and Neural Network approaches. In this way, an intelligent learning system adaptive to learning styles can be built. Further research efforts are being made to accommodate various other kinds of learner characteristics such as emotion and motivation as well as learning mastery in providing adaptive learning support.

• 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.

• Journal of the Korea Society of Computer and Information
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• v.24 no.3
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• pp.65-75
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• 2019

Non-Functional Requirements (NFR) play a crucial role during the software development process. Currently, NFRs are considered more important than Functional Requirements and can determine the success of a software system. NFRs can be very complicated to understand due to their subjective manner and especially their conflicting nature. Self-adaptive systems (SAS) are operating in dynamically changing environment. Furthermore, the configuration of the SAS systems is dynamically changing according to the current systems context. This means that the configuration that manages the trade-off between NFRs in this context may not be suitable in another. This is because the NFRs satisfaction is based on a per-context basis. Therefore, one context configuration to satisfy one NFR may produce a conflict with another NFR. Furthermore, current approaches managing Non-Functional Requirements trade-off stops managing them during the system runtime which of concern. To solve this, we propose fragmentizing the NFRs and their alternative solutions in form of Multi-entity Bayesian network fragments. Consequently, when changes occur, our system creates a situation specific Bayesian network to measure the impact of the system's conditions and environmental changes on the NFRs satisfaction. Moreover, it dynamically decides which alternative solution is suitable for the current situation.