• Journal of Institute of Control, Robotics and Systems
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• v.7 no.8
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• pp.689-696
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• 2001

Large-scale Multi-disciplinary Systems(LMS) such as transportation, aerospace, defense etc. are complex systems in which there are many subsystems, interfaces, functions and demanding performance requirements. Because many contractors participate in the development, it is necessary to apply methods of sharing common objectives and communicating design status effectively among all of the stakeholders. The processes and methods of systems engineering which includes system requirement analysis; functional analysis; architecting; system analysis; interface control; and system specification development provide a success-oriented disciplined approach to the project. This paper shows not only the methodology and the results of model-based systems engineering to Automated Guided Transit(AGT) system as one of LMS systems, but also propose the extension of the model-based tool to help manage a project by linking WBS (Work Breakdown Structure), work organization, and PBS (Product Breakdown Structure). In performing the model-based functional analysis, the focus was on the operation concept of an example rail system at the top-level and the propulsion/braking function, a key function of the modern automated rail system. The model-based behavior analysis approach that applies a discrete-event simulation method facilitates the system functional definition and the test and verification activities. The first application of computer-aided tool, RDD-100, in the railway industry demonstrates the capability to model product design knowledge and decisions concerning key issues such as the rationale for architecting the top-level system. The model-based product design knowledge will be essential in integrating the follow-on life-cycle phase activities. production through operation and support, over the life of the AGT system. Additionally, when a new generation train system is required, the reuse of the model-based database can increase the system design productivity and effectiveness significantly.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.18-23
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• 1993

In this paper, we attempt to estimate the state of a finite state system. In such system, we can observe time series data which has some significant behaviors corresponding to its system states. The behavior is characterized by feature parameters extracted from time series. Our thought is that the system output time series data is expressed as a sequence of behavior patterns which are represented by clusters in feature parameters space. An algorithm jointing fuzzy clustering to fuzzy finite state transition model is suggested.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.134.6-134
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• 2001

The purpose of navigation algorithm is to reach a given target point without collision with obstacles while an autonomous mobile robot is navigating. To achieve a safe navigation, this paper presents an effective navigation algorithm for the autonomous mobile robot equipped with ultrasonic sensors in unknown environments. The proposed navigation algorithm consists of an obstacle-avoidance behavior, a target-reaching behavior and a fuzzy-based decision maker. In the obstacle-avoidance behavior and the target-reaching behavior, artificial immune networks are used to select a proper steering angle, make the autonomous mobile robot avoid obstacles and approach a given target point. The decision maker using fuzzy inference systems weights the steering angles selected ...

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1997.10a
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• pp.181-184
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• 1997

Practical applications of learning systems usually involve complex domains exhibiting nonlinear behavior and dilution by noise. Consequently, an intelligent system must be able to adapt to nonlinear processes as well as probabilistic phenomena. An important class of application for a knowledge based systems in prediction: forecasting the future trajectory of a process as well as the consequences of any decision made by e system. This paper examines the robustness of data mining tools under varying levels of noise while predicting nonlinear processes in the form of chaotic behavior. The evaluated models include the perceptron neural network using backpropagation (BPN), the recurrent neural network (RNN) and case based reasoning (CBR). The concepts are crystallized through a case study in predicting a Henon process in the presence of various patterns of noise.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.2
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• pp.261-266
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• 2014

The current status of domestic monitoring centers was reviewed and the pattern-based security monitoring system and the centralized security monitoring system, both of which are the characteristics of security monitoring systems, were analyzed together with their advantages and disadvantages. In addition, as for a development plan of domestic security monitoring systems, in order to improve the problems of the existing pattern-based centralized monitoring system, Honeynet and Darknet, which are based on anomalous behavior detection, were analyzed and their application plans were described.

• Industrial Engineering and Management Systems
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• v.15 no.3
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• pp.215-223
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• 2016

Design of personnel teams has been studied from diverse perspectives; the most common are the people and systems requirements perspectives. All these point of view are linked, which is the reason why it is necessary to study them simultaneously. Considering this gap, a decision making model is developed based on factors, models, and requirements mentioned in the literature. The model is applied to a real case. The findings indicate that the Personnel Behavior Based Lean model (PBBL) can be converted into a decision making model for the selection of team members. The study is focused not only on the individual candidates' knowledge, skills, and aptitudes, but also on how the model considers the company requirements, conflicts, and the importance of each person to the project.

• Asia pacific journal of information systems
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• v.17 no.3
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• pp.25-53
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• 2007

The Expectation Confirmation Model (ECM) of information systems investigates the continued information systems usage behavior. This paper expands the original post-adoption beliefs and searches the applications in the emerging hedonic information systems. Previous IS researches focused on the organizational environments. However as the information technology (especially internet) evolves, information systems have not only emerged for the organizations but also for the individual users, such as internet portals, internet communities, on-line games etc. These information systems so called Hedonic Information Systems aims to provide self-fulfilling value rather than instrumental value to the users. Researches in other disciplines, including marketing and consumer behavior research, illustrate that the hedonic and utilitarian perspective of goods and services have different influence on the consumer behavior. Goods and services used to be classified into either hedonic or utilitarian aspect but now they may belong to both aspects simultaneously. Moreover consumer's goals or tasks have both hedonic utilitarian aspects. When a consumer makes a decision to purchase or repurchase goods or services, he/she compares the hedonic and utilitarian perspectives of goods to find most suitable ones to satisfy their goals/tasks. Finally, consumer's behavior is determined by the trade-off between what the goods can provide to the consumers and in what extent the goods fulfill consumer's purchase behavior. Consumer also shows that the salience of hedonic perspective is relatively greater when consumer decides which of several items to give up (forfeiture choices) than the time when they decide which item to acquire (acquisition choices). Some researches in MIS discipline have found out that the information systems also have both hedonic and utilitarian perspectives. The decision process of whether to use information systems or not is similar to that of a consumer's decision of purchasing or repurchasing goods or services. However most of researches in MIS tend to focus on the extrinsic motivation variables which only cover the utilitarian perspective of information systems. It is only recent that researches start to investigate the intrinsic motivation variable - Perceived Enjoyment - for the hedonic perspective. Considering the consumer's purchasing decision process, users of information systems evaluate the systems through balancing between intrinsic (hedonic) and extrinsic (utilitarian) variables according to their main tasks or tendencies. This paper proposes a model that is based on the ECM of IS Continuance model modified from Expectation Confirmation Model to fit into the continued usage of information system. It first started from the decision process regarding hedonic and utilitarian perspectives in the consumer behavior literatures. The model deals with continued usage of information systems beyond the mere technology adoption as in most of the previous MIS researches. This research is particularly important to the hedonic information systems, because their business model depends on the frequent usages rather simple adoption at the beginning. Because the basic model only considered the extrinsic motivations (perceived usefulness) to explain the users' behavior and as the information systems can have both hedonic and utilitarian dimensions, it should consider both perspectives. Therefore, this newly proposed model considers intrinsic variable (perceived enjoyment) as well. Since the individual user can have a preference on either aspects that is between the hedonic and utilitarian perspective depending on his/her main tasks or goals, some variables (Hedonic Orientation and Utilitarian Orientation) meaning the extents of users' pursuing from the information system were additionally studied.

• ETRI Journal
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• v.21 no.4
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• pp.52-64
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• 1999

QoS monitoring is a kind of real-time systems which allows each level of the system to track the ongoing QoS levels achieved by the lower network layers. For these systems, real-time communications between corresponding transport protocol objects is essential for their correct behavior. When two or more entities are employed to perform a certain task as in the case of communication protocols, the capability to do so is called interoperability and considered as the essential aspect of correctness of communication systems. This paper describes a formal approach on modeling and interoperability test case generation of a real-time QoS monitoring protocol. For this, we specify the behavior of flow monitoring of transport layer QoS protocol, i.e., METS protocol, which is proposed to address QoS from an end-to-end's point of view, based on QoS architecture model which includes ATM net work in lower layers. We use a real-time Input/Output finite State Machine to model the behavior of real-time flow monitoring over time. From the modeled real-time I/OFSM, we generate interoperability test cases to check the correctness of METS protocol's flow monitoring behaviors for two end systems. A new approach to efficient interoperability testing is described and the method of interoperability test cases generation is shown with the example of METS protocol's flow monitoring. The current TTCN is not appropriate for testing real-time and multimedia systems. Because test events in TTCN are for message-based system and not for stream-based systems, the real-time in TTCN can only be approximated. This paper also proposes the notation of real-time Abstract Test Suite by means of real-time extension of TTCN. This approach gives the advantages that only a few syntactical changes are necessary, and TTCN and real-time TTCN are compatible. This formal approach on interoperability testing can be applied to the real-time protocols related to IMT-2000, B-ISDN and real-time systems.

• Journal of Information Processing Systems
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• v.20 no.2
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• pp.159-172
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• 2024

The number of healthcare products available for pets has increased in recent times, which has prompted active research into wearable devices for pets. However, the data collected through such devices are limited by outliers and missing values owing to the anomalous and irregular characteristics of pets. Hence, we propose pet behavior recognition based on a hybrid one-dimensional convolutional neural network (CNN) and long short- term memory (LSTM) model using pet wearable devices. An Arduino-based pet wearable device was first fabricated to collect data for behavior recognition, where gyroscope and accelerometer values were collected using the device. Then, data augmentation was performed after replacing any missing values and outliers via preprocessing. At this time, the behaviors were classified into five types. To prevent bias from specific actions in the data augmentation, the number of datasets was compared and balanced, and CNN-LSTM-based deep learning was performed. The five subdivided behaviors and overall performance were then evaluated, and the overall accuracy of behavior recognition was found to be about 88.76%.

• International Journal of Control, Automation, and Systems
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• v.1 no.1
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• pp.111-118
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• 2003

This paper proposes a two dimensional behavior analysis method for fish in a water tank based on the ARX method and the Kalman filter algorithm using image processing technology. In modeling the behavior of fish, the input is denoted as the environmental change and uses M-sequence. The output is expressed by the partnership between fish. The behavior model of individual fish is identified by the ARX method. It is then estimated by the Kalman filter algorithm. Finally, the fish behavior is analyzed by FFT. To prove the effectiveness of the pro-posed algorithm, it is applied to two tilapias in a water tank with dimensions of 100cm$\times$100cm$\times$50cm. The effectiveness of the proposed method is demonstrated through ARX identification, estimation of Kalman filter, and FFT analysis.