• Journal of Computing Science and Engineering
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• v.5 no.1
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• pp.85-110
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• 2011

Achieving situation awareness is especially challenging for real-time data stream applications because they i) operate on continuous unbounded streams of data, and ii) have inherent realtime requirements. In this paper we showed how formal data stream modeling and analysis can be used to better understand stream behavior, evaluate query costs, and improve application performance. We used MEDAL, a formal specification language based on Petri nets, to model the data stream queries and the quality-of-service management mechanisms of RT-STREAM, a prototype system for data stream management. MEDAL's ability to combine query logic and data admission control in one model allows us to design a single comprehensive model of the system. This model can be used to perform a large set of analyses to help improve the application's performance and quality of service.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.17 no.5
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• pp.94-102
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• 2003

This paper presents active management of feeder automation systems using active database. DAS(Distribution Automation System) has been managed for feeder automation in passive manner. Therefore, feeder automation system has to be managed by operator when feeder overloadings is detected. It may be possible for propagating the feeder overloadings area by operator's mistake. To overcome this defect, the author proposed the feeder automation technique with active manner to obtain feasible feeder reconfiguration. Active database can manage feeder automation system by data driven monitoring of events and by corresponding actions without operator's intervening. To manage feeder automation system with active manner, production rule, active rule manager are designed. And active database system architecture for feeder automation system is proposed. Test results on the KEPCO's 108 bus distribution system show that the performance is efficient and robust.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.24 no.6
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• pp.605-612
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• 2015

Three dimensional (3D) position determination and motion recognition using a 3D depth sensor camera are applied to a developed penguin-shaped robot, and its validity and closeness are investigated. The robot is equipped with an Asus Xtion Pro Live as a 3D depth camera, and a sound module. Using the skeleton information from the motion recognition data extracted from the camera, the robot is controlled so as to follow the typical three mode-reactions formed by the operator's gestures. In this study, the extraction of skeleton joint information using the 3D depth camera is introduced, and the tracking performance of the operator's motions is explained.

• Nuclear Engineering and Technology
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• v.37 no.5
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• pp.491-502
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• 2005

Reliable human performance is a prerequisite in securing the safety of complicated process systems such as nuclear power plants. However, the amount of available knowledge that can explain why operators deviate from an expected performance level is so small because of the infrequency of real accidents. Therefore, in this study, a database that contains a set of useful information extracted from simulated emergencies was developed in order to provide important clues for understanding the change of operators' performance under stressful conditions (i.e., real accidents). The database was developed under Microsoft Windows TM environment using Microsoft Access $97^{TM}$ and Microsoft Visual Basic $6.0^{TM}$. In the database, operators' performance data obtained from the analysis of over 100 audio-visual records for simulated emergencies were stored using twenty kinds of distinctive data fields. A total of ten kinds of operators' performance data are available from the developed database. Although it is still difficult to predict operators' performance under stressful conditions based on the results of simulated emergencies, simulation studies remain the most feasible way to scrutinize performance. Accordingly, it is expected that the performance data of this study will provide a concrete foundation for understanding the change of operators' performance in emergency situations.

• Proceedings of the Korean Nuclear Society Conference
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• 1995.10a
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• pp.185-190
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• 1995

Conventional alarm system has many difficulties in the operator's identifying the plant status during special situations such as design basis accidents. To solve the shortcomings, an on-line alarm annunciator system, called dynamic alarm console (DAC), was developed. In the DAC, a signal is generated as alarm by the use of an adaptive setpoint check strategy based on operating mode, and time delay technique is used not to generate nuisance alarms. After alarm generation, if activated alarm is a level precursor alarm or a consequencial alarm, it would be suppressed, and the residual alarms go through dynamic prioritization which provide the alarms with pertinent priorities to the current operating mode. Dynamic prioritization is achieved by going through the system- and mode-oriented prioritization. The DAC has the alarm hierarchical structure based on the physical and functional importance of alarms. Therefore the operator can perceive alarm impacts on the safety or performance of the plant with the alarm propagation from equipment level to plant functional level. In order to provide the operator with the most possible cause of the event and quick cognition of the plant status even without recognizing the individual alarms, reactor trip status tree (RTST) was developed. The DAC and the RTST have been simulated with on-line data obtained from the full-scope simulator for several abnormal cases. The results indicated that the system can provide the operator with useful and compact information fur the earlier termination and mitigation of an abnormal state.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.1
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• pp.139-144
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• 2017

As technologies related to sensor network are currently emerging and the use of GeoSensor is increasing along with the development of IoT technology, spatial query processing systems to efficiently process spatial sensor data are being actively studied. However, existing spatial query processing systems do not support a spatial-temporal data type and a spatial-temporal operator for processing spatial-temporal sensor data. Therefore, they are inadequate for processing spatial-temporal sensor data like GeoSensor. Accordingly, this paper developed a spatial-temporal query processing system, for efficient spatial-temporal query processing of spatial-temporal sensor data in a sensor network. Lastly, this paper verified the utility of System through a scenario, and proved that this system's performance is better than existing systems through performance assessment of performance time and memory usage.

• Proceedings of the ESK Conference
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• 1993.04a
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• pp.18-26
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• 1993

When designing workplaces, controls should be placed within the reach of operator's arm or foot to guarantee effective performance. The aviation industry is perhaps the chief user of anthropometric data for its need to weight minimization and space optimization. In designing a workplace which must cater to a wide range of operator size, it might be sufficient to plan only for the 'average person'. Static arm reach measurements which are taken in conventional, standardized positions provide the necessary information, but they cannot be directly applied to dynamic situations. In this research, an approximate algorithm to generate the workspace of the human body including foot reach and trunk motion is proposed and tested. The robot kinematics was employed to represent the human body as a multi-link system.

• Journal of Computing Science and Engineering
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• v.2 no.4
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• pp.375-393
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• 2008

The dynamic cast operation allows flexibility in the design and use of data management facilities in object-oriented programs. Dynamic cast has an important role in the implementation of the Data Management Services (DMS) of the Mission Data System Project (MDS), the Jet Propulsion Laboratory's experimental work for providing a state-based and goal-oriented unified architecture for testing and development of mission software. DMS is responsible for the storage and transport of control and scientific data in a remote autonomous spacecraft. Like similar operators in other languages, the C++ dynamic cast operator does not provide the timing guarantees needed for hard real-time embedded systems. In a recent study, Gibbs and Stroustrup (G&S) devised a dynamic cast implementation strategy that guarantees fast constant-time performance. This paper presents the definition and application of a cosimulation framework to formally verify and evaluate the G&S fast dynamic casting scheme and its applicability in the Mission Data System DMS application. We describe the systematic process of model-based simulation and analysis that has led to performance improvement of the G&S algorithm's heuristics by about a factor of 2. In this work we introduce and apply a library for extracting semantic information from C++ source code that helps us deliver a practical and verifiable implementation of the fast dynamic casting algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.6
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• pp.2925-2948
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• 2019

In order to improve the utilization of irrigation water resources of greenhouse tomatoes, a water-saving irrigation decision-making model based on genetic optimization T-S fuzzy neural network is proposed in this paper. The main work are as follows: Firstly, the traditional genetic algorithm is optimized by introducing the constraint operator and update operator of the Krill herd (KH) algorithm. Secondly, the weights and thresholds of T-S fuzzy neural network are optimized by using the improved genetic algorithm. Finally, on the basis of the real data set, the genetic optimization T-S fuzzy neural network is used to simulate and predict the irrigation volume for greenhouse tomatoes. The performance of the genetic algorithm improved T-S fuzzy neural network (GA-TSFNN), the traditional T-S fuzzy neural network algorithm (TSFNN), BP neural network algorithm(BPNN) and the genetic algorithm improved BP neural network algorithm (GA-BPNN) is compared by simulation. The simulation experiment results show that compared with the TSFNN, BPNN and the GA-BPNN, the error of the GA-TSFNN between the predicted value and the actual value of the irrigation volume is smaller, and the proposed method has a better prediction effect. This paper provides new ideas for the water-saving irrigation decision in greenhouse tomatoes.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.24 no.6
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• pp.115-122
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• 2010

The main purpose of centralized monitoring system is to manage factory electrical installation efficiently by on-line data acquisition and supervisory control. The existing centralized system is only able to be managed by operator whenever electrical installation's faults are detected. Therefore, it may be possible for propagating the installation's faults when operator make the unexpected mistakes. To overcome the unexpected mistakes, in this paper, the author presents a centralized monitoring system for factory electrical installation using active database. by using active database production rule, stated system can minimize unexpected mistake and can operate centralized monitoring system efficiently. Test results on the five factory electrical installations show that performance is efficient and robust.