• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.9
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• pp.512-519
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• 2000

A Neural networks has been used for a expert system and fault diagnosis system. It is possible to nonlinear function mapping and parallel processing. Therefore It has been developing for a Diagnosis system of nuclear plower plant. In general Neural Networks is a static mapping but Dynamic Neural Network(DNN) is dynamic mapping.쪼두 a fault occur in system a state of system is changed with transient state. Because of a previous state signal is considered as a information DNN is better suited for diagnosis systems than static neural network. But a DNN has many weights so a real time implementation of diagnosis system is in need of a rapid network architecture. This paper presents a algorithm for RCP monitoring Alarm diagnosis system using Self Dynamic Neural Network(SDNN). SDNN has considerably fewer weights than a general DNN. Since there is no interlink among the hidden layer. The effectiveness of Alarm diagnosis system using the proposed algorithm is demonstrated by applying to RCP monitoring in Nuclear power plant.

• Journal of the Korean Society of Clothing and Textiles
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• v.39 no.2
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• pp.175-189
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• 2015

This study empirically confirmed how an art infusion into fashion products affect consumer's preference through Study 1 and Study 2. Study 1 examined the effect of an art infusion and the difference of an art infusion effect according to self-monitoring scale by designing groups composed of 2 (art infusion: infusion versus non-infusion) ${\times}2$ (self-monitoring: high versus low). Study 2 examined the difference of an art infusion effect according to the luxury level of fashion brands by designing groups composed of 2 (art infusion: infused versus non-infused) ${\times}2$ (fashion brand luxury levels: high versus mid versus low). This study was conducted using a convenience sample of women in their 20s and 30s residing in the Seoul and Daegu region. In Study 1, 162 participants were randomly assigned to two experiment situations of art infusion. In Study 2, 192 participants were randomly assigned to six experiment situations of art infusion and luxury level of fashion brands. For the data analysis, we conducted reliability analysis, two-way ANOVA and simple main effect analysis using SPSS 18.0 statistics package. The results of Study 1 and 2 are as follows. First, consumer's preference was shown to be higher for fashion products with art infusion rather than fashion products without art infusion. Second, the positive effect of art infusion on consumer's preference was significant in the group of high selfmonitors. But there was a non-significant effect of art infusion in the group of low self-monitors. Lastly, the positive effect of art infusion on consumer's preference is higher in the case of a mid-level luxury brand rather than in the case of a high-level luxury brand and low-level luxury brand.

• Journal of Sensor Science and Technology
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• v.19 no.2
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• pp.124-129
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• 2010

For the industrial printing applications, the stability of the piezo-driven inkjet printhead is a major requirement. In this paper, we focused on the failure modes of the inkjet printhead and realized a method to detect and repair them at high speed. The printhead monitoring is performed by detecting the residual vibration of the actuating plate using the self- sensing capability of the piezoelectric material. To measure the channel acoustics and to identify the malfunctioning nozzle, we devised the bridge sensing circuitry and failure detection algorithm. The residual vibration signals can be affected by the boundary conditions of the channel acoustics, so it is possible to identify the failure causes by analyzing the monitoring signals. Therefore it is also possible to apply a proper restoring process to the defective printhead. The experimental results show that this method is effective in improving the reliability of the industrial printing.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.1
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• pp.173-187
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• 2022

Recent studies have focused on self-management of hypertension using smart devices (cellular phones, tablets, watches). It has proven to be an effective tool for early detection and control of high Blood Pressure (BP) without affecting patients' daily routines. This systematic review surveys the existing self-monitoring systems, evaluate their effectiveness and compares the different approaches. We investigated the current systems in terms of various attributes, including methods used, sample size, type of investigation, inputs/ outputs, rate of success in controlling BP, group of users with higher response rate and beneficiaries, acceptability, and adherence to the system. We identified some limitations, shortcomings, and gaps in the research conducted recently studying the impact of mobile technology on managing hypertension. These shortcomings can generate future research opportunities and enable it to become more realistic and adaptive. We recommended including more observable factors and human behaviors that affect BP. Furthermore, we suggested that vital monitoring/logging and medication tuning are insufficient to improve hypertension control. There is also a need to observe and alter patient behavior and lifestyles.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.5
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• pp.159-167
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• 2002

In this paper. we present a new method for monitoring of ECU's self diagnostic signals of vehicle without wire. In order to measure the ECU's self diagnostic signals, the interfaced circuit is designed to communicate ECU and designed terminal according to the IOS, SAE regulation of communication protocol standard. Micro-processor 80C196KC is used for communicating ECU's self diagnositc signals and the results are sent to the wireless terminal and PC monitoring system. Wireless terminal is also developed by 80C196KC, LCD, RF module, and keypad. The command from the keypad is sent to ECU through RF module and the result show on the Graphic LCD in real time. Software on PC is developed to monitor the ECU's self diagnostic signals using the Visual C++ complier in which RS232 port is programmed by half duplex method. The algorithms for measuring the ECU's self diagnostic signals are verified to monitor both ECU and portable terminal state. At the same time, the information to fix the vehicle's problem can be shown on the developed software. The possibility for remote measurement of ECU self diagnostic signal is verified through the developed systems and algorithms.

• Neonatal Medicine
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• v.17 no.1
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• pp.1-12
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• 2010

Graphic monitoring assists the clinician at the bedside in several ways. It can be helpful in fine-tuning or adjusting ventilator parameters. Graphic monitoring may help to determine the patient's response to pharmacologic agents. The clinician also has the ability to trend monitored events over a prolonged period of time. The neonatal patient's self respiration, synchrony to ventilator and respiratory efforts can be well recognized with graphic monitoring. Of all, it may enable detection of complications before they become clinically apparent. This article introduces the basics of real-time graphics.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.4
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• pp.447-451
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• 2010

Monitoring and analyzing the status of smart objects, the ubiquitous smart monitoring system provides several information such as user-state index, service states and system operation among the services in real time. It also provides self-optimization and self-management for enhancing the performance of services. In order to expand the application scope of this real-time monitoring system, it is indispensible to process huge amount of stream data. In this paper, we propose a load balancing scheme to solve the overload of the monitoring agents. Our proposed scheme reduces deadline miss ratio of entire data by more than 80%.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.4
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• pp.481-486
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• 2012

This thesis examines the development and application of 'Health Monitoring System' which monitors periodically the state of a pipe of petrochemical plant by using magnetostrictive sensor technology. The existing guided-wave inspection methods cannot be applied to welding part inspection in pipe, and has a limit of precision when applied to general parts because of noise, reflected waves, and so on. This technology uses the information on displacement of a defect through periodic monitoring, which makes more precise inspection, and can be utilized very usefully in a petrochemical plant.

• Educational Technology International
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• v.20 no.2
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• pp.223-255
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• 2019

The purpose of this study is to draw implications for designing online tools to support monitoring in collaborative learning. For this purpose, eighteen research papers that explored learner dashboards and group awareness tools were analyzed. The driving questions for this analysis related to the information and outcomes that must be monitored, whose performance they represent, and who monitors the extent of learning. The analytical frameworks used for this study included the following: three modes of co-regulation in terms of who regulates whose learning (self-regulation in collaborative learning, other regulation, and socially shared regulation) and four categories of dashboard information to determine which information is monitored (information about preparation, participation, interaction, and achievements). As a result, five design implications for learner dashboards that support monitoring were posited: a) Monitoring tools for collaborative learning should support multiple targets: the individual learner, peers, and the entire group; b) When supporting personal monitoring, information about the individual and peers should be displayed simultaneously to allow direct comparison; c) Information on collaborative learning achievements should be provided in terms of the content of knowledge acquired rather than test scores; d) In addition to information related to interaction between learners, the interaction between learners and learning materials can also be provided; and e) Presentation of the same information to individuals or groups should be variable.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.11
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• pp.1074-1081
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• 2011

As robotics systems are becoming more complex there is the need to promote component based robot development, where systems can be constructed as the composition and integration of reusable building block. One of the most important challenges facing component based robot development is safeguarding against software component failures and malfunctions. The health monitoring of the robot software is most fundamental factors not only to manage system at runtime but also to analysis information of software component in design phase of the robot application. And also as a lot of monitoring events are occurred during the execution of the robot software components, a simple data treatment and efficient memory management method is required. In this paper, we propose an efficient events monitoring and data management method by modeling robot software component and monitoring factors based on robot software framework. The monitoring factors, such as component execution runtime exception, Input/Output data, execution time, checkpoint-rollback are deduced and the detail monitoring events are defined. Furthermore, we define event record and monitor record pool suitable for robot software components and propose a efficient data management method. To verify the effectiveness and usefulness of the proposed approach, a monitoring module and user interface has been implemented using OPRoS robot software framework. The proposed monitoring module can be used as monitoring tool to analysis the software components in robot design phase and plugged into self-healing system to monitor the system health status at runtime in robot systems.