• Journal of Institute of Control, Robotics and Systems
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• v.15 no.4
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• pp.406-412
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• 2009

ECG is used on purpose to keep good health or monitor cardiac function of aged person as well as on purpose to diagnose the disease of heart patients. The ambulatory ECG monitoring system under guarantee of safety and accuracy is very efficient to prevent the progress of heart disease and sudden death. These systems can detect the temporary change of ECG that is very significant to diagnose heart disease such as myocardial ischemia, arrhyamia and cardiac infarction. In this paper, we describe the ECG signal analysis algorithm and measurement device for ECG monitoring. The authors designed a small-size portable ECG device that consisted of instrumentation amplifier, micro-controller, filter and RF module. The device measures ECG with four electrodes on the body and detects QRS complex and ST level change in realtime. Also it transmits the measured signals to the personal computer. The developed software for ECG analysis in personal computer has the function to detect the feature points and ST level changes.

• Steel and Composite Structures
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• v.50 no.6
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• pp.609-625
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• 2024

This paper presents an in-depth analysis of the nonlinear vibration of microbeams, with a particular emphasis on their application in sports monitoring systems. The research utilizes classical beam theory, modified couple stress theory, and von-Kármán nonlinear parameters to explore the behavior of microbeams. These microbeams are characterized by a non-uniform geometry, with materials that continuously change along the beam radius and a thickness that varies along the beam length. The main contribution lies in its exploration of the stability of smart sensors in sports structures, particularly those with non-uniform geometries. The research findings indicate that these non-uniform microbeams, when used in smart systems made of functionally graded temperature-dependent materials, can operate effectively in thermal environments. The smart system developed in this study demonstrates significant potential for use in sports applications, particularly in monitoring and gathering information. The insights gained from this research contribute to the understanding of the performance and optimization of microbeams in sports applications, particularly in the context of non-uniform geometries. This research, therefore, provides a foundation for the development of advanced, reliable, and efficient monitoring systems in sports applications.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.183-183
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• 2000

In this paper, web-based remote monitoring for cold-rolling system is developed and the analysis of spatial control system is performed. The remote monitoring system is able to grasp the status of cold-rolling system regardless of time and locations. We analyzed spatial control algorithm of the system with the collected data. The usefulness of spatial control system is shown by simulation studies.

• Proceedings of the KSR Conference
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• 2007.11a
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• pp.411-418
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• 2007

To analyze dynamic and long-term behavior of high speed rail system, and seismic measurements been installed at the various locations in the high speed rail system. Among these, 76 measurements were installed Chunan and Deajeon, and 80 measurements between Kwangmyung and Chunan. From these 156 measurements, real time data are continuously corrected and be sent to the main monitoring system to be used further analysis. These two systems were installed by different institution, and so there are not only basic differences in the system itself, but system running methods and data collecting/transferring methodology. There has been systematic difficulties due to these differences. This study shows the whole steps of high speed rail data monitoring systems include measurement equipment itself and data collecting/transferring system. study will proposed a more effective methods for collecting. This study also discuss the real time analysis method which can be used for future high speed rail monitoring system.

• Journal of the Korea Society of Computer and Information
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• v.23 no.4
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• pp.1-8
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• 2018

In this paper, we propose an adaptive partition cache replacement policy and evaluate the performance of our scheme using various monitoring ratios to help lifetime extension of non-volatile main memory systems without performance degradation. The proposal combines conventional LRU (Least Recently Used) replacement policy and Early Eviction Zone (E2Z), which considers a dirty bit as well as LRU bits to select a candidate block. In particular, this paper shows the performance of non-volatile memory using various monitoring ratios and determines optimized monitoring ratio and partition size of E2Z for reducing the number of writebacks using cache hit counter logic and hit predictor. In the experiment evaluation, we showed that 1:128 combination provided the best results of writebacks and runtime, in terms of performance and complexity trade-off relation, and our proposal yielded up to 42% reduction of writebacks, compared with others.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.17 no.32
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• pp.145-154
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• 1994

In this paper, monitoring processor in a circuit switched network is considered. Monitoring processor monitors communication links, and offers a grade of service in each link to controller. Such an information is useful for an effective maintenance of system. Two links with nonsymmetric system Parameters are considered. each link is assumed independent M/M/1/1 type. The Markov process is introduced to compute busy and idle portions of monitoring processor and monitored rate of each link. Inter-idle times and inter-monitoring times of monitoring processor between two links are respectively computed. A recursive formula is introduced to make computational procedure rigorous.

• Smart Structures and Systems
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• v.10 no.3
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• pp.209-228
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• 2012

Structural health monitoring with wireless sensor networks has received much attention in recent years due to the ease of sensor installation and low deployment and maintenance costs. However, sensor network technology needs to solve numerous challenges in order to substitute conventional systems: large amounts of data, remote configuration of measurement parameters, on-site calibration of sensors and robust networking functionality for long-term deployments. We present a structural health monitoring network that addresses these challenges and is used in several deployments for monitoring of bridges and buildings. Our system supports a diverse set of sensors, a library of highly optimized processing algorithms and a lightweight solution to support a wide range of network runtime configurations. This allows flexible partitioning of the application between the sensor network and the backend software. We present an analysis of this partitioning and evaluate the performance of our system in three experimental network deployments on civil structures.

• International journal of advanced smart convergence
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• v.12 no.3
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• pp.104-108
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• 2023

This paper deals with research on innovative systems using Python-based artificial intelligence technology in the field of plant growth monitoring. The importance of monitoring and analyzing the health status and growth environment of plants in real time contributes to improving the efficiency and quality of crop production. This paper proposes a method of processing and analyzing plant image data using computer vision and deep learning technologies. The system was implemented using Python language and the main deep learning framework, TensorFlow, PyTorch. A camera system that monitors plants in real time acquires image data and provides it as input to a deep neural network model. This model was used to determine the growth state of plants, the presence of pests, and nutritional status. The proposed system provides users with information on plant state changes in real time by providing monitoring results in the form of visual or notification. In addition, it is also used to predict future growth conditions or anomalies by building data analysis and prediction models based on the collected data. This paper is about the design and implementation of Python-based plant growth monitoring systems, data processing and analysis methods, and is expected to contribute to important research areas for improving plant production efficiency and reducing resource consumption.

• International Journal of Reliability and Applications
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• v.2 no.1
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• pp.57-71
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• 2001

Global competition to increase production output and to improve quality is spurring manufacturing companies to use condition monitoring and fault diagnostic systems for predictive maintenance. As monitoring, testing, and measuring techniques develop, predictive control of components and complete systems have become more practical and affordable. In this article, we will consider the computer based data acquisition system for condition monitoring and the condition parameter analysis techniques for fault detection and diagnostics in the machinery and briefly discuss reliability prediction and the limit value determination in condition monitoring.

• Journal of Information Processing Systems
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• v.7 no.2
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• pp.321-340
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• 2011

In this article, the current technological state of OPC (Openness, Productivity, and Collaboration; formerly "OLE for Process Control") standards and the problem statement of these OPC standards are discussed. The development of an OPC clientserver framework for monitoring and control systems is introduced by using the new OPC Unified Architecture (UA) specifications, Service Oriented Architecture (SOA), web services, XML, etc. The developed framework in turn minimizes the efforts of developers in learning new techniques and allows system architects and designers to perform dependency analysis on the development of monitoring and control applications. The potential areas of the proposed framework and the redundancy strategies to increase the efficiency and reliability of the system are also represented according to the initial results from the system that was developed by the Visual Studio 2008 and OPC UA SDK.