• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권10호
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• pp.4781-4803
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• 2017

Environmental monitoring systems using Wireless Sensor Networks (WSNs) face the challenge of high power consumption, due to the high levels of multi-hop data communication involved. In order to overcome the issue of fast energy depletion, a proof-of-concept implementation proves that adopting a clustering algorithm in environmental monitoring applications will significantly reduce the total power consumption for environment sensor nodes. In this paper, an energy-efficient WSN-based environmental monitoring system is proposed and implemented, using eight sensor nodes deployed over an area of $1km^2$, which took place in the city of Tabuk in Saudi Arabia. The effectiveness of the proposed environmental monitoring system has been demonstrated through adopting a number of real experimental studies.

• 소성∙가공
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• 제18권2호
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• pp.144-149
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• 2009

Recently, the monitoring technology of machining process is very important to improve productivity and quality in manufacturing filed. Such monitoring technology has been performed to measurement using vibration signal, acoustic emission signal and tool dynamometer. However, micro machining is limited small-scale parts machining because micro tool is very small and weakness to generate signal in micro machining process. Therefore, this study has efficient sensing technology for real monitoring system in micro machine that is proposed to supplement a disadvantage of single-sensor by multi sensor. From experimental result, it was evaluated tool wear and cutting situation according to repetitive slot cutting condition and changing cutting condition, and it was performed monitoring spindle rpm and condition according to compare acceleration signal with current signal.

• 비파괴검사학회지
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• 제28권3호
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• pp.254-262
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• 2008

The objective of the proposed study is to produce a tool-condition monitoring (TCM) strategy that will lead to a more efficient and economical drilling tool usage. Drill-wear monitoring is an important attribute in the automatic cutting processes as it can help preventing damages of the tools and workpieces and optimizing the tool usage. This study presents the architectures of a multi-layer feed-forward neural network with back-propagation training algorithm for the monitoring of drill wear. The input features to the neural networks were extracted from the AE signals using the wavelet transform analysis. Training and testing were performed under a moderate range of cutting conditions in the dry drilling of steel plates. The results indicated that the extracted input features from AE signals to the supervised neural networks were effective for drill wear monitoring and the output of the neural networks could be utilized for the tool life management planning.

• 한국공작기계학회논문집
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• 제17권1호
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• pp.77-85
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• 2008

The objective of the study is to construct a sensor fusion system for tool-condition monitoring (TCM) that will lead to a more efficient and economical drill usage. Drill-wear monitoring has an important attribute in the automatic machining processes as it can help preventing the damage of tools and workpieces, and optimizing the drill usage. In this study, we present the architectures of a multi-layer feed-forward neural network with Levenberg-Marquardt training algorithm based on sensor fusion for the monitoring of drill-wear condition. The input features to the neural networks were extracted from AE, vibration and current signals using the wavelet packet transform (WPT) analysis. Training and testing were performed at a moderate range of cutting conditions in the dry drilling of steel plates. The results show good performance in drill- wear monitoring by the proposed method of sensor fusion and neural network analysis.

• 한국컴퓨터정보학회논문지
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• 제22권6호
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• pp.79-86
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• 2017

In this paper, we implement a common module that can integrate multiple biometric information for integrated patient monitoring system. Conventional biomedical instruments have many devices attached to each patient, making it difficult to monitor abnormality signs of many patients in real time. In this paper, we propose a module for an integrated monitoring system that can perform centralized monitoring using a common module that integrates multiple measurement devices. A protocol for sending and receiving packets between the measuring device and the common module is designed, and the packets transmitted through the network are stored and managed through the integrated monitoring system and provide information to various users such as medical staff. The results of this study are expected to contribute to the management of patients and efficient medical services in hospitals.

• Mass Spectrometry Letters
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• 제10권2호
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• pp.66-70
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• 2019

Rivaroxaban (RRN) is the first available active direct factor Xa inhibitor (anticoagulant) with oral administration. Due to its success in market, there have been efforts to develop various RRN formulations, and the development of good analytical methods for its in vivo evaluation is an essential prerequisite. Thus, here, a simple and efficient method to determine RRN in rat plasma using liquid-liquid extraction (LLE) and liquid chromatography and multiple reaction monitoring (LC-MRM) was presented. The use of ethyl acetate as the LLE solvent results appropriate extraction and purification of RRN and it also helps the significant reduction of rat plasma volume required for RRN quantitation. The developed method showed good analytical performance including specificity, linearity ($r^2{\geq}0.999$ within 0.5 - 500 ng/mL), sensitivity (the lower limit of quantitation at 0.5 ng/mL), accuracy (89.3 - 107.0%), precision (${\geq}12.7%$), and recovery (89.2 - 105.7%). Additionally, RRN in sample extracts showed good stability. Finally, the applicability of the validated method to the PK evaluation of RRN was confirmed after its oral administration to normal rats. The present method is the first analytical method employing LLE for the simple and efficient extraction and purification of RRN in rat plasma. Therefore, the present method can contribute to the development of new RRN formulations as well as to the monitoring of RRN in special clinical situations through its efficient determination in various samples with or without minor modification.

• 통합자연과학논문집
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• 제8권2호
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• pp.128-134
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• 2015

This paper focuses on the applicability of a continuous monitoring method on trace sulfur compounds in the ambient air by TD and GC/PFPD. The target compounds for monitoring include H2S(hydrogen sulfide), Methyl mercaptan, Dimethyl Sulfide, and Dimethyl disulfide. The result of QA/QC on monitoring instruments satisfies all the standards of Odor Measurement and Analysis Method, showing that the reproductivity of the compounds by concentration is within 10%, linearity is above 0.98 of a correlation efficient, method detection limit is 0.16 ppb by MM standard, and recovery rate is over 70%. Monitoring was conducted for two years from March 2006 to February 2008. As a result of the monitoring, the average concentration of H2S was 0.08 ppb, with the maximum concentration at 16.15 ppb. The result indicates that it is reasonable to do continuous monitoring as there appears a spontaneous event of high concentration by the condition of the site during monitoring odor-causing substances. Therefore, it is suggested that the continuous monitoring method used in this paper is appropriate to identify the characteristics of sudden occurrence and concentration variations of sulfur compounds.

• 한국정보과학회논문지:소프트웨어및응용
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• 제37권11호
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• pp.812-825
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• 2010

서비스 지향 컴퓨팅은 서비스를 동적으로 조합하여 사용자가 요구하는 비즈니스 프로세스를 개발하는 재사용 패러다임이다. 서비스 소비자는 서비스 제공자가 제공한 인터페이스만을 통하여 서비스의 기능성을 사용한다. 즉, 서비스의 내부 상태는 블랙박스 형태로 알 수 없기 때문에 서비스 소비자는 서비스의 품질용 알 수 없고 이는 중요한 도메인에 서비스의 도입용 어렵게 만든다. 따라서 서비스 모니터링에 대한 필요성이 증가하고 있다. 하지만 서비스 내부의 정보를 실시간으로 획득하고 품질을 측정하기 어렵기 때문에 현재는 각 벤더들이 제공하는 특정 제품을 이용하여 서비스와의 상호작용 없이 모니터링이 이루어지고 있다. 하지만 이는 데이터의 포괄성, 정확성 측면에서 한계가 있고 모니터링으로 발생하는 오버헤드를 최소화 시키기 위한 효율성을 고려하지 않았기 때문에 이를 해결하기 위한 모니터링 프레임워크가 요구된다. 본 논문에서는 효율적인 서비스 모니터링을 위한 모니터링 프레임워크를 제시한다. 먼저 모니터링 프레임워크 설계 요구사항을 정의한다. 정의된 요구사항을 기반으로 모니터링 프레임워크 아키텍처를 제시하고 모니터링 데이터를 효율적으로 전송하기 위한 패턴을 제시한다. 또한 모니터링 프레임워크의 설계 및 구현을 보여주고 실험을 통해 모니터링 프레임워크의 효율성을 보여준다.

• 대한의용생체공학회:의공학회지
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• 제33권3호
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• pp.128-134
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• 2012

Currently, high-intensity laser therapy (HILT) is increasingly used in various muscle disorders like muscle tension. Our proposed study includes the development of the real-time monitoring system using a myotonometer for HILT. The developed system consists of a piezoelectric sensor and laser distance sensor for muscle stiffness monitoring during the treatments. The results demonstrated that the level of muscle tension was rapidly decreased after 3 minutes of the high-intensity laser treatment when compared to the control group. The combined HILT and realtime muscle tension monitoring system may help to evaluate the therapeutic procedure and efficient treatments for various muscle pains.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1997년도 하계학술대회 논문집 D
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• pp.764-766
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• 1997

This paper presents a DSM Monitoring Methodology which is able to evaluate the impact of DSM programs under processing. For an effective assessment of DSM programs, it is foremost necessary to examine the market characteristics on the specific end-use appliance according to the customer's adoption of DSM programs. The Proposed Monitoring system contains a diffusion process of high efficient end-use considering major factors of DSM impact such as, price, price elasticity and lifetime of end-use apparatus or appliance. The case study shows the propriety and necessity of DSM monitoring in order to diagnose the current state and provide a baseline of DSM policy