• The Transactions of the Korean Institute of Electrical Engineers B
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• v.55 no.11
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• pp.572-576
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• 2006

As the increasing of capacity and technology of power facilities, rotating machines such as turbine generators and water turbines are getting higher at capacity but smaller in size. Thus the monitoring and diagnosis of generators for fault detection and protection has attracted intensive interest. Most of electrical faults of rotating machines appear in their windings. In case of an after-fault in high capacity rotating machines, the recovering cost is usually very expensive and additional time is necessary for returning in a normal situation. In this paper, the magnetic flux patterns in air-gap of a generator under various fault states as well as a normal state are simulated by a conventional FEM tool. These results are successfully applied to detection and diagnosis of the short-circuit condition in rotor windings of a high capacity generator.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.16 no.5
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• pp.145-150
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• 2007

Optical communication according to request of technology of communications and optical fiber to be full filed faster communication and pass over transmission capacity limit per unit area, per unit hour appeared, and this optical fiber acts the biggest role to influence performance of optical communication network. Optical fiber(PMF Polarization Maintaining Fiber) is used, and is used by electric field measurement, self-discipline measurement, sensor(Sensor) Department by high definition measure such as thermometry and storehouse component that use because make broad sense status and polarized light information in passageway and union with storehouse integrated circuit etc. that use broad sense interference developing could transmit in state that keep transmitting broad sense plane of polarization is polarized light existence. Also, research is developed by optical fiber for Coherent communication recently.

• The Transactions of the Korea Information Processing Society
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• v.6 no.5
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• pp.1263-1271
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• 1999

This paper designs the performance analysis layer for the various performance analysis of parallel programs using event expressions are similar to the normal program language to analyze the events which display a dynamic state exchange of a program. The event expressions suggest operations for overloading and functions which are needed in performance analysis, such as a filtering operation, data format translation functions, performance analysis, static functions, and etc. By using the event expressions, the programmer can modify the event trace data to analyze the performance and analyze more easily and variously than the pre-developed tools.

• Journal of Multimedia Information System
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• v.4 no.4
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• pp.163-170
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• 2017

Internet of things (IoT) is a new paradigm for collecting, processing and analyzing various contents in order to detect anomalies and to monitor particular patterns in a specific environment. The collected data can be used to discover new patterns and to offer new insights. IoT-enabled data mashup is a new technology to combine various types of information from multiple sources into a single web service. Mashup services create a new horizon for different applications. Environmental monitoring is a serious tool for the state and private organizations, which are located in regions with environmental hazards and seek to gain insights to detect hazards and locate them clearly. These organizations may utilize IoT - enabled data mashup service to merge different types of datasets from different IoT sensor networks in order to leverage their data analytics performance and the accuracy of the predictions. This paper presents an IoT - enabled data mashup service, where the multimedia data is collected from the various IoT platforms, then fed into an environmental cognition service which executes different image processing techniques such as noise removal, segmentation, and feature extraction, in order to detect interesting patterns in hazardous areas. The noise present in the captured images is eliminated with the help of a noise removal and background subtraction processes. Markov based approach was utilized to segment the possible regions of interest. The viable features within each region were extracted using a multiresolution wavelet transform, then fed into a discriminative classifier to extract various patterns. Experimental results have shown an accurate detection performance and adequate processing time for the proposed approach. We also provide a data mashup scenario for an IoT-enabled environmental hazard detection service and experimentation results.

• Earthquakes and Structures
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• v.22 no.5
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• pp.503-515
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• 2022

This paper presents the development of seismic fragility curves for a precast reinforced concrete bridge instrumented with a structural health monitoring (SHM) system. The bridge is located near an active seismic fault in the Dominican Republic (DR) and provides the only access to several local communities in the aftermath of a potential damaging earthquake; moreover, the sample bridge was designed with outdated building codes and uses structural detailing not adequate for structures in seismic regions. The bridge was instrumented with an SHM system to extract information about its state of structural integrity and estimate its seismic performance. The data obtained from the SHM system is integrated with structural models to develop a set of fragility curves to be used as a quantitative measure of the expected damage; the fragility curves provide an estimate of the probability that the structure will exceed different damage limit states as a function of an earthquake intensity measure. To obtain the fragility curves a digital twin of the bridge is developed combining a computational finite element model and the information extracted from the SHM system. The digital twin is used as a response prediction tool that minimizes modeling uncertainty, significantly improving the predicting capability of the model and the accuracy of the fragility curves. The digital twin was used to perform a nonlinear incremental dynamic analysis (IDA) with selected ground motions that are consistent with the seismic fault and site characteristics. The fragility curves show that for the maximum expected acceleration (with a 2% probability of exceedance in 50 years) the structure has a 62% probability of undergoing extensive damage. This is the first study presenting fragility curves for civil infrastructure in the DR and the proposed methodology can be extended to other structures to support disaster mitigation and post-disaster decision-making strategies.

• Journal of Korean Society of Environmental Engineers
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• v.39 no.5
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• pp.265-276
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• 2017

Heavy metals leaching from closed mines have been causing severe environmental problems in nearby soil ecosystems. Mine reclamation in Korea has been recently implemented based on the heavy metal immobilization (a.k.a., stabilization). Since the immobilization temporarily fixes the heavy metals to the soil matrix, the potential risk of heavy metal leaching still exists. Therefore the appropriate monitoring and the related policies are required to safeguard the soils, where all the cultivations occur. The current monitoring methods are based on either heavy metal concentration or simple toxicity test. Those methods, however, are fragmented and hence it is difficult to evaluate the site in an integrated manner. In this study, as the integrated approach, ecological functional state evaluation with a multivariate statistical tool was employed targeting physiochemical soil properties, heavy metal concentrations, microbial enzymatic activity, and arsenic respiratory reductase gene quantity. Total 60 soil samples obtained from three mines (Pungjeong, Jeomdong, Seosung) were analyzed. As a result, the stabilized layer soil and lower layer soil have shown the similar pattern in Pungjeong mine. In contrast, Jeomdong and Seosung mine have shown the similarity between the stabilized layer soil and the cover layer soil, indicating the possible contamination of the cover layer soil.

• Journal of Digital Contents Society
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• v.18 no.6
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• pp.1175-1182
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• 2017

Recent trend in the manufacturing industry is focused on the convergence with IoT and Big Data, by emergence of the 4th Industrial Revolution. To realize a smart factory, the proposed system based on MTConnect technology collects and integrates various status information of machines from many production facilities including heterogeneous devices. Also it can distribute the acquisited status of heterogeneous manufacturing machines to the remote devices. As a key technology of a flexible automated production line, the proposed system can provide much possibility to manage important information such as error detection and processing state management in the unmanned automation line.

• Journal of Microbiology and Biotechnology
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• v.20 no.1
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• pp.21-29
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• 2010

The phenolic compounds are a major contaminant class often found in industrial wastewaters and the biological treatment is an alternative tool commonly employed for their removal. In this sense, monitoring microbial community dynamics is crucial for a successful wastewater treatment. This work aimed to monitor the structure and activity of the bacterial community during the operation of a laboratory-scale continuous submerged membrane bioreactor (SMBR), using PCR and RT-PCR followed by denaturing gradient gel electrophoresis (DGGE) and 16S rRNA libraries. Multivariate analyses carried out using DGGE profiles showed significant changes in the total and metabolically active dominant community members during the 4-week treatment period, explained mainly by phenol and ammonium input. Gene libraries were assembled using 16S rDNA and 16S rRNA PCR products from the fourth week of treatment. Sequencing and phylogenetic analyses of clones from the 16S rDNA library revealed a high diversity of taxa for the total bacterial community, with predominance of Thauera genus (ca. 50%). On the other hand, a lower diversity was found for metabolically active bacteria, which were mostly represented by members of Betaproteobacteria (Thauera and Comamonas), suggesting that these groups have a relevant role in the phenol degradation during the final phase of the SMBR operation.

• Journal of Biosystems Engineering
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• v.42 no.1
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• pp.23-43
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• 2017

Purpose: As application-specific wireless sensor networks are gaining popularity, this paper discusses the development and field performance of the GHAN, a greenhouse area network system to monitor, control, and access greenhouse microenvironments. GHAN, which is an upgraded system, has many new functions. It is an intelligent wireless sensor and actuator network (WSAN) system for next-generation greenhouses, which enhances the state of the art of greenhouse automation systems and helps growers by providing them valuable information not available otherwise. Apart from providing online spatial and temporal monitoring of the greenhouse microclimate, GHAN has a modified vapor pressure deficit (VPD) fuzzy controller with an adaptive-selective mechanism that provides better control of the greenhouse crop VPD with energy optimization. Using the latest soil-matrix potential sensors, the GHAN system also ascertains when, where, and how much to irrigate and spatially manages the irrigation schedule within the greenhouse grids. Further, given the need to understand the microclimate control dynamics of a greenhouse during the crop season or a specific time, a statistical assessment tool to estimate the degree of optimality and spatial variability is proposed and implemented. Methods: Apart from the development work, the system was field-tested in a commercial greenhouse situated in the region of Punjab, India, under different outside weather conditions for a long period of time. Conclusions: Day results of the greenhouse microclimate control dynamics were recorded and analyzed, and they proved the successful operation of the system in keeping the greenhouse climate optimal and uniform most of the time, with high control performance.

• Journal of KIISE:Computing Practices and Letters
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• v.5 no.5
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• pp.639-650
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• 1999

Generally, a performance management consists of the iterative process of performance monitoring, performance analysis, and performance tuning. In this paper, we describe the design and implementation of performance monitor and performance tuner which can be used on the top of SPAX, also known as TICOM IV. SPAX has a hierarchical structure. All nodes, each of which has a local memory, are connected to the interconnection network and constructed to form clusters. Therefore, it is necessary to develop a new performance monitor reflecting the underlying hierarchical structure of SPAX, to implement performance monitoring more effectively. Implemented performance monitor can monitor the state of nodes, clusters, and total system of SPAX at realtime. And, implemented performance tuner can change the value of variables related to the performance of SPAX. System manager can perform an effective performance management by using the proposed performance management tools.