• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.35 no.5
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• pp.459-465
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• 2022

This paper reports a method to use a wireless sensor network deployed in the field to real-time monitor soil moisture, warning when the moisture level reaches a specific value, and wirelessly controlling an additional device (LED or water supply system, etc.). In addition, we report all processes related to wireless irrigation system, including field deployment of sensors, real-time monitoring using a smartphone, data calibration, and control of additional devices deployed in the field by smartphone. A commercially available open-source Internet of Things (IoT) platform, NodeMCU, was used, which was combined with a 9V battery, LED and soil humidity sensor to be integrated into a portable prototype. The IoT-based soil humidity sensor prototype deployed in the field was installed next to a tree for on-site demonstration for the measurement of soil humidity in real-time for about 30 hours, and the measured data was successfully transmitted to a smartphone via Wifi. The measurement data were automatically transmitted via e-mail in the form of a text file, stored on the web, followed by analyses and calibrations. The user can check the humidity of the soil real-time through a personal smartphone. When the humidity of a soil reached a specific value, an additional device, an LED device, placed in the field was successfully controlled through the smartphone. This LED can be easily replaced by other electronic devices such as water supplies, which can also be controlled by smartphones. These results show that farmers can not only monitor the condition of the field real-time through a sensor monitoring system manufactured simply at a low cost but also control additional devices such as irrigation facilities from a distance, thereby reducing unnecessary energy consumption and helping improve agricultural productivity.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.27 no.10
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• pp.1361-1369
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• 2003

Design performance of hybrid power generation systems, comprised of a gas turbine and an atmospheric pressure molten carbonate fuel cell, has been analyzed. Two different configurations were analyzed and performances were compared. A reference calculation was performed for the design condition of a system under development and simulated results agreed well with the published data. Performances were analyzed in terms of main design parameters including turbine inlet temperature, operating temperature of the fuel cell and pressure ratio. Also examined were the effects of fuel utilization factor and heat exchanger effectiveness. It was found that the relationship between the turbine inlet temperature and the fuel cell temperature should be critically examined to evaluate achievable design performance. Considering current state of the art technologies, a system with the combustor located before the turbine could achieve higher efficiency and specific power than the other system with the combustor located after the turbine.

• Journal of Advanced Marine Engineering and Technology
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• v.36 no.5
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• pp.662-673
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• 2012

This study introduces a condition diagnosis technique for a turbine governor system. The governor system is an important control system to handle turbine speed in a nuclear power plant. The turbine governor system includes turbine valves and stop valves which have their own functions in the system. Because a turbine governor system is operated by high oil pressure, it is very difficult to maintain under stable operating conditions. Turbine valves supply oil pressure to the governor system for proper operation. Using the pressure variation of turbine and governor valves, operating conditions of the turbine governor control system are detected and identified. To achieve automatic detection of valve status, time-based and frequency-based analysis is employed. In this study, a new approach, wavelet decomposition, was used to extract specific features from the pressure signals of the governor and stop valves. The extracted features, which represent the operating conditions of the turbine governor system, include important information to control and diagnose the valves. After extracting the specific features, decision rules were used to classify the valve conditions. The rules were generated by a decision tree algorithm (a typical simple method for data-based rule generation). The results given by the wavelet-based analysis were compared to detection results using time- and frequency-based approaches. Compared with the several related studies, the wavelet transform-based analysis, the proposed in this study has the advantage of easier application without auxiliary features.

• Mycobiology
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• v.34 no.1
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• pp.7-13
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• 2006

Arbuscular mycorrhizas (AM) have mutualistic symbiosis with plants and thus efforts have been placed on application of these symbiotic relationships to agricultural and environmental fields. In this study, AM fungi were collected from 25 sites growing with 16 host plant species in Korea and cultured with Sorghum bicolor in greenhouse condition. AM fungal spores were extracted and identified using both morphological and molecular methods. Using morphological characters, total 15 morpho-speices were identified. DNA was extracted from single spore of AM fungi and a partial region on 18S rDNA was amplified using nested PCR with AM fungal specific primers AML1/AML2. A total of 36 18S rDNA sequences were analyzed for phylogenetic analysis and 15 groups of AM fungi were identified using both morphological and molecular data of spores. Among the species, 4 species, Archaeospora leptoticha, Scutellospora castanea, S. cerradensis, S. weresubiae were described for the first time in Korea and two species in Glomus and a species in Gigaspora were not identified. Morphological and molecular identification of AM fungal spores in this study would help identify AM fungal community colonizing roots.

• Child Health Nursing Research
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• v.22 no.1
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• pp.54-60
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• 2016

Purpose: The purpose of this study was to evaluate levels and correlations of epilepsy specific knowledge, attitude and anxiety in mothers of children with epilepsy. Methods: Participants were 176 mothers of children with epilepsy living in B and Y cities. Data were analyzed using descriptive statistics, t-test, ANOVA, and Pearson correlation coefficients with the SPSS 21.0 program. Results: Participants scored 57.2 (${\pm}1.7$) out of 100 points on epilepsy-related knowledge; 35.6 (${\pm}5.0$) out of 48 points on attitude toward epilepsy; 58.1 (${\pm}15.3$) out of 85 on anxiety related to a child's epileptic condition. The participants had higher levels of epilepsy-related knowledge if their family monthly income was three million KRW or higher (t=-2.92, p=.004); if there was no side effect from the medication (t=-2.91, p=.004); and if the mothers' perception of the child's health was good (F=6.181, p=.001). There was a positive correlation between knowledge and attitude related to epilepsy (r=.321, p<.001), and a negative correlation between knowledge and anxiety (r=-.257, p=.001). Conclusion: Findings indicate that interventions which reduce mothers' anxiety by providing epilepsy specific knowledge and help to achieve more positive attitudes to better ways of coping with child's disease.

• Journal of the Korean Society of Propulsion Engineers
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• v.8 no.4
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• pp.84-90
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• 2004

A performance evaluation is made in terms of thrust, impulse bit. and specific impulses for a set of mono-propellant hydrazine thrusters producing 0.95 lbf of nominal thrust at an inlet pressure of 350 psia. With a brief description on the hot-firing test configuration and procedures. a typical data obtained from steady-state firing mode is given directly showing the variational behavior of propellant supply pressure, mass flow rate, vacuum condition, and thrust. The performance features are successfully compared to the reference criteria of 1-lbf standard mono-propellant rocket engine. Additionally. a statistical inter-thruster treatment is concisely depicted for the justification of selected thrusters as a grouped member of flight model for spacecraft propulsion system.

• Korean Institute of Interior Design Journal
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• no.18
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• pp.31-37
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• 1999

This study aims to provide architectural basis of the new space planning in university library and anticipate direction in future. This study is to analyze the spatial transition in the existing facility, based on field observation of the domestic university library and on theoretical data from the related article. The result that include a transition of the existing facility and the present is as following as below. 1) Spatial transitions by networking are making specific system room. The minimum area of this specific system room is 33.95$m^2$. 2) Spatial transition by information service is forming computer room. the minimum area of a environmental carrel, which is possibly located to computer room, is 2.98~3.42$m^2$. 3) Spatial transition by spreading multimedia information is to make the multimedia information is to make the multimedia room. It is necessary to independent, flexibility, and extensionable space. 4) Library interior spatial transition by developing information technology is prospected that in case of reading room, office enlarge the scale, in case of stack decrease the scale. The university library must be kept up their function and also be functioned as electronic library which serve new information.

• Smart Structures and Systems
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• v.30 no.6
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• pp.613-626
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• 2022

Guaranteeing the quality and integrity of structural health monitoring (SHM) data is very important for an effective assessment of structural condition. However, sensory system may malfunction due to sensor fault or harsh operational environment, resulting in multiple types of data anomaly existing in the measured data. Efficiently and automatically identifying anomalies from the vast amounts of measured data is significant for assessing the structural conditions and early warning for structural failure in SHM. The major challenges of current automated data anomaly detection methods are the imbalance of dataset categories. In terms of the feature of actual anomalous data, this paper proposes a data anomaly detection method based on data-level and deep learning technique for SHM of civil engineering structures. The proposed method consists of a data balancing phase to prepare a comprehensive training dataset based on data-level technique, and an anomaly detection phase based on a sophisticatedly designed network. The advanced densely connected convolutional network (DenseNet) and Transformer encoder are embedded in the specific network to facilitate extraction of both detail and global features of response data, and to establish the mapping between the highest level of abstractive features and data anomaly class. Numerical studies on a steel frame model are conducted to evaluate the performance and noise immunity of using the proposed network for data anomaly detection. The applicability of the proposed method for data anomaly classification is validated with the measured data of a practical supertall structure. The proposed method presents a remarkable performance on data anomaly detection, which reaches a 95.7% overall accuracy with practical engineering structural monitoring data, which demonstrates the effectiveness of data balancing and the robust classification capability of the proposed network.

• Journal of the Ergonomics Society of Korea
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• v.33 no.1
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• pp.69-76
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• 2014

Objective: This study aims to present literature providing researchers with insights on specific fields of research and highlighting the major issues in the research topics. A systematic review is suggested using content analysis on literatures regarding "visual search", "eye movement", and "eye track". Background: Literature review can be classified as "narrative" or "systematic" depending on its approach in structuring the content of the research. Narrative review is a traditional approach that describes the current state of a study field and discusses relevant topics. However, since literatures on specific area cover a broad range, reviewers inherently give subjective weight on specific issues. On the contrary, systematic review applies explicit structured methodology to observe the study trends quantitatively. Method: We collected meta-data of journal papers using three search keywords: visual search, eye movement, and eye track. The collected information contains an unstructured data set including many natural languages which compose titles and abstracts, while the keyword of the journal paper is the only structured one. Based on the collected terms, seven categories were evaluated by inductive categorization and quantitative analysis from the chronological trend of the research area. Results: Unstructured information contains heavier content on "stimuli" and "condition" categories as compared with structured information. Studies on visual search cover a wide range of cognitive area whereas studies on eye movement and eye track are closely related to the physiological aspect. In addition, experimental studies show an increasing trend as opposed to the theoretical studies. Conclusion: By systematic review, we could quantitatively identify the characteristic of the research keyword which presented specific research topics. We also found out that the structured information was more suitable to observe the aim of the research. Chronological analysis on the structured keyword data showed that studies on "physical eye movement" and "cognitive process" were jointly studied in increasing fashion. Application: While conventional narrative literature reviews were largely dependent on authors' instinct, quantitative approach enabled more objective and macroscopic views. Moreover, the characteristics of information type were specified by comparing unstructured and structured information. Systematic literature review also could be used to support the authors' instinct in narrative literature reviews.

• Journal of the Society of Naval Architects of Korea
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• v.60 no.2
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• pp.135-145
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• 2023

Developing high-fidelity Computational Fluid Dynamics (CFD) simulation methods used to evaluate the airwake characteristics along a flight deck of a large ship, the various kind of data such as actual ship measurement and wind tunnel results are required to verify the accuracy of CFD simulation. Inflow velocity profile at the bow, local unsteady flow field data around the flight deck, and highly reliable wind tunnel data which were measured after reviewing Atmospheric Boundary Layer (ABL) simulation and Reynolds Number effects were also used to determine the key parameters such as turbulence model, time resolution and accuracy, grid resolution and type, inflow condition, domain size, simulation length, and so on in STAR CCM⁺. Velocity ratio and turbulent intensity difference between Full-scale CFD and actual ship measurement at the measurement points show less than 2% and 1.7% respectively. And differences in velocity ratio and turbulence intensity between wind tunnel test and small-scale CFD are both less than 2.2%. Based upon this fact, the selected parameters in CFD simulation are highly reliable for a specific wind condition.