• Smart Media Journal
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• v.4 no.2
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• pp.17-25
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• 2015

In this paper proposes an idea for using NFC(Near Field Communication) on smalt mobile devices, you can easily control the electric wheelchair system. In this system with previous researches controlled a power wheelchair in a mobile device using Bluetooth communication, the board communicates with the integrated control of the wheelchair. With smart mobile devices, the wheelchair control board integrating the signal generated by checking real time so that the user can easily monitor the state of the wheelchair. Users are using smalt mobile devices, the wheelchair can be controlled easily, and the setting at any time according to the state of the individual and can be used. HEX format control is directly in hardware, allowing analysis was read, the user settings are typically used to match cards which support NFC technology such as bus card for registration, storing the selected information and enable read and were applicable. By applying this system, wheelchairs oriented aids disabled and older people able to access to provide with stability.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.4
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• pp.321-330
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• 2021

By reviewing domestic and international papers, this study examines various fields in which drones are used, and based on the results, fields are suggested in which drones can be used for the work of firefighters. Overall, the research results show that drones are most commonly used for search (51%), disaster and fire monitoring (35%), and delivery (14%). Specifically, in the search field, using a drone is more efficient in terms of manpower, equipment, time, and cost than using people, which is the current practice. Secondly, in disaster and fire monitoring, drones can analyze and identify disasters and fire sites in real time. Therefore, it was confirmed that the use of drones is helpful in securing the safety of firefighters and identifying a disaster site. Third, research in logistics shows that drones can secure the so-called golden time in emergency situations by delivering rescue and relief supplies, emergency medicine, and blood in short order. In a rapidly changing disaster environment, and considering aging in firefighters, this study is meaningful in that it promotes drone utilization in the firefighting field by investigating basic data on drone utilization plans.

• Journal of the Korean Institute of Gas
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• v.1 no.1
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• pp.27-32
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• 1997

Continual monitoring of abnormal operating conditions i a key issue in maintaining high product quality and safe operation, since the undetected process abnormality may lead to the undesirable operations, finally producing low quality products, or breakdown of equipment. The statistical projection method recently highlighted has the advantage of easily building reference model with the historical measurement data in the statistically in-control state and not requiring any detailed mathematical model or knowledge-base of process. As the complexity of process increases, however, we have more measurement variables and recycle streams. This situation may not only result in the frequent occurrence of process Perturbation, but make it difficult to pinpoint trouble-making causes or at most assignable source unit due to the confusing candidates. Consequently, an ad hoc skill to monitor and diagnose in plat-wide scale is needed. In this paper, we propose a hierarchical plant-wide monitoring methodology based on hierarchical decomposition and principal component analysis for handling the complexity and interactions among process units. This have the effect of preventing special events in a specific sub-block from propagating to other sub-blocks or at least delaying the transfer of undesired state, and so make it possible to quickly detect and diagnose the process malfunctions. To prove the performance of the proposed methodology, we simulate the Tennessee Eastman benchmark process which is operated continuously with 41 measurement variables of five major units. Simulation results have shown that the proposed methodology offers a fast and reliable monitoring and diagnosis for a large scale chemical plant.

• Korean Journal of Agricultural Science
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• v.32 no.2
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• pp.215-221
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• 2005

The residual study of pesticide has been used in various areas, such as food safety, environmental protection, establishment of tolerance, and explaining the pathway and reaction mode of pesticides, and its importance was expected to increase further more. The aspect of food safety, the pesticide residue survey have been practiced at many organizations, but there were no verification of analytical results at present. In this experiment, we focused on instrumental stability, including response of each instrument and the recovery ratio of each organization's method. As samples for this experiment, we prepared cucumber and sesame, and chose 4 pesticides (bifenthrin, chlorpyrifos, diazinon, and ethoprophos), which were mostly detected from pesticide residue survey and widely used for each crop. The standard deviation of peak areas in the chromatogram of each pesticide were under 1.212 %, so it showed that most instruments were stable. The relationship of recovery ratio of each organization were over 0.996 for every pesticide and each organization. Finally, the analytical results for pesticide residue from each participated organization were not statically significant and we could put confidence in the result from each organization.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.1
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• pp.75-84
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• 2018

Increasing the operation rate of components and stabilizing the operation through timely management of the core parts are crucial for improving the efficiency of the railroad maintenance industry. The demand for diagnosis technology to assess the condition of rolling stock components, which employs history management and automated big data analysis, has increased to satisfy both aspects of increasing reliability and reducing the maintenance cost of the core components to cope with the trend of rapid maintenance. This study developed a big data platform-based system to manage the rolling stock component condition to acquire, process, and analyze the big data generated at onboard and wayside devices of railroad cars in real time. The system can monitor the conditions of the railroad car component and system resources in real time. The study also proposed a machine learning technique that enabled the distributed and parallel processing of the acquired big data and automatic component fault diagnosis. The test, which used the virtual instance generation system of the Amazon Web Service, proved that the algorithm applying the distributed and parallel technology decreased the runtime and confirmed the fault diagnosis model utilizing the random forest machine learning for predicting the condition of the bearing and wheel parts with 83% accuracy.

• Journal of Digital Convergence
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• v.18 no.3
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• pp.171-177
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• 2020

Under the influence of the Fourth Industrial Revolution, there are many tries to promote productivity enhancement and competitiveness by adapting smart farm technology that converges ICT technologies in agriculture. This smart farming technology is emerging as a new paradigm for future growth in agriculture. The development of real-time cultivation environment monitoring and automatic control system is needed to implement smart farm. Furthermore, the development of intelligent system that manages cultivation environment using monitoring data of the growth of crops is required. In this paper, a fast and efficient development method for implementing a cloud-based smart farm management system using a highly compatible and scalable web platform is proposed. It was verified that the proposed method using the web platform is effective and stable system implementation through the operation of the actual implementation system.

• Journal of the Korean Geotechnical Society
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• v.25 no.5
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• pp.53-64
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• 2009

Many slope failures are induced by rainfall infiltration. A lot of recent researches are therefore focused on rainfall-induced slope instability and the rainfall infiltration is recognized as the important triggering factor. The rainfall infiltrates into the soil slope and makes the matric suction lost in the slope and even the positive pore water pressure develops near the surface of the slope. They decrease the resisting shear strength. In Korea, a few public institutions suggested conservative slope design guidelines that assume a fully saturated soil condition. However, this assumption is irrelevant and sometimes soil properties are misused in the slope design method to fulfill the requirement. In this study, a more relevant slope stability evaluation method is suggested to take into account the real rainfall infiltration phenomenon. Unsaturated soil properties such as shear strength, soil-water characteristic curve and permeability for Korean weathered soils were obtained by laboratory tests and also estimated by artificial neural network models. For real-time assessment of slope instability, failure warning criteria of slope based on deterministic and probabilistic analyses were introduced to complement uncertainties of field measurement data. The slope stability evaluation technique can be combined with field measurement data of important factors, such as matric suction and water content, to develop an early warning system for probably unstable slopes due to the rainfall.

• Journal of Korean Society of Steel Construction
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• v.21 no.4
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• pp.413-420
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• 2009

Heavy structures such as large roof structures and superbeams were lifted using hydraulic jacks. Moreover, member verticality and horizontality checks were performed at every construction stage to monitor the measuring tapes for their structural safety, using CCTV. When the relative displacement exceeded the predetermined limit, the hydraulic systems were terminated. After adjusting the relative displacement manually, lifting was resumed. The accuracy of the relative displacement was found not to be reliable, however, due to eye check using CCTV, and it took a long time due to manual adjustment. Moreover, real-time monitoring was impossible. To address these problems, the monitoring-evaluation system for the stable lifting of heavy structures was proposed, using the total station of the automatic-target-recognition type, laser-distance-measuring devices, a data logger, a strain gauge, and others. After developing a program for the operation of the system and for the acquisition of data, a mock-up test was conducted in a large-scale structural laboratory to evaluate the accuracy and applicability of the system. The stable acquisition and applicability of data was confirmed in the test.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.4
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• pp.119-125
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• 2022

The power supply for the anti-aircraft radar homing sensor should allow the system to receive power quickly and stably without the influence of noise. For this purpose, DC-DC converters are widely used for reliable power conversion. Also, switching of DC-DC converters Frequency noise should not cause false alarms and ghosts that may affect the detection and tracking performance of the system, and it should have a check function that can monitor power in real time while the homing sensor is operating. In order to apply to anti-aircraft radar homing sensor, we developed a multi-output switching power supply with maximum output 𐩒𐩒𐩒 W, efficiency 80% or more (@100% load), output power by receiving 28VDC input, and power supply to achieve more than 80% efficiency. A DC-DC converter was applied to this large output, and the multi-output flyback method was applied to the rest of the low-power output.

• Journal of the Korean Society of Food Science and Nutrition
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• v.42 no.3
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• pp.464-477
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• 2013

There is a great need to develop a training program proven to change behavior and improve knowledge. The purpose of this study was to evaluate employee hygiene knowledge, hygiene practice, and cleanliness, before and after HACCP system implementation at one small-size restaurant. The efficiency of the system was analyzed using time-temperature control after implementation of u-HACCP$^{(R)}$. The employee hygiene knowledge and practices showed a significant improvement (p<0.05) after HACCP system implementation. In non-heating processes, such as seasoned lettuce, controlling the sanitation of the cooking facility and the chlorination of raw ingredients were identified as the significant CCP. Sanitizing was an important CCP because total bacteria were reduced 2~4 log CFU/g after implementation of HACCP. In bean sprouts, microbial levels decreased from 4.20 logCFU/g to 3.26 logCFU/g. There were significant correlations between hygiene knowledge, practice, and microbiological contamination. First, personnel hygiene had a significant correlation with 'total food hygiene knowledge' scores (p<0.05). Second, total food hygiene practice scores had a significant correlation (p<0.05) with improved microbiological qualities of lettuce salad. Third, concerning the assessment of microbiological quality after 1 month, there were significant (p<0.05) improvements in times of heating, and the washing and division process. On the other hand, after 2 months, microbiological was maintained, although only two categories (division process and kitchen floor) were improved. This study also investigated time-temperature control by using ubiquitous sensor networks (USN) consisting of an ubi reader (CCP thermometer), an ubi manager (tablet PC), and application software (HACCP monitoring system). The result of the temperature control before and after USN showed better thermal management (accuracy, efficiency, consistency of time control). Based on the results, strict time-temperature control could be an effective method to prevent foodborne illness.