• Journal of the Korean Society for Precision Engineering
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• v.30 no.7
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• pp.673-678
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• 2013

Driving gear units can be affected by various problems, including those associated with external or internal defects in the bearing, problems with the lubricant oil, high-loading of the railway, and frequent impacts generated by rail joints. Temperature monitoring is a basic method in diagnosing abnormal conditions in the reduction gear and other components. This paper describes a new wireless monitoring system for the temperature diagnosis of abnormal conditions of the reduction gear. Integrated circuit (IC)-type temperature sensors were installed in the reduction gear box of a high-speed railway car. The temperature data from the reduction gear were acquired and analyzed in situ during high-speed rail operation. Analysis of these data was used to alert the driver and/or maintenance personnel when problems occurred.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.575-576
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• 2017

Recently, research have smart gateways can provide additional services through the IoT and Big Data. However, the existing System is number of devices connected increases to the Server, the stability of the network is degraded and data security is poor. In this paper, we design a smart gateway VPN tunneling control system based on IoT to solve these problems. we propose an effective VPN tunneling technology for low-end targets such as routers, and a method for efficiently controlling traffic in real-time in an environment where the quality of the Internet line changes dramatically. It is possible to control the sensor in the home safely through the VPN at the remote place.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.623-625
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• 2018

As the issue of particulate matter spreads, services for providing particulate matter information in real time are increasing. However, when a sensor node for collecting particulate matter is defective, a corresponding service may not be provided. To solve these problems, it is necessary to predict and deduce particulate matter. In this paper, a particulate matter prediction model is designed using artificial neural network algorithm based on past particulate matter and meteorological data to predict particulate matter. Also, the prediction results are compared by learning the input data of the model in the design stage.

• ETRI Journal
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• v.36 no.6
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• pp.913-923
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• 2014

This paper proposes a global mapping algorithm for multiple robots from an omnidirectional-vision simultaneous localization and mapping (SLAM) approach based on an object extraction method using Lucas-Kanade optical flow motion detection and images obtained through fisheye lenses mounted on robots. The multi-robot mapping algorithm draws a global map by using map data obtained from all of the individual robots. Global mapping takes a long time to process because it exchanges map data from individual robots while searching all areas. An omnidirectional image sensor has many advantages for object detection and mapping because it can measure all information around a robot simultaneously. The process calculations of the correction algorithm are improved over existing methods by correcting only the object's feature points. The proposed algorithm has two steps: first, a local map is created based on an omnidirectional-vision SLAM approach for individual robots. Second, a global map is generated by merging individual maps from multiple robots. The reliability of the proposed mapping algorithm is verified through a comparison of maps based on the proposed algorithm and real maps.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.12
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• pp.1021-1026
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• 2016

The graph-based SLAM (Simultaneous Localization and Mapping) approach has been gaining much attention in SLAM research recently thanks to its ability to provide better maps and full trajectory estimations when compared to the filtering-based SLAM approach. Even though graph-based SLAM requires batch processing causing it to be computationally heavy, recent advancements in optimization and computing power enable it to run fast enough to be used in real-time. However, data association problems still require large amount of computation when building a pose graph. For example, to find loop closures it is necessary to consider the whole history of the robot trajectory and sensor data within the confident range. As a pose graph grows, the number of candidates to be searched also grows. It makes searching the loop closures a bottleneck when solving the SLAM problem. Our approach to alleviate this bottleneck is to sample a limited number of pose nodes in which loop closures are searched. We propose a heuristic for sampling pose nodes that are most advantageous to closing loops by providing a way of ranking pose nodes in order of usefulness for closing loops.

• The Journal of the Korea institute of electronic communication sciences
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• v.5 no.3
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• pp.332-338
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• 2010

In this paper, Zigbee/PLC gateway system is designed for Ubiquitous health care. A protocol conversion algorithm for smooth information exchange between Zigbee and PLC communication has been implemented on the gatway. If a moving object is detected by wireless sensor, the data is transmitted to gateway. Zigbee/PLC gateway analyzes received data and transmits to Power Line Communication for real-time monitoring. Implemented system is can support elder who lives alone activity analysis, crime prevention system, Home network service.

• Journal of Sensor Science and Technology
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• v.5 no.3
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• pp.75-85
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• 1996

Real time water quality monitoring system in a large area has been developed. The system is hierarchically composed of CCMS(Central Control and Monitoring System), data loggers and water pollution measuring instruments, which enable systematic and efficient data collection and management. Also in this work we designed and constructed the instruments for measuring basic elements in water quality such as salinity, electrical conductivity, temperature, dissolved oxygen and the amount of coli in water.

• The Korean Journal of Physiology and Pharmacology
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• v.23 no.4
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• pp.237-249
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• 2019

Confirming the direct link between neural circuit activity and animal behavior has been a principal aim of neuroscience. The genetically encoded calcium indicator (GECI), which binds to calcium ions and emits fluorescence visualizing intracellular calcium concentration, enables detection of in vivo neuronal firing activity. Various GECIs have been developed and can be chosen for diverse purposes. These GECI-based signals can be acquired by several tools including two-photon microscopy and microendoscopy for precise or wide imaging at cellular to synaptic levels. In addition, the images from GECI signals can be analyzed with open source codes including constrained non-negative matrix factorization for endoscopy data (CNMF_E) and miniscope 1-photon-based calcium imaging signal extraction pipeline (MIN1PIPE), and considering parameters of the imaged brain regions (e.g., diameter or shape of soma or the resolution of recorded images), the real-time activity of each cell can be acquired and linked with animal behaviors. As a result, GECI signal analysis can be a powerful tool for revealing the functions of neuronal circuits related to specific behaviors.

• KIISE Transactions on Computing Practices
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• v.23 no.1
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• pp.74-79
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• 2017

The Geostationary Ocean Color Imager (GOCI), the world's first ocean color sensor operated in a geostationary orbit, can be utilized to mitigate damages by monitoring marine disasters in real time such as red tides, green algae, sargassum, cold pools, typhoons, and so on. In this paper, we described a methodology and procedure for processing GOCI data in order to maximize its utilization potential. The GOCI data processing procedure is divided into data reception, data processing, and data distribution. The kinds of GOCI data are classified as raw, level 1, and level 2. "Raw" refers to an unstructured data type immediately generated after reception by satellite communications. Level 1 is defined as a radiance data type of two dimensions, generated after radiometric and geometric corrections for raw data. Level 2 indicates an ocean color data type from level-1 data using ocean color algorithms.

• Journal of Information Technology Services
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• v.21 no.2
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• pp.97-107
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• 2022

Recently, interest in smart factories is increasing. Investments to improve intelligence/automation are also being made continuously in manufacturing plants. Facility automation based on sensor data collection is now essential. In addition, we are operating our factories based on data generated in all areas of production, including production management, facility operation, and quality management, and an integrated standard information system. When producing LCD polarizer products, it is most important to link trace information between data generated by individual production processes. All systems involved in production must ensure that there is no data loss and data integrity is ensured. The large-capacity data collected from individual systems is composed of key values linked to each other. A real-time quality analysis processing system based on connected integrated system data is required. In this study, large-capacity data collection, storage, integration and loss prevention methods were presented for optimization of LCD polarizer production. The identification Risk model of inspection products can be added, and the applicable product model is designed to be continuously expanded. A quality inspection and analysis system that maximizes the yield rate was designed by using the final inspection image of the product using big data technology. In the case of products that are predefined as analysable products, it is designed to be verified with the big data knn analysis model, and individual analysis results are continuously applied to the actual production site to operate in a virtuous cycle structure. Production Optimization was performed by applying it to the currently produced LCD polarizer production line.