• Proceedings of the KIEE Conference
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• 2005.07b
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• pp.1315-1317
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• 2005

Generally, the high Tc superconductor(HTS) doesn't generate any loss in DC condition, but generate considerable loss in AC condition. Until now AC loss in superconductor has been researched on measuring method of short sample by using electrical method and magnetization method. But it is not easy to estimate AC loss in high class magnet system with results of measuring AC Joss in short sample. In this paper, we carry out research on measuring method by using calorimetric method used in measuring AC loss in high class magnet system. We make the inductive and non-inductive superconducting magnet and measure the generated AC loss, then we compare the measured results with the calculated results using Norris equation. This measuring method of AC loss using calorimetric method can measure not only AC loss in superconducting magnet but losses in conducting, radiant and low temperature. Consequently it is thought that efficient design and fabrication of superconducting magnet system will be possible by means of AC loss measurement method using calorimetric method.

• The KIPS Transactions:PartD
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• v.16D no.4
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• pp.613-620
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• 2009

It is necessary to develop a system of judging whether or not the parts are defective easily at low cost, especially in a small scale factory which manufactures a large variety of products in small amounts. To develop such system, we require to recognize objects using human's cognitive ability under various circumstances. Human's high intelligence originates mostly from neocortex of human brain. The HTM theory, which is proposed by Jeff Hopkins, is one of the recent researches to model the operation principle of neocortex. In this paper we developed PRESM (Parts image REcognition System for small scale Manufacturing industry) system based on the HTM theory to judge badness of manufactured products. As a result of application to the real field of workplace environments we identified the superiority of our recognition system.

• KIPS Transactions on Computer and Communication Systems
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• v.5 no.9
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• pp.247-260
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• 2016

Sensor networks have been used in many applications such as smart home, smart factory, etc. based on sensor data. Sensor networks can change system requirements and architectures depending on their application areas. Currently, sensor network application cases in ocean environments are very rare because the ocean environments have much difficult accessibility more poor conditions, higher wave heights, more frogs, much heavier salinity, etc., compared with ground environments. In this paper, we propose the requirements, architecture and design of a sensor network system for the littoral sea cage culture monitoring and we also introduce its operation results through the development. The developed system based on our research provides users with functionalities to extract, monitor, and manage underwater environmental conditions suitable to littoral sea cage culturing of fishes.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.10a
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• pp.552-555
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• 2010

In this paper, we propose a context-aware system using wireless multi sensor module to monitor the state for industrial factory environment. Wireless multi sensor module combines sensing values which are collected from each acceleration, pressure, temperature and gas sensors. Moreover, it delivers this data to server after being encoded by RS code. Thereafter, RS decoder decodes the values that are received from wireless multi sensor module and fixes errors which occur in wireless communication. Based on decoded data, context-aware algorithm sets critical range and compares it to the sensing values, if the sensing values are out of the range, an event occurs by the algorithm. At the same time, if there is another sensing value which is out of the range for standby time T seconds, the algorithm orders 3 steps-alarm to occur depending on each situation. Through this system, it becomes eventually possible to monitor machines' condition effectively. From the simulation, we confirm that this system is efficient to status monitoring of industrial automation equipment.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.11
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• pp.2069-2076
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• 2008

In this paper, we develop an electrostatic monitoring system which is composed of an electrostatic prediction system and a warning message transmission system. The electrostatic prediction system in a factory receives the value of electrostatic charge from the electrostatic sensor and predicts the next value by using past data and sends the value to the warning message transmission system through the bluetooth communication. The warning message transmission system gets a warning signal and transmits the warning message to the worker's cellphone through a commercial SMS web by a socket program running on Windows PC in a control room. We propose electrostatic forecasting algorithms based on LSR(least square regression) using weight factors in an electrostatic prediction system. Simulation results show that the algorithm with dynamically variable weight factors is best with 64.69V standard deviation and a warning message transmitted by the warning message transmission system is displayed on cellphone after about 5 seconds.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.5
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• pp.47-52
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• 2021

Recently, demand for artificial intelligence solutions for production process management has been increasing in the manufacturing industry. However, through the application of AI solutions in the manufacturing industry, there are limitations to legacy smart factory solutions such as POP and MES.Therefore, in order to overcome this, this paper aims to improve production management efficiency by applying guidance, an artificial intelligence concept, to image recognition systems. In the system flow, As_is To be separated and actual work flow was applied, and the process was improved for overall productivity efficiency. The pre-processing plan for AI guidance learning was established and the relevant AI model was designed, developed, and simulated, resulting in a 97% recognition rate.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.9
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• pp.1144-1151
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• 2021

The pressing process is a compression process in which a product is made by applying force to a heated or unheated material to transform it into the desired shape. Due to the characteristics of press equipment that produces products through continuous compression for a short time, product defects occur continuously, and systems for solving these problems are being developed using various technologies. This paper proposes a real-time defect detection system based on an artificial intelligence algorithm that detects defects. By attaching various sensors to the press device, the relationship between equipment status and defects is defined and collected based on a big data platform. By developing an artificial intelligence algorithm based on the collected data and implementing the developed algorithm using an embedded board, we will show the practicality of the system by applying it to the actual field.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.12
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• pp.1691-1697
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• 2018

There has been a steady study of unmanned vehicle. So far, continuous research has brought news of the commercialization of unmanned vehicle. In addition, it has been applied in a variety of fields with another industry. A lot of research has been done, too, to apply inert driving indoors. Using LoRa network, which is a network dedicated to IoT, unmanned vehicle control system that is applied to LoRa network from a small space, or from an office hospital to a factory, is installed to increase efficiency when the performs special tasks. This paper presents solutions to a variety of problems by using LoRa network, which is dedicated to IoT, to recognize an unmanned vehicle as a single object, to communicate with surrounding objects, and to receive information necessary for driving indoors from a cloud server.

• Journal of Korean Society of Rural Planning
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• v.24 no.4
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• pp.15-25
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• 2018

This study was designed to understand the change of rural landscape and to consider problems followed by development restrictions lifted for Neobiul Village in Ansan City, Korea. Physical landscape changes were comprehended by a field study and interview with local residents, and the residents' perception regarding the landscape changes were analyzed with the REP investigation method. The results can be summarized into the following three points: First, due to the lift of development restrictions and the deregulation of land use, the number of factories and warehouses for rent increased, which became a new source of income for the village. Second, the residents' complaints increased due to the increased traffic volume and waste from a sudden influx of factories and warehouses, which could not be handled by a small farming village. Third, a mix of landscape combining both city and farming village was formed due to the influx of external capital and the need of rental income, although the residents rather wanted Neobiul Village to become a residential village than a factory location. Furthermore, even in the farmlands near the village where development restrictions have not been lifted, the level of dependence on the farming industry has decreased as a consequence of the increase in farmland rent and weekend farms. This paper confirmed that the change of rural landscape followed by lifted development restrictions affects the everyday life of residents living in Neobiul Village. This study has significant implications in that it suggests a case showing the effects of national policies such as lifting development restrictions for rural villages in suburban areas.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.1
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• pp.63-68
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• 2019

Emerging applications such as Smart factory, in-car network, wide area power network require strict bounds on the end-to-end network delays. Flow-based scheduler in traditional Integrated Services (IntServ) architecture could be possible solution, yet its complexity prohibits practical implementation. Sub-optimal class-based scheduler cannot provide guaranteed delay since the burst increases rapidly as nodes are passed by. Therefore a leaky-bucket type regulator placed next to the scheduler is being considered widely. This paper proposes a simple server that achieves both fair scheduling and traffic regulation at the same time. The performance of the proposed server is investigated, and it is shown that a few msec delay bound can be achieved even in large scale networks.