• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.22 no.3
• /
• pp.57-62
• /
• 2022

Recently, the tracking radar continues research to develop a new operation algorithm that can acquire and track a target in various environments. In general, modeling similar to the real target and environment is used to develop a new operation algorithm, but there is a limit to modeling the real environment. In this paper, a RAW data storage device was developed to efficiently develop a new operation algorithm required for the tracking radar using millimeter wave to acquire and track the target. The RAW data storage equipment is designed so that the signal processing device of the tracking radar using millimeter wave can save the RAW data output from 8 channels to OOOMSPS. RAW data storage equipment consists of data acquisition equipment and data storage equipment. The data acquisition equipment was implemented using a commercial Xilinx KCU 105 Evaluation KIT capable of high-speed data communication interface, and the data storage equipment was implemented by applying a computer compatible with the commercial Xilinx KCU 105 Evaluation KIT. In this paper, the performance of the implemented RAW data storage equipment was verified through repeated interlocking tests with the signal processing device of the millimeter wave tracking radar.

• Journal of Korean Society for Atmospheric Environment
• /
• v.23 no.E2
• /
• pp.66-73
• /
• 2007

The introduction of tracer gas techniques to ventilation studies in indoor environments provides valuable information that used to be unattainable from conventional testing environments. Data acquisition systems (DASs) containing analogue-to-digital (A/D) converters are usually used to function the key role that records signals to storage in digital format. In the testing process, there exist a number of components in the measuring equipment which may produce system-based inference to the monitored results. These unwanted fluctuations may cause significant error in data analysis, especially when non-linear algorithms are involved. In this study, a pre-processor is developed and applied to separate the unwanted fluctuations (noise or interference) in raw measurements and to reduce the uncertainty in the measurement. Moving average, notch filter, FIR (Finite Impulse Response) filters, and IIR (Infinite Impulse Response) filters are designed and applied to collect the desired information from the raw measurements. Tracer gas concentrations are monitored during leakage and ventilation tests in the model test room. The signal analysis functions are introduced to carry out the digital signal processing (DSP) work. Overall the FIR filters process the $CO_2$ measurement properly for ventilation rate and mean age of air calculations. It is found that, the Kaiser filter was the most applicable digital filter for pre-processing the tracer gas measurements. Although the IIR filters help to reduce the random noise in the data, they cause considerable changes to the filtered data, which is not desirable.

• International Journal of Internet, Broadcasting and Communication
• /
• v.13 no.3
• /
• pp.148-154
• /
• 2021

We propose the AI Smart Factory Model for integrated management of production processes in this paper .It is an integrated platform system for the production of food packaging containers, consisting of a platform system for the main producer, one or more production partner platform systems, and one or more raw material partner platform systems while each subsystem of the three systems consists of an integrated storage server platform that can be expanded infinitely with flexible systems that can extend client PCs and main servers according to size and integrated management of overall raw materials and production-related information. The hardware collects production site information in real time by using various equipment such as PLCs, on-site PCs, barcode printers, and wireless APs at the production site. MES and e-SCM data are stored in the cloud database server to ensure security and high availability of data, and accumulated as big data. It was built based on the project focused on dissemination and diffusion of the smart factory construction, advancement, and easy maintenance system promoted by the Ministry of SMEs and Startups to enhance the competitiveness of small and medium-sized enterprises (SMEs) manufacturing sites while we plan to propose this model in the paper to state funding projects for SMEs.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.24 no.1
• /
• pp.40-53
• /
• 2021

Research vessels(R/Vs) used for ocean research move to the planned research area and perform ocean observations suitable for the research purpose. The five research vessels of the Korea Institute of Ocean Science & Technology(KIOST) are equipped with global positioning system(GPS), water depth, weather, sea surface layer temperature and salinity measurement equipment that can be observed at all times during cruise. An information platform is required to systematically manage and utilize the data produced through such continuous observation equipment. Therefore, the data flow was defined through a series of business analysis ranging from the research vessel operation plan to observation during the operation of the research vessel, data collection, data processing, data storage, display and service. After creating a functional design for each stage of the business process, KIOST Underway Meteorological & Oceanographic Information System(KUMOS), a Web-Geographic information system (Web-GIS) based information platform, was built. Since the data produced during the cruise of the R/Vs have characteristics of temporal and spatial variability, a quality management system was developed that considered these variabilities. For the systematic management and service of data, the KUMOS integrated Database(DB) was established, and functions such as R/V tracking, data display, search and provision were implemented. The dataset provided by KUMOS consists of cruise report, raw data, Quality Control(QC) flagged data, filtered data, cruise track line data, and data report for each cruise of the R/V. The business processing procedure and system of KUMOS for each function developed through this study are expected to serve as a benchmark for domestic ocean-related institutions and universities that have research vessels capable of continuous observations during cruise.

• Korean journal of food and cookery science
• /
• v.21 no.3 s.87
• /
• pp.290-300
• /
• 2005

Increased sanitation management of foodservice establishments is required because most of the reported foodborne-disease outbreaks were in the foodservice industry. The purpose of this study was to determine the important control points for good sanitation. In this study, we inspected twenty foodservice establishments in Seoul, Kyunggi, Kyungnam with a self-developed monitoring tool. These foodservice establishments included secondary schools, universities, and industries. Six of them had appointed as the HACCP-certified establishments from the Korea Food and Drug Administration. The inspection was conducted from June to August in 2002. The inspection tool consisted of nine dimensions and sixty-five items. The dimensions were 'personal sanitation', 'supply of raw food', 'food storage', 'handling of raw food and ready-to-eat', 'cleaning and sterilization', 'waste control', 'pest control', and 'control of establishment and equipment' The highest possible score of this inspection tool is 105 points. Statistical data analysis was completed using the SPSS Package(11.0) for descriptive analysis Kruskal-Wallis. The score for the secondary schools (83.6 points) was higher than for the others and number of in compliance item was 50.9 on average. Therefore, we concluded that the secondary schools' sanitation condition was good. The foodservice establishments acquired HACCP certification was 89.7 points, which was significantly higher than that of establishments not applying foodservices in total score. Instituting the HACCP system in a foodservice is very effective for sanitation management. Many out of the compliance observations were found in the dimensions of 'waste control', 'control of establishment and equipment', and 'supply of raw food' 'Clean condition of refrigerator' item was $65\%$ out of the compliance that was the highest percent in this study. 'Notify and observance of heating/reheating temperature' was $45\%$ out of compliance. Items which were over $30\%$ out of compliance were 'sterilization of knifes and chopping boards in cooking', 'education of workers', 'maintain refrigerator temperature blow $5^{\circ}C$', and 'countermeasure of infection workers' In the results, most of the foodservice establishments were poorly managed in temperature control and cross-contamination. The important control points revealed in this study were preventing contamination, cooking temperature compliance, management of raw food and refrigerator. Therefore foodservice establishments should pay attention to education and training about important control points. The systematic sanitation management monitoring tool developed in this study can be effectively applied for conducting self-inspection and improving the sanitary conditions of their own foodservice operations.