• Convergence Security Journal
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• v.22 no.1
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• pp.29-38
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• 2022

The importance of prevention of epidemics is increasing due to the serious spread of infectious diseases. For prevention of epidemics, we need to focus on the non-contact industry. Therefore, in this paper, a face recognition door lock that controls access through non-contact is designed and developed. First very simple features are combined to find objects and face recognition is performed using Haar-based cascade algorithm. Then the texture of the image is binarized to find features using LBPH. An non-contact door lock system which composed of Raspberry PI 3B+ board, an ultrasonic sensor, a camera module, a motor, etc. are suggested. To verify actual performance and ascertain the impact of light sources, various experiment were conducted. As experimental results, the maximum value of the recognition rate was about 85.7%.

• Journal of Korean Society of Archives and Records Management
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• v.24 no.1
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• pp.111-136
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• 2024

This study aims to identify the current status of the village citizen archivist training program (hereinafter "training program") and propose a competency-based training program operational model to improve it. With the steadily increasing number of training programs, revitalizing programs and systemizing operations become imperative. This study focuses on achieving the program's goals, the competence of village citizen archivists, and the continuity of training programs and archiving activities. To this end, the meaning and role of village citizen archivists were investigated through domestic and international literature. Moreover, the current status of training programs from 2015 to 2023 was identified, and the implications of literature reviews and case studies were verified through interviews with the program educators. The implications of the interview were summarized as the program operational plan for each goal, the competence of village citizen archivists, and the development plan, thereby being reflected in the operational model. The competency-based education program operational model was proposed to incorporate a model structure, design principles, curricular modules for each goal, and considerations for each stage of education program operation.

• Tunnel and Underground Space
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• v.34 no.2
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• pp.154-168
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• 2024

The Tunnel Boring Machine (TBM) disc cutter is subjected to wear and damage during the rock excavation process, and the worn disc cutter should be replaced on time. The manual inspection by workers is generally required to determine the disc cutter replacement. In this case, the workers are exposed to dangerous environments, and the measurements are sometimes inaccurate. In this study, we developed a technology that measures the disc cutter wear in real time. From a series of laboratory tests, a magnetic sensor was selected as the wear sensor, and the real-time disc cutter measurement system was developed integrating wireless communication modules, power supply and data processing board. In addition, the measurement system was verified in actual TBM excavation circumstances. As a result, it was confirmed that the accuracy and stability of the system.

• The Journal of Bigdata
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• v.8 no.2
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• pp.83-95
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• 2023

Big data analytics and AI play a critical role in the development of smart plants. This study presents a big data platform for plant data and an 'AutoML platform' for AI-based plant O&M(Operation and Maintenance). The big data platform collects, processes and stores large volumes of data generated in plants using Hadoop, Spark, and Kafka. The AutoML platform is a machine learning automation system aimed at constructing predictive models for equipment prognostics and process optimization in plants. The developed platforms configures a data pipeline considering compatibility with existing plant OISs(Operation Information Systems) and employs a web-based GUI to enhance both accessibility and convenience for users. Also, it has functions to load user-customizable modules into data processing and learning algorithms, which increases process flexibility. This paper demonstrates the operation of the platforms for a specific process of an oil company in Korea and presents an example of an effective data utilization platform for smart plants.

• Journal of Korean Tunnelling and Underground Space Association
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• v.2 no.2
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• pp.11-21
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• 2000

Tunnelling has been created as a great extent in view of less land space available because the growth of population in metropolitan has been accelerated at a faster pace than the development of the cities. In tunnelling, it is often faced that measures are obliged to be taken without confirmation for such abnormality as diverged movement of surrounding rock mass, growing crack of shotcrete and yielding of rockbolts. In this case, it is usually said that the judgments of experienced engineers for the selection of measure are importance and allowed us to get over the situations in many construction sites. But decrease of such experienced engineers need us to develop the new system to assist the selection of measures for the abnormality without any experiences of similar tunnelling sites. In this study, After a lot of tunnelling reinforcement methods were surveyed and the detail application were studied, an expert system was developed to predict the safety of tunnel and choose proper tunnel reinforcement system using fuzzy quantification theory and fuzzy inference rule based on tunnel information database. The expert system developed in this study have two main parts named pre-module and post-module. Pre-module decides tunnel information imput items based on the tunnel face mapping information which can be easily obtained in-situ site. Then, using fuzzy quantification theory II, fuzzy membership function is composed and tunnel safety level is inferred through this membership function. The comparison result between the predicted reinforcement system level and measured ones was very similar. In-situ data were obtained in three tunnel sites including subway tunnel under Han river. This system will be very helpful to make the most of in-situ data and suggest proper applicability of tunnel reinforcement system developing more resonable tunnel support method from dependance of some experienced experts for the absent of guide.

• The KIPS Transactions:PartC
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• v.13C no.1 s.104
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• pp.83-94
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• 2006

This paper describes ATM cell encipherment method using Rijndael Algorithm adopted as an AES(Advanced Encryption Standard) by NIST in 2001. ISO 9160 describes the requirement of physical layer data processing in encryption/decryption. For the description of ATM cell encipherment method, we implemented ATM data encipherment equipment which satisfies the requirements of ISO 9160, and verified the encipherment/decipherment processing at ATM STM-1 rate(155.52Mbps). The DES algorithm can process data in the block size of 64 bits and its key length is 64 bits, but the Rijndael algorithm can process data in the block size of 128 bits and the key length of 128, 192, or 256 bits selectively. So it is more flexible in high bit rate data processing and stronger in encription strength than DES. For tile real time encryption of high bit rate data stream. Rijndael algorithm was implemented in FPGA in this experiment. The boundary of serial UNI cell was detected by the CRC method, and in the case of user data cell the payload of 48 octets (384 bits) is converted in parallel and transferred to 3 Rijndael encipherment module in the block size of 128 bits individually. After completion of encryption, the header stored in buffer is attached to the enciphered payload and retransmitted in the format of cell. At the receiving end, the boundary of ceil is detected by the CRC method and the payload type is decided. n the payload type is the user data cell, the payload of the cell is transferred to the 3-Rijndael decryption module in the block sire of 128 bits for decryption of data. And in the case of maintenance cell, the payload is extracted without decryption processing.

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.449-461
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• 2021

Analysis Ready Data (ARD) for optical satellite images represents a pre-processed product by applying spectral characteristics and viewing parameters for each sensor. The atmospheric correction is one of the fundamental and complicated topics, which helps to produce Top-of-Atmosphere (TOA) and Top-of-Canopy (TOC) reflectance from multi-spectral image sets. Most remote sensing software provides algorithms or processing schemes dedicated to those corrections of the Landsat-8 OLI sensors. Furthermore, Google Earth Engine (GEE), provides direct access to Landsat reflectance products, USGS-based ARD (USGS-ARD), on the cloud environment. We implemented the Orfeo ToolBox (OTB) atmospheric correction extension, an open-source remote sensing software for manipulating and analyzing high-resolution satellite images. This is the first tool because OTB has not provided calibration modules for any Landsat sensors. Using this extension software, we conducted the absolute atmospheric correction on the Landsat-8 OLI images of Railroad Valley, United States (RVUS) to validate their reflectance products using reflectance data sets of RVUS in the RadCalNet portal. The results showed that the reflectance products using the OTB extension for Landsat revealed a difference by less than 5% compared to RadCalNet RVUS data. In addition, we performed a comparative analysis with reflectance products obtained from other open-source tools such as a QGIS semi-automatic classification plugin and SAGA, besides USGS-ARD products. The reflectance products by the OTB extension showed a high consistency to those of USGS-ARD within the acceptable level in the measurement data range of the RadCalNet RVUS, compared to those of the other two open-source tools. In this study, the verification of the atmospheric calibration processor in OTB extension was carried out, and it proved the application possibility for other satellite sensors in the Compact Advanced Satellite (CAS)-500 or new optical satellites.

• Journal of Korea Society of Industrial Information Systems
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• v.18 no.5
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• pp.81-92
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• 2013

The satellite includes many release mechanisms such as solar array deployment, antenna deployment, cover to protect contamination in scientific equipment, pyro value of the propulsion subsytem, and bypass device in Li-Ion cell module. A drive the initiators is a critical to the successful mission because the initiators of release mechanism driving by the pyrotechnic circuit is operated in single short. The pyrotechnic circuit has to provide switching network for safety. A typical switching network has defect consisting of high current rating fire switch to handle switching transient current during fire the initiator. The pyrotechnic circuit is required some form of power conditioning to reduce the peak power demanded from the bus if the initiators are to be fired from the main bus. This paper design a pyrotechnic circuit synchronized to the fire-command to activate the fire switch to overcome use high current rating fire switch to handle switching transient current during fire the initiator. The pyrotechnic circuit provides a current limited widow pulse for fire current synchronized to the fire-command to insure that fire switch will only carry the current but never switch it. The current limited widow pulse for fire current can be possible to use low current rating and light mass switch in switching network. The current limit function in the pyrotechnic circuit reduces supply voltage to initiator and provides the effect of power conditioning function to reduce peak bus power. The pyrotechnic circuit to apply satellite development on geostationary orbit is verified the function by test in development model.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.12
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• pp.855-864
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• 2013

Decision tree classification is one of the important problems in data mining fields and data minings have been important tasks in the fields of large database technologies. Therefore the coupling efforts of data mining systems and database systems have led the developments of database primitives supporting data mining functions such as decision tree classification. These primitives consist of the special database operations which support the SQL implementation of decision tree classification algorithms. These primitives have become the consisting modules of database systems for the implementations of the specific algorithms. There are two aspects in the developments of database primitives which support the data mining functions. The first is the identification of database common primitives which support data mining functions by analysis. The other is the provision of the extended mechanism for the implementations of these primitives as an interface of database systems. In data mining, some primitives want be stored in DBMS is one of the difficult problems. In this paper, to solve of the problem, we describe the database primitives which construct and apply the optimized decision tree classifiers. Then we identify the useful operations for various classification algorithms and discuss the implementations of these primitives on the commercial DBMS. We implement these primitives on the commercial DBMS and present experimental results demonstrating the performance comparisons.

• Journal of KIISE
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• v.44 no.9
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• pp.932-945
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• 2017

In this paper, a new hardware and software architecture for a stereo vision processing system including rectification, disparity estimation, and visualization was developed. The developed method, named LArge scale stereo matching method using Support Point Interpolation (LASPI), shows excellence in real-time processing for obtaining dense disparity maps from high quality image regions that contain high density support points. In the real-time processing of high definition (HD) images, LASPI does not degrade the quality level of disparity maps compared to existing stereo-matching methods such as Efficient LArge-scale Stereo matching (ELAS). LASPI has been designed to meet a high frame-rate, accurate distance resolution performance, and a low resource usage even in a limited resource environment. These characteristics enable LASPI to be deployed to safety-critical applications such as an obstacle recognition system and distance detection system for autonomous vehicles. A Field Programmable Gate Array (FPGA) for the LASPI algorithm has been implemented in order to support parallel processing and 4-stage pipelining. From various experiments, it was verified that the developed FPGA system (Xilinx Virtex-7 FPGA, 148.5MHz Clock) is capable of processing 30 HD ($1280{\times}720pixels$) frames per second in real-time while it generates disparity maps that are applicable to real vehicles.