• 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 Platform Technology
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• v.11 no.6
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• pp.106-115
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• 2023

In this paper, we propose a sensor data sharing system for the safe and smooth operation of autonomous vehicles on two-way single lanes in traffic-isolated areas and implement the core module, the situational awareness technology. Two-way single lanes pose challenges for autonomous vehicles, particularly when encountering parked vehicles or oncoming traffic, leading to reversing issues. We introduce a system using infrastructure cameras to detect vehicles' approach, enter, and leave on twoway single lanes in real-time, transmitting this information to autonomous vehicles via V2N communication, thereby expanding the sensing range of the autonomous vehicles. The core part of the proposed system is the situational awareness of the two-way single lane using infrastructure cameras. In this paper, we implement this using object detection and tracking technology. Finally, we validate the implemented situational awareness technology using data collected from actual two-way single lanes.

• 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.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.6
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• pp.329-336
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• 2016

In the outdoor advertising and industrial sites, are trying to implement the LED electric bulletin board system that is based on image processing in order to express a variety of intention in real time. Recently, in various field, rather than simple text representation, the importance of intuitive communication using images is increasing. Thus, instead of outputting the simple input information for communication, a system that can output a real-time information being sought. Therefore, the system is directed to overcoming by converting the problem of mapping an image on a variety of conventional LED display that can not be output images, the possible image output formats. Using an LED of low power, it has developed to output the efficient messages and images within a limited resources. This paper provides a system capable of managing the LED display on the wireless network. Atmega2560, Wi-Fi module, using the server and Android applications client, rather than printing a text only, it is a system to reduce the load generated image output character output in to the conversion process as can be managed by the server.

• Korean Journal of Applied Biomechanics
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• v.18 no.2
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• pp.59-64
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• 2008

D. W. KANG, J. S. CHOI, and G. R. TACK, A Study on Real-Time Sports Activity Classification & Monitoring Using a Tri-axial Accelerometer. Korean Jouranl of Sport Biomechanics, Vol. 18, No. 2, pp. 59-64, 2008. This study was conducted to study the real-time sports activity classification and monitoring using single waist mounted tri-axial accelerometer. This monitoring system detects events of sports activities such as walking, running, cycling, transitions between movements, resting and emergency event of falls. Accelerometer module was developed small and easily attachable on waist using wireless communication system which does not constrain sports activities. The sensor signal was transferred to PC and each movement pattern was classified using the developed algorithm in real-time environment. To evaluate proposed algorithm, experiment was performed with several sports activities such as walking, running, cycling movement for 100sec each and falls, transition movements(sit to stand, lie to stand, stand to sit, lie to sit, stand to lie and sit to lie) for 20 times each with 5 healthy subjects. The results showed that successful detection rate of the system for all activities was 95.4%. In this study, through sports activity monitoring. it was possible to classify accurate sports activities and to notify emergency event such as falls. For further study, the accurate energy consumption algorithm for each sports activity is under development.