• The Journal of the Korea Contents Association
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• v.9 no.4
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• pp.55-64
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• 2009

For realizing ubiquitous computing, many research activities are geared towards various areas including embedded computing, RFID, USN, home networking, context-awareness, and etc. By using the ability of RFID technology to recognize a number of objects simultaneously, more convenient ubiquitous application services are effectively provided. In this case, RFID middleware playing a role as a bridge between RFID reader devices and application services is required as well. In this paper, we propose a method of handling a number of types of RFID reader devices in ALE middleware of EPCglobal. For this, the information of connection and data protocol for a reader device is stored in a database as ontology meta-data, and used to interpret the data read by a reader device. By adding ontology data into a database, even though an RFID device newly emerges, ALE middleware can not only handle the device, but also be effectively extended through reusing ontology data, without any changes in the middleware.

• The Transactions of the Korea Information Processing Society
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• v.4 no.4
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• pp.908-922
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• 1997

In this paper,we present an dffcient way to describe the commplex meaning embedded in video data for the cintent-based retrival in a video database.Intead of viewing the data stored in a file as continuous bit stream,we associate the desired interval in the stream with a set of atteibute and value pairs which describe its meaning.Since the meaning of video data can be cimplex and can change dyamically. It is necessary to com-bine the fixed schema of attributes used in the traditional database systrm with a description method through a set of attribute and value pairs that can be defined dynamically.As the cintent of viedo data can be expressed differently according to the view point of a user,it is important ot maintain the meaning of the attribute and value pairs cinsistently for different users.This paper proposes the dffctive way to manage the set of attri-bute and value pairs.In addition,it also describes a way to define a new video presentation by separating a video stream phsycally or by sharing the portion of a bit stream,and the new method can minimize the required storage space.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.9
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• pp.347-356
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• 2015

Due to the rapid development of IoT(Internet of Things) technology, traditional taxis are connected through dispatchers and location systems. Typically, modern taxis have embedded with GPS(Global Positioning System), which aims for obtaining the route information. By analyzing the frequency of taxi trip events, we can find the frequent route for a given query time. However, a scalability problem would occur when we convert the raw location data of taxi trip events into the analyzed frequency information due to the volume of location data. For this problem, we propose a NoSQL based top-K query system for taxi trip events. First, we analyze raw taxi trip events and extract frequencies of all routes. Then, we store the frequency information into hash-based index structure of MongoDB which is a document-oriented NoSQL database. Efficient top-K query processing for frequent route is done with the top of the MongoDB. We validate the efficiency of our algorithms by using real taxi trip events of New York City.

• The KIPS Transactions:PartD
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• v.10D no.2
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• pp.187-194
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• 2003

Main Memory storage system can increase the performance of the system by assigning enough slack time to real-time transactions. Due to its high response time of main memory devices, main memory resident data management systems have been used for location management of personal mobile clients to cope with urgent location related operations. In this paper we have developed a multi-threaded main memory storage system as a core component of real-time retrieval system to handle a huge amount of readers and writers of main memory resident data. The storage system is implemented as an embedded component which is working with the help of a disk resident database system. It uses multi-threaded executions and utilizes latches for its concurrency control rather than complex locking method. It only saves most recent data on main memory and data synchronization is done only when disk resident database asks for update transactions. The system controls the number of read threads and update threads to guarantee the minimum requirements of real-time retrievals.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.10B
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• pp.883-890
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• 2006

The study of sensor network database is beginning to liven up as we are interested in Ubiquitous Computing technology in hardware, communication, database and so on. Especially, as new smart sensors have capabilities of real-time information gathering and analysis of each sensor node, data processing becomes an important issue in Ubiquitous Computing. In thesis, we have applied TinyDB(query processing system) to carry sensor node with line tracer which can follow the fixed path. After we gathered data around path, we have processed data in TinyDB GUI, gathered data, displayed data on a web server. Also we have a web browser on an embedded board for convenient user interface and implemented touch screen such that users can operate with a finger.

• Journal of the Korea Society of Computer and Information
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• v.20 no.5
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• pp.99-106
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• 2015

This research is focused on the development of the proprietary database embedded in the OTT device, which is used for searching and indexing video contents, and also the development of the search algorithm in the form of the critical components of the interface application with the OTT's database to provide video query searching, such as remote control smartphone application. As the number of available channels has increased to anywhere from dozens to hundreds of channels, it has become increasingly difficult for the viewer to find programs they want to watch. To address this issue, content providers are now in need of methods to recommend programs catering to each viewer's preference. the present study aims provide of the algorithm which recommends contents of OTT program by analyzing personal watching pattern based on one's history.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.1
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• pp.1-10
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• 2008

In this paper, we designed a facial feature(eyes, a moult and a nose) detection hardware based on the ICT transform which was developed for face detection earlier. Our design used a pipeline architecture for high throughput and it also tried to reduce memory size and memory access rate. The algerian and its hardware implementation were tested on the BioID database, which is a worldwide face detection test bed, and its facial feature detection rate was 100% both in software and hardware, assuming the face boundary was correctly detected. After synthesizing the hardware on Dongbu $0.18{\mu}m$ CMOS library, its die size was $376,821{\mu}m^2$ with the maximum operating clock 78MHz.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.2
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• pp.415-420
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• 2010

This paper describes the design overview of shared file system $SANique^{TM}$ and analyzes the performance evaluation results of I/O intensive stress test based on various cluster file system architectures. Especially, we illustrate the performance analysis for the comparison results between the $SANique^{TM}$ and the Linux file system EXT3 system that is used to generally in Unix world. In order to perform our evaluation, Oracle 10g database system is operated on the top of cluster file system, and we developed the various kinds of testing tools which are compiled by ESQL/C from Oracle. Three types of architectures are used in this performance evaluation. Those are the cluster file system $SANique^{TM}$, EXT3 and the combined architecture of $SANique^{TM}$ and EXT3. In this paper, we present that the results of $SANique^{TM}$ outperforms other cluster file systems in the overhead for providing the true sharing over the connecting server nodes.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.2
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• pp.365-375
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• 2019

A PLC (Programmable Logic Controller) is a highly-reliable industrial digital computer which supports real-time embedded control applications for safety-critical control systems. Real-time operating systems such as uC/OS have been used for PLCs and must meet real-time constraints. As PLCs have been widely used for industrial control systems and connected to the Internet, they have been becoming a main target of cyberattacks. In this paper, we propose an execution code sanitizer to enhance the security of PLC systems. The proposed sanitizer analyzes PLC programs developed by an IDE before downloading the program to a target PLC, and mitigates security vulnerabilities of the program. Our sanitizer can detect vulnerable function calls and illegal memory accesses in development of PLC programs using a database of vulnerable functions as well as the other database of code patterns related to pointer misuses. Based on these DBs, it detects and removes abnormal use patterns of pointer variables and existence of vulnerable functions shown in the call graph of the target executable code. We have implemented the proposed technique and verified its effectiveness through experiments.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.2
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• pp.503-523
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• 2022

Nowadays, many attendance applications utilise biometric techniques such as the face, fingerprint, and iris recognition. Biometrics has become ubiquitous in many sectors. Due to the advancement of deep learning algorithms, the accuracy rate of biometric techniques has been improved tremendously. This paper proposes a web-based attendance system that adopts facial recognition using open-source deep learning pre-trained models. Face recognition procedural steps using web technology and database were explained. The methodology used the required pre-trained weight files embedded in the procedure of face recognition. The face recognition method includes two important processes: registration of face datasets and face matching. The extracted feature vectors were implemented and stored in an online database to create a more dynamic face recognition process. Finally, user testing was conducted, whereby users were asked to perform a series of biometric verification. The testing consists of facial scans from the front, right (30 - 45 degrees) and left (30 - 45 degrees). Reported face recognition results showed an accuracy of 92% with a precision of 100% and recall of 90%.