• Journal of the Korean BIBLIA Society for library and Information Science
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• v.29 no.3
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• pp.297-320
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• 2018

This study aims to improve the access and retrieval of images and to find a way to effectively generate tags as a tool for providing explanation of images. To do this, this study investigated the features of human tagging and machine tagging, and compare and analyze them. Machine tags had the highest general attributes, some specific attributes and visual elements, and few abstract attributes. The general attribute of the human tag was the highest, but the specific attribute was high for the object and scene where the human tag constructor can recognize the name. In addition, sentiments and emotions, as well as subjects of abstract concepts, events, places, time, and relationships are represented by various tags. The tag set generated through this study can be used as basic data for constructing training data set to improve the machine learning algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.1 no.1
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• pp.19-31
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• 2007

RFID tag is detected by an RFID antenna and information is read from the tag detected, by an RFID reader. RFID tag detection by an RFID reader is very important at the deployment stage. Tag detection is influenced by factors such as tag direction on a target object, speed of a conveyer moving the object, and the contents of an object. The water content of the object absorbs radio waves at high frequencies, typically approximately 900 MHz, resulting in unstable tag signal power. Currently, finding the best conditions for factors influencing the tag detection requires very time consuming work at deployment. Thus, a quick and simple RFID tag detection scheme is needed to improve the current time consuming trial-and-error experimental method. This paper proposes a back-propagation learning-based RFID tag detection prediction scheme, which is intelligent and has the advantages of ease of use and time/cost savings. The results of simulation with the proposed scheme demonstrate a high prediction accuracy for tag detection on a water content, which is comparable with the current method in terms of time/cost savings.

• Journal of Multimedia Information System
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• v.8 no.1
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• pp.57-60
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• 2021

Industry 4.0 is continuous automation by applying the latest smart technologies to traditional manufacturing industries. It means that large-scale M2M (Machine-to-Machine) communication and IoT (Internet of Things) technologies are well integrated to build efficient production systems by analyzing and diagnosing various issues without human intervention. Edge computing is widely used for M2M services that handle real-time interactions between devices at industrial machinery tool sites. Here, secure data transmission is required while interacting. Thus, this paper focused on a method of creating and maintaining secret key and security tag used for message authentication between end-devices and edge-device.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.259-263
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• 2015

The vulnerabilities related to Flash player which is widely used in internet browsers and office programs are gradually increased. To detect Flash malwares, previous work focuses on predefined features of ActionScript. However above work cannot detect new/mutated Flash malwares, since predefined features could not cover the new patterns of new/mutated Flash mawares. To solve this problem, we propose a Flash malware detection method that uses machine learning to learn Flash Tag patterns and classify Flash by using machine learning.

• Journal of Korea Society of Industrial Information Systems
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• v.13 no.5
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• pp.133-141
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• 2008

Social Web is turning current Web into social platform for knowing people and sharing information. This paper takes major social tagging systems as examples, namely delicious, flickr and youtube, to analyze the social phenomena in the Social Web in order to identify the way of mediating and linking social data. A simple Tag Ontology (TO) is proposed to integrate different social tagging data and mediate and link with other related social metadata. Through several machine learning for tagging data, tag groups and similar user groups are extracted, and then used to learn the tagging ontology. A recommender system adopting the tag ontology is also suggested as an applying field.

• Journal of Internet of Things and Convergence
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• v.8 no.5
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• pp.17-25
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• 2022

Recently the massive amount of data has been generated because of the number of edge devices increases. And especially, the number of raw unstructured HTML documents has been increased. Therefore, MRC(Machine Reading Comprehension) in which a natural language processing model finds the important information within an HTML document is becoming more important. In this paper, we propose HTDE(HTML Tag Depth Embedding Method), which allows the BERT to train the depth of the HTML document structure. HTDE makes a tag stack from the HTML document for each input token in the BERT and then extracts the depth information. After that, we add a HTML embedding layer that takes the depth of the token as input to the step of input embedding of BERT. Since tokenization using HTDE identifies the HTML document structures through the relationship of surrounding tokens, HTDE improves the accuracy of BERT for HTML documents. Finally, we demonstrated that the proposed idea showing the higher accuracy compared than the accuracy using the conventional embedding of BERT.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.10 s.352
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• pp.27-34
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• 2006

This paper has implemented a very small($1.4{\times}2.8[Cm^2]$) 13.56[MHz] RFID reader ensuring machine ID recognition correctly in a noise space of Tag-to-Reader within 3Cm. For operation of the RFID system, at first, this paper has designed the loop antenna of a reader and the fading model of back-scattering on microwave propagation following to 13.56[MHz] RFID Air Interface ISO/IEC specification. Secondly, this paper has proposed the automatically path selected RF switching circuit and the firmware operation relationship by measuring and analyzing the very small RFID RF issues. Finally, as a very small reader main body, this paper has shown the DSP board and software functions made for extraction of $1{\sim}2$ machine ID information and error prevention simultaneously with carrying of 13.56[MHz] RFID signals that the international standard specification ISO/IEC 18000-3 defined.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.18 no.1
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• pp.13-21
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• 2009

Interactive Graphic Robotics Integrated Programming(IGRIP) can handle various types of robot models and can exchange graphic or numerical data easily with other CAD software. In a cutting process of shape-steels, however. IGRIP is inconvenient because the users must generate all the tag points manually. In this study we developed an automation program module in order to generate the tag points automatically in IGRIP This program can read and analyze the macro data containing the information for cutting processes of shape-steels and can generate automatically the parts, the devices, the tag points and the Graphic Simulation Language(GSL) program files useful in IGRIP.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.15 no.3
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• pp.159-165
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• 2015

The need for the recognition of music emotion has become apparent in many music information retrieval applications. In addition to the large pool of techniques that have already been developed in machine learning and data mining, various emerging applications have led to a wealth of newly proposed techniques. In the music information retrieval community, many studies and applications have concentrated on tag-based music recommendation. The limitation of music emotion tags is the ambiguity caused by a single music tag covering too many subcategories. To overcome this, multiple tags can be used simultaneously to specify music clips more precisely. In this paper, we propose a novel technique to rank the proper tag combinations based on the acoustic similarity of music clips.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.4
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• pp.25-31
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• 2009

In this paper, the implementation of a production control system based on RFID has been studied in order to obtain an exact Cost Center data such as the name of workers included a process of work and a time period to finish the process. The cost center of a worker will be correctly obtained by checking the work time using RFID tag data and by transmitting the data to a server of ERP or POP system. And also warming up time, cleaning time, power failure, and out of order sign will be checked and calculated using the data stored in RFID tags attached in workers and machine facilities. Therefore, exact Cost Center data will be obtained by the production control system with touch screens entering the data according to the situation in real time.