• Title/Summary/Keyword: Prior Tags

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Web Image Retrieval using Prior Tags based on WordNet Semantic Information (워드넷 의미정보로 선별된 우선 태그와 이를 이용한 웹 이미지의 검색)

  • Kweon, Dae-Hyeon;Hong, Jun-Hyeok;Cho, Soo-Sun
    • Journal of Korea Multimedia Society
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    • v.12 no.7
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    • pp.1032-1042
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    • 2009
  • This research is for early extraction and utilization of semantic information from the tags in tagged Web image retrieval. Generally, users attach a tag to a Web image with little thought of the order, up to over 100 ones. In this paper, we suggest a method of selecting prior tags based on their importance when tagged images are uploaded, and using them in image retrieval. Ideas came from the recognition of the important tags which give a better description of the image as the tags sharing more semantic information with other tags of the same image. This method includes calculation of relation scores between tags based on WordNet and multilevel search of tagged images with the scores. For evaluation, we compared the suggested method and other retrieval methods searching images with simple matching of tags to a given keyword. As the results, we found the superiority of our method in precision and recall rate.

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Bayesian Cognizance of RFID Tags (Bayes 풍의 RFID Tag 인식)

  • Park, Jin-Kyung;Ha, Jun;Choi, Cheon-Won
    • Journal of the Institute of Electronics Engineers of Korea TC
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    • v.46 no.5
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    • pp.70-77
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    • 2009
  • In an RFID network consisting of a single reader and many tags, a framed and slotted ALOHA, which provides a number of slots for the tags to respond, was introduced for arbitrating a collision among tags' responses. In a framed and slotted ALOHA, the number of slots in each frame should be optimized to attain the maximal efficiency in tag cognizance. While such an optimization necessitates the knowledge about the number of tags, the reader hardly knows it. In this paper, we propose a tag cognizance scheme based on framed and slotted ALOHA, which is characterized by directly taking a Bayes action on the number of slots without estimating the number of tags separately. Specifically, a Bayes action is yielded by solving a decision problem which incorporates the prior distribution the number of tags, the observation on the number of slots in which no tag responds and the loss function reflecting the cognizance rate. Also, a Bayes action in each frame is supported by an evolution of prior distribution for the number of tags. From the simulation results, we observe that the pair of evolving prior distribution and Bayes action forms a robust scheme which attains a certain level of cognizance rate in spite of a high discrepancy between the Due and initially believed numbers of tags. Also, the proposed scheme is confirmed to be able to achieve higher cognizance completion probability than a scheme using classical estimate of the number of tags separately.

A Specialized Reader for High Speed UHF RFID Tag Inlay Inspection Equipment (고속 UHF RFID 태그 검사 장비를 위한 전용 리더)

  • Bae, Sung Woo;Park, Jun-Seok;Seong, Yeong Rak;Oh, Ha-Ryoung
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.63 no.1
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    • pp.63-69
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    • 2014
  • RFIDs have not become widespread as expected partly due to the cost, size, read range, and reliability problems of tags. The success rate of reading must be improved in order for RFIDs to be widely adopted. Quality control of tags is crucial to meet this requirement. In this study, we designed and implemented a high-performance reader used in inspection equipment that conducts prior inspection of tags. To improve performance of the developed reader, the baseband modem and command processor (CP) were designed using H/W logic and implemented with FPGA. The inspection of small pitch inlays was made possible through the antenna shielding device and H/W command processor function. This equipment enables accurate evaluation of performance and identification of tags satisfying a given read range. By contributing to sort out defective tags, the results can ultimately lead to more stable RFID services.

Analysis of Music Mood Class using Folksonomy Tags (폭소노미 분위기 태그를 이용한 음악의 분위기 유형 분석)

  • Moon, Chang Bae;Kim, HyunSoo;Kim, Byeong Man
    • Science of Emotion and Sensibility
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    • v.16 no.3
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    • pp.363-372
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    • 2013
  • When retrieving music with folksonomy tags, internal use of numeric tags (AV tags: tags consisting of Arousal and Valence values ) instead of word tags can partially solve the problem posed by synonyms. However, the two predecessor tasks should be done correctly; the first task is to map word tags to their numeric tags; the second is to get numeric tags of the music pieces to be retrieved. The first task is verified through our prior study and thus, in this paper, its significance is seen for the second task. To this end, we propose the music mapping table defining the relation between AV values and music and ANOVA tests are performed for analysis. The result shows that the arousal values and valence values of music have different distributions for 12 mood tags with or without synonymy and that their type I error values are P<0.001. Consequently, it is checked that the distribution of AV values is different according to music mood.

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A Novel RFID Dynamic Testing Method Based on Optical Measurement

  • Zhenlu Liu;Xiaolei Yu;Lin Li;Weichun Zhang;Xiao Zhuang;Zhimin Zhao
    • Current Optics and Photonics
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    • v.8 no.2
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    • pp.127-137
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    • 2024
  • The distribution of tags is an important factor that affects the performance of radio-frequency identification (RFID). To study RFID performance, it is necessary to obtain RFID tags' coordinates. However, the positioning method of RFID technology has large errors, and is easily affected by the environment. Therefore, a new method using optical measurement is proposed to achieve RFID performance analysis. First, due to the possibility of blurring during image acquisition, the paper derives a new image prior to removing blurring. A nonlocal means-based method for image deconvolution is proposed. Experimental results show that the PSNR and SSIM indicators of our algorithm are better than those of a learning deep convolutional neural network and fast total variation. Second, an RFID dynamic testing system based on photoelectric sensing technology is designed. The reading distance of RFID and the three-dimensional coordinates of the tags are obtained. Finally, deep learning is used to model the RFID reading distance and tag distribution. The error is 3.02%, which is better than other algorithms such as a particle-swarm optimization back-propagation neural network, an extreme learning machine, and a deep neural network. The paper proposes the use of optical methods to measure and collect RFID data, and to analyze and predict RFID performance. This provides a new method for testing RFID performance.

Optimal Time Structure for Tag Cognizance Scheme based on Framed and Slotted ALOHA in RFID Networks (RFID 망에서 프레임화 및 슬롯화된 ALOHA에 기반한 Tag 인식 방식을 위한 최적 시간 구조)

  • Choi, Cheon-Won
    • Journal of the Institute of Electronics Engineers of Korea TC
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    • v.47 no.9
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    • pp.29-36
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    • 2010
  • Consider an RFID network configured as a star such that a single reader is surrounded by a crowd of tags. In the RFID network, prior to attaining the information stored at a tag, the reader must cognize the tags while arbitrating a collision among tags' responses. For this purpose, we present a tag cognizance scheme based on framed and slotted ALOHA, which statically provides a number of slots in each frame for the tags to respond. For the evaluation of the cognizance performance, we choose the cognizance completion probability and the expected cognizance completion time as key performance measures. Then, we present a method to numerically calculate the performance measures. Especially, for small numbers of tags, we derive them in a closed form. Next, we formulate a problem to find an optimal time structure which either maximizes the cognizance completion probability under a constraint on the cognizance time or minimizes the expected cognizance completion time. By solving the problem, we finally obtain an optimal number of slots per frame for the tags to respond. From numerical results, we confirm that there exist a finite optimal number of slots for the tags to respond. Also, we observe that the optimal number of slots maximizing the cognizance completion probability tends to approach to the optimal number of slots minimizing the expected cognizance completion time as the constraint on the cognizance time becomes loose.

A Study of Speech Control Tags Based on Semantic Information of a Text (텍스트의 의미 정보에 기반을 둔 음성컨트롤 태그에 관한 연구)

  • Chang, Moon-Soo;Chung, Kyeong-Chae;Kang, Sun-Mee
    • Speech Sciences
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    • v.13 no.4
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    • pp.187-200
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    • 2006
  • The speech synthesis technology is widely used and its application area is also being broadened to an automatic response service, a learning system for handicapped person, etc. However, the sound quality of the speech synthesizer has not yet reached to the satisfactory level of users. To make a synthesized speech, the existing synthesizer generates rhythms only by the interval information such as space and comma or by several punctuation marks such as a question mark and an exclamation mark so that it is not easy to generate natural rhythms of people even though it is based on mass speech database. To make up for the problem, there is a way to select rhythms after processing language from a higher level information. This paper proposes a method for generating tags for controling rhythms by analyzing the meaning of sentence with speech situation information. We use the Systemic Functional Grammar (SFG) [4] which analyzes the meaning of sentence with speech situation information considering the sentence prior to the given one, the situation of a conversation, the relationship among people in the conversation, etc. In this study, we generate Semantic Speech Control Tag (SSCT) by the result of SFG's meaning analysis and the voice wave analysis.

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A Machine Learning Approach to Korean Language Stemming

  • Cho, Se-hyeong
    • Journal of the Korean Institute of Intelligent Systems
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    • v.11 no.6
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    • pp.549-557
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    • 2001
  • Morphological analysis and POS tagging require a dictionary for the language at hand . In this fashion though it is impossible to analyze a language a dictionary. We also have difficulty if significant portion of the vocabulary is new or unknown . This paper explores the possibility of learning morphology of an agglutinative language. in particular Korean language, without any prior lexical knowledge of the language. We use unsupervised learning in that there is no instructor to guide the outcome of the learner, nor any tagged corpus. Here are the main characteristics of the approach: First. we use only raw corpus without any tags attached or any dictionary. Second, unlike many heuristics that are theoretically ungrounded, this method is based on statistical methods , which are widely accepted. The method is currently applied only to Korean language but since it is essentially language-neutral it can easily be adapted to other agglutinative languages.

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OFSA: Optimum Frame-Slotted Aloha for RFID Tag Collision Arbitration

  • Lee, Dong-Hwan;Choi, Ji-Hoon;Lee, Won-Jun
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.5 no.11
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    • pp.1929-1945
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    • 2011
  • RFID technologies have attracted a lot of attention in recent years because of their cost/time-effectiveness in large-scale logistics, supply chain management (SCM) and other various potential applications. One of the most important issues of the RFID-based systems is how quickly tags can be identified. Tag collision arbitration plays a more critical role in determining the system performance especially for passive tag-based ones where tag collisions are dealt with rather than prevented. We present a novel tag collision arbitration protocol called Optimum Frame-Slotted Aloha (OFSA). The protocol has been designed to achieve time-optimal efficiency in tag identification through an analytic study of tag identification delay and tag number estimation. Results from our analysis and extensive simulations demonstrate that OFSA outperforms other collision arbitration protocols. Also, unlike most prior anti-collision protocols, it does not require any modification to the current standards and architectures facilitating the rollout of RFID systems.

Agri-Food Business Models Based on NFC

  • Lee, Sung Chul;Kim, Nam Jung;Park, Jae Eun;Yu, Seong Gu;Moon, Junghoon
    • Agribusiness and Information Management
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    • v.4 no.1
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    • pp.32-40
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    • 2012
  • In recent times, NFC technology adaptations for smartphones have been increasing. This study proposes the adaptation of agri-food business models based on NFC technology and presents the basic technological characteristics of NFC. An NFC tag can store more information than prior tagging technology methods, such as QR codes, and provides a better user experience. Based on the unique features of NFC, this study suggests an NFC business model application for the agri-food business.

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