• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.2
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• pp.370-375
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• 2011

In this paper, we propose an antenna module with high isolation between Tx and Rx in RFID reader module. The proposed module consists of a quadrafilar antenna and a directional coupler with a switchable dummy load to improve the directivity. The proposed module achieves the isolation higher than 20 dB between Tx and Rx. To show the validity of the proposed scheme, we have performed the measurement of tagging range and multi-tagging ability. The experiment results show that the detecting range and multi-tagging ability are enhanced by 81% and 200%, respectively.

• Proceedings of the Korean Society of Medical Physics Conference
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• 2002.09a
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• pp.360-362
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• 2002

Myocardial tagging technique such as spatial modulation of magnetization (SPAMM) allows the study of myocardial motion with high accuracy. Tagging contrast of such a tagging images can affect to the accuracy of the estimation of tag intersection in order to analyze the myocardial motion. Tagging contrast can be affected by tagline spacing. The aim of this study was to investigate the relationship between tagline spacing of SPAMM image and tagging contrast-to-noise ratio (CNR) experimentally. One healthy volunteer was undergone electrocardiographically triggered MR imaging with SPAMM-based tagging pulse sequence at a 1.5T MR scanner (Gyroscan Intera, Philips Medical System, Netherland). Horizontally modulated stripe patterns were imposed with a range from 3.6mm to 9.6mm of tagline spacing. Images of the left ventricle (LV) wall were acquired at the mid-ventricle level during cardiac cycle with FEEPI (TR/TE/FA=5.8/2.2/10). Tagging CNR for each image was calculated with a software which developed in our group. During contraction, tagging CNR was more rapidly decreased in case of short tagline spacing than in case of long tagline spacing. In the same heart phase, CNR was increased corresponding with tag line spacing. Especially, at the fully contracted heart phase, CNR was more rapidly increased than the other heart phases as a function of tagline spacing.

• Progress in Medical Physics
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• v.13 no.4
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• pp.224-228
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• 2002

Myocardial tagging technique such as spatial modulation of magnetization (SPAMM) allows the study of myocardial motion with high accuracy. However, the accuracy of the estimation of tag intersection can be affected by tagline spacing. The aim of this study was to investigate the relationship between tagline spacing of SPAMM image and tagging contrast-to-noise ratio (CNR) in in-vivo study. Two healthy volunteers were undergone electrocardiographically triggered MR imaging with SPAMM-based tagging pulse sequence at a 1.5T MR scanner. Horizontally modulated stripe patterns were imposed with a range from 3.6 to 9.6 mm of tagline spacing. Images of the left ventricle(LV) wall were acquired at the mid-ventricle level during cardiac cycle with FE-EPI (TR/TE = 5.8/2.2 msec, FA= 10$^{\circ}$. Tagging CNR for each image was calculated with a software which developed in our group. During contraction, tagging CNR was more rapidly decreased in case of narrow tagline spacing than in case of wide tagline spacing. In the same heart phase, CNR was increased corresponding with tagline spacing. Especially, at the fully contracted heart phase, CNR was more rapidly increased than the other heart phases as a function of tagline spacing. The results indicated that the optimization of tagline spacing provides better tagging CNR in order to analyze the myocardial motion more accurately.

• The Journal of the Acoustical Society of Korea
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• v.37 no.6
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• pp.475-482
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• 2018

In this paper, we present a study on data augmentation methods for DNN (Deep Neural Network)-based audio tagging. In this system, an audio signal is converted into a mel-spectrogram and used as an input to the DNN for audio tagging. To cope with the problem associated with a small number of training data, we augment the training samples using time stretching, pitch shifting, dynamic range compression, and block mixing. In this paper, we derive optimal parameters and combinations for the augmentation methods through audio tagging simulations.

• Journal of Multimedia Information System
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• v.5 no.3
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• pp.147-154
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• 2018

Natural language processing (NLP) is an emerging research area in which we study how machines can be used to perceive and alter the text written in natural languages. We can perform different tasks on natural languages by analyzing them through various annotational tasks like parsing, chunking, part-of-speech tagging and lexical analysis etc. These annotational tasks depend on morphological structure of a particular natural language. The focus of this work is part-of-speech tagging (POS tagging) on Hindi language. Part-of-speech tagging also known as grammatical tagging is a process of assigning different grammatical categories to each word of a given text. These grammatical categories can be noun, verb, time, date, number etc. Hindi is the most widely used and official language of India. It is also among the top five most spoken languages of the world. For English and other languages, a diverse range of POS taggers are available, but these POS taggers can not be applied on the Hindi language as Hindi is one of the most morphologically rich language. Furthermore there is a significant difference between the morphological structures of these languages. Thus in this work, a POS tagger system is presented for the Hindi language. For Hindi POS tagging a hybrid approach is presented in this paper which combines "Probability-based and Rule-based" approaches. For known word tagging a Unigram model of probability class is used, whereas for tagging unknown words various lexical and contextual features are used. Various finite state machine automata are constructed for demonstrating different rules and then regular expressions are used to implement these rules. A tagset is also prepared for this task, which contains 29 standard part-of-speech tags. The tagset also includes two unique tags, i.e., date tag and time tag. These date and time tags support all possible formats. Regular expressions are used to implement all pattern based tags like time, date, number and special symbols. The aim of the presented approach is to increase the correctness of an automatic Hindi POS tagging while bounding the requirement of a large human-made corpus. This hybrid approach uses a probability-based model to increase automatic tagging and a rule-based model to bound the requirement of an already trained corpus. This approach is based on very small labeled training set (around 9,000 words) and yields 96.54% of best precision and 95.08% of average precision. The approach also yields best accuracy of 91.39% and an average accuracy of 88.15%.

• Bulletin of the Korean Chemical Society
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• v.33 no.11
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• pp.3665-3670
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• 2012

Metal-p-$NH_2$-Bn-DOTA (paraammionobenzyl-1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid: ABDOTA) complex was synthesized and purified for bio-tagging to quantify biological target materials using laser ablation (LA)-ICP-MS. Since the preparation of a pure and stable tagging complex is the key procedure for quantification, magnetic particles were used to purify the synthesized metal-ABDOTA complex. The magnetic particles immobilized with the complex attracted to a permanent magnet, resulting in fast separation from free un-reacted metal ions in solution. Gd ions formed the metal-complex with a higher yield of 64.3% (${\pm}3.9%$ relative standard deviation (RSD)) than Y ions, 52.3% (${\pm}2.5%$ RSD), in the pH range 4-7. The complex bound to the magnetic particles was released by treatment with a strong base, of which the recovery was 81.7%. As a reference, a solid phase extraction (SPE) column packed with Chelex-100 resin was employed for separation under similar conditions and produced comparable results. The tagging technique complemented polydimethylsiloxane (PDMS) microarray chip sampling in LA-ICP-MS, allowing determination of small sample volumes at high throughputs. For application, immunoglobulin G (IgG) was immobilized on the pillars of PDMS microarray chips and then tagged with the prepared Gd complex. IgG could then be determined through measurement of Gd by LA-ICP-MS. A detection limit of 1.61 ng/mL (${\pm}0.75%$ RSD) for Gd was obtained.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.56 no.5
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• pp.660-666
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• 2023

This study aimed to examine the effect of external pop-up satellite archival tags (PSATs) attachment and water temperature on the oxygen consumption rate (OCR) of the olive flounder (mean body weight 2281.7 g). The OCRs of fish were measured under conditions of three different water temperature conditions (15, 20, and 25℃) and two different tagging methods [non-tagging, control; bio-logger external attachment with a miniature PSAT (dummy mrPAT), BEA] using a closed flow-through respirometer. The OCRs of fish linearly increased with the increase in water temperature in both the control and BEA (P<0.001); however, the OCRs of BEA were approximately 1.8-1.9 times lower than those of the control at each water temperature (P<0.001). The Q₁₀ values of the control and BEA were the highest in the water temperature range of 15 to 20℃, but sensitivity to water temperature changes was higher in BEA than in the control. The metabolic energy loss rate (MEL) of fish increased with increasing water temperature regardless of external tagging, but the MEL of the control was higher than that of BEA (P<0.001). These results demonstrate that OCR, thermal sensitivity, and energy expenditure are all affected in adult olive flounder with external PSAT attachment.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.1
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• pp.83-91
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• 2014

The passive UHF RFID tags for item-level tagging are now explosively used in the supply chain and retail applications as they have several advantages, the two most relevant are cost and a longer read range. However, the signal interference problem between RFID tags and smart devices in real world is expected according to the smart-phone and tablet market growth together. The performance of RFID tags can be significantly less. The popular examples are the read-success rates and read range reduction. Especially, KT Corp. recently emphasized the serious signal interference at 900 MHz of LTE and old RFID frequencies through their public demonstration. By popular demands, this paper suggests the interference tolerance measurement method between the passive UHF RFID tag and the transmitted signal from a smart device. In addition, we selected three passive UHF RFID tags(Inlay) available on the market and quantitatively evaluated read range reduction results by interference signals using the PCR(Performance Change Rates) index. As a result, the LTE system is about three times as effective as the WCDMA system in terms of interference effects, and the read range performance of two RFID tags about 60 % drop.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.1B
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• pp.78-84
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• 2010

A fixed 900 MHz near field RFID system is developed to provide information; market efficiency, jewelry information and the circulation history information in real time, to the customers. The developed RFID system for the jewelry management consists of a reader, antenna and a CPU in a integrated type. The system size is $38\;{\times}\;25\;{\times}\;19\;cm^3$, the operated frequency band of the reader antenna is 905 ~ 926 MHz. The maximum gain of the embedded reader antenna is 5.1 dBii(@ 910 MHz). Honeycomb tag manufactured by RSI Co. is suitable for the jewelry management than another other commercial near field tags. The tagging method and the tagging location of Honeycomb tag are suggested. In the suggested system, the maximum reading range is about 16 cm, and the zone with 100 % recognition rate is 10 cm from the radom of the reader antenna.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.9
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• pp.1210-1215
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• 2018

Recently, as the IoT(Internet of Things) and AI(Artificial Intelligence) technologies have developed, smart toys that can understand and act on the language of human beings are being studied. In this paper, we study voice learning using CNN(Convolutional Neural Network) by applying artificial intelligence based voice secretary technology to smart toy. When a human voice command gives, Smart Toy recognizes human voice, converts it into text, analyzes the morpheme, and conducts tagging and voice learning. As a result of test for the simulator program implemented using Python, no malfunction occurred in a single command. And satisfactory results were obtained within the selected simulation condition range.