• Journal of Ecology and Environment
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• v.41 no.12
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• pp.345-350
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• 2017

Background: Ecological research often requires monitoring of a specific individual over an extended period of time. To enable non-invasive re-identification, consistent external marking is required. Treefrogs possess lateral lines for crypticity. While these patterns decrease predator detection, they also are individual specific patterns. In this study, we tested the use of lateral lines in captive and wild populations of Dryophytes japonicus as natural markers for individual identification. For the purpose of the study, the results of visual and software assisted identifications were compared. Results: In normalized laboratory conditions, a visual individual identification method resulted in a 0.00 rate of false-negative identification (RFNI) and a 0.0068 rate of false-positive identification (RFPI), whereas Wild-ID resulted in RFNI = 0.25 and RFNI = 0.00. In the wild, female and male data sets were tested. For both data sets, visual identification resulted in RFNI and RFPI of 0.00, whereas the RFNI was 1.0 and RFPI was 0.00 with Wild-ID. Wild-ID did not perform as well as visual identification methods and had low scores for matching photographs. The matching scores were significantly correlated with the continuity of the type of camera used in the field. Conclusions: We provide clear methodological guidelines for photographic identification of D. japonicus using their lateral lines. We also recommend the use of Wild-ID as a supplemental tool rather the principal identification method when analyzing large datasets.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.664-665
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• 2016

This paper proposes an identification system based on QR (Quick Response) code for production and disposal information of Internet of Things (IoT) devices. Three thousands and five hundreds of electronic devices have replaced and discarded in South Korea in a year, and twenty millions to fifty millions tons of e-wastes have happened throughout the world every year. According to Gartner, market research institution, the number of IoT devices will increase from 2.3 billions in 2013 to 30 billions in 2020, however, the regulations and systems which take into account environment were not prepared. The identification systems for reflecting information of devices, which are produced or discarded, are required to resolve the problem. The proposed identification system based on QR code can store much more massive data such as the producer, product's model, serial number, recycling rate, recovering rate, recyclability rate, recoverability rate than RFID (Radio-Frequency Identification). Also, users can immediately recognize production and disposal information by a QR code application in a smartphone.

• Phonetics and Speech Sciences
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• v.1 no.1
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• pp.63-67
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• 2009

In this paper, in order to protect music copyrights, we propose a music identification system which is scalable to the number of pieces of registered music and robust to signal-level variations of registered music. For its implementation, we define the new concepts of 'music word' and 'music phoneme' as recognition units to construct 'music acoustic models'. Then, with these concepts, we apply the HMM-based framework used in continuous speech recognition to identify the music. Each music file is transformed to a sequence of 39-dimensional vectors. This sequence of vectors is represented as ordered states with Gaussian mixtures. These ordered states are trained using Baum-Welch re-estimation method. Music files with a suspicious copyright are also transformed to a sequence of vectors. Then, the most probable music file is identified using Viterbi algorithm through the music identification network. We implemented a music identification system for 1,000 MP3 music files and tested this system with variations in terms of MP3 bit rate and music speed rate. Our proposed music identification system demonstrates robust performance to signal variations. In addition, scalability of this system is independent of the number of registered music files, since our system is based on HMM method.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.1002-1005
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• 1991

It is important to express the specific growth rate of a fermentation reaction as a function of substrate and product concentration in developing bioprocess automation techniques such as modeling of the reactor and controlling it via an advanced control scheme. Typical methods of identification utilize graphical representation of the rate constant data or nonlinear regression with an appropriate noise filter. But the former method fails when the data are erroneous and the latter are mathematically complicated to apply in the field. Neural network is another candidate for the identification from time series data since it is insensitive to the random data error and easy to implement. In this study, we will develop a neural network method of specific growth rate estimation from the time series state variable data and test the performance.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.165-169
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• 2007

Due to the complexity of underwater acoustic channel, signal estimation in underwater acoustic communication field is considerably affected from time-varying multipath fading channels. On this reason, the original signals should have many long training signals to estimate the channel and the purposed signals, and the bit rate of signals having information may have small rate. In order to avoid this loss of efficiency in underwater communication, this paper employed a blind channel identification method which don't use training signals. Simulations have predicted performance of the employed method in multipath environment and an aquatic plant experiment has verified the simulation results.

• Journal of Society of Preventive Korean Medicine
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• v.14 no.2
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• pp.105-120
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• 2010

Objectives : This study aims to evaluate the effects of expiration-to-inspiration time ratio (E/I-ratio) on heart rate, which represents cardiac autonomic function, and cold-heat in the healthy people. Methods : 49 healthy young volunteers(male : female = 32 : 17) were recruited in the study. The participants completed the questionnaire for yin-yang pattern identification and then we measured the chest plethysmogram for respiration signal and the electrocardiogram for NN intervals during different E/I-ratio from 1 to 2. We compared heart rate variability including RMS-SD, VLF, LF and HF, and the trend-cycle factors decomposed from NN interval data by time series analysis among the respective E/I-ratio. We also confirmed the difference on the trend-cycle factors according to the score of the questionnaire for cold and heat pattern identification. Results : There were differences on the trend-cycle factors from NN interval data, but no significant difference on heart rate variability, among the respective E/I-ratio. We also found significant relationship between the trend-cycle factors and the heat pattern identification scores. Conclusions : The results indicate that cardiac autonomic function can be modulated by the E/I-ratio and the modulation will be slower and more tendencious than respiratory sinus arrhythmia.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.2
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• pp.184-189
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• 2013

In this paper, we propose the injurious moving picture filtering system using certain sounds contained in the injurious moving picture to filter injurious moving picture which is distributed without limitation in internet and internet storage space. For this purpose, the Gaussian Mixture Model which can well represent the characteristics of the sound, is used and frame level likelihood estimation is used to calculate the likelihood between filtering target data and the sound models. Also, the pruning method which can real-time proceed by reducing the comparing number of data, is applied for real-time processing, and MWMR method which showed good performance from existing speaker identification, is applied for the distinguish performance of high precision. In the identification experiment result, in case of the frame rate which is the proportion of total frame to high likelihood frame, is set to 50%, identification error rate is 6.06%, and in case of frame rate is set to 60%, error rate is 3.03%. As the result, the proposed system can distinguish between general and injurious moving picture effectively.

• The Journal of Internal Korean Medicine
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• v.34 no.3
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• pp.267-277
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• 2013

Objectives : The aim of this study was to investigate the correlation between Cold-Heat pattern tendency and demographic traits, physical character, and vital signs in hypertensive patients taking anti-hypertensive agents. Methods : 28 hypertensive patients 30 to 69 years old were recruited. We assessed their general characteristics, physical characteristics (height, weight, waist circumference, etc.), vital signs without respiratory rate (blood pressure, pulse rate, temperature) and administered a Cold-Heat pattern questionnaire. After that, we analyzed statistical data on separate groups according to Cold-Heat characteristics or other criteria. Results : 1. Heat group patients had statistically higher scores in waist, body mass index (BMI), waist circumference and pulse rate. 2. Over weighted group patients had statistically lower scores in cold Pattern Identification. 3. Higher BMI group (above 23/25) patients had statistically significantly higher Heat scores and lower Cold scores, higher waist circumference group patients had lower Cold scores. Conclusions : From the above result in hypertensive patients taking hypertensive agents, Heat group had a obesity tendency and the inverse is also valid. Later, progressed study based on more samples and varied data will contribute to diagnosis the Cold-heat Pattern identification in hypertensive patients.

• Korean Journal of Remote Sensing
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• v.40 no.2
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• pp.219-228
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• 2024

Vessels can operate with their Automatic Identification System (AIS) turned off, prompting the development of strategies to identify them. Among these, utilizing satellites to collect radio frequency (RF) data in the absence of AIS has emerged as the most effective and practical approach. The purpose of this study is to develop a matching algorithm for RF with AIS data and find the RF's applicability to classify a suspected ship. Thus, a matching procedure utilizing three RF datasets and AIS data was employed to identify ships in the Yellow Sea and the Korea Strait. The matching procedure was conducted based on the proximity to AIS points, ensuring accuracy through various distance-based sections, including 2 km, 3 km, and 6 km from the AIS-based estimated points. Within the RF coverage, the matching results from the first RF dataset and AIS data identified a total of 798 ships, with an overall matching rate of 78%. In the cases of the second and third RF datasets, 803 and 825 ships were matched, resulting in an overall matching rate of 84.3% and 74.5%, respectively. The observed results were partially influenced by differences in RF and AIS coverage. Within the overlapped region of RF and AIS data, the matching rate ranged from 80.2% to 98.7%, with an average of 89.3%, with no duplicate matches to the same ship.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06b
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• pp.426-428
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• 2012

In order to identify proteins that are present in biological samples, these samples are separated and analyzed under the sequential procedure as follows: protein purification and digestion, peptide fragmentation by tandem mass spectrometry (MS/MS) which breaks peptides into fragments, peptide identification, and protein identification. One of the widely used methods for protein identification is based on probabilistic approaches such as ProteinProphet and BaysPro. However, they do not consider the difference in peptide identification probabilities according to their length. Here, we propose a probabilistic graphical model-based approach to protein identification from MS/MS data considering peptide identification probabilities, number of sibling peptides, and peptide length. We compared our approach with ProteinProphet using a yeast MS/MS dataset. As a result, our model identified 27 more proteins than ProteinProphet at 1% of FDR (false discovery rate), confirming the importance of peptide length information in protein identification.