• Nuclear Engineering and Technology
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• v.54 no.1
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• pp.269-274
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• 2022

An artificial neural network (ANN) that identifies radionuclides from low-count gamma spectra of a NaI scintillator is proposed. The ANN was trained and tested using simulated spectra. 14 target nuclides were considered corresponding to the requisite radionuclide library of a radionuclide identification device mentioned in IEC 62327-2017. The network shows an average identification accuracy of 98.63% on the validation dataset, with the gross counts in each spectrum N_c = 100~10000 and the signal to noise ratio SNR = 0.05-1. Most of the false predictions come from nuclides with low branching ratio and/or similar decay energies. If the N_c>1000 and SNR>0.3, which is defined as the minimum identifiable condition, the averaged identification accuracy is 99.87%. Even when the source and the detector are covered with lead bricks and the response function of the detector thus varies, the ANN which was trained using non-shielding spectra still shows high accuracy as long as the minimum identifiable condition is satisfied. Among all the considered nuclides, only the identification accuracy of ²³⁵U is seriously affected by the shielding. Identification of other nuclides shows high accuracy even the shielding condition is changed, which indicates that the ANN has good generalization performance.

• Mycobiology
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• v.46 no.2
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• pp.168-171
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• 2018

In 2016, a severe leaf spot disease was found on Iris ensata Thumb. in Nanjing, China. The symptom was elliptical, fusiform, or irregularly necrotic lesion surrounded by a yellow halo, from which a small-spored Alternaria species was isolated. The fungus was identified as Alternaria iridiaustralis based on morphological characteristics. The pathogenicity tests revealed that the fungus was the causal pathogen of the disease. Phylogenic analyses using sequences of ITS, gpd, endoPG, and RPB2 genes confirmed the morphological identification. This study is the first report of A. iridiaustralis causing leaf spots on I. ensata in China.

• Structural Monitoring and Maintenance
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• v.1 no.4
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• pp.411-425
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• 2014

A relatively low frequency Lamb wave-based damage identification method called damage imaging method for rectangular composite plate is presented. A damage index (DI) is generated from the delay matrix of the Lamb wave response signals, and it is used to indicate the location and approximate area of the damage. The viability of this method is demonstrated by analyzing the numerical and experimental Lamb wave response signals from rectangular composite plates. The technique only requires the response signals from the plate after damage, and it is capable of performing near real time damage identification. This study sheds some light on the application of Lamb wave-based damage detection algorithm for plate-type structures by using the relatively low frequency (e.g., in the neighborhood of 100 kHz, more suitable for the best capability of the existing fiber optic sensor interrogator system with the sampling frequency of 500 kHz) Lamb wave response and a reference-free damage detection technique.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.05a
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• pp.87-87
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• 2004

An air-conditioner has various noise sources such as a fan noise, a motor noise, and a vibration induced noise. To reduce these noise effectively, noise sources must be identified. Especially in this paper, the structure borne sound radiated from the motor bracket of the indoor air-conditioner is considered. To do this, the operational deflection shape, which is used for understanding of the behavior of the motor bracket at a particular frequency, is obtained and compared with the sound intensity, which is used for the noise identification. Through this study, the noise sources of indoor air-conditioner are defined and the effective noise reduction method is proposed.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1116-1118
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• 1996

This paper designs a digital controller by making use of the $H^{\infty}$ control algorithm and $\mu$-synthesis in order to keep a balance of the VTOL(Vertical Take Off and Landing Plane) vehicle with 4 fans. A identification of the actual model is acquired by the vehicle rolling, pitching and yawing angles for a pseude-random signal input and various identification theories. In spite of parameter variations and existing disturbances, the designed controller showes its robust performance through simulations and experiments.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.8A
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• pp.805-814
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• 2008

Both EPCglobal Generation-2 (Gen2) for passive RFID systems and Intelleflex for semi-passive RFID systems use probabilistic slotted ALOHA with Q algorithm, which is a kind of dynamic framed slotted ALOHA (DFSA), as the tag anti-collision algorithm. A better tag anti-collision algorithm can reduce collisions so as to increase the efficiency of tag identification. In this paper, we introduce and analyze the estimation methods of the number of slots and tags for DFSA. To increase the efficiency of tag identification, we propose two new tag anti-collision algorithms, which are Chebyshev's inequality (CHI) algorithm and hybrid Q algorithm, and compare them with the conventional Q algorithm and adaptive adjustable framed Q (AAFQ) algorithm, which is mentioned in Part I. The simulation results show that AAFQ performs the best in Gen2 scenario. However, in Intelleflex scenario the proposed hybrid Q algorithm is the best. That is, hybrid Q provides the minimum identification time, shows the more consistent collision ratio, and maximizes throughput and system efficiency in Intelleflex scenario.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.10A
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• pp.987-996
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• 2008

In this paper, the conventional anti-collision algorithms, such as Channel Monitoring algorithm and Pulse Protocol algorithm are analyzed. To decrease tag identification time, and increase system throughput and efficiency, we propose a new reader anti-collision algorithm, Pulse Protocol-based Hybrid Reader Anti-collision Algorithm, using Slot-occupied Probability under dense reader environment. The proposed algorithm uses Slot-occupied Probability to improve the performance of Pulse Protocol Algorithm. That is, A reader checks Slot-occupied Probability after generating random backoff time. If Slot-occupied Probability is greater than 0, it uses another new random backoff time to avoid reader collision. We also compare the performance of the proposed algorithm with those of Channel Monitoring and Pulse Protocol algorithms in respect of identification time system throughput, and system efficiency. Simulation results show that the proposed algorithm has an increment of 5% of identification time and system throughput as increasing the number of readers.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.8A
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• pp.794-804
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• 2008

In this paper, we analyze the performance of probabilistic slotted anti-collision algorithm used in EPCglobal Class-1 Generation-2 (Gen2). To increase throughput and system efficiency, and to decrease tag identification time and collision ratio, we propose new tag anti-collision algorithms, which are FAFQ (fired adjustable flamed Q) algorithm and AAFQ (adaptive adjustable framed Q) algorithm, by using QueryAdjust command. We also propose grouping method based on Gen2 to improve the efficiency of tag identification. The simulation results show that all the proposed algorithms outperform Q algorithm, and AAFQ algorithm performs the best. That is, AAFQ has an increment of 5% of system efficiency and a decrement of 4.5% of collision ratio. For FAFQ and AAFQ algorithm, the performance of grouping method is similar to that of ungrouping method. However, for Q algorithm in Gen2, grouping method can increase throughput and system efficiency, and decrease tag identification time and collision ratio compared with ungrouping method.

• Animal Bioscience
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• v.35 no.11
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• pp.1656-1665
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• 2022

Objective: Water buffalo, an important domestic animal in tropical and subtropical regions, play an important role in agricultural economy. It is an important source for milk, meat, horns, skin, and draft power, especially its rich milk that is the great source of cream, butter, yogurt, and many cheeses. In recent years, long noncoding RNAs (lncRNAs) have been reported to play pivotal roles in many biological processes. Previous studies for the mammary gland development of water buffalo mainly focus on protein coding genes. However, lncRNAs of water buffalo remain poorly understood, and the regulation relationship between mammary gland development/milk production traits and lncRNA expression is also unclear. Methods: Here, we sequenced 22 samples of the milk somatic cells from three lactation stages and integrated the current annotation and identified 7,962 lncRNA genes. Results: By comparing the lncRNA genes of the water buffalo in the early, peak, and late different lactation stages, we found that lncRNA gene lnc-bbug14207 displayed significantly different expression between early and late lactation stages. And lnc-bbug14207 may regulate neighboring milk fat globule-EGF factor 8 (MFG-E8) and hyaluronan and proteoglycan link protein 3 (HAPLN3) protein coding genes, which are vital for mammary gland development. Conclusion: This study provides the first genome-wide identification of water buffalo lncRNAs and unveils the potential lncRNAs that impact mammary gland development.

• Journal of Astronomy and Space Sciences
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• v.30 no.3
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• pp.127-132
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• 2013

Here we review the effort of Fermi Asian Network (FAN) in exploring the supernova remnants (SNRs) with state-of-art high energy observatories, including Fermi Gamma-ray Space Telescope and Chandra X-ray Observatory, in the period of 2011- 2012. Utilizing the data from Fermi LAT, we have discovered the GeV emission at the position of the Galactic SNR Kes 17 which provides evidence for the hadronic acceleration. Our study also sheds light on the propagation of cosmic rays from their acceleration site to the intersteller medium. We have also launched an identification campaign of SNR candidates in the Milky Way, in which a new SNR G308.3-1.4 have been uncovered with our Chandra observation. Apart from the remnant, we have also discovered an associated compact object at its center. The multiwavelength properties of this X-ray source suggest it can possibly be the compact binary that survived a supernova explosion.