• Journal of Communications and Networks
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• v.11 no.6
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• pp.544-555
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• 2009

This work continues a trend of developments aimed at exploiting the physical layer of the open systems interconnection (OSI) model to enhance wireless network security. The goal is to augment activity occurring across other OSI layers and provide improved safeguards against unauthorized access. Relative to intrusion detection and anti-spoofing, this paper provides details for a proof-of-concept investigation involving "air monitor" applications where physical equipment constraints are not overly restrictive. In this case, RF fingerprinting is emerging as a viable security measure for providing device-specific identification (manufacturer, model, and/or serial number). RF fingerprint features can be extracted from various regions of collected bursts, the detection of which has been extensively researched. Given reliable burst detection, the near-term challenge is to find robust fingerprint features to improve device distinguishability. This is addressed here using wavelet domain (WD) RF fingerprinting based on dual-tree complex wavelet transform (DT-$\mathbb{C}WT$) features extracted from the non-transient preamble response of OFDM-based 802.11a signals. Intra-manufacturer classification performance is evaluated using four like-model Cisco devices with dissimilar serial numbers. WD fingerprinting effectiveness is demonstrated using Fisher-based multiple discriminant analysis (MDA) with maximum likelihood (ML) classification. The effects of varying channel SNR, burst detection error and dissimilar SNRs for MDA/ML training and classification are considered. Relative to time domain (TD) RF fingerprinting, WD fingerprinting with DT-$\mathbb{C}WT$ features emerged as the superior alternative for all scenarios at SNRs below 20 dB while achieving performance gains of up to 8 dB at 80% classification accuracy.

• Journal of Korea Multimedia Society
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• v.19 no.4
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• pp.725-735
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• 2016

High-resolution satellite images are used in the fields of mapping, natural disaster forecasting, agriculture, ocean-based industries, infrastructure, and environment, and there is a progressive increase in the development and demand for the applications of high-resolution satellite images. Users of the satellite images desire accurate quality of the provided satellite images. Moreover, the distinguishability of each image captured by an actual satellite varies according to the atmospheric environment and solar angle at the captured region, the satellite velocity and capture angle, and the system noise. Hence , NIIRS must be measured for all captured images. There is a significant deficiency in professional human resources and time resources available to measure the NIIRS of few hundred images that are transmitted daily. Currently, NIIRS is measured every few months or even few years to assess the aging of the satellite as well as to verify and calibrate it [3]. Therefore, we develop an algorithm that can measure the national image interpretability rating scales (NIIRS) of a typical satellite image rather than an artificial target satellite image, in order to automatically assess its quality. In this study, the criteria for automatic edge region extraction are derived based on the previous works on manual edge region extraction [4][5], and consequently, we propose an algorithm that can extract the edge region. Moreover, RER and H are calculated from the extracted edge region for automatic edge region extraction. The average NIIRS value was measured to be 3.6342±0.15321 (2 standard deviations) from the automatic measurement experiment on a typical satellite image, which is similar to the result extracted from the artificial target.

• Journal of Electrical Engineering and Technology
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• v.7 no.6
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• pp.959-964
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• 2012

Internal pressure of vacuum interrupter (VI) is one of the most important parameters in VI operation and may increase due to the outgassing from the materials inside VI or gas permeation through metal flange or ceramic vessel. The increase of the pressure above a certain level leads to the failures of switching or insulation. Therefore, an effective pressure check of VI is essential and an analysis of partial discharge (PD) characteristics is an effective monitoring method to identify the degree of the internal pressure of VI. This paper introduces a research work on monitoring the internal pressure of VI by analyzing PDs which were measured using a capacitive PD coupler. The authors have developed cost effective capacitive coupler based on the ceramic material that has an excellent insulation properties and the main component of the capacitive coupler is made by SrTiO3. Detectable internal pressure range and distinguishability of the internal pressure of VI were investigated. From the PD tests results, the internal pressure range, from $10^{-2}$ torr to 500 torr, can be monitored by PD measurements using the capacitive coupler and PD inception voltage (PDIV) follows the Paschen's law. In addition, rise time of PD pulse at 13.2kV decreases with the increase of the internal pressure of VI.

• Journal of the Korean Wood Science and Technology
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• v.45 no.2
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• pp.202-212
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• 2017

This study was to establish the interrelation between chemical compositions and near infrared (NIR) spectra for the classification on distinguishability of domestic gymnosperms. Traditional wet chemistry methods and infrared spectral analyses were performed. In chemical compositions of five softwood species including larch (Larix kaempferi), red pine (Pinus densiflora), Korean pine (Pinus koraiensis), cypress (Chamaecyparis obtusa), and cedar (Cryptomeria japonica), their extractives and lignin contents provided the major information for distinction between the wood species. However, depending on the production region and purchasing time of woods, chemical compositions were different even though in same species. Especially, red pine harvested from Naju showed the highest extractive content about 16.3%, whereas that from Donghae showed about 5.0%. These results were expected due to different environmental conditions such as sunshine amount, nutrients and moisture contents, and these phenomena were also observed in other species. As a result of the principal component analysis (PCA) using NIR between five species (total 19 samples), the samples were divided into three groups in the score plot based on principal component (PC) 1 and principal component (PC) 2; group 1) red pine and Korean pine, group 2) larch, and group 3) cypress and cedar. Based on the chemical composition results, it was concluded that extractive content was highly relevant to wood classification by NIR analysis.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.5
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• pp.1610-1629
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• 2021

Failures frequently occurred in manufacturing machines due to complex and changeable manufacturing environments, increasing the downtime and maintenance costs. This manuscript develops a novel deep learning-based method named Multi-Domain Convolutional Neural Network (MDCNN) to deal with this challenging task with vibration signals. The proposed MDCNN consists of time-domain, frequency-domain, and statistical-domain feature channels. The Time-domain channel is to model the hidden patterns of signals in the time domain. The frequency-domain channel uses Discrete Wavelet Transformation (DWT) to obtain the rich feature representations of signals in the frequency domain. The statistic-domain channel contains six statistical variables, which is to reflect the signals' macro statistical-domain features, respectively. Firstly, in the proposed MDCNN, time-domain and frequency-domain channels are processed by CNN individually with various filters. Secondly, the CNN extracted features from time, and frequency domains are merged as time-frequency features. Lastly, time-frequency domain features are fused with six statistical variables as the comprehensive features for identifying the fault. Thereby, the proposed method could make full use of those three domain-features for fault diagnosis while keeping high distinguishability due to CNN's utilization. The authors designed massive experiments with 10-folder cross-validation technology to validate the proposed method's effectiveness on the CWRU bearing data set. The experimental results are calculated by ten-time averaged accuracy. They have confirmed that the proposed MDCNN could intelligently, accurately, and timely detect the fault under the complex manufacturing environments, whose accuracy is nearly 100%.

• Journal of Environmental Science International
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• v.30 no.5
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• pp.391-397
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• 2021

This study aims to establish the measures required for strengthening the internal stability of and executing the systematic plan for Gangwon-do in relation to the "urban regeneration preliminary project" launched by the Ministry of Land, Infrastructure, and Transport. The results of this study are as follows. The unit project carried out via the Gangwon-do urban regeneration preliminary project presented the tendency for the standardization of the H/W and S/W projects such as the establishment of the community anchor space and the resident competency reinforcement project. Further, rather than focusing on the contents that could objectively measure the effects of the project, it concentrated more on the performance indicators that are required for verifying the execution of unit projects like the establishment of buildings and operating programs. It was found to be insufficient with regard to the practicality of the project, the correlation with the New Deal Project, and the validity of the project contents. To improve these aspects, Gangwon-do would be required to highlight its distinguishability from the other regions and increase its practicality by operating the field-centered urban regeneration educational program, inducing the participation of experts in each of the areas in case there is a need to execute a project plan and discover a project with placeness. It also needs to focus on strengthening its connection with the urban regeneration new deal project by discovering the resident leaders and professional manpower, and establishing the performance indicators needed for systematically monitoring the regional changes in accordance to the urban regeneration preliminary project.

• Animal Bioscience
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• v.35 no.10
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• pp.1592-1605
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• 2022

Objective: The objective of this study was to select an effective in vitro digestion-fermentation model to estimate the effect of decreasing dietary crude protein (CP) on odor emission during pig production and to suggest potential prediction markers through in vitro and in vivo experiments. Methods: In the in vitro experiment, three diet formulations with different CP contents (170 g/kg, 150 g/kg, and 130 g/kg) but containing the same standardized ileal digestible essential amino acids (SID-EAA) were assessed. Each diet was evaluated by two different in vitro gastric-intestinal phase digestion methods (flask and dialysis), combined with fresh pig feces-ferment inoculation. Eighteen growing barrows (31.9±1.6 kg) were divided into three groups: control diet (180 g CP/kg, without SID-EAA adjustment), 170 g CP/kg diet, and 150 g CP/kg diet for 4 weeks. Results: The in vitro digestion results indicated that in vitro digestibility was affected by the gastric-intestinal phase digestion method and dietary CP level. According to the gas kinetic and digestibility results, the dialysis method showed greater distinguishability for dietary CP level adjustment. Nitrogen-related odor compounds (NH₃-N, indole, p-cresol, and skatole) were highly correlated with urease and protease activity. The feeding study indicated that both EAA-adjusted diets resulted in a lower odor emission especially in p-cresol and skatole. Both protease and urease activity in feces were also closely related to odor emissions from nitrogen metabolism compounds. Conclusion: Dialysis digestion in the gastric-intestinal phase followed by fresh fecal inoculation fermentation is suitable for in vitro diet evaluation. The enzyme activity in the fermentation and the fecal samples might provide a simple and effective estimation tool for nitrogen-related odor emission prediction in both in vitro and in vivo experiments.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.47
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• pp.63-94
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• 2002

On the purpose to suggest an advanced scheme in assessing the domestic wheat quality, this paper reviewed the inspection systems of wheat in major wheat producing countries as well as the quality criteria which are being used in wheat grading and classification. Most wheat producing countries are adopting both classifications of class and grade to provide an objective evaluation and an official certification to their wheat. There are two main purposes in the wheat classification. The first objectives of classification is to match the wheat with market requirements to maximize market opportunities and returns to growers. The second is to ensure that payments to glowers aye made on the basis of the quality and condition of the grain delivered. Wheat classes has been assigned based on the combination of cultivation area, seed-coat color, kernel and varietal characteristics that are distinctive. Most reputable wheat marketers also employ a similar approach, whereby varieties of a particular type are grouped together, designed by seed coat colour, grain hardness, physical dough properties, and sometimes more precise specification such as starch quality, all of which are genetically inherited characteristics. This classification in simplistic terms is the categorization of a wheat variety into a commercial type or style of wheat that is recognizable for its end use capabilities. All varieties registered in a class are required to have a similar end-use performance that the shipment be consistent in processing quality, cargo to cargo and year to year, Grain inspectors have historically determined wheat classes according to visual kernel characteristics associated with traditional wheat varieties. As well, any new wheat variety must not conflict with the visual distinguishability rule that is used to separate wheats of different classes. Some varieties may possess characteristics of two or more classes. Therefore, knowledge of distinct varietal characteristics is necessary in making class determinations. The grading system sets maximum tolerance levels for a range of characteristics that ensure functionality and freedom from deleterious factors. Tests for the grading of wheat include such factors as plumpness, soundness, cleanliness, purity of type and general condition. Plumpness is measured by test weight. Soundness is indicated by the absence or presence of musty, sour or commercially objectionable foreign odors and by the percentage of damaged kernels that ave present in the wheat. Cleanliness is measured by determining the presence of foreign material after dockage has been removed. Purity of class is measured by classification of wheats in the test sample and by limitation for admixtures of different classes of wheat. Moisture does not influence the numerical grade. However, it is determined on all shipments and reported on the official certificate. U.S. wheat is divided into eight classes based on color, kernel Hardness and varietal characteristics. The classes are Durum, Hard Red Spring, Hard Red Winter, Soft Red Winter, Hard White, soft White, Unclassed and Mixed. Among them, Hard Red Spring wheat, Durum wheat, and Soft White wheat are further divided into three subclasses, respectively. Each class or subclass is divided into five U.S. numerical grades and U.S. Sample grade. Special grades are provided to emphasize special qualities or conditions affecting the value of wheat and are added to and made a part of the grade designation. Canadian wheat is also divided into fourteen classes based on cultivation area, color, kernel hardness and varietal characteristics. The classes have 2-5 numerical grades, a feed grade and sample grades depending on class and grading tolerance. The Canadian grading system is based mainly on visual evaluation, and it works based on the kernel visual distinguishability concept. The Australian wheat is classified based on geographical and quality differentiation. The wheat grown in Australia is predominantly white grained. There are commonly up to 20 different segregations of wheat in a given season. Each variety grown is assigned a category and a growing areas. The state governments in Australia, in cooperation with the Australian Wheat Board(AWB), issue receival standards and dockage schedules annually that list grade specifications and tolerances for Australian wheat. AWB is managing "Golden Rewards" which is designed to provide pricing accuracy and market signals for Australia's grain growers. Continuous payment scales for protein content from 6 to 16% and screenings levels from 0 to 10% based on varietal classification are presented by the Golden Rewards, and the active payment scales and prices can change with market movements.movements.

• The Korean Journal of Mycology
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• v.32 no.1
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• pp.1-7
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• 2004

To establish the phylogenetic relationships of Dictyophora spp., rDNA-ITS regions of 11 strains of veiled lady mushroom collected from various countries were amplified and sequenced. It was observed that the 11 strains were divided into four groups based on PCR band patterns of each ITS region cleaved by eight different restriction enzymes in cleaved amplified polymorphic sequence analysis (CAPS). The phylogenic relationship of each group by cleaved amplified polymorphic sequence (CAPS) analysis matches well with previously reported morphological phylogeny, such as 5 strains of D. indusiata, 4 strains of D. echinovolvata, and a strain of Phallus rugulosus. Sequence analysis using the cluster V methods showed more detail classification than CAPS analysis. The 5.8S region showed two point nucleotide base exchanges from G to A according to four groups, and four groups were subdivided by sequence variation of ITS I and ITS II regions. But sequence variation of Phallus rugulosus was not showed in full ITS region. This study further delineates the taxonomic level at which ITS sequences, in comparison to ribosomal gene sequence, are most useful in systematics and other mushroom study.