• Asian-Australasian Journal of Animal Sciences
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• 제28권5호
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• pp.620-631
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• 2015

A total of 59 lactic acid bacteria (LAB) strains were isolated from corn stover silage. According to phenotypic and chemotaxonomic characteristics, 16S ribosomal DNA (rDNA) sequences and recA gene polymerase chain reaction amplification, these LAB isolates were identified as five species: Lactobacillus (L.) plantarum subsp. plantarum, Pediococcus pentosaceus, Enterococcus mundtii, Weissella cibaria and Leuconostoc pseudomesenteroides, respectively. Those strains were also screened for antimicrobial activity using a dual-culture agar plate assay. Based on excluding the effects of organic acids and hydrogen peroxide, two L. plantarum subsp. plantarum strains ZZU 203 and 204, which strongly inhibited Salmonella enterica ATCC $43971^T$, Micrococcus luteus ATCC $4698^T$ and Escherichia coli ATCC $11775^T$ were selected for further research on sensitivity of the antimicrobial substance to heat, pH and protease. Cell-free culture supernatants of the two strains exhibited strong heat stability (60 min at $100^{\circ}C$), but the antimicrobial activity was eliminated after treatment at $121^{\circ}C$ for 15 min. The antimicrobial substance remained active under acidic condition (pH 2.0 to 6.0), but became inactive under neutral and alkaline condition (pH 7.0 to 9.0). In addition, the antimicrobial activities of these two strains decreased remarkably after digestion by protease K. These results preliminarily suggest that the desirable antimicrobial activity of strains ZZU 203 and 204 is the result of the production of a bacteriocin-like substance, and these two strains with antimicrobial activity could be used as silage additives to inhibit proliferation of unwanted microorganism during ensiling and preserve nutrients of silage. The nature of the antimicrobial substances is being investigated in our laboratory.

• 한국정보전자통신기술학회논문지
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• 제7권4호
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• pp.159-167
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• 2014

Local device-to-device (D2D) communication between two smart mobile devices is becoming increasingly popular. The first key step in starting a D2D communication is to discover and identify the remote target device to establish a link. However, existing device discovery mechanisms either require users to explicitly identify the ID of the target device or rely on inaccurate beamforming technology. This paper presents two novel device identification algorithms using a variety of embedded sensors. The algorithms only require that users to point two devices towards each other. This paper describes the algorithms, analyzes their accuracy using analytical models, and verifies the results using simulations.

• 품질경영학회지
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• 제51권3호
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• pp.403-418
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• 2023

Purpose: The acceleration of technological innovation, specifically Industry 4.0, has triggered the emergence of a quality management paradigm known as Quality 4.0. This study aims to provide a systematic overview of dispersed studies on Quality 4.0 across various disciplines and to stimulate further academic discussions and industrial transformations. Methods: Text mining and machine learning approaches are applied to learn and identify key research topics, and the suggested key references are manually reviewed to develop a state-of-the-art overview of Quality 4.0. Results: 1) A total of 27 key research topics were identified based on the analysis of 1234 research papers related to Quality 4.0. 2) A relationship among the 27 key research topics was identified. 3) A multilevel framework consisting of technological enablers, business methods and strategies, goals, application industries of Quality 4.0 was developed. 4) The trends of key research topics was analyzed. Conclusion: The identification of 27 key research topics and the development of the Quality 4.0 framework contribute to a better understanding of Quality 4.0. This research lays the groundwork for future academic and industrial advancements in the field and encourages further discussions and transformations within the industry.

• 정보처리학회논문지:컴퓨터 및 통신 시스템
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• 제3권10호
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• pp.323-328
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• 2014

지그비 기반의 U헬스 시스템에서 가장 취약한 부분인 지그비 통신을 사용하는 무선 구간에서의 취약점을 분석하고 해당 취약점을 보완하기 위해 본 논문을 제안한다. 지그비에서 기존에 제기되었던 취약점들 이외에 본 논문에서는 지그비 통신에서 사용하는 64bit의 고유식별주소를 노출하는 것 자체를 취약점으로 규정하고 고유식별주소의 노출을 막기 위해 임시식별주소를 사용하였다. 제안 시스템은 지그비 보안 서비스 중에서 암호화를 위해 하나의 네트워크 키만을 사용하는 레지덴셜 모드의 메커니즘을 사용한다. 레지덴셜 모드는 전체 네트워크의 모든 노드들이 하나의 공통키를 사용하기 때문에 키가 유출될 경우 지그비 네트워크의 보안체계가 한 번에 무너질 위험성이 있다. 그러므로 이러한 위험에 대비하기 위해 네트워크 키를 보안 정책에 따라서 주기적으로 갱신하는 방식을 사용했다. 본 제안 시스템의 평가와 비교 분석에서는 기존 시스템에서 노출되었던 고유식별주소를 숨길 수 있고, 공용 네트워크 키 또한 주기적으로 갱신하므로 키 유출로 인해 발생할 수 있는 위험성을 감소시켰다.

• Asian-Australasian Journal of Animal Sciences
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• 제22권2호
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• pp.155-161
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• 2009

Mammal microsomal glutathione transferase 1 (MGST1) can conjugate many toxic or carcinogenic substances and depress oxidative stress. In this study, Chicken MGST1 and its variants were cloned for the first time and were composed of 956 or 944 nucleotides. The 12 nt deletion in the exon 2 did not alter the GT-AG rule and the ORFs for the two MGST1 variants were the same, which both comprised 465 nucletides and encoded a peptide with 155 amino acids. It was found that the two different splice variants identified using RT-PCR expressed in all three organs investigated of Dwarf Brown Chicken, namely liver, spleen and shell gland. Moreover, the expression level of MGST1 mRNA in the liver of Dwarf Brown chickens was the highest (p<0.01), and there were no significant differences between the spleen and the shell gland. These results provide a base for studying the biological function of Chicken MGST1.

• International Journal of Aerospace System Engineering
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• 제2권1호
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• pp.43-46
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• 2015

Aeroelastic gust response analysis plays an important role in design of aircrafts. For gust response analysis, frequency domain aerodynamics method has been typically used with generalized aerodynamic influence coefficient matrices at various reduced frequencies. However, it cannot be applied to the aeroservoelastic analysis, such as gust alleviation control. Time-domain state space (SS) models must be built. It attacks little attention that gust response analysis relies on continuous gust time-domain input signal in terms of its PSD function. The aim the current study is to provide a reduced-order modeling (ROM) method based on CFD to model gust responses for continuous gust responses for continuou gust inputs in time domain. The paper analyzed the gust response of AGARD445.6 wing subjected to the Dryden gust with ROMs and compared the difference between the rigid structure and elastic one. The results demonstrate that structure elastic effect effect should be considered in the design of aircraft.

• Journal of Microbiology and Biotechnology
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• 제27권1호
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• pp.122-129
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• 2017

Termites are destructive to agriculture, forestry, and buildings, but they can also promote agro-ecosystem balance through the degradation of lignocellulose. Termite-triggered cellulose digestion may be clarified through microbial metabolism of cellulose products. In the present study, we characterized the activities of cellulase and its three components synthesized by the cellulase-producing fungal strain HDZK-BYTF620 isolated from the gut of Odontotermes formosanus. The protein components of cellulases were synthesized by strain HDZK-BYTF620, which were isolated and characterized using polyacrylamide gel electrophoresis, and the expression of the cellulases was studied at the proteome level.

• 한국콘텐츠학회논문지
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• 제8권1호
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• pp.93-102
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• 2008

스폰서십의 효과를 결정짓는 여러 요인 중 기업이 스폰서하는 공동체(community)의 구성원들이 어떤 태도를 가지고 있는가 하는 점이 가장 중요한 요인이라 할 수 있다. 공동체 구성원의 태도를 이해하는데 매우 중요한 이론으로 동일시(identification) 혹은 일체감 이론을 생각할 수 있다. 공동체 구성원이 자신이 속한 공동체에 어느 정도의 일체감을 느끼는가에 따라 공동체에 대한 행동과 공동체에 스폰서하는 기업에 대한 태도가 달라질 수 있다. 본 연구에서는 공동체의식 개념을 적용하여 공동체 일체감의 주요 선행요인을 확인하고, 공동체 일체감과 기업의 스폰서십에 대한 반응간의 관계를 살펴보고자 하였다. 연구방법으로는 설문조사와 공변량 구조분석등을 사용하였다. 연구결과 공동체 의식이 공동체 일체감과 공동체에 대한 충성도에 영향을 미치는 것을 알 수 있었다. 공동체 의식의 세부 요소별로 보면, 욕구의 충족, 소속감, 정서적 유대감은 공동체 일체감과 공동체 충성도에 모두 긍정적 영향을 미치며, 영향력은 공동체 충성도에만 영향을 미치는 것을 알 수 있었다. 또한 공동체 일체감이 높을수록 공동체 충성도가 높아지며, 공동체 충성도가 높아지면 스폰서에 대한 태도가 개선되는 반응이 나타남을 확인할 수 있었다.

• Genomics & Informatics
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• 제14권1호
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• pp.2-11
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• 2016

The advances in mass spectrometry-based proteomics technologies have enabled the generation of global proteome data from tissue or body fluid samples collected from a broad spectrum of human diseases. Comparative proteomic analysis of global proteome data identifies and prioritizes the proteins showing altered abundances, called differentially expressed proteins (DEPs), in disease samples, compared to control samples. Protein biomarker candidates that can serve as indicators of disease states are then selected as key molecules among these proteins. Recently, it has been addressed that cellular pathways can provide better indications of disease states than individual molecules and also network analysis of the DEPs enables effective identification of cellular pathways altered in disease conditions and key molecules representing the altered cellular pathways. Accordingly, a number of network-based approaches to identify disease-related pathways and representative molecules of such pathways have been developed. In this review, we summarize analytical platforms for network-based protein biomarker discovery and key components in the platforms.

• Smart Structures and Systems
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• 제32권1호
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• pp.61-81
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• 2023

This study presents an ensemble learning based Bayesian model updating approach for structural damage diagnosis. In the developed framework, the structure is initially decomposed into a set of substructures. The autoregressive moving average (ARMAX) model is established first for structural damage localization based structural motion equation. The wavelet packet decomposition is utilized to extract the damage-sensitive node energy in different frequency bands for constructing structural surrogate models. Four methods, including Kriging predictor (KRG), radial basis function neural network (RBFNN), support vector regression (SVR), and multivariate adaptive regression splines (MARS), are selected as candidate structural surrogate models. These models are then resampled by bootstrapping and combined to obtain an ensemble model by probabilistic ensemble. Meanwhile, the maximum entropy principal is adopted to search for new design points for sample space updating, yielding a more robust ensemble model. Through the iterations, a framework of surrogate ensemble learning based model updating with high model construction efficiency and accuracy is proposed. The specificities of the method are discussed and investigated in a case study.