• Title/Summary/Keyword: Component Identification

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Approach for Microwave Frequency Measurement Based on a Single Photonic Chip Combined with a Phase Modulator and Microring Resonator

  • Zhang, Jiahong;Zhu, Chuyi;Yang, Xiumei;Li, Yingna;Zhao, Zhengang;Li, Chuan
    • Current Optics and Photonics
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    • 제2권6호
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    • pp.576-581
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    • 2018
  • A new approach for identification of a microwave frequency using an integrated optical waveguide chip, combined with a phase modulator (PM) and two microring resonators (MRRs), is proposed, theoretically deduced, and verified. By wavelength tuning to set the PM under the condition of a double side band (DSB), the measurement range can be started from the dc component, and the measurement range and response slope can be adjusted by designing the radius and transmission coefficient of the MRR. Simulations reveal that the amplitude comparison function (ACF) has a monotonic relationship from dc to 32.5 GHz, with a response slope of 5.15 dB under conditions of DSB modulation, when the radius values, transmission coefficients, and the loss factors are designed respectively as $R_1=400{\mu}m$, $R_2=600{\mu}m$, $t_1=t_2=0.63$, and ${\gamma}_1={\gamma}_2=0.66$. Theoretical calculations and simulation results both indicate that this new approach has the potential to be used for measuring microwave frequencies, with the advantages of compact structure and superior reconfigurability.

Information Systems in Interdisciplinary Research: Analytic and Holistic Ways to Access Information Science Knowledge

  • Engerer, Volkmar P.
    • Journal of Information Science Theory and Practice
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    • 제7권2호
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    • pp.6-22
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    • 2019
  • The paper explores how information science knowledge can be used systematically in digital, interdisciplinary research settings and gives a conceptual analysis of the relationship between information science knowledge as donor and other research as receiver in an interdisciplinary project environment. The validity of the approach is demonstrated by the author's work on the project "The Primacy of Tense: A. N. Prior Now and Then." The study proposes a hybrid approach, combining analysis and synthesis. The analytical component identifies information systems, assigns an information system type to them, and accesses the information science knowledge associated with that type. The synthetic part focuses on the connections between information systems according to the receiver discipline's practices. The paper makes explicit the actions of experienced information professionals, thereby making their expertise accessible to others. The analytical and synthetic strategies are explained by linking them to two modes of researchers in the receiver discipline, how they act as researchers and what they know about it. The paper offers information professionals concrete assistance with identification of the appropriate strategy for accessing professional knowledge and taking appropriate actions and development decisions.

Computer vision monitoring and detection for landslides

  • Chen, Tim;Kuo, C.F.;Chen, J.C.Y.
    • Structural Monitoring and Maintenance
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    • 제6권2호
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    • pp.161-171
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    • 2019
  • There have been a few checking frameworks intended to ensure and improve the nature of their regular habitat. The greater part of these frameworks are constrained in their capacities. In this paper, the insightful checking framework intended for debacle help and administrations has been exhibited. The ideal administrations, necessities and coming about plan proposition have been indicated. This has prompted a framework that depends fundamentally on ecological examination so as to offer consideration and security administrations to give the self-governance of indigenous habitats. In this sense, ecological acknowledgment is considered, where, in light of past work, novel commitments have been made to help include based and PC vision situations. This epic PC vision procedure utilized as notice framework for avalanche identification depends on changes in the normal landscape. The multi-criteria basic leadership strategy is used to incorporate slope data and the level of variety of the highlights. The reproduction consequences of highlight point discovery are shown in highlight guide coordinating toward discover steady and coordinating component focuses and effectively identified utilizing these two systems, by examining the variety in the distinguished highlights and the element coordinating.

Bioprospecting of Novel and Bioactive Metabolites from Endophytic Fungi Isolated from Rubber Tree Ficus elastica Leaves

  • Ding, Zhuang;Tao, Tao;Wang, Lili;Zhao, Yanna;Huang, Huiming;Zhang, Demeng;Liu, Min;Wang, Zhengping;Han, Jun
    • Journal of Microbiology and Biotechnology
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    • 제29권5호
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    • pp.731-738
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    • 2019
  • Endophytic fungi are an important component of plant microbiota, and have the excellent capacity for producing a broad variety of bioactive metabolites. These bioactive metabolites not only affect the survival of the host plant, but also provide valuable lead compounds for novel drug discovery. In this study, forty-two endophytic filamentous fungi were isolated from Ficus elastica leaves, and further identified as seven individual taxa by ITS-rDNA sequencing. The antimicrobial activity of these endophytic fungi was evaluated against five pathogenic microorganisms. Two strains, Fes1711 (Penicillium funiculosum) and Fes1712 (Trichoderma harzianum), displayed broad-spectrum bioactivities. Our following study emphasizes the isolation, identification and bioactivity testing of chemical metabolites produced by T. harzianum Fes1712. Two new isocoumarin derivatives (1 and 2), together with three known compounds (3-5) were isolated, and their structures were elucidated using NMR and MS. Compounds 1 and 2 exhibited inhibitory activity against Escherichia coli. Our findings reveal that endophytic fungi from the rubber tree F. elastica leaves exhibit unique characteristics and are potential producers of novel natural bioactive products.

Bayesian forecasting approach for structure response prediction and load effect separation of a revolving auditorium

  • Ma, Zhi;Yun, Chung-Bang;Shen, Yan-Bin;Yu, Feng;Wan, Hua-Ping;Luo, Yao-Zhi
    • Smart Structures and Systems
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    • 제24권4호
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    • pp.507-524
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    • 2019
  • A Bayesian dynamic linear model (BDLM) is presented for a data-driven analysis for response prediction and load effect separation of a revolving auditorium structure, where the main loads are self-weight and dead loads, temperature load, and audience load. Analyses are carried out based on the long-term monitoring data for static strains on several key members of the structure. Three improvements are introduced to the ordinary regression BDLM, which are a classificatory regression term to address the temporary audience load effect, improved inference for the variance of observation noise to be updated continuously, and component discount factors for effective load effect separation. The effects of those improvements are evaluated regarding the root mean square errors, standard deviations, and 95% confidence intervals of the predictions. Bayes factors are used for evaluating the probability distributions of the predictions, which are essential to structural condition assessments, such as outlier identification and reliability analysis. The performance of the present BDLM has been successfully verified based on the simulated data and the real data obtained from the structural health monitoring system installed on the revolving structure.

SHORT-ROOT Controls Cell Elongation in the Etiolated Arabidopsis Hypocotyl

  • Dhar, Souvik;Kim, Jinkwon;Yoon, Eun Kyung;Jang, Sejeong;Ko, Kangseok;Lim, Jun
    • Molecules and Cells
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    • 제45권4호
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    • pp.243-256
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    • 2022
  • Transcriptional regulation, a core component of gene regulatory networks, plays a key role in controlling individual organism's growth and development. To understand how plants modulate cellular processes for growth and development, the identification and characterization of gene regulatory networks are of importance. The SHORT-ROOT (SHR) transcription factor is known for its role in cell divisions in Arabidopsis (Arabidopsis thaliana). However, whether SHR is involved in hypocotyl cell elongation remains unknown. Here, we reveal that SHR controls hypocotyl cell elongation via the transcriptional regulation of XTH18, XTH22, and XTH24, which encode cell wall remodeling enzymes called xyloglucan endotransglucosylase/hydrolases (XTHs). Interestingly, SHR activates transcription of the XTH genes, independently of its partner SCARECROW (SCR), which is different from the known mode of action. In addition, overexpression of the XTH genes can promote cell elongation in the etiolated hypocotyl. Moreover, confinement of SHR protein in the stele still induces cell elongation, despite the aberrant organization in the hypocotyl ground tissue. Therefore, it is likely that SHR-mediated growth is uncoupled from SHR-mediated radial patterning in the etiolated hypocotyl. Our findings also suggest that intertissue communication between stele and endodermis plays a role in coordinating hypocotyl cell elongation of the Arabidopsis seedling. Taken together, our study identifies SHR as a new crucial regulator that is necessary for cell elongation in the etiolated hypocotyl.

Damage detection of bridges based on spectral sub-band features and hybrid modeling of PCA and KPCA methods

  • Bisheh, Hossein Babajanian;Amiri, Gholamreza Ghodrati
    • Structural Monitoring and Maintenance
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    • 제9권2호
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    • pp.179-200
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    • 2022
  • This paper proposes a data-driven methodology for online early damage identification under changing environmental conditions. The proposed method relies on two data analysis methods: feature-based method and hybrid principal component analysis (PCA) and kernel PCA to separate damage from environmental influences. First, spectral sub-band features, namely, spectral sub-band centroids (SSCs) and log spectral sub-band energies (LSSEs), are proposed as damage-sensitive features to extract damage information from measured structural responses. Second, hybrid modeling by integrating PCA and kernel PCA is performed on the spectral sub-band feature matrix for data normalization to extract both linear and nonlinear features for nonlinear procedure monitoring. After feature normalization, suppressing environmental effects, the control charts (Hotelling T2 and SPE statistics) is implemented to novelty detection and distinguish damage in structures. The hybrid PCA-KPCA technique is compared to KPCA by applying support vector machine (SVM) to evaluate the effectiveness of its performance in detecting damage. The proposed method is verified through numerical and full-scale studies (a Bridge Health Monitoring (BHM) Benchmark Problem and a cable-stayed bridge in China). The results demonstrate that the proposed method can detect the structural damage accurately and reduce false alarms by suppressing the effects and interference of environmental variations.

Identification and characterization of fish breeding habitats on Lake Kyoga as an approach to sustainable fisheries management

  • Rebecca Walugembe Nambi;Abebe Getahun;Fredrick Jones Muyodi;John Peter Obubu
    • Fisheries and Aquatic Sciences
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    • 제26권4호
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    • pp.282-293
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    • 2023
  • Nile perch and Nile tilapia are major commercial species in Uganda, and thus require continuous production. However, their production is impacted by anthropogenic activities such as fishing in breeding habitats. The aim of this study was to identify and characterize Nile perch and Nile tilapia fish breeding habitats on Lake Kyoga. Water quality, lake bottom, fish and vegetation type samples were collected from 20 sites in April of 2021 and 2022. Key informant interviews were conducted with experienced fishermen at five fish landing sites. The water quality parameters indicated significant difference within the sites using analysis of variance. Sandy and muddy bottom types were equally spread at 40% each by use of a pie chart. Fish gonads showed no significant difference among the 20 sites. Bivariate correlation analysis of the vegetation types indicated a strong negative correlation with Nile perch while Nile tilapia had a positive correlation. Principal component analysis of the water quality, fish gonads and habitat vegetation components cumulatively contributed 82.5% in characterizing a fish breeding habitat. Four sites for Nile perch and four sites for Nile tilapia were characterized as breeding sites on Lake Kyoga and are recommended for mapping and gazettement as breeding habitats for sustainable fisheries management.

Identification of pollutant sources and evaluation of water quality improvement alternatives of the Geum river

  • shiferaw, Natnael;Kim, Jaeyoung;Seo, Dongil
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2022년도 학술발표회
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    • pp.475-475
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    • 2022
  • The aim of this study is to identify the significant pollutant sources from the tributaries that are affecting the water quality of the study site, the Geum River and provide a solution to enhance the water quality. Multivariate statistical analysis modles such as cluster analysis, Principal component analysis (PCA) and positive matrix factorization (PMF) were applied to identify and prioritize the major pollutant sources of the two major tributaries, Gab-cheon and Miho-cheon, of the Geum River. PCA identifies three major pollutant sources for Gab-cheon and Miho-cheon, respectively. For Gab-cheon, wastewater treatment plant (WWTP), urban, and agricultural pollutions are identified as major pollutant sources. For Miho-cheon, agricultural, urban, and forest land are identified as major pollutant sources. On the contrary, PMF identifies three pollutant sources in Gab-cheon, same as PCA result and two pollutant sources in Miho-cheon. Water quality control scenarios are formulated and improvement of water quality in the river locations are simulated and analyzed with the Environmental Fluid Dynamic Code (EFDC) model. Scenario results were evaluated using a water quality index developed by Canadian Council of Ministers of the Environment. PCA and PMF appears to be effective to identify water pollution sources for the Geum river and also its tributaries in detail and thus can be used for the development of water quality improvement alternative of the above water bodies.

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Comparison of the Performance of Clustering Analysis using Data Reduction Techniques to Identify Energy Use Patterns

  • Song, Kwonsik;Park, Moonseo;Lee, Hyun-Soo;Ahn, Joseph
    • 국제학술발표논문집
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    • The 6th International Conference on Construction Engineering and Project Management
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    • pp.559-563
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    • 2015
  • Identification of energy use patterns in buildings has a great opportunity for energy saving. To find what energy use patterns exist, clustering analysis has been commonly used such as K-means and hierarchical clustering method. In case of high dimensional data such as energy use time-series, data reduction should be considered to avoid the curse of dimensionality. Principle Component Analysis, Autocorrelation Function, Discrete Fourier Transform and Discrete Wavelet Transform have been widely used to map the original data into the lower dimensional spaces. However, there still remains an ongoing issue since the performance of clustering analysis is dependent on data type, purpose and application. Therefore, we need to understand which data reduction techniques are suitable for energy use management. This research aims find the best clustering method using energy use data obtained from Seoul National University campus. The results of this research show that most experiments with data reduction techniques have a better performance. Also, the results obtained helps facility managers optimally control energy systems such as HVAC to reduce energy use in buildings.

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