• Title/Summary/Keyword: Linear Structure Model

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Development of Selection Model of Subway Station Influence Area (SIA) in Seoul City using Chi-square Automatic Interaction Detection (CHAID) (CHAID분석을 이용한 서울시 지하철 역세권 지가 영향모형 개발)

  • Choi, Yu-Ran;Kim, Tae-Ho;Park, Jung-Soo
    • Journal of the Korean Society for Railway
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    • v.11 no.5
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    • pp.504-512
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    • 2008
  • In general, based on criteria of subway law, radius 500m from subway station is defined as SIA (Subway Station Influence Area). Therefore, in this paper, selection models of SIA are developed to identify appropriate SIA for specific legions in Seoul metropolitan city based on CHAID analysis. As a result, following outputs are obtained; (1) walking distance from subway station is the most influential factor to define SIA (2) SIAs vary with regions (i. e. Gangnam area: 767m, Gangbuk area: 452m), and (3) walking distance from subway station is influential to land price of SIA. In addition, in Gangnam, the structure of land price of the closest section has a polynomial trend curve rather than linear compared in comparison with other sections. Therefore, it is desirable for current definition of SIA (radius 500m from subway station) to be redefined to reflect characteristics of land use and walking distance according to each region respectively.

The impact of the change in the splitting method of decision trees on the prediction power (의사결정나무의 분기법 변화가 예측력에 미치는 영향)

  • Chang, Youngjae
    • The Korean Journal of Applied Statistics
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    • v.35 no.4
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    • pp.517-525
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    • 2022
  • In the era of big data, various data mining techniques have been proposed as major analysis methodologies. As complex and diverse data is mass-produced, data mining techniques have attracted attention as a method that forms the foundation of data science. In this paper, we focused on the decision tree, which is frequently used in practice and easy to understand as one of representative data mining methods. Specifically, we analyzed the effect of the splitting method of decision trees on the model performance. We compared the prediction power and structures of decision tree models with different split methods based on various simulated data. The results show that the linear combination split method can improve the prediction accuracy of decision trees in the case of data simulated from nonlinear models with complex structure.

Synthesis and radiolabeling of PEGylated dendrimer-G2-Gemifloxacin with 99mTc to Biodistribution study in rabbit

  • Mohtavinejad, Naser;Dolatshahi, Shaya;Amanlou, Massoud;Ardestani, Mehdi Shafiee;Asadi, Mehdi;Pormohammad, Ali
    • Advances in nano research
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    • v.10 no.5
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    • pp.461-470
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    • 2021
  • Infection is one of the major mortality causes throughout the globe. Nuclear medicine plays an important role in diagnosis of deep infections such as osteomyelitis, arthritis infection, heart valve and heart prosthesis infections. Techniques such as labeled leukocytes are sensitive and selective for tracking the inflammations but they are not suitable for differentiating infection from inflammation. Anionic linear-globular dendrimer-G2 was synthesized then conjugation to gemifloxacin antibiotic. The structures were identified by FT-IR, 1H-NMR, C-NMR, LC-MS and DLS. The toxicity of gemifloxacin and dendrimer-gemifloxacin complex was compared by MTT test. Dendrimer-G2-gemifloxacin was labeled by Technetium-99m and its in-vitro stability and radiochemical purity were investigated. In-vivo biodistribution and SPECT imaging were studied in a rabbit model. Identify and verify the structure of the each object was confirmed by FT-IR, 1H-NMR, C-NMR and LC-MS, also, the size and charge of this compound were 128 nm and -3/68 mv respectively. MTT test showed less toxicity of the dendrimer-G2-gemifloxacin than free gemifluxacin (P < 0.001). Radiochemical yield was > %98. Human serum stability was 84% up to 24 h. Biodistribution study at 50 min, 24 and 48 h showed that the complex is significantly absorbed by the intestine and accumulation in the lungs and affects them, finally excreted through the kidneys, biodistribution results are consistent with results from full image means of SPECT/CT technique.

The Influence of Human Capital on GDP Dynamics: Modeling in the COVID-19 Conditions

  • Derii, Zhanna;Zosymenko, Tetiana;Shaposhnykov, Kostiantyn;Tochylina, Yuliia;Krylov, Denys;Papaika, Oleksandr
    • International Journal of Computer Science & Network Security
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    • v.22 no.3
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    • pp.67-76
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    • 2022
  • COVID-19 struck labor markets around the world, exposing and exacerbating the gender inequalities within the human capital structure. The last, in its turn, jeopardizes the return of the national economies to the growth trajectory undermined by pandemic impact. The authors assume that COVID-19 disproportionately affected the employment rates of women and men, which led to increased gender inequality in the labor market, which, in turn, affected GDP growth rates in the EU. To prove this hypothesis two research questions are discovered: 1) whether there was a different correlation between the number of COVID-19 cases in the EU and indicators of the labor market for women and men; and 2) whether there was a link between the growth of gender inequality in the EU labor market and the GDP dynamics in these countries. The analysis of the correlation between the number of cases of COVID-19 and indicators of the labor market in the EU revealed faster growth of women's unemployment rates compared to men's ones as the COVID-19 incidence unfolded. Multiple linear regression and factor analysis have been used to investigate the influence of gender inequality in the labor market on GDP dynamics. Despite the methodological limitations, the proposed model is both a sound argument and an analytical basis in favor of gender-responsive economic recovery backed by the systematic and consistent gender equality policy of a government.

Seed Dispersal by Water, Wind, Birds, and Bats in the Caliraya Watershed, Laguna

  • Giancarlo Pocholo L. Enriquez;Lillian Jennifer V. Rodriguez
    • Proceedings of the National Institute of Ecology of the Republic of Korea
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    • v.4 no.1
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    • pp.28-42
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    • 2023
  • Seed dispersal supports community structure, maintains genetic connectivity across fragmented landscapes, and influences vegetation assemblages. In the Philippines, only two seed dispersal studies have compared different dispersal agents. We examined the seed dispersal patterns of water, wind, birds, and bats in the Caliraya Watershed, Philippines. We aimed to determine the floral species that were dispersed and how the forest characteristics influenced seed dispersal. By running seed rain traps and drift litter collection from March to June 2022, we analyzed 14,090 seeds in a privately owned study site within the watershed. Water did not exclusively disperse any species and acted as a secondary disperser. Seed density (seeds/trap) was significantly higher for bird-dispersed (n=166) and bat-dispersed (n=145) seeds than for wind-dispersed (n=79) seeds (One-way analysis of variance [ANOVA]: F2,87=16.21, P<0.0001). Species number (species/trap) was significantly higher for bird-dispersed (n=3.7) and bat-dispersed (n=3.9) seeds than for wind-dispersed (n=0.2) seeds (One-way ANOVA: F2,87 =16.67, P<0.0001). Birds dispersed more species because they are more diverse and access a wider variety of fruits, unlike bats. Birds and bats target different fruits and provide separate seed dispersal services. Generalized linear model analyses revealed that the number and basal area of fleshy fruit trees most strongly influenced the bird seed dispersal patterns. Therefore, we recommend a three-way approach to restoration efforts in the Caliraya Watershed: (1) ensure the presence of fleshy fruit trees in restoration zones, (2) assist the establishment of mid-successional and wind-dispersed trees, and (3) intensify the conservation efforts for both flora and faunal diversity.

Combined Application Effects of Arbuscular Mycorrhizal Fungi and Biochar on the Rhizosphere Fungal Community of Allium fistulosum L.

  • Chunxiang Ji;Yingyue Li;Qingchen Xiao;Zishan Li;Boyan Wang;Xiaowan Geng;Keqing Lin;Qing Zhang;Yuan Jin;Yuqian Zhai;Xiaoyu Li;Jin Chen
    • Journal of Microbiology and Biotechnology
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    • v.33 no.8
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    • pp.1013-1022
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    • 2023
  • Arbuscular mycorrhizal fungi (AMF) are widespread soil endophytic fungi, forming mutualistic relationships with the vast majority of land plants. Biochar (BC) has been reported to improve soil fertility and promote plant growth. However, limited studies are available concerning the combined effects of AMF and BC on soil community structure and plant growth. In this work, a pot experiment was designed to investigate the effects of AMF and BC on the rhizosphere microbial community of Allium fistulosum L. Using Illumina high-throughput sequencing, we showed that inoculation of AMF and BC had a significant impact on soil microbial community composition, diversity, and versatility. Increases were observed in both plant growth (the plant height by 8.6%, shoot fresh weight by 12.1%) and root morphological traits (average diameter by 20.5%). The phylogenetic tree also showed differences in the fungal community composition in A. fistulosum. In addition, Linear discriminant analysis (LDA) effect size (LEfSe) analysis revealed that 16 biomarkers were detected in the control (CK) and AMF treatment, while only 3 were detected in the AMF + BC treatment. Molecular ecological network analysis showed that the AMF + BC treatment group had a more complex network of fungal communities, as evidenced by higher average connectivity. The functional composition spectrum showed significant differences in the functional distribution of soil microbial communities among different fungal genera. The structural equation model (SEM) confirmed that AMF could improve the microbial multifunctionality by regulating the rhizosphere fungal diversity and soil properties. Our findings provide new information on the effects of AMF and biochar on plants and soil microbial communities.

Effects of bacterial β-mannanase on apparent total tract digestibility of nutrients in various feedstuffs fed to growing pigs

  • Ki Beom Jang;Yan Zhao;Young Ihn Kim;Tiago Pasquetti;Sung Woo Kim
    • Animal Bioscience
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    • v.36 no.11
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    • pp.1700-1708
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    • 2023
  • Objective: The objective of this study was to determine the effects of β-mannanase on metabolizable energy (ME) and apparent total tract digestibility (ATTD) of protein in various feedstuffs including barley, copra meal, corn, corn distillers dried grains with solubles (DDGS), palm kernel meal, sorghum, and soybean meal. Methods: A basal diet was formulated with 94.8% corn and 0.77% amino acids, minerals, and vitamins and test diets replacing corn-basal diets with barley, corn DDGS, sorghum, soybean meal, or wheat (50%, respectively) and copra meal or palm kernel meal (30%, respectively). The basal diet and test diets were evaluated by using triplicated or quadruplicated 2×2 Latin square designs consisting of 2 diets and 2 periods with a total of 54 barrows at 20.6±0.6 kg (9 wk of age). Dietary treatments were levels of β-mannanase supplementation (0 or 800 U/kg of feed). Fecal and urine samples were collected for 4 d following a 4-d adaptation period. The ME and ATTD of crude protein (CP) in feedstuffs were calculated by a difference procedure. Data were analyzed using Proc general linear model of SAS. Results: Supplementation of β-mannanase improved (p<0.05) ME of barley (10.4%), palm kernel meal (12.4%), sorghum (6.0%), and soybean meal (2.9%) fed to growing pigs. Supplementation of β-mannanase increased (p<0.05) ATTD of CP in palm kernel meal (8.8%) and tended to increase (p = 0.061) ATTD of CP in copra meal (18.0%) fed to growing pigs. Conclusion: This study indicates that various factors such as the structure and the amount of β-mannans, water binding capacity, and the level of resistant starch vary among feedstuffs and the efficacy of supplemental β-mannanase may be influenced by these factors.

An efficient 2.5D inversion of loop-loop electromagnetic data (루프-루프 전자탐사자료의 효과적인 2.5차원 역산)

  • Song, Yoon-Ho;Kim, Jung-Ho
    • Geophysics and Geophysical Exploration
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    • v.11 no.1
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    • pp.68-77
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    • 2008
  • We have developed an inversion algorithm for loop-loop electromagnetic (EM) data, based on the localised non-linear or extended Born approximation to the solution of the 2.5D integral equation describing an EM scattering problem. Source and receiver configuration may be horizontal co-planar (HCP) or vertical co-planar (VCP). Both multi-frequency and multi-separation data can be incorporated. Our inversion code runs on a PC platform without heavy computational load. For the sake of stable and high-resolution performance of the inversion, we implemented an algorithm determining an optimum spatially varying Lagrangian multiplier as a function of sensitivity distribution, through parameter resolution matrix and Backus-Gilbert spread function analysis. Considering that the different source-receiver orientation characteristics cause inconsistent sensitivities to the resistivity structure in simultaneous inversion of HCP and VCP data, which affects the stability and resolution of the inversion result, we adapted a weighting scheme based on the variances of misfits between the measured and calculated datasets. The accuracy of the modelling code that we have developed has been proven over the frequency, conductivity, and geometric ranges typically used in a loop-loop EM system through comparison with 2.5D finite-element modelling results. We first applied the inversion to synthetic data, from a model with resistive as well as conductive inhomogeneities embedded in a homogeneous half-space, to validate its performance. Applying the inversion to field data and comparing the result with that of dc resistivity data, we conclude that the newly developed algorithm provides a reasonable image of the subsurface.

Dispersion Characteristics of Wave Forces on Interlocking Caisson Breakwaters by Cross Cables (크로스 케이블로 결속된 인터로킹 케이슨 방파제의 파력분산특성)

  • Seo, Ji Hye;Yi, Jin Hak;Park, Woo Sun;Won, Deck Hee
    • Journal of Korean Society of Coastal and Ocean Engineers
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    • v.27 no.5
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    • pp.315-323
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    • 2015
  • Damage level of coastal structures has been scaled up according to increase of wave height and duration of the storm due to the abnormal global climate change. So, the design criteria for new breakwaters is being intensified and structural strengthening is also conducted for the existing breakwaters. Recently, interlocking concept has been much attention to enhance the structural stability of the conventional caisson structure designed individually to resist waves. The interlocking caisson breakwater may be survival even if unusual high wave occurs because the maximum wave force may be reduced by phase lags among the wave forces acting on each caisson. In this study, the dispersion characteristics of wave forces using interlocking system that connect the upper part of caisson with cable in the normal direction of breakwater was investigated. A simplified linear model was developed for computational efficiency, in which the foundation and connection cables were modelled as linear springs, and caisson structures were assumed to be rigid. From numerical experiments, it can be found that the higher wave forces are transmitted through the cable as the angle of incident wave is larger, and the larger the stiffness of the interlocking cable makes larger wave dispersion effect.

A Basic Study on the Differential Diagnostic System of Laryngeal Diseases using Hierarchical Neural Networks (다단계 신경회로망을 이용한 후두질환 감별진단 시스템의 개발)

  • 전계록;김기련;권순복;예수영;이승진;왕수건
    • Journal of Biomedical Engineering Research
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    • v.23 no.3
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    • pp.197-205
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    • 2002
  • The objectives of this Paper is to implement a diagnostic classifier of differential laryngeal diseases from acoustic signals acquired in a noisy room. For this Purpose, the voice signals of the vowel /a/ were collected from Patients in a soundproof chamber and got mixed with noise. Then, the acoustic Parameters were analyzed, and hierarchical neural networks were applied to the data classification. The classifier had a structure of five-step hierarchical neural networks. The first neural network classified the group into normal and benign or malign laryngeal disease cases. The second network classified the group into normal or benign laryngeal disease cases The following network distinguished polyp. nodule. Palsy from the benign laryngeal cases. Glottic cancer cases were discriminated into T1, T2. T3, T4 by the fourth and fifth networks All the neural networks were based on multilayer perceptron model which classified non-linear Patterns effectively and learned by an error back-propagation algorithm. We chose some acoustic Parameters for classification by investigating the distribution of laryngeal diseases and Pilot classification results of those Parameters derived from MDVP. The classifier was tested by using the chosen parameters to find the optimum ones. Then the networks were improved by including such Pre-Processing steps as linear and z-score transformation. Results showed that 90% of T1, 100% of T2-4 were correctly distinguished. On the other hand. 88.23% of vocal Polyps, 100% of normal cases. vocal nodules. and vocal cord Paralysis were classified from the data collected in a noisy room.