Analysis on Electric Field Based on Three Dimensional Atmospheric Electric Field Apparatus

Xing, Hong-yan,He, Gui-xian,Ji, Xin-yuan The Korean Institute of Electrical Engineers 2018 Journal of Electrical Engineering & Technology Vol.13 No.4

As a key component of lighting location system (LLS) for lightning warning, the atmospheric electric field measuring is required to have high accuracy. The Conventional methods of the existent electric field measurement meter can only detect the vertical component of the atmospheric electric field, which cannot acquire the realistic electric field in the thunderstorm. This paper proposed a three dimensional (3D) electric field system for atmospheric electric field measurement, which is capable of three orthogonal directions in X, Y, Z, measuring. By analyzing the relationship between the electric field and the relative permittivity of ground surface, the permittivity is calculated, and an efficiency 3D measurement model is derived. On this basis, a three-dimensional electric field sensor and a permittivity sensor are adopted to detect the spatial electric field. Moreover, the elevation and azimuth of the detected target are calculated, which reveal the location information of the target. Experimental results show that the proposed 3D electric field meter has satisfactory sensitivity to the three components of electric field. Additionally, several observation results in the fair and thunderstorm weather have been presented.

Bayesian case influence analysis for GARCH models based on Kullback–Leibler divergence

Hong-Xia Hao,Jinguan Lin,Hong-Xia Wang,Xing-Fang Huang 한국통계학회 2016 Journal of the Korean Statistical Society Vol.45 No.4

Influence analysis has become an important tool for statistical analysis. This paper is concerned with Bayesian case influence analysis for generalized autoregressive conditional heteroscedasticity (GARCH) model. Case influence analysis is developed for both the joint and marginal posterior distributions based on the Kullback–Leibler divergence (K–L divergence). A simplified expression is presented for computing the K–L divergence between the full data posterior distribution and the case-deleted posterior distributions. The related computations can be done numerically by Markov Chain Monte Carlo samples from posterior distribution with full data. Some simulation studies are carried out to examine the performance of the proposed methods and show the relations between case-deletion model (CDM) and mean-shift outlier model (MSOM) for the GARCH models. Meanwhile, the methods are also illustrated by a real data.

Analysis on Electric Field Based on Three Dimensional Atmospheric Electric Field Apparatus

Hong-yan Xing,Gui-xian He,Xin-yuan Ji 대한전기학회 2018 Journal of Electrical Engineering & Technology Vol.13 No.4

As a key component of lighting location system (LLS) for lightning warning, the atmospheric electric field measuring is required to have high accuracy. The Conventional methods of the existent electric field measurement meter can only detect the vertical component of the atmospheric electric field, which cannot acquire the realistic electric field in the thunderstorm. This paper proposed a three dimensional (3D) electric field system for atmospheric electric field measurement, which is capable of three orthogonal directions in X, Y, Z, measuring. By analyzing the relationship between the electric field and the relative permittivity of ground surface, the permittivity is calculated, and an efficiency 3D measurement model is derived. On this basis, a three-dimensional electric field sensor and a permittivity sensor are adopted to detect the spatial electric field. Moreover, the elevation and azimuth of the detected target are calculated, which reveal the location information of the target. Experimental results show that the proposed 3D electric field meter has satisfactory sensitivity to the three components of electric field. Additionally, several observation results in the fair and thunderstorm weather have been presented.

Chemical, optical, and electrical characterization of Ga2O3 thin films grown by plasma-enhanced atomic layer deposition

Xing Li,Hong-Liang Lu,Hong-Ping Ma,Jian-Guo Yang,Jin-Xin Chen,Wei Huang,Qixin Guo,Jijun Feng,David Wei Zhang 한국물리학회 2019 Current Applied Physics Vol.19 No.2

Thin Ga2O3 films were grown on Si (100) using trimethylgallium (TMG) and oxygen as the precursors through plasma-enhanced atomic layer deposition. The depositions were made over a temperature range of 80–250 °C with a growth per cycle of around 0.07 nm/cycle. Surface self-saturating growth was obtained with TMG pulse time ≥20 ms at a temperature of 150 °C. The root mean square surface roughness of the obtained Ga2O3 films increased from 0.1 nm to 0.3 nm with increasing the growth temperature. Moreover, the x-ray photoelectron spectroscopy analysis indicated that the obtained film was Ga-rich with the chemical oxidation states Ga3+ and Ga1+, and no carbon contamination was detected in the films after Ar+ sputtering. The electron density of films measured by x-ray reflectivity varied with the growth temperature, increasing from 4.72 to 5.80 g/cm3 . The transmittance of Ga2O3 film deposited on a quartz substrate was obtained through ultraviolet visible (UV–Vis) spectroscopy. An obvious absorption in the deep UV region was demonstrated with a wide band gap of 4.6–4.8 eV. The spectroscopic ellipsometry analysis indicated that the average refractive index of the Ga2O3 film was 1.91 at 632.8 nm and increased with the growth temperature due to the dense structure of the films. Finally, the I-V and C-V characteristics proved that the Ga2O3 films prepared in this work had a low leakage current of 7.2 × 10−11 A/cm2 at 1.0 MV/cm and a high permittivity of 11.9, suitable to be gate dielectric.

Undecanoic Acid, Lauric Acid, and N-Tridecanoic Acid Inhibit Escherichia coli Persistence and Biofilm Formation

( Xing Jin ),( Jiacheng Zhou ),( Gabriella Richey ),( Mengya Wang ),( Sung Min Choi Hong ),( Seok Hoon Hong ) 한국미생물생명공학회(구 한국산업미생물학회) 2021 Journal of microbiology and biotechnology Vol.31 No.1

Persister cell formation and biofilms of pathogens are extensively involved in the development of chronic infectious diseases. Eradicating persister cells is challenging, owing to their tolerance to conventional antibiotics, which cannot kill cells in a metabolically dormant state. A high frequency of persisters in biofilms makes inactivating biofilm cells more difficult, because the biofilm matrix inhibits antibiotic penetration. Fatty acids may be promising candidates as antipersister or antibiofilm agents, because some fatty acids exhibit antimicrobial effects. We previously reported that fatty acid ethyl esters effectively inhibit Escherichia coli persister formation by regulating an antitoxin. In this study, we screened a fatty acid library consisting of 65 different fatty acid molecules for altered persister formation. We found that undecanoic acid, lauric acid, and N-tridecanoic acid inhibited E. coli BW25113 persister cell formation by 25-, 58-, and 44-fold, respectively. Similarly, these fatty acids repressed persisters of enterohemorrhagic E. coli EDL933. These fatty acids were all medium-chain saturated forms. Furthermore, the fatty acids repressed Enterohemorrhagic E. coli (EHEC) biofilm formation (for example, by 8-fold for lauric acid) without having antimicrobial activity. This study demonstrates that medium-chain saturated fatty acids can serve as antipersister and antibiofilm agents that may be applied to treat bacterial infections.

Mining Frequent Sub-hypergraph in an Uncertain Hypergraph for Knowledge Transfer

Xing Wang,Bin-Xing Fang,Hui He,Hong-Li Zhang 보안공학연구지원센터 2015 International Journal of Database Theory and Appli Vol.8 No.4

The knowledge transfer learning can generalize across domains where the types of objects and variables are different. Previous studies ignored connectivity and creativity of domain knowledge. Thus, these studies just transfer knowledge from a source domain to a target domain that not effectively use the knowledge from other domains. We proposed a method, called Multi-domain second order knowledge integration (MSKI), for integrating to address this problem. We hybridize and create new knowledge, which is formalized into an uncertain hypergraph. Then, we proposed a method to mine frequent sub-hypergraph from the uncertain hypergraph (MFS-UHG). The frequent sub-hypergraphs are pivot knowledge, which has to be transferred with high priority. We embed the pivot knowledge in the progress of MLN structure learning. The experimental evaluation on four domain datasets shows that the MSKI outperforms state-of-the-art MLN-based transfer learning.

A high-efficiency simulation method of wind field and its application on transmission line

Xing Fu,Xing-Heng Zhang,Hong-Nan Li,Gang Li,Hui-Juan Liu 한국풍공학회 2021 Wind and Structures, An International Journal (WAS Vol.33 No.4

Generally, the fluctuating wind is simplified as several independent one-dimensional multivariate stationary Gaussian processes in simulating a natural wind field. The correlation in the lateral, longitudinal and vertical directions should all be considered in the simulation of longitudinal wind field for the large-span spatial structures. In fact, this type of structure has lots of simulation points. The calculation amount of wind field simulation by the harmonic superposition method depends on the scale of cross-spectral density matrix, which is directly related to the number of simulated points, leading to a low efficiency when generating the time-varying wind speed. This paper innovatively proposes a high-efficiency simulation method for the longitudinal wind field based on Taylor’s hypothesis. Subsequently, the effectiveness of the proposed wind field method was verified by the numerical simulation. Finally, the dynamic responses of a transmission tower-line system under the wind loadings generated with the new method and traditional method are calculated and compared. The percentages difference of the mean and maximum axial force at the main tower members are less than 0.02% and 1%, respectively, indicating the effectiveness of the proposed time delay method. The results also show that the proposed simulation method of wind field can not only ensure the simulation accuracy, but also significantly improve the efficiency of wind speed generation, which is suitable for the wind load simulation of large-span spatial structures.

A Dependence Stability Bound based on the VC Dimension for Relational Classification

Xing Wang,Hui He,Bin-Xing Fang,Hong-Li Zhang 보안공학연구지원센터 2015 International Journal of Database Theory and Appli Vol.8 No.3

Relational classification (RC) is concerned with the application of statistical learning to relational data. RC models do not have improved stability to smooth the perturbations generated by variations in the correlation between the relational data. Therefore, few studies have attempted to derive a bound and develop a stability learning framework for RC models. To solve this problem, we derive a learning bound with a new measure dependence stability and a limited Vapnik–Chervonenkis (VC) dimension. Based on the learning bound, we then design a stable learning framework that serves as a guideline for the development of new learning algorithms for a broad class of RC models. Applying a Markov logic network on synthesized and real-world datasets, our experimental results demonstrate that our bound can be tight if the RC model has appropriate dependence stability and limited VC dimension and our learning framework increases the stability of RC models while reducing the deviation between empirical risk and true risk.

Effects of SRBSDV-infected rice plants on the fitness of vector and non-vector rice planthoppers

Hong-Xing Xu,Hong-Xing Xu,Xu-Song Zheng,Yajun Yang,Jue-Feng Zhang Zhang,Zhong-Xian Lu 한국응용곤충학회 2016 Journal of Asia-Pacific Entomology Vol.19 No.3

Southern rice black-streaked dwarf virus (SRBSDV) is a new member of the genus Fijivirus and transmitted by whitebacked planthopper (WBPH), Sogatella furcifera (Horváth). The rice area affected by SRBSDV and the subsequent damages are increasing rapidly. In current study, we evaluated the effects of SRBSDV-infected plants on the ecological fitness and the tolerance to adverse environmental factors of vector WBPH and non-vector brown planthopper (BPH), Nilaparvata lugens (Stål). Our study revealed that the fitness of WBPH and BPH were both influenced by feeding on SRBSDV-infected rice. Fecundity ofWBPH feeding on the SRBSDV-infected rice plants were higher than those on healthy plants, nymphal duration of male WBPH prolonged markedly by 0.77 d (P b 0.05), while the weight of brachypterous female adults significantly decreased (P b 0.05), and the average survival time shortened both at 26 °C and 31 °C, respectively. Median lethal time of WBPH on SRBSDV-infected and healthy rice plants were 80 h and 112 h at 26 °C, 64 h and 88 h at 31 °C, respectively. As for non-vector BPH, nymph survival rate decreased significantly by 11.22% (P b 0.05) and the longevity of female adults also shortened (P b 0.05), while hatchability of BPH eggs increased (P b 0.05). Survival time of BPH feeding on healthy rice at 26 °Cwas significant longer than those feeding on healthy and infected rice at 31 °C. The above results imply that the vectorWBPH suffers much stronger effects than non-vector BPH fromfeeding on SRBSDVinfected rice plants.

The Acquisition of Chinese Characters: Corpus Analyses and Connectionist Simulations

Hong Bing Xing,Hua Shu,Ping Li 서울대학교 인지과학연구소 2004 Journal of Cognitive Science Vol.5 No.1