안테나의 산란 및 결합 해석과 무선 에너지 전송에의 응용

학위논문 (박사)-- 서울대학교 대학원 : 전기·컴퓨터공학부, 2015. 8. 남상욱.This dissertation proposes analytical models for scattering by an antenna and coupling among antennas. The scattering properties of an antenna are analyzed using the theory of characteristic modes. The current of an antenna terminated in a load is expanded into the characteristic currents of a short-circuited antenna. When an antenna is very small compared to the wavelength of the incident electromagnetic field, the antenna rarely scatters unless the load reactance is close to the negative of the input reactance, i.e., the antenna can be modeled as a minimum scattering antenna. When the current of an antenna and its input impedance are determined using only one characteristic mode, the open-circuited antenna rarely scatters the electromagnetic field, i.e., the antenna can be modeled as a canonical minimum scattering antenna. The voltages and currents at the feed ports of coupled antennas can be calculated using impedance parameters. In this dissertation, three methods for calculating impedance parameters among coupled antennas are proposed. The first method is to use a generalized scattering matrix, the second is to use the current distributions of the antennas, and the third is to use the equivalent current that generates the same field as that generated by the antenna. A method is also proposed for calculating the electromagnetic fields generated by coupled antennas using a generalized scattering matrix when an electromagnetic field is incident on them or when sources are applied to their feed ports. These methods can be used both when the antennas are in free space and when they are near objects. If the antennas are minimum scattering antennas, the calculations of the impedance parameters and electromagnetic field are simplified. The models for scattering and coupling proposed in this dissertation are applied to the analysis of wireless energy transfer via the near field. Many antennas used in wireless energy transfer via the near field can be modeled as minimum scattering antennas because such wireless energy transfer generally operate at a frequency below or near the lowest resonant frequency of the antennas. In this dissertation, the maximum power transfer efficiency of a wireless energy transfer system and the load impedance that maximizes the power transfer efficiency are derived from the impedance parameters.Abstract i Contents iii List of Figures vi List of Tables viii Chapter 1 Introduction 1 1.1 Introduction 1 1.2 Notation Used in This Dissertation 5 Chapter 2 Generalized Scattering Matrix and Theory of Characteristic Modes 7 2.1 Generalized Scattering Matrix 7 2.1.1 Spherical Waves 7 2.1.2 Power Waves 11 2.1.3 Generalized Scattering Matrix 13 2.2 Theory of Characteristic Modes 16 2.2.1 Characteristic Modes Based on a Generalized Scattering Matrix 16 2.2.2 Characteristic Modes Based on Integral Equations 18 2.2.3 Modal Excitation Coefficient 40 Chapter 3 Analysis of Scattering by an Antenna 44 3.1 Analysis of the Transmitting and Scattering Properties of an Antenna Using the Theory of Characteristic Modes 44 3.1.1 Current Distribution of a Loaded Antenna 44 3.1.2 Representation of the Current of an Antenna in Terms of Characteristic Currents 45 3.1.3 Scattering Properties of an Antenna 46 3.1.4 Transmitting Properties of a Small Antenna near Objects 53 3.1.5 Validation 55 3.1.6 Minimum Scattering Antenna 57 3.2 Determination of the Generalized Scattering Matrix of an Antenna Using the Theory of Characteristic Modes 60 3.2.1 Determination of the Generalized Scattering Matrix of an Antenna from Characteristic Modes 60 3.2.3 Minimum Scattering Antenna 64 3.2.4 Validation 66 Chapter 4 Analysis of Coupling among Antennas 70 4.1 Analysis of Coupling among Antennas Using a Generalized Scattering Matrix 71 4.1.1 Analysis of Coupling between Two Antennas in Free Space 71 4.1.2 Analysis of Coupling among Antennas in an Environment 90 4.2 Determination of Impedance Parameters among Antennas Using Their Current Distributions 100 4.2.1 Equivalent Circuit for Transmitting and Receiving Antennas 100 4.2.2 Input Impedance of an Antenna near Objects 103 4.2.3 Self Impedance for Coupled Antennas 105 4.2.4 Mutual Impedance for Coupled Antennas 106 4.3 Determination of Impedance Parameters among Antennas Using Equivalent Currents 109 4.3.1 Calculation of Impedance Parameters among Antennas Using Equivalent Currents 109 4.3.2 Example: Two Helical Antennas in Half Space 112 Chapter 5 Analysis of Wireless Energy Transfer 118 5.1 Introduction 118 5.2 Maximum Power Transfer Efficiency and Optimum Load Impedance 119 5.3 Example 121 5.4 Properties of Wireless Energy Transfer 124 Chapter 6 Conclusion 128 Appendix 131 Bibliography 134 Abstract in Korean 139Docto

Pruning Self-Attention for Zero-Shot Multi-Speaker Text-to-Speech

For personalized speech generation, a neural text-to-speech (TTS) model must be successfully implemented with limited data from a target speaker. To this end, the baseline TTS model needs to be amply generalized to out-of-domain data (i.e., target speaker's speech). However, approaches to address this out-of-domain generalization problem in TTS have yet to be thoroughly studied. In this work, we propose an effective pruning method for a transformer known as sparse attention, to improve the TTS model's generalization abilities. In particular, we prune off redundant connections from self-attention layers whose attention weights are below the threshold. To flexibly determine the pruning strength for searching optimal degree of generalization, we also propose a new differentiable pruning method that allows the model to automatically learn the thresholds. Evaluations on zero-shot multi-speaker TTS verify the effectiveness of our method in terms of voice quality and speaker similarity.Comment: INTERSPEECH 202

AILTTS: Adversarial Learning of Intermediate Acoustic Feature for End-to-End Lightweight Text-to-Speech

The quality of end-to-end neural text-to-speech (TTS) systems highly depends on the reliable estimation of intermediate acoustic features from text inputs. To reduce the complexity of the speech generation process, several non-autoregressive TTS systems directly find a mapping relationship between text and waveforms. However, the generation quality of these system is unsatisfactory due to the difficulty in modeling the dynamic nature of prosodic information. In this paper, we propose an effective prosody predictor that successfully replicates the characteristics of prosodic features extracted from mel-spectrograms. Specifically, we introduce a generative model-based conditional discriminator to enable the estimated embeddings have highly informative prosodic features, which significantly enhances the expressiveness of generated speech. Since the estimated embeddings obtained by the proposed method are highly correlated with acoustic features, the time-alignment of input texts and intermediate features is greatly simplified, which results in faster convergence. Our proposed model outperforms several publicly available models based on various objective and subjective evaluation metrics, even using a relatively small number of parameters.Comment: Submitted to INTERSPEECH 202

A computational approach for identifying pathogenicity islands in prokaryotic genomes

BACKGROUND: Pathogenicity islands (PAIs), distinct genomic segments of pathogens encoding virulence factors, represent a subgroup of genomic islands (GIs) that have been acquired by horizontal gene transfer event. Up to now, computational approaches for identifying PAIs have been focused on the detection of genomic regions which only differ from the rest of the genome in their base composition and codon usage. These approaches often lead to the identification of genomic islands, rather than PAIs. RESULTS: We present a computational method for detecting potential PAIs in complete prokaryotic genomes by combining sequence similarities and abnormalities in genomic composition. We first collected 207 GenBank accessions containing either part or all of the reported PAI loci. In sequenced genomes, strips of PAI-homologs were defined based on the proximity of the homologs of genes in the same PAI accession. An algorithm reminiscent of sequence-assembly procedure was then devised to merge overlapping or adjacent genomic strips into a large genomic region. Among the defined genomic regions, PAI-like regions were identified by the presence of homolog(s) of virulence genes. Also, GIs were postulated by calculating G+C content anomalies and codon usage bias. Of 148 prokaryotic genomes examined, 23 pathogenic and 6 non-pathogenic bacteria contained 77 candidate PAIs that partly or entirely overlap GIs. CONCLUSION: Supporting the validity of our method, included in the list of candidate PAIs were thirty four PAIs previously identified from genome sequencing papers. Furthermore, in some instances, our method was able to detect entire PAIs for those only partial sequences are available. Our method was proven to be an efficient method for demarcating the potential PAIs in our study. Also, the function(s) and origin(s) of a candidate PAI can be inferred by investigating the PAI queries comprising it. Identification and analysis of potential PAIs in prokaryotic genomes will broaden our knowledge on the structure and properties of PAIs and the evolution of bacterial pathogenesis

CT Examinations for COVID-19: A Systematic Review of Protocols, Radiation Dose, and Numbers Needed to Diagnose and Predict

Purpose Although chest CT has been discussed as a first-line test for coronavirus disease 2019 (COVID-19), little research has explored the implications of CT exposure in the population. To review chest CT protocols and radiation doses in COVID-19 publications and explore the number needed to diagnose (NND) and the number needed to predict (NNP) if CT is used as a first-line test. Materials and Methods We searched nine highly cited radiology journals to identify studies discussing the CT-based diagnosis of COVID-19 pneumonia. Study-level information on the CT protocol and radiation dose was collected, and the doses were compared with each national diagnostic reference level (DRL). The NND and NNP, which depends on the test positive rate (TPR), were calculated, given a CT sensitivity of 94% (95% confidence interval [CI]: 91%–96%) and specificity of 37% (95% CI: 26%–50%), and applied to the early outbreak in Wuhan, New York, and Italy. Results From 86 studies, the CT protocol and radiation dose were reported in 81 (94.2%) and 17 studies (19.8%), respectively. Low-dose chest CT was used more than twice as often as standard-dose chest CT (39.5% vs.18.6%), while the remaining studies (44.2%) did not provide relevant information. The radiation doses were lower than the national DRLs in 15 of the 17 studies (88.2%) that reported doses. The NND was 3.2 scans (95% CI: 2.2–6.0). The NNPs at TPRs of 50%, 25%, 10%, and 5% were 2.2, 3.6, 8.0, 15.5 scans, respectively. In Wuhan, 35418 (TPR, 58%; 95% CI: 27710–56755) to 44840 (TPR, 38%; 95% CI: 35161–68164) individuals were estimated to have undergone CT examinations to diagnose 17365 patients. During the early surge in New York and Italy, daily NNDs changed up to 5.4 and 10.9 times, respectively, within 10 weeks. Conclusion Low-dose CT protocols were described in less than half of COVID-19 publications, and radiation doses were frequently lacking. The number of populations involved in a first-line diagnostic CT test could vary dynamically according to daily TPR; therefore, caution is required in future planning

The cyclin kinase inhibitor p21CIP1/WAF1 limits glomerular epithelial cell proliferation in experimental glomerulonephritis

The cyclin kinase inhibitor p21CIP1/WAF1 limits glomerular epithelial cell proliferation in experimental glomerulonephritis.BackgroundDuring glomerulogenesis, visceral glomerular epithelial cells (VECs) exit the cell cycle and become terminally differentiated and quiescent. In contrast to other resident glomerular cells, VECs undergo little if any proliferation in response to injury. However, the mechanisms for this remain unclear. Cell proliferation is controlled by cell-cycle regulatory proteins where the cyclin-dependent kinase inhibitor p21Cip1,WAF1 (p21) inhibits cell proliferation and is required for differentiation of many nonrenal cell types.MethodsTo test the hypothesis that p21 is required to maintain a differentiated and quiescent VEC phenotype, experimental glomerulonephritis was induced in p21 knockout (-/-) and p21 wild-type (+/+) mice with antiglomerular antibody. DNA synthesis (proliferating cell nuclear antigen, bromodeoxyuridine staining), VEC proliferation (multilayers of cells in Bowman's space), matrix accumulation (periodic acid-Schiff, silver staining), apoptosis (TUNEL), and renal function (serum urea nitrogen) were studied on days 5 and 14 (N = 6 per time point). VECs were identified by location, morphology, ezrin staining, and electron microscopy. VEC differentiation was measured by staining for Wilms’ tumor-1 gene.ResultsKidneys from unmanipulated p21-/- mice were histologically normal and did not have increased DNA synthesis, suggesting that p21 was not required for the induction of VEC terminal differentiation. Proliferating cell nuclear antigen and bromodeoxyuridine staining was increased 4.3- and 3.3-fold, respectively, in p21-/- mice with glomerulonephritis (P < 0.0001 vs. p21+/+ mice). At each time point, VEC proliferation was also increased in nephritic p21-/- mice (P < 0.0001 vs. p21+/+ mice). VEC re-entry into the cell cycle was associated with the loss of Wilms’ tumor-1 gene staining. Nephritic p21-/- mice had increased extracellular matrix protein accumulation and apoptosis and decreased renal function (serum urea nitrogen) compared with p21+/+ mice (P < 0.001).ConclusionThese results show that the cyclin kinase inhibitor p21 is not required by VECs to attain a terminally differentiated VEC phenotype. However, the loss of p21, in disease states, is associated with VEC re-entry into the cell cycle and the development of a dedifferentiated proliferative phenotype

Towards pathogenomics: a web-based resource for pathogenicity islands

Pathogenicity islands (PAIs) are genetic elements whose products are essential to the process of disease development. They have been horizontally (laterally) transferred from other microbes and are important in evolution of pathogenesis. In this study, a comprehensive database and search engines specialized for PAIs were established. The pathogenicity island database (PAIDB) is a comprehensive relational database of all the reported PAIs and potential PAI regions which were predicted by a method that combines feature-based analysis and similarity-based analysis. Also, using the PAI Finder search application, a multi-sequence query can be analyzed onsite for the presence of potential PAIs. As of April 2006, PAIDB contains 112 types of PAIs and 889 GenBank accessions containing either partial or all PAI loci previously reported in the literature, which are present in 497 strains of pathogenic bacteria. The database also offers 310 candidate PAIs predicted from 118 sequenced prokaryotic genomes. With the increasing number of prokaryotic genomes without functional inference and sequenced genetic regions of suspected involvement in diseases, this web-based, user-friendly resource has the potential to be of significant use in pathogenomics. PAIDB is freely accessible at

Signal crosstalk between estrogen and peroxisome proliferator-activated receptor α on adiposity

Peroxisome proliferator-activated receptor α and estrogen are believed to be involved in metabolic changes leading to obesity. To test this relationship, we divided female wildtype and PPARα-deficient mice fed on a high fat diet into the following groups: mock-operated, ovariectomized (OVX), and E2-treated. The visceral white adipose tissue and plasma cholesterol levels were increased significantly in wild type OVX and decreased in the E2-treated group, but interestingly not in PPARα-deficient mice. The mRNA levels of lipoprotein lipase in adipose tissue were also increased in only wild type OVX and decreased significantly in E2-treated mice. These novel results suggest the possibility of signaling crosstalk between PPARα and E2, causing obesity in vivo.This work was supported by a grant from the Korean Ministry of Heath and Welfare (A000385) and a grant from the Seoul R & BD Program (11117M0214882)