Image reconstruction of a two-dimensional dielectric object by TE wave illumination

[[abstract]]In this paper, the inverse problem of a homogeneous dielectric cylinder with unknown cross-section shape and dielectric constant by TE wave illumination is investigated. We have presented a study of applying the genetic algorithm to reconstruct the shapes and relative permittivity of a homogeneous dielectric cylinder by TE wave. Based on the equivalence principle, boundary condition and measured scattered fields, we have derived a set of nonlinear surface integral equations and reformulated the imaging problem into an optimized problem. Numerical results have been carried out and good reconstruction has been obtained.[[conferencetype]]國際[[conferencedate]]20040621~20040626[[conferencelocation]]Kharkov, Ukrain

Numeral Understanding in Financial Tweets for Fine-grained Crowd-based Forecasting

Numerals that contain much information in financial documents are crucial for financial decision making. They play different roles in financial analysis processes. This paper is aimed at understanding the meanings of numerals in financial tweets for fine-grained crowd-based forecasting. We propose a taxonomy that classifies the numerals in financial tweets into 7 categories, and further extend some of these categories into several subcategories. Neural network-based models with word and character-level encoders are proposed for 7-way classification and 17-way classification. We perform backtest to confirm the effectiveness of the numeric opinions made by the crowd. This work is the first attempt to understand numerals in financial social media data, and we provide the first comparison of fine-grained opinion of individual investors and analysts based on their forecast price. The numeral corpus used in our experiments, called FinNum 1.0 , is available for research purposes.Comment: Accepted by the 2018 IEEE/WIC/ACM International Conference on Web Intelligence (WI 2018), Santiago, Chil

NumHG: A Dataset for Number-Focused Headline Generation

Headline generation, a key task in abstractive summarization, strives to condense a full-length article into a succinct, single line of text. Notably, while contemporary encoder-decoder models excel based on the ROUGE metric, they often falter when it comes to the precise generation of numerals in headlines. We identify the lack of datasets providing fine-grained annotations for accurate numeral generation as a major roadblock. To address this, we introduce a new dataset, the NumHG, and provide over 27,000 annotated numeral-rich news articles for detailed investigation. Further, we evaluate five well-performing models from previous headline generation tasks using human evaluation in terms of numerical accuracy, reasonableness, and readability. Our study reveals a need for improvement in numerical accuracy, demonstrating the potential of the NumHG dataset to drive progress in number-focused headline generation and stimulate further discussions in numeral-focused text generation.Comment: NumEval@SemEval-2024 Datase

FFTPL: An Analytic Placement Algorithm Using Fast Fourier Transform for Density Equalization

We propose a flat nonlinear placement algorithm FFTPL using fast Fourier transform for density equalization. The placement instance is modeled as an electrostatic system with the analogy of density cost to the potential energy. A well-defined Poisson's equation is proposed for gradient and cost computation. Our placer outperforms state-of-the-art placers with better solution quality and efficiency

Comparative Study of Some Population-based Optimization Algorithms on Inverse Scattering of a Two-Dimensional Perfectly Conducting Cylinder in Slab Medium

[[abstract]]The application of four techniques for the shape reconstruction of a 2-D metallic cylinder buried in dielectric slab medium by measured the cattered fields outside is studied in the paper. The finite-difference time-domain (FDTD) technique is employed for electromagnetic analyses for both the forward and inverse scattering problems, while the shape reconstruction problem is transformed into optimization one during the course of inverse scattering. Then, four techniques including asynchronous particle swarm optimization (APSO), PSO, dynamic differential evolution (DDE) and self-adaptive DDE (SADDE) are applied to reconstruct the location and shape of the 2-Dmetallic cylinder for comparative purposes. The statistical performances of these algorithms are compared. The results show that SADDE outperforms PSO, APSO and DDE in terms of the ability of exploring the optima. However, these results are considered to be indicative and do not generally apply to all optimization problems in electromagnetics.[[incitationindex]]SCI[[incitationindex]]EI[[booktype]]紙本[[booktype]]電子

Factors Affecting Occupational Exposure to Needlestick and Sharps Injuries among Dentists in Taiwan: A Nationwide Survey

BACKGROUND: Although the risks of needlestick and sharps injuries (NSIs) for dentists are well recognized, most papers published only described the frequency of occupational exposure to NSIs. Less has been reported assessing factors contributing to exposure to NSIs. The purpose of this study was to update the epidemiology of NSIs among dentists in Taiwan and identify factors affecting NSIs in order to find preventive strategies. METHODOLOGY/PRINCIPAL FINDINGS: A nationwide survey was conducted in dentists at 60 hospitals and 340 clinics in Taiwan. The survey included questions about factors supposedly affecting exposure to NSIs, such as dentist and facility characteristics, knowledge and attitudes about infectious diseases, and practices related to infection control. Univariate and multivariate logistic regression analyses were conducted to determine the association between risk factors and exposure to NSIs. In total, 434 (74.8%) of 580 dentists returned the survey questionnaires, and 100 (23.0%) reported that they had experienced more than one NSI per week. Our data showed that the risk of occupational NSIs is similarly heightened by an older age (odds ratio [OR], 3.18; 95% confidence interval [CI], 1.62-6.25), more years in practice (OR, 2.57; 95% CI, 1.41-4.69), working in clinics (OR, 1.73; 95% CI, 1.08-2.77), exhibiting less compliance with infection-control procedures (OR, 1.82; 95% CI, 1.04-3.18), having insufficient knowledge of blood-borne pathogens (OR, 1.67; 95% CI, 1.04-2.67), and being more worried about being infected by blood-borne pathogens (OR, 1.82; 95% CI, 1.05-3.13). CONCLUSIONS/SIGNIFICANCE: High rates of NSIs and low compliance with infection-control procedures highly contribute to the chance of acquiring a blood-borne pathogen infection and threaten occupational safety. This study reveals the possible affecting factors and helps in designing prevention strategies for occupational exposure to NSIs