Relation Extraction Using Convolution Tree Kernel Expanded with Entity Features

PACLIC 21 / Seoul National University, Seoul, Korea / November 1-3, 200

Strict Intuitionistic Fuzzy Distance/Similarity Measures Based on Jensen-Shannon Divergence

Being a pair of dual concepts, the normalized distance and similarity measures are very important tools for decision-making and pattern recognition under intuitionistic fuzzy sets framework. To be more effective for decision-making and pattern recognition applications, a good normalized distance measure should ensure that its dual similarity measure satisfies the axiomatic definition. In this paper, we first construct some examples to illustrate that the dual similarity measures of two nonlinear distance measures introduced in [A distance measure for intuitionistic fuzzy sets and its application to pattern classification problems, \emph{IEEE Trans. Syst., Man, Cybern., Syst.}, vol.~51, no.~6, pp. 3980--3992, 2021] and [Intuitionistic fuzzy sets: spherical representation and distances, \emph{Int. J. Intell. Syst.}, vol.~24, no.~4, pp. 399--420, 2009] do not meet the axiomatic definition of intuitionistic fuzzy similarity measure. We show that (1) they cannot effectively distinguish some intuitionistic fuzzy values (IFVs) with obvious size relationship; (2) except for the endpoints, there exist infinitely many pairs of IFVs, where the maximum distance 1 can be achieved under these two distances; leading to counter-intuitive results. To overcome these drawbacks, we introduce the concepts of strict intuitionistic fuzzy distance measure (SIFDisM) and strict intuitionistic fuzzy similarity measure (SIFSimM), and propose an improved intuitionistic fuzzy distance measure based on Jensen-Shannon divergence. We prove that (1) it is a SIFDisM; (2) its dual similarity measure is a SIFSimM; (3) its induced entropy is an intuitionistic fuzzy entropy. Comparative analysis and numerical examples demonstrate that our proposed distance measure is completely superior to the existing ones

Accelerated Policy Evaluation: Learning Adversarial Environments with Adaptive Importance Sampling

The evaluation of rare but high-stakes events remains one of the main difficulties in obtaining reliable policies from intelligent agents, especially in large or continuous state/action spaces where limited scalability enforces the use of a prohibitively large number of testing iterations. On the other hand, a biased or inaccurate policy evaluation in a safety-critical system could potentially cause unexpected catastrophic failures during deployment. In this paper, we propose the Accelerated Policy Evaluation (APE) method, which simultaneously uncovers rare events and estimates the rare event probability in Markov decision processes. The APE method treats the environment nature as an adversarial agent and learns towards, through adaptive importance sampling, the zero-variance sampling distribution for the policy evaluation. Moreover, APE is scalable to large discrete or continuous spaces by incorporating function approximators. We investigate the convergence properties of proposed algorithms under suitable regularity conditions. Our empirical studies show that APE estimates rare event probability with a smaller variance while only using orders of magnitude fewer samples compared to baseline methods in both multi-agent and single-agent environments.Comment: 10 pages, 5 figure

Contribution of digital governments to digital transformation of firms: evidence from China

International audienceRapid advances in information and communication technologies have promoted the evolution of digital governments and the digital transformation of firms (DTF). As a provider of public services and a regulator, the government is associated closely with the operations of firms. However, the manner by which a digital government contributes to the DTF remains unknown. In this study, we use a sample of Chinese A-share listed firms in 2021 to determine the configurations of digital government components that generate different levels of DTF via fuzzy set qualitative comparative analysis. Empirical results show that the synergy of multiple digital government components, instead of a single digital government component, generates high and non-high levels of DTF. Additionally, a digital government heterogeneously affects the digital transformation of state-owned and non-state-owned firms. Non-state-owned firms are more dependent on high-performing digital governments than state-owned firms in achieving high levels of DTF. These findings contribute to the understanding of the important role of digital governments and promote investigations into the driving mechanisms of the DTF

Investigation of diffusion length distribution on polycrystalline silicon wafers via photoluminescence methods

Characterization of the diffusion length of solar cells in space has been widely studied using various methods, but few studies have focused on a fast, simple way to obtain the quantified diffusion length distribution on a silicon wafer. In this work, we present two different facile methods of doing this by fitting photoluminescence images taken in two different wavelength ranges or from different sides. These methods, which are based on measuring the ratio of two photoluminescence images, yield absolute values of the diffusion length and are less sensitive to the inhomogeneity of the incident laser beam. A theoretical simulation and experimental demonstration of this method are presented. The diffusion length distributions on a polycrystalline silicon wafer obtained by the two methods show good agreement

A mathematical programming method based on prospect theory for online physician selection under an R-set environment.

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.This study develops an R-mathematical programming method for multiple attribute group decision-making (MAGDM) problems with assessment values of alternatives and truth degrees of pairwise alternative comparisons represented by R-sets while the decision maker holds subjective bounded rationality. First, a novel scalar multiplication operation and defuzzification of R-sets are proposed to allow the use of R-sets in MAGDM problems. Subsequently, based on prospect theory and R-sets, a new technique is proposed to compute the individual overall prospect value of an alternative by simultaneously considering the positive ideal solution (PIS) and negative ideal solution (NIS). Additionally, the R-group consistency index (R-GCI) and R-group inconsistency index (R-GII) are defined using the individual overall prospect values of alternatives. The decision makers’ weights, attribute weights, PIS, and NIS are estimated by establishing a novel R-mathematical programming model, which is solved by the external archive-based constrained state transition, while the collective overall prospect values are computed to derive the final ranking order of alternatives. Thus, a new RLINMAP method is developed to solve MAGDM. A practical instance concerning online physician selection is provided with the corresponding sensitive and comparative analyses to verify the applicability, validity, and superiority of the developed method

Quantized impedance dealing with the damping behavior of the one-dimensional oscillator

A quantized impedance is proposed to theoretically establish the relationship between the atomic eigenfrequency and the intrinsic frequency of the one-dimensional oscillator in this paper. The classical oscillator is modified by the idea that the electron transition is treated as a charge-discharge process of a suggested capacitor with the capacitive energy equal to the energy level difference of the jumping electron. The quantized capacitance of the impedance interacting with the jumping electron can lead the resonant frequency of the oscillator to the same as the atomic eigenfrequency. The quantized resistance reflects that the damping coefficient of the oscillator is the mean collision frequency of the transition electron. In addition, the first and third order electric susceptibilities based on the oscillator are accordingly quantized. Our simulation of the hydrogen atom emission spectrum based on the proposed method agrees well with the experimental one. Our results exhibits that the one-dimensional oscillator with the quantized impedance may become useful in the estimations of the refractive index and one- or multi-photon absorption coefficients of some nonmagnetic media composed of hydrogen-like atoms