Paper recommendation has become an increasingly important yet challenging task due to the rapidly expanding volume and scope of publications in the broad research community. Due to the lack of user profiles in public digital libraries, most existing methods for paper recommendation are through paper similarity measurements based on citations or contents, and still suffer from various performance issues. In this paper, we construct a graphical form of citation relations to identify relevant papers and design a hybrid recommendation model that combines both citation- and content-based approaches to measure paper similarities. Considering that citations at different locations in one article are likely of different significance, we define a concept of citation similarity with varying weights according to the sections of citations. We evaluate the performance of our recommendation method using Spearman correlation on real publication data from public digital libraries such as CiteSeer and Wanfang. Extensive experimental results show that the proposed hybrid method exhibits better performance than state-of-the-art techniques, and achieves 40% higher recommendation accuracy in average in comparison with citation-based approaches.

With the advances in computer processing that have yielded an enormous increase in performance, numerical analytical approaches based on electromagnetic theory have recently been applied to mobile radio propagation analysis. One such approach is the ray-tracing method based on geometrical optics and the uniform geometrical theory of diffraction. In this paper, ray-tracing techniques that have been proposed in order to improve computational accuracy and speed are surveyed. First, imaging and ray-launching methods are described and their extended methods are surveyed as novel fundamental ray-tracing techniques. Next, various ray-tracing acceleration techniques are surveyed and categorized into three approaches, i.e., deterministic, heuristic, and brute force. Then, hybrid methods are surveyed such as those employing Physical optics, the Effective Roughness model, and the Finite-Difference Time-Domain method that have been proposed in order to improve analysis accuracy.

In this paper, we present a discriminative word-character hybrid model for joint Chinese word segmentation and POS tagging. Our word-character hybrid model offers high performance since it can handle both known and unknown words. We describe our strategies that yield good balance for learning the characteristics of known and unknown words and propose an error-driven policy that delivers such balance by acquiring examples of unknown words from particular errors in a training corpus. We describe an efficient framework for training our model based on the Margin Infused Relaxed Algorithm (MIRA), evaluate our approach on the Penn Chinese Treebank, and show that it achieves superior performance compared to the state-of-the-art approaches reported in the literature.

Clonal Selection Algorithm (CSA), based on the clonal selection theory proposed by Burnet, has gained much attention and wide applications during the last decade. However, the proliferation process in the case of immune cells is asexual. That is, there is no information exchange during different immune cells. As a result the traditional CSA is often not satisfactory and is easy to be trapped in local optima so as to be premature convergence. To solve such a problem, inspired by the quantum interference mechanics, an improved quantum crossover operator is introduced and embedded in the traditional CSA. Simulation results based on the traveling salesman problems (TSP) have demonstrated the effectiveness of the quantum crossover-based Clonal Selection Algorithm.

An exact solution of the propagation constant of a cylindrical waveguide has been obtained in the event of the conductivity of the waveguide-composing conductor being finite. The said analysis has been reduced to a problem to solve a transcendental equation concerning an eigenvalue of the individual modes of the in-guide electromagnetic wave, and calculation of Jn-1(z)/Jn(z) by using of Bessel function becomes necessary. With a large conductivity the absolute value of the complex number z becomes excessively large, and none of calculation method with high accuracy has been found with the aid of a computer. This paper has solved the problem by using a continued fraction for the calculation with regard to which a recurrence formula is utilized. With the TE01 wave that has conventionally been used as a millimeter-wave guide, it is cleared that it is sufficient to select the number of the calculation terms of the continued fraction to the extent of approximately 1000 in the accuracy in accordance with this calculation method. It is also cleared that the approximation solution obtained by a method of perturbation coincides with the exact solution for the conductivity σ 102 [S/m].