Neural Machine Translation by Fusing Key Information of Text

When the Transformer proposed by Google in 2017, it was first used for machine translation tasks and achieved the state of the art at that time. Although the current neural machine translation model can generate high quality translation results, there are still mistranslations and omissions in the translation of key information of long sentences. On the other hand, the most important part in traditional translation tasks is the translation of key information. In the translation results, as long as the key information is translated accurately and completely, even if other parts of the results are translated incorrect, the final translation results’ quality can still be guaranteed. In order to solve the problem of mistranslation and missed translation effectively, and improve the accuracy and completeness of long sentence translation in machine translation, this paper proposes a key information fused neural machine translation model based on Transformer. The model proposed in this paper extracts the keywords of the source language text separately as the input of the encoder. After the same encoding as the source language text, it is fused with the output of the source language text encoded by the encoder, then the key information is processed and input into the decoder. With incorporating keyword information from the source language sentence, the model’s performance in the task of translating long sentences is very reliable. In order to verify the effectiveness of the method of fusion of key information proposed in this paper, a series of experiments were carried out on the verification set. The experimental results show that the Bilingual Evaluation Understudy (BLEU) score of the model proposed in this paper on the Workshop on Machine Translation (WMT) 2017 test dataset is higher than the BLEU score of Transformer proposed by Google on the WMT2017 test dataset. The experimental results show the advantages of the model proposed in this paper.     

马钢2500m~3高炉炉渣的冶金性能

在目前的原燃料条件下,为保证马钢2500m3高炉炉渣具有良好的流动性和较高的脱硫能力,炉渣的CaO／SiO2应控制在1．05至1．15之间,炉渣温度不低于1450℃．     

电力有源滤波器控制器的研究与仿真分析

建立了包括有源电力滤波器（ＡＰＦ）在内的公共连接点（ＰＣＣ）的数学模型;针对实际控制器计算过程中的时间延迟,提出对负载电流值进行预测的两种算法,对逆变器的开关元件提出一种新型脉宽调制（ＰＷＭ）控制方案,并采用电力电子仿真软件包进行了仿真验证。     

电镀塑料制品对结构设计及成形工艺的要求

为保证电镀塑料制品的质量,提出了符合电镀要求的塑料制品设计原则,并且指出在注塑成形时,对塑料经过充分干燥,采用较高的注塑温度,较低的注射压力和较慢的注射速度,是使镀层获得良好结合强度的先决条件。     

Structural Studies of DNA–Cationic Lipid Complexes Confined in Lithographically Patterned Microchannel Arrays

We have used lithographically patterned microchannel arrays with channel widths ranging from 1 to 20 m, fabricated using electron beam lithography and reactive ion etching, in structural studies of DNA–cationic lipid complexes in confinement. Various techniques have been developed for loading these DNA–membrane complexes into the microchannels or to form the complexes in situ by sequentially depositing DNA and lipid solutions into the microchannels. Optical microscopy studies indicate that such complex formation is strongly influenced by the periodic channel structure even at channel widths much larger than the persistent length of the DNA molecules. Preliminary x-ray diffraction experiments conducted at Stanford Synchrotron Radiation Laboratory (SSRL) yielded only a weak signal from the lipid bilayers in the complexes. The use of a microfocused x-ray beam produced by the newly developed Bragg–Fresnel optics at a third-generation synchrotron facility may dramatically increase the signal-to-noise ratio and allow observation of orientational as well as positional ordering of DNA molecules induced by the microchannels. Structural control of the DNA–membrane complexes has a broad range of potential applications in gene probe technology and as mesoscopic biomolecular composites.     

Globally Exponential Stability for Delayed Neural Networks Under Impulsive Control

In this paper, the dynamic behaviors of a class of neural networks with time-varying delays are investigated. Some less weak sufficient conditions based on p-norm and ∞-norm are obtained to guarantee the existence, uniqueness of the equilibrium point for the addressed neural networks without impulsive control by applying homeomorphism theory. And then, by utilizing inequality technique, Lyapunov functional method and the analysis method, some new and useful criteria of the globally exponential stability with respect to the equilibrium point under impulsive control we assumed are derived based on p-norm and ∞-norm, respectively. Finally, an example with simulation is given to show the effectiveness of the obtained results.     

基于词性的文本挖掘算法在IDS日志中的应用

提出一种以词性为参考值的文本挖掘算法,能有效挖掘与种子词有关的关联规则。基于Bootstrapping算法思想,既减少了预处理阶段对于词根还原的依赖,能处理日志中出现的中文词汇。增加了对于日志文本上下的理解,提高了关联规则的有效性,并应用与IDS日志挖掘之中,有效改善挖掘效率,为规则库提供关联规则。     

Genetic regulatory network-based symbiotic evolution

The main theme of this paper is to present a novel evolution, the genetic regulatory network-based symbiotic evolution (GRNSE), to improve the convergent speed and solution accuracy of genetic algorithms. The proposed GRNSE utilizes genetic regulatory network (GRN) reinforcement learning to improve the diversity and symbiotic evolution (SE) initialization to achieve the parallelism. In particular, GRN-based learning increases the global rate by regulating members of genes in symbiotic evolution. To compare the efficiency of the proposed method, we adopt 41 benchmarks that contain many nonlinear and complex optimal problems. The influences of dimension, individual population size, and gene population size are examined. A new control parameter, the population rate is introduced to initiate the ratio between the gene and chromosome. Finally, all the studies of there 41 benchmarks demonstrate that from the statistic point of view, GRNSE give a better convergence speed and a more accurate optimal solution than GA and SE.     

A computer-enabled solution procedure for food wholesalers’ distribution decision in cities with a circular transportation infrastructure

This paper addresses the food distribution decision from a wholesaler's perspective, as the wholesalers are often faced with thorny issues such as when, where, how to deliver products at the lowest costs to best satisfy the retailers’ changing needs. This research relies on a distribution problem encountered at Northern Grocery Company in Beijing as an example to develop a two-stage solution procedure and subsequent computer-enabled programs for identifying efficient vehicle routing alternatives. The solution process, which integrates heuristic search algorithms and an integer programming model, can be applied to a wide range of distribution problems with specified route durations and a circular transportation network structure as exemplified by City of Beijing.