Advanced Materials Research Vol. 981

Abstract: The theory model of the reflective optical current transformer (OCT) has been established using Jones matrix method, and the proper devices have been chose. According to the characteristics of the transformer’s output, signal processing circuits including photoelectric translating circuit, preamplifier, correlation detector, lowpass filter and ARM processor have been designed. The simulation mode was established in the Matlab environment. The simulation analysis as well as the noise analysis was carried out. Finally, the analysis of the relationship between transformer's input and output was analyzed by using function fitting method. The fitting coefficients and error were given and quadratic or quartic curve fitting was proposed.

Abstract: We numerically simulated the containerless rapid solidification for micrometer level solder ball used in BGA packaging, based on prior models for heterogeneous droplet nucleation and non-equilibrium solidification, to predict the solidification microstructure of solder ball. Results of simulations for Sn-5mass%Pb solder ball produced under different conditions are discussed.

Abstract: A fiber Raman amplifier (FRA) based on the properties of silica fiber can not only get a wideband gain spectrum by using multiple pumps, but also has the nature of low noise and cost. In the study of FRA, gain-flatness is one of the most key and hot issues. In this paper, we focus on the gain flatness of fiber Raman amplifier by multi-pump, and various parameters in term if power and number of pump source are analyzed comprehensively. According to the numerical results obtained, the optimized within power and number of the pump source are determined. And we controlled the gain-flatness of FRA within ±1 dB from 1512nm to 1566nm in a dense wavelength division multiplexing system with 67 channels.

Abstract: Semantic feature modeling is an important research topic in CAD, in which geometric constraints in model are solved automatically. A semantic feature modeling method is given in this paper. Firstly, the feature dependent graph is built based on geometric constraints. Secondly, the feature dependent graph is decomposed according to the complexity of subgraphs and the whole problem of solving geometric constraints is divided into several small ones. Thirdly, these small problems are solved. At the same time, the modeling architecture based on the decomposition of feature dependent graph is given. Experimental results show that when the proposed method is applied, the modeling performance is improved.

Abstract: Word sense disambiguation is key to many application problems in natural language processing. In this paper, a specific classifier of word sense disambiguation is introduced into machine translation system in order to improve the quality of the output translation. Firstly, translation of ambiguous word is deleted from machine translation of Chinese sentence. Secondly, ambiguous word is disambiguated and the classification labels are translations of ambiguous word. Thirdly, these two translations are combined. 50 Chinese sentences including ambiguous words are collected for test experiments. Experimental results show that the translation quality is improved after the proposed method is applied.

Abstract: Word sense disambiguation is widely applied to information retrieval, semantic comprehension and automatic summarization. It is an important research problem in natural language processing. In this paper, the center window is determined from the target ambiguous word. The words in the center window are extracted as discriminative features. At the same time, a new method of word sense disambiguation is proposed and the disambiguation classifier is given. The classifier is optimized and tested on SemEval-2007 #Task5 corpus. Experimental results show that the accuracy rate of disambiguation arrives at 64.2%.

Abstract: As one of the most popular mobile operating system, Android has been troubled by privilege escalation attacks. This is because that the original Android ignores the inspection of transmitted data in intent. It only checks the permission of intent to determine whether the Inter-Process Communication (IPC) could continue. We developed Nipdroid to solve the mentioned defect in Android IPC detection. Nipdroid is based on the technology of marking and tracking sensitive data. After the original Android detection, Nipdroid extracts the sensitive tags from intent, and matches them with the permission lists of both communication apps, and then checks whether there is unreasonable data transmission in IPC. Experiments show that Nipdroid is effective on both preventing privilege escalation attacks and protecting user's sensitive data.

Abstract: XML is a new standard for data representation and exchange, which has been widely used on the Internet. XML retrieval has caused more and more researchers concern. How to improve the retrieval efficiency has become an important study field, this paper proposes the retrieval method based on keyword weight and structure extension, which can get the middle retrieval results in accordance with calculating the keyword weight, and further to retrieval by implementing structural extension of middle retrieval results, then can get the final query results. The experiment results show that the retrieval method has high accuracy and the recall rate compared with the traditional retrieval method.

Abstract: The hybrid brain-computer interface (BCI) based on electroencephalography (EEG) become more and more popular. Motor imagery, steady state visual evoked potentials (SSVEPs) and P300 are main training Paradigms. In our previous research, BCI systems based on motor imagery can be extended by speech imagery. However, noise and artifact may be produced by different mental tasks and EEG signals are also different among users, so the classification accuracy can be improved by selecting optimum frequency range for each user. Mutual information (MI) is usually used to choose optimal features. After extracted the features from each narrow frequency range of EEG by common spatial patterns (CSP), the features are assessed by MI. Then, the optimum frequency range can be acquired. The final classification results are calculated by support vector machine (SVM). The average result of optimum frequency range from seven subjects is better than the result of a fixed frequency range.

Abstract: In this paper, the index structure, PR-quadtree for spatial data, is used to store data for a database. The properties of the quadtree are studied. With the properties prunning rules are set up for searching the Skyline set of the data stored in the quadtree. Through detailed analysis for the tree the method of finding some approximate skyline points is designed, by which a new skyline searching algorithm is given. The new algorithm is more effective.