一起银行汇票纠纷给我们的启示

2001年12月31日，B公司向其开户银行——A银行申请开出了一张转账银行汇票，汇票号码NO．00016266，金额￥100000．00，收款人为C公司。

The Analysis of Handel Variations as an Example for Brahms Variations

＂Variations＂ is one of the main musical forms in compositional process. Johannes Brahms is one of the most important Romantic composers that used this form. Variations and Fugue on a Theme by Handel, Op. 24, （Op. 24, 1862） is a piece that Johannes Brahms wrote for solo piano in a highly creative style, which was classically arranged. Brahms took the theme from an aria in George Frederic Handel＇s Harpsichord Suite in B-flat major, HWV 434 （1733）. In Handel＇s work, the original theme was turned into five variations. With the purpose of exploring chromatic possibilities after the piano was developed from harpsichord, Brahms made 25 magnificent variations with an extensive fugue in his work. The purpose of this work is to prepare an explanatory document for pianists who intend to perform this piece and who are not familiar with such work. Also, it is hoped that piano performers will find explanatory points in this composition （e.g., stylistic characteristics） through comparisons with his other variations and start performing it more frequently

Extraction Algorithm of English Text Summarization for English Teaching

In order to improve the ability of sharing and scheduling capability of English teaching resources, an improved algorithm for English text summarization is proposed based on Association semantic rules. The relative features are mined among English text phrases and sentences, the semantic relevance analysis and feature extraction of keywords in English abstract are realized, the association rules differentiation for English text summarization is obtained based on information theory, related semantic roles information in English Teaching Texts is mined. Text similarity feature is taken as the maximum difference component of two semantic association rule vectors, and combining semantic similarity information, the accurate extraction of English text Abstract is realized. The simulation results show that the method can extract the text summarization accurately, it has better convergence and precision performance in the extraction process.

Video Concept Detection Based on Multiple Features and Classifiers Fusion

The rapid growth of multimedia content necessitates powerful technologies to filter, classify, index and retrieve video documents more efficiently. However, the essential bottleneck of image and video analysis is the problem of semantic gap that low level features extracted by computers always fail to coincide with high-level concepts interpreted by humans. In this paper, we present a generic scheme for the detection video semantic concepts based on multiple visual features machine learning. Various global and local low-level visual features are systelrtically investigated, and kernelbased learning method equips the concept detection system to explore the potential of these features. Then we combine the different features and sub-systen on both classifier-level and kernel-level fusion that contribute to a more robust system Our proposed system is tested on the TRECVID dataset. The resulted Mean Average Precision （MAP） score is rmch better than the benchmark perforrmnce, which proves that our concepts detection engine develops a generic model and perforrrs well on both object and scene type concepts.

Enhancing Domain Knowledge with Semantic Models of Web Documents

The paper considers the problem of semantic processing of web documents by designing an approach, which combines extracted semantic document model and domain- related knowledge base. The knowledge base is populated with learnt classification rules categorizing documents into topics. Classification provides for the reduction of the dimensio0ality of the document feature space. The semantic model of retrieved web documents is semantically labeled by querying domain ontology and processed with content-based classification method. The model obtained is mapped to the existing knowledge base by implementing inference algorithm. It enables models of the same semantic type to be recognized and integrated into the knowledge base. The approach provides for the domain knowledge integration and assists the extraction and modeling web documents semantics. Implementation results of the proposed approach are presented.

Technology Embedded Imagination for Arab Women

With advancing channels of communication easing the availability of technological tools, the young minds of women in the Arabian Peninsula are ready to adopt forthcoming challenges. The embrace of storytelling in the digital realm by these young minds reflects the interplay of traditional culture, western modernism, and changes brought about by media industries. These women have adopted and used new media as a vehicle to maneuver their interesting and fresh ideas and have seen the rectilinear screen of a computer as an exit through which to come out and say something to the masses. The thinking methodology has culminated in pragmatic and dynamic visuals in order to celebrate, inform, and create awareness about the issues that they see in the region and among the people. With this freedom of expression, they are creating a new visual culture and transforming themselves into a meaningful workforce. With emerging technological tools, they blend intuitive, pragmatic, emotional, and contextual imagination with a highly-sophisticated production pipeline in order to incorporate the challenges of synthesizing ＂dialect＂ and ＂codes＂ that have traditionally been segregated in the culture. Their work is an amalgamation of arts/design, animation, life footage, and meaningful communication. With cyclical evaluation, they entwine the two elements, creativity, and technicality with massive exposure of Digital Assists Management （DAM）. This paper explains how current technological tools and contextualized teaching instructions foster meaningful content with the elicitation and mergence of Arab anthropological characteristics.