The significance of cultural awareness in foreign language learning is an issue that earns hot discussion in the both fields of linguistics and instructional science. Being different from others, the observing angle i...The significance of cultural awareness in foreign language learning is an issue that earns hot discussion in the both fields of linguistics and instructional science. Being different from others, the observing angle in this paper lies in how the signal is processed. The four skills of listening, speaking, reading and writing are classified, by ways of signal processing, into two categorizes, namely receptive skills to which listening and reading belong, and productive skills to which speaking and writing belong. By analyzing the signal processing progress occurred in each of the four skills, the author is to argue the functions of cultural awareness in each of these four skills, in order to reinforce the importance of emphasizing cultural awareness in the new standards for English in China.展开更多
Cloud Computing as a disruptive technology, provides a dynamic, elastic and promising computing climate to tackle the challenges of big data processing and analytics. Hadoop and MapReduce are the widely used open sour...Cloud Computing as a disruptive technology, provides a dynamic, elastic and promising computing climate to tackle the challenges of big data processing and analytics. Hadoop and MapReduce are the widely used open source frameworks in Cloud Computing for storing and processing big data in the scalable fashion. Spark is the latest parallel computing engine working together with Hadoop that exceeds MapReduce performance via its in-memory computing and high level programming features. In this paper, we present our design and implementation of a productive, domain-specific big data analytics cloud platform on top of Hadoop and Spark. To increase user’s productivity, we created a variety of data processing templates to simplify the programming efforts. We have conducted experiments for its productivity and performance with a few basic but representative data processing algorithms in the petroleum industry. Geophysicists can use the platform to productively design and implement scalable seismic data processing algorithms without handling the details of data management and the complexity of parallelism. The Cloud platform generates a complete data processing application based on user’s kernel program and simple configurations, allocates resources and executes it in parallel on top of Spark and Hadoop.展开更多
文摘The significance of cultural awareness in foreign language learning is an issue that earns hot discussion in the both fields of linguistics and instructional science. Being different from others, the observing angle in this paper lies in how the signal is processed. The four skills of listening, speaking, reading and writing are classified, by ways of signal processing, into two categorizes, namely receptive skills to which listening and reading belong, and productive skills to which speaking and writing belong. By analyzing the signal processing progress occurred in each of the four skills, the author is to argue the functions of cultural awareness in each of these four skills, in order to reinforce the importance of emphasizing cultural awareness in the new standards for English in China.
文摘Cloud Computing as a disruptive technology, provides a dynamic, elastic and promising computing climate to tackle the challenges of big data processing and analytics. Hadoop and MapReduce are the widely used open source frameworks in Cloud Computing for storing and processing big data in the scalable fashion. Spark is the latest parallel computing engine working together with Hadoop that exceeds MapReduce performance via its in-memory computing and high level programming features. In this paper, we present our design and implementation of a productive, domain-specific big data analytics cloud platform on top of Hadoop and Spark. To increase user’s productivity, we created a variety of data processing templates to simplify the programming efforts. We have conducted experiments for its productivity and performance with a few basic but representative data processing algorithms in the petroleum industry. Geophysicists can use the platform to productively design and implement scalable seismic data processing algorithms without handling the details of data management and the complexity of parallelism. The Cloud platform generates a complete data processing application based on user’s kernel program and simple configurations, allocates resources and executes it in parallel on top of Spark and Hadoop.
