Presented in this paper is the development of the driver for the data acquisition card with a peripheral component interconnection （PCI） local bus on the ion cyclotron range of frequency heating （1CRH） system. The...Presented in this paper is the development of the driver for the data acquisition card with a peripheral component interconnection （PCI） local bus on the ion cyclotron range of frequency heating （1CRH） system. The driver is mainly aimed at the embedded VxWorks system （real-time operating system） which is widely used in various fields of real-time systems. An efficient way is employed to develop this driver, which will advance the real-time control of the ICRH system on the experimental advanced superconductor tokamak （EAST）. The driver is designed using the TORNADO integrated development environment （IDE）, and implemented in C plus language. The details include the hardware configuration, analogue/digital （A/D） and digital/analogue （D/A） conversion, input and output （I/O） operation of the driver to support over five cards. The data acquisition card can be manipulated in a low-level program and meet the requirements of A/D conversion and D/A outputs.展开更多
Sentiment analysis, a hot research topic, presents new challenges for understanding users＇ opinions and judg-ments expressed online. They aim to classify the subjective texts by assigning them a polarity label. In th...Sentiment analysis, a hot research topic, presents new challenges for understanding users＇ opinions and judg-ments expressed online. They aim to classify the subjective texts by assigning them a polarity label. In this paper, weintroduce a novel machine learning framework using auto-encoders network to predict the sentiment polarity label at theword level and the sentence level. Inspired by the dimensionality reduction and the feature extraction capabilities of theauto-encoders, we propose a new model for distributed word vector representation ＂PMI-SA＂ using as input pointwise-mutual-information ＂PMI＂ word vectors. The resulted continuous word vectors are combined to represent a sentence. Anunsupervised sentence embedding method, called Contextual Recursive Auto-Encoders ＂CoRAE＂, is also developed forlearning sentence representation. Indeed, CoRAE follows the basic idea of the recursive auto-encoders to deeply composethe vectors of words constituting the sentence, but without relying on any syntactic parse tree. The CoRAE model consistsin combining recursively each word with its context words （neighbors＇ words： previous and next） by considering the wordorder. A support vector machine classifier with fine-tuning technique is also used to show that our deep compositionalrepresentation model CoRAE improves significantly the accuracy of sentiment analysis task. Experimental results demon-strate that CoRAE remarkably outperforms several competitive baseline methods on two databases, namely, Sanders twittercorpus and Facebook comments corpus. The CoRAE model achieves an efficiency of 83.28% with the Facebook dataset and97.57% with the Sanders dataset.展开更多
Translation validation was invented in the 90＇s by Pnueli et al. as a technique to formally verify the correctness of code generators. Rather than certifying the code generator or exhaustively qualifying it, translat...Translation validation was invented in the 90＇s by Pnueli et al. as a technique to formally verify the correctness of code generators. Rather than certifying the code generator or exhaustively qualifying it, translation validators attempt to verify that program transformations preserve semantics. In this work, we adopt this approach to formally verify that the clock semantics and data dependence are preserved during the compilation of the Signal compiler. Translation valida- tion is implemented for every compilation phase from the initial phase until the latest phase where the executable code is generated, by proving the transformation in each phase of the compiler preserves the semantics. We represent the clock semantics, the data dependence of a program and its trans- formed counterpart as first-order formulas which are called clock models and synchronous dependence graphs （SDGs）, respectively. We then introduce clock refinement and depen- dence refinement relations which express the preservations of clock semantics and dependence, as a relation on clock mod- els and SDGs, respectively. Our validator does not require any instrumentation or modification of the compiler, nor any rewriting of the source program.展开更多
文摘Presented in this paper is the development of the driver for the data acquisition card with a peripheral component interconnection （PCI） local bus on the ion cyclotron range of frequency heating （1CRH） system. The driver is mainly aimed at the embedded VxWorks system （real-time operating system） which is widely used in various fields of real-time systems. An efficient way is employed to develop this driver, which will advance the real-time control of the ICRH system on the experimental advanced superconductor tokamak （EAST）. The driver is designed using the TORNADO integrated development environment （IDE）, and implemented in C plus language. The details include the hardware configuration, analogue/digital （A/D） and digital/analogue （D/A） conversion, input and output （I/O） operation of the driver to support over five cards. The data acquisition card can be manipulated in a low-level program and meet the requirements of A/D conversion and D/A outputs.
文摘Sentiment analysis, a hot research topic, presents new challenges for understanding users＇ opinions and judg-ments expressed online. They aim to classify the subjective texts by assigning them a polarity label. In this paper, weintroduce a novel machine learning framework using auto-encoders network to predict the sentiment polarity label at theword level and the sentence level. Inspired by the dimensionality reduction and the feature extraction capabilities of theauto-encoders, we propose a new model for distributed word vector representation ＂PMI-SA＂ using as input pointwise-mutual-information ＂PMI＂ word vectors. The resulted continuous word vectors are combined to represent a sentence. Anunsupervised sentence embedding method, called Contextual Recursive Auto-Encoders ＂CoRAE＂, is also developed forlearning sentence representation. Indeed, CoRAE follows the basic idea of the recursive auto-encoders to deeply composethe vectors of words constituting the sentence, but without relying on any syntactic parse tree. The CoRAE model consistsin combining recursively each word with its context words （neighbors＇ words： previous and next） by considering the wordorder. A support vector machine classifier with fine-tuning technique is also used to show that our deep compositionalrepresentation model CoRAE improves significantly the accuracy of sentiment analysis task. Experimental results demon-strate that CoRAE remarkably outperforms several competitive baseline methods on two databases, namely, Sanders twittercorpus and Facebook comments corpus. The CoRAE model achieves an efficiency of 83.28% with the Facebook dataset and97.57% with the Sanders dataset.
文摘Translation validation was invented in the 90＇s by Pnueli et al. as a technique to formally verify the correctness of code generators. Rather than certifying the code generator or exhaustively qualifying it, translation validators attempt to verify that program transformations preserve semantics. In this work, we adopt this approach to formally verify that the clock semantics and data dependence are preserved during the compilation of the Signal compiler. Translation valida- tion is implemented for every compilation phase from the initial phase until the latest phase where the executable code is generated, by proving the transformation in each phase of the compiler preserves the semantics. We represent the clock semantics, the data dependence of a program and its trans- formed counterpart as first-order formulas which are called clock models and synchronous dependence graphs （SDGs）, respectively. We then introduce clock refinement and depen- dence refinement relations which express the preservations of clock semantics and dependence, as a relation on clock mod- els and SDGs, respectively. Our validator does not require any instrumentation or modification of the compiler, nor any rewriting of the source program.
