Compact voltage-mode multi-valued literal gate using nanoscale ballistic MOSFETs

A CMOS voltage-mode multi-valued literal gate is presented. The ballistic electron transport characteristic of nanoscale MOSFETs is smartly used to compactly achieve universal radix-4 literal operations. The proposed literal gates have small numbers of transistors and low power dissipations, which makes them promising for future nanoscale multi-valued circuits. The gates are simulated by HSPICE.

Smart universal multiple-valued logic gates by transferring single electrons

This paper proposes smart universal multiple-valued (MV) logic gates by transferring single electrons (SEs). The logic gates are based on MOSFET based SE turnstiles that can accurately transfer SEs with high speed at high temperature. The number of electrons transferred per cycle by the SE turnstile is a quantized function of its gate voltage, and this characteristic is fully exploited to compactly finish MV logic operations. First, we build arbitrary MV literal gates by using pairs of SE turnstiles. Then, we propose universal MV logic-to-value conversion gates and MV analog-digital conversion circuits. We propose a SPICE model to describe the behavior of the MOSFET based SE turnstile. We simulate the performances of the proposed gates. The MV logic gates have small number of transistors and low power dissipations.

汉语文本语篇语句焦点确定及焦点与重音关系研究

This study investigated the method of the focus identification in Chinese text discourse and the relationship between accent and focus, large corpus analysis and decision tree were used in the research. The main results are: 1. Based on the concept of the Focus and understanding of the discourse, Foci identification is consistent and steady; 2. Special Focus markers and specific Focus constructions have greater influence than special constituent order on identifying Focus in Chinese discourse; while information states also have great influence on focus identifying; part of speech，information state, the relative position in the sentence, focus-sensitive operator, specific Focus constructions, contrast relations, relations between the sentences are important factors to focus identifying; 3. Using multi-dimensional tagging and knowledge discovery, it is a feasible way to construct and employ decision trees by computing tagging results to identify Focus; 4. Focus predicting also depends on literal types and styles of the discourse, several types of decision trees should be constructed for different literal types; 5. In the monologue discourse, the most prominent accent is located on the Focus word or in the scope of the Focus; there are some kinds of rules on accent assignment in broad Focus; it is necessary to analyze and classify focus structure for the research of relations between accent and Focus.

不同学习策略对改变学生物理要领错误的影响

In the field of misconceptions research, previous research was focused mainly on the effect of naive concepts on the learning of scientific concept. In this study, from the viewpoint of declarative and procedural knowledge, conceptual errors on Newtonian mechanics were studied comparatively between high-performance and low-performance students. Furthermore, the effects of self-explain learning strategies and reflective learning on the change of subjects' conceptual errors were explored. The result of experiments indicated: 1. There was significant difference in the number of conceptual errors of declarative and procedural knowledge between high-performance students and low-performance students. And Low-performance students made more conceptual errors of procedural knowledge than that of declarative knowledge. For high-performance students, there was no distinct difference between these two kinds of errors. 2. In the distribution of conceptual errors, most errors of declarative knowledge were mainly focused on the understanding of concepts of friction and acceleration. The errors of procedure knowledge most errors concentrated on the judgment of vector direction and the conceptual understanding. 3. Compared with high-performance students, the representation of conceptual declarative knowledge of low-performance students is less complex, more concrete and context bound. 4. The comparative analysis of problem-solving strategies showed: high-performance students preferred to apply analytic strategy, solving problems based on physical concepts and principles; low-performance students preferred to use context strategy, solving problem according to the literal meaning of problems, subjective and groundless presumption and wrong concepts and principles. 5. Self-explain strategies can help students correct their conceptual errors effectively. Reflective learning could help students to correct the concept errors in some degree, but the distinct effect was not observed.