Energy Aware Design and Analysis for Synchronous and Asynchronous Circuits

Power dissipation has become a major concern for IC designers. Various low power design techniques have been developed for synchronous circuits. Asynchronous circuits, however. have gained more interests recently due to their benefits in lower noise, easy timing control, etc. But few publications on energy reduction techniques for asynchronous logic are available. Power awareness indicates the ability of the system power to scale with changing conditions and quality requirements. Scalability is an important figure-of-merit since it allows the end user to implement operational policy. just like the user of mobile multimedia equipment needs to select between better quality and longer battery operation time. This dissertation discusses power/energy optimization and performs analysis on both synchronous and asynchronous logic. The major contributions of this dissertation include: 1 ) A 2-Dimensional Pipeline Gating technique for synchronous pipelined circuits to improve their power awareness has been proposed. This technique gates the corresponding clock lines connected to registers in both vertical direction (the data flow direction) and horizontal direction (registers within each pipeline stage) based on current input precision. 2) Two energy reduction techniques, Signal Bypassing & Insertion and Zero Insertion. have been developed for NCL circuits. Both techniques use Nulls to replace redundant Data 0\u27s based on current input precision in order to reduce the switching activity while Signal Bypassing & Insertion is for non-pipelined NCI, circuits and Zero Insertion is for pipelined counterparts. A dynamic active-bit detection scheme is also developed as an expansion. 3) Two energy estimation techniques, Equivalent Inverter Modeling based on Input Mapping in transistor-level and Switching Activity Modeling in gate-level, have been proposed. The former one is for CMOS gates with feedbacks and the latter one is for NCL circuits

Theory of Charged Gels: Swelling, Elasticity, and Dynamics

The fundamental attributes of charged hydrogels containing predominantly water and controllable amounts of low molar mass electrolytes are of tremendous significance in biological context and applications in healthcare. However, a rigorous theoretical formulation of gel behavior continues to be a challenge due to the presence of multiple length and time scales in the system which operate simultaneously. Furthermore, chain connectivity, the electrostatic interaction, and the hydrodynamic interaction all lead to long-range interactions. In spite of these complications, considerable progress has been achieved over the past several decades in generating theories of variable complexity. The present review presents an analytically tractable theory by accounting for correlations emerging from topological, electrostatic, and hydrodynamic interactions. Closed-form formulas are derived for charged hydrogels to describe their swelling equilibrium, elastic moduli, and the relationship between microscopic properties such as gel diffusion and macroscopic properties such as elasticity. In addition, electrostatic coupling between charged moieties and their ion clouds, which significantly modifies the elastic diffusion coefficient of gels, and various scaling laws are presented. The theoretical formulas summarized here are useful to adequately capture the essentials of the physics of charged gels and to design new hydrogels with specified elastic and dynamical properties

The Exclusivity Principle Determines the Correlation Monogamy

Adopting the graph-theoretic approach to the correlation experiments, we analyze the origin of monogamy and prove that it can be recognised as a consequence of exclusivity principle(EP). We provide an operational criterion for monogamy: if the fractional packing number of the graph corresponding to the union of event sets of several physical experiments does not exceed the sum of independence numbers of each individual experiment graph, then these experiments are monogamous. As applications of this observation, several examples are provided, including the monogamy for experiments of Clauser-Horne-Shimony-Holt (CHSH) type, Klyachko-Can-Binicio\u{g}lu-Shumovsky (KCBS) type, and for the first time we give some monogamy relations of Swetlichny's genuine nonlocality. We also give the necessary and sufficient condition for several experiments to be monogamous: several experiments are monogamous if and only if the Lov\'asz number the union exclusive graph is less than or equal to the sum of independence numbers of each exclusive graph

Construction of Cultural Identity through Language Education of Junior-Senior High Schools in China during 1949-1997

The construction of cultural identity is a very complex issue and is affected by many factors, one of which is education. To make Chinese people acknowledge their own political civilization and cultural tradition, after the founding of the People's Republic of China in 1949, the Chinese education departments integrated Marxist education by using Chinese language courses in junior-senior high schools (JSHSs) as a medium. To achieve such integration, Chinese language courses must teach language knowledge while disseminating Marxism. A large number of works with Sinicized Marxism content was included in textbooks and interpreted according to relevant theories. Additionally, teachers of Chinese language courses must have high literacy regarding Marxist theory. Judging from the current social reality, the Chinese language courses in China’s JSHSs have prompted the adherence, identification and internalization of Marxism among JSHS students since the founding of the People’s Republic of China and have laid the foundation for the formation of a socio-political culture guided by Marxism in the general public

Radar-based Hail-producing Storm Detection Using Positive Unlabeled Classification

Machine learning methods have been widely used in many fields of weather forecasting. However, some severe weather, such as hailstorm, is difficult to be completely and accurately recorded. These inaccurate data sets will affect the performance of machine-learning-based forecasting models. In this paper, a weather-radar-based hail-producing storm detection method is proposed. This method utilizes the bagging class-weighted support vector machine to learn from partly labeled hail case data and the other unlabeled data, with features extracted from radar and sounding data. The real case data from three radars of North China are used for evaluation. Results suggest that the proposed method could improve both the forecast accuracy and the forecast lead time comparing with the commonly used radar parameter methods. Besides, the proposed method works better than the method with the supervised learning model in any situation, especially when the number of positive samples contaminated in the unlabeled set is large