Two Isomers of C60F48: Computed Inter-isomeric Equilibrium

C₆₀F₄₈ has been known to exist in two isomeric forms of D₃ and S₆ symmetries. However, the quantum-chemical calculations have not agreed on their stability order though a near-isoenergetic picture is otherwise always encountered. In order to clarify the situation, the entropy effects are evaluated for synthetic temperatures of about 500K. The entropy evaluations suggest that the D₃ isomer should be more stable in the potential energy by 2.05-2.55 kcal/mol (to which term the ab initio data are closer than the semiempirical ones).     

Data fitting with a spline using a real-coded genetic algorithm

To obtain a good approximation for data fitting with a spline, frequently we have to deal with knots as variables. The problem to be solved then becomes a continuous nonlinear and multivariate optimization problem with many local optima. Therefore, it is difficult to obtain the global optimum. In this paper, we propose a method for solving this problem by using a real-coded genetic algorithm. Our method can treat not only data with a smooth underlying function, but also data with an underlying function having discontinuous points and/or cusps. We search for the best model among candidate models by using the Bayes Information Criterion (BIC). With this, we can appropriately determine the number and locations of knots automatically and simultaneously. Five examples of data fitting are given to show the performance of our method.     

Numerical Modeling of Silicon Photodiodes for High-Accuracy Applications Part I. Simulation Programs

The suitability of the semiconductor-device modeling program PC-1D for high-accuracy simulation of silicon photodiodes is discussed. A set of user interface programs optimized to support high-accuracy batch-mode operation of PC-1D for modeling the internal quantum efficiency of photodiodes is also described. The optimization includes correction for the dark current under reverse- and forward-bias conditions before calculating the quantum efficiency, and easy access to the highest numerical accuracy available from PC-1D, neither of which is conveniently available with PC-1D’s standard user interface.     

A formal model of asynchronous communication and its use in mechanically verifying a biphase mark protocol

We present a formal model of asynchronous communication between two digital hardware devices. The model takes the form of a function in the Boyer-Moore logic. The function transforms the signal stream generated by one processor into that consumed by an independently clocked processor, given the phases and rates of the two clocks and the communications delay. The model can be used quantitatively to derive concrete performance bounds on communications at ISO protocol level 1 (physical level). We use the model to show that an 18-bit/cell biphase mark protocol reliably sends messages of arbitrary length between two processors provided the ratio of the clock rates is within 5% of unity.     

几何造型的自由畸变方法

几何造型是计算机图形学的重要研究内容，ＣＡＤ／ＣＡＭ的核心技术，现行的许多造型系统仅限于造型二次曲面及旋转曲面，没有自由曲面造型能力，本文研究的自由畸变为法，很容易扩展这些系统的自由曲面造型功能，该方法已成功地用于扩展ＭＯＶＩＥ．ＢＹＵ系统的自由曲面造型功能。     

Test Generation for Crosstalk-Induced Faults: Framework and Computational Results

Due to technology scaling and increasing clock frequency, problems due to noise effects lead to an increase in design/debugging efforts and a decrease in circuit performance. This paper addresses the problem of efficiently and accurately generating two-vector tests for crosstalk induced effects, such as pulses, signal speedup and slowdown, in digital combinational circuits. These noise effects can propagate through a circuit and create a logic error in a latch or at a primary output. We have developed a mixed-signal test generator, called XGEN, that incorporates classical static values as well as dynamic signals such as transitions and pulses, and timing information such as signal arrival times, rise/fall times, and gate delay. In this paper we first discuss the general framework of the test generation algorithm followed by computational results. Comparison of results with SPICE simulations confirms the accuracy of this approach.     

FEATURE SOLID MODELING TOOL SYSTEM:FSMTS

In conformity with the principle of Design for Manufacture,feature-based design strate-(?)es have been developed.As the“feature”is relevant to the“macro process plan”and“macro NCprograms”,obviously,“feature”is beyond the power of conventional solid modellers.Neverthe-less,substantial breakthrough has not been made in the solid modeling field,except“feature at-taching”or“feature recognizing”methods have been taken on.In this paper,the theory,concepts,system architecture,and algorithm principles of solid modeling tool system have beenrepresented.The practice of Feature Solid Modeling Tool System (FSMTS) developed atHuazhong University has proved that the tool may be a new foundation of Feature-Based Design.     

Automated model generation for performance engineering of building automation networks

Large technical systems need to be designed both reliable and efficient. Specialized design tools offer therefore a simplified, abstract design and extend details autonomously in the background. Analytic and simulation based models could improve the quality by testing and dimensioning the design before implementation, but setting up the necessary models is time-consuming and expensive. Therefore many developers ask for analysis tools which are able to create their models from the available information in the design tools. This paper presents such an automated modeling approach basing on an existing design database at the example of a network analysis for building automation fieldbuses. The process of automated modeling is unfolded, and the potentials and limitations are discussed.     

Predictive modeling of mercury speciation in combustion flue gases using GMDH-based abductive networks

Modeling mercury speciation is an important requirement for estimating harmful emissions from coal-fired power plants and developing strategies to reduce them. First-principle models based on chemical, kinetic, and thermodynamic aspects exist, but these are complex and difficult to develop. The use of modern data-based machine learning techniques has been recently introduced, including neural networks. Here we propose an alternative approach using abductive networks based on the group method of data handling (GMDH) algorithm, with the advantages of simplified and more automated model synthesis, automatic selection of significant inputs, and more transparent input–output model relationships. Models were developed for predicting three types of mercury speciation (elemental, oxidized, and particulate) using a small dataset containing six inputs parameters on the composition of the coal used and boiler operating conditions. Prediction performance compares favourably with neural network models developed using the same dataset, with correlation coefficients as high as 0.97 for training data. Network committees (ensembles) are proposed as a means of improving prediction accuracy, and suggestions are made for future work to further improve performance.