基于GIS的大气污染扩散模拟的设计与实现

对于城市空气环境问题的管理和决策,大气污染扩散模拟系统提供了科学的依据.论述了一个基于GIS,采用Visual Basic.NET、组件MapObjects和组件Surfer8.0相结合的大气污染扩散模拟系统的设计与实现,同时介绍了大气污染扩散的模拟过程、系统的主要功能、MapObjects与Surfer8.0两个组件的部分属性和方法,并给出了实现系统的关键代码.     

傅立叶变换的收敛性与解析形式探讨

傅立叶变换自提出之日,便受到以严格著称的数学家们诟病。傅立叶变换之所以对近代工程和自然科学产生了深刻的影响,在于傅立叶变换符合实际情况,给工程应用带来了极大的便利。通过分析阶跃信号的傅立叶变换的存在性及数学推导过程,从数学角度和工程角度探讨信号傅立叶变换存在的条件。     

Robust joint modeling of mean and dispersion through trimming

The Maximum Likelihood Estimator (MLE) and Extended Quasi-Likelihood (EQL) estimator have commonly been used to estimate the unknown parameters within the joint modeling of mean and dispersion framework. However, these estimators can be very sensitive to outliers in the data. In order to overcome this disadvantage, the usage of the maximum Trimmed Likelihood Estimator (TLE) and the maximum Extended Trimmed Quasi-Likelihood (ETQL) estimator is recommended to estimate the unknown parameters in a robust way. The superiority of these approaches in comparison with the MLE and EQL estimator is illustrated by an example and a simulation study. As a prominent measure of robustness, the finite sample Breakdown Point (BDP) of these estimators is characterized in this setting.     

Decision process modeling across internet and real world by double helical model of chance discovery

A case is presented for the double helical processing of chance discovery — human and an automated data mining system co-work, each progressing spirally toward the creative reconstruction of ideas. Especially, the discovery of what we call chances, significant novel events, is realized in this process. The example shown here is an application to questionnaire analysis for understanding new behaviors of Internet users. Internet users are born and bred with face-to-face human relations in the real world, but their interactions with WWW are distilling new value-criteria, keeping personal real-world senses of rationality, empathy, ethics, etc. In our method for aiding the discovery based on the double-helix model, the in-depth interaction of the Internet, the fundamental (i.e., common both in the Internet and in the real world) characters and the behaviors of people are discussed with revealing unnoticed value-criteria. Yukio Ohsawa, Ph.D.: BS, U. Tokyo, 1990, MS, 1992, DS, 1995. Research associate Osaka U. (1995). Associate prof. Univ. of Tsukuba (1999-) and also researcher of Japan Science and Technology Corp (2000-). He has been working for the program com. of the Workshop on Multiagent and Cooperative Computation, Annual Conf. Japanese Soc. Artificial Intelligence, International Conf. MultiAgent Systems, Discovery Science, Pacific Asia Knowledge Discovery and Data Mining, International Conference on Web Intelligence, etc. He chaired the First International Workshop of Japanese Soc. on Artificial Intelligence, Chance Discovery International Workshop Series and the Fall Symposium on Chance Discovery from AAAI. Guest editor of Special Issues on Chance Discovery for the Journal of Contingencies and Crisis Management, Journal of Japan Society for Fuzzy Theory and intelligent informatics, regular member of editorial board for Japanese Society of Artificial Intelligence. Currently he is authoring book “Chance Discovery” from Springer Verlag, “Knowledge Managament” from Ohmsha etc. Yumiko Nara, Ph.D.: She graduated from Nara Women’s University in 1987 and obtained her Master and Ph.D. degrees from Nara Women’s University respectively in 1993 and 1996. From 1987 through 1990 she worked for Sumitomo Bank. She is at Osaka Kyoiku University as lecturer (1997–2001) and as associate professor (2002-). She serves as a member of The Japan Sociological Society, The Japan Association for Social and Economic Systems Studies, The Japan Society of Home Economics, and The Japan Risk Management Society. She is an editorial committee member of the journal of Social and Economic Systems Studies (2001-), and a council member of The Japan Risk Management Society (1997-). In 1997, she received research awards from The Japan Society of Home Economics and The Japan Risk Management Society for studies on risk management.     

Computational modeling and comparison of three co-laminar microfluidic mixing techniques

This study compares three common microfluidic mixing techniques: electroosmosis with patterned zeta potential, hydrodynamic focusing and physical constrictions. All three techniques provide a higher degree of mixing than a comparable channel without a mixer, but at the cost of higher power requirements. Of the three techniques, the electroosmotic mixer requires the greatest amount of power to produce a high degree of mixing, unless the channels are much smaller than those typical for microfluidic devices. The power requirement of the physical constriction mixer may be lowered by using multiple constrictions, with only a small loss in mixing effectiveness. The physical constriction mixer is recommended, since it has power requirements similar to the hydrodynamic focusing mixer but only requires the use of a single pump. However, if the mixing liquids contain particulates, a hydrodynamic focusing mixer may be preferred, because the physical constriction mixer may clog, depending on the particulate size.     

Theory and techniques of data mining in CGF behavior modeling

For the large quantity of data,rules and models generated in the course of computer generated forces (CGFs) behavior modeling,the common analytical methods are statistical methods based on the tactical rules,tactical doctrine and empirical knowledge.However,from the viewpoint of data mining,we can find many of these analytical methods are also each-and-every different data mining methods.In this paper,we survey the data mining theory and techniques that have appeared in the course of CGF behavior modeling f...     

Examination of thermo-physical and material property interactions in cereal foams by means of Boltzmann modeling techniques

Cereal foam is a high complex material undergoing several temperature-dependent processes under thermal treatment, such as phase transitions, biochemical reactions and structural changes. Simultaneous heat and mass transfer plays an important role to investigate optimization studies in cereal-based foams. In porous media such as cereal foams, thermal conduction is of minor impact on the overall heat transfer, since the major part of heat is transferred through the gas phase filled with water vapor. This becomes evident comparing the thermal diffusivities of solid and gaseous components of the foam, where the difference is in the order of five magnitudes. The objective of this study is to model the coupled heat and mass diffusion processes in cereal-based foam under thermal treatment by means of Lattice Boltzmann methods. The proposed model is then used to perform parameter variation studies, showing the impact of material property changes offering the possibility on optimizing heat transfer through the foam.     

Using data mining techniques for multi-diseases prediction modeling of hypertension and hyperlipidemia by common risk factors

Many previous studies have employed predictive models for a specific disease, but fail to note that humans often suffer from not only one disease, but associated diseases as well. Because these associated multiple diseases might have reciprocal effects, and abnormalities in physiological indicators can indicate multiple associated diseases, common risk factors can be used to predict the multiple associated diseases. This approach provides a more effective and comprehensive forecasting mechanism for preventive medicine. This paper proposes a two-phase analysis procedure to simultaneously predict hypertension and hyperlipidemia. Firstly, we used six data mining approaches to select the individual risk factors of these two diseases, and then determined the common risk factors using the voting principle. Next, we used the Multivariate Adaptive Regression Splines (MARS) method to construct a multiple predictive model for hypertension and hyperlipidemia. This study uses data from a physical examination center database in Taiwan that includes 2048 subjects. The proposed analysis procedure shows that the common risk factors of hypertension and hyperlipidemia are Systolic Blood Pressure (SBP), Triglycerides, Uric Acid (UA), Glutamate Pyruvate Transaminase (GPT), and gender. The proposed multi-diseases predictor method has a classification accuracy rate of 93.07%. The results of this paper provide an effective and appropriate methodology for simultaneously predicting hypertension and hyperlipidemia.     

Forecasting of monthly river flow with autoregressive modeling and data-driven techniques

This study was conducted by using autoregressive (AR) modeling and data-driven techniques which include gene expression programming (GEP), radial basis function network and feed-forward neural networks, and adaptive neural-based fuzzy inference system (ANFIS) techniques to forecast monthly mean flow for K?z?l?rmak River in Turkey. The lagged monthly river flow measurements from 1955 to 1995 were taken into consideration for development of the models. The correlation coefficient and root-mean-square error performance criteria were used for evaluating the accuracy of the developed models. When the results of developed models were compared with flow measurements using these criteria, it was shown that the AR(2) model gave the best performance among all developed models and the GEP and ANFIS models had good performance in data-driven techniques.     

Single event upset induced by single event double transient and its well-structure dependency in 65-nm bulk CMOS technology

Single event upset (SEU) is one of the most important origins of soft errors in aerospace applications.As technology scales down persistently, charge sharing is playing a more and more significant effect on SEU of flip-flop. Charge sharing can often bring about multi-node charge collection in storage nodes and non-storage nodes in a flip-flop. In this paper, multi-node charge collection in flip-flop data input and flip-flop clock signal is investigated by 3D TCAD mixed-mode simulations, and the simulate results indicate that single event double transient (SEDT) in flip-flop data input and flip-flop clock signal can also cause a SEU in flip-flop. This novel mechanism is called the SEDT-induced SEU, and it is also verified by heavy-ion experiment in 65 nm twin-well process. The simulation results also indicate that this mechanism is closely related with the well-structure,and the triple-well structure is more effective to increase the SEU threshold of this mechanism than twin-well structure.     

Application of ANN and RSM techniques for modeling electrospinning process of polycaprolactone

Neural Computing and Applications - Due to increasing application of nanofibers in many research fields, comprehensive knowledge of the electrospinning process as the most popular method of fiber...     

Specific applications of different modeling techniques for microwave package and structures design

Different simulation methods for analyzing microwave interconnects are presented. Dynamic and static as well as two-dimensional (2D) or three-dimensional (3D) methods are investigated, such as the method of moments (MoM), the SDM, and TLM method, in their specific domains of predilection. Results are finally compared together with those obtained from a commercial software product based on the FEM method. © 1995 John Wiley & Sons, Inc.     

Reliability analysis of the complex mode indicator function and Hilbert Transform techniques for operational modal analysis

This study presents application of the CMIF and the Hilbert Transform techniques onto simulated response data obtained using a numerical model of a typical school building from Turkey. White noise is added to the data in order to achieve a noise to signal ratio of 5%. 100 Monte Carlo analysis sequences are carried out and the modal parameters (the frequencies, the mode shapes and the damping ratios) are identified at each Monte Carlo run for both techniques. The results are compared with the identifications obtained from the simulated data using stochastic subspace based system identification technique. The overall results of the study show that the mode shapes are clearly identified the best by using the CMIF technique. The damping ratios are estimated better by using the stochastic subspace based system identification technique whereas the frequencies are best determined by the CMIF. The results also show that both the CMIF and the Hilbert Transform techniques are sensitive to the type of window used as well as the averaging and the decimation process. It is apparent that the CMIF technique is as robust as the frequently used stochastic subspace based system identification technique and can be confidently used for modal parameter estimation of stiff low to mid rise reinforced concrete structures.     

Comparison of homogeneous and heterogeneous modeling of transient scattering from dispersive media directly in the time domain

Accurate modeling of pulse propagation and scattering in dispersive medium is a problem in many disciplines (i.e. electromagnetics and acoustics). The inclusion of an additional term in the wave equation (the derivative of the convolution between the causal time-domain propagation factor and the acoustic pressure) that takes into account the dispersive nature of the medium is utilized to make these problems tractable. The resulting modified wave equation (either homogeneous or heterogeneous) is applicable to either linear or non-linear propagation. For the case of an acoustic wave propagating in a two-dimensional heterogeneous dispersive medium, a finite-difference time-domain (FDTD) representation of the modified linear wave equation can been used to solve for the acoustic pressure. The method is applied to the case of scattering from and propagating through a 2D infinitely long cylinder with real world material properties. It is found that ignoring the heterogeneity in the medium can lead to significant error in the propagated/scattered field.     

The commercial use of segmentation and predictive modeling techniques for database marketing in the Netherlands

Although the application of segmentation and predictive modeling is an important topic in the database marketing (DBM) literature, no study has yet investigated the extent of adoption of these techniques. We present the results of a Dutch survey involving 228 database marketing companies. We find that managers tend to rely on intuition and on the long-standing methods RFM and cross-tabulation. Our results indicate that the application of segmentation and response modeling is positively related to company and database size, frequency of customer contact, and the use of a direct channel of distribution. The respondents indicate that future research should focus on models applicable for Internet marketing, long-term effects of direct marketing, irritation from direct marketing offers, and segmentation and predictive modeling techniques.     

利用小波变换定位与辨识短时电压变动

文章研究了小波变换检测短时电压变动问题,并利用小波变换对这几种典型的暂态扰动进行了MATLAB仿真.仿真结果表明,小波变换不仅能够有效地检测出电压变动发生的起止点从而确定扰动发生的持续时长,还能够准确地辨识电压变动的类型,为暂态电能质量问题的检测与解决提供了依据.