成人高校人才培养模式解析

成人高校目前人才培养与劳动力市场的关系模式,基本上可以归结为“对口”与“适应”两种取向。但是,无论取向何种模式,透过毕业生就业以及就业后的发展实际看,都各有利弊。因此,成人高校在人才培养的取向上,不能单纯追求或固守其中的某一种模式,而应根据社会主义市场经济发展和劳动力市场的需求,建立起多元化、多层次的人才培养模式。     

冲激噪声环境中LFM信号的特征参数估计

SαS稳定分布是一类非常重要的非高斯随机分布,具有这类分布的噪声称为冲激噪声。在冲激噪声情况下,α阶以上的矩均不存在,导致基于二阶矩的高斯模型算法性能下降,甚至不能正常工作。该文提出了一种在冲激噪声环境下线性调频信号特征参数估计的算法,通过分析冲激噪声的具体特点,给出了修正的低阶矩模糊函数,并结合Radon变换估计了冲激噪声环境下LFM信号的参数。该算法既可应用于冲激噪声下,又可应用于高斯噪声环境,故具有较好的鲁棒性。最后用计算机仿真验证了该算法的有效性。     

商业银行个人金融服务的国际比较

目前,我国商业银行以代发工资、代收费等业务为突破口,已开发了近40个品种的个人金融服务业务。谁能提供更快捷、方便的金融服务,谁就会拥有更多的客户。进一步的对外开放,个人金融服务的巨大市场是中外银行竞争的焦点。个人金融服务市场从以往简单地通过银行储蓄存款获得利息并保障安全,已跳跃到支付结算、外汇买卖、临时透支、贷款融资、经营投资和综合理财等全方位、多层次的服务。这些对国内各家商业银行拓展个人金融服务提出了巨大的机遇和挑战。     

近代中国整合中西文化冲突的价值选择模式及现代启示

中国近代文化变迁的过程 ,在一定意义上表现为中西文化的冲突与整合的过程。为整合中西文化冲突 ,近代中国先后采取了文化传统主义、文化折中主义、文化虚无主义与文化综合创新等价值选择模式。近代文化整合的经验教训启示我们 ,在新时期文化建设问题上 ,必须正确处理文化的一元与多元、整体性与可分性、时代性与民族性的关系 ,坚持走综合创新之路     

On the Convergence of the Monte Carlo Maximum Likelihood Method for Latent Variable Models

While much used in practice, latent variable models raise challenging estimation problems due to the intractability of their likelihood. Monte Carlo maximum likelihood (MCML), as proposed by Geyer & Thompson (1992 ), is a simulation-based approach to maximum likelihood approximation applicable to general latent variable models. MCML can be described as an importance sampling method in which the likelihood ratio is approximated by Monte Carlo averages of importance ratios simulated from the complete data model corresponding to an arbitrary value of the unknown parameter. This paper studies the asymptotic (in the number of observations) performance of the MCML method in the case of latent variable models with independent observations. This is in contrast with previous works on the same topic which only considered conditional convergence to the maximum likelihood estimator, for a fixed set of observations. A first important result is that when is fixed, the MCML method can only be consistent if the number of simulations grows exponentially fast with the number of observations. If on the other hand, is obtained from a consistent sequence of estimates of the unknown parameter, then the requirements on the number of simulations are shown to be much weaker.     

Spatial variation in soil inorganic nitrogen across an arid urban ecosystem

We explored variations in inorganic soil nitrogen (N) concentrations across metropolitan Phoenix, Arizona, and the surrounding desert using a probability-based synoptic survey. Data were examined using spatial statistics on the entire region, as well as for the desert and urban sites separately. Concentrations of both NO₃-N and NH₄-N were markedly higher and more heterogeneous amongst urban compared to desert soils. Regional variation in soil NO₃-N concentration was best explained by latitude, land use history, population density, along with percent cover of impervious surfaces and lawn, whereas soil NH₄-N concentrations were related to only latitude and population density. Within the urban area, patterns in both soil NO₃-N and NH₄-N were best predicted by elevation, population density and type of irrigation in the surrounding neighborhood. Spatial autocorrelation of soil NO₃-N concentrations explained 49% of variation among desert sites but was absent between urban sites. We suggest that inorganic soil N concentrations are controlled by a number of ‘local’ or ‘neighborhood’ human-related drivers in the city, rather than factors related to an urban-rural gradient.     

城市森林效益与可持续性研究展望

正确认识城市森林的功能和效益 ,探索不同管理措施对城市森林效益的影响 ,对实现城市森林的可持续性具有十分重要的意义。本文综述了城市森林对生态环境和生态过程产生的影响及生态和社会效益 ;分析了城市森林可持续性的内涵及特征 ;对城市森林可持续性模式及评价标准、城市森林生态学等领域的研究成果和发展方向进行了归纳分析。在分析目前我国城市生态环境面临的问题的基础上 ,进一步提出城市森林是构建城市绿色空间的主体。建设可持续城市森林是实现城市经济和环境可持续发展的重要途径。     

浅谈网络环境下中学政治课研究性教学模式

基于网络环境下的研究性学习是目前研究性学习与信息技术的整合 ,尤其是与互联网技术整合的崭新课题 ,是当今国际教学改革的一个“亮点” ,探讨网络环境下中学政治课研究性教学模式的新课题。     

战略联盟--企业竞争新模式

战略联盟是企业之间为了一定目的 ,通过一定方式组成的网络式联合体。面对日趋激烈的市场竞争和外部环境的变化 ,企业之间既竞争又合作 ,战略联盟是一种全新的企业竞争模式     

Bayesian analysis of mixture modelling using the multivariate t distribution

A finite mixture model using the multivariate t distribution has been shown as a robust extension of normal mixtures. In this paper, we present a Bayesian approach for inference about parameters of t-mixture models. The specifications of prior distributions are weakly informative to avoid causing nonintegrable posterior distributions. We present two efficient EM-type algorithms for computing the joint posterior mode with the observed data and an incomplete future vector as the sample. Markov chain Monte Carlo sampling schemes are also developed to obtain the target posterior distribution of parameters. The advantages of Bayesian approach over the maximum likelihood method are demonstrated via a set of real data.