理解生成探幽

哲学理解的生成,是由生成方法、生成路径和生成判据三个步骤来完成的。具体地说:在理解生成的方法中,并存着演绎法、归纳法、目的法三种方法,而目的法是生成理解的根本方法,因为生成理解就在于揭示目的;在理解生成的路径中,如果采用目的方法,则要解决理解的层面性和客观性问题,因为层面性和客观性牵涉到生成某一具体理解的最佳途径;在理解生成的判据中,某一具体理解的生成,其判据就是信念的确立,因为正是信念才构成个人与现实之间的价值关系。     

低碳视角下农业集约化、绿色化与资源再生化 的实现机制研究

在实现"碳达峰碳中和"目标的重要历史机遇期,推动实现农业集约化、绿色化和资源再生化,构建资源节约型、绿色低碳型、生态循环型的农业发展模式,对于农业可持续发展具有重要意义。以2000-2018年我国31个省份为研究对象,通过面板向量自回归模型(PVAR),刻画资源消耗、农业产出、农业碳排放之间的动态传导机制。结果表明:(1)东部农业"碳达峰"节点出现较早,东北、西部相对较晚;2018年农业碳排放居前三的省份为湖南、黑龙江、河南,居后三的为北京、天津、上海;(2)资源消耗和农业产出之间呈现"低投入高产出"的农业集约化生产模式,但影响力微弱;农业产出和农业碳排放之间"高产出高排放"的情形长期面临农业绿色化的严峻考验;农业碳排放与资源消耗之间呈现"低排放低投入"的资源再生化现象,影响力短期微弱长期较强;(3)推动实现农业集约化、绿色化、资源再生化的关键在于探索降低农业碳排放的多重路径。因此,应强化农业集约化生产,充分发展资源再生化模式,探索形成农业绿色化格局新路径,以此来加快实现碳减排目标,推动农业可持续发展。     

Sampling from spatial databases

This paper deals with techniques for obtaining random point samples from spatial databases. We seek random points from a continuous domain (usually ²) which satisfy a spatial predicate that is represented in the database as a collection of polygons. Several applications of spatial sampling (e.g. environmental monitoring, agronomy, forestry, etc) are described. Sampling problems are characterized in terms of two key parameters: coverage (selectivity), and expected stabbing number (overlap). We discuss two fundamental approaches to sampling with spatial predicates, depending on whether we sample first or evaluate the predicate first. The approaches are described in the context of both quadtrees and R-trees, detailing the sample first, acceptance/rejection tree, and partial area tree algorithms. A sequential algorithm, the one-pass spatial reservoir algorithm is also described. The relative performance of the various sampling algorithms is compared and choice of preferred algorithms is suggested. We conclude with a short discussion of possible extensions.     

A Population Approach to Analysis of Variance Models

Several authors have contributed to what can now be considered a rather complete theory for analysis of variance in cases with orthogonal factors. By using this theory on an assumed basic reference population, the orthogonality concept gives a natural definition of independence between factors in the population. By looking upon the treated units in designed experiments as a formal sample from a future population about which we want to make inference, a natural parametrization of expectations and variances connected to such experiments arises. This approach seems to throw light upon several controversial questions in the theory of mixed models. Also, it gives a framework for discussing the choice of conditioning in models     

A Multivariate Model for Repeated Failure Time Measurements

A parametric multivariate failure time distribution is derived from a frailty-type model with a particular frailty distribution. It covers as special cases certain distributions which have been used for multivariate survival data in recent years. Some properties of the distribution are derived: its marginal and conditional distributions lie within the parametric family, and association between the component variates can be positive or, to a limited extent, negative. The simple closed form of the survivor function is useful for right-censored data, as occur commonly in survival analysis, and for calculating uniform residuals. Also featured is the distribution of ratios of paired failure times. The model is applied to data from the literature     

The Sandwich Generation: Dependency, Proximity, and Task Assistance Needs of Parents

This study was designed to determine the extent of sandwiched families and the impact of dependency and proximity to task assistance provided to parent(s). Data were collected in Idaho, Oregon, Utah, and Michigan from a random sample of 40–65-year-old respondents. Fifteen percent are sandwiched between needs of aging parents and financially dependent children. Respondents are much more likely to be providing assistance to mothers than fathers. Parents are most likely to live near, but not necessarily with, the respondent. Spouses and partners' parents, however, are likely to live farther away. Task assistance provided most often to aging parent(s) includes help with transportation and shopping; financial assistance was reported least often. Income of respondent and dependency and proximity of parents are significantly related to providing assistance to parents. This study offers a unique glimpse at the relationships between personal characteristics, dependency, proximity, and task assistance issues as they pertain to the sandwich generation.     

A hybrid ARIMA and support vector machines model in stock price forecasting

Traditionally, the autoregressive integrated moving average (ARIMA) model has been one of the most widely used linear models in time series forecasting. However, the ARIMA model cannot easily capture the nonlinear patterns. Support vector machines (SVMs), a novel neural network technique, have been successfully applied in solving nonlinear regression estimation problems. Therefore, this investigation proposes a hybrid methodology that exploits the unique strength of the ARIMA model and the SVMs model in forecasting stock prices problems. Real data sets of stock prices were used to examine the forecasting accuracy of the proposed model. The results of computational tests are very promising.     

测试实数编码遗传算法的困难度

分析了遗传算法困难度测试在遗传算法研究中的重要意义. 鉴于当前这方面的研究集 中于二进制编码遗传算法,对实数编码遗传算法的困难度测试进行了分析. 探讨了实数编码遗 传算法困难度分析的适应值与距离相关系数测试法与基于随机游走模型的相关函数测试法, 提出了最佳一阶函数逼近测试法,做了大量实验,并根据实证分析结果对三种方法进行了比较 与评价.     

Innovation through initiatives—a framework for building new capabilities in public sector research organizations

The accelerating pace of change in science and technology has resulted in new attention to the process of identifying and developing ideas that ultimately lead to new scientific capabilities and business opportunities for an organization. The need to refresh research programs and capabilities is as important in federally funded research institutions as it is for industry. This paper explores the critical success factors for new initiatives at a federal laboratory, and building on lessons learned through this study and in private industry, identifies a more systematic process that could potentially improve the effectiveness of these initiatives in achieving results.     

Spatial Data Usage,Spatial Thinking and Spatial Knowledge Generation: The Case of Planning Practitioners in Arequipa,Peru

Spatial thinking and spatial knowledge generation in decision-making are still not mature fields of study in planning research, despite these being crucial elements in addressing the issues of the twenty-first-century city. This article contributes to their understanding by exploring their interrelationships with spatial data usage. Through storylines, it analyzes the arguments that planning practitioners offer in support of infrastructure-led decisions in Arequipa (Peru), before and after spatial data usage. The article concludes that spatial data usage improve spatial thinking to different extents, yet suggests aligning spatial data generation and the inclusion of GIS-based spatial analyses with the spatial knowledge needed by routine planning practice.