On mind &; Turing’s machines

Turing’s notion of human computability is exactly right not only for obtaining a negative solution of Hilbert’s Entscheidungsproblem that is conclusive, but also for achieving a precise characterization of formal systems that is needed for the general formulation of the incompleteness theorems. The broad intellectual context reaches back to Leibniz and requires a focus on mechanical procedures; these procedures are to be carried out by human computers without invoking higher cognitive capacities. The question whether there are strictly broader notions of effectiveness has of course been asked for both cognitive and physical processes. I address this question not in any general way, but rather by focusing on aspects of mathematical reasoning that transcend mechanical procedures.Section 1 discusses Gödel’s perspective on mechanical computability as articulated in his [193?], where he drew a dramatic conclusion from the undecidability of certain Diophantine propositions, namely, that mathematicians cannot be replaced by machines. That theme is taken up in the Gibbs Lecture of 1951; Gödel argues there in greater detail that the human mind infinitely surpasses the powers of any finite machine. An analysis of the argument is presented in Section 2 under the heading Beyond calculation. Section 3 is entitled Beyond discipline and gives Turing’s view of intelligent machinery; it is devoted to the seemingly sharp conflict between Gödel’s and Turing’s views on mind. Their deeper disagreement really concerns the nature of machines, and I’ll end with some brief remarks on (supra-) mechanical devices in Section 4.     

基于多目标遗传算法的仿人机器人中枢神经运动控制器的设计

针对多自由度仿人机器人的运动控制,从神经生理学和机器人学的角度研究了基于中 枢模式生成器（CPGs）的仿人运动控制策略．提出了一种将多目标遗传算法应用于(CPGs)参 数优化的方法．首先构造用于仿人机器人运动控制的(CPGs)的结构,其参数通过遗传算法按 相应的评价函数得到优化．     

服装压感舒适性评价方法

服装压感舒适性评价主要有客观评价法、主观评价法和主客观综合评价法．客观评价法多是通过服装压的客观测量来体现的,服装压的客观测量分为间接测量与直接测量,直接测量因其测试方法简单被广泛应用．主观评价法由于能解决许多客观测量不能解决的问题,能比较公正地反映受试者的着装感受,也是服装压感舒适性评价的一种重要方法．但由于服装压感舒适性评价的复杂性,单独使用任何一种方法均不全面,只有将两种方法结合起来,采用主客观综合评价法才能更加完善地进行评价．同时,也指出了服装压感舒适性评价法的发展趋势及注意事项．     

Multi‐objective risk assessment of freshwater inflow on ecosystem sustainability in San Antonio bay,Texas

Abstract:

San Antonio Bay is located on the coast of Texas between Galveston Bay and Corpus Christi Bay and is the primary bay in the Guadalupe Estuary. Three rivers feed San Antonio Bay from two river basins, including the Blanco and Guadalupe Rivers in the Guadalupe River Basin and the San Antonio River in the San Antonio River Basin. The Canyon Reservoir regulates the flow of fresh water in the middle and lower reaches of the Guadalupe River. These inflows are a primary regulator of salinity and, thus, the productivity of commercially important estuarine species. Increasing demand for water has prompted plans for an increased diversion of 49.3 million m³ (40,000 acre‐feet) from the reservoir. An additional amount of 61.6 million m³ (50,000 acre‐feet) from the mouth of the river is to be pumped back to San Antonio to relieve over‐pumping of the Edwards Aquifer. Because the Guadalupe River Basin contributes 58.1 percent of the freshwater inflow to the estuary, it is not known what the impact of these actions will have on the ecological integrity of the San Antonio Bay. Water resource management in the San Antonio Basin consists of decision making under risk and uncertainty related to randomness in the critical parameters such as the salinity in the bay, biological productivity, and total flow into the bay. The aim of this study is to investigate the trade‐offs between the competing objectives of maximizing biological productivity in the bay and minimizing flow using Stochastic Compromise Programming (SCP). The SCP model solves a multi‐objective function subject to constraints that must be maintained at three different prescribed levels of probability providing a global set of solutions for the water resource management problem under input uncertainty. The SCP model provides information on the trade‐offs among the objective function value, tolerance values of the constraint at the prescribed levels of probability, which could be valuable to policy makers in risk assessment. Solutions were found using three distance functions. Model outputs may suggest the minimum amount of freshwater needed to maximize biological productivity of the bay at specified risk level for assessing the impact of upcoming diversion program. Results indicate that current flows in the Guadalupe River are of sufficient volume to satisfy harvest requirements.     

Combined forecasts in portfolio optimization: A generalized approach

In this paper a general mathematical model for portfolio selection problem is proposed. By considering a forecasting performance according to the distributional properties of residuals, we formulate an extended mean-variance-skewness model with 11 objective functions. Returns and return errors for each asset obtained using different forecasting techniques, are combined in optimal proportions so as to minimize the mean absolute forecast error. These proportions are then used in constructing six criteria related to the mean, variance and skewness of return forecasts of assets in the future and forecasting errors of returns of assets in the past. The obtained multi-objective model is scalarized by using the conic scalarization method which guarantees to find all non-dominated solutions by considering investor preferences in non-convex multi-objective problems. The obtained scalar problem is solved by utilizing F-MSG algorithm. The performance of the proposed approach is tested on a real case problem generated on the data derived from Istanbul Stock Exchange. The comparison is conducted with respect to different levels of investor preferences over return, variance, and skewness and obtained results are summarized.     

Computation of probabilistic linear programming problems involving normal and log-normal random variables with a joint constraint

A method for solving single- and multi-objective probabilistic linear programming problems with a joint constraint is presented. It is assumed that the parameters in the probabilistic linear programming problems are random variables, and the probabilistic problem is converted to an equivalent deterministic mathematical programming problem. In this paper the parameters are generally considered as normal and log-normal random variables. A non-linear programming method is used to solve the single-objective deterministic problem, and a fuzzy programming method is used to solve the multi-objective deterministic problem. Finally, a numerical example is presented to illustrate the methodology.     

考虑避碰约束的编队卫星入网路径规划

提出了一种新的考虑避碰约束的编队卫星入网路径规划策略。首先通过常规编队卫星入网的多脉冲线性规划方法,得到一组卫星入网的脉冲序列,以此预测轨道机动过程中各星之间的最小距离,当最小距离小于安全距离时,将最小距离前后脉冲施加时刻的相对位置作为约束条件,重新规划卫星入网轨迹,迭代进行直到满足避碰要求。仿真结果表明,该方法由于减少了路径规划过程中约束条件的个数,能够快速地规划出考虑避碰约束时的编队卫星入网轨迹,且有效节省燃料消耗。     

基于DNA编码的多重约束目标的智能组合优化

在组卷策略中,多重约束目标的智能组合优化问题一直是人们研究的热点．大多数的优化算法都是基于传统的遗传算法,这些算法的适应度不高,并且交叉算子和变异算子对适应度的影响很大．针对这些缺陷,本文提出了一种新的优化算法DNA_YH算法,该算法将DNA编码引入到多重约束目标的组合优化问题中,并完成了DNA编码、初始化种群、个体适应度计算和遗传操作的优化过程．经过实验证明DNA_YH算法的最优适应度高于其他相关算法,并且交叉算子和变异算子对适应度的影响都很小,得到了较好的优化效果．     

2002—2011年江苏省农业现代化发展水平评价

根据《江苏统计年鉴(2002—2012)》的统计数据,运用熵值法和层次分析法相结合的主客观联合赋权法,对"十五"、"十一五"江苏省农业现代化水平进行评价.结果表明:江苏省农业现代化发展状态良好,研究时段农业现代化水平指数稳步上升,且上升势头强劲,2011年已进入完全成熟阶段,但是可持续发展状况起伏较大,尚不够稳定.     

高校新区建设项目后评估研究

阐述了新校区建设项目后评估的内容,对目前新校区建设项目存在的项目建设目标的完成情况不够理想、学校负债严重、对社会和环境的影响的评估不够全面和师生满意度不高等问题进行了分析和探讨,提出充分共享资源、多渠道筹措资金和加强节约型校园建设的后评估建议。