Uncertainty and asymmetric information: An overview

This paper provides an overview of the literature on fisheries economics related to uncertainty and asymmetric information. It is argued that uncertainty is relevant in connection with present and future stock sizes and prices, while asymmetric information is important for cost functions, catches, catch per unit of effort, and effort. The literature on uncertainty and asymmetric information can be seen as providing the basis of an argument for using taxes in fisheries management. It is, therefore, surprising that over 55 countries regulate their fisheries with individual quotas, while taxes are not used at all.     

Evaluation of Inference Adequacy in Cumulative Logistic Regression Models: An Empirical Validation of ISWRidge Relationships

Internal solitary wave propagation over a submarine ridge results in energy dissipation, in which the hydrodynamic interaction between a wave and ridge affects marine environment. This study analyzes the effects of ridge height and potential energy during wave-ridge interaction with a binary and cumulative logistic regression model. In testing the Global Null Hypothesis, all values are p 〈0.001, with three statistical methods, such as Likelihood Ratio, Score, and Wald. While comparing with two kinds of models, tests values obtained by cumulative logistic regression models are better than those by binary logistic regression models. Although this study employed cumulative logistic regression model, three probability functions p^1, p^2 and p^3, are utilized for investigating the weighted influence of factors on wave reflection. Deviance and Pearson tests are applied to cheek the goodness-of-fit of the proposed model. The analytical results demonstrated that both ridge height （X1 ） and potential energy （X2 ） significantly impact （p 〈 0. 0001 ） the amplitude-based refleeted rate; the P-values for the deviance and Pearson are all 〉 0.05 （0.2839, 0.3438, respectively）. That is, the goodness-of-fit between ridge height （ X1 ） and potential energy （X2） can further predict parameters under the scenario of the best parsimonious model. Investigation of 6 predictive powers （ R2, Max-rescaled R^2, Sorners＇ D, Gamma, Tau-a, and c, respectively） indicate that these predictive estimates of the proposed model have better predictive ability than ridge height alone, and are very similar to the interaction of ridge height and potential energy. It can be concluded that the goodness-of-fit and prediction ability of the cumulative logistic regression model are better than that of the binary logistic regression model.     

Evaluation of Inference Adequacy in Cumulative Logistic Regression Models： An Empirical Validation of ISW-Ridge Relationships

Internal solitary wave propagation over a submarine ridge results in energy dissipation, in which the hydrodynamic interaction between a wave and ridge affects marine environment. This study analyzes the effects of ridge height and potential energy during wave-ridge interaction with a binary and cumulative logistic regression model. In testing the Global Null Hypothesis, all values are p<0.001, with three statistical methods, such as Likelihood Ratio, Score, and Wald. While comparing with two kinds of models, tests values obtained by cumulative logistic regression models are better than those by binary logistic regression models. Although this study employed cumulative logistic regression model, three probability functions p^1, p^2 and p^3, are utilized for investigating the weighted influence of factors on wave reflection. Deviance and Pearson tests are applied to check the goodness-of-fit of the proposed model. The analytical results demonstrated that both ridge height (X1) and potential energy (X2) significantly impact (p<0.0001) the amplitude-based reflected rate; the P-values for the deviance and Pearson are all >0.05 (0.2839, 0.3438, respectively). That is, the goodness-of-fit between ridge height (X1) and potential energy (X2) can further predict parameters under the scenario of the best parsimonious model.Investigation of 6 predictive powers (R2, Max-rescaled R2, Somers'D, Gamma, Tau-a, and c, respectively) indicate that these predictive estimates of the proposed model have better predictive ability than ridge height alone, and are very similar to the interaction of ridge height and potential energy. It can be concluded that the goodness-of-fit and prediction ability of the cumulative logistic regression model are better than that of the binary logistic regression model.     

国土资源数据管理初探

在分析国土资源数据及其管理特点的基础上,基于国土资源信息化和数据资源保护,将国土资源数据整体上分为资料数据、基础数据、业务数据、管理数据和元数据5类,提出了各类数据进行计算机管理的组织方法和采用的相关技术。     

基于C/S的矿产资源开发储量管理信息系统的研发

为实现矿产资源储量管理网络实时查询功能,在目前国土资源部金土工程的储量管理软件的基础上,开发出了"基于C/S的矿产资源开发储量管理信息系统".该系统采用了结构化的程序设计方法,操作系统平台采用了MS Windows系统,程序开发平台采用了Borland公司Delphi,数据库的查询语言采用标准SQL查询语言,主要实现了矿产资源开发和储量数据的综合查询和汇总功能.     

基于NS2的TCPW性能改进算法研究

TCP Westwood(TCPW)和Vegas都是基于测量的TCP New-Reno增强算法。TCPW针对ACK流直接估算可用带宽,在慢启动和线性递增部分依然采用传统Reno的盲目递增的机制,导致发送端较为频繁的重传。对这几种算法原理进行分析阐述,并提出1种改进方法,更精确的测量估计带宽,通过网络仿真工具NS2进行验证,明显去除TCP全局同步现象,增强网络性能。     

高频电力线信息传输的电机模型与仿真

研究在电机驱动系统中,电力线通信的建模问题,着重讨论在高频时电机输入阻抗的特性下,电机模型的建立.通过实验测量得到电机和电力线在频率100 kHz～40 MHz的输入阻抗特性曲线,并分析高频输入阻抗的谐振特点.在Matlab中,提出基于阻抗公式的分析法、最小均方值误差估计法以及最优化方法进行模型的参数识别,将得到的参数代入模型中可以得到电机的阻抗模型.电机模型的精确度可以通过仿真曲线和测量曲线的逼近程度看出,从结果看仿真得到的阻抗曲线跟实际测量的阻抗曲线走向基本一致.     

太湖蓝藻水华遥感动态监测预警信息系统

太湖蓝藻水华暴发对其周边地区的生态、经济和社会造成了严重影响,对蓝藻水华进行监测预警对于改善太湖水环境具有重要意义。本文在分析蓝藻水华遥感监测预警研究动态基础上,从信息系统构建角度,结合太湖蓝藻水华监测情况,对太湖蓝藻水华遥感监测预警流程进行系统性分析,提出建立太湖蓝藻水华遥感监测预警系统的总体框架,利用C#语言和IDL语言实现了该框架的软件架构,并且论述了实现该系统框架所采用的系统集成技术和软件模式技术。     

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3S技术支持下的小型遗址提取方法

针对仅利用地物光谱分析方法不能识别某些小型遗址的现状,提出基于地物空间关系知识,多源信息复合提取遗址的思路获取目标信息。以安徽省巢湖柘皋地区为例,利用SPOT-5卫星影像和地形图数据,综合运用3S技术进行小型遗址信息提取研究。经过和巢湖文管部门普查记录对比,证明了该方法有效性。该方法可缩小遗址探查范围,为考古普查工作节约大量时间、人力和物力。