A useful tool for statistical estimation: genetic algorithms

In this article, we introduce genetic algorithms (GAs) as a viable tool in estimating parameters in a wide array of statistical models. We performed simulation studies that compared the bias and variance of GAs with classical tools, namely, the steepest descent, Gauss–Newton, Levenberg–Marquardt and don't use derivative methods. In our simulation studies, we used the least squares criterion as the optimizing function. The performance of the GAs and classical methods were compared under the logistic regression model; non-linear Gaussian model and non-linear non-Gaussian model. We report that the GAs' performance is competitive to the classical methods under these three models.     

Communicating about the Risks and Benefits of Genetically Modified Foods: The Mediating Role of Trust

Recent research suggests that public attitudes toward emerging technologies are mainly driven by trust in the institutions promoting and regulating these technologies. Alternative views maintain that trust should be seen as a consequence rather than a cause of such attitudes. To test its actual role, direct as well as mediating effects of trust were tested in an attitude change experiment involving 1,405 consumers from Denmark, Germany, Italy, and the United Kingdom. After prior attitudes to genetic modification in food production had been assessed, participants received different information materials (either product-specific information or balanced/general information about genetic modification in food production) and were asked to evaluate different types of genetically modified foods (either beer or yoghurt). The information materials were attributed to different information sources (either an industry association, a consumer organization, or a government source). After completion, perceived risk and perceived benefit were assessed, and participants indicated their trust in the information sources to which the materials had been attributed. Direct and trust-mediated attitude change effects were estimated in a multi-sample structural equation model. The results showed that information provision had little effect on people's attitudes toward genetically modified foods, and that perceptions of information source characteristics contributed very little to attitude change. Furthermore, the type of information strategy adopted had almost no impact on postexperimental attitudes. The extent to which people trusted the information sources appeared to be driven by people's attitudes to genetically modified foods, rather than trust influencing the way that people reacted to the information. Trust was not driving risk perception-rather, attitudes were informing perceptions of the motivation of the source providing the information.     

Inductive,Evolutionary, and Neural Computing Techniques for Discrimination: A Comparative Study*

This paper provides a comparative study of machine learning techniques for two-group discrimination. Simulated data is used to examine how the different learning techniques perform with respect to certain data distribution characteristics. Both linear and nonlinear discrimination methods are considered. The data has been previously used in the comparative evaluation of a number of techniques and helps relate our findings across a range of discrimination techniques.     

Modeling Network Latency and Parallel Processing in Distributed Database Design

The design of responsive distributed database systems is a key concern for information systems managers. In high bandwidth networks latency and local processing are the most significant factors in query and update response time. Parallel processing can be used to minimize their effects, particularly if it is considered at design time. It is the judicious replication and placement of data within a network that enable parallelism to be effectively used. However, latency and parallel processing have largely been ignored in previous distributed database design approaches. We present a comprehensive approach to distributed database design that develops efficient combinations of data allocation and query processing strategies that take full advantage of parallelism. We use a genetic algorithm to enable the simultaneous optimization of data allocation and query processing strategies. We demonstrate that ignoring the effects of latency and parallelism at design time can result in the selection of unresponsive distributed database designs.     

Genetic counseling students’ experiences with mental illness during training: An exploratory study

Mental illness is a substantive issue for graduate students. We investigated experiences of mental illness during training among genetic counseling students, a subgroup of graduate students for which little data exists on this topic. Genetic counseling students and recent graduates (n?=?227) completed an online survey, from who 11 were selected to participate in semi-structured telephone interviews. Thematic analysis and member checking were employed to interpret the interviews. An overarching theme of importance to participants’ mental health during genetic counseling training was safety, with subthemes of: trust/confidentiality, stigma and fear of labeling, developing a unique professional identity, and ability to engage in self care strategies. Our data could help genetic counseling training programs develop strategies to support students’ mental health.     

Integrating Social Network Effects in the Share‐Of‐Choice Problem

Accounting for social network effects in marketing strategies has become an important issue. Taking a step back, we seek to incorporate and analyze social network effects on new product development and then propose a model to engineer product diffusion over a social network. We build upon the share‐of‐choice (SOC) problem, which is a strategic combinatorial optimization problem used commonly as one of the methods to analyze conjoint analysis data by marketers in order to identify a product with largest market share, and show how to incorporate social network effects in the SOC problem. We construct a genetic algorithm to solve this computationally challenging (NP‐Hard) problem and show that ignoring social network effects in the design phase results in a significantly lower market share for a product. In this setting, we introduce the secondary operational problem of determining the least expensive way of influencing individuals and strengthening product diffusion over a social network. This secondary problem is of independent interest, as it addresses contagion models and the issue of intervening in diffusion over a social network, which are of significant interest in marketing and epidemiological settings.     

Optimizing minimum information pair-copula using genetic algorithm to select optimal basis functions

Constructing pair-copula using the minimum information approach is an appropriate and flexible way to survey the dependency structure between variables of interest. Minimum information pair-copula method approximates multivariate copula by applying some constraints between desired variables that are elicited from the data itself or experts’ judgment. In minimum information pair-copula, selecting basis constraints is a challenge. In this article, we apply genetic algorithms as a heuristic way to select basis constraints to optimize approximated pair-copula. The results gained show that our method optimizes model selection criteria and lead to better pair-copula approximation. Finally, we apply our proposed method to approximate pair-copula density in real dataset.     

煤炭产业国际竞争力的遗传—投影寻踪评价

结合煤炭产业发展实际,提出了煤炭产业竞争力评价的指标体系。采用探索性数据分析方法——投影寻踪法,结合遗传算法,建立了遗传—投影寻踪综合评价模型。以全球11个主要产煤国作为研究样本,根据投影方向参数计算得出了各国的煤炭产业竞争力评价分类特征值和总体综合特征值,并对我国煤炭产业竞争力进行了分析,对于认清我国煤炭竞争力与国外主要产煤国之间的差距与不足,进而提升我国煤炭产业的国际竞争力具有重要的现实意义。     

价格敏感型供应链网络规划模型及其混合遗传算法

针对价格敏感型供应链中,供应价格与批量之间通常具有非线性的函数关系,建立了采购、需求和物流服务环节均具有价格敏感性的多供应商、多配送中心和多零售商的供应链网络规划整数非线性规划INLP模型,设计解决此NP-hard问题的混合遗传算法,以启发式算法修复进化过程中出现的非法染色体,提高算法寻优速度,通过算例及与SAS/OR模块运行结果的比较,验证该算法具有很强的稳定性和高效性。     

葡萄糖耐受者空腹甘油三酯与重IGF-1启动子区的多态性研究

目的为了检测IGF-1基因启动子区的微卫星多态性中的等位基因与Ⅱ型糖尿病的相关性,并在葡萄糖耐受性人群中进行相关性状的定量分析。方法 IGF-1基因启动子多态性的研究通过对347名Ⅱ型糖尿病患者和109名葡萄糖耐受性者作为对照进行的研究。结果本研究没有发现启动子区缺少等位基因的与Ⅱ型糖尿病或是葡萄糖耐受性者中的葡萄糖耐受机制间存在相互关系(P =0．25)。在Ⅱ型葡萄糖耐受性糖尿病患者的空腹血清甘油三酯水平与野生型等位基因间存在相互关系(P=0．002)。结论本研究表明,IGF-1基因启动子多态性的野生型等位基因与葡萄糖耐受性人群空腹血清甘油三酯水平增加之间存在相互关系。