Modelling consumer choice through the random regret minimization model: An application in the food domain

In line with findings on post-purchase food-choice regret, one can expect that pre-purchase anticipated regret with respect to forgone (non-chosen) alternatives has an impact on consumer food choices, especially when the choice is considered to be important. The traditional Random Utility Maximization (RUM) models for discrete choices may not fully capture this impact. This study investigates the usefulness and potential in the food domain of a discrete choice model that follows the regret minimization principle, the Random Regret Minimization (RRM) model, as an alternative and complement to existing RUM models. The two models are applied to consumer stated choices of cheese in a choice experiment. The study also investigates whether and to what extent a number of personality traits determine whether particular consumers rather choose according to utility-maximization, or regret-minimization principles. Results show that at the aggregate level the two models have a similar goodness of fit to the data and prediction ability. Still, each of them shows better fit for particular subgroups of consumers, based on personality traits. Hence, the present study reveals a potential for the RRM model applications in the food domain, and adds to the empirical literature supporting previous findings on the RRM model found in other contexts. Further research is needed to explore in which situations and for which consumer segments the RRM model is the most useful model.     

HIGHER PLANT BIOMARKERS IN PALEOGENE CRUDE OILS FROM THE YUFUTSU OIL-AND GASFIELD AND OFFSHORE WILDCATS, JAPAN

Geochemical investigation of Paleogene oils from the onshore Yufutsu oil- and gasfield, southern Hokkaido, and from two nearby offshore wells, revealed the presence of numerous biomarkers of higher plant origin. Biomarkers in the oils belong to different groups of both angiosperm and gymnosperm origin; they include bicyclic sesquiterpanes, diterpanes, and triterpanes and their aromatized counterparts, which suggests a terrestrial origin for the oils. The oils were characterized as having a high wax content, a low content of organosulphur compounds, a high pristane/phytane ratio, and a low C₂₇/(C₂₇+C₂₉) sterane ratio.
Although the oils from on- and offshore Southern Hokkaido are similar in their geochemical composition, notable differences were observed in the biomarker signature of both saturate and aromatic fractions. The oils from the offshore wells appeared to have a greater abundance of higher plant biomarkers compared to those from the Yufutsu field, suggesting an enrichment in higher plant components. Differences in biomarker fingerprint could not be linked to the maturity effect, since the oils appeared to be of similar maturity levels, corresponding to the late stage of the oil window (0.9–1.2%, Rc). The differences in the biomarker signatures between the oils from the Yufutsu field and the offshore wells are likely to be due to facies variations in source organic matter, resulting from differences in the quantity and quality of land plant input.     

Model Selection for Unsupervised Learning of Visual Context

This study addresses the problem of choosing the most suitable probabilistic model selection criterion for unsupervised learning of visual context of a dynamic scene using mixture models. A rectified Bayesian Information Criterion (BICr) and a Completed Likelihood Akaike’s Information Criterion (CL-AIC) are formulated to estimate the optimal model order (complexity) for a given visual scene. Both criteria are designed to overcome poor model selection by existing popular criteria when the data sample size varies from small to large and the true mixture distribution kernel functions differ from the assumed ones. Extensive experiments on learning visual context for dynamic scene modelling are carried out to demonstrate the effectiveness of BICr and CL-AIC, compared to that of existing popular model selection criteria including BIC, AIC and Integrated Completed Likelihood (ICL). Our study suggests that for learning visual context using a mixture model, BICr is the most appropriate criterion given sparse data, while CL-AIC should be chosen given moderate or large data sample sizes.     

电路电磁兼容建模与仿真

提出了对暴露在任意外场中的传输线进行时频分析的新方法，这种方法非常稳定，它能够与任意的传输线模型和电路仿真方法兼容，并且使用这种方法得到的仿真值和实际值之间的差别小于1％。     

Note of clarification on Scholten and Sherman (2006): Erratum.

Reports an error in "Tradeoffs and Theory: The Double-Mediation Model" by Marc Scholten and Steven J. Sherman (Journal of Experimental Psychology: General, 2006 May, Vol 135[2], 237-261). This article was inadvertently printed with the incorrect title. The original title was "Tradeoffs and Conflict: The Double-Mediation Model." This title highlights the relation between tradeoffs and conflict as investigated by the authors and accounted for by their model. However, readers are asked to refer to the article by the title with which it was printed to facilitate its retrieval.. (The following abstract of the original article appeared in record 2006-06642-006.) Most theories of decision making suggest that, when options imply tradeoffs between their attributes, conflict increases as tradeoff size increases, because greater sacrifices are to be incurred in choosing one option instead of another. An alternative view is that conflict decreases as tradeoff size increases, because stronger arguments can be made for any decision. The authors propose a unified model, the double-mediation model, which combines the mediating effects of sacrifice and argumentation. Our model generally predicts an inverse U-shaped relation between tradeoff size and conflict. Results support this prediction. Also, when the decision situation increases the mediating effect of sacrifice relative to that of argumentation, the relation between tradeoff size and conflict changes in an upward direction; conversely, when the decision situation increases the mediating effect of argumentation relative to that of sacrifice, the relation changes in a downward direction. Results support these predictions as well. Commonalities and differences between our model and other formulations are discussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

水泥浆失水制约下套管与井眼间隙的研究

通过对水泥浆失水规律的室内试验分析以厦对注水泥顶替过程中水泥浆失水桥堵套管与井眼间隙问题的研究，建立了顶替过程中滤失层不发生水泥浆失水而桥堵环形空间的临界失水量计算模型，提出了调配水泥浆失水性能和确定合理套管井眼间隙的具体方法，对注水泥现场施工和井身结构设计具有一定的指导意义。     

HEGF中CO井筒流动及扩散规律研究

目前,高能气体压裂广泛的应用于低渗透油气田,可以有效清除近井地带由于钻井、射孔和各种措施造成的污染和堵塞,达到油气井增产、注水井增注的目的。但最近一些低渗透油气田却出现了频繁的CO气体中毒事件,给油田及员工带来巨大的损失。针对这一现象,运用现场数据以及物理模拟和数学模拟方法首次通过对CO气体流动、扩散等的综合研究,建立了CO井筒流动及大气扩散模型。同时,也考察了井筒压力、气油比、风速、气体泄放速率、大气稳定度等主要因素对CO气体扩散的影响。通过现场实例计算,证实模型具有较高的准确性。此项工作的完成为建立监控系统提供基础技术依据,同时对合理、有效的开发油气田以及煤层气的开发将具有重要的实际意义。     

Oligo(ethylene oxide) side‐chain steric screening effects on conductimetric properties of grafted poly(4‐vinylpyridinium) salts in aqueous solutions

A set of poly[N‐oligo(ethylene oxide)yl 4‐vinylpyridinium tosylate] (P4VOEOOTs) has been prepared by spontaneous polymerization of 4‐vinylpyridine. This method gives a grafted polyelectrolyte having a positive charge on every backbone pyridinic moiety. The P4VP15Ts, P4VP164Ts, P4VP350Ts and P4VP750Ts aqueous solution conductivities were determined in the concentration range from 6 × 10^?4 to 10^?2 M at 25 °C. The variation of the conductivity versus concentration of the investigated system exhibits typical polyelectrolyte behaviour. The polyelectrolyte mobility was found to be dependent on the oligo(ethylene oxide) (OEO) side‐chain length. Manning's rod‐like model fails to describe these results. A simple steric effect is proposed to explain the influence of the OEO length. Copyright © 2003 Society of Chemical Industry     

我国上市公司股票评级研究——财务结构模型分析法在股票市场中的应用

目前,我国股票市场上的股票评级尚处于探索阶段,评级时多采用专家法或历史法,而对于影响股票评级的各因素的确定以及因素间的相互作用缺乏定量分析。研究将结构模型应用到我国股票市场的股票评级中,建立关于我国股票评级的财务结构模型;分析各个因素对股票评级的影响;建立股票评级经验模式值。     

Effective Location Based Services with Dynamic Data Management in Mobile Environments

With the proliferation of mobile computing technologies, location based services have been identified as one of the most promising target application. We classify mobile information service domains based on feature characteristics of the information sources and different patterns of mobile information access. By carefully examining the service requirements, we identify the dynamic data management problem that must be addressed for effective location based services in mobile environments. We then devise a general architecture and cost model for servicing both location independent and location dependent data. Based on the architecture and cost model, we propose a set of dynamic data management strategies that employs judicious caching, proactive server pushing and neighborhood replication to reduce service cost and improve response time under changing user mobility and access patterns. Detail behavior analysis helps us in precisely capturing when and how to apply these strategies. Simulation results suggest that different strategies are effective for different types of data in response to different patterns of movement and information access. Shiow-yang Wu is an associate professor of the Department of Computer Science and Information Engineering at National Dong Hwa University, Hualien, Taiwan, R.O.C. He received the BS and MS degrees in computer engineering from National Chiao Tung University, Hsinchu, Taiwan, ROC, and the PhD degree in computer science from the University of Texas at Austin in 1984, 1986, and 1995, respectively. His research interests include data/knowledge bases, mobile computing, distributed processing, intelligence information systems, and electronic commerce. Kun-Ta Wu was born in Taipei, Taiwan, R.O.C., in 1976. He received the B.S. degree in computer science from Soochow University, Taipei, Taiwan, R.O.C., in 1999 and the M.S. degree in computer science and information engineering from National Dong Hwa University, Hualien, Taiwan, R.O.C., in 2001. Currently, he is an Assistant Researcher in the Domestic Division at Science and Technology Information Center, National Science Council, R.O.C., as a member of Information Gathering and Analysis Group of National Information and Communication Security Taskforce. His research interests include mobile computing, wireless network and information security.