Because the introduction of a vibro-impact structure can widen the bandwidth and improve the harvesting efficiency of the vibration energy harvesting (VEH) systems, an analytical method for a VEH system based on vibro-impact is proposed to employ the stochastic response and stability. Firstly, the piezoelectric control equation is decoupled by the generalized harmonic transformation, which obtains an uncoupled equivalent system. Secondly, the Itô stochastic differential equation with amplitude is analytically derived by applying the proposed analytical method. Furthermore, the influence of crucial parameters on the mean square voltage (MSV) and the mean output power is explored, such as the coupling factors and restitution coefficient. Finally, the top Lyapunov exponent (TLE) can be derived based on the linearized averaged Itô equations and the condition for the stability with probability one is obtained. It turned out that restitution coefficient r and time constant ratio μ have remarkable effects on the system’s stability.

Focusing on multiple attractors wind-induced vibration energy harvesting system with unilateral impact under the excitation of Gaussian white noise, the stochastic response characteristics, and energy harvesting performance of the systems are presented and discussed. The stochastic averaging of the energy envelope and a conversion mechanism for decoupling the electromechanical equations are introduced to derive the theoretical probability density functions. Numerical simulation results are given to verify the correctness of such theoretical methods. Effects of the noise intensity, restitution coefficient, time constant ratio and coupling coefficient on the mean square voltage are analyzed. It is found that increments of the restitution coefficient and the piezoelectric coupling coefficient of the electrical part have a positive effect on the output voltage of the system, while other factors are opposite. Analysis can help explain the physical mechanisms of the system and provide ideas for optimizing energy harvesting performance by properly tuning the coefficients.

Discontinuity and non-smoothness of system displacement and velocity caused by mechanical impact make the related research on dynamics of vibro-impact systems very difficult and complex. For the sake of bypassing the problems resulting from impact to some extent, Zhuravlev and Ivanov coordinate transformations were proposed, which can effectively convert the vibro-impact system to one without impact terms. In this paper, a more direct and universal transformation for general bilateral rigid vibro-impact systems is proposed. It is inspired by the main technique of Ivanov transformation, which makes the trajectories remain continuous in an auxiliary phase space. It can be directly applied to common vibro-impact systems, whether the positions of barriers are symmetrical or the restitution coefficients of barriers on both sides are consistent. In particular, this method can also be applied to the unilateral vibro-impact system. Validity of the proposed methodology is examined by means of case studies.

数据智能是综合的数字体系,靠单点的技术和单款产品很难实现目的,所以数据智能包括综合技术体系以及智能应用体系两个方面.其中,综合技术体系融合了大数据、人工智能、云计算、物联网等多种技术,应用于数据处理、分析、决策;智能应用体系连接物理世界与数字世界,核心包括人机智能交互、自动化知识构建和服务,以及机器辅助决策等应用.

Understanding the process of consumer decision making is important for many decision support systems. Consumers evaluate different alternatives and then come to a decision. Prior research suggests that consumer evaluations leading to choice are comparative in nature and can be affected by other alternatives or reference products. This study proposes a mixtures-of-experts model framework to examine the role of different reference products in consumer choice of multi-attribute products. While multiple external and internal reference points have been proposed, previous studies have very rarely investigated more than one reference point in the same model. Using data from a choice-based conjoint experiment, our empirical model enables us to identify which product consumers tend to use as the reference product by incorporating four different reference products and includes consumer characteristics to examine how consumers differ in their utilization of different reference products. The results show that our model outperforms other reference-dependent models in prior literature. In our empirical context of smartphone choices, the most commonly used reference product is the most preferred product in the choice set, while the least preferred product and the average product are rarely used. We also examine the role of consumer characteristics such as gender, product familiarity, and product interest in utilizing reference products. This paper provides insights into the unobserved comparison process in consumer choice, which can be applied to decision support systems such as recommendation engines.

在大数据时代,"互联网+"有着良好的发展前景.随着网络的发展,电子商务行业逐渐被人熟知.电子商务是发展经济、改善民生的重要途径,因此河北省要实现乡村振兴,可着力于发展河北省农村电商.电子商务行业在农村的发展有部分优势,也存在很多困难,需要针对性地解决,同时需要创新,与大数据进行融合,谋求长久的发展.

[目的]本文主要就数据中台相关研究背景、技术架构和关键技术以及在行业中的落地应用展开介绍,并结合技术发展趋势提出未来研究和应用发展方向.[方法]本文综述了数据中台相关领域的国内外研究,并提出数据中台通用技术架构,分别对大数据技术平台、数据资产管理平台、数据分析挖掘平台和统一服务总线的核心技术和功能进行了展开讨论.[结果]基于本文提出的数据中台的相关技术框架,数据中台在相关行业已经得到初步应用和实践,其中互联网、金融和政府等行业走在前沿.[结论]数据中台的相关技术会越来越向自动化、智能化方向发展,其支撑的上层业务应用将会在一系列相关技术突破的推动下在各行业形成爆发式的发展.

In the present paper, considering the significant nonsmooth factors, friction and impact, the responses and asymptotic stability with probability one of a system are investigated for the cases of additive and multiplicative Gaussian white noise random excitations. First, the original system which contains impact and viscoelastic terms can be approximated as an equivalent system by using nonsmooth transformation and converting the viscoelastic force to the sum of stiffness and damping terms. Then, the stationary probability density functions are analytically obtained by utilizing the stochastic averaging method. And the equation of the Top Lyapunov Exponent is also obtained with the help of combining the stochastic averaging method and Khasminskii method, which is used to discuss the effects of various parameters on the system's stability. The validity of the analytical results derived from the proposed procedures is verified by comparing with directly numerical simulation. In particular, under certain conditions, there are examples about how to control the change of stability of the system by adjusting the variation of the restitution coefficient and the friction from the mathematical standpoint. (C) 2019 Elsevier Ltd. All rights reserved.

个性化推荐系统已成为各大电商向消费者提供个性化购物体验的重要工具之一,通过推荐系统,商家可以提高收入和消费者满意度.但传统推荐系统通常只利用消费者在当前网站的历史信息推荐个性化商品,无法获得消费者在其他网站的数据来优化推荐效果.大数据时代,一些第三方公司抓住机遇,利用不同公司的多源大数据提供更好的个性化推荐服务.然而,这种新型的推荐系统对消费者购物行为的影响存在极大的未知性.探究基于多源大数据的个性化推荐系统对消费者购物行为的影响.为了建立推荐系统与消费者购物行为之间的因果关系,采用实地实验有效地避免传统研究方法存在的内生性问题,并具有较好的外部有效性.一方面,基于内部数据和外部数据构造解释性变量,探究内部数据特征和外部数据特征与推荐效果之间的关系;另一方面,通过检验消费者特征与内外部数据的推荐效果间的交互效应,进一步分析外部数据和内部数据的推荐效果如何随消费者的特征变化,帮助企业更好地利用多源大数据提升推荐效果.研究结果表明,基于内部数据的推荐系统能够显著提升消费者点击个性化推荐商品的概率,可以降低消费者决策时间,激励消费者浏览更多的商品.外部数据的推荐效果不仅与外部公司网站的用户数量相关,也会受到外部网站与当前网站的关联程度的影响.消费者特征对基于内部数据和外部数据的推荐效果起调节作用,如果消费者是当前网站的老用户,利用该消费者在当前网站的内部数据提供个性化推荐的效果更佳.通过分析基于多源大数据的推荐效果对消费者购物行为的影响,进一步完善个性化推荐领域的理论框架.研究结果对如何利用多源数据构建更加有效的推荐系统具有重要指导价值,并为不同网站之间的数据共享机制提供重要的管理建议.

Untethered and wirelessly-controlled microrobots have many applications in the field of biomedicine. Therefore, many laboratories and scientists have invested more scientific research into magnetic microrobots which can make more contributions to medical care. Many magnetic field devices and microrobots are manufactured. In the development of micro-robots, helical microrobots have been well developed. Rigid-body robots account for the majority of these, but they may cause damage to human organs during treatment. However, soft and deformable robots can relieve more medical restrictions. In general, helical microrobots are driven by uniform fields which have their own limitations while the gradient magnetic field can relieve more restrictions and have more functions. This paper presents a flexible deformable helical swimmer controlled in a rotating gradient magnetic field. Helical swimmers are covered with magnetic nano-particles and the helical structure is derived from the inner fiber structure of the lotus root. The soft helical swimmers are controlled to swim several special trajectories in the rotating gradient magnetic field and we analyze the frequency and other factors for velocity or other effects.

In this paper, the stationary response of a van der Pol vibro-impact system with Coulomb friction excited by Gaussian white noise is studied. The Zhuravlev nonsmooth transformation of the state variables is utilized to transform the original system to a new system without the impact term. Then, the stochastic averaging method is applied to the equivalent system to obtain the stationary probability density functions (pdfs). The accuracy of the analytical results obtained from the proposed procedure is verified by those from the Monte Carlo simulation based on the original system. Effects of different damping coefficients, restitution coefficients, amplitudes of friction and noise intensities on the response are discussed. Additionally, stochastic P-bifurcations are explored.

This paper reports a new hybrid energy harvesting approach which combines triboelectricity and piezoelectricity based on low-frequency (less than 5 Hz, such as environmental vibrations) stochastic resonance. A vibration configuration was well designed to enhance the conversion efficiency of mechanical energy to electricity via the stochastic vibration mechanism. Furthermore, the electric output performance of the proposed generator is significantly strengthened by adding triboelectric effects to bi-stable structured energy harvester. Power density of the piezoelectric part and triboelectric part are 1.85mW/cm 3 and 1.81mW/cm 3 , respectively, showing attractive potential for generating high output by harvesting low-frequency vibration from the environment over a broad frequency band.

Most research on the performance of foreign versus domestic brands in emerging markets has examined dependent measures of product evaluation or purchase intention. However, consumers who intend to buy a product may switch to competing brands, thus displaying an intention–behavior discrepancy (IBD). Drawing on literature on country associations and dual process theory, the authors examine the performance of foreign versus domestic brands on IBD in emerging markets and the moderating role of consumer prior knowledge. They conduct an intention survey followed by a postpurchase survey in the Chinese automobile and smartphone industries and find that foreign brands have an advantage on IBD relative to domestic brands, indicating that they have the dual advantage of higher evaluations and lower IBDs. Furthermore, foreign brands’ advantage on IBD is smaller for consumers with inaccurate prior knowledge because they are more likely to systematically reprocess information and discount foreign brands’ favorable country associations. For these consumers, overestimating the product reduces foreign brands’ advantage to a lesser degree than underestimating it as a result of confirmation bias. These findings provide implications for brands in emerging markets.

Although keyword auctions are often studied in the context of a single keyword in the literature, firms generally have to participate in multiple keyword auctions at the same time. Advertisers purchase a variety of keywords that can be categorized as generic-relevant, focal-brand, and competing-brand keywords. At the same time, firms also have to choose how the keywords can be matched to search queries: exact, phrase, or broad. This study empirically examines how keyword categories and match types influence the performance of advertising campaigns. We build a hierarchical Bayesian model to address the endogeneity problem contained in the simultaneous equations of the click-through rate, the conversion rate, cost per click, and rank, and we use the Markov Chain Monte Carlo method to identify the parameters. Our results suggest that it is important to differentiate among the various bidding strategies for various keyword categories and match types. We also report results related to financial performance such as number of sales, profit, and return on investment for different keywords. These findings shed light on the practice of sponsored search advertising by offering insights into how to manage ad campaigns when advertisers have to bid on multiple keywords. The online appendix is available at https://doi.org/10.1287/isre.2017.0724 .

本文研究了消费者知识、购买意愿强度、购买延迟时间等因素对消费者自述偏好和实际偏好不一致的影响,并研究了促使消费者形成准确知识的前因.本文采用的数据来自汽车购买意愿(即自述偏好)和购买行为(即实际偏好)的两阶段问卷调查以及一个包括806个车型信息的汽车数据库.实证研究的结果表明,消费者的不准确知识、购买意愿强度以及购买延迟时间均对自述偏好和实际偏好不一致具有很强的解释力,而消费者对目标产品的属性评价没有显著影响.本文进一步将不准确知识分为消费者低估和高估目标产品两种情况,发现自述偏好和实际偏好的不一致主要是由消费者低估目标产品造成的.实证研究还表明,某个属性相对表现越突出,消费者就越容易对该属性形成准确知识.

当今社会，各大电商在进行品牌塑造时，逐渐意识到品牌信息有效传播的重要性，并作出不少改善，如在线交流，商品评价等功能方式。但电商通常是运用互联网跟消费者进行非直面的交流，往往会导致信息的大量损耗，因此，电商仍需完善信息传播渠道，通过建立规范的、具较强互动性的交流平台，逐步提升品牌知名度，最大限度地满足消费者需求。

销量预测作为企业营销决策和战略管理中的重要环节,一直是研究的热点.但由于销量受企业内部环境和外部环境中多种因素影响,销量预测一直是极具挑战性的研究问题.现有的销量预测模型常使用商品的历史销量和商品属性等变量来预测销量,很少考虑利用其他商品信息来提高预测精确度.本文首先通过市场购物篮分析,找出销量相互影响的商品品类.然后根据市场购物篮分析结果构建品类之间的关联网络,并利用网络中与待预测品类相关联的其他品类的销量信息来提高预测准确度.为了解决预测过程中存在的内生性问题,本文采用向量自回归模型对预测问题进行建模,同时控制节假日等因素对销量的影响.本文用一家国内大型超市的真实数据进行验证,结果表明本文提出的方法比传统方法具有更高的精确度.最后,本文基于得到的研究结果,为企业的库存管理和营销策略提出一些管理建议.

随着时代的发展,云计算逐步进入我们的生活,并将成为信息化发展的主要手段.主要根据云计算的相关概述,结合云计算的发展阶段以及发展现状,对我国云计算产业发展对策进行探析,可靠性、可用性、安全性是云计算必须面对的重要问题.中国新型的云计算企业是以后来者的身份进入云计算市场,还缺乏与产业深入融合的能力,因此在技术、产品、服务模式等领域进行了探索.

When a retailer distributes manufacturer coupons to consumers without perfectly identifying their product valuations, consumers may have incentives to trade coupons. We develop a model to capture the coupon trading phenomenon and compare three scenarios: (I) no coupon, (II) coupon without trading, and (III) coupon with trading. We find that coupon trading can increase the profits of either the retailer or the manufacturers, but not at the same time. The retailer benefits from coupon trading when the coupon market is competitive and consumer hassle cost is low, while the manufacturers benefit from coupon trading when the coupon market is uncompetitive and consumer hassle cost is high. In addition, coupon trading does not always increase total demand. Firms benefit from coupon trading by charging higher prices, which leads to a decreased total demand. As a result, consumers end up with a higher average cost under coupon trading. We also compare coupon trading with improved coupon targeting, and find that coupon trading may allow firms to gain higher profits than improved coupon targeting. Further, we extend the main model to a competitive setting where the products are substitutable, and find that the main results still hold Finally, we employ numerical analysis to identify the optimal coupon face values in different scenarios, and the results suggest that coupon trading combined with incentive mechanisms may lead to Pareto improvement for the channel as a whole. (C) 2013 New York University. Published by Elsevier Inc. All rights reserved.