基于可拓学的新型职业农民培育模式创新研究

“产业兴旺”是乡村振兴的重点, 是乡村振兴的经济基础, 是解决农村一切问题的前提。为了破解乡村产业兴旺中高素质农民短缺所造成的人才制约问题, 本研究梳理了现有新型职业农民培育文献, 对负责新型职业农民培育的政府部门工作人员进行深度访谈, 以此为基础形成新型职业农民培育供需现状调查问卷, 基于分析结果厘清了新型职业农民培育规模和培育内容两个供需矛盾问题。基于可拓学原理, 建立了矛盾问题的可拓模型, 并通过可拓变换来解决矛盾问题, 最终形成了新的新型职业农民培育模式。此研究对有效提升新型职业农民培育效能, 促进乡村产业兴旺的有效实施具有重要意义。     

Usability,quality, value and e-learning continuance decisions

Previous research suggests that an eventual information technology (IT) success depend on both its initial adoption (acceptance) and subsequent continued usage (continuance). Expectancy disconfirmation theory (EDT) has been successfully used to predict users’ intention to continue using information technologies. This study proposed a decomposed EDT model to examine cognitive beliefs and affect that influence users’ continuance decision in the context of e-learning service. The proposed model extended EDT by decomposing the perceived performance component into usability, quality, and value. Research hypotheses derived from this model are empirically validated using the responses to a survey on e-learning usage among 183 users. The results suggest that users’ continuance intention is determined by satisfaction, which in turn is jointly determined by perceived usability, perceived quality, perceived value, and usability disconfirmation.     

遗传BP神经网络在大宗商品市场风险预警中的应用

研究利用遗传BP神经网络预警大宗商品电子交易市场风险的应用方法,将定量分析的思维方式引入大宗商品市场风险评价管理中.为此目的,建构了一个基于遗传BP神经网络的预警模型（GA-BPNNM）,在市场调研的基础上建立了大宗商品电子交易市场风险评价指标体系,并通过实验确定了预警模型的最佳训练函数和隐层的最佳节点数.GA-BPNNM借助BP神经网络强大的自学习能力和非线性映射能力,克服传统手段在分析大宗商品电子交易市场风险时因其定义的模糊性和诱发因素的多样性所带来的困难;同时通过遗传算法与BP网络两者相互融合优化,解决BP神经网络易落入局部最优、收敛速度慢以及遗传算法易早熟等问题.仿真测试实验表明,GA-BPNNM预测结果优于标准BP神经网络预测方法,用于大宗商品电子交易市场风险损失程度预警是有效可行的.     

Design and implementation of a case-based reasoning system for marketing plans

Unstructured intangible experiences and knowledge are usually difficult to represent and instantiate, which engenders the hardship of knowledge transfer and sharing. Past marketing plans are such valuable documents containing strategic planning knowledge and experiences.Case-Based Reasoning (CBR), which consists of retrieving, reusing, revising, and retaining cases, has been proved effective in retrieving information and knowledge from prior situations and being widely researched and applied in a great variety of problem territories.This paper targets at designing a CBR architecture and a method that facilitate the sharing and retrieving of cases of great concern to the marketing personnel. After an intensive survey of CBR methods and applications, a CBR system embedding multi-attribute decision making method, which provides both overall similarity level and similarity level of each selected attribute, is proposed to enhance the adaptation of a new marketing plan. In addition, a multi-attribute gap analysis diagram is developed to visualize the similarity along with the gap between candidate and target cases, so as to better support interaction and group decision making in the process of strategically formulating a new marketing plan. The CBR system was implemented and successfully demonstrated on case retrieval of a telecommunication company.     

Genetic mechanism-based coupling algorithm for solving coordinated scheduling problems of yard systems in container terminals

This study develops models and methods utilized for solving the coordination scheduling problem in the yard of a container terminal. Based on the information shared by the yard storage subsystem and the YC scheduling subsystem, and the interaction between these subsystems, a coordination scheduling model, which is composed of a storage subsystem model, a YC scheduling subsystem and a coordinate controller model, is developed. A coupling algorithm, which is based on a genetic mechanism, is developed to solve the coordination scheduling problem. The algorithm adopts the genetic selection, crossover and mutation operations to adjust the yard storage plan and the YC scheduling plan. The performance of the coordination scheduling model and that of the proposed coupling algorithm are confirmed with reference to a numerical example.     

Energy security in Group of Seven (G7): a quantitative approach for renewable energy policy

This study examined the renewable energies and their impact on the economies of the Group of Seven (G7) countries. Results showed that the electricity produced from wind energy in the United States and then Germany is more than any other member countries. Due to its voluminous volcanoes, Italy has had favorable conditions for the development of geothermal energy, which has led it to be used as an efficient energy source in Italy. Results also showed that the installed capacity of geothermal systems is the lowest and hydropower systems are the highest in all G7 countries. It also concluded that, despite the high share of hydropower energy from total renewable energy capacity, the use of wind and solar energies is rapidly rising. As a result, it found that the development of solar energy occurs faster than the other renewable energies.     

消费者网络购物搜索效率的眼动追踪实验研究

目的 在信息碎片化和快消费的时代,为提升电子商务APP信息检索系统的交互性能,更好地为消费者提供精准、优质、快捷的网购服务,通过使用眼动追踪实验的方法,探究视觉密度与消费者网购搜索效率的关系.方法 设计两组实验,通过眼动仪收集眼动轨迹的过程和数据,借助SPSS 25.0对数据进行方差分析.结果 在任务导向情境下,被试在网格布局的商品导航界面上搜索效率比列表模式的搜索效率高;在非任务导向情境下,消费者在宫格导航的界面上搜索效率相对较高;浅色背景下消费者网购的搜索效率更高.结论 电商APP界面信息组织要素构成比例不同,会导致不同的信息密度,电商APP的设计人员可根据界面分区的功能合理布局信息组织要素,进而优化界面信息密度,提升消费者搜索体验.