Flavor and Stability of "Horchata De Chufas"

Horchata is a sweetened water extract of chufa tubers (Cyperus esculentus) which is very popular in Spain, and has potential in the U.S. The objectives of this research were to characterize horchatas from different types of chufa, and to monitor flavor and stability of unheated and pasteurized horchatas during storage (2°C). Trained panelists rated the following attributes: color, chalkiness, sweetness, vanilla-like, nutty, earthiness, bitterness, and off-flavor. Horchatas made with chufa grown in Spain and chufa from Spain but grown in Florida showed higher vanilla and nutty levels than horchata from the Florida type. During storage (2°C), vanilla, nutty, and sweetness decreased, and other attributes increased. Heating to 70 and 95°C for 1 min did not alter sensory attributes initially, prevented off-flavor development, and slowed changes in desirable attributes for 35 days.     

Laboratory and Field Consumer Evaluation Relationships for Menu Items Processed in Retortable Trays for Quantity Foodservice

Problems associated with provision of food in quantity foodservices prompted the development and use of prepared food items processed in retortable trays. Consumer acceptance of such foods was required so that the items could be screened for foodservice application. Consumer tests, using small portion samples and sensory testing under laboratory conditions, gave a relatively reliable prediction of acceptability of most of the items under extended-use consumer testing during a field trial. Final field acceptance of some items was influenced by external factors not accounted for in laboratory testing.     

智能交通信号控制系统初探

城市交通拥挤是当今世界普遍关注的问题,它所带来的严重危害日益影响到人们的日常生活和社会经济的发展,而城市交通信号控制系统对解决这一问题发挥着不可替代的作用。从高性能智能交通信号控制系统的要求出发,针对目前我国城市交通问题的现状．对智能交通信号协调控制系统进行初步的研究和探讨。     

Making costly manufacturing smart with transfer learning under limited data: A case study on composites autoclave processing

The integration of advanced manufacturing processes with ground-breaking Artificial Intelligence methods continue to provide unprecedented opportunities towards modern cyber-physical manufacturing processes, known as smart manufacturing or Industry 4.0. However, the “smartness” level of such approaches closely depends on the degree to which the implemented predictive models can handle uncertainties and production data shifts in the factory over time. In the case of change in a manufacturing process configuration with no sufficient new data, conventional Machine Learning (ML) models often tend to perform poorly. In this article, a transfer learning (TL) framework is proposed to tackle the aforementioned issue in modeling smart manufacturing. Namely, the proposed TL framework is able to adapt to probable shifts in the production process design and deliver accurate predictions without the need to re-train the model. Armed with sequential unfreezing and early stopping methods, the model demonstrated the ability to avoid catastrophic forgetting in the presence of severely limited data. Through the exemplified industry-focused case study on autoclave composite processing, the model yielded a drastic (88%) improvement in the generalization accuracy compared to the conventional learning, while reducing the computational and temporal cost by 56%.     

基于柔性逻辑的智能控制器设计与仿真

研究倒立摆复杂系统优化控制问题,传统优化控制要建立精确数学模型,但与实际不符。对复杂系统采用具有认知和仿人功能、适应不确定环境等特性的智能控制方法较传统控制方法更具优势。为此,提出一种柔性泛逻辑学的智能控制模型,具有三个典型参数(e、h、k),分别反映了控制过程中的决策门限、被控量之间的关系和测量误差,能更好地掌握控制的思路。对三级倒立摆的控制采用上述方法进行仿真,实验证明了模型的正确性和有效性,并且具有良好的抗干扰能力,为复杂系统控制寻求了一种新的有效途径。     

RFID技术在智能交通管理中应用

本文主要介绍RFDI技术定义及系统工作原理,并重点关注RFID技术在智能交通领域的实际应用方式。同时RFID技术也成功解决了车辆自动识别和信息采集问题,为智能交通管理和服务系统的建立提供了强大的信息支撑和保障。     

基于语义分析的设计实体智能搜索

本文提出了在设计联盟组织过程中实现互联网上设计实体智能搜索的方法。根据对互联网上设计实体搜索问题的分析建立了设计实体智能搜索策略；定义了提取设计实体查询向量和描述向量的语义分析规则；提出了基于语义分析的设计实体智能搜索算法；最后编程实现了各项功能。     

水厂生产运行管理决策支持系统的开发

介绍了水厂生产管理决策支持系统的设计原理和方法，其中主要讲述了数据库和知识库的建立，并阐述了该系统的运行功能、管理和维护方法。     

CIM技术在塑性成型工程的应用

本文根据国外ＣＩＭ技术发展的概况，针对塑性成形工程的特点，提出了塑性成形工程中实施ＣＩＭＳ技术应用和研究的几个重要的方向，同时，从系统集成的角度，指出基于知识集成的智能制造系统应是ＣＩＭＳ进一步发展的重点，最后，对这类系统建模的基本技术与方法进行了讨论。     

Applying a student modeling with non-monotonic diagnosis to Intelligent Virtual Environment for Training/Instruction

We present a student modeling approach that has been designed to be part of an Intelligent Virtual Environment for Training and/or Instruction (IVET). In order to provide the proper tutoring to a student, an IVET needs to keep and update dynamically a student model taking into account the student’s behaviour in the Virtual Environment. For that purpose, the proposed student model employs a student ontology, a pedagogic diagnosis module and a Conflict Solver module. The goal of the pedagogic diagnosis module is to infer which learning objectives have been acquired or not by the student. Nevertheless, the diagnosis process can be complicated by the fact that while learning the student will not only acquire new knowledge, but he/she may also forget some previously acquired knowledge, or he/she may have some oversights that could mislead the tutor about the true state of the student’s knowledge. All of these situations will lead to contradictions in the student model that must be solved so that the diagnosis can continue. Thus, our approach consists in applying diagnosis rules until a contradiction arises. At that moment, a conflict solver module is responsible of classifying and solving the contradiction. Next, the student ontology is updated according to the resolution adopted by the Conflict Solver and the diagnosis can continue. This paper mainly focuses on the design of the proper mechanisms of the student model to deal with the non monotonic nature of the pedagogic diagnosis.