Development of a knowledge based hybrid neural network (KBHNN) for studying the effect of diafiltration during ultrafiltration of whey

The membrane surface dynamics is very difficult to predict and can be roughly estimated by the available models but a true depiction is always difficult since the magnitude and direction of driving forces change as a function of time. The present study is an effort to address the issue, so that the combinatorial approach of deterministic and stochastic modelling might present a better understanding of membrane dynamics. The effect of diafiltration has also been incorporated to investigate the effects it has on the membrane. A stochastic model developed by a knowledge based hybrid neural network (KBHNN) was trained using the Levenberg–Marqurt algorithm where the film layer model was used as the deterministic layer, called the first principle model (FPM). Present work employs two different types of KBHNN architecture with an effort to understand the suitability and applicability of the hybrid network in case of predictions for an ultrafiltration (UF) process. In one sort of architecture neural part was in series with the FPM and in the other one it was in parallel with the FPM. The high correlation coefficient (R²) value portrays the correctness and preciseness of the underlining assumptions and establishes the validity of the developed network.     

让同学们“轻松”学习物理化学

我们为解决物理化学难教难学的问题,在教学实践中实施了一些有效的方法,强调换位思考与方法教育,旨在让同学们体验到物理化学的逻辑趣味性,让他们既轻松又有效地学好物理化学。     

移动互联技术助力博物馆社会化服务

移动互联网技术和智能手机发展给博物馆带来了新的契机,同时也给观众带来了新颖独特的体验,利用移动互联网延伸博物馆的社会教育服务功能,科技与文化相结合,将文化送到公众手上,科技助力文化传播可以让文化更亲民,让文化服务更惠民。借助移动互联网技术,利用3G/4G手机、PAD等各类移动终端,运用最新的掌上微游、数字导览、知识图谱、社交互动等方式打造可以随身携带的博物馆。     

以项目式教学为主线的《环境行为学》教学探索

本文介绍了以项目式教学为主线的 《环境行为学》教学方法,以区别于传统学院 式理论授课的形式。为对应新方法容易引发 的三个问题，作者在理论知识组织、课程时 间结构、项目选题、控制工作量、考核与评 分这五个方面发展出独特的策略与措施， 在课堂内外对学生自主进行的小研究项目全 过程进行妥善组织与督导。从对历届学生的 调查以及作业成果看，该方法对提高学生的 学习动机、加深知识的掌握程度具有显著 效果。     

Integrating an urban green space typology into procedural 3D visualization for collaborative planning

Urban green spaces offer multiple ecosystem services (ES), which provide a variety of benefits to human well-being. Yet in urban planning they are not taken into account systematically. Recently new tools have been developed integrating ES into procedural modeling and visualization to raise stakeholder awareness for the explicit ES trade-offs that have to be made. These tools yet do not allow fast and comprehensive integration of ES provision in urban environments. In this paper we show how urban green space typologies can be linked to ES provision for facilitating collaboration between stakeholders of different backgrounds. Based on a generic typology green spaces were mapped and linked with information on potentially provided ES and their parameters. Further, pattern designs of the green space types were described with a form-based code. Both the map of green space types and the pattern designs were integrated into the parametric modeling and visualization chain of Esri CityEngine resulting in 3D visualizations of the green space patterns and correlating ES indicators. The green space typology allows for integrating different kinds of knowledge from both science and practice communities. The procedural model enables rapid interactive visualization of urban patterns and calculation of simple indicator values on the provision of ES. The simple approach for mapping green space types with low data requirements and the generic green space design patterns allow for transferability to other places and application to large areas. The developed approach is simple and fast yet comprehensive to communicate the vital importance of all green space types within the urban environment.     

An empirical study on the quantitative notion of task difficulty

Most Adaptive and Intelligent Web-based Educational Systems (AIWBES) use tasks in order to collect evidence for inferring knowledge states and adapt the learning process appropriately. To this end, it is important to determine the difficulty of tasks posed to the student. In most situations, difficulty values are directly provided by one or more persons. In this paper we explore the relationship between task difficulty estimations made by two different types of individuals, teachers and students, and compare these values with those estimated from experimental data. We have performed three different experiments with three different real student samples. All these experiments have been done using the SIETTE web-based assessment system. We conclude that heuristic estimation is not always the best solution and claim that automatic estimation should improve the performance of AIWBES.     

Expert diagnosis of polymer electrolyte fuel cells

Diagnosing faulty conditions of engineering systems is a highly desirable process within control structures, such that control systems may operate effectively and degrading operational states may be mitigated. The goal herein is to enhance lifetime performance and extend system availability. Difficulty arises in developing a mathematical model which can describe all working and failure modes of complex systems. However the expert's knowledge of correct and faulty operation is powerful for detecting degradation, and such knowledge can be represented through fuzzy logic. This paper presents a diagnostic system based on fuzzy logic and expert knowledge, attained from experts and experimental findings. The diagnosis is applied specifically to degradation modes in a polymer electrolyte fuel cell. The defined rules produced for the fuzzy logic model connect observed operational modes and symptoms to component degradation. The diagnosis is then tested against common automotive stress conditions to assess functionality.     

Key choices in the design of Simple Knowledge Organization System (SKOS)

Simple Knowledge Organization System (SKOS) provides a data model and vocabulary for expressing Knowledge Organization Systems (KOSs) such as thesauri and classification schemes in Semantic Web applications. This paper presents the main components of SKOS and their formal expression in Web Ontology Language (OWL), providing an extensive account of the design decisions taken by the Semantic Web Deployment (SWD) Working Group of the World Wide Web Consortium (W3C), which between 2006 and 2009 brought SKOS to the status of W3C Recommendation. The paper explains key design principles such as “minimal ontological commitment” and systematically cites the requirements and issues that influenced the design of SKOS components.By reconstructing the discussion around alternative features and design options and presenting the rationale for design decisions, the paper aims at providing insight into how SKOS turned out as it did, and why. Assuming that SKOS, like any other successful technology, may eventually be subject to revision and improvement, the critical account offered here may help future editors approach such a task with deeper understanding.     

全国计算机等级考试二级公共基础知识应试对策研究

本文从计算机二级公共基础知识部分的考核重点和考察方式等方面分析，总结了二级公共基础知识应试对策。     

Medical knowledge management for specific hospital departments

Medical knowledge representation and management is concerned with how to organise the often vague clinical experience of medical staff required for computable models. However, few knowledge management and acquisition tools have entered routine use, since such tools are not perceived by physicians as part of the clinical information process. An attempt to partially solve this problem, we identify two key aspects of knowledge representation and management tasks. The first is to adopt a medical knowledge standardisation to provide a consistent terminology control and to simplify the integration between knowledge management tools and the health information system. The second is to establish an effective knowledge acquisition process in specific medical fields by adapting knowledge acquisition tools. Therefore, the main goal of this work is to define computational models and to design mechanisms for the effective acquisition and management of medical knowledge in real-life hospital departments. To this end, we analyse the representation of medical knowledge (based on deep-causal models) and the development of knowledge management tools (based on ontologies), integrated within the information processing activities of the clinical user. Finally, we illustrate its applicability in the Intensive Care Unit and Pediatry scenarios.