Teaching chemical engineering using Jupyter notebook: Problem generators and lecturing tools

The primary objective of this study is to develop teaching materials for chemical engineering students (or students pursuing other related B.Sc./M.Sc. degrees) that encourage self-learning to facilitate understanding and the development of problem-solving skills. Tools are oriented to support the teaching of “Introduction to Chemical Engineering” courses to 1^st year B.Sc. students in Chemical Engineering, 2^nd year B.Sc. students in Chemistry, and 3^rd year B.Sc. students in Biochemistry at the Universidad Complutense de Madrid (UCM). Problem generators of standard exercises, as an additional complement to the exercises that are used in the lectures, seminars, and assignments to facilitate the learning of the students, have been developed. These generators provide exercises to students with “unlimited” initial values (with certain restrictions). The software that was used to develop these materials was Jupyter Notebook, which runs under the Python 3.6 language. The problem generators can be classified into fixed problem generators, case-based generators, and random problem generators. Additionally, lecturing tools have been developed to support teaching using live/interactive examples. These examples can learning understanding of various topics of the courses.     

基于Tableau的北京市房屋租赁市场现状分析

随着经济的日益发展,房地产市场价格持续上涨、居高不下,较大的购房压力促使我国房屋租赁市场快速发展。文章基于Python爬虫技术对链家房产服务平台网站的北京市所有租房信息进行数据获取,并结合商业智能软件Tableau进行数据分析,通过树状图、气泡图、条形图和甘特图等,从不同方面对数据进行多维度处理与展示,探究北京市房屋租赁发展现状,为相关研究提供参考。     

基于Python的油田生产资料预处理软件设计与应用

油田内部生产资料类型包括钻井、录井、测井、试油等多种类型。针对资料整理过程中存在的问题如:从原始资料库中下载的资料格式多样;不同石油软件所需加载的数据格式不同;已有资料预处理软件功能均较单一等,从编程语言优选、软件兼容性、软件功能集成化三个方面出发,选取Python语言进行软件设计,利用Python扩展性强的特点,设计出红番茄资料预处理软件,并在新疆油田进行试点,生产资料整理时间缩短至原耗时间的约33%。Python语言在油田生产中的应用可为具有相同问题的其他油田提供参考。     

Performance investigation in modified and improved augmented power generation Kalina cycle using Python

In the generation of electricity and cogeneration, Kalina cycle is considered as one of the competitors to organic Rankine cycle. With the simplicity and identical components of the binary mixture, Kalina system makes it more prominent to get developed and implemented as well with its environmental friendly associate. This work proposes a new improved Kalina cycle system to convert the natural source from sun to useful work. The proposed system utilizes heat source suitable to medium temperature heat applications. The proposed cycle have 2 units of solar collector, favoring an additional heat recovery and higher performance. Solar hot source temperature and pressure are 190°C and 45 bar with additional flow to the turbine of 1.15 kg/s. Energy and second law analysis have considered in evaluating the performance of the proposed plant. The energy analysis shows minimum value of net power, energy efficiency and plant efficiency as 241 kW, 15.5% and 5.7. The exergy analysis defines that, to the proposed cycle, the exergy efficiency initializes at 77% with more exergy destruction at turbine with 31%. With the parametric analysis, the system is amended to have the maximum values of energy and exergy performances as 18.5%, 7.1% and 85%. The parametric study identifies the optimum value of the inlet temperature and pressure of the pump and turbine.     

Modeling and Verification of a Sentiment Analysis System Using Aspect-Oriented Petri Nets

An increasing number of social media and networking platforms have been widely used. People usually post the online comments to share their own opinions on the networking platforms with social media. Business companies are increasingly seeking effective ways to mine what people think and feel regarding their products and services. How to correctly understand the online customers’ reviews becomes an important issue. This study aims to propose a method with the aspect-oriented Petri nets (AOPN) to improve the examination correctness without changing any process and program. We collect those comments from the online reviews with Scrapy tools, perform sentiment analysis using SnowNLP, and examine the analysis results to improve the correctness. In this paper, we apply our method for a case of the online movie comments. The experimental results have shown that AOPN is helpful for the sentiment analysis and verifying its correctness.     

基于SpringBoot框架的中长期水文预报系统设计与开发

鉴于中长期水文预报能有效为宏观防洪形势分析和水资源管理提供科学依据,提出了Java环境下基于SpringBoot框架开发的中长期水文预报系统。该系统集成了包含随机森林、支持向量机、小波分析、贝叶斯模型平均等多种模型方法的Python模型库以提高开发效率;采用了基于RabbitMQ技术的异种语言调用与基于RESTful技术的轻量级接口设计以降低系统响应时间。并搭建了全国主要江河流域共10个断面的中长期水文预报系统作为示例进行分析,实现了中长期水文预报业务化运行,可为同类系统开发提供参考示范。     

Basic human–robot interaction system running on an embedded platform

Robotics will be a dominant area in society throughout future generations. Its presence is currently increasing in most daily life settings, with devices and mechanisms that facilitate the accomplishment of diverse tasks, as well as in work scenarios, where machines perform more and more jobs. This increase in the presence of autonomous robotic systems in society is due to their great efficiency and security compared to human capacity, which is thanks mainly to the enormous precision of their sensor and actuator systems. Among these, vision sensors are of the utmost importance. Humans and many animals naturally enjoy powerful perception systems, but, in robotics, this constitutes a constant line of research. In addition to having a high capacity for reasoning and decision-making, these robots incorporate important advances in their perceptual systems, allowing them to interact effectively in the working environments of this new industrial revolution. Drawing on the most basic interaction between humans, looking at the face, an innovative system is presented in this paper, which was developed for an autonomous and DIY robot. This system is composed of three modules. First, the face detection component, which detects human faces in the current image. Second, the scene representation algorithm, which offers a wider field of view than that of the single camera used, mounted on a servo-pan unit. Third, the active memory component, which was designed and implemented according to two competing dynamics: life and salience. The algorithm intelligently moves the servo-pan unit with the aim of finding new faces, follow existing ones and forgetting those that no longer appear on the scene. The system was developed and validated using a low-cost platform based on a Raspberry Pi3 board.     

A web-based,interactive visualization tool for social environmental survey data

Understanding human motivations and actions related to environmental problems is central to modeling complex, human-natural systems. However, social science survey data on environmental issues are often presented in relatively static reports and figures and are not easily accessible for participatory deliberation. Federal data sharing mandates motivate innovative data visualization and sharing mechanisms. We developed an open-source, web-based Survey Data Viewer as a visual interface to explore quantitative social science survey data. We used the Python Django web framework and the D3.js visualization library to create and deploy the tool. The Viewer was implemented using a water-related survey administered to a large, random sample of Utah adults in public venues. The Viewer allows users to visualize question responses based on demographic variables with percentages and mean response levels. We developed a standardized template for encoding survey data and metadata that permits the generalization of the tool to other similar surveys.     

网联车辆自适应巡航控制算法验证平台设计

自适应巡航控制系统是一种车辆高级辅助驾驶系统，不仅可以减轻驾驶员工作负担，还能增强车辆的行车安全和驾乘舒适性。基于MATLAB和Python混合编程，在网络协议环境下设计智能车巡航控制算法验证平台；该平台能够模拟多种不同典型行车场景，其实时的信息采集与动画演示功能能够直观有效地展现车辆状态。结合所开发的平台软件，设计出增量式模型预测控制器（IMPC）和智能驱动驾驶（IDM）控制器，所提出的IMPC算法不仅能综合考虑网联车巡航多目标的特点，同时还满足巡航系统快速性和准确性的要求。最后结合典型驾驶工况，开展智能车的车辆自适应巡航控制实验。实验结果表明，基于MATLAB和Python混合编程的软件系统能有效模拟各种驾驶情景，并能结合智能车验证该自适应巡航控制算法的结果。