Python Technology Research Articles

The Spatial Structure and Evolution Educational Anxiety—Research on Provincial Panel Based on Big Data Search

This research uses Python technology to obtain the daily Baidu index data of 175 groups of relevant vocabulary, such as “education and training” in 31 provinces and cities from 2011 to 2020. Using Baidu search index to construct a data model of “education anxiety” total index and macro variables, it explores the temporal and spatial distribution and regional characteristics of education anxiety in various provinces in China. Research shows that at the regional level, the level of educational anxiety in East China, Central South, and North China is relatively high, and it has further increased over time, and the level of educational anxiety in Southeast, Northeast and Northwest regions is also gradually increasing. At the provincial level: by 2020, 15 provinces will enter the high level of education anxiety, and the level of education anxiety in other provinces will also increase significantly. The fixed effect model found that factors such as provincial GDP, urbanization rate, and education expenditure have statistically significant effects on “education anxiety”. Based on this, policy recommendations for alleviating education anxiety are put forward.

Analysis of China Fund customer complaint based on High frequency data mining using Python technology

Analysis of China Fund customer complaint based on High frequency data mining using Python technology

A NOVEL FRAMEWORK FOR PRIVACY-PRESERVING USING DATA AGGREGATION IN INTERNET OF THINGS (IOT)

Today with the development of Internet of Things (IoT) technology its security and privacy becomes very much essential because this technology provide the facility for accessing the devices or resources from anywhere and anytime. For providing the security and privacy to IoT various technology has been developed but in this we propose data aggregation mechanism in which it uses one-time pad and symmetric key to make our data secure and preserve the privacy of it. This mechanism takes less computation time, improve processing speed and also require less cost in implementation. The implementation of proposed approach is done in widely used Python technology which produce better results. In last the proposed mechanism provide more security and preserve our data.

Male and Female Users' Differences in Online Technology Community Based on Text Mining.

With the emergence of online communities, more and more people are participating in online technology communities to meet personalized learning needs. This study aims to investigate whether and how male and female users behave differently in online technology communities. Using text data from the Python Technology Community, through the LDA (Latent Dirichlet Allocation) model, sentiment analysis, and regression analysis, this paper reveals the different topics of male and female users in the online technology community, their sentimental tendencies and activity under different topics, and their correlation and mutual influence. The results show the following: (1) Male users tend to provide information help, while female users prefer to participate in the topic of making friends and advertising. (2) When communicating in the technology community, male and female users mostly express positive emotions, but female users express positive emotions more frequently. (3) Different emotional tendencies of male and female users under different topics have different effects on their activity in the community. The activity of female users is more susceptible to emotional orientation.

Symmetry Analysis in Analyzing Cognitive and Emotional Attitudes for Tourism Consumers by Applying Artificial Intelligence Python Technology

Symmetries play very important roles in the analysis of cognitive and emotional attitudes. The analysis with Python technology, including optimized artificial intelligence technology, is designed on the basis of symmetry principles. Destination image perception as a branch of destination image research is of great significance to tourists’ decision-making and destination image building. Ice-snow tourism is a hot topic nowadays, and research on perceptions of images of ice-snow tourism has become a focus. In this paper, python programming was used to crawl online travel journals and reviews about Jilin province’s ice-snow tourism on the Internet to analyze the frequency of frequently used words, their classification, word cloud and co-occurrence network, and other aspects of image perception, and proceed to the emotional perception of and emotional attitude to the emotional images and an overall image analysis. The study found that: (1) Perceptions of images of ice-snow tourism can be divided into five categories: tourism attractions, tourism activities, tourism facilities, tourism features and the tourism service environment. The frequency of tourism attractions is the highest, followed by tourism facilities and the tourism service environment. “Changbai Mountain” and “rime” are the core words, that is, tourists are most impressed by the scenic spot and landscape of “Changbai Mountain and rime.” (2) Positive emotional expressions accounted for 67.23% of perceptions of images of ice-snow tourism. Tourists gave a positive evaluation for Changbai Mountain, the snow landscape of Tianchi and skiing facilities. Meanwhile, passive emotional expressions accounted for 21.07% and tourists gave passive evaluations for travel, transportation, accommodation and catering. (3) Tourists spoke highly of overall images of ice-snow tourism in Jilin Province but few were willing to revisit. In the conclusion, strategies are put forward to improve image perceptions of ice-snow tourism and promote the sustainable development of ice and snow tourism.

Analysis of the Collaboration that Is Produced in Online Learning Using Python Technology

Universities and institutions began to create their virtual campuses by using eLearning platforms whether commercial or not. Within these, it has highlighted among other tools instead of the didactic forums where students among themselves and students and teaching teams could discuss and in general build knowledge within a collaborative context. The data coming from these forums have been analyzed, with different techniques, and have allowed obtaining some very interesting conclusions. However, in recent academic years there is a clear trend of migration of collaborative work that previously occurred in the forums to social networks and mobiles. This poses a problem since these tools are not coordinated by the teaching teams. A preliminary work analyzes this trend and points out the consequences to which it may give rise. The present work exposes a methodology to automate the information obtained from Facebook working group, which have been designed by the students themselves.

PyWPS: overview, new features in version 4 and existing implementations

PyWPS 4 is a re–make of the Python implementation of the WPS standard. It is the result of the work of over a dozen individual contributors, during a period of almost three years. One of the goals driving this re–implementation was to embrace modern Python technologies and the possibilities they open.This technical note reviews some of the more advanced possibilities this new PyWPS implementation opens. Request activity is now logged into a structured database, relying on a generic Object–Relational Mapping engine. The adoption of WSGI (Web Server Gateway Interface) opens new ways for load balancing request execution and application encapsulation, that are exemplified with modern Python technologies. Furthermore, PyWPS 4 is designed with containerisation in mind, expediting both development and deployment and improving security.

Development of ERP Financial Statement Evaluation System

With the sustained development of national economy, more and more enterprises begin to transform to informatization. As an important part of enterprise informatization, ERP (Enterprise Resource Planning) makes the demand for ERP talents growing day by day. However, there are many problems in the existing ERP examination system, such as large workload, difficult to guarantee the quality of question-making, low quality of automatic marking. In financial statements, a unit grid of financial statements has both formulas and data. At present, there is no system to evaluate the formulas, which creates great difficult for automatic setting questions and marking. These problems seriously affect the quality and efficiency of enterprise’s talent selection for ERP financial statements. This system is based on Yonyou ERP financial statement module, using MVC framework, C#, SQL Server and python technology to develop ERP financial statement skills evaluation system, which mainly solves the problem that it could not automatically generate test papers and mark the papers in financial statement evaluation system at present.

Hashtag Generator and Content Authenticator

In the recent past, Online Marketing applications have been a focus of research. But still there are enormous challenges on the accuracy and authenticity of the content posted through social media. And if the social media business platforms are considered, majority of the users who try to add a market value to their own product face the problem of not getting enough attention from their target audience. The purpose of this research is to develop a safe and efficient trending hashtag generating application solution for social media business users which generates trending and relevant hashtags for user content in order to get a broad reach of target audience, automatically generates a meaningful caption to their relevant posts and guarantees the authenticity of the product at the same time. The user content is analyzed and filters the important keywords, generates a meaningful caption, suggest related trending keywords and generates trending hashtags to get the required reach for online marketers. Additionally, the marketing products’ content authentication is ensured. The application uses Natural Language Processing, Machine Learning, API technologies, Java and Python technologies. A unique database is assigned to users which contains rankings for each user. The target audience who engages in buying products get to know about the status of the sellers with respect to authenticity of the content. It is believed that the application provides a promising solution to existing audience reach problems of online marketers and buyers. The significance of this system is to help marketers and buyers to engage in online buying and selling with much effective, reliable and safer ways. This mitigate the vulnerability of bad social media marketing influences and helps to establish a safe and reliable online marketing practice to make both sellers and buyers happy. This paper provides a brief description on how to perform an organized online marketing discipline via the Trending Hashtag Generator & Image Authenticator application.

Use of EPICS and Python technology for the development of a computational toolkit for high heat flux testing of plasma facing components

The high heat flux testing and characterization of the divertor and first wall components are a challenging engineering problem of a tokamak. These components are subject to steady state and transient heat load of high magnitude. Therefore, the accurate prediction and control of the cooling parameters is crucial to prevent burnout. The prediction of the cooling parameters is based on the numerical solution of the critical heat flux (CHF) model. In a test facility for high heat flux testing of plasma facing components (PFC), the integration of computations and experimental control is an essential requirement. Experimental physics and industrial control system (EPICS) provides powerful tools for steering controls, data simulation, hardware interfacing and wider usability. Python provides an open source alternative for numerical computations and scripting. We have integrated these two open source technologies to develop a graphical software for a typical high heat flux experiment. The implementation uses EPICS based tools namely IOC (I/O controller) server, control system studio (CSS) and Python based tools namely Numpy, Scipy, Matplotlib and NOSE. EPICS and Python are integrated using PyEpics library. This toolkit is currently under operation at high heat flux test facility at Institute for Plasma Research (IPR) and is also useful for the experimental labs working in the similar research areas. The paper reports the software architectural design, implementation tools and rationale for their selection, test and validation.

Bluetooth Based Automatic Hotel Service System Using Python

This paper describes a Bluetooth based automatic hotel service system. This paper describes the protocol and provides the implementation details. Nowadays hotels are spending lot of money for the attendance, tracking of the employees and apart from that, there is no fully satisfied service for customers. Instead of using manual power if we apply Bluetooth technology, then the proposed system will cut off the daily wages of hotels. We hope that the implementation and protocol details will aid the wireless technology community in near future. Index: Bluetooth, Python Technology, Arduino.