Ajax Requests Research Articles

Modular approach to the development of specialized software for remote interaction with respondents using WEB-technologies

The article presents some aspects and results of the development of a prototype software for remote interaction between a researcher and a respondent. The main goal is to ensure the possibility of dynamic adaptation of stimulus material and questionnaires during one session. The structure of the software elements, key requirements for its functionality, software implementation tools and possibilities for further improvement are determined. Key features of the platform's functionality:- six main types of modules for building an experiment or survey;- constructor for modules - instructions, questions, forms;- constructor for scenarios for conducting an experiment or survey;- a database of ready-made scenarios for operational use in remote interaction with the respondent;- the ability to add new functions of interaction with the respondent (complex methods, tasks, etc.) and data analysis tools without the need to install additional software;- timing for each individual module within the experiment or survey scenario;- the ability to monitor the respondent's work in real time. The criteria for choosing the developer's tools were performance and scalability, ease of use, intuitive interface, free and affordable, cross-platform, integration with programming languages, security, and flexibility.We used technologies that provide the user interface and processing of client actions in the browser: HTML (HyperText Markup Language) to create the structure of the web page, CSS (Cascading Style Sheets) for visual design, JavaScript as the main programming language for dynamic interaction on the client side, jQuery framework to simplify the work with the DOM, AJAX requests and other tools. The programming language used to write the server side of a web application is PHP. The software product was tested based on our own marketing research experience and with the involvement of third-party experts.The specific set of research methods and techniques depends on the tasks of the end user, and therefore is not the key issue of this article.Particular attention is paid to the feasibility of integrating some mathematical tools for processing primary data in order to improve the convenience and efficiency of analysis for dynamic adjustment of the research procedure. Software of this type can be useful in various fields of human science: sociology, psychology, economics.

A CNN-ASSISTED DECISION SUPPORT SYSTEM FOR ANCIENT WORLD COIN CLASSIFICATION

The work is devoted to solving the problem of automating the classification of coins from the ancient world. The purpose of the work is to create a neural network model and a system for the classification of ancient coins. The object of research is photographs of coins from ancient cities in the polis of the northern Black Sea region. The subject of research is the process of coin classification. A system architecture, a neural network architecture, and an application for the classification of ancient coins are proposed. The results of the system's operation are demonstrated, and the quality of network training is evaluated. The models were trained using self-generated data samples consisting of sets of color images of coins (200 by 200 resolution) of several types and images of coins that play the role of all other coins and should be classified as not belonging to a given class. The relationship between the ratio of class coins to other coins was also found. For obverse sample 783-7831, 100% accuracy in ten epochs was achieved when the ratio between samples was 1:1, with ratios of 1:4 and 1:7, 30 epochs were required to achieve 100% accuracy. The following technologies were used to implement the Web system: a framework for Python – Django for writing the server part; a JavaScript programming language for writing the user part of the system; and a jQuery library to improve the interaction of the user part with the user. For interaction between the user and the server part of the applications, the AJAX request technology was used, which allows data to be transferred to the server part imperceptibly for the user without reloading the page. Sqlite3 was used as the main application database.

Learning How to Listen: Automatically Finding Bug Patterns in Event-Driven JavaScript APIs

Event-driven programming is widely practiced in the JavaScript community, both on the client side to handle UI events and AJAX requests, and on the server side to accommodate long-running operations such as file or network I/O. Many popular event-based APIs allow event names to be specified as free-form strings without any validation, potentially leading to <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">lost events</i> for which no listener has been registered and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">dead listeners</i> for events that are never emitted. In previous work, Madsen <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">et al.</i> presented a precise static analysis for detecting such problems, but their analysis does not scale because it may require a number of contexts that is exponential in the size of the program. Concentrating on the problem of detecting dead listeners, we present an approach to <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">learn</i> how to use event-based APIs by first mining a large corpus of JavaScript code using a simple static analysis to identify code snippets that register an event listener, and then applying statistical modeling to identify anomalous patterns, which often indicate incorrect API usage. In a large-scale evaluation on 127,531 open-source JavaScript code bases, our technique was able to detect 75 anomalous listener-registration patterns, while maintaining a precision of 90.9% and recall of 7.5% over a validation set, demonstrating that a learning-based approach to detecting event-handling bug patterns is feasible. In an additional experiment, we investigated instances of these patterns in 25 open-source projects, and reported 30 issues to the project maintainers, of which 7 have been confirmed as bugs.

Design of EPICS and Web-Based Remote Control Software of Near-Infrared Sky Brightness Monitor in Antarctica

The Near-infrared Sky Brightness Monitor (NIRBM) aims to measure the middle infrared sky background in Antarctica. The NIRBM mainly consists of an InGaAs detector, a chopper, a reflector, a cooler and a black body. The reflector can rotate to scan the sky with a field of view ranging from 0{\deg} to 180{\deg}. Electromechanical control and weak signal readout functions are accomplished by the same circuit, whose core chip is a STM32F407VG microcontroller. Considering the environment is harsh for humans in Antarctica, a multi-level remote control software system is designed and implemented. A set of EPICS IOCs are developed to control each hardware module independently via serial port communication with the STM32 microcontroller. The tornado web framework and PyEpics are introduced as a combination where PyEpics is used to monitor or change the EPICS Process Variables, functioning as a client for the EPICS framework. Tornado is responsible for the specific operation process of inter-device collaboration, and expose a set of interfaces to users to make calls. Considering the high delay and low bandwidth of the network environment, the tornado back-end is designed as a master-and-agent architecture to improve domestic user experience. The master node is deployed in Antarctic while multiple agent nodes can be deployed domestic. The master and agent nodes communicate with each other through the WebSocket protocol to exchange latest information so that bandwidth is saved. The GUI is implemented in the form of single-page application based on the Vue framework which communicates with tornado through WebSocket and AJAX requests. The web page integrates device control, data curve drawing, alarm display, auto observation and other functions together.

Web-GIS and livestock trace tools for epidemiological surveillance, control and management

Web-GIS and livestock trace tools for epidemiological surveillance, control and management

Implementation of Interactive Real Time Online Co-shopping Using Push AJAX

Abstract Online shopping has witnessed explosive growth: there are hundreds of millions of online shoppers that are part of an online retail industry worth of hundreds of billions of dollars. While online shopping has its own advantages (such as convenience, product reviews, price and selection range), recent focus has been in using technology to mimic the social interactions found in physical shopping malls and stores in what is called as “social shopping”. Put simply, in social shopping shoppers’ friends become involved in the shopping experience. An important aspect of social shopping is “co-shopping” where ad-hoc collaborative shopping groups are formed in which one person can drive an online shopping experience for one or more other people. This requires a mechanism that provisions multiple users to conduct real time online shopping collaboratively from multiple locations. For example, family members at remote locations can view the product online simultaneously as if they are shopping together in real time. To this end we have designed a special collaborative browsing window in which all the co-shoppers need to login. One user becomes the leader and invites others from his friends’ list for shopping. Other users need to accept this invitation and join the shopping. The leader upon liking a product initiates the co-shopping by clicking on “Share this product with selected friends” button. On clicking this button an AJAX request, which contains URL of the product and list of IDs of selected friends, goes to the server. The server receives the URL of the product and list of IDs of friends and pushes this URL to all the selected friends in an asynchronous manner using PUSH AJAX technology. This URL gets loaded into an HTML iFrame on every client's browsing window. Shoppers can communicate with each other using a simple chat window.

Automated browsing in AJAX websites

Web automation applications are widely used for different purposes such as B2B integration, automated testing of web applications or technology and business watch. One crucial part in web automation applications is for them to easily generate and reproduce navigation sequences. This problem is specially complicated in the case of the new breed of AJAX-based websites. Although recently some tools have also addressed the problem, they show some limitations either in usability or their ability to deal with complex websites. In this paper, we propose a set of new techniques to build an automatic web navigation system able to deal with these complexities. Our main contributions are: a new method for recording navigation sequences able to scale to a wider range of events, an algorithm to identify in a change-resilient manner the target element of a user action, and a novel method to detect when the effects caused by a user action (including the effects of scripting code and AJAX requests) have finished. In addition, we have also tested our approach with a high number of real web sources and have compared it with other relevant web automation tools obtaining very good results.