JavaScript Code Research Articles

SPECTRAL: AWESOME SPECTRAL INDICES DEPLOYED VIA THE GOOGLE EARTH ENGINE JAVASCRIPT API

Abstract. Spectral Indices derived from Remote Sensing (RS) data are widely used for characterizing Earth System dynamics. The increasing amount of spectral indices led to the creation of spectral indices catalogues, such as the Awesome Spectral Indices (ASI) ecosystem. Google Earth Engine (GEE) is a cloud-based geospatial processing service with an Application Programming Interface (API) that is accessible through JavaScript (Code Editor) and Python. Tools for computing indices, including raster operations, normalized differences, and expression evaluation methods have been developed in the API. However, users still have to hard-code spectral indices for the JavaScript library since there are no implementations that link catalogues of spectral indices to the Code Editor. Here we present spectral, a module that links the Awesome Spectral Indices (ASI) catalogue to GEE for querying and computing spectral indices inside the Code Editor. The module allows accessing and computing spectral indices from the catalogue for multiple remote sensing products in GEE. All indices can be queried by using a key-value model and computed by using a single method. The module demonstrates that spectral indices can be easily computed inside the Code Editor. Image and Image Collection objects can be used for the calculation of all spectral indices in the catalogue if the specific dataset counts with the required bands. We anticipate that spectral will be used by most GEE users for Earth System research. Analyses conducted by the community will be sped up by avoiding hard-coding and RS investigations will be boosted.

Commodity Information Collection and System Construction of e-Commerce Platform Based on Network Data

In order to quickly and accurately collect the massive commodities and corresponding transaction data of large-scale e-commerce platforms, and improve the ability of data analysis and mining, this paper proposes a platform commodity information collection system based on splash technology. The system prerenders the javascript code in the product page, combined with the Scrapy crawler framework, to realize a system that quickly and effectively collects product data from different platforms, and uses “mobile phone” as the retrieval keyword to verify the designed system, respectively. The experimental results show that the system can effectively collect up to 60,000 comments and 6,000 system requests. Conclusion. The platform commodity information collection system based on splash technology has certain application value and promotion for the commodity data collection of different platforms of e-commerce.

Detection of Obfuscated Malicious JavaScript Code

Websites on the Internet are becoming increasingly vulnerable to malicious JavaScript code because of its strong impact and dramatic effect. Numerous recent cyberattacks use JavaScript vulnerabilities, and in some cases employ obfuscation to conceal their malice and elude detection. To secure Internet users, an adequate intrusion-detection system (IDS) for malicious JavaScript must be developed. This paper proposes an automatic IDS of obfuscated JavaScript that employs several features and machine-learning techniques that effectively distinguish malicious and benign JavaScript codes. We also present a new set of features, which can detect obfuscation in JavaScript. The features are selected based on identifying obfuscation, a popular method to bypass conventional malware detection systems. The performance of the suggested approach has been tested on JavaScript obfuscation attacks. The studies have shown that IDS based on selected features has a detection rate of 94% for malicious samples and 81% for benign samples within the dimension of the feature vector of 60.

An Online Integrated Development Environment (IDE) by using Lightweight Framework Render Studio

The task plans to work with an internet based IDE utilizing web advancements. We had numerous internet based IDE's for other programming dialects like C, Python, and so on. Thus, we intended to plan an internet based IDE for Web advancements and named it as "Render Studio". It is predominantly for amateurs. The Render Studio gives you a spotless connection point to the execution of the HTML code, CSS code, and JavaScript code all the while, which gives you a moment result and helps in decreasing the existence intricacy. IDE is the Integrated Development Environment which gives the climate to execute a specific program of any language. One point of the IDE is to lessen the setup important to sort out numerous improvement utilities. All things considered, it gives similar arrangement of abilities as one strong unit. Decreasing arrangement time can increment engineer efficiency, particularly in situations where figuring out how to utilize the IDE is quicker than physically coordinating and realizing the singular apparatuses in general. More tight joining of all advancement errands can possibly work on by and large efficiency past assisting with arrangement assignments. On the web or electronic IDE is a web-based compiler which permits you to aggregate source code and execute it online in more than one language. The product will order the program and return the result to the client.

An Approach for Malicious JavaScript Detection Using Adaptive Taylor Harris Hawks Optimization-Based Deep Convolutional Neural Network

JavaScript has to become a pervasive web technology that facilitates interactive and dynamic Web sites. The extensive usage and the properties permit the authors to simply obfuscate the code and make JavaScript an interesting place for hackers. JavaScript is usually used for adding functionalities and improving the usage of web applications. Despite several merits and usages of JavaScript, the major issue is that several recent cyber-attacks like drive-by-download attacks utilized the susceptibility of JavaScript codes. This paper devises a novel technique for detecting malicious JavaScript. Here, JavaScript codes are fed to the feature extraction phase for extracting the noteworthy features that include execution time, function calls, conditional statements, break statements, and Boolean. The extracted features are further subjected to data transformation wherein log transformation is adapted to normalize the data. Then, feature selection is performed using mutual information.

Towards enhanced PDF maldocs detection with feature engineering: design challenges

In this paper, we perform an in-depth analysis of a large corpus of PDF maldocs to identify the key set of significantly important features and help in maldoc detection. Existing industry-based tools for the detection are inefficient and cannot prevent PDF maldocs because they are generic and depend primarily on a signature-based approach. Besides, several other methods developed by academics suffer heavily from reduced effectiveness. The feature-set using machine learning classifiers is prone to various known attacks, such as mimicry and parser confusion. Also, we discover that increasingly more malicious files i) contain evasive and obfuscated JavaScript code, ii) include hidden contents (mostly outside the objects), iii) have a corrupted document structure, and iv) usually contain short JavaScript code blocks. We utilise maldoc attacks’ evolution over a decade to highlight the essential features (e.g., concept drifts) that impact detectors and classifiers.

Benefits and Challenges of Using NodeJS

Node.js, the JavaScript runtime environment is very popular among Full Stack Developers for building Web applications. It gives the developer to write server-side code in JavaScript and able to manage both client and server side. Node.js ensures outstanding performance, it applies event-driven, non-blocking input output and asynchronous paradigm. The study is based on benefits and challenges of using Node.js. The results of study are from comparing different web development programming languages with JavaScript which is used in Node.js. And in the end some suggestions on how to improve those areas and make it more feasible.

An Empirical Study on Rule Violation History of JavaScript Code Blocks on Stack Overflow

JavaScript code blocks on Stack Overflow (SO) are often used in software projects. However, little is known about the issue of rule violation risk in SO JavaScript code blocks. Rule violation is one of the factors which degrades the quality of Java Script code. To prevent prevalence of rule violation by reusing SO JavaScript code blocks, it is needed to investigate how secure SO JavaScript code blocks are against rule violation. To examine the issue, we performed a quantitative analysis to investigate how many rule violations are, when first rule violation occurs and what is the trend of rule violations in evolution history of Stack Overflow JavaScript code blocks. We collected SO posts related to JavaScript and extracted the code blocks contained in the posts. By using ESLint, the most popular rule violation detection tool, we identified rule violations in the evolution history of our target code blocks. We then performed quantitative analyses on the identified rule violations. As the results of the analyses, we found that: (1) 60% of the studied code blocks evolve with any rule violations. (2) In the rule violated code blocks, 92% of the code blocks get first rule violation occurrence in the early phase of their evolution. (3) 80% of the rule violated code blocks never fix existing rule violations during their evolution. Our findings suggest that SO should provide a policy which can reduce rule violations in submitted JavaScript code blocks. The findings can also make SO users attend to rule violations when reusing SO JavaScript code blocks.

Implementation of Android Application In React-Native: Daily Dairy

Abstract: This paper describes the whole process of android application development using the react-native framework and firebase of google and developed the application “DailyDairy''. The Application is developed for medium-sized and digitally illiterate dairy farmers. The software is divided into milk distribution management and payment transactions, statistics and analysis can be a variety of technical data to analyze, synthesize, organize, and the User Interface is practical, economic, and user-friendly. This application also solves the differences between Vendor and his Customers. This paper also describes the integration of firebase firestore (database provided by google) with android application development with javascript framework react-native and code editor used in is visual studio code by Microsoft. Keywords: Dairy Management, Android application, Vendor, Customer, Milk, Dairy Farmer, Digital Literacy

NFC Based Login for Mobile Apps and Websites

Abstract: This paper is concerned to show how a mobile phone equipped with Near Field Communication (NFC) can be used to construct a Single Sign-On authentication system (Celikkan & Gelis, 2014, August). When logging in to numerous online sites, customers no longer have to juggle a plethora of usernames and passwords to keep track of. As omnipresent computing devices, smartphones are utilised for a wide range of functions, from authentication to tracking to medical care to entertainment and epayment. Among NFC's many advantages is that it uses short-range communication, which enhances security while also making it simple to use. Our Chrome browser extension allows users to easily authenticate and manage their personal information from their mobile devices. Owing to browser security restrictions, JavaScript code (used in the Google Chrome extension) cannot access computer system resources when executing in a browser. As a result, the Java applet is used to run the software on the user's computer. With the help of the extension, NFC Reader may be accessed and used, and a connection between Java and JavaScript can be established. Using NFC, the user does not have to input any account information because it is automatically uploaded to the online login page. IndexTerms: NFC, Login, Mobile apps , website, RFID , Authentication, Sign-in

Integrating web applications into popular survey platforms for online experiments.

Research using custom-made web applications is burgeoning as scholars increasingly conduct their experiments online. We show how researchers can integrate their web applications into popular survey software such as Qualtrics in five simple steps and provide the full JavaScript code and screenshots. This procedure allows participants to seamlessly switch from Qualtrics to their web applications without leaving the survey platform. This integration has two benefits: (1) it eliminates the risk that participants inadvertently drop out of the survey while switching from the survey software to the web application and vice versa; and (2) it saves researchers the fees charged by survey companies to host an external link on the survey platform. Hence, we make it easier to conduct research on targeted (e.g., national) samples using web applications.

You Don't Need an App-Conducting Mobile Smoking Research Using a Qualtrics-Based Approach.

With the increasing availability of smartphones, many tobacco researchers are exploring smartphone-delivered mobile smoking interventions as a disseminable means of treatment. Most effort has been focused on the development of smartphone applications (apps) to conduct mobile smoking research to implement and validate these interventions. However, developing project-specific smartphone apps that work across multiple mobile platforms (e.g., iOS and Android) can be costly and time-consuming. Here, using a hypothetical study, we present an alternate approach to demonstrate how mobile smoking cessation and outcome evaluation can be conducted without the need of a dedicated app. Our approach uses the Qualtrics platform, a popular online survey host that is used under license by many academic institutions. This platform allows researchers to conduct device-agnostic screening, consenting, and administration of questionnaires through Qualtrics's native survey engine. Researchers can also collect ecological momentary assessment data using text messaging prompts with the incorporation of Amazon Web Services' Pinpoint. Besides these assessment capabilities, Qualtrics has the potential for delivering personalized behavioral interventions through the use of JavaScript code. By customizing the question's web elements in Qualtrics (e.g., using texts, images, videos, and buttons), researchers can integrate interactive web-based interventions and complicated behavioral and cognitive tasks into the survey. In conclusion, this Qualtrics-based methodology represents a novel and cost-effective approach for conducting mobile smoking cessation and assessment research.

A graphical front-end interface for React.js considering state-transition diagrams

We present a graphical front-end interface for creating dynamical web pages by means of React.js. Its user does not have to write JavaScript codes for specifying the dynamical behaviour of the web components but has only to draw state-transition diagrams graphically on the developed graphical editor. Using the graphical editor, the user draws a state-transition diagram that specifies the dynamical behaviour of each web component in terms of circles representing the states of the component and arrows representing the conditional transitions among the states. Then, the developed translator converts the state-transition diagrams into web components of React.js in JavaScript that constitute the target web page. This system of the graphical editor and the translator enables general users without knowledge and experiences in programming to create dynamical web pages. Aspiring programmers may start learning JavaScript and React.js by comparing their diagrams and the translated JavaScript codes.

Webmapping of Floods in the West of the Ivorian Coast

To provide answers to the problem of the management of its coastal zone, Côte d’Ivoire has initiated a pooling of data collected on the coast to feed its environmental information management system. To this end, it was a question of creating an interactive platform for decision support for the development of this coastal zone. To achieve this objective, high spatial resolution raster data from 15 to 90 m from the Shuttle Radar Topography Mission and land cover vector data from 2017 were collected for processing in Websig software (QGIS 3.4, PostGreSql 10.5, PostGIS), published and displayed in Geoserveur for programming HTML, CSS and JavaScript codes in Atom. The results first made it possible to visualize the main issues in the interface, in particular, the rivers, the classified forests, the degraded forests, the intact forests, the housing and the industrial plantations and then to assess the risks of floods in Sassandra and San-Pédro. For overflow hazards 100 m beyond the shore, it is the houses, part of the forests and some bare soil that are submerged. As for the risks of overflowing 200 to 500 m beyond the shore, it is a large part of the housing, soils and intact forests that will be flooded. This tool must be made available to the final beneficiaries (users) by putting it online and listing it in the main search engines.

Wróżenie z tekstonów. Przekład dystrybutywny na przykładzie generatora Sea and Spar Between (2010) Stephanie Strickland i Nicka Montforta

Texton Telling. Distributed Translation Based on Stephanie Strickland and Nick Montfort’s Sea and Spar Between Generator (2010) The article presents challenges of translating poetry generators in multi-authorial, creative collaboration and within the context of understanding text as process. Stephanie Strickland and Nick Montfort’s Sea and Spar Between is in many respects a translational challenge that in some languages might seem an impossible task. Polish, our target language, imposes some serious constraints: one-syllable words become disyllabic or multisyllabic; kennings have different morphological, lexical, and grammatical arrangement, and most of the generative rhetoric of the original (like anaphors) must take into consideration the grammatical gender of Polish words. As a result, the JavaScript code, instructions that accompany the JavaScript file, and arrays of words that this poetry generator draws from, needed to be expanded and rewritten. Moreover, in several crucial points of this rule-driven work, natural language forced us to modify the code. In translating Sea and Spar Between, the process of negotiation between the source language and the target language involves more factors than in the case of traditional translation. Strickland and Montfort read Dickinson and Melville and parse their readings into a computer program (in itself a translation, or port, from Python to JavaScript) which combines them in almost countless ways. This collision of cultures, languages, and tools becomes amplified if one wants to transpose it into a different language. This transposition involves the original authors of Sea and Spar Between, the four original translators of Dickinson and Melville into Polish, and us, turning into a multilayered translational challenge, something we propose to call a distributed translation. While testing the language and the potential of poetry translation in the digital age, the experiment – we hope – has produced some fascinating and thought-provoking poetry.

Программное извлечение данных из word-документов на основе ситуационно-ориентированного подхода

The article discusses the use of situation-oriented approach to software processing word-documents. The documents under consideration are prepared by the user in the environment of the Microsoft Word processor or its analogs and are used in the future as data sources. The openness of the Office Open XML and Open Document Format made it possible to apply the concept of virtual documents mapped to ZIP archives for programmatic access to XML components of word documents in a situational environment. The importance of developing preliminary agreements regarding the placement of information in the document for subsequent search and retrieval, for example, using pre-prepared templates, is substantiated. For the DOCX and ODT formats, the article discusses the use of key phrases, bookmarks, content controls, custom XML components to organize the extraction of entered data. For each option, tree-like models of access to the extracted data, as well as the corresponding XPath expressions, are built. It is noted that the use of one or another option depends on the functionality and limitations of the word processor and is characterized by varying complexity of developing a blank template, entering data by the user and programming data extraction. The applied solution is based on entering metadata into the article using content controls placed in a stub template and bound to elements of a custom XML component. The developed hierarchical situational model of HSM provides extraction of an XML component, loading it into a DOM object and XSLT transformations to obtain the resulting data: an error report and JavaScript code for subsequent use of the extracted metadata.

Detecting Web-Based Attacks with SHAP and Tree Ensemble Machine Learning Methods

Attacks using Uniform Resource Locators (URLs) and their JavaScript (JS) code content to perpetrate malicious activities on the Internet are rampant and continuously evolving. Methods such as blocklisting, client honeypots, domain reputation inspection, and heuristic and signature-based systems are used to detect these malicious activities. Recently, machine learning approaches have been proposed; however, challenges still exist. First, blocklist systems are easily evaded by new URLs and JS code content, obfuscation, fast-flux, cloaking, and URL shortening. Second, heuristic and signature-based systems do not generalize well to zero-day attacks. Third, the Domain Name System allows cybercriminals to easily migrate their malicious servers to hide their Internet protocol addresses behind domain names. Finally, crafting fully representative features is challenging, even for domain experts. This study proposes a feature selection and classification approach for malicious JS code content using Shapley additive explanations and tree ensemble methods. The JS code features are obtained from the Abstract Syntax Tree form of the JS code, sample JS attack codes, and association rule mining. The malicious and benign JS code datasets obtained from Hynek Petrak and the Majestic Million Service were used for performance evaluation. We compared the performance of the proposed method to those of other feature selection methods in the task of malicious JS code content detection. With a recall of 0.9989, our experimental results show that the proposed approach is a better prediction model.

Malicious Javascript Detection based on Clustering Techniques

Malicious JavaScript code is still a problem for website and web users. The complication and equivocation of this code make the detection which is based on signatures of antivirus programs becomes ineffective. So far, the alternative methods using machine learning have achieved encouraging results, and have detected malicious JavaScript code with high accuracy. However, according to the supervised learning method, the models, which are introduced, depend on the number of labeled symbols and require significant computational resources to activate. The rapid growth of malicious JavaScript is a real challenge to the solutions based on supervised learning due to the lacking of experience in detecting new forms of malicious JavaScript code. In this paper, we deal with the challenge by the method of detecting malicious JavaScript based on clustering techniques. The known symbols that will be analyzed, the characteristics which are extracted, and a detection processing technique applied on output clusters are included in the model. This method is not computationally complicated, as well as the typical case experiments gave positive results; specifically, it has detected new forms of malicious JavaScript code.

Development of interactive biological web applications with R/Shiny.

Development of interactive web applications to deposit, visualize and analyze biological datasets is a major subject of bioinformatics. R is a programming language for data science, which is also one of the most popular languages used in biological data analysis and bioinformatics. However, building interactive web applications was a great challenge for R users before the Shiny package was developed by the RStudio company in 2012. By compiling R code into HTML, CSS and JavaScript code, Shiny has made it incredibly easy to build web applications for the large R community in bioinformatics and for even non-programmers. Over 470 biological web applications have been developed with R/Shiny up to now. To further promote the utilization of R/Shiny, we reviewed the development of biological web applications with R/Shiny, including eminent biological web applications built with R/Shiny, basic steps to build an R/Shiny application, commonly used R packages to build the interface and server of R/Shiny applications, deployment of R/Shiny applications in the cloud and online resources for R/Shiny.

Decision Making Support System for Managing Advertisers By Ad Fraud Detection

Abstract Efficient lead management allows substantially enhancing online channel marketing programs. In the paper, we classify website traffic into human- and bot-origin ones. We use feedforward neural networks with embedding layers. Moreover, we use one-hot encoding for categorical data. The data of mouse clicks come from seven large retail stores and the data of lead classification from three financial institutions. The data are collected by a JavaScript code embedded into HTML pages. The three proposed models achieved relatively high accuracy in detecting artificially generated traffic.