Distributed sensor-driven web applications through multi-device usage patterns

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Multi-Threaded Actors

In this paper we introduce a new programming model of multi-threaded actors which feature the parallel processing of their messages. In this model an actor consists of a group of active objects which share a message queue. We provide a formal operational semantics, and a description of a Java-based implementation for the basic programming abstractions describing multi-threaded actors. Finally, we evaluate our proposal by means of an example application.Comment: In Proceedings ICE 2016, arXiv:1608.0313

Before-Commit Client State Management Services for AJAX Applications

Heavily script-based browser applications change the manner in which users interact with Web browsers. Instead of downloading a succession of HTML pages, users download a single application and use that application for a long period of time. The application is not a set of HTML pages, but rather a single page that can possible modify its own presentation based on data exchanged with a server. In such an environment, it is necessary to provide some means for the client to manage its own state. We describe the initial results of our work in providing client-side state management services for these script-based applications. We focus on browser-based services that can help the user before any data is committed on the server. Our services include state checkpointing, property binding, operation logging, operational replay, ATOM/RSS data updates, and application-controlled persistence

Accessible user interface support for multi-device ubiquitous applications: architectural modifiability considerations

The market for personal computing devices is rapidly expanding from PC, to mobile, home entertainment systems, and even the automotive industry. When developing software targeting such ubiquitous devices, the balance between development costs and market coverage has turned out to be a challenging issue. With the rise of Web technology and the Internet of things, ubiquitous applications have become a reality. Nonetheless, the diversity of presentation and interaction modalities still drastically limit the number of targetable devices and the accessibility toward end users. This paper presents webinos, a multi-device application middleware platform founded on the Future Internet infrastructure. Hereto, the platform's architectural modifiability considerations are described and evaluated as a generic enabler for supporting applications, which are executed in ubiquitous computing environments

Abmash: Mashing Up Legacy Web Applications by Automated Imitation of Human Actions

Many business web-based applications do not offer applications programming interfaces (APIs) to enable other applications to access their data and functions in a programmatic manner. This makes their composition difficult (for instance to synchronize data between two applications). To address this challenge, this paper presents Abmash, an approach to facilitate the integration of such legacy web applications by automatically imitating human interactions with them. By automatically interacting with the graphical user interface (GUI) of web applications, the system supports all forms of integrations including bi-directional interactions and is able to interact with AJAX-based applications. Furthermore, the integration programs are easy to write since they deal with end-user, visual user-interface elements. The integration code is simple enough to be called a "mashup".Comment: Software: Practice and Experience (2013)

Evaluation of Progressive Web Application to develop an Offline-First Task Management App

Adding more features to web apps progressively to feel and work like native apps is a recent design philosophy. This research study was conducted on Progressive Web Apps (PWAs) to develop an offline-first task management app. The main idea of Pmain goalancing web apps gradually by adding new features to existing or new web applicenable developersowser support. Hence, the main goal of this study was to explore PWAs features available in the browsers,thoroughly reviewe developers to implement an offline-first web applications. The study was carried out in two ways. The first part thoroughly reviewed theories about the web, native apps, and PWAs features that are available in browsers. An the thesisst task management app called Annual Clock was designed and implemented for Aalto universThe applicationd part of the thesis. To implement the app, React.js was used for the frontthe end and Node.js for the baa ckend. The application was fully impthe lemented using most PWA features to work offline, install on home screen, load fast, send push notification, etc. To conclude, the implemented app presents solutions to most offline-first web app problems and will be used as a valuable reference for the university and other researchers who would like to develop an offline-first PWAs. Nonetheless, there are many areas left untouched and need to be solved in the future like saving images, audios and videos in browser storage, increasing the size of browser storages for large data and background synchronization support by all browsers

Organized Behavior Classification of Tweet Sets using Supervised Learning Methods

During the 2016 US elections Twitter experienced unprecedented levels of propaganda and fake news through the collaboration of bots and hired persons, the ramifications of which are still being debated. This work proposes an approach to identify the presence of organized behavior in tweets. The Random Forest, Support Vector Machine, and Logistic Regression algorithms are each used to train a model with a data set of 850 records consisting of 299 features extracted from tweets gathered during the 2016 US presidential election. The features represent user and temporal synchronization characteristics to capture coordinated behavior. These models are trained to classify tweet sets among the categories: organic vs organized, political vs non-political, and pro-Trump vs pro-Hillary vs neither. The random forest algorithm performs better with greater than 95% average accuracy and f-measure scores for each category. The most valuable features for classification are identified as user based features, with media use and marking tweets as favorite to be the most dominant.Comment: 51 pages, 5 figure