Samply: A user-friendly smartphone app and web-based means of scheduling and sending mobile notifications for experience-sampling research

Undertaking an experience-sampling study via smartphones is complex. Scheduling and sending mobile notifications often requires the use of proprietary software that imposes limits on participants’ operating systems (whether iOS or Android) or the types of questions that can be asked via the application. We have developed an open-source platform—Samply—which overcomes these limitations. Researchers can access the entire interface via a browser, manage studies, schedule and send notifications linking to online surveys or experiments created in any Internet-based service or software, and monitor participants' responses—all without the coding skills usually needed to program a native mobile application. Participants can download the Samply Research mobile application for free from Google Play or the App Store, join a specific study, receive notifications and web links to surveys or experiments, and track their involvement. The mobile application leverages the power of the React Native JavaScript library, which allows it to be rendered in the native code of Android and iOS mobile operating systems. We describe Samply, provide a step-by-step example of conducting an experience-sampling study, and present the results of two validation studies. Study 1 demonstrates how we improved the website’s usability for researchers. Study 2 validates the mobile application’s data recording ability by analyzing a survey’s participation rate. The application’s possible limitations and how mobile device settings might affect its reliability are discussed.

Android App Development: A Review

Android is a software stack for mobile devices that includes an operating system, middleware, and key applications. Android is a software platform and operating system for mobile devices based on the Linux operating system and developed by Google and the Open Handset Alliance. It allows developers to write managed code in a Java-like language that utilizes Google-developed Java libraries but does not support programs developed in native code. The unveiling of the Android platform on 5 November 2007 was announced with the founding of the Open Handset Alliance, a consortium of 34 hard-ware, software and telecom companies devoted to advancing open standards for mobile devices. When released in 2008, most of the Android platform will be made available under the Apache free-software and open-source license.

Readable and efficient HEP data analysis with bamboo

With the LHC continuing to collect more data and experimental analyses becoming increasingly complex, tools to efficiently develop and execute these analyses are essential. The bamboo framework defines a domain-specific language, embedded in python, that allows to concisely express the analysis logic in a functional style. The implementation based on ROOT’s RDataFrame and cling C++ JIT compiler approaches the performance of dedicated native code. Bamboo is currently being used for several CMS Run 2 analyses that rely on the NanoAOD data format, which will become more common in Run 3 and beyond, and for which many reusable components are included, but it provides many possibilities for customisation, which allow for straightforward adaptation to other formats and workflows.

Evolution of Malware in the Digital Transformation Age

As corporations are stepping into the new digital transformation age and adopting leading-edge technologies such as cloud, mobile, and big data, it becomes crucial for them to contemplate the risks and rewards of this adoption. At the same time, the new wave of malware attacks is posing a severe impediment in implementing these technologies. This chapter discusses some of the complications, challenges, and issues plaguing current malware analysis and detection techniques. Some of the key challenges discussed are automation, native code, obfuscations, morphing, and anti-reverse engineering. Solutions and recommendations are provided to solve some of these challenges. To stimulate further research in this thriving area, the authors highlight some promising future research directions. The authors believe that this chapter provides an auspicious basis for future researchers who intend to know more about the evolution of malware and will act as a motivation for enhancing the current and developing the new techniques for malware analysis and detection.

Scenarios to use React Native, native code or integrate both technologies

En los últimos años, diferentes técnicas y frameworks han surgido con el fin de proveer una solución para crear aplicaciones cross-platform. El objetivo es desarrollar un solo código que puede ser desplegado en diferentes sistemas operativos y proveer una experiencia completamente nativa. Desde 2015, React Native ha sido promocionado como una opción para desarrollar aplicaciones móviles con el objetivo de escribir el código una sola vez y desplegarlo en cualquier plataforma perfectamente. Al momento no hay otra librería JavaScript que permita el desarrollo de aplicaciones móviles nativas. Este trabajo realiza un análisis experimental con una visión imparcial, basada en la experiencia del desarrollo de aplicaciones móviles utilizando React Native y código nativo. Analiza varios escenarios para elegir analíticamente código nativo, React Native o una combinación de ambos para desarrollar una aplicación móvil. Algunas conclusiones encontradas sostienen que la elección de la tecnología depende de la naturaleza del proyecto, tiempo, presupuesto, experiencia del equipo de desarrollo y los requerimientos de la aplicación.