Catalogue Search | MBRL
Are you sure you want to remove the book from the shelf?
{{itemTitle}}
2,231
result(s) for
"Android"
Sort by:
Android Studio Giraffe Essentials - Kotlin Edition: Developing Android Apps Using Android Studio 2022.3.1 and Kotlin
Fully updated for Android Studio Giraffe and the new UI, this book teaches you how to develop Android-based applications using the Kotlin programming language.This book begins with the basics and outlines how to set up an Android development and testing environment, followed by an introduction to programming in Kotlin, including data types, control flow, functions, lambdas, and object-oriented programming. Asynchronous programming using Kotlin coroutines and flow is also covered in detail.Chapters also cover the Android Architecture Components, including view models, lifecycle management, Room database access, the Database Inspector, app navigation, live data, and data binding.More advanced topics such as intents are also covered, as are touch screen handling, gesture recognition, and the recording and playback of audio. This book edition also covers printing, transitions, and foldable device support.The concepts of material design are also covered in detail, including the use of floating action buttons, Snackbars, tabbed interfaces, card views, navigation drawers, and collapsing toolbars.Other key features of Android Studio and Android are also covered in detail, including the Layout Editor, the ConstraintLayout and ConstraintSet classes, MotionLayout Editor, view binding, constraint chains, barriers, and direct reply notifications. Chapters also cover advanced features of Android Studio, such as App Links, Gradle build configuration, in-app billing, and submitting apps to the Google Play Developer Console.Assuming you already have some programming experience, are ready to download Android Studio and the Android SDK, have access to a Windows, Mac, or Linux system, and have ideas for some apps to develop, you are ready to get started.
eBook
Concurrent validity and reliability of a free smartphone application for evaluation of jump height
Background/Objectives: Jump test assessment is commonly used for physical tests, with different type of devices used for its evaluation. The purpose of the present study was to examine the validity and reliability of a freely accessible mobile application (VertVision, version 2.0.5) for measuring jump performance. Methods: With that intent, thirty-eight college age recreationally active subjects underwent test assessment after a specific warm-up, performing countermovement jumps (CMJs) and squat jumps (SJs) on a contact platform while being recorded with a smartphone camera. Jump height was the criterion variable, with the same formula being used for both methods. Data analysis was performed by two experienced observers. Results: The results showed strong correlations with the contact platform (ICC > 0.9) for both jumps. Furthermore, between-observer reliability was also high (ICC > 0.9; CV ≤ 2.19), with lower values for smallest worthwhile change (≤0.23) and typical error of measurement (≤0.14). Estimation error varied when accounting for both observers, with the SJ accounting for bigger differences (4.1–6.03%), when compared to the CMJ (0.73–3.09%). Conclusions: The study suggests that VertVision is a suitable and handy method for evaluating jump performance. However, it presents a slight estimation error when compared to the contact platform.
Journal
Android phones & tablets for dummies
\"Getting a smartphone or tablet is more enjoyable when you have an informative and entertaining guide to assist you! Whether you're upgrading from an older model or totally new to the complex world of Android devices, this book makes it easier than ever to get up and running with the latest and greatest technology. From setup and configuration to taking advantage of all those intricate bells and whistles, you'll want to keep this go-to reference close by every step of the way\"--Publisher.
Book
Survey on Blockchain-Based Data Storage Security for Android Mobile Applications
This research paper investigates the integration of blockchain technology to enhance the security of Android mobile app data storage. Blockchain holds the potential to significantly improve data security and reliability, yet faces notable challenges such as scalability, performance, cost, and complexity. In this study, we begin by providing a thorough review of prior research and identifying critical research gaps in the field. Android’s dominant position in the mobile market justifies our focus on this platform. Additionally, we delve into the historical evolution of blockchain and its relevance to modern mobile app security in a dedicated section. Our examination of encryption techniques and the effectiveness of blockchain in securing mobile app data storage yields important insights. We discuss the advantages of blockchain over traditional encryption methods and their practical implications. The central contribution of this paper is the Blockchain-based Secure Android Data Storage (BSADS) framework, now consisting of six comprehensive layers. We address challenges related to data storage costs, scalability, performance, and mobile-specific constraints, proposing technical optimization strategies to overcome these obstacles effectively. To maintain transparency and provide a holistic perspective, we acknowledge the limitations of our study. Furthermore, we outline future directions, stressing the importance of leveraging lightweight nodes, tackling scalability issues, integrating emerging technologies, and enhancing user experiences while adhering to regulatory requirements.
Journal Article
Android Studio Iguana Essentials - Java Edition: Developing Android Apps Using Android Studio 2023.2.1 and Java
This book, fully updated for Android Studio Iguana (2023.2.1) and the new UI, teaches you how to develop Android-based applications using the Java programming language.This book begins with the basics and outlines how to set up an Android development and testing environment, followed by an overview of areas such as tool windows, the code editor, and the Layout Editor tool. An introduction to the architecture of Android is followed by an in-depth look at the design of Android applications and user interfaces using the Android Studio environment.Chapters also cover the Android Architecture Components, including view models, lifecycle management, Room database access, content providers, the Database Inspector, app navigation, live data, and data binding.More advanced topics, such as intents, are also covered, as are touch screen handling, gesture recognition, and audio recording and playback. This book edition also covers printing, transitions, and foldable device support.The concepts of material design are also covered in detail, including the use of floating action buttons, Snackbars, tabbed interfaces, card views, navigation drawers, and collapsing toolbars.Other key features of Android Studio and Android are also covered in detail, including the Layout Editor, the ConstraintLayout and ConstraintSet classes, MotionLayout Editor, view binding, constraint chains, barriers, and direct reply notifications. Chapters also cover advanced features of Android Studio, such as App Links, Gradle build configuration, in-app billing, and submitting apps to the Google Play Developer Console.Assuming you already have some Java programming experience, are ready to download Android Studio and the Android SDK, have access to a Windows, Mac, or Linux system, and have ideas for some apps to develop, you are ready to get started.
eBook
Learn Android Studio 3 with Kotlin : efficient Android app development
\"Build Android apps using the popular and efficient Android Studio 3 suite of tools, an integrated development environment (IDE) with which Android developers can now use the Kotlin programming language. With this book, you'll learn the latest and most productive tools in the Android tools ecosystem, ensuring quick Android app development and minimal effort on your part. Along the way, you'll use Android Studio to develop apps tier by tier through practical examples. These examples cover core Android topics such as Activities, Intents, BroadcastReceivers, Services and AsyncTask. Then, you'll learn how to publish your apps and sell them online and in the Google Play store. You will: Use Android Studio 3 to quickly and confidently build your first Android apps ; Build an Android user interface using activities and layouts, event handling, images, menus and the action bar ; Incorporate new elements including fragments ; Learn how data is persisted ; Use Kotlin to build apps.\"--Publisher's description.
Book
Visualising Static Features and Classifying Android Malware Using a Convolutional Neural Network Approach
Android phones are widely recognised as the most popular mobile phone operating system. Additionally, tasks like browsing the internet, taking pictures, making calls, and sending messages may be completed with ease in daily life because of the functionality that Android phones offer. The number of situations in which users are harmed by unauthorised access to data emerging from these processes is growing daily. Because the Android operating system is open source and generated applications are not thoroughly reviewed before being released onto the market, this scenario has been the primary focus of hackers. Therefore, technologies to distinguish between malware and benign Android applications are required. CNN-based techniques are proven to produce important and successful outcomes when applied to Android malware detection on images. The CICMalDroid 2020 dataset, which is currently utilised in the literature, was used for this purpose. The features of the apps in the dataset were obtained using the AndroPyTool tool, and faster analysis files of 17,089 Android applications were obtained using the parallel execution technique. Permissions, intents, receivers, and services were used as static analysis features in this article. After these features were obtained, as data preprocessing, the ones with a grand total equal to 1 for each feature in the whole dataset were excluded in order to exclude the features that were specially created by the applications themselves. For each of the features specified for each application, a comma-separated text was obtained according to the usage status of the application. The BERT method was used to digitise the pertinent texts in order to create a unique embedding vector for every feature. Following the digitisation of the vectors, picture files were produced based on the length of each feature. To create a single image file, these image files were combined side by side. Finally, these image files were classified with CNNs. Experimental results were obtained by applying CNNs to the dataset used in the study. As a result of the experiments, a CNN with two outputs provided the highest performance with an accuracy of 91%, an F1-score of 89%, a Recall of 90%, and a Precision of 91%.
Journal Article