Mobile and handheld device programming Books

Book SynopsisThis textbook is about learning Android and developing native apps using the Java programming language. It follows Java and Object-Oriented (OO) programmers’ experiences and expectations and thus enables them to easily map Android concepts to familiar ones. Each chapter of the book is dedicated to one or more Android development topics and has one or more illustrating apps. The topics covered include activities and transitions between activities, Android user interfaces and widgets, activity layouts, Android debugging and testing, fragments, shared preferences, SQLite and firebase databases, XML and JSON processing, the content provider, services, message broadcasting, async task and threading, the media player, sensors, Android Google maps, etc. The book is intended for introductory or advanced Android courses to be taught in one or two semesters at universities and colleges. It uses code samples and exercises extensively to explain and clarify Android coding and concepts. It is written for students and programmers who have no prior Android programming knowledge as well as those who already have some Android programming skills and are excited to study more advanced concepts or acquire a deeper knowledge and understanding of Android programming. All the apps in the book are native Android apps and do not need to use or include third-party technologies to run.Table of Contents1. Java Review.- 2. Getting Started with Android.- 3. Your First Android Application.- 4. Debugging and Testing Using Junit, Espresso, and Mockito Frameworks.- 5. Activity Lifecycle and Passing Objects Between Screens Using Parcelable Interface.- 6. User Interface Essential Classes, Layouts, Styles, Themes, and Dimensions.- 7. ListView, ScrollList, Date and Time Pickers, and RecyclerView.- 8. Toolbar, Menu, Dialog Boxes, Shared Preferences, Implicit Intent, and Directory Structure.- 9. Fragments, Dynamic Binding, Inheritance, Pinching, and Screen Swiping.- 10. Parsing Remote XML and JSON Files, Using HTTPUrlConnection, XmlPullParser, and AsyncTask.- 11. Android SQLite, Firebase, and Room Databases.- 12. Content Provider, Service, Message Broadcasting, and Multimedia Player.- 13. Sensors, Location-Based Service, and Google Maps.

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Book SynopsisThis open access book summarizes knowledge about several file systems and file formats commonly used in mobile devices. In addition to the fundamental description of the formats, there are hints about the forensic value of possible artefacts, along with an outline of tools that can decode the relevant data. The book is organized into two distinct parts: Part I describes several different file systems that are commonly used in mobile devices. · APFS is the file system that is used in all modern Apple devices including iPhones, iPads, and even Apple Computers, like the MacBook series. · Ext4 is very common in Android devices and is the successor of the Ext2 and Ext3 file systems that were commonly used on Linux-based computers. · The Flash-Friendly File System (F2FS) is a Linux system designed explicitly for NAND Flash memory, common in removable storage devices and mobile devices, which Samsung Electronics developed in 2012. · The QNX6 file system is present in Smartphones delivered by Blackberry (e.g. devices that are using Blackberry 10) and modern vehicle infotainment systems that use QNX as their operating system. Part II describes five different file formats that are commonly used on mobile devices. · SQLite is nearly omnipresent in mobile devices with an overwhelming majority of all mobile applications storing their data in such databases. · The second leading file format in the mobile world are Property Lists, which are predominantly found on Apple devices.· Java Serialization is a popular technique for storing object states in the Java programming language. Mobile application (app) developers very often resort to this technique to make their application state persistent. · The Realm database format has emerged over recent years as a possible successor to the now ageing SQLite format and has begun to appear as part of some modern applications on mobile devices. · Protocol Buffers provide a format for taking compiled data and serializing it by turning it into bytes represented in decimal values, which is a technique commonly used in mobile devices. The aim of this book is to act as a knowledge base and reference guide for digital forensic practitioners who need knowledge about a specific file system or file format. It is also hoped to provide useful insight and knowledge for students or other aspiring professionals who want to work within the field of digital forensics. The book is written with the assumption that the reader will have some existing knowledge and understanding about computers, mobile devices, file systems and file formats.Table of ContentsPart I: Mobile File System Formats.- 1. APFS.- 2. Ext4.- 3. The Flash-Friendly File System (F2FS).- 4. QNX6.- Part II: Mobile File Formats.- 5. SQLite.- 6. Property Lists.- 7. Java Serialization.- 8. Realm.- 9. Protocol Buffers.

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Book SynopsisManaging data in a mobile computing environment invariably involves caching or replication. In many cases, a mobile device has access only to data that is stored locally, and much of that data arrives via replication from other devices, PCs, and services. Given portable devices with limited resources, weak or intermittent connectivity, and security vulnerabilities, data replication serves to increase availability, reduce communication costs, foster sharing, and enhance survivability of critical information. Mobile systems have employed a variety of distributed architectures from client–server caching to peer-to-peer replication. Such systems generally provide weak consistency models in which read and update operations can be performed at any replica without coordination with other devices. The design of a replication protocol then centers on issues of how to record, propagate, order, and filter updates. Some protocols utilize operation logs, whereas others replicate state. Systems might provide best-effort delivery, using gossip protocols or multicast, or guarantee eventual consistency for arbitrary communication patterns, using recently developed pairwise, knowledge-driven protocols. Additionally, systems must detect and resolve the conflicts that arise from concurrent updates using techniques ranging from version vectors to read–write dependency checks. This lecture explores the choices faced in designing a replication protocol, with particular emphasis on meeting the needs of mobile applications. It presents the inherent trade-offs and implicit assumptions in alternative designs. The discussion is grounded by including case studies of research and commercial systems including Coda, Ficus, Bayou, Sybase’s iAnywhere, and Microsoft’s Sync Framework. Table of Contents: Introduction / System Models / Data Consistency / Replicated Data Protocols / Partial Replication / Conflict Management / Case Studies / Conclusions / BibliographyTable of ContentsIntroduction.- System Models.- Data Consistency.- Replicated Data Protocols.- Partial Replication.- Conflict Management.- Case Studies.- Conclusions.- Bibliography.

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Book SynopsisThis unique, accessible textbook gives a comprehensive introduction to software architecture, using ‘clean architecture’ concepts with agile methods and model-driven development. The work introduces the key concepts of software architectures and explains the importance of architectural design for the long-term usefulness and sustainability of software systems. In addition, it describes more than 30 architectural styles and patterns that can be used for constructing mobile applications, enterprise and web applications, machine-learning systems, and safety-critical systems.Topics and features: Combines clean-architecture principles with agile model-driven development Employs practical examples and real industrial cases to illustrate architectures for mobile apps, web apps, enterprise systems, safety-critical systems and machine-learning systems Explores support tools for architectural design and system development using the approach Provides tutorial questions and slides to support teaching and learning Delivers material that has been class-tested over 10 years with more than 1,000 students The textbook can be used to support teaching of an undergraduate module in software architecture, yet also includes more advanced topics suitable for a specialised software architecture module at master’s level. It also will be eminently suitable and relevant for software practitioners and researchers needing or wanting to explore the field in short courses or self-study.Dr. Kevin Lano is Reader in Software Engineering, Department of Informatics, King's College London, UK. Dr. Sobhan Yassipour Tehrani is a Lecturer, Department of Computer Science, University College London, UK.Table of ContentsIntroduction to Software Architecture Concepts.- Introduction to Clean Architecture Concepts,- Development Methods.- Compound Components and Complex Connectors.- Architectural Styles.- Mobile Application Architectures.- Enterprise Systems and Application Servers.- Web Application and Enterprise Information System Architectures.- Service-oriented Architectures.- Safety-critical and Embedded Systems Architectures.- Architectural Design for Machine Learning Systems.- Software Architectures and Re-engineering.- References.- Appendix A: User guide for the architecture diagram tool.- Appendix B: User guide for AgileUML.- Index.

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Book SynopsisThe book covers the concepts of Python programming language along with mobile application development. Starting from fundamentals, the book continues with the explanation of mobile app development using Kivy framework. All the chapters offer questio

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Book SynopsisWith the proliferation of GPS devices in daily life, trajectory data that records where and when people move is now readily available on a large scale. As one of the most typical representatives, it has now become widely recognized that taxi trajectory data provides rich opportunities to enable promising smart urban services. Yet, a considerable gap still exists between the raw data available, and the extraction of actionable intelligence. This gap poses fundamental challenges on how we can achieve such intelligence. These challenges include inaccuracy issues, large data volumes to process, and sparse GPS data, to name but a few. Moreover, the movements of taxis and the leaving trajectory data are the result of a complex interplay between several parties, including drivers, passengers, travellers, urban planners, etc. In this book, we present our latest findings on mining taxi GPS trajectory data to enable a number of smart urban services, and to bring us one step closer to the vision of smart mobility. Firstly, we focus on some fundamental issues in trajectory data mining and analytics, including data map-matching, data compression, and data protection. Secondly, driven by the real needs and the most common concerns of each party involved, we formulate each problem mathematically and propose novel data mining or machine learning methods to solve it. Extensive evaluations with real-world datasets are also provided, to demonstrate the effectiveness and efficiency of using trajectory data. Unlike other books, which deal with people and goods transportation separately, this book also extends smart urban services to goods transportation by introducing the idea of crowdshipping, i.e., recruiting taxis to make package deliveries on the basis of real-time information. Since people and goods are two essential components of smart cities, we feel this extension is bot logical and essential. Lastly, we discuss the most important scientific problems and open issues in mining GPS trajectory data.Table of Contents1. Trajectory data map-matching 1.1 Introduction 1.2 Definitions and problem formulation 1.3 SD-Matching algorithm 1.4 Evaluations 1.5 Conclusions and discussions 2. Trajectory data compression 2.1 Introduction 2.2 Basic concepts and system overview 2.3 HCC algorithm 2.4 System implementation 2.5 Evaluations 2.6 Conclusions 3. Trajectory data protection 3.1 Introduction 3.2 Preliminary 3.3 Trajectory protection mechanism 3.4 Performance evaluations 3.5 Conclusions Part II: Enabling Smart Urban Services: Travellers 4. TripPlanner: Personalized trip planning leveraging heterogeneous trajectory data 4.1 Introduction 4.2 TripPlanner System 4.3 Dynamic network modelling 4.4 The two-phase approach 4.5 System evaluations 4.6 Conclusions and future work 5. ScenicPlanner: Recommending the most beautiful driving routes 5.1 Introduction 5.2 Preliminary 5.3 The two-phase approach 5.4 Experimental evaluations 5.5 Conclusion and future work Part III: Enabling Smart Urban Services: Drivers 6. GreenPlanner: Planning fuel-efficient driving routes 6.1 Introduction 6.2 Basic concepts and problem formulation 6.3 Personal fuel consumption model building 6.4 Fuel-efficient driving route planning 6.5 Evaluations 6.6 Conclusions and future work 7. Hunting or waiting: Earning more by understanding taxi service strategies 7.1 Introduction 7.2 Empirical study 7.3 Taxi strategy formulation 7.4 Understanding taxi service strategies 7.5 Conclusions Part IV: Enabling Smart Urban Services: Passengers 8. iBOAT: Real-time detection of anomalous taxi trajectories from GPS traces 8.1 Introduction 8.2 Preliminaries and problem definition 8.3 Isolation-based online anomalous trajectory detection 8.4 Empirical evaluations 8.5 Fraud behaviour analysis 8.6 Conclusions and future work 9. Real-Time imputing trip purpose leveraging heterogeneous trajectory data 9.1 Introduction 9.2 Basic concepts and problem statement 9.3 Imputing trip purposes 9.4 Enabling real-time response 9.5 Evaluations 9.6 Conclusions and future work Part V: Enabling Smart Urban Services: Urban Planners 10. GPS environment friendliness estimation with trajectory data 10.1 Introduction 10.2 Basic concepts 10.3 Methodology 10.4 Experiments 10.5 Limitations and future work 10.6 Conclusions 11. B-Planner: Planning night bus routes using taxi trajectory data 11.1 Introduction 11.2 Candidate bus stop identification 11.3 Bus route selection 11.4 Experimental evaluations 11.5 Conclusions and future work 12. VizTripPurpose: Understanding city-wide passengers’ travel behaviours 12.1 Introduction 12.2 System overview 12.3 Trip2Vec model 12.4 User interfaces 12.5 Case studies 12.6 Conclusions and future work Part VI: Enabling Smart Urban Services: Beyond People Transportation 13. CrowdDeliver: Arriving as soon as possible 13.1 Introduction 13.2 Basic concepts, assumptions and problem statement 13.3 Overview of CrowdDeliver 13.4 Two-phase approach 13.5 Evaluations 13.6 Conclusions and future work 14. CrowdExpress: Arriving by the user-specified deadline 14.1 Introduction 14.2 Preliminary, problem statement and system overview 14.3 Offline package transport network building 14.4 Online taxi scheduling and package routing 14.5 Experimental evaluations 14.6 Conclusions and future work Part VII: Open Issues and Conclusions 15. Open Issues 16. Conclusions

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Book SynopsisThis book gathers selected high-quality research papers presented at International Conference on Mobile Computing and Sustainable Informatics (ICMCSI 2021) organized by Pulchowk Campus, Institute of Engineering, Tribhuvan University, Nepal, during 29–30 January 2021. The book discusses recent developments in mobile communication technologies ranging from mobile edge computing devices, to personalized, embedded and sustainable applications. The book covers vital topics like mobile networks, computing models, algorithms, sustainable models and advanced informatics that supports the symbiosis of mobile computing and sustainable informatics.Table of ContentsChapter 1. Mitigating the Latency Induced Delay in IP Telephony through an Enhanced De-Jitter Buffer.- Chapter 2. A Cyber – Safety IoT Enabled Wearable Microstrip Antenna for X – Band applications.- Chapter 3. Keyword Recognition from EEG Signals on Smart Devices a Novel Approach.- Chapter 4. Security Analysis for Sybil Attack in Sensor Network using Compare and Match-Position Verification Method.- Chapter 5. Certain Strategic Study on Machine Learning based Graph Anomaly Detection.- Chapter 6. Machine Learning Perspective in VLSI Computer Aided Design at Different Abstraction Levels.- Chapter 7. A Practical Approach to Measure Data Center Efficiency using Power Usage Effectiveness.- Chapter 8. Advancing e-Government using Internet of Things.- Chapter 9. A New Network Forensic Investigation Process Model.- Chapter 10. MDTA : A New Approach of Supervised Machine Learning for Android Malware Detection And Threat Attribution using Behavioral Reports.- Chapter 11. Investigating the role of user Experience and Design in Recommender Systems: A Pragmatic Review.- Chapter 12. A Review on Intrusion Detection Approaches in Resource Constrained IoT Environment.- Chapter 13. The Future 5G Mobile Network Performance in Webservices with NDN Technology.- Chapter 14. Survey for Electroencephalography EEG signals Classification Approaches.- Chapter 15. Analysis of Road Accidents using Data Mining Paradigm.

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Book SynopsisOcean covers 70.8% of the Earth’s surface, and it plays an important role in supporting all life on Earth. Nonetheless, more than 80% of the ocean’s volume remains unmapped, unobserved and unexplored. In this regard, Underwater Sensor Networks (USNs), which offer ubiquitous computation, efficient communication and reliable control, are emerging as a promising solution to understand and explore the ocean. In order to support the application of USNs, accurate position information from sensor nodes is required to correctly analyze and interpret the data sampled. However, the openness and weak communication characteristics of USNs make underwater localization much more challenging in comparison to terrestrial sensor networks.In this book, we focus on the localization problem in USNs, taking into account the unique characteristics of the underwater environment. This problem is of considerable importance, since fundamental guidance on the design and analysis of USN localization is very limited at present. To this end, we first introduce the network architecture of USNs and briefly review previous approaches to the localization of USNs. Then, the asynchronous clock, node mobility, stratification effect, privacy preserving and attack detection are considered respectively and corresponding localization schemes are developed. Lastly, the book’s rich implications provide guidance on the design of future USN localization schemes.The results in this book reveal from a system perspective that underwater localization accuracy is closely related to the communication protocol and optimization estimator. Researchers, scientists and engineers in the field of USNs can benefit greatly from this book, which provides a wealth of information, useful methods and practical algorithms to help understand and explore the ocean.Table of Contents 1. Introduction1.1 Network Architecture of Underwater Sensor Networks1.2 Prior Arts in Localization1.3 Underwater Weak Communication Characteristics 2. Asynchronous Localization of Underwater Sensor Networks with Mobility Prediction2.1 Introduction2.2 System Modeling and Problem Formulation2.3 Design of Asynchronous Localization Approach2.4 Performance Analysis2.4.1 Convergence2.4.2 Cramer-Rao Lower Bound2.5 Simulation2.5.1 Simulation of Active Sensor Node2.5.2 Simulation of Passive Sensor Node2.6 SummaryReferences 3. Asynchronous Localization of Underwater Sensor Networks with Consensus-Based Unscented Kalman Filtering3.1 Introduction3.2 System Modeling and Problem Formulation3.3 Design of Consensus-Based UKF Localization Approach3.4 Performance Analysis3.4.1 Observability Analysis3.4.2 Convergence Conditions3.4.3 Cramer-Rao Lower Bound3.4.4 Computational Complexity Analysis3.5 Simulation3.6 SummaryReference 4. Reinforcement Learning Based Asynchronous Localization of Underwater Sensor Networks4.1 Introduction4.2 System Modeling and Problem Formulation4.3 Design of Reinforcement Learning Based Asynchronous Localization Approach4.4 Performance Analysis4.4.1 Convergence Conditions4.4.2 Cramer-Rao Lower Bound4.4.3 Computational Complexity Analysis4.5 Simulation4.5.1 Advantage of the RL-Based Localization Strategy4.5.3 Simulation of Active Sensor Node4.5.4 Simulation of Passive Sensor Node4.6 SummaryReference 5. Privacy Preserving Asynchronous Localization of Underwater Sensor Networks5.1 Introduction5.2 System Modeling and Problem Formulation5.3 Design of Privacy Preserving Based Localization Approach5.3.1 Design of Active Sensor Node Localization Strategy5.3.2 Design of Ordinary Sensor Node Localization Strategy5.4 Performance Analysis5.4.1 Equivalence Analysis 5.4.1.1 Equivalence Analysis of Active Sensor Node 5.4.1.2 Equivalence Analysis of Ordinary Sensor Node5.4.2 Level of Privacy Preservation5.4.3 Communication Complexity Analysis5.5 Simulation5.5.1 Simulation of Active Sensor Node5.5.2 Simulation of Ordinary Sensor Node5.6 SummaryReference 6. Privacy-Preserving Asynchronous Localization of Underwater Sensor Network with Attack Detection and Ray Compensation6.1 Introduction6.2 System Modeling and Problem Formulation6.3 Design of Privacy-Preserving Localization Approach6.4 Performance Analysis6.4.1 Equivalence Analysis6.4.2 Influencing Factors of Localization Errors6.4.3 Privacy-Preserving Property6.4.4 Tradeoff Between Privacy and Transmission Cost6.5 Simulation6.6 SummaryReference 7. Deep Reinforcement Learning Based Privacy-Preserving Localization of Underwater Sensor Networks7.1 Introduction7.2 System Modeling and Problem Formulation7.3 Design of Privacy-Preserving Localization Protocol7.4 Design of DRL-based Localization Approach7.4.1 Localization when All Data is Unlabeled7.4.2 Localization when Labelled Data Occupies the Majority7.4.3 Localization when Unlabeled Data Occupies the Majority7.5 Performance Analysis7.5.1 Equivalence of the Localization Protocols7.5.2 Privacy Preservation Analysis7.5.3 Global Optimum Analysis7.5.4 Computation Complexity Analysis7.6 Simulation7.6.1 Advantage of the DRL-Based Localization Strategy7.6.2 Simulation of Unsupervised DRL-Based Estimator7.6.3 Simulation of Supervised DRL-Based Estimator7.6.4 Simulation of Semisupervised DRL-Based Estimator7.7 SummaryReference8. Conclusion and future perspective

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Book SynopsisThis book features a collection of high-quality, peer-reviewed papers presented at the Second International Conference on Ubiquitous Intelligent Systems (ICUIS 2022) organized by Shree Venkateshwara Hi-Tech Engineering College, Tamil Nadu, India, during March 10–11, 2022. The book covers topics such as cloud computing, mobile computing and networks, embedded computing frameworks, modeling and analysis of ubiquitous information systems, communication networking models, big data models and applications, ubiquitous information processing systems, next-generation ubiquitous networks and protocols, advanced intelligent systems, Internet of Things, wireless communication and storage networks, intelligent information retrieval techniques, AI-based intelligent information visualization techniques, cognitive informatics, smart automation systems, health care informatics and bioinformatics models, security and privacy of intelligent information systems, and smart distributed information systems.Table of ContentsDevelopment of a Linear-Scaling Consensus Mechanism of the Distributed Data Ledger Technology.- A Six-Point Based Approach for Enhanced Broadcasting using Selective Forwarding Mechanism in Mobile Ad Hoc Networks.- Crop Price Prediction using Machine Learning Naive Bayes Algorithms.- The Performance Evaluation of Adaptive energy Conservation Scheme using IoT.- Towards the prominent use of Internet of Things(IoT) in Universities.- Depression Analysis of Real Time Tweets during Covid Pandemic.- Diabetic Retinopathy Detection Using Deep Learning.- Regional Language Translator using Natural Language Processing.- Fabric Defect Detection using Deep Learning Techniques.- Analysis of Research Paper Titles Containing Covid-19 keyword using Various Visualization Techniques.- Survey on Handwritten Characters Recognition in Deep Learning.- A Survey on Wild Creatures Alert System to Protect Agriculture Lands Domestic Creatures and People.- A Study on Surveillance System using Deep Learning Methods.- IRHA: An Intelligent RSSI based Home automation System.- A Review Paper on Machine Learning Techniques & Its Applications in Health Care Sector.- Enhanced Mask-RCNN for Ship Detection and Segmentation.- Data Scientist Job Change Prediction Using Machine Learning Classification Techniques.- Error Correction Scheme with Decimal Matrix Code for SRAM Emulation TCAMs.- Knowledge Discovery in Web usage Patterns using Pageviews and Data Mining Association.- Video Anomaly Detection using Optimization based Deep Learning.- A Fusional Cubic-Sine Map model for Secure Medical Image Transmission.- Innovative Technologies Developed for Autonomous Marine Vehicles by ENDURUNS Project.- Machine Learning Approaches to Predict Breast Cancer: Bangladesh Perspective.- A Comparative Review on Image Analysis with Machine Learning for Extended Reality (XR) Applications.- SWOT Analysis of Behavioural Recognition through Variable Modalities.- E-Mixup and Siamese Networks for Musical Key Estimation.- Microarray Data Classification using Feature Selection and Regularized Methods with Sampling Methods.- Visual Place Recognition using Region of Interest Ex-traction with Deep Learning based Technique.- Electronic Mobility Aid for Detection of Roadside Tree Trunks and Street-Light Poles.- Real Time Video Image Edge Detection System Using MyRIO.- Research Paper to Design & Develop an Algorithm for Optimization Chatbot.- Analysis of MRI Images to Discover Brain Tumor Detection Using Convolutional Neural Network and VGG-16.- Missing Data Recovery using Tensor Completion-based models for IoT-based Air Quality Monitoring System.- Stock Market Prediction through a Chatbot : A Human-Centered AI Approach.- Air Writing Recognition using Mediapipe and OpenCV.- Blockchain based Email Communication with Sha-256 Algorithm.- Sentimental Analysis on Amazon Reviews using Machine Learning.- Season based Crop Recommendation System using Transfer Learning: A Review.- Speed breaker Identification using Deep Learning Convolutional Neural Network.- Political Communication and Election Result: Facebook Account Analysis Jambi Governor Candidates in the 2020 Regional Election.- Intelligent System for Diagnosis of Pulmonary Tuberculosis using XGBoosting Method.- Web based Voice Assistant for Railways using Deep Learning Approach.- Segmentation and Classification Approach to Improve Breast Cancer Screening.- Analysis of a Software tool Developed to Determine the Activity of Anomalous Processes.- Study of Wave Models of Trajectories and Signals of Loading e ects in Computer Echolocation.- EnneaOntology: A Proposed Enneagram Ontology.- IoT based Signal Patrolling for Precision Vehicle Control.- Land use/cover Novel Dataset Based on Deep Learning: Case study of Fayoum, Egypt.- Exploring The effect of Word Embeddings and Bag-of-Words for Vietnamese Sentiment Analysis.- A Portable System for Automated Measurement of Striped Catfish Length using Computer Vision.- IoT based Automated Monitoring System for the Measurement of Soil Quality.- Pattern Recognition on Railway Points with Machine Learning: A Real Case Study.- Sustainability in Development of Grant Applications.- New Category of Equivalence Classes of Intuitionistic Fuzzy Delta-Algebras with their Applications.- Deep Neural Networks for Stock Market Price Predictions in VUCA Environments.- Building a Traffic flow Management System based on Neural Networks.- The Impact of Ruang Cerita Application on the Neuro Depression and Anxiety of Private University Students.- JobSeek Mobile Application: Helps Reduce Unemployment on the Agribusiness Sectors During New Normal.- Application's Impact on the SepuisLife Company's Insurance Sales Process During the Pandemic.- The Effect of Learning Using Videos on Online Learning of Private University during the Covid-19 Pandemic.- Implementation of Artificial Intelligence and Robotic that Replace Employee in Indonesia.- The Impact of Online Game Brain Addiction on Computers and Cellphones on College Students Who Take Online Classes.

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Book SynopsisThe book constitutes proceedings of the 12th Industry Symposium held in conjunction with the 18th edition of the International Conference on Distributed Computing and Intelligent Technology (ICDCIT 2022). The focus of the industry symposium is on Mobile Application Development: Practice and Experience. This book focuses on software engineering research and practice supporting any aspects of mobile application development. The book discusses findings in the areas of mobile application analysis, models for generating these applications, testing, debugging & repair, localization & globalization, app review analytics, app store mining, app beyond smartphones and tablets, app deployment, maintenance, and reliability of apps, industrial case studies of automated software engineering for mobile apps, etc. Papers included in the book describe new or improved ways to handle these aspects or address them in a more unified manner, discussing benefits, limitations, and costs of provided solutions. The volume will be useful for master, research students as well as industry professionals.Table of ContentsChapter 1: A survey on Mobile Application Development Models.- Chapter 2: Mobile Technology for Smart Agriculture Deployment case for Pearl Millet disease detection.- Chapter 3: Energy Consumption Based Profiling of Android Apps.- Chapter 4: Impact of Covid-19 on IT Business.- Chapter 5: ANNDroid_A framework for Android malware detection using feature selection techniques and machine learning algorithms.

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Book SynopsisChapter 1. Edge Computing.- Chapter 2. Scalability and Fault Tolerance for Real-Time Edge Applications.- Chapter 3. Resource-constrained Offloading in Edge Computing.- Chapter 4. Privacy Preserving Offloading.- Chapter 5. SDN-Based and Energy Aware Offloading.- Chapter 6. Optimization for Edge.- Chapter 7. FutureWork.

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Book SynopsisThis book gathers selected high-quality research papers presented at International Conference on Mobile Computing and Sustainable Informatics (ICMCSI 2022) organized by Pulchowk Campus, Institute of Engineering, Tribhuvan University, Nepal, during January 11–12, 2023. The book discusses recent developments in mobile communication technologies ranging from mobile edge computing devices to personalized, embedded, and sustainable applications. The book covers vital topics like mobile networks, computing models, algorithms, sustainable models, and advanced informatics that support the symbiosis of mobile computing and sustainable informatics.Table of Contents​Measuring the technical efficiency of Thai rubber export using the spatial stochastic frontier model under the BCG conceptChanamart Intapan, Chukiat ChaiboonsriAnalysis of Digital data Consumption of video streaming platforms during COVID-19Lizeth Aracelly Lopez-Orosco, Valeria Alexandra Solano-Guevara, Adriana Margarita Turriate-Guzman, Luis-Rolando Alarcón-LlontopA Prototype of Wireless Power Transmission System Based on ArduinoMd. Rawshan Habib, Ahmed Yousuf Suhan, Md. Shahnewaz Tanvir, Abhishek Vadher, Md. Mossihur Rahman, Shuva Dasgupta Avi, Shabuj Dasgupta AmiShort review on blockchain technology for smart city securityAlanoud Alquwayzani, M M Hafizur RahmanEfficient Analysis of Sequences of Security Problems in Access Control SystemsAnh Tuan TruongArtificial Intelligence in Agriculture: Machine Learning based Early Detection of Insects and Diseases with Environment and Substance Monitoring us-ing IoTGnana Rajesh D, Yaqoob Yousuf Said Al Awfi, Murshid Qasim Mohammed AlmaawaliDesign Concepts for Mobile Computing Direction Finding SystemsJuliy Boiko, Oleksiy Polikarovskykh, Vitalii Tkachuk, Hanna Yehoshyna, Lesya KarpovaA Hybrid Machine Learning Model for Urban Mid- and Long-term Electricity Load ForecastingXianghua Tang, Zhihui Jiang, Lijuan Zhang, Jiayu Wang, Youran Zhang, Liping ZhangOptimizing Long Short-Term Memory by Improved Teacher Learning Based Optimization for Ethereum Price ForecastingMarija Milicevic, Luka Jovanovic, Nebojsa Bacanin, Miodrag Zivkovic, Dejan Jovanovic, Milos Antonijevic, Nikola Savanovic, Ivana StrumbergerA Sophisticated review on Open Verifiable Health Care system in CloudMandava Varshini, Kolla Akshaya, Katakam Krishna Premika, A Vijaya KumarFuzzy Metadata Augmentation for Multimodal Data ClassificationYuri Gordienko, Maksym Shulha, Yuriy Kochura, Oleksandr Rokovyi, Oleg Alienin, Sergii StirenkoDevelopment of information accuracy control systemMehdiyeva A M, Sardarova I Z, Mahmudova Z AMODELLING AN EFFICIENT APPROACH TO ANALYZE CLONE PHISHING AND PREDICT CYBER-CRIMESBondili Sri Harsha Sai Singh, Mohammed Fathima, Mohammad Sameer, Thota Teja Mahesh, Dinesh Kumar A, K PadmanabanThe Application of Mobile Phones to Enable Traffic Flow OptimisationT Shilowa, J P van Deventer, M J Hattingh

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Book SynopsisThis book introduces readers to the fundamentals of the cross-technology coexistence problem in heterogeneous wireless networks. It also highlights a range of mechanisms designed to combat this problem and improve network performance, including protocol design, theoretical analysis, and experimental evaluation.In turn, the book proposes three mechanisms that can be combined to combat the cross-technology coexistence problem and improve network performance. First, the authors present a fast signal identification method. It provides the basis for the subsequent protocol design and allows heterogeneous devices to adopt proper transmission strategies. Second, the authors present two cross-technology interference management mechanisms in both the time domain and the frequency domain, which can mitigate interference and increase transmission opportunities for heterogeneous devices, thus improving network performance. Third, they present a cross-technology communication mechanism based on symbol-level energy modulation, which allows heterogeneous devices to transmit information directly without a gateway, improving transmission efficiency and paving the way for new applications in IoT scenarios. Lastly, they outline several potential research directions to further improve the efficiency of cross-technology coexistence. This book is intended for researchers, computer scientists, and engineers who are interested in the research areas of wireless networking, wireless communication, mobile computing, and Internet of Things. Advanced-level students studying these topics will benefit from the book as well.Table of Contents1. Introduction 1.1 Overview 1.2 Background 1.2.1 The Channel Specifications 1.2.2 The PHY Layer Specifications 1.2.3 The MAC Layer Specifications 1.3 Cross-technology coexistence problem 1.4 Book structure 2. Heterogeneous Signal Identification 2.1 Introduction 2.2 Motivation 2.3 System design 2.3.1 Dataset Construction 2.3.2 Signal identification through FFT features 2.3.3 Signal identification through deep learning 2.4 Experimental evaluation 2.5 Summary 3. Cross-Technology Communication through Symbol-Level Energy Modulation 3.1 Introduction 3.2 Motivation 3.3 System design 3.3.1 Overview 3.3.1 CTC design at the transmitter side 3.3.2 CTC design at the receiver side 3.4 Theoretical analysis 3.5 Experimental evaluation 3.6 Summary 4. Cross-Technology Interference Management in Frequency domain 4.1 Introduction 4.2 Motivation 4.3 System design 4.3.1 Overview 4.3.2 Standard WiFi transmission process 4.3.3 Payload encoding at WiFi transmitter 4.3.4 Process at WiFi transmitter 4.4 Experimental evaluation 4.5 Summary 5. Cross-Technology Interference Management in Time Domain 5.1 Introduction 5.2 Motivation 5.3 System design 5.3.1 Overview 5.3.2 E-CCA design 5.4 Performance Evaluation 5.5 Summary 6. Conclusion and Future Work 6.1 Conclusions 6.2 Future research directions

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Book SynopsisCreate apps for iOS and Android phones and tablets using Flutter, a Google framework that produces two outputs for a single app.

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