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Location-Based Internationalization and Localization With Mobile Computing

The Android system operates on many smartphones in many locales. Websites and web tools have their own requirements in day-to-day life. To reach the maximum users, the app and website should handle all the resources such as text strings, functions, layouts, graphics, and any other static data that the app/website needs. It requires internationalization and localization of the website and app to support multiple languages. The basic idea of this chapter is to present an approach for localizing the Android application according to the location data that the app received from the device, but many users do not allow the “access location” feature so this approach will be a dead end in this case. The authors have proposed some other techniques to achieve this feature of localization and internationalization by implementing the “choose language” service so that the app can itself optimize its content and translate it into the user's native language.

Why Does Privacy Paradox Exist?

In this exploratory study, the main aim was to find, ‘why do people disclose information when they are concerned about their privacy?’. The reasons that provide a plausible explanation to the privacy paradox have been conjectural. From the analysis of the eighteen in-depth interviews using grounded theory, themes were then conceptualized. We found rational and irrational explanations in terms of cognitive biases and heuristics that explain the privacy paradox among mobile users. We figured out some reasons in this context of mobile computing which were not emphasized earlier in the privacy paradox literature such as Peanut Effect, Fear of Missing Out- FoMo, Learned Helplessness, and Neophiliac Personality. These results add to the privacy paradox discourse and provide implications for smartphone users for making privacy-related decisions more consciously rather than inconsiderately disclosing information. Also, the results would help marketers and policymakers design nudges and choice architectures that consider privacy decision-making hurdles.

Database Recovery Technique for Mobile Computing: A Game Theory Approach

Intelligent multilevel node authentication in mobile computing using clone node, 2021 index ieee transactions on mobile computing vol. 20, mobile computing and sustainable informatics, computer mathematical modeling based on the improved genetic algorithm and mobile computing.

In order to change the problem of data redundancy in a genetic algorithm, this paper proposes a computer mathematical model based on the combination of an improved genetic algorithm and mobile computing. Combined with the least square method, MATLAB software is used to solve the equations, determine the range of parameters, and solve the estimation parameter range and identification problems. The improved genetic algorithm combined with mobile computing and least square method to establish a mathematical model greatly increased the individual search space and increased the operation rate of 90% compared to the basic genetic algorithm or mobile computing. The results show that the improved genetic algorithm and mobile computing have a certain ability to identify the optimal solution and greatly improve the work efficiency.

Integrated Fan‐Out ( InFO ) for Mobile Computing

Mobile computing as a support to teach the concept of function.

We make a proposal to teach the concept of function using mobile computing. This proposal is based on research that has support in education theories such as Constructivism and Problem Solving Learning. In the first part we show the difficulties that undergraduate Computer Science students have in the first semester of Engineering while working with that mathematical concept. And application to be used by the students anywhere and anytime in mobile devices is designed that process data and is intended to show them the concept of function in a problem solving situation. The proposed activities are part of the education methodology used in the research and within this paper we show the diagnostic questionnaire as one of the methodological tools and its results supporting the designed activities and its application to mobile devices

Prediction of Mineralization Prospects Based on Geological Semantic Model and Mobile Computer Machine Learning

Mineral resources are indispensable in the development of human society and are the foundation of national economic development. As the prospecting target shifts from outcrop ore to concealed ore, from shallow to deep, the difficulty of prospecting becomes more and more difficult. Therefore, the prediction of mineralization prospects is of great significance. This paper is aimed at completing the prediction of mineralization prospects by constructing geological semantic models and using mobile computer learning to improve the accuracy of prediction of mineralization prospects and expanding the application of semantic mobile computing. We use five different semantic relations to build a semantic knowledge library, realize semantic retrieval, complete information extraction of geological text data, and study mineral profiles. Through the distributed database of mobile computing, the association rules and random forest algorithm are used to describe the characteristics of minerals and the ore-controlling elements, find the association rules, and finally combine the geological and mineral data of the area and use the random forest algorithm to realize the prospect of mineralization district forecast. The geological semantic model constructed in the article uses the knowledge library for associative search to achieve an accuracy rate of 87.9% and a recall rate of 96.5%. The retrieval effect is much higher than that of traditional keyword retrieval methods. The maximum value of the posterior result of the mineralization prospect is 0.9027, the average value is 0.0421, and the standard deviation is 0.1069. The picture is brighter, and the probability of mineralization is higher.

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Mobile Computing and Sustainable Informatics

Proceedings of ICMCSI 2023

• Conference proceedings
• © 2023
• Subarna Shakya 0 ,
• George Papakostas 1 ,
• Khaled A. Kamel 2

Pulchowk Campus, Tribhuvan University, Kathmandu, Nepal

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Department of Computer Science, International Hellenic University, Kavala, Greece

Computer science department, texas southern university, houston, usa.

• Presents high-quality research papers in mobile computing and sustainable informatics
• Features the outcomes of ICMCSI 2023, held in Nepal
• Serves as a reference resource for researchers and practitioners in academia and industry

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies (LNDECT, volume 166)

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Table of contents (56 papers)

Front matter, measuring the technical efficiency of thai rubber export using the spatial stochastic frontier model under the bcg concept.

• Chanamart Intapan, Chukiat Chaiboonsri

Analysis of Digital Data Consumption of Video Streaming Platforms During COVID-19

• Lizeth Aracelly Lopez-Orosco, Valeria Alexandra Solano-Guevara, Adriana Margarita Turriate-Guzman, Luis-Rolando Alarcón-Llontop

A Prototype of a Wireless Power Transmission System Based on Arduino

• Md. Rawshan Habib, Ahmed Yousuf Suhan, Md. Shahnewaz Tanvir, Abhishek Vadher, Md. Mossihur Rahman, Shuva Dasgupta Avi et al.

Short Review on Blockchain Technology for Smart City Security

• Alanoud Alquwayzani, M. M. Hafizur Rahman

Efficient Analysis of Sequences of Security Problems in Access Control Systems

• Anh Tuan Truong

Artificial Intelligence in Agriculture: Machine Learning Based Early Detection of Insects and Diseases with Environment and Substance Monitoring Using IoT

• D. Gnana Rajesh, Yaqoob Yousuf Said Al Awfi, Murshid Qasim Mohammed Almaawali

Design Concepts for Mobile Computing Direction Finding Systems

• Juliy Boiko, Oleksıy Polıkarovskykh, Vitalii Tkachuk, Hanna Yehoshyna, Lesya Karpova

A Hybrid Machine Learning Model for Urban Mid- and Long-Term Electricity Load Forecasting

• Xianghua Tang, Zhihui Jiang, Lijuan Zhang, Jiayu Wang, Youran Zhang, Liping Zhang

Optimizing Long Short-Term Memory by Improved Teacher Learning-Based Optimization for Ethereum Price Forecasting

• Marija Milicevic, Luka Jovanovic, Nebojsa Bacanin, Miodrag Zivkovic, Dejan Jovanovic, Milos Antonijevic et al.

A Sophisticated Review on Open Verifiable Health Care System in Cloud

• Mandava Varshini, Kolla Akshaya, Katakam Krishna Premika, A. Vijaya Kumar

Fuzzy Metadata Augmentation for Multimodal Data Classification

• Yuri Gordienko, Maksym Shulha, Yuriy Kochura, Oleksandr Rokovyi, Oleg Alienin, Sergii Stirenko

Development of an Information Accuracy Control System

• A. M. Mehdiyeva, I. Z. Sardarova, Z. A. Mahmudova

Modelling an Efficient Approach to Analyse Clone Phishing and Predict Cyber-Crimes

• Bondili Sri Harsha Sai Singh, Mohammed Fathima, Mohammad Sameer, Thota Teja Mahesh, A. Dinesh Kumar, K. Padmanaban

The Application of Mobile Phones to Enable Traffic Flow Optimisation

• T. Shilowa, J. P. van Deventer, M. J. Hattingh

A Hypothesis on Cloud Sourcing Sharing Users’ Mobile Devices Through Virtualization

• Nazmus Sakib, Al Hasib Mahamud

An Analytical Assessment of Machine Learning Algorithms for Predicting Campus Placements

• S. Bala Dhanalakshmi, Raksheka Rajakumar, Swetha Shankar, R. Sowndharya Rani, N. Deepa, C. Subha Priyadharshini

Building Hindi Text Dataset on Stock Market Tweets and Sentiment Analysis Using NLP

• Choudhary Anushka, Gupta Mohit, S. K. Lavanya

Fine-Tuning of RoBERTa for Document Classification of ArXiv Dataset

• Kshetraphal Bohara, Aman Shakya, Bishal Debb Pande

Comparative Analysis of Using Event Sourcing Approach in Web Application Based on the LAMP Stack

• Marian Slabinoha, Stepan Melnychuk, Vitalia Kropyvnytska, Bohdan Pashkovskyi
• Mobile Cloud Computing Models
• Mobile and Ubiquitous Computing Architectures
• Sustainable Data Analytics
• Sustainable Information Modelling
• Sustainable Information Systems
• ICMCSI 2023 Proceedings

About this book

Editors and affiliations.

Subarna Shakya

George Papakostas

Khaled A. Kamel

About the editors

George A. Papakostas  received a diploma in Electrical and Computer Engineering in 1999 and an M.Sc. and Ph.D. degree in Electrical and Computer Engineering in 2002 and 2007, respectively, from the Democritus University of Thrace(DUTH), Greece. Dr. Papakostas is a Tenured Full Professor in the Department of Computer Science, at International Hellenic University, Greece. Dr. Papakostas has 10 years of experience in large-scale systems design, as a senior software engineer and technical manager in INTRACOM TELECOM S.A. and INTALOT S.A. companies. Currently, he is the Director of the “MLV Research Group” (Machine Learning & Vision Research Group). He has (co)authored more than 200 publications in indexed journals, international conferences and book chapters, 1 book (in greek), 2 edited books and 5 journal special issues. His publications have more than 3000 citations with h-index 32 (GoogleScholar). His research interests include machine learning, computer/machine vision, pattern recognition, and computational intelligence. Dr. Papakostas served as a reviewer in numerous journals and conferences, and he is a member of the IAENG, MIR Labs, EUCogIII and the Technical Chamber of Greece (TEE).

Khaled A . Kamel is currently Chairman and Professor at Texas Southern university, College of Science and technology, Department of Computer Science, Houston, TX. He has published many research articles in refereed journals and IEEE conferences. He has more than 30 years of teaching and research experience. He has been General Chair, Session Chair, TPC Chair, and Panelist in several conferences and acted as Reviewer and Guest Editor in referred journals. His research interest includes networks, computing, and communication systems.

Bibliographic Information

Book Title : Mobile Computing and Sustainable Informatics

Book Subtitle : Proceedings of ICMCSI 2023

Editors : Subarna Shakya, George Papakostas, Khaled A. Kamel

Series Title : Lecture Notes on Data Engineering and Communications Technologies

DOI : https://doi.org/10.1007/978-981-99-0835-6

Publisher : Springer Singapore

eBook Packages : Intelligent Technologies and Robotics , Intelligent Technologies and Robotics (R0)

Copyright Information : The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023

Softcover ISBN : 978-981-99-0834-9 Published: 27 May 2023

eBook ISBN : 978-981-99-0835-6 Published: 26 May 2023

Series ISSN : 2367-4512

Series E-ISSN : 2367-4520

Edition Number : 1

Number of Pages : XVI, 799

Number of Illustrations : 94 b/w illustrations, 289 illustrations in colour

Topics : Computational Intelligence , Mobile Computing , Mobile and Network Security , Artificial Intelligence

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