“Where Is the App for That?” Developing Neurosurgical Smartphone Technology for Patients and Providers

Technological advances are growing rapidly, including mobile device technology, one of which is an Android smartphone that is experiencing rapid progress with a variety of features so that it can spoil its users, with the rapid development of smartphone technology, many users benefit, but many are disadvantaged by the growing smartphone. technology, so that many perpetrators or persons who commit crimes and seek profits with smartphone facilities. Case simulation by securing Samsung Galaxy A8 brand android smartphone evidence using the MOBILedit forensic express forensic tool with the National Institute of Standards and Technology (NIST) method which consists of four stages of collection, examination, analysis and reporting. The results of testing the Samsung Galaxy A8 android smartphone are carried out with the NIST method and the MOBILedit Forensic Express tool obtained by data backup, extraction and analysis so that there are findings sought for investigation and evidence of crimes committed by persons using android smartphone facilities.

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Faculty Opinions recommendation of Enhancing early psychosis treatment using smartphone technology: A longitudinal feasibility and validity study.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.732100098.793567546 ◽

2019 ◽

Author(s):

Vijay Mittal

Keyword(s):

Early Psychosis ◽

Validity Study ◽

Smartphone Technology

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Digital Childhood?

The Oxford Handbook of Mobile Communication and Society ◽

10.1093/oxfordhb/9780190864385.013.9 ◽

2020 ◽

pp. 128-143

Author(s):

Mariya Stoilova ◽

Sonia Livingstone ◽

Giovanna Mascheroni

Keyword(s):

Social Inequalities ◽

Childhood Experiences ◽

Communicative Practices ◽

Global Trends ◽

Digital Divides ◽

The Everyday ◽

The World ◽

Smartphone Technology ◽

Long Term Consequences

Mobile devices play a growing role in the everyday lives of children around the world, prompting important questions about their effects on childhood experiences. Exploring the recent global trends in children’s use of smartphone devices, the authors examine the reconfiguring of children’s communicative practices and cultures of connectivity, documenting the opportunities and risks that smartphone technology affords. Throughout the chapter the authors challenge the notion of “digital childhoods,” drawing on the most reliable research on children and smartphones including findings from Global Kids Online, which suggest that digital divides intersect with existing social inequalities, exacerbating the barriers for less privileged children. This raises further questions about the long-term consequences for children’s development, rights, and future access to opportunities and resources.

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Stimmen: A citizen science approach to minority language sociolinguistics

Linguistics Vanguard ◽

10.1515/lingvan-2019-0017 ◽

2021 ◽

Vol 7 (s1) ◽

Author(s):

Nanna Haug Hilton

Keyword(s):

Citizen Science ◽

Smartphone Application ◽

Minority Language ◽

Phonological Variation ◽

Methodological Issues ◽

Speech Corpora ◽

Societal Context ◽

Smartphone Technology ◽

Language Areas

Abstract This paper presents the project Stimmen fan Fryslân ‘Voices of Fryslân’. The project relies on a smartphone application developed to involve local communities in the creation of speech corpora, particularly of lesser used languages. This paper lays out the scientific and societal context of the project, showcases the smartphone application and gives an overview of the results from the project that attracted more than 15,000 users. Some key methodological issues are considered, and the paper discusses the role of smartphone technology for citizen science in minority language areas while also showing new maps with distributions of lexical and phonological variation in Frisian.

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Betalogger: Smartphone Sensor-based Side-channel Attack Detection and Text Inference Using Language Modeling and Dense MultiLayer Neural Network

ACM Transactions on Asian and Low-Resource Language Information Processing ◽

10.1145/3460392 ◽

2021 ◽

Vol 20 (5) ◽

pp. 1-17

Author(s):

Abdul Rehman Javed ◽

Saif Ur Rehman ◽

Mohib Ullah Khan ◽

Mamoun Alazab ◽

Habib Ullah Khan

Keyword(s):

Neural Network ◽

Language Modeling ◽

Attack Detection ◽

Machine Learning Algorithms ◽

Second Phase ◽

Sensitive Data ◽

Phase Sequence ◽

Smartphone Technology ◽

Conventional Machine ◽

Sequence Generator

With the recent advancement of smartphone technology in the past few years, smartphone usage has increased on a tremendous scale due to its portability and ability to perform many daily life tasks. As a result, smartphones have become one of the most valuable targets for hackers to perform cyberattacks, since the smartphone can contain individuals’ sensitive data. Smartphones are embedded with highly accurate sensors. This article proposes BetaLogger , an Android-based application that highlights the issue of leaking smartphone users’ privacy using smartphone hardware sensors (accelerometer, magnetometer, and gyroscope). BetaLogger efficiently infers the typed text (long or short) on a smartphone keyboard using Language Modeling and a Dense Multi-layer Neural Network (DMNN). BetaLogger is composed of two major phases: In the first phase, Text Inference Vector is given as input to the DMNN model to predict the target labels comprising the alphabet, and in the second phase, sequence generator module generate the output sequence in the shape of a continuous sentence. The outcomes demonstrate that BetaLogger generates highly accurate short and long sentences, and it effectively enhances the inference rate in comparison with conventional machine learning algorithms and state-of-the-art studies.

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Spatial Roadway Condition-Assessment Mapping Utilizing Smartphones and Machine Learning Algorithms

Transportation Research Record Journal of the Transportation Research Board ◽

10.1177/03611981211006105 ◽

2021 ◽

pp. 036119812110061

Author(s):

Charalambos Kyriakou ◽

Symeon E. Christodoulou ◽

Loukas Dimitriou

Keyword(s):

Machine Learning ◽

Learning Algorithms ◽

Condition Assessment ◽

Machine Learning Algorithms ◽

Supervised Machine Learning ◽

Geographical Information ◽

Related Field ◽

Pavement Surface ◽

Automated Method ◽

Smartphone Technology

The paper presents a data-driven framework and related field studies on the use of supervised machine learning and smartphone technology for the spatial condition-assessment mapping of roadway pavement surface anomalies. The study explores the use of data, collected by sensors from a smartphone and a vehicle’s onboard diagnostic device while the vehicle is in movement, for the detection of roadway anomalies. The research proposes a low-cost and automated method to obtain up-to-date information on roadway pavement surface anomalies with the use of smartphone technology, artificial neural networks, robust regression analysis, and supervised machine learning algorithms for multiclass problems. The technology for the suggested system is readily available and accurate and can be utilized in pavement monitoring systems and geographical information system applications. Further, the proposed methodology has been field-tested, exhibiting accuracy levels higher than 90%, and it is currently expanded to include larger datasets and a bigger number of common roadway pavement surface defect types. The proposed system is of practical importance since it provides continuous information on roadway pavement surface conditions, which can be valuable for pavement engineers and public safety.

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