Mobile app reading speed test

Aim: To validate the accuracy and repeatability of a mobile app reading speed test compared with the traditional paper version. Method: Twenty-one subjects wearing their full refractive correction glasses read 14 sentences of decreasing print size between 1.0 and -0.1 logMAR, each consisting of 14 words (Radner reading speed test) at 40 cm with a paper-based chart and twice on iPad charts. Time duration was recorded with a stop watch for the paper chart and on the App itself for the mobile chart allowing critical print size (CPS) and optimal reading speed (ORS) to be derived objectively. Results: The ORS was higher for the mobile app charts (194±29 wpm; 195±25 wpm) compared with the paper chart (166±20 wpm; F=57.000, p<0.001). The CPS was lower for the mobile app charts (0.17±0.20 logMAR; 0.18±0.17 logMAR) compared with the paper chart (0.25±0.17 logMAR; F=5.406, p=0.009). The mobile app test had a mean difference repeatability of 0.30±22.5 wpm, r=0.917 for ORS, and a CPS of 0.0±0.2 logMAR, r=0.769. Conclusions: Repeatability of the app reading speed test is as good (ORS) or better (CPS) than previous studies on the paper test. While the results are not interchangeable with paper-based charts, mobile app tablet-based tests of reading speed are reliable and rapid to perform, with the potential to capture functional visual ability in research studies and clinical practice.

Mobile app Aston contrast sensitivity test

BACKGROUND: Contrast detection is an important aspect of the assessment of visual function; however, clinical tests evaluate limited spatial frequencies and contrasts. This study validates the accuracy and inter-test repeatability of a swept-frequency near and distance mobile app Aston contrast sensitivity test, which overcomes this limitation compared to traditional charts. METHOD: Twenty subjects wearing their full refractive correction underwent contrast sensitivity testing on the new near application (near app), distance app, CSV-1000 and Pelli-Robson charts with full correction and with vision degraded by 0.8 and 0.2 Bangerter degradation foils. In addition repeated measures using the 0.8 occluding foil were taken. RESULTS: The mobile apps (near more than distance, p = 0.005) recorded a higher contrast sensitivity than printed tests (p < 0.001); however, all charts showed a reduction in measured contrast sensitivity with degradation (p < 0.001) and a similar decrease with increasing spatial frequency (interaction > 0.05). Although the coefficient of repeatability was lowest for the Pelli-Robson charts (0.14 log units), the mobile app charts measured more spatial frequencies, took less time and were more repeatable (near: 0.26 to 0.37 log units; distance: 0.34 to 0.39 log units) than the CSV-1000 (0.30 to 0.93 log units). The duration to complete the CSV-1000 was 124 ± 37 seconds, Pelli-Robson 78 ± 27 seconds, near app 53 ± 15 seconds and distance app 107 ± 36 seconds. CONCLUSIONS: While there were differences between charts in contrast levels measured, the new Aston near and distance apps are valid, repeatable and time-efficient method of assessing contrast sensitivity at multiple spatial frequencies.

Tangible mobile app store design for China's new generation migrant worker

China has the largest numbers of Internet users and mobile phone subscribers in the world, as well as the most extensive peacetime internal migration on the planet. Mobile phone uses play a very important role in migrant responses to alienation and discrimination. There are 150 million to 200 million migrant workers in China, 60% of them are the second-generation migrant workers. They support the nation’s manufacturing and industry. The majority of these individuals is poor and is from rural areas of the country. These young people are currently ignored by mainstream mobile device manufacturers, even though this constituency will be a growing consumptive segment in the future. Thus, my research will target the new-generation migrant workers in China, and concentrates on their mobile lives to best develop a tangible mobile devices application store that will improve their mobile experiences.

Wishlist: progettazione ed implementazione di una piattaforma di mobile social network per dispositivi Android

Questo elaborato tratta della progettazione e dell'implementazione di una piattaforma social, destinata alla commercializzazione, per creare, gestire, condividere un insieme di liste organizzate di oggetti. La piattaforma è di tipo client-server, dove il client consiste in un'applicazione Android e il server in un'applicazione Node.js e un database MySQL che offrono un'API RESTful. Nello specifico è stata trattata l'implementazione delle notifiche push (anche geolocalizzate) e la sincronizzazione dei dati per l'utilizzo offline.

Desarrollo de una aplicación que facilita la enseñanza y el estudio del póker en su variante Texas Hold'em

[ES] PokerTrainer es una aplicación para dispósitivos móviles con Android como sistema operativo. Está dirigida a aquellos jugadores de póker en su variante Texas Hold'em que quieran aprender ciertos conceptos básicos que les van a ayudar a mejorar su juego. Se basa en la gamificación mediante un sistema de quiz de contenidos teóricos referidos al póker.

Evaluation of Machine Learning Classifiers for Mobile Network Intrusion Detection Systems

Mobile malwares are increasing with the growing number of Mobile users. Mobile malwares can perform several operations which lead to cybersecurity threats such as, stealing financial or personal information, installing malicious applications, sending premium SMS, creating backdoors, keylogging and crypto-ransomware attacks. Knowing the fact that there are many illegitimate Applications available on the App stores, most of the mobile users remain careless about the security of their Mobile devices and become the potential victim of these threats. Previous studies have shown that not every antivirus is capable of detecting all the threats; due to the fact that Mobile malwares use advance techniques to avoid detection. A Network-based IDS at the operator side will bring an extra layer of security to the subscribers and can detect many advanced threats by analyzing their traffic patterns. Machine Learning(ML) will provide the ability to these systems to detect unknown threats for which signatures are not yet known. This research is focused on the evaluation of Machine Learning classifiers in Network-based Intrusion detection systems for Mobile Networks. In this study, different techniques of Network-based intrusion detection with their advantages, disadvantages and state of the art in Hybrid solutions are discussed. Finally, a ML based NIDS is proposed which will work as a subsystem, to Network-based IDS deployed by Mobile Operators, that can help in detecting unknown threats and reducing false positives. In this research, several ML classifiers were implemented and evaluated. This study is focused on Android-based malwares, as Android is the most popular OS among users, hence most targeted by cyber criminals. Supervised ML algorithms based classifiers were built using the dataset which contained the labeled instances of relevant features. These features were extracted from the traffic generated by samples of several malware families and benign applications. These classifiers were able to detect malicious traffic patterns with the TPR upto 99.6% during Cross-validation test. Also, several experiments were conducted to detect unknown malware traffic and to detect false positives. These classifiers were able to detect unknown threats with the Accuracy of 97.5%. These classifiers could be integrated with current NIDS', which use signatures, statistical or knowledge-based techniques to detect malicious traffic. Technique to integrate the output from ML classifier with traditional NIDS is discussed and proposed for future work.

The Smartphone App Economy and App Ecosystems

This chapter gives an overview of the smartphone app economy and its various constituent ecosystems. It examines the role of the app store model and the proliferation of mobile apps in the shift from value chains controlled by network operators and handset manufacturers, to value networks – or ecosystems – focused around operating systems and apps. It outlines some of the benefits and disadvantages for developers of the app store model for remuneration and distribution. The chapter concludes with a discussion of recent research on the size and employment effects of the app economy.

Sviluppo di applicazioni mobile Cross-Platform: Flutter come caso di studio

L’obiettivo dell'elaborato è quello di dare una panoramica sullo stato dell'arte riguardo lo sviluppo di applicazioni mobile, descrivendo i vantaggi e gli svantaggi degli approcci nativo e cross-platform, ed analizzare un framework creato dal team Dart di Google per sviluppare applicazioni cross-platform per le piattaforme Android e iOS chiamato Flutter. Il framework Flutter verrà analizzato mediante lo sviluppo di un’applicazione concreta, e successivamente confrontato con la medesima app sviluppata utilizzando l’approccio nativo su piattaforma Android.

Case study on mobile applications UX: effect of the usage of a crosss-platform development framework

Cross-platform development frameworks for mobile applications promise important advantages in cost cuttings and easy maintenance, posing as a very good option for organizations interested in the design of mobile applications for several platforms. Given that platform conventions are especially important for the User eXperience (UX) of mobile applications, the usage of framework where the same code defines the behavior of the app in different platforms could have negative impact in the UX. The objetive of this study is comparing the cross-platform and the native approach for being able to determine if the selected development approach has any impact on the users in terms of UX. To be able to set a base line under this subject, study on cross-platform frameworks was performed to select the most appropriate one from a UX point of view. In order to achieve the objectives of this work, two development teams have developed two versions of the same application; one using framework that generates Android and iOS versions automatically, and another team developing native versions of the same application. The alternative versions for each platform have been evaluated with 37 users with a combination of a laboratory usability test and a longitudinal study. The results show that differences are minimal in the Android version, but in iOS, even if a reasonable good UX can be obtained with the usage of this framework by an UX-conscious design team, a higher level of UX can be obtained directly developing in native code.

A case study on cross-platform development frameworks for mobile applications and UX

Cross-platform development frameworks for mobile applications promise important advantages in cost cuttings and easy maintenance, posing as a very good option for organizations interested in the design of mobile applications for several platforms. Given that platform conventions are especially important for the User eXperience (UX) of mobile applications, the usage of a framework where the same code defines the behavior of the app in different platforms could have a negative impact in the UX. This paper describes a study where two independent teams have designed two different versions of a mobile application, one using a framework that generates Android and iOS versions automatically, and another team using native tools. The alternative versions for each platform have been evaluated with 37 users with a combination of a laboratory usability test and a longitudinal study. The results show that differences are minimal in the Android platform, but in iOS, even if a reasonably good UX can be obtained with the usage of this framework by an UX-conscious design team, a higher level of UX can be obtained directly developing with a native tool.

Mining mobile apps reviews to support release planning

The mobile apps market is a tremendous success, with millions of apps downloaded and used every day by users spread all around the world. For apps’ developers, having their apps published on one of the major app stores (e.g. Google Play market) is just the beginning of the apps lifecycle. Indeed, in order to successfully compete with the other apps in the market, an app has to be updated frequently by adding new attractive features and by fixing existing bugs. Clearly, any developer interested in increasing the success of her app should try to implement features desired by the app’s users and to fix bugs affecting the user experience of many of them. A precious source of information to decide how to collect users’ opinions and wishes is represented by the reviews left by users on the store from which they downloaded the app. However, to exploit such information the app’s developer should manually read each user review and verify if it contains useful information (e.g. suggestions for new features). This is something not doable if the app receives hundreds of reviews per day, as happens for the very popular apps on the market. In this work, our aim is to provide support to mobile apps developers by proposing a novel approach exploiting data mining, natural language processing, machine learning, and clustering techniques in order to classify the user reviews on the basis of the information they contain (e.g. useless, suggestion for new features, bugs reporting). Such an approach has been empirically evaluated and made available in a web-­‐based tool publicly available to all apps’ developers. The achieved results showed that the developed tool: (i) is able to correctly categorise user reviews on the basis of their content (e.g. isolating those reporting bugs) with 78% of accuracy, (ii) produces clusters of reviews (e.g. groups together reviews indicating exactly the same bug to be fixed) that are meaningful from a developer’s point-­‐of-­‐view, and (iii) is considered useful by a software company working in the mobile apps’ development market.

Emerging perspectives on the design, use, and evaluation of mobile and handheld devices

Human-computer interaction is a growing field of study in which researchers and professionals aim to understand and evaluate the impact of new technologies on human behavior. With the integration of smart phones, tablets, and other portable devices into everyday life, there is a greater need to understand the influence of such technology on the human experience. Emerging Perspectives on the Design, Use, and Evaluation of Mobile and Handheld Devices is an authoritative reference source consisting of the latest scholarly research and theories from international experts and professionals on the topic of human-computer interaction with mobile devices. Featuring a comprehensive collection of chapters on critical topics in this dynamic field, this publication is an essential reference source for researchers, educators, students, and practitioners interested in the use of mobile and handheld devices and their impact on individuals and society as a whole. This publication features timely, research-based chapters pertaining to topics in the design and evaluation of smart devices including, but not limited to, app stores, category-based interfaces, gamified mobility applications, mobile interaction, mobile learning, pervasive multimodal applications, smartphone interaction, and social media use.

Secure Web Service Clients on Mobile Devices

Enterprise apps on mobile devices typically need to communicate with other system components by consuming web services. Since most of the current mobile device platforms (such as Android) do not provide built-in features for consuming SOAP services, extensions have to be designed. Additionally in order to accommodate the typical enhanced security requirements of enterprise apps, it is important to be able to deal with SOAP web service security extensions on client side. In this article we show that neither the built-in SOAP capabilities for Android web service clients are sufficient for enterprise apps nor are the necessary security features supported by the platform as is. After discussing different existing extensions making Android devices SOAP capable we explain why none of them is really satisfactory in an enterprise context. Then we present our own solution which accommodates not only SOAP but also the WS-Security features on top of SOAP. Our solution heavily relies on code generation in order to keep the flexibility benefits of SOAP on one hand while still keeping the development effort manageable for software development. Our approach provides a good foundation for the implementation of other SOAP extensions apart from security on the Android platform as well. In addition our solution based on the gSOAP framework may be used for other mobile platforms in a similar manner.

mHealth in Urology: A Review of Experts' Involvement in App Development

Smartphones are increasingly playing a role in healthcare and previous studies assessing medical applications (apps) have raised concerns about lack of expert involvement and low content accuracy. However, there are no such studies in Urology. We reviewed Urology apps with the aim of assessing the level of participation of healthcare professionals (HCP) and scientific Urology associations in their development.

Plan de negocios Bicigo app

La gran cantidad de personas interesadas actualmente en cuidar de su salud por medio de la Bicicleta, es una tendencia que cada vez toma más fuerza y por esto, se tomara como ventaja que la ciudad de Bogotá con sus últimos alcaldes han decidió apoyar el uso de esta. Aplicación para realizar grupos de ciclistas y poder salir cualquier día de la semana acompañado de más personas por un tema de transporte pero también de ocio. El objetivo es que las personas que no utilizan la bicicleta por miedo a salir solos, puedan unirse a diferentes grupos y hacer bici paseos por la ciudad, también contemplamos el hecho de que existen personas que quieren montar bicicleta como aficionados, es decir que salen por la carreteras aledañas a la capital pero muchas veces no tienen grupo con quien rodar. Queremos para el año 2020, lograr ser una de las aplicaciones de Bicicletas más exitosa de la ciudadanía de Bogotá, siendo una de las aplicaciones que mas apoya el uso diario y deportivo de la bicicleta. Nuestra aplicación ofrece el servicio principalmente de reunir gente y hacer paseos con diferentes personas haciendo uso de las bicicletas, dentro de la ciudad como ocio y transporte se realizarían en la mañana y noches, pero así mismo realizar grupos para hacer uso de la bicicleta por carreteras, es decir más como modo profesional o aficionado. Nuestra aplicación cuenta con una interface para seleccionar el tipo de bici usuario y segundo por donde o a donde quiere dirigirse para así mismo mostrarle las rutas cercanas a él. Nuestra característica principal es la unión de diferentes grupos, personas y entidades para hacer uso de la Bicicleta, tenemos una plataforma interactiva y fácil de usar, tan fácil que cualquier persona que no esté inmersa en el mundo de los Smartphone o aplicaciones pueda aprender a usarla. Unas de las ventajas con las que cuento es que desde muy joven me ha gustado montar en bicicletas y es así como decido crear una aplicación ya que compañeros, familiares y conocidos no salían a montar bicicleta solo conmigo, preferían que fuese un grupo más grande. Así mismo cuento con 3 compañeros de la universidad Javeriana que son programadores y ellos me van a brindar apoyo con la programación de la aplicación, y una compañera cercana a mí que estudio diseño industrial y me brindara apoyo con el diseño e imagen corporativa de la aplicación. Cuento con planta física para ubicar la oficina de nuestra empresa. Esta aplicación va dirigida principalmente a los habitantes de la ciudad de Bogotá, interesados en el cuidado de su salud combinado con medio de transporte, y personas correspondientes al estrato 2 en adelante, ya que son las personas que normalmente hacen uso de la bicicleta o que son personas potenciales para empezar hacer uso de la bicicleta. . La ciudad de Bogotá cuenta con 8’037.732 habitantes y este proyecto va ser desarrollado en toda la ciudad, toca tener en cuenta que la ciudad esta mesclada entre la diferente estratificación, no dirigimos a los estratos 2 y 3 que tenga la posibilidad de tener su Bicicleta y un celular tipo Smartphone, para los estratos 4, 5 y 6 sabemos que tiene la facilidad de obtener una bicicleta y ellos son nuestro usuario potencial el cual generaríamos un cambio y tomarían su bicicleta para hacer ejercicio como ocio y como medio de transporte. En cuanto a la proyección financiera para la aplicación, como se mencionó anteriormente, contamos con una gran ventaja, ya que la inversión requerida será menor debido a la propiedad con la que cuento para llevar a cabo el proyecto. Una propiedad de 60 metros cuadrados para empezar, la cual cuenta con salas de reunión y auditorio, un parqueaderos exteriores. Al hacer la calculación se va tener en cuenta el pago de un arriendo sin importan que sea de nuestra propiedad y así poder evidenciar realmente como es el estado financiero y no subsidiarla. Por otro lado, la inversión en efectivo que se necesitara será aproximadamente de $100.000.000 que serán $50.000.000 de mis padres y el restante saldrán de mis ahorros, Javier Amortegui Babativa, los cuales serán distribuidos para adecuación de planta, equipos y sistemas $17.616.880, para publicidad y mercadeo: $30.000.000, creación de la aplicación $34.000.000, sistemas IOS + Android $421.600, Gastos de composición empresarial y bancarios $11.000.000 y por último se va tener un provisión para imprevistos por el restante $6.961.520. Nuestras proyecciones de ventas han sido basadas en aplicaciones similares con un mismo formato de lucro con el tema de bicicletas pero no con la misma idea de negocio, nuestras proyecciones de ventas estimadas serán de $20.000.000 a $25.000.000 los primeros 3 meses, mientras tomamos fuerza en el mercado.