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Smartphones are omnipresent and indispensable in today’s society. Research in psychology and education points to both helpful and detrimental implications of smartphone usage for performance and well-being. Competitive and high-performance athletes represent a subsection of a demographic deeply intrenched in smartphone usage, yet few studies have shed light on the impact of smartphones usage in athletes’ lives. The overarching aim of this research was to advance knowledge on athletes’ use of smartphones. The mixed methods research program, with sequential pacing and qualitative priority, was informed by a critical realist paradigm. Data were collected through focus groups, remote tracking and surveys, and individual interviews with competitive and high-performance athletes. The research culminated in four distinct but related studies and four articles. The purpose of Study 1 was to qualitatively investigate varsity athletes’ lived experiences with smartphones. Five focus groups were conducted with a sample of 21 varsity athletes (9 men, 12 women) representing nine different sports (i.e., track and field, basketball, rowing, fencing, Nordic ski, rugby, swimming, lacrosse, and soccer). The inductive and reflexive thematic analysis led to the creation of three main themes. The first theme pertained to general usage experiences (i.e., characteristics of usage, awareness and nature of usage, restrictions of usage), revealing that social media is a focal point of athletes’ usage. The other two themes concerned athletes’ concurrent experiences of negative (i.e., stress, distraction, disengagement) and positive (i.e., self-regulation, social connectedness) smartphone usage. The majority of varsity athletes (81%) self-identified as moderate or heavy smartphone users, and relied on their devices throughout the day for communication and self-management. Findings suggest that smartphone usage exists along a continuum of negative/unhelpful to positive/helpful usage rather than as distinct “good” or “bad” usage. Usage is complex and often paradoxical for sport preparation, performance, recovery, and well-being. The purpose of Study 2 was to develop and pilot test a novel research application designed to examine, in an ecologically valid way, the prevalence and features of smartphone usage among a sample of athletes, in tandem with a selection of psychosocial variables. An interdisciplinary research team was formed to create the mobile research application and measure its tracking ability and accuracy to inform Study 3. The smartphone usage of five (n = 5) studentathletes was tracked in real-time over a 15-day period. Participants also completed a mobile self-report survey on psychosocial variables deemed important to athletes’ performance and wellbeing (i.e., mindfulness, mental health, and self-regulation). Results of the pilot study demonstrated a sizable range in total hours of smartphone usage, with an average of 31.1 hours per week, predominantly for social media. Real-time smartphone usage averages surpassed athletes’ self-reported time spent studying (20h per week) and training for sport (11.4h per week). All participants reported moderate-to-high self-regulation capacity, mindfulness, and mental health. The pilot study provided proof of feasibility for a longitudinal study using the research application and methods. It afforded the opportunity to make technical adjustments based on participant feedback, enhance usability and ecological validity, and subject the data to preliminary algorithms to extract detailed information from a large data pool. Building on Study 2, the purpose of Study 3 was to investigate the prevalence and features of competitive student-athletes’ smartphone usage and psychosocial outcomes using a longitudinal in vivo design. Over the course of one year, student-athletes’ smartphone usage was automatically tracked via the mobile app they installed on their phone and they also completed a self-report survey through the app on a monthly basis to assess self-regulation, mindfulness, mental health, stress, loneliness, and perfectionistic self-presentation. Although 20 participants volunteered to complete the study, only 10 participants consistently completed the survey and were retained in the final dataset. Descriptive analyses showed that the student-athletes used their smartphones for an average of 24.15 hours per week, predominantly for social media, and they formed two distinct user groups (i.e., heavy and light usage). Psychosocial profiles revealed they had moderate-to-high psychosocial functioning and highly nuanced changes in psychosocial outcomes and usage over time. There were no significant relationships between amount of smartphone usage and psychosocial outcomes, except for one positive relationship between usage and mental health in the winter. Findings support a new wave of literature deemphasizing a simple negative relationship between smartphone usage and psychosocial outcomes, and encourage further study of individual characteristics, such as purpose of usage. This study illustrates that although it is resource intensive, it is feasible to leverage the smartphone as an in vivo research tool to collect complex, ecologically valid usage data in tandem with psychosocial self-reports. It lays a foundation for larger-scale studies to assess the impact of athletes’ usage on their psychosocial functioning. The purpose of Study 4 was to qualitatively examine the self-regulatory processes, conditions, and outcomes related to the smartphone usage of competitive and high-performance athletes, and to postulate a model to inform research and applied practice in this area. Guided by the results of the previous studies showing prevalent social media usage among athletes, Study 4 also furthered explored athletes’ use of social media. Twenty-four (n = 24) competitive and highperformance athletes from eight different sports participated in individual, in-depth interviews. A directed content analysis, informed by the models of self-regulated learning and self-regulatory strength, was performed to analyze the data. While many themes aligned with components of both or either self-regulation models, new themes were generated. To account for all the data and explain athletes’ smartphone usage in and around the sport setting, the “Self-regulation and Smartphone Usage Model” (SSUM) was created. The SSUM includes five broad components: (a) self-regulation capacity, (b) self-regulation processes, (c) conditions (i.e., context of usage, type of usage, awareness of usage, autonomy of usage, and concurrence of usage), (d) outcomes, and (e) self-regulation competencies. Findings support a paradoxical relationship between smartphone usage and self-regulation. On the one hand, athletes use their smartphones to engage and master helpful self-regulation processes and on the other, they face increased self-regulatory demands because of their smartphones—particularly social media—which can lead to self-regulatory depletion. Overall, the current research sheds light on a new facet of competitive athletes’ livesthe smartphone. It underscores a deeply individualized, nuanced relationship between athletes and their phones, regardless of age, sex, type of sport, or competitive level. These devices can both inhibit and facilitate self-regulation and influence performance and well-being. Regardless of the purpose of usage, smartphones must be effectively managed. Thus, athletes must develop self-regulatory competencies specifically for this tool. This research shows the value of tracking real-time usage of phones and provides a conceptual map for working with athletes to leverage the benefits of smartphone technology.

Mobiltelefoner har idag utvecklats till smarta datorer som kan ge ett brett utbud av information och tjänster som kan nås närsomhelst och överallt. Många menar att den ökade närvaron av mobila enheter kommer att påverka sättet hur folk tänker och beter sig, även när vi är ute och reser. På grund av den snabba utvecklingen har även spelandet blivit mer rörligt, och genom mobiltelefonerna flyttas den virtuella världen ut i den verkliga världen. Att tillämpa spelmoment i en annars inte spelrelaterad kontext kallas spelifiering, och metoden används huvudsakligen för att uppmuntra till motivation, nöje och engagemang. Designprocessen i det här arbetet handlar därför om hur man på bästa sätt tillämpar spelmoment i en turismkontext med syfte att bidra till en bättre och roligare upplevelse, och för att uppmuntra turister till att interagera med sin omgivning och för att lära sig mer om resmålet. Arbetet berör således ämnena turism, spel, spelifiering, och vad som motiverar till dessa.

This thesis sets out to investigate the representation of smartphones by one of the biggest English daily newspapers of the world – the New York Times – and further sheds light on the potential influence the newspaper has on the norms of smartphone behavior. The research is conducted in two parts. For the first research question through a quantitative and the second research question a qualitative content analysis of New York Times articles about smartphones from the years 2007 and 2016. For the content analysis as well as the analysis of the results three different theoretical frameworks are applied: Stuart Hall’s (1997b) representation theory, McGuire’s (2001) media effect factors and social norms theory, mainly according to Cristina Bicchieri (2017). Since assumptions on the outcome of research question one exist on the grounds of previous research conducted in the field, two hypotheses were formed:H1 – In 2007 the coverage of smartphones will be mainly positive and focus on technological aspects.H2 – In 2016 the coverage will be more critical about the consequences of the pervasion and influence of the smartphone in society.The main findings of the thesis are, for research question one, a validation of the hypotheses through the quantitative content analysis and application of the representation theory through which a distinction in the representation of the smartphones denotation and connotation could be made. And for research question two, that the strongest potential of influence on norms of smartphone behavior lies in conveying and updating and thus sometimes changing of empirical and normative expectations together with further intertwined factors.

The skill of cooking a meal from start to end is becoming a stressful every day activity in many homes in Denmark. Less and less parents focus on including their children in preparing dinner because they see it as a time-consuming activity that the child would rather be left out of. In this paper we examine the importance of teaching children how to cook from a young age as well as we investigate in why it can seem like such a big task for them to actually get started with cooking. The study focuses on how to develop an interactive tablet and smartphone application that provides children with an explorative platform for them to develop their cooking skills on. The detailed process of developing a simple tablet/smartphone application is explored in order to arrive at an understand of the challenges children face when cooking, how we encourage them to cook and how we facilitate them with the best possible options for this. By doing several explorative workshops and studying previous research about how children learn, understand and explore their creativity, we arrive at an understanding of the challenges, limits and benefits there would be with an application like this.

Internet of Things devices, such as smartphonesand smartwatches, are currently becoming widely accessible andprogressively advanced. As the use of these devices steadilyincreases, so does the access to large amounts of sensory data.In this project, we developed a system that recognizes certainactivities by applying a linear classifier machine learning modelto a data set consisting of examples extracted from accelerometersensor data. We obtained the data set by collecting data from amobile device while performing commonplace everyday activities.These activities include walking, standing, driving, and ridingthe subway. The raw accelerometer data was then aggregatedinto data points, consisting of several informative features. Thecomplete data set was subsequently split into 80% training dataand 20% test data. A machine learning algorithm, in this case,a support vector machine, was presented with the training dataset and finally classified all test data with a precision higher than90%. Hence, meeting our set objective to build a service with acorrect classification score of over 90%.Human activity recognition has a large area of application,including improved health-related recommendations and a moreefficiently engineered system for public transportation. / Internet of Things-enheter, så som smarta telefoner och klockor, blir numera allt mer tillgängliga och tekniskt avancerade. Eftersom användningen av dessa smarta enheter stadigt ökar, ökar också tillgången till stora mängder data från sensorer i dessa enheter. I detta projekt utvecklade vi ett system som känner igen vissa aktiviteter genom att tillämpa en linjär klassificerande maskininlärningsmodell på en uppsättning data som extraherats från en accelerometer, en sensor i en smart telefon. Datauppsättningen skapades genom att samla in data från en smart telefon medan vi utförde vardagliga aktiviteter, så som promenader, stå stilla, köra bil och åka tunnelbana. Rå accelerometerdata samlades in och gjordes om till datavektorer innehållandes statistiska mått. Den totala datauppsättningen delades sedan upp i 80% träningsdata och 20% testdata. En maskininlärningsalgoritm, i detta fall en supportvektormaskin, introducerades med träningsdatan och klassificerade slutligen testdatan med en precision på över 90%. Därmed uppfylldes vårt uppsatta mål med att bygga en tjänst med en korrekt klassificering på över 90%. Igenkänning av mänsklig aktivitet har ett stort användningsområde, och kan bidra till förbättrade hälsorekommendationer och en mer effektiv kollektivtrafik. / Kandidatexjobb i elektroteknik 2020, KTH, Stockholm

Video stabilization is an important aspect of video processing, especially for handheld devices where unintended camera movement can significantly degrade the resulting recording. This paper investigates four image based methods for video stabilization. The study explores the Lukas-Kanade, Inverse Compositional Lukas-Kanade, Farnebäck Optical Flow, and GMFlow methods, evaluating their sub-pixel accuracy, real-time performance, and robustness to in-frame motion such as a person walking in front of the camera. The results indicate that while all methods achieve sub-pixel precision, real-time execution on a mobile phone is not feasible with the current implementations. Furthermore, the methods exhibit varying levels of difficulty in handling in-frame motion, with RANSAC-based approaches partially compensating for non-camera-induced movement. The paper also discusses the potential of machine learning techniques, represented by GMFlow, in enhancing stabilization quality at the cost of computational complexity. The findings offer valuable insights for the development of more efficient and robust video stabilization solutions.

[EN] This thesis project has a different and innovative approach to detect seismic events in real time gaining knowledge of the community through a hierarchical architecture in 3 layers: The first layer, a low-cost distributed network which takes advantage of the current huge trend; the smartphone; a multi-sensor, multi-network, multi-task device embedded into a small processing computer able to be reprogrammed, for example, in an "accelerograph" through an efficient in precision and power consumption Android application. The second layer called Intermediate Server, corresponds to a computer with sufficient hardware to handle incoming messages from users of the first layer and deduce on these samples, if a seismic peak has occurred, and if appropriate, notify in real-time to the users (smartphones) gaining extra time in making a better decision involving harm reduction, as well as economic and structural losses, and most importantly human lives losses. It considers spatial and temporal analyzes obtaining a customizable server to the specific characteristics of the area. Finally, the third layer called the Control Center is the place where all the information from the lower levels makes sense, being the leader in the post-event emergency management; it can extend to a bidirectional help: first, users (smartphones) attend to Control Center with multimedia information from their environment (comments, videos and images) thus achieving an overview of the disaster in order to efficiently manage the various aid-centers; and second, it assists users through their own smartphones, with information that a particular user unknown but the Control Center knows by other users: roads destroyed, landslides, roads offline support centers, places of danger, etc.). All validated through an extensive evaluation of each layer through seismic data obtained from the National Geophysical Institute of the National Polytechnic School in Ecuador (IGEPN), data which part of this research is based; obtaining promising and relevant results alerting until 12 seconds ahead at the epicenter, reducing false positives and this time could be increased by further afield. / [ES] Este proyecto de Tesis presenta una diferente e innovadora pro-puesta para detectar eventos sísmicos en tiempo real obteniendo conocimiento de la comunidad mediante una arquitectura jerárquica en 3 capas: La primera capa, una red de sensores de bajo costo distribuida que aprovecha el gran boom electrónico actual, el smartphone; un equipo multi-sensor, multi-red, multi-procesamiento dentro de un pequeño ordenador capaz de ser reprogramado convirtiéndolo por ejemplo, en un "acelerógrafo" por medio de una aplicación en Android eficiente en precisión y consumo de energía. La segunda capa llamada Servidor Intermedio, corresponde a un ordenador con las capacidades suficientes para gestionar la llegada de mensajes provenientes de usuarios de la primera capa y deducir con estas muestras, si ha existido un pico sísmico o no, y si es el caso, notificar en tiempo real a los usuarios (smartphones) ganando tiempo extra en la toma de una mejor decisión que implique la reducción de daños y pérdidas tanto económicas, estructurales y lo más importante, vidas humanas. Este considera análisis tanto espaciales como temporales obteniendo un servidor personalizable a las características específicas de la zona. Por último, la tercera capa llamada el Centro de Control es el lugar donde toda la información de los niveles inferiores toma sentido siendo el líder en la gestión post-evento de la emergencia; permite extender a una ayuda bidireccional: primero cada smartphone asiste a éste con información multimedia de su entorno (comentarios, videos e imágenes) logrando así una visión global del desastre, y con esta, gestionar eficientemente a los diferentes cuerpos de ayuda; y segundo asistir a los usuarios por medio de su smartphone con información que un usuario en particular desconoce y que el Centro de Control conoce por otros usuarios: Carreteras destruidas, deslaves, caminos sin conexión, centros de apoyo, lugares de peligro, etc.). Todo validado mediante una extensa evaluación de cada una de las capas con información sísmica obtenida del Instituto Geofísico Nacional de la Escuela Politécnica Nacional del Ecuador (IGEPN), lugar donde se basa parte de esta investigación, obteniendo prometedores y relevantes resultados alertando hasta con 12 segundos de antelación en el lugar del epicentro, reduciendo los falsos positivos, y pudiendo incrementar este tiempo en lugares más alejados. / [CA] Aquest projecte de Tesi presenta una diferent i innovadora proposta per a detectar esdeveniments sísmics en temps real obtenint coneixement de la comunitat mitjançant una arquitectura jeràrquica en 3 capes: La primera capa, una xarxa de sensors de baix cost distribuïda que aprofita el gran boom electrònic actual, el l' smartphone; un equip multi-sensor, multi-xarxa, multi-processament dins d'un petit ordinador capaç de ser reprogramat convertint-ho per exemple, en un accelerògraf per mitjà d'una aplicació en Android eficient en precisió i consum d'energia. La segona capa anomenada Servidor Intermedi, correspon a un ordinador amb les capacitats suficients per a gestionar l'arribada de missatges provinents d'usuaris de la primera capa i deduir amb aquestes mostres, si ha existit un pic sísmic o no, i si és el cas, notificar en temps real als usuaris (smartphones) guanyant temps extra en la presa d'una millor decisió que implique la reducció de danys i pèrdues tant econòmiques, estructurals i el més important, vides humanes; aquest considera anàlisi tant espacials com a temporals obtenint un servidor personalitzable a les característiques específiques de la zona. Finalment, la tercera capa anomenada el Centre de Control és el lloc on tota l'informació dels nivells inferiors pren sentit sent el líder en la gestió post-esdeveniment de l'emergència; permet estendre a una ajuda bidireccional, primer cada smartphone assisteix a aquest amb l'informació multimèdia del seu entorn (comentaris, videos i imatges) aconseguint així una visió global del desastre i amb aquesta, gestionar eficientment als diferents cossos d'ajuda; i posteriorment assistir als usuaris per mitjà del seu smartphone amb informació que un usuari en particular desconeix i que el Centre de Control coneix per altres usuaris: Carreteres destruïdes, esllavissades, camins sense connexió, centres de suport, llocs de perill, etc.). Tot validat mitjançant una extensa avaluació de cadascuna de les capes amb informació sísmica obtinguda de l'Institut Geofísic Nacional de l'Escola Politècnica Nacional de l'Equador (IGEPN), lloc on es basa part d'aquesta recerca, obtenint prometedors i rellevants resultats alertant fins a amb 12 segons d'antelació en el lloc de l'epicentre, reduint els falsos positius i podent incrementar-se en llocs més allunyats. / Zambrano Vizuete, AM. (2015). ARQUITECTURA DE UN SISTEMA DISTRIBUIDO PARA GESTIÓN DE EMERGENCIAS SÍSMICAS [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/56002

Yes / This study aims to introduce a new phased array design with improved radiation properties for future cellular networks. The procedure of the array design is simple and has been accomplished on a low-cost substrate material while offering several interesting features with high performance. Its schematic involves eight air-filled slot-loop metal-ring elements with a 1 × 8 linear arrangement at the top edge of the 5G smartphone mainboard. Considering the entire board area, the proposed antenna elements occupy an extremely small area. The antenna elements cover the range of 21–23.5 GHz sub-mm-wave 5G bands. Due to the air-filled function in the configurations of the elements, low-loss and high-performance radiation properties are observed. In addition, the fundamental characteristics of the introduced array are insensitive to various types of substrates. Moreover, its radiation properties have been compared with conventional arrays and better results have been observed. The proposed array appears with a simple design, a low complexity profile, and its attractive broad impedance bandwidth, end-fire radiation mode, wide beam steering, high radiation coverage, and stable characteristics meet the needs of 5G applications in future cellular communications. Additionally, the smartphone array design offers sufficient efficiency when it comes to the appearance and integration of the user’s components. Thus, it could be used in 5G hand-portable devices.

Accurate measurement of soil moisture (SM) has a significant impact on agricultural production, hydrological modeling, forestry, horticulture, waste management, and other environmental fields. Particularly in precision agriculture (PA), high spatiotemporal resolution information about surface SM is crucial. However, the use of invasive SM probes and other sensors is expensive and requires extensive manpower. Moreover, these intrusive techniques provide point measurements and are unsuitable for large agricultural fields. As an alternative, this dissertation explores the remote sensing of surface SM by utilizing the surface reflectivity estimated from global navigation satellite systems reflectometry (GNSS-R) data acquired through smartphones and off-the-shelf, cost-effective U-blox global navigation satellite systems (GNSS) receivers. To estimate surface reflectivity, the GNSS receivers are attached underneath a small unmanned aircraft system (UAS), which flies over agricultural fields. Additionally, this dissertation investigates a fully custom UAS-based dual-polarized L-band microwave radiometric measurement technique over agricultural areas to estimate surface brightness temperature (����). The radiometer measures surface emissivity as ����, allowing for the estimation of surface SM while considering the detection and removal of radio frequency interference (RFI) from the radiometric measurements. This radiometer processes the data in near real-time onboard the UAS, collecting raw in-phase and quadratic (I&Q) signals across the study field. This feature mitigates the RFI onboard and significantly reduces post-processing time. In summary, this study highlights the utilization of smartphones and semi-custom GNSS receivers in conjunction with UAS-based GNSS-R techniques and UAS-based L-band microwave radiometry for the estimation of surface reflectivity and ����. The radiometric measurement of surface emissivity is related to surface reflectivity through the relationship (Emissivity = 1 -Reflectivity).