Mobilnotifikationer är ett relativt nytt fenomen och mobilanvändare idag får allt fler notifikationer skickade till sig per dag. Hur de faktiskt påverkar användare, både sett till mobilanvändning och användarbeteenden, är fortfarande ett tämligen outforskat område. Denna studie utforskar hur mobilnotifikationer påverkar studenters upplevda stressnivåer och fokus under schemalagda skolaktiviteter. För att undersöka detta jämfördes en normal vecka med en vecka då notifikationer tystades med hjälp av stör-ej-funktionen i mobiltelefonen. Under denna period loggades mobilanvändningen och deltagarna fick föra en dagbok för reflektioner kring sitt beteende under dagen. Undersökningen avslutades med semi-strukturerade intervjuer. Resultaten av undersökningen visade att mobilanvändningen höll en jämn nivå under hela undersökningen. Ingen stress upplevdes av deltagarna i samband med mottagna notifikationer i skolmiljön, däremot upplevdes bättre fokus då stör-ej-funktionen aktiverades och notifikationerna tystades. Ett samband mellan få antal mottagna notifikationer och bättre upplevt fokus upptäcktes.  Undersökningen har även haft ett metodologiskt syfte då fler undersökningar krävs i detta område. En slutsats vi drar efter avslutad studie är att tillvägagångsättet lämpar sig bra för att jämföra upplevd med faktisk mobilanvändning. Kombinationen dagbok och semi-strukturerade intervjuer var även ett bra tillvägagångssätt för att fånga upp deltagarnas beteenden och reflektioner. / The average user receives approximately 46 smartphone notifications every day. But there is little research regarding how users are affected by them. In this paper we assess the impact of mobile notifications in learning situations with regards to perceived stress and focus. This was achieved by monitoring the users’ mobile usage during two weeks. The first week, they proceeded as normal. During the second week they were asked to activate the do-not-disturb mode during scheduled school activities. During this time their mobile usage was documented both through software and from daily occurring survey. This was followed up by semi-structured group interviews. The results showed that the mobile usage remained the same during the second week. The participants were not stressed at all but there was an increase in perceived focus when the do-not-disturb mode was switched on. The results show a relation between a low number of received notifications and increased perceived focus. The study was also carried out with a methodological purpose, since the area is rather new. We came to the conclusion that the method is appropriate for investigating the differences between perceived and actual mobile usage. The study was successful in its implementation of daily occurring surveys and semi structured interviews. This combination allowed for great user reflections.

Smartphone capnography is a new concept for respiratory monitoring using a colorimetric sensor in combination with a smartphone and an Android application. Compared to using an infrared spectrophotometric carbon dioxide analyzer (IR-analyzer), the gold standard for respiratory carbon dioxide monitoring, smartphone capnography offers a cheaper and less bulky solution. This master thesis evaluates the performance of smartphone capnography and the colorimetric sensor engineered for this concept. Three different techniques (side stream, shunt stream and main stream) were tested. Additionally, an iPhone application was developed as a proof of concept when using an iPhone for smartphone capnography.   An experimental set-up simulating human breathing was assembled and measurements, at different breathing rates (6-30 breaths/min) and carbon dioxide levels (2-7vol%), were performed with an IR-analyzer as reference. Results showed that capnograms from smartphone capnography was comparable to those from the IR-analyzer and that the approximate accuracy was ±0.25vol% for up to 6 days of use. Results strongly motivate further elaboration of the concept and the three different techniques for measuring. / ”Smartphone capnography” är ett nytt koncept för att monitorera andning. Principen är en kombination av en kolorimetrisk sensor, en smartphone samt en Androidapplikation. Jämfört med den dominerande tekniken, en IR-spektrofotometrisk koldioxidanalysator (IR-analysator), så är “smartphone capnography” både billigare och mindre skrymmande. Detta examensarbete utvärderar konceptet ”smartphone capnography” och en kolorimetrisk sensor speciellt utvecklad för ändamålet. Tre olika tekniker (side stream, shunt stream och main stream) har utvärderats. Slutligen utvecklades en iPhoneapplikation för att visa att konceptet ”smartphone capnography” kan användas även med denna typ av smartphone.   Utvärderingen bestod i att göra mätningar i en experimentell uppställning som simulerar andning. Mätningar gjordes vid varierande andningsfrekvenser (6-30 andetag/min) och koldioxidnivåer (2-7vol%). Mätdata från ”smartphone capnography” jämfördes med mätdata från en IR-analysator. Resultaten visar att kapnogram från ”Smartphone capnography” är jämförbara med kapnogram från IR-analysatorn och att den uppskattade noggrannheten är ±0,25vol% för upp till 6 dagars användning. De goda resultaten motiverar fortsatt utveckling av konceptet smartphone capnography samt de olika mätteknikerna.

[pt] Os dispositivos móveis estão amplamente presentes no cotidiano das pessoas. Com a difusão dos smartphones, surgem conflitos e incômodos por conta das interrupções e intrusões dos aparelhos durante interações sociais, fenômeno denominado como tecnoferência por McDaniel e Coyne (2016). Esta pesquisa buscou investigar a influência do uso de smartphones na relação entre pais e filhos e entender deque forma a presença da tecnologia interfere no contexto familiar. Participaram do estudo 30 responsáveis de crianças de 8 e 9 anos de idade provindos dos estados do Rio de Janeiro, Minas Gerais, Curitiba e Goiás, de diferentes faixas econômicas. Foram realizadas entrevistas semiestruturadas com os participantes por vídeo chamada via WhatsApp durante o período da pandemia de Covid-19. Os dados foram analisados com o software ATLAS.ti, sendo adotada a abordagem quali-quantitativa. Dentre os principais resultados, destacam-se diferentes impactos da utilização do smartphone pelos pais nas interações com seus filhos. Foram percebidas associações entre tecnoferência – invasões do celular durante interações de pais com seus filhos – e conflitos no convívio familiar. As entrevistas apontam para incômodos dos responsáveis sobre seu próprio uso e sobre o uso dos outros membros da família gerando insatisfação e descontentamento. Em contraste, os responsáveis destacaram a utilização compartilhada da tecnologia touch screen como recurso aliado nas interações com os filhos. O presente trabalho traz indicações sobre a necessidade de discussões futuras dos benefícios e malefícios do uso de smartphones por pais e crianças no ambiente familiar. / [en] Mobile devices are present in people s lives. With the spread of smartphones, conflicts and annoyances arise due to interruptions and intrusions of devices during social interactions, a phenomenon called technoference by McDaniel and Coyne (2016). This research sought to investigate the influence of the use of smartphones on the relationship between parents and children and, thus, to understand how the presence of technology interferes in the family context. Thirty caregivers of 8 and 9 year old children from the states of Rio de Janeiro, Minas Gerais, Curitiba and Goiás, from different economic backgrounds participated in the study. Semi-structured interviews were conducted with participants via video calling using WhatsApp during the Covid-19 pandemic period. The data were analyzed using the ATLAS.ti software, within a qualitative and quantitative approach. Among the main results, different impacts stand out, such as the use of parents; smartphone during interactions with their children. Associations were noticed between technoference - cell phone invasions during interactions between parents and their children - and conflicts in family life. The interviews point to parents; worrying about their own use of the technology, and about the use of other family members, generating dissatisfaction. On the other hand, parents also highlighted the shared use of touch screen technology as an ally resource in interactions with their children. The present research provides indications about the need for future discussions regarding the benefits and harms of the use of smartphones by parents and children in the family environment.

Smartphones are capable of a multitude of things, yet it is still common to hear about the smartphone as a whole as being harmful to humans. In order to challenge the perception of smartphones as harmful, a concept was manifested in the form of seven iterations of prototypes. The concept, called Broadcastr, revolved around broadcasting to one's immediate surroundings what one was doing on one's smartphone. While continuously developing the prototypes, the concept was evaluated by the researcher. Evaluation occurred both in the process of prototyping itself as well as by exposing it to other people. The final design consisted of a Raspberry Pi Zero W, which was connected to an Android app via Bluetooth. The Android app ran in the background and monitored whether a new app was activated by the smartphone user. When this happened, a message was sent to the Raspberry Pi, which would display an icon on a 0.9" 128x64 OLED display, which corresponded to the category of the app being activated. It was found that the prototype showed an indication of being capable of challenging perceptions of the smartphone as being harmful, and that it became a useful tool for others to know what the smartphone user was doing. Finally, two possible future research projects were presented. One project would focus on another type of device's activity being broadcasted, while the other would introduce the broadcasting device to a high school class to study its effects.

Rapporten beskriver processutvecklingen av integration inom smart-enheter och gör jämförelse med de traditionella datormodeller som exempelvis TensorFlow. Maskininlärning är ett område som för närvarande observeras av många människor på grund av dess anmärkningsvärda önskan inom olika intelligenta områden som datorseende, naturlig språkbehandling, föreslagna datorsystem, etcetera. Problem med utdata och tidsserier. Resursbegränsningen av smart-enheter gör det svårt att uppfatta olika aktiviteter som helt annorlunda än en stor process. En rekommenderad användarvänlig process för att utföra design, utveckling, utvärdering och leverans av maskininlärning-modeller för resurs begränsade inbäddade enheter. TensorFlow och TensorFlow Lite valdes ut för att utföra examensarbetet som tillhandahåller arbetsflödet för en maskininlärning-modell designad för en dator, bärbar dator eller en komprimerad och optimerad version av samma modell integrerad på en enda enhet har begränsade resurser. Modellerna jämförs och resultaten erhålls. Resultatet det visar sig att TensorFlow Lite-modellen är extremt starkt integrerad med maskininlärning i inbyggda enheter Lagringen av den utvecklade modell filen, tid det tog för att förutsäga värdet jämfördes. Resultaten visade att TensorFlow Lite-modellen var korrekt i jämförelse med basmodellen, då storleken på TensorFlow Lite var 60 % mindre än basstorleken och responstid för TensorFlow Lite-modellen var 70 % mindre än basmodellen. Detta visar att det finns en möjlighet att integrera maskininlärning i enheter med den process som föreslås i avhandlingen. Slutligen är modellen gjord på en Android-smartphone, dess praktiska funktionalitet och genomförbarhet har visat. Ramverket har ett unikt och pålitligt tillvägagångssätt, vilket ger flexibilitet samtidigt som det klarar utmaningen att integrera i Android-enheter. / The thesis describes development of Machine learning (ML) integration procedure in smartphone and provides a comparison with the traditional computer models like TensorFlow. Machine learning is a field that promotes a lot of observation in the current era due to its notable desire in various Intelligent applications such as computer vision, natural language processing, recommendation systems, and time series problems. The limitation of resources on a smartphone makes it challenging to apprehend varied completely different activities with high precision. A user-friendly procedure is proposed to perform the designing, development, evaluation and deployment of Machine learning models for embedded devices with limited resources. TensorFlow (TF) and TensorFlow lite (TF Lite) were selected to perform the task. The thesis provides the procedure of a base Machine learning model designed for a computer, laptop or a machine to a compressed and optimized version of the same model for integration on a device with limited resources. The models were compared, and results were obtained. It was found that the TensorFlow lite model is extremely favorable for Machine learning integration in embedded devices. The storage of the developed model file and the time taken for the prediction of the value was compared. The results showed that the TensorFlow lite model was as accurate as the basic model, the size of the TensorFlow lite model was 60% less than the size of the base model and the response time of the TensorFlow lite model was 70% less than the base model. This showed that the Machine learning integration to the embedded devices is promising with the procedure proposed in the thesis. Finally, the model was deployed in the android smart phone and its practicality and feasibility of use was showed. The framework adopts a unique and reliable approach that provides flexibility while passing the challenge of Machine learning integrated in the android device.

The amount of force or power when applied can move one object from one position to another or the capacity of a system to do work is called energy. It exists in everybody whether they are human beings or animals or non-living things. There are many forms of energy such as: kinetic, potential, light, sound, gravitational, elastic, electromagnetic or nuclear. According to the law of conservation of energy, any form of energy can be converted into another form and the total energy will remain the same. Energy can be broadly classified into two main groups’ i.e. renewable and nonrenewable resources. Many of the renewable energy a technology have been around for years, and as the time go by, are increasing in efficiency. Keywords: solar panel improvement, motor control, energy –efficient Solarplatten, Motosteuerung, Energieeffizenz

Background: With the adoption of smartphones, a new mean of communication emerged for businesses, calling for deep knowledge on how to leverage this profitable direct-link to consumers. However, previous literature has mainly studied the subject from a quantitative standpoint with a theoretical foundation built on traditional advertising, hence, not studying the subject on its own. It is therefore relevant to study the topic from the ground up, exploring users perspective on main factors driving their attitudes towards mobile advertising.Purpose: To explore consumer attitudes toward mobile advertising.Methodology: A qualitative exploratory study based on 4 focus groups, sampled through convenience sampling and analysed using direct content analysis.Conclusion: Findings indicate that, mobile advertising lack credibility, which drives negative attitudes and that entertainment was non-present in mobile advertising. Perceptions expressed a vast element of irritation and that informativeness depends on the relevance of ads forming the outcome of attitude. Additionally, personalization emerged as a component influencing the majority of the studied factors, and consequently suggested to be further studied as a factor on its own.

ITC/USA 2015 Conference Proceedings / The Fifty-First Annual International Telemetering Conference and Technical Exhibition / October 26-29, 2015 / Bally's Hotel & Convention Center, Las Vegas, NV / Falls prevention efforts for older adults have become increasingly important and are now a significant research effort. As part of the prevention effort, analysis of gait has become increasingly important. Data is typically collected in a laboratory setting using 3-D motion capture, which can be time consuming, invasive and requires expensive and specialized equipment as well as trained operators. Inertial sensors, which are smaller and more cost effective, have been shown to be useful in falls research. Smartphones now contain Micro Electro-Mechanical (MEM) Inertial Measurement Units (IMUs), which make them a compelling platform for gait data acquisition. This paper reports the development of an iOS app for collecting accelerometer data and an offline machine learning system to classify a subject, based on this data, as faller or non-faller based on their history of falls. The system uses the accelerometer data captured on the smartphone, extracts discriminating features, and then classifies the subject based on the feature vector. Through simulation, our preliminary and limited study suggests this system has an accuracy as high as 85%. Such a system could be used to monitor an at-risk person's gait in order to predict an increased risk of falling.

In this thesis we look into usability in the context of smartphone applications. We selected three research areas to investigate, namely Wireless Personal Area Networks, Context-awareness, and Remote Information Access. These areas are investigated through a series of experiments, which focuses on important aspects of usability within software applications. Additionally, we mainly use smartphone devices in the experiments. In experiment 1, Multi-Platform Bluetooth Remote Control, we investigated Wireless Personal Area Networks. Specifically, we implemented a system consisting of two clients, which were created for Java ME and Windows Mobile, and integrated with a server application installed on a Bluetooth-enabled laptop. For experiments 2 and 3, Context-aware Meeting Room and PainDroid: an Android Application for Pain Management, we looked closely at the research area of Contextawareness. The Context-aware Meeting Room was created to automatically send meeting participants useful meeting notes during presentations. In experiment 3, we investigated the use of on-device sensors for the Android platform, providing an additional input mechanism for a pain management application, where the accelerometer and magnetometer were used. Finally, the last research area we investigated was Remote Information Access, where we conducted experiment 4, Customised Android Home Screen. We created a system that integrated both a cloud-based server application and a mobile client running on the Android platform. We used the cloud-computing platform to provide context management features, such as the ability to store the user configuration that was automatically pushed to the mobile devices.

The easy access to the Internet, computers and mobile devices brings new technological means of ability testing. The aim of this thesis is to investigate whether there is any difference in the results when an ability test of deductive reasoning is administered with two different platforms, computer and smartphone. In an experiment with within-subjects design the differences between platforms when it came to the level of the test score and usability were investigated. In addition, the test-retest reliability in the ability test was assessed. No significant differences between the scores from the platforms were observed. However, test-retest reliability was low and between r = .372 for smartphone and r = .526 for computer. The low reliability can explain why the score levels with different platforms could not be separated. The usability results indicate that the participants preferred to take the test with a computer, rather than with a smartphone, where even the most experienced users of smartphones disfavor test delivered on smartphone. It is recommended to replicate the experiment with more participants, and also with other handheld platforms, like tablet PC. / Den enkla tillgången till Internet, datorer och smarttelefoner innebär nya tekniska möjligheter till begåvningstestning. Syftet med detta examensarbete är att undersöka om det blir någon skillnad i resultat när ett begåvningstest för deduktiv förmåga utförs på två olika plattformar, dator och smarttelefon. I ett experiment med inompersonsdesign undersöktes skillnaderna mellan plattformarna när det gällde nivå hos testpoäng och användbarhet. Dessutom studerades begåvningstestets test-retest-reliabilitet. Inga signifikanta skillnader mellan testresultaten för det två plattformarna observerades. Test-retest-reliabiliteten var dock låg och varierade mellan r=.372 för smarttelefon och r=.526 för dator. Den låga reliabiliteten kan förklara varför poängnivåerna vid olika plattformar inte kunde skiljas åt. Gällande användbarheten indikerar resultatet att deltagarna föredrog att ta testet på dator framför smarttelefon, där även de mest mobilvana svarade till smarttelefonernas nackdel. Rekommendation för fortsatta studier är att replikera experimentet med större urval, samt att även testa med övriga handhållna datorer, som pekplattor.