With the rapid development of computers and technology, virtual assistants (VA) are becoming more and more common and intelligent. However, virtual assistants, such as Apple's Siri, Amazon's Alexa, and Google Assistant, do not currently have any physical functions. As an important part of the internet of things (IoT), the field of robotics has become a new trend in the usage of VA. In this project, a mobile robot, Fetch, is connected with the Amazon Echo Dot through the Amazon web service (AWS) and a local robot operation system (ROS) bridge server. We demonstrated that the robot could be controlled by voice commands through an Amazon Alexa. Given certain commands, Fetch was able to move in a desired direction as well as track and follow a target object. The follow model was also learned by Neural Network training, which allows for the target position to be predicted in future maps. / Master of Science / Nowadays, virtual personalized assistants (VPAs) exist everywhere around us. For example, Siri or android VPAs exist on every smartphone. More and more people are getting household Virtual Assistants, such as Amazon Alexa, Google Assistant, and Microsoft's Cortana. If the virtual assistants can connect with objects which have physical functions like an actual robot, they will be able to provide better services and more functions for humans. In this project, a mobile robot, Fetch, is connected with the Echo dot from Amazon. This connection allows us to control the robot by voice command. You can ask the robot to move in a given direction or track and follow a certain object. In order to let the robot learn how to predict the position of the target when the target is lost, a map is built as an influence factor. Since a designed algorithm of target position prediction is difficult to implement, we opted to use a machine learning method instead. Therefore, a machine learning algorithm was tested on the following model.

Multiple sclerosis is a complex disease and one for which the aetiology remains largely unanswered. Anti-dsDNA antibodies have been found intrathecally and bordering lesions in multiple sclerosis patients and in view of their known pathogenity in lupus nephritis the aim of this project was to further investigate their role in multiple sclerosis. Using the acute experimental allergic encephalomyelitis (EAE) model in the Lewis rat, the inflammatory phase of disease was profiled using immunohistological and ELISA methods and was related to clinical sign severity. The parameters of interest were central nervous system deposits of IgM, IgG, B cells and C3 and anti-DNA antibodies in sera, cerebrospinal fluid and in situ. In situ evaluation of anti-dsDNA antibodies was also performed in tissue taken from Biozzi (AH) mice (relapsing/remitting EAE model) and from a multiple sclerosis patient. Inflammatory deposits specifically at sites of perivascular cuffing were found to increase with increasing clinical sign severity. At the time clinical signs had plateaued in the Lewis rat, intrathecal anti-dsDNA antibodies were at their highest level and anti-ssDNA antibodies at their lowest. The latter possibly due to their involvement in the 'clearing-up' process following tissue damage. Using novel DNA probes fluorescence suggestive of the presence of anti-dsDNA iii antibodies was seen in both animal and human tissue. Within human tissue the antibodies appeared to accumulate around active lesions and within vessels, raising the question of these antibodies having differing location dependent functions. EAE models have the potential to investigate these findings further and to evaluate new therapies.

Alkaline glutaraldehyde (GTA) has been used as a high level chemical disinfectant and sterilant for many years and is known to kill a broad spectrum of organisms ranging from vegetative eukaryotes to bacterial endospores. Although the mechanism of sporicidal action has been studied on numerous occasions, GTA's exact mechanism(s) of action are still debated. In addition to the uncertainty of GTA's mechanism(s) of action, GTA has also shown significant variability in the time required to kill endospores and naked viruses. A better knowledge of the lethal mechanism(s) of GTA is needed to understand this discrepancy in kill times for GTA against spores of different species. Similar trends have been observed in GTA's activity against non-enveloped viruses. Based on previous work, one proposed major mechanism of GTA's sporicidal activity is related to the number of available primary amines located on the surface of microbes. In this study, we have compared the efficacy of GTA on spores from 5 Bacillus species. We have also developed a method for staining these spores with amine reactive dyes to create fluorescent profiles correlating to the abundance of free amino groups on each spore type. We also describe a method for staining non-enveloped viruses to identify exposed primary amino groups on capsid proteins that may act as targets for GTA, using amine reactive Gold nanoparticles. We found that GTA 6-Log10 reduction times for various spore types varied at both the batch and species level. Spore coat thickness and fluorescence were useful tools in predicting the susceptibility of spores to GTA. Amine reactive gold particles (AuNPs) also proved useful in identifying virus susceptibility to GTA. Ultimately, more reliable disinfection testing methods are needed, and caution should be used when trying to extrapolate data generated from surrogate organisms to other species.

The purpose of this research is to measure the social shifts that take place in a home where artificial intelligent (AI) devices like Echo Dot and Google Home are fully integrated into their everyday life. Research is currently limited, being that the widespread use of these devices is roughly seven years old. Three main outcomes of this study were related to how often Alexa is being used in homes to solve everyday problems, the lack of overall privacy and security concerns users had, and the level of integration into the home as a member of the family. Some limitations and challenges are my ability to compare the households before and after installing these devices in the home; pinpointing when and where the device is used (i.e., room placement); collecting data on whether the device is used often or sparingly; and the depth of interactions these families actually have with the device on a whole. The broader implications behind the increased integration of AI devices is centered around health, labor, social inequality and ethics.

Multiple sclerosis is a complex disease and one for which the aetiology remains largely unanswered. Anti-dsDNA antibodies have been found intrathecally and bordering lesions in multiple sclerosis patients and in view of their known pathogenity in lupus nephritis the aim of this project was to further investigate their role in multiple sclerosis. Using the acute experimental allergic encephalomyelitis (EAE) model in the Lewis rat, the inflammatory phase of disease was profiled using immunohistological and ELISA methods and was related to clinical sign severity. The parameters of interest were central nervous system deposits of IgM, IgG, B cells and C3 and anti-DNA antibodies in sera, cerebrospinal fluid and in situ. In situ evaluation of anti-dsDNA antibodies was also performed in tissue taken from Biozzi (AH) mice (relapsing/remitting EAE model) and from a multiple sclerosis patient. Inflammatory deposits specifically at sites of perivascular cuffing were found to increase with increasing clinical sign severity. At the time clinical signs had plateaued in the Lewis rat, intrathecal anti-dsDNA antibodies were at their highest level and anti-ssDNA antibodies at their lowest. The latter possibly due to their involvement in the `clearing-up¿ process following tissue damage. Using novel DNA probes fluorescence suggestive of the presence of anti-dsDNA iii antibodies was seen in both animal and human tissue. Within human tissue the antibodies appeared to accumulate around active lesions and within vessels, raising the question of these antibodies having differing location dependent functions. EAE models have the potential to investigate these findings further and to evaluate new therapies. / Covance Laboratories Ltd.

No description available.

During these last recent years cloud computing and cloud services have started to gain traction, which has been most notable among companies. Amazon have proven to be one of the powerhouses on providing scalable and flexible cloud computing services. However, cloud computing is still a relatively new area. From an outsider’s point of view, the overwhelming information and available services might prove to be difficult to familiarize with. The aim of this thesis is to explore how Amazon Web Services can be applied during software development and observing how difficult it might be to use these services. Three test applications that utilized different Amazon Web Services were implemented to get an insight into how Amazon Web Services can be applied from a cloud computing beginner’s point of view. These applications were developed in an iterative manner, where a case study was performed on each application. At the start of each new iteration a literature study was conducted, where sources were reviewed to see if it provided essential information. In total, nine different Amazon Web Services were used to implement and test the three respective test applications. Results of the case study were interpreted and evaluated with regards to the learnability and appliance of Amazon Web Services. Issues that were identified during the development process showed that Amazon Web Services were not userfriendly for users that have little to no experience with cloud computing services. Further research on other Amazon Web Services, such as Elastic Cloud Computing, as well as other cloud computing platforms like Google or IBM, may provide a deeper and more accurate insight on the appliances of cloud computing. / Under dem senaste åren så har molntjänster blivit ett allt mer populärt område, speciellt inom företag. Ett av dem största utgivare inom molntjänst branschen är Amazon som erbjuder skalbara och flexibla molntjänster. Molntjänster är dock ett relativt nytt område, vilket innebär att någon som inte är insatt i ämnet kan finna all tillgänglig information överväldigande och svår att bekanta sig med. Målet med det här tesen är att utforska olika Amazon Web Service som kan användas inom mjukvaruutveckling och observera problem som kan uppstå med dessa tjänster. Tre testapplikationer som använde sig av Amazon Web Services var skapade för att få en fördjupad kunskap om hur dessa tjänster fungerar och vad för möjligheter de har. Dessa applikationer utvecklades iterativt och en fallstudie utfördes för varje applikation. I början av varje ny iteration genomfördes en litteraturstudie, där källorna var kritiskt granskade för att se ifall dem innehöll väsentlig information för tesen. Sammanlagt användes nio olika Amazon Web Services för att implementera och testa de tre olika testapplikationerna. Resultaten från fallstudien tolkades och utvärderades med avseende på Amazon Web Services lärbarhet och tillämpningsbarhet. Problem som samlades ihop under utvecklingsprocessen visade att Amazons Web Services inte var särskilt användarvänligt för utvecklare med liten eller ingen erfarenhet inom Amazon Web Services. Ytterligare forskning inom andra Amazon Web Services som Elastic Cloud Computing och forskning som undersöker andra molntjänst plattformar som Google Cloud, skulle kunna bidra med en djupare förståelse och mer exakt inblick kring tillämpning av molntjänster.

There is an ever-growing and increasing amount of technology options that use speech recognition software. Currently, the market includes smartphones, computers, and individual smart home personal assistants that allow for hands-free access to this technology. Research studies have explored the utility of these assistive devices for the completion of activities of daily living; however, there is limited research looking at the accuracy of voice recognition software within smart home personal assistants in populations with disordered speech. In persons with amyotrophic lateral sclerosis (ALS), symptoms include changes to motor functions, speech in particular, and it is unknown how some of these devices may respond to their disordered speech. The present study aimed to examine the accuracy of the Amazon Echo to respond appropriately to commands given by dysarthric patients with ALS. Participants were asked to read a variety of commands to an Amazon Echo. The sentences and responses by the Amazon Echo were audio-recorded for transcription and intelligibility ratings, which were then analyzed to look for relationships between intelligibility, auditory-perceptual features of speech, and sentence type. Results revealed there was no significant relationship between command intelligibility and accuracy of response by the Amazon Echo, nor was there a significant relationship between any of the auditory-perceptual ratings and accuracy of response. There was, however, a significant and positive association between conversational intelligibility and accuracy of responses by the Amazon Echo. This study provides support for use of hands-free assistive technology in patients with ALS to aid in the maintenance of quality of life and activities of daily living.

Texte remanié de: Diss.--Hannover--Universität, 2005. / Notes bibliogr. Bibliogr. p. 435-459.

Zugl.: Heidelberg, Univ., Diss., 2007