Today, there is an increasing demand for smart robots that can make decisions on their own and cooperate with humans in changing environments. The application areas for robotic arms with camera vision are likely to increase in the future of artificial intelligence as algorithms become more adaptable and intelligent than ever. The purpose of this bachelor’s thesis is to develop a robotic arm that recognises arbitrarily placed objects with camera vision and has the ability to pick and place the objects when they appear in unpredictable positions. The robotic arm has three degrees of freedom and the construction is modularised and 3D-printed with respect to maintenance, but also in order to be adaptive to new applications. The camera vision sensor is integrated in an external camera tripod with its field of view over the workspace. The camera vision sensor recognises objects through colour filtering and it uses an edge detection algorithm to return measurements of detected objects. The measurements are then used as input for the inverse kinematics, that calculates the rotation of each stepper motor. Moreover, there are three different angular potentiometers integrated in each axis to regulate the rotation by each stepper motor. The results in this thesis show that the robotic arm is able to pick up to 90% of the detected objects when using barrel distortion correction in the algorithm. The findings in this thesis is that barrel distortion, that comes with the camera lens, significantly impacts the precision of the robotic arm and thus the results. It can also be stated that the method for barrel distortion correction is affected by the geometry of detected objects and differences in illumination over the workspace. Another conclusion is that correct illumination is needed in order for the vision sensor to differentiate objects with different hue and saturation. / Idag ökar efterfrågan på smarta robotar som kan ta egna beslut och samarbeta med människor i föränderliga miljöer. Tillämpningsområdena för robotar med kamerasensorer kommer sannolikt att öka i en framtid av artificiell intelligens med algoritmer som blir mer intelligenta och anpassningsbara än tidigare. Syftet med detta kandidatexamensarbete är att utveckla en robotarm som, med hjälp av en kamerasensor, kan ta upp och sortera godtyckliga objekt när de uppträder på oförutsägbara positioner. Robotarmen har tre frihetsgrader och hela konstruktionen är 3D-printad och modulariserad för att vara underhållsvänlig, men också anpassningsbar för nya tillämpningsområden. Kamerasensorn ¨ar integrerad i ett externt kamerastativ med sitt synfält över robotarmens arbetsyta. Kamerasensorn detekterar objekt med hjälp av en färgfiltreringsalgoritm och returnerar sedan storlek, position och signatur för objekten med hjälp av en kantdetekteringsalgoritm. Objektens storlek används för att kalibrera kameran och kompensera för den radiella förvrängningen hos linsen. Objektens relativa position används sedan till invers kinematik för att räkna ut hur mycket varje stegmotor ska rotera för att erhålla den önskade vinkeln på varje axel som gör att gripdonet kan nå det detekterade objektet. Robotarmen har även tre olika potentiometrar integrerade i varje axel för att reglera rotationen av varje stegmotor. Resultaten i denna rapport visar att robotarmen kan detektera och plocka upp till 90% av objekten när kamerakalibrering används i algoritmen. Slutsatsen från rapporten är att förvrängningen från kameralinsen har störst påverkan på robotarmens precision och därmed resultatet. Det går även att konstatera att metoden som används för att korrigera kameraförvrängningen påverkas av geometrin samt orienteringen av objekten som ska detekteras, men framför allt variationer i belysning och skuggor över arbetsytan. En annan slutsats är att belysningen över arbetsytan är helt avgörande för om kamerasensorn ska kunna särskilja objekt med olika färgmättad och nyans.

Voiced communication plays a fundamental role in society. Voice research seeks to improve understanding of the fundamental physics governing voice production, with the eventual goal of improving methods to diagnose and treat voice disorders. For this thesis, three different aspects of voice production research were studied. First, porcine vocal fold medial surface geometry was determined, and the three-dimensional geometric distortion induced by freezing the larynx, especially in the region of the vocal folds, was quantified. It was found that porcine vocal folds are qualitatively geometrically similar to canine and human vocal folds, as well as commonly used models, and that freezing of tissue in the larynx causes distortion of around 5%. Second, a setup of multiple high-resolution cameras and a stereo-endoscopy system simultaneously recorded positions on the superior surface of synthetic, self-oscillating vocal fold models to estimate the error in the measurement of the three-dimensional location by the stereo-endoscopy system. The error was found to be low in the transverse plane, whereas the error was relatively large in the inferior-superior direction, suggesting that the stereo-endoscope is applicable for in vivo measurements of absolute distances of the glottis in the transverse plane such as glottal length, width, and area. Third, a function for strain-varying Poisson's ratio for silicone was developed from experimental data. It is anticipated that the findings herein can aid voice researchers as they study voice production, leading to improved voice care.

This thesis presents four-quadrant CMOS current-mode multiplier architectures based on the bipolar Gilbert cell multiplier architecture. Multipliers are designed using the CMOS subthreshold region to take advantage of the subthreshold exponential I-V relationship that closely matches bipolar modeling. It is discovered that biasing to remove drift current components and to address higher order effects such as ideality factor mismatch, threshold mismatch, body effect, and short channel effects, is important to provide a linear multiplier. It is also shown that distortion caused by device size mismatch and offset input currents can be used to cancel the distortion introduced by drift currents when designing in weak and moderate inversion. This concept allows for linear multiplier designs with larger input currents which results in dramatic improvements in bandwidth over traditional weak inversion circuits. Three multiplier circuits are simulated and fabricated in an AMIS 0.35-um process. Circuits with less than 1 % nonlinear error and distortion (THD) across 100 % dynamic input range and with bandwidths greater than 100 MHz can be built. Also, low power multiplier solutions are presented that consume less than 40 nW of dynamic power.

This thesis demonstrates that the composite cascode differential stage, operating in the subthreshold region, can form the basis of a high gain (113 dB) and low-power op amp (28.1 µW). The circuit can be fabricated without adding a compensation capacitance. The advantages of this architecture include high voltage gain, low bandwidth, low harmonic distortion, low quiescent current and power, and small chip area. These advantages suggest that this design might be well-suited for biomedical applications where low power, low noise bio-signal amplifiers capable of amplifying signals in the millihertz-to-kilohertz range is required.

With an increased availability of healthcare data and a rapid development of analysis techniques, artificial intelligence (AI) is currently contributing to a paradigm shift in healthcare. Areas that were previously considered only possible to be managed by human experts are now increasingly being managed with the help of AI. A large part of the research in this field points to the positive aspects that the introduction of AI in healthcare can bring. What is less often highlighted is the need for relevant data to ensure that the AI solutions generate results that promote equality. In order for this to happen, it is required, among other things, that the algorithms in the AI solutions are trained on neutral and objective data. The aim of this study is to use an exploratory design to investigate existing knowledge about bias in AI tools for decision support among clinical, Swedish healthcare personnel. This has been done via interviews with representatives from Swedish healthcare who work with AI. In the interviews, the status of knowledge about how data is created, implemented and used in AI for decision support was examined. The awareness of how this affects the results obtained in the form of bias and what is done to counteract this was investigated. The analysis of the respondents' answers showed that there is an indirect image of knowledge regarding bias and its consequences, but that this is not discussed in the terms that the research uses. Various different actions are performed that prevent the emergence of bias. Distinctive about the result, however, was that the respondents in many cases did not describe the motive for these actions. Actions seem to be carried out but this without fully knowing to what benefit. / Med en ökad tillgänglighet av sjukvårdsdata samt en snabb utveckling av analystekniker, bidrar just nu artificiell intelligens (AI) till ett paradigmskifte inom hälso- och sjukvården. Områden som tidigare ansågs att endast vara möjliga att skötas av mänskliga experter, börjar nu till en allt större del att skötas med hjälp av AI. En stor del av forskningen i detta fält pekar på de positiva aspekter som införande av AI inom vården kan bära med sig. Det som mer sällan lyfts fram är behovet av relevant data för att säkra att AI- lösningarna genererar resultat som främjar jämlikhet. För att detta ska kunna ske krävs bland annat att algoritmerna i AI-lösningarna tränas på neutral och objektiv data.  Syftet med denna studie är att genom en explorativ design undersöka existerande kunskap om bias i AI-verktyg för beslutsstöd bland klinisk, svensk hälso- och sjukvårdspersonal. Detta har gjorts via intervjuer med representanter från svensk hälso- och sjukvård som arbetar med AI. I intervjuerna undersöktes status för kunskap kring hur data skapas, implementeras och används i AI för beslutsstöd. Medvetenheten om hur detta påverkar det resultat som erhålls i form av bias och vad som görs för att motverka detta undersöktes. Analysen av respondenternas svar visade på att det finns en indirekt kunskap gällande bias och konsekvenserna av dessa men att det inte talas om detta i de termer som forskningen använder. Diverse olika handlingar utförs som förebygger uppkomst till bias. Utmärkande för resultatet var dock att respondenterna i många fall inte beskrev motivet med dessa handlingar. Handlingar verkar utföras men detta utan att helt veta till vilken nytta.

Despite the developmental and clinical importance of body image during the pre-adolescent and adolescent years, there remains a dearth of information on the body image experiences of immigrant children and adolescents. This thesis represents a purposeful attempt to examine body image experiences among immigrant and ethnic minority children and adolescents in Canada and the United States (US). Specifically, the thesis integrates multiple methods (scoping reviews, qualitative interpretive description, quantitative multi-level modeling) and samples (clinical and population-based samples) to systematically contribute to the academic literature focusing on body image experiences among immigrant and ethnic minority children and adolescents in Canada and the US. Consisting of four conceptually related studies, this thesis makes the following methodological and conceptual contributions to epidemiological and clinical research and practice. First, the results from all four studies point to the need to develop standardized approaches for identifying and classifying immigrant and ethnic-minority children and adolescents. This will substantially increase the field’s ability to systematically characterize the nature and magnitude of body image dissatisfaction, body image distortion, and their associated outcomes among immigrant and ethnic minority children and adolescents. In addition, this systematic classification has the potential to inform the development or adaptation of universal and targeted preventative intervention strategies. Second, Study’s 1 and 2 demonstrate a clear need to further examine the constructs and experiences of acculturation and acculturative stress in relation to the body image experiences of immigrant and ethnic minority children and adolescents. The literature is unclear with respect to whether or not immigrant adolescents’ adoption of the values, behaviours and ideals of the Canadian or US culture increases their risk for body image concerns. On the other hand, we are also unclear as to whether or not immigrant adolescents’ retaining of the values, behaviours and ideals of their culture of origin may offer protection from poor body image experiences. Similarly, we are unclear about whether—and to what extent—stress as a result of adolescents’ acculturative experiences (i.e. acculturative stress) influence the onset or pervasiveness of body image concerns. Greater understanding about these constructs and processes and the extent to which they are implicated in the body image experiences among immigrant children and adolescents has the potential to inform culturally competent and targeted intervention approaches. Results from Study 3 indicate that immigrant adolescents have body image and appearance-related concerns that extend beyond what has typically been found among non-immigrant adolescents. More specifically, immigrant adolescents are concerned about the appearance of their skin (texture, complexion), their hair, their teeth, as well as other bodily features. It would be prudent for future researchers and clinicians to consider this information in relation to measuring, classifying and addressing body image dissatisfaction among immigrant adolescents. Finally, Study 4 demonstrates that females and first generation immigrants with body image dissatisfaction are at significantly elevated risk for body image distortion. This suggests that the assessment and intervention for body image dissatisfaction—particularly among females—soon after the migratory experience may play an important role in reducing body image distortion experiences. Taken together, the findings of this thesis strengthen the body image field by demonstrating that there are several unique aspects about being an immigrant that can influence adolescents’ body image experiences; and therefore, should be considered from a conceptual and methodological standpoint in future research and implementation of body image interventions. / Dissertation / Doctor of Philosophy (PhD) / Body image dissatisfaction and body image distortion have been linked to serious psychological outcomes, including depression and eating disorders. Yet, we know very little about the nature of these experiences among immigrant and ethnic minority children and adolescents. This thesis uses qualitative and quantitative methods, as well as general population and clinical samples to investigate body image dissatisfaction and body image distortion among immigrant and ethnic minority children and adolescents in Canada and the United States. Results provide important information that can inform the development of preventative interventions targeting body image dissatisfaction and body image distortion among immigrant and non-immigrant children and adolescents.

The objective of this research work is to investigate, design and measurement of a digital predistortion linearizer that is able to compensate the dynamic nonlinear distortion of a High Power Amplifier (PA). The effectiveness of the proposed baseband predistorter (PD) on the performance of a WLAN OFDM transmitter utilizing a nonlinear PA with memory effect is observed and discussed. For this purpose, a 10W Class-A/B power amplifier with a gain of 22 dB, operated over the 3.5 GHz frequency band was designed and implemented. The proposed baseband PD is independent of the operating RF frequency and can be used in multiband applications. Its operation is based on the Hammerstein system, taking into account PA memory effect compensation, and demonstrates a noticeable improvement compared to memoryless predistorters. Different types of modelling procedures and linearizers were introduced and investigated, in which accurate behavioural models of Radio Frequency (RF) PAs exhibiting linear and nonlinear memory effects were presented and considered, based on the Wiener approach employing a linear parametric estimation technique. Three new linear methods of parameter estimation were investigated, with the aim of reducing the complexity of the required filtering process in linear memory compensation. Moreover, an improved wiener model is represented to include the nonlinear memory effect in the system. The validity of the PA modelling approaches and predistortion techniques for compensation of nonlinearities of a PA were verified by several tests and measurements. The approaches presented, based on the Wiener system, have the capacity to deal with the existing trade-off between accuracy and convergence speed compared to more computationally complex behavioural modelling algorithms considering memory effects, such as those based on Volterra series and Neural Networks. In addition, nonlinear and linear crosstalks introduced by the power amplifier nonlinear behaviour and antennas mutual coupling due to the compact size of a MIMO OFDM transmitter have been investigated.

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