With arrival of affordable digital technology we are increasingly coming into contact with digital images. Cameras are no longer dedicated devices, but part of almost every mobile phone, PDA and laptop. This paper discusses methods for enhancing quality of digital images with focus on removing noise, creating high dynamic range (HDR) images and extending depth of field (DOF). It contains familiarization with technical means for acquiring digital image, explains origin of image noise. Further attention is drawn to HDR, from explaining the term, physical basis, difference between HDR sensing and HDR displaying, to survey and historical development of methods dealing with creating HDR images. The next part is explaining DOF when displaying, physical basis of this phenomenon and review of methods used for DOF extension. The paper mentions problem of acquiring images needed for solving given tasks and designs method for acquiring images. Using it a database of test images for each task was created. Part of the paper also deals with design of a program, that implements discussed methods, for solving the given tasks. With help of proposed class imgmap, quality of output images is improved, by modifying maps of input images. The paper describes methods, improvements, means of setting parameters and their effects on algorithms and control of program using proposed GUI. Finally, comparison with free software for extending DOF takes place. The proposed software provides at least comparable results, the correct setting of parameters for specific cases allows to achieve better properties of the resulting image. Time requirements of image processing are worse because designed software was not optimised.

This master’s thesis deals with the wavelet transform and its use in processing and removing noise from images acquired by nuclear magnetic resonance. It defines fundamental terms for this work as mother wavelet or thresholding. Above all, it describes the principle of wavelet transform, thresholding techniques and criteria for evaluating the effectiveness of filtration. It describes the relation between wavelet transforms and digital filter banks. The experimental section describes the designed filtering method for removing noise from an image captured by the technique of nuclear magnetic resonance. We applied to different kinds of mother wavelets. Evaluation of the effectiveness of filtering was performed using the signal to noise ratio, relative contrast and the steepness of the intensity changes in signal intensity. It also discusses the comparison of properties of the image and selecting the mother wavelets based on image characteristics. Images were compared in terms of a histogram, cumulative histogram, k-space and the difference image.

The aim of this thesis is implementation of wavelet transform algorithm for noise reduction. The noise reduction itself is focused on improving informative capabilities of sonographic (ultrasound) images in medicine. For this purpose, thresholding of detailed coefficients on individual levels of multiresolution analysis was used. Common procedures were not used for searching for the most suitable thresholds of those levels. The alternative concept's design is based on fundamental empirical approach, where the individual thresholds are optimised by evolution algorithms. However, with this algorithmic procedure, more problems manifest regarding the objective evaluation of the success of noise reduction. Because of this, the program uses commonly used parameters such as mean square error of the whole image, linear slope edge approximation, relative contrast of two differently bright and distinct points and the standard deviation of compact surface. Described theoretical knowledge is used in developed application DTWT. It executes multilevel decomposition and reversed reconstruction by discrete time wavelet transform, thresholding of detailed coefficients and final evaluation of performed noise reduction. The developed tool can be used separately to reduce noise. For our purposes, it has been modified in way, that it executed through the component for evolutionary optimization of parameters (Optimize Parameters) in created scenario in RapidMiner program. In the optimization process, this component used evaluation received from DTWT program as fitness function. Optimal thresholds were sought separately for three wavelet families - Daubeschies, Symmlets and Coiflets. The evolution algorithm chose soft threshold for all three wavelet families. In comparison to hard threshold, it is more suitable for noise reduction, but it has tendencies to blur the edges more. The devised method had in most cases greater evaluated success of noise reduction with wavelet transform with threshold search done by evolution algorithms, than commonly used filters. In visual comparison however the wavelet transform introduced some minor depreciating artefacts into the image. It is always about compromise between noise reduction and maximal preservation of image information. Objectively evaluating this dilemma is not easy and is always dependant on subjective viewpoint which in case of sonographic images is that of the attending physician.

Noise levels in hospital settings have risen beyond the recommended range of 35-40 decibels, resulting in poor patient healing outcomes and other health conditions ranging from sleep deprivation, anxiety, agitation, delirium, depression, and high heart rate and blood pressure. These negative patient health experiences are evidenced by poor scores for the Hospital Consumer Assessment of Healthcare Providers and Systems, which are indicators of patients' perceptions of care. This project explored whether an educational activity for 48 direct care staff, who include registered nurses and nursing assistants, in a cardiac unit on the impact of noise pollution on patient healing would increase staff members' knowledge of interventions to reduce noise pollution. The information processing theory guided this project. Eighty-nine percent of the participants strongly agreed that the educational activity was relevant to their practice as health care providers on the cardiac monitored unit. All participants strongly agreed that they would be able to identify when the unit was noisy and when noise was impacting a patient both physiologically and psychologically. Participants indicated that they could implement the suggested behavioral modifications to promote a healing environment. Participants strongly agreed that the speaker was effective in communicating the importance of noise pollution and its impact on patient healing and ways in which to combat the problem (89%), and they were generally satisfied with the learning activity (91%). Reducing noise pollution might create a healing environment for cardiac patients, thus positively impacting patient satisfaction and well-being.

Innowearable AB has developed a product called Inno-XTM that calculates musclefatigue during three exercises: squat jumps, wall sit, and leg extension. Inno-X uses an accelerometer and a surface electromyography sensor. The goal of thisproject was to create the signal processing part of a machine-learning (ML) pipeline that classifies the exercises in real-time. Data was collected from the sensors to create a training environment that could later be translated to a real-time environment using a sliding window technique. A Savitsky-Golay filter (SG), lowpass, and highpass filters were tested in order to remove noise from the signal. The best filter proved to be the SG filter. Both time and frequency domain features were used in feature extraction. The finished product used 24 features from both domains combined. These methods together with the ML algorithms created in a collabora-tive project led to a classification accuracy for the training environment of 98.62%, while the real-time environment reached 90%. By collecting a larger and more diverse dataset, and addressing the issue of leg extension and wall sit exercises being too similar, real-time classification can be further improved which will make the ML pipeline usable for Innowearables’ customers. / Innowearable AB har utvecklat en produkt som heter Inno-XTM som räknar ut muskeltröttheten vid 3  övningar: upphopp, jägarvila och benextensioner. Inno-X använder en accelerometer och en yt-elektromyografi-sensor. Målet med projektet var att skapa signalprocesseringsdelen av en machine learning (ML) pipelinesom klassificerar dessa övningar i realtid. Data samlades in från sensorerna för att skapa en träningsmiljö som sedan kunde gå  över i realtidsmiljö genom attanvända en sliding-window teknik. Savitsky-Golay (SG) filter, högpassfilter, och lågpassfilter användes för att reducera brus i sensorsignalerna. SG filtret presterade bäst. Features från både tids- och frekvensdomän användes i feature extraction. Slutprodukten använde 24 features kombinerat från båda domänen. Dessa metoder tillsammans med ML algoritmer som togs fram i ett partnerprojekt gav ett resultat i träningsmiljön på 98.62% i klassificeringsnoggrannhet och 90% för realtidsmiljön. Genom att samla större mängd data med mer diversitet och lösa problemetatiken i att jägarvila och benextensioner  är för lika, kommer realtidsklas-sifikationen förbättras vilket hade gjort att ML pipelinen blir användbar för Innowearables kunder.

Eftersom användningen av små UAV:s (Unmanned Aerial Vehicles) fortsätter att öka, harbullret från deras framdrivningssystem blivit ett ökande problem. Denna rapport är resultatetav ett masterprojekt med målet att utveckla en framdrivningsmetod med låga bullernivåerför små UAV:s.Projektet startade med en informationssökning där målet var att hitta information ombullerkällor i nuvarande system samt information om de fundamentala sätten på vilket luftflödekan skapas.När informationssökningen var färdig, genererades ett stort antal olika koncept. Konceptetsom författarna ansåg ha mest potential, var en propeller med en ny metod för passivkontroll av gränsskiktet. Konceptet har ett luftintag nära rotationscentrum. Efter att luftenhar kommit in i detta luftintag, leds den genom interna kanaler och accelereras radiellt utåtpå grund av centrifugalkraften. Luften sprutas sedan ut genom en slits nära framkantenpropellerbladets lågtryckssida. Denna ström av luft färdas över propellerbladet och sugsin genom en slits nära vingens bakkant. Därefter sprutas luften ut genom ett utlopp närapropellerbladets spets.Tanken är att den beskrivna metoden ska fördröja eller förhindra avlösning. Detta skullepotentiellt möjliggöra högre lyftkraft vid lägre rotationshastigheter, vilket därigenom potentielltsänker bullernivåerna. Förenklade modeller av det valda konceptet har utvecklats ochanalyserats med hjälp av CFD (Computational Fluid Dynamics) och jämförts med simuleringarav en referensmodell utan gränsskiktskontroll. Resultaten indikerar att flödet ikonceptmodellen strömmar genom kanalerna och över propellerbladet som det var tänkt.Lyftkraften och effektiviteten ökade med 4.3 % respektive 1.9 %, jämfört med referensmodellen,vid samma rotationshastighet. Den möjliga minskningen av rotationshastigheten pågrund av ökningen i lyftkraft resulterar i en minskning av bullernivån med 0.9 dB. Detbör noteras att resultaten från simuleringarna bör ses med försiktighet och att ytterligarearbete måste göras innan några definitiva slutsatser kan dras beträffande potentiella prestandaökningarav konceptet jämfört med en konventionell propeller. / As the use of small UAVs (Unmanned Aerial Vehicles) keeps increasing, the noise emittedfrom their propulsion systems have become an increasing issue. This report is the resultof a master thesis project with the aim of developing a propulsion method with low noiseemissions for small UAVs.The project started with a background study, where the aim was to find informationabout sources of noise in current systems and information about the fundamental ways inwhich air flow can be created.When the background study was finished, a large number of different concepts were generated.The concept that the authors considered having the most potential, was a propellerwith a new method for passive circulation control. The concept has an air intake close tothe rotational center. After air has entered this inlet it is led through internal channels andis accelerated radially outwards due to centrifugal forces. The air is then ejected through aslot close to the leading edge on the low pressure side on the propeller blade. This stream ofair travels over the propeller blade and is the sucked in through a slot close to the trailingedge. After this, the air is ejected through an outlet close to the propeller blades tip.The idea is that the method described should delay or prevent boundary layer separation.This would potentially allow for higher thrust at lower rotational speeds, thus potentiallylowering the noise emissions. Simplified models of the chosen concept have been developedand analyzed using CFD (Computational Fluid Dynamics) and compared to simulations ofa baseline model with no circulation control. The results indicate that the fluid flow in theconcept model flows through the channels and over the propeller blade, as intended. Thethrust and efficiency were increased by 4.3 % and 1.9 % respectively, compared to the baselinemodel, at the same rotational speed. The possible reduction of the rotational speed due tothe increase in thrust, results in a reduction of the noise level by 0.9 dB. It should be notedthat the results from the simulations should be viewed with caution and the that furtherwork needs to be done before any clear conclusions can be drawn regarding the potentialperformance increase of the concept compared to a conventional propeller.

A Thesis Submitted to the School of Graduate Studies in Partial Fulfilment of the Requirements for the Degree Master of Science / This thesis examines how emotion is conveyed in music from different eras, and attempts to reconcile differences between psychological and music-theoretical approaches. Chapter 1 introduces the concepts embodied by the two manuscripts within this thesis. Chapters 2 and 3 describe two separate but related complimentary research projects. Chapter 2, entitled “Breaking with Common Practice: Exploring Modernist Musical Emotion”, compares perceived emotion in prelude sets by D. Shostakovich, F. Chopin, and J.S. Bach. This work seeks to clarify the relationship between historic changes in music’s structure and conveyed emotion, particularly in the twentieth century–which remains largely unexplored. Building on previous work, we used commonality analysis to break down the unique and joint contributions of various cues to perceived emotion and provide insight into their changing roles in the twentieth century. The work described in Chapter 3, “Cleaning up our work: Applying decision hygiene to analysis of musical structure”, was inspired by previous attempts in diverse fields (e.g., medicine, judicial sentencing) to resolve unwarranted disagreement, and used a novel procedure to distinguish genuine disagreement from disagreement that is not reflective of true differences of opinion amongst music theorists. Unlike other fields involving judgement, individual theorists’ unique perspectives are valuable. Therefore, rather than forcing inauthentic agreement, our procedure clarified and enhanced individual perspectives in musical analysis. Taken together, the research described in Chapters 2 and 3 bridge the gap between epistemologically different approaches to disseminating musical knowledge–cognition and theory. / Thesis / Master of Science (MSc) / Music’s expressive capabilities has inspired scholarship from psychology, music theory, musicology, and philosophy for centuries. Although research in psychology has produced consensus about how certain musical elements contribute to its emotional meaning, musicological research shows that music’s structure evolved across history. Little research has explored emotional communication in music from the twentieth century, raising important questions about how emotion is conveyed in the music of our time. This oversight may contribute to continuing disagreement between music psychologists and music theorists on how music’s structure affects its perceived meaning. Thus, by bridging the gap between theory and cognition, this thesis aims to: (i) shed light on the role of music’s evolving structure–particularly in the twentieth century–on perceived emotion; and (ii) reduce error in music analysis while preserving valuable differences in theorists’ perspectives through applying a novel method inspired by optimized decision-making procedures.

A denoising autoencoder is a type of neural network which excels at removingnoise from noisy input data. In this project, a denoising autoencoder isoptimized for removing noise from mobile positioning data. The mobilepositioning data with noise is generated specifically for this project. In orderto generate realistic noise, a study in how real world noise looks like is carriedout. The project aims to answer the question: can a denoising autoencoderbe used to remove noise from mobile positioning data? The results showthat using this method can effectively cut the noise in half. In this reportit is mainly analyzed how the amount of hidden layers and respective sizesaffected the performance. It was concluded that the most optimal design forthe autoencoder was a single hidden layer model with multiple more nodes inthe hidden layer than the input and output layer. / En brusreducerande autoencoder är ett sorts neuralt nätverk som är specialiserat för att ta bort brus från indata. I detta projekt optimeras en brusreducerande autoencoder för att ta bort brus från mobilpositioneringsdata. Till projektet skapades helt ny mobilpositioneringsdata med realistiskt brus. Detta gjordes genom att studera hur verkligt brus ser ut och skapa ett program som efterliknar detta. Projektets syfte var att undersöka om en brusreducerande autoencoder kan användas för att ta bort brus från mobilpositioneringsdata. Resultaten visar att metoden kan ta bort ungefär hälften av bruset. I rapporten undersöks och analyseras även hur antalet dolda lager och antalet noder i dessa lager påverkade mängden brus som autoencodern lyckades ta bort. Från de gjorda testerna drogs slutsatsen att den mest optimala designen var en enkel design med ett enda dolt lager som hade betydligt fler noder än input- och outputlagren.

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Noise reduction in vehicle exhaust systems is crucial for mitigating the adverse health effects of noise from roadside traffic. Improvements to engine exhaust systems could be one avenue to reduce vehicle and roadside noise. Therefore, understanding the insertion loss and transmission loss is of crucial importance as these constitute important metrics for the effectiveness of mufflers in exhaust systems. In addition, knowledge about the maximum emitted sound power is also desirable as it is an important characteristic of the exhaust system affecting the final emitted noise. This study provides an overview of the theoretical underpinnings of the acoustics that model engine exhaust systems, where the maximum sound powers are presented, as well as explores the sensitivity of the insertion and transmission loss to input variables. A sensitivity analysis of the transmission and insertion loss was conducted using data provided by Scania, a large Swedish truck manufacturer, from which it was concluded that the provided transfer matrix exhibit stable behavior. More generally, in face of specific perturbations, if some conditions are meet, the resulting change to the insertion and transmission loss may only be an upwards or downwards translation, or no change at all.