Tranås reningsverk transporterar varje vecka 25-30 ton avvattnat rötslam till deponi. Ju mer vatten slammet innehåller, ju högre blir dess massa och volym och därmed även deponeringskostnaderna. Det är därför ytterst viktigt att avvattningen av slammet fungerar bra. I denna studie undersöktes möjligheterna att optimera avvattningen genom att byta polymersort som flockar slammet samt justera skruvhastigheten på skruvpressen Volute®. Valet av polymer beror på polymerernas avvattningsegenskaper och om de gav en bra drift vid skruvpressen, som leder till låga halter av suspenderade substanser (SS) i rejektvattnet. En optimering skulle minska mängden slam som deponeras och därmed dra ner på transportkostnaderna.   Syftet med studien var att undersöka vilken eller vilka polymerer som bäst fungerar i samband med avvattningen av rötslammet på Tranås reningsverk.   Undersökningen gjordes genom att jämföra avvattningsegenskaperna för fem olika polymersorter. För jämförelsen användes TS-halt på slammet som bestämdes före och efter avvattningen vid olika skruvhastigheter, samt SS-halt i rejektvattnet vid ordinarieinställning av skruvhastigheten. Resultaten från denna studie jämfördes med provresultat som Tranås reningsverk själva uppmätt när de mätte TS-halten på avvattnat rötslam vid användning av två olika polymersorter.  Studien visar att samtliga polymerer fungerade bäst vid låg frekvens (skruvhastighet). De två bästa polymererna var Superfloc® C-448 och Zetag® 8165. Tillsättning av Superfloc® C-448  gav en jämn TS-halt vid olika skruvhastigheter och resulterade i den högsta TS-halten på det avvattnade slammet, vilket vittnar om goda avvattningsegenskaper och en bra drift. Vid en fast inställning på skruvhastigheten (det vill säga 18 Hz) visade sig Zetag® 8165 vara den bästa polymeren. Detta eftersom den vid den skruvhastigheten ledde tillsättning av Zetag® 8165 till den högsta TS-halten i jämförelse med samtliga polymerer, och den resulterade i även den lägsta SS-halten.   Samtliga polymerer som analyserades i den här studien fick högst TS-halt vid skruvhastigheten 16 Hz, förutom Zetag® 8165 som hade sitt högsta mätvärde vid frekvensen 18 Hz. Zetag® 8165 hade dock sina tre högsta värden inom skruvhastighetsintervallet 16-18 Hz, vilket också är det optimala intervallet för att få så bra avvattning som möjligt utifrån tolkningen av resultaten från denna studie.  Studiens resultat tyder på att polymerer inte ska ha en specifik laddning för att kunna uppnå en optimal avvattning, utan det är kombinationen av laddning och molekylvikt som avgör avvattningens resultat. / Tranås treatment plant transports 25-30 tons of sewage sludge to landfill weekly. The more water the sludge contains, the higher its mass and volume, and thus the landfill costs. It is therefore extremely important that the dewatering of the sludge works well. In this study, the possibilities for optimizing the dewatering of sewage sludge were investigated by replacing the polymer species that flocculates the sludge and adjusting the screw speed of the Volute® screw press. The choice of polymer depends on the dewatering properties of the polymers and if they provide good operation at the screw press, which results in low levels of suspended substances (SS) in the reflux water. An optimization would reduce the amount of sludge deposited and thereby reduce transport costs.  The purpose of the study was to investigate which or any of the polymers that work best in connection with the dewatering of the sludge at Tranås treatment plant.  The study was done by comparing the dewatering properties of five different polymer species. For the comparison, the TS content of the sludge was determined before and after the dewatering at different screw speeds, as well as the SS content in the scrubbing water at the standard screw speed setting was used for the comparison.   The results from this study were compared to test results that Tranås treatment plants themselves measured when measuring the TS content of dewatered sewage sludge using two different polymer species.  The study shows that all polymers worked best at low frequency (screw speed). The two best polymers were Superfloc® C-448 and Zetag® 8165. Addition of Superfloc® C-448 gave a uniform TS content at different screw speeds, resulting in the highest TS content of the dewatered sludge, indicating good dewatering properties and a good operation. At a fixed setting at the screw speed (that is 18 Hz), Zetag® 8165 proved to be the best polymer. This because, at the screw speed, an addition of Zetag® 8165 resulted in the highest measured TS content in comparison to all polymers, and it also resulted in the lowest SS content.  All polymers analyzed in this study achieved peak TS content at 16 Hz, except Zetag® 8165 which had its highest measurement at the 18 Hz frequency. However, the Zetag® 8165 had its three highest values in the 16-18 Hz screw speed range, which is also the optimal range for the best dewatering possible based on the interpretation of the results of this study.  The study results indicate that polymers should not have a specific charge to achieve optimal drainage, but it is the combination of charge and molecular weight that determines the dewatering results.

Kartläggning med robotar är ett område som redan tidigt i robotiken setts somviktigt, med många moderna produkter som möjliggjorts av forskningens framsteg.Särskilt med senare tidens implementation av sannolikhetslära och datoralgoritmer föratt lösa problemet SLAM (Simultaneous Localization And Mapping). Detta projekt harhaft som syfte att konstruera en robot som kan röra sig i ett rum och kartlägga allaväggar och föremål den ser, inspirerat av tidiga SLAM applikationer. Det roboten sermålas sedan upp i en datorapplikation för att ge användaren en bild av rummetsstruktur. Ett flertal moderna men relativt enkla komponenter och metoder haranvänts för konstruktionen och designen av roboten som utvecklats.Friformframställning med 3D-skrivare användes för att skapa robotens chassi, enArduino Nano mikrokontroller styr sensorer och motorer ochBluetooth-kommunikation möjliggör skickande av mätvärden till en dator.Datorapplikationen som skrevs i programmeringsspråket Python använder sedaninbyggda moduler som hjälp för att grafiskt illustrera de mätningar roboten gjort.Resultatet blev slutligen en robot som kan utföra korrekta rumsmätningar då antaletförflyttningar är väldigt få och en datorapplikation med användarvänlig struktur somritar upp dem. Begränsningar i funktionaliteten återstod trots försök att kompenseraför hårdvarufel, dock kan roboten ligga till grund för ytterligare förbättringar ochvidare applikationer.

Wireless capsule endoscopy (WCE) offers a patient-friendly, non-invasive and painless investigation of the entire small intestine, where other conventional wired endoscopic instruments can barely reach. As a critical component of the capsule endoscopic examination, physicians need to know the precise position of the endoscopic capsule in order to identify the position of intestinal disease after it is detected by the video source. To define the position of the endoscopic capsule, we need to have a map of inside the human body. However, since the shape of the small intestine is extremely complex and the RF signal propagates differently in the non-homogeneous body tissues, accurate mapping and localization inside small intestine is very challenging. In this dissertation, we present an in-body simultaneous localization and mapping technique (Body-SLAM) to enhance the positioning accuracy of the WCE inside the small intestine and reconstruct the trajectory the capsule has traveled. In this way, the positions of the intestinal diseases can be accurately located on the map of inside human body, therefore, facilitates the following up therapeutic operations. The proposed approach takes advantage of data fusion from two sources that come with the WCE: image sequences captured by the WCE's embedded camera and the RF signal emitted by the capsule. This approach estimates the speed and orientation of the endoscopic capsule by analyzing displacements of feature points between consecutive images. Then, it integrates this motion information with the RF measurements by employing a Kalman filter to smooth the localization results and generate the route that the WCE has traveled. The performance of the proposed motion tracking algorithm is validated using empirical data from the patients and this motion model is later imported into a virtual testbed to test the performance of the alternative Body-SLAM algorithms. Experimental results show that the proposed Body-SLAM technique is able to provide accurate tracking of the WCE with average error of less than 2.3cm.

" In the field of Robotics, Monocular Simultaneous Localization and Mapping (Monocular SLAM) has gained immense popularity, as it replaces large and costly sensors such as laser range finders with a single cheap camera. Additionally, the well-developed area of Computer Vision provides robust image processing algorithms which aid in developing feature detection technique for the implementation of Monocular SLAM. Similarly, in the field of digital electronics and embedded systems, hardware acceleration using FPGAs, has become quite popular. Hardware acceleration is based upon the idea of offloading certain iterative algorithms from the processor and implementing them on a dedicated piece of hardware such as an ASIC or FPGA, to speed up performance in terms of timing and to possibly reduce the net power consumption of the system. Good strides have been taken in developing massively pipelined and resource efficient hardware implementations of several image processing algorithms on FPGAs, which achieve fairly decent speed-up of the processing time. In this thesis, we have developed a very simple algorithm for feature detection in an indoor environment by means of a single camera, based on Canny Edge Detection and Hough Transform algorithms using OpenCV library, and proposed its integration with existing feature initialization technique for a complete Monocular SLAM implementation. Following this, we have developed hardware accelerators for Canny Edge Detection & Hough Transform and we have compared the timing performance of implementation in hardware (using FPGAs) with an implementation in software (using C++ and OpenCV). "

Examensarbetet är utfört i Rottneros bruks barkpanna och syftet med arbetet är att genom provkörningar och beräkningar, tillslut finna hur mycket slam som är praktiskt möjligt att blanda in i bränslemixen till pannan. Intresset i att elda slam är idag väldigt stort hos producenter av slam, då istället för att skicka iväg slammet för hantering kan en förbränning hos dem själva istället göras. Det stora intresset i att elda slammet själv, ligger i att på det sättet kan stora ekonomiska besparingar göras. Eftersom Rottneros bruk får slam som restprodukt från deras reningsverk, blir detta även aktuellt hos dem. Rottneros Bruk har idag ett företag som kommer och hämtar allt slam, behovet för detta skulle kunna efter denna studie minska.   Målet med studien är att hitta en bränslemix till pannan med så stor slamhalt som är praktiskt möjlig. Detta för att den ekonomiska besparingen ska bli så stor som möjligt, då besparingen ökar med andelen slam som går att blanda in i bränslemixen. För att en maximalt fungerande slammängd i bränslemixen ska vara acceptabel, krävs det att både bränslemixen är körvänlig i pannan samt att kraven på utsläppen uppfylls. Körbarheten innefattar att effekten, temperaturen samt slaggbildningen i pannan ligger på en sådan nivå att de inte blir problematiskt. När det kommer till miljöaspekten krävs det att så kallade gränsvärden för NOx och CO utsläpp inte överskrids. Dessa gränsvärden är unika för Rottneros bruk, som i sin tur får konsekvenser i form av böter ifall dem överskrids.        För att kunna lösa detta har provkörningar och beräkningar gjorts hos pannan.  Provkörningarna som genomförts har haft olika slammängder samt torrhalter på bränslemixen, för att på detta sätt se hur pannan reagerar under olika förhållanden. Genom beräkningar och data ifrån provkörningarna kan ett framtagande göras för hur mycket slam som går att blanda in i bränslemixen.   Det resultat som fås från denna studie säger att en fungerande bränslemix till pannan kan ha en maximal slaminblandning på 1,5-2 procent. Med denna mängd slam i bränslemixen kommer en årlig besparing för Rottneros bruk ligga på 207,6-276,9 kkr/år. Bränslemixen kommer både uppfylla gränsvärdena för utsläpp av NOx och CO samt att körbarheten i pannan kommer vara acceptabel. Den låga inbladningen av slam beror först och främst på att utsläppen av NOx annars kommer överskridas, detta på grund av att kvävet i slammet. Torrhalten hos bränslet har även ett stort inflytande på hur stora utsläppen blir av NOx och CO. Då torrhalten hos slammet, flisen och barken varierar, är detta något som hänsyn har tagits till då den maximala slaminblandingen hos bränslemixen tagits fram.

Semi-invariant natural killer T (iNKT) cells are critical components of the host immune response in peripheral tissues such as the lung, liver, and gut, and they play important roles in cancer, bacterial infections, autoimmunity, wound repair, and atherosclerosis. Tissue-resident iNKT cells exert their effects early in the developing immune response by rapidly producing a wide variety of cytokines and chemokines, and it was recently discovered that different tissues possess iNKT cell subsets that preferentially produce IFN-γ (NKT1), IL-4 (NKT2), or IL-17 (NKT17). Despite their critical role in the immune response, the mechanisms that regulate iNKT cell function in the periphery remain unclear. Signaling lymphocyte activation marker (SLAM) proteins are cell surface-expressed molecular switches that are expressed on all hematopoietic cells. The nine SLAM family receptors serve a variety of functions including promotion of cell-cell adhesion, regulation of cytokine production, co-stimulation, and inhibition. Importantly, SLAM family receptors are critical for the development of iNKT cells. Yet, numerous efforts to ascribe discrete roles of SLAM family receptors in iNKT cell function has proven difficult. We conducted a comprehensive analysis of SLAM family receptor co-expression on iNKT cell subsets in the lung, spleen, liver, and thymus and identified co-expression profiles that varied in a tissue and strain-dependent manner. Interestingly, we found that SLAM family receptor expression profiles varied among different iNKT cell subsets. In particular, we noted a close association of SLAMf6 expression with the NKT2 and NKT17 subsets in both the periphery and in the thymus. Further investigation using SLAMf6-deficient mice revealed a critical role for SLAMf6 in NKT2 and NKT17 subset development, and in iNKT IL-4 and IL-17 cytokine production in the periphery. This investigation also revealed that the SLAMf6high NKT2 and NKT17 subsets exhibited significantly higher proliferative capacity than the NKT1 subset and the NKT2 and NKT17 proliferation was dependent, in part, on SLAMf6 expression. Since Slam family genes are highly polymorphic, we next investigated whether these polymorphisms regulated iNKT function. We employed a B6.129 congenic mouse exhibiting impaired NKT cell function, in which a 6.6 Mbp 129/SvJ locus encompassing Slam genes was introgressed onto the C57BL/6 background. To test the hypothesis that Slam gene polymorphisms regulate iNKT cell function, we refined this genetic interval by generating B6.129 subcongenic lines and assessing iNKT cell function. Unexpectedly, we found that while Slam gene polymorphisms in this model do regulate iNKT cell function, the dominant regulator was in a 0.14 Mbp interval centromeric to the Slam genes. Further experimentation revealed that impaired iNKT cell development and function was associated with changes in the expression of Fcgr3 (Fc gamma receptor III) on iNKT cells, suggesting it as a novel candidate gene regulating iNKT cell function. Taken together, these data reveal for the first time a specific role for SLAMf6 on NKT2 and NKT17 subset development and function. In addition, these data identify Fcgr3 as a novel candidate gene that regulates iNKT cell subset development and cytokine production. Cumulatively, these data reveal the presence of discrete regulatory mechanisms at work in different iNKT subsets, a finding that has broad implications for our understanding of iNKT-cell mediated immunity.

The ability to navigate in an unknown environment is an enabler for truly utonomous systems. Such a system must be aware of its relative position to the surroundings using sensor measurements. It is instrumental that these measurements are monitored for disturbances and faults. Having correct measurements, the challenging problem for a robot is to estimate its own position and simultaneously build a map of the environment. This problem is referred to as the Simultaneous Localization and Mapping (SLAM) problem. This thesis studies several topics related to SLAM, on-board sensor processing, exploration and disturbance detection. The particle filter (PF) solution to the SLAM problem is commonly referred to as FastSLAM and has been used extensively for ground robot applications. Having more complex vehicle models using for example flying robots extends the state dimension of the vehicle model and makes the existing solution computationally infeasible. The factorization of the problem made in this thesis allows for a computationally tractable solution. Disturbance detection for magnetometers and detection of spurious features in image sensors must be done before these sensor measurements can be used for estimation. Disturbance detection based on comparing a batch of data with a model of the system using the generalized likelihood ratio test is considered. There are two approaches to this problem. One is based on the traditional parity space method, where the influence of the initial state is removed by projection, and the other on combining prior information with data in the batch. An efficient parameterization of incipient faults is given which is shown to improve the results considerably. Another common situation in robotics is to have different sampling rates of the sensors. More complex sensors such as cameras often have slower update rate than accelerometers and gyroscopes. An algorithm for this situation is derived for a class of models with linear Gaussian dynamic model and sensors with different sampling rates, one slow with a nonlinear and/or non-Gaussian measurement relation and one fast with a linear Gaussian measurement relation. For this case, the Kalman filter is used to process the information from the fast sensor and the information from the slow sensor is processed using the PF. The problem formulation covers the important special case of fast dynamics and one slow sensor, which appears in many navigation and tracking problems. Vision based target tracking is another important estimation problem in robotics. Distributed exploration with multi-aircraft flight experiments has demonstrated localization of a stationary target with estimate covariance on the order of meters. Grid-based estimation as well as the PF have been examined. / The third article in this thesis is included with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Linköping University's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this material, you agree to all provisions of the copyright laws protecting it.Please be advised that wherever a copyright notice from another organization is displayed beneath a figure, a photo, a videotape or a Powerpoint presentation, you must get permission from that organization, as IEEE would not be the copyright holder.

Chemical substances are spread diffusely and uncontrollably as a result of the increased consumption of goods. REVAQ is a certification system that works to reduce the flow of hazardous substances to Swedish treatment plants and to create a sustainable nutrient recycling. According to REVAQ, the yearly accumulating rate of metals should not exceed 0.2% in soil per year. Silver and bismuth are two metals that do not fulfill this requirement. The silver concentration in sludge decreased during the last decade, however the last few years, it has leveled off. The bismuth concentration has increased significantly since 2005. The aim of this study was to explore the types of plastics and paints that could be found to contain silver respectively bismuth, and to investigate whether these can be important sources of measured concentrations of silver and bismuth in sludge. The results of the substance flow analysis which was used in this study show that bismuth is probably found in ABS plastics, polyethylene plastics and polyamide plastics. These plastics are mainly found in household items. The inflows of metals in plastic to Stockholm are estimated to be 5 kg silver and 1.2 to 5.7 tons bismuth. In paints, the numbers are 19 kg of silver and 2.5 to 3.3 tons of bismuth. The stocks of metals in plastic in Stockholm are estimated to be 25 - 50 kg silver and 5.7 to 57 ton bismuth and in paints between 98 and 195 kg silver and 12 to 33 tons bismuth. The outflow of metals in plastic to Henriksdals treatment plants are estimated to be 300 g silver and 5-25 kg bismuth and in paints 0.5 kg silver and between 62 to 82 kg bismuth. According to this study, bismuth in plastic and paint are a contributing source to the measured concentrations in sludge (4.4 - 21 % respective 54 - 73 %). Silver in plastic and paints are not a relevant source for the amount of silver in sludge in treatment plants. / Kemiska ämnen sprids diffust och okontrollerat till följd av en ökad konsumtion av varor. REVAQ är ett certifieringssystem som arbetar för att minska flödet av farliga ämnen till svenska reningsverk och att skapa en hållbar återföring av växtnäring. Enligt REVAQ får inte den årliga ackumuleringshastigheten för metaller öka mer än 0,2 % i mark, vilket den gör för silver och vismut. Silverhalten i slam har de senaste årtionde minskat signifikant, men de senaste åren dock planat ut. Vismut har ökat avsevärt sedan 2005. Därför är det viktigt att identifiera källor till silver och vismut i slam. Syftet med denna studie har varit att utforska vilka typer av plaster och färger silver respektive vismut återfinns i samt att undersöka om dessa kan vara signifikanta källor till uppmätta halter av silver och vismut i slam. Resultatet av den substansflödesanalys som använts i denna studie visar att vismut används i ABS-plast, polyetenplast och troligen även i polyamidplast. Plasterna används främst i hushållsartiklar. Inflödet av plast till Stockholm beräknas innehålla 5 kg silver och 1,2 - 5,7 ton vismut och för färg 19 kg silver och 2,5 - 3,3 ton vismut. Stocken för plast i Stockholm beräknas innehålla 25 - 50 kg silver och 5,7 - 57 ton vismut och för färg 97 - 194 kg silver och 12 -33 ton vismut.  Utflödet av metaller till Henriksdal reningsverk beräknas vara 300 g silver och 5- 25 kg för plast och 0,5 kg silver och 62 - 82 kg vismut för färg. Enligt denna studie är vismut i plast och färg en bidragande källa till uppmätta halter i slam (4,4 - 21 % respektive 54 - 73 % ). Silver i plast och färg är inte en bidragande källa till uppmätta mängder silver i reningsverkets slam.

Simultaneous Localization and Mapping (SLAM) is a recursive probabilistic inferencing process used for robot navigation when Global Positioning Systems (GPS) are unavailable. SLAM operates by building a map of the robot environment, while concurrently localizing the robot within this map. The ultimate goal of SLAM is to operate anywhere using the environment's natural features as landmarks. Such a goal is difficult to achieve for several reasons. Firstly, different environments contain different types of natural features, each exhibiting large variance in its shape and appearance. Secondly, objects look differently from different viewpoints and it is therefore difficult to always recognize them. Thirdly, in most outdoor environments it is not possible to predict the motion of a vehicle using wheel encoders because of errors caused by slippage. Finally, the design of a SLAM system to operate in a large-scale outdoor setting is in itself a challenge. <br /><br /> The above issues are addressed as follows. Firstly, a camera is used to recognize the environmental context (e. g. , indoor office, outdoor park) by analyzing the holistic spectral content of images of the robot's surroundings. A type of feature (e. g. , trees for a park) is then chosen for SLAM that is likely observable in the recognized setting. A novel tree detection system is introduced, which is based on perceptually organizing the content of images into quasi-vertical structures and marking those structures that intersect ground level as tree trunks. Secondly, a new tree recognition system is proposed, which is based on extracting Scale Invariant Feature Transform (SIFT) features on each tree trunk region and matching trees in feature space. Thirdly, dead-reckoning is performed via an Inertial Navigation System (INS), bounded by non-holonomic constraints. INS are insensitive to slippage and varying ground conditions. Finally, the developed Computer Vision and Inertial systems are integrated within the framework of an Extended Kalman Filter into a working Vision-INS SLAM system, named VisSLAM. <br /><br /> VisSLAM is tested on data collected during a real test run in an outdoor unstructured environment. Three test scenarios are proposed, ranging from semi-automatic detection, recognition, and initialization to a fully automated SLAM system. The first two scenarios are used to verify the presented inertial and Computer Vision algorithms in the context of localization, where results indicate accurate vehicle pose estimation for the majority of its journey. The final scenario evaluates the application of the proposed systems for SLAM, where results indicate successful operation for a long portion of the vehicle journey. Although the scope of this thesis is to operate in an outdoor park setting using tree trunks as landmarks, the developed techniques lend themselves to other environments using different natural objects as landmarks.

Stereo imaging is routinely used in Simultaneous Localization and Mapping (SLAM) systems for the navigation and control of autonomous spacecraft proximity operations, advanced robotics, and robotic mapping and surveying applications. A key step (and generally the most computationally expensive step) in the generation of high fidelity geometric environment models from image data is the solution of the dense stereo correspondence problem. A novel method for solving the stereo correspondence problem to sub-pixel accuracy in the Fourier frequency domain by exploiting the Convolution Theorem is developed. The method is tailored to challenging aerospace applications by incorporation of correction factors for common error sources. Error-checking metrics verify correspondence matches to ensure high quality depth reconstructions are generated. The effect of geometric foreshortening caused by the baseline displacement of the cameras is modeled and corrected, drastically improving correspondence matching on highly off-normal surfaces. A metric for quantifying the strength of correspondence matches is developed and implemented to recognize and reject weak correspondences, and a separate cross-check verification provides a final defense against erroneous matches. The core components of this phase based dense stereo algorithm are implemented and optimized in the Compute Uni ed Device Architecture (CUDA) parallel computation environment onboard an NVIDIA Graphics Processing Unit (GPU). Accurate dense stereo correspondence matching is performed on stereo image pairs at a rate of nearly 10Hz.