Object tracking is a well-studied problem within the the area of image processing. The ability to track objects has improved drastically during the last decades, however, it is still considered a complex problem to solve. The importance of object tracking is reflected by the broad area of applications such as video surveillance, human-computer interaction, and robot navigation. The purpose of this study was to examine, evaluate, and make a summary of the most common object tracking methods. In this paper a thorough review of the object tracking process is presented. This includes selection of object representation, object features, methods for object detection, and methods for tracking the object over succeeding frames. A summary of the object tracking methods covered in this paper is presented in the result section, including advantages, disadvantages, and for which context each method is suitable for.

A lot of different techniques can be used to determine the position of objects in underground mines. What they have in common is that they’re very expensive or require a specific infrastructure. In this master’s thesis the goal was to produce an algorithm to increase the positioning on vehicles in a cheap and easy way by only using gyroscopeand dead reckoning. To illustrate the movement of the vehicle in the underground mines the Mobilaris Mining Intelligence system (MMI) was used. The algorithm is designed to be used alongside the current algorithm that locates objects by using their RSSI value from the Cisco Access points in the underground mine. With this information it’s possible to relocate a vehicle if the algorithm ”chose” the wrong way. Testing shows that this is a good way to increase the positioning of vehicles in underground mines.

The aim of this thesis is to investigate possibilities to reduce primary steam consumption of the integrated pulp and paper mill in Obbola. For this purpose, a pinch analysis has been performed. The thesis has been carried out on site and necessary data for the analysis was produced mainly using the sensors installed for controlling the process. Based on the data, a representation of the heat exchanges at the mill was obtained and from this emerges an understanding of how optimized the heat exchange is. From the analysis, it was found that the energy savings potential amounts to 7 MW, which corresponds to 6% of present steam consumption of approximately 112 MW. One of the identified pinch violations was the flue gases in the recovery boiler used to preheat combustion air and process ventilation when it can be used to meet a thermal demand at higher temperatures or potentially to generate steam, the latter has not been investigated. Steam preheating of air to the paper dryer, steam preheating of water that is used to thaw logs and steam that is used in some of the process ventilations were also among the identified violations. Possible measures to optimize heat exchange and eliminate pinch violations have been investigated. These include flashing of paper mill condensate to replace the live steam in the air preheaters to the paper dryer and replace this thermal energy with secondary heat in the feed water treatment plant. As well as using part of the heat from the flue gas cooling system to preheat feed water. Increasing the operational temperature in the water treatment plant turned out to be possible regardless of whether a flash is introduced or not. The savings with contra without the flash would amount to 1.13 MW and 0.85 MW, respectively, and the net heat savings of a reconstruction is only 0.28 MW. The heat that can be released from the flue gas cooling system corresponds to 0.46 MW and is expected to be higher in the summer when heat necessity in other ends of the system decreases. To suggest optimization of heat exchanges at the mill, it was also investigated how much excess of warm and hot water was that present in the secondary heating system. The investigation showed that if the temperature in the warm water tank would be regulated, an excess of hot water would be sufficiently large to provide secondary heat to the optimization measures discussed and to provide for all ventilations currently using live steam. In all cases profitability should be investigated and for the case of any ventilation consideration should be given to distance from a secondary heating source and if there is a glycol circuit present or not.

This bachelor thesis examines the impacts of installed microgeneration of PV power in the distribution grid. The thesis examines the selected distribution grids power quality and how it is affected in terms of exceeding currents, voltages and reverse power flows and how the future trend of microgeneration of PV power will develop. A case study is made on Gotland with the support of the distribution grid owner, GEAB. Three of GEAB's distribution grids with different customer configurations and grid structures are being used to create different case scenarios. The production from the PV plants is calculated with production data from a project that GEAB performed with PV plants but dismantled in 2016. The Newton-Raphson power flow method is used to run the simulations of the grids with different amount of installed PV power. The results show that exceeding maximum current is the first parameter to limit and affect the power quality for all grids. After this the three grids can handle different amounts of installed PV power with respect of the remaining parameters. The simulations also show that losses in the grid are reduced due to installations of PV plants, although their small magnitude do not make them a significant aspect to consider when evaluating microgeneration in the distribution grid. When comparing to future scenarios it is concluded that the grids are dimensioned to handle a various amount of installed microgeneration without the power quality being affected.  To analyse the sensitivity of the results a sensitivity analysis is performed on the slack node voltage by alternating the voltage level. The result indicates that a higher slack node voltage gives more exceeding voltages for the city power grid and the two rural grids.

<p> This qualitative grounded theory study investigated the value of iPads in K-12 schools when used in one-to-one ratios. The purpose of the study was to understand the perspectives of teachers using iPads in one-to-one ratios for teaching and learning in the classroom and administrators responsible for the implementation of these devices. The problem was that little was known about the value iPads bring to teaching and learning when used in one-to-one configurations. Two research questions guided this study: From the viewpoint of a teacher, what is the perceived value of iPads when used in one-to-one settings for learning and instruction? and: From the viewpoint of an administrator, what is the perceived value of iPads when used in one-to-one settings for learning and instruction? In one phase, phenomenological interviews captured the lived experiences of 16 teachers using iPads to implement instruction. In a separate phase, a focus group with five administrators discussed their perceptions of the educational value of iPads. The findings of this study were uncovered through the analysis of transcripts of the interviews with teachers and two focus group sessions. The data were analyzed and coded to better understand the phenomenon. Through this analysis, six themes and related subthemes were discovered. These themes were (1) ease of use, (2) district support, (3) teacher mindset, (4) student-centered learning, and (5) evidence of the SAMR model of technology use. These findings may be useful for teachers who use the devices and administrators in school districts considering the adoption of the devices.</p>

Many biological and artificial systems are made up from similar, relatively simple elements that interact directly with their nearest neighbors. Despite the simplicity of the individual building blocks, systems of this type, network systems, often display complex behavior — an observation which has inspired disciplines such as artificial neural networks and modular robotics. Network systems have several attractive properties, including distributed functionality, which enables robustness, and the possibility to use the same elements in different configurations. The uniformity of the elements should also facilitate development of efficient methods for system design, or even self-reconfiguration. These properties make it interesting to investigate the idea of constructing mechatronic systems based on networks of simple elements. This thesis concerns modeling and optimal design of a class of active mechanical network systems referred to as Neuro-Mechanical Networks (NMNs). To make matters concrete, a mathematical model that describes an actuated truss with an artificial recurrent neural network superimposed onto it is developed and used. A typical NMN is likely to consist of a substantial number of elements, making design of NMNs for various tasks a complex undertaking. For this reason, the use of numerical optimization methods in the design process is advocated. Application of such methods is exemplified in four appended papers that describe optimal design of NMNs which should take on static configurations or follow time-varying trajectories given certain input stimuli. The considered optimization problems are nonlinear, non-convex, and potentially large-scale, but numerical results indicate that useful designs can be obtained in practice. The last paper in the thesis deals with a solution method for optimization problems with matrix inequality constraints. The method described was developed primarily for solving optimization problems stated in some of the other appended papers, but is also applicable to other problems in control theory and structural optimization.

The increasing use of bre-reinforced composite materials in the manufacturing of high performance structures is primarily driven by their superior strength-toweight ratio when compared to traditional metallic alloys. This provides the ability to design and manufacture lighter structures with improved mechanical properties. However, the specic manufacturing process of composite structures, along with the orthotropic material properties exhibited by bre-reinforced composite materials, result in a complex structural design process where a number of dierent design parameters and manufacturing issues, which aect the mechanical properties of the composite structure, have to be considered. An ecient way to do this is to implement structural optimization techniques in the structural design process thus improving the ability of the design process to nd design solutions which satisfy the structural requirements imposed on the composite structure. This thesis describes a two phase composite structure optimization method based on a novel material homogenization approach. The proposed method consists of a stiness optimization problem and a lay-up optimization problem, respectively, with the aim to obtain a manufacturable composite structure with maximized stiness properties. The homogenization material approach is applied in both optimization problems, such that the material properties of the composite structure are homogenized. In the proposed method the stiness optimization problem provides a composite structure with maximized stiness properties by nding the optimal distribution of composite material across the design domain. The aim of the lay-up optimization problem is to obtain a manufacturable lay-up sequence of bre-reinforced composite plies for the composite structure which, as far as possible, retains the stiness properties given by the stiness optimization problem. The ability of the composite structure optimization method to obtain manufacturable composite structures is tested and conrmed by a number of numerical tests.

This thesis is about the creation of a tool (SDS) for statistical analysis of stochasticSystem Dynamics models. System Dynamics is a specific field of simulation models based on a system of ordinary differential equations and algebraic equations.The tool is intended for analyzing stochastic System Dynamics models in various fields including biology, ecology, agriculture, economy, epidemiology, military strategy, physics, chemistry and many other fields. In particular, this project was initiated tofulfill the needs of a joint epidemiological project at Uppsala University (UU) andKarolinska Institute (KI). It is also intended to be used in basic courses in simulation at KI and the Swedish University of Agricultural Sciences (SLU).A stochastic model has to be run a large number of times to reveal its behavior. The SDS performs the analysis in the following way. First it connects to the SystemDynamics engine containing the model. Then a specified number of simulation runsare ordered. For each run the results of specified quantities are collected. From thecollected data, various statistical measures are calculated such as averages, standard deviations and confidence intervals. The statistics can then be presented graphically inform of distributions, histograms, scatter plots, and box plots. Finally, all features of SDS were thoroughly tested using manual testing. SDS wasthoroughly tested for statistical correctness, and then evaluated against some stochastic models.

A data stream management system (DSMS) is similar to a database system with the difference that a DSMS can search data directly in on-line streams as well as querying stored data, while a DBMS can search only stored data. Stream queries are called continuous queries because they run all the time until they are terminated. SCSQ is an extensible DSMS allowing different kinds of data sources to be integrated and queried. A SCSQ interface to a data stream system is called a datastream wrapper. A datastream wrapper allows continuous queries to be specified over an external datastream producing system. The Controller Area Network bus (CAN bus), is astandard for interfacing data streams from different kinds of equipment and engines,such as wheel loaders and other vehicles. The objective of the project is to developan interface, called a CAN bus data stream wrapper, to enable SCSQ to access to streams of sensor readings from industrial equipment through CAN bus standard interfaces. It enables the SCSQ user to specify continuous queries over equipmentdata streams.

One of Vironova's electron microscopy services is to classify liposomes. This includes determining the structure of a liposome and presence of a liposomal encapsulation. A typical service analysis contains a lot of electron microscopy images, so automatic classification is of great interest. The purpose of this project is to evaluate convolutional neural networks for solving lamellarity and encapsulation classification problems. The available data sets are imbalanced so a number of techniques toovercome this problem are studied. The convolutional neural network models have reasonable performance and offer great flexibility, so they can be an alternative to the support vector machines method which is currently used to perform automatic classification tasks. The project also includes the feasibility study of convolutional neural networks from Vironova's perspective.