The aim of this thesis is to employ and evaluate an evaluation board with the standard microprocessor freescale MPC5554EVB board for implementation of control algorithms which are created in Matlab/Simulink instead of using dSPACE prototyping hardware. The Simulink real-time model shall be compiled to the MPC5554EVB board. TargetLink is a powerful software tool which allows an automatic generation of efficient C code from Simulink and facilitates model-based control design. The goal of this thesis is to learn how to use TargetLink in a control design workflow from model to real code and what are the limitations of a microprocessor platform and to evaluate the capabilities of TargetLink to generate a working code for a generic microprocessor.

Due to the large influx of computers in our daily lives, human-computer interaction has become crucially important. For a long time, focusing on what users need has been critical for designing interaction methods. However, new perspective tends to extend this attitude to encompass how human desires, interests, and ambitions can be met and supported. This implies that the way we interact with computers should be revisited. Centralizing human values rather than user needs is of the utmost importance for providing new interaction techniques. These values drive our decisions and actions, and are essential to what makes us human. This motivated us to introduce new interaction methods that will support human values, particularly human well-being.

The aim of this thesis is to design new interaction methods that will empower human to have a healthy, intuitive, and pleasurable interaction with tomorrow’s digital world. In order to achieve this aim, this research is concerned with developing theories and techniques for exploring interaction methods beyond keyboard and mouse, utilizing human body. Therefore, this thesis addresses a very fundamental problem, human motion analysis.

Technical contributions of this thesis introduce computer vision-based, marker-less systems to estimate and analyze body motion. The main focus of this research work is on head and hand motion analysis due to the fact that they are the most frequently used body parts for interacting with computers. This thesis gives an insight into the technical challenges and provides new perspectives and robust techniques for solving the problem.

From an early age, people display the ability to quickly and effortlessly interpret the orientation and movement of human body parts, thereby allowing one to infer the intentions of others who are nearby and to comprehend an important nonverbal form of communication. The ease with which one accomplishes this task belies the difficulty of a problem that has challenged computational systems for decades, human motion analysis.

Technological developments over years have resulted into many systems for measuring body segment positions and angles between segments. In these systems human body is typically considered as a system of rigid links connected by joints. The motion is estimated by the use of measurements from mechanical, optical, magnetic, or inertial trackers. Among all kinds of sensors, optical sensing encompasses a large and varying collection of technologies.

In a computer vision context, human motion analysis is a topic that studies methods and applications in which two or more consecutive images from an image sequences, e.g. captured by a video camera, are processed to produce information based on the apparent human body motion in the images.

Many different disciplines employ motion analysis systems to capture movement and posture of human body for applications such as medical diagnostics, virtual reality, human-computer interaction etc.

This thesis gives an insight into the state of the art human motion analysissystems, and provides new methods for capturing human motion.

This paper presents a novel approach for performing intuitive gesture based interaction using depth data acquired by Kinect. The main challenge to enable immersive gestural interaction is dynamic gesture recognition. This problem can be formulated as a combination of two tasks; gesture recognition and gesture pose estimation. Incorporation of fast and robust pose estimation method would lessen the burden to a great extent. In this paper we propose a direct method for real-time hand pose estimation. Based on the range images, a new version of optical flow constraint equation is derived, which can be utilized to directly estimate 3D hand motion without any need of imposing other constraints. Extensive experiments illustrate that the proposed approach performs properly in real-time with high accuracy. As a proof of concept, we demonstrate the system performance in 3D object manipulation On two different setups; desktop computing, and mobile platform. This reveals the system capability to accommodate different interaction procedures. In addition, a user study is conducted to evaluate learnability, user experience and interaction quality in 3D gestural interaction in comparison to 2D touchscreen interaction.

A direct method for recovering three-dimensional (3D) head motion parameters from a sequence of range images acquired by Kinect sensors is presented. Based on the range images, a new version of the optical flow constraint equation is derived, which can be used to directly estimate 3D motion parameters without any need of imposing other constraints. Since all calculations with the new constraint equation are based on the range images, Z(x, y, t), the existing techniques and experiences developed and accumulated on the topic of motion from optical flow can be directly applied simply by treating the range images as normal intensity images I(x, y, t). In this reported work, it is demonstrated how to employ the new optical flow constraint equation to recover the 3D motion of a moving head from the sequences of range images, and furthermore, how to use an old trick to handle the case when the optical flow is large. It is shown, in the end, that the performance of the proposed approach is comparable with that of some of the state-of-the-art approaches that use range data to recover 3D motion parameters.

Currently, the most common way to control an electric wheelchair is to use joystick. However, there are some individuals unable to operate joystick-driven electric wheelchairs due to sever physical disabilities, like quadriplegia patients. This paper proposes a novel head pose estimation method to assist such patients. Head motion parameters are employed to control and drive an electric wheelchair. We introduce a direct method for estimating user head motion, based on a sequence of range images captured by Kinect. In this work, we derive new version of the optical flow constraint equation for range images. We show how the new equation can be used to estimate head motion directly. Experimental results reveal that the proposed system works with high accuracy in real-time. We also show simulation results for navigating the electric wheelchair by recovering user head motion.

This paper presents a novel approach for performing intuitive 3D gesture-based interaction using depth data acquired by Kinect. Unlike current depth-based systems that focus only on classical gesture recognition problem, we also consider 3D gesture pose estimation for creating immersive gestural interaction. In this paper, we formulate gesture-based interaction system as a combination of two separate problems, gesture recognition and gesture pose estimation. We focus on the second problem and propose a direct method for recovering hand motion parameters. Based on the range images, a new version of optical flow constraint equation is derived, which can be utilized to directly estimate 3D hand motion without any need of imposing other constraints. Our experiments illustrate that the proposed approach performs properly in real-time with high accuracy. As a proof of concept, we demonstrate the system performance in 3D object manipulation. This application is intended to explore the system capabilities in real-time biomedical applications. Eventually, system usability test is conducted to evaluate the learnability, user experience and interaction quality in 3D interaction in comparison to 2D touch-screen interaction.

Background: The ALS Online Genetics Database (ALSoD) website holds mutation, geographical, and phenotype data on genes implicated in amyotrophic lateral sclerosis (ALS) and links to bioinformatics resources, publications, and tools for analysis. On average, there are 300 unique visits per day, suggesting a high demand from the research community. To enable wider access, we developed a mobile-friendly version of the website and a smartphone app. Objective: We sought to compare data traffic before and after implementation of a mobile version of the website to assess utility. Methods: We identified the most frequently viewed pages using Google Analytics and our in-house analytic monitoring. For these, we optimized the content layout of the screen, reduced image sizes, and summarized available information. We used the Microsoft. NET framework mobile detection property (HttpRequest. IsMobileDevice in the Request. Browser object in conjunction with HttpRequest. UserAgent), which returns a true value if the browser is a recognized mobile device. For app development, we used the Eclipse integrated development environment with Android plug-ins. We wrapped the mobile website version with the WebView object in Android. Simulators were downloaded to test and debug the applications. Results: The website automatically detects access from a mobile phone and redirects pages to fit the smaller screen. Because the amount of data stored on ALSoD is very large, the available information for display using smartphone access is deliberately restricted to improve usability. Visits to the website increased from 2231 to 2820, yielding a 26% increase from the pre-mobile to post-mobile period and an increase from 103 to 340 visits (230%) using mobile devices (including tablets). The smartphone app is currently available on BlackBerry and Android devices and will be available shortly on iOS as well. Conclusions: Further development of the ALSoD website has allowed access through smartphones and tablets, either through the website or directly through a mobile app, making genetic data stored on the database readily accessible to researchers and patients across multiple devices.

En tung industri har oftast utrustning installerad som kan bidra till övertoner på ett elnät. Samtidigt är oftast elnäten starka inom dessa industrier vilket ska bidra till att reducera spänningsövertonerna som går att finna på respektive fas.Studien har arbetat med de villkor och föreskrifter som gäller både för en ansluten elanläggning till Vattenfalls elnät, men även hur en elkvalitetsmätning ska genomföras och vilka krav som behöver uppfyllas.Åkers Sweden AB, där studien har ägt rum, har induktionsugnar för smältning av metaller. Det förekommer olika tekniska lösningar samt 3 olika fabrikat. Mätningar har genomförts på samtliga dessa fabrikat för att kontrollera om någon av dessa urskiljer sig gentemot de övriga.Genomförda mätningar indikerar att spänningsövertoner förekommer men inte i sådan utsträckning att man inte uppfyller gällande regelverk. Det finns dock anledning till att fortsätta arbetet och utöka mätningarna till övriga objekt inom företaget som inte har ingått i denna studie.Företaget har ett effektabonnemang och en kontroll av detta med avseende på nu gällande effekt och förbrukning under 2015 har genomförts för att kunna ge förslag på eventuella förändringar. Eftersom företaget har ungefär samma produktionsvolym 2016 som 2015 finns anledning till att se över nu gällande avtal för att kunna erhålla en kostnadsreducering.En enkät har skickats ut till samtliga anställda inom företaget med syfte att både upplysa de anställda om vilka kvalitetsproblem som kan förekomma inom ett elnät, men även få en återkoppling på hur de anställda upplever nuvarande situation. Enkäten fick låg svarsfrekvens men svaren som inkom indikerade att de anställda upplever att företaget har en god elkvalitet.

To develop a Real-Time system, which can capture and track the web user’s head motion. Based on the head motion information, the system should be able to identify whether the user is interested in the current homepage or not. A future system property would be to find out in which area of the homepage the user’s interest is moving.

Today’s ultra-connected world is generating a huge amount of data stored in databases and cloud environment especially in the era of transportation. These databases need to be processed and analyzed to extract useful information and present it as a valid element for transportation managers for further use, such as road safety, shipping delays, and shipping optimization. The potential of data mining algorithms is largely untapped, this paper shows large-scale techniques such as associations rule analysis, multiple criteria analysis, and time series to improve road safety by identifying hot-spots in advance and giving chance to drivers to avoid the dangers. Indeed, we proposed a framework DM-MCDA based on association rules mining as a preliminary task to extract relationships between variables related to a road accident, and then integrate multiple criteria analysis to help decision-makers to make their choice of the most relevant rules. The developed system is flexible and allows intuitive creation and execution of different algorithms for an extensive range of road traffic topics. DM-MCDA can be expanded with new topics on demand, rendering knowledge extraction more robust and provide meaningful information that could help in developing suitable policies for decision-makers.

This report contains an investigation of fluid injection techniques used in the purpose of reducing deleterious flow effects occurring in the draft tube of Francis turbines when operating outside nominal load. There is a focus on implement ability at Jämtkrafts hydroelectric power plants and two power plants were investigated, located in series with each other named Lövhöjden and Ålviken. The only profitable scenario found with some degree of certainty was an increase in the operating range upwards to allow overload operation.

Findings show that both air and water can be introduced in various locations to improve hydraulic efficiency around the turbine parts as well as reduce pressure pulsations in harmful operating regions. Investments in such systems have proven useful and profitable at several facilities with poorly adapted operating conditions. But due to losses in efficiency when operating injection systems, it turns out unprofitable in situations where it does not improve the operating range in a way that is resulting in increased annual or peak production.

The problem of generating oscillations of the inertia wheel pendulum is considered. We combine exact feedback linearization with two-relay controller, tuned using frequency-domain tools, such as computing the locus of a perturbed relay system. Explicit expressions for the parameters of the controller in terms of the desired frequency and amplitude are derived. Sufficient conditions for orbital asymptotic stability of the closed-loop system are obtained with the help of the Poincare map. Performance is validated via experiments. The approach can be easily applied for a minimum phase system, provided the behavior of the states of the zero dynamics is of no concern. Copyright (C) 2011 John Wiley & Sons, Ltd.

The purpose of the paper is to analyze the performance of several global position regulators for robot manipulators with Coulomb friction. All the controllers include a proportional-differential part and a switched part whereas the difference between the controllers is in the way of compensation of the gravitational forces. Stability analysis is also revisited within the nonsmooth Lyapunov function framework for the controllers with and without gravity pre-compensation. Performance issues of the proposed controllers are evaluated in an experimental study of a five degrees-of-freedom robot manipulator. In the experiments, we choose two criteria for performance analysis. In the first set of experiments, we set the same gains to all the controllers. In the second set of experiments, the gains of the controller were chosen such that the work done by the manipulator is similar.

This report introduces various mobile network technologies, 1G to 5G. Focus is on the future 5G mobile networks, how it works and what opportunities will come with it. The report also covers the base stations that will be used in the future mobile network, with a brief description of the terminal in 5G network and the services that will be available with it. The protocol stack in 5G network is also covered. Moreover the report presents the Wi-Fi 802.11u standard that will be a part of the future mobile network. We can also read about how the 5G network will solve certain problems that are related to today's networks technologies. Finally, the report describes different access technologies that are used in the telecommunications systems.

The automotive safety company Veoneer are producers of high end driver visual assistance systems, but the knowledge about the absolute accuracy of their dynamic calibration algorithms that estimate the vehicle’s orientation is limited.

In this thesis, a novel measurement system is proposed to be used in gathering reference data of a vehicle’s orientation as it is in motion, more specifically the pitch and roll angle of the vehicle. Focus has been to estimate how the uncertainty of the measurement system is affected by errors introduced during its construction, and to evaluate its potential in being a viable tool in gathering reference data for algorithm performance evaluation.

The system consisted of three laser distance sensors mounted on the body of the vehicle, and a range of data acquisition sequences with different perturbations were performed by driving along a stretch of road in Linköping with weights loaded in the vehicle. The reference data were compared to camera system data where the bias of the calculated angles were estimated, along with the dynamic behaviour of the camera system algorithms. The experimental results showed that the accuracy of the system exceeded 0.1 degrees for both pitch and roll, but no conclusions about the bias of the algorithms could be drawn as there were systematic errors present in the measurements.

AbstractCloud computing is a computing model that allows better management, higher utiliza-tion and reduced operating costs for datacenters while providing on demand resourceprovisioning for different customers. Data centers are often enormous in size andcomplexity. In order to fully realize the cloud computing model, efficient cloud man-agement software systems that can deal with the datacenter size and complexity needto be designed and built.This thesis studies automated cloud elasticity management, one of the main andcrucial datacenter management capabilities. Elasticity can be defined as the abilityof cloud infrastructures to rapidly change the amount of resources allocated to anapplication in the cloud according to its demand. This work introduces algorithms,techniques and tools that a cloud provider can use to automate dynamic resource pro-visioning allowing the provider to better manage the datacenter resources. We designtwo automated elasticity algorithms for cloud infrastructures that predict the futureload for an application running on the cloud. It is assumed that a request is either ser-viced or dropped after one time unit, that all requests are homogeneous and that it takesone time unit to add or remove resources. We discuss the different design approachesfor elasticity controllers and evaluate our algorithms using real workload traces. Wecompare the performance of our algorithms with a state-of-the-art controller. We ex-tend on the design of the best performing controller out of our two controllers anddrop the assumptions made during the first design. The controller is evaluated with aset of different real workloads.All controllers are designed using certain assumptions on the underlying systemmodel and operating conditions. This limits a controller’s performance if the modelor operating conditions change. With this as a starting point, we design a workloadanalysis and classification tool that assigns a workload to its most suitable elasticitycontroller out of a set of implemented controllers. The tool has two main components,an analyzer and a classifier. The analyzer analyzes a workload and feeds the analysisresults to the classifier. The classifier assigns a workload to the most suitable elasticitycontroller based on the workload characteristics and a set of predefined business levelobjectives. The tool is evaluated with a set of collected real workloads and a set ofgenerated synthetic workloads. Our evaluation results shows that the tool can help acloud provider to improve the QoS provided to the customers.

Peer-assisted cloud storage systems use the unutilizedresources of the clients subscribed to a storage cloudto offload the servers of the cloud. The provider distributesdata replicas on the clients instead of replicating on the localinfrastructure. These replicas allow the provider to providea highly available, reliable and cheap service at a reducedcost. In this work we introduce NileStore, a protocol forreplication management in peer-assisted cloud storage. Theprotocol converts the replica placement problem into a lineartask assignment problem. We design five utility functionsto optimize placement taking into account the bandwidth,free storage and the size of data in need of replication oneach peer. The problem is solved using a suboptimal greedyoptimization algorithm. We show our simulation results usingthe different utilities under realistic network conditions. Ourresults show that using our approach offloads the cloud serversby about 90% compared to a random placement algorithmwhile consuming 98.5% less resources compared to a normalstorage cloud.

We introduce NileStore, a replica placement algorithm based on an economical model for use in Peer-assisted cloud storage. The algorithm uses storage and bandwidth resources of peers to offload the cloud provider’s resources. We formulate the placement problem as a linear task assignment problem where the aim is to minimize time needed for file replicas to reach a certain desired threshold. Using simulation, We reduce the probability of a file being served from the provider’s servers by more than 97.5% under realistic network conditions.

Video-on-Demand (VoD) and video sharing services accountfor a large percentage of the total downstream Internet traf-fic. In order to provide a better understanding of the loadon these services, we analyze and model a workload tracefrom a VoD service provided by a major Swedish TV broad-caster. The trace contains over half a million requests gener-ated by more than 20000 unique users. Among other things,we study the request arrival rate, the inter-arrival time, thespikes in the workload, the video popularity distribution, thestreaming bit-rate distribution and the video duration distri-bution. Our results show that the user and the session ar-rival rates for the TV4 workload does not follow a Poissonprocess. The arrival rate distribution is modeled using a log-normal distribution while the inter-arrival time distributionis modeled using a stretched exponential distribution. Weobserve the “impatient user” behavior where users abandonstreaming sessions after minutes or even seconds of startingthem. Both very popular videos and non-popular videos areparticularly affected by impatient users. We investigate ifthis behavior is an invariant for VoD workloads.

Accurate understanding of workloads is key to efficient cloud resource management as well as to the design of large-scale applications. We analyze and model the workload of Wikipedia, one of the world's largest web sites. With descriptive statistics, time-series analysis, and polynomial splines, we study the trend and seasonality of the workload, its evolution over the years, and also investigate patterns in page popularity. Our results indicate that the workload is highly predictable with a strong seasonality. Our short term prediction algorithm is able to predict the workload with a Mean Absolute Percentage Error of around 2%.

Workload burstiness and spikes are among the main reasons for service disruptions and decrease in the Quality-of-Service (QoS) of online services. They are hurdles that complicate autonomic resource management of datacenters. In this paper, we review the state-of-the-art in online identification of workload spikes and quantifying burstiness. The applicability of some of the proposed techniques is examined for Cloud systems where various workloads are co-hosted on the same platform. We discuss Sample Entropy (SampEn), a measure used in biomedical signal analysis, as a potential measure for burstiness. A modification to the original measure is introduced to make it more suitable for Cloud workloads.

Autoscaling algorithms for elastic cloud infrastructures dynami-cally change the amount of resources allocated to a service ac-cording to the current and predicted future load. Since there areno perfect predictors, no single elasticity algorithm is suitable foraccurate predictions of all workloads. To improve the quality ofworkload predictions and increase the Quality-of-Service (QoS)guarantees of a cloud service, multiple autoscalers suitable for dif-ferent workload classes need to be used. In this work, we intro-duce WAC, a Workload Analysis and Classification tool that as-signs workloads to the most suitable elasticity autoscaler out of aset of pre-deployed autoscalers. The workload assignment is basedon the workload characteristics and a set of user-defined Business-Level-Objectives (BLO). We describe the tool design and its maincomponents. We implement WAC and evaluate its precision us-ing various workloads, BLO combinations and state-of-the-art au-toscalers. Our experiments show that, when the classifier is tunedcarefully, WAC assigns between 87% and 98.3% of the workloadsto the most suitable elasticity autoscaler.

Elasticity algorithms for cloud infrastructures dynamically change the amount of resources allocated to a running service according to the current and predicted future load. Since there is no perfect predictor, and since different applications’ workloads have different characteristics, no single elasticity algorithm is suitable for future predictions for all workloads. In this work, we introduceWAC, aWorkload Analysis and Classification tool that analyzes workloads and assigns them to the most suitable elasticity controllers based on the workloads’ characteristics and a set of business level objectives.

WAC has two main components, the analyzer and the classifier. The analyzer analyzes workloads to extract some of the features used by the classifier, namely, workloads’ autocorrelations and sample entropies which measure the periodicity and the burstiness of the workloads respectively. These two features are used with the business level objectives by the clas-sifier as the features used to assign workloads to elasticity controllers. We start by analyzing 14 real workloads available from different applications. In addition, a set of 55 workloads is generated to test WAC on more workload configurations. We implement four state of the art elasticity algorithms. The controllers are the classes to which the classifier assigns workloads. We use a K nearest neighbors classifier and experiment with different workload combinations as training and test sets. Our experi-ments show that, when the classifier is tuned carefully, WAC correctly classifies between 92% and 98.3% of the workloads to the most suitable elasticity controller.

This thesis studies cloud capacity auto-scaling, or how to provision and release re-sources to a service running in the cloud based on its actual demand using an auto-matic controller. As the performance of server systems depends on the system design,the system implementation, and the workloads the system is subjected to, we focuson these aspects with respect to designing auto-scaling algorithms. Towards this goal,we design and implement two auto-scaling algorithms for cloud infrastructures. Thealgorithms predict the future load for an application running in the cloud. We discussthe different approaches to designing an auto-scaler combining reactive and proactivecontrol methods, and to be able to handle long running requests, e.g., tasks runningfor longer than the actuation interval, in a cloud. We compare the performance ofour algorithms with state-of-the-art auto-scalers and evaluate the controllers’ perfor-mance with a set of workloads. As any controller is designed with an assumptionon the operating conditions and system dynamics, the performance of an auto-scalervaries with different workloads.In order to better understand the workload dynamics and evolution, we analyze a6-years long workload trace of the sixth most popular Internet website. In addition,we analyze a workload from one of the largest Video-on-Demand streaming servicesin Sweden. We discuss the popularity of objects served by the two services, the spikesin the two workloads, and the invariants in the workloads. We also introduce, a mea-sure for the disorder in a workload, i.e., the amount of burstiness. The measure isbased on Sample Entropy, an empirical statistic used in biomedical signal processingto characterize biomedical signals. The introduced measure can be used to charac-terize the workloads based on their burstiness profiles. We compare our introducedmeasure with the literature on quantifying burstiness in a server workload, and showthe advantages of our introduced measure.To better understand the tradeoffs between using different auto-scalers with differ-ent workloads, we design a framework to compare auto-scalers and give probabilisticguarantees on the performance in worst-case scenarios. Using different evaluation cri-teria and more than 700 workload traces, we compare six state-of-the-art auto-scalersthat we believe represent the development of the field in the past 8 years. Knowingthat the auto-scalers’ performance depends on the workloads, we design a workloadanalysis and classification tool that assigns a workload to its most suitable elasticitycontroller out of a set of implemented controllers. The tool has two main components;an analyzer, and a classifier. The analyzer analyzes a workload and feeds the analysisresults to the classifier. The classifier assigns a workload to the most suitable elasticitycontroller based on the workload characteristics and a set of predefined business levelobjectives. The tool is evaluated with a set of collected real workloads, and a set ofgenerated synthetic workloads. Our evaluation results shows that the tool can help acloud provider to improve the QoS provided to the customers.

In this thesis, a novel color measurement system has been developed and its performance evaluated.It is a modular spectral imaging goniophotometer that measures angle resolved spectralreflectance and transmittance of materials, e.g. textiles, papers, coated materials and flexibleelectronics. It is a highly flexible system that can, unlike most commercial systems, capturereflectance images of both high spectral and spatial resolution over a wide range of measurementgeometries.

It is important that the system can produce geometrically correct images of the samples, as well ascapture spectral information with high accuracy, i.e. the system needs to be both geometricallyand photometrically calibrated. A line-scan spectral camera and a high accuracy translationstage provide 2D-scans of the sample, where imaged area, sample position and measurementgeometry is controlled by a high precision robotic arm. Assessment of spectral and spatialresolution, characterization of the light source and spectral accuracy of the camera are someof the evaluations carried out. Spectral accuracy, and thus color measurement accuracy, isevaluated with the color difference formula CIE ∆E^∗_ab. During these evaluations the system isable to measure colors at ∆E^∗_ab < 14 and ∆E^∗_ab < 30 for a matte and glossy sample respectively,both of which are standard color calibration samples. These results show large color differencesthat are most likely caused by the low signal-to-noise ratio for short wavelengths due to thelight source. Finally, the system’s angle resolved measurement capability is demonstrated bymeasurements of goniochromatic samples whose color shifts with the viewing angle. The changein color is successfully captured for viewing angles in the range of 0 to 45 degrees from the surfacenormal.

A growing global population and large demands for crops worldwide is driving agricultural technological advances forward. In developing new automatic control functions for front end loader applications, Ålö AB needed a reliable and effective plant model of their front end loader Quicke Q5M. The plant model should include the associated mechanical and hydraulic system and be capable of rendering simulation and 3D animation in real time. An automated put down control function would also be of benefit for farming operators, speeding up the commonly performed farming task of putting down material from an elevated position. A plant model for the Quicke Q5M with a Load Sensing hydraulic system was developed in MATLAB Simulink with Simscape Multibody and Simscape Fluids. The performance of the simulated plant model was evaluated. The plant model showed some consistent results when compared to sensor data logs from a real-world front end loader. An automatic put down control function for material was also developed and tested in Simulink. A collision detection algorithm was constructed by analyzing sensor data logs from a real-world tractor putting down material on the ground. Velocity and acceleration estimations were made from angular position and pressure sensors to detect the contact between material and ground. The control function automatically stopped the lowering movement when contact was detected. The performance and accuracy of the control system under different scenarios were analyzed and discussed. Although the simulations of the plant model and proposed control function seemed realistic, the consistency of the plant model was hard to quantify since there was no time left for any thourough physical tests. It is recommended that future development of both the plant model and control system begin with an implementation test of the control system in a real-world tractor. This would help determine how accurately the plant model represents the front end loader. It would also allow evaluation and further tuning of the control function in a real physical environment.

Nowadays E-learning as a form of learning depending on networks and computer devices has been expanding by leaps and bounds. As a special kind of E-learning, M-learning (mobile learning) aims at the use of mobile devices anywhere at anytime by anybody. In this paper, the technologies to develop a M-learning system is deeply analyzed according to the layer model at first. Secondly, from the view of application, the standardization in M-learning is researched in order to accelerate the development and popularization of M-learning. Finally, quality estimation of M-learning system is discussed from the view of QoE (quality of experiences). The experience form end-user is the sole effective norm to judge the result of M-learning technology. It is no doubt that technologies, standardization and evaluation will play very important parts in the course of M-learning development.

To guarantee the quality of service (QoS) of a wireless network, a new packet scheduling algorithm using cross-layer design technique is proposed in this article. First, the demand of packet scheduling for multimedia transmission in wireless networks and the deficiency of the existing packet scheduling algorithms are analyzed. Then the model of the QoS-guaranteed packet scheduling (QPS) algorithm of high speed downlink packet access (HSDPA) and the cost function of packet transmission are designed. The calculation method of packet delay time for wireless channels is expounded in detail, and complete steps to realize the QPS algorithm are also given. The simulation results show that the QPS algorithm that provides the scheduling sequence of packets with calculated values can effectively improve the performance of delay and throughput.

This report presents my bachelor thesis performed at the Department of Applied Physics and Electronics at UmeåUniversity. The Digital Media Lab was the assigner, supervising and assisting me during the project.

A simple and smart system to verify a person’s identity using hand geometry as a biometrical identity is developed. The system should tolerate some deviation in hand placement and will not use pins or pegs. A complete system, hardware and software, is delivered. A webcam based hand-scanner is constructed and designed to operate on a PC utilizing Matlab for image processing.

This work presents an extension of a design procedure for dynamic output feedback design for systems with nonlinearities satisfying quadratic constraints. In this work we used an axial gas compressor model described by the 3-state Moore-Greitzer compressor model (MG) that has some challenges for output feedback control design (Planovsky and Nikolaev 1990), (Rubanova 2013). The more general constraints for the investigation of the robustness with respect to parametric uncertainties and measurement noise are shown.

Cross Control is a company that produces embedded computer solutions. A computer’ s normal input voltage is 18-30 VDC and consumes at the most 50W. The computers are sold to several different customers, who use them in anything from forwarders to trains. In separate vehicles the supply dc current varies from one vehicle to another. This creates needs to convert the voltage to a level that the computers can handle. Such a device is called a DC/DC-converter. Voltage conversion can be performed in different ways, either through linear regulation, or by using switching technology. The goal of our work is to design a DC/DC-converter that meets the requirements raised in cooperation with CrossControl. To achieve sufficient efficiency, and since galvanic isolation between input and output voltage is a requirement, the converter is based on a switched flyback solution. The transformer is the most important component for the converter function. Therefore, a large part of the project was focused on selecting a suitable one. The result is a prototype that is capable of regulating the output voltage to 24VDC for the entire input range, and can handle a load of 50W. The effectiveness ended at 80% which is 5% below target. To improve the prototype it is necessary to protect it from voltage outside input range. To achieve 85% efficiency one could redesign the snubber network.

Following an ongoing change towards an increasingly renewable power generation system Swedish grid operators are facing several challenges in coming years. As authorities plan for the decommissioning of nuclear power an increased reliance on de-centralised energy sources such as photo-voltaic distributed generation (PVDG) is expected. A technology observed in some cases to accompany local power quality issues severe enough to impose grid expansion measures from distribution system operators (DSOs). Considering a combination of an indicative utilisation inefficiency of classical grid expansion measures and a recent year maturing of various energy storage technologies, this report sets out to evaluate the possibility of utilising centralised energy storage systems (ESSs) for deferment of classical grid expansion measures.

For the purpose of identifying the most prominent problem scenarios of modern production- and consumption behaviours as well as the possible solutions offered by centralised ESSs, a literature review of journal articles and technical reports was conducted in combination with a case-study of an existing urban grid operated by Umeå Energi Elnät AB (UEEN). The work regarding ESSs is directed with specific focus towards evaluating which ESS services can potentially facilitate grid expansion deferment and what ESS placement is advisable for efficient utilisation. Assessing possible grid safety implications, potential for peak load shaving and the presently most suitable energy storage technology was also within the scope of the study.

The literature review reveals PVDG induced feeder line over-voltage and transformer overload the most likely and previously observed implications imposing grid expansion measures. The former more prominent in elongated, typically rural, grids and the latter in more densely populated urban grids. For deferment of over-voltage related grid expansion measures a centralised ESS can be utilised for voltage support provided placement is made close to the affected grid section, presumably far out the affected feeder line. This result is coherent throughout the reviewed literature and is supported by the results of the case-study. Distribution transformer overload and its imposed grid expansion measures can be deferred through load re-allocation and peak load shaving, two services proven achievable by centralised ESSs and the capacity for which increases if ESS placement is made closer the distribution transformer.

Provided present regulatory and standards are adhered to upon installation, significant negative impact of centralised ESSs on distribution grid safety can be avoided. Most energy storage technologies, including battery based energy storage technologies indicated from the literature review providing the most suitable characteristics for use in centralised distribution grid ESSs, utilise well established systems for grid connection hence no presently unsolvable grid safety implications are identified. Technical reports of real applications of centralised ESSs reinforce this argument as successful implementation without ESS caused grid safety implications have been achieved in the Swedish distribution grid in the past.

Humans are increasingly relying on complex systems that heavily adopts Artificial Intelligence (AI) techniques. Such systems are employed in a growing number of domains, and making them explainable is an impelling priority. Recently, the domain of eXplainable Artificial Intelligence (XAI) emerged with the aims of fostering transparency and trustworthiness. Several reviews have been conducted. Nevertheless, most of them deal with data-driven XAI to overcome the opaqueness of black-box algorithms. Contributions addressing goal-driven XAI (e.g., explainable agency for robots and agents) are still missing. This paper aims at filling this gap, proposing a Systematic Literature Review. The main findings are (i) a considerable portion of the papers propose conceptual studies, or lack evaluations or tackle relatively simple scenarios; (ii) almost all of the studied papers deal with robots/agents explaining their behaviors to the human users, and very few works addressed inter-robot (inter-agent) explainability. Finally, (iii) while providing explanations to non-expert users has been outlined as a necessity, only a few works addressed the issues of personalization and context-awareness

This work describes a master’s thesis in engineering physics at Umeå University carried out during the spring semester of 2014. In the thesis the student has constructed and tested a temperature controlled cell for cooling/heating of surface-enhanced-Raman-spectroscopy (SERS) substrates for rapid detection of volatile substances. The thesis was carried out at the Swedish Defence Research Agency (FOI) in Umeå, Sweden. A Linkam Scientific Instruments TS1500 cell was equipped with a Peltier element for cooling/heating and a thermistor temperature sensor. A control system was constructed, based on an Arduino Uno microcontroller board and a pulse-width-modulated (PWM) H-bridge motor driver to control the Peltier element using a proportional-integral (PI) control algorithm. The temperature controlled cell was able to regulate the temperature of a SERS substrate within -15 to +110 °C and maintain the temperature over prolonged periods at ±0.22 °C of the set point temperature. Gas phase of 2-chloro-2-(difluoromethoxy)-1,1,1-trifluoro-ethane (isoflurane) was flowed through the cell and SERS spectra were collected at different temperatures and concentrations. This test showed that the signal is increased when the substrate is cooled and reversibly decreased when the substrate was heated.

Keywords: temperature control, Raman scattering, surface enhanced Raman spectroscopy SERS, SERS substrate, volatile substances, Peltier module, thermistor, PWM, H-bridge, PI(D) control.

An intuitive solution for the problem of adaptive attenuation of a disturbance formed as a finite sum of unknown sinusoidal signals is proposed for an internally stable discrete-time plant. The compensator is formed as a weighted sum of stable filters. An identification-based procedure for adaptive tuning of the coefficients is proposed for the case of unknown disturbance. We also propose a time-invariant compensator that provides perfect attenuation of a disturbance for the case when a model identification error is sufficiently small and disturbance frequencies are known. The technique is applied to a case study on a challenging benchmark example in the field of active vibration control. Attenuation of a disturbance formed as a sum of up to three sinusoidal signals with unknown/time-varying frequencies is demonstrated via simulation and experimental studies. (C) 2013 European Control Association. Published by Elsevier Ltd. All rights reserved.

MODELING AND IDENTIFICATION OF DYNAMICS OF A HYDRAULIC ACTUATOR WITH A SPOOL VALVE. PART I. MODELING

Approaches to the problem of modeling of hydraulic actuator are considered. A model for the spool dynamics consisting of a linear block and two static nonlinear subsystems is presented.

MODELING AND IDENTIFICATION OF DYNAMICS OF A HYDRAULIC ACTUATOR WITH A SPOOL VALVE. PART II: IDENTIFICATION

A method for identification of dynamic model parameters is suggested for the case when only pressures in the hydraulic cylinders but not the valve displacements are measured. The approach is verified by presented results of experiments.

A problem of position control of a forestry crane is studied. Several features of industrial hydraulic systems are pointed out, namely a nonlinearity of a valve and a pressure compensator. A novel model of a hydraulic system with the pressure compensator is presented and analyzed, a static nonlinearity inversion and a velocity feedforward control term are introduced. Real-time experiments with controllers which use only position measurements illustrate utility of these terms.

A problem of position control of a single-link hydraulic drive, including model uncertainties and disturbances, is studied. Main properties of mobile hydraulic systems are taking into account, namely a nonlinearity of a valve and a pressure compensator. A discontinuous control law coupled with a static nonlinearity inversion and a feed-forward term of velocity is proposed. Besides, a novel model with pressure compensator is presented and the closed-loop stability analysis is provided. Results of experiments carried out on a forestry crane confirm the efficacy of the proposed approach.

The potential offered by the intra-body communication (IBC) over the past few years has resulted in a spike of interest for the topic, specifically for medical applications. Fat-IBC is subsequently a novel alternative technique that utilizes fat tissue as a communication channel. This work aimed to identify such transmission medium and its performance in varying blood-vessel systems at 2.45 GHz, particularly in the context of the IBC and medical applications. It incorporated three-dimensional (3D) electromagnetic simulations and laboratory investigations that implemented models of blood vessels of varying orientations, sizes, and positions. Such investigations were undertaken by using ex-vivo porcine tissues and three blood-vessel system configurations. These configurations represent extreme cases of real-life scenarios that sufficiently elucidated their principal influence on the transmission. The blood-vessel models consisted of ex-vivo muscle tissues and copper rods. The results showed that the blood vessels crossing the channel vertically contributed to 5.1 dB and 17.1 dB signal losses for muscle and copper rods, respectively, which is the worst-case scenario in the context of fat-channel with perturbance. In contrast, blood vessels aligned-longitudinally in the channel have less effect and yielded 4.5 dB and 4.2 dB signal losses for muscle and copper rods, respectively. Meanwhile, the blood vessels crossing the channel horizontally displayed 3.4 dB and 1.9 dB signal losses for muscle and copper rods, respectively, which were the smallest losses among the configurations. The laboratory investigations were in agreement with the simulations. Thus, this work substantiated the fat-IBC signal transmission variability in the context of varying blood vessel configurations.

Fokus läggs mer och mer på hur olinjära laster påverkar spänningsgodheten pånätet. Ledorden är att ”du skall icke sabotera din grannes spänningskvalitet!”.Detta gillar nätbolagen och allmänheten men i vissa delar av nätet är det inte lika nödvändigt att hålla så hårt på elkvaliteten. Industrier har ofta anläggningar som är avskilda öar från det elektriska fastlandet. Därför gjordes mätningar på befintlig anläggning med stor del frekvensomriktardrift för att kunna jämföra med simuleringar från dimensioneringsprogram och slutligen utifrån resultatet dra slutsatser om hur man ska utveckla tankesättet vid dimensionering av frekvensomriktare för att göra den mer kostnadseffektiv.

This thesis is performed at WSP in Skellefteå, specializing in Rönnskär Education in Skelleftehamn.

Rönnskär’s construction began by Boliden AB in 1928 and it was ready for production in 1930. It produces copper, lead, zinc clinker, gold and silver. In 2010 Rönnskär produced 190000 tons of copper and in 2013 it produced 206 000 tons. Current number of employees is 866.

The electricity supply of the industrial area of Rönnskär is in very high priority and transformer failures leading to lengthy downtime and expensive repairs. Power transformers must have high operational availability transformers which purchases for production must be robust.

This is a comparative study between dry type and oil insulated transformers which summarized in form of recommendation for the future purchases.

The work will highlight the parameters of operational availability and operational safety make calculations for rated short time currents and losses in transformers based on manufacturers data.

The aim of this thesis is to compare various parameters of dry and oil immersed transformers from different manufacturers summarized in a comparison table according to the apparent power and voltage which shows the difference between various types of transformers.

This work is primarily based on the theory of transformers and at the same time on continuous dialogue with the client and the transformer manufacturer.

The recommendations should be viewed as a preliminary study, a deeper analysis and further investigation is required when purchasing transformers, depending on the circumstances and the conditions.

An economic analysis has not been performed because of the limited information.

Keyword for this study is AOS: Availability and Operational Safety.

This thesis is performed at WSP in Skellefteå, specializing in Rönnskär Education in Skelleftehamn.

Rönnskär’s construction began by Boliden AB in 1928 and it was ready for production in 1930. It produces copper, lead, zinc clinker, gold and silver. In 2010 Rönnskär produced 190000 tons of copper and in 2013 it produced 206 000 tons. Current number of employees is 866.

The electricity supply of the industrial area of Rönnskär is in very high priority and transformer failures leading to lengthy downtime and expensive repairs. Power transformers must have high operational availability transformers which purchases for production must be robust.

This is a comparative study between dry type and oil insulated transformers which summarized in form of recommendation for the future purchases.

The work will highlight the parameters of operational availability and operational safety make calculations for rated short time currents and losses in transformers based on manufacturers data.

The aim of this thesis is to compare various parameters of dry and oil immersed transformers from different manufacturers summarized in a comparison table according to the apparent power and voltage which shows the difference between various types of transformers.

This work is primarily based on the theory of transformers and at the same time on continuous dialogue with the client and the transformer manufacturer.

The recommendations should be viewed as a preliminary study, a deeper analysis and further investigation is required when purchasing transformers, depending on the circumstances and the conditions.

An economic analysis has not been performed because of the limited information.

Keyword for this study is AOS: Availability and Operational Safety

Brain-computer interface (BCI) systems can provide people with ability to communicate and control real world systems using neural activities. Therefore, it makes sense to develop an assistive framework for command and control of a future robotic system which can assist the human robot collaboration. In this paper, we have employed electroencephalographic (EEG) signals recorded by electrodes placed over the scalp. The human-hand movement based motor imagery mentalization is used to collect brain signals over the motor cortex area. The collected µ-wave (8–13 Hz) EEG signals were analyzed with event-related desynchronization/synchronization (ERD/ERS) quantification to extract a threshold between hand grip and release movement and this information can be used to control forestry crane grasping and release functionality. The experiment was performed with four healthy persons to demonstrate the proof-of concept BCI system. From this study, it is demonstrated that the proposed method has potential to assist the manual operation of crane operators performing advanced task with heavy cognitive work load.

In this paper, we investigate the use of fat tissue as a communication channel between in-body, implanted devices at R-band frequencies (1.7–2.6 GHz). The proposed fat channel is based on an anatomical model of the human body. We propose a novel probe that is optimized to efficiently radiate the R-band frequencies into the fat tissue. We use our probe to evaluate the path loss of the fat channel by studying the channel transmission coefficient over the R-band frequencies. We conduct extensive simulation studies and validate our results by experimentation on phantom and ex-vivo porcine tissue, with good agreement between simulations and experiments. We demonstrate a performance comparison between the fat channel and similar waveguide structures. Our characterization of the fat channel reveals propagation path loss of ∼0.7 dB and ∼1.9 dB per cm for phantom and ex-vivo porcine tissue, respectively. These results demonstrate that fat tissue can be used as a communication channel for high data rate intra-body networks.