This report describes a project aimed at determining the angle of the landing platform to the drones using a tilted platform, IMU, and image processing algorithms. The goal of this project is to determine the safe landing of drones and drone landings by optimizing the landing location via platform tilt adjustment and angle computation. A robotic arm was used to tilt the rectangular platform, and a web camera was used to get images from the top view. Image processing methods built-in MATLAB allow for approximate landing angle determination and angle determination is also done with IMU. The findings confirm the system’s efficiency, with reasonable angle estimates and successful drone landings.

The growing global demand for clean energy is critical, and wind power plays a crucial role in addressing this need. The increasing demand is driving advancements in the field of offshore wind power and one promising innovation is the counter-rotating vertical axis turbines (CRVT), specifically designed for floating wind power installations. The aim of this project was to develop a dynamic simulation and 3D visualization of a floating wind turbine using CRVT technology. In this project, simplified force models were created with the aim to incorporate more complex models from experts in wind and water dynamics in the future. The simplified force calculations included gravity, buoyancy, the Morison equation, as well as forces from a simple mooring and a generator. The implemented aerodynamic forces were obtained from a complex model developed by an expert in aerodynamics. The simulation was conducted in Matlab, utilizing first-principal physics for dynamics calculations. All the measurements used to compute the geometry of the wind turbine were imported from a CSV file. Finally, the RK4 method was employed to compute the steps, and a Maya model was created for the visualization of the wind turbine. In conclusion, the simulation successfully enabled the wind turbine's motion in all six degrees of freedom and provided a visual representation of the results. However, significant approximations were made, and additional validation is necessary to ensure the accuracy of the simulation.

Calcium signaling has been identified with triggering of gene transcriptions associated with learning and neuroprotection in neurons. Studies indicate that dysregulation of calcium signaling is correlated with severe Alzheimer Disease pathologies. A stable calcium wave or signal arising from triggers in dendritic synapses needs to reach soma with constant amplitude for proper functioning of neurons. In this study, we introduce "CalciumSim", a calcium dynamics simulator which works on dimensionally reduced model. Numerical analysis is conducted to obtain the best configuration of neuron geometry to make the code efficient and fast. Alongside, biologically important insights are derived by modulating and changing parameters of the simulation. The ability of "CalciumSim" to work with real neuron geometries allows user to study calcium signalling in a realistic model. / Mathematics

Disasters are characterized by large numbers of victims and required resources, overwhelming the available resources. Disaster response involves various entities like Incident Commanders, dispatch centers, emergency operations centers, area command and hospitals. An effective emergency response system should facilitate coordination between these various entities. Victim triage, emergency resource allocation and victim dispatch to hospitals form an important part of an emergency response system. In this present research effort, an emergency response system with the aforementioned components is developed. Triage is the process of prioritizing mass casualty victims based on severity of injuries. The system presented in this thesis is a low-cost victim triage system with RFID tags that aggregate all victim information within a database. It will allow first responders' movements to be tracked using GPS. A web-based real time resource allocation tool that can assist the Incident Commanders in resource allocation and transportation for multiple simultaneous incidents has been developed. This tool ensures that high priority resources at emergency sites are received in least possible time. This web-based tool also computes the patient dispatch schedule from each disaster site to each hospital. Patients are allocated to nearest hospitals with available medical facilities. This tool can also assist resource managers in emergency resource planning by computing the time taken to receive required resources from the nearest depots using Google Maps. These web-based tools complements emergency response systems by providing decision-making capabilities.

Solar photovoltaic energy has gained great importance in the last couple of years, as its costs getlower and the total installed capacity increases. As a result of this, new technologies are arisingwithin the field, with the objective of increasing performance and reducing costs. One of themis the half-cell solar modules which, among other advantages, are said to perform better undershaded conditions compared to standard modules.This project checks the veracity of this statement. For that, a Matlab/Simulink model capable ofrepresenting the behavior of the JAM60S21-365-MR solar module has been created, andexperimentally calibrated with measurements performed in an actual panel. After the modelaccuracy has been checked, it has been used to simulate various shaded scenarios for standardand half-cell modules, to carry out an equivalent comparison between the two.The results for the model show a maximum error of 0.62% for the reference case, and of 6.06%for the worst 4-module-string simulation. This has been found to be an acceptable error, whichis created mainly as a result of temperature measuring inaccuracies and the rough estimation ofsolar cell model parameters. To reduce it, it is recommended that these issues are addressed.Which module does better under shading has been found to be dependent on multiple factors:The temperature and irradiance at which the module operates, its constructive parameters, thenumber of series or parallel connected devices and the shape and size of the shadow. This lastone is the one with the biggest impact in electrical power output. Because of it, the most usualcases for shadowing in PV facilities have been compared. For equivalent modules, shading in thedirection of the string of a single cell is less detrimental in half-cell modules; however, if thatshadow covers a whole row, it is equally damaging. If a full cell is 50% shaded in this scenario, a20% less power is lost in the half cell module compared to the normal one. On the other hand,shadowing in the direction on the bypass-diode line tends to slightly benefit standard modulesfor equal cell parameters if the shadowed full-cell percentage is below 50%, for both cell androw shading. However, as this value increases, half-cell modules tend to gain an advantage overstandard ones.

GNSS positioning has become a key element in everyday life of millions of people, from the person using google maps to move around an unknown city to the mailman or the DRON pilot who require it to carry out their work. All of them benefit in some way from the GNSS constellations and the position algorithms.The European Union through their GNSS constellation, Galileo, has recently made available a new service called Galileo High Accuracy Service (HAS). With the aim of improving the positioning solutions already provided by the Open Service (OS) to a centimetric level with the target of professional and commercial users requiring this high accuracy. As a result, in this Master Thesis project the steps of the development and implementation of a Software-Defined Radio to collect the High Accuracy corrections transmitted through Galileo GNSS constellation are going to be shown. The SDR itself is going to be made available so that other persons from companies to academia can benefit from it and see how the corrections are extracted and either use the algorithm or implement its own to be able to use this High Accuracy Service.

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Using MATLAB and a National Instruments data acquisition card, a signal processing program meant to monitor the behavior of rotordynamic systems in real-time was developed and tested. By using traditional analysis methods in this field of engineering, commonly desired data representations such as bode, polar, orbit, full spectrum plots were able to be produced to a very high accuracy. Additional capabilities offered by this application are slow roll compensation, synchronous and sub-synchronous filtering, and true three dimensional plotting. The verification of this program was done by comparing the results to the ones acquired with Bently Nevada’s “Automated Diagnostics for Rotating Equipment” (ADRE) system. In addition to a data acquisition program, theoretical models of the two-disk rotor were created to estimate the unknown physical parameters of the system. By simulating the rotor with and without gyroscopic effects included, estimates for the stiffness, damping, eccentricity, initial phase, and initial skew values present in the system were determined.

Underwater networks are a field that has been gathering attention. Land-based methods of network construction from discovery to advanced routing are all well established. Due to the unique constraints of operating in an underwater environment, many of these tried-and-true approaches need modification if they function at all. Peer discovery and lowlevel networking have been dealt with by previous research. In this thesis we describe and evaluate eight possible routing schemes with different system-knowledge requirements. We show that with a minimal set of information it is possible to achieve near-optimal results with energy costs considerably lower than centralized optimal algorithms. We demonstrate this by constructing and evaluating a custom simulation environment in MATLAB. This is implemented in a mixed procedural and array-centric approach. Simulated networks are structured on a line topology. All nodes a spaced along the horizontal axis at a random depth. It is assumed that neighbor-discovery has been completed before the simulation starts, and all nodes have access to a global list of connected neighbors. We demonstrate the effectiveness of distributed algorithms in an ideal environment, leading to the conclusion that near-optimal results can be achieved with local information only.

With the rapid growth of Internet-of-Things (IoT), billions of devices are expected to be interconnected to provide various services appealing to users. Many devices will get an access to valuable information which is likely to increase the number of malicious attacks on these devices in the future. Therefore, security is considered as one of the most critical challenges in the development of IoT. In order to secure resource-constrained devices such as sensors or radio frequency identification (RFID) tags which form the backbone of IoT, lightweight cryptographic algorithms are required. This thesis focuses on the problem of message authentication. To authenticate a message means to verify that the message: (1) comes from the right sender (i.e. its authenticity), and (2) has not been modified (i.e. its integrity). It is challenging to use traditional message authentication methods in resource-constrained devices because typically they can allocate only a few hundred gates for implementing security due to their limited computing, storage and energy resources. To address these needs, a new message authentication algorithm based on a Cryptographic Cyclic Redundancy Check (C-CRC) was developed by KTH in collaboration with Ericsson. In this thesis, we implemented C-CRC and compared it with KECCAK Message Authentication Code (KMAC) standardized by the National Institute of Standards and Technology (NIST) in 2016. First, MATLAB and Verilog versions were developed for both algorithms. The comparison of these two versions allowed us to verify the correctness of algorithms functionality. After that, the Verilog descriptions were simulated in ModelSim and synthesized using Synopsys design compiler. Finally, placement and routing was performed using Cadence SoC Encounter. The evaluation results show that C-CRC outperforms KMAC in terms of area, power, throughput per area, and energy per bit. However, C-CRC is worse than KMAC in terms of latency. We have also investigated several different options of implementing C-CRC, including producing more than one bit of output per clock cycle. We found that such a technique improves throughput of C-CRC with the minimal penalty in area and power consumption