Musical Instrument Digital Interface(MIDI) is a technical standard that specifies acommunication protocol for digital instrument data and is mainly used by computers,synthesizers and electronic keyboards. A MIDI controller is any hardware or software that cangenerate and transfer MIDI data to a MIDI device, usually to play a sound or change controlparameters within a music software. An important property of a MIDI controller is to intuitively go from idea to execution withminimal effort. In this respect machine learning has really opened up for new musicalexpressions within musical devices. During this project a prototype with an implementedmachine learning algorithm which could deliver a wider array of functionality with a simplerinterface. The device developed should also be able to play Hi-Fi audio with at least 96 kHzsampling frequency and 24-bit bit-resolution. Without professional measurement equipment audio quality could not be completelymeasured. However, the development of the completed prototype as a whole was successful. Drawn symbols could be classified with a 70% accuracy, Hi-Fi audio could be played and MIDI-messages could be sent over USB to a music software.

This project aimed to create a simple open-source embedded graphical user interface library that could be used on more or less any microcontroller platform. The programming language was intended to be C++ for the GUI but as the project evolved C was chosen above C++. This was a decision based primarily on the fact that STM's development environment, STMCubeIDE, is less compatible with C++. The IDE offers great hardware support which in the end was more important than the advantages given by C++. The hardware used in this project was an STM32F469 microcontroller. It has an ARM CortexM4 processor core and 2 Mbyte of flash memory and 384 Kbytes of RAM. Wrapper functions for the Board Support Package, BSP, were written as a part of the library to allow easy access tothe BSP needed for the hardware configuration. The first part of the project goal was achieved, a simple GUI library was created. The resulting GUI library supports user interaction through buttons, it can display the current time andvisualizes given data in graphs. The graph function can display the data live, as a scatter plot, a bar plot and a line plot. The library also supports an alarm function that allows the user to decide what will happen after the alarm time is up. However, even though the GUI library was written to be device-independent, the product has not been tested on other platforms. For further development, this GUI library could be tested on another microcontroller. This would provide answers to how much software changes are needed to make the product as hardwareindependent as possible. To make the library lighter and faster, there is a possibility of optimizing the GUI core.

Energy-saving wireless sensors are increasingly used in the industry. Users can remotely monitor the status of the measured device and do not need to frequently replace the battery of the device. In this thesis, we studied a low-cost energy-independent wireless speed sensor system that can power itself by the rotation of the host. The BMG250 MEMS gyroscope is responsible for temperature and angular velocity measurement, and the nRF52832 SoC sends data to the remote monitoring terminal through BLE communication. This study aims to discover the energy consumption and energy saving methods of the entire process of data collection, data transfer, and data transmission. Finally, in order to meet the various test requirements, an energy consumption standard will be summed up to calculate the energy consumption of the entire system.

Rockfall, which is the detachment of rocks from a mountain, is a major hazard in the mining industry. To help combat this issue, this thesis aims to develop a sensor platform that is able to detect both the potential risk for rockfall and if any rocks do hit the ground. The platform requires wireless communication in order to output relevant information and in order to be part of an IoT-network of sensors.The design of the platform used three different sensors, a geophone, an accelerometer and a microphone. The main focus of the design process was to keep the platform low power, enabling long operation times. The final design had data output from both the microphone and accelerometer, with the accelerometer able to pick up the impact from a falling barbell. Wireless transmission of data is possible for up to 7.5 meters using Bluetooth Low Energy. The low power design was met, with an average current consumption of 26 milliamperes during transmission using Bluetooth Low Energy. That gives a theoretical operation time of 27 days with the battery used. As the accelerometer can pick up a falling object and with a theoretical lifetime of 27 days for the platform, it can be argued that the goals, except for detecting potential risk for rockfall, were met. In order to properly function, however, the platform needs more development, but the most important conclusion of the work is that it seems possible to build this type of platform. Further research and development outside the scope of the thesis is connecting several platforms together.

The design, test and implementation of a custom Ethernet card for embedded microcontrollers is described. The development of this Ethernet card is an educational effort to understand the various intricacies involved in constructing an Ethernet solution for embedded microcontrollers. The secondary motivation is to research the areas of the design can be ruggedized for high temperature and pressure applications. This report covers in detail the overall effort to which Henry Chang contributed. / text

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With the proliferation of cheap bulk SSD storage and better batteries in the last few years we are experiencing an explosion in the number of Internet of Things (IoT) devices flooding the market, smartphone connected point-of-sale devices (e.g. Square), home monitoring devices (e.g. NEST), fitness monitoring devices (e.g. Fitbit), and smart-watches. With new IoT devices come new security threats that have yet to be adequately evaluated. We propose uLeech, a new embedded trusted platform module for next-generation power scavenging devices. Such power scavenging devices are already widely deployed. For instance, the Square point-of-sale reader uses the microphone/speaker interface of a smartphone for communications and as a power supply. Such devices are being used as trusted devices in security-critical applications, without having been adequately evaluated. uLeech can securely store keys and provide cryptographic services to any connected smartphone. Our design also facilitates physical side-channel security analysis by providing interfaces to facilitate the acquisition of power traces and clock manipulation attacks. Thus uLeech empowers security researchers to analyze leakage in next- generation embedded and IoT devices and to evaluate countermeasures before deployment. Even the most secure systems reveal their secrets through secret-dependent computation. Secret- dependent computation is detectable by monitoring a system’s time, power, or outputs. Common defenses to side-channel emanations include adding noise to the channel or making algorithmic changes to mitigate specific side-channels. Unfortunately, existing solutions are not automatic, not comprehensive, or not practical. We propose an isolation-based approach for eliminating power and timing side-channels that is automatic, comprehensive, and practical. Our approach eliminates side-channels by leveraging integrated decoupling capacitors to electrically isolate trusted computation from the adversary. Software has the ability to request a fixed- power/time quantum of isolated computation. By discretizing power and time, our approach controls the granularity of side-channel leakage; the only burden on programmers is to ensure that all secret-dependent execution differences converge within a power/time quantum. We design and implement three approaches to power/time-based quantization and isolation: a wholly-digital version, a hybrid version that uses capacitors for time tracking, and a full- custom version. We evaluate the overheads of our proposed controllers with respect to software implementations of AES and RSA running on an ARM- based microcontroller and hardware implementations AES and RSA using a 22nm process technology. We also validate the effectiveness and real-world efficiency of our approach by building a prototype consisting of an ARM microcontroller, an FPGA, and discrete circuit components. Lastly, we examine the root cause of Electromagnetic (EM) side-channel attacks on Integrated Circuits (ICs) to augment the Quantized Computing design to mitigate EM leakage. By leveraging the isolation nature of our Quantized Computing design, we can effectively reduce the length and power of the unintended EM antennas created by the wire layers in an IC.

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Any system in the world constitutes particles like electrons. To analyze the behaviors of these systems the behavior of these particles must be predicted. The ground state energy of a molecule is the most important information about a molecule and can calculate by solving the Schrodinger equation. But as the number of atoms increase, the number of variable (coordinates of the atom) that the equation represent increases by three times. Due to the large state space and the nonlinear nature of the Schrodinger equation, it is very difficult to solver this equation. Quantum Monte Carlo (QMC) is a very efficient method to solve the Schrodinger equation for accurate results. This methods uses random numbers to sample the complex equation and get very accurate results. Due to the large data involved in this method, it exhibits rich amount of data parallelism. Variational path integral (VPI) simulations are a class of QMC methods that permit direct computation of expectation values of coordinate-space observables for the nodeless ground states of many-body quantum systems. High degree of data parallelism involved in this method facilitates the use of Graphical Processing Units (GPUs), a powerful type of processor well known to computer gamers. In comparison to the other parallel systems, like CPU clusters, GPU hardware can be much faster and is significantly cheaper. The goal of this thesis is to implement the VPI simulation algorithm on GPU to compute the coordinate-space observables of a Neon cluster.