The founders of Momo Medical envisioned a health care product that would help nurses worldwide with pressure ulcer prevention. Pressure ulcers are a chronic wound that affects the skin of patients who do not regularly change bed posture. As it currently stands, nurses lack the manpower and time to change the postureof patients in a timely manor. Thus, a goal was set to create a product that would reduce this strain on nurses.The goal was to design a non-intrusive product that keeps track of the posture of a patient on a hospital bed, and send an alarm if this has not changed in a set amount of time. A constraint with this was that the product has to lay directly underneath the mattress of the patient. Furthermore, the product has to make use of as few sensors as possible. With these constrains, the project group was divided in three subgroups: the sensor, the algorithm, and the testing subgroup.This report will focus on the design, implementation, and evaluation of the algorithm. The algorithm has to be designed to process the sensor data and return, with 90% accuracy, the posture of the patient. It also has to be able to determine with 99% accuracy whether or not there is a patient on the bed. An optional objective was to design an algorithm to determine the heart and respiration rate of the patient, with 80% accuracy, but this was of lower priority. It was soon decided to give priority to posture detection and not further investigate detection of the heart and respiration rate.In the final product, the information about the patient’s posture will be displayed in a graphical user interface (GUI). This GUI has to be user-friendly and intuitive to use by the nurses. During the prototyping phase, however, a different GUI was used, one that displayed various debugging information. This prototype GUI was necessary to test the various algorithms.Several different mathematical models have been investigated, implemented, and tested. These models range from taking the variance of the sensor data, to deploying a Fourier transform on a polynomial curve based on the sensor data. With preliminary test data, an accuracy of 93% was achieved using a neural network. With the final testing data however, only the neural network reached the required accuracy of 90%, though only just, at 90.8%. With future iterations of the algorithm, more research and data collection is advised, as neural networks work better with larger data sets.

One of the main problems with Instance-Level Image Retrieval in video data is that for query videos with multiple objects of the same instance, extracting features from keyframes of this query video is time consuming. This thesis aims to solve this problem by implementing a Convolutional Neural Network based approach, which significantly reduces the extraction time and increases the accuracy. After analysing multiple methods, Second-Order Loss and Attention for image Retrieval (SOLAR) was found to be the most promising method. SOLAR will be tested based on three performance metrics: the mean average precision, the recall and the extraction time per image. The performance will be evaluated based on a selection of videos and images from a dataset provided by Dr. Andrea Nanetti from the Engineering Historical Memory project. For this dataset SOLAR achieved a mean average precision of 83 %, a recall of 85 % and an extraction time of 0.73 seconds per image. To conclude, SOLAR is specialised in detecting and describing landmarks due to its pre-trained model, but for a more general case the backbone model should be trained differently which will increase the accuracy. Future work could also include speed improvement by looking at object detection methods.

Distributed feeding in photo-conducting antennas (PCAs) leads to simple optical designs, less prone to overheating, as well to terahertz (THz) antennas that can operate non-dispersively over wide bandwidths. However, the efficient analysis of pulsed PCAs was so far limited to architectures characterized by feeds small with respect to the THz wavelengths. In this thesis, an efficient and rigorous procedure for the time domain analysis of an infinitely long slot antenna printed on photo conductive material and excited by a distributed pulsed laser is presented. The procedure is electromagnetically rigorous, and relies on spectral representations of the fields in both the frequency and spatial domains.

Problem Definition This bachelor final project was an assignment given by the start up Momo Medical named: "Improving health care with technology". This project was to use their existing technology and ideas to create a system to prevent pressure ulcers. Pressure ulcer are the medical condition that happens when a patient is left too long in the same position in bed. In order to combat this the nurses turn the patient onto a new posture every 3 to 4 hours. To improve upon this Momo Medical decided to built a sensor pad that has to be placed under the mattress in order to track the patients bed posture and to alarm the nurses when a patient has been on a side too long. The project group was divided into three parts: the sensor group who would look at the sensor pad, the algorithm group who would use the data from the sensor pad to determine the bed posture and the test group that had to built a system that could verify the algorithm. This report will talk about the test group. Based upon the data that Momo Medical acquired it was also possible to acquire the heart rate and the respiratory rate from the sensor data. A way to acquire this data was also looked at. The design requirement that were set were 95% accuracy for bed posture and 90% for respiratory rate and heart rate. Design Description In order achieve these requirements a few different types of reference signals were looked at that could be used in order to detect the bed posture, respiratory rate and heart rate. In the end an accelerometer and an commercial grade ECG chest strap were chosen. The accelerometer could measure the patients orientation and thus his bed posture. When the accelerometer is attached to the chest it is also able to measure the chest compressing as a result of breathing. The ECG chest strap was chosen as this gave a good platform upon which the accelerometer and the micro controller could be attached. Evaluation A prototype was built upon our design and it was tested in different situations. In the end the accuracy for the bed posture detection was 99%, the accuracy of the respiratory rate was 91% and of the heart rate it was 95%. With these accuracies it meant that the design requirements were met. The disadvantage was that the system influences the sensor pad while the patient is wearing the prototype. Another disadvantage was that due to the low sampling speed it was not possible to attach the heart rate receiver to the testing group's prototype, but had to be attached to the sensor group's prototype. These two disadvantages could be improved in the future by making the prototype smaller and faster.

Millimeter- and submillimeter wave applications, such as point-to-point wireless communications in beyond-5G scenarios, long-range automotive radars and astronomy and astrophysics science cases from space require antennas with high-gain beams that are steerable. At lower (microwave) frequencies, fully sampled phased arrays with thousands of elements have been demonstrated for this purpose. However, above roughly 100 GHz, integrated-circuit technology faces major bottlenecks in terms of size, power efficiency, thermal management and technological immaturity. Consequently, only integrated phased arrays with very few elements have been reported in the literature above 100 GHz. To still achieve the gain and enable beam scanning, mechanically actuated reflectors are now typically employed. However, such solutions are bulky, power-hungry and do not allow rapid beam steering. To overcome these limitations, we propose, analyze, design, fabricate and demonstrate a new antenna architecture in this thesis: the scanning lens phased array. The scanning lens phased array is a compact, low-power and very sparse array of integrated lens antennas that we demonstrate with scanning capabilities up to 25 degrees around broadside. A hybrid electro-mechanical approach to beam steering is employed: the array factor is scanned electronically and the element patterns are steered mechanically. The grating lobes that arise in the array factor due to the array’s sparsity are suppressed by the high directivity of the lens elements. This results in a clean, highgain beam towards the desired scan angle...@en

This thesis serves to finalise the bachelor graduation project on the topic of self-supervised federated learning, specifically the on-chip implementation of the algorithms. The goal of the project is to implement a self-supervised learning setup in a decentralised approach using Field-Programmable Gate Arrays (FPGAs) for the processing of data. In this thesis, we endeavour to illustrate the possibility of employing FPGAs to move the fairly compute-intensive self-supervised learning algorithms to the edge. We have developed a number of modules that can accelerate key algorithmic blocks that underlie the major bottlenecks of the classical application of the algorithms and showcase prospective results, which are extensively discussed afterwards to pave a clear path towards truly autonomous and efficient edge-intelligence.