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Contributed
20 records found
Instrumented Skeleton Sled
Focussing on Data Processing and User Interface
This report details the design of an instrumentation system to be used on a skeleton sled. The system will measure several quantities on a skeleton track for the athlete to learn from. This data is stored during the run using several sensors on the sled and processed and visualis
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Smart Teddy: Elderly monitoring and support system using ambient intelligence
Human Interaction and Integration
In September 2018, the Smart Teddy project was founded by a group of researchers within the Hague University of Applied Sciences1 in the Netherlands. The Smart Teddy project is a multidisciplinary project aiming to create an interactive system, using a teddy bear as a focus point
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FPGAs in Big Data
On the transparent and efficient acceleration of big data frameworks
The increasing volume and latency requirements of big data impose challenges on the processing capacity of existing computing systems. FPGA accelerators can be leveraged to overcome these challenges, but questions remain as to how these accelerators are best deployed to accelerat
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N-shot Training Methodology
For Spiking Neural Networks(SNNs)
Traditional Artificial Neural Networks(ANNs)like CNNs have shown tremendous opportunities in various domains like autonomous cars, disease diagnosis, etc. Proven learning algorithms like backpropagation help ANNs in achieving higher accuracy. But there is a serious challenge with
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HPC Based Acceleration for Optimization of Predictive Models
Lithography Overlay Performance Modeling
This thesis project achieves designing and comparing two parallel implementations for exhaustive grid search along a large model space to find the optimum mapping model for overlay predictions used in ASML lithography machines. The search algorithm leads to an effectively intrac
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Automated Medical History Taking in Primary Care
A Reinforcement Learning Approach
Online searching for healthcare information has gradually become a widely used internet case. Suppose a patient suffers the symptom but is unsure of the action he needs to take, a self-diagnosis tool can help the patient identify the possible conditions and whether this patient n
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High throughput data interfacing
For real-time medical imaging applications
Current high-end medical X-ray intervention devices provide a tremendous amount of high-definition images per second. Combined with the additional inputs from the numerous auxiliary devices, processing and compositing the data in real-time quickly becomes an arduous engineering c
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Real-time Face and Landmark Localization for Eyeblink-Response Detection
A heterogenous CPU-GPU approach
Pavlovian eyeblink conditioning is a powerful experiment used in the field of neuroscience to measure multiple aspects of how we learn in our daily life. To track the movement of the eyelid during an experiment, researchers traditionally made use of potentiometers or electromyogr
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Full-Whisker Tracking System
A new algorithm for accurate whisker tracking in untrimmed head-fixed mice.
The movement of whiskers in head-fixed mice is of high interest for neurological research, as it allows scientists to learn more about learning processes during active touch. However, manual tracking of whiskers in thousands of frames is not feasible, and reliable tracking of ind
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The Smart Teddy Project
Design of a data acquisition system to monitor seniors with dementia and detect dangerous situations
The amount of people dealing with dementia is rising globally. The amount of caretakers is, however, not. Therefore, technological aids are needed to support people dealing with dementia and relieve the stress on their caretakers. Current solutions provide tracking of people with
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Smart Teddy: Design of the Power Operations and Distribution
Elderly Monitoring and Support System Using Ambient Intelligence
With the increasing demand in home-care service to provide early intervention at the homes of seniors suffering from early stage dementia, the Smart Teddy prototype offers a technological solution to disburden caregivers, to promote and track the health and conditions of the seni
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ρ-VEX ASIC
The Design of an ASIC for a Dynamically Reconfigurable VLIW Processor with 24-port Register File
The ρ-VEX is a runtime reconfigurable VLIW processor. It is able to exploit both ILP as well as TLP by running one program in multiple lanes, or several programs concurrently. To accurately quantify its performance compared to other processors, it is implemented as an IC.
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Tydi-lang: a language for typed streaming hardware
A manual for future Tydi-lang compiler developers
Transferring composite data structures with variable-length fields often requires designing non-trivial protocols that are not compatible between hardware designs. When each project designs its own data format and protocols the ability to collaborate between hardware developers i
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Multi-GPU Brain
A multi-node implementation for an extended Hodgkin-Huxley simulator
Current brain simulators do no scale linearly to realistic problem sizes (e.g. >100,000 neurons), which makes them impractical for researchers. The goal of the thesis is to explore the use of true multi-GPU acceleration on computationally challenging brain models and to assess
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Unitary Decomposition
Implemented in the OpenQL programming language for quantum computation
Unitary Decomposition is an algorithm for translating a unitary matrix into many small unitary matrices, which correspond to a circuit that can be executed on a quantum computer. It is implemented in the quantum programming framework of the QCA-group at TU Delft: OpenQL, a librar
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Quantum Algorithms
For pattern-matching in genomic sequences
Fast sequencing and analysis of (microorganism, plant or human) genomes will open up new vistas in fields like personalised medication, food yield and epigenetic research. Current state-of-the-art DNA pattern matching techniques use heuristic algorithms on computing clusters of C
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Insurance – A Machine Learning Perspective
Predicting Automobile Liability Insurance Pure Premiums Using Machine Learning Methods
This thesis explores the use of machine learning techniques in an effort to increase insurer competitiveness. It asks whether it is possible to accurately estimate the expected financial loss of a given insurance contract and how this information can be used to gain a competitiv
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Adding fault tolerance to OpenCL
Through redundant heterogeneous computing
The ever-increasing demand for computing has led to the need for specialized heterogeneous hardware, and the frameworks required to utilize them. Besides the traditional central processing units, more and more programs will make use of specialized hardware to accelerate computati
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A Toolchain for Streaming Dataflow Accelerator Designs for Big Data Analytics
Defining an IR for Composable Typed Streaming Dataflow Designs
Tydi is an open specification for streaming dataflow designs in digital circuits, allowing designers to express how composite and variable-length data structures are transferred over streams using clear, data-centric types. This provides a higher-level method for defining interfa
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Low latency Convolutional Neural Network (CNN) inference research is gaining more and more momentum for tasks such as speech and image classications. This is because CNNs have the ability to surpass human accuracy in classication of images. For improving the measurement setup of
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