Sökning: "Low power design"

Visar resultat 16 - 20 av 689 uppsatser innehållade orden Low power design.

1. 16. Towards Building Privacy-Preserving Language Models: Challenges and Insights in Adapting PrivGAN for Generation of Synthetic Clinical Text

   Master-uppsats, Stockholms universitet/Institutionen för data- och systemvetenskap

   Författare :Atena Nazem; [2023]
   Nyckelord :Generative Adversarial Networks; privacy-preserving language models; clinical text data; reinforcement learning; synthetic data;

   Sammanfattning : The growing development of artificial intelligence (AI), particularly neural networks, is transforming applications of AI in healthcare, yet it raises significant privacy concerns due to potential data leakage. As neural networks memorise training data, they may inadvertently expose sensitive clinical data to privacy breaches, which can engender serious repercussions like identity theft, fraud, and harmful medical errors. LÄS MER

3. 17. Evaluation of hardware and firmware for a Data Readout system of the PANDA Electro-Magnetic Calorimeter

   Master-uppsats, Uppsala universitet/Institutionen för informationsteknologi

   Författare :Ehsan Noorzaei; [2023]
   Nyckelord :;

   Sammanfattning : PANDA is the next generation hadron physics detector under construction at the Facility for Antiproton and Ion Research (FAIR) in Darmstadt, Germany to accurately detect and parameterize events with kinetic energies from 1MeV to 8GeV. PANDA is a 4π detector and due to its unique shape, all the readout electronics from ADC modules, power supplies, and a controller unit is housed in liquid-cooled crates mounted inside the detector. LÄS MER

4. 18. Deep Neural Networks as SurrogateModels for Fuel Performance Codes

   Kandidat-uppsats, Uppsala universitet/Tillämpad kärnfysik

   Författare :Wenhan Zhou; [2023]
   Nyckelord :Transuranus; AI; Nuclear Fuel Rods;

   Sammanfattning : The core component of a nuclear power plant is the reactor and the fuel rods that supply it with fission fuel. Efficient and safe energy extraction is thus highly dependent on the reactor design and the conditions of the fuel rods. To anticipate high-quality operation and potential risks in advance, one must perform simulations on the fuel rods. LÄS MER

5. 19. Performance Evaluation of Different RPL Formation Strategies

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Ziyi Chang; [2023]
   Nyckelord :IPv6 Routing Protocol for Low-Power and Lossy Networks RPL ; Multiple Sinks; Packet Delivery Ratio PDR ; Internet of Things; IPv6 Routing Protocol for Low-Power and Lossy Networks RPL ; Multi-Sink; Packet Delivery Ratio PDR ; Sakernas Internet;

   Sammanfattning : The size of the IoT network is expanding due to advancements in the IoT field, leading to increased interest in the multi-sink mechanism. The IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL) is a representative IoT protocol that focuses on the Low-Power and Lossy Networks. LÄS MER

7. 20. Low-power Implementation of Neural Network Extension for RISC-V CPU

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Dario Lo Presti Costantino; [2023]
   Nyckelord :Artificial intelligence; Deep learning; Neural networks; Edge computing; Convolutional neural networks; Low-power electronics; RISC-V; AI accelerators; Parallel processing; Artificiell intelligens; Deep learning; Neurala nätverk; Edge computing; konvolutionella neurala nätverk; Lågeffektelektronik; RISC-V; AI-acceleratorer; Parallell bearbetning;

   Sammanfattning : Deep Learning and Neural Networks have been studied and developed for many years as of today, but there is still a great need of research on this field, because the industry needs are rapidly changing. The new challenge in this field is called edge inference and it is the deployment of Deep Learning on small, simple and cheap devices, such as low-power microcontrollers. LÄS MER