Sökning: "system architectures"
Visar resultat 1 - 5 av 367 uppsatser innehållade orden system architectures.
1. A Prevention Technique for DDoS Attacks in SDN using Ryu Controller Application
Master-uppsats, Blekinge Tekniska Högskola/Institutionen för datavetenskapSammanfattning : Software Defined Networking (SDN) modernizes network control, offering streamlined management. However, its centralized structure makes it more vulnerable to distributed Denial of Service (DDoS) attacks, posing serious threats to network stability. LÄS MER
2. EMONAS : Evolutionary Multi-objective Neuron Architecture Search of Deep Neural Network
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Customized Deep Neural Network (DNN) accelerators have been increasingly popular in various applications, from autonomous driving and natural language processing to healthcare and finance, etc. However, deploying them directly on embedded system peripherals within real-time operating systems (RTOS) is not easy due to the paradox of the complexity of DNNs and the simplicity of embedded system devices. LÄS MER
3. Lateral Control of Heavy Vehicles
Master-uppsats, KTH/Väg- och spårfordon samt konceptuell fordonsdesignSammanfattning : The automotive industry has been involved in making vehicles autonomous to different levels in the past decade rapidly. Particularly in the commercial vehicle market, there is a significant necessity to make trucks have a certain level of automation to help reduce dependence on human efforts to drive. LÄS MER
4. Data-driven decisions in Sports
Magister-uppsats, Luleå tekniska universitet/Institutionen för system- och rymdteknikSammanfattning : In recent years, many sectors such as insurance, banking, retail, etc. have adopted Big Data architectures to boost their business activities. Such tools not only suppose a greater profit for thesecompanies but also allow them to gain a better understanding of their customers and their needs. LÄS MER
5. Adversarial Machine (Deep) Learning-basedRobustification in 5G Networks
Master-uppsats, Luleå tekniska universitet/Institutionen för system- och rymdteknikSammanfattning : A significant development in wireless communication and artificial intelligence has been made possible by the combination of 5G networks with deep learning methods. This paper explores the complex interactions between these areas, concentrating on the dangers that adversarial attacks represent in the context of 5G network slicing. LÄS MER