Sökning: "CSP"

Visar resultat 6 - 10 av 126 uppsatser innehållade ordet CSP.

1. 6. Modererande påverkan av finansiell prestation på förhållandet mellan CSR och styrelsesammansättningen : En kvantitativ studie på 433 börsnoterade nordiska bolag

   Kandidat-uppsats, Högskolan i Gävle/Avdelningen för ekonomi

   Författare :Lorin Batti; Delinna Tewolde; [2023]
   Nyckelord :Corporate Financial Performance CFP ; Corporate Social Responsibility CSR ; Environmental; Social and Governance ESG ; Board characteristics; Nordic firms; Board Governance; Corporate Social Performance CSP ; Finansiell prestation CFP ; Corporate Social Responsibility CSR ; Environmental; Social Governance ESG ; Styrelseegenskaper; nordiska bolag; Bolagsstyrning;

   Sammanfattning : Syfte: Ett växande intresse för CSR och dess betydelse lyfter fram rollen av bolagsstyrning. Bland annat ifrågasattes styrelsens roll i att utveckla strategier och uppfylla krav från diverse intressentgrupper. LÄS MER

3. 7. Confidential Federated Learning with Homomorphic Encryption

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

   Författare :Zekun Wang; [2023]
   Nyckelord :Cloud Technology; Confidential Computing; Federated Learning; Homomorphic Encryption; Trusted Execution Environment; Molnteknik; Konfidentiell databehandling; Federerad inlärning; Homomorfisk kryptering; Betrodd körningsmiljö;

   Sammanfattning : Federated Learning (FL), one variant of Machine Learning (ML) technology, has emerged as a prevalent method for multiple parties to collaboratively train ML models in a distributed manner with the help of a central server normally supplied by a Cloud Service Provider (CSP). Nevertheless, many existing vulnerabilities pose a threat to the advantages of FL and cause potential risks to data security and privacy, such as data leakage, misuse of the central server, or the threat of eavesdroppers illicitly seeking sensitive information. LÄS MER

4. 8. A Bayesian Bee Colony Algorithm for Hyperparameter Tuning of Stochastic SNNs : A design, development, and proposal of a stochastic spiking neural network and associated tuner

   Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Signaler och system

   Författare :Oskar Falkeström; [2023]
   Nyckelord :edge computing; edge user allocation; constraint satisfaction problem; bin packing problem; spiking neural networks; SNN; stochastic spiking neural networks; neuromorphic computing; hyperparameter tuning; swarm intellience; artificial bee colony algorithm; tree-structured Parzen estimator; stochastic optimization; Bayesian optimization.;

   Sammanfattning : With the world experiencing a rapid increase in the number of cloud devices, continuing to ensure high-quality connections requires a reimagining of cloud. One proponent, edge computing, consists of many distributed and close-to-consumer edge servers that are hired by the service providers. LÄS MER

5. 9. Introducing GA-SSNN: A Method for Optimizing Stochastic Spiking Neural Networks : Scaling the Edge User Allocation Constraint Satisfaction Problem with Enhanced Energy and Time Efficiency

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

   Författare :Nathan Allard; [2023]
   Nyckelord :;

   Sammanfattning : As progress within Von Neumann-based computer architecture is being limited by the physical limits of transistor size, neuromorphic comuting has emerged as a promising area of research. Neuromorphic hardware tends to be substantially more power efficient by imitating the aspects of computations in networks of neurons in the brain. LÄS MER

7. 10. The Applicability and Scalability of Graph Neural Networks on Combinatorial Optimization

   Master-uppsats, KTH/Matematik (Avd.)

   Författare :Peder Hårderup; [2023]
   Nyckelord :applied mathematics; combinatorial optimization; machine learning; graph neural networks; scalability; tillämpad matematik; kombinatorisk optimering; maskininlärning; grafiska neurala nätverk; skalbarhet;

   Sammanfattning : This master's thesis investigates the application of Graph Neural Networks (GNNs) to address scalability challenges in combinatorial optimization, with a primary focus on the minimum Total Dominating set Problem (TDP) and additionally the related Carrier Scheduling Problem (CSP) in networks of Internet of Things. The research identifies the NP-hard nature of these problems as a fundamental challenge and addresses how to improve predictions on input graphs of sizes much larger than seen during training phase. LÄS MER