Sökning: "removal technique"
Visar resultat 16 - 20 av 85 uppsatser innehållade orden removal technique.
16. What's the Deal with Stegomalware? : The Techniques, Challenges, Defence and Landscape
Kandidat-uppsats, Linnéuniversitetet/Institutionen för datavetenskap och medieteknik (DM)Sammanfattning : Stegomalware is the art of hiding malicious software with steganography. Steganography is the technique of hiding data in a seemingly innocuous carrier. The occurrence of stegomalware is increasing, with attackers using ingenious techniques to avoid detection. LÄS MER
17. Complications after coronectomy of third molars
Master-uppsats, Umeå universitet/Institutionen för odontologiSammanfattning : ABSTRACT Background Removal of mandibular third molars can be associated with postoperative complications. Coronectomy with partial removal of the crown, is described as an alternative surgical method when risks for post-operative complications are substantial. LÄS MER
18. Removal of per- and polyfluoroalkyl substances(PFAS) from contaminated leachate usingaeration foam fractionation
Master-uppsats, Uppsala universitet/Institutionen för geovetenskaperSammanfattning : Leachate from landfills is contaminated in many ways and per- and polyfluoroalkyl substances (PFAS)-contamination is one of them. Recent studies have demonstrated the environmental and human concerns of PFAS. Therefore, the treatment of leachate is important. LÄS MER
19. A novel and feasible material recycling technique for end-of-life textiles as All-Cellulose Composites (ACCs)
Master-uppsats, Högskolan i Borås/Akademin för textil, teknik och ekonomiSammanfattning : Today’s consumption of textiles generates a large volume of textile waste. Therefore, it is needed to find solutions to re-use the textile waste rather recycling fibers into new fibers. Research using pre- and post-consumer textiles in composites is ongoing and an interesting direction. LÄS MER
20. Machine Unlearning and hyperparameters optimization in Gaussian Process regression
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : The establishment of the General Data Protection Regulation (GDPR) in Europe in 2018, including the "Right to be Forgotten" poses important questions about the necessity of efficient data deletion techniques for trained Machine Learning models to completely enforce this right, since retraining from scratch such models whenever a data point must be deleted seems impractical. We tackle such a problem for Gaussian Process Regression and define in this paper an efficient exact unlearning technique for Gaussian Process Regression which completely include the optimization of the hyperparameters of the kernel function. LÄS MER