5 research outputs found
Disseny, control i implementaci贸 d'un inversor trif脿sic per un vehicle el猫ctric
Premi al millor Projecte de Fi de Carrera presentat durant l'any 2014 en l'脿mbit d'Automoci贸 que atorga la C脌TEDRA SEAT-UPCEl projecte consisteix en una breu descripci贸 dels diferents processos que es duen a terme desde la concepci贸 d'un convertidor, orientat al control d'un motor s铆ncron d'imants permanents, fins a la seva aplicaci贸 definitiva. Concretament, el convertidor desenvolupat t茅 com a objectiu final la seva integraci贸 en un vehicle el猫ctric de competici贸.
Es fa una petita introducci贸 a la Formula Student, competici贸 en la que el vehicle el猫ctric CAT06e va competir la temporada 2012-2013 i el CAT07e competir脿 la temporada d'enguany.
Ambd贸s traccionats per dos convertidors com el desenvolupat en aquest projecte. Es
tracten diversos aspectes te貌rics fonamentals pel correcte desenvolupament del convertidor.
Al tractar-se d'un inversor trif脿sic que alimenta un motor s铆ncron d'imants permanents, es descriuen les equacions usades en el disseny i es presenten les transformacions matricials necess脿ries en el control. Una vegada establertes les equacions, s'exposa el procediment seguit
per mesurar determinats par脿metres que posteriorment s'usaran en el control.
Es presenten els diversos c脿lculs duts a terme per el dimensionament de les principals parts del convertidor, com el bus de cont铆nua o els semiconductors. Tamb茅 es fa refer猫ncia al disseny mec脿nic del conjunt aix铆 com la refrigeraci贸 de l'electr貌nica de pot猫ncia. Aquests dissenys es duen a terme en base les condicions de contorn imposades per l'aplicaci贸 final, 茅s a dir, del vehicle de competici贸.
Seguidament es descriuen les parts del codi implementat en el convertidor m茅s importants, com el c脿lcul de posici贸 i velocitat o el control de parell. Finalment es presenten els resultats experimentals extrets de les proves en la bancada.Award-winnin
HiMMe, A Next-Generation Sequencing Quality Assessment and Correction Tool Based on Hidden Markov Models
Both deoxyribonucleic acid (DNA) and ribonucleic acid (RNA) play a crucial role in the existence and proper development of all living organisms. In addition, it is through these molecules that the genetic information is passed from parent to offspring. It is no surprise that, over the last decades, a lot of efforts have been put into developing technology that help us better understand their underlying mechanisms.
Similarly to how computers work using only ones and zeros, DNA and RNA only need four different characters to encrypt all the genetic information. Thanks to the sequencing technology development over the past decades, it is possible nowadays to sequence these molecules in a relatively fast and inexpensive way. However, as in any measurement, there is noise involved and this needs to be addressed if one is to reach conclusions based on these kind of data.
The hidden Markov model (HMM) is a perfect fit for this case. Through a Markov chain, the model can capture genetic patterns, while, by introducing the emission probabilities, the noise involved in the process can be taken into account. In addition, previous knowledge can be used by training the model to fit, for instance, a given organism or sequencing technology.
In this thesis, the HMM theory is applied for two purposes, (1) to assess the reliability of sequencing data, and (2) to correct potential errors in the sequences observed. The results show that the HMM model is capable of identifying genetic patterns in the sequence and to repair potential errors, thus improving the reliability of the data before any downstream analysis is performed. For these purposes, HiMMe has been developed and is publicly available on https://github.com/jordiabante/HiMMe
STATISTICAL SIGNAL PROCESSING METHODS FOR EPIGENETIC LANDSCAPE ANALYSIS
Since the DNA structure was discovered in 1953, a great deal of effort has been put into studying this molecule in detail. We now know DNA comprises an organism鈥檚 genetic makeup and constitutes a blueprint for life. The study of DNA has dramatically increased our knowledge about cell function and evolution and has led to remarkable discoveries in biology and medicine.
Just as DNA is replicated during cell division, several chemical marks are also passed onto progeny during this process. Epigenetics studies these marks and represents a fascinating research area given their crucial role. Among all known epigenetic marks, 5mc DNA methylation is probably one of the most important ones given its well-established association with various biological processes, such as development and aging, and disease, such as cancer. The work in this dissertation focuses primarily on this epigenetic mark, although it has the potential to be applied to other heritable marks.
In the 1940s, Waddington introduced the term epigenetic landscape to conceptually describe cell pluripotency and differentiation. This concept lived in the abstract plane until Jenkinson et al. 2017 & 2018 estimated actual epigenetic landscapes from WGBS data, and the work led to startling results with biological implications in development and disease. Here, we introduce an array of novel computational methods that draw from that work. First, we present CPEL, a method that uses a variant of the original landscape proposed by Jenkinson et al., which, together with a new hypothesis testing framework, allows for the detection of DNA methylation imbalances between homologous chromosomes. Then, we present CpelTdm, a method that builds upon CPEL to perform differential methylation analysis between groups of samples using targeted bisulfite sequencing data. Finally, we extend the original probabilistic model proposed by Jenkinson et al. to estimate methylation landscapes and perform differential analysis from nanopore data.
Overall, this work addresses immediate needs in the study of DNA methylation. The methods presented here can lead to a better characterization of this critical epigenetic mark and enable biological discoveries with implications for diagnosing and treating complex human diseases
Disseny, control i implementaci贸 d'un inversor trif脿sic per un vehicle el猫ctric
Premi al millor Projecte de Fi de Carrera presentat durant l'any 2014 en l'脿mbit d'Automoci贸 que atorga la C脌TEDRA SEAT-UPCEl projecte consisteix en una breu descripci贸 dels diferents processos que es duen a terme desde la concepci贸 d'un convertidor, orientat al control d'un motor s铆ncron d'imants permanents, fins a la seva aplicaci贸 definitiva. Concretament, el convertidor desenvolupat t茅 com a objectiu final la seva integraci贸 en un vehicle el猫ctric de competici贸.
Es fa una petita introducci贸 a la Formula Student, competici贸 en la que el vehicle el猫ctric CAT06e va competir la temporada 2012-2013 i el CAT07e competir脿 la temporada d'enguany.
Ambd贸s traccionats per dos convertidors com el desenvolupat en aquest projecte. Es
tracten diversos aspectes te貌rics fonamentals pel correcte desenvolupament del convertidor.
Al tractar-se d'un inversor trif脿sic que alimenta un motor s铆ncron d'imants permanents, es descriuen les equacions usades en el disseny i es presenten les transformacions matricials necess脿ries en el control. Una vegada establertes les equacions, s'exposa el procediment seguit
per mesurar determinats par脿metres que posteriorment s'usaran en el control.
Es presenten els diversos c脿lculs duts a terme per el dimensionament de les principals parts del convertidor, com el bus de cont铆nua o els semiconductors. Tamb茅 es fa refer猫ncia al disseny mec脿nic del conjunt aix铆 com la refrigeraci贸 de l'electr貌nica de pot猫ncia. Aquests dissenys es duen a terme en base les condicions de contorn imposades per l'aplicaci贸 final, 茅s a dir, del vehicle de competici贸.
Seguidament es descriuen les parts del codi implementat en el convertidor m茅s importants, com el c脿lcul de posici贸 i velocitat o el control de parell. Finalment es presenten els resultats experimentals extrets de les proves en la bancada.Award-winnin
Disseny, control i implementaci贸 d'un inversor trif脿sic per un vehicle el猫ctric
Premi al millor Projecte de Fi de Carrera presentat durant l'any 2014 en l'脿mbit d'Automoci贸 que atorga la C脌TEDRA SEAT-UPCEl projecte consisteix en una breu descripci贸 dels diferents processos que es duen a terme desde la concepci贸 d'un convertidor, orientat al control d'un motor s铆ncron d'imants permanents, fins a la seva aplicaci贸 definitiva. Concretament, el convertidor desenvolupat t茅 com a objectiu final la seva integraci贸 en un vehicle el猫ctric de competici贸.
Es fa una petita introducci贸 a la Formula Student, competici贸 en la que el vehicle el猫ctric CAT06e va competir la temporada 2012-2013 i el CAT07e competir脿 la temporada d'enguany.
Ambd贸s traccionats per dos convertidors com el desenvolupat en aquest projecte. Es
tracten diversos aspectes te貌rics fonamentals pel correcte desenvolupament del convertidor.
Al tractar-se d'un inversor trif脿sic que alimenta un motor s铆ncron d'imants permanents, es descriuen les equacions usades en el disseny i es presenten les transformacions matricials necess脿ries en el control. Una vegada establertes les equacions, s'exposa el procediment seguit
per mesurar determinats par脿metres que posteriorment s'usaran en el control.
Es presenten els diversos c脿lculs duts a terme per el dimensionament de les principals parts del convertidor, com el bus de cont铆nua o els semiconductors. Tamb茅 es fa refer猫ncia al disseny mec脿nic del conjunt aix铆 com la refrigeraci贸 de l'electr貌nica de pot猫ncia. Aquests dissenys es duen a terme en base les condicions de contorn imposades per l'aplicaci贸 final, 茅s a dir, del vehicle de competici贸.
Seguidament es descriuen les parts del codi implementat en el convertidor m茅s importants, com el c脿lcul de posici贸 i velocitat o el control de parell. Finalment es presenten els resultats experimentals extrets de les proves en la bancada.Award-winnin