Search results for "python"
showing 10 items of 160 documents
Cilvēka kustību novērošana, izmantojot inerciālos sensorus
2020
Cilvēka kustību novērošana, izmantojot inerciālos sensorus, mūsdienas ir ļoti populāra pētniecības metode, ko pielieto medicīnā, rehabilitācijā, sportā un citās nozarēs. Darbā tika izpētītas tehnoloģiskās iespējas, lai veiktu cilvēka kustību novērošanu, kā arī esošie pielietojumi cilvēka kustību novērošanai hokejā. Darba mērķis ir veikt profesionāla un entuziasta līmeņa hokejistu hokeja metienu kustību novērošanu, lai noteiktu, kura entuziasta hokeja metiens procentuāli visvairāk atbilst profesionāla hokeja metiena sasniegtajam lineārajām paātrinājumam. Novēroto datu apstrādei, tika izmantota “Python” programmēšanas valoda, ar kuru tika …
Stimulētās mašīnmācīšanās problēmu veidi un risināšanas metodes un rīki
2018
Stimulētā mašīnmācīšanās ir viena no mašīnmācīšanās apakšnozarēm, kas to padara par vienu no mākslīgā intelekta apakšnozarēm. Ar stimulētās mašīnmācīšanas palīdzību un tās paņēmieniem var modelēt fizikālajā pasaulē sastopamas problēmas un veidus, kā tās risināt ar datora palīdzību. Šajā darbā tiks apskatītas vienkāršākās problēmas, kuras parasti tiek risinātas, apgūstot stimulētās mašīnācīšanās pamatprincipus un metodes to risināšanai, un kuras tiek iekļautas mašīnmācīšanās apakšnozare, kā arī pieejamie un nepieciešamie rīki, lai būtu iespējams šīs problēmas modelēt datoram saprotamā veidā un ar to palīdzību būtu iespējams atrisināt tās problēmas, kas ir sastopamas mūsu fiziskajā pasaulē.
WCxf: An exchange format for Wilson coefficients beyond the Standard Model
2018
We define a data exchange format for numerical values of Wilson coefficients of local operators parameterising low-energy effects of physics beyond the Standard Model. The format facilitates interfacing model-specific Wilson coefficient calculators, renormalisation group (RG) runners, and observable calculators. It is designed to be unambiguous (defining a non-redundant set of operators with fixed normalisation in each basis), extensible (allowing the addition of new EFTs or bases by the user), and robust (being based on industry standard file formats with parsers implemented in many programming languages). We have implemented the format for the Standard Model EFT (SMEFT) and for the weak e…
Klientu rēķinu maksāšanas paradumu prognozēšana izmantojot mašīnmācīšanos
2018
Kvalifikācijas darbā ir izstrādāta sistēma, kas sastāv no mašīnmācīšanās modeļa izstrādes un tīmekļa atskaišu vietnes. Mašīnmācīšanās modelis ir paredzēts debitoru rēķinu apmaksas laika prognozēšanai namu pārvaldes uzņēmumam, balstoties uz vēsturiskiem klientu un rēķinu maksājumu datiem. Tīmekļa vietnē tiek atspoguļoti klientu dati, statistika par rēķiniem, to maksājumiem un modeļu trenēšanas rezultātiem. Izmantojot regresiju, klasifikāciju un kombinēto metodi, tika apmācīti un salīdzināti prognozēšanas modeļi. Ievada dati ir ģenerēti, izmantojot izpētītās klienta datubāzes struktūras pamattabulas. Prognozēšanas modeļi ir realizēti Python valodā. Sistēmas grafiskā saskarne ir nodrošināta tī…
Sviluppo di un software per l’analisi di immagini di Diffusion Kurtosis Imaging
2013
L’analisi mediante RM del tensore di diffusione (Diffusion Tensor Imaging, DTI) consente di valutare anche in vivo e con modalità non invasive il processo di diffusione delle molecole d’acqua nei tessuti biologici. La peculiare organizzazione di alcuni tessuti biologici (es: muscoli, sostanza bianca del sistema nervoso centrale e tessuti ad alta cellularità) influenza tale fenomeno rendendolo anisotropo e quindi ben valutabile con tali tecniche di studio. Nonostante i grandi vantaggi di tale tecnica, il DTI è basato su un modello molto semplificato che assume che lo spostamento per diffusione segua un profilo gaussiano il che è molto raro in un ambiente variegato come i tessuti biologic…
Design of Multiresolution Operators Using Statistical Learning Tools: Application to Compression of Signals
2012
Using multiresolution based on Harten's framework [J. Appl. Numer. Math., 12 (1993), pp. 153---192.] we introduce an alternative to construct a prediction operator using Learning statistical theory. This integrates two ideas: generalized wavelets and learning methods, and opens several possibilities in the compressed signal context. We obtain theoretical results which prove that this type of schemes (LMR schemes) are equal to or better than the classical schemes. Finally, we compare traditional methods with the algorithm that we present in this paper.
Weak pseudo-bosons
2020
We show how the notion of {\em pseudo-bosons}, originally introduced as operators acting on some Hilbert space, can be extended to a distributional settings. In doing so, we are able to construct a rather general framework to deal with generalized eigenvectors of the multiplication and of the derivation operators. Connections with the quantum damped harmonic oscillator are also briefly considered.
Canonical Retina-to-Cortex Vision Model Ready for Automatic Differentiation
2020
Canonical vision models of the retina-to-V1 cortex pathway consist of cascades of several Linear+Nonlinear layers. In this setting, parameter tuning is the key to obtain a sensible behavior when putting all these multiple layers to work together. Conventional tuning of these neural models very much depends on the explicit computation of the derivatives of the response with regard to the parameters. And, in general, this is not an easy task. Automatic differentiation is a tool developed by the deep learning community to solve similar problems without the need of explicit computation of the analytic derivatives. Therefore, implementations of canonical visual neuroscience models that are ready…
Heuristics for a Real-World Mail Delivery Problem
2011
We are solving a mail delivery problem by combining exact and heuristic methods. The problem is a tactical routing problem as routes for all postpersons have to be planned in advance for a period of several months. As for many other routing problems, the task is to construct a set of feasible routes serving each customer exactly once at minimum cost. Four different modes (car, moped, bicycle, and walking) are available, but not all customers are accessible by all modes. Thus, the problem is characterized by three interdependent decisions: the clustering of customers into districts, the choice of a mode for each district, and the routing of the postperson through its district. We present a t…
Interactive Gradually Generating Relevance Query Refinement Under the Human-Mediated Scenario in Multilingual Settings
2016
As opposed to query modelling, relevance generating interactive query refinement (QR) is a technique aimed at exploiting syntax variations of gradually extended, being removed or replaced with some other keywords query, which depending on the factors like e.g. the information resource, the database structure, or the keyword alignment, facilitates significantly the searching process. Therefore our motivation is to explore the dynamism of the precision trend depended upon the factors analyzed. For a couple of language pairs which constitute multilingual settings, we develop a user-centred framework that imposes distributed search optimization. Our data set contains variety of query types subm…