Search results for "ritmi"
showing 10 items of 258 documents
Precīzie kvantu algoritmi, izmantojot 1-kvantu-vaicājuma izsaukumus
2018
Darbā ir analizēti zināmi unikāli precīzie kvantu algoritmi, kuru īpašības ir atšķirīgas no citiem literatūrā atrodamiem algoritmiem, un uzsākts pētīt iespējas vispārināt šajos algoritmos esošos paņēmienus. Darbā ir noformulēts jauns skaitļošanas modelis, kas ir saistīts ar precīzo kvantu vaicājumu modeli. Veikti skaitliski aprēķini, lai palīdzētu saprast jaunā modeļa iespējas un ierobežojumus. Izteiktas hipotēzes un virzieni, kādos turpināt analīzi un pētījumu.
Impact of chaotic dynamics on the performance of metaheuristic optimization algorithms : An experimental analysis
2022
Random mechanisms including mutations are an internal part of evolutionary algorithms, which are based on the fundamental ideas of Darwin's theory of evolution as well as Mendel's theory of genetic heritage. In this paper, we debate whether pseudo-random processes are needed for evolutionary algorithms or whether deterministic chaos, which is not a random process, can be suitably used instead. Specifically, we compare the performance of 10 evolutionary algorithms driven by chaotic dynamics and pseudo-random number generators using chaotic processes as a comparative study. In this study, the logistic equation is employed for generating periodical sequences of different lengths, which are use…
On optimal deployment of low power nodes for high frequency next generation wireless systems
2018
Recent development of wireless communication systems and standards is characterized by constant increase of allocated spectrum resources. Since lower frequency ranges cannot provide sufficient amount of bandwidth, new bands are allocated at higher frequencies, for which operators resort to deploy more base stations to ensure the same coverage and to utilize more efficiently higher frequencies spectrum. Striving for deployment flexibility, mobile operators can consider deploying low power nodes that could be either small cells connected via the wired backhaul or relays that utilize the same spectrum and the wireless access technology. However, even though low power nodes provide a greater fl…
Quantitative Analysis of Dynamic Association in Live Biological Fluorescent Samples
2014
Determining vesicle localization and association in live microscopy may be challenging due to non-simultaneous imaging of rapidly moving objects with two excitation channels. Besides errors due to movement of objects, imaging may also introduce shifting between the image channels, and traditional colocalization methods cannot handle such situations. Our approach to quantifying the association between tagged proteins is to use an object-based method where the exact match of object locations is not assumed. Point-pattern matching provides a measure of correspondence between two point-sets under various changes between the sets. Thus, it can be used for robust quantitative analysis of vesicle …
How does serendipity affect diversity in recommender systems? A serendipity-oriented greedy algorithm
2018
Most recommender systems suggest items that are popular among all users and similar to items a user usually consumes. As a result, the user receives recommendations that she/he is already familiar with or would find anyway, leading to low satisfaction. To overcome this problem, a recommender system should suggest novel, relevant and unexpected i.e., serendipitous items. In this paper, we propose a serendipity-oriented, reranking algorithm called a serendipity-oriented greedy (SOG) algorithm, which improves serendipity of recommendations through feature diversification and helps overcome the overspecialization problem. To evaluate our algorithm, we employed the only publicly available datase…
Listwise Recommendation Approach with Non-negative Matrix Factorization
2018
Matrix factorization (MF) is one of the most effective categories of recommendation algorithms, which makes predictions based on the user-item rating matrix. Nowadays many studies reveal that the ultimate goal of recommendations is to predict correct rankings of these unrated items. However, most of the pioneering efforts on ranking-oriented MF predict users’ item ranking based on the original rating matrix, which fails to explicitly present users’ preference ranking on items and thus might result in some accuracy loss. In this paper, we formulate a novel listwise user-ranking probability prediction problem for recommendations, that aims to utilize a user-ranking probability matrix to predi…
On the Extension of the DIRECT Algorithm to Multiple Objectives
2020
AbstractDeterministic global optimization algorithms like Piyavskii–Shubert, direct, ego and many more, have a recognized standing, for problems with many local optima. Although many single objective optimization algorithms have been extended to multiple objectives, completely deterministic algorithms for nonlinear problems with guarantees of convergence to global Pareto optimality are still missing. For instance, deterministic algorithms usually make use of some form of scalarization, which may lead to incomplete representations of the Pareto optimal set. Thus, all global Pareto optima may not be obtained, especially in nonconvex cases. On the other hand, algorithms attempting to produce r…
LR-NIMBUS : an interactive algorithm for uncertain multiobjective optimization with lightly robust efficient solutions
2022
In this paper, we develop an interactive algorithm to support a decision maker to find a most preferred lightly robust efficient solution when solving uncertain multiobjective optimization problems. It extends the interactive NIMBUS method. The main idea underlying the designed algorithm, called LR-NIMBUS, is to ask the decision maker for a most acceptable (typical) scenario, find an efficient solution for this scenario satisfying the decision maker, and then apply the derived efficient solution to generate a lightly robust efficient solution. The preferences of the decision maker are incorporated through classifying the objective functions. A lightly robust efficient solution is generated …
DGA detection using machine learning methods
2016
Yksi yleisimmistä kyberhyökkäysistä on käyttää ryhmä yksityisiä tietokoneita (private computers), joita käytetään esimerkiksi salaisien tietojen levittämiseen. Näitä koneryhmiä kutsutaan botnet. Botnetit pysyvät havaitsemattomana käyttämällä Domain Name Generation (DGA) menetelmää, joka luo ajoittain ja ratkaisee suurina lukumäärinä erillaisia pseudosatunnaisia verkkotunnuksia, kunnes jokin näistä pseudosatunnaisista verkkotunnuksista DNS palvelin hyväksyy. Tämän tutkielman tarkoitus on kehitellä ei- ohjattuja koneoppimismenetelmiä ja vertailla näiden tarkkuutta ohjattuihin koneoppimismenetelmiin DGA hyökkäyksien havaitsemiseen. Lisäksi, tutkielmassa esitellään Random One Class Support Vect…
Attēlu apstrādes rīks datorredzes algoritmiem
2016
Kvalifikācijas darba produkts "Attēlu apstrādes rīks datorredzes algoritmiem" ir lietojumprogramma, kas paredzēta ātrai un vieglai attēlu apstrādei. Šīs programmas mērķis ir padarīt ērtāku un ātrāku attēlu kopu sagatavošanu, kas paredzētas dažādu datorredzes algoritmu izmantošanai un testēšanai. Programma piedāvā lietotājam izgriezt attēla reģionus, atlasīt vēlamos saglabāšanas kritērijus un eksportēt iegūtos datus kā jaunus attēlus. Tā rezultātā tiek iegūts ievadattēlu aprakstošs fails, kas norāda objektu atrašanās vietu uz attēla un tam piederošās iezīmes. Iegūto informāciju kopā ar ievadattēliem un izvadattēliem iespējams viegli nodot citiem lietotajiem vai citām programmām. Šādas attēlu…