Holographic dual of the Standard Model on the throat

We apply recent techniques to construct geometries, based on local Calabi-Yau manifolds, leading to warped throats with 3-form fluxes in string theory, with interesting structure at their bottom. We provide their holographic dual description in terms of RG flows for gauge theories with almost conformal duality cascades and infrared confinement. We describe a model of a throat with D-branes at its bottom, realizing a 3-family Standard Model like chiral sector. We provide the explicit holographic dual gauge theory RG flow, and describe the appearance of the SM degrees of freedom after confinement. As a second application, we describe throats within throats, namely warped throats with discontinuous warp factor in different regions of the radial coordinate, and discuss possible model building applications.Comment: 46 pages, 21 figures, reference adde

Pseudolocalization Realization for Skype Software

Käesoleva bakalaureusetöö eesmärgiks on luua pseudolokaliseerimise rakendus Skype’i jaoks. Lokaliseerimine on tarkvara kultuurile kohandamine, mis hõlmab endas nii tõlkimist kui ka numbriformaatide, piltide jm kohandamist kohalikule kultuurile. Peamised lokaliseerimise probleemid on seotud teksti pikenemisega tõlgetes (eriti kui sisendkeeleks on inglise keel), koodi sisse kirjutatud tekstiga, mis jääb seetõttu tõlkimata, mitmest eri sõnest kokkupandud tekstiga, vale märgikodeerimisega (ingl k. encoding), erinevate numbriformaatide ning sobimatute piltidega. Üks viis lokaliseerimise käigus tekkivad probleeme ennetada on pseudolokaliseerimine. Pseudolokaliseerimine kujutab endast lokaliseerimisprotsessi imiteerimist enne teksti päriselt tõlkesse saatmist. See tähendab tekstifaili tekstiväljade muutmist teatud sobival viisil ja seejärel faili vaatamist kasutajaliideses. Erinevad pseudolokaliseerimise meetodid aitavad ennetada kodeeritud tõlkimata teksti, teksti pikenemise, märgikodeerimise- ja mitmest eri sõnest kokkupandud tekstiga seotud probleeme. Olemasolevad pseudolokaliseerimise rakendused, mida on ka antud töös hinnatud, ei ole Skype’i jaoks sobilikud. Seega arendati eraldiseisev pseudolokaliseerimisrakendus, mis realiseerib sulumeetodi (sõne asendatakse “X sõne X”-ga), võtmemeetodi (sõne asendatakse tema keelefaili identifikaatoriga) ja masintõlkemeetodi Microsoft Translator’i abil (sõne asendatakse masintõlkega). Sulumeetod aitab leida kokku kirjutatud sõnesid ning koodi kirjutatud teksti, masintõlke meetod aitab leida potentsiaalseid probleeme teksti pikenemisega ning märgikodeeringuga seotud probleeme. Võtmemeetod aitab keelefailist kiiresti leida sõne, mis kasutajaliideses probleeme põhjustab. Loodud rakendus on juba Skype’i lokaliseerimismeeskonna poolt kasutuses ning probleemide ennetamisega aitab see kokku hoida probleemide hilisemaks lahendamiseks kuluvaid ressursse. Muu hulgas programmeeriti töö käigus ka ühendus Microsoft Translator’iga programmeerimiskeeles Java, mis varem puudus, ning mida on võimalik ka teistel kasutada.The aim of the current work is to develop a pseudolocalization application for solving possible issues in user interfaces for Skype clients. Localization is the process of adapting a product to a target market. Localization involves translation as well customization related to different number formats, graphical imagery etc. Localization is carried out at the end of the development process in order to avoid the need to re-localize due to changes in the design or text. Therefore all mistakes found during the localization process come with a high price. Common problems are text expansion in translated texts compared to the original (especially if the source text is in English), hard-coded text, character encoding problems, format issues, unsuitable imagery etc. One of the methods to foresee localization problems is pseudolocalization. Pseudolocalization is a practice of simulating the localization process before the actual translation work by replacing the translatable text with modified text [6]. Different pseudolocalization methods address various localization problems including text expansion, hard coded strings, concatenated strings, encoding problems, etc This work gives a short overview of common localization problems as well as a number of well-known pseudolocalization methods that can be used to prevent those problems. The existing solutions for pseudolocalization were analysed as well. This information can be useful when choosing which solution to use for pseudolocalization or deciding how pseudolocalization can be of help in the development process. The application developed in the practical part of this thesis implements three pseudolocalization methods – machine translation, prefix/suffix and string identifier methods and works with XML file types used internally in Skype. Using these methods helps to prevent localization issues related to text expansion, encoding, hard-coded text and string concatenation as well as helps finding the problematic strings from the language file quicker when using string identifier method. The application is already in use by the Skype localization team. During the development of the pseudolocalization application for Skype, the connection to the Microsoft translator was developed in Java that did not exist before. This can also be used by other users to connect to Microsoft Translator with Java

Universal Compressed Text Indexing

The rise of repetitive datasets has lately generated a lot of interest in compressed self-indexes based on dictionary compression, a rich and heterogeneous family that exploits text repetitions in different ways. For each such compression scheme, several different indexing solutions have been proposed in the last two decades. To date, the fastest indexes for repetitive texts are based on the run-length compressed Burrows-Wheeler transform and on the Compact Directed Acyclic Word Graph. The most space-efficient indexes, on the other hand, are based on the Lempel-Ziv parsing and on grammar compression. Indexes for more universal schemes such as collage systems and macro schemes have not yet been proposed. Very recently, Kempa and Prezza [STOC 2018] showed that all dictionary compressors can be interpreted as approximation algorithms for the smallest string attractor, that is, a set of text positions capturing all distinct substrings. Starting from this observation, in this paper we develop the first universal compressed self-index, that is, the first indexing data structure based on string attractors, which can therefore be built on top of any dictionary-compressed text representation. Let $\gamma$ be the size of a string attractor for a text of length $n$. Our index takes $O(\gamma\log(n/\gamma))$ words of space and supports locating the $occ$ occurrences of any pattern of length $m$ in $O(m\log n + occ\log^{\epsilon}n)$ time, for any constant $\epsilon>0$. This is, in particular, the first index for general macro schemes and collage systems. Our result shows that the relation between indexing and compression is much deeper than what was previously thought: the simple property standing at the core of all dictionary compressors is sufficient to support fast indexed queries.Comment: Fixed with reviewer's comment

The study of probability model for compound similarity searching

Information Retrieval or IR system main task is to retrieve relevant documents according to the users query. One of IR most popular retrieval model is the Vector Space Model. This model assumes relevance based on similarity, which is defined as the distance between query and document in the concept space. All currently existing chemical compound database systems have adapt the vector space model to calculate the similarity of a database entry to a query compound. However, it assumes that fragments represented by the bits are independent of one another, which is not necessarily true. Hence, the possibility of applying another IR model is explored, which is the Probabilistic Model, for chemical compound searching. This model estimates the probabilities of a chemical structure to have the same bioactivity as a target compound. It is envisioned that by ranking chemical structures in decreasing order of their probability of relevance to the query structure, the effectiveness of a molecular similarity searching system can be increased. Both fragment dependencies and independencies assumption are taken into consideration in achieving improvement towards compound similarity searching system. After conducting a series of simulated similarity searching, it is concluded that PM approaches really did perform better than the existing similarity searching. It gave better result in all evaluation criteria to confirm this statement. In terms of which probability model performs better, the BD model shown improvement over the BIR model