Many quantum computation algorithms, and processes like measurement based quantum computing, require the initial state of the quantum computer to be an eigenstate of a specific unitary operator. Here we study how quantum states that are eigenstates of finite dimensional irreducible representations of the special unitary (SU(d)) and the permutation (S_n) groups can be efficiently constructed in the computational basis formed by tensor products of the qudit states. The procedure is a unitary transform, which first uses Schur-Weyl duality to map every eigenstate to a unique Schur basis state, and then recursively uses the Clebsch - Gordan transform to rotate the Schur basis state to the computational basis. We explicitly provide an efficient quantum algorithm, and the corresponding quantum logic circuit, to generate any desired eigenstate of SU(2) and SU(3) irreducible representations in the computational basis.

D’un pays d'émigrants, le Cap-Vert a commencé dans les années 90, en particulier dans la seconde moitié, à recevoir les étrangers, en particulier ceux des pays voisins de la CEDEAO, suite à l'accord de la libre circulation des personnes inscrites dans le Protocole de la libre circulation ratifié par le Cap-Vert. Le pays est devenu un pôle d'attraction de travailleurs étrangers suite à l'essor du tourisme et des activités connexes, notamment la construction civile et les travaux publics, le commerce, l´hôtellerie et la restauration.<p>L´objectif de ce travail vise à analyser la construction des images de l'immigration en provenance de pays membres de la CEDEAO au Cap-Vert, les représentations et les attitudes réciproques à l´égard de ce phénomène et les contextes dans lesquels elles se produisent. L'hypothèse de base est qu´on est dans un pays où les autochtones ont toujours vécu avec des étrangers, pas dans leur pays d´origine, mais dans des nombreuses destinations d'émigration. De même, cette coexistence, que fut la plupart du temps avec les Européens et les Américains blancs, commence à s´établir avec les voisins du continent, non pas dans un pays tiers mais au Cap Vert. Par conséquent, l'objectif est de comprendre les relations entre les groupes sociaux, nationaux et immigrés, à la suite de la fixation et l'insertion des immigrés dans les secteurs socio-économiques nationaux, particulièrement dans le marché du travail, où on trouve un taux de chômage élevé.<p>Cette étude est fondée sur un dialogue avec les théories des migrations internationales et les théories des représentations sociales et qui soutiennent la thèse.<p><p>From a country of emigrants, Cape Verde transformed into a country of immigrants during the 90’s, mainly in the second half of that decade. The country started receiving immigrants especially from the neighbourhood countries of the ECOWAS region, due to the free movement of people subscribed in the Protocol of movement of people ratified by Cape Verde. The country has been a focus of attraction of labour workers following the boom in tourism and related activities, including construction and public works, commerce, hotels, and restaurants services. <p>This work has the main objective to analyse the construction of the images of the people coming from the ECOWAS countries members in Cape Verde, the representations and reciprocal attitudes in relation to this phenomenon and the contexts in which they occur. It is assumed that we are in a country where the local population always interacted with foreigners not in their origins but in the various migratory destinations. Similarly, this coexistence that happened mainly with white Europeans and Americans is happening with the neighbours of the continent. Consequently, it is intended to understand the relationships the social groups, nationals and immigrants establish among them as a result of establishment and insertion in the national socioeconomic sectors, mainly at the labour market, where, along with high unemployment rate, it is, verified a massive inclusion of the ECOWAS foreigners. <p>The current study is based on a dialogue with the international migration theories and the social representation theories that will support the thesis. <p><p><p> / Doctorat en Sciences politiques et sociales / info:eu-repo/semantics/nonPublished

A case study of two adolescent mothers of the same age is presented (17 years old) withwhich it is intended to explore the maternal representations and mother-baby interactions, that is, the different ways of “being with” a baby. The study pretends to discuss that it is not adolescent motherhood in itself a risk factor, but other mediating variables such as support network and the reflective function with which each young mother counts. Maternal repre- sentations were assessed through a semi-structured interview about maternal representations (Traverso, 2006) and the mother-infant interactions were measured and filmed through the Mother-Infant Global Ratings for two and four months (Murray, Fiori-Cowley & Cooper,1996). / Se presenta un estudio de caso de dos madres adolescentes de la misma edad (17 años), con el cual se intenta explorar las representaciones maternas y las interacciones madre-bebe, es decir, las distintas maneras de “estar con” el bebe. El estudio pretende discutir que la maternidad adolescente en sí misma no es un factor de riesgo, sino que otras variables moderadoras como la calidad de las redes de sostenimiento y la función reflexiva con que cada joven madre cuenta. Las representaciones maternas fueron evaluadas a través de una entrevista semi-estructurada sobre representaciones maternas (Traverso, 2006) y las interacciones madre-bebe fueron medidas y filmadas a través del Mother-Infant Global-Ratings para dos y cuatro meses (Murray, Fiori-Cowley & Cooper, 1996).

The master's thesis deals with the problem of restoring a block of missing samples in a digital audio signal. This problem is formulated as an optimization task, which seeks the sparsest time-frequency representation of a signal within the set of feasible reconstructed signals. Several particular formulations are discussed, namely the analyzing and the synthesizing model, both for convex and non-convex approaches. Suitable algorithms are proposed for solving these formulations, and in the convex case, the method is further enhanced by various procedures to compensate for the energy drop in the inpainted signal segment. The proposed algorithms are tested on real recordings, and their performance is shown to be competitive with the state-of-the-art.

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Patent monitoring is about tracking the upcoming inventions in a particular field, predicting future trends, and specific intellectual property rights of interest. It is the process of finding relevant patents on a particular topic based on a specific query. With patent monitoring, one can keep them updated on the new technology in the market. Also, they can find potential licensing opportunities for their inventions. The outputs of patent monitoring are essential for companies, academics, and inventors looking forward to using the latest patents that can enhance further innovation. Nevertheless, there is no widely accepted best approach to patent monitoring. Usually, most patent monitoring systems are based on complex search and find, often leading to insignificant hit rates and highly human intervention. As the number of patents published each year increases massively and with patents being critical to accelerating innovation, the current approach to patent monitoring has two main drawbacks. Firstly, human-driven patent monitoring is time consuming and expensive process. In addition, there is a risk of overlooking interesting documents due to inadequate searching tools and processes, which could cost companies fortunes while at the same time hindering further innovation and creativity. This thesis presents a smart patent monitoring assistant tool that applies natural language processing. The use of several natural language processing methods is investigated to find, classify and rank relevant documents. The tool was trained on a dataset that contains the title, abstract, and claims of patent documents. Given a dataset of patent documents, the aim of this thesis is to create a tool that can classify patents into two classes relevant and not relevant. Furthermore, the tool can rank documents based on relevancy. The evaluation result of the tool gave satisfying results when it came to receiving the expected patents. In addition, there is a significant improvement in terms of performance for memory usage and the time it took to train the model and get results. / Patentövervakning handlar om att övervaka kommande uppfinningar, förutsäga framtida trender, eller specifika immateriella rättigheter och används för att hitta relevanta patent inom ett visst område. Med patentövervakning är det möjligt att hålla patent uppdaterade enligt den senaste tekniken på marknaden samt att hitta potentiella möjligheter att licensiera innehavda patent till tredje part. Målgruppen för patentövervakning är företag, akademiker, och uppfinnare som vill hitta de senaste patenten för att uppnå maximal innovation. Dock finns det ingen generell metod för att bedriva patentövervakning. Vanligtvis används komplexa sökmetoder som resulterar i undermåliga resultat och kräver manuellt ingripande. I och med att andelen patent ökar varje år har nuvarande metod två huvudsakliga nackdelar. Till att börja med är mänsklig patentövervakning en tidskrävande och dyr process. Vidare är det en betydande risk att missa viktiga eller på andra sätt intressanta dokument till följd av en bristande sökprocess. Detta kan möjligtvis resultera i att företag missar stora möjligheter samt utebliven innovation och kreativitet. Detta arbete presenterar ett smart verktyg för patentövervakning baserat på natural language processing. Vi analyserar användningen av ett flertal processer för att hitta, klassificera, och rangordna relevant dokument. Verktyget tränades på ett dataset som innehåller patentets titel, abstrakt, och vad patentet gör anspråk på. Givet ett godtyckligt dataset är målet med detta arbete att utveckla ett verktyg med förmågan att klassificera relevanta och icke-relevanta patent samt rangordna dessa utifrån relevans. Resultatet visar att verktyget gav tillfredsställande gällande att hitta önskvärda patent. Vidare uppnåddes en signifikant förbättring när det gäller prestanda för minnesanvändning och tiden som krävs för att träna modeller och erhålla resultat.

Recurrent Neural Networks (RNNs) are pivotal in deep learning for time series prediction, but they suffer from 'exploding values' and 'gradient decay,' particularly when learning temporally distant interactions. Long Short-Term Memory (LSTM) and Gated Recurrent Units (GRU) have addressed these issues to an extent, but the precise mitigating mechanisms remain unclear. Moreover, the success of feedforward neural networks in time series tasks using an 'attention mechanism' raises questions about the solutions offered by LSTMs and GRUs. This study explores an alternative explanation for the challenges faced by RNNs in learning long-range correlations in the input data. Could the issue lie in the movement of the representations - how hidden nodes store and process information - across nodes instead of localization? Evidence presented suggests that RNNs can indeed possess "moving representations," with certain training conditions reducing this movement. These findings point towards the necessity of further research on localizing representations.

This study investigates the news discourses to find out how deaf people and/or deafness is represented and analyses how the discourses might be affected by or influence common attitudes and prejudices about deaf people and/or deafness. First, however, this study analysed the contents of the news articles quantitatively in order to find frequencies of different news topics with references to deaf people and/or deafness and whether deaf people were allowed to talk or not. After the content analysis, ten articles were selected for the discourse analysis.   The results of the content analysis show that deaf people are represented and allowed to talk in most of the articles, but that hearing people are also represented in a majority of the articles. Most articles are about culture and personalities, but there are also articles about for example sign language and hearing devices. Most deaf people are represented as individuals, but they are also represented as representatives for the deaf and as both individuals and representatives.   The discourse analysis shows that deaf people are represented as a linguistic and cultural minority in both cultural and personal discourses but represented as broken and in need of being fixed for integration in society in medical discourses. In medical discourses, only experts talk about deafness and no deaf people are represented. In other discourses, both deaf and hearing people talk about deaf people, sign language and deaf culture. In some of the discourses, however, it is clear that deaf people are represented from the hearing viewpoint on deafness. There were discursive discrimination of deafness in medical discourses but occurred rarely in other discourses except when the medical view on deafness is present. Deaf people are represented as a minority distinct from the hearing majority in most articles and some of the cultural discourses show attempts to build a bridge between the deaf world and the hearing society. The majority of the discourses point to pluralism as a social practice but some of those discourses also point to inclusion and exclusion as social practices. The medical discourses however point to both assimilation and exclusion as social practices.

This thesis investigated lexical representations of children who stutter (CWS) and children who do not stutter (CWNS) using a duration-blocked gating task. This thesis tested the hypothesis that children who stutter have underspecified phonological representations for words, are less sensitive to incremental and segmental information for lexical items, and therefore require more acoustic-phonetic information to activate words in their lexicon. Pilot data collected from fourteen children (ages 5;6 to 10;1): 7 CWS and 7 CWNS matched on age were included in this thesis. Results showed that children in both talker groups required relatively equal amounts of acoustic-phonetic information to identify target words. A regression model revealed that age in months predicted performance on the gating task for CWNS, but that age in months did not predict performance on the gating task for CWS suggesting a difference in the developmental maturity of lexical representations in CWS. Possible conclusions from these pilot data are presented along with recommendations for future research. / text

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