Во введении обоснована актуальность темы ВКР, определены объект и предмет исследования, сформулирована цель работы, поставлены задачи, которые необходимо решить для достижения цели исследования, обозначена степень разработанности темы, показана научная новизна результатов проведенного исследования. В первой главе на основе анализа теоретических основ управления проектами показано, что знание их необходимо для корректной оценки качества инвестиционно-строительного проекта (ИСП). Во второй главе на основе анализа показателей качества решений проектно-конструкторской документации, показано, что для оценки качества ИСП целесообразно рассматривать: проектные решения, проектно-конструкторскую деятельность и исполнение проектной документации. В третьей главе описаны методики оценки качества инвестиционно-строительного проекта, проведен сравнительный анализ методик на основе их применения на примере конкретного объекта капитального строительства (физкультурно-спортивный комплекс). В заключении приведены результаты, полученные в ходе исследования, и основные выводы по ВКР. / In the introduction the relevance of the final qualifying work is substantiated, the object and subject of research are defined, the purpose of the work is formulated, tasks are set, the scientific novelty of research is shown. In the first chapter it is shown based on the analysis of the theoretical foundations of project management that knowledge of them is necessary for a correct assessment of the quality of an investment construction project. In the second chapter it is shown based on the analysis of the quality indicators of design documentation solutions that it is advisable to consider: design solutions, design activities and execution of design documentation to assess the quality of an investment construction project. The third chapter describes the methods of assessing the quality of an investment and construction project, a comparative analysis of the methods based on their application on the example of a specific object of capital construction (a sports complex). In conclusion, the results obtained during the study and the main conclusions on the work are presented.

Procedural Content Generators (PCG) typically excel at generating a large amount of content in a short period of time. Whilst this is making PCG very applicable for the game industry, simplistic implementations of PCG lack in Usability whereas complex implementations of PCG lack in Controllability. The purpose of this study is therefore to deepen our understanding on the correlation between Controllability and Usability in algorithmic generators that utilizes a generic and constructive approach to generate terrain in games.Furthermore the findings in this study can be used in the field of procedural terrain generators to study deterministic generators that utilize Automatic generation, from a Usability or Controllability perspective.

Objective non-intrusive speech quality assessment aimed to emulate and correlate with human judgement has received more attention over the years. It is a difficult problem due to three reasons: data scarcity, noisy human judgement, and a potential uneven distribution of bias of mean opinion scores (MOS). In this paper, we introduce the Latent Mean-Opinion-Score Network (LaMOSNet) that leverage on individual judge’s scores to increase the data size, and new ideas to deal with both noisy and biased labels. We introduce a methodology called Optimistic Judge Estimation as a way to reduce bias in MOS in a clear way. We also implement stochastic gradient noise and mean teacher, ideas from noisy image classification, to further deal with noisy and uneven bias distribution of labels. We achieve competitive results on VCC2018 modeling MOS, and state-of-the-art modeling only listener dependent scores. / Objektiv referensfri ljudkvalitétsbedömning ämnad att härma och korrelera med mänsklig bedömning har fått mer uppmärksamhet med åren. Det är ett svårt problem på grund av tre anledningar: brist på data, varians i mänsklig bedömning, och en potentiell ojämn fördelning av bias av medel bedömningsvärde (mean opinion score, MOS). I detta papper introducerar vi Latent Mean-Opinion-Score Network (LaMOSNet) som tar nytta av individuella bedömmares poäng för att öka datastorleken, och nya idéer för att handskas med både varierande och partisk märkning. Jag introducerar en metodologi som kallas Optimistisk bedömmarestimering, ett sätt att minska partiskheten i MOS på ett klart sätt. Jag implementerar också stokastisk gradient variation och medellärare, idéer från opålitlig bild igenkänning, för att ännu mer hantera opålitliga märkningar. Jag får jämförelsebara resultat på VCC2018 när jag modellerar MOS, och state-of-the-art när jag modellerar enbart beömmarnas märkning.

This project focuses on deep neural network (DNN)-based non-intrusive speech quality assessment, specifically addressing the challenge of predicting mean-opinion-score (MOS) with interpretable posterior distributions. The conventional approach of providing a single point estimate for MOS lacks interpretability and doesn't capture the uncertainty inherent in subjective assessments. This thesis introduces DeePMOS, a novel framework capable of producing MOS predictions in the form of posterior distributions, offering a more nuanced and understandable representation of speech quality. DeePMOS adopts a CNN-BLSTM architecture with multiple prediction heads to model Gaussian and Beta posterior distributions. For robust training, we use a combination of maximum-likelihood learning, stochastic gradient noise, and a student-teacher learning setup to handle limited and noisy training data. Results showcase DeePMOS's competitive performance, particularly with DeePMOS-B achieving state-of-the-art utterance-level performance. The significance lies in providing accurate predictions along with a measure of confidence, enhancing transparency and reliability. This opens avenues for application in domains such as telecommunications and audio-processing systems. Future work could explore additional posterior distributions, evaluate the model on high-quality datasets, and consider incorporating listener-dependent scores. / Detta projekt fokuserar på icke-intrusiv bedömning av tal-kvalitet med hjälp av djupa neurala nätverk (DNN), särskilt för att hantera utmaningen att förutsäga mean-opinion-score (MOS) med tolkningsbara posteriora fördelningar. Den konventionella metoden att ge en enda punktsuppskattning för MOS saknar tolkningsbarhet och fångar inte osäkerheten som är inneboende i subjektiva bedömningar. Denna avhandling introducerar DeePMOS, en ny ramverk kapabel att producera MOS-förutsägelser i form av posteriora fördelningar, vilket ger en mer nyanserad och förståelig representation av tal-kvalitet. DeePMOS antar en CNN-BLSTM-arkitektur med flera förutsägelsehuvuden för att modellera Gaussiska och Beta-posteriora fördelningar. För robust träning använder vi en kombination av maximum-likelihood learning, stokastisk gradientbrus och en student-lärare inlärningsuppsättning för att hantera begränsad och brusig träningsdata. Resultaten visar DeePMOS konkurrenskraftiga prestanda, särskilt DeePMOS-B som uppnår state-of-the-art prestanda på uttalnivå. Signifikansen ligger i att ge noggranna förutsägelser tillsammans med en mått på förtroende, vilket ökar transparensen och tillförlitligheten. Detta öppnar möjligheter för tillämpningar inom områden som telekommunikation och ljudbehandlingssystem. Framtida arbete kan utforska ytterligare posteriora fördelningar, utvärdera modellen på högkvalitativa dataset och överväga att inkludera lyssnarberoende poäng.

Text in English / Undergraduate students at the Eduardo Mondlane University (UEM) experience great difficulty in developing their translation competence during their training period. On the one hand, they show many signs of poor quality during their training when they accomplish practical translation assignments on and off-campus. On the other hand, the quality of the final work submitted in partial fulfilment of the requirements for the Bachelor Honours Degree (Licenciatura) suggests that most students fail to go beyond the minimum standards with regard to translation competence. Yet, comprehensive research aimed at understanding factors hindering translation competence at the UEM has been scanty. Besides, the few studies available have some significant lacunae, for they focus on Portuguese language development; are limited to error analysis, and often ignore students‟ perspectives. Consequently, the problem of finding a balanced approach to developing students‟ translation competence has remained unaddressed. Therefore, this study has been conducted with the purpose of investigating the translation competence of the UEM undergraduates in order to establish the major obstacles to their translation competence development, and consequently come up with suggestions for improving the current translator-training degree programme. The study design uses qualitative methods translated into a case study approach. First, questionnaire data is analysed to gain lecturers‟ and students‟ perspectives on translation competence at the UEM. Second, a students‟ error typology is developed following a macro- and micro-textual analysis of their translations. The study concludes that substandard bilingual skills, compounded by curricular, attitudinal/motivational, pedagogical and infrastructural/instrumental factors, negatively impact the students‟ development of translation competence at the UEM and that addressing these may pave the way towards improving the current translation-training programme. / Linguistics and Modern Languages / M.A. (Linguistics)

Submitted in fulfillment of the requirements for the Doctoral Degree in Nursing, Durban University of Technology, Durban, South Africa, 2016. / This mixed methods study aimed to assess the functioning and processes of the Fast Queue Service Point in order to analyse the quality of care rendered in primary health care (PHC) facilities in the eThekwini district of the KwaZulu­ Natal Province in South Africa. The Fast Queue Service Point provides service in PHC facilities for health care users requiring short consultations. Congestion of PHC facilities is a result of increased access to PHC services with the introduction of free PHC services. This congestion was aggravated by the decentralization of services from hospitals to PHC level such as the introduction on Nurse Initiated Management of Anti-Retroviral Therapy (NIMART). In 2010, the National Core Standards (NCS) for health establishments were formulated further to the PHC Service package, to address issues of quality. An explanatory sequential mixed methods study design was used and data collection was conducted in two phases; the quantitative data collection phase consisting of two subsets of observations namely; the retrospective record review and structured observations of the Fast Queue Service Point process. The Statistical Package for the Social Sciences (SPSS) version 22 was used to analyse data. During the second phase semi-structured interviews were conducted with PHC staff members to describe their experiences of the Fast Queue Service Point and to clarify issues from the quantitative phase. Although Fast Queue Service users received sufficient care, there were important care assessments that had been inadequately performed or omitted. These included discussing side effects of medications and or immunizations and management thereof. Childrens' weights were not interpreted, an important aspect for children under five years of age. There was also lack of supportive supervision coupled with shortage of resources and too many time-consuming written records that were required to compile accurate statistics. Retraining and in-servicing of health personnel and making resources available, would assist in strengthening patient assessment, management and recording thereof. While clinic managers require to offer supportive supervision to health care providers, provision of lower categories of staff would be beneficial in supporting PNs and ENs so that they have time to compile records for statistics purposes, which were found to be taking up the bulk of their time. The framework for continuous quality improvement in implementing a Fast Queue Service in PHC settings was developed based on the findings of the study / D

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The use of audio and video communication has increased exponentially over the last decade and has gone from speech over GSM to HD resolution video conference between continents on mobile devices. As the use becomes more widespread the interest in delivering high quality media increases even on devices with limited resources. This includes both development and enhancement of the communication chain but also the topic of objective measurements of the perceived quality. The focus of this thesis work has been to perform enhancement within speech encoding and video decoding, to measure influence factors of audio and video performance, and to build methods to predict the perceived video quality. The audio enhancement part of this thesis addresses the well known problem in the GSM system with an interfering signal generated by the switching nature of TDMA cellular telephony. Two different solutions are given to suppress such interference internally in the mobile handset. The first method involves the use of subtractive noise cancellation employing correlators, the second uses a structure of IIR notch filters. Both solutions use control algorithms based on the state of the communication between the mobile handset and the base station. The video enhancement part presents two post-filters. These two filters are designed to improve visual quality of highly compressed video streams from standard, block-based video codecs by combating both blocking and ringing artifacts. The second post-filter also performs sharpening. The third part addresses the problem of measuring audio and video delay as well as skewness between these, also known as synchronization. This method is a black box technique which enables it to be applied on any audiovisual application, proprietary as well as open standards, and can be run on any platform and over any network connectivity. The last part addresses no-reference (NR) bitstream video quality prediction using features extracted from the coded video stream. Several methods have been used and evaluated: Multiple Linear Regression (MLR), Artificial Neural Network (ANN), and Least Square Support Vector Machines (LS-SVM), showing high correlation with both MOS and objective video assessment methods as PSNR and PEVQ. The impact from temporal, spatial and quantization variations on perceptual video quality has also been addressed, together with the trade off between these, and for this purpose a set of locally conducted subjective experiments were performed.