Sambandsanalys av surveydata kompliceras av förekomsten av slumpfel och metodeffekter i de avgivna svaren. Dessa felkällor kan leda till betydande över- eller underskattning av sambanden mellan undersökta variabler, och riskerar att leda till felaktiga slutsatser. En sedan länge känd metod för att estimera och kontrollera för slumpfel och metodeffekter i enkätdata är den så kallade Multitrait Multimethod-metoden (MTMM). Nackdelen med MTMM-metoden är att den kräver att varje fråga som ska analyseras ställs minst tre gånger i samma enkät, vilket gör att ansatsen i praktiken oftast inte är möjlig att tillämpa. Sedan 2012 finns dock ett verktyg, SQP 2.0, som gör det möjligt att skatta slumpfel och metodeffekter i enkätdata utan att genomföra MTMM-experiment. Den här uppsatsen utvärderar prediktionerna från SQP 2.0 på en enkät om arbetslivsrelaterade frågor besvarad av svenska och brittiska respondenter. Programvarans prediktioner jämförs med resultat från MTMM-experiment, och effekten på sambandsanalysen av att tillämpa SQP-programvarans prediktioner av slumpfel och metodeffekter studeras. Slutsatserna från studien är att SQP 2.0 ger predicerade värden för slumpfel och metod-effekter som ligger nära de MTMM-estimerade i de flesta fall, men att betydande avvikelser också förekommer. Vidare konstateras att korrigering för slumpfel och metodeffekter har en betydande effekt på absolutvärdet av korrelationerna mellan variabler under de studerande förhållandena: korrelationerna i det studerade fallet ökar kraftigt efter justering. Korrelationernas relativa storlek förändras i mindre utsträckning, men för en enkät med mer varierade frågetyper kan också dessa påverkas kraftigt. / Correlation analysis of survey data is complicated by the presence of random errors and method effects in the answers given. These factors can lead to significant over- or underestimation of the correlations between variables. A well-established method for estimating and controlling for random error and method effects in survey data is the Multitrait-Multimethod (MTMM) approach. The disadvantage of this method is that it requires that each survey item to be analysed is asked multiple times in the same survey, making the approach hard to use in many practical situations. Since 2012 there is a tool available, SQP 2.0, to predict random errors and method effects in survey data without performing MTMM experiments. This paper evaluates the use of predictions from the SQP 2.0 software on the correlation analysis of a survey of work related matters answered by Swedish and British respondents. The software's predictions are compared with results from MTMM experiments, and the effect on the correlations of applying the SQP software's predictions of random errors and method effects are studied. The conclusion of the study is that SQP 2.0 gives predicted values for random error and method effects that are close to the MTMM-estimates in most cases, but that considerable deviations also occur. It is further concluded that controlling for random error and method effects has a significant effect on the absolute values of the correlations between variables in the studied cases: the correlations in the study increase substantially after adjustment. The relative sizes of the correlations between variables change to a lesser extent, but a questionnaire with more varied question types may have lead to different results in this respect.

Thesis (MScEng)--University of Stellenbosch, 2011. / ENGLISH ABSTRACT: The perceived quality of Voice over Internet Protocol (IP) (VoIP) communication relies on the network which is used to transport voice packets between the end points. Variable network characteristics such as bandwidth, delay and loss are critical for real-time voice traffic and are not always guaranteed by networks. It is important for network service providers to determine the Quality of Service (QoS) it provides to its customers. The solution proposed here is to predict the perceived quality of a VoIP call, in real-time by using network statistics. The main objective of this thesis is to develop a network analysis tool, which gathers meaningful statistics from network traffic. These statistics will then be used for predicting the perceived quality of a VoIP call. This study includes the investigation and deployment of two main components. Firstly, to determine call quality, it is necessary to extract the voice streams from captured network traffic. The extracted sound files can then be analysed by various VoIP quality models to determine the perceived quality of a VoIP call. The second component is the analysis of network characteristics. Loss, delay and jitter are all known to influence perceived call quality. These characteristics are, therefore, determined from the captured network traffic and compared with the call quality. Using the statistics obtained by the repeated comparison of the call quality and network characteristics, a network specific algorithm is generated. This Non-Intrusive Quality Prediction Algorithm (NIQPA) uses basic characteristics such as time of day, delay, loss and jitter to predict the quality of a real-time VoIP call quickly in a non-intrusive way. The realised algorithm for each network will differ, because every network is different. Prediction results can then be used to adapt either the network (more bandwidth, packet prioritising) or the voice stream (error correction, change VoIP codecs) to assure QoS. / AFRIKAANSE OPSOMMING: Die kwaliteit van spraak oor die internet (VoIP) kommunikasie is afhanklik van die netwerk wat gebruik word om spraakpakkies te vervoer tussen die eindpunte. Netwerk eienskappe soos bandwydte, vertraging en verlies is krities vir intydse spraakverkeer en kan nie altyd gewaarborg word deur netwerkverskaffers nie. Dit is belangrik vir die netwerk diensverskaffers om die vereiste gehalte van diens (QoS) te verskaf aan hul kliënte. Die oplossing wat hier voorgestel word is om die kwaliteit van ’n VoIP oproep intyds te voorspel, deur middel van die netwerkstatistieke. Die belangrikste doel van hierdie projek is om ’n netwerk analise-instrument te ontwikkel. Die instrument versamel betekenisvolle statistiek deur van netwerkverkeer gebruik te maak. Hierdie statistiek sal dan gebruik word om te voorspel wat die gehalte van ’n VoIP oproep sal wees vir sekere netwerk toestande. Hierdie studie berus op die ondersoek en implementering van twee belangrike komponente. In die eerste plek, moet oproep kwaliteit bepaal word. Spraakstrome word uit die netwerkverkeer onttrek. Die onttrekte klanklêers kan dan geanaliseer word deur verskeie spraak kwaliteitmodelle om die kwaliteitdegradasie van ’n spesifieke VoIP oproep vas te stel. Die tweede komponent is die analise van netwerkeienskappe. Pakkieverlies, pakkievertraging en bibbereffek is bekend vir hul invloed op VoIP kwaliteit en is waargeneem. Hierdie netwerk eienskappe word dus bepaal uit die netwerkverkeer en daarna vergelyk met die gemete gesprekskwaliteit. Statistiek word verkry deur die herhaalde vergelyking van gesprekkwaliteit en netwerk eienskappe. Uit die statistiek kan ’n algoritme (vir die spesifieke network) gegenereer word om spraakkwaliteit te voorspel. Hierdie Nie-Indringende Kwaliteit Voorspellings-algoritme (NIKVA), gebruik basiese kenmerke, soos die tyd van die dag, pakkie vertraging, pakkie verlies en bibbereffek om die kwaliteit van ’n huidige VoIP oproep te voorspel. Hierdie metode is vinnig, in ’n nie-indringende manier. Die gerealiseerde algoritme vir die verskillende netwerke sal verskil, want elke netwerk is anders. Die voorspelling van spraakgehalte kan dan gebruik word om òf die netwerk aan te pas (meer bandwydte, pakkie prioriteit) òf die spraakstroom aan te pas (foutkorreksie, verander VoIP kodering) om die goeie kwaliteit van ’n VoIP oproep te verseker.

Transmission of video content over wireless access networks (in particular, Wireless Local Area Networks (WLAN) and Third Generation Universal Mobile Telecommunication System (3G UMTS)) is growing exponentially and gaining popularity, and is predicted to expose new revenue streams for mobile network operators. However, the success of these video applications over wireless access networks very much depend on meeting the user’s Quality of Service (QoS) requirements. Thus, it is highly desirable to be able to predict and, if appropriate, to control video quality to meet user’s QoS requirements. Video quality is affected by distortions caused by the encoder and the wireless access network. The impact of these distortions is content dependent, but this feature has not been widely used in existing video quality prediction models. The main aim of the project is the development of novel and efficient models for video quality prediction in a non-intrusive way for low bitrate and resolution videos and to demonstrate their application in QoS-driven adaptation schemes for mobile video streaming applications. This led to five main contributions of the thesis as follows:(1) A thorough understanding of the relationships between video quality, wireless access network (UMTS and WLAN) parameters (e.g. packet/block loss, mean burst length and link bandwidth), encoder parameters (e.g. sender bitrate, frame rate) and content type is provided. An understanding of the relationships and interactions between them and their impact on video quality is important as it provides a basis for the development of non-intrusive video quality prediction models.(2) A new content classification method was proposed based on statistical tools as content type was found to be the most important parameter. (3) Efficient regression-based and artificial neural network-based learning models were developed for video quality prediction over WLAN and UMTS access networks. The models are light weight (can be implemented in real time monitoring), provide a measure for user perceived quality, without time consuming subjective tests. The models have potential applications in several other areas, including QoS control and optimization in network planning and content provisioning for network/service providers.(4) The applications of the proposed regression-based models were investigated in (i) optimization of content provisioning and network resource utilization and (ii) A new fuzzy sender bitrate adaptation scheme was presented at the sender side over WLAN and UMTS access networks. (5) Finally, Internet-based subjective tests that captured distortions caused by the encoder and the wireless access network for different types of contents were designed. The database of subjective results has been made available to research community as there is a lack of subjective video quality assessment databases.

The recently released High Efficiency Video Coding (HEVC) standard, which halves the transmission bandwidth requirement of encoded video for almost the same quality when compared to H.264/AVC, and the availability of increased network bandwidth (e.g. from 2 Mbps for 3G networks to almost 100 Mbps for 4G/LTE) have led to the proliferation of video streaming services. Based on these major innovations, the prevalence and diversity of video application are set to increase over the coming years. However, the popularity and success of current and future video applications will depend on the perceived quality of experience (QoE) of end users. How to measure or predict the QoE of delivered services becomes an important and inevitable task for both service and network providers. Video quality can be measured either subjectively or objectively. Subjective quality measurement is the most reliable method of determining the quality of multimedia applications because of its direct link to users’ experience. However, this approach is time consuming and expensive and hence the need for an objective method that can produce results that are comparable with those of subjective testing. In general, video quality is impacted by impairments caused by the encoder and the transmission network. However, videos encoded and transmitted over an error-prone network have different quality measurements even under the same encoder setting and network quality of service (NQoS). This indicates that, in addition to encoder settings and network impairment, there may be other key parameters that impact video quality. In this project, it is hypothesised that video content type is one of the key parameters that may impact the quality of streamed videos. Based on this assertion, parameters related to video content type are extracted and used to develop a single metric that quantifies the content type of different video sequences. The proposed content type metric is then used together with encoding parameter settings and NQoS to develop content-based video quality models that estimate the quality of different video sequences delivered over IP-based network. This project led to the following main contributions: (1) A new metric for quantifying video content type based on the spatiotemporal features extracted from the encoded bitstream. (2) The development of novel subjective test approach for video streaming services. (3) New content-based video quality prediction models for predicting the QoE of video sequences delivered over IP-based networks. The models have been evaluated using subjective and objective methods.

Folienmanagement ist von wirtschaftlicher Bedeutung im Freiland-Gemüsebau im Frühjahr. Aber die Prognose des optimalen Zeitpunktes der Abnahme von Plastik-Abdeckungen vom Bestand ist mit den bereits verfügbaren Mitteln zu ungenau, um die heutigen Anforderungen an die Produktionssicherheit zu erfüllen. Der bislang verwendete empirische Ansatz benötigt aktuelle Referenzmessungen unter den Abdeckungen, welche kostspielig sind. Das Ziel dieser Arbeit war es, die Grundlagen eines mechanistischeren Modellansatzes zu entwickeln, welcher auf dem physikalischen und biologischen Verständnis von Energiehaushalt, Pflanzenwachstum und den Prozessen der Qualitätsentwicklung unter den Abdeckungen beruht, um die zukünftige Produktionssicherheit zu verbessern. Entsprechende Feldversuche wurden durchgeführt, um Daten zum Pflanzenwachstum und Mikroklima unter und über der Abdeckung zu erhalten und neue sowie etablierte Untermodelle zu parametrisieren. Weiterhin wurden Laborversuche zum Verständnis z.B. der optischen Eigenschaften der Abdeckungen, Blätter und des Bodens ausgeführt. Außerdem wurde eine neue Methode zur Bestimmung des Blattflächenindex bei Kopfsalat und Kohlrabi geprüft und für die effiziente Erhebung der Pflanzendaten etabliert (Sandmann et al. 2013). Im Ergebnis können nun verschiedene Prozesse der Gemüseproduktion unter Abdeckungen besser verstanden und mit hinreichender Genauigkeit mathematisch beschrieben werden, z.B. Strahlungshaushalt (Graefe & Sandmann 2014) und Blattflächenwachstum. Die meisten Ziele der Arbeit wurden erreicht. Weitere Arbeit ist vor allem notwendig für die Modellierung der Lufttemperatur unter der Abdeckung und die Entwicklung eines mechanistischen Ansatzes zur Beschreibung der Pflanzenqualität. Hier konnte die Pflanzenqualität wegen der subjektiv beeinflussten Daten nur über einen empirischen Ansatz modelliert werden. Die übliche Erfassung der Pflanzenqualität sollte überdacht werden, um zukünftig möglichst objektive Werte zu erhalten. / Plastic film management is economically of importance for vegetable growing in the field in early spring, but the prediction of the best moment of removal of plastics from the crops is currently too imprecise to fulfill contemporary requirements in production safety. The broadly used approach for prediction is of empirical nature and is depending on current reference data from below covers, which are expensive to gather. The aim of this thesis was to develop the scientific foundations for a more mechanistic model approach, based on the physical and biological understanding of the energy balance, plant growth and plant quality formation process below plastic covers in order to increase future production safety. Field trials at three sites, with two species and several cover materials and removal strategies were carried out to gain data from plants and microclimate beneath and above covers for parameterization of new and established submodels. Additionally, laboratory experiments were performed to understand e.g. the optical properties of plastics, leaves and soil. Furthermore, a new method for determining leaf area index in lettuce and kohlrabi was adopted and established for a more efficient plant data collection (Sandmann et al. 2013). As a result, several processes of vegetable production using plastic covers are now better understood and can be described mathematically and sufficiently precise, e.g. the short wave radiation budget (Graefe & Sandmann 2014) and leaf area growth. Most, but not all aims of the thesis could be achieved. Further work will be necessary according to modeling of air temperature below the covers, leaf gas exchange and the development of a mechanistic approach for plant quality formation. Here, plant quality could only be modelled via an empirical approach, due to subjectively influenced data. Common plant quality data acquisition should be reconsidered to yield as much as possible objective values in the future.

LTE (Long Term Evolution) a été développé et normalisé par le 3GPP (3rd Generation Partnership Project). C’est un réseau à commutation de paquets. Cela signifie que la voix sur LTE (VoLTE) est un service de VoIP avec les exigences de qualité de service garantis au lieu de transmettre dans un réseau à commutation de circuits tels que les systèmes existants (2G/3G). VoLTE est déployé dans un réseau entièrement IP combinée avec IMS (IP Sous-système Multimédia). De ce fait, le déploiement de VoLTE est assez complexe et comment assurer la qualité de transmission de la voix sur les réseaux LTE est un très grand défi. Ainsi, il faut plusieurs solutions différentes pour renforcer et améliorer la qualité de transmission de la voix sur les réseaux LTE. Dans cette thèse, nous présentons des solutions en vue d’améliorer la qualité de transmission de la voix sur les réseaux LTE pour les services audio à bandes étroites et larges. Pour cela, il nous faudra différents facteurs complets en solutions. L’un d’eux est QoE (Qualité de l’Expérience) qui est une nouvelle tendance. Et afin de déterminer la perception des utilisateurs pour le service en temps réel tel que VoLTE, nous utilisons le E-model étendu et le WB (large bande) E-model pour des services audio à bandes étroites et larges respectivement. Les solutions proposées ici portent principalement sur des éléments clés dans les réseaux LTE, tels que le codage par chaine, MAC (Contrôle d’Accès Moyen) des systèmes de planification et la qualité de voix du moniteur décrits comme suit. Tout d’abord, des algorithmes améliorés pour renforcer le codec de la chaine LTE (codeur et décodeur) ont été proposés. Pour améliorer le codeur de chaine LTE, un algorithme d’adaptation conjointe a été déployé. Le but de cet algorithme est de minimiser la redondance générée par codage en chaine avec une légère réduction de la perception de l’utilisateur. Ensuite, afin d’améliorer le décodeur par chaine LTE, un algorithme amélioré Log-MAP a été présenté. Cet algorithme vise à obtenir la performance BER (Bit Error Rate) qui est le plus proche du Log-MAP avec une complexité de calcul réduite par rapport à l’état de l’art. Deuxièmement, la chaine et les systèmes QoS de planification améliorés de la perception de l’utilisateur et du mode de priorité VoIP ont été proposés. Ces planificateurs sont déployés à la fois pour les utilisateurs d’audio à larges et à étroites bandes. Les résultats numériques montrent qu’ils surpassent plusieurs planificateurs en vedette tels que FLS, M-LWDF et EXP/PF en termes de retard, de taux de perte de paquets, de débit cellulaire, d’indice et de l’équité et d’efficacité spectrale dans presque tous les cas. Enfin, pour assurer la qualité vocale de transmission sur le réseau LTE, la prédiction de la satisfaction des utilisateurs est essentielle. Pour cette raison, nous présentons deux modèles non intrusifs pour mesurer la qualité de la voix sur les réseaux LTE. Ces modèles sont utilisés pour les utilisateurs d’audio à bandes étroites et larges bandes. Les modèles proposés ne se réfèrent pas au signal original. Par conséquent, ils sont très appropriés pour prédire la qualité de l’appel vocal sur les réseaux LTE / LTE (Long Term Evolution) has been developed and standardized by 3GPP (3rd Generation Partnership Project). It is a packet-switched network. This means voice over LTE (VoLTE) is a VoIP service with the guaranteed QoS requirements instead of transmitted in a circuit-switched network such as the legacy system (2G/3G). Since VoLTE is deployed in an All-IP network combined with IMS (IP Multimedia Subsytem), thus, the VoLTE deployment is quite complex and how to ensure voice transmission quality over LTE networks is a very big challenge. Therefore, there needs to be many different solutions to enhance and improve voice transmission quality over LTE networks. In this dissertation, we present solutions to enhance and improve voice transmission quality over LTE networks for both narrowband and wideband audio services. In order to do that, there needs to be many different factors complemented in solutions. One of them is QoE (Quality of Experience) which is a new trend. And in order to determine user perception for real-time service such as VoLTE, we use extended E-model and WB (Wideband) E-model for narrowband and wideband audio services, respectively. The proposed solutions in this thesis mainly focus on key elements in LTE networks such as channel coding, MAC (Medium Access Control) scheduling schemes and monitor voice quality described as follows. First, enhanced/improved algorithms for enhancing LTE channel codec (coder and decoder) have been proposed. In order to enhance LTE channel coder, a joint source-channel code rate adaption algorithm has been deployed. The goal of this algorithm is to minimize redundancy generated by channel coding with a slight reduction of user perception. Next, in order to enhance LTE channel decoder, an improved Log-MAP algorithm has been presented. This algorithm aims at obtaining BER performance that is closest to the LOP-MAP with the computational complexity reduced in comparison with state-of-the-art. Second, channel- and QoS-Aware scheduling schemes with the enhancement of user perception and VoIP priority mode have been proposed. These schedulers are deployed for both narrowband and wideband audio users. The numerical results show that they outperform several featured schedulers such as FLS, M-LWDF, and EXP/PF in terms of delay, packet loss rate, cell throughput, fairness index, and spectral efficiency in almost cases. Last, in order to ensure voice transmission quality over LTE network, prediction of user satisfaction is essential. For this reason, we present two object non-intrusive models for measuring voice quality in LTE networks. These models are used for narrowband and wideband audio users. The proposed models do not refer to the original signal, thus, they are very suitable for predicting voice call quality in LTE networks

L’industrie microélectronique est un domaine compétitif, confronté de manière permanente à plusieurs défis. Pour évaluer les étapes de fabrication, des tests de qualité sont appliqués. Ces tests étant discontinus, une défaillance des équipements peut causer une dégradation de la qualité du produit. Des alarmes peuvent être déclenchées pour indiquer des problèmes. D’autre part, on dispose d’une grande quantité de données des équipements obtenues à partir de capteurs. Une gestion des alarmes, une interpolation de mesures de qualité et une réduction de données équipements sont nécessaires. Il s’agit dans notre travail à développer des méthodes génériques d’analyse multi-variée permettant d’agréger toutes les informations disponibles sur les équipements pour prédire la qualité de produit en prenant en compte la qualité des différentes étapes de fabrication. En se basant sur le principe de reconnaissance de formes, nous avons proposé une approche pour prédire le nombre de produits restant à produire avant les pertes de performance liée aux spécifications clients en fonction des indices de santé des équipement. Notre approche permet aussi d'isoler les équipements responsables de dégradation. En plus, une méthodologie à base de régression régularisée est développée pour prédire la qualité du produit tout en prenant en compte les relations de corrélations et de dépendance existantes dans le processus. Un modèle pour la gestion des alarmes est construit où des indices de criticité et de similarité sont proposés. Les données alarmes sont ensuite utilisées pour prédire le rejet de produits. Une application sur des données industrielles provenant de STMicroelectronics est fournie. / The microelectronics industry is a highly competitive field, constantly confronted with several challenges. To evaluate the manufacturing steps, quality tests are applied during and at the end of production. As these tests are discontinuous, a defect or failure of the equipment can cause a deterioration in the product quality and a loss in the manufacturing Yield. Alarms are setting off to indicate problems, but periodic alarms can be triggered resulting in alarm flows. On the other hand, a large quantity of data of the equipment obtained from sensors is available. Alarm management, interpolation of quality measurements and reduction of correlated equipment data are required. We aim in our work to develop generic methods of multi-variate analysis allowing to aggregate all the available information (equipment health indicators, alarms) to predict the product quality taking into account the quality of the various manufacturing steps. Based on the pattern recognition principle, data of the degradation trajectory are compared with health indices for failing equipment. The objective is to predict the remaining number of products before loss of the performance related to customer specifications, and the isolation of equipment responsible for degradation. In addition, regression- ased methods are used to predict the product quality while taking into account the existing correlation and the dependency relationships in the process. A model for the alarm management is constructed where criticality and similarity indices are proposed. Then, alarm data are used to predict the product scrap. An application to industrial data from STMicroelectronics is provided.