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yes / Every industry has significant data output as a product of their working process, and with the recent advent of big data mining and integrated data warehousing it is the case for a robust methodology for assessing the quality for sustainable and consistent processing. In this paper a review is conducted on Data Quality (DQ) in multiple domains in order to propose connections between their methodologies. This critical review suggests that within the process of DQ assessment of heterogeneous data sets, not often are they treated as separate types of data in need of an alternate data quality assessment framework. We discuss the need for such a directed DQ framework and the opportunities that are foreseen in this research area and propose to address it through degrees of heterogeneity.

<p>This research combines the economic contribution analysis of hardwood industries in Indiana and the economic impact analysis of furbearer hunting and trapping in Indiana. This research employs input-output analysis using Impact Analysis for Planning (IMPLAN) software. </p>

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Data Quality confirms the correct and meaningful representation of real world information. Researchers have proposed frameworks to measure and analyze the Data Quality. Still modern organizations find it very challenging to state the level of enterprise Data Quality maturity. This study aims at defining the Data Quality of a system also examine the Data Quality Assessment practices. A definition for Data Quality is suggested with the help of systematic literature review. Literature review also provided a list of dimensions and initiatives for Data Quality Assessment. A survey is conducted to examine these aggregated aspects of Data Quality in an organization actively using ERP and CRM systems. The survey was aimed at collecting organizational awareness of Data Quality and to study the practices followed to ensure the Data Quality in ERP and CRM systems. The survey results identified data validity, accuracy and security as the main areas of interest for Data Quality. The results also indicate that, due to audit requirements of ERP systems, ERP systems have higher demand of Data Quality as compared to CRM systems.

This study describes the differences of parents’, teachers’, and the researcher’s assessment of quality of five different child care programs. This study focuses on infant and toddler classrooms or care settings. Parents, and teachers/providers completed the Infant/Toddler Environment Rating Scale and the Definition of Quality Questionnaire in order to rate the quality of infant and toddler child care programs. The findings from the questionnaires supported existing research that indicates a majority of child care programs in the United Stated range from poor to mediocre; and parents utilizing all types of cares, licensed/certified or otherwise, tended to overrate the quality of child care programs. In this study, the only exception to this tendency was the ratings of quality in the licensed and accredited center, where parents’, teachers’, and the researcher’s ratings were similar. This study provides a new contribution to the field of child care research in its finding that some of the teachers in all the different types of care settings investigated (with the exception of the licensed and accredited center) also tended to overrate the quality of infant and toddler child care programs. Follow up interviews were conducted with some of the parents and teachers, in order to explore the reasons behind their ratings of quality. The consensus was that parents and teachers identified characteristics of quality that were dissimilar to those identified by child care experts. There are many possible reasons for this result, including lack of adequate information to help them identify determinant characteristics of quality programs, that there was difficulty in assessing quality, and that there was a lack of demand for quality programs. / Master of Science

No / RATIONALE, AIMS & Tools for the assessment of the quality of research studies tend to be specific to a particular research design (e.g. randomized controlled trials, or qualitative interviews). This makes it difficult to assess the quality of a body of research that addresses the same or a similar research question but using different approaches. The aim of this paper is to describe the development and preliminary evaluation of a quality assessment tool that can be applied to a methodologically diverse set of research articles. METHODS: The 16-item quality assessment tool (QATSDD) was assessed to determine its reliability and validity when used by health services researchers in the disciplines of psychology, sociology and nursing. Qualitative feedback was also gathered from mixed-methods health researchers regarding the comprehension, content, perceived value and usability of the tool. RESULTS: Reference to existing widely used quality assessment tools and experts in systematic review confirmed that the components of the tool represented the construct of 'good research technique' being assessed. Face validity was subsequently established through feedback from a sample of nine health researchers. Inter-rater reliability was established through substantial agreement between three reviewers when applying the tool to a set of three research papers (kappa = 71.5%), and good to substantial agreement between their scores at time 1 and after a 6-week interval at time 2 confirmed test-retest reliability. CONCLUSIONS: The QATSDD shows good reliability and validity for use in the quality assessment of a diversity of studies, and may be an extremely useful tool for reviewers to standardize and increase the rigour of their assessments in reviews of the published papers which include qualitative and quantitative work.

Yes / This work presents a methodology to optimize the selection of multiple parameter levels of an image acquisition, degradation, or post-processing process applied to stimuli intended to be used in a subjective image or video quality assessment (QA) study. It is known that processing parameters (e.g. compression bit-rate) or techni- cal quality measures (e.g. peak signal-to-noise ratio, PSNR) are often non-linearly related to human quality judgment, and the model of either relationship may not be known in advance. Using these approaches to select parameter levels may lead to an inaccurate estimate of the relationship between the parameter and subjective quality judgments – the system’s quality model. To overcome this, we propose a method for modeling the rela- tionship between parameter levels and perceived quality distances using a paired comparison parameter selection procedure in which subjects judge the perceived similarity in quality. Our goal is to enable the selection of evenly sampled parameter levels within the considered quality range for use in a subjective QA study. This approach is tested on two applications: (1) selection of compression levels for laparoscopic surgery video QA study, and (2) selection of dose levels for an interventional X-ray QA study. Subjective scores, obtained from the follow-up single stimulus QA experiments conducted with expert subjects who evaluated the selected bit-rates and dose levels, were roughly equidistant in the perceptual quality space - as intended. These results suggest that a similarity judgment task can help select parameter values corresponding to desired subjective quality levels. / Parts of this work were performed within the Telesurgery project (co-funded by iMinds, a digital research institute founded by the Flemish Government; project partners are Unilabs Teleradiology, SDNsquare and Barco, with project support from IWT) and the PANORAMA project (co-funded by grants from Belgium, Italy, France, the Netherlands, the United Kingdom, and the ENIAC Joint Undertaking).

Depth-Image-Based Rendering (DIBR) est une technologie fondamentale dans plusieurs applications liées à la 3D, telles que la vidéo en mode point de vue libre (FVV), la réalité virtuelle (VR) et la réalité augmentée (AR). Cependant, l'évaluation de la qualité des vues synthétisées par DIBR a également posé de nouveaux problèmes, car ce processus induit de nouveaux types de distorsions, qui sont intrinsèquement différentes des distorsions provoquées par le codage vidéo. Ce travail est destiné à mieux évaluer la qualité des vues synthétisées par DIBR en multimédia immersif. Au chapitre 2, nous proposons deux métriques complètements sans référence (NR). Le principe de la première métrique NR NIQSV consiste à utiliser plusieurs opérations morphologiques d’ouverture et de fermeture pour détecter et mesurer les distorsions, telles que les régions floues et l’effritement. Dans la deuxième métrique NR NIQSV+, nous améliorons NIQSV en ajoutant un détecteur de “black hole” et une détection “stretching”.Au chapitre 3, nous proposons deux métriques de référence complète pour traiter les distorsions géométriques à l'aide d'un masque de désocclusion et d'une méthode de correspondance de blocs multi-résolution. Au chapitre 4, nous présentons une nouvelle base de données d'images synthétisée par DIBR avec ses scores subjectifs associés. Ce travail se concentre sur les distorsions uniquement induites par différentes méthodes de synthèse de DIBR qui déterminent la qualité d’expérience (QoE) de ces applications liées à DIBR. En outre, nous effectuons également une analyse de référence des mesures d'évaluation de la qualité objective de pointe pour les vues synthétisées par DIBR sur cette base de données. Le chapitre 5 conclut les contributions de cette thèse et donne quelques orientations pour les travaux futurs. / Depth-Image-Based Rendering (DIBR) is a fundamental technology in several 3D-related applications, such as Free viewpoint video (FVV), Virtual Reality (VR) and Augmented Reality (AR). However, new challenges have also been brought in assessing the quality of DIBR-synthesized views since this process induces some new types of distortions, which are inherently different from the distortions caused by video coding. This work is dedicated to better evaluate the quality of DIBRsynthesized views in immersive multimedia. In chapter 2, we propose a completely No-reference (NR) metric. The principle of the first NR metrics NIQSV is to use a couple of opening and closing morphological operations to detect and measure the distortions, such as “blurry regions” and “crumbling”. In the second NR metric NIQSV+, we improve NIQSV by adding a “black hole” and a “stretching” detection. In chapter 3, we propose two Fullreference metrics to handle the geometric distortions by using a dis-occlusion mask and a multi-resolution block matching methods.In chapter 4, we present a new DIBR-synthesized image database with its associated subjective scores. This work focuses on the distortions only induced by different DIBR synthesis methods which determine the quality of experience (QoE) of these DIBR related applications. In addition, we also conduct a benchmark of the state-of-the-art objective quality assessment metrics for DIBR-synthesized views on this database. The chapter 5 concludes the contributions of this thesis and gives some directions of future work.

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.