Yes / In England, care homes for older people have been subject to four different regulatory bodies within the last six years (see Table 1). The government has announced further change with the creation of a new regulator of adult health and social care in 2009 (CSCI, 2007). The current regulatory body, the Commission for Social Care Inspection (CSCI) will merge with the Healthcare Commission and the Mental Health Act Commission to create the Care Quality Commission. The Department of Health (DOH) is currently reviewing the future regulation of health and adult social care in England (DOH, 2005; DOH, 2006a) and the way that CSCI carries out the regulation and inspection of a range of social care agencies including care homes for older people. Substantial reforms of the regulatory system of regulation and inspection were embodied in the Care Standards Act (CSA) 2000 that was part of the wider Government agenda to modernize health and social care services. The Act established new regulatory bodies for care services and workers and along with the regulations and mandatory National Minimum Standards (NMS) created a framework to ensure greater consistency of quality and to better protect vulnerable children and adults (Engelman and Spencer, 2003). The impact of these changes for both inspectors and providers of care services has been significant. Regulators have had to adjust and adopt new ways of working whilst carrying out their statutory responsibilities. Care providers have had to respond to the revised changes in standards and requirements of registration. This article examines inspection as a mechanism for improving the quality of care standards. It reports on a study conducted in 2004 that sought the views of managers of care homes for older people about the NMS and the inspection process at that time. The role of inspectors will be considered in light of the findings and published literature.

The need for cost-effective usability evaluation has led to the development of methodologies to support the usability practitioner in finding usability problems during formative evaluation. Even though various methods exist for performing usability evaluation, practitioners seldom have the information needed to decide which method is appropriate for their specific purpose. In addition, most methods do not have an integrated relationship with a theoretical foundation for applying the method in a reliable and efficient manner. Practitioners often have to apply their own judgment and techniques, leading to inconsistencies in how the method is applied in the field. Usability practitioners need validated information to determine if a given usability evaluation method is effective and why it should be used instead of some other method. Such a desire motivates the need for formal, empirical comparison studies to evaluate and compare usability evaluation methods. In reality, the current data for comparing usability evaluation methods suffers from a lack of consistent measures, standards, and criteria for identifying effective methods. The work described here addresses three important research activities. First, the User Action Framework was developed to help organize usability concepts and issues into a knowledge base that supports usability methods and tools. From the User Action Framework, a mapping was made to the Usability Problem Inspector; a tool to help practitioners conduct a highly focused inspection of an interface design. Second, the reliability of the User Action Framework was evaluated to determine if usability practitioners could use the framework in a consistent manner when classifying a set of usability problems. Third, a comprehensive comparison study was conducted to determine if the Usability Problem Inspector, based on the User Action Framework, could produce results just as effective as two other inspection methods (i.e., the heuristic evaluation and the cognitive walkthrough). The comparison study used a new comparison approach with standards, measures, and criteria to prove the effectiveness of methods. Results from the User Action Framework reliability study showed higher agreement scores at all classification levels than was found in previous work with a similar classification tool. In addition, agreement using the User Action Framework was stronger than the results obtained from the same experts using the heuristic evaluation. From the inspection method comparison study, results showed the Usability Problem Inspector to be more effective than the heuristic evaluation and consistent with effectiveness scores from the cognitive walkthrough. / Ph. D.

The task of railroad inspection is a tedious one. It requires a lot of skilled experts and long hours of frequent on-field inspection. Automated ground equipment systems that have been developed to address this problem have the drawback of blocking the rail service during inspection process. As an alternative, using aerial imagery from a UAV, Computer Vision and Machine Learning based techniques were developed in this thesis to analyze two kinds of defects on the rail tracks. The defects targeted were missing spikes on tie plates and cracks on ties. In order to perform this inspection, the rail region was identified in the image and then the tie plate and tie regions on the track were detected. These steps were performed using morphological operations, filtering and intensity analysis. Once the tie plate was localized, the regions of interest on the plate were used to train a machine learning model to recognize missing spikes. Classification using SVM resulted in an accuracy of around 96% and varied greatly based on the tie plate illumination and ROI alignment for Lampasas and Chickasha subdivision datasets. Also, many other different classifiers were used for training and testing and an ensemble method with majority vote scheme was also explored for classification. The second category of learning model used was a multi-layered neural network. The major drawback of this method was, it required a lot of images for training. However, it performed better than feature based classifiers with availability of larger training dataset. As a second kind of defect, tie conditions were analyzed. From the localized tie region, the tie cracks were detected using thresholding and morphological operations. A machine learning classifier was developed to predict the condition of a tie based on training examples of images with extracted features. The multi-class classification accuracy obtained was around 83% and there were no misclassifications seen between two extreme classes of tie condition on the test data. / Master of Science

This thesis presents an inspection method based on RGB-D profiling for the rail industry. The proposed approach uses inexpensive RGB-D cameras to generate color and geometrical information of the observations, and stitches each consecutive scan from the sensor to form a map, provided that the two scans contain the information from the same observation. Using a technique known as pairwise registration, the errors between these consecutive scans are minimized using error minimization algorithms such as Iterative Closest Point and Normal Distributions Transform. Once the error between each consecutive scan is minimized, the scans are then converted into a global co-ordinate frame work to form a global map of all the added scans. The proposed approach could be used as a map-based identification technique by comparing the past global map to newly acquired scans while also reducing computation time effectively. The effectiveness of this approach is demonstrated by developing a system that uses multiple RGB-D cameras to detect railway defects such as spikes. The applicability of the proposed approach to other applications is then evaluated by profiling long lengths of road. / Master of Science

Residential deck and balcony failures are preventable if the decks and balconies are maintained and inspected regularly. Inspection of in-service decks or balconies is not common and often is unregulated or building codes do not appear to be widely enforced. With every failure, the need for a comprehensive inspection manual for residential wood decks and balconies becomes more apparent. Research was conducted on inspection techniques, common deck and balcony construction methods, maintenance issues, decay detection and the evolution of the building code regulations on decks and balconies. Eight decks were inspected to find the extent of structural inadequacies and non-conformance with building codes. Using the information gathered from the research and inspections, a Manual for the Inspection of Residential Wood Decks and Balconies was written for professional inspectors and building officials. The manual includes recommended methods to prepare for inspection to preparation of final reports. It contains an appendix with information on the "pick test" for detecting early decay, information on adequate deck attachment, and a sample report for a complete deck inspection. / Master of Science

京都大学 / 新制・課程博士 / 博士(工学) / 甲第25258号 / 工博第5217号 / 京都大学大学院工学研究科都市社会工学専攻 / (主査)教授 杉浦 邦征, 教授 八木 知己, 教授 KIM Chul-Woo / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DGAM

Construction and maintenance can have huge implications on the long-term functioning of GSI facilities. GSI facilities investigated were bioretention, permeable pavement, sand filters, infiltration trenches, and vegetated swales. This study first highlights the most important construction and maintenance items based on relevant studies and state stormwater manuals. Fairfax County, VA was used as a case study to evaluate the County's current stormwater program and illuminate common maintenance issues found for each GSI type. Data analysis of 3141 inspection records illustrated particular deficiencies for each GSI type and that there are differences between public and private facilities, most likely depending on site conditions and frequency of routine maintenance. Sediment accumulation was found to be the most common maintenance issue (27.8% of inspections), supporting the importance of adequate pretreatment and good housekeeping when implementing GSI. The Northern Virginia Soil and Water Conservation District (NVSWCD) performed a study surveying 63 public bioretention facilities in which they measured ponding depth, filter media depth, ponding area, and infiltration rates. The NVSWCD concluded that deficiencies found in facilities could mostly be attributed to inadequacies during construction. By comparing current post-construction inspections performed by the County to the NVSWCD data, it was found that these County inspections are failing to detect these inadequacies in bioretention facilities from improper construction. It is recommended that MS4s thoroughly record and track construction and post-construction inspection items to improve the longevity of its facilities and better inform future decision making regarding GSI. / Master of Science / Studies have shown that the proper construction and maintenance of green stormwater infrastructure (GSI) is a critical factor concerning its long-term performance; however, little research has been conducted on the necessary protocols and frequency to ensure its longevity. Many MS4s and stormwater managers are implementing these facilities without providing the adequate institutional framework to ensure the proper construction and maintenance. This study concentrates on illuminating the construction and maintenance factors critical for the performance of GSI. Facility types investigated were bioretention, permeable pavement, sand filters, infiltration trenches, and vegetated swales. The effects of local site-conditions and level of routine maintenance on frequency of facility deficiencies was quantified using 3141 records of maintenance and inspection data from Fairfax County, VA. Sediment and debris accumulation were found to be the most common deficiency highlighting the importance of good housekeeping and pretreatment devices. The Northern Virginia Soil and Water Conservation District (NVSWCD) performed a comprehensive review of 63 bioretention facilities in which they inspected elements considered critical to pollutant removal performance including ponding depth, filter media depth, and infiltration rates. By comparing the findings from the NVSWCD to current post-construction inspections performed by the County, it was found that current inspection protocols are missing important design components of bioretention facilities. This study also highlights the importance of thorough and thoughtful databases to track and record inspection and maintenance data surrounding GSI. The proper construction and maintenance of GSI is ultimately dependent on a multitude of factors including site-conditions, facility design specifications, and institutional support.

Dans le contexte économique et compétitif actuel, ce qui permet aux entreprises de se distinguer c'est leur réactivité à fournir des produits de plus en plus complexes sen répondant à des besoins toujours plus diversifiés. Pour faire face à cette exigence de réactivité et malgré ces contraintes, les approches d'ingénierie intégrée sont apparues pour une meilleure gestion du cycle de vie des produits. Dans ce contexte la prise en compte des variabilités et leurs interdépendances a été démontrée comme étant indispensable à l'amélioration des performances (coût, risque, qualité, …). Ce travail de thèse est consacré à l'élaboration d'un plan d'inspection optimal pour : la maîtrise de ces variabilités et leurs effets sur le comportement du produit, l'usage et les fonctionnalités de celui-ci. Pour cela un cadre méthodologique pour la co-conception des activités de contrôles de conformités et celles de suivi de fabrication a été formalisé. Ce cadre permet une prise de décision opérationnelle grâce à l'utilisation des outils opérationnels et assure la satisfaction des objectifs stratégiques (réduction des coûts, amélioration de la qualité, augmentation de la productivité, …). Suite à une synthèse approfondie de la littérature relative à la planification la qualité et de l'amélioration (conjointe) de la performance, les outils AMDEC, KC flowdown, et Activity Based Costing (ABC) ont été retenus. Cependant ces outils présentent certains manques à combler et ont fait donc l'objet de certaines modifications (adaptations) pour convenir au mieux aux besoins du cadre méthodologique proposé. L'intégration d'AMDEC et de KC flowdown a abouti à un nouvel outil nommé ACDE (Analyse de la Causalité, des Défaillances, et leurs Effets). Ainsi l'adaptation d'ABC à l'estimation de coût de la qualité par « Quality-Driven ABC » a été proposée. L'application de ces derniers a été proposée dans le cadre de la planification d'inspection « au juste nécessaire ». / In the current economic and competitive environment, what distinguish the companies is their reactivity to provide increasingly complex products with increasingly diverse needs. To achieve this reactivity despite constraints, integrated engineering approachs have been emerged to better manage and organize the product life cycle. In this context, it is essential to take into account the characteristics' variations and their interdependencies to improve the performance (cost, risk, quality ...). This thesis was devoted to the generation of an optimal inspection plan including process variations monitoring and product variations control. A methodological framework for the co-conception of product control and process monitoring activities has been formalized and validated. This framework allows operational decision-making by the intervention of operational tools and ensures the satisfaction of strategic objectives (cost reduction, improved quality, increased productivity ...). FMEA, KC flowdown, and Activity Based Costing (ABC) were selected following a comprehensive literature review on quality planning and performance improvement. However, these tools present some lack to fill up and therefore are subjected to certain adaptations in order to best fit the needs of the proposed methodological framework. Integration of FMEA and KC flowdown resulted in a new tool called ACDE. As well the adaptation of ABC to estimate the cost of quality by "Quality-Driven ABC" was proposed. The application of these latter has been proposed to limit the inspection planning to “bare essentials activities.

Most existing structural health monitoring (SHM) techniques are based on measured acceleration data. Such practice, however, is highly expensive to operate, mainly due to cumbersome, time-consuming and expensive installation of sensors and their data acquisition systems. As an emerging noncontact method, the vision-based displacement sensor systems have attracted significant research interests and offered a promising alternative to the conventional sensors for SHM. However, most existing vision-based sensors require physical access to the structure to install a predesigned target panel, which has a higher contrast and thus is easier to track. Besides, most studies are carried out in controlled laboratory environments. The accuracy and robustness of vision sensors in the outdoor field conditions have not been fully investigated. It is also noted that current researches are mainly focusing on the measurement performance evaluation of vision sensors, without discussing the use of the measured displacement data for SHM. This dissertation develops a high-precision vision sensor system for remote and real-time measurement of multipoint structural displacements by tracking natural targets on structural surfaces. Two sets of software packages are developed respectively based on two advanced template matching algorithms (i.e., the upsampled cross correlation and the orientation code matching) incorporated with different subpixel techniques. Comprehensive experiments, including laboratory shaking table tests and field bridge tests, are carried out to evaluate its performance. Satisfactory agreements are observed between the displacements measured by the proposed vision sensor and those measured by high-performance reference displacement sensors. Moreover, this study examines the robustness of the vision sensor against ill environmental conditions such as dim light, background image disturbance and partial template occlusion. This dissertation further explores the potentials of the vision sensor for fast and inexpensive SHM applications, by demonstrating the usefulness of the displacement data for experimental modal analysis, finite element (FE) model updating, damage detection, etc. For a three-story frame structure, the modal analysis shows that the obtained natural frequencies and mode shapes from displacement measurements by using one camera match well with those by using four accelerometers. In fact, the vision sensor can achieve smoother mode shapes which would make damage localization more accurate, while the resolution of mode shapes from accelerometers is limited by the sensor number. This has been demonstrated from the damage detection result of beam structures based on the mode shape curvature (MSC) index. To address the needs for monitoring aging railway and highway bridges, coupled train-track-bridge and vehicle-bridge FE models are firstly developed to study the dynamic interactions between bridges and moving trains/vehicles. Subsequently, a time-domain model updating approach for railway bridges is proposed based on the in-situ measurement of the bridges’ dynamic displacement histories by the proposed vision sensor. This dissertation further proposes a bridge damage detection procedure that utilizes vehicle-induced displacement response and the MSC index without requiring prior knowledge about the traffic excitation.

Manufacturing industries are facing major challenges in terms of improving product quality and increasing throughput while sustaining production costs to acceptable levels. Product-oriented processes, both legacy and new, are poorly monitored and controlled on the basis of distributed loop controllers that are aiming to maintain critical process variables within acceptable bounds. Thus, poor quality product results when such processes are subjected to large disturbances - operational failures, environmental changes, and changes in loading conditions. In this research, product quality modeling and control based on a vision inspection methodology is proposed to improve product quality and increase productivity. The main contributions of this research are twofold. First, this research introduces a product quality modeling methodology that combines both physical-based modeling and data-driven modeling. The quality model is the link between information coming from the inspection of product features and the specification of process control strategies. It is essential to control and optimize the process. Physical-based modeling is used to model the product temperature profile, and data-driven modeling is used to train the mapping from the product temperature profile to each quality metric. The break down of the sub models increase the flexibility of model development and reduce the effort to change the model when the quality metrics change. The second contribution is the development of a novel approach to control product quality based on vision inspection, which is developed as part of a hybrid, hierarchical architecture. The high-level control module involves scheduling of multiple plant processes, diagnostics of the failure condition in the process, and the supervision of the whole process. The mid-level control module, which is the focus of the work presented here, takes advantage of baking product quality indicators and oven parameter measurements to optimize zone temperature and conveyor speed set points so that the best product quality is achieved even in the presence of disturbances. The low-level control module consists of basic control loops. Each of them controls parameters of each operation in the process separately. They are generally simple and easy to implement.