Aerodynamics and air quality management of highway tunnels : R. N. Schlaug, T. J. Carlin.

Mode of access: Internet.

Relationships between land-use and chemical quality of Illinois streams /

Cover title.

Environmental characteristics and water quality of hydrologic benchmark network stations in the eastern United States, 1963-95 /

Mode of access: Internet.

Environmental characteristics and water quality of hydrologic benchmark network stations in the midwestern United States, 1963-95 /

Mode of access: Internet.

Market-level information and the diffusion of competing technologies:an exploratory analysis of the LAN industry

Market-level information diffused by print media may contribute to the legitimation of an emerging technology and thus influence the diffusion of competing technological standards. After analyzing more than 10,000 trade media abstracts from the Local Area Networks (LAN) industry published between 1981 and 2000, we found the presence of differential effects on the adoption of competing standards by two market-level information types: technology and product availability. The significance of these effects depends on the technology's order of entry and suggests that high-tech product managers should make strategic use of market-level information by appropriately focusing the content of their communications. © 2007 Elsevier B.V. All rights reserved.

Decision-making in product quality based on failure knowledge

Decision-making in product quality is an indispensable stage in product development, in order to reduce product development risk. Based on the identification of the deficiencies of quality function deployment (QFD) and failure modes and effects analysis (FMEA), a novel decision-making method is presented that draws upon a knowledge network of failure scenarios. An ontological expression of failure scenarios is presented together with a framework of failure knowledge network (FKN). According to the roles of quality characteristics (QCs) in failure processing, QCs are set into three categories namely perceptible QCs, restrictive QCs, and controllable QCs, which present the monitor targets, control targets and improvement targets respectively for quality management. A mathematical model and algorithms based on the analytic network process (ANP) is introduced for calculating the priority of QCs with respect to different development scenarios. A case study is provided according to the proposed decision-making procedure based on FKN. This methodology is applied in the propeller design process to solve the problem of prioritising QCs. This paper provides a practical approach for decision-making in product quality. Copyright © 2011 Inderscience Enterprises Ltd.

Learning user and product distributed representations using a sequence model for sentiment analysis

In product reviews, it is observed that the distribution of polarity ratings over reviews written by different users or evaluated based on different products are often skewed in the real world. As such, incorporating user and product information would be helpful for the task of sentiment classification of reviews. However, existing approaches ignored the temporal nature of reviews posted by the same user or evaluated on the same product. We argue that the temporal relations of reviews might be potentially useful for learning user and product embedding and thus propose employing a sequence model to embed these temporal relations into user and product representations so as to improve the performance of document-level sentiment analysis. Specifically, we first learn a distributed representation of each review by a one-dimensional convolutional neural network. Then, taking these representations as pretrained vectors, we use a recurrent neural network with gated recurrent units to learn distributed representations of users and products. Finally, we feed the user, product and review representations into a machine learning classifier for sentiment classification. Our approach has been evaluated on three large-scale review datasets from the IMDB and Yelp. Experimental results show that: (1) sequence modeling for the purposes of distributed user and product representation learning can improve the performance of document-level sentiment classification; (2) the proposed approach achieves state-of-The-Art results on these benchmark datasets.

Why (and When) are Preferences Convex? Threshold Effects and Uncertain Quality

It is often assumed (for analytical convenience, but also in accordance with common intuition) that consumer preferences are convex. In this paper, we consider circumstances under which such preferences are (or are not) optimal. In particular, we investigate a setting in which goods possess some hidden quality with known distribution, and the consumer chooses a bundle of goods that maximizes the probability that he receives some threshold level of this quality. We show that if the threshold is small relative to consumption levels, preferences will tend to be convex; whereas the opposite holds if the threshold is large. Our theory helps explain a broad spectrum of economic behavior (including, in particular, certain common commercial advertising strategies), suggesting that sensitivity to information about thresholds is deeply rooted in human psychology.

Reciprocally Exclusive Contracts and Endogenous Quality

Our paper investigates exclusive dealing and purchasing in successive duopolies. First we show that using a limited set of feasible contracts, exclusive dealing and purchasing is going to be preferred, regardless of the level of product differentiation. In the next step, we make the choice of quality endogenous and derive the equilibrium conditions for qualities under the aforementioned contractual arrangement. Our final proposition shows that in this case the choice of quality depends exclusively on the valuation of the median consumer.

Prospective Estimation of Radiation Dose and Image Quality for Optimized CT Performance

X-ray computed tomography (CT) is a non-invasive medical imaging technique that generates cross-sectional images by acquiring attenuation-based projection measurements at multiple angles. Since its first introduction in the 1970s, substantial technical improvements have led to the expanding use of CT in clinical examinations. CT has become an indispensable imaging modality for the diagnosis of a wide array of diseases in both pediatric and adult populations [1, 2]. Currently, approximately 272 million CT examinations are performed annually worldwide, with nearly 85 million of these in the United States alone [3]. Although this trend has decelerated in recent years, CT usage is still expected to increase mainly due to advanced technologies such as multi-energy [4], photon counting [5], and cone-beam CT [6].

Despite the significant clinical benefits, concerns have been raised regarding the population-based radiation dose associated with CT examinations [7]. From 1980 to 2006, the effective dose from medical diagnostic procedures rose six-fold, with CT contributing to almost half of the total dose from medical exposure [8]. For each patient, the risk associated with a single CT examination is likely to be minimal. However, the relatively large population-based radiation level has led to enormous efforts among the community to manage and optimize the CT dose.

As promoted by the international campaigns Image Gently and Image Wisely, exposure to CT radiation should be appropriate and safe [9, 10]. It is thus a responsibility to optimize the amount of radiation dose for CT examinations. The key for dose optimization is to determine the minimum amount of radiation dose that achieves the targeted image quality [11]. Based on such principle, dose optimization would significantly benefit from effective metrics to characterize radiation dose and image quality for a CT exam. Moreover, if accurate predictions of the radiation dose and image quality were possible before the initiation of the exam, it would be feasible to personalize it by adjusting the scanning parameters to achieve a desired level of image quality. The purpose of this thesis is to design and validate models to quantify patient-specific radiation dose prospectively and task-based image quality. The dual aim of the study is to implement the theoretical models into clinical practice by developing an organ-based dose monitoring system and an image-based noise addition software for protocol optimization.

More specifically, Chapter 3 aims to develop an organ dose-prediction method for CT examinations of the body under constant tube current condition. The study effectively modeled the anatomical diversity and complexity using a large number of patient models with representative age, size, and gender distribution. The dependence of organ dose coefficients on patient size and scanner models was further evaluated. Distinct from prior work, these studies use the largest number of patient models to date with representative age, weight percentile, and body mass index (BMI) range.

With effective quantification of organ dose under constant tube current condition, Chapter 4 aims to extend the organ dose prediction system to tube current modulated (TCM) CT examinations. The prediction, applied to chest and abdominopelvic exams, was achieved by combining a convolution-based estimation technique that quantifies the radiation field, a TCM scheme that emulates modulation profiles from major CT vendors, and a library of computational phantoms with representative sizes, ages, and genders. The prospective quantification model is validated by comparing the predicted organ dose with the dose estimated based on Monte Carlo simulations with TCM function explicitly modeled.

Chapter 5 aims to implement the organ dose-estimation framework in clinical practice to develop an organ dose-monitoring program based on a commercial software (Dose Watch, GE Healthcare, Waukesha, WI). In the first phase of the study we focused on body CT examinations, and so the patient’s major body landmark information was extracted from the patient scout image in order to match clinical patients against a computational phantom in the library. The organ dose coefficients were estimated based on CT protocol and patient size as reported in Chapter 3. The exam CTDIvol, DLP, and TCM profiles were extracted and used to quantify the radiation field using the convolution technique proposed in Chapter 4.

With effective methods to predict and monitor organ dose, Chapters 6 aims to develop and validate improved measurement techniques for image quality assessment. Chapter 6 outlines the method that was developed to assess and predict quantum noise in clinical body CT images. Compared with previous phantom-based studies, this study accurately assessed the quantum noise in clinical images and further validated the correspondence between phantom-based measurements and the expected clinical image quality as a function of patient size and scanner attributes.

Chapter 7 aims to develop a practical strategy to generate hybrid CT images and assess the impact of dose reduction on diagnostic confidence for the diagnosis of acute pancreatitis. The general strategy is (1) to simulate synthetic CT images at multiple reduced-dose levels from clinical datasets using an image-based noise addition technique; (2) to develop quantitative and observer-based methods to validate the realism of simulated low-dose images; (3) to perform multi-reader observer studies on the low-dose image series to assess the impact of dose reduction on the diagnostic confidence for multiple diagnostic tasks; and (4) to determine the dose operating point for clinical CT examinations based on the minimum diagnostic performance to achieve protocol optimization.

Chapter 8 concludes the thesis with a summary of accomplished work and a discussion about future research.

Adult orthodontics: internet information and a national survey

Aims: 1. To investigate the reliability and readability of information on the Internet on adult orthodontics. 2. To evaluate the profile and treatment of adults by specialist orthodontists in the Republic of Ireland (ROI). Materials and methods: 1. An Internet search was conducted in May 2015 using three search engines (Google, Yahoo and Bing), with two search terms (“adult orthodontics” and “adult braces”). The first 50 websites from each engine were screened and exclusion criteria applied. Included websites were then assessed for reliability using the JAMA benchmarks, the DISCERN and LIDA tools and the presence of the HON seal. Readability was assessed using the FRES. 2. A pilot-tested questionnaire about adult orthodontics was distributed to 122 eligible specialist orthodontists in the ROI. Questions addressed general and treatment information about adult orthodontic patients, methods of information provision and respondent demographics. Results: 1. Thirteen websites met the inclusion criteria. Three websites contained all JAMA benchmarks and one displayed the HON Seal. The mean overall score for DISCERN was 3.9/5 and the mean total LIDA score was 115/120. The average FRES score was 63.1. 2. The questionnaire yielded a response rate of 83%. The typical demographic profile of adult orthodontic patients was professional females between 25-35 years. The most common incisor relationship and skeletal base was Class II, division 1 (51%) and Class II (61%) respectively. Aesthetic upper brackets and metal lower brackets were the most frequently used appliances. Only 30% of orthodontists advise their adult patients to find extra information on the Internet. Conclusions: 1. The reliability and readability of information on the Internet on adult orthodontics is of moderate quality. 2. The provision of adult orthodontic treatment is common among specialist orthodontists in the Republic of Ireland.

Performance Information and Innovation in the Canadian Government (Working Paper 43)

The presentation made at the conference addressed the issue of linkages between performance information and innovation within the Canadian federal government1. This is a three‐part paper prepared as background to that presentation. • Part I provides an overview of three main sources of performance information - results-based systems, program evaluation, and centrally driven review exercises – and reviews the Canadian experience with them. • Part II identifies and discusses a number of innovation issues that are common to the literature reviewed for this paper. • Part III examines actual and potential linkages between innovation and performance information. This section suggests that innovation in the Canadian federal government tends to cluster into two groups: smaller initiatives driven by staff or middle management; and much larger projects involving major programs, whole departments or whole-of-government. Readily available data on smaller innovation projects is skimpy but suggests that performance information does not play a major role in stimulating these initiatives. In contrast, two of the examples of large-scale innovation show that performance information plays a critical role at all stages. The paper concludes by supporting the contention of others writing on this topic: that more research is needed on innovation, particularly on its link to performance information. In that context, other conclusions drawn in this paper are tentative but suggest that the quality of performance information is as important for innovation as it is for performance management. However, innovation is likely to require its own particular performance information that may not be generated on a routine basis for purposes of performance management, particularly in the early stages of innovation. And, while the availability of performance information can be an important success factor in innovation, it does not stand alone. The commonality of a number of other factors identified in the literature surveyed for this paper strongly suggests that equal if not greater priority needs to be given to attenuating factors that inhibit innovation and to nurturing incentives.

Extracting Patterns from Educational Traces via Clustering and Associated Quality Metrics

Clustering algorithms, pattern mining techniques and associated quality metrics emerged as reliable methods for modeling learners’ performance, comprehension and interaction in given educational scenarios. The specificity of available data such as missing values, extreme values or outliers, creates a challenge to extract significant user models from an educational perspective. In this paper we introduce a pattern detection mechanism with-in our data analytics tool based on k-means clustering and on SSE, silhouette, Dunn index and Xi-Beni index quality metrics. Experiments performed on a dataset obtained from our online e-learning platform show that the extracted interaction patterns were representative in classifying learners. Furthermore, the performed monitoring activities created a strong basis for generating automatic feedback to learners in terms of their course participation, while relying on their previous performance. In addition, our analysis introduces automatic triggers that highlight learners who will potentially fail the course, enabling tutors to take timely actions.

Aplicação da metodologia Advanced Product Quality Planning no desenvolvimento de um novo produto no setor automóvel

Este projeto surgiu com a necessidade da constituição de uma equipa multidisciplinar, incluindo uma pessoa responsável pela qualidade no desenvolvimento de um novo produto da fábrica. O produto é a estrutura metálica de um encosto de trás de um automóvel. Para o desenvolvimento do produto foi usado o método Advanced Product Quality Planning, vastamente utilizado no setor automóvel. Com o intuito de melhor perceber os problemas que podem surgir no novo produto foi estudado um produto fabricado no local de estágio e outro produzido numa outra fábrica do mesmo grupo, que têm algumas semelhanças a nível de processo e de design, respetivamente. Foram utilizadas algumas ferramentas da qualidade para explorar os problemas existentes na fábrica a nível do produto já existente e comprovado se algumas ações de melhoria propostas foram, ou não, bem-sucedidas. Com os outputs retirados da análise dos defeitos internos e externos foi elaborado o Plano de Controlo, que inclui a listagem de controlos necessários para se conseguir prever a qualidade do novo produto.