944 resultados para Quality attributes


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Chemical engineering education is challenged around the world by demands and rapid changes encompassing a wide range of technical and social drivers. Graduates must be prepared for practice in increasingly diverse workplace environments in which generic or transferable attributes such as communication and teamwork together with technical excellence are mandated by prospective employers and society at large. If academe is to successfully deliver on these graduate attributes, effective curriculum design needs to include appropriate educational processes as well as course content. Conventional teacher centred approaches, stand-alone courses and retro-fitted remedial modules have not delivered the desired outcomes. Development of the broader spectrum of attributes is more likely when students are engaged with realistic and relevant experiences that demand the integration and practice of these attributes in contexts that the students find meaningful. This paper describes and evaluates The University of Queensland's Project Centred Curriculum in Chemical Engineering (PCC), a programme-wide approach to meeting these requirements. PCC strategically integrates project-based learning with more traditional instruction. Data collected shows improved levels of student attainment of generic skills with institutional and nationally benchmarked indicators showing significant increases in student perceptions of teaching quality, and overall satisfaction with the undergraduate experience. Endorsements from Australian academic, professional and industry bodies also support the approach as more effectively aligning engineering education with professional practice requirements.

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Developing economies offer tremendous potential for future growth and organizations appreciating these consumers’ requirements stand to reap considerable returns. However, compared with more developed economies published consumer studies are few. In particular, there is a dearth of service quality research and hardly any from Africa. Furthermore, the little available research tends to apply Western methodologies, which may not be entirely appropriate. This research investigates East African consumer perceptions of retail banking using an approach that takes account of the research context. Qualitative research was undertaken to define the relevant service attributes. Performance along these was then investigated through a survey with over 2000 respondents. Principal component analysis identifies 13 core service dimensions and multinomial logistic regression reveals which are the key drivers of customer satisfaction. Comparison of the results with studies from other regions confirms that established standardized research instruments are likely to miss or under-represent service attributes important in developing countries.

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This dissertation examines the effect of regulations, resource and referral agencies, and subsidies on price and quality of care in child care centers. This research is based on a carefully developed conceptual framework that incorporates the factors affecting the demand and supply of child care. The first step in developing this framework is sketching out the structural equations. The structural equations help us understand the underlying behavior of individuals and firms making a decision. The exogenous variables are vector of attributes relating to family characteristics, child characteristics, regulations, subsidy, community characteristics and prices of inputs. Based on the structural equations, reduced form equations are estimated to find the effect of each of the exogenous variables on each of the endogenous variables. Reduced form equations help us answer public policy questions. The sample for this study is from the 1990 Profile of Child Care Settings (PCCS) data in which 2,089 center based programs were interviewed.^ Child/Staff Ratio (Group Level). Results indicate that among subsidies, only the state subsidy per child in poverty has a significant effect on the child/staff ratio at the group level. Presence of resource and referral agencies also increase the child/staff ratio at the group level. Also when the maximum center group size regulation for 25-36 months becomes more stringent, the child/staff ratio at the group level decreases.^ Child/Staff Ratio (Center Level). When the regulations for the maximum child/staff ratio for age groups 13-24 months and 37-60 months become lax, the child/staff ratio for the center increases. As the regulation for maximum group size for infants becomes stringent, the child/staff ratio decreases. An interesting finding is that as the regulations for maximum group size for age groups 13-24 months and 25-36 months become stringent, the child/staff ratio for the center increases. Another significant finding is that when a center is located in a rural area the child/staff ratio is significantly lower.^ Center Weighted Average Hourly Fees. Maximum group size regulations for age groups 25-36 months and 37-60 months have a negative effect on center hourly fee. Maximum child staff regulations for age groups 13-24 months and 37-60 months have a negative effect on center hourly fee. Maximum child staff regulations for age groups 0-12 months and 25-36 months have a positive effect on center hourly fee. Findings also indicate that the center average hourly price is lower when there is a resource and referral agency present. Cost adjusted prekindergarten funds and JOBS child care subsidies have a negative effect on average hourly fee. Cost adjusted social services block grant and state subsidy per child in poverty have a positive effect on the average hourly price. A major finding of this dissertation is the interaction of subsidy and regulatory variables.^ Another major finding is that child/staff ratio at the group level is lower when there is an interaction between geographic location and nature of center sponsorship. ^

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Voice communication systems such as Voice-over IP (VoIP), Public Switched Telephone Networks, and Mobile Telephone Networks, are an integral means of human tele-interaction. These systems pose distinctive challenges due to their unique characteristics such as low volume, burstiness and stringent delay/loss requirements across heterogeneous underlying network technologies. Effective quality evaluation methodologies are important for system development and refinement, particularly by adopting user feedback based measurement. Presently, most of the evaluation models are system-centric (Quality of Service or QoS-based), which questioned us to explore a user-centric (Quality of Experience or QoE-based) approach as a step towards the human-centric paradigm of system design. We research an affect-based QoE evaluation framework which attempts to capture users' perception while they are engaged in voice communication. Our modular approach consists of feature extraction from multiple information sources including various affective cues and different classification procedures such as Support Vector Machines (SVM) and k-Nearest Neighbor (kNN). The experimental study is illustrated in depth with detailed analysis of results. The evidences collected provide the potential feasibility of our approach for QoE evaluation and suggest the consideration of human affective attributes in modeling user experience.

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The current study looks at the relationship between servicescape, emotional product involvement, perceived quality of local foods, the positive emotion of pleasure, and revisit intention in an upscale buffet style restaurant on a university campus in the Southeastern U.S. Test results show positive relationships between all of the constructs in the proposed conceptual model. The study also gives practitioners and academics insights into practices that can help to market the use of local foods through the restaurant environment in order to engage emotionally involved customers. This marketing can illicit pleasurable feelings and increase perceived product quality of local foods with the purpose of getting customers to revisit the restaurant. Suggestions for further research on the subject are proposed.

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This dissertation examines the effect of regulations, resource and referral agencies, and subsidies on price and quality of care in child care centers. This research is based on a carefully developed conceptual framework that incorporates the factors affecting the demand and supply of child care. The first step in developing this framework is sketching out the structural equations. The structural equations help us understand the underlying behavior of individuals and firms making a decision. The exogenous variables are vector of attributes relating to family characteristics, child characteristics, regulations, subsidy, community characteristics and prices of inputs. Based on the structural equations, reduced form equations are estimated to find the effect of each of the exogenous variables on each of the endogenous variables. Reduced form equations help us answer public policy questions. The sample for this study is from the 1990 Profile of Child Care Settings (PCCS) data in which 2,089 center based programs were interviewed. Child/Staff Ratio (Group Level): Results indicate that among subsidies, only the state subsidy per child in poverty has a significant effect on the child/staff ratio at the group level. Presence of resource and referral agencies also increase the child/staff ratio at the group level. Also when the maximum center group size regulation for 25-36 months becomes more stringent, the child/staff ratio at the group level decreases. Child/Staff Ratio (Center Level): When the regulations for the maximum child/staff ratio for age groups 13-24 months and 37-60 months become lax, the child/staff ratio for the center increases. As the regulation for maximum group size for infants becomes stringent, the child/staff ratio decreases. An interesting finding is that as the regulations for maximum group size for age groups 13-24 months and 25-36 months become stringent, the child/staff ratio for the center increases. Another significant finding is that when a center is located in a rural area the child/staff ratio is significantly lower. Center Weighted Average Hourly Fees: Maximum group size regulations for age groups 25-36 months and 37-60 months have a negative effect on center hourly fee. Maximum child staff regulations for age groups 13-24 months and 37-60 months have a negative effect on center hourly fee. Maximum child staff regulations for age groups 0-12 months and 25-36 months have a positive effect on center hourly fee. Findings also indicate that the center average hourly price is lower when there is a resource and referral agency present. Cost adjusted prekindergarten funds and JOBS child care subsidies have a negative effect on average hourly fee. Cost adjusted social services block grant and state subsidy per child in poverty have a positive effect on the average hourly price. A major finding of this dissertation is the interaction of subsidy and regulatory variables. Another major finding is that child/staff ratio at the group level is lower when there is an interaction between geographic location and nature of center sponsorship.

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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.

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The extractive industry is characterized by high levels of risk and uncertainty. These attributes create challenges when applying traditional accounting concepts (such as the revenue recognition and matching concepts) to the preparation of financial statements in the industry. The International Accounting Standards Board (2010) states that the objective of general purpose financial statements is to provide useful financial information to assist the capital allocation decisions of existing and potential providers of capital. The usefulness of information is defined as being relevant and faithfully represented so as to best aid in the investment decisions of capital providers. Value relevance research utilizes adaptations of the Ohlson (1995) to assess the attribute of value relevance which is one part of the attributes resulting in useful information. This study firstly examines the value relevance of the financial information disclosed in the financial reports of extractive firms. The findings reveal that the value relevance of information disclosed in the financial reports depends on the circumstances of the firm including sector, size and profitability. Traditional accounting concepts such as the matching concept can be ineffective when applied to small firms who are primarily engaged in nonproduction activities that involve significant levels of uncertainty such as exploration activities or the development of sites. Standard setting bodies such as the International Accounting Standards Board and the Financial Accounting Standards Board have addressed the financial reporting challenges in the extractive industry by allowing a significant amount of accounting flexibility in industryspecific accounting standards, particularly in relation to the accounting treatment of exploration and evaluation expenditure. Therefore, secondly this study examines whether the choice of exploration accounting policy has an effect on the value relevance of information disclosed in the financial reports. The findings show that, in general, the Successful Efforts method produces value relevant information in the financial reports of profitable extractive firms. However, specifically in the oil & gas sector, the Full Cost method produces value relevant asset disclosures if the firm is lossmaking. This indicates that investors in production and non-production orientated firms have different information needs and these needs cannot be simultaneously fulfilled by a single accounting policy. In the mining sector, a preference by large profitable mining companies towards a more conservative policy than either the Full Cost or Successful Efforts methods does not result in more value relevant information being disclosed in the financial reports. This finding supports the fact that the qualitative characteristic of prudence is a form of bias which has a downward effect on asset values. The third aspect of this study is an examination of the effect of corporate governance on the value relevance of disclosures made in the financial reports of extractive firms. The findings show that the key factor influencing the value relevance of financial information is the ability of the directors to select accounting policies which reflect the economic substance of the particular circumstances facing the firms in an effective way. Corporate governance is found to have an effect on value relevance, particularly in the oil & gas sector. However, there is no significant difference between the exploration accounting policy choices made by directors of firms with good systems of corporate governance and those with weak systems of corporate governance.

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Postharvest disease management is one of the key challenges in commercial mango supply chains. Comprehensive investigations were made regarding the impact of geographic locality on postharvest disease development and other quality parameters in 'Sindhri' and 'Samar Bahisht (S.B.) Chaunsa' mangoes under ambient (33±1°C; 55-60% RH) and low temperature storage/simulated shipping (12±1°C; 80- 85% RH) conditions (28 or 35 days storage for 'Sindhri' and 21 or 28 days for 'S.B. Chaunsa'). Physiologically mature (days from fruit set were 95-100 and 110-115 for 'Sindhri' and 'S.B Chaunsa', respectively) 'Sindhri' and 'S.B. Chaunsa' fruits were harvested from five geographic localities and subjected to ambient and simulated shipping conditions. Under ambient conditions, no disease incidence was observed till fruit eating stage in 'Sindhri'. However, in 'S.B. Chaunsa', significant variation in different localities was observed with respect to disease incidence. Maximum and at par disease was exhibited by the fruit collected from district Vehari and Khanewal in 'S.B. Chaunsa'. Under simulated shipping conditions, disease development varied significantly with respect to different locations and storage durations. In 'Sindhri', fruit of M. Garh, while, 'S.B. Chaunsa' fruit of districts R.Y. Khan, M. Garh and Khanewal showed higher disease incidence. Fruit peel colour development was significantly reduced as storage days increased. Fruit firmness, skin shriveling, fresh weight loss, dry matter, biochemical and organoleptic attributes also varied significantly among the fruit sourced from different orchards of different localities. Analysis of N contents in leaves and fruit peel revealed that N contents of leaf and peel were positively correlated with disease severity in mango. Botryodiplodia spp., Phomopsis mangiferae, Alternaria alternata, Colletotrichum gloeosporioides were the pathogens isolated from fruits of all locations; however, the prevalence frequency varied with the geographic localities. In conclusion, the production locality, cultivar and nutrition (nitrogen content of fruit peel) had significant effect on fruit quality out-turn at ripe stage in terms of disease development so area specific disease management system needs to be implemented for better quality at retail.

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This dissertation research points out major challenging problems with current Knowledge Organization (KO) systems, such as subject gateways or web directories: (1) the current systems use traditional knowledge organization systems based on controlled vocabulary which is not very well suited to web resources, and (2) information is organized by professionals not by users, which means it does not reflect intuitively and instantaneously expressed users’ current needs. In order to explore users’ needs, I examined social tags which are user-generated uncontrolled vocabulary. As investment in professionally-developed subject gateways and web directories diminishes (support for both BUBL and Intute, examined in this study, is being discontinued), understanding characteristics of social tagging becomes even more critical. Several researchers have discussed social tagging behavior and its usefulness for classification or retrieval; however, further research is needed to qualitatively and quantitatively investigate social tagging in order to verify its quality and benefit. This research particularly examined the indexing consistency of social tagging in comparison to professional indexing to examine the quality and efficacy of tagging. The data analysis was divided into three phases: analysis of indexing consistency, analysis of tagging effectiveness, and analysis of tag attributes. Most indexing consistency studies have been conducted with a small number of professional indexers, and they tended to exclude users. Furthermore, the studies mainly have focused on physical library collections. This dissertation research bridged these gaps by (1) extending the scope of resources to various web documents indexed by users and (2) employing the Information Retrieval (IR) Vector Space Model (VSM) - based indexing consistency method since it is suitable for dealing with a large number of indexers. As a second phase, an analysis of tagging effectiveness with tagging exhaustivity and tag specificity was conducted to ameliorate the drawbacks of consistency analysis based on only the quantitative measures of vocabulary matching. Finally, to investigate tagging pattern and behaviors, a content analysis on tag attributes was conducted based on the FRBR model. The findings revealed that there was greater consistency over all subjects among taggers compared to that for two groups of professionals. The analysis of tagging exhaustivity and tag specificity in relation to tagging effectiveness was conducted to ameliorate difficulties associated with limitations in the analysis of indexing consistency based on only the quantitative measures of vocabulary matching. Examination of exhaustivity and specificity of social tags provided insights into particular characteristics of tagging behavior and its variation across subjects. To further investigate the quality of tags, a Latent Semantic Analysis (LSA) was conducted to determine to what extent tags are conceptually related to professionals’ keywords and it was found that tags of higher specificity tended to have a higher semantic relatedness to professionals’ keywords. This leads to the conclusion that the term’s power as a differentiator is related to its semantic relatedness to documents. The findings on tag attributes identified the important bibliographic attributes of tags beyond describing subjects or topics of a document. The findings also showed that tags have essential attributes matching those defined in FRBR. Furthermore, in terms of specific subject areas, the findings originally identified that taggers exhibited different tagging behaviors representing distinctive features and tendencies on web documents characterizing digital heterogeneous media resources. These results have led to the conclusion that there should be an increased awareness of diverse user needs by subject in order to improve metadata in practical applications. This dissertation research is the first necessary step to utilize social tagging in digital information organization by verifying the quality and efficacy of social tagging. This dissertation research combined both quantitative (statistics) and qualitative (content analysis using FRBR) approaches to vocabulary analysis of tags which provided a more complete examination of the quality of tags. Through the detailed analysis of tag properties undertaken in this dissertation, we have a clearer understanding of the extent to which social tagging can be used to replace (and in some cases to improve upon) professional indexing.

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This design thesis is an inquiry of the highly industrialized urban landscape of the Lake Calumet Complex on the South Side of the City of Chicago. It examines geologic and anthropogenic strata within this region as waste used for staging various social, industrial, and ecological systems. Today, these social, industrial, and ecological systems are not responsive to each other and certainly do not possess resilient attributes that would allow them to interact within the landscape in perpetuity. The resulting design strategy seeks to re-think the treatment of waste in the landscape into a new framework for future park design. This park will serve as grounds to interweave these complex systems in order to rehabilitate ecosystem functions and improve water quality. Additionally the park hybridizes many social and ecological functions to improve community recreational opportunities and gain public acceptance and appeal.

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Tomato ( Lycopersicon esculentum Mill) is the leading vegetable in terms of production in Kenya. The Kenyan local market has a wide variety of tomato cultivars with a wide range of morphological and sensorial characteristics. However, information on the nutritional and postharvest quality of these varieties is lacking. The aim of this research was to investigate and identify tomato varieties of superior postharvest quality and recommend them to small and medium scale farmers. In this study, six tomato varieties were grown in a greenhouse and analyzed at three maturity stages (mature green, turning and red ripe). The tomatoes were analyzed at specific days after harvest and storage at room temperature (25o C). Percentage weight loss, color, respiration and ethylene production rates were analyzed to assess the postharvest quality of the tomatoes. The color was measured using a Minolta Chromameter while the respiration rate and ethylene production rates were determined using the static system approach. Color, weight loss, respiration and ethylene production rates were positively affected by storage time when harvested at the three maturity stages. The percentage weight loss of the tomato fruits was higher in the determinate varieties, and at the turning stage of maturity (3.8 %). Minor color changes were observed after storage of the tomatoes harvested at red stage for six days. Both rates of respiration and ethylene production were low, with the respiration rate ranging between 56-10 ml CO2 Kg-1h-1. The Chonto F1 variety had the highest rate of ethylene production (5.4 μL C2H4 Kg-1h-1) on the 4th day of storage after harvest at the red ripe stage. Overall, the indeterminate tomato varieties displayed better postharvest quality that can prolong the fruits shelf life for marketing. In turn, the turning stage of maturity proved to be a better stage to harvest tomatoes as the color development was more uniform.

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Credible spatial information characterizing the structure and site quality of forests is critical to sustainable forest management and planning, especially given the increasing demands and threats to forest products and services. Forest managers and planners are required to evaluate forest conditions over a broad range of scales, contingent on operational or reporting requirements. Traditionally, forest inventory estimates are generated via a design-based approach that involves generalizing sample plot measurements to characterize an unknown population across a larger area of interest. However, field plot measurements are costly and as a consequence spatial coverage is limited. Remote sensing technologies have shown remarkable success in augmenting limited sample plot data to generate stand- and landscape-level spatial predictions of forest inventory attributes. Further enhancement of forest inventory approaches that couple field measurements with cutting edge remotely sensed and geospatial datasets are essential to sustainable forest management. We evaluated a novel Random Forest based k Nearest Neighbors (RF-kNN) imputation approach to couple remote sensing and geospatial data with field inventory collected by different sampling methods to generate forest inventory information across large spatial extents. The forest inventory data collected by the FIA program of US Forest Service was integrated with optical remote sensing and other geospatial datasets to produce biomass distribution maps for a part of the Lake States and species-specific site index maps for the entire Lake State. Targeting small-area application of the state-of-art remote sensing, LiDAR (light detection and ranging) data was integrated with the field data collected by an inexpensive method, called variable plot sampling, in the Ford Forest of Michigan Tech to derive standing volume map in a cost-effective way. The outputs of the RF-kNN imputation were compared with independent validation datasets and extant map products based on different sampling and modeling strategies. The RF-kNN modeling approach was found to be very effective, especially for large-area estimation, and produced results statistically equivalent to the field observations or the estimates derived from secondary data sources. The models are useful to resource managers for operational and strategic purposes.

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OBJECTIVE: To evaluate the scored Patient-generated Subjective Global Assessment (PG-SGA) tool as an outcome measure in clinical nutrition practice and determine its association with quality of life (QoL). DESIGN: A prospective 4 week study assessing the nutritional status and QoL of ambulatory patients receiving radiation therapy to the head, neck, rectal or abdominal area. SETTING: Australian radiation oncology facilities. SUBJECTS: Sixty cancer patients aged 24-85 y. INTERVENTION: Scored PG-SGA questionnaire, subjective global assessment (SGA), QoL (EORTC QLQ-C30 version 3). RESULTS: According to SGA, 65.0% (39) of subjects were well-nourished, 28.3% (17) moderately or suspected of being malnourished and 6.7% (4) severely malnourished. PG-SGA score and global QoL were correlated (r=-0.66, P<0.001) at baseline. There was a decrease in nutritional status according to PG-SGA score (P<0.001) and SGA (P<0.001); and a decrease in global QoL (P<0.001) after 4 weeks of radiotherapy. There was a linear trend for change in PG-SGA score (P<0.001) and change in global QoL (P=0.003) between those patients who improved (5%) maintained (56.7%) or deteriorated (33.3%) in nutritional status according to SGA. There was a correlation between change in PG-SGA score and change in QoL after 4 weeks of radiotherapy (r=-0.55, P<0.001). Regression analysis determined that 26% of the variation of change in QoL was explained by change in PG-SGA (P=0.001). CONCLUSION: The scored PG-SGA is a nutrition assessment tool that identifies malnutrition in ambulatory oncology patients receiving radiotherapy and can be used to predict the magnitude of change in QoL.