Weight Estimation Model Research Articles

Result Merging for Structured Queries on the Deep Web with Active Relevance Weight Estimation

Data integration systems on the Deep Web offer a transparent means to query multiple data sources at once. Result merging– the generation of an overall ranked list of results from different sources in response to a query– is a key component of a data integration system. In this work we present a result merging model, called Active Relevance Weight Estimation model. Different from the existing techniques for result merging, we estimate the relevance of a data source in answering a query at query time. The relevances for a set of data sources are expressed with a (normalized) weighting scheme: the larger the weight for a data source the more relevant the source is in answering a query. We estimate the weights of a data source in each subset of the data sources involved in a training query. Because an online query may not exactly match any training query, we devise methods to obtain a subset of training queries that are related to the online query. We estimate the relevance weights of the online query from the weights of this subset of training queries. Our experiments show that our method outperforms the leading merging algorithms with comparable response time.

Correlation of ultrasonographic estimated fetal weight with actual birth weight in a tertiary hospital in Lagos, Nigeria.

Sonographic fetal weight estimation is an important component of antenatal care. To sonographically estimate fetal weight at term and to compare estimated with actual birth weights to determine the validity of estimated fetal weights. In the prospective study, a convenience sample of 282 women was recruited. Ethical approval and informed consent of patients were obtained. An experienced sonographer estimated fetal weights by measuring BPD, HC, AC and FL using a scanner with Hadlock 3 weight estimation model. Actual birth weights were measured with a Crown weighing scale by a midwife. Data was analyzed with SPSS software version 17.0 while descriptive and inferential statistics were used to interpret results. Results were tested at error level set at p≤ 0.05. Mean estimated and actual birth weights were 3378±40g and 3393±60g respectively. Difference between the two means was not significant. Eleven percent of fetuses were sonographically estimated to be microsomic while 14.5% were microsomic at birth; 12.1% were sonographically estimated to be macrosomic but 15.2% were macrosomic at birth. Most macrosomic fetuses were delivered through cesarean section(CS) and fetal weights increased with maternal age and parity. Sonographically estimated fetal weight using Hadlock 3 weight estimation model without validation correlated positively with actual birth weight in a Nigerian population.

A Risk Evaluation Algorithm of the Parameter Measurement based on Reliability Design for Ships

A new evaluation method of the parameter measurement risk based on reliability design is present in the paper. Based on the Weight Estimation and reliability model, the calculated model of measurement risk probability is described. The equipment’s measurement reliability and system’s reliability design are fully taken into account in this approach. It provides a theoretical support for the quantitative assessment of parameter measurement risk. And this modeling would be a helpful step to the performance valuation of measuring systems.

A structural weight estimation model of FPSO topsides using an improved genetic programming method

The weight information of an FPSO (floating production, storage, and offloading) plant is one of the important data needed to estimate the amount of production material (e.g., plates) needed and to determine the suitable production method for its construction. In addition, the weight information is a key factor that affects the building cost and the production period of the FPSO plant. Although the importance of the weight has long been recognised, the weight, especially of the topside, has been roughly estimated using the existing similar data as well as the designer's experience. To improve this task, a weight estimation model for FPSO plant topsides was developed in this study using the improved genetic programming (GP) method. For this reason, various past records on the estimation of the weight of the FPSO plant were collected through a literature survey, and then the weight estimation model using GP was established by fixing the independent variables based on these data. In addition, correlation analysis was performed to make up for the weak points of genetic programing, which is apt for inducing overfitting when the number of data is relatively smaller than that of the independent variables. That is, by reducing the number of variables through the analysis of the correlation between the independent variables, an increase in the number of weight data can be expected. Finally, to evaluate the applicability of the suggested model, it was applied to an example of the weight estimation of the FPSO plant topside. Compared with the results of the multiple nonlinear regression analysis that was conducted in the previous study, the results showed that the suggested model can be applied to the weight estimation process of the FPSO plant at the early design stage.

Analysis of impact of use of composite materials on direct operating costs of airliners

The impact of the use of composite materials on the direct operating cost( DOC) of airliners needs to be evaluated at the preliminary stage of aircraft design. An analysis of the influence of the use of composite materials on aircraft cost and weight was carried out. A revised model for airliner weight and cost estimation was developed. An evaluation method was proposed to quantify the benefits of the use of composite materials in airliner design. A 150-seat airliner was used as a case for study. The impact of the percentage of the use of composite materials on DOC was evaluated for airliner design. The impacts of the fluctuation of aircraft price,fuel price and maintenance cost on DOC were investigated. The results show that the DOC of airliners declines with the increase of the percentage of the use of composite materials. With the increase of fuel prices,application of composite materials in aircraft design can bring remarkable economic benefits as the reduction of the costs of manufacturing and maintenance of the airframe of composite materials can lead to a significant decrease of the DOC of aircrafts of composite materials.

Simplified nonlinear model for the weight estimation of FPSO plant topside using the statistical method

The weight information of an FPSO plant, especially of the FPSO (floating, production, storage, and off-loading), is one of the important data needed to estimate the amount of production material (e.g. plates) and to determine the suitable production method for its construction. In addition, the weight information is a key factor that affects the building cost and the production period of the FPSO plant. Although the importance of the weight has long been recognised, the weight, especially of the topside, has been roughly estimated using the existing design and production data as well as the designer's experience. To improve this task, a nonlinear simplified model for the weight estimation of the FPSO plant topside using the statistical method was developed in this study. To do this, various past records on the estimation of the weight of the FPSO plant were collected through literature survey, and then correlation analysis and multiple regression analysis were performed to develop a nonlinear simplified model for weight estimation. Finally, to evaluate the applicability of the developed model, it was applied to an example of the weight estimation of the FPSO plant topside. The results showed that the developed model can be applied to the weight estimation process of the FPSO plant at the early design stage.

개선된 유전적 프로그래밍 방법을 이용한 부유식 해양 구조물의 중량 추정 모델 연구

The weight estimation of floating offshore structures such as FPSO, TLP, semi-Submersibles, Floating Offshore Wind Turbines etc. in the preliminary design, is one of direct measures of both construction cost and basic performance. Through both literature investigation and internet search, the weight data of floating offshore structures such as FPSO and TLP was collected. In this study, the weight estimation model with the genetic programming was suggested for FPSO. The weight estimation model using genetic programming was established by fixing the independent variables based on this data. In addition, the correlation analysis was performed to make up for the weak points of genetic programming; it is apt to induce over-fitting when the number of data is relatively smaller than that of independent variables. That is, by reducing the number of variables through the analysis of the correlation between the independent variables, the increasing effect in the number of weight data can be expected. The reliability of the developed weight estimation model was within 2% of error rate.

Market Risk Factor and the Weighted Repeat Sales Method

In this paper, we identify a critical issue in the weighted repeat sales (WRS) method—the omission of market risk in the weight estimation model specified by Case and Shiller (1989). We demonstrate that the omission of market risk is conceptually unjustified. We propose a modified WRS model that is empirically supported, but also contributes to the broad discussion on the holding period dependence of real estate risk. We also show that the Case-Shiller weighting method is likely to be mis-specified in nine of the ten cities where the Case- Shiller metro indices are “tradable” with housing options and futures contracts listed on the Chicago Mercantile Exchange. Using a large sample of repeat sales from the Washington DC area, the original repeat sales method of Bailey, Muth, and Nourse (1963) and the Case-Shiller method are compared against the modified WRS. The results indicate that market risk plays an important role in the index estimation.

Evaluation of the accuracy of ultrasonography fetal weight estimation models; assessing regression formulae in a Turkish population

In this study, we aimed to evaluate the accuracy of fetal weight prediction, to investigate the validity of sonographic fetal anthropometric parameters in a Turkish population and to assess the most commonly used sonographic formulas for estimation of fetal birth weight. Our retrospective, cross-sectional study included 126 singleton deliveries between June 2010 and January 2011, at the Department of Obstetrics and Gynecology of the GATA Haydarpaşa Training Hospital. Ultrasonography measurement results were applied to nine different fetal weight estimation formulas. Mean error, mean absolute error, mean percentage error and mean absolute percentage error rates were calculated. Under- or overestimation rates and correlation coefficients were also calculated. Fetal biparietal diameter (BPD) and abdominal circumference (AC) were significantly correlated with the actual birth weight and the power analysis for both parameters was calculated as 81%. The highest correlation coefficients in our general population were those of the F1 (Hadlock 1) and F2 (Hadlock 2) models. The highest mean percentage error was detected on F8 (Merz 2) model. Fetal weight estimation modalities were observed to give the best results in a weight range of 3,000 and 3,500 g. Regression formulae used in our population, in general, tended to underestimate, however Hadlock 1 and 2 formulations provided the most accurate results. The Hadlock 1 formula estimated the closest to the actual birth weight in fetuses expected to be born under 3,000 g or over 3,500 g.

유전적 프로그래밍 방법을 이용한 부유식 해양 구조물의 중량 추정 모델

In the initial design stage, the technology for estimating and managing the weight of a floating offshore structure, such as a FPSO (Floating, Production, Storage, and Off-loading unit) and an offshore wind turbine, has a close relationship with the basic performance and the price of the structure. In this study, using the genetic programming (GP), being used a lot in the approximate estimating model and etc., the weight estimation model of the floating offshore structure was studied. For this purpose, various data for estimating the weight of the floating offshore structure were collected through the literature survey, and then the genetic programming method for developing the weight estimation model was studied and implemented. Finally, to examine the applicability of the developed model, it was applied to examples of the weight estimation of a FPSO topsides and an offshore wind turbine. As a result, it was shown that the developed model can be applied the weight estimation process of the floating offshore structure at the early design stage.

Validity of Weight Estimation Models in Pigs Reared under Different Management Conditions.

A study was carried out to determine the relationship between linear body measurements and live weight in Landrace and Large White pigs reared under different management conditions in Zimbabwe. Data was collected for body length, heart girth, and live weight in 358 pigs reared under intensive commercial conditions. The stepwise multiple linear regression method was done to develop a model using a random selection of 202 records of pigs. The model showed that age, body length, and heart girth were useful predictors of live weight in these pigs with significantly high positive correlations observed. The model was internally validated using records of the remaining 156 pigs and there was a significantly high positive correlation between the actual and predicted weights. The model was then externally validated using 40 market age pigs reared under communal conditions and there was a significantly low positive correlation between the actual and predicted weights. The results of the study show that while linear measurements can be useful in predicting pig weights the appropriateness of the model is also influenced by the management of the pigs. Models can only be applicable to pigs reared under similar conditions of management.

Self-adaptation evaluation method in real time dynamics decision-making system based on grey close relationship

Purpose – The evaluation scores of each criterion and the integration are given by decision makers, respectively. Owing to the heavy time-pressure in real time decision-making, decision makers may have different judgment abilities, which reflects the instability and inconsistent weight of criteria and scores. It will lead to the unreliable results. To rank alternatives more rational, the consistency of decision makers is considered. The paper aims to discuss these issues. Design/methodology/approach – First, the weight estimation model of the criteria is developed to find the dynamic change and the inconsistency of decision makers, which is based on the objects of weight stability and the consistency measured by the distance between scores of each criterion and the integration. Following that, scores of alternatives given by each decision maker are modified according to the requirement of stability and consistency of the decision-making. In addition, the weight of decision makers is deduced based on the self-consistency and group's similarity that measured by grey close relationship. In the last, the score of alternatives can be modified according to the weight of the decision maker and criteria, and then, alternatives can be ranked via the final score. Findings – The self-adaptation evaluation method is suggested in real time decision-making environment. Originality/value – Its application step and feasibility is showed via a real decision-making problem.

Correlation between CT-estimated tumor volume, pathologic tumor volume, and final pathologic specimen weight in children with Wilms' tumor

ObjectiveTo evaluate the relationship of Wilms' tumor (WT) volume to weight, and evaluate computed tomography (CT) scan-derived final pathologic specimen weight estimation models. MethodsWe retrospectively reviewed WT patients from 2003 to 2011 who had a pre-operative CT scan, final pathologic specimen weight, and tumor dimensions. A partial nephrectomy tumor cohort (n = 12) was used derive WT density. A radical nephrectomy cohort (n = 45) was used to develop a simplified estimation equation of final pathologic specimen weight, and analysis of all known estimation models was performed. ResultsFifty-two patients were identified. WT volume and weight were not equivalent (p = 0.0410). WT density was 1.3091 g/cm3. WT volume and final pathologic specimen weight were not significant (p = 0.0007). Our model (p = 0.9983) and CT estimated ellipsoidal volume (p = 0.0741) were able to estimate final pathologic specimen weight in all tumors. However, CT-estimated ellipsoidal volume failed to estimate final pathologic specimen weight in specimens < 250 g (p = 0.0066). ConclusionPathologic WT volume is not equivalent to final pathologic specimen weight. Final pathologic specimen weight can be estimated from a pre-operative CT scan, which suggests that it may be used to improve pre-operative surgical planning and to reduce treatment morbidity.

A conceptual wing-box weight estimation model for transport aircraft

AbstractThis paper presents an overview of an advanced, conceptual wing-box weight estimation and sizing model for transport aircraft. The model is based on linear thin-walled beam theory, where the wing-box is modelled as a simple, swept tapered multi-element beam. It consists of three coupled modules, namely sizing, aeroelastic analysis, and weight prediction. The sizing module performs generic wing-box sizing using a multi-element strategy. Three design cases are considered for each wing-box element. The aeroelastic analysis module accounts for static aeroelastic requirements and estimates their impact on the wing-box sizing. The weight prediction module estimates the wing-box weight based on the sizing process, including static aeroelastic requirements. The breakdown of the models into modules increases its flexibility for future enhancements to cover complex wing geometries and advanced aerospace materials. The model has been validated using five different transport aircraft. It has shown to be sufficiently robust, yielding an error bandwidth of ±3%, an average error estimate of -0·2%, and a standard error estimate of 1·5%.

Assessment of the Accuracy of Multiple Sonographic Fetal Weight Estimation Formulas: A 10-Year Experience From a Single Center

The primary aim of this study was to compare the accuracy of sonographic fetal weight estimation models. The secondary aim was to define the most accurate time (4-7 or 3 days before delivery) for evaluating fetal weight. In this retrospective cohort study, a total of 12,798 sonographic fetal weight estimations were analyzed, of which 9459 were performed within 3 days of delivery and 3339 within 4 to 7 days. The cohort included all singleton pregnancies recorded at a single medical center from January 2000 to December 2010, with 24 weeks' gestation minimum. Predicted birth weights were calculated according to 23 sonographic fetal weight estimation models; in total, 294,354 sonographic weight estimations were evaluated and compared to the actual birth weights. The accuracy of the models in predicting birth weight differed considerably. The most accurate models used 3 or more fetal measurements followed by models using abdominal circumference only. The models developed by Sabbagha et al (Am J Obstet Gynecol 1989; 160:854-862) proved most accurate, with a mean percent error of -0.2% and greater than 92% of estimates within 15% of birth weight (P < .05). Nineteen sonographic fetal weight estimation models (82.6%) better predicted fetal weight at 4 to 7 days before delivery (P < .001). Twenty-two (95%) of the models were less accurate at the extreme ends of fetal weight. Different formulas for fetal weight estimation vary greatly; we recommend that each center should evaluate the most accurate formula according to its attending population. Estimation of fetal weight performed 4 to 7 days before delivery using most models was more accurate than estimations performed 3 days before delivery.

A fresh look at weight-estimation models for soil mites (Acari)

Biomass data can be challenging to obtain for studies involving soil microarthropods, whose small body sizes make them difficult to weigh using anything but the most sensitive balances. Researchers can circumvent weighing by using aspects of body size (length, width and volume) to estimate biomass. However, size-based estimates are trustworthy only if they can be shown to correctly predict actual weights. Here, we provide a review of published weight-estimation models for soil mites (Arachnida: Acari) and test them using mites collected from grassland and woodland habitats in Alberta, Canada. Our analyses show that the models we tested mostly result in an underestimation of actual weight, although some show this bias more than others. Oribatida in particular suffer from this underestimation, while Prostigmata show some strong overestimations. However, some Oribatida weight prediction models work surprisingly well on other taxa. Based on these results, we provide suggestions of what models might be best used for different mite taxa.

A reliable game fish weight estimation model for Atlantic tarpon (Megalops atlanticus)

Rapid growth of popular and lucrative catch-and-release marine sportfisheries worldwide has highlighted the need for reliable weight estimation methods for use in fishing tournaments, pursuit of fishing records, and to support scientific research that allows captured fish to be released alive. This paper describes new methods to predict weight from measurements of body size of game fish. Here we also evaluated efficacy of a widely used historical model and compared this to several new statistical and analytical weight estimation models that we developed herein. We applied these candidate models to a unique morphometric data set on Atlantic tarpon (Megalops atlanticus) which contained information on body weight W as a function of fork length L and dorsal girth G for more than 1100 individuals from Florida, the Gulf of Mexico, Caribbean Sea and western Africa. A popular formula (W=G2L/800), developed more than a century ago specifically for tarpon was originally derived from geometric and physical relationships between fish body weight and shape. We found this model to be negatively biased >−15% (i.e., underestimates individual fish weights) across the tarpon's entire size range up to 130kg (the current world record). Bias for our “new” ellipsoid volumetric formulation, which extends the principles of allometry, was less than 1% across the entire range of observed sizes. Our new estimator was used by Texas Parks and Wildlife Department to assist fishery management in setting “minimum maximum” sizes for recreationally caught tarpon that have the potential to break the Texas State record. It has also supported catch-and-release tarpon fisheries and tournaments in Florida, Texas, Mexico, and Trinidad. It provides a reliable means to accurately estimate weights of tarpon of potential (world) record sizes.

Prediction of fetal macrosomia: effect of sonographic fetal weight‐estimation model and threshold used

To compare the accuracy of 21 sonographic fetal weight-estimation models and abdominal circumference (AC) as a single measure for the prediction of fetal macrosomia (> 4000 g) using either fixed or optimal model-specific thresholds. A total of 4765 sonographic weight estimations performed within 3 days prior to delivery were analyzed. The predictive accuracy of 21 published sonographic fetal weight-estimation models was calculated using three different thresholds: a fixed threshold of 4000 g; a model-specific threshold obtained from the inflexion point of the receiver-operating characteristics (ROC) curve; and a model-specific threshold associated with the highest overall accuracy. Cluster analysis was used to determine whether a certain combination of fetal biometric indices is associated with a higher predictive accuracy than others. For a fixed threshold of > 4000 g, there was considerable variation among the models in sensitivity (range, 13.6-98.5%) and specificity (range, 63.6-99.8%) for fetal macrosomia. Use of the threshold derived from the inflexion point of the ROC curve decreased the intermodel variation to a minimum (sensitivity, 84.4-91.4%; and specificity, 79.5-86.3%). Even when this optimal model-specific threshold was applied, models based on three to four biometric indices were more accurate than were models based on only two biometric indices or on AC as a single measure (P=0.03). Sonographic fetal weight-estimation models based on three to four biometric indices appear to be more accurate than are models based on two indices or on AC as a single measure, for the diagnosis of macrosomia. In these cases, the use of an optimal, model-specific threshold is associated with a higher degree of accuracy than is the uniform use of a fixed threshold of an estimated weight of > 4000 g.

Ultrasound estimation of fetal weight: A formula for a Pakistani population

To assess and validate the best model for fetal weight estimation in the Pakistani population. The cohort included 178 women with singleton pregnancies at term (37-41 weeks) who had an ultrasound scan within 7 days of delivery. A proportionality formula was used to compensate for the fetal weight gain between the scan and the delivery. Data points from 119 pregnancies were used to derive the fetal weight formula, which was subsequently tested on the remaining 59 pregnancies. The best model for fetal weight estimation from ultrasound biometric parameters was selected. The selected model showed an interclass correlation coefficient with birthweight of 0.89. The systematic and random errors were -10 and 250 g, respectively. This validity assessment compared favorably with the performance of the more commonly used formulae when applied to our population. We describe a new model for fetal weight estimation in a Pakistani population which produces more valid and reliable estimates than currently used models derived from other populations.

Evaluation of the Accuracy of Different Methods Used to Estimate Weights in the Pediatric Population: So TY, Farrington E, Abasher RF. Pediatrics 2009;123:e1045–51

This prospective observational study from North Carolina sought to compare the accuracy of three existing methods to estimate the weight of children. Additionally, it identified several predictive factors that were used to derive two new weight-estimation models. Subjects were selected from children under 10 years old who were inpatients at the University of North Carolina's Children's Hospital. The Broselow tape, Leffler formula, and Theron formula were used to estimate the weight of each subject, which was then compared to actual weight using analysis of variance on the percentage difference of the values.