Weight Estimation Research Articles

GeoHi-GNN: Geometry-aware hierarchical graph representation learning for normal estimation

Normal estimation has been one of the key tasks in point cloud analysis, while it is challenging when facing with severe noises or complex regions. The challenges mainly come from the selection of supporting points for estimation, that is, improper selections of points and points' scale will lead to insufficient information, loss of details, etc. To this end, this paper proposes one feature-centric fitting scheme, GeoHi-GNN, by learning geometry-aware hierarchical graph representation for fitting weights estimation. The main functional module is the continuously conducted Hierarchically Geometric-aware (HG) module, consisting of two core operations, namely, the graph node construction (GNC) and the geometric-aware dynamic graph convolution (GDGC). GNC aims to aggregate the feature information onto a smaller number of nodes, providing global-to-local information while avoiding the interferences from noises in larger scales. With these nodes distributed in different scales, GDGC dynamically updates the node features regarding to both intrinsic feature and extrinsic geometric information. Finally, the hierarchical graphical features are cascaded to estimate the weights for supporting points in the surface fitting. Through the extensive experiments and comprehensive comparisons with the state-of-the-arts, our scheme has exhibited many attractive advantages such as being geometry-aware and robust, empowering further applications like more accurate surface reconstruction.

Deriving disability weights for the Netherlands: findings from the Dutch disability weights measurement study

BackgroundThe aims of this study were to establish national disability weights based on the health state preferences of a Dutch general population sample, examine the relation between results and respondent’s characteristics, and compare disability weights with those estimated in the European disability weights study.MethodsIn this cross-sectional study, a web-based survey was administered to a general population 18–75 years from the Netherlands. The survey included paired comparison questions. Paired comparison data were analysed using probit regression and located results onto the 0-to-1 disability weight scale using non-parametric regression. Bootstrapping was used to estimate 95% uncertainty intervals (95%UI). Spearman’s correlation was used to investigate the relation of probit regression coefficients between respondent’s characteristics.Results3994 respondents completed the questionnaire. The disability weights ranged from 0.007 (95%UI: 0.003–0.012) for mild distance vision impairment to 0.741 (95% UI: 0.498–0.924) for intensive care unit admission. Spearman’s correlation of probit coefficients between sub-groups based on respondent’s characteristics were all above 0.95 (p < 0.001). Comparison of disability weights of 140 health states that were included in the Dutch and European disability weights study showed a high correlation (Spearman’s correlation: 0.942; p < 0.001); however, for 76 (54.3%) health states the point estimate of the Dutch disability weight fell outside of the 95%UI of the European disability weights.ConclusionsRespondent’s characteristics had no influence on health state valuations with the paired comparison. However, comparison of the Dutch disability weights to the European disability weights indicates that health state preferences of the general population of the Netherlands differ from those of other European countries.

Fuzzy Logic Based Adaptive Parameter Estimation System in Moving Measurement Systems

Fast and accurate weighing of the weighing systems used in industrial filling systems is of great importance in terms of increasing production capacity and maintaining product quality. In facilities that grind and process grain, machines and equipment are positioned horizontally and vertically on steel structures. Since these machines continuously perform grinding, transferring, filling, and emptying operations, they create continuous vibration in the mechanical systems they are connected to. Moving weighing systems are significantly affected by these mechanical systems. When the impact effect of pneumatic valves-controlled covers in moving weighing systems is added to these structural mechanical vibrations, there are significant waits and delays in weighing systems that measure performance. For this reason, in a performance measurement system in a flour mill, the measurement interval increases as the amount of weighing increases. For example, in a moving weighing system that performs 50 kg performance weighing, the measurement interval can increase up to 15 seconds, which is quite long. In this study, an applied study has been conducted to increase the weighing performance in moving weighing systems and to minimize the measurement interval. The data collection process in the study focuses on two main components: load cell data and IMU data. Thus, it is aimed to overcome the difficulties of traditional methods used in weighing systems, which are generally observed to be insufficient to combat slow and noisy data. The analysis techniques used in this study are Kalman Filtering, Dynamic Q and R Matrix Updates, Comparative Analysis and Statistical Analysis. The Kalman filter was used for the integration of Load cell and IMU data and was applied to filter out noise and oscillations in the weighing data and make more accurate weight estimates. The results obtained showed that the dynamic Kalman filtering method can provide faster and more accurate weighing results compared to traditional methods, with error rates varying between 0.4% and 1% for different combinations of Q and R values in measurements made on the scale. Dynamic Kalman filtering method effectively filters oscillatory and noisy load cell signals, with error rates of 0.7% to 1% for Q=0.02 and R=17 parameters, and error rates of 0.4% to 0.7% for Q=0.07 and R=13 parameters. was able to obtain more accurate weight estimates. This study has shown that the dynamic Kalman filtering method is a potential method that can be used in industrial filling systems. This method can contribute to increasing production capacity and maintaining product quality by providing faster and more accurate weighing results. In this respect, the research has a unique contribution. This method provides a revolutionary development in industrial weighing systems and fills an important gap in the literature.

A Comparative Study of Fetal Weight Estimation by Symphysiofundal Height and Ultrasound Biometry in Women at Term

A Comparative Study of Fetal Weight Estimation by Symphysiofundal Height and Ultrasound Biometry in Women at Term

Accurate birth weight prediction from fetal biometry using the Gompertz model

ObjectivesMonitoring of fetal growth and estimation of birth weight is of clinical importance. During pregnancy, ultrasound fetal biometry values including femur length, head circumference, abdominal circumference, biparietal diameter are measured and used to place fetuses on “growth charts”. There is no simple growth-model-based, predictive formula in use for fetal biometry. Estimation of fetal weight at birth currently depends on ultrasound data taken a short time before birth. Study designOur cohort (“Seethapathy cohort”) consists of ultrasound biometry measurements and other data for 774 pregnant women in Chennai, India, 2015–2017. We use the Gompertz model, a standard model for constrained growth, with just three intuitive parameters, to model the growth of fetal biometry, and a machine learning (ML) model trained on these parameters to predict birth weight (BW). ResultsThe Gompertz model convincingly fits the growth of fetal biometry values. Two Gompertz parameters—t0 (inflection time) and c (rate of decrease of growth rate)—seem universal to all fetuses, while the third, A, is an overall scale specific to each fetus, capturing individual variation. On the Seethapathy cohort we can infer A for each fetus from ultrasound data available by the 24 or 35 weeks. Our ML model predicts birth weight with < 8 % error, outperforming published methods that have access to late-term ultrasound data. The same model gives an 8.4 % error in BW prediction on an independent validation cohort of 365 women. ConclusionsThe Gompertz model fits fetal biometry growth and enables birth weight estimation without need of late-term ultrasounds. Aside from its clinical predictive value, we suggest its use for future growth standards, with almost all variation described by a single scale parameter A.

Total body weight estimation by 3D camera systems: Potential high-tech solutions for emergency medicine applications? A scoping review.

Weight estimation is required in adult patients when weight-based medication must be administered during emergency care, as measuring weight is often not possible. Inaccurate estimations may lead to inaccurate drug dosing, which may cause patient harm. High-tech 3D camera systems driven by artificial intelligence might be the solution to this problem. The aim of this review was to describe and evaluate the published literature on 3D camera weight estimation methods. A systematic literature search was performed for articles that studied the use of 3D camera systems for weight estimation in adults. Data on the study characteristics, the quality of the studies, the 3D camera methods evaluated, and the accuracy of the systems were extracted and evaluated. A total of 14 studies were included, published from 2012 to 2024. Most studies used Microsoft Kinect cameras, with various analytical approaches to weight estimation. The 3D camera systems often achieved a P10 of 90% (90% of estimates within 10% of actual weight), with all systems exceeding a P10 of 78%. The studies highlighted a significant potential for 3D camera systems to be suitable for use in emergency care. The 3D camera systems offer a promising method for weight estimation in emergency settings, potentially improving drug dosing accuracy and patient safety. Weight estimates were satisfactorily accurate, often exceeding the reported accuracy of existing weight estimation methods. Importantly, 3D camera systems possess characteristics that could make them very appropriate for use during emergency care. Future research should focus on developing and validating this methodology in larger studies with true external and clinical validation.

Correlation of sonographically measured fetal abdominal wall thickness with birth weight in diabetes

ObjectiveTo determine the association between sonographically measured abdominal wall thickness (AWT) and birth weight of fetuses of pregnant women with diabetes. MethodsThis retrospective study included 185 pregnant women who presented to a level I perinatal centre between January 2021 and December 2022. All mothers had diabetes, and were divided into the following subgroups: diet-controlled gestational diabetes mellitus; insulin-dependent gestational diabetes mellitus; type 1 diabetes mellitus; and type 2 diabetes mellitus. At the time of admission, gestational age varied between 29 + 2 and 41 + 2 weeks (+days) of gestation. Weight estimation was performed routinely using the Hadlock I formula. Fetal AWT was determined retrospectively at the same axial level as used for the measurement of abdominal circumference. Only women with a sonographic fetal weight estimation within 5 days before delivery were included. ResultsFor the whole cohort, a moderate positive correlation was found between fetal AWT and estimated fetal weight (r = 0.411, p < 0.001), a moderate correlation was found between fetal AWT and birth weight (r = 0.493, p < 0.001), a weak correlation was found between fetal AWT and body length (r = 0.365, p < 0.001), and a weak correlation was found between fetal AWT and body length percentile (r = 0.276, p < 0.001). No strong differences in parameters were found between the diabetes subgroups. Receiver operating characteristic (ROC) curve analysis was performed to identify newborns with birth weight > 4000 g (macrosomia) and birth weight > 90th percentile according to Voigt in the group with gestational age > 37 weeks. ROC curve analysis was performed to identify newborns with birth weight > 90th percentile in the whole cohort. AWT and sonographically estimated fetal weight were included in the calculation. The combination of AWT and estimated fetal weight only led to a marginal improvement compared with estimated fetal weight alone for predicting newborns with birth weight > 4000 g in the group with gestational age > 37 weeks [area under the curve (AUC) 0.857 vs 0.871], and for predicting newborns with birth weight > 90th percentile in the group with gestational age > 37 weeks (AUC 0.840 vs 0.846) and in the whole cohort (AUC 0.816 vs 0.826). ConclusionA sonographically measured AWT of 7.1 mm in fetuses of diabetic mothers is predictive of birth weight > 90th percentile with sensitivity of 61 %, specificity of 85 %, and AUC of 0.748. ROC curve analysis showed that estimated fetal weight determined by ultrasound (using Hadlock formula I) seems to be slightly superior for the identification of macrosomic fetuses with birth weight > 90th percentile. A threshold value for estimated fetal weight of 3774 g had sensitivity of 70 %, specificity of 86 %, and AUC of 0.816. The combination of AWT and estimated fetal weight in a single formula only yielded a marginal improvement in accuracy compared with the use of estimated fetal weight alone.

A study to determine a practical method for weight estimation of deceased persons

BackgroundBody weight is an important parameter for estimating the postmortem interval (PMI) at a crime scene. However, a challenge arises at crime scenes when a weight scale for measuring the total body weight is unavailable. Anthropometry-based models to estimate body weight have been developed in previous studies. This study aims to determine the accuracy of body weight estimations by practitioners, test the anthropometry-based models for applicability to deceased individuals, and examine a potential new method based on applying heel weight. MethodsA prospective study was conducted at the Isala Hospital in the Netherlands. During the study period, deceased people that were admitted to the hospital mortuary were included consecutively. The body weight of deceased persons estimated by practitioners was compared to the actual body weight. Anthropometric measurements were taken and used to perform eight sex dependant anthropometry-based models, with accuracy for the actual body weight calculated using RMSE values. A Pearson's correlation test was used to determine the correlation between heel weight and total body weight. ResultsDuring the study period, a total of 100 cases, 56 males and 44 females, were included. Overall, only 33.3 % of practitioners' estimations were within 5 % of the actual measured weight. The model based on abdominal and thigh circumference performed best for weight estimation in males and the models based on mid-arm circumference, abdominal circumference, calf circumference and, in one model, subscapular skinfold performed best in females. A Pearson's correlation test revealed a weak positive correlation between weight of the heel and total body weight (Pearson's correlation coefficient: 0.214). DiscussionEstimations of underweight or obese patients posed a challenge for weight estimation. Especially in these cases, study results showed that anthropometry-based models have potential for daily practice. However, additional research is required to assess the reliability of the best performing models before implementation in forensic casework. The correlation between the weight of the heel and body weight was low, therefore implementation of the current method is not recommended, and further research is required.

A prospective blinded diagnostic accuracy study to assess the accuracy of fetal weight estimation at term by clinical method using Leopold’s maneuvers and ultrasonography in predicting the actual birth weight

ABSTRACT Context: Over-medicalization of normal pregnancy is associated with unnecessary inductions of labor leading to operative deliveries. In a busy outpatient department (OPD) or low-resource setup where ultrasound availability, experience, and cost will be a concern, routine ultrasound at term can be avoided if the clinical estimation of fetal weight is more or less equal to the actual birth weight. Aims: To assess the reliability and validity of fetal weight estimation at term by ultrasound and clinical estimation. Settings and Design: A prospective study of diagnostic accuracy was done over a period of 1.5 years in a tertiary hospital, which included 100 women with term singleton pregnancies admitted in obstetric wards or labor room. Methods and Material: To find out the agreement between actual birthweight and ultrasound fetal weight interclass correlation coefficient (ICC) was used. Mean difference plots (Bland–Altman plots) were done. The mean percentage error was compared with the consultant estimate and registrar estimate across groups. The sensitivity, specificity, and predictive values by clinical and ultrasound estimate were calculated for actual birth weight ≤ 2.5 kg. Results: Both methods of fetal weight estimation have moderate reliability in predicting the actual birth weight. The sensitivity of identifying birthweight &lt; 2.5 kg babies by ultrasound was slightly higher. For birth weight less than 2.5 kg, there was an overestimation of fetal weight by clinical estimation done by postgraduate with mean percentage error being statistically significant as compared with ultrasound estimation. Conclusions: In a developing country like ours where ultrasound is not readily available in all healthcare setups, the clinical method is an easy, cost-effective, simple one that can be used by all medical professionals after adequate training.

Association of concomitant H1 antihistamine and immune checkpoint inhibitor therapy on survival outcome and safety in patients with advanced primary lung cancer: a cohort study.

Antihistamines alleviate the side effects of antitumor drugs and exert antitumor effects. This study aimed to investigate the potential impact of short-term concomitant use of antihistamines with immune checkpoint inhibitor (ICI) therapy on the efficacy and immune-related adverse events (irAEs) of immunotherapy for patients with advanced lung cancer. We retrospectively analyzed the medical records of 211 patients diagnosed with advanced primary lung cancer and treated with immunotherapy at Tianjin Medical University Cancer Institute and Hospital between January 1, 2018, and January 1, 2022. Among these patients, 109 who received H1 antihistamine during the infusion of anti-programmed cell death-1 (PD-1) and anti-programmed cell death ligand 1 (PD-L1) antibodies were assigned to the experimental group; meanwhile, the remaining 102 patients who did not receive H1 antihistamines were assigned to the control group. Balancing was achieved through inverse probability of treatment weight (IPTW) estimation. The data were analyzed using Kaplan-Meier curves and Cox regression analyses. The median progression-free survival (mPFS) was 12.7 months in the experimental group and 4.3 months in the control group, while the median overall survival (mOS) was 32.8 months in the experimental group and 18.1 months in the control group. In the experimental group, patients treated with only H1 antihistamines had longer mPFS and mOS compared with those who received H1 plus H2 antihistamines. Similarly, in the control group, patients who did not receive antihistamines had a longer mPFS and mOS than those who only received H2 antihistamines. After conducting multivariate analyses, we found that H1 and H2 antihistamines were respectively identified as good and poor independent prognostic factors for both progression-free survival (PFS) and overall survival (OS). The rates of irAEs in the experimental and control groups were 52.4% and 69.2%, respectively, and grade ≥3 irAEs occurred in 4.5% and 25.9% of patients, respectively. Concomitant use of H1 antihistamines can improve immunotherapy efficacy and reduce irAEs. Meanwhile, concomitant use of H2 antihistamines is associated with reduced PFS and OS time.

The tibiotarsus of a giant darter from the upper Miocene of Amazonia and weight estimates for fossil darters

Fossil darters are known from every continent since the Oligocene. However, it was in the Miocene of South America that this group reached its maximum diversity. Macranhinga ranzii is the largest darter from the Solimões Formation, described based on the left and right femora as well as the distal end of a tarsometarsus and four vertebrae. Here, we describe for the first time the left tibiotarsus of this species by comparing it with the tibiotarsus of the extant Anhinga anhinga and other fossil anhingids. We also calculated and compared the body mass of Ma. ranzii to that of all known tibiotarsi fossil anhingids using two calculation methods. The tibiotarsus described here is morphologically similar to that of other anhingids, however, in addition to its large size and robustness, it presents diagnostic characters (e.g., torus linearis) that allow us to attribute it to the genus Macranhinga and differentiate it from other fossil species of this genus whose tibiotarsi are known. The estimated body mass of Ma. ranzii ranges from 14.39 to 19.1 kg, ranking it the highest estimated body mass among the darters where the tibiotarsi were found.

Simplified modeling study of the forward fuselage structure based on the overall structural rapid design software for civil aircraft

Abstract In order to solve the problems of poor weight estimation accuracy and difficult layout design trade-offs in the concept demonstration and overall program definition stage of civil aircraft, Aircraft Layout, a civil aircraft overall program structure rapid design software, is used to establish a numerical calculation-based layout program rapid design simulation platform. Based on the forward fuselage structure, this paper gives the results of rapid modeling and finite element simulation and analysis of the forward fuselage isotropic section of a certain type of aircraft, which provides a reference for the optimization design of the structural components of the forward fuselage section of a certain type of aircraft in the conceptual scheme design stage.

Comprehensive survey of body weight estimation: techniques, datasets, and applications

Comprehensive survey of body weight estimation: techniques, datasets, and applications

Operation, Expansion, and Improvement of the Snow Load Alert System “YukioroSignal”

The “YukioroSignal” system, which provides snow load alerts, was developed to inform decision-making regarding snow removal from house roofs. It was launched in Niigata Prefecture in 2018 and expanded to cover all special heavy snowfall areas in Japan, including the Hokkaido, Tohoku, and Hokuriku regions in 2024. The system uses the SNOWPACK model to estimate high-accuracy snow weight from real-time snow depth data published online at observation points. At locations where snow depth gauges are not installed, such as in mountainous areas, snow weight is estimated using inverse distance-weighted interpolation, but accuracy is reduced. To overcome this problem, this study attempted to integrate this information with the snow water equivalent distribution calculated using the simple-layer snow distribution model. To validate this improvement, manual observations of snow weight were performed at 98 sites and compared with simulation results. The accuracy of snow weight estimation at distances far away from snow depth stations was improved. The six-year operation of YukioroSignal showed the additional required information that is vulnerable to damage even with less snowfall, such as vacant houses, and caution of changes in hazard levels by an increase in snowburst in a short period.

Effect of the PROFIT-BR exercise program on physical fitness of children: a protocol study

BackgroundConsidering that school environments are important and have the potential to promote an active lifestyle with direct impacts on physical, motor, cognitive, affective, and psychological aspects, the objective of this study was to evaluate the effect of a physical exercise program in the school context.MethodsA parallel, two-arm experimental research project carried out over 19 weeks, with two non-consecutive weekly classes of 60 min, with the inclusion of PROFIT-BR in the initial 15 min of the class followed by 40 min based on specific physical education skills on indicators of physical fitness in children. Estimates of excess weight and visceral fat will be measured and assessed by body mass index and waist-to-height ratio, respectively, and cardiorespiratory fitness by performance in the six-minute run/walk test. Flexibility will be assessed by the sit and reach test; and muscle strength measured by the number of sit-ups in one minute. The 2 kg medicine ball throw and the horizontal jump will be used to measure upper and lower limb power, respectively, the square test used as a measure of agility, and the 20-meter run test used to measure speed. To analyze the differences between baseline and post-intervention values, repeated measures ANOVA adjusted for somatic maturation will be used. The magnitude of the effect size will be estimated by “partial eta squared”. Statistical analyses will be carried out using SPSS version 24.0 software and a 5% probability of error in the analyses will be accepted.DiscussionThe main theoretical assumption of the proposal is the cause-and-effect relationship between the regular practice of physical exercise in childhood and adolescence and several parameters of health and motor performance. The elaborated program has a lot of applicability because it was wondering from the perspective of the school, in terms of materials, space, and objectives of physical education.

Application en routine des résultats d’un essai randomisé : performance de l’échographie en pratique courante pour le dépistage de la macrosomie fœtale

ObjectiveTo evaluate the performance of ultrasound at 36 weeks of gestation for screening fetal macrosomia according to the criteria of the randomized “DAME” trial. MethodRetrospective observational study over 2 years in a type 3 maternity hospital. The primary outcome was birth weight above the 97th percentile on Audipog birth weight curves. The sensitivity, specificity, positive and negative predictive value of ultrasound at 36 SA for predicting macrosomia were calculated. For each patient, the absolute value of the difference between actual and estimated weight [EPF difference=(Birth weight − Estimated weight)/Birth weight] was calculated. Among undetected macrosomic newborns (≥97th Audipog percentile), risk factors associated with misdiagnosis were investigated (false negatives versus true positives). ResultsUltrasound estimation of fetal weight at 36 SA to detect fetal macrosomia had a sensitivity of 43.7% and a specificity of 82.1%. With a positive predictive value for ultrasound of 36,9% and a negative predictive value of 85.8%. The mean absolute value of the difference between estimated and actual birth weight was 287g (95% CI [115–409]), with a mean relative difference of 6.8% (95% CI [3.0–11.3]). A relative difference of less than 10% between the estimated weight and the birth weight was found in 68.5% of the patients. Among macrosomic newborns (≥97th percentile), a third-trimester estimated fetal weight at or above the 90th percentile, along with a history of fetal macrosomia in a previous pregnancy, reduced the risk of false negatives in the screening ultrasound at 36 weeks of gestation. ConclusionUltrasound performed at 36 weeks’ gestation in a population targeted for suspected fetal macrosomia in routine practice has moderate sensitivity and positive predictive value. It would be timely for teams also applying this protocol to share their results, in order to verify whether or not our findings can be generalized to a larger scale.

Genetic improvement and conservation of goats in tropic

Goats indeed have a significant historical and contemporary importance in human civilization, particularly in the realm of agriculture and food production. Their adaptability and widespread distribution have made them crucial for various societies across the world. Goats have played a central role in the Neolithic agricultural revolution, aiding in the spread of human civilization globally. Their adaptability allowed them to thrive in diverse environments, contributing to the sustenance and expansion of human settlements. Goats are highly adaptable and are found in a wide range of geographical regions. Their presence spans across continents, from tropical to temperate climates, showcasing their ability to thrive in various environmental conditions. There is diversity in the production performance of goats based on the region of the world and the specific breeds. Genetic improvement programs aim to enhance economically important traits such as milk production, growth rates and fiber production, thereby increasing productivity and income for goat farmers. Understanding the genetic parameters such as heritabilities and repeatabilities for various traits is crucial for designing effective breeding programs. These parameters provide insights into the genetic potential of goats for traits like milk production, growth and fiber quality. Heritability estimates for reproductive traits, body weight, daily gain and direct and maternal heritability are important for implementing selective breeding strategies aimed at improving overall productivity and efficiency in goat farming. Genetic improvement programs have been implemented in tropical environments to enhance milk production traits in goats. Genetic improvements have also targeted fiber production in goats, with a focus on traits such as grease fleece weight and average fiber diameter. These efforts aim to enhance the quality and quantity of fiber produced by goats for various commercial purposes. Despite the importance of conserving goat breeds with unique characteristics, planned conservation programs in tropical regions are often neglected. It’s emphasized that preserving indigenous goat breeds in their native habitats is essential for maintaining genetic diversity and ensuring future resilience in goat farming.

Accuracy of supervised measurement of fetal weight in a residency program.

To evaluate the accuracy of ultrasound estimates of fetal weight made by residents. A cross-sectional study was conducted on consecutive pregnancies attended in an obstetric ward. All participants provided their consent to participate. Inclusion criteria were singleton pregnancies with ultrasound evaluation and delivery within 14 days. Congenital abnormalities and stillbirths were excluded. Ultrasound scans were performed by two residents, one observer per subject, following standardized methodology and supervised by senior staff. Fetal weight was calculated using the four-parameter Hadlock 1985 formula. Birth weight was measured using a standard clinical scale. Bland-Altman and mixed-effects analyses were performed. In a 6-month period, 95 gestations were recruited at 30-41 weeks, and birth weights ranged from 1200 to 4080 g. The bias between methods was -28 g (CI95%, -74 to 18) with 95% limits of agreement of ±440 g. The 95% deviation between methods was of ±16%. Parity had the most significant effect on the bias between methods; operator and maternal weight had no significant effect. Supervised measurement of fetal weight by residents demonstrated high accuracy. Parity bias may be associated with visceral fat deposition independent of maternal weight gain. A methodology for medical evaluation is presented.

Multi-criteria decision-based hybrid energy selection system using CRITIC weighted CODAS approach

A complex and multicriteria decision making (MCDM) problem arises in a bid to select the most appropriate hybrid energy system among several combinations in distributed electricity generation as it involves conflicting criteria that must be simultaneously considered. In this work, Criteria Importance Through Intercriteria Correlation (CRITIC) along with Combinative Distance-Based Assessment (CODAS) was employed to select a suitable hybrid energy system combination for water pumping from four conflicting alternatives of Biomass-Battery (S1), PV-Battery (S2), PV-Biomass (S3), and PV-Biomass-Battery (S4) by objective weight estimation. This was followed by a confirmation by the Additive Ratio Assessment (ARAS) method for the solution. The results presented show that CRITIC method reveals 0.275, 0.224, 0.248, and 0.252 as different weights of the four alternatives of S1, S2, S3, and S4, respectively. The ranking results reveal S4 as the best alternative based on an assessment score of 0.4693. The same hybrid system was confirmed by ARAS based on overall performance and degree of utility of 0.287697 and 0.823716, respectively.

Deep Learning Applied to Imbalanced Malware Datasets Classification

In the current day, the evolution and exponential proliferation of malware involve modifications and camouflage of their structure through techniques like obfuscation, polymorphism, metamorphism, and encryption. With the advancements in deep learning, methods such as convolutional neural networks (CNN) have emerged as potent tools for deciphering intricate patterns within this malicious software. The present research uses the capacity of CNN to learn the global structure of the code converted to an RGB or grayscale image and decipher the patterns present in the malware datasets generated from these images. The study explores fine-tuning techniques, including bicubic interpolation, ReduceLROnPlateau, and class weight estimation, in order to generalize the model and reduce the risk of overfitting for malware that uses evasion techniques against classification. Taking advantage of transfer learning and the MobileNet architecture, we created a MobileNet fine-tuning (FT) model. The application of this new model in four datasets, including Microsoft Big 2015, Malimg, MaleVis, and a new Fusion dataset, achieved 98.71%, 99.08%, 96.04%, and 98.04% accuracy, respectively, which underscores the robustness of the proposed model. The Fusion dataset is a combination of the first three datasets, consisting of a set of 32,601 known malware image files representing a mix of 59 different families. Despite the success, the study reveals performance deterioration with an increase in the number of malware families, highlighting the need for further exploration into the limits of CNNs in malware classification.