Average Percentage Deviation Research Articles

Tinjauan Kinerja Simpang Empat Bersinyal Menggunakan Program KAJI dan SIDRA (Studi Kasus: Simpang Pasar Moodu, Gorontalo)

The Moodu Market intersection is a signalized intersection formed by the convergence of Jalan Sultan Botutihe-Jalan Matolodula and Jalan Prof Dr. H. Aloei Saboe. This intersection is one of the accesses to the Aloei Saboe Hospital, Fourth Campus of the State University of Gorontalo, offices in Bone Bolango Regency, and close to Moodu market. Large traffic flows that pass through this intersection causes congestion. The purpose of this research was to analyze the permormance of the intersection to determine the level of service at the intersection. The analytical method used to determine the performance of the intersection was conducted using the KAJI and SIDRA programs. Observations were conducted in three days (Monday, 22 March 2021; Thursday, 25 March 2021; and Sunday, 28 March 2021) starting att 06.00-18.00 WITA. The data used in the analysis included the intersection’s geometry, signal time, traffic volume, side barrier, cruise speed, pedestrian, and the population of Gorontalo City. The data was processed to find the values used to determine the performance of the intersection. Based on the results of analysis using the KAJI program, the average delay was 16.73 seconds for the north approach (Jalan Prof. Dr. H. Aloei Saboe), 12.75 seconds for the south approach (Jalan Matolodula), 25.86 seconds for the east approach (Jalan Sultan Botutihe), and 52.67 secinds for the west approach (Jalan Sultan Botutihe). Meanwhile, the results of the analysis using the SIDRA program showed that the average delay was 64.4 seconds for the north approach (Jalan Prof. Dr. H. Aloei Saboe), 13.1 seconds for the south approach (Jalan Matolodula), 42.0 seconds for the east approach (Jalan Sultan Botutihe), and 13.3 seconds the west approach (Jalan Sultan Botutihe). The average delay of the intersection based on the KAJI program was 32.11 seconds where its Level of Service was D while the average delay of the intersection based on the SIDRA program was 36.8 secinds whereas its Level of Service was D. The average percentage difference in the intersection delay using the KAJI and SIDRA Program was 12.75%.

Numerical simulations of turbulent and flow characteristics of complex river reach in Pakistan

The study included the numerical simulation of a curved open channel flow of Chashma Barrage for different velocities along left & right river banks, and water depths downstream of the river reach. The physical model was constructed in one of the experimental trays at the Irrigation Research Institute. Different trials were carried out at low, medium, and high discharges after the calibration of the physical model. A 2D computational fluid dynamics ANSYS FLUENT software was used to simulate various turbulences and flow properties for various discharges (500,000, 800,000, and 957,289 cusecs) using two different turbulent models: k-epsilon and Reynolds’s stress. The simulation findings were compared to the physical modeling results in terms of velocities and water depths for verification. In both velocity (18−27%) and water depth (18−36%) measurements, the k-model had a lower average percentage error than the RS model. On verification using physical modeling, the total average percentage difference from the k-model for all discharges was less than 25%. Numerical simulations based on computational fluid dynamics can be used to better understand turbulence and flow parameters, as well as to assess and develop barrage engineering.

Commissioning a secondary dose calculation software for a 0.35T MR-linac.

Secondary external dose calculations for a 0.35 T magnetic resonance image‐guided radiation therapy (MRgRT) are needed within the radiation oncology community to follow safety standards set forth within the field. We evaluate the commercially available software, RadCalc, in its ability to accurately perform monitor unit dose calculations within a magnetic field. We also evaluate the potential effects of a 0.35 T magnetic field upon point dose calculations.Monitor unit calculations were evaluated with (wMag) and without (noMag) a magnetic field considerations in RadCalc for the ViewRay MRIdian. The magnetic field is indirectly accounted for by using asymmetric profiles for calculation. The introduction of double‐stacked multi‐leaf collimator leaves was also included in the monitor unit calculations and a single transmission value was determined. A suite of simple and complex geometries with a variety field arrangements were calculated for each method to demonstrate the effect of the 0.35 T magnetic field on monitor unit calculations. Finally, 25 patient‐specific treatment plans were calculated using each method for comparison.All simple geometries calculated in RadCalc were within 2% of treatment planning system (TPS) values for both methods, except for a single noMag off‐axis comparison. All complex muilt‐leaf collimator (MLC) pattern calculations were within 5%. All complex phantom geometry calculations were within 5% except for a single field within a lung phantom at a distal point. For the patient calculations, the noMag method average percentage difference was 0.09 ± 2.5% and the wMag average percentage difference was 0.08 ± 2.5%. All results were within 5% for the wMag method.We performed monitor unit calculations for a 0.35 T MRgRT system using a commercially available secondary monitor unit dose calculation software and demonstrated minimal impact of the 0.35 T magnetic field on monitor unit dose calculations. This is the first investigation demonstrating successful calculations of dose using RadCalc in the low‐field 0.35 T ViewRay MRIdian system.

A hash map-based memetic algorithm for the distributed permutation flowshop scheduling problem with preventive maintenance to minimize total flowtime

Distributed scheduling problems have been an active research topic due to their close connection with the multifactory production environment in today’s decentralized economy. In this paper, the distributed permutation flowshop scheduling problem with preventive maintenance is studied with the goal of minimizing the total flowtime. A mathematical model and a hash map-based algorithm are presented to tackle the problem. The Nawaz–Enscore–Ham heuristic is improved and incorporated with the distributed Liu–Reeves heuristic to provide a promising initial solution in a finite number of steps. The proposed algorithm employs the data structure of the hash map to store all the candidate solutions in the form of key–value pairs. The selection, crossover, and mutation operators are also modified to expand the scope of exploration in the discrete domain. The local search hybridizes the job insertion operator and the job swap operator to further improve the obtained offspring solutions and utilizes the characteristic of the population hash map to reduce the efforts of solution evaluations. The candidate solution obtained by the local search is hashed by a rotating hash method and then placed at the node with the corresponding hash code. A series of experiments were conducted to verify the effectiveness of the hybrid local search operators and hash map strategy. Computational results indicate that the multiple strategies not only help to escape from the local optimization but also improve the computational efficiency. When compared with 10 state-of-the-art algorithms, the proposed algorithm generates an average relative percentage deviation of 0.134%, which is significant improvement.

Reparametrised Pöschl–Teller oscillator and analytical molar entropy equation for diatomic molecules

In this study, the reparametrised Pöschl–Teller (RPT) oscillator is constructed for applications to diatomic molecules. Equations for bound state eigen energies and molar entropy are derived for the oscillator. With the aid of the proposed model, seven diatomic molecules are analysed including 7Li2 (a 3Σu +), Na2 (c 1Πu), HCl (X 1Σ+), MgO (X 1Σ+), SO (X 3Σ-), SiO (X 2Σ+), and TiO (X 2Σ+). The average absolute deviation (AAD) and mean absolute percentage deviation (MAPD) are employed as the goodness of fit indicators. Computed AAD and MAPD reveal that the RPT oscillator is an excellent model for the diatomic molecules, the potential is approximately equivalent to the improved Tietz and improved Scarf potentials in the literature. An MAPD of 0.3609% from observed data of gaseous HCl molecule is obtained using the equation of molar entropy proposed in this work. This is an indication that the RPT oscillator is a good model for representing the internal vibration of the HCl molecule.

Heuristics to optimize total completion time subject to makespan in no-wait flow shops with sequence-dependent setup times

We propose four algorithms for the no-wait flow shop scheduling problem. The objective is minimizing total completion time such that makespan is not greater than a maximum value. We address the problem with sequence-dependent setup times, an important production constraint that has never been considered for this problem before. The proposed algorithms start from an initial solution and then iterate through a process that destroys and repairs the incumbent solution in order to improve it. The methods are build combining distinct destruction and construction mechanisms, where the search intensification-diversification is explored at different levels. After an initial assessment, the best proposed algorithm (IG 4) is chosen to be compared with three literature methods (PAL, TOB, ISA-2) developed for similar problems. Computational experiments revealed that the overall average relative percentage deviation of PAL, TOB, ISA-2, and IG 4 are 10.97%, 4.44%, 2.07%, and 0.36%, respectively. The statistical analysis confirms that IG 4 significantly outperforms the existing methods.

Multi-operator immune genetic algorithm for project scheduling with discounted cash flows

The resource constrained project scheduling problem with discounted cash flows (RCPSPDC) is one of the most challenging problems owing to its NP-hard characteristics. This complex combinatorial optimization problem is most relevant to project management, building and construction management, and production planning. Although several solution methods have been suggested to solve the RCPSPDC, no single method has been shown to be the best for a wide range of problems. In this study, a multi-operator immune genetic algorithm, called MO-IGA, is proposed which integrates a genetic algorithm (GA) and an immune algorithm (IA) to solve the RCPSPDC. Two different operators for each crossover, mutation, immunization, and local search operation are utilized dynamically in the MO-IGA framework. Variable insertion neighborhood search (VINS) and forward–backward improvement (FBI) are utilized for local search to enrich the searching behavior and exploration. The algorithm starts with the same probability for each crossover, mutation, immunization, and local search operator; however, the probability is updated dynamically depending on the success of each operator in producing the quality solution. An activity move rule (AMR) has been utilized to delay the task with negative cash flows as much as possible, which further improves the overall project’s net present value (NPV). A standard benchmark dataset, comprising 17,280 project instances ranging from 25 to 100 activities, is used to test the performance and effectiveness of the proposed MO-IGA. The proposed MO-IGA outperforms several datasets based on both a lower value of the average percentage deviation and the number of feasible schedule generations. The proposed MO-IGA is also shown to be more effective than the multi-operator GA (MO-GA) and multi-operator IA (MO-IA). Extensive numerical analysis, statistical tests, and comparisons with state-of-the-art algorithms proves the effectiveness of the proposed approach.

Comparison of Race Time-Differences Between and Within Para and Able-Bodied Cross-Country Skiers.

PurposeTo compare differences in race time (i.e., the average percent difference in race time for each skier compared to the winner, RTdiffs) between female and male Para and able-bodied (AB) skiers, and to examine whether RTdiffs change across seasons.MethodsRace data from World Cups (WCs), World Championships (WCHs), and Paralympic/Olympic Winter Games (PWG/OWGs) of the 2011–2020 seasons was extracted from the website of the International Paralympic Committee and the International Ski Federation. All individual distance races for female and male visually impaired standing (VI), physically impaired sitting (SIT) and standing (STAND), and AB skiers with ≥10 competitors were included in the analyses. We investigated the main effect of skiing groups (i.e., VI, STAND, SIT, and AB skiers) and sex on RTdiffs for top-3 and top-8 skiers. Furthermore, the main effect of season and skiing group on RTdiffs for top-3 and top-8 skiers were investigated. All models were adjusted for distance, skiing style (classical- and freestyle), and event type (WC, WCH, and PWG/OWG).ResultsRTdiffs were significantly larger in Para compared to AB skiers (top-3: 2.1 vs. 0.9%; top-8: 6.2 vs. 2.1%, all p < 0.01), and in female compared to male skiers (top-3: 1.8 vs. 1.3%; top-8: 4.9 vs. 3.5%, all p < 0.05). For top-3 skiers, RTdiffs did not significantly differ between the Para categories (all p > 0.2), while for top-8 skiers RTdiffs were significantly larger for VI compared to SIT and STAND (7.0 vs. 5.5 and 5.6%, respectively, all p < 0.05). RTdiffs were stable across the 2011–2020 seasons for top-3 skiers (VI: 1.7–3.6%, STAND: 1.1–2.2%, SIT: 1.0–3.9%, AB: 0.4–1.1%; all p > 0.1) and top-8 skiers (VI: 3.4–12.0%, STAND: 2.6–5.7%, SIT: 1.9–5.9%, AB: 0.1–1.7%; all p > 0.1).ConclusionThe larger RTdiffs in Para compared to AB skiers indicate larger variability in performance, which are in part disability related. Female skiers displayed larger RTdiffs than their male counterparts, indicating larger variability in performance among the female skiers. Our results provide insights about performance demands in Para cross-country skiing, which is of relevance for coaches and skiers.

Correlation of treatment time to target volume for GammaPod treatments: A simple second calculation.

PurposeThe GammaPod is a novel device for stereotactic breast treatments that employs 25 rotating Co‐60 sources while the patient is continuously translated in three axes to deliver a highly conformal dose to the target. There is no commercial software available for independent second calculations. The purpose of this study is to determine an efficient way to estimate GammaPod treatment times based on target volume and use it as a second calculation for patient‐specific quality assurance.MethodsFifty‐nine GammaPod (Xcision Medical Systems, LLC.) breast cancer patient treatments were used as the fitting dataset for this study. Similar to the Curie‐seconds concept in brachytherapy, we considered dose‐rate × time/(prescribed dose) as a function of target volumes. Using a MATLAB (Mathworks, Natick, MA, USA) script, we generated linear (with 95% confidence interval (CI)) and quadratic fits and tested the resulting equations on an additional set of 30 patients.ResultsWe found a strong correlation between the dose‐rate × time/(prescribed dose) and patients’ target volumes for both the linear and quadratic models. The linear fit was selected for use and using the polyval function in MATLAB, a 95% CI graph was created to depict the accuracy of the prediction for treatment times. Testing the model on 30 additional patients with target volumes ranging from 20 to 188 cc yielded treatment times from 10 to 25 min that in all cases were within the predicted CI. The average absolute difference between the predicted and actual treatment times was 1.0 min (range 0–3.3 min). The average percent difference was 5.8% (range 0%–18.4%).ConclusionThis work has resulted in a viable independent calculation for GammaPod treatment times. This method has been implemented as a spreadsheet that is ready for clinical use to predict and verify the accuracy of breast cancer treatment times.

Monte Carlo simulations and phantom validation of low-dose radiotherapy to the lungs using an interventional radiology C-arm fluoroscope.

To use MC simulations and phantom measurements to investigate the dosimetry of a kilovoltage x-ray beam from an IR fluoroscope to deliver low-dose (0.3-1.0Gy) radiotherapy to the lungs. PENELOPE was used to model a 125kV, 5.94mm Al HVL x-ray beam produced by a fluoroscope. The model was validated through depth-dose, in-plane/cross-plane profiles and absorbed dose at 2.5-, 5.1-, 10.2- and 15.2-cm depths against the measured beam in an acrylic phantom. CT images of an anthropomorphic phantom thorax/lungs were used to simulate 0.5Gy dose distributions for PA, AP/PA, 3-field and 4-field treatments. DVHs were generated to assess the dose to the lungs and nearby organs. Gafchromic film was used to measure doses in the phantom exposed to PA and 4-field treatments, and compared to the MC simulations. Depth-dose and profile results were within 3.2% and 7.8% of the MC data uncertainty, respectively, while dose gamma analysis ranged from 0.7 to 1.0. Mean dose to the lungs were 1.1-, 0.8-, 0.9-, and 0.8- Gy for the PA, AP/PA, 3-field, and 4-field after isodose normalization to cover∼95% of each lung volume. Skin dose toxicity was highest for the PA and lowest for the 4-field, and both arrangements successfully delivered the treatment on the phantom. However, the dose distribution for the PA was highly non-uniform and produced skin doses up to 4Gy. The dose distribution for the 4-field produced a uniform 0.6Gy dose throughout the lungs, with a maximum dose of 0.73Gy. The average percent difference between experimental and Monte Carlo values were -0.1% (range -3% to +4%) for the PA treatment and 0.3% (range -10.3% to +15.2%) for the 4-field treatment. A 125kV x-ray beam from an IR fluoroscope delivered through two or more fields can deliver an effective low-dose radiotherapy treatment to the lungs. The 4-field arrangement not only provides an effective treatment, but also significant dose sparing to healthy organs, including skin, compared to the PA treatment. Use of fluoroscopy appears to be a viable alternative to megavoltage radiation therapy equipment for delivering low-dose radiotherapy to the lungs.

Estimating the Relative Crystallinity of Biodegradable Polylactic Acid and Polyglycolide Polymer Composites by Machine Learning Methodologies.

Biodegradable polymers have recently found significant applications in pharmaceutics processing and drug release/delivery. Composites based on poly (L-lactic acid) (PLLA) have been suggested to enhance the crystallization rate and relative crystallinity of pure PLLA polymers. Despite the large amount of experimental research that has taken place to date, the theoretical aspects of relative crystallinity have not been comprehensively investigated. Therefore, this research uses machine learning methods to estimate the relative crystallinity of biodegradable PLLA/PGA (polyglycolide) composites. Six different artificial intelligent classes were employed to estimate the relative crystallinity of PLLA/PGA polymer composites as a function of crystallization time, temperature, and PGA content. Cumulatively, 1510 machine learning topologies, including 200 multilayer perceptron neural networks, 200 cascade feedforward neural networks (CFFNN), 160 recurrent neural networks, 800 adaptive neuro-fuzzy inference systems, and 150 least-squares support vector regressions, were developed, and their prediction accuracy compared. The modeling results show that a single hidden layer CFFNN with 9 neurons is the most accurate method for estimating 431 experimentally measured datasets. This model predicts an experimental database with an average absolute percentage difference of 8.84%, root mean squared errors of 4.67%, and correlation coefficient (R2) of 0.999008. The modeling results and relevancy studies show that relative crystallinity increases based on the PGA content and crystallization time. Furthermore, the effect of temperature on relative crystallinity is too complex to be easily explained.

Design and testing of an automated cookstove fuel feeder for standardized laboratory testing

Laboratory testing of cookstoves aims to compare performance of stove designs under controlled and uniform conditions, with fuel feeding being an important parameter. This study explores whether a robotic cookstove feeder can reduce variability between laboratory tests of a cookstove, produce statistically similar firepower and measured emissions rates, and reduce tester interaction time during standard cookstove testing as compared to a trained human operator. A series of modified ISO/FDIS 19867-1 tests were performed by the robotic cookstove feeder designed for this project and compared to equivalent tests performed by two human operators. Testing included four unique configurations, two levels of firepower per configuration, and five replicates per firepower. The results showed that the robot cookstove feeder did not reduce variability, but was as consistent as the results from the human tests. A matched pair t-test at a 90% confidence interval revealed no statistical difference in firepower or PM2.5 emissions rates. However, the human and robot's CO2 emissions rates were very similar, with the robot average lower by 6.2% (SD = 6.4%) and higher by 4.2% (SD = 6.2%) on average for the high and medium testing power respectively. The human and robot's CO emissions rates differed more, with the average percent difference being 9.8% (SD = 25.4%) higher for the robot at high power and 21.7% (SD = 19.5%) higher for the medium power. A comparison of the tester interaction time showed that the robot on average saved the operator some time, although additional data are needed for this metric. Finally, there were mixed feelings about usability from the operators, with one operator reporting that the robot did not reduce the testing burden significantly. The results indicate that the robot is capable of performing repeatable cookstove testing and future iterations of the robot may provide opportunities to increase consistency in testing across cookstoves, operators, and testing facilities.

Surface tension of binary mixtures of benzene + propionic acid and butanoic acid between 298.15 K and 318.15 K: Measurement and modeling

Experimental measurement of the surface tension of benzene + propanoic acid and benzene + butanoic acid has been carried out in the temperature range of 298.15 K to 318.15 K and atmospheric pressure. 170 new experimental points of surface tension have been obtained. Three theoretical models, i.e., Linear gradient theory (LGT), Shereshefsky model (SM), and the extended Langmuir model (LM), were used to modeling the surface tension and adsorption phenomenon of these binary mixtures. The three models correlated the surface tension of the benzene + carboxylic acid mixtures, and the average percent deviation was, 0.04% for LGT, 0.08% for SM, and 0.05% for LM. The Helmholtz density term and the liquid and vapor densities required in computing density with LGT were obtained with perturbed chain-statistical associating fluid theory equation of state (PC-SAFT EOS). Based on SM, the standard Gibbs energy of adsorption and the free energy change in the surface region were calculated. The free energy change was used to obtain the excess number of molecular layers in the surface region. The required parameters of the LM were adjusted, the standard Gibbs energy of adsorption was calculated, and negative deviations from ideality were determined. Also mole fractions of solute 0at surface were calculated by using LM. Additionally, by using surface tensions at different temperatures, specific surface enthalpy and specific surface entropy were calculated for (benzene + carboxylic acid) mixtures.

Volume fraction based Hind-Ubbelohde approach predicts viscosity with higher accuracy

In the present work, an attempt has been made to explore a modification by using a volume fraction HU approach. This proposed modification has been tested for 196 binaries, 13 ternaries and 5 quaternary mixtures over varying temperatures. The results have been discussed by comparing the Average Absolute Percentage Deviation (AAPD) as a benchmark for agreement with experimental findings. The Grand AAPDs give a clear superiority to the proposed approach as compared to the original HU and other approaches.

How state agencies are managing chronic wasting disease

ABSTRACT Chronic wasting disease (CWD) affects cervids. This research note described a U.S. national survey of ongoing management and communication efforts by state wildlife agencies in response to CWD. Questionnaires were distributed to all 50 states in 2020 (response rate = 76%, n = 38). States with CWD were predicted to differ from states with no known cases of this disease (independent variable). The dependent variables were all related to CWD: current and proposed surveillance, current practices, public involvement, survey research, and other communication forms. Across all 47 variables, the average percent difference between CWD and non-CWD states was 27%, all but seven comparisons were double-digit differences, and the overall average for the effect sizes was .30. Although the findings implied that CWD states were more engaged with the disease, non-CWD states need to recognize that the disease shows no signs of slowing down and will likely spread to most states.

Determination of aflatoxin B1 in wheat based on colourimetric sensor array technology: Optimization of sensor features and model parameters to improve the model generalization performance

Wheat is highly susceptible to contamination by fungal toxins during storage and transportation. Among them, aflatoxin B1 (AFB1) is the most common, has the highest degree of pollution and is the most toxic and carcinogenic. Therefore, this study proposed a novel means for the detection of AFB1 content in wheat according to colourimetric sensor array technology. A highly specific colourimetric sensor array was prepared to collect volatile gas information of wheat samples. The firefly algorithm and the sparrow search algorithm (SSA) were applied to optimize the sensor features and the parameters of the back propagation neural network (BPNN), respectively. The results obtained showed that the average correlation coefficient of prediction (RP) of the optimized BPNN model improved from 0.94 to 0.97, the average root mean square error of prediction (RMSEP) decreased from 3.6 to 2.5 and the average relative percent deviation (RPD) increased from 4.3 to 6.2. The results of the study show that it is feasible to achieve AFB1 detection in wheat using a specific colourimetric sensor array. In addition, the optimization of the enter characteristics and parameters of the model is necessary in the model calibration process to enhance the predictive performance and stability of the model while reducing the model complexity to a certain extent.

Deep Reinforcement Learning-Based Job Shop Scheduling of燬mart燤anufacturing

Industry 4.0 production environments and smart manufacturing systems integrate both the physical and decision-making aspects of manufacturing operations into autonomous and decentralized systems. One of the key aspects of these systems is a production planning, specifically, Scheduling operations on the machines. To cope with this problem, this paper proposed a Deep Reinforcement Learning with an Actor-Critic algorithm (DRLAC). We model the Job-Shop Scheduling Problem (JSSP) as a Markov Decision Process (MDP), represent the state of a JSSP as simple Graph Isomorphism Networks (GIN) to extract nodes features during scheduling, and derive the policy of optimal scheduling which guides the included node features to the best next action of schedule. In addition, we adopt the Actor-Critic (AC) network’s training algorithm-based reinforcement learning for achieving the optimal policy of the scheduling. To prove the proposed model’s effectiveness, first, we will present a case study that illustrated a conflict between two job scheduling, secondly, we will apply the proposed model to a known benchmark dataset and compare the results with the traditional scheduling methods and trending approaches. The numerical results indicate that the proposed model can be adaptive with real-time production scheduling, where the average percentage deviation (APD) of our model achieved values between 0.009 and 0.21 compared with heuristic methods and values between 0.014 and 0.18 compared with other trending approaches.

The Reproducibility of Global Longitudinal Strain in Normal and Hypertensive Patients: A Single Centre Study

Hypertensive patients may encounter early and subtle myocardial changes. Global longitudinal strain (GLS) enables the early detection of left ventricular (LV) systolic dysfunction. Inter-observer variability and training duration are known limitations of GLS. The aims of the study were to: (A) Measure GLS in both normal and healthy individuals; and (B) Test the intra-and-inter observer GLS measurement variability in both groups. The study included 30 participants: 15 healthy individuals (group 1) and 15 hypertensive individuals (group 2) were included using strict exclusion criteria. LV GLS was measured in all participants using two-dimensional speckle-tracking echocardiography. Images were acquired and measured by one sonographer-operator and re-measured by two independent sonographers-observers one and two. Average GLS for group 1(-17.4%+/-1.6). Average GLS for group 2 (-17.0%+/-1.6). Weich-two sample t-test p= 0.46. The average percentage differences of the GLS measurements between the operator and two observer groups had a relatively small delta between groups, the greatest variability was seen in the HTN group (Graph 1). When examining these results further, it showed there was greater variability amongst observer 1 measurements with an average percentage difference of -0.6+/-2.3 in comparison to original operator -0.2 +/-1.8. The average percentage difference in LV GLS for the single operator was less than for the two observers, indicating that the inter-observer variability is an important limitation to consider when analysing measurements. While a statistically non-significant reduction in LV GLS in hypertensive-patients was found, a larger sample size along with allowance for GLS differences between sexes may yield different results.

Measurement of Oil–Gas–Water Flows in Vertical Pipes Using Electromagnetic Flowmeter and Dual-Conductance Sensors

Three-phase flows are significantly complicated in comparison to single-phase flows and gas&#x2013;liquid two-phase flows. So far, faced with the presence of two nonconductive dispersed phases in oil&#x2013;gas&#x2013;water three-phase flows, the measurement characteristics of electromagnetic flowmeter (EMF) in three-phase flows are an unresolved problem. The flowrate of three-phase flows is difficult to measure due to the nonuniformity arising from interactions between dispersed phases. Aiming at the difficult problem of production logging in oil wells of three-phase flows, this article reports an experimental study on measuring three-phase flows via the EMF and the dual-conductance sensors. Among them, the phase holdups of three-phase flow in vertical pipe are extracted through newly designed distributed coaxial double-ring conductance sensor (DRCS) and rotating electric field conductance sensor (REFCS). A three-phase flow loop test in a pipe of 20 mm inner diameter is carried out. The results show that the EMF has the ability to substantively measure the flowrate of water phase under three flow patterns (bubble, slug, and churn flows) when the water cut is above 60&#x0025;, and the average absolute percentage deviation (AAPD) for prediction of superficial water velocity is 3.55&#x0025;. The measurement of superficial gas and oil velocities is implemented by solving the drift-flux models of three-phase flow based on the phase holdups and superficial water velocity, and the AAPDs for predictions of superficial gas and oil velocities are 4.33&#x0025; and 5.95&#x0025;, respectively. This research provides a new measurement strategy for production logging of oil, gas, and water three-phase flow production profile by combining the EMF with dual-conductance sensors.

Exact Three-Dimensional Stability Analysis of Plate Using an Direct Variational Energy Method

In this paper, direct variational calculus was put into practical use to analyses the three dimensional (3D) stability of rectangular thick plate which was simply supported at all the four edges (SSSS) under uniformly distributed compressive load. In the analysis, both trigonometric and polynomial displacement functions were used. This was done by formulating the equation of total potential energy for a thick plate using the 3D constitutive relations, from then on, the equation of compatibility was obtained to determine the relationship between the rotations and deflection. In the same way, governing equation was obtained through minimization of the total potential energy functional with respect to deflection. The solution of the governing equation is the function for deflection. Functions for rotations were obtained from deflection function using the solution of compatibility equations. These functions, deflection and rotations were substituted back into the energy functional, from where, through minimizations with respect to displacement coefficients, formulas for analysis were obtained. In the result, the critical buckling loads from the present study are higher than those of refined plate theories with 7.70%, signifying the coarseness of the refined plate theories. This amount of difference cannot be overlooked. However, it is shown that, all the recorded average percentage differences between trigonometric and polynomial approaches used in this work and those of 3D exact elasticity theory is lower than 1.0%, confirming the exactness of the present theory. Thus, the exact 3D plate theory obtained, provides a good solution for the stability analysis of plate and, can be recommended for analysis of any type of rectangular plates under the same loading and boundary condition. Doi: 10.28991/CEJ-2022-08-01-05 Full Text: PDF