Search results for: error rate

Authors: Prashant Pandey

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In the present article, an effective Laguerre collocation method is used to obtain the approximate solution of a system of coupled fractional-order non-linear reaction-advection-diffusion equation with prescribed initial and boundary conditions. In the proposed scheme, Laguerre polynomials are used together with an operational matrix and collocation method to obtain approximate solutions of the coupled system, so that our proposed model is converted into a system of algebraic equations which can be solved employing the Newton method. The solution profiles of the coupled system are presented graphically for different particular cases. The salient feature of the present article is finding the stability analysis of the proposed method and also the demonstration of the lower variation of solute concentrations with respect to the column length in the fractional-order system compared to the integer-order system. To show the higher efficiency, reliability, and accuracy of the proposed scheme, a comparison between the numerical results of Burger’s coupled system and its existing analytical result is reported. There are high compatibility and consistency between the approximate solution and its exact solution to a higher order of accuracy. The exhibition of error analysis for each case through tables and graphs confirms the super-linearly convergence rate of the proposed method.

Keywords: fractional coupled PDE, stability and convergence analysis, diffusion equation, Laguerre polynomials, spectral method

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Authors: Lebogang Jane Msiza, Felix Dapare Dakora

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Photosynthesis is a process by which plants convert light energy to chemical energy for metabolic processes. Plants are known for converting inorganic CO₂ in the atmosphere to organic C by photosynthesis. A decrease in stomatal conductance causes a decrease in the transpiration rate of leaves, thus increasing the water-use efficiency of plants. Water-use efficiency in plants is conditioned by soil moisture availability and is enhanced under conditions of water deficit. This study evaluated leaf photosynthesis and water-use efficiency in 12 legume species inoculated with 26 rhizobial isolates from soybean, 15 from common bean, 10 from cowpea, 15 from Bambara groundnut, 7 from lessertia and 10 from Kersting bean. Gas-exchange studies were used to measure photosynthesis and water-use efficiency. The results revealed a much higher photosynthetic rate (20.95µmol CO₂ m-2s-1) induced by isolated tutpres to a lower rate (7.06 µmol CO₂ m-2s-1) by isolate mgsa 88. Stomatal conductance ranged from to 0.01 mmol m-2.s-1 by mgsa 88 to 0.12 mmol m-2.s-1 by isolate da-pua 128. Transpiration rate also ranged from 0.09 mmol m-2.s-1 induced by da-pua B2 to 3.28 mmol m-2.s-1 by da-pua 3, while water-use efficiency ranged from 91.32 µmol CO₂ m-1 H₂O elicited by mgsa 106 to 4655.50 µmol CO₂ m-1 H₂O by isolate tutswz 13. The results revealed the highest photosynthetic rate in soybean and the lowest in common bean, and also with higher stomatal conductance and transpiration rates in jack bean and Bambara groundnut. Pigeonpea exhibited much higher water-use efficiency than all the tested legumes. The findings showed significant differences between and among the test legume/rhizobia combinations. Leaf photosynthetic rates are reported to be higher in legumes with high stomatal conductance, which suggests that legume productivity can be improved by manipulating leaf stomatal conductance.

Keywords: legumes, photosynthetic rate, stomatal conductance, water-use efficiency

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Authors: Xiaopeng Shang, Xin YU, Jun CHANG

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Calcium barium sulphoaluminate (CBSA), derived from calcium sulphoaluminate(CSA), has excellent cementitious properties. In this study, the sintering system of CBSA with a theoretical stoichiometric Ca3BaAl6SO16 was investigated. Rietveld refinement was performed using TOPAS 4.2 software to quantitatively calculate the content of CBSA and the actual ionic site occupancy of Ba2+. The results indicate that the contents of Ca4-xBaxAl6SO16 increases with increasing sintering temperature in the 1200℃-1400℃ ranges. When sintered at 1400℃ for 180min, the content of CBSA reaches 88.4%. However, CBSA begins to decompose at 1440℃ and the content of which decreases. The replacement rate of Ba2+ was also enlarged by increasing sintering temperature and prolonged sintering time. Sintering at 1400℃ for 180min is considered as the optimum when replacement rate of Ba2+ and the content of CBSA were taken into account. Ca3.2Ba0.8Al6SO16 with a content of 88.4% was synthesized.

Keywords: calcium barium sulphoaluminate, sintering system, Ba2+ replacement rate, Rietveld refinement

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Authors: Weishou Shen, Chunyan Yang, Zhongliang Li

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The crop climate productivity and the distribution of cropland reflect long-term adaption of agriculture to climate. In order to fully understand the impact of climate change on cropland ecosystem in Tibet, the spatiotemporal changes of crop climate productivity and cropland distribution were analyzed with the help of GIS and RS software. Results indicated that the climate change to the direction of wet and warm in Tibet in the recent 30 years, with a rate of 0.79℃/10 yr and 23.28 mm/10yr respectively. Correspondingly, the climate productivity increased gradually, with a rate of 346.3kg/(hm2•10a), of which, the fastest-growing rate of the crop climate productivity is in Southern Tibet Mountain- plain-valley. During the study period, the total cropland area increased from 32.54 million ha to 37.13 million ha, and cropland has expanded to higher altitude area and northward. Overall, increased cropland area and crop climate productivity due to climate change plays a positive role for agriculture in Tibet.

Keywords: climate change, productivity, cropland area, Tibet plateau

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Authors: Alastair Hales, Xi Jiang

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Numerical methods are used to evaluate the operation of confined face-to-face piezoelectric fan arrays as pitch, P, between the blades is varied. Both in-phase and counter-phase oscillation are considered. A piezoelectric fan consists of a fan blade, which is clamped at one end, and an extremely low powered actuator. This drives the blade tip’s oscillation at its first natural frequency. Sufficient blade tip speed, created by the high oscillation frequency and amplitude, is required to induce vortices and downstream volume flow in the surrounding air. A single piezoelectric fan may provide the ideal solution for low powered hot spot cooling in an electronic device, but is unable to induce sufficient downstream airflow to replace a conventional air mover, such as a convection fan, in power electronics. Piezoelectric fan arrays, which are assemblies including multiple fan blades usually in face-to-face orientation, must be developed to widen the field of feasible applications for the technology. The potential energy saving is significant, with a 50% power demand reduction compared to convection fans even in an unoptimised state. A numerical model of a typical piezoelectric fan blade is derived and validated against experimental data. Numerical error is found to be 5.4% and 9.8% using two data comparison methods. The model is used to explore the variation of pitch as a function of amplitude, A, for a confined two-blade piezoelectric fan array in face-to-face orientation, with the blades oscillating both in-phase and counter-phase. It has been reported that in-phase oscillation is optimal for generating maximum downstream velocity and flow rate in unconfined conditions, due at least in part to the beneficial coupling between the adjacent blades that leads to an increased oscillation amplitude. The present model demonstrates that confinement has a significant detrimental effect on in-phase oscillation. Even at low pitch, counter-phase oscillation produces enhanced downstream air velocities and flow rates. Downstream air velocity from counter-phase oscillation can be maximally enhanced, relative to that generated from a single blade, by 17.7% at P = 8A. Flow rate enhancement at the same pitch is found to be 18.6%. By comparison, in-phase oscillation at the same pitch outputs 23.9% and 24.8% reductions in peak downstream air velocity and flow rate, relative to that generated from a single blade. This optimal pitch, equivalent to those reported in the literature, suggests that counter-phase oscillation is less affected by confinement. The optimal pitch for generating bulk airflow from counter-phase oscillation is large, P > 16A, due to the small but significant downstream velocity across the span between adjacent blades. However, by considering design in a confined space, counterphase pitch should be minimised to maximise the bulk airflow generated from a certain cross-sectional area within a channel flow application. Quantitative values are found to deviate to a small degree as other geometric and operational parameters are varied, but the established relationships are maintained.

Keywords: piezoelectric fans, low energy cooling, power electronics, computational fluid dynamics

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Authors: David F. Nettleton, Elodie Bugnicourt, Christian Wasiak, Alejandro Rosales

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In this presentation, preliminary results are given for the modeling and calibration of two different industrial winding MIMO (Multiple Input Multiple Output) processes using machine learning techniques. In contrast to previous approaches which have typically used ‘black-box’ linear statistical methods together with a definition of the mechanical behavior of the process, we use non-linear machine learning algorithms together with a ‘white-box’ rule induction technique to create a supervised model of the fitting error between the expected and real force measures. The final objective is to build a precise model of the winding process in order to control de-tension of the material being wound in the first case, and the friction of the material passing through the die, in the second case. Case 1, Tension Control of a Winding Process. A plastic web is unwound from a first reel, goes over a traction reel and is rewound on a third reel. The objectives are: (i) to train a model to predict the web tension and (ii) calibration to find the input values which result in a given tension. Case 2, Friction Force Control of a Micro-Pullwinding Process. A core+resin passes through a first die, then two winding units wind an outer layer around the core, and a final pass through a second die. The objectives are: (i) to train a model to predict the friction on die2; (ii) calibration to find the input values which result in a given friction on die2. Different machine learning approaches are tested to build models, Kernel Ridge Regression, Support Vector Regression (with a Radial Basis Function Kernel) and MPART (Rule Induction with continuous value as output). As a previous step, the MPART rule induction algorithm was used to build an explicative model of the error (the difference between expected and real friction on die2). The modeling of the error behavior using explicative rules is used to help improve the overall process model. Once the models are built, the inputs are calibrated by generating Gaussian random numbers for each input (taking into account its mean and standard deviation) and comparing the output to a target (desired) output until a closest fit is found. The results of empirical testing show that a high precision is obtained for the trained models and for the calibration process. The learning step is the slowest part of the process (max. 5 minutes for this data), but this can be done offline just once. The calibration step is much faster and in under one minute obtained a precision error of less than 1x10-3 for both outputs. To summarize, in the present work two processes have been modeled and calibrated. A fast processing time and high precision has been achieved, which can be further improved by using heuristics to guide the Gaussian calibration. Error behavior has been modeled to help improve the overall process understanding. This has relevance for the quick optimal set up of many different industrial processes which use a pull-winding type process to manufacture fibre reinforced plastic parts. Acknowledgements to the Openmind project which is funded by Horizon 2020 European Union funding for Research & Innovation, Grant Agreement number 680820

Keywords: data model, machine learning, industrial winding, calibration

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Authors: Erfan Niazi, Marianne Fenech

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Red Blood Cells (RBCs) or erythrocytes tend to form chain-like aggregates under low shear rate called rouleaux. This is a reversible process and rouleaux disaggregate in high shear rates. Therefore, RBCs aggregation occurs in the microcirculation where low shear rates are present but does not occur under normal physiological conditions in large arteries. Numerical modeling of RBCs interactions is fundamental in analytical models of a blood flow in microcirculation. Population Balance Modeling (PBM) is particularly useful for studying problems where particles agglomerate and break in a two phase flow systems to find flow characteristics. In this method, the elementary particles lose their individual identity due to continuous destructions and recreations by break-up and agglomeration. The aim of this study is to find RBCs aggregation in a dynamic situation. Simplified PBM was used previously to find the aggregation rate on a static observation of the RBCs aggregation in a drop of blood under the microscope. To find aggregation rate in a dynamic situation we propose an experimental set up testing RBCs sedimentation. In this test, RBCs interact and aggregate to form rouleaux. In this configuration, disaggregation can be neglected due to low shear stress. A high-speed camera is used to acquire video-microscopic pictures of the process. The sizes of the aggregates and velocity of sedimentation are extracted using an image processing techniques. Based on the data collection from 5 healthy human blood samples, the aggregation rate was estimated as 2.7x10³(±0.3 x10³) 1/s.

Keywords: red blood cell, rouleaux, microfluidics, image processing, population balance modeling

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Authors: Waleed A. Basuliman, Khalid S. AlSaleh, Mohamed Z. Ramadan

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Applying the anthropometric dimensions is considered one of the important factors when designing any human-machine system. In this study, the estimation of anthropometric dimensions has been improved by developing artificial neural network that aims to predict the anthropometric measurements of the male in Saudi Arabia. A total of 1427 Saudi males from age 6 to 60 participated in measuring twenty anthropometric dimensions. These anthropometric measurements are important for designing the majority of work and life applications in Saudi Arabia. The data were collected during 8 months from different locations in Riyadh City. Five of these dimensions were used as predictors variables (inputs) of the model, and the remaining fifteen dimensions were set to be the measured variables (outcomes). The hidden layers have been varied during the structuring stage, and the best performance was achieved with the network structure 6-25-15. The results showed that the developed Neural Network model was significantly able to predict the body dimensions for the population of Saudi Arabia. The network mean absolute percentage error (MAPE) and the root mean squared error (RMSE) were found 0.0348 and 3.225 respectively. The accuracy of the developed neural network was evaluated by compare the predicted outcomes with a multiple regression model. The ANN model performed better and resulted excellent correlation coefficients between the predicted and actual dimensions.

Keywords: artificial neural network, anthropometric measurements, backpropagation, real anthropometric database

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Authors: Himanshu Singh, Rishi Kant, Shantanu Bhattacharya

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This paper adopts a top-down approach for mathematical modeling to predict the size reduction from micro to nano-scale through persistent etching. The process is simulated using a finite difference approach. Previously, various researchers have simulated the etching process for 1-D and 2-D substrates. It consists of two processes: 1) Convection-Diffusion in the etchant domain; 2) Chemical reaction at the surface of the particle. Since the process requires analysis along moving boundary, partial differential equations involved cannot be solved using conventional methods. In 1-D, this problem is very similar to Stefan's problem of moving ice-water boundary. A fixed grid method using finite volume method is very popular for modelling of etching on a one and two dimensional substrate. Other popular approaches include moving grid method and level set method. In this method, finite difference method was used to discretize the spherical diffusion equation. Due to symmetrical distribution of etchant, the angular terms in the equation can be neglected. Concentration is assumed to be constant at the outer boundary. At the particle boundary, the concentration of the etchant is assumed to be zero since the rate of reaction is much faster than rate of diffusion. The rate of reaction is proportional to the velocity of the moving boundary of the particle. Modelling of the above reaction was carried out using Matlab. The initial particle size was taken to be 50 microns. The density, molecular weight and diffusion coefficient of the substrate were taken as 2.1 gm/cm3, 60 and 10-5 cm2/s respectively. The etch-rate was found to decline initially and it gradually became constant at 0.02µ/s (1.2µ/min). The concentration profile was plotted along with space at different time intervals. Initially, a sudden drop is observed at the particle boundary due to high-etch rate. This change becomes more gradual with time due to declination of etch rate.

Keywords: particle size reduction, micromixer, FDM modelling, wet etching

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Authors: S. Aisyah Azizan, M. Syafiq Azmi, Yuki Harada, Yoshinobu Maeda, Takaomi Matsutani

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We introduced an all-optical multi-casting characteristics with wavelength conversion based on a novel all-optical triode using negative feedback semiconductor optical amplifier. This study was demonstrated with a transfer speed of 10 Gb/s to a non-return zero 231-1 pseudorandom bit sequence system. This multi-wavelength converter device can simultaneously provide three channels of output signal with the support of non-inverted and inverted conversion. We studied that an all-optical multi-casting and wavelength conversion accomplishing cross gain modulation is effective in a semiconductor optical amplifier which is effective to provide an inverted conversion thus negative feedback. The relationship of received power of back to back signal and output signals with wavelength 1535 nm, 1540 nm, 1545 nm, 1550 nm, and 1555 nm with bit error rate was investigated. It was reported that the output signal wavelengths were successfully converted and modulated with a power penalty of less than 8.7 dB, which the highest is 8.6 dB while the lowest is 4.4 dB. It was proved that all-optical multi-casting and wavelength conversion using an optical triode with a negative feedback by three channels at the same time at a speed of 10 Gb/s is a promising device for the new wavelength conversion technology.

Keywords: cross gain modulation, multicasting, negative feedback optical amplifier, semiconductor optical amplifier

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Authors: Mumtaz Begum Mustafa, Siti Salwah Salim, Feizal Dani Rahman

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Recently, Automatic Speech Recognition (ASR) systems were used to assist children in language acquisition as it has the ability to detect human speech signal. Despite the benefits offered by the ASR system, there is a lack of ASR systems for Malay-speaking children. One of the contributing factors for this is the lack of continuous speech database for the target users. Though cross-lingual adaptation is a common solution for developing ASR systems for under-resourced language, it is not viable for children as there are very limited speech databases as a source model. In this research, we propose a two-stage adaptation for the development of ASR system for Malay-speaking children using a very limited database. The two stage adaptation comprises the cross-lingual adaptation (first stage) and cross-age adaptation. For the first stage, a well-known speech database that is phonetically rich and balanced, is adapted to the medium-sized Malay adults using supervised MLLR. The second stage adaptation uses the speech acoustic model generated from the first adaptation, and the target database is a small-sized database of the target users. We have measured the performance of the proposed technique using word error rate, and then compare them with the conventional benchmark adaptation. The two stage adaptation proposed in this research has better recognition accuracy as compared to the benchmark adaptation in recognizing children’s speech.

Keywords: Automatic Speech Recognition System, children speech, adaptation, Malay

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Authors: Dhawal Ladani

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Shell and tube type heat exchangers are predominantly used in heat exchange between two fluids and other applications. This paper projects the optimal design of the pipe used in the heat exchanger in such a way to minimize the vibration occurring in the pipe. Paper also consists of the comparison of the different design of the pipe to get the maximize the heat transfer rate by converting laminar flow into the turbulent flow. By the updated design the vibration in the pipe due to the flow is also decreased. Computational Fluid Dynamics and Thermal Heat Transfer analysis are done to justifying the result. Currently, the straight pipe is used in the shell and tube type of heat exchanger where as per the paper the pipe consists of the curvature along with the pipe. Hence, the heat transfer area is also increased and result in the increasing in heat transfer rate. Curvature type design is useful to create turbulence and minimizing the vibration, also. The result will give the output comparison of the effect of laminar flow and the turbulent flow in the heat exchange mechanism, as well as, inverse effect of the boundary layer in heat exchanger is also justified.

Keywords: heat exchanger, heat transfer rate, laminar and turbulent effect, shell and tube

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Authors: Mohamed Ahmed Gesraha, Amany Ramadan Ebeid

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Aphids are noxious and serious persistent pests in the open fields worldwide. Many authors studied the possibility of aphid control by applying Ladybirds and Lacewings at different releasing rates under open-field conditions. Results clarify that releasing 3rd instar larvae of Coccinella undecimpunctata at the rate of 1 larva:50 aphid was more effective than 1:100 or 1:200 rates for controlling Aphis gossypii population in Okra field; reflecting more than 90% reduction in the aphid population within 15 days. When Chrysoperla carnea 2nd larval instar were releasing at 1:5, 1:10, and 1:20 (predator: aphid), it was noticed that the former rate was the most effective one, inducing 98.93% reduction in aphid population; while the two other rates reflecting less reduction. Additionally, in the case of double releases, the reduction percentage at the 1:5 rate was 99.63%, emphasize that this rate was the most effective one; the other rates induced 97.05 and 95.64% reduction. Generally, a double release was more effective in all tested rates than the single one because of the cumulative existence of the predators in large numbers at the same period of the experiment. It could be concluded that utilizing insect predators (Coccinella undecimpunctata or Chrysoperla carnea) at an early larval stag were faire enough to reduce the aphids’ populations under open fields conditions.

Keywords: releasing predators, lacewings, ladybird, open fields

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Authors: Witthaya Mekhum, Wutthikorn Malikong

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The objective of this study is to investigate the increasing desktop computer performance after overclocking central processing unit or CPU by running a computer component at a higher clock rate (more clock cycles per second) than it was designed at the rate of 0.1 GHz for each level or 100 MHz starting at 4000 GHz-4500 GHz. The computer performance is tested for each level with 4 programs, i.e. Hyper PI ver. 0.99b, Cinebench R15, LinX ver.0.6.4 and WinRAR . After the CPU overclock, the computer performance increased. When overclocking CPU at 29% the computer performance tested by Hyper PI ver. 0.99b increased by 10.03% and when tested by Cinebench R15 the performance increased by 20.05% and when tested by LinX Program the performance increased by 16.61%. However, the performance increased only 8.14% when tested with Winrar program. The computer performance did not increase according to the overclock rate because the computer consists of many components such as Random Access Memory or RAM, Hard disk Drive, Motherboard and Display Card, etc.

Keywords: overclock, performance, central processing unit, computer

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Authors: Dojoon Jung, Kiwoong Moon, Joong Lee

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The height of criminals is one of the important clues that can determine the scope of the suspect's search or exclude the suspect from the search target. Although measuring the height of criminals by video alone is limited by various reasons, the 3D data of the scene and the Closed Circuit Television (CCTV) footage are matched, the height of the criminal can be measured. However, it is still difficult to measure the height of CCTV footage in the non-contact type measurement method because of variables such as position, posture, and head shape of criminals. In this paper, we propose a method of matching the CCTV footage with the 3D data on the crime scene and measuring the height of the person using the 3D human body model in the matched data. In the proposed method, the height is measured by using 3D human model in various scenes of the person in the CCTV footage, and the measurement value of the target person is corrected by the measurement error of the replay CCTV footage of the reference person. We tested for 20 people's walking CCTV footage captured from an indoor and an outdoor and corrected the measurement values with 5 reference persons. Experimental results show that the measurement error (true value-measured value) average is 0.45 cm, and this method is effective for the measurement of the person's height in CCTV footage.

Keywords: human height, CCTV footage, 2D/3D matching, 3D human body model

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Authors: Gómez Romero Jacob, García Peña Elvia Inés

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The co-digestion process of crude cheese whey (CCW) with fruit vegetable waste (FVW) for biohydrogen production was investigated in batch and continuous systems, in stirred 1.8 L bioreactors at 37°C. Five different C/N ratios (7, 17, 21, 31, and 46) were tested in batch systems. While, in continuous system eight conditions were evaluated, hydraulic retention time (from 60 to 10 h) and organic load rate (from 21.96 to 155.87 g COD/L d). Data in batch tests showed a maximum specific biohydrogen production rate of 10.68 mmol H2/Lh and a biohydrogen yield of 449.84 mL H2/g COD at a C/N ratio of 21. In continuous co-digestion system, the optimum hydraulic retention time and organic loading rate were 17.5 h and 80.02 g COD/L d, respectively. Under these conditions, the highest volumetric production hydrogen rate (VPHR) and hydrogen yield were 11.02 mmol H2/L h, 800 mL H2/COD, respectively. A pyrosequencing analysis showed that the main acclimated microbial communities for co-digestion studies consisted of Bifidobacterium, with 85.4% of predominance. Hydrogen producing bacteria such as Klebsiella (9.1%), Lactobacillus (0.97%), Citrobacter (0.21%), Enterobacter (0.27%), and Clostridium (0.18%) were less abundant at this culture period. The microbial population structure was correlated with the lactate, acetate, and butyrate profiles obtained. Results demonstrated that the co-digestion of CCW with FVW improves biohydrogen production due to a better nutrient balance and improvement of the system’s buffering capacity.

Keywords: acclimatation, biohydrogen, co-digestion, microbial community

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Authors: Tatiana N. Astakhova, Alexander E. Saprygin, Tatyana A. Golovko, Alexander N. Savostyanov, Mikhail S. Vlasov, Natalia V. Borisova, Alexandera G. Karpova, Urana N. Kavai-ool, Elena D. Mokur-ool, Nikolay A. Kolchanov, Lubomir I. Aftanas

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The aim of the study is to compare behaviorally and EEG reactions in Turkic-speaking inhabitants of Siberia (Tuvinians and Yakuts) and Russians during the recognition of syntax errors in native and foreign languages. 63 healthy aboriginals of the Tyva Republic, 29 inhabitants of the Sakha (Yakutia) Republic, and 55 Russians from Novosibirsk participated in the study. All participants completed a linguistic task, in which they had to find a syntax error in the written sentences. Russian participants completed the task in Russian and in English. Tuvinian and Yakut participants completed the task in Russian, English, and Tuvinian or Yakut, respectively. EEG’s were recorded during the solving of tasks. For Russian participants, EEG's were recorded using 128-channels. The electrodes were placed according to the extended International 10-10 system, and the signals were amplified using ‘Neuroscan (USA)’ amplifiers. For Tuvinians and Yakuts EEG's were recorded using 64-channels and amplifiers Brain Products, Germany. In all groups 0.3-100 Hz analog filtering, sampling rate 1000 Hz were used. Response speed and the accuracy of recognition error were used as parameters of behavioral reactions. Event-related potentials (ERP) responses P300 and P600 were used as indicators of brain activity. The accuracy of solving tasks and response speed in Russians were higher for Russian than for English. The P300 amplitudes in Russians were higher for English; the P600 amplitudes in the left temporal cortex were higher for the Russian language. Both Tuvinians and Yakuts have no difference in accuracy of solving tasks in Russian and in their respective national languages (Tuvinian and Yakut). However, the response speed was faster for tasks in Russian than for tasks in their national language. Tuvinians and Yakuts showed bad accuracy in English, but the response speed was higher for English than for Russian and the national languages. With Tuvinians, there were no differences in the P300 and P600 amplitudes and in cortical topology for Russian and Tuvinian, but there was a difference for English. In Yakuts, the P300 and P600 amplitudes and topology of ERP for Russian were the same as Russians had for Russian. In Yakuts, brain reactions during Yakut and English comprehension had no difference and were reflected foreign language comprehension -while the Russian language comprehension was reflected native language comprehension. We found out that the Tuvinians recognized both Russian and Tuvinian as native languages, and English as a foreign language. The Yakuts recognized both English and Yakut as a foreign language, only Russian as a native language. According to the inquirer, both Tuvinians and Yakuts use the national language as a spoken language, whereas they don’t use it for writing. It can well be a reason that Yakuts perceive the Yakut writing language as a foreign language while writing Russian as their native.

Keywords: EEG, language comprehension, native and foreign languages, Siberian inhabitants

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Authors: Manish Kumar Rajak, Sanjay Gupta

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Mobile ad hoc networks (MANETs) are infrastructure less and intercommunicate using single-hop and multi-hop paths. Network based congestion avoidance which involves managing the queues in the network devices is an integral part of any network. QoS: A set of service requirements that are met by the network while transferring a packet stream from a source to a destination. Especially in MANETs, packet loss results in increased overheads. This paper presents a new algorithm to avoid congestion using one or more queue on nodes and corresponding flow rate decided in advance for each node. When any node attains an initial value of queue then it sends this status to its downstream nodes which in turn uses the pre-decided flow rate of packet transfer to its upstream nodes. The flow rate on each node is adjusted according to the status received from its upstream nodes. This proposed algorithm uses the existing infrastructure to inform to other nodes about its current queue status.

Keywords: mesh networks, MANET, packet count, threshold, throughput

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Authors: Ahmed Z. Mazen, Nejat Rahmanian, Iqbal Mujtaba, Ali Hassanpour

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In oil and gas well drilling, the drill bit is an important part of the Bottom Hole Assembly (BHA), which is installed and designed to drill and produce a hole by several mechanisms. The efficiency of the bit depends on many drilling parameters such as weight on bit, rotary speed, and mud properties. When the bit is pulled out of the hole, the evaluation of the bit damage must be recorded very carefully to guide engineers in order to select the bits for further planned wells. Having a worn bit for hole drilling may cause severe damage to bit leading to cutter or cone losses in the bottom of hole, where a fishing job will have to take place, and all of these will increase the operating cost. The main factor to reduce the cost of drilling operation is to maximize the rate of penetration by analyzing real-time data to predict the drill bit wear while drilling. There are numerous models in the literature for prediction of the rate of penetration based on drilling parameters, mostly based on empirical approaches. One of the most commonly used approaches is Bourgoyne and Young model, where the rate of penetration can be estimated by the drilling parameters as well as a wear index using an empirical correlation, provided all the constants and coefficients are accurately determined. This paper introduces a new methodology to estimate the eight coefficients for Bourgoyne and Young model using the gPROMS parameters estimation GPE (Version 4.2.0). Real data collected form similar formations (12 ¼’ sections) in two different fields in Libya are used to estimate the coefficients. The estimated coefficients are then used in the equations and applied to nearby wells in the same field to predict the bit wear.

Keywords: Bourgoyne and Young model, bit wear, gPROMS, rate of penetration

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Authors: Milad Yousefi, Moslem Yousefi, Ricarpo Poley, Amer Nordin Darus

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Design optimization of heat exchangers is a very complicated task that has been traditionally carried out based on a trial-and-error procedure. To overcome the difficulties of the conventional design approaches especially when a large number of variables, constraints and objectives are involved, a new method based on a well-stablished evolutionary algorithm, particle swarm optimization (PSO), weighted sum approach and a novel constraint handling strategy is presented in this study. Since, the conventional constraint handling strategies are not effective and easy-to-implement in multi-objective algorithms, a novel feasibility-based ranking strategy is introduced which is both extremely user-friendly and effective. A case study from industry has been investigated to illustrate the performance of the presented approach. The results show that the proposed algorithm can find the near pareto-optimal with higher accuracy when it is compared to conventional non-dominated sorting genetic algorithm II (NSGA-II). Moreover, the difficulties of a trial-and-error process for setting the penalty parameters is solved in this algorithm.

Keywords: Heat exchanger, Multi-objective optimization, Particle swarm optimization, NSGA-II Constraints handling.

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Authors: Anurag Gaur Nidhi

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Targeted drug delivery is a method of delivering medication to a patient in a manner that increases the concentration of the medication in some parts of the body relative to others. Targeted drug delivery seeks to concentrate the medication in the tissues of interest while reducing the relative concentration of the medication in the remaining tissues. This improves efficacy of the while reducing side effects. In the present work, we investigate the effect of magnetic field, flow rate and particle concentration on the capturing of magnetic particles transported in a stent implanted fluidic channel. Iron oxide magnetic nanoparticles (Fe3O4) nanoparticles were synthesized via co-precipitation method. The synthesized Fe3O4 nanoparticles were added in the de-ionized (DI) water to prepare the Fe3O4 magnetic particle suspended fluid. This fluid is transported in a cylindrical tube of diameter 8 mm with help of a peristaltic pump at different flow rate (25-40 ml/min). A ferromagnetic coil of SS 430 has been implanted inside the cylindrical tube to enhance the capturing of magnetic nanoparticles under magnetic field. The capturing of magnetic nanoparticles was observed at different magnetic magnetic field, flow rate and particle concentration. It is observed that capture efficiency increases from 47-67 % at magnetic field 2-5kG, respectively at particle concentration 0.6 mg/ml and at flow rate 30 ml/min. However, the capture efficiency decreases from 65 to 44 % by increasing the flow rate from 25 to 40 ml/min, respectively. Furthermore, it is observed that capture efficiency increases from 51 to 67 % by increasing the particle concentration from 0.3 to 0.6 mg/ml, respectively.

Keywords: capture efficiency, implant assisted-Magnetic drug targeting (IA-MDT), magnetic nanoparticles, In-vitro study

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Authors: Shahin A. Abdel-Naby, Asad T. Hassan

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Astrophysical plasma environments can be classified into collisionally ionized (CP) and photoionizedplasmas (PP). In the PP, ionization is caused by an external radiation field, while it is caused by electron collision in the CP. Accurate and reliable laboratory astrophysical data for electron-ion recombination is needed for plasma modeling for low and high-temperatures. Dielectronic recombination (DR) is the dominant recombination process for the CP for most of the ions. When a free electron is captured by an ion with simultaneous excitation of its core, a doubly-exited intermediate state may be formed. The doubly excited state relaxes either by electron emission (autoionization) or by radiative decay (photon emission). DR process takes place when the relaxation occurs to a bound state by a photon emission. DR calculations at low-temperatures are problematic and challenging since small uncertaintiesin the low-energy DR resonance positions can produce huge uncertainties in DR rate coefficients.DR rate coefficients for N²⁺ and O³⁺ ions are calculated using state-of-the-art multi-configurationBreit-Pauli atomic structure AUTOSTRUCTURE collisional package within the generalized collisional-radiative framework. Level-resolved calculations for RR and DR rate coefficients from the ground and metastable initial states are produced in an intermediate coupling scheme associated withn = 0 and n = 1 core-excitations. DR cross sections for these ions are convoluted with the experimental electron-cooler temperatures to produce DR rate coefficients. Good agreements are foundbetween these rate coefficients and theexperimental measurements performed at CRYRING heavy-ionstorage ring for both ions.

Keywords: atomic data, atomic process, electron-ion collision, plasmas

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Authors: Osama Abdallah Mohammed Enan, Amin Babiker A/Nabi Mustafa

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The aim of this study is to evaluate and analyze different parameters of WCDMA (wideband code division multiplication). Moreover, this study also incorporates brief yet throughout analysis of WCDMA’s components as well as its internal architecture. This study also examines different power controls. These power controls may include open loop power control, closed or inner group loop power control and outer loop power control. Different handover techniques or methods of WCDMA are also illustrated in this study. These handovers may include hard handover, inter system handover and soft and softer handover. Different duplexing techniques are also described in the paper. This study has also presented an idea about different parameters of WCDMA that leads the system towards QoS issues. This may help the operator in designing and developing adequate network configuration. In addition to this, the study has also investigated various parameters including Bit Energy per Noise Spectral Density (Eb/No), Noise rise, and Bit Error Rate (BER). After simulating these parameters, using MATLAB environment, it was investigated that, for a given Eb/No value the system capacity increase by increasing the reuse factor. Besides that, it was also analyzed that, noise rise is decreasing for lower data rates and for lower interference levels. Finally, it was examined that, BER increase by using one type of modulation technique than using other type of modulation technique.

Keywords: duplexing, handover, loop power control, WCDMA

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Authors: Abdelgawad, Salah El-Tahawy

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This paper aimed to establish econometrical equation models for the Nile delta region in Egypt, which will represent a basement for future predictions of Lumpy skin disease outbreaks and its pathway in relation to climate change. Data of lumpy skin disease (LSD) outbreaks were collected from the cattle farms located in the provinces representing the Nile delta region during 1 January, 2015 to December, 2015. The obtained results indicated that there was a significant association between the degree of the LSD outbreaks and the investigated climate factors (temperature, wind speed, and humidity) and the outbreaks peaked during the months of June, July, and August and gradually decreased to the lowest rate in January, February, and December. The model obtained depicted that the increment of these climate factors were associated with evidently increment on LSD outbreaks on the Nile Delta of Egypt. The model validation process was done by the root mean square error (RMSE) and means bias (MB) which compared the number of LSD outbreaks expected with the number of observed outbreaks and estimated the confidence level of the model. The value of RMSE was 1.38% and MB was 99.50% confirming that this established model described the current association between the LSD outbreaks and the change on climate factors and also can be used as a base for predicting the of LSD outbreaks depending on the climatic change on the future.

Keywords: LSD, climate factors, Nile delta, modeling

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Authors: Rui Huang, Thomas Richard, Masood Mostofi

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The lifetime of impregnated diamond bits and their drilling efficiency are in part governed by the bit wear conditions, not only the extent of the diamonds’ wear but also their exposure or protrusion out of the matrix bonding. As much as individual diamonds wear, the bonding matrix does also wear through two-body abrasion (direct matrix-rock contact) and three-body erosion (cuttings trapped in the space between rock and matrix). Although there is some work dedicated to the study of diamond bit wear, there is still a lack of understanding on how matrix erosion and diamond exposure relate to the bit drilling response and drilling efficiency, as well as no literature on the process that governs bit sharpening a procedure commonly implemented by drillers when the extent of diamond polishing yield extremely low rate of penetration. The aim of this research is (i) to derive a correlation between the wear state of the bit and the drilling performance but also (ii) to gain a better understanding of the process associated with tool sharpening. The research effort combines specific drilling experiments and precise mapping of the tool-cutting face (impregnated diamond bits and segments). Bit wear is produced by drilling through a rock sample at a fixed rate of penetration for a given period of time. Before and after each wear test, the bit drilling response and thus efficiency is mapped out using a tailored design experimental protocol. After each drilling test, the bit or segment cutting face is scanned with an optical microscope. The test results show that, under the fixed rate of penetration, diamond exposure increases with drilling distance but at a decreasing rate, up to a threshold exposure that corresponds to the optimum drilling condition for this feed rate. The data further shows that the threshold exposure scale with the rate of penetration up to a point where exposure reaches a maximum beyond which no more matrix can be eroded under normal drilling conditions. The second phase of this research focuses on the wear process referred as bit sharpening. Drillers rely on different approaches (increase feed rate or decrease flow rate) with the aim of tearing worn diamonds away from the bit matrix, wearing out some of the matrix, and thus exposing fresh sharp diamonds and recovering a higher rate of penetration. Although a common procedure, there is no rigorous methodology to sharpen the bit and avoid excessive wear or bit damage. This paper aims to gain some insight into the mechanisms that accompany bit sharpening by carefully tracking diamond fracturing, matrix wear, and erosion and how they relate to drilling parameters recorded while sharpening the tool. The results show that there exist optimal conditions (operating parameters and duration of the procedure) for sharpening that minimize overall bit wear and that the extent of bit sharpening can be monitored in real-time.

Keywords: bit sharpening, diamond exposure, drilling response, impregnated diamond bit, matrix erosion, wear rate

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Authors: Myunggon Yoon, Jung-Ho Moon

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In this paper, we present a transfer function representation of a general one-dimensional combustor. The input of the transfer function is a heat rate perturbation of a burner and the output is a flow velocity perturbation at the burner. This paper considers a general combustor model composed of multiple cans with different cross sectional areas, along with a non-zero flow rate.

Keywords: combustor, dynamics, thermoacoustics, transfer function

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Authors: Matteo Gentilucci, Marco Materazzi, Gilberto Pambianchi

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Climate change is an increasingly central issue in the world, because it affects many of human activities. In this context regional studies are of great importance because they sometimes differ from the general trend. This research focuses on a small area of central Italy which overlooks the Adriatic Sea, the province of Macerata. The aim is to analyze space-based climate changes, for precipitation and temperatures, in the last 3 climatological standard normals (1961-1990; 1971-2000; 1981-2010) through GIS software. The data collected from 30 weather stations for temperature and 61 rain gauges for precipitation were subject to quality controls: validation and homogenization. These data were fundamental for the spatialization of the variables (temperature and precipitation) through geostatistical techniques. To assess the best geostatistical technique for interpolation, the results of cross correlation were used. The co-kriging method with altitude as independent variable produced the best cross validation results for all time periods, among the methods analysed, with 'root mean square error standardized' close to 1, 'mean standardized error' close to 0, 'average standard error' and 'root mean square error' with similar values. The maps resulting from the analysis were compared by subtraction between rasters, producing 3 maps of annual variation and three other maps for each month of the year (1961/1990-1971/2000; 1971/2000-1981/2010; 1961/1990-1981/2010). The results show an increase in average annual temperature of about 0.1°C between 1961-1990 and 1971-2000 and 0.6 °C between 1961-1990 and 1981-2010. Instead annual precipitation shows an opposite trend, with an average difference from 1961-1990 to 1971-2000 of about 35 mm and from 1961-1990 to 1981-2010 of about 60 mm. Furthermore, the differences in the areas have been highlighted with area graphs and summarized in several tables as descriptive analysis. In fact for temperature between 1961-1990 and 1971-2000 the most areally represented frequency is 0.08°C (77.04 Km² on a total of about 2800 km²) with a kurtosis of 3.95 and a skewness of 2.19. Instead, the differences for temperatures from 1961-1990 to 1981-2010 show a most areally represented frequency of 0.83 °C, with -0.45 as kurtosis and 0.92 as skewness (36.9 km²). Therefore it can be said that distribution is more pointed for 1961/1990-1971/2000 and smoother but more intense in the growth for 1961/1990-1981/2010. In contrast, precipitation shows a very similar shape of distribution, although with different intensities, for both variations periods (first period 1961/1990-1971/2000 and second one 1961/1990-1981/2010) with similar values of kurtosis (1st = 1.93; 2nd = 1.34), skewness (1st = 1.81; 2nd = 1.62 for the second) and area of the most represented frequency (1st = 60.72 km²; 2nd = 52.80 km²). In conclusion, this methodology of analysis allows the assessment of small scale climate change for each month of the year and could be further investigated in relation to regional atmospheric dynamics.

Keywords: climate change, GIS, interpolation, co-kriging

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Authors: Fazıl Gökgöz, Fahrettin Filiz

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Load forecasting has become crucial in recent years and become popular in forecasting area. Many different power forecasting models have been tried out for this purpose. Electricity load forecasting is necessary for energy policies, healthy and reliable grid systems. Effective power forecasting of renewable energy load leads the decision makers to minimize the costs of electric utilities and power plants. Forecasting tools are required that can be used to predict how much renewable energy can be utilized. The purpose of this study is to explore the effectiveness of LSTM-based neural networks for estimating renewable energy loads. In this study, we present models for predicting renewable energy loads based on deep neural networks, especially the Long Term Memory (LSTM) algorithms. Deep learning allows multiple layers of models to learn representation of data. LSTM algorithms are able to store information for long periods of time. Deep learning models have recently been used to forecast the renewable energy sources such as predicting wind and solar energy power. Historical load and weather information represent the most important variables for the inputs within the power forecasting models. The dataset contained power consumption measurements are gathered between January 2016 and December 2017 with one-hour resolution. Models use publicly available data from the Turkish Renewable Energy Resources Support Mechanism. Forecasting studies have been carried out with these data via deep neural networks approach including LSTM technique for Turkish electricity markets. 432 different models are created by changing layers cell count and dropout. The adaptive moment estimation (ADAM) algorithm is used for training as a gradient-based optimizer instead of SGD (stochastic gradient). ADAM performed better than SGD in terms of faster convergence and lower error rates. Models performance is compared according to MAE (Mean Absolute Error) and MSE (Mean Squared Error). Best five MAE results out of 432 tested models are 0.66, 0.74, 0.85 and 1.09. The forecasting performance of the proposed LSTM models gives successful results compared to literature searches.

Keywords: deep learning, long short term memory, energy, renewable energy load forecasting

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Authors: Prasanjit Das, M. M. K. Khan, M. G. Rasul, Jie Wu, I. Youn

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Mineral scale formation is undoubtedly a more serious problem in the mineral industry than other process industries. To better understand scale growth and suppression, an experimental model is proposed in this study for supersaturated crystallised solutions commonly found in mineral process plants. In this experiment, surface crystallisation of potassium nitrate (KNO3) on the wall of the agitation tank and agitation effects on the scale growth and suppression are studied. The new quantitative scale suppression model predicts that at lower agitation speed, the scale growth rate is enhanced and at higher agitation speed, the scale suppression rate increases due to the increased flow erosion effect. A lab-scale agitation tank with and without baffles were used as a benchmark in this study. The fluid dynamic effects on scale growth and suppression in the agitation tank with three different size impellers (diameter 86, 114, 160 mm and model A310 with flow number 0.56) at various ranges of rotational speed (up to 700 rpm) and solution with different concentration (4.5, 4.75 and 5.25 mol/dm3) were investigated. For more elucidation, the effects of the different size of the impeller on wall surface scale growth and suppression rate as well as bottom settled scale accumulation rate are also discussed. Emphasis was placed on applications in the mineral industry, although results are also relevant to other industrial applications.

Keywords: agitation tank, crystallisation, impeller speed, scale

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Authors: Jacqueline Y. Thompson, Sam Watson, Lee Middleton, Karla Hemming

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Introduction: The odds ratio (estimated via logistic regression) is a well-established and common approach for estimating covariate-adjusted binary treatment effects when comparing a treatment and control group with dichotomous outcomes. Its popularity is primarily because of its stability and robustness to model misspecification. However, the situation is different for the relative risk and risk difference, which are arguably easier to interpret and better suited to specific designs such as non-inferiority studies. So far, there is no equivalent, widely acceptable approach to estimate an adjusted relative risk and risk difference when conducting clinical trials. This is partly due to the lack of a comprehensive evaluation of available candidate methods. Methods/Approach: A simulation study is designed to evaluate the performance of relevant candidate methods to estimate relative risks to represent conditional and marginal estimation approaches. We consider the log-binomial, generalised linear models (GLM) with iteratively weighted least-squares (IWLS) and model-based standard errors (SE); log-binomial GLM with convex optimisation and model-based SEs; log-binomial GLM with convex optimisation and permutation tests; modified-Poisson GLM IWLS and robust SEs; log-binomial generalised estimation equations (GEE) and robust SEs; marginal standardisation and delta method SEs; and marginal standardisation and permutation test SEs. Independent and identically distributed datasets are simulated from a randomised controlled trial to evaluate these candidate methods. Simulations are replicated 10000 times for each scenario across all possible combinations of sample sizes (200, 1000, and 5000), outcomes (10%, 50%, and 80%), and covariates (ranging from -0.05 to 0.7) representing weak, moderate or strong relationships. Treatment effects (ranging from 0, -0.5, 1; on the log-scale) will consider null (H0) and alternative (H1) hypotheses to evaluate coverage and power in realistic scenarios. Performance measures (bias, mean square error (MSE), relative efficiency, and convergence rates) are evaluated across scenarios covering a range of sample sizes, event rates, covariate prognostic strength, and model misspecifications. Potential Results, Relevance & Impact: There are several methods for estimating unadjusted and adjusted relative risks. However, it is unclear which method(s) is the most efficient, preserves type-I error rate, is robust to model misspecification, or is the most powerful when adjusting for non-prognostic and prognostic covariates. GEE estimations may be biased when the outcome distributions are not from marginal binary data. Also, it seems that marginal standardisation and convex optimisation may perform better than GLM IWLS log-binomial.

Keywords: binary outcomes, statistical methods, clinical trials, simulation study

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