Abstract: Water quality and heavy metals pollution of the Damietta Nile Branch at Damietta governorate were investigated in the current work. Fourteen different sampling points were selected along the Damietta Nile branch from Ras EL-Bar (sample 1) to Sheremsah (sample 14). Physical and chemical parameters and the concentrations of Cd, Cr, Cu, Ni, Fe, Al, Hg, Pb and Zn were investigated for water quality assessment of Damietta Nile Branch at Damietta Governorate. Most of the samples show that the water is suitable for drinking and irrigation purposes. All locations of samples near the sea are unsuitable water but the samples in the south direction away from the sea are suitable or good water for drinking and irrigation.
Abstract: This paper presents a hybrid system solar cell antenna for 5G mobile communications networks. We propose here a solar cell antenna with either a front face collection grid or mesh patch. The solar cell antenna of our contribution combines both optical and radiofrequency signals. Thus, we propose two solar cell antenna structures in the frequency bands of future 5G standard respectively in both 2.6 and 3.5 GHz bands. Simulation using the Advanced Design System (ADS) software allows us to analyze and determine the antenna parameters proposed in this work such as the reflection coefficient (S11), gain, directivity and radiated power.
Abstract: This paper considers the modelling of a non-stationary
bivariate integer-valued autoregressive moving average of order
one (BINARMA(1,1)) with correlated Poisson innovations. The
BINARMA(1,1) model is specified using the binomial thinning
operator and by assuming that the cross-correlation between the
two series is induced by the innovation terms only. Based on
these assumptions, the non-stationary marginal and joint moments
of the BINARMA(1,1) are derived iteratively by using some initial
stationary moments. As regards to the estimation of parameters of
the proposed model, the conditional maximum likelihood (CML)
estimation method is derived based on thinning and convolution
properties. The forecasting equations of the BINARMA(1,1) model
are also derived. A simulation study is also proposed where
BINARMA(1,1) count data are generated using a multivariate
Poisson R code for the innovation terms. The performance of
the BINARMA(1,1) model is then assessed through a simulation
experiment and the mean estimates of the model parameters obtained
are all efficient, based on their standard errors. The proposed model
is then used to analyse a real-life accident data on the motorway in
Mauritius, based on some covariates: policemen, daily patrol, speed
cameras, traffic lights and roundabouts. The BINARMA(1,1) model
is applied on the accident data and the CML estimates clearly indicate
a significant impact of the covariates on the number of accidents on
the motorway in Mauritius. The forecasting equations also provide
reliable one-step ahead forecasts.
Abstract: In an electric power grid connected wind generation system, dynamic control strategy is essential to use the wind energy efficiently as well as for an energy optimization. The present study has focused on decoupled power regulation of doubly fed induction generator, operating in wind turbine, in accordance with the vector control approach by applying fractional order proportional integral (FOPI) controller. The FOPI controller is designed based on a simple method; up such that the response of closed loop process is similar to the response of a specified fractional model whose transfer function is Bode’s ideal function. In this tuning operation, the parameters of the proposed fractional controller are established analytically using the impulse closed-loop response of the controlled process. To show the superior action of the developed FOPI controller in comparison with standard PI controller in different function conditions, the study is validated through simulation using the software MATLAB/Simulink.
Abstract: Recent rapid progress in ICT (Information and Communication Technology) has advanced the penetration of sensor networks (SNs) and their attractive applications. Agriculture is one of the fields well able to benefit from ICT. Plant factories control several parameters related to plant growth in closed areas such as air temperature, humidity, water, culture medium concentration, and artificial lighting by using computers and AI (Artificial Intelligence) is being researched in order to obtain stable and safe production of vegetables and medicinal plants all year anywhere, and attain self-sufficiency in food. By providing isolation from the natural environment, a plant factory can achieve higher productivity and safe products. However, the biggest issue with plant factories is the return on investment. Profits are tenuous because of the large initial investments and running costs, i.e. electric power, incurred. At present, LED (Light Emitting Diode) lights are being adopted because they are more energy-efficient and encourage photosynthesis better than the fluorescent lamps used in the past. However, further cost reduction is essential. This paper introduces experiments that reveal which color of LED lighting best enhances the growth of cultured radish sprouts. Radish sprouts were cultivated in the experimental environment formed by a hydroponics kit with three cultivation shelves (28 samples per shelf) each with an artificial lighting rack. Seven LED arrays of different color (white, blue, yellow green, green, yellow, orange, and red) were compared with a fluorescent lamp as the control. Lighting duration was set to 12 hours a day. Normal water with no fertilizer was circulated. Seven days after germination, the length, weight and area of leaf of each sample were measured. Electrical power consumption for all lighting arrangements was also measured. Results and discussions: As to average sample length, no clear difference was observed in terms of color. As regards weight, orange LED was less effective and the difference was significant (p < 0.05). As to leaf area, blue, yellow and orange LEDs were significantly less effective. However, all LEDs offered higher productivity per W consumed than the fluorescent lamp. Of the LEDs, the blue LED array attained the best results in terms of length, weight and area of leaf per W consumed. Conclusion and future works: An experiment on radish sprout cultivation under 7 different color LED arrays showed no clear difference in terms of sample size. However, if electrical power consumption is considered, LEDs offered about twice the growth rate of the fluorescent lamp. Among them, blue LEDs showed the best performance. Further cost reduction e.g. low power lighting remains a big issue for actual system deployment. An automatic plant monitoring system with sensors is another study target.
Abstract: Aloe Vera is a short-stemmed succulent plant which is commonly used in Myanmar traditional medicine. A. vera gel was also used as food addictive. This study aims to improve the Myanmar folk medicine to a functional beverage. In this research, Aloe vera was fermented with Saccharomyces cerevisiae for 6 months. Three different processes were carried out. Process I contains A. vera 10%, sugar 30%, water 50%, and starter culture 10%, process II contains A. vera 10%, sugar 15%, honey 15%, and water 50%, starter culture 10%; process III contains A. vera 10%, honey 30%, water 50%, starter culture 10%. During wine fermentation, the wine parameters such as alcohol content, total soluble solid (ºBrix), pH, color and cell population were analyzed. After 30 days of fermentation, total cell population remained 2.8x106 in P-I, P-II and 3.2x106 in P-III. Total soluble solid content dropped to 15.8 in P-I, P-II and 15.7 in P-III. After 30 days, clear wine was transferred to other vassals for racking. After 6 months of racking, microbial population reached under detectable level and alcohol content was round about 11% but not significantly different among these processes. P-II was found to have the highest color intensity at 450 nm and it got the most taster satisfaction when sensory evaluation was carried out using five hedonic scales after 6 month of racking.
Abstract: A precise, sensitive, rapid and selective method for the solvent extraction, spectrophotometric determination of palladium(II) using para-methylphenyl thiourea (PMPT) as an extractant is developed. Palladium(II) forms yellow colored complex with PMPT which shows an absorption maximum at 300 nm. The colored complex obeys Beer’s law up to 7.0 µg ml-1 of palladium. The molar absorptivity and Sandell’s sensitivity were found to be 8.486 x 103 l mol-1cm-1 and 0.0125 μg cm-2 respectively. The optimum conditions for the extraction and determination of palladium have been established by monitoring the various experimental parameters. The precision of the method has been evaluated and the relative standard deviation has been found to be less than 0.53%. The proposed method is free from interference from large number of foreign ions. The method has been successfully applied for the determination of palladium from alloy, synthetic mixtures corresponding to alloy samples.
Abstract: The prediction of the rheological behavior of concrete is at the center of current concerns of the concrete industry for different reasons. The shortage of good quality standard materials combined with variable properties of available materials imposes to improve existing models to take into account these variations at the design stage of concrete. The main reasons for improving the predictive models are, of course, saving time and cost at the design stage as well as to optimize concrete performances. In this study, we will highlight the different properties of the granular mixtures that affect the rheological properties of concrete. Our objective is to identify the intrinsic parameters of the aggregates which make it possible to predict the yield stress of concrete. The work was done using two typologies of grains: crushed and rolled aggregates. The experimental results have shown that the rheology of concrete is improved by increasing the packing density of the granular mixture using rolled aggregates. The experimental program realized allowed to model the yield stress of concrete by a modified model of Chateau et al. through a dimensionless parameter following Krieger-Dougherty law. The modelling confirms that the yield stress of concrete depends not only on the properties of cement paste but also on the packing density of the granular skeleton and the shape of grains.
Abstract: This study developed a method for teaching
acupuncture manipulation in small groups optimized with the
theory of motor learning. Sixty acupuncture students and their
teacher participated in our research. Motion videos were recorded
of their manipulations using the lifting-thrusting method. These
videos were analyzed using Simi Motion software to acquire the
movement parameters of the thumb tip. The parameter velocity
curves along Y axis was used to generate small teaching groups
clustered by a self-organized map (SOM) and K-means. Ten groups
were generated. All the targeted instruction based on the comparative
results groups as well as the videos of teacher and student was
provided to the members of each group respectively. According to
the theory and research of motor learning, the factors or technologies
such as video instruction, observational learning, external focus and
summary feedback were integrated into this teaching method. Such
efforts were desired to improve and enhance the effectiveness of
current acupuncture teaching methods in limited classroom teaching
time and extracurricular training.
Abstract: The Bacterial Foraging Optimization (BFO) algorithm is inspired by the behavior of bacteria such as Escherichia coli or Myxococcus xanthus when searching for food, more precisely the chemotaxis behavior. Bacteria perceive chemical gradients in the environment, such as nutrients, and also other individual bacteria, and move toward or in the opposite direction to those signals. The application example considered as a case study consists in establishing the dependency between the reaction yield of hydrogels based on polyacrylamide and the working conditions such as time, temperature, monomer, initiator, crosslinking agent and inclusion polymer concentrations, as well as type of the polymer added. This process is modeled with a neural network which is included in an optimization procedure based on BFO. An experimental study of BFO parameters is performed. The results show that the algorithm is quite robust and can obtain good results for diverse combinations of parameter values.
Abstract: The information of the impact cutting behavior of plants stalk plays an important role in the design and fabrication of plants cutting equipment. It is difficult to investigate a theoretical method for defining cutting properties of plants stalks because the cutting process is complex. Thus, it is necessary to set up an experimental approach to determine cutting parameters for a single stalk. To measure the shear force, shear energy and shear strength of plant stalk, a special impact cutting tester was fabricated. It was similar to an Izod impact cutting tester for metals but a cutting blade and data acquisition system were attached to the end of pendulum's arm. The apparatus was included four strain gages and a digital indicator to show the real-time cutting force of plant stalk. To measure the shear force and also testing the apparatus, two plants’ stalks, like buxus and privet, were selected. The samples (buxus and privet stalks) were cut under impact cutting process at four loading rates 1, 2, 3 and 4 m.s-1 and three internodes fifth, tenth and fifteenth by the apparatus. At buxus cutting analysis: the minimum value of cutting energy was obtained at fifth internode and loading rate 4 m.s-1 and the maximum value of shear energy was obtained at fifteenth internode and loading rate 1 m.s-1. At privet cutting analysis: the minimum value of shear consumption energy was obtained at fifth internode and loading rate: 4 m.s-1 and the maximum value of shear energy was obtained at fifteenth internode and loading rate: 1 m.s-1. The statistical analysis at both plants showed that the increase of impact cutting speed would decrease the shear consumption energy and shear strength. In two scenarios, the results showed that with increase the cutting speed, shear force would decrease.
Abstract: Intersection is a critical area on a highway which is a place of conflict points and congestion due to the meeting of two or more roads. Conflicts that occur at the intersection include diverging, merging, weaving, and crossing. To deal with these conflicts, a crossing control system is needed, at a plot of intersection there are two control systems namely signal intersections and non-signalized intersections. The control system at a plot of intersection can affect the intersection performance. In Indonesia there are still many intersections with poor intersection performance. In analyzing the parameters to measure the performance of a plot of intersection in Indonesia, it is guided by the 1997 Indonesian Road Capacity Manual. For this reason, this study aims to develop laboratory diagnostics at plot intersections to analyze parameters that can affect the performance of an intersection. The research method used is research and development. The laboratory diagnosis includes anamnesis, differential diagnosis, inspection, diagnosis, prognosis, specimens, analysis and sample data analysts. It is expected that this research can encourage the development and application of laboratory diagnostics at a plot of intersection in Indonesia so that intersections can function optimally.
Abstract: This paper aims at bringing a scientific contribution to the cardiac arrhythmia biomedical diagnosis systems; more precisely to the study of the amelioration of cardiac arrhythmia classification performance using artificial neural network, adaptive neuro-fuzzy and fuzzy inference systems classifiers. The purpose of this amelioration is to enable cardiologists to make reliable diagnosis through automatic cardiac arrhythmia analyzes and classifications based on high confidence classifiers. In this study, six classes of the most commonly encountered arrhythmias are considered: the Right Bundle Branch Block, the Left Bundle Branch Block, the Ventricular Extrasystole, the Auricular Extrasystole, the Atrial Fibrillation and the Normal Cardiac rate beat. From the electrocardiogram (ECG) extracted parameters, we constructed a matrix (360x360) serving as an input data sample for the classifiers based on neural networks and a matrix (1x6) for the classifier based on fuzzy logic. By varying three parameters (the quality of the neural network learning, the data size and the quality of the input parameters) the automatic classification permitted us to obtain the following performances: in terms of correct classification rate, 83.6% was obtained using the fuzzy logic based classifier, 99.7% using the neural network based classifier and 99.8% for the adaptive neuro-fuzzy based classifier. These results are based on signals containing at least 360 cardiac cycles. Based on the comparative analysis of the aforementioned three arrhythmia classifiers, the classifiers based on neural networks exhibit a better performance.
Abstract: In this study, a spectral element method (SEM) is employed to predict the free vibration of a Euler-Bernoulli beam resting on a Winkler foundation with elastically restrained ends. The formulation of the dynamic stiffness matrix has been established by solving the differential equation of motion which was transformed to frequency domain. Non-dimensional natural frequencies and shape modes are obtained by solving the partial differential equations, numerically. Numerical comparisons and examples are performed to show the effectiveness of the SEM and to investigate the effects of various parameters, such as the springs at the boundaries and the elastic foundation parameter on the vibration frequencies. The obtained results demonstrate that the present method can also be applied to solve the more general problem of the dynamic analysis of structures with higher order precision.
Abstract: Reasonable energy saving for dehumidification is feasible with the use of desiccants. Desiccants are able to lower the humidity content in the air irrespective of the dew point temperature. In this paper, a tube bundle liquid desiccant air conditioner was experimentally designed and evaluated using lithium chloride as a desiccant. Several experiments were conducted to evaluate the influence of the inlet parameters on the dehumidifier performance. The results show a reduction in the relative humidity in the range of 17 to 46%, and the change in the humidity ratio was between 1.5 to 4.7 g/kg, depending on the inlet conditions. A water removal rate in the range between 0.54 and 1.67 kg/h was observed. The effects of air relative humidity and the desiccant flow rate on the dehumidifier’s performance were investigated. It was found that the moisture removal rate remarkably increased with increasing desiccant flow rate and air inlet humidity ratio. The dehumidifier effectiveness increased sharply with increasing desiccant flow rate. Also, it was found that the dehumidifier effectiveness slightly decreased with air humidity ratio.
Abstract: This paper provides a comprehensive study pertaining to diagnosis of intermittent high vibrations on an industrial gas turbine using detailed vibrations analysis, followed by its rectification. Engro Polymer & Chemicals Limited, a Chlor-Vinyl complex located in Pakistan has a captive combined cycle power plant having two 28 MW gas turbines (make Hitachi) & one 15 MW steam turbine. In 2018, the organization faced an issue of high vibrations on one of the gas turbines. These high vibration peaks appeared intermittently on both compressor’s drive end (DE) & turbine’s non-drive end (NDE) bearing. The amplitude of high vibration peaks was between 150-170% on the DE bearing & 200-300% on the NDE bearing from baseline values. In one of these episodes, the gas turbine got tripped on “High Vibrations Trip” logic actuated at 155µm. Limited instrumentation is available on the machine, which is monitored with GE Bently Nevada 3300 system having two proximity probes installed at Turbine NDE, Compressor DE &at Generator DE & NDE bearings. Machine’s transient ramp-up & steady state data was collected using ADRE SXP & DSPI 408. Since only 01 key phasor is installed at Turbine high speed shaft, a derived drive key phasor was configured in ADRE to obtain low speed shaft rpm required for data analysis. By analyzing the Bode plots, Shaft center line plot, Polar plot & orbit plots; rubbing was evident on Turbine’s NDE along with increased bearing clearance of Turbine’s NDE radial bearing. The subject bearing was then inspected & heavy deposition of carbonized coke was found on the labyrinth seals of bearing housing with clear rubbing marks on shaft & housing covering at 20-25 degrees on the inner radius of labyrinth seals. The collected coke sample was tested in laboratory & found to be the residue of lube oil in the bearing housing. After detailed inspection & cleaning of shaft journal area & bearing housing, new radial bearing was installed. Before assembling the bearing housing, cleaning of bearing cooling & sealing air lines was also carried out as inadequate flow of cooling & sealing air can accelerate coke formation in bearing housing. The machine was then taken back online & data was collected again using ADRE SXP & DSPI 408 for health analysis. The vibrations were found in acceptable zone as per ISO standard 7919-3 while all other parameters were also within vendor defined range. As a learning from subject case, revised operating & maintenance regime has also been proposed to enhance machine’s reliability.
Abstract: This paper includes experimental results and analytical studies about increasing resistance of single-span reinforced concreted frames against impact factor and their modeling according to optimization methods and optimizing the behavior of these frames under impact loads. During this study, about 30 designs for different frames were modeled and made using specialized software like ANSYS and Sap and their behavior were examined under variable impacts. Then suitable strategies were offered for frames in terms of concrete mixing in order to optimize frame modeling. To reduce the weight of the frames, we had to use fine-grained stones. After designing about eight types of frames for each type of frames, three samples were designed with the aim of controlling the impact strength parameters, and a good shape of the frame was created for the impact resistance, which was a solid frame with muscular legs, and as a bond away from each other as much as possible with a 3 degree gradient in the upper part of the beam.
Abstract: Concrete Damaged Plasticity Model (CDPM) is capable of modeling the stress-strain behavior of confined concrete. Nevertheless, the accuracy of the model largely depends on its parameters. To date, most research works mainly focus on the identification and modification of the parameters for fiber reinforced polymer (FRP) confined concrete prior to damage. And, it has been established that the FRP-strengthened concrete behaves differently to FRP-repaired concrete. This paper presents a modified plastic damage model within the context of the CDPM in ABAQUS for modelling of a uniformly FRP-confined repaired concrete under monotonic loading. The proposed model includes infliction damage, elastic stiffness, yield criterion and strain hardening rule. The distinct feature of damaged concrete is elastic stiffness reduction; this is included in the model. Meanwhile, the test results were obtained from a physical testing of repaired concrete. The dilation model is expressed as a function of the lateral stiffness of the FRP-jacket. The finite element predictions are shown to be in close agreement with the obtained test results of the repaired concrete. It was observed from the study that with necessary modifications, finite element method is capable of modeling FRP-repaired concrete structures.
Abstract: The neural network quantization is highly desired
procedure to perform before running neural networks on mobile
devices. Quantization without fine-tuning leads to accuracy drop of
the model, whereas commonly used training with quantization is done
on the full set of the labeled data and therefore is both time- and
resource-consuming. Real life applications require simplification and
acceleration of quantization procedure that will maintain accuracy of
full-precision neural network, especially for modern mobile neural
network architectures like Mobilenet-v1, MobileNet-v2 and MNAS. Here we present a method to significantly optimize training with
quantization procedure by introducing the trained scale factors for
discretization thresholds that are separate for each filter. Using the
proposed technique, we quantize the modern mobile architectures of
neural networks with the set of train data of only ∼ 10% of the
total ImageNet 2012 sample. Such reduction of train dataset size and
small number of trainable parameters allow to fine-tune the network
for several hours while maintaining the high accuracy of quantized
model (accuracy drop was less than 0.5%). Ready-for-use models and
code are available in the GitHub repository.
Abstract: Nowadays, solar energy is used for energy purposes such as the use of thermal energy for domestic, industrial and power applications, as well as the conversion of the sunlight into electricity by photovoltaic cells. In this study, the thermodynamic simulation of the solar Rankin cycle with phase change material (paraffin) was first studied. Then energy and exergy analyses were performed. For optimization, a single and multi-objective genetic optimization algorithm to maximize thermal and exergy efficiency was used. The parameters discussed in this paper included the effects of input pressure on turbines, input mass flow to turbines, the surface of converters and collector angles on thermal and exergy efficiency. In the organic Rankin cycle, where solar energy is used as input energy, the fluid selection is considered as a necessary factor to achieve reliable and efficient operation. Therefore, silicon oil is selected for a high-temperature cycle and water for a low-temperature cycle as an operating fluid. The results showed that increasing the mass flow to turbines 1 and 2 would increase thermal efficiency, while it reduces and increases the exergy efficiency in turbines 1 and 2, respectively. Increasing the inlet pressure to the turbine 1 decreases the thermal and exergy efficiency, and increasing the inlet pressure to the turbine 2 increases the thermal efficiency and exergy efficiency. Also, increasing the angle of the collector increased thermal efficiency and exergy. The thermal efficiency of the system was 22.3% which improves to 33.2 and 27.2% in single-objective and multi-objective optimization, respectively. Also, the exergy efficiency of the system was 1.33% which has been improved to 1.719 and 1.529% in single-objective and multi-objective optimization, respectively. These results showed that the thermal and exergy efficiency in a single-objective optimization is greater than the multi-objective optimization.