International Journal of Engineering
Volume:33 Issue: 5, May 2020

In this study, modeling of hydrogen, nitrogen, carbon monoxide, methane and carbon dioxide sorption on UTSA-16 framework extrudates in the pressure swing adsorption process was carried out. The pure gas adsorption of these gases at the pressure range (0 to 80) bars at (298, 313, and 338) K have also been measured in a fixed bed. Langmuir, Toth, Sips, UNILAN, Virial and Dubinin-Astakhov adsorption models were tested on adsorption data to estimate the sorption capacity, intensity and energy. Cuckoo search optimization algorithm was used for solving the problem to estimate the parameters of adsorption models. The results show that Langmuir isotherm provided the best fit to the equilibrium data with a square of residuals (Fobj) of 0.022, 0.2670, 0.4840, 0.1813 and 1.9619 for hydrogen, nitrogen, carbon monoxide, methane and carbon dioxide respectively. There was a good agreement between the predicted theoretical breakthrough curves and the experimental results with Langmuir, Dubinin-Astakhov, Sips, Toth and UNILAN, respectively.

In this study, the effects of three different viscous damper configurations, chevron, diagonal and toggle, as well as brace stiffness on the performance of brace-viscous damper system in various steel frams under different earthquake records were investigated. A finite element software, ANSYS, is exploited to develop the numerical models. To verify the numerical simulations, their results were compared with those of the experimental studies in the literature. The results show the reduction in the base shear force given by the toggle configuration is larger than that due to the chevron and diagonal configurations. Regarding the brace stiffness (area), for a reference damping coefficient of 500 N.m/s, a 54% increase in the brace area (from 42 to 91.8 mm2) results in a 21.26, 38.61, and 17.57% reduction in the structure displacement response for the diagonal, chevron, and toggle configurations, respectively. Further, using the results of the numerical simulations, we proposed the spatially-optimized distribution of the brace-viscous damper system.

River bank filtratio filtration (RBF) is one of the novel water abstraction alternatives to tackle poor water quality problem in Malaysia. This study was conducted to investigate the potential use of zeolite and activated carbon as filter media in the laboratory RBF system. Characteristics of the materials were first determined using the surface analyzer and X-ray fluorescence method. Filter column and filtration rate that resembles the RBF system at one of the rivers in Malaysia was designed and pre-determined. The removal performance of the total coliform in terms of the Most Probable Number (MPN), Escherichia coli, suspended solids (SS), UV254 representing the Natural Organic Matter (NOM), and colour was determined at 2 different configurations; Column A which consists of a mixture of zeolite and activated carbon, and Column B which has two distinctive layers of zeolite (bottom) and activated carbon (top). Results indicated that the filtration rate of 18.3cm3/min and retention time of 30 minutes had shown good removal performance for almost all the parameters. The removal of total coliform and E. coli were excellent with 95 and 99% reduction, respectively and 67 to 84% removal efficiency for SS. Column A performed better in removal of SS and colour whereas for Column B, performed better in removal of total coliform, E. coli, and UV254.

Speed humps used as a tool of traffic calming technique that applied to force drivers to reduce their vehicle’ speeds at some locations. For developed countries, the implementations of speed humps are often used within residential areas as well as at locations of schools crossing.  For developing countries (e.g. Iraq), speed humps are used even at urban and urban highways.   This paper investigates the effect of applying such speed humps on pavement condition index (PCI).  For the purpose of this study, ten urban and rural highway sites that paved by asphalt concrete have been selected from Al-Diwaniyah city, Iraq. Each site has been divided to sections before and after the humps.  Each section has been surveyed to record the distress types used in calculations the values of PCI.  It has been noticed that the rutting distress is the dominant type for sections just before the humps.  The PCI values were significantly lower at sections near the humps compared with the faraway sections.  In addition, the effect of speed humps on the PCI values can be neglected at urban highways where minimal trucks used these highways.  The results of the paper suggested that an attention should be provided to identify reasonable warrants for installing of speed humps on flexible highway pavements.

The simultaneous effects of soil and existing structures are known as the site-city interaction (structure-soil-structure). The impact of site-city interaction on structure behavior is effective. Thus, this interaction in some regions decreases the responses while increases in other areas. In addition, the site-city interaction of many parameters including the soil type, density rate, height of buildings is effective for evaluation. So far, none of investigation has focused on the effects of nature and shape of seismic wave and the plate which affects these waves in site-city interaction in three dimensions. Thus, the present study aimed to consider the effect of parameters mentioned in structure and foundation responses. The results indicated that the highest reduction for Love wave occurs in acceleration responses of structure in the cluster relative to the individual state, compared to the rest of the waves. Therefore, the reduction is about 30 and 50% for the base and top nodes of structures, respectively.

The tuned liquid column damper (TLCD) having a uniform cross-sectional tube of U-shaped, occupied with liquid is used as a vibrational response mitigation device. The tuned liquid column ball damper (TLCBD) is a modified TLCD, where, an immovable orifice, positioned at the middle part of the horizontal portion, is replaced by a metal ball. Different studies on the unconstrained optimization performance of TLCBD subjected to the stochastic earthquake have been performed where limitations on the maximum amplitude of liquid present in the vertical portion of the tube were not imposed. In the case of the high magnitude of earthquake and space constraint, the excessive liquid movement might get generated in the vertical portion of the tube which can create challenging circumstances. This can be taken care of by restricting the liquid movement up to a certain limit. The present investigation considers the optimum performance of the structure with TLCBD for mitigating the vibrational response with limited liquid movement in the vertical portion of the tube. A numerical study has been carried out to demonstrate the difference between constrained and unconstrained optimization of structure-TLCBD system. Numerical results show the influence of constraining cases on optimum parameters and performance behavior of the structure-TLCBD system.

Headwater accident is a natural phenomenon that occurs in every flow channel, resulting in tremendous incidents that involve vulnerable lives and destruction of its surroundings. This study focuses on simulation of potential headwater accidents at Lata Kinjang waterfall (Perak, Malaysia) with the aim of understanding the behavior of headwater accidents from the hydraulic aspect. By deploying the Lattice Boltzmann Method (LBM) for Shallow Water Flow with Turbulence Modeling (LABSWETM), a two-dimensional simulation was carried out to investigate the headwater condition of the study area. The outputs from the LABSWETM model simulation were presented in terms of water height progression and velocity profile. The water-height results showed a decrease in water level within the flow channel and an increase in downstream, while the velocity-profile results revealed an increase in velocity at downstream. Thus, under current hydraulic conditions, Lata Kinjang waterfall has a high potential for the occurrence of headwater accidents. Nonetheless, this study provide suggestions to mitigate the phenomenon efficiently.

In the present study, a new method for retrofitting reinforced concrete beam is introduced in which steel-concrete composite jackets containing steel fiber is used. For this purpose, 75% of the peripheral surface of reinforced concrete beams was initially reinforced using steel plates and bolts, and steel fiber reinforced concrete was used between the steel plates and the peripheral surfaces of the beam. Thus, due to the relatively high tensile strength of concrete reinforced with steel fibers, not only the cross-section and moment of inertia of the beam will increase, but the tensile strength of the beam will also increase. The variables studied were steel fiber value (0, 1 and 2% by volume of concrete) and type of retrofitting (concrete jacket, steel-concrete composite jacket, and carbon fiber reinforced polymer (CFRP) sheet). Thus, 8 reinforced concrete beams were constructed and their response to four-point loading was compared by examining the parameters such as crack load, yield load, ultimate load, ductility, stiffness, and energy absorption capacity. The results showed that steel fiber-reinforced composite jackets delay the formation of the first crack in concrete and the yield of steel rebars with confinement and they result in an increase in energy absorption capacity of the beams by 89 to 129% depending on the amount of steel fiber. On the other hand, the use of steel-concrete composite jackets, due to their higher flexural stiffness, exhibits higher flexural capacity compared to steel-reinforced concrete jackets and CFRP sheets. They have a much better performance in terms of ductility.

SHAKE2000 and DEEPSOIL are the two most important programs to calculate the response analysis of soil layer. In order to analyze the similarities and differences between them, and to guide the improvement of the method and program of seismic response analysis of soil layer, 25 KiK net seismic records from 9 stations were selected as the research objects in this paper, from the aspects of surface acceleration, acceleration response spectrum and maximum shear strain of the surface. SHAKE2000 and DEEPSOIL are used to calculate the soft soil site.The results showed that when the soil nonlinearity is not obvious, most of the differences of PGA results calculated by SHAKE2000 and DEEPSOIL can be ignored. The error of the maximum value of soil shear strain calculated by SHAKE2000 and DEEPSOIL is less than 20%. When the soil nonlinearity is obvious, only a few of the differences of PGA results can be ignored, and the error of the maximum value of soil shear strain calculated by SHAKE2000 and DEEPSOIL is less than 20%. In most cases, the acceleration response spectra calculated by SHAKE2000 and DEEPSOIL are not different. Based on the measured records, there are great differences between the calculated results of SHAKE2000 and DEEPSOIL and the measured records, but generally, the calculation method of SHAKE2000 is better than DEEPSOIL and SHAKE2000 is closer to the strong earthquake records.

The exponential rise in wireless communication demands and allied applications have revitalized academia-industries to develop more efficient routing protocols. Wireless Sensor Network (WSN) being battery operated network, it often undergoes node death-causing pre-mature link outage, data drop and retransmission causing delay and energy exhaustion. Furthermore, the presence of a malicious node to impacts network performance adversely. In this paper, a highly robust and efficient Evolutionary computing assisted WSN routing protocol is developed for QoS and energy-efficiency. Our proposed routing protocol encompasses two key functions Network Condition Aware Node Profiling and Malicious Node Detection (NCAMND) exploits or mines the dynamic node/network parameters to identify malicious node, and Evolutionary Computing assisted Dual-Disjoint Forwarding Path (EC-DDFP) model learns over node/network connectivity and availability information to obtain a dual-disjoint path with no-shared components to ensure QoS centric and energy-efficient routing. Simulation results affirm that the proposed routing protocol achieves higher throughput, low energy consumption, and low delay that confirm its suitability for real-time WSN systems.

This paper suggests a decentralized adaptive sliding mode formation procedure for affine nonlinear multi-quadrotor under a fixed directed topology wherever the followers are conquered by dynamical uncertainties. Compared with the previous studies which primarily concentrated on linear single-input single-output (SISO) agents or nonlinear agents with constant control gain, the proposed method is applied on affine nonlinear agents with nonlinear control gain such as the quadrotor. This designing procedure overcomes the problem of unknown nonlinear affine functions of the quadrotors. Fuzzy systems are engaged both to compensate recursively the unknown nonlinear functions and to apply the expert’s knowledge on the formation technique. On-line updating the controller parameters, achieving the formation of quadrotor, boundedness of all signals involved in the closed loop of the quadrotor, and chattering reduction are the focal features of the proposed formation methodology. To demonstrate the persistency and efficiency of the methodology, a numerical example of the multi-quadrotor system is considered in this paper.

Today, due to the limited supply and rapid consumption of fossil fuels, transitioning towards renewable energy supplies has become more important than ever.. The purpose of this paper is to present a new linear permanent magnet vernier machine structure which is designed to capture wave energy and improve the performance of the prototype vernier machine. By halving the proposed vernier machine, amending gear ratio and changing the shape of permanent magnet (PM) and teeth, the performance of the proposed vernier machine increases compared to the prototype vernier machine. This novelty causes the proposed vernier machine to be lighter, more economical and more efficient than the prototype vernier machine. Moreover, the main parameters of the proposed vernier machine compared to the prototype vernier machine are improved, so that in the proposed vernier machine, induced voltage, PM flux and thrust force are increased by 30, 68 and 27% respectively. In addition, the ripple of thrust force is reduced by 5%,  and the self-inductance is diminished by 55%. All analyses have been performed in the same conditions with the finite element method using Ansys Maxwell software.

Today, there is a high number of injuries and various wastes and debris produced during natural and unnatural events. This study aims to investigate the reverse logistics planning problem in the response and reaction phases as well as improvement and reconstruction in earthquake conditions by using a real case study. Regarding the high complexity of this type of optimization problem, a multi-objective model as a multi-vehicle relief logistic problem considering satisfaction levels, is developed concerning the environmental conditions paying attention to uncertainty. To address the problem, an exact solver by using epsilon constraint method is conducted to validate the model. To solve the model optimality, a well-established non-dominated sorting genetic algorithm is tuned and compared with multi-objective particle swarm optimization algorithm to solve the model. Having a conclusion about the main finding of this research, the use of the reverse logistics in the response and the recovery phases has been approved by the results of this paper. Most broadly, the application of the proposed model is validated by using a real case in Tehran, Iran to show the managerial insights of this research.

In the mining industry, at the beginning of development of a project, a consultant is assigned to build a design feasibility study to incorporate the client requirement, government regulation, and other inputs into the design. The consultant usually faces overwhelmed stages due to changes caused by the client and other stakeholders and has to repeat the process of inputting requirements into the design, which will cause delays for the projects. To enhance this design process and improve the quality, the use of “ House of Quality (HoQ)” as part of Quality Function Deployment (QFD) was carried out. In this study it was attempted to improve the design of the Explosive Storage Area, which is the most complicated area where client expectations on the design are required, to meet the regulation. This study also aims to see how much time is saved during the design stages by using the HoQ. From the study, the technical importance rating of the containerized building showed the highest point (13%) followed by a radius between detonation and ammonium nitrate storage area (11%). The improvement design was developed and prioritized based on the rating from technical importance and the results of the design showed great satisfaction of the client. The duration of the design stage was also saved by almost 3 days of the normal design process without using QFD. This study showed the ability of QFD to enhance and assist during the design phase in the feasibility study, and resulted in great client satisfaction for the final product.

Nowadays, with the growth of technology and the industrialization of societies, work-related accidents, and consequently the threat of human capital and material resources are among the problems of the countries of the world. The most important legal solution in most countries to control occupational accidents and illnesses is to conduct periodic site visits and identify hazardous sites. To the best of our knowledge, no study from the supply chain point of view has been reported to model and address this kind of problem. Thus, this paper is to select the best route that reduces the time elapsed between the workshops and the visit time of the inspectors by using two-tier supply chain simulation coupled with the vehicle routing problem (VRP) to give them more opportunity to visit more workshops. In this study, by considering the number of workshops, the limitation of the number of the existing inspectors and the priority of inspecting the workshops, a bi-objective mathematical model is presented. The main aims are to maximize the number of visited workshops and minimize travel times and workshops visit times. In this study, three meta-heuristics (i.e., SA, SEO and RDA) and two hybrid algorithms are used to address the model. Then, the quality of the meta-heuristics and hybrid algorithms are evaluated and compared by using four metrics. The SEO algorithm provides the best performance; however, in a long time, the hybrid GASA algorithm provides the worst performance. Finally, a real-case study is used to validate the presented model.

Many portfolio optimization problems deal with allocation of assets which carry a relatively high market price. Therefore, it is necessary to determine the integer value of assets when we deal with portfolio optimization. In addition, one of the main concerns with most portfolio optimization is associated with the type of constraints considered in different models. In many cases, the resulted problem formulations do not yield in practical solutions. Therefore, it is necessary to apply some managerial decisions in order to make the results more practical. This paper presents a portfolio optimization based on an improved knapsack problem with the cardinality, floor and ceiling, budget, class, class limit and pre-assignment constraints for asset allocation. To handle the uncertainty associated with different parameters of the proposed model, we use robust optimization techniques. The model is also applied using some realistic data from US stock market. Genetic algorithm is also provided to solve the problem for some instances.

Synthesis of ZnO nanostructures films by a co-precipitation followed by the deposition processed onto a glass substrate by spin-coating technique was carried out. The effect of annealing temperatures (from 250 to 325 °C for 30 min) on the structural and optical properties of the ZnO films have been investigated. The structural studies reveal that ZnO films are polycrystalline with hexagonal wurtzite structure. The X-ray diffraction (XRD) data show a better crystallinity at (101) crystal plane for the annealed films at 300 °C than the other ZnO films. The average grain size increases (from 31 to 36 nm) with an increase in annealing temperatures. The band gap energy is approximately 3.40 eV for the as-prepared films and varies from 3.25 to 3.18 eV with an increase in annealing temperatures. The photoluminescence (PL) results show a weak ultraviolet and relatively broad visible emissions respect to various defect structures in the ZnO films, in which the interstitial and vacancy oxygen are the main factors influencing the electronic properties in the whole ZnO films.

In this work, molecular dynamics (MD) simulations were employed to investigate the effects of duty cycle changes and utilization of tantalum nitride interlayer on the surface roughness and adhesion of Ta coating deposited by pulsed-DC plasma assisted chemical vapor deposition. To examine the simulation results, some selected deposition conditions were experimentally implemented and characterized through scanning electron microscopy, atomic force microscopy (AFM) and microscratch tests. The Ta and Ta/TaN coatings were deposited on AISI316L stainless steel substrate in a plasma atmosphere consist of Ar, H2, N2 and TaCl5 vapor at 350 °C. The results showed that at the same duty cycles the surface roughness of Ta/TaN coating is at least 40% less than that of the single layer Ta coating. By increasing the duty cycle from 17 to 40%, the surface roughness significantly decreases about 80%. This is attributed to the further exposure of surface against high energy ions bombardment at higher duty cycles. The presence of TaN interlayer due to its lower lattice mismatch with Ta (under 2%), contributes to the nucleation of Ta grains which consequently leads to reducing the surface roughness. The enhanced adhesion of the Ta coatings on TaN is discussed in view of improving the interfacial stresses as shown by the MD simulations. The MD simulations results were shown to be in good agreement with the experimental data.

Electron beam welding has shown a remarkable job in the space industry for welding of components. It is performed under a vacuum environment that eliminates foreign matter such as hydrogen, oxygen, and other gases. Joining of similar and dissimilar materials is the main advantage of electron beam welding with high depth to width ratio as well as sharp focus at the point where parts are to be welded. EBW reduces the HAZ (heat affected zone), making it one of the most acceptable welding processes. In this study, evaluation of the effect of joining parameters on the mechanical strength and hardness is conducted using Minitab software. The strength of the electron beam weld varies with welding parameters. Therefore, correct and optimized parameter selection imparted the highest welding strength. Some welding parameters directly affect weld strength; those were judiciously selected for our experiments. Therefore, 3x3 arrays were selected for investigation on the microhardness and ultimate tensile strength of Fe49Co2V. Three levels and four factors are chosen for analysis. The input parameters are selected as Accelerating Voltage (KV), Welding Speed (mm/min), Beam Current (mA), and Focus Current (mA). This study reveals the maximum welding strength obtained at High Voltage (55 KV), High Beam current (7 mA), Moderate Speed (20 mm/min), and moderate focus current (2365 mA). Similarly, the microhardness obtained at a High Voltage (55 KV), High beam current (7 mA), high welding speed (30 mm/min) and minimum focus current (2210 mA). This study reveals the maximum welding strength obtained at High Voltage (55KV), High beam current (7mA), moderate speed (20 mm/min) & moderate focus current (2365mA). Similarly, the micro-hardness obtained at a High Voltage (55KV), High beam current (7mA), and the high welding speed (30 mm/min) & minimum focus current (2210mA).

Cobalt ferrite or CoFe2O4 has unique physical and magnetic properties depend on its synthesis method. The application of cobalt ferrite as nanomedicine material become more interesting, however analysis on physical and magnetic properties based on synthesis method have not been discussed. The cobalt ferrite in this research was synthesised using two different the sol-gel with duration sintering variations of 500℃, 800℃, and 1100℃ and unsintered sonochemical. The phase identification analysis and crystal size used XRD and morphology  analysis used SEM, the functional group bond analysis used FTIR, and magnetic property analysis used VSM. The smallest crystal size from the XRD result was 13.25 nm with 57.04% crystallinity. The morphology from the synthesized cobalt ferrite was mostly agglomerated. The FTIR showed functional group vibration at 601-636 cm-1 that signified the spinel structure of the cobalt ferrite. There was a change of hysteresis loop curve from hard magnetic to soft magnetic, and there was a sample with a paramagnetic curve.

Residual stresses are created usually undesirably during manufacturing processes, including casting, welding, metal forming, etc. Residual stresses alone or in combination with other factors can cause the destruction and fracture of components or significant decline in their service life. Therefore, it is crucial to measure the residual stresses. Contour method is a destructive testing method capable of measuring residual stresses of the cut surface along with being simple and low-cost. This method is able to create a two-dimensional map of residual stresses perpendicular to the sectioned surface. Measuring hollow samples is still a dilemma when using the contour method. In this study, hollow cylindrical samples with inner diameters of 20 and 40 mm were quenched at temperatures of 300ºC, 400ºC, and 850ºC. Both numerical analyses and experimental measurements were performed for the samples. The contour method was practiced for both hollow and filled samples. Overall review of the results was promising. However, the results obtained in the vicinity of the edges illustrated large deviations. Steel shafts were inserted to cylindrical holes to rectify the lack of constraint near the edges. The measurements on the filled samples were greatly improved.

In this paper, the statistical analyses are presented to study the thermal efficiency and power output of gas turbine (GT) power plants. For analyzing gas turbine operation and performance, a novel approach is developed utilizing the response surface methodology (RSM) which is based on the central composite design (CCD) method. An attempt is made to study the effect of some operational factors (inlet temperatures of turbine and compressor, inlet pressure of compressor, lower heating value of fuel (LHV) and air mass flow rate)  and design parameters (pressure drop of combustion chamber and isentropic efficiency of equipment) on the system’s response. Based on the DoE analysis, regression models are presented to quantify the effects of these parameters on thermal efficiency and net work of the Brayton based gas turbine cycle. The proposed correlations obtained by the analysis have a remarkably satisfactory performance for all simulation data. The error analysis shows a maximum error of 5.5% in numerical computations of response functions for GT power plants. The optimal point of the thermal efficiency and net power output based on the optimized conditions were found to be 45.71% and 4.182 MW, respectively

Steel laser tailor-welded blanks (TWBs) are produced by end-to-end joining of base sheets using different welding methods. In this article, the formability of laser TWBs of St12 and St14 with thicknesses of 1 mm and 1.5 in single point incremental forming process were experimentally and numerically investigated. First, the forming limit wall angle was experimentally determined for each of the base sheets. Then, SPIF of TWBs samples was carried out at the thinner sheet wall angle; 67°. For numerical investigation, the mechanical properties of the weld zone were obtained. For one combination of TWBs, the finite element (FE) simulation of incremental forming was performed by the use of ABAQUS/Explicit FE software. The simulation process was validated by comparing the results with those of experiments. Then, the effect of SPIF on thickness, stress and strain distribution of other combinations of TWBs was numerically investigated. The results showed that using the FE model, the SPIF of TWBs without performing high cost experimental tests can be properly investigated. Also, the results revealed that in steel laser TWBs with different thicknesses, the maximum and minimum principal strains are concentrated at the corners and the walls of the thinner sheet of TWBs, respectively. Hence, the maximum amount of effective strain is concentrated at the thinner side of TWBs corners and the weld zone of the two blanks. For the same reason, rupture is observed at these regions.

The effect of moisture absorption and high temperature on the compressive strength of unidirectional IM7/977-2 carbon/epoxy resins have been investigated experimentally. The specimens were divided into 4 groups, and tested under 4 different conditions by varying the testing temperature and moisture parameters. The fiber orientation selected were 0o, ±45o and 90o. The reported results showed that the compressive strength, fracture load and compressive modulus of the specimens were degraded under the influence of moisture absorption and high temperature. The largest compressive strength degradation was observed in the unidirectional specimens. Furthermore, the most severe case was noted for the specimens that were immersed in water and tested at 80°C. The observed reduction in the strength varies depending on the fiber orientation, immersion time and test temperature. The results indicate the importance of considering environmental parameters in designing the composite structures for compression loadings.

This article proposes a new approach for centralized path planning of multiple aircraft in presence of the obstacle-laden environment under low flying rules. The problem considers as a unified nonlinear constraint optimization problem. The minimum time and control investigate as the cost functions and the maximum velocity and power consider as the constraints. The pseudospectral method applies as a popular and fast direct method to solve the constrained path planning problem. The three-degree-of-freedom nonlinear point mass equations of motion with realistic operational aircraft constraints consider through the simplified mathematical model. The fixed obstacle considers as a combination of spheres with different radius. Also, the moving obstacles consider as a sphere with a known radius and fly at a constant speed. The effectiveness of the proposed concept will be demonstrated by presenting four case studies with a different number of aircraft along with the static and moving obstacles in various scenarios to ensure safe and effective flights.

Filtration index of the drilling fluid is an important parameter of well drilling, especially at drilling-in the reservoirs. Standard parameter in the study of drilling fluids is static filtration index. At the same time, it is more feasible to determine dynamic filtration index, if considering actual conditions of the well. Use of polymer carbonate-weighted drilling fluids is advisable at drilling-in oil and gas formations; but, it is also necessary to take into account fractional composition of the weighting agent. Aim of the work is to study the influence of weighting-bridging agent's fractional composition on drilling fluid's dynamic filtration index. Taking into account main theories of bridging agent selection, such as the theory of Abrams, Kaeuffer and Vickers, will make it possible to define the influence of carbonates “blend” on the filtration losses of the drilling fluid. Dynamic high pressure high temperature (HPHT) filter was used in this research, which allows measuring filtration properties of the drilling fluid as in standard HTHP test, with fluid circulating inside the cell. In order to get results that are closer to real conditions, in addition to the standard paper filter, studies were carried out on ceramic disks with a known porosity. Theories on selection of bridging agents considered in the paper have their advantages and disadvantages. Depending on available data on the reservoir (for example, data availability on porosity and permeability) and access to high-quality bridging material, a more effective theory is chosen and the negative effect of the drilling fluid on the productivity of the formation is reduced.

In this paper, we present a novel and efficient algorithm for image inpainting based on the structure and texture components. In our method, after decomposing the image into its texture and structure components using PCA (Principal Component Analysis), these components are inpainted separately using the proposed algorithm. Finally, the inpainted image is simply acquired by adding the two inpainted images. For structure inpainting we used quadtree concept to identify the importance of each pixel located on the boundary of the target region. Subsequently, we detect the correct path for filling so that this path demonstrates an orientation for the better structure inpainting. It is noteworthy that structure inpainting is more important because human vision is sensitive to the coherence of structure. For texture inpainting, we use Euclidean distance in the texture component for patch selection. Also, the geometric feature is considered by LSK (Local Steering Kernel) in the original image to assist chooing a better patch candidate. The experimental results of our algorithm demonstrate the effectiveness of the proposed method.

Content-based image retrieval is one of the interesting subjects in image processing and machine vision. In image retrieval systems, the query image is compared with images in the database to retrieve images containing similar content. Image comparison is done using features extracted from the query and database images. In this paper, the features are extracted based on the human visual system. Since the human visual system considers the texture and the edge orientation in images for comparison, the colour difference histogram associated with the image’s texture and edge orientation is extracted as a feature. In this paper, the features are selected using the Shannon entropy criterion. The proposed method is tested using the Corel-5K and Corel-10K databases. The precision and recall criteria were used to evaluate the proposed system. The experimental results show the ability of the proposed system for more accurate retrieval rather than recently content-based image retrieval systems.

Video contents have variations in temporal and spatial dimensions, and recognizing human actions requires considering the changes in both directions. To this end, convolutional neural networks (CNNs) and recurrent neural networks (RNNs) and their combinations have been used to tackle the video dynamics. However, a hybrid architecture usually results in a more complex model and hence a greater number of parameters to be optimized. In this study, we propose to use a stack of gated recurrent unit (GRU) layers on top of a two-stream inflated convolutional neural network. Raw frames and optical flow of the video are processed in the first and second streams, respectively. We first segment the video frames in order to be able to track the video contents in more details and by using 3D CNNs extract spatial-temporal features, called local features. We then import the sequence of local features to the GRU network, and use a weighted averaging operator to aggregate the outcome of the two processing flows, called global features. The evaluations confirm acceptable results for the two HMDB51 and UCF101 datasets. The proposed method resulted in a 1.6% improvement in the classification accuracy of the HMDB51 challenging dataset compared to the best reported results.

Video compression has become a source of different research studies. It is necessary in order to address channel bandwidth limitations and growing video demand, including digital libraries and streaming media delivery via the Internet. A video is a number of frames captured by a camera while a scene is a series of consecutive frames captured from a specific narrative viewpoint. To compress a video, firstly, the intra frames are separated from inter frames using scene change detection methods. Then, block-based motion estimation algorithms are used to eliminate the temporal redundancy between successive frames. This paper describes some scene change detection methods for use on the uncompressed video to detect scene types such as cut, dissolve, wipe, etc. Absolute Frame Difference (AFD), Mean Absolute Frame Differences (MAFD), Mean Histogram Absolute Frame Difference (MHAFD), and Maximum Gradient Value (MGV) techniques are adaptively tested on different video types to identify accurate scene change in both low and high object motion scenes. Test results show that the proposed approach (MHAFD) obtains a better accuracy, F1-scor measure of 100%, especially for cuts and gradual transitions (wipe) video types. Dissolve scene change is detected with a high precision of 100% (i.e., no false detection) with the (MAFD) detector. Besides, in terms of time complexity for analyzing all the video samples, the proposed method (MHAFD ) provides the best result compared to the selected detectors.

Biometrics plays a crucial role in security systems. Gait recognition as an aspect of behavioral biometrics deals with identifying human based on the walking. In this research, we proposed a new method to identify people according to their gait characteristics. This approach is performed via several steps; a) the video frames of a walking subject is recorded. b) each video is decomposed into eight phases, wherein each phase, there are several frames. One frame per phase is selected. c) the extracted frame is segmented to separate the subject from the background. d) the image is converted to a binary image, and the skeletonization is applied to obtain the silhouette of the image. e) the fast Fourier transform is applied to each frame, and several statistical features are calculated. The average of the statistical measures for eight frames of a video is computed as a feature vector for the subject. Finally, the correlation is used to identify the subject based on the feature vector. The accuracy of 100% is achieved for the recognition of the subjects in the CASIA dataset.

Video quality assessment is a crucial routine in the broadcasting industry. Due to the duration and the excessive number of video files, a computer-based video quality assessment mechanism is the only solution. While it is common to measure the quality of a video file at the compression stage by comparing it against the raw data, at later stages, no reference video is available for comparison. Therefore, a no-reference (Blind) video quality assessment (NR-VQA) technique is essential. The current NR-VQA methods predict only the mean opinion score (MOS) and do not provide further information about the distribution of people score. However, this distribution is informative for the evaluation of QoE. In this paper, we propose a method for predicting the empirical distribution of human opinion scores in the assessment of video quality. To this end, we extract some frame-level features, and next, we feed these features to a recurrent neural network. Finally, the distribution of opinion score is predicted in the last layer of the RNN. The experiments show that averages of predicted distributions have comparable or better results with previous methods on the KonVid-1k dataset.

Recognizing the license plate from a set of low-resolution video frames using an Optical Character Recognition system (OCR) is a very challenging task. OCR systems fail to properly work in this condition. The use of high-quality cameras is a costly solution to this situation. To overcome this problem, we propose a weighted interpolation method that enhances the resolution of the license plate, using consecutive frames of a video. For this purpose, first, we register the low-resolution video frames of the license plate to the reference license plate in two steps. In the first step, a coarse registration is performed by matching the SURF features. Then a fine registration on the license plate region is performed using the phase correlation technique. After registration, the reference image of the license plate is up-sampled to the desired scale. We propose a method for estimating the intensity of pixels in the up-sampled image with an unknown value. In this method, we use a weighted averaging strategy to estimate the intensity of unknown pixels using the neighboring pixels from video frames.  The obtained super-resolution is suitable for OCR. Experimental results show that applying the proposed method on low-resolution frames of the license plate, improves the quality of the license plate significantly.

This paper presents a novel method to speedup content-based image retrieval (CBIR) systems. The proposed method can be very useful for retrieving images from a large database. For this task, Zernike and Wavelet features are first extracted from the query image, then an interval of potential matching images is computed from the database images using the extracted feature. Therefore, the query image is compared with images in the interval rather than the whole database which to speedup the retrieval process. Particle swarm optimization is employed to select relevant features among Zernike and Wavelet features, which leads to decrease feature extraction time. Three types of experiments are conducted to evaluate effectiveness the proposed method in terms of database reduction, retrieval accuracy and retrieval time. In the best case, the Corel-1k database is averagely reduced up to 33.98% from its original size, and preserving 71.92% of relevant images. Retrieval accuracy in reduced database is increased by 1% in comparison with retrieving from the original database. Meanwhile, the retrieval time is reduced up to 58.57% in comparison with retrieval time from the original database.

On many occasions, the evaluation of a phenomenon based on a single feature could not solely be resulted in comprehensive and accurate results. Moreover, even if we have several features, we don’t know in advance, which feature offers a better description of the phenomenon. Thus, selecting the best features and especially their combination could lead to better results. An affinity graph is a tool that can describe the relationship between the samples. In this paper, we proposed a graph-based sample-based ranking method that sorts the graphs based on six proposed parameters. The sorting is performed such that the graphs at the top of the list have better performance compared to the graphs at the bottom. Furthermore, we propose a fusion method to merge the information of various features and improve the accuracy of label propagation. Moreover, a method is proposed for parameter optimizations and the ultimate decision fusion. The experimental results indicate that the proposed scheme, apart from correctly ranking the graphs according to their accuracy, in the fusion step, increases the accuracy compared to the use of a single feature.

Foreground extraction is one of the crucial subjects in image processing, which drives different applications in industry. The reality behind the continuous research in this area is the various challenging problems we encounter during the separation process of foreground and background images. Among the source separation approaches, the independent component analysis (ICA) is the most prevalent, being involved in different areas of signal separation applications. Despite the improvements being achieved in foreground extraction, the sudden luminance variations and background movements adversely impact the results of techniques in this regard. In this paper, a novel structure called HSIC_ICA is introduced to address the mentioned problem using a modified version of the ICA algorithm which, leverages the Hilbert-Schmidt Independence Criterion (HSIC) instead of the common objective functions.  Moreover, the unmixing matrix elements of ICA are extracted through a Particle Swarm Optimization (PSO) evolutionary algorithm in a much faster way. The experimental results clearly show that the proposed method outperforms over the significant works being cited among the references, using Wallflower dataset.

The present paper proposes a novel vector control based method to connect a wind plant equipped with a Doubly-Fed Induction Generator to the grid. It also provides separate control capacity of injection power to the grid under wind shortages in addition to optimum performance in normal climatic conditions. The mathematical modeling of converters of the grid and rotor side is presented, which provides such a control tool. The idea of using an energy storage system has been presented to reduce power swings of the wind plant to grid in the dc-link of back-to-back converter of the rotor side. In order to achieve an optimal control system, the strategy of maximum wind power tracking and unit power factor of the wind farm are included in the control system. However, the power exchange strategy with the unit power factor is related to the type of operation of the grid, and reactive injection power can also be controlled when needed. Finally, a simulation of the studied system and the proposed control system in the SIMULINK environment of MATLAB software is presented, which provides a powerful tool for these types of systems. The results obtained from the conducted studies on a sample system demonstrate the efficiency and accuracy of the proposed method.

Monitoring the facial expressions of patients in clinical environments is a necessity in addition to vital sign monitoring. Pain monitoring of patients by facial expressions from video sequences eliminates the need for another person to accompany patients. In this paper, a novel approach is presented to monitor the expression of face and notify in case of pain using tracking fiducial points of face in video sequences and spatio-temporal Local Binary Patterns (LBPs) for eyes and eyebrows. The motion of eight fiducial points on facial features such as mouth, eyes, eyebrows are tracked by Lucas-Kanade algorithm and the movement angles are recorded in a feature vector which along with the spatio-temporal histogram of LBPs creates a concatenated feature vector. Spatio-temporal LBPs boost the proposed algorithm to capture minor deformations on eyes and eyebrows. The feature vectors are then compared and classified using the Chi-square similarity measure. Experimental results show that leveraging spatio-temporal LBPs improves the accuracy by 12% on STOIC database.