Contact dynamic modeling of a liquid droplet between two approaching porous materials

A computational fluid dynamics model based on a finite difference solution to mass and momentum conservation equations (Navier–Stokes equations) for a liquid droplet transport between two porous or nonporous contacting surfaces (CSs) is developed. The CS dynamic (equation of motion) and the spread of the incompressible liquid available on the primary surface for transfer are coupled with the Navier–Stokes equations. The topologies of the spread dynamic between and inside both surfaces (primary and CSs) are compared with experimental data. The amount of mass being transferred into the CS, predicted by the model, is also compared to the experimental measurements. The impact of the initial velocity on the spread topology and mass transfer into the pores is addressed. © 2014 American Institute of Chemical Engineers AIChE J, 60: 2346–2353, 2014     

VALIDATION OF THE FRACTURE MECHANICS TEST METHOD EGF P1–87D (ESIS P1–90/ESIS P1–92): ANALYSIS OF AN EXPERIMENTAL ROUND ROBIN

Abstract— The elastic—plastic fracture mechanics test method EGF P1–87 D: EGF Recommendations for Determining the Fracture Resistance of Ductile Materials has been validated by an extensive round robin, covering fracture tests and their evaluation as well as scanning electron fractography. The results confirmed the suitability of the procedure, but suggested some modifications. The resulting procedure ESIS P1–90 was then further modified and its actual designation is ESIS P1–92.
The present report provides comprehensive information on the determination of crack growth resistance curves and initiation values. Particular emphasis is on single specimen techniques and on determining the stretch zone width. Beyond the validation of the ESIS procedure the information given is pertinent to elastic-plastic fracture testing in general.     

Chaos-based image encryption using hybrid model of linear-feedback shift register system and deoxyribonucleic acid

Multimedia Tools and Applications - The security of digital images has been under much more attack recently. A novel image security based on a hybrid model of deoxyribonucleic acid (DNA),...     

Elite artificial bees' colony algorithm to solve robot's fuzzy constrained routing problem

One of the fundamental challenges of the robotics field is robot's movement. That is, why route planning is an eminent issue of robotics research and it is used to enhance autonomy of moving robots in complex environments. The objective of route planning problem is to find the shortest route without collide from initiation point to destination point so that the amount of energy consumption by robot would not exceed a predefined amount. Because neither the amount of energy consumption nor the robot's passed distance index cannot be measured precisely due to environmental conditions, and fuzzy data is used for modeling the problem and the problem would be called “Robot Fuzzy Constrained shortest Route” problem. The main contributions of this study are fivefold: (i) The mathematical model of fuzzy constrained shortest route problem (FCSRP) is formulated; (ii) An elite artificial bees' colony (EABC) algorithm is used to solve the robot's FSCRP; (iii) The proposed EABC algorithm is simulated with two fuzzy networks; (iv) The performance of the proposed approach is compared with the performance of genetic algorithm and particle swarm optimization algorithm; and (v) The results show the convergence speed of the EABC algorithm is higher than the existing algorithms.     

An EM based probabilistic two-dimensional CCA with application to face recognition

Recently, two-dimensional canonical correlation analysis (2DCCA) has been successfully applied for image feature extraction. The method instead of concatenating the columns of the images to the one-dimensional vectors, directly works with two-dimensional image matrices. Although 2DCCA works well in different recognition tasks, it lacks a probabilistic interpretation. In this paper, we present a probabilistic framework for 2DCCA called probabilistic 2DCCA (P2DCCA) and an iterative EM based algorithm for optimizing the parameters. Experimental results on synthetic and real data demonstrate superior performance in loading factor estimation for P2DCCA compared to 2DCCA. For real data, three subsets of AR face database and also the UMIST face database confirm the robustness of the proposed algorithm in face recognition tasks with different illumination conditions, facial expressions, poses and occlusions.     

Jet entrainment rate in air curtain of open refrigerated display cases

Experimental and computational methods are used to address those parameters that have significant effects on the amount of entrained (warm) air in an open refrigerated display case. These parameters are identified, quantified, and the rate of entrainment is expressed as a function of these parameters. It is found that the turbulence intensity, the shape of the mean velocity profile at the discharge air grill, and the Reynolds number are mainly responsible for the amount of entrained air in a display case. It is also concluded that lower Reynolds numbers will reduce the amount of the entrained air in the display case, however, the trade off will be higher temperature of the food products on shelves. Digital particle image velocimetry (DPIV) was used to map the entire mean velocity flowfield and the turbulence intensity. The laser doppler velocimetry technique was also used to verify the mean velocity and turbulence intensity measurements made by DPIV. The results indicated an excellent agreement between both methods. Parametric studies for the rate of entrainment of the outside air into the display case were performed using a computational fluid dynamics tool. The results indicate that lowering the Reynolds number of the air curtain reduces the entrainment rate. However, sufficiently high momentum should still exist to enforce the integrity of the air curtain structure.     

Dietary PUFA Increase Apoptosis in Stomach of Patients with Dyspeptic Symptoms and Infected with <Emphasis Type="Italic">H. pylori</Emphasis>

Drug-resistant strains of Helicobacter pylori and poor treatment response are the main reasons for the failure in eradicating it in patients. Polyunsaturated fatty acids (PUFA) have an inhibitory effect on bacterial growth. The aim of this study was to investigate the effect of PUFA in combination with standard triple therapy on apoptosis in H. pylori infected subjects with dyspeptic symptoms. This study was a double-blind clinical trial in which 34 H. pylori infected subjects with dyspeptic symptoms were randomly divided into two groups of 17 patients. The control group received standard triple therapy (amoxicillin, clarithromycin and omeprazole) and the experimental group received the standard therapy and PUFA for two weeks. Gene expression levels of caspase-3, BCL-2 and Bad proteins were studied with real-time PCR, while protein levels were quantified in frozen sections and using immunohistochemistry. Compared with the control group, a significant increase (p < 0.01) was observed in the expression of caspase-3 and Bad genes and a significant reduction (p < 0.05) in the expression of Bcl-2 gene. The protein level of active caspase-3 and Bad protein was significantly increased and the level of Bcl-2 protein was significantly decreased (p < 0.05). The results of this study show that oral administration of PUFA in combination with the standard triple therapy increased apoptosis in H. pylori-infected patients with dyspeptic symptoms. This increase in apoptosis may partly reduce drug resistance in these patients. Our results suggest inclusion of a dietary PUFA containing fatty acid supplement may improve treatment of patients that are refractory to the standard triple therapy.     

An Efficient Computational Hybrid Filter to the SLAM Problem for an Autonomous Wheeled Mobile Robot

The using of an autonomous wheeled mobile robot (AWMR) that perform diverse processes in a numerous number of applications without human’s interposition in an unknown environment is thriving, nowadays. An AWMR can search the environment, create an adequate map, and localizing itself into this map, by interpreting the environment, autonomously. The FastSLAM is a structure for simultaneous localization and mapping (SLAM) for an AWMR. The correctness and efficiency of the estimation of the FastSLAM often depend on the accurate a previous knowledge of the control and measurement noise covariance matrices. Also, inaccurate previous knowledge may seriously degrade their efficiency. One of the major causes of losing particle manifold is sample impoverishment in the FastSLAM. These cases of the most main problems. This paper presents a robust new method to solve these problems as called Hybrid filter SLAM. In this method, for learning the measurement and control noise covariance matrices for increasing correctness and consistency are utilized Intuitionistic Fuzzy Logic System (IFLS). In order to optimize efficiency of sampling from Cuckoo Search (CS). The results of the simulation and experimental shown that the Hybrid filter SLAM is efficient than the FastSLAM that has less number of computations and good performance for the larger environment.

     

Parallel multi-objective artificial bee colony algorithm for software requirement optimization

Requirements Engineering - In incremental software development approaches, the product is developed in various releases. In each release, a set of requirements is proposed for the development....     

Solving the Task Starvation and Resources Problem Using Optimized SMPIA in Cloud

In this study, a new feature is added to the smart message passing interface (SMPI) approach (SMPIA) based on the prioritization method, which can completely eliminate the task starvation and lack of sufficient resources problems through prioritizing the tasks. The proposed approach is based on prioritizing the tasks and the urgency of implementation. Tasks are prioritized based on execution time, workload, the task with a more sensitive priority is executed earlier by the free source. The idea of demand-bound functions (DBFs) was extended to the SMPIA setting based on partitions and caps. For each task, two DBFs are constructed, DBFLOand DBFHI, for the LO and HI criticality modes, respectively. The simulation results returned by MATLAB showed that with the optimized SMPIA (O-SMPIA), the parameters of maximum service execution time, response time, delay time, and throughput improved in this work. In addition, the results confirmed that the reduction of execution time, completion time, and resource consumption time did not affect the response time and throughput of workflow tasks and did not cause inefficient use of resources in virtual machines (VMs) and data centers (DCs). The evaluation of performance metrics showed that the delay, response time of the Greedy algorithm was less than that of Max-Min and Min-Min. At the same time, the execution time of Max-Min was less than the others and the throughput of the Greedy was longer. The effect and throughput of O-SMPIA became more obvious as change to the job count and the number of cloud workloads increased. It is also worth mentioning that one of the main advantages of the O-SMPIA to other methods is the efficient use of time to execute all the defined tasks by CPU.