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Considering the importance of financial accountability of public hospitals, identifying financial accountability assessment indicators in these hospitals is important. In a way that in the absence of appropriate indicators, taking accountability by hospitals and evaluating it by the public is difficult or impossible.  Therefore, this research examined the financial accountability of hospitals based on the national accountability checklist.

The research method is exploratory and survey type. The sample consists of 101 people selected from financial managers, accounting directors, and those in charge of budgets of public hospitals and clinics of Fars Province in 2018. One sample t-test and mid-test were used in this study. 

From the perspective of experts, indicators mentioned in national accountability checklist including the identification of financial statements items, the identification of items of changes in financial statements, the presentation of items of account turnover changes in net value, the presentation of comparison items of budget and performance, the disclosure of explanatory notes of financial statements and general criteria supply a basis for improving financial accountability of public hospitals. 

Regarding the transparency and more financial accountability managers of hospitals and financial authorities of the Medical Sciences Universities as well as the Ministry of Health and Medical Education should provide appropriate opportunities for financial reporting of the public sector based on the framework of national accountability checklist disclosure (indicators) in hospitals.

The minimum crossing number problem is among the oldest and most fundamental problems arising in the area of automatic graph drawing. In this paper, eight population-based meta-heuristic algorithms are utilized to tackle the minimum crossing number problem for two special types of graphs, namely complete graphs and complete bipartite graphs. A 2-page book drawing representation is employed for embedding graphs in the plane. The algorithms consist of Artificial Bee Colony algorithm, Big Bang-Big Crunch algorithm, Teaching-Learning-Based Optimization algorithm, Cuckoo Search algorithm, Charged System Search algorithm, Tug of War Optimization algorithm, Water Evaporation Optimization algorithm, and Vibrating Particles System algorithm. The performance of the utilized algorithms is investigated through various examples including six complete graphs and eight complete bipartite graphs. Convergence histories of the algorithms are provided to better understanding of their performance. In addition, optimum results at different stages of the optimization process are extracted to enable to compare the meta-heuristics algorithms.

In structural design, either the experience of designer is used or a uniform grouping is usually utilized to group the elements. This type of grouping affects the fundamental cost of the buildings, including the cost of concrete, steel and formwork, as well as secondary costs such as laboratory, checking, fabrication and etc. However, the secondary costs are not usually considered in the cost function. Strategies can also be used to automate the grouping of members in structural design. In this strategy beams and columns are automatically grouped into a limited number of groups to achieve the lowest cost. In this study, enhanced colliding bodies optimization algorithm is used to automatically group the beams and columns of the reinforced concrete structures and also to optimize their cost. The proposed procedure applied to three reinforced concrete frames with four, eight and twelve stories and the influence of automatic grouping of the members in optimal cost is investigated. Using this method, the beams and columns are automatically grouped and the results show that the optimal cost obtained from the automatic grouping is less than the manual grouping of the members.

For an efficient solution of the equations arising from finite element analysis, the stiffness matrix of the model should be structured. This can be done by reducing the profile or wavefront of the corresponding graph matrix of the structure depending on whether skyline or frontal method being used, respectively. One of the efficient methods to achieve this goal is the use of the method of King, extended by Sloan. In this paper the coefficients of the priority function utilized in the generalized Sloan’s method are optimized using the recently developed metaheuristic algorithm, so-called vibrating particles system. The results are compared to those of other metaheuristic algorithms consisting of the particle swarm optimization, colliding bodies optimization, enhanced colliding bodies optimization, and tug of war optimization. These metaheuristics, are used for optimum nodal numbering of the graph models of the finite element meshes to reduce the profile and wavefront of the corresponding sparse matrices. Comparison of the results achieved by these metaheuristic algorithms and those of the King and Sloan, demonstrates the efficiency of the new metaheuristic utilized for profile and wavefront optimization.

Considering both size and dimensions of the offshore wind turbine structures, design optimization of such structures is a fruitful yet, simultaneously, onerous task due to the tempestuous complexity of the problem, which mostly comes from their environment. However, in this study, a computerized methodology based on meta-heuristic algorithms, consisting of the Colliding Bodies Optimization (CBO), Enhanced Colliding Bodies Optimization (ECBO), and Vibrating Particle System (VPS), is presented such that more economic upshots can be accomplished. Hence, minimization of the total weight of the structure subjected to a number of structural constraints, including a frequency constraint, by applying the above mentioned algorithms is the underlying goal of this study. Using the data from Horns Rev I offshore wind farm, which is located in the coastlines of Denmark in the North Sea, this study is performed based on a simplified structural model of a monopile offshore wind turbine structure, which can be utilized in preliminary stages of pertinent projects for conducting suitable comparisons.

In the present study, mixing of two fluids of different viscosities in a micromixer with oscillating stirrer was simulated by MRT-LBM and the effect of aspect ratio (AR) of stirrer on mixing efficiency was analyzed. The simulation was performed at Re=50, Sc=10. The results showed that at low values of amplitude (K), at low values of Strouhal number (St), increase of AR causes increase in mixing efficiency and at other values of St it decreases and then increases. At intermediate values of K, at low and intermediate St, mixing efficiency decreases with the increase of AR and at high values of St, it first decreases and then increases. At high values of K, at low and high St, increasing AR causes no improvement in mixing efficiency and at intermediate values of St, mixing efficiency decreases and then increases. In this research, the best mixing efficiency for viscosity logarithmic ratio (R) =2 is at AR=0.7, St=1, K=0.5. The effect of AR and St on mixing efficiency at different R was analyzed and results revealed that for two fluids of different viscosities, at very low values of St, mixing efficiency increases with the increase of R and at others decreases considerably. In general, for two fluids of different viscosities, stirrer with low values of AR has better mixing efficiency.

Shear failure of slender beams made of high strength concrete (HSC) is one of the most crucial failures in design of reinforced concrete members. The accuracy of the existing design codes for HSC unlike the normal strength concrete (NSC) beams seems to be limited in prediction of shear capacity. This paper proposes a new set of shear strength models for HSC slender beams without web reinforcement using conventional multiple linear regression, advanced machine learning methods of multivariate adaptive regression splines (MARS) and group method of data handling (GMDH) network. In order to achieve high-fidelity and robust regression models, this study employs a comprehensive database including 250 experimental tests. Various influencing parameters including the longitudinal steel ratio, shear span-to-depth ratio, compressive strength of concrete, size of the beam specimens, and size of coarse aggregate are considered. The results indicate that the MARS approach has the best estimation in terms of both accuracy and safety aspects in comparison with regression methods and GMDH approach. Moreover, the accuracy and safety of predictions of MARS model is also remarkably more than the most common design equations. Furthermore, the robustness of proposed models is confirmed through sensitivity and parametric analyses.

Despite widespread application of grillage structures in many engineering fields such as civil, architecture, mechanics, their analysis and design make them more complex than other type of skeletal structures. This intricacy becomes more laborious when the corresponding analysis and design are based on plastic concepts. In this paper, Finite Element Method is utilized to find the lower and the upper bounds solutions of rectangular planner grids and this method is compared with analogues Finite Difference Method to indicate the efficiency of proposed approach.

Archaeologists believe that men who lived in Archaeological sites of Mazandaran such as Komishan cave, Hutu and Kamarband, After leaving the cave were gradually formed the Gohar tappeh. Over time, people living with the loss of previous places were higher places. In Neolithic village has been form of rural life there, and And the Bronze period considered and the state of urbanization has found. Archaeological studies dating this area back to seven thousand years and findings of the Bronze era (the third millennium), Iron II Age (mid-second millennium B.C.) unfold it. this study provided Archaeoseismology based on knowledge paleoseismological on the fault system of the Khazar in the protohistory area on Gohar tappeh in Behshahr of Mazandaran province. Field reviews of paleoseismological has been in the archeology trenches of the Gohar tappeh site and geophysical data (GPR and geoelectric) from this range is evaluated at the appropriate scale. On the basis of paleoseismology researches, five earthquake events in period of 3500 to 5000 past years, with magnitude of 7 -6.2 on the moment magnitude scale (Mw) detected. The maximum displacement of detected index in paleoseismological observations by the Geophysical perceptions and GPR data also confirmed. Moreover the average course back of earthquake events is estimated at about 375 years. According to Archaeoseismology researches conducted in area, occurrence of earthquake events has been identified that in Range a few hundred years ago Cause loss or migration and immigration of protohistorical Gohar Tappeh people.

Vibrating particles system (VPS) optimization is a recently developed metaheuristic algorithm for optimization. This algorithm is inspired by the free vibration of freedom systems’ single degree with viscous damping. In this method, each answer is modeled as a particle that moves to its equilibrium position; new positions of the vibrating particle system are updated according to a historically best position. Enhanced Vibrating Particles system (EVPS) uses new approaches to improve the performance of the VPS algorithm. In this study, a dynamic method and modal based approach consisting of natural frequencies and mode shapes are used in the objective function formulation. To demonstrate the performance of the VPS and EVPS, different truss structures including several multiple elements scenarios with noise and without noise in modal data are considered for detecting damage problems. Additionally, all scenarios are studied with significant mutations. Results show that the EVPS algorithm has reached better answer compared to the VPS algorithm for damage detection problems.

In this study, the thermal characteristics of two impinging flame jets are investigated. For the flame structure and temperature field analysis, a non-contact method named Mach-Zehnder Interferometry is used. Mach zehnder method is utilized to determine the effective parameters of flame structure in different amount of Reynolds number and equivalence ratio. The hydraulic diameter of the burners is considered 1.3 mm with 20 mm length and 10 mm width. The angle between two burners is 77 degree. The effect of fuel/air ratio is investigated, when Reynolds number is 70 and equivalence ratio varies between 0.8 and 2.5. Maximum temperature and velocity occurs in equivalence ratio of 1 but at this point, increasing of Reynolds number leads to enhance the maximum temperature and at the same time the growth of the maximum temperature domain.

This paper presents a new non-gradient nature-inspired method, Lion Pride Optimization Algorithm (LPOA) for solving optimal design problems. This method is inspired by the natural collective behavior of lions in their social groups "lion prides". Comparative studies are carried out using fifteen mathematical examples, two benchmark structural design problems, in order to verify the effectiveness of the proposed technique. The LPOA algorithm is also compared with other algorithms for some mathematical and structural problems. The results have proven that the proposed algorithm provides desirable performance in terms of accuracy and convergence speed in all the considered problems.

In this paper, an efficient approach is presented for finding optimal domain decomposition in conjunction with k-median method. Using the clique graph, the connectivity properties of finite element meshes is represented. In order to divide the nodes of the graph or the meshes of the finite element model into k subdomains, k-median approach is employed. For optimal subdomaining, a recently developed metaheuristic algorithm so-called Global Sensitivity Analysis Based (GSAB), is utilized. The performance of the proposed method is investigated through three finite element models for minimize the cost of k-median problem. A comparison of the numerical results obtained using the proposed method with standard Colliding Bodies Optimization (CBO) and Particle Swarm Optimization (PSO) algorithms indicates that the proposed technique is capable of locating more promising solutions using less computational efforts.

The unique characteristics of the Underwater Acoustic Communication (UWAC) channel cause the UWAC systems to be very vulnerable to the malicious attacks. So, the bionic-based UWAC has been used due to its good covert performance, and its suitable frequency and correlation properties. It may not be covert in all the underwater environments, or an adversary can detect the message anyway. Therefore, this paper aims at proposing an improved Merkle hash tree based secure scheme that can resist the current possible underwater attacks, i.e., the replay attack, the fabricated message attack, the message altering attack, and the analyst attack. The security analysis indicates that the proposed scheme is resilient to the mentioned attacks. Also, the performance evaluations show that the proposed scheme is proportional to the UWAC limitations due to its efficiency in terms of energy consumption, communication overhead, and computation cost.

Eggplant (Solanum melongena L.) is an economically important crop with a wide range of fruit shapes and colors. Breeding programs in eggplant focus mainly on fruit quality. Production of commercial triploid cultivars and emission of seeds in fruits may increase acceptability by consumer and increase fruit quality. Induced tetraploidy and cross between di and tetraploid parental line is a conventional method used in different fruits and vegetables like watermelon. The current study aim to find how may induced tetraploidy affect pollen grain quality, its fertility, seed and transplant vigor in different eggplant cultivars. Aiming to investigate autotetraploidy in four qultivars of Solanum melongena L., Keshtzar, Yalda, Chahboland and Passargad on fertility, number of days till fruit-set, germination rate and percentage and successful transplanting percentage, a survey was done in a completely randomized design. Tetraploid plants were derived from seed maceration/shoot tip treatment (0.5, 1 and 2 percent of colchicine). To ensure ploidy level, chromosome counting of root tips and flow-cytometry was done during the experiment. To quantify germination percentage and rate, 15 seeds of each cultivar in each ploidy level were placed in petri-dishes in three replications. The seeds of each ploidy form were sown in seedling trays and after seedling period, plugs were transplanted in field for evaluation of characteristics in different ploidy levels. Growth and development rate of plant in seedling stage observed since seeds were cultivated. As soon as hypocotyl appeared on the surface, they were counted. Then seedling emergence and rate were calculated. To test viability of pollen grains, they were stained using acetocarmen. In order to find best parental lines, 18 plants from each cultivar and in each ploidy level were cultivated in the greenhouse condition in three replications. Then all plants were crossed competley (direct and reciprocal). Di and tetraploid plants were tested to find out which one would be better as which parent. Number of days till fruit-set, characteristics of seed and seedling and growth rate in seedling stage were significantly (P≤5%) influenced by changes on levels of poloidy. Pollen grain staining with acetocarmine for evaluation of fertility percentage in pollen grains showed that with an increase in ploidy level, fertility may significantly increase (P≤5%). In an effort to triploid plant production, none of the crosses between di and tetraploid plant could bear fruit. With the overall results, despite slower growth, can be tetraploid plant, due to improved germination and seedling emergence, survival and reproductive capabilities, higher transplanting success in this category of plants, induced increase in the number of chromosomal bundles can be considered as a good way to create genetic variation and prepare parental lines with desirable traits for use in the breeding programs.

Construction site layout planning is one of the managerial aspects of the construction industry and has significant impacts on performance of the sites. Since in real site layout optimization, many objectives are involved, therefore multi-objective algorithms are needed. In this study, multi-objective version of two meta-heuristics, CBO and ECBO, are developed and their applicability and performance are checked on a case study. The quality of the results obtained, verify the ability of these algorithms in finding optimal pareto front on this problem. Another tool that is utilized in this study is data envelopment analysis (DEA) which by calculating the efficiency of optimal pareto front layouts, can help decision makers to select the final layout among the candidates. It should be mentioned that the DEA has previously been used in models with multiple inputs and outputs.

The whale optimization algorithm (WOA) is a recently developed swarm-based optimization algorithm inspired by the hunting behavior of humpback whales. This study attempts to enhance the original formulation of the WOA by hybridizing it with some concepts of the colliding bodies optimization (CBO) in order to improve solution accuracy, reliability and convergence speed. The new method, called WOA-CBO algorithm, is applied to construction site layout planning problem. To show the efficiency and performance of the WOA and WOA-CBO in construction site layout problems, three case studies are selected. First case is a discrete and equal area facility layout problem that every facility could assign to any location. Second case is an unequal area version of discrete facility layout problem with more constraints and the last case is a continuous model of construction site layouts. These cases are studied by WOA, CBO and WOA-CBO, and the results are compared with each other.

Offshore pipelines are usually constructed by the use of girth welds, while welds may naturally contain flaws. Currently, fracture assessment procedures such as BS 7910 are based on the stress-based methods and their responses for situations with large plastic strain is suspicious. DNV-OS-F101 with limited modifications proposes a strain-based procedure for such plastic loads. In this paper 3D nonlinear elastic-plastic finite element analyses using the ABAQUS software are performed in order to compare existing stress- and strain-based procedures beside newly strain-based method which is called CRES approach in order to improve the criteria used in current guidelines particularly at large plastic strains. It is concluded that although BS 7910 values are closer to finite element results than other methods in elastic region, but it is still conservative. In the area of large plastic strain, CRES method is very less conservative in both case of with and without internal pressure in comparison to others. The comparison of numerical simulation results with those available experimental data reveals a good agreement.

Due to the high-dimension of the sonar dataset, classification of them is a very complex task. Multi-Layer Perceptron Neural Network (MLP NN) is one of the most applicable tools in solving complicated problems as well as classifying between target and non-target in sonar applications. In this paper, a new kind of swarm-based metaheuristic search method, called Elephant Herding Optimization (EHO), is proposed for training the NN. The EHO method is inspired by the herding behavior of elephant group. In nature, the elephants belonging to different clans live together under the leadership of a matriarch, and the male elephants will leave their family group when they grow up. These two behaviors can be modelled into two following operators: clan updating operator and separating operator. The simulation results show that the new classifier performs better than the other benchmark algorithms and also original BBO in terms of avoidance trapping in local optima, classification accuracy, and convergence speed. This paper also implements the designed classifier on the FPGA substrate for testing the real-time application of the proposed method.

Castellated beams and composite action of beams are widely applicable methods to increase the capacity of the beams. Semi-rigid connections can also redistribute internal moments in order to attain a better distribution. Combination of these methods helps to optimize the cost of the beam. In this study, some meta-heuristic algorithms consisting of the particle swarm optimization, colliding bodies optimization, and enhanced colliding bodies optimization are used for optimization of semi-rigid jointed composite castellated beams. Profile section, cutting depth, cutting angle, holes spacing, number of filled end holes of the castellated beams and rigidity of connection are considered as the optimization variables. Constraints include the construction, moment, shear, deflection and vibration limitations. Effect of partial fixity and commercial cutting shape of a castellated beam for a practical range of beam spans and loading types are studied through three numerical examples. The efficiency of three meta-heuristic algorithms is compared.

Lavortement chez les vaches laitières se réfère généralement à la mort du fœtus entre les jours 47 à 265 de la grossesse. Étant donné que lavortement peut engendrer la réduction considérable des revenus et la perte de capital des producteurs, il est nécessaire de prendre des mesures de prévention et daccorder un budget approprié à cet effet. Dans la présente étude, 128 fœtus avortés provenant de 8 fermes laitières de la province de Qazvin en Iran ont été examinés au second semestre de l’an 2015. Les échantillons de fœtus testés comprenaient un mélange homogène des tissus du cerveau, des reins, de la rate, du foie et des poumons du fœtus avorté. Après lextraction du matériel génétique, des expériences PCR et RT-PCR ont été réalisées pour identifier BVDV, BHV-1, parasite de Neospora caninum et la bactérie de Leptospirose. Finalement, en effectuant le test de PCR, les échantillons de bandes bp380 pour les bactéries leptospires, bandes bp340 pour le parasite de Neospora caninum et la bande bp173 pour le virus BHV-1 ont été considérés comme positifs dans l'électrophorèse sur gel. En effectuant également le test RT-PCR, le résultat de la bande bp290 pour le virus BVDV était positif. À la fin, sur 128 fœtus avortés, 39 échantillons (30,47%) ont été infectés par Neospora caninum, 26 (20,31%) ont été infectés par le virus BVDV, 17 (13,28%) ont été infectés par le BHV- 1 et 18 échantillons (14,06%) ont été infectés par les bactéries de Leptospirose.

Vibrating particles system (VPS) is a new meta-heuristic algorithm based on the free vibration of freedom system’ single degree with viscous damping. In this algorithm, each agent gradually approach to its equilibrium position; new agents are generated according to current agents and a historically best position. Enhanced vibrating particles system (EVPS) employs a new alternative procedure to enhance the performance of the VPS algorithm. Two different truss structures are investigated to demonstrate the performance of the VPS and EVPS weight optimization of structures.

In this research work, in order to estimate the drying properties of eggplant and turnip in a combined microwave-convection dryer it was used artificial neural network method in order to estimate the Drying process was accomplished in three temperature levels (40, 55, and 70 °C), three inlet air velocity levels (0.5, 1.1 and 1.7 m/s) and three microwave power levels (270, 450 and 630 W) in a combined microwave-convection dryer that the three parameters were utilized as input in predicting the effective moisture diffusion coefficient and specific energy consumption in artificial neural network. A feed forward and cascade forward back propagation neural network with training functions of Levenberg - Marquardt (LM) and Bayesian Regulation (BR) for training of patterns. According to results, the highest value of the effective moisture diffusion coefficient for eggplant and turnip was obtained 3.39×10-9 and 3.05×10-9 m2/s, respectively. Results of ANN investigations showed that the optimum feed forward back propagation network with 3-20-20-2 topology and training function of Levenberg – Marquardt could predict the effective moisture diffusion coefficient and specific energy consumption with determination coefficients of 0.9821 and 0.9952 and mean square error of 0.00014 in various drying conditions of eggplant and turnip. Also the highest determination coefficients for prediction of drying rate and moisture ration obtained 0.9698 and 0.9988 with the value of mean square error of 0.0045 in cascade back propagation neural network with training algorithm of Levenberg – Marquardt.

Labor productivity is one the most important factors in achieving project success at different stages of a project. In this research a new method is presented to model labor productivity for different types of contractors based on system dynamic (SD) simulation. Using cause and effect feedback loops, a qualitative model is constructed. The relationships between different parameters are then determined by expert judgment and real data obtained from several real projects, and the quantitative model is built. The labor productivity is simulated by the proposed SD model considering all affecting factors. For higher accuracy, the model is examined on two types of contractors and two models are constructed. The total productivity of each contractor is obtained and the effect of different parameters on the labor productivity is investigated.