Collection of Nanoscience and Nanotechnology

The collection is a repository of open access articles with a wide-ranging coverage, consolidating original research activities at the forefront of Nanoscience and Nanotechnology to provide a major reference source of comprehensive fundamental and applied knowledge in all disciplines of science, engineering and medicine related to Nanotechnology. It compasses analytical, experimental and numerical works to make substantial advances in these fields through enhancing the fundamental understanding of physics, chemistry, biology and technology of nanomaterials and devices.

DOCUMENTS25
VIEWS890
SCORE5

SCORE PERCENTILE100

Data imprecision under λ-geometry model: Range searching problem
M. Davoodi, A. Mohades

Scientia Iranica (2013). Vol. 20

Abstract
Because of constraints in exact modeling, measuring and computing, it is inevitable that algorithms that solve real world problems have to avoid errors. Hence, proposing models to handle error, and designing algorithms that work well in practice, are challenging fields. In this paper, we introduce a model called the λ-geometry model to handle a dynamic form of imprecision, which allows the precision to change monotonically in the input data of geometric algorithms. λ-geometry is a generalization of region-based models and provides the output of problems as functions, with respect to the level of precision. This type of output helps to design exact algorithms and is also useful in decision making processes. Furthermore, we study the problem of orthogonal range searching in one and two dimensional space under the model of λ-geometry, and propose efficient algorithms to solve it.
Abstract
Because of constraints in exact modeling, measuring and computing, it is inevitable that algorithms that solve real world problems have to avoid errors. Hence, proposing models [...]
- 11
- read
ERP success prediction: An artificial neural network approach
S. Rouhani, A. Ravasan

Scientia Iranica (2013). Vol. 20

Abstract
The Enterprise Resource Planning system (ERP) has been pointed out as a new information systems paradigm. However, achieving a proper level of ERP success relies on a variety of factors that are related to an organization or project environment. In this paper, the idea of predicting ERP post-implementation success based on organizational profiles has been discussed. As with the need to create the expectations of organizations of ERP, an expert system was developed by exploiting the Artificial Neural Network (ANN) method to articulate the relationships between some organizational factors and ERP success. The expert system role is in preparation to obtain data from the new enterprises that wish to implement ERP, and to predict the probable system success level. To this end, factors of organizational profiles are recognized and an ANN model is developed. Then, they are validated with 171 surveyed data obtained from Middle East-located enterprises that experienced ERP. The trained expert system predicts, with an average correlation coefficient of 0.744, which is respectively high, and supports the idea of dependency of ERP success on organizational profiles. Besides, a total correct classification rate of 0.685 indicates good prediction power, which can help firms predict ERP success before system implementation.
Abstract
The Enterprise Resource Planning system (ERP) has been pointed out as a new information systems paradigm. However, achieving a proper level of ERP success relies on a variety [...]
- 38
- read
Finding the optimum location in a one-median network problem with correlated demands using simulated annealing
M. Bashiri, M. Bakhtiarifar

Scientia Iranica (2013). Vol. 20

Abstract
The one median location problem with stochastic demands can be solved as a deterministic problem by considering the mean of weights as demands. There are also some other approaches in consideration of this problem. However, it is better to find the probability for each node that shows the chance of the node being in the optimal location, especially when demands are correlated to each other. With this approach, alternative answers with their optimality probability can be found. In small networks with a few nodes, it is not so difficult to solve the problem, because a multivariate normal probability for each node should be calculated. But, when the number of nodes increases, not only do the number of probability calculations increase, but also, the computation time for each multivariate normal distribution grows exponentially. In this paper, a meta-heuristic algorithm, based on modified Simulated Annealing (SA), with consideration of a short term memory module is proposed to find the optimality probability more efficiently. The algorithm was performed on some sample networks with correlated demands.
Abstract
The one median location problem with stochastic demands can be solved as a deterministic problem by considering the mean of weights as demands. There are also some other approaches [...]
- 16
- read
The effects of machine breakdown on hull structure production process
M. Ozkok

Scientia Iranica (2013). Vol. 20

Abstract
In the production environment, there are many disruptions, such as machine breakdown, rush orders, and so on. Under these circumstances, the shipyards have to meet customer demand. If this is not done, the shipyard may face customer loss, since they cannot meet the deadline. So, it is very important to understand the effects of machine breakdown on system throughput. In this study, the hull production system of a shipyard situated in Turkey has been considered. In the first step of the study, the structure of the double bottom block, which is produced in the shipyard production system, and the workstations, which constitute the production system, were identified. Secondly, the simulation model of the production system was created using simulation software. By creating some machine breakdowns for various work stations in the production system, the effects of breakdown on system throughput have been investigated. As a result of the study, the critical rates of machine breakdown, which have affected system throughput, have been determined. The main contribution of the study is to allow production engineers to take measures against machine breakdowns in advance, so that target throughput can be reached.
Abstract
In the production environment, there are many disruptions, such as machine breakdown, rush orders, and so on. Under these circumstances, the shipyards have to meet customer [...]
- 17
- read
Bayesian estimation of seismic hazards in Iran
A. Yazdani, M. Kowsari

Scientia Iranica (2013). Vol. 20

Abstract
Seismic hazard assessment is a basic tool for rational planning and designing in areas of different seismic activity. The Bayesian probability estimation was applied in this study to assess seismic hazard. The estimation procedure provides a posterior probability distribution that integrates prior estimates based on the knowledge of the process, and the likelihood of occurrence based on historical data. The Bayesian approach was applied to calculate the probability that a certain cut-off magnitude would be exceeded at certain time intervals in different regions of Iran. The results for the cut-off magnitude of 6.5 indicate that the highest probability of seismic hazard exists in the Alborz, Kopeh-Dagh, Bandar-Abas, Kerman, and Zagros regions. The seismic hazard is lowest for the Esfahan–Sirgan region, the Arabian Platform, the Persian Gulf, and Kavir in Central Iran. The comparison between the Bayesian results and the seismotectonic models of Iran reveals that it is possible to partition the spatially distributed epicenters of earthquake events into different regions. In general, these regional divisions agree with previously proposed seismotectonic provinces of Iran.
Abstract
Seismic hazard assessment is a basic tool for rational planning and designing in areas of different seismic activity. The Bayesian probability estimation was applied in this [...]
- 8
- read
Multi-pass turning process parameter optimization using teaching–learning-based optimization algorithm
R. Rao, V. Kalyankar

Scientia Iranica (2013). Vol. 20

Abstract
The primary objective in multi-pass turning operations is to produce products with low cost and high quality, with a lower number of cuts. Parameter optimization plays an important role in achieving this goal. Process parameter optimization in a multi-pass turning operation usually involves the optimal selection of cutting speed, feed rate, depth of cut and number of passes. In this work, the parameter optimization of a multi-pass turning operation is carried out using a recently developed advanced optimization algorithm, named, the teaching–learning-based optimization algorithm. Two different examples are considered that have been attempted previously by various researchers using different optimization techniques, such as simulated annealing, the genetic algorithm, the ant colony algorithm, and particle swarm optimization, etc. The first example is a multi-objective problem and the second example is a single objective multi-constrained problem with 20 constraints. The teaching–learning-based optimization algorithm has proved its effectiveness over other algorithms.
Abstract
The primary objective in multi-pass turning operations is to produce products with low cost and high quality, with a lower number of cuts. Parameter optimization plays an [...]
- 29
- read
Grey stochastic multi-criteria decision-making approach based on expected probability degree
J. Wang, H. Zhang, S. Ren

Scientia Iranica (2013). Vol. 20

Abstract
After definition of the discrete grey stochastic variable and its expected value, the expected probability degree is defined. For multi-criteria decision-making problems, in which the criteria weights are incompletely certain and the criteria values of alternatives are in the form of grey stochastic variables, a grey stochastic multi-criteria decision-making approach is proposed. In this method, the evaluation value of each alternative under each criterion can be transformed to comprise the expected probability degree judgment matrix, based on which, a non-linear programming model can be enacted. In the end, the genetic algorithm is used to solve the model to attain the criteria weights, and the ranking of alternatives can be produced consequently. The feasibility and validity of this approach are illustrated by an example.
Abstract
After definition of the discrete grey stochastic variable and its expected value, the expected probability degree is defined. For multi-criteria decision-making problems, [...]
- 5
- read
Numerical simulation for predicting concentration profiles of cohesive sediments in surf zone
M. Nikmanesh, N. Talebbeydokhti

Scientia Iranica (2013). Vol. 20

Abstract
A hybrid numerical model is introduced for simulation of cohesive sediments concentration profiles in a surf zone. For this purpose, wave height reduction must be considered, due to muddy beds and wave breaking. Models, such as Sanford and Maa’s erosion model, Krone’s sedimentation model, Tajima’s wave breaking model and the visco-elastic–plastic rheological model, are used to investigate the interaction of wave and bed and to predict the concentration profile. A splitting algorithm has been used to split the three-dimensional advection–diffusion equation into a horizontal, two-dimensional equation, and a vertical, one-dimensional equation, due to different length scales. The one-dimensional equation is discretized over a non uniform grid, and, then solved implicitly using the QUICKEST scheme (third order in time and space). The two-dimensional equation is divided into two parts (advection and diffusion) and each part is separately solved at different time steps. A suitable mesh, regarding space and time intervals, is chosen for considering the stability of the present model. The computational domain extends from the shoreline to the deepwater zone. Finally, the results are analyzed and compared with experimental and field data and other models. Good agreement has been obtained with the data and other numerical models.
Abstract
A hybrid numerical model is introduced for simulation of cohesive sediments concentration profiles in a surf zone. For this purpose, wave height reduction must be considered, [...]
- 8
- read
An improved teaching-learning-based optimization algorithm for solving unconstrained optimization problems
R. Rao, V. Patel

Scientia Iranica (2013). Vol. 20

Abstract
Teaching–Learning-Based Optimization (TLBO) algorithms simulate the teaching–learning phenomenon of a classroom to solve multi-dimensional, linear and nonlinear problems with appreciable efficiency. In this paper, the basic TLBO algorithm is improved to enhance its exploration and exploitation capacities by introducing the concept of number of teachers, adaptive teaching factor, tutorial training and self motivated learning. Performance of the improved TLBO algorithm is assessed by implementing it on a range of standard unconstrained benchmark functions having different characteristics. The results of optimization obtained using the improved TLBO algorithm are validated by comparing them with those obtained using the basic TLBO and other optimization algorithms available in the literature.
Abstract
Teaching–Learning-Based Optimization (TLBO) algorithms simulate the teaching–learning phenomenon of a classroom to solve multi-dimensional, linear and nonlinear [...]
- 30
- read
Calculation of pressure drop inside condensing vertical pipes in new inlet pressures using a new modified three-fluid model
H. Saffari, N. Dalir

Scientia Iranica (2013). Vol. 20

Abstract
Using the new modified three-fluid model, the effect of variation of inlet pressure on predictions of pressure drop in the downward condensing annular flow of steam inside vertical pipes is studied. To achieve this, using the new modified three-fluid model and Stevanovic et al.’s correlation for the steam–liquid film interfacial friction coefficient, pressure drop is calculated in two new inlet pressures (i.e., 1.5 and 2.5 (MPa)), for which there is no available experimental data of pressure drop. The pressure drop predictions of the new modified three-fluid model and those of the Stevanovic et al.’s correlation are compared.
Abstract
Using the new modified three-fluid model, the effect of variation of inlet pressure on predictions of pressure drop in the downward condensing annular flow of steam inside [...]
- 28
- read
Design optimization of reinforced concrete 3D structures considering frequency constraints via a charged system search
A. Kaveh, A. Behnam

Scientia Iranica (2013). Vol. 20

Abstract
This paper presents an optimal design of three dimensional multi-story reinforced concrete structures using recently developed meta-heuristic algorithms, namely; the charged system search and the enhanced charged system search. The design is based on the ACI 318-05 code and loadings are based on ASCE7-05. Analysis of the structures is performed by the standard stiffness method. All members are subjected to biaxial moments and axial loads. Pre-determined sections are assumed for beams and columns, and the corresponding interaction curves are utilized to check whether the selected section for each member is acceptable. The objective function is taken as the weight of the structure, and constraints consist of the slenderness of compression members, the maximum allowable drift of the structure and the natural frequency of the structure. It should be mentioned that second order effects are also considered and that the end moments of the columns are magnified when needed. First, a 7-story frame with 3 spans is considered and optimized. Then, a sensitivity analysis is performed by optimal design of nine frames having 3 stories and 2 spans. In each story, different span lengths and loading conditions are assumed, and the results are compared.
Abstract
This paper presents an optimal design of three dimensional multi-story reinforced concrete structures using recently developed meta-heuristic algorithms, namely; the charged [...]
- 17
- read
Mild Brønsted basic ionic liquids catalyzed three component synthesis of pyrazolo[1,2-a][1,2,4]triazole-1, 3-dione and 2-amino-3-cyano-5,10-dioxo-4-phenyl-5, 10-dihydro-4H-benzo[g]chromene derivatives
H. Shaterian, M. Kangani

Scientia Iranica (2013). Vol. 2

Abstract
Pyrazolo[1,2-a][1,2,4]triazole-1,3-dione derivatives were synthesized via a three component reaction of arylaldehydes, 4-phenylurazole and malononitrile in the presence of a catalytic amount of 2-hydroxyethylammonium formate and 2-hydroxyethylammonium acetate as effective mild basic ionic liquids, without using any additional co-catalyst, under solvent-free conditions at room temperature in good yields. Ionic liquids as catalysts were recovered and reused. In addition, the preparation of 2-amino-3-cyano-5,10-dioxo-4-phenyl-5,10-dihydro-4H-benzo[g]chromene derivatives from the reaction of arylaldehydes, malononitrile and 2-hydroxy-1,4-dihydronaphthalene-1,4-dione under solvent-free conditions at ambient temperature in the presence of mentioned catalysts is reported.
Abstract
Pyrazolo[1,2-a][1,2,4]triazole-1,3-dione derivatives were synthesized via a three component reaction of arylaldehydes, 4-phenylurazole and malononitrile in the presence of [...]
- 58
- read
Nanocarriers, nanovaccines, and nanobacteria as nanobiotechnological concerns in modern vaccines
P. Gill

Scientia Iranica (2013). Vol. 20

Abstract
This review briefly describes the concerns of nanobiotechnology in the design and development of novel vaccines using the most known nanocarriers, including nature-made nanocarriers (such as bacterial spores, virus-like particles, exosomes, and bacteriophages), man-made nanocarriers (such as Proteosomes, liposomes, virosomes, SuperFluids, and nanobeads), and their applications in therapeutic and protective immunization, as well as their advantages and disadvantages. Here, we focus on the development of nano-based vaccines as “nanovaccines” for inducing immune systems, and the foreseeable promises and problems when compared with existing vaccines. Also, we review a potential nano-hazard for vaccines, so-called nanobacterial contamination.
Abstract
This review briefly describes the concerns of nanobiotechnology in the design and development of novel vaccines using the most known nanocarriers, including nature-made nanocarriers [...]
- 28
- read
Estimation of the mean of a socially undesirable characteristic
Z. Hussain, J. Shabbir

Scientia Iranica (2013). Vol. 20

Abstract
This paper focuses on presenting a generalization of the scrambled response models of Hussain and Shabbir [Hussain, Z. and Shabbir, J. “On estimation of mean of a sensitive quantitative variable”, InterStat, (#006), (2007)] and Gjestvang and Singh [Gjestvang, C.R. and Singh, S. “An improved randomized response model: estimation of mean”, Journal of Applied Statistics, 36(12), pp. 1361–1367 (2009)]. The suggested generalization is helpful in procuring honest data on socially undesirable characteristics. The suggested estimator is found to be unconditionally more efficient in terms of variablity. From a privacy point of view, comparison of the proposed class of models is made using the privacy protection measure by Zaizai et al. [Zaizai, Y., Jingu, W. and Junfeng, L. “An efficiency and protection based comparison among the quantitative randomized response strategies”, Communications in Statistics-Theory and Methods, 38, pp. 400–408 (2009)]. Unlike many scrambled response models, the proposed class of models is free from the need of known parameters of scrambling variables. The relative numerical efficiency of the proposed model is simulated for some fixed values of the parameters. The practical application of the proposed model is also studied through a small scale survey.
Abstract
This paper focuses on presenting a generalization of the scrambled response models of Hussain and Shabbir [Hussain, Z. and Shabbir, J. “On estimation of mean of a sensitive [...]
- 15
- read
Spatial correlation aware protocols for efficient data aggregation of moving object in wireless sensor networks
S. Pourpeighambar, M. Sabaei

Scientia Iranica (2013). Vol. 20

Abstract
In Wireless Sensor Networks (WSNs), power consumption of sensor nodes is the main constraint. Emerging in-network aggregation techniques are increasingly being sought after to address this key challenge and to save precious energy. One application of WSNs is in data gathering of moving objects. In order to achieve complete coverage, this type of application requires spatially dense sensor deployment, which, under close observation, exhibits important spatial correlation characteristics. The Rate Distortion (RD) theory is a data aggregation technique that can take advantage of this type of correlation with the help of a cluster based communication model. Due to object movement, the Rate-Distortion based aggregation incurs high computation overhead. This paper first introduces an introduction for the rate-distortion based moving object data aggregation model. Then, to overcome the high computation overhead, several low overhead protocols are proposed based on this model, namely, a static cluster-based protocol that uses static clustering, a dynamic cluster-based protocol that uses dynamic clustering, and a hybrid protocol which takes advantage of the other two protocols. Simulation results show that with the hybrid method, it is possible to save more than 36% of the nodes’ energy when compared to the other approaches.
Abstract
In Wireless Sensor Networks (WSNs), power consumption of sensor nodes is the main constraint. Emerging in-network aggregation techniques are increasingly being sought after [...]
- 9
- read
Determination of optimum injection flow rate to achieve maximum micro bubble drag reduction in ships; an experimental approach
H. Sayyaadi, M. Nematollahi

Scientia Iranica (2013). Vol. 20

Abstract
Reduction in ship resistance, in order to decrease fuel consumption and also achieve higher speeds, has been the topic of major research over the last three decades. One of the most attractive ideas in this field is micro bubble drag reduction, which attempts to obtain optimum injection flow rate based on ship specifications. The model test results of a 70 cm catamaran model was used to quantify the effect of air injection rate on drag reduction, and to estimate a simple formulation for calculating an efficient injection rate by considering the main parameters of the ship, such as: length, width and speed. The test results show that excessive air injection decreases the drag reduction effect, while suitable injection reduces total drag by about 5%–8%.
Abstract
Reduction in ship resistance, in order to decrease fuel consumption and also achieve higher speeds, has been the topic of major research over the last three decades. One of [...]
- 28
- read
Investigation of joist floor diaphragm flexibility on inelastic behavior of steel braced structures
M. Hadianfard, S. Sedaghat

Scientia Iranica (2013). Vol. 20

Abstract
The flexibility of floor diaphragms has a significant influence on the behavior of building structures. Commonly, in analyzing structures, floor diaphragms are considered rigid. This assumption distributes lateral loads between the resistant elements according to their rigidities, and decreases the degree of freedom that creates easier analysis. However, in steel structures with braced frames and long span floors, diaphragms usually behave flexibly. The seismic responses of such structures vary to the expected response of typical rigid floor structures. Ignoring the effects of diaphragm flexibility can lead to non-economic or unsafe structural design. In this paper, the nonlinear responses of braced steel buildings with flexible concrete block-joist floor diaphragms are investigated under both static lateral load and dynamic ground motion, and they are compared with the responses of structures with the assumption of rigid diaphragms. This study demonstrates that span ratio is an important parameter in the flexibility of floor diaphragms, and if this ratio exceeds three, the variation of results between the two assumptions of flexible and rigid diaphragms may not be ignored. In addition, results show that diaphragm flexibility changes the seismic response of the structures and linear analysis is not sufficient to explain this behavior.
Abstract
The flexibility of floor diaphragms has a significant influence on the behavior of building structures. Commonly, in analyzing structures, floor diaphragms are considered [...]
- 114
- read
A novel technique for mitigating motion artifacts in 3D brain imaging systems
U. Bhowmik, R. Adhami

Scientia Iranica (2013). Vol. 20

Abstract
Over the past several years,there have been substantial improvements in the area of three-dimensional (3D) cone-beam Computed Tomography (CT) imaging systems. Nevertheless, more improvement is needed to detect and mitigate motion artifacts in the clinical follow-up of neurological patients with multiple sclerosis, tumors, and stroke, etc., in which failure to detect motion artifacts often leads to misdiagnosis of disease. In this paper, we propose a marker-based innovative approach to detect and mitigate motion artifacts in 3D cone-beam brain CT systems without using any external motion tracking sensors. Motion is detected by comparing the motion-free ideal marker projections and the corresponding measured marker projections. Once motion is detected, motion parameters (six degrees-of-freedom of motion) are estimated using a numerical optimization technique. Artifacts, caused by motions, are mitigated in the back projection stage of the 3D reconstruction process by correcting the position of every reconstruction voxel according to the estimated motion parameters. We refer to this algorithm as the MB_FDK (Marker-based Feldkemp–Davis–Kress) algorithm. MB_FDK has been evaluated on a modified 3D Shepp–Logan phantom with a range of simulated motion. Simulation results demonstrate a quantitative and qualitative validation of motion detection and artifact mitigation techniques.
Abstract
Over the past several years,there have been substantial improvements in the area of three-dimensional (3D) cone-beam Computed Tomography (CT) imaging systems. Nevertheless, [...]
- 35
- read
A new method for the oxidation of 1, 4-dihydropyridine derivatives by guanidinium nitrate in the presence of silica sulfuric acid under mild, heterogeneous and metal-free conditions
M. Nikoorazm

Scientia Iranica (2013). Vol. 20

Abstract
In this paper, a new and convenient method is introduced for the oxidation of a variety of Hantzsch 1, 4-dihydropyridine derivatives to their corresponding pyridine compounds using guanidinium nitrate and silica sulfuric acid. The reactions were carried out in dichloromethane at room temperature and the products were isolated at high to excellent yields.
Abstract
In this paper, a new and convenient method is introduced for the oxidation of a variety of Hantzsch 1, 4-dihydropyridine derivatives to their corresponding pyridine compounds [...]
- 231
- read
Peer evaluation of multi-attribute analysis techniques: Case of a light rail transit network choice
H. Poorzahedy, A. Rezaei

Scientia Iranica (2013). Vol. 20

Abstract
This paper attempts to present a method for differentiating between multi-attribute decision procedures and to identify some competent procedures for major decision problems, where a matrix of alternative-measure of effectiveness and a vector of weights for the latter are available. In this respect, several known multi-attribute analysis procedures are chosen, and the same procedures are exploited to evaluate themselves, based on some evaluation criteria. This is done from an engineering viewpoint and in the context of a transportation problem, using a real case light rail transit network choice problem for the City of Mashhad, and the results are presented. Two concepts have been proposed in this respect and used in this evaluation; peer evaluation and information evaluation, which are investigated in this paper. In the evaluation of five multi-attribute decision procedures, based on nine criteria, and with the help of these procedures themselves in the context of the case under study, the results revealed that these procedures found Electre, Linear Assignment, Simple Additive Weighting, TOPSIS, and Minkowski Distance better than others, in the same order as given. This is backed by a wide range of sensitivity analyses. Nevertheless, despite specific conclusions made regarding the better decision procedures among those evaluated, this paper finds its contribution mainly in the approach to such evaluations and choices.
Abstract
This paper attempts to present a method for differentiating between multi-attribute decision procedures and to identify some competent procedures for major decision problems, [...]
- 5
- read

show more

information

About this publication

How to submit

Open access

Contact

Data imprecision under λ-geometry model: Range searching problem

ERP success prediction: An artificial neural network approach

Finding the optimum location in a one-median network problem with correlated demands using simulated annealing

The effects of machine breakdown on hull structure production process

Bayesian estimation of seismic hazards in Iran

Multi-pass turning process parameter optimization using teaching–learning-based optimization algorithm

Grey stochastic multi-criteria decision-making approach based on expected probability degree

Numerical simulation for predicting concentration profiles of cohesive sediments in surf zone

An improved teaching-learning-based optimization algorithm for solving unconstrained optimization problems

Calculation of pressure drop inside condensing vertical pipes in new inlet pressures using a new modified three-fluid model

Design optimization of reinforced concrete 3D structures considering frequency constraints via a charged system search

Mild Brønsted basic ionic liquids catalyzed three component synthesis of pyrazolo[1,2-a][1,2,4]triazole-1, 3-dione and 2-amino-3-cyano-5,10-dioxo-4-phenyl-5, 10-dihydro-4H-benzo[g]chromene derivatives

Nanocarriers, nanovaccines, and nanobacteria as nanobiotechnological concerns in modern vaccines

Estimation of the mean of a socially undesirable characteristic

Spatial correlation aware protocols for efficient data aggregation of moving object in wireless sensor networks

Determination of optimum injection flow rate to achieve maximum micro bubble drag reduction in ships; an experimental approach

Investigation of joist floor diaphragm flexibility on inelastic behavior of steel braced structures

A novel technique for mitigating motion artifacts in 3D brain imaging systems

A new method for the oxidation of 1, 4-dihydropyridine derivatives by guanidinium nitrate in the presence of silica sulfuric acid under mild, heterogeneous and metal-free conditions

Peer evaluation of multi-attribute analysis techniques: Case of a light rail transit network choice

information

Sign up at Scipedia and complete your profile

Click on "CREATE A DOCUMENT" in your profile page

Upload your manuscript in LaTeX or Word, or create it from scratch with our online editor

Click on "SUBMIT FOR PUBLICATION" at the manuscript page, and select your preferred journal or collection

Click on "SUBMIT FOR PUBLICATION" at the manuscript page, select your preferred collection and complete the submission form

The editorial board will ensure that the publishing requirements are adhered to, before your paper is published

Categories