The Honeybee Search Algorithm: A Cooperative Coevolutionary Framework for 3D Reconstruction

2016 ◽  
pp. 241-272
Author(s):  
Gustavo Olague
Keyword(s):  
3D Reconstruction ◽  
Search Algorithm

scholarly journals Nature-Inspired Optimization Algorithms for the 3D Reconstruction of Porous Media

Algorithms ◽  
2020 ◽  
Vol 13 (3) ◽  
pp. 65
Author(s):  
George Papakostas ◽  
John Nolan ◽  
Athanasios Mitropoulos
Keyword(s):  
Porous Media ◽  
3D Reconstruction ◽  
Materials Science ◽  
Search Algorithm ◽  
Optimization Algorithms ◽  
Gravitational Search Algorithm ◽  
Data Representation ◽  
Statistical Properties ◽  
Original Material ◽  
Reconstruction Procedure

One of the most challenging problems that are still open in the field of materials science is the 3D reconstruction of porous media using information from a single 2D thin image of the original material. Such a reconstruction is only feasible subject to some important assumptions that need to be made as far as the statistical properties of the material are concerned. In this study, the aforementioned problem is investigated as an explicitly formulated optimization problem, with the phase of each porous material point being decided such that the resulting 3D material model shows the same statistical properties as its corresponding 2D version. Based on this problem formulation, herein for the first time, several traditional (genetic algorithms—GAs, particle swarm optimization—PSO, differential evolution—DE), as well as recently proposed (firefly algorithm—FA, artificial bee colony—ABC, gravitational search algorithm—GSA) nature-inspired optimization algorithms were applied to solve the 3D reconstruction problem. These algorithms utilized a newly proposed data representation scheme that decreased the number of unknowns searched by the optimization process. The advantages of addressing the 3D reconstruction of porous media through the application of a parallel heuristic optimization algorithm were clearly defined, while appropriate experiments demonstrating the greater performance of the GA algorithm in almost all the cases by a factor between 5%–84% (porosity accuracy) and 3%–15% (auto-correlation function accuracy) over the PSO, DE, FA, ABC, and GSA algorithms were undertaken. Moreover, this study revealed that statistical functions of a high order need to be incorporated into the reconstruction procedure to increase the reconstruction accuracy.

Detection, Averaging, and 3D Reconstruction of Biological Specimens on Hypercubes (Transputer-based) Computers

1990 ◽  
Vol 48 (1) ◽  
pp. 454-455
Author(s):  
Jose-Maria Carazo ◽  
I. Benavides ◽  
S. Marco ◽  
J.L. Carrascosa ◽  
E.L. Zapata
Keyword(s):  
3D Reconstruction ◽  
3D Structure ◽  
Three Dimensional ◽  
Software Tools ◽  
Mapping Method ◽  
Computer Architectures ◽  
Parallel Computer ◽  
Reconstruction Process ◽  
Computing Power ◽  
Order Of Magnitude

Obtaining the three-dimensional (3D) structure of negatively stained biological specimens at a resolution of, typically, 2 - 4 nm is becoming a relatively common practice in an increasing number of laboratories. A combination of new conceptual approaches, new software tools, and faster computers have made this situation possible. However, all these 3D reconstruction processes are quite computer intensive, and the middle term future is full of suggestions entailing an even greater need of computing power. Up to now all published 3D reconstructions in this field have been performed on conventional (sequential) computers, but it is a fact that new parallel computer architectures represent the potential of order-of-magnitude increases in computing power and should, therefore, be considered for their possible application in the most computing intensive tasks.We have studied both shared-memory-based computer architectures, like the BBN Butterfly, and local-memory-based architectures, mainly hypercubes implemented on transputers, where we have used the algorithmic mapping method proposed by Zapata el at. In this work we have developed the basic software tools needed to obtain a 3D reconstruction from non-crystalline specimens (“single particles”) using the so-called Random Conical Tilt Series Method. We start from a pair of images presenting the same field, first tilted (by ≃55°) and then untilted. It is then assumed that we can supply the system with the image of the particle we are looking for (ideally, a 2D average from a previous study) and with a matrix describing the geometrical relationships between the tilted and untilted fields (this step is now accomplished by interactively marking a few pairs of corresponding features in the two fields). From here on the 3D reconstruction process may be run automatically.

Structural Studies on the Eukaryotic Ribosome

1990 ◽  
Vol 48 (1) ◽  
pp. 256-257
Author(s):  
Adriana Verschoor ◽  
Ronald Milligan ◽  
Suman Srivastava ◽  
Joachim Frank
Keyword(s):  
Chick Embryo ◽  
3D Reconstruction ◽  
Single Particle ◽  
Mass Density ◽  
Particle Surface ◽  
Uranyl Acetate ◽  
Electron Microscopic ◽  
Eukaryotic Ribosome ◽  
Negative Stain ◽  
Reconstruction Methods

We have studied the eukaryotic ribosome from two vertebrate species (rabbit reticulocyte and chick embryo ribosomes) in several different electron microscopic preparations (Fig. 1a-d), and we have applied image processing methods to two of the types of images. Reticulocyte ribosomes were examined in both negative stain (0.5% uranyl acetate, in a double-carbon preparation) and frozen hydrated preparation as single-particle specimens. In addition, chick embryo ribosomes in tetrameric and crystalline assemblies in frozen hydrated preparation have been examined. 2D averaging, multivariate statistical analysis, and classification methods have been applied to the negatively stained single-particle micrographs and the frozen hydrated tetramer micrographs to obtain statistically well defined projection images of the ribosome (Fig. 2a,c). 3D reconstruction methods, the random conical reconstruction scheme and weighted back projection, were applied to the negative-stain data, and several closely related reconstructions were obtained. The principal 3D reconstruction (Fig. 2b), which has a resolution of 3.7 nm according to the differential phase residual criterion, can be compared to the images of individual ribosomes in a 2D tetramer average (Fig. 2c) at a similar resolution, and a good agreement of the general morphology and of many of the characteristic features is seen.Both data sets show the ribosome in roughly the same ’view’ or orientation, with respect to the adsorptive surface in the electron microscopic preparation, as judged by the agreement in both the projected form and the distribution of characteristic density features. The negative-stain reconstruction reveals details of the ribosome morphology; the 2D frozen-hydrated average provides projection information on the native mass-density distribution within the structure. The 40S subunit appears to have an elongate core of higher density, while the 60S subunit shows a more complex pattern of dense features, comprising a rather globular core, locally extending close to the particle surface.

Optimal broadcast scheduling method for VANETs: An adaptive discrete firefly approach

2020 ◽  
Vol 39 (6) ◽  
pp. 8125-8137
Author(s):  
Jackson J Christy ◽  
D Rekha ◽  
V Vijayakumar ◽  
Glaucio H.S. Carvalho
Keyword(s):  
Intelligent Transportation System ◽  
Search Algorithm ◽  
Mac Protocol ◽  
High Mobility ◽  
Optimal Solution ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Traffic Density ◽  
Scheduling Problem ◽  
Broadcast Scheduling

Vehicular Adhoc Networks (VANET) are thought-about as a mainstay in Intelligent Transportation System (ITS). For an efficient vehicular Adhoc network, broadcasting i.e. sharing a safety related message across all vehicles and infrastructure throughout the network is pivotal. Hence an efficient TDMA based MAC protocol for VANETs would serve the purpose of broadcast scheduling. At the same time, high mobility, influential traffic density, and an altering network topology makes it strenuous to form an efficient broadcast schedule. In this paper an evolutionary approach has been chosen to solve the broadcast scheduling problem in VANETs. The paper focusses on identifying an optimal solution with minimal TDMA frames and increased transmissions. These two parameters are the converging factor for the evolutionary algorithms employed. The proposed approach uses an Adaptive Discrete Firefly Algorithm (ADFA) for solving the Broadcast Scheduling Problem (BSP). The results are compared with traditional evolutionary approaches such as Genetic Algorithm and Cuckoo search algorithm. A mathematical analysis to find the probability of achieving a time slot is done using Markov Chain analysis.

Comparison of Meta-heuristic Algorithms on Benchmark Functions

2019 ◽  
Vol 2 (3) ◽  
pp. 508-517
Author(s):  
FerdaNur Arıcı ◽  
Ersin Kaya
Keyword(s):  
Heuristic Algorithms ◽  
Optimization Problems ◽  
Search Algorithm ◽  
Optimization Algorithms ◽  
Gravitational Search Algorithm ◽  
Differential Evolution Algorithm ◽  
Population Based ◽  
Time Interval ◽  
Bee Colony ◽  
Different Characteristics

Optimization is a process to search the most suitable solution for a problem within an acceptable time interval. The algorithms that solve the optimization problems are called as optimization algorithms. In the literature, there are many optimization algorithms with different characteristics. The optimization algorithms can exhibit different behaviors depending on the size, characteristics and complexity of the optimization problem. In this study, six well-known population based optimization algorithms (artificial algae algorithm - AAA, artificial bee colony algorithm - ABC, differential evolution algorithm - DE, genetic algorithm - GA, gravitational search algorithm - GSA and particle swarm optimization - PSO) were used. These six algorithms were performed on the CEC’17 test functions. According to the experimental results, the algorithms were compared and performances of the algorithms were evaluated.

An Improved Version of Algebraic Codebook Search Algorithm for an AMR-WB Speech Coder

Informatica ◽  
2017 ◽  
Vol 28 (2) ◽  
pp. 403-414 ◽  
Author(s):  
Ming-Che Yeh ◽  
Cheng-Yu Yeh ◽  
Shaw-Hwa Hwang
Keyword(s):  
Search Algorithm ◽  
Speech Coder

3D reconstruction and calculation of surface area and volume of bell pepper

2007 ◽  
Vol 3 (1) ◽  
pp. 89-113
Author(s):  
Zoltán Gillay ◽  
László Fenyvesi
Keyword(s):  
3D Reconstruction ◽  
Surface Area ◽  
Three Dimensional ◽  
Reference Method ◽  
Bell Pepper ◽  
Three Dimensional Model ◽  
Acceptable Error ◽  
Volume Calculation ◽  
Bell Peppers ◽  
Area And Volume

There was a method developed that generates the three-dimensional model of not axisymmetric produce, based on an arbitrary number of photos. The model can serve as a basis for calculating the surface area and the volume of produce. The efficiency of the reconstruction was tested on bell peppers and artificial shapes. In case of bell peppers 3-dimensional reconstruction was created from 4 images rotated in 45° angle intervals. The surface area and the volume were estimated on the basis of the reconstructed area. Furthermore, a new and simple reference method was devised to give precise results for the surface area of bell pepper. The results show that this 3D reconstruction-based surface area and volume calculation method is suitable to determine the surface area and volume of definite bell peppers with an acceptable error.

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