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Computation, Volume 7, Issue 3 (September 2019)

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Open AccessArticle
Modeling and Analysis of Autonomous Agents’ Decisions in Learning to Cross a Cellular Automaton-Based Highway
Computation 2019, 7(3), 53; https://doi.org/10.3390/computation7030053 - 18 Sep 2019
Viewed by 224
Abstract
For a better understanding of the nature of complex systems modeling, computer simulations and the analysis of the resulting data are major tools which can be applied. In this paper, we study a statistical modeling problem of data coming from a simulation model [...] Read more.
For a better understanding of the nature of complex systems modeling, computer simulations and the analysis of the resulting data are major tools which can be applied. In this paper, we study a statistical modeling problem of data coming from a simulation model that investigates the correctness of autonomous agents’ decisions in learning to cross a cellular automaton-based highway. The goal is a better understanding of cognitive agents’ performance in learning to cross a cellular automaton-based highway with different traffic density. We investigate the effects of parameters’ values of the simulation model (e.g., knowledge base transfer, car creation probability, agents’ fear and desire to cross the highway) and their interactions on cognitive agents’ decisions (i.e., correct crossing decisions, incorrect crossing decisions, correct waiting decisions, and incorrect waiting decisions). We firstly utilize canonical correlation analysis (CCA) to see if all the considered parameters’ values and decision types are significantly statistically correlated, so that no considered dependent variables or independent variables (i.e., decision types and configuration parameters, respectively) can be omitted from the simulation model in potential future studies. After CCA, we then use the regression tree method to explore the effects of model configuration parameters’ values on the agents’ decisions. In particular, we focus on the discussion of the effects of the knowledge base transfer, which is a key factor in the investigation on how accumulated knowledge/information about the agents’ performance in one traffic environment affects the agents’ learning outcomes in another traffic environment. This factor affects the cognitive agents’ decision-making abilities in a major way in a new traffic environment where the cognitive agents start learning from existing accumulated knowledge/information about their performance in an environment with different traffic density. The obtained results provide us with a better understanding of how cognitive agents learn to cross the highway, i.e., how the knowledge base transfer as a factor affects the experimental outcomes. Furthermore, the proposed methodology can become useful in modeling and analyzing data coming from other computer simulation models and can provide an approach for better understanding a factor or treatment effect. Full article
(This article belongs to the Section Computational Engineering)
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Open AccessArticle
Chemical-Reactivity Properties, Drug Likeness, and Bioactivity Scores of Seragamides A–F Anticancer Marine Peptides: Conceptual Density Functional Theory Viewpoint
Computation 2019, 7(3), 52; https://doi.org/10.3390/computation7030052 - 14 Sep 2019
Viewed by 211
Abstract
A methodology based on concepts that arose from Density Functional Theory (CDFT) was chosen for the calculation of global and local reactivity descriptors of the Seragamide family of marine anticancer peptides. Determination of active sites for the molecules was achieved by resorting to [...] Read more.
A methodology based on concepts that arose from Density Functional Theory (CDFT) was chosen for the calculation of global and local reactivity descriptors of the Seragamide family of marine anticancer peptides. Determination of active sites for the molecules was achieved by resorting to some descriptors within Molecular Electron Density Theory (MEDT) such as Fukui functions. The pKas of the six studied peptides were established using a proposed relationship between this property and calculated chemical hardness. The drug likenesses and bioactivity properties of the peptides considered in this study were obtained by resorting to a homology model by comparison with the bioactivity of related molecules in their interaction with different receptors. With the object of analyzing the concept of drug repurposing, a study of potential AGE-inhibition abilities of Seragamides peptides was pursued by comparison with well-known drugs that are already available as pharmaceuticals. Full article
(This article belongs to the Special Issue New Advances in Density Functional Theory and Its Application)
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Open AccessArticle
Computing Spatiotemporal Accessibility to Urban Opportunities: A Reliable Space-Time Prism Approach in Uncertain Urban Networks
Computation 2019, 7(3), 51; https://doi.org/10.3390/computation7030051 - 10 Sep 2019
Viewed by 242
Abstract
Space-time prism (STP) is a comprehensive and powerful model for computing accessibility to urban opportunities. Despite other types of accessibility measures, STP models capture spatial and temporal dimensions in a unified framework. Classical STPs assume that travel time in street networks is a [...] Read more.
Space-time prism (STP) is a comprehensive and powerful model for computing accessibility to urban opportunities. Despite other types of accessibility measures, STP models capture spatial and temporal dimensions in a unified framework. Classical STPs assume that travel time in street networks is a deterministic and fixed variable. However, this assumption is in contradiction with the uncertain nature of travel time taking place due to fluctuations and traffic congestion. In addition, travel time in street networks mostly follows non-normal probability distributions which are not modeled in the structure of classical STPs. Neglecting travel time uncertainty and disregarding different types of probability distributions cause unrealistic accessibility values in STP-based metrics. In this way, this paper proposes a spatiotemporal accessibility model by extending classical STPs to non-normal stochastic urban networks and blending this modified STP with the attractiveness of urban opportunities. The elaborated model was applied on the city of Isfahan to assess the accessibility of its traffic analysis zones (TAZs) to Kowsar discount retail markets. A significant difference was found between the results of accessibility values in normally and non-normally distributed networks. In addition, the results show that the northern TAZs had larger accessibility level compared to the southern ones. Full article
(This article belongs to the Special Issue Transport Modelling for Smart Cities)
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Open AccessArticle
Molecular Dynamics of Water Embedded Carbon Nanocones: Surface Waves Observation
Computation 2019, 7(3), 50; https://doi.org/10.3390/computation7030050 - 10 Sep 2019
Viewed by 272
Abstract
We employed molecular dynamics simulations on the water solvation of conically shaped carbon nanoparticles. We explored the hydrophobic behaviour of the nanoparticles and investigated microscopically the cavitation of water in a conical confinement with different angles. We performed additional molecular dynamics simulations in [...] Read more.
We employed molecular dynamics simulations on the water solvation of conically shaped carbon nanoparticles. We explored the hydrophobic behaviour of the nanoparticles and investigated microscopically the cavitation of water in a conical confinement with different angles. We performed additional molecular dynamics simulations in which the carbon structures do not interact with water as if they were in vacuum. We detected a waving on the surface of the cones that resembles the shape agitations of artificial water channels and biological porins. The surface waves were induced by the pentagonal carbon rings (in an otherwise hexagonal network of carbon rings) concentrated near the apex of the cones. The waves were affected by the curvature gradients on the surface. They were almost undetected for the case of an armchair nanotube. Understanding such nanoscale phenomena is the key to better designed molecular models for membrane systems and nanodevices for energy applications and separation. Full article
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Open AccessArticle
Enhanced Feature Subset Selection Using Niche Based Bat Algorithm
Computation 2019, 7(3), 49; https://doi.org/10.3390/computation7030049 - 06 Sep 2019
Viewed by 366
Abstract
Redundant and irrelevant features disturb the accuracy of the classifier. In order to avoid redundancy and irrelevancy problems, feature selection techniques are used. Finding the most relevant feature subset that can enhance the accuracy rate of the classifier is one of the most [...] Read more.
Redundant and irrelevant features disturb the accuracy of the classifier. In order to avoid redundancy and irrelevancy problems, feature selection techniques are used. Finding the most relevant feature subset that can enhance the accuracy rate of the classifier is one of the most challenging parts. This paper presents a new solution to finding relevant feature subsets by the niche based bat algorithm (NBBA). It is compared with existing state of the art approaches, including evolutionary based approaches. The multi-objective bat algorithm (MOBA) selected 8, 16, and 248 features with 93.33%, 93.54%, and 78.33% accuracy on ionosphere, sonar, and Madelon datasets, respectively. The multi-objective genetic algorithm (MOGA) selected 10, 17, and 256 features with 91.28%, 88.70%, and 75.16% accuracy on same datasets, respectively. Finally, the multi-objective particle swarm optimization (MOPSO) selected 9, 21, and 312 with 89.52%, 91.93%, and 76% accuracy on the above datasets, respectively. In comparison, NBBA selected 6, 19, and 178 features with 93.33%, 95.16%, and 80.16% accuracy on the above datasets, respectively. The niche multi-objective genetic algorithm selected 8, 15, and 196 features with 93.33%, 91.93%, and 79.16 % accuracy on the above datasets, respectively. Finally, the niche multi-objective particle swarm optimization selected 9, 19, and 213 features with 91.42%, 91.93%, and 76.5% accuracy on the above datasets, respectively. Hence, results show that MOBA outperformed MOGA and MOPSO, and NBBA outperformed the niche multi-objective genetic algorithm and the niche multi-objective particle swarm optimization. Full article
(This article belongs to the Special Issue Machine Learning for Computational Science and Engineering)
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Open AccessArticle
Colebrook’s Flow Friction Explicit Approximations Based on Fixed-Point Iterative Cycles and Symbolic Regression
Computation 2019, 7(3), 48; https://doi.org/10.3390/computation7030048 - 03 Sep 2019
Viewed by 269
Abstract
The logarithmic Colebrook flow friction equation is implicitly given in respect to an unknown flow friction factor. Traditionally, an explicit approximation of the Colebrook equation requires evaluation of computationally demanding transcendental functions, such as logarithmic, exponential, non-integer power, Lambert W and Wright Ω [...] Read more.
The logarithmic Colebrook flow friction equation is implicitly given in respect to an unknown flow friction factor. Traditionally, an explicit approximation of the Colebrook equation requires evaluation of computationally demanding transcendental functions, such as logarithmic, exponential, non-integer power, Lambert W and Wright Ω functions. Conversely, we herein present several computationally cheap explicit approximations of the Colebrook equation that require only one logarithmic function in the initial stage, whilst for the remaining iterations the cheap Padé approximant of the first order is used instead. Moreover, symbolic regression was used for the development of a novel starting point, which significantly reduces the error of internal iterations compared with the fixed value staring point. Despite the starting point using a simple rational function, it reduces the relative error of the approximation with one internal cycle from 1.81% to 0.156% (i.e., by a factor of 11.6), whereas the relative error of the approximation with two internal cycles is reduced from 0.317% to 0.0259% (i.e., by a factor of 12.24). This error analysis uses a sample with 2 million quasi-Monte Carlo points and the Sobol sequence. Full article
(This article belongs to the Section Computational Engineering)
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Open AccessArticle
Configuration and Registration of Multi-Camera Spectral Image Database of Icon Paintings
Computation 2019, 7(3), 47; https://doi.org/10.3390/computation7030047 - 29 Aug 2019
Viewed by 508
Abstract
At the cost of added complexity and time, hyperspectral imaging provides a more accurate measure of the scene’s irradiance compared to an RGB camera. Several camera designs with more than three channels have been proposed to improve the accuracy. The accuracy is often [...] Read more.
At the cost of added complexity and time, hyperspectral imaging provides a more accurate measure of the scene’s irradiance compared to an RGB camera. Several camera designs with more than three channels have been proposed to improve the accuracy. The accuracy is often evaluated based on the estimation quality of the spectral data. Currently, such evaluations are carried out with either simulated data or color charts to relax the spatial registration requirement between the images. To overcome this limitation, this article presents an accurately registered image database of six icon paintings captured with five cameras with different number of channels, ranging from three (RGB) to more than a hundred (hyperspectral camera). Icons are challenging topics because they have complex surfaces that reflect light specularly with a high dynamic range. Two contributions are proposed to tackle this challenge. First, an imaging configuration is carefully arranged to control the specular reflection, confine the dynamic range, and provide a consistent signal-to-noise ratio for all the camera channels. Second, a multi-camera, feature-based registration method is proposed with an iterative outlier removal phase that improves the convergence and the accuracy of the process. The method was tested against three other approaches with different features or registration models. Full article
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Open AccessArticle
Modeling of Multivalent Ligand-Receptor Binding Measured by kinITC
Computation 2019, 7(3), 46; https://doi.org/10.3390/computation7030046 - 28 Aug 2019
Viewed by 289
Abstract
In addition to the conventional Isothermal Titration Calorimetry (ITC), kinetic ITC (kinITC) not only gains thermodynamic information, but also kinetic data from a biochemical binding process. Moreover, kinITC gives insights into reactions consisting of two separate kinetic steps, such as protein folding or [...] Read more.
In addition to the conventional Isothermal Titration Calorimetry (ITC), kinetic ITC (kinITC) not only gains thermodynamic information, but also kinetic data from a biochemical binding process. Moreover, kinITC gives insights into reactions consisting of two separate kinetic steps, such as protein folding or sequential binding processes. The ITC method alone cannot deliver kinetic parameters, especially not for multivalent bindings. This paper describes how to solve the problem using kinITC and an invariant subspace projection. The algorithm is tested for multivalent systems with different valencies. Full article
(This article belongs to the Section Computational Chemistry)
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Open AccessArticle
Numerical Simulation Using Finite-Difference Schemes with Continuous Symmetries for Processes of Gas Flow in Porous Media
Computation 2019, 7(3), 45; https://doi.org/10.3390/computation7030045 - 24 Aug 2019
Viewed by 347
Abstract
This article presents the applications of continuous symmetry groups to the computational fluid dynamics simulation of gas flow in porous media. The family of equations for one-phase flow in porous media, such as equations of gas flow with the Klinkenberg effect, is considered. [...] Read more.
This article presents the applications of continuous symmetry groups to the computational fluid dynamics simulation of gas flow in porous media. The family of equations for one-phase flow in porous media, such as equations of gas flow with the Klinkenberg effect, is considered. This consideration has been made in terms of difference scheme constructions with the preservation of continuous symmetries, which are presented in original parabolic differential equations. A new method of numerical solution generation using continuous symmetry groups has been developed for the equation of gas flow in porous media. Four classes of invariant difference schemes have been found by using known group classifications of parabolic differential equations with partial derivatives. Invariance of necessary conditions for stability has been shown for the difference schemes from the presented classes. Comparison with the classical approach for seeking numerical solutions for a particular case from the presented classes has shown that the calculation speed is greater by several orders than for the classical approach. Analysis of the accuracy for the presented method of numerical solution generation on the basis of continuous symmetries shows that the accuracy of generated numerical solutions depends on the accuracy of initial solutions for generations. Full article
(This article belongs to the Section Computational Engineering)
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Open AccessArticle
Bio-Inspired Deep-CNN Pipeline for Skin Cancer Early Diagnosis
Computation 2019, 7(3), 44; https://doi.org/10.3390/computation7030044 - 22 Aug 2019
Cited by 1 | Viewed by 420
Abstract
Skin cancer is the most common type of cancer, as also among the riskiest in the medical oncology field. Skin cancer is more common in people who work or practice outdoor sports and those that expose themselves to the sun. It may also [...] Read more.
Skin cancer is the most common type of cancer, as also among the riskiest in the medical oncology field. Skin cancer is more common in people who work or practice outdoor sports and those that expose themselves to the sun. It may also develop years after radiographic therapy or exposure to substances that cause cancer (e.g., arsenic ingestion). Numerous tumors can affect the skin, which is the largest organ in our body and is made up of three layers: the epidermis (superficial layer), the dermis (middle layer) and the subcutaneous tissue (deep layer). The epidermis is formed by different types of cells: melanocytes, which have the task of producing melanin (a pigment that protects against the damaging effects of sunlight), and the more numerous keratinocytes. The keratinocytes of the deepest layer are called basal cells and can give rise to basal cell carcinomas. We are interested in types of skin cancer that originate from melanocytes, i.e., the so-called melanomas, because it is the most aggressive. The dermatologist, during a complete visit, evaluates the personal and family history of the patient and carries out an accurate visual examination of the skin, thanks to the use of epi-luminescence (or dermoscopy), a special technique for enlarging and illuminating the skin. This paper mentions one of the most widely used diagnostic methods due to its simplicity and validity—the ABCDE method (Asymmetry, edge irregularity, Color Variegation, Diameter, Evolution). This methodology, based on “visual” investigation by the dermatologist and/or oncologist, has the advantage of not being invasive and quite easy to perform. This approach is affected by the opinion of who (physicians) applies it. For this reason, certain diagnosis of cancer is made, however, only with a biopsy, a procedure during which a portion of tissue is taken and then analyzed under a microscope. Obviously, this is particularly invasive for the patient. The authors of this article have analyzed the development of a method that obtains with good accuracy the early diagnosis of skin neoplasms using non-invasive, but at the same time, robust methodologies. To this end, the authors propose the adoption of a deep learning pipeline based on morphological analysis of the skin lesion. The results obtained and compared with previous approaches confirm the good performance of the proposed pipeline. Full article
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Open AccessArticle
Search for Global Maxima in Multimodal Functions by Applying Numerical Optimization Algorithms: A Comparison between Golden Section and Simulated Annealing
Computation 2019, 7(3), 43; https://doi.org/10.3390/computation7030043 - 22 Aug 2019
Viewed by 572
Abstract
In the field of engineering when a situation is not resolved analytically, efforts are made to develop methods that approximate a possible solution. These efforts have originated the numerical methods known at present, which allow formulating mathematical problems that can be solved using [...] Read more.
In the field of engineering when a situation is not resolved analytically, efforts are made to develop methods that approximate a possible solution. These efforts have originated the numerical methods known at present, which allow formulating mathematical problems that can be solved using logical and arithmetic operations. This paper presents a comparison between the numerical optimization algorithms golden section search and simulated annealing, which are tested in four different scenarios. These scenarios are functions implemented with a feedforward neural network, which emulate a partial shading behavior in photovoltaic modules with local and global maxima. The presence of the local maxima makes it difficult to track the maximum power point, necessary to obtain the highest possible performance of the photovoltaic module. The programming of the algorithms was performed in C language. The results demonstrate the effectiveness of the algorithms to find global maxima. However, the golden section search method showed a better performance in terms of percentage of error, computation time and number of iterations, except in test scenario number three, where a better percentage of error was obtained with the simulated annealing algorithm for a computational temperature of 1000. Full article
(This article belongs to the Section Computational Engineering)
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Open AccessReview
Recent Progress towards Chemically-Specific Coarse-Grained Simulation Models with Consistent Dynamical Properties
Computation 2019, 7(3), 42; https://doi.org/10.3390/computation7030042 - 20 Aug 2019
Viewed by 386
Abstract
Coarse-grained (CG) models can provide computationally efficient and conceptually simple characterizations of soft matter systems. While generic models probe the underlying physics governing an entire family of free-energy landscapes, bottom-up CG models are systematically constructed from a higher-resolution model to retain a high [...] Read more.
Coarse-grained (CG) models can provide computationally efficient and conceptually simple characterizations of soft matter systems. While generic models probe the underlying physics governing an entire family of free-energy landscapes, bottom-up CG models are systematically constructed from a higher-resolution model to retain a high level of chemical specificity. The removal of degrees of freedom from the system modifies the relationship between the relative time scales of distinct dynamical processes through both a loss of friction and a “smoothing” of the free-energy landscape. While these effects typically result in faster dynamics, decreasing the computational expense of the model, they also obscure the connection to the true dynamics of the system. The lack of consistent dynamics is a serious limitation for CG models, which not only prevents quantitatively accurate predictions of dynamical observables but can also lead to qualitatively incorrect descriptions of the characteristic dynamical processes. With many methods available for optimizing the structural and thermodynamic properties of chemically-specific CG models, recent years have seen a stark increase in investigations addressing the accurate description of dynamical properties generated from CG simulations. In this review, we present an overview of these efforts, ranging from bottom-up parameterizations of generalized Langevin equations to refinements of the CG force field based on a Markov state modeling framework. We aim to make connections between seemingly disparate approaches, while laying out some of the major challenges as well as potential directions for future efforts. Full article
(This article belongs to the Section Computational Chemistry)
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Open AccessArticle
A Modification of the Fast Inverse Square Root Algorithm
Computation 2019, 7(3), 41; https://doi.org/10.3390/computation7030041 - 18 Aug 2019
Viewed by 378
Abstract
We present a new algorithm for the approximate evaluation of the inverse square root for single-precision floating-point numbers. This is a modification of the famous fast inverse square root code. We use the same “magic constant” to compute the seed solution, but then, [...] Read more.
We present a new algorithm for the approximate evaluation of the inverse square root for single-precision floating-point numbers. This is a modification of the famous fast inverse square root code. We use the same “magic constant” to compute the seed solution, but then, we apply Newton–Raphson corrections with modified coefficients. As compared to the original fast inverse square root code, the new algorithm is two-times more accurate in the case of one Newton–Raphson correction and almost seven-times more accurate in the case of two corrections. We discuss relative errors within our analytical approach and perform numerical tests of our algorithm for all numbers of the type float. Full article
(This article belongs to the Section Computational Engineering)
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Open AccessArticle
Design and Implementation of a Microcontroller Based Active Controller for the Synchronization of the Petrzela Chaotic System
Computation 2019, 7(3), 40; https://doi.org/10.3390/computation7030040 - 17 Aug 2019
Viewed by 412
Abstract
This paper presents an active control design for the synchronization of two identical Petrzela chaotic systems (Petrzela, J.; Gotthans, T. New chaotic dynamical system with a conic-shaped equilibrium located on the plane structure. Applied Sciences. 2017, 7, 976) on master-slave configuration. For the [...] Read more.
This paper presents an active control design for the synchronization of two identical Petrzela chaotic systems (Petrzela, J.; Gotthans, T. New chaotic dynamical system with a conic-shaped equilibrium located on the plane structure. Applied Sciences. 2017, 7, 976) on master-slave configuration. For the active control, the parameters of both systems are assumed to be a priori known, the control law by means of the dynamic of the error synchronization is designed to guarantee the convergence to zero of error states and the synchronization process is verified by numerical simulation. By taking advantage of the execution and implementation facilities of microcontroller based chaotic systems in digital devices, the active controller is implemented in a 32 bits ARM microcontroller. The experimental results were obtained by using the fourth order Runge-Kutta numerical method to integrate the differential equations of the controller, where the results were measured with a digital oscilloscope. Full article
(This article belongs to the Section Computational Engineering)
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Open AccessArticle
From Complex System Analysis to Pattern Recognition: Experimental Assessment of an Unsupervised Feature Extraction Method Based on the Relevance Index Metrics
Computation 2019, 7(3), 39; https://doi.org/10.3390/computation7030039 - 09 Aug 2019
Viewed by 485
Abstract
The so-called Relevance Index (RI) metrics are a set of recently-introduced indicators based on information theory principles that can be used to analyze complex systems by detecting the main interacting structures within them. Such structures can be described as subsets of the variables [...] Read more.
The so-called Relevance Index (RI) metrics are a set of recently-introduced indicators based on information theory principles that can be used to analyze complex systems by detecting the main interacting structures within them. Such structures can be described as subsets of the variables which describe the system status that are strongly statistically correlated with one another and mostly independent of the rest of the system. The goal of the work described in this paper is to apply the same principles to pattern recognition and check whether the RI metrics can also identify, in a high-dimensional feature space, attribute subsets from which it is possible to build new features which can be effectively used for classification. Preliminary results indicating that this is possible have been obtained using the RI metrics in a supervised way, i.e., by separately applying such metrics to homogeneous datasets comprising data instances which all belong to the same class, and iterating the procedure over all possible classes taken into consideration. In this work, we checked whether this would also be possible in a totally unsupervised way, i.e., by considering all data available at the same time, independently of the class to which they belong, under the hypothesis that the peculiarities of the variable sets that the RI metrics can identify correspond to the peculiarities by which data belonging to a certain class are distinguishable from data belonging to different classes. The results we obtained in experiments made with some publicly available real-world datasets show that, especially when coupled to tree-based classifiers, the performance of an RI metrics-based unsupervised feature extraction method can be comparable to or better than other classical supervised or unsupervised feature selection or extraction methods. Full article
(This article belongs to the Special Issue Machine Learning for Computational Science and Engineering)
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Open AccessArticle
Numerical Simulation of the Phase Transition Control in a Cylindrical Sample Made of Ferromagnetic Shape Memory Alloy
Computation 2019, 7(3), 38; https://doi.org/10.3390/computation7030038 - 29 Jul 2019
Viewed by 427
Abstract
The paper considers ferromagnetic alloys, which exhibit the shape memory effect during phase transition from the high-temperature cubic phase (austenite) to the low-temperature tetragonal phase (martensite) in the ferromagnetic state. In these alloys, significant macroscopic strains are generated during the direct temperature phase [...] Read more.
The paper considers ferromagnetic alloys, which exhibit the shape memory effect during phase transition from the high-temperature cubic phase (austenite) to the low-temperature tetragonal phase (martensite) in the ferromagnetic state. In these alloys, significant macroscopic strains are generated during the direct temperature phase transition from the austenitic to the martensitic state, provided that the process proceeds under the action of the applied mechanical stresses. The critical phase transition temperatures in such alloys depend not only on the stress fields, but also on the magnetic field. By changing the magnetic field, it is possible to control the process of phase transition. In this work, within the framework of the finite deformation theory, we develop a model that allows us to describe the process of the control of the direct (austenite-martensite) and reverse (martensite-austenite) phase transitions in ferromagnetic shape memory polycrystalline materials under the action of external force, thermal, and magnetic fields with the aid of the magnetic field. In view of the fact that the magnetic field affects the material deformation, which, in turn, changes the magnetic field, we formulated and solved a coupled boundary value problem. As an example, we considered the problem of a shift of the outer surface of a long hollow cylinder made of ferromagnetic alloy. The numerical implementation of the problem was based on the finite element method using the step-by-step loading procedure. Complete recovery of the strains accumulated during the direct phase transition and reverting of the axially-displaced outer surface of the cylinder to its original position occurred both on heating of the sample to the temperatures of the reverse phase transition and at a constant temperature, when the magnetic field previously applied in the martensitic state was removed. Full article
(This article belongs to the Section Computational Engineering)
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Open AccessArticle
Visualization and Experiential Learning of Mathematics for Data Analytics
Computation 2019, 7(3), 37; https://doi.org/10.3390/computation7030037 - 23 Jul 2019
Viewed by 514
Abstract
The information and communications technology (ICT) industry workforce is now required to deal with ’Big Data’, and there is a need to fill the computational skill shortage in data analytics. The integrated skills of combining computer and mathematics capabilities is much sought after [...] Read more.
The information and communications technology (ICT) industry workforce is now required to deal with ’Big Data’, and there is a need to fill the computational skill shortage in data analytics. The integrated skills of combining computer and mathematics capabilities is much sought after by every industry embarking on digital transformation. Studies conducted internationally and by the Australian Industry Group show the requirements for improving computational skills in the workplace. This research takes a positive step to address this issue by introducing visualization and experiential learning in the ICT curriculum in order to uplift mathematics skills required for data analytics. We present the use of such innovative methods adopted in a higher education setting. The results and positive impact achieved through this study are presented. Full article
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Open AccessReview
A Review on Computational Modeling Tools for MOF-Based Mixed Matrix Membranes
Computation 2019, 7(3), 36; https://doi.org/10.3390/computation7030036 - 18 Jul 2019
Viewed by 599
Abstract
Computational modeling of membrane materials is a rapidly growing field to investigate the properties of membrane materials beyond the limits of experimental techniques and to complement the experimental membrane studies by providing insights at the atomic-level. In this study, we first reviewed the [...] Read more.
Computational modeling of membrane materials is a rapidly growing field to investigate the properties of membrane materials beyond the limits of experimental techniques and to complement the experimental membrane studies by providing insights at the atomic-level. In this study, we first reviewed the fundamental approaches employed to describe the gas permeability/selectivity trade-off of polymer membranes and then addressed the great promise of mixed matrix membranes (MMMs) to overcome this trade-off. We then reviewed the current approaches for predicting the gas permeation through MMMs and specifically focused on MMMs composed of metal organic frameworks (MOFs). Computational tools such as atomically-detailed molecular simulations that can predict the gas separation performances of MOF-based MMMs prior to experimental investigation have been reviewed and the new computational methods that can provide information about the compatibility between the MOF and the polymer of the MMM have been discussed. We finally addressed the opportunities and challenges of using computational studies to analyze the barriers that must be overcome to advance the application of MOF-based membranes. Full article
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Open AccessArticle
Underwater Optical Wireless Communications with Chromatic Dispersion and Time Jitter
Computation 2019, 7(3), 35; https://doi.org/10.3390/computation7030035 - 11 Jul 2019
Viewed by 507
Abstract
The obsolete communication systems used in the underwater environment necessitates the development and use of modern telecommunications technologies. One such technology is the optical wireless communications, which can provide very high data rates, almost infinite bandwidth and very high transmission speed for real [...] Read more.
The obsolete communication systems used in the underwater environment necessitates the development and use of modern telecommunications technologies. One such technology is the optical wireless communications, which can provide very high data rates, almost infinite bandwidth and very high transmission speed for real time fast and secure underwater links. However, the composition and the optical density of seawater hinder the communication between transmitter and receiver, while many significant effects strongly mitigate the underwater optical wireless communication (UOWC) systems’ performance. In this work, the influences of chromatic dispersion and time jitter are investigated. Chromatic dispersion causes the temporal broadening or narrowing of the pulse, while time jitter complicates the detection process at the receiver. Thus, the broadening of the optical pulse due to chromatic dispersion is studied and the influence of the initial chirp is examined. Moreover, the effect of the time jitter is also taken into consideration and for the first time, to the best of our knowledge, a mathematical expression for the probability of fade is extracted, taking into account the influence of both of the above-mentioned effects for a UOWC system. Finally, the appropriate numerical results are presented. Full article
(This article belongs to the Special Issue Optical Wireless Communication Systems)
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Open AccessArticle
Serial DF Relayed FSO Links over Mixture Gamma Turbulence Channels and Nonzero Boresight Spatial Jitter
Computation 2019, 7(3), 34; https://doi.org/10.3390/computation7030034 - 05 Jul 2019
Viewed by 636
Abstract
Over the past few years, terrestrial free space optical (FSO) communication systems have demonstrated increasing research and commercial interest. However, due the signal’s propagation path, the operation of FSO links depends strongly on atmospheric conditions and related phenomena. One such significant phenomenon is [...] Read more.
Over the past few years, terrestrial free space optical (FSO) communication systems have demonstrated increasing research and commercial interest. However, due the signal’s propagation path, the operation of FSO links depends strongly on atmospheric conditions and related phenomena. One such significant phenomenon is the scintillation caused by atmospheric turbulence effects; in order to address the significant performance degradation that this causes, several statistical models have been proposed. Here, turbulence-induced fading of the received optical signal is investigated through the recently presented mixture Gamma distribution, which accurately describes the irradiance fluctuations at the receiver’s input of the FSO link. Additionally, at the same time, it significantly reduces the mathematical complexity of the expressions used for the description of composite channels with turbulence along with nonzero boresight pointing error-induced fading. In order to counterbalance the performance mitigation due to these effects, serial decode-and-forward relays are employed, and the performance of the system is estimated through derived mathematical expressions. Full article
(This article belongs to the Special Issue Optical Wireless Communication Systems)
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Open AccessArticle
Transdermal Optical Wireless Links with Multiple Receivers in the Presence of Skin-Induced Attenuation and Pointing Errors
Computation 2019, 7(3), 33; https://doi.org/10.3390/computation7030033 - 28 Jun 2019
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Abstract
The last few years, the scientific field of optical wireless communications (OWC) has witnessed tremendous progress, as reflected in the continuous emergence of new successful high data rate services and variable sophisticated applications. One such development of vital research importance and interest is [...] Read more.
The last few years, the scientific field of optical wireless communications (OWC) has witnessed tremendous progress, as reflected in the continuous emergence of new successful high data rate services and variable sophisticated applications. One such development of vital research importance and interest is the employment of high speed, robust, and energy-effective transdermal optical wireless (TOW) links for telemetry with implantable medical devices (IMDs) that also have made considerable progress lately for a variety of medical applications, mainly including neural recording and prostheses. However, the outage performance of such TOW links is significantly degraded due to the strong attenuation that affects the propagating information-bearing optical signal through the skin, along with random misalignments between transmitter and receiver terminals, commonly known as pointing error effect. In order to anticipate this, in this work we introduce a SIMO TOW reception diversity system that employs either OOK or more power-effective L-PPM schemes. Taking into account the joint impact of skin-induced attenuation and non-zero boresight pointing errors, modeled through the suitable Beckmann distribution, novel closed-form mathematical expressions for the average BER of the total TOW system are derived. Thus, the possibility of enhancing the TOW availability by using reception diversity configurations along with the appropriate modulation format is investigated. Finally, the corresponding numerical results are presented using the new derived theoretical outcomes. Full article
(This article belongs to the Special Issue Optical Wireless Communication Systems)
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