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Computation, Volume 7, Issue 1 (March 2019)

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Open AccessArticle EMG Feature Selection and Classification Using a Pbest-Guide Binary Particle Swarm Optimization
Computation 2019, 7(1), 12; https://doi.org/10.3390/computation7010012 (registering DOI)
Received: 24 January 2019 / Revised: 15 February 2019 / Accepted: 15 February 2019 / Published: 22 February 2019
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Abstract
Due to the increment in hand motion types, electromyography (EMG) features are increasingly required for accurate EMG signals classification. However, increasing in the number of EMG features not only degrades classification performance, but also increases the complexity of the classifier. Feature selection is [...] Read more.
Due to the increment in hand motion types, electromyography (EMG) features are increasingly required for accurate EMG signals classification. However, increasing in the number of EMG features not only degrades classification performance, but also increases the complexity of the classifier. Feature selection is an effective process for eliminating redundant and irrelevant features. In this paper, we propose a new personal best (Pbest) guide binary particle swarm optimization (PBPSO) to solve the feature selection problem for EMG signal classification. First, the discrete wavelet transform (DWT) decomposes the signal into multiresolution coefficients. The features are then extracted from each coefficient to form the feature vector. After which pbest-guide binary particle swarm optimization (PBPSO) is used to evaluate the most informative features from the original feature set. In order to measure the effectiveness of PBPSO, binary particle swarm optimization (BPSO), genetic algorithm (GA), modified binary tree growth algorithm (MBTGA), and binary differential evolution (BDE) were used for performance comparison. Our experimental results show the superiority of PBPSO over other methods, especially in feature reduction; where it can reduce more than 90% of features while keeping a very high classification accuracy. Hence, PBPSO is more appropriate for application in clinical and rehabilitation applications. Full article
(This article belongs to the Section Computational Engineering)
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Open AccessArticle On Parameter Estimation for Bandlimited Optical Intensity Channels
Computation 2019, 7(1), 11; https://doi.org/10.3390/computation7010011
Received: 11 January 2019 / Revised: 6 February 2019 / Accepted: 14 February 2019 / Published: 18 February 2019
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Abstract
Parameter estimation is of paramount importance in every digital receiver. This is not only true for radio, but also for optical links; otherwise, subsequent processing stages, like detector units or error correction schemes, could not be operated reliably. However, for a bandlimited optical [...] Read more.
Parameter estimation is of paramount importance in every digital receiver. This is not only true for radio, but also for optical links; otherwise, subsequent processing stages, like detector units or error correction schemes, could not be operated reliably. However, for a bandlimited optical intensity channel, the problem of parameter estimation is strongly related to non-negative pulse shapes satisfying also the Nyquist criterion to keep the detection process as simple as possible. To the best of the author’s knowledge, it is the first time that both topics—parameter estimation on the one hand and bandlimited intensity modulation on the other—are jointly investigated. Since symbol timing and signal amplitude are the parameters of interest in this case, the corresponding Cramer–Rao lower bounds are derived as the theoretical limit of the jitter variance generated by the related estimator algorithms. In this context, a maximum likelihood solution is developed for the recovery of both timing and amplitude. Since this approach requires a receiver matched filter destroying the Nyquist criterion of the non-negative pulse shape, we compare it to a flat receiver filter preserving the required orthogonality property. It turned out that the jitter performance of the matched filter method is close to the Cramer-Rao lower bound in the medium-to-low SNR range, but due to inter-symbol interference effects an error floor emerges at higher SNR values. The flat filter solution avoids this drawback, although the price to be paid is a larger noise level at the filter output, so that a somewhat increased jitter variance is observed. Full article
(This article belongs to the Special Issue Optical Wireless Communication Systems)
Open AccessArticle Probabilistic Fatigue Life Prediction of Dissimilar Material Weld Using Accelerated Life Method and Neural Network Approach
Computation 2019, 7(1), 10; https://doi.org/10.3390/computation7010010
Received: 27 December 2018 / Revised: 11 January 2019 / Accepted: 14 January 2019 / Published: 2 February 2019
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Abstract
Welding alloy 617 with other metals and alloys has been receiving significant attention in the last few years. It is considered to be the benchmark for the development of economical hybrid structures to be used in different engineering applications. The differences in the [...] Read more.
Welding alloy 617 with other metals and alloys has been receiving significant attention in the last few years. It is considered to be the benchmark for the development of economical hybrid structures to be used in different engineering applications. The differences in the physical and metallurgical properties of dissimilar materials to be welded usually result in weaker structures. Fatigue failure is one of the most common failure modes of dissimilar material welded structures. In this study, fatigue life prediction of dissimilar material weld was evaluated by the accelerated life method and artificial neural network approach (ANN). The accelerated life testing approach was evaluated for different distributions. Weibull distribution was the most appropriate distribution that fits the fatigue data very well. Acceleration of fatigue life test data was attained with 95% reliability for Weibull distribution. The probability plot verified that accelerating variables at each level were appropriate. Experimental test data and predicted fatigue life were in good agreement with each other. Two training algorithms, Bayesian regularization (BR) and Levenberg–Marquardt (LM), were employed for training ANN. The Bayesian regularization training algorithm exhibited a better performance than the Levenberg–Marquardt algorithm. The results confirmed that the assessment methods are effective for lifetime prediction of dissimilar material welded joints. Full article
(This article belongs to the Section Computational Engineering)
Open AccessArticle Dynamic Load Balancing Techniques for Particulate Flow Simulations
Received: 30 November 2018 / Revised: 18 January 2019 / Accepted: 20 January 2019 / Published: 23 January 2019
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Abstract
Parallel multiphysics simulations often suffer from load imbalances originating from the applied coupling of algorithms with spatially and temporally varying workloads. It is, thus, desirable to minimize these imbalances to reduce the time to solution and to better utilize the available hardware resources. [...] Read more.
Parallel multiphysics simulations often suffer from load imbalances originating from the applied coupling of algorithms with spatially and temporally varying workloads. It is, thus, desirable to minimize these imbalances to reduce the time to solution and to better utilize the available hardware resources. Taking particulate flows as an illustrating example application, we present and evaluate load balancing techniques that tackle this challenging task. This involves a load estimation step in which the currently generated workload is predicted. We describe in detail how such a workload estimator can be developed. In a second step, load distribution strategies like space-filling curves or graph partitioning are applied to dynamically distribute the load among the available processes. To compare and analyze their performance, we employ these techniques to a benchmark scenario and observe a reduction of the load imbalances by almost a factor of four. This results in a decrease of the overall runtime by 14% for space-filling curves. Full article
(This article belongs to the Section Computational Engineering)
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Open AccessArticle Numerical Simulation on Supercritical CO2 Fluid Dynamics in a Hollow Fiber Membrane Contactor
Received: 27 November 2018 / Revised: 28 December 2018 / Accepted: 10 January 2019 / Published: 15 January 2019
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Abstract
This research answers the following question: What is the fluid dynamic behavior of a supercritical fluid (SCF) inside a membrane module? At this time, there is very little or no reported information that can provide an answer to this question. The research studies [...] Read more.
This research answers the following question: What is the fluid dynamic behavior of a supercritical fluid (SCF) inside a membrane module? At this time, there is very little or no reported information that can provide an answer to this question. The research studies related to the themes of supercritical CO2 (SC-CO2), hollow fiber membrane contactors (HFMCs), and numerical simulations have mainly reported on 2D simulations, but in this work, 3D profiles are presented. Simulations were performed based on the experimental results and other simulations, using the geometry of a commercial module. The results were mainly based on the different operating conditions and geometric dimensions. A mesh study was performed to ensure the mesh non-dependence of the results presented here. It was observed that the velocity profile developed at 10 mm from the wall of the supercritical CO2 entrance pipe. A profile equilibrium around the fiber close to the entrance of the module was achieved in the experimental hollow fiber membrane contactor when compared to the case of the commercial hollow fiber membrane contactor. The results of this research provided a visualization of the boundary layer, which did not cover the entire fiber length. Finally, the results of this paper are interesting for technical applications and contribute to our understanding of the hydrodynamics of SCFs. Full article
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Open AccessArticle Optical Boundaries for LED-Based Indoor Positioning System
Received: 17 December 2018 / Revised: 5 January 2019 / Accepted: 9 January 2019 / Published: 14 January 2019
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Abstract
Overlap of footprints of light emitting diodes (LEDs) increases the positioning accuracy of wearable LED indoor positioning systems (IPS) but such an approach assumes that the footprint boundaries are defined. In this work, we develop a mathematical model for defining the footprint boundaries [...] Read more.
Overlap of footprints of light emitting diodes (LEDs) increases the positioning accuracy of wearable LED indoor positioning systems (IPS) but such an approach assumes that the footprint boundaries are defined. In this work, we develop a mathematical model for defining the footprint boundaries of an LED in terms of a threshold angle instead of the conventional half or full angle. To show the effect of the threshold angle, we compare how overlaps and receiver tilts affect the performance of an LED-based IPS when the optical boundary is defined at the threshold angle and at the full angle. Using experimental measurements, simulations, and theoretical analysis, the effect of the defined threshold angle is estimated. The results show that the positional time when using the newly defined threshold angle is 12 times shorter than the time when the full angle is used. When the effect of tilt is considered, the threshold angle time is 22 times shorter than the full angle positioning time. Regarding accuracy, it is shown in this work that a positioning error as low as 230 mm can be obtained. Consequently, while the IPS gives a very low positioning error, a defined threshold angle reduces delays in an overlap-based LED IPS. Full article
(This article belongs to the Special Issue Optical Wireless Communication Systems)
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Open AccessArticle Reduction Potential Predictions for Some 3-Aryl-Quinoxaline-2-Carbonitrile 1,4-Di-N-Oxide Derivatives with Known Anti-Tumor Properties
Received: 11 December 2018 / Revised: 24 December 2018 / Accepted: 9 January 2019 / Published: 10 January 2019
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Abstract
The ability for DFT: B3LYP calculations using the 6-31g and lanl2dz basis sets to predict the electrochemical properties of twenty (20) 3-aryl-quinoxaline-2-carbonitrile 1,4-di-N-oxide derivatives with varying degrees of cytotoxic activity in dimethylformamide (DMF) was investigated. There was a strong correlation for [...] Read more.
The ability for DFT: B3LYP calculations using the 6-31g and lanl2dz basis sets to predict the electrochemical properties of twenty (20) 3-aryl-quinoxaline-2-carbonitrile 1,4-di-N-oxide derivatives with varying degrees of cytotoxic activity in dimethylformamide (DMF) was investigated. There was a strong correlation for the first reduction and moderate-to-low correlation of the second reduction of the diazine ring between the computational and the experimental data, with the exception of the derivative containing the nitro functionality. The four (4) nitro group derivatives are clear outliers in the overall data sets and the derivative E4 is ill-behaved. The remaining three (3) derivatives containing the nitro groups had a strong correlation between the computational and experimental data; however, the computational data falls substantially outside of the expected range. Full article
(This article belongs to the Section Computational Chemistry)
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Open AccessEditorial Acknowledgement to Reviewers of Computation in 2018
Published: 10 January 2019
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Abstract
Rigorous peer-review is the corner-stone of high-quality academic publishing [...] Full article
Open AccessArticle Advanced Markov-Based Machine Learning Framework for Making Adaptive Trading System
Received: 14 November 2018 / Revised: 19 December 2018 / Accepted: 28 December 2018 / Published: 3 January 2019
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Abstract
Stock market prediction and trading has attracted the effort of many researchers in several scientific areas because it is a challenging task due to the high complexity of the market. More investors put their effort to the development of a systematic approach, i.e., [...] Read more.
Stock market prediction and trading has attracted the effort of many researchers in several scientific areas because it is a challenging task due to the high complexity of the market. More investors put their effort to the development of a systematic approach, i.e., the so called “Trading System (TS)” for stocks pricing and trend prediction. The introduction of the Trading On-Line (TOL) has significantly improved the overall number of daily transactions on the stock market with the consequent increasing of the market complexity and liquidity. One of the most main consequence of the TOL is the “automatic trading”, i.e., an ad-hoc algorithmic robot able to automatically analyze a lot of financial data with target to open/close several trading operations in such reduced time for increasing the profitability of the trading system. When the number of such automatic operations increase significantly, the trading approach is known as High Frequency Trading (HFT). In this context, recently, the usage of machine learning has improved the robustness of the trading systems including HFT sector. The authors propose an innovative approach based on usage of ad-hoc machine learning approach, starting from historical data analysis, is able to perform careful stock price prediction. The stock price prediction accuracy is further improved by using adaptive correction based on the hypothesis that stock price formation is regulated by Markov stochastic propriety. The validation results applied to such shares and financial instruments confirms the robustness and effectiveness of the proposed automatic trading algorithm. Full article
(This article belongs to the Section Computational Engineering)
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Open AccessArticle The Impact of Stochasticity and Its Control on a Model of the Inflammatory Response
Received: 23 October 2018 / Revised: 4 December 2018 / Accepted: 27 December 2018 / Published: 28 December 2018
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Abstract
The dysregulation of inflammation, normally a self-limited response that initiates healing, is a critical component of many diseases. Treatment of inflammatory disease is hampered by an incomplete understanding of the complexities underlying the inflammatory response, motivating the application of systems and computational biology [...] Read more.
The dysregulation of inflammation, normally a self-limited response that initiates healing, is a critical component of many diseases. Treatment of inflammatory disease is hampered by an incomplete understanding of the complexities underlying the inflammatory response, motivating the application of systems and computational biology techniques in an effort to decipher this complexity and ultimately improve therapy. Many mathematical models of inflammation are based on systems of deterministic equations that do not account for the biological noise inherent at multiple scales, and consequently the effect of such noise in regulating inflammatory responses has not been studied widely. In this work, noise was added to a deterministic system of the inflammatory response in order to account for biological stochasticity. Our results demonstrate that the inflammatory response is highly dependent on the balance between the concentration of the pathogen and the level of biological noise introduced to the inflammatory network. In cases where the pro- and anti-inflammatory arms of the response do not mount the appropriate defense to the inflammatory stimulus, inflammation transitions to a different state compared to cases in which pro- and anti-inflammatory agents are elaborated adequately and in a timely manner. In this regard, our results show that noise can be both beneficial and detrimental for the inflammatory endpoint. By evaluating the parametric sensitivity of noise characteristics, we suggest that efficiency of inflammatory responses can be controlled. Interestingly, the time period on which parametric intervention can be introduced efficiently in the inflammatory system can be also adjusted by controlling noise. These findings represent a novel understanding of inflammatory systems dynamics and the potential role of stochasticity thereon. Full article
(This article belongs to the Special Issue Computational Modeling in Inflammation and Regenerative Medicine)
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Open AccessArticle Thermal Behavior of a Building with Incorporated Phase Change Materials in the South and the North Wall
Received: 16 October 2018 / Revised: 10 December 2018 / Accepted: 18 December 2018 / Published: 21 December 2018
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Abstract
Energy consumption in the building sector is responsible for a very large amount of electricity consumption worldwide. The reduction of this consumption is a crucial issue in order to achieve sustainability. The objective of this work is to investigate the use of phase [...] Read more.
Energy consumption in the building sector is responsible for a very large amount of electricity consumption worldwide. The reduction of this consumption is a crucial issue in order to achieve sustainability. The objective of this work is to investigate the use of phase change materials (PCMs) in the building walls in order to reduce the heating and the cooling loads. The novelty of this work is based on the investigation of different scenarios about the position of the PCM layer in the south and the north walls. PCMs can improve the thermal performance and the thermal comfort of a building due to their ability to store large amounts of thermal energy in latent form and so to reduce the temperature fluctuations of the structural components, keeping them within the desired temperature levels. More specifically, this work presents and compares the heating loads, the cooling loads and the temperature distribution of a building in Athens (Greece), with and without PCMs in different positions in the south wall and in the north walls. The simulation is performed with the commercial software TRNSYS 17, using the TRNSYS component: type 1270 (PCM Wall). The results proved that the maximum energy savings per year were achieved by the combination of the insulation and the PCM layer in the north and south walls. More specifically, the reductions in the heating and the cooling loads were found to be 1.54% and 5.90%, respectively. Furthermore, the temperature distribution with the use of a PCM layer is the most acceptable, especially during the summer period. Full article
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Open AccessArticle Optical Wireless Communication Based Indoor Positioning Algorithms: Performance Optimisation and Mathematical Modelling
Received: 11 October 2018 / Revised: 10 December 2018 / Accepted: 18 December 2018 / Published: 20 December 2018
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Abstract
In this paper, the performance of the optimal beam radius indoor positioning (OBRIP) and two-receiver indoor positioning (TRIP) algorithms are analysed by varying system parameters in the presence of an indoor optical wireless channel modelled in line of sight configuration. From all the [...] Read more.
In this paper, the performance of the optimal beam radius indoor positioning (OBRIP) and two-receiver indoor positioning (TRIP) algorithms are analysed by varying system parameters in the presence of an indoor optical wireless channel modelled in line of sight configuration. From all the conducted simulations, the minimum average error value obtained for TRIP is 0.61 m against 0.81 m obtained for OBRIP for room dimensions of 10 m × 10 m × 3 m. In addition, for each simulated condition, TRIP, which uses two receivers, outperforms OBRIP and reduces position estimation error up to 30%. To get a better understanding of error in position estimation for different combinations of beam radius and separation between light emitting diodes, the 90th percentile error is determined using a cumulative distribution frequency (CDF) plot, which gives an error value of 0.94 m for TRIP as compared to 1.20 m obtained for OBRIP. Both algorithms also prove to be robust towards change in receiver tilting angle, thus providing flexibility in the selection of the parameters to adapt to any indoor environment. In addition, in this paper, a mathematical model based on the concept of raw moments is used to confirm the findings of the simulation results for the proposed algorithms. Using this mathematical model, closed-form expressions are derived for standard deviation of uniformly distributed points in an optical wireless communication based indoor positioning system with circular and rectangular beam shapes. Full article
(This article belongs to the Special Issue Optical Wireless Communication Systems)
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