Adaptive Network-Based Fuzzy Inference Systems Coupled with Genetic Algorithms for Predicting Soil Permeability Coefficient

This paper extends hybrid-type optimization models of genetic algorithm adaptive network-based fuzzy inference system (GA-ANFIS) for predicting the soil permeability coefficient (SPC) of different types of soil. In these models, GA optimizes parameters of a subtractive clustering technique that controls the structure of the ANFIS model’s fuzzy rule base. Simultaneously, a hybrid leaning algorithm is employed in the ANFIS, as a trained fuzzy inference system (FIS), which optimally determines the parameter sets of the examined FISs in ANFIS. Using an updated large database of SPCs consisting of 338 fine-grained, 178 mixed and 94 granular soil samples, GA-ANFIS framework constructs different models of predicting the permeability coefficient of respectively fine-grained, mixed and granular soils. A fuzzy C-mean technique has been used to cluster the entire data samples of each type of soil and divide them uniformly into training and testing data sets. Different prediction models of SPC have been trained and tested for each of the three soil types, and the appropriate models have been selected. The selected models have been compared with ANN and modified-by-GA empirical prediction models. Results show that the constructed GA-ANFIS models outperform the other models in terms of the prediction accuracy and the generalization capability.     

Characterisation of Signal Modality: Exploiting Signal Nonlinearity in Machine Learning and Signal Processing

A novel method for online tracking of the changes in the nonlinearity within both real-domain and complex–valued signals is introduced. This is achieved by a collaborative adaptive signal processing approach based on a hybrid filter. By tracking the dynamics of the adaptive mixing parameter within the employed hybrid filtering architecture, we show that it is possible to quantify the degree of nonlinearity within both real- and complex-valued data. Implementations for tracking nonlinearity in general and then more specifically sparsity are illustrated on both benchmark and real world data. It is also shown that by combining the information obtained from hybrid filters of different natures it is possible to use this method to gain a more complete understanding of the nature of the nonlinearity within a signal. This also paves the way for building multidimensional feature spaces and their application in data/information fusion.     

Finite element modeling of low-velocity impact on laminated composite plates and cylindrical shells

In this study, composite laminates and shell structures subjected to low-velocity impact are investigated by numerical analysis using ABAQUS finite element code. In order to model the impact phenomena by commercial finite element codes, various procedures are available. Accurate modeling requires the appropriate selection of element type, solution method, impactor modeling method, meshing pattern and contact modeling. In this investigation, by considering several case studies with various conditions, validity of the existed modeling processes is examined. In each case, by comparing the results of various methods with the related available experimental test results in existing literature, the best procedure is proposed which can serve as benchmark method in low-velocity impact modeling of composite structures for future investigations.     

Preparation of electrospun nanofibers based on wheat gluten containing azathioprine for biomedical application

In this study, wheat gluten fibers loaded by the azathioprine were fabricated and their physicochemical properties were studied. The nanofibers were characterized by using the scanning electron microscopy (SEM), Fourier transformed-infrared spectroscopy, X-ray diffractometry, thermogravimetric, and differential thermal analysis. The SEM images showed that the addition of polyvinyl alcohol decreased the fibers’ diameters. The diameters of 77.14?±?14.11?nm were obtained for the wheat gluten–polyvinyl alcohol loaded drug fibers. In addition, the cell viability evaluation conducted by the MTT assay proved no cytotoxicity of the prepared nonofibers at concentrations up to 4?mg/mL to human umbilical vein endothelial cell.     

On the scheduling with past-sequence-dependent setup times and learning effects on a single machine

This paper deals with a single-machine scheduling problem with setup time and learning effects. The setup times are proportional to the length of the already processed jobs, i.e., the setup times are job-independent and past-sequence-dependent, and the learning effects are job-independent and position-dependent. The objective is to minimize the sum of earliness penalties subject to no tardy jobs. Wang, Wang, Gao, and Huang [Int J Adv Manuf Technol 48: 739–746, 2010] showed that an optimal sequence for this problem could be obtained by arranging jobs in non-increasing order of processing times. In this paper, we first demonstrate that this result is incorrect, and then introduce new exact solution strategies that polynomially solve problems whose earliness penalties are strictly increasing functions of job earliness. Polynomial time solutions are also presented for some special cases.     

Optimization of ultrasound-assisted extraction for the maximum quantity and quality of phenolics from Stachys lavandulifolia

The response surface methodology was used to evaluate the effects of extraction time, power of ultrasound, liquid to solid ratio, and solvent composition on the quantity and quality (from aspect of antioxidant activity) phenolics of Stachys lavandulifolia. The best extraction time, power of ultrasound, liquid to solid ratio, and solvent composition for both the quality and quantity of phenolics were 14 min, 300 W, 40 (v/w), and 57% methanol, respectively. Only the liquid to solid ratio was effective on the quality of phenolics. Also, the comparison between the ultrasound-assisted extraction and maceration methods showed the suitability of ultrasound-assisted extraction for extracting phenolics from this plant.     

Multi-layer coding strategy for multi-hop block fading channels with outage probability

This paper considers communication over a multi-hop Rayleigh block-fading channel, where there is no direct link between the transmission ends, and communication is carried out through the use of multiple cascaded relays, employing the Decode and Forward (DF) strategy. It is assumed that the relays cannot do buffering or apply coding over consecutive transmission blocks, and they can merely re-encode the retried information and forward an encoded version of information to the next hop. In this case, assuming the channel information of each hop is not available at the corresponding transmitter and considering the destination either receives a minimum rate R₀ or declare an outage event, a multi-layer coding strategy in addition to a single-layer code of the minimum rate R₀ are employed, where the optimal power allocation policy across code layers is derived, leading to the maximum average achievable rate for a given outage probability.     

Application of Geo-electrical Tomography in Coupled Hydro-mechanical–Chemical Investigations in Heap Leaching

Mine Water and the Environment - A shortcoming of the heap leaching process is its inherent limited metal recovery rate, due primarily to preferential pathways, which reduces the efficiency of the...