A mixed integer programming model for remanufacturing in reverse logistics environment

Recently, there has been a growing interest in reverse logistics due to environmental deterioration. Firms incorporate reverse flow to their systems for such reasons as ecological and economic factors, government regulations and social responsibilities. In this paper a new mixed integer mathematical model for a remanufacturing system, which includes both forward and reverse flows, is proposed and illustrated on a numerical example. The proposed model provides the optimal values of production and transportation quantities of manufactured and remanufactured products while solving the location problem of dissassembly, collection and distribution facilities. The model is validated by using a set of experimental data reflecting practical business situation. Sensitivity analysis of the model is also presented.     

Seasonal changes in the proximate chemical compositions and fatty acids of chub mackerel (Scomber japonicus) and horse mackerel (Trachurus trachurus) from the north eastern Mediterranean Sea

The effects of seasonal variations on the proximate chemical compositions and fatty acid profiles of chub mackerel (Scomber japonicus) and horse mackerel (Trachurus trachurus) captured in the north‐eastern Mediterranean Sea were investigated. Protein fluctuations were observed in two species for all seasons. The lipid content of both species was lower in winter than in autumn and spring. In all seasons, the major fatty acids in both species were observed to be palmitic acid (16:0), stearic acid (18:0), oleic acid (18:1 ω9), eicosapentaenoic acid (20:5 ω3) and docosahexaenoic acid (20:6 ω3). Chub mackerel and horse mackerel exhibited seasonal fluctuations in their fatty acid contents. The fatty acid profile of the two species had a higher degree of unsaturation during winter. The levels of EPA in chub mackerel in winter, spring and autumn were 5.96%, 4.86% and 4.33%, respectively, while those of DHA were 24.94%, 18.75% and 17.12%, respectively. The levels of EPA in horse mackerel in winter, spring and autumn were 5.42%, 5.03% and 4.86%, respectively, while those of DHA were 14.96%, 13.31% and 11.10%, respectively. The PUFA (polyunsaturated fatty acids) values and ω3/ω6 ratios in the two species were highest in winter. The results indicate that chub mackerel and horse mackerel captured in the north‐eastern Mediterranean Sea, which are among the most important fish in Turkey and of international commercial value, are a good source of nutrition for human consumption in terms of their proximate chemical composition and fatty acids.     

Matching three-phase AC loads to PVG for maximum power transfer using an enhanced version of the Akbaba model and double step-up converter

The matching of three-phase AC loads to photovoltaic generators (PVGs) for maximum power transfer using an enhanced version of the Akbaba model for I–V characteristic of PVGs is investigated. With an enhanced version of the Akbaba model, the model parameters are expressed directly in terms of percent solar radiation. With this improvement on the Akbaba model, only a single input, which is the percent solar radiation for a particular location on the globe, is required for the calculation of the complete performance of the PVG-load system, including available maximum (peak) power. With this new approach all previously needed iterative calculations to determine system performance are eliminated. As an application example, this new approach is applied to the matching of a three-phase load to PVG for maximum power transfer through a double DC–DC step-up converter and a six-step inverter. The effectiveness and accuracy of the model is demonstrated through detailed numerical results.     

TRANSIENT MODELING OF HYDRODESULFURIZATION IN A FIXED-BED REACTOR

Transient gas-solid reactions in a fixed-bed reactor have been modeled and applied to hydrodesulfurization with the Langmuir-Hinshelwood mechanism. Three levels of process space are used: the bed, pellet, and grain in meter, millimeter, and micron sizes, respectively. The resulting nonlinear partial differential equations were solved via finite differencing and alternating-direction-iterative methods. The model was validated through comparison of experimental and theoretical results. Theoretical conversion was 99.98% compared to an experimental value of 99.90% for thiophene at steady state. Transient temperature profiles and the mass balance approach were used for verification. Steady-state temperature was predicted within 0.5%.     

Cracked semi-infinite cylinder and finite cylinder problems

This work considers the analysis of a cracked semi-infinite cylinder and a finite cylinder. Material of the cylinder is assumed to be linearly elastic and isotropic. One end of the cylinder is bonded to a fixed support while the other end is subjected to axial tension. Solution of this problem can be obtained by superposition of solutions for an infinite cylinder subjected to uniformly distributed tensile load at infinity (I) and an infinite cylinder having a penny-shaped rigid inclusion at z = 0 and two penny-shaped cracks at z = ±L (II). General expressions for the perturbation problem (II) are obtained by solving Navier equations with Fourier and Hankel transforms. When the radius of the inclusion approaches the radius of the cylinder, the end at z = 0 becomes fixed and when the radius of the cracks approach the radius of the cylinder, the ends at z = ±L become cut and subject to uniform tensile load. Formulation of the problem is reduced to a system of three singular integral equations. By using Gauss–Lobatto and Gauss–Jacobi integration formulas, these three singular integral equations are converted to a system of linear algebraic equations which is solved numerically.     

Application of ANN in the prediction of the pore concentration of aluminum metal foams manufactured by powder metallurgy methods

In this work, the effect of fabrication parameters on the pore concentration of aluminum metal foam, manufactured by the powder metallurgy process, has been studied. The artificial neural network (ANN) technique has been used to predict pore concentration as a function of some key fabrication parameters. Aluminum metal foam specimens were fabricated from a mixture of aluminum powders (mean particle size 60 μm) and NaCl at 10, 20, 30, 40(wt)% content under a pressure of 200, 250, and 300 MPa. All specimens were then sintered at 630°C for 2.5 h in argon atmosphere. For pore formation (foaming), sintered specimens were immersed into 70°C hot running water. Finally, the pore concentration of specimens was recorded to analyze the effect of fabrication parameters (namely, NaCl ratio, NaCl particle size, and compacting pressure) on the foaming behavior of compacted specimens. It has been recorded that the above-mentioned fabrication parameters are effective on pore concentration profile while pore diameters remain unchanged. In the ANN training module, NaCl content (wt)%, NaCl particle size (μm), and compacting pressure (MPA) were employed as inputs, while pore concentration % (volume) of compacts related to fabrication parameters was employed as output. The ANN program was successfully used to predict the pore concentration % (volume) of compacts related to fabrication parameters.     

Support vector machines combined with feature selection for breast cancer diagnosis

Breast cancer is the second largest cause of cancer deaths among women. At the same time, it is also among the most curable cancer types if it can be diagnosed early. Research efforts have reported with increasing confirmation that the support vector machines (SVM) have greater accurate diagnosis ability. In this paper, breast cancer diagnosis based on a SVM-based method combined with feature selection has been proposed. Experiments have been conducted on different training-test partitions of the Wisconsin breast cancer dataset (WBCD), which is commonly used among researchers who use machine learning methods for breast cancer diagnosis. The performance of the method is evaluated using classification accuracy, sensitivity, specificity, positive and negative predictive values, receiver operating characteristic (ROC) curves and confusion matrix. The results show that the highest classification accuracy (99.51%) is obtained for the SVM model that contains five features, and this is very promising compared to the previously reported results.     

Performance evaluation of a new backoff method for IEEE 802.11

Since DCF is the main protocol of accessing other mobile stations in ad hoc networks such as IEEE 802.11 WLANs, a self-controlling method for each station is necessary, called the backoff algorithm. An exponential backoff method has been used in WLANs and significant efforts have been made to analyze its throughput and other important properties such as delay and jitter. In this article, we propose a new backoff algorithm and model it with a discrete-time Markov chain; measuring its saturation throughput under several conditions and several set of parameters which are to be adjusted according to the network condition, with the aim of approaching maximum throughput when stations are saturated.     

Iterative Least Squares Functional Networks Classifier

This paper proposes unconstrained functional networks as a new classifier to deal with the pattern recognition problems. Both methodology and learning algorithm for this kind of computational intelligence classifier using the iterative least squares optimization criterion are derived. The performance of this new intelligent systems scheme is demonstrated and examined using real-world applications. A comparative study with the most common classification algorithms in both machine learning and statistics communities is carried out. The study was achieved with only sets of second-order linearly independent polynomial functions to approximate the neuron functions. The results show that this new framework classifier is reliable, flexible, stable, and achieves a high-quality performance     

Spatial Distribution of Excess Pore-Water Pressure due to Piezocone Penetration in Overconsolidated Clay

This paper presents the results of an analysis of the spatial distribution of the excess pore-water pressure induced by piezocone penetration into overconsolidated clays. From the experimental results obtained for moderately and heavily overconsolidated clays, it was observed that the excess pore-water pressure increases monotonically from the piezocone surface to the outer boundary of the shear zone and then decreases logarithmically, approaching zero at the outer boundary of the plastic zone. It was also found that the size of the shear zone decreases from approximately 2.2 to 1.5 times the cone radius with increasing overconsolidation ratio (OCR), whereas the plastic radius is about 11 times the piezocone radius, regardless of the OCR. The expressions developed in this study based on the modified Cam clay model and the cylindrical cavity expansion theory, which take into consideration the effects of the strain rate and stress anisotropy, provide a good prediction of the initial pore-water pressure at the piezocone location. The method of predicting the spatial distribution of excess pore-water pressure proposed in this study is based on a linearly increasing Δushear in the shear zone and a logarithmically decreasing Δuoct, and was verified by comparing the pore-water pressure measured in overconsolidated specimens in the calibration chamber.