Varnish layer hardness of oriental beech (fagus orientalist L.) wood as affected by impregnation and bleaching

The impacts of impregnation and bleaching on the varnish layer hardness of Oriental beech (Fagus orientalist L.) wood were investigated. A number of bleaching combinations {[NaOH−H₂O₂], [NaOH−Ca(OH)₂−H₂O₂], [NaOH−MgSO₄−H₂O₂] [NaHSO₃−H₂C₂O₄], [NaSiO₃−H₂O₂], [KMnO₄+NaHSO₃+H₂O₃]} were applied at 18% concentration for bleaching to both impregnated and unimpregnated specimens of Oriental beech wood. Subsequently, water-based (WB) varnish was coated over the samples and the varnish layer hardness values were determined in accordance with ASTM D 4366-95. All of the chemicals used for bleaching reduced the surface hardness. However, after varnish coating, the hardness of most samples was similar to that of the varnish-coated natural (control) samples.     

Robust multilayer neural network based on median neuron model

Multilayer perceptron has been widely used in time series forecasting for last two decades. However, it is a well-known fact that the forecasting performance of multilayer perceptron is negatively affected when data have outliers and this is an important problem. In recent years, some alternative neuron models such as generalized-mean neuron, geometric mean neuron, and single multiplicative neuron have been also proposed in the literature. However, it is expected that forecasting performance of artificial neural network approaches based on these neuron models can be also negatively affected by outliers since the aggregation function employed in these models is based on mean value. In this study, a new multilayer feed forward neural network, which is called median neuron model multilayer feed forward (MNM-MFF) model, is proposed in order to deal with this problem caused by outliers and to reach high accuracy level. In the proposed model, unlike other models suggested in the literature, MNM which has median-based aggregation function is employed. MNM is also firstly defined in this study. MNM-MFF is a robust neural network method since aggregation functions in MNM-MFF are based on median, which is not affected much by outliers. In addition, to train MNM-MFF model, particle swarm optimization method was utilized. MNM-MFF was applied to two well-known time series in order to evaluate the performance of the proposed approach. As a result of the implementation, it was observed that the proposed MNM-MFF model has high forecasting accuracy and it is not affected by outlier as much as multilayer perceptron model. Proposed method brings improvement in 7 % for data without outlier, in 90 % for data with outlier, in 95 % for data with bigger outlier.     

Ring opening polymerization of 2,5-dihydro-2,5-dimethoxyfuran by electrochemical initiation

Summary 2,5-Dihydro-2,5-dimethoxyfuran (DHMF) was polymerized via constant current electrolysis (CCE), in CH₃CN-NaClO₄ solvent-electrolyte couple. Poly(DHMF) was obtained from the anolyte. The effect of current density, temperature, monomer and electrolyte concentrations on the polymer yield have been examined. The apparent activation energy for CCE of DHMF was found to be 37.2 kj/mol. The FTIR and ¹H-NMR analyses show that DHMF polymerizes by a ring opening. Molecular weight of poly(DHMF) was found by using cryoscopy.     

Design of Lu2O3-reinforced Cf/SiC-ZrB2-ZrC ultra-high temperature ceramic matrix composites: Wetting and interfacial reactivity by ZrSi2 based alloys

The wettability and infiltration of molten ZrSi₂ and ZrSi₂-Lu₂O₃ alloys into C_f/SiC and B₄C-infiltrated C_f/SiC composites were investigated to understand the interfacial interactions that occur during the development of C_f/SiC-ZrC and C_f/SiC-ZrB₂-ZrC-Lu₂O₃ materials. A significant evaporation of Si from the liquid affected the wetting behaviour of the alloy when tested in a vacuum at 1670 °C. The better wetting and spreading of the alloy over the surface was observed for the composites with lower overall porosity (12 %). On the other hand, the formation of an outer dense layer, followed up by the uniform infiltrated region up to ～ 1 mm was observed for the C_f/SiC with higher porosity (21 %). The infiltrated alloy reacted with SiC matrix to form ZrC or with B₄C-infiltrated SiC matrix to form ZrB₂-ZrC-SiC. The Lu₂O₃ particles were not wetted by the melt, and were pushed away of the reaction zone by the solidification front.     

An LMI approach to synthesis subject to almost asymptotic regulation constraints

A multi-objective controller synthesis problem is considered in which an output is to be regulated approximately by assuring a bound on the steady-state peak amplification in response to an infinite-energy disturbance, while also guaranteeing a desired level of performance measured in terms of the worst-case energy gain from a finite-energy input to a performance output. Relying on a characterization of the controllers with which almost asymptotic regulation is accomplished, the problem of guaranteeing the desired level of performance is reduced to solving a system of linear matrix inequalities subject to a set of linear equality constraints. Based on the solution of this system, a procedure is outlined for the construction of a suitable controller whose order is equal to the order of the plant plus the order of the exogenous system.     

Magnetoresistance behaviour in CoFe/Cu multilayers: thin Cu layer effect

The magnetoresistance properties of the CoFe/Cu multilayers have been investigated as a function of thin non-magnetic Cu layer thickness (from 2.5 to 0.3 nm). CoFe/Cu multilayers were electrodeposited on Ti substrates from a single electrolyte containing their metal ions under potentiostatic control. The structural analysis of the films was made using X-ray diffraction. The peaks appeared at 2θ ≈ 44°, 51°, 74° and 90° are the main Bragg peaks of the multilayers, arising from the (111), (200), (220) and (311) planes of the face-centered cubic structure, respectively. The magnetic characterization was performed by using vibration sample magnetometer in magnetic fields up to ±1600 kA/m. At 0.6, 1.2 and 2.0 nm Cu layer thicknesses, the high saturation magnetization values were observed due to antiferromagnetic coupling of adjacent magnetic layers. Magnetoresistance measurements were carried out using the Van der Pauw method in magnetic fields up to ±1000 kA/m at room temperature. All multilayers exhibited giant magnetoresistance (GMR), and the similar trend in GMR values and GMR field sensitivity was observed depending on the Cu layer thickness.     

Preserving spatial information and overcoming variations in appearance for face recognition

Local feature-based approaches mainly aim to achieve robustness to variations in facial images by assuming that only some parts of the facial images may be affected. However, such approaches may lose spatial information. In this study, a compromise feature extraction scheme is studied which extracts local features while preserving spatial information. The proposed scheme exploits an ensemble of classifiers where each member is constructed using randomly selected design parameters including the size, number and location of sub-images for local feature extraction. Experiments conducted on FERET and ORL databases have shown that proposed scheme surpasses the local feature-based reference systems which focus on either local information or preserving spatial information.     

Bicriteria robotic operation allocation in a flexible manufacturing cell

Consider a manufacturing cell of two identical CNC machines and a material handling robot. Identical parts requesting the completion of a number of operations are to be produced in a cyclic scheduling environment through a flow shop type setting. The existing studies in the literature overlook the flexibility of the CNC machines by assuming that both the allocation of the operations to the machines as well as their respective processing times are fixed. Consequently, the provided results may be either suboptimal or valid under unnecessarily limiting assumptions for a flexible manufacturing cell. The allocations of the operations to the two machines and the processing time of an operation on a machine can be changed by altering the machining conditions of that machine such as the speed and the feed rate in a CNC turning machine. Such flexibilities constitute the point of origin of the current study. The allocation of the operations to the machines and the machining conditions of the machines affect the processing times which, in turn, affect the cycle time. On the other hand, the machining conditions also affect the manufacturing cost. This study is the first to consider a bicriteria model which determines the allocation of the operations to the machines, the processing times of the operations on the machines, and the robot move sequence that jointly minimize the cycle time and the total manufacturing cost. We provide algorithms for the two 1-unit cycles and test their efficiency in terms of the solution quality and the computation time by a wide range of experiments on varying design parameters.     

Throughput optimization in two-machine flowshops with flexible operations

In this study, a two-machine flowshop producing identical parts is considered. Each of the identical parts is assumed to require a number of manufacturing operations, and the machines are assumed to be flexible enough to perform different operations. Due to economical or technological constraints, some specific operations are preassigned to one of the machines. The remaining operations, called flexible operations, can be performed on either one of the machines, so that the same flexible operation can be performed on different machines for different parts. The problem is to determine the assignment of the flexible operations to the machines for each part, with the objective of maximizing the throughput rate. We consider various cases regarding the number of parts to be produced and the capacity of the buffer between the machines. We present solution methods for each variant of the problem.