Fabrication of superhydrophobic and antibacterial surface on cotton fabric by doped silica-based sols with nanoparticles of copper

The study discussed the synthesis of silica sol using the sol-gel method, doped with two different amounts of Cu nanoparticles. Cotton fabric samples were impregnated by the prepared sols and then dried and cured. To block hydroxyl groups, some samples were also treated with hexadecyltrimethoxysilane. The average particle size of colloidal silica nanoparticles were measured by the particle size analyzer. The morphology, roughness, and hydrophobic properties of the surface fabricated on cotton samples were analyzed and compared via the scanning electron microscopy, the transmission electron microscopy, the scanning probe microscopy, with static water contact angle (SWC), and water shedding angle measurements. Furthermore, the antibacterial efficiency of samples was quantitatively evaluated using AATCC 100 method. The addition of 0.5% (wt/wt) Cu into silica sol caused the silica nanoparticles to agglomerate in more grape-like clusters on cotton fabrics. Such fabricated surface revealed the highest value of SWC (155° for a 10-μl droplet) due to air trapping capability of its inclined structure. However, the presence of higher amounts of Cu nanoparticles (2% wt/wt) in silica sol resulted in the most slippery smooth surface on cotton fabrics. All fabricated surfaces containing Cu nanoparticles showed the perfect antibacterial activity against both of gram-negative and gram-positive bacteria.     

Identifying Potato Varieties Using Machine Vision and Artificial Neural Networks

The objective of this study is to develop a method for identifying and discriminating 10 potato varieties by combining machine vision and artificial neural network methods. The potato varieties include Agria, Savalan, Florida, Fontaneh, Natasha, Verona, Karso, Elody, Satina, and Emrad. A total number of 72 characteristic parameters specifying color, textural, and morphological features are found among these varieties. By using principal component analysis, 16 principal features are selected for identifying and discriminating potato varieties. The data obtained from image processing were classified using linear discriminant analysis and non-linear artificial neural network method. The accuracy of discriminant analysis were 73.3, 93.3, 73.3, 40, 73.3, 73.3, 66.7, 80, 40, and 53.3%, respectively, for the varieties used in this study. The classification accuracy was improved by 100% for all the varieties using neural network analysis and the correct classification ratio was 100% using this method. It is revealed from the results that machine vision technique and neural network analysis could identify potato varieties with acceptable accuracy.     

First principle study of electronic and optical properties of planar GeC,SnC and SiC nanosheets

The electronic structures and optical properties of XC (X = Ge, Sn, Si) nanosheets are investigated in the present study using the full potential linearized augment plane wave (FP-LAPW) technique based on the first principles density-functional theory (DFT). Using the calculated dielectric function within the random phase approximation (RPA), the reflectivity, absorption coefficient, energy-loss function and refraction index of these nanosheets for parallel and perpendicular electric field polarizations are well described. Our electronic structure calculations for XC (X = Ge, Sn, Si) nanosheets confirmed the semiconductor property of these compounds. To ensure the accuracy of our work, we have also calculated the energy gap and optical constants of XC (X = Ge, Sn, Si) bulks in Zinc-blende structure and compared our obtained results with the previous works. The results of our comparison study show that the values of static refractive index and static dielectric constant for XC (X = Ge, Sn, Si) nanosheets in a parallel electric field polarization are greater than those in a perpendicular electric field polarization.     

Illumination invariant feature extraction and mutual-information-based local matching for face recognition under illumination variation and occlusion

An efficient method for face recognition which is robust under illumination variations is proposed. The proposed method achieves the illumination invariants based on the illumination-reflection model employing local matching for best classification. Different filters have been tested to achieve the reflectance part of the image, which is illumination invariant, and maximum filter is suggested as the best method for this purpose. A set of adaptively weighted classifiers vote on different sub-images of each input image and a decision is made based on their votes. Image entropy and mutual information are used as weight factors. The proposed method does not need any prior information about the face shape or illumination and can be applied on each image separately. Unlike most available methods, our method does not need multiple images in training stage to get the illumination invariants. Support vector machines and k-nearest neighbors methods are used as classifier. Several experiments are performed on Yale B, Extended Yale B and CMU-PIE databases. Recognition results show that the proposed method is suitable for efficient face recognition under illumination variations.     

Convergence analysis of max-consensus algorithm in probabilistic communication networks with Bernoulli dropouts

In the presence of probabilistic communication networks between agents, the convergence analysis of max-consensus algorithm (MCA) is addressed in this paper. It is considered that at each iteration of MCA, all agents share their measurements with adjacent agents via local communication networks which is applicable in many multi-agent systems (MASs). It is assumed that the communication networks have Bernoulli dropouts, i.e. the information exchanged between agents may be lost with Bernoulli distribution. In the proposed method, the information topology of MAS is modelled as a dynamic graph with the Bernoulli adjacency matrix. It is proved that in the presence of Bernoulli dropouts and under non-restrictive assumptions concerning the MAS features and communication topology, the MCA converges with a probability one in the finite time. Furthermore, the upper bounds are provided by means of deterministic and probabilistic expressions for the expectation and dispersion of convergence time, respectively. It is shown that the proposed upper bounds are asymptotic, i.e. there are specific conditions of MAS in which the convergence time of MCA tends to the proposed upper bounds. The convergence accuracy of MCA is discussed in terms of probabilistic equations. The validity of the proposed theorems is illustrated by means of simulation results.     

Effect of aluminum on microstructural and magnetic properties of nanostructured (Fe85Ni15)97Al3 alloy produced via mechanical alloying

In the present study, mechanical alloying process was employed for preparation of the nanocrystalline (Fe₈₅Ni₁₅)₉₇Al₃ alloy through ball mill method. The structure, mechanical properties, and magnetic behavior of the alloy at various milling times of 0, 4, 16, 32 and 64 h were studied by X-ray analysis, vibrating sample magnetometer (VSM) and scanning electron microscopy (SEM) measurements. The bcc Fe(Ni) phase was successfully formed within 32 h ball-milling. It was found that an increment in the milling time leads to higher lattice parameter while it decreases the grain size from 172 to 16 nm. Also, the VSM test results indicated that by increasing the milling time to 32 h, the saturation magnetization (M_s) and coercivity (H_c) increased.     

Electro-thermo-mechanical nonlinear free vibration of nanobeam resting on the winkler-pasternak foundations based on nonlocal elasticity using differential transform method

Microsystem Technologies - This study presents electro-thermo-mechanical nonlinear vibration of nanobeam resting on the Winkler-Pasternak foundations. The nanobeam is considered as an...     

A contractor pre-qualification model based on the quality function deployment method

Contractors play a significant role in construction projects and selection of the most appropriate contractor for the project is a critical decision for clients. The pre-qualification of construction contractors is accounted as a very important step in contractor selection for every project. The main purpose of pre-qualification is to identify an array of eligible contractors, which is required for post-qualification steps and further considerations. Although there have been numerous models for contractor pre-qualification, there are inadequate researches to present a contractor pre-qualification model with consideration of the project objectives or the project owner’s requirements. A new contractor pre-qualification model was developed with the aim of resolving this issue. This model employs the quality function deployment (QFD) method, and considers both the project owner’s requirements and the contractor’s abilities. The results reveal that consideration of the project objectives or the project owner’s requirements and expectations can influence contractor pre-qualification.     

A Proxy MIPv6 Handover Scheme for Vehicular Ad-hoc Networks

With the rapid growth in the number of mobile devices, such as cellular phones, PDAs and laptops, the need for seamless and ubiquitous Internet connectivity is tangible. Vehicular ad-hoc network (VANET) is a rapidly developing technology, which makes vehicle-to-vehicle and vehicle-to-infrastructure communication feasible. However, when a vehicle travels from one point of attachment to another, handoff delays and provision of seamless connectivity are considered as important issues. Ubiquitous and integrated Internet connectivity can be achieved if on road moving vehicles are connected. However, when vehicle density is small and/or vehicle velocities are different, end users may suffer from a high level of connection failure. IP mobility protocols are designed by Internet Engineering Task Force to provide acceptable levels of continuous Internet connectivity, maintaining mobile node communications as they travel amongst points of attachments. However, the current IP mobility approaches applied on VANET did not resolve the connection failure issues efficiently. Therefore, in this paper a new effective solution is proposed in order to eliminate the large amount of handover latency and eventually high packet loss ratio.