Large Area Self-Assembled Ultrathin Polyimine Nanofilms Formed at the Liquid–Liquid Interface Used for Molecular Separation

Separation membranes with higher molecular weight cut-offs are needed to separate ions and small molecules from a mixed feed. The molecular sieving phenomenon can be utilized to separate smaller species with well-defined dimensions from a mixture. Here, the formation of freestanding polyimine nanofilms with thicknesses down to ≈14 nm synthesized via self-assembly of pre-synthesized imine oligomers is reported. Nanofilms are fabricated at the water–xylene interface followed by reversible condensation of polymerization according to the Pieranski theory. Polyimine nanofilm composite membranes are made via transferring the freestanding nanofilm onto ultrafiltration supports. High water permeance of 49.5 L m^-2 h⁻¹ bar⁻¹ is achieved with a complete rejection of brilliant blue-R (BBR; molecular weight = 825 g mol⁻¹) and no more than 10% rejection of monovalent and divalent salts. However, for a mixed feed of BBR dye and monovalent salt, the salt rejection is increased to ≈18%. Membranes are also capable of separating small dyes (e.g., methyl orange; MO; molecular weight = 327 g mol⁻¹) from a mixed feed of BBR and MO. Considering a thickness of ≈14 nm and its separation efficiency, the present membrane has significance in separation processes.     

Heat Transfer Analysis for Gas-to-Liquids Transportation Through Trans Alaska Pipeline

Gas-to-liquids (GTL) technology involves the conversion of natural gas to liquid hydrocarbons. In this article, theoretical studies have been presented to determine the feasibility of transporting GTL products through the Trans-Alaska Pipeline System (TAPS). To successfully transport GTL through TAPS, heat loss along the route must be carefully determined. This study presents heat transfer and fluid dynamic calculations to evaluate this feasibility. Because of heat loss, the fluid temperature decreases in the direction of flow and this affects the fluid properties, which in turn influence convection coefficient and pumping power requirements. The temperature and heat loss distribution along the pipeline at different locations have been calculated. Fairly good agreement with measured oil temperatures is observed. The powers required to pump crude oil and GTL individually, against various losses have been calculated. Two GTL transportation modes have been considered; one as a pure stream of GTL and the second as a commingled mixture with crude oil. These results show that the pumping power and heat loss for GTL are less than that of the crude oil for the same volumetric flow rate. Therefore, GTL can be transported through TAPS using existing equipment at pump stations.     

A genetic‐based neuro‐fuzzy controller for blind equalization of time‐varying channels

This paper presents a neuro‐fuzzy network (NFN) where all its parameters can be tuned simultaneously using genetic algorithms (GAs). The approach combines the merits of fuzzy logic theory, neural networks and GAs. The proposed NFN does not require a priori knowledge about the system and eliminates the need for complicated design steps such as manual tuning of input–output membership functions, and selection of fuzzy rule base. Although, only conventional GAs have been used, convergence results are very encouraging. A well‐known numerical example derived from literature is used to evaluate and compare the performance of the network with other equalizing approaches. Simulation results show that the proposed neuro‐fuzzy controller, all parameters of which have been tuned simultaneously using GAs, offers advantages over existing equalizers and has improved performance. From the perspective of application and implementation, this paper is very interesting as it provides a new method for performing blind equalization. The main contribution of this paper is the use of learning algorithms to train a feed‐forward neural network for M‐ary QAM and PSK signals. This paper also provides a platform for researchers of the area for further development. Copyright © 2008 John Wiley & Sons, Ltd.     

Multiple exemplar-based facial image retrieval using independent component analysis.

In this paper, we design a content-based image retrieval system where multiple query examples can be used to indicate the need to retrieve not only images similar to the individual examples, but also those images which actually represent a combination of the content of query images. We propose a scheme for representing content of an image as a combination of features from multiple examples. This scheme is exploited for developing a multiple example-based retrieval engine. We have explored the use of machine learning techniques for generating the most appropriate feature combination scheme for a given class of images. The combination scheme can be used for developing purposive query engines for specialized image databases. Here, we have considered facial image databases. The effectiveness of the image retrieval system is experimentally demonstrated on different databases.     

Electrical Conduction in Nano-Structured La0.9Sr0.1Al0.85Co0.05Mg0.1O3 Perovskite Oxide

Nanocrystalline La_0.9Sr_0.1Al_0.85Co_0.05Mg_0.1O₃ oxide powder was synthesized by a citrate–nitrate auto-ignition process and characterized by thermal analysis, X-ray diffraction, and impedance spectroscopy measurements. Nanocrystalline (50–100 nm) powder with perovskite structure could be produced at 900°C by this process. The powder could be sintered to a density more than 96% of the theoretical density at 1550°C. Impedance measurements on the sintered samples unequivocally established the potential of this process in developing nanostructured lanthanum aluminate-based oxides. The sintered La_0.9Sr_0.1Al_0.85Co_0.05Mg_0.1O₃ sample exhibited a conductivity of 2.40 × 10⁻² S/cm in air at 1000°C compared with 4.9 × 10⁻³ S/cm exhibited by La_0.9Sr_0.1Al_0.85Mg_0.15O₃.     

Energy sector planning using multiple-index pinch analysis

Pinch analysis was initially developed as a methodology for optimizing energy efficiency in process plants. Applications of pinch analysis applications are based on common principles of using stream quantity and quality to determine optimal system targets. This initial targeting step identifies the pinch point, which then allows complex problems to be decomposed for the subsequent design of an optimal network using insights drawn from the targeting stage. One important class of pinch analysis problems is energy planning with footprint constraints, which began with the development of carbon emissions pinch analysis; in such problems, energy sources and demands are characterized by carbon footprint as the quality index. This methodology has been extended by using alternative quality indexes that measure different sustainability dimensions, such as water footprint, land footprint, emergy transformity, inoperability risk, energy return on investment and human fatalities. Pinch analysis variants still have the limitation of being able to use one quality index at a time, while previous attempts to develop pinch analysis methods using multiple indices have only been partially successful for special cases. In this work, a multiple-index pinch analysis method is developed by using an aggregate quality index, based on a weighted linear function of different quality indexes normally used in energy planning. The weights used to compute the aggregate index are determined via the analytic hierarchy process. A case study for Indian power sector is solved to illustrate how this approach allows multiple sustainability dimensions to be accounted for in energy planning.     

Improvement of lubrication and cooling in grinding

The presence of air boundary layer around a grinding wheel impedes the proper entry of cutting fluid into grinding zone and thereby lubrication and cooling are hampered. It leads to the thermal damage to the workpiece and rapid wheel wear. This experimental work is aimed at increasing the lubrication and cooling effects in grinding by a novel method of using scraper board. The experiments are conducted, using the scraper board, to find the critical region where the air pressure is zero. The coolant jet has then impinged into the grinding zone which is maintained within the critical region. The requirement of specific energy, surface texture, and mechanical properties of the ground surface are analyzed and compared with the traditional grinding and the grinding at various positions of scraper board. Results show that the grinding ratio improved by 35.6and 119%, surface roughness decreased by 36 and 54.2%, while the requirement of specific energy is reduced by 50.8 and 57.3% when scraper board is positioned at the critical distance in comparison to the 57.5° position and no scraper board, respectively. The results indicate that the introduction of fluid in the present method can improve the process efficiency and the product quality effectively.     

Cryptanalysis of RSA with two decryption exponents

In this paper, we consider RSA with N=pq, where p,q are of same bit size, i.e., q<p<2q. We study the weaknesses of RSA when multiple encryption and decryption exponents are considered with same RSA modulus N. A decade back, Howgrave-Graham and Seifert (CQRE 1999) studied this problem in detail and presented the bounds on the decryption exponents for which RSA is weak. For the case of two decryption exponents, the bound was N^0.357. We have exploited a different lattice based technique to show that RSA is weak beyond this bound. Our analysis provides improved results and it shows that for two exponents, RSA is weak when the RSA decryption exponents are less than N^0.416. Moreover, we get further improvement in the bound when some of the most significant bits (MSBs) of the decryption exponents are same (but unknown).     

Reconstruction Based Recognition of Scenes with Multiple Repeated Components

This paper proposes an invariance based recognition scheme for scenes with multiple repeated components. The scheme considers three component subsets which characterize the scene completely. Each such three component subset is reconstructed using single image based information. We have developed a mathematical framework for the projective reconstruction based on relative affine structure of each such three component building block. This is extended to the case when each of the components is a quadric. A set of projective invariants of three quadrics has also been obtained by us. Although the reconstruction scheme is general and applicable to all multiple repeated components, it requires the computation of infinite homography. The infinite homography and hence the reconstruction scheme are only image computable with the given information in the case of translational repetition. We therefore develop a recognition strategy for the specific case of translationally repeated quadrics. As a recognition strategy for scenes with multiple translationally repeated quadric components, we propose to compute and store invariant values for each such three component subsets. Experiments on real data have shown the applicability of this approach for recognition of aerial images of power plants. The discriminatory power of the invariants and the stability of the recognition results have also been experimentally demonstrated.