Mixed matrix membranes on the basis of Matrimid and palladium-zeolitic imidazolate framework for hydrogen separation

Iranian Polymer Journal - Gas separation membranes with enhanced performance were developed by the introduction of nanosized palladium particles. In this study, gas separation performance of...     

A systematic review and meta-analysis of artificial neural network application in geotechnical engineering: theory and applications

Artificial neural network (ANN) aimed to simulate the behavior of the nervous system as well as the human brain. Neural network models are mathematical computing systems inspired by the biological neural network in which try to constitute animal brains. ANNs recently extended, presented, and applied by many research scholars in the area of geotechnical engineering. After a comprehensive review of the published studies, there is a shortage of classification of study and research regarding systematic literature review about these approaches. A review of the literature reveals that artificial neural networks is well established in modeling retaining walls deflection, excavation, soil behavior, earth retaining structures, site characterization, pile bearing capacity (both skin friction and end-bearing) prediction, settlement of structures, liquefaction assessment, slope stability, landslide susceptibility mapping, and classification of soils. Therefore, the present study aimed to provide a systematic review of methodologies and applications with recent ANN developments in the subject of geotechnical engineering. Regarding this, a major database of the web of science has been selected. Furthermore, meta-analysis and systematic method which called PRISMA has been used. In this regard, the selected papers were classified according to the technique and method used, the year of publication, the authors, journals and conference names, research objectives, results and findings, and lastly solution and modeling. The outcome of the presented review will contribute to the knowledge of civil and/or geotechnical designers/practitioners in managing information in order to solve most types of geotechnical engineering problems. The methods discussed here help the geotechnical practitioner to be familiar with the limitations and strengths of ANN compared with alternative conventional mathematical modeling methods.

     

Surface structural and solar absorptance features of nitrate-based copper-cobalt oxides composite coatings: Experimental studies and molecular dynamic simulation

The copper and cobalt oxides composites coatings on aluminum substrates have been successfully synthesized via sol-gel method using nitrate-based sol precursors. The composites were characterized by X-ray Diffraction (XRD), X-ray photoelectron spectroscopy (XPS), Field Emission Scanning Electron Microscopy (FESEM), Atomic Force Microscopy (AFM), and UV–Vis–NIR spectrophotometry. The sol-gel reactions were discussed and Molecular Dynamics (MD) simulation was integrated into the study to predict molecules assembly properties. The XRD analyses revealed that the CuO and the Co₃O₄ composites were formed after the annealing process with the average difference of the calculated lattice parameters compared to ICDDs was 1.17%. The surface electronic structure was mainly consisted of tetrahedral Cu(I), octahedral Cu(II), tetrahedral Co(II), octahedral Co(III) as well as surface, sub-surface and lattice oxygen O^?. The XRD, XPS and MD simulation results showed that there was minimal (or possibly non-existing) indication of copper-cobalt mixed phase oxides formations. FESEM and AFM surveys revealed that the coating had a porous surface composed of interlinked nanoparticles in the range of ~?10 to ~?40?nm. UV–Vis–NIR reflectance spectra showed that the sol precursors concentration and the dip-drying cycle significantly influenced the absorptance value with optimum absorptance (α) of 88.7% exhibited by coating synthesized using sol concentration of 0.1?M and 10 dip-drying cycles. High absorptance value and simplicity in the synthesis process render the coatings to be very promising candidates for solar selective absorber (SSA) applications.     

An efficient routing protocol for cognitive radio networks of energy-limited devices

Telecommunication Systems - In the era of Internet-of-things (IoT), the future 5G networks are supposed to provide ubiquitous connectivity, high speed, as well as low latency and energy efficiency...     

Arabic sign language intelligent translator

ABSTRACT

Arabic sign language (ArSL) is method of communication between deaf communities in Arab countries; therefore, the development of systemsthat can recognize the gestures provides a means for the Deaf to easily integrate into society. In this research we implemented a computational structurefor an intelligent interpreter that automatically recognizes the isolated dynamic gestures. The proposed system recognizes and translates gesturesperformed with one or both hands. It comprises five subsystems, building dataset, video processing, feature extraction, mapping between ArSL and Arabictext, and text generation. To apply the system, 100-signs of ArSL was used, which was applied on 1500 video files. It's were divided into five classes:alphabet, numbers, "prepositions, pronouns and question words", Arabic life expressions, and "nouns and verbs". The evaluation indicated that thesystem automatically recognizes and translates isolated dynamic ArSL gestures by highly accurate manner. The results showed that the system accuracy is 95.8%.     

Experimentelle und analytische Untersuchung des out‐of‐plane‐Verhaltens von unbewehrten Mauerwerkswänden unter Erdbebenbelastung

Experimental and analytical investigation of the seismic out‐of‐plane behavior of unreinforced masonry walls In addition to the vertical and horizontal load‐bearing in‐plane, masonry must also withstand out‐of‐plane loads that occur in earthquake scenarios. The out‐of‐plane behavior of unreinforced masonry walls depends on a variety of parameters and is very complex due to the strong non‐linearity. Current design methods in German codes and various international codes have not been explicitly developed for out‐of‐plane behavior and contain considerable conservatism. In the present work, shaking‐table experiments with heat‐insulating masonry walls have been conducted to investigate the out‐of‐plane behavior of vertical spanning unreinforced masonry walls. As shown in previous numerical investigations, important parameters are neglected in existing design and analysis models and the out‐of‐plane capacity is underestimated significantly. In the conducted experiments the results of these numerical investigations are verified. Furthermore, the development of an analytical design model to determine the force‐displacement relationship and the out‐of‐plane load‐bearing capacity considering all significant parameters is presented.     

Auto-recognition and part model complexity quantification of regular-freeform revolved surfaces through delta volume generations

Engineering with Computers - Vast research works implementing feature-based technology have successfully been devoted. However, work on recognition of revolved regular-freeform surfaces is still...     

Effect of transition metal doping on the sintering and electrochemical properties of GDC buffer layer in SOFCs

A dense Ce_0.9Gd_0.1O_2−d (GDC) interlayer is an essential component of the SOFCs to inhibit interfacial elemental diffusion between zirconia-based electrolytes (eg YSZ) and cathodes. However, the characteristic high sintering temperature of GDC (>1400°C) makes it challenging to fabricate an effective highly dense interlayer owing to the formation of more resistive (Zr,Ce)O₂ interfacial solid solutions with YSZ at those temperatures. To fabricate a useful GDC interlayer, we studied the influence of transition metal (TM) (Co, Cu, Fe, Mn, & Zn) doping on the sintering and electrochemical properties of GDC. Dilatometry data showed dramatic drops in the necking and final sintering temperatures for the TM-doped GDCs, improving the densification of the GDC in the order of Fe > Co > Mn > Cu > Zn. However, the electrochemical impedance data showed that among various transition metal dopants, Mn doping resulted in the best electrochemical properties. Anode supported SOFCs with Mn-doped, nano, and commercial-micron GDC interlayers were compared with regard to their performance and stability levels. Although all of the SOFCs showed stable performance, the SOFC with the Mn-doped GDC interlayer showed the highest power density of 1.14 W cm⁻² at 750°C. Hence, Mn-doped GDC is suggested for application as an effective diffusion barrier layer in SOFCs.