Human Centric Facial Expression Recognition

Facial expression recognition (FER) is an area of active research, both in computer science and in behavioural science. Across these domains there is evidence to suggest that humans and machines find it easier to recognise certain emotions, for example happiness, in comparison to others. Recent behavioural studies have explored human perceptions of emotion further, by evaluating the relative contribution of features in the face when evaluating human sensitivity to emotion. It has been identified that certain facial regions have more salient features for certain expressions of emotion, especially when emotions are subtle in nature. For example, it is easier to detect fearful expressions when the eyes are expressive. Using this observation as a starting point for analysis, we similarly examine the effectiveness with which knowledge of facial feature saliency may be integrated into current approaches to automated FER. Specifically, we compare and evaluate the accuracy of ‘full-face’ versus upper and lower facial area convolutional neural network (CNN) modelling for emotion recognition in static images, and propose a human centric CNN hierarchy which uses regional image inputs to leverage current understanding of how humans recognise emotions across the face. Evaluations using the CK+ dataset demonstrate that our hierarchy can enhance classification accuracy in comparison to individual CNN architectures, achieving overall true positive classification in 93.3% of cases

Investigating the Relationship Between Managers Capabilities and Performance of Consumer Cooperatives in Kerman City

The objective of the current article is to identify the relation between managers' capabilities and performance of consumer cooperative in Kerman city. This study was carried out in correlating method and research method was library study and reviewing annual performance and document reports. Statistical population of this study consisted of 21 managers of consumer cooperative in Kerman in 2010. Statistical analysis was conducted using SPSS 16 to calculate descriptive statistics, correlation and regression. Based on literature, for performance evaluation, the paper used financial indicators such as ROA, ROE and profit margin. Also managers' capabilities were examined by three variables: education, working experience and education disciplines related to cooperative activity. According to correlation analysis, working experience and education disciplines related to cooperative activity have significant positive relationship with cooperative performance but there is no significant relationship between education and cooperative performance. The result of multiple regression analysis indicated that work experience is the most effective variable on cooperative performance. 35.2% of the changes in performance is caused by work experience and education disciplines related to cooperative activity

Novel functionalized carbon nanotubes for improving the surface properties and performance of polyethersulfone (PES) membrane

Amine functionalized Multi-walled carbon nanotubes (F-MWCNTs)/polyethersulfone (PES) membranes were prepared using phase inversion induced by immersion precipitation. Crude MWCNTs were chemically treated using strong acids (H2SO4/HNO3) and 1,3-phenylenediamine (mPDA) to produce the functional amine groups (single bondNH2) on their surfaces. F-MWCNTs with different concentration were blended in the casting solution containing PES, polyvinylpyrrolidone (PVP) and dimethylacetamide (DMAC). Pure water was used as non-solvent. The FTIR spectra indicated that the amine functional groups were produced on the surface of MWCNTs. The membranes prepared with different concentrations of F-MWCNTs were characterized using contact angle, field emission scanning electron microscopy (FESEM), scanning electron microscopy (SEM), atomic force microscopy (AFM) and permeation tests. The surface hydrophilicity of membranes was significantly improved by addition of F-MWCNTs in the casting solution. An increment in the porosity, pore size and surface roughness of the membranes was observed by increasing F-MWCNTs content up to 1 wt.%. Further addition of F-MWCNTs caused a reduction in porosity and roughness of formed membrane. The membranes prepared with 0.5 and 1 wt.% of F-MWCNTs showed higher performance than neat membrane. Addition of F-MWCNTs in the casting solution improved the BSA rejection and antifouling properties of PES membrane

Feasibility of membrane processes for the recovery and purification of bio-based volatile fatty acids: A comprehensive review

Volatile fatty acids (VFAs) can be produced from fermentation/anaerobic digestion of wastes and are a valuable substrate for numerous applications, such as those related to the food, tanning, petrochemicals, pharmaceuticals, cosmetics, and chemicals industry. They are also inexpensive raw materials for developing alternative sources of energy. However, the separation and purification of VFAs produced from fermented wastewaters are not straightforward goals, due to the low concentration of these compounds in the fermentation broths and owing to the complexity of these mixtures. Cost-effective and sustainable technologies must be developed to recover VFAs efficiently and allow their beneficial use. In this paper, a comprehensive review of VFAs recovery/purification methods is provided, with focus on membrane-based processes. First, the VFAs production methods, application, and conventional processes (distillation, precipitation, adsorption, and extraction) for their recovery are briefly reviewed. Then, the ability of various membrane-based techniques to separate and purify VFAs are evaluated and discussed in detail. This discussion includes the processes of microfiltration/ultrafiltration, nanofiltration, reverse osmosis, forward osmosis, membrane distillation, electrodialysis, membrane contractor, and pervapo- ration. Extensive background and examples of applications are also provided to show the effectiveness of membrane processes. Finally, challenges and future research directions are highlighted

Recent advances in functionalized polymer membranes for biofouling control and mitigation in forward osmosis

Forward osmosis (FO) is an osmotically driven process widely studied for water desalination, wastewater treatment, and water reuse, as well as dilution and concentration of aqueous streams. However, its application is still hampered by the lack of ideal draw solutes, high-performance membranes, and fouling/biofouling. Biofouling is particularly challenging when FO is applied for seawater desalination and wastewater treatment. Over the last decade, many attempts have been made to exploit advances in materials science to obtain membranes with anti-biofouling properties to prevent or to reduce the detrimental effects of this phenomenon. In this review, we address the various approaches of membrane surface functionalization for biofouling control and mitigation. Recent developments in surface modification of thin-film composite and asymmetric membranes using surface coating, surface functionalization, and incorporation of tailored materials for biofouling control in FO are critically discussed. The future perspectives of anti-biofouling materials and FO membranes are reviewed to shed light on the future research directions for developing the true potential surface modification approach for the FO process