Effective prediction and resource allocation method (EPRAM) in fog computing environment for smart healthcare system

Multimedia Tools and Applications - Recently, many concepts in technology has been changed. According to the digital transformation trends, Internet of Things (IoT) represents an interested...     

Some picture fuzzy Bonferroni mean operators with their application to multicriteria decision making

In this paper, we extend the Bonferroni mean (BM) operator with the picture fuzzy numbers (PFNs) to propose novel picture fuzzy aggregation operators and demonstrate their application to multicriteria decision making (MCDM). On the basis of the algebraic operational rules of PFNs and BM, we introduce some aggregation operators: the picture fuzzy Bonferroni mean, the picture fuzzy normalized weighted Bonferroni mean, and the picture fuzzy ordered weighted Bonferroni mean. Then, a new picture fuzzy MCDM method is proposed with the help of the proposed operators. Lastly, a practical application of proposed model is given to verify the developed model and related results of the proposed model is compared with the results of the existing models to indicate its applicability.     

Flexible poly(styrene-ethylene-butadiene-styrene) hybrid nanofibers for bioengineering and water filtration applications

Among the thermoplastic elastomers that play important roles in the polymer industry due to their superior properties, styrene-based species and polyurethane block copolymers are of great interest. Poly(styrene-ethylene-butadiene-styrene) (SEBS) as a triblock copolymer seems to have the potential to meet many demands in different applications due to various industrial requirements where durability, biocompatibility, breaking elongation, and interfacial adhesion are important. In this study, the SEBS triblock copolymer was functionalized with natural (Satureja hortensis, SH) and synthetic (nanopowder, TiO₂) agents to obtain composite nanofibers by electrospinning and electrospraying methods for use in biomedical and water filtration applications. The results were compared with thermoplastic polyurethane (TPU) composite nanofibers, which are commonly used in these fields. Here, functionalized SEBS nanofibers exhibited antibacterial effect while at the same time improving cell viability. In addition, because of successful water filtration by using the SEBS composite nanofibers, the material may have a good potential to be used comparably to TPU for the application.     

Purification,structural data and biological properties of polysaccharide from Prunus amygdalus gum

This work demonstrates the efficiency of almond gum polysaccharides (AGPs) as bioactive compounds. AGPs were first extracted using H₂O₂, in the presence of NaOH, at different times and temperatures. The optimal extraction conditions were 4% H₂O₂ and 2 N NaOH, for 7 h at 50 °C, leading to an extraction yield of 58.2% (w/w). After a purification step, the retained AGPs were characterised using high‐performance liquid chromatography showing a molecular weight of 99.3 kDa. The monosaccharide composition of AGPs were assessed using gas chromatography–mass spectrometry. AGPs were found to be a complex heteropolysaccharide with a repeating unit mainly composed of galactose, arabinose, xylose, mannose, rhamnose, and glucuronic acid with the respective ratios: 45:26:7:10:1:11. The acidic nature of the polysaccharide is due to the presence of glucuronic acid. Total antioxidant activity, free radical‐scavenging activity and reducing power assay of AGPs were investigated. The obtained results showed high antioxidant activities of AGPs. Furthermore, beyond 60 mg mL^?1, AGPs exhibited bacterial growth inhibition for five pathogenic strains: Escherichia coli, Staphylococcus aureus, Enterococcus feacalis, Pseudomonas aeruginosa and Salmonella typhimurium.     

Biodegradation of low‐density polyethylene/thermoplastic starch foams before and after electron beam irradiation

Foamy low‐density polyethylene/plasticized starch (LDPE/PLST) blends at different compositions were produced in the presence of azodicarbonamide (ACA) compound as foaming agent. The LDPE/PLST blends before and after electron beam irradiation were investigated in terms of mechanical properties, bulk density, and structure morphology. Moreover, the biodegradability of these materials was evaluated by the soil burial test for 2 months, in which the buried sheets were also examined by scanning electron microscopy (SEM). The results showed that the increase of PLST content from 24 to 30% was accompanied by a decrease in the yield and break stresses of 10 and 20% for the unirradiated blends without the foaming agent, respectively. Further decrease in these mechanical parameters was observed after the foaming process. The bulk density, void fraction, cell size measurements as well as the examination by SEM illustrate clearly the cell growth of the foam structure. The soil burial test and SEM micrographs indicate the growth of microorganisms overall the blend sheets and that the blend was completely damaged after two months of burying. © 2007 Wiley Periodicals, Inc. J Appl Polym Sci 2007     

Chlorophyll adsorption on acid-activated clay

An acid-activated clay (Çanakkale montmorillonite from Turkey) was used to adsorb chlorophyll from hexane solutions. The phenomenon seems to be mainly driven by the interaction of chlorophyll with acid sites. The adsorption of chlorophyll on Brönsted acid sites was indicated by a characteristic infrared band for the -OH group at 3671 cm^?1. The variations in the structure of clay mineral and chlorophyll during adsorption have been examined by differential thermal analysis, thermogravimetry and infrared spectroscopy of the activated clay before and after adsorption of chlorophyll. Oxidation of adsorbed chlorophyll was completed at quite a high temperature.     

A statistical framework for few-shot action recognition

Along with the exponential growth of online video creation platforms such as Tik Tok and Instagram, state of the art research involving quick and effective action/gesture recognition remains crucial. This work addresses the challenge of classifying short video clips, using a domain-specific feature design approach, capable of performing significantly well using as little as one training example per action. The method is based on Gunner Farneback’s dense optical flow (GF-OF) estimation strategy, Gaussian mixture models, and information divergence. We first aim to obtain accurate representations of the human movements/actions by clustering the results given by GF-OF using K-means method of vector quantization. We then proceed by representing the result of one instance of each action by a Gaussian mixture model. Furthermore, using Kullback-Leibler divergence (KL-divergence), we attempt to find similarities between the trained actions and the ones in the test videos. Classification is done by matching each test video to the trained action with the highest similarity (a.k.a lowest KL-divergence). We have performed experiments on the KTH and Weizmann Human Action datasets using One-Shot and K-Shot learning approaches, and the results reveal the discriminative nature of our proposed methodology in comparison with state-of-the-art techniques.