Hall effect on unsteady Hartmann flow with heat transfer under exponential decaying pressure gradient

The unsteady Hartmann flow of an electrically conducting, viscous, incompressible fluid bounded by two parallel non-conducting porous plates is studied with heat transfer taking the Hall effect into consideration. An external uniform magnetic field and a uniform suction and injection are applied perpendicular to the plates while the fluid motion is subjected to an exponential decaying pressure gradient. The two plates are kept at different but constant temperatures while the Joule and viscous dissipations are included in the energy equation. The effect of the ion slip and the uniform suction and injection on both the velocity and temperature distributions is examined. On leave from: Department of Engineering Mathematics and physics, Fac. of Engineering, El-Fayoum University, El-Fayoum, Egypt.     

Self‐Assembly of Mechanoplasmonic Bacterial Cellulose–Metal Nanoparticle Composites

Nanocomposites of metal nanoparticles (NPs) and bacterial nanocellulose (BC) enable fabrication of soft and biocompatible materials for optical, catalytic, electronic, and biomedical applications. Current BC–NP nanocomposites are typically prepared by in situ synthesis of the NPs or electrostatic adsorption of surface functionalized NPs, which limits possibilities to control and tune NP size, shape, concentration, and surface chemistry and influences the properties and performance of the materials. Here a self‐assembly strategy is described for fabrication of complex and well‐defined BC–NP composites using colloidal gold and silver NPs of different sizes, shapes, and concentrations. The self‐assembly process results in nanocomposites with distinct biophysical and optical properties. In addition to antibacterial materials and materials with excellent senor performance, materials with unique mechanoplasmonic properties are developed. The homogenous incorporation of plasmonic gold NPs in the BC enables extensive modulation of the optical properties by mechanical stimuli. Compression gives rise to near‐field coupling between adsorbed NPs, resulting in tunable spectral variations and enhanced broadband absorption that amplify both nonlinear optical and thermoplasmonic effects and enables novel biosensing strategies.     

Incremental Learning Framework for Mining Big Data Stream

At this current time, data stream classification plays a key role in big data analytics due to its enormous growth. Most of the existing classification methods used ensemble learning, which is trustworthy but these methods are not effective to face the issues of learning from imbalanced big data, it also supposes that all data are pre-classified. Another weakness of current methods is that it takes a long evaluation time when the target data stream contains a high number of features. The main objective of this research is to develop a new method for incremental learning based on the proposed ant lion fuzzy-generative adversarial network model. The proposed model is implemented in spark architecture. For each data stream, the class output is computed at slave nodes by training a generative adversarial network with the back propagation error based on fuzzy bound computation. This method overcomes the limitations of existing methods as it can classify data streams that are slightly or completely unlabeled data and providing high scalability and efficiency. The results show that the proposed model outperforms state-of-the-art performance in terms of accuracy (0.861) precision (0.9328) and minimal MSE (0.0416).     

A multifractal edge detector

Multimedia Tools and Applications - Significant research has been conducted into image edge detection, usually focusing on gradient and higher order derivative approaches. Recent development in the...     

A pair-mode model for underwater single image enhancement

Enhancing underwater images is a challenging problem owing to light scattering and absorption in underwater environments. Such environments provoke several combined degradations in images including color attenuation, blurring and low contrast. Using image processing techniques to enhance this kind of image remains very attractive because of its low-cost of implementation and typically its small number of parameters when compared to more complex learning techniques. This paper proposes an image processing model which first, analyses the color characteristics of the degraded image. Second, decides about the suitable enhancement steps (i.e., mode of operation) to be performed. It operates in two modes (mode-1 and mode-2), both of which investigate a combination of contrast and chromaticity enhancement techniques. The proposed model was tested on 5141 images collected from various, well-known datasets. It was evaluated using eight different measures, some of which are reference-based, and the rest are blind-based. A set of qualitative and quantitative comparisons was conducted, applying more than 20 methods varying between image processing and deep learning. Besides its efficiency and simplicity, the proposed model demonstrates an ability to achieve good contrast ranges, natural-looking colors, and superior or equivalent quality enhancements when compared to other methods.

     

Kinematic analysis of the multi-link five-point suspension system in point coordinates

In this paper, a numerical algorithm for the kinematic analysis of a multi-link five-point suspension system is presented. The kinematic analysis is carried out in terms of the rectangular Cartesian coordinates of some defined points in the links and at the joints. Geometric constraints are introduced to fix the relative positions between the points belonging to the same rigid body. Position, velocity and acceleration analyses are carried out. The presented formulation in terms of this system of coordinates is simple and involves only elementary mathematics. The results of the kinematic analysis are presented and discussed.     

Acoustic of monolithic dome structures

Monolithic dome structures were built in the 1970s in Europe and America. These dome structures share common benefits of being cost-efficient, earth-friendly, extremely durable, and easily maintained. Monolithic shells are easily constructed and are extremely cost-effective. Monolithic domes respond efficiently to any climate, even to extremely cold or hot temperatures. In terms of utility savings, monolithic domes can cut electricity consumption by up to one-third, thereby saving 60–70% of total energy costs. Moreover, monolithic structures provide the highest survivability rates from destructions. The interior of monolithic domes have perfect, concave shapes to ensure that sound travels through the dome and perfectly collected at different vocal points. These dome structures are utilized for domestic use because the scale allows the focal points to be positioned across daily life activities, thereby affecting the soni ccomfort of the internal space. This study examines the various acoustic treatments and parametric configurations of monolithic dome sizes. A geometric relationship of acoustic treatment and dome radius is established to provide architects guidelines on the correct selection of absorption needed to maintain the acoustic comfort of these special spaces.     

Stabilization of refined olive oil by enrichment with chlorophyll pigments extracted from Chemlali olive leaves

This paper presents the first investigation on the effect of enrichment refined olive oil by chlorophyll pigment extracted from Chemlali olive leaves during storage (6 months). The changes that occurred in the quality indices, fatty acids, sterol, and phenolic content were investigated during the storage of refined olive oil under RT (20°C) and accelerated conditions (50°C) in the dark. Additionally, the pigments (chlorophyll and carotene) changes during 6 months of oil storage were evaluated. At the end of the storage, more than 90% of chlorophyll pigments decomposed in all samples, while, carotene pigment loss was lower showing up to 60 and 85% loss for oil stored at 20 and 50°C, respectively, at the end of storage. The reduction of total phenolic compounds exhibited similar degradation profiles, being reduced by 5% and up to 60% for the enriched refined olive oil stored at 20 and 50°C in 6 months, respectively. In the fatty acid composition, an increase in oleic acid and a decrease in linoleic and linolenic acids were less significant in enriched than non‐enriched refined olive oil. On the other hand, sterol composition was less affected by storage in enriched oil samples. However, the sterol concentration of the oil samples showed an increase in β‐sitosterol, 24‐methylene cholesterol, stigmasterol, and a decrease in cholesterol, Δ5, 24‐stigmastadienol percentage at the end of storage. Based on the Rancimat method, the oils with added leaf pigment extract had the lowest peroxide value and the highest stability. After 6 months of storage, the oxidative resistance of refined olive oil fell to 0.2 and to zero for enriched refined olive oil stored at 20 and 50°C, respectively.     

Extra-Virgin Olive Oil and Cheap Vegetable Oils: Distinction and Detection of Adulteration as Determined by GC and Chemometrics

Refined oils including corn, sunflower, soybean, and palm oils as well as low-quality olive oil such as refined lampante and pomace olive oils are commonly used for extra-virgin olive oil (EVOO) adulteration. Indeed, K ₂₇₀ could be used as a parameter for the detection of EVOO fraud for each type of the studied refined oils, 10 % olive, 4 % pomace olive, 10 % palm, 5 % corn, and 2 % soybean oils. Moreover, the adulteration could also be detected by the increase of the trans fatty acid contents with 10 % pomace olive, 3 % soybean, 3 % sunflower, 2 % corn, and 10 % palm oils. Actually, stigmasta-3,5-diene content is one of the most effective means of detecting refined oils in EVOO at low levels: 2 % olive, 0.4 % pomace olive, 1 % palm, 0.2 % soybean, 0.5 % sunflower, and 0.1 % corn oils. Finally, the application of linear discriminant analysis could represent an alternative and innovative tool for faster and cheaper evaluation of EVOO adulteration.     

Development of novel potentiometric sensors for determination of tartrazine dye concentration in foodstuff products

Tartrazine dye Na₃TZ in foodstuff products was determined by a new modified carbon paste electrode, encoded sensor A, and a coated silver wire electrode, encoded sensor B, based on tartrazine TZ- cetryltrimethyl ammoniumbromide CTAB as a chemical modifier TZ-CTA. The electrodes exhibit the following characteristics listed respectively: a Nernstian slope of 17.9 ± 0.5 and 19.4 ± 0.2 mV/decade for tartrazine ion over a wide concentration range from 4.3 × 10⁻⁷ to 1.0 × 10⁻² and 1.1 × 10⁻⁷ to 1.0 × 10⁻² M. The lower detection limits: 3.2 × 10⁻⁷ and 5.5 × 10⁻⁸ M. Short response time (5–8 s) over the pH range 3.8–7.7 and 4.2–8.1. The proposed sensors display significantly high selectivity for TZ ion over a wide variety of sugars, some anions, common organic, inorganic compounds and additives. The developed electrodes were applied to the potentiometric determination of tartrazine ion in different kinds of foodstuffs: solid jelly (strawberry and custard) powder samples and soft drink (orange) samples with satisfactory results.