On the Role of C Addition on α Precipitation in a β Titanium Alloy

The onset of α nucleation in a carbon containing β-titanium alloy has been investigated by coupling atom probe tomography (APT) with transmission electron microscopy. The analysis of the APT results indicates that in addition to ω precipitates that can act as potential α nucleation sites, carbon atoms tend to form clusters within the β-matrix, which in turn give rise to additional nucleation sites for α, resulting in finer scale α precipitates due to increased nucleation density.     

Crispatotrochus-mimicking coatings improve the flexural properties of organic fibres

This brief communication describes the application and utility of thin film coral-mimetic coatings to natural fibres and provides quantitative values for the actual enhancement of their flexural properties.     

Training neural networks using Central Force Optimization and Particle Swarm Optimization: Insights and comparisons

Central Force Optimization (CFO) is a novel and upcoming metaheuristic technique that is based upon physical kinematics. It has previously been demonstrated that CFO is effective when compared with other metaheuristic techniques when applied to multiple benchmark problems and some real world applications. This work applies the CFO algorithm to training neural networks for data classification. As a proof of concept, the CFO algorithm is first applied to train a basic neural network that represents the logical XOR function. This work is then extended to train two different neural networks in order to properly classify members of the Iris data set. These results are compared and contrasted to results gathered using Particle Swarm Optimization (PSO) in the same applications. Similarities and differences between CFO and PSO are also explored in the areas of algorithm design, computational complexity, and natural basis. The paper concludes that CFO is a novel and promising meta-heuristic that is competitive with if not superior to the PSO algorithm, and there is much room to further improve it.     

Novel superabsorbent materials from bacterial cellulose

A novel process for the production of superabsorbent materials (hydrogels) from bacterial cellulose (BC) was developed. Prior to crosslinking with a water‐soluble polyethylene glycol diacrylate (PEGDA), BC was first carboxymethylated and functionalized with glycidyl methacrylate. The degree of crosslinking influenced the swelling properties of the hydrogels. The use of greater amounts of PEGDA enhanced the formation of a thicker macromolecular network containing fewer capillary spaces in the crosslinked gel. The maximum water retention value of the hydrogels containing 2.5–3.5 mmol of carboxyl groups per gram of gel reached 125 g g^?1 in distilled water, and 29 g g^?1 in saline (0.9% NaCl solution). The highly porous hydrogel architecture with a pore size of 350–600 µm created a high specific surface area. This enables rapid mass penetration in superabsorbent applications. The superabsorbent hydrogels reached 80% of their maximum water absorption capacity in 30 min. © 2018 Society of Chemical Industry     

A study on the synthesis,characterization and properties of polyaniline/magnesium boride nanocomposites

The present paper reports the novel synthesis of polyaniline/magnesium boride (PAni/MgB₂) nanocomposites. Nanowires 50–100 nm in diameter grown by the sol–gel technique were incorporated in the PAni to prepare PAni/MgB₂ nanocomposites, which yielded an enhancement of conductivity by 5 orders of magnitude. PAni was synthesized through the chemical oxidative polymerization method. The composition of the prepared nanocomposites was tunable, i.e. the amount of dopant was varied and the effects on various parameters were observed by different techniques. The morphology of PAni/MgB₂ nanocomposites was determined using SEM. The temperature dependence of the conductivity of all composites was measured in the temperature range 300–450 K and it was observed that samples having a high concentration of MgB₂ show the highest conductivity. The molecular structure of the nanocomposites was further characterized by Fourier Transform IR spectroscopy which showed small structural changes in the backbone of PAni. I?V measurements showed that the current increases on increasing MgB₂ content. UV?visible spectra exposed the occurrence of an indirect optical transition in the composite. © 2013 Society of Chemical Industry     

Non-Intrusive Monitoring of Everyday Behavioral Activities in an Indoor Environment

A non-intrusive design for monitoring everyday activities of an elderly person is presented. The proposed system is intended to be used in the bedroom, allowing the elders to stay at home in a safe environment. The required hardware design is simple in structure and cost effective. The sensor design is implemented by using capacitive sensors and an Arduino microcontroller unit. And a real time graphical user interface is implemented to monitor the elderly person. The performance analysis shows that the sensor design is able to differentiate between a human body and a house pet.     

Systematic skin segmentation: merging spatial and non-spatial data

Skin detection is used in applications ranging from face detection, tracking of body parts, hand gesture analysis, to retrieval and blocking objectionable content. We present a systematic approach for robust skin segmentation using graph cuts. The skin segmentation process starts by exploiting the local skin information of detected faces. The detected faces are used as foreground seeds for calculating the foreground weights of the graph. If local skin information is not available, we opt for the universal seed. To increase the robustness, the decision tree based classifier is used to augment the universal seed weights when no local information is available in the image. With this setup, we achieve robust skin segmentation, outperforming off-line trained classifiers. The setup also provides a generic skin detection system, using positive training data only. With face detection, we take advantage of the contextual information present in the scene. With the weight augmentation, we provide a setup for merging spatial and non-spatial data. Experiments on two datasets with annotated pixel-level ground truth show that the systematic skin segmentation approach outperforms other approaches and provides robust skin detection.