ANT-colony based disjoint set assortment in wireless sensor networks

Wireless Networks - Wireless sensor network (WSN) consists of small sized devices containing different sensors to monitor physical, environmental and medical conditions during surveillance of...     

Quasi-static compressive behaviour of aluminium cenosphere syntactic foams

In this paper, cenosphere particles embedded in AA2014 aluminium matrix are used to fabricate syntactic foam by stir casting method. The particle size is about 100?µm and foam density is about 1990?kg?m^?3. Compression tests at strain rate 0.001/s are performed on foam samples to characterise their mechanical properties which are then used in numerical analysis on commercial finite element analysis software ABAQUS/CAE with isotropic elastic-plastic material model. Experimental and numerical results show good conformity in deformation behaviour with elastic and plateau zones showing average deviations less than 5% and 20%, respectively. Foams showed high yield stress and energy absorption capabilities that can be useful in making blast and impact resistant structures.     

Distance and similarity measures of Pythagorean fuzzy sets based on the Hausdorff metric with application to fuzzy TOPSIS

Pythagorean fuzzy sets (PFSs) were proposed by Yager in 2013 to treat imprecise and vague information in daily life more rigorously and efficiently with higher precision than intuitionistic fuzzy sets. In this paper, we construct new distance and similarity measures of PFSs based on the Hausdorff metric. We first develop a method to calculate a distance between PFSs based on the Hasudorff metric, along with proving several properties and theorems. We then consider a generalization of other distance measures, such as the Hamming distance, the Euclidean distance, and their normalized versions. On the basis of the proposed distances for PFSs, we give new similarity measures to compute the similarity degree of PFSs. Some examples related to pattern recognition and linguistic variables are used to validate the proposed distance and similarity measures. Finally, we apply the proposed methods to multicriteria decision-making by constructing a Pythagorean fuzzy Technique for Order Preference by Similarity to an Ideal Solution and then present a practical example to address an important issue related to social sector. Numerical results indicate that the proposed methods are reasonable and applicable and also that they are well suited in pattern recognition, linguistic variables, and multicriteria decision-making with PFSs.     

Microscopic melanoma detection and classification: A framework of pixel‐based fusion and multilevel features reduction

The numbers of diagnosed patients by melanoma are drastic and contribute more deaths annually among young peoples. An approximately 192,310 new cases of skin cancer are diagnosed in 2019, which shows the importance of automated systems for the diagnosis process. Accordingly, this article presents an automated method for skin lesions detection and recognition using pixel‐based seed segmented images fusion and multilevel features reduction. The proposed method involves four key steps: (a) mean‐based function is implemented and fed input to top‐hat and bottom‐hat filters which later fused for contrast stretching, (b) seed region growing and graph‐cut method‐based lesion segmentation and fused both segmented lesions through pixel‐based fusion, (c) multilevel features such as histogram oriented gradient (HOG), speeded up robust features (SURF), and color are extracted and simple concatenation is performed, and (d) finally variance precise entropy‐based features reduction and classification through SVM via cubic kernel function. Two different experiments are performed for the evaluation of this method. The segmentation performance is evaluated on PH2, ISBI2016, and ISIC2017 with an accuracy of 95.86, 94.79, and 94.92%, respectively. The classification performance is evaluated on PH2 and ISBI2016 dataset with an accuracy of 98.20 and 95.42%, respectively. The results of the proposed automated systems are outstanding as compared to the current techniques reported in state of art, which demonstrate the validity of the proposed method.     

Investigation on material mixing during FSW of AA7475 to AISI304

AA7xxx and AISI304 stainless steel (SS) are employed in promising applications. Al alloy-to-SS dissimilar joining is difficult and challenging. Major challenge in the joining of these alloys is the difficulty in mixing of these materials which possess exotic and widely distant properties. AA7475-T761 is a high strength aluminum alloy which is used in key aircraft components. Maiden AA7475-T761 and AISI304 dissimilar joints were fabricated using friction stir welding. Welding was performed with tool having pin diameter of 4 mm and offset of 1.25 mm on Aluminum side. Tool rotational speed, traverse speed and shoulder diameter were varied in the range of 450–560 rpm, 50–63 mm/min, and 12–14 mm, respectively. Mechanical tests showed that joint formed with 14 mm diameter, 560 rpm and 50 mm/min gave the best joint efficiency of 71% of Al-alloy at 7.31% elongation. The materials mixing issues during processing were analyzed with SEM mircrostructure and fractography. Metallography also revealed that offset is critical to the success of joint as it controlled effective mixing of SS and Al in 15 and 85 vol.%, respectively. SS fragments from thermo-mechanically affected zone of SS were found to be partially sheared forming layer of thickness equal to tool traverse/revolution ratio.     

Egg white proteins and β-cyclodextrin: effective cryoprotectant mixture against oxidative changes in the myofibrillar proteins of Culter alburnus

The effect of egg white protein (EWP) and β-cyclodextrin (β-CD) mixture was analysed on the myofibrillar proteins (MP) of Culter alburnus during a frozen storage at −18 °C for 60 days. Different proportions of EWP:β-CD mixture (0%, 2%, 4% and 6%) were added into MP to analyse their effect against oxidative changes. During the study, sulphydryl contents and Ca-ATPase activity (0.297 to 0.136 mmol g⁻¹) decreased. Moreover, protein denaturation also prompted the surface hydrophobicity (11.47 to 32.06 μg) and carbonyls (26.36 to 49 mg.28 nmol mg⁻¹) of control MP. A significant decline was observed in emulsifying properties. Besides, EWP:β-CD showed remarkable stability against oxidative changes, by significantly reducing the carbonyls (26.26 to 37.69 nmol mg⁻¹) and surface hydrophobicity (11.51 to 20.31 μg) and also the decline of Ca-ATPase activity (0.29 to 0.19 mmol g⁻¹). It can be concluded that EWP:β-CD (6%) is an efficient approach against oxidative changes in MP from Culter alburnus.     

Simultaneously achievement of high recoverable energy density and efficiency in sodium niobate-based ceramics

Journal of Materials Science: Materials in Electronics - Single lead-free Na0.73Bi0.09(Nb1???xTax)O3 (x?=?0, 0.10, 0.20, 0.30, and 0.40) ceramic phases were processed...     

Selection of optimal denoising-based regularization hyper-parameters for performance improvement in a sensor validation model

Multilayered auto-associative neural architectures have widely been used in empirical sensor modeling. Typically, such empirical sensor models are used in sensor calibration and fault monitoring systems. However, simultaneous optimization of related performance metrics, i.e., auto-sensitivity, cross-sensitivity, and fault-detectability, is not a trivial task. Learning procedures for parametric and other relevant non-parametric empirical models are sensitive to optimization and regularization methods. Therefore, there is a need for active learning strategies that can better exploit the underlying statistical structure among input sensors and are simple to regularize and fine-tune. To this end, we investigated the greedy layer-wise learning strategy and denoising-based regularization procedure for sensor model optimization. We further explored the effects of denoising-based regularization hyper-parameters such as noise-type and noise-level on sensor model performance and suggested optimal settings through rigorous experimentation. A visualization procedure was introduced to obtain insight into the internal semantics of the learned model. These visualizations allowed us to suggest an implicit noise-generating process for efficient regularization in higher-order layers. We found that the greedy-learning procedure improved the overall robustness of the sensor model. To keep experimentation unbiased and immune to noise-related artifacts in real sensors, the sensor data were sampled from simulators of a nuclear steam supply system of a pressurized water reactor and a Tennessee Eastman chemical process. Finally, we compared the performance of an optimally regularized sensor model with auto-associative neural network, auto-associative kernel regression, and fuzzy similarity-based sensor models.     

Banana peel: an effective biosorbent for aflatoxins

This work reports the application of banana peel as a novel bioadsorbent for in vitro removal of five mycotoxins (aflatoxins (AFB1, AFB2, AFG1, AFG2) and ochratoxin A). The effect of operational parameters including initial pH, adsorbent dose, contact time and temperature were studied in batch adsorption experiments. Scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR) and point of zero charge (pH_pzc) analysis were used to characterise the adsorbent material. Aflatoxins’ adsorption equilibrium was achieved in 15 min, with highest adsorption at alkaline pH (6–8), while ochratoxin has not shown any significant adsorption due to surface charge repulsion. The experimental equilibrium data were tested by Langmuir, Freundlich and Hill isotherms. The Langmuir isotherm was found to be the best fitted model for aflatoxins, and the maximum monolayer coverage (Q₀) was determined to be 8.4, 9.5, 0.4 and 1.1 ng mg^?1 for AFB1, AFB2, AFG1 and AFG2 respectively. Thermodynamic parameters including changes in free energy (ΔG), enthalpy (ΔH) and entropy (ΔS) were determined for the four aflatoxins. Free energy change and enthalpy change demonstrated that the adsorption process was exothermic and spontaneous. Adsorption and desorption study at different pH further demonstrated that the sorption of toxins was strong enough to sustain pH changes that would be experienced in the gastrointestinal tract. This study suggests that biosorption of aflatoxins by dried banana peel may be an effective low-cost decontamination method for incorporation in animal feed diets.