Ear recognition with feed-forward artificial neural networks

Biometrics has become one of the most important techniques in recognizing a person’s identity. A person’s face, iris and fingerprint are mostly used in biometrics today. It has been established that there are no two ears exactly alike, even in the cases of identical twins. In this paper, we define a 7-element ear feature set and design and train a feed-forward artificial neural network to recognize a human ear. We train and test the network with 51 ear pictures from 51 different persons. Simulation experiments with various networks with various number of layers and number of neurons per layer and with and without noise are conducted. Results indicate that a 95 % ear recognition accuracy is achieved with a simple 3-layer feed-forward neural network with only a total of 18 neurons even in the presence of some noise. This design outstands previous work in simplicity and implementation cost.     

Synthesis and physicochemical investigation of chitosan-built hydrogel with induced glucose sensitivity

There is an urgent need to treat diabetes, and therefore, this work reports on a chitosan-built hydrogel functionalized by a glucose sensing moiety, which simulates pancreatic activity. The effect of external stimuli on various internal properties was investigated to establish the action of the hydrogel. The model drugs, fluorescein (D1) and rhodamine (D2), with a diol architecture, were investigated spectroscopically with 75.94% loading and 65.63% release. Consequently, a ligand to glucose ratio of 2:1 in comparison with a ligand to model drug ratio of 1:1 was addressed. The system was expected to lead to findings on applications for the self-controlled release of insulin in response to blood glucose levels.     

Automated detection of exudates and macula for grading of diabetic macular edema

Medical systems based on state of the art image processing and pattern recognition techniques are very common now a day. These systems are of prime interest to provide basic health care facilities to patients and support to doctors. Diabetic macular edema is one of the retinal abnormalities in which diabetic patient suffers from severe vision loss due to affected macula. It affects the central vision of the person and causes total blindness in severe cases. In this article, we propose an intelligent system for detection and grading of macular edema to assist the ophthalmologists in early and automated detection of the disease. The proposed system consists of a novel method for accurate detection of macula using a detailed feature set and Gaussian mixtures model based classifier. We also present a new hybrid classifier as an ensemble of Gaussian mixture model and support vector machine for improved exudate detection even in the presence of other bright lesions which eventually leads to reliable classification of input retinal image in different stages of macular edema. The statistical analysis and comparative evaluation of proposed system with existing methods are performed on publicly available standard retinal image databases. The proposed system has achieved average value of 97.3%, 95.9% and 96.8% for sensitivity, specificity and accuracy respectively on both databases.     

W-type hexaferrite nanoparticles: A consideration for microwave attenuation at wide frequency band of 0.5-10 GHz

The static and dynamic magnetic properties of W-type hexaferrites are tuned to meet the requirements of wide band frequencies for attenuation of electromagnetic interference and microwave absorptions purposes. For this purpose, the W-type hexaferrite of entirely new composition of BaCoZnFe_16−2yAl_yCe_yO₂₇ (y = 0, 0.2, 0.4, 0.6, 0.8 and 1.0) has been synthesized by the chemical co-precipitation. The material is characterized using X-ray diffraction (XRD), scanning electron microscopy (SEM) and vibrating sample magnetometer (VSM). The complex permittivity (?_r = ?′ − j?″) and permeability (μ_r = μ′ − jμ″) spectra are determined using Vector Network Analyzer (VNA) in a range from 0.5 GHz to 10 GHz. During this study, it is noticeable that the Al³⁺ and Ce³⁺ ions have considerable effect on the shape of the nanoparticles. Samples having Al-Ce contents y = 0.2 and y = 0.4 showed large values for magnetization (70.5 emu/g) and remanent magnetization (32.9 emu/g). In addition, more than 99% absorption (>−20 dB) is noted for this sample composition. Based on these results it is concluded that the microwave absorption characteristics of these compounds can be tuned for the required frequency by varying the thickness of the absorber. Due to this reason, potential employment of the synthesized nanoparticles for absorption of electromagnetic radiations at wide frequency band of 0.5-10 GHz has been proposed.     

Scanning electron microscopy of bio‐fabricated Fe2O3 nanoparticles and their application to control brown rot of citrus

Citrus is the leading fruit crop of Pakistan and exported to different parts of the world. Due to suitable weather condition, this crop is affected by different biotic factors which seriously deteriorate its quality and quantity. During the months of November 2018 to January 2019, citrus brown rot symptoms were recurrently observed on sweet oranges in National Agricultural Research Centre (NARC), Islamabad. Causal agent of citrus brown rot was isolated, characterized, and identified as Fusarium oxysporum. For environment‐friendly control of this disease, leaf extract of Azadirachta indica was used for the green synthesis of iron oxide (Fe₂O₃) nanoparticles. These nanoparticles were characterized before their application for disease control. Fourier transform infrared spectroscopy (FTIR) of these synthesized nanoparticles described the presence of stabilizing and reducing compounds like alcohol, phenol, carboxylic acid, and alkaline and aromatic compounds. X‐Ray diffraction (XRD) analysis revealed the crystalline nature and size (24 nm) of these nanoparticles. Energy dispersive X‐Ray (EDX) analysis elaborated the presence of major elements in the samples. Scanning electron microscopy (SEM) confirmed the spinal shaped morphology of prepared nanoparticles. Successfully synthesized nanoparticles were evaluated for their antifungal potential. Different concentrations of Fe₂O₃ nanoparticles were used and maximum mycelial inhibition was observed at 1.0 mg/ml concentration. On the basis of these findings, it could be concluded that Fe₂O₃ nanoparticles, synthesized in the leaf extract of A. indica, can be successfully used for the control of brown rot of sweet oranges.