A lightweight autonomous MAV for indoor search and rescue

Micro Aerial Vehicles (MAVs) have great potentials to be applied for indoor search and rescue missions. In this paper, we propose a modular lightweight design of an autonomous MAV with integrated hardware and software. The MAV is equipped with the 2D laser scanner, camera, mission computer and flight controller, running all the computation onboard in real time. The onboard perception system includes a laser‐based SLAM module and a custom‐designed visual detection module. A dual Kalman filter design provides robust state estimation by multiple sensor fusion. Specifically, the fusion module provides robust altitude measurement in the circumstance of surface changing. In addition, indoor‐outdoor transition is explicitly handled by the fusion module. In order to efficiently navigate through obstacles and adapt to multiple tasks, a task tree‐based mission planning method is seamlessly integrated with path planning and control modules. The MAV is capable of searching and rescuing victims from unknown indoor environments effectively. It was validated by our award‐winning performance at the 2017 International Micro Air Vehicle Competition (IMAV 2017), held in Toulouse, France. The performance video is available on https://youtu.be/8H19ppS_VXM .     

Deep Learning Based Process Analytics Model for Predicting Type 2 Diabetes Mellitus

Process analytics is one of the popular research domains that advanced in the recent years. Process analytics encompasses identification, monitoring, and improvement of the processes through knowledge extraction from historical data. The evolution of Artificial Intelligence (AI)-enabled Electronic Health Records (EHRs) revolutionized the medical practice. Type 2 Diabetes Mellitus (T2DM) is a syndrome characterized by the lack of insulin secretion. If not diagnosed and managed at early stages, it may produce severe outcomes and at times, death too. Chronic Kidney Disease (CKD) and Coronary Heart Disease (CHD) are the most common, long-term and life-threatening diseases caused by T2DM. Therefore, it becomes inevitable to predict the risks of CKD and CHD in T2DM patients. The current research article presents automated Deep Learning (DL)-based Deep Neural Network (DNN) with Adagrad Optimization Algorithm i.e., DNN-AGOA model to predict CKD and CHD risks in T2DM patients. The paper proposes a risk prediction model for T2DM patients who may develop CKD or CHD. This model helps in alarming both T2DM patients and clinicians in advance. At first, the proposed DNN-AGOA model performs data preprocessing to improve the quality of data and make it compatible for further processing. Besides, a Deep Neural Network (DNN) is employed for feature extraction, after which sigmoid function is used for classification. Further, Adagrad optimizer is applied to improve the performance of DNN model. For experimental validation, benchmark medical datasets were used and the results were validated under several dimensions. The proposed model achieved a maximum precision of 93.99%, recall of 94.63%, specificity of 73.34%, accuracy of 92.58%, and F-score of 94.22%. The results attained through experimentation established that the proposed DNN-AGOA model has good prediction capability over other methods.     

A survey and taxonomy on virtual data center embedding

The Journal of Supercomputing - Data center network virtualization is being considered as a promising technology to provide a performance guarantee for cloud computing applications. One important...     

Fabrication of core–shell nanocomposites with enhanced photocatalytic efficacy

The current study establishes the unprecedented involvement in the evolution and production of novel core–shell nanocomposites composed of nanosized titanium dioxide and aniline‐o‐phenylenediamine copolymer. TiO₂@copoly(aniline and o‐phenylenediamine) (TiO₂@PANI‐o‐PDA) core–shell nanocomposites were chemically synthesized in a molar ratio of 5:1 of the particular monomers and several weights of nano‐TiO₂ via oxidative copolymerization. The construction of the TiO₂@PANI‐o‐PDA core–shell nanocomposites was ascertained from Fourier transform IR spectroscopy, UV–visible spectroscopy and XRD. A reasonable thermal behavior for the original copolymer and the TiO₂@PANI‐o‐PDA core–shell nanocomposites was investigated. The bare PANI‐o‐PDA copolymer was thermally less stable than the TiO₂@PANI‐o‐PDA nanocomposites. The core–shell feature of the nanocomposites was found to have core and shell sizes of 17 nm and 19–26 nm, respectively. In addition, it was found that the addition of a high ratio of TiO₂ nanoparticles increases the electrical conductivity and consequently lowers the electrical resistivity of the TiO₂@PANI‐o‐PDA core–shell nanocomposites. The hybrid photocatalysts exhibit a dramatic photocatalytic efficacy of methylene blue degradation under solar light irradiation. A plausible interpretation of the photocatalytic degradation results of methylene blue is also demonstrated. Our setup introduces a facile, inexpensive, unique and efficient technique for developing new core–shell nanomaterials with various required functionalities and colloidal stabilities. © 2018 Society of Chemical Industry     

A novel binary gaining–sharing knowledge-based optimization algorithm for feature selection

Neural Computing and Applications - To obtain the optimal set of features in feature selection problems is the most challenging and prominent problem in machine learning. Very few human-related...     

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.     

Harmful effects of pyrethroid ester insecticide on the male reproductive system mainly through affecting testicular function and inflammatory markers

Pyrethroid esters are widely used as insecticides worldwide. In this study, we aimed to evaluate the harmful effect of deltamethrin on the male reproductive system through the assessment of reproductive hormones, inflammatory markers, and testicular function. To achieve our aim, eighty male 7-9-week-old, Wistar rats were taken, weighed, and divided into four experimental groups. The first group was kept as a control group, and the other three groups were given deltamethrin orally at different concentrations (0.87, 8.7, and 17.4 mg/kg body weight) for nine weeks. The results indicated that deltamethrin administration associated with a significant decrease in reproductive hormones, especially FSH, LH, and significant elevation in the interleukin 2 (IL2), interleukin 6 (IL6), histamine, and cortisol levels. Also, the significance of inhibition of sperm motility and viability, decreased testis weights, sperm count, and fructose in semen were noted. These findings clarify the harmful effect of deltamethrin on the male reproductive system by producing a significant alteration in reproductive hormones, inflammatory markers as well as testicular function.     

Trend Analysis and Spatial Prediction of Groundwater Levels Using Time Series Forecasting and a Novel Spatio-Temporal Method

Water Resources Management - Overexploitation of groundwater in the Malayer Plain has resulted in a continuous decline of groundwater levels over recent years with associated risks to water...