Detection of Malicious Profiles and Protecting Users in Online Social Networks

Wireless Personal Communications - Everyone today actively uses online social networks to get in touch with their friends, for career opportunities, and business also. Some of the most popular...     

Design of backpropagated neurocomputing paradigm for Stuxnet virus dynamics in control infrastructure

Neural Computing and Applications - In the present study, a novel application of backpropagated neurocomputing heuristics (BNCH) is presented for epidemic virus model that portrays the Stuxnet...     

Cryorolling and warm forming of AA6061 aluminum alloy sheets

Cryorolling is a severe plastic deformation (SPD) process used to obtain ultrafine-grained aluminum alloy sheets along with higher strength and hardness than in conventional cold rolling, but it results in poor formability. An alternative method to improve both strength and formability of cryorolled sheets by warm forming after cryorolling without any post-heat treatment is proposed in this work. The formability of cryorolled AA6061 Al alloy sheets in the warm working temperature range is characterized in terms of forming limit diagrams (FLDs) and limiting dome height (LDH). Strain distributions and thinning in biaxially stretched samples are studied. Hardness of the formed samples is correlated with ultimate tensile strength to estimate post-forming mechanical properties. The limit strains and LDH have been found to be higher than in the case of the conventional processing route (cold rolled, annealed and formed at room temperature), making this hybrid route capable of producing sheet metal parts of aluminum alloys with high strength and formability. In order to combine the advantages of enhanced formability and better post-forming strength than the conventional cold rolled and annealed sheets, warm forming at 250°C has been found to be suitable for this alloy in the temperature range that has been studied.     

Laser-treated austenitic steel and nickel alloy for human implants

The recent research in biocompatible materials has been useful in replacing and supporting the fractured natural human bones/joints. Under some condition, negative reaction like release of ions from the bare metal toward the human body fluid leads to corrosion. In this proposed research paper, the biocompatibility of the laser surface-modified austenitic stainless steel (SS316L) and nickel-based superalloy (Inconel 718) was studied. The investigation on laser-modified surfaces is evaluated through electrochemical polarization analysis using simulated body fluid (SBF). The samples subjected to electrochemical polarization analysis were characterized by optical image analysis, SEM, EDS, and XRD analysis. It was inferred that laser surface-modified materials provided enhanced corrosion resistance and bare nickel alloy is more susceptible to corrosion by SBF.     

Extranasal Staphylococcus aureus colonization predisposes to bloodstream infections in patients on hemodialysis with noncuffed internal jugular vein catheters

Introduction: Staphylococcal infection of endogenous origin is an important cause of morbidity and mortality in patients who receive hemodialysis (HD). The risk of such infections in nasal carriers of the organism is well defined. Extranasal carriage of the organism at extranasal sites may pose similar risks. Methods: A total of 70 patients about to undergo internal jugular vein catheterization for HD were enrolled in this prospective observational study. Swab cultures were obtained from anterior nares, posterior pharynx, axillae, toe web spaces, and vascular access sites at baseline and 1 week later. A patient was defined as a persistent carrier when the same organism was grown in both samples. Staphylococcus aureus bloodstream infections were assessed by blood and catheter tip cultures over a 90‐day period. Findings: The mean age of the patients was 43.71 ± 16.2 years. Persistent S. aureus carriage at anterior nares, throat, axilla, toe web spaces, vascular access site, and all sites was documented in 27.9%, 11.4%, 40%, 32.9%, 4.3%, and 64.2% of patients, respectively. Fifteen patients developed S. aureus infections. Catheter related S. aureus infections (CRI) were more likely in persistent carriers than nonpersistent carriers with odds ratios (95% CI) of 10.2 (2.8–37.1), 8.6 (1.7–42.2), 17.3 (3.4–86.0), 3.0 (0.9–9.8), and 1.9 (0.2–22.4) for anterior nares, throat, axilla, toe web spaces, and vascular access site carriers, respectively. The probability of developing CRI in persistent S. aureus carriers was 55% compared to none in noncarriers at 90 days (P = 0.04). Discussion: Extranasal S. aureus carriage is as significant a risk factor as nasal carriage for staphylococcal infections in patients on HD through catheters. The study is limited by lack of molecular phenotyping.     

Utility of 18 F‐FDG PET/CT scan to diagnose the etiology of fever of unknown origin in patients on dialysis

Introduction: Studies on fever of unknown origin (FUO) in patients of chronic kidney disease and end stage renal disease patients on dialysis were not many. In this study, we used 18 F‐FDG PET/CT scan whole body survey for detection of hidden infection, in patients on dialysis, labelled as FUO. Methods: In this retrospective study, 20 patients of end stage renal disease on dialysis were investigated for the cause of FUO using 18F‐FDG PET/CT scan. All these patients satisfied the definition of FUO as defined by Petersdorf and Beeson. Any focal abnormal site of increased FDG concentration detected by PET/CT, either a solitary or multiple lesions was documented and at least one of the detected abnormal sites of radio tracer concentration was further examined for histopathology. Findings: All patients were on renal replacement therapy. Of these, 18 were on hemodialysis and two were on peritoneal dialysis. 18F‐FDG PET/CT scan showed metabolically active lesions in 15 patients and metabolically quiescent in five patients. After 18F‐FDG PET/CT scan all, but one patient had a change in treatment for fever. Anti‐tuberculous treatment was given in 15 patients, antibiotics in four patients and anti‐malaria treatment in one patient. Discussion: The present study is first study of 18F‐FDG PET/CT scan in patients of end stage renal disease on dialysis with FUO. The study showed that the 18 F FDG PET/CT scan may present an opportunity to attain the diagnosis in end stage renal disease patients on dialysis with FUO.     

Substitution Effects on Rare-Earth Ions-Doped Nickel-Zinc Ferrite Nanoparticles

Rare-earth ions (RE³⁺)-doped Ni-Zn ferrite nanoparticles with a structural formula of Ni_0.5Zn_0.5Fe_1.8RE_0.2O₄ (RE³⁺ = Nd, Ce, La and Pr) were synthesized at room temperature by a sol-gel auto-combustion method. The structural and magnetic properties of Ni-Zn ferrite samples were carried out by XRD, vibrating sample magnetometer (VSM), field emission scanning electron microscopy (FE-SEM) and FT-IR spectroscopy. XRD pattern of Ni-Zn ferrite revealed that all the diffraction planes are in agreement with cubic spinel phase and the addition of Fe₂O₃ phase was also observed. In the case of RE ions-doped Ni-Zn ferrite in addition to the Fe₂O₃ phase, very low intensity peaks corresponding to some secondary phase are also present. The average crystallite sizes were found to be from 42 to 56 nm using the Scherer formula. The lattice constant (a) values are gradually decreased from 8.378 to 8.349 Å with different substitutions of RE³⁺ ions in the Ni-Zn ferrite samples. VSM analysis revealed that saturation magnetization values are decreased and coercivity values are increased with substitution of different RE³⁺ ions. FE-SEM images exhibits that particles are spherical in shape. FT-IR interpretation revealed that two main metal oxygen bands (564 and 411 cm^?1) are observed in all the substituted Ni-Zn ferrite samples.     

Automated detection of glioblastoma tumor in brain magnetic imaging using ANFIS classifier

This article proposes a novel and efficient methodology for the detection of Glioblastoma tumor in brain MRI images. The proposed method consists of the following stages as preprocessing, Non‐subsampled Contourlet transform (NSCT), feature extraction and Adaptive neuro fuzzy inference system classification. Euclidean direction algorithm is used to remove the impulse noise from the brain image during image acquisition process. NSCT decomposes the denoised brain image into approximation bands and high frequency bands. The features mean, standard deviation and energy are computed for the extracted coefficients and given to the input of the classifier. The classifier classifies the brain MRI image into normal or Glioblastoma tumor image based on the feature set. The proposed system achieves 99.8% sensitivity, 99.7% specificity, and 99.8% accuracy with respect to the ground truth images available in the dataset.     

Intrusion Detection Based on Bidirectional Long Short-Term Memory with Attention Mechanism

With the recent developments in the Internet of Things (IoT), the amount of data collected has expanded tremendously, resulting in a higher demand for data storage, computational capacity, and real-time processing capabilities. Cloud computing has traditionally played an important role in establishing IoT. However, fog computing has recently emerged as a new field complementing cloud computing due to its enhanced mobility, location awareness, heterogeneity, scalability, low latency, and geographic distribution. However, IoT networks are vulnerable to unwanted assaults because of their open and shared nature. As a result, various fog computing-based security models that protect IoT networks have been developed. A distributed architecture based on an intrusion detection system (IDS) ensures that a dynamic, scalable IoT environment with the ability to disperse centralized tasks to local fog nodes and which successfully detects advanced malicious threats is available. In this study, we examined the time-related aspects of network traffic data. We presented an intrusion detection model based on a two-layered bidirectional long short-term memory (Bi-LSTM) with an attention mechanism for traffic data classification verified on the UNSW-NB15 benchmark dataset. We showed that the suggested model outperformed numerous leading-edge Network IDS that used machine learning models in terms of accuracy, precision, recall and F1 score.     

Fractional Order Nonlinear Bone Remodeling Dynamics Using the Supervised Neural Network

This study aims to solve the nonlinear fractional-order mathematical model (FOMM) by using the normal and dysregulated bone remodeling of the myeloma bone disease (MBD). For the more precise performance of the model, fractional-order derivatives have been used to solve the disease model numerically. The FOMM is preliminarily designed to focus on the critical interactions between bone resorption or osteoclasts (OC) and bone formation or osteoblasts (OB). The connections of OC and OB are represented by a nonlinear differential system based on the cellular components, which depict stable fluctuation in the usual bone case and unstable fluctuation through the MBD. Untreated myeloma causes by increasing the OC and reducing the osteoblasts, resulting in net bone waste the tumor growth. The solutions of the FOMM will be provided by using the stochastic framework based on the Levenberg-Marquardt backpropagation (LVMBP) neural networks (NN), i.e., LVMBPNN. The mathematical performances of three variations of the fractional-order derivative based on the nonlinear disease model using the LVMPNN. The static structural performances are 82% for investigation and 9% for both learning and certification. The performances of the LVMBPNN are authenticated by using the results of the Adams-Bashforth-Moulton mechanism. To accomplish the capability, steadiness, accuracy, and ability of the LVMBPNN, the performances of the error histograms (EHs), mean square error (MSE), recurrence, and state transitions (STs) will be provided.