A new high accuracy method for two-dimensional biharmonic equation with nonlinear third derivative terms: application to Navier–Stokes equations of motion

In this paper, we propose a new compact fourth-order accurate method for solving the two-dimensional fourth-order elliptic boundary value problem with third-order nonlinear derivative terms. We use only 9-point single computational cell in the scheme. The proposed method is then employed to solve Navier–Stokes equations of motion in terms of streamfunction–velocity formulation, and the lid-driven square cavity problem. We describe the derivation of the method in details and also discuss how our streamfunction–velocity formulation is able to handle boundary conditions in terms of normal derivatives. Numerical results show that the proposed method enables us to obtain oscillation-free high accuracy solution.     

A ubiquitous mobile communication architecture for next-generation heterogeneous wireless systems

Rapid progress in research and development of wireless networking and communication technologies have created different types of wireless systems (e.g., Bluetooth, IEEE 802.11, UMTS, and satellite networks). These systems are envisioned to coordinate with each other to provide ubiquitous high-data-rate services to mobile users. In this article, the architecture for ubiquitous mobile communications (AMC) is introduced that integrates these heterogeneous wireless systems. AMC eliminates the need for direct service level agreements among service providers by using a third party, a network interoperating agent. Instead of deploying a totally new infrastructure, AMC extends the existing infrastructure to integrate heterogeneous wireless systems. It uses IP as the interconnection protocol. By using IP as the gluing protocol, transparency to the heterogeneities of the individual systems is achieved in AMC. Third-party-based authentication and billing algorithms are designed for AMC. New mobility management protocols are also developed to support seamless roaming between different wireless systems.     

Nanogel Encapsulated Hydrogels As Advanced Wound Dressings for the Controlled Delivery of Antibiotics

Biocompatible and degradable dual-delivery gel systems based on hyperbranched dendritic−linear−dendritic copolymers (HBDLDs) is herein conceptualized and accomplished via thiol-ene click chemistry. The elasticity of the hydrogels is tunable by varying the lengths of PEG (2, 6, 10 kDa) or the dry weight percentages (20, 30, 40 wt%), and are found to range from 2–14.7 kPa, comparable to human skin. The co-delivery of antibiotics is achieved, where the hydrophilic drug novobiocin sodium salt (NB) is entrapped within the hydrophilic hydrogel, while the hydrophobic antibiotic ciprofloxacin (CIP) is encapsulated within the dendritic nanogels (DNGs) with hydrophobic cores (DNGs-CIP). The DNGs-CIP with drug loading capacity of 2.83 wt% are then physically entrapped within the hybrid hydrogels through UV curing. The hybrid hydrogels enable the quick release of NB and prolonged released of CIP. In vitro cell infection assays showed that the antibiotic-loaded hybrid hydrogels are able to treat bacterial infections with significant bacterial reduction. Hybrid hydrogel band aids are fabricated and exhibited better antibacterial activity compared with commercial antimicrobial band aids. Remarkably, most hydrogels and hybrid hydrogels show enhanced human dermal cell proliferation and could be degraded into non-toxic constituents, showing great promise as wound dressing materials.     

A Cross-Layer (Layer 2 + 3) Handoff Management Protocol for Next-Generation Wireless Systems

Next-generation wireless systems (NGWS) integrate different wireless networks, each of which is optimized for some specific services and coverage area to provide ubiquitous communications to the mobile users. It is an important and challenging issue to support seamless handoff management in this integrated architecture. The existing handoff management protocols are not sufficient to guarantee handoff support that is transparent to the applications in NGWS. In this work, a cross-layer (Layer 2 + 3) handoff management protocol, CHMP, is developed to support seamless intra and intersystem handoff management in NGWS. Cross-layer handoff management protocol uses mobile's speed and handoff signaling delay information to enhance the handoff performance of Mobile IP that is proposed to support mobility management in wireless IP networks. First, the handoff performance of Mobile IP is analyzed with respect to its sensitivity to the link layer (Layer 2) and network layer (Layer 3) parameters. Then, a cross-layer handoff management architecture is developed using the insights learnt from the analysis. Based on this architecture, the detailed design of CHMP is carried out. Finally, extensive simulation experiments are carried out to evaluate the performance of CHMP. The theoretical analysis and simulation results show that CHMP significantly enhances the performance of both intra and intersystem handoffs.     

Impact of gate-oxide tunneling on mixed-signal design and simulation of a nano-CMOS VCO

Design optimization for performance enhancement in analog and mixed-signal circuits is an active area of research as technology scaling is moving towards the nanometer scale. This paper presents an approach towards the efficient simulation and characterization of mixed-signal circuits, using a 45 nm CMOS voltage controlled oscillator (VCO) with frequency divider as a case study. The performance characteristics of the analog and digital blocks in the circuit are simulated and the accuracy issues arising due to separate analog and digital simulation engines are considered. The tremendous impact of gate tunneling current on device performance is quantitatively analyzed with the help of an “effective tunneling capacitance”, which allows accurate modeling and simulation of digital blocks with almost analog accuracy. To meet the design specifications of the analog VCO using digital CMOS technology, we follow a design of experiments (DOE) approach. The functional specifications of the VCO optimized in this design are the center frequency and minimization of overall power consumption as well as minimization of power due to gate-oxide tunneling current leakage, a component that was not important in previous generations of CMOS technologies but is dominant at 45 nm and below. Due to the large number of available design parameter (gate-oxide thickness and transistor sizes), the concurrent achievement of all optimization goals is difficult. A DOE approach is shown to be very effective and a viable alternative to standard design exploration in the nanometer regime.     

CL-AGKA: certificateless authenticated group key agreement protocol for mobile networks

Wireless Networks - Wireless group communication has gained much popularity recently due to the increase in portable, lightweight devices. These devices are capable of performing group...     

Machine learning approach to recognize ventricular arrhythmias using VMD based features

The occurrence of life-threatening ventricular arrhythmias (VAs) such as Ventricular tachycardia (VT) and Ventricular fibrillation (VF) leads to sudden cardiac death which requires detection at an early stage. The main aim of this work is to develop an automated system using machine learning tool for accurate prediction of VAs that may reduce the mortality rate. In this paper, a novel method using variational mode decomposition (VMD) based features and C4.5 classifier for detection of ventricular arrhythmias is presented. The VMD model was used to decompose the electrocardiography (ECG) signals to extract useful informative features. The method was tested for ECG signals obtained from PhysioNet database. Two standard databases i.e. CUDB (Creighton University Ventricular Tachyarrhythmia Database) and VFDB (MIT-BIH Malignant Ventricular Ectopy Database) were considered for this work. A set of time–frequency features were extracted and ranked by the gain ratio attribute evaluation method. The ranked features are subjected to support vector machine (SVM) and C4.5 classifier for classification of normal, VT and VF classes. The best detection was obtained with sensitivity of 97.97%, specificity of 99.15%, and accuracy of 99.18% for C4.5 classifier with a 5 s data analysis window. These results were better than SVM classifier result having an average accuracy of 86.87%. Hence, the proposed method demonstrates the efficiency in detecting the life-threatening VAs and can serve as an assistive tool to clinicians in the diagnosis process.