Machine Learning Empowered Security Management and Quality of Service Provision in SDN-NFV Environment

With the rising demand for data access, network service providers face the challenge of growing their capital and operating costs while at the same time enhancing network capacity and meeting the increased demand for access. To increase efficacy of Software Defined Network (SDN) and Network Function Virtualization (NFV) framework, we need to eradicate network security configuration errors that may create vulnerabilities to affect overall efficiency, reduce network performance, and increase maintenance cost. The existing frameworks lack in security, and computer systems face few abnormalities, which prompts the need for different recognition and mitigation methods to keep the system in the operational state proactively. The fundamental concept behind SDN-NFV is the encroachment from specific resource execution to the programming-based structure. This research is around the combination of SDN and NFV for rational decision making to control and monitor traffic in the virtualized environment. The combination is often seen as an extra burden in terms of resources usage in a heterogeneous network environment, but as well as it provides the solution for critical problems specially regarding massive network traffic issues. The attacks have been expanding step by step; therefore, it is hard to recognize and protect by conventional methods. To overcome these issues, there must be an autonomous system to recognize and characterize the network traffic’s abnormal conduct if there is any. Only four types of assaults, including HTTP Flood, UDP Flood, Smurf Flood, and SiDDoS Flood, are considered in the identified dataset, to optimize the stability of the SDN-NFV environment and security management, through several machine learning based characterization techniques like Support Vector Machine (SVM), K-Nearest Neighbors (KNN), Logistic Regression (LR) and Isolation Forest (IF). Python is used for simulation purposes, including several valuable utilities like the mine package, the open-source Python ML libraries Scikit-learn, NumPy, SciPy, Matplotlib. Few Flood assaults and Structured Query Language (SQL) injections anomalies are validated and effectively-identified through the anticipated procedure. The classification results are promising and show that overall accuracy lies between 87% to 95% for SVM, LR, KNN, and IF classifiers in the scrutiny of traffic, whether the network traffic is normal or anomalous in the SDN-NFV environment.     

Development of optimized triaxially electrospun titania nanofiber-in-nanotube core-shell structure

One dimensional (1D) nanostructures and its derivatives can be manipulated to serve special functions like hollow structure, and higher surface area. 1D TiO₂ nanotube-in-nanofibers (NF@NT) are developed through triaxial electrospinning followed by a calcination process. A blended solution of polyvinyl pyrrolidone and tetra-butyl titanate is used in outer and inner layers of nanofibers, respectively, while paraffin oil is used in the middle layer. The optimized triaxial nanofibers of 669.4 ± 52.43 nm are developed at 7.5 w/w% concentration, 28 kV applied voltage, and 24 cm spinning distance. TiO₂ NF@NT structure is obtained through calcination of optimized triaxial nanofibers at 550°C. Subsequently, the morphology of TiO₂ NF@NT and its uniform diameter distribution is confirmed through scanning electron microscopy. Fourier-transform infrared spectroscopy results indicates the formation of TiO₂ NF@NT. X-Rays diffraction pattern peaks also reveals the presence of both anatase and rutile crystalline phases. The presence of only titanium (Ti) and oxygen (O) elements in the TiO₂ NF@NT is confirmed through energy dispersive X-ray spectroscopy. Brunauer–Emmett–Teller analysis indicates that TiO₂ NF@NT has a higher specific surface area of ~141.68 m²/g compared with the solid TiO₂ nanofiber (~75.31 m²/g). This study can be adopted to develop TiO₂ NF@NT for wide range of application.     

SDN-Based Centralized Channel Assignment Scheme Using Clustering in Dense WLAN Environments

Wireless Personal Communications - IEEE WLAN 802.11 uses a contention-based medium access control protocol. Adjacent WLAN access points (APs) and stations (STAs) sharing the same channels causes...     

Normal metal, ohmic contacts to high-temperature superconducting YBa2Cu3O7-δ thin films suitable for multichip modules

Normal metal, ohmic contacts to high-temperature superconductor (HTSC) materials will be used to form via structures between HTSC interconnect levels, and also, substrate bonding pads in a superconducting multichip module (SMCM). Specific contact resistivities below 10⁻⁸ Ω cm² will be required for such contacts to control signal attenuation and local contact heating of the LN₂cooled SMCM. Previous work on normal metal/superconducting contacts has not focused on metallization schemes which will be stable during subsequent high-temperature processing. Metal contacts of gold, silver, and palladium were formed on superconducting thin films of YBa₂Cu₃O_7-δ via evaporation and sputtering through a shadow mask followed by annealing in various ambients and at several temperatures. Palladium contacts oxidized readily during anneal, and sputtered gold contacts required additional processing and exhibited higher specific contact resistivities. The best contacts were obtained by a controlled-cooling oxygen anneal of evaporated gold or silver, as indicated by normal-state specific contact resistivities of 3 × 10⁻⁵ Ω cm² and 4 × 10⁻⁵ Ω cm², respectively. This work differs from previously published results by describing contacts which required no extensive preparation of the HTSC surface and were stable to 700 °C, indicating these contacts would be compatible with subsequent high-temperature processing of the additional HTSC layers required in a multi-level SMCM.     

Biodegradable polymeric injectable implants for long‐term delivery of contraceptive drugs

Development of injectable, long‐lasting, contraceptive drug delivery formulations, and implants are highly desired to avoid unplanned pregnancies while improving patient compliance and reducing adverse side effects and treatment costs. The present study reports on the fabrication and characterization of two levonorgestrel (LNG) microsphere injectable formulations. Poly(?‐caprolactone) (PCL) with 12.5% and 24% (w/w) LNG were fabricated into microspheres, measuring 300 ± 125 µm, via the oil‐in‐water (o/w) emulsion solvent evaporation technique. Formulations showed sustained drug release up to 120 days. FTIR, XRD, DSC, and TGA confirmed the absence of LNG chemical interaction with PCL as well as its molecular level distribution. The in vitro release of LNG was calculated to be Fickian diffusion controlled and properly characterized. The inclusion of multiple elevated release temperatures allowed for the application of the Arrhenius model to calculate drug release constants and representative sampling intervals, demonstrating the use of elevated temperatures for accelerated‐time drug release studies. © 2017 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2018 , 135, 46068.     

Designed synthesis of silver nanoparticles in responsive polymeric system for their thermally tailored catalytic activity towards hydrogenation reaction

Poly(N-isopropylacrylamide-acrylamide-methacrylic acid) [p(NIPa-AAm-Ma)] polymer microgels were prepared by free radical precipitation polymerization method. AgNPs were fabricated in the sieves of polymer network by chemical reduction using AgNO₃ salt as a precursor of silver ions. Various techniques like dynamic light scattering (DLS), transmission electron microscopy (TEM), Fourier transform infrared microscopy (FTIR), and UV-Visible spectroscopy were used for characterization of pure and composite microgels. The diameter of AgNPs fabricated in polymeric network was found to be in the range of 10-15 nm. Stimuli responsive behavior of hybrid microgels was same as that of pure microgels. Catalytic efficiency of the hybrid microgels was investigated by reducing 4-Nitroaniline (4-NA) into 4-Aminoaniline (4-AA) using NaBH₄ as reducing agent under different conditions of temperature of the medium, concentration of reducing agent, 4-Nitroaniline and hybrid microgels to explore the catalysis process. Kinetic and thermodynamic aspects of reduction of 4-Nitroaniline in the presence of catalyst were also discussed on the basis of values of Arrhenius and Eyring parameters like pre-exponential factor, activation energy, enthalpy of activation and entropy of activation. Catalytic activity of the hybrid microgels was found to be thermally tunable in the temperature range of 25-70 oC. The value of rate constant (k _app ) for reduction of 4-NA was minimum at 55 °C, which can be attributed to volume phase transition of the hybrid microgels.     

Tailoring of optical band gap and electrical conductivity in a-axis oriented Ni doped Chromium Oxide thin films

Ni doped Cr₂O₃ (NCO) films have attracted much attention due to their applications in the field of photovoltaics. This study reports the tailoring of structural, electrical and optical properties as a function of Ni doping in Chromium oxide (Cr₂O₃). NCO thin films were grown by Pulsed laser deposition (PLD) using 2nd harmonic Nd:YAG Laser on n-Si (100) with in-situ annealing of 450?°C. Structural analyses based on X-ray diffractometry (XRD) and Raman Spectroscopy showed the inconsistent variation in crystallinity and shift in $A_{1g}$ band in turn revealing the successful incorporation of Ni into Chromium oxide host lattice. In addition, electrical measurements also showed an inconsistent variation in resistivity ranging from 10² to 10⁴$\Omega ?\mathit{cm}$. The properties showed widening of band gap energy (E_g) from 3.41 to 3.60?eV as a function of Ni doping concentration with significantly decreased reflectance in the range of 500–600?nm thereby increasing the absorption, a pre-requisite for solar absorbers.     

Performance Evaluation of AOMDV on Realistic and Efficient VANet Simulations

Wireless Personal Communications - The digital transmission amongst vehicles and roadway equipment is necessary for the realization of smart transportation systems. Vehicular ad-hoc network (VANet)...     

Influence of temperature on viscoelastic–viscoplastic behavior of poly(lactic acid) under loading–unloading

Experimental data are reported on poly(lactic acid) (PLA) in tensile loading–unloading tests and relaxation tests under stretching and retraction at temperatures ranging from room temperature up to 50°C. Two characteristic features of the time‐dependent response of PLA are revealed: (i) with a decrease in minimum stress under retraction at a fixed temperature, relaxation curves change their shape from monotonically decaying with time (simple relaxation), to non‐monotonic (mixed relaxation) to monotonically increasing (inverse relaxation) and (ii) with an increase in temperature, inverse relaxation after unloading down to the zero stress evolves into mixed relaxation with a pronounced shift of the peak position to smaller relaxation times. Constitutive equations are derived for the mechanical behavior of PLA, and adjustable parameters in the stress–strain relations are found by fitting the observations. Ability of the model to predict the time‐dependent response under cyclic deformation is confirmed by numerical simulation. POLYM. ENG. SCI., 57:239–247, 2017. © 2016 Society of Plastics Engineers