A policy based framework for quality of service management in software defined networks

Growth in multimedia traffic over the Internet increases congestion in the network architecture. Software-Defined Networking (SDN) is a novel paradigm that solves the congestion problem and allows the network to be dynamic, intelligent, and it centrally controls the network devices. SDN has many advantages in comparison to traditional networks, such as separation of forwarding and control plane from devices, global centralized control, management of network traffic. We design a policy-based framework to enhance the Quality of Service (QoS) of multimedia traffic flows in a potential SDN environment. We phrase a max-flow-min-cost routing problem to determine the routing paths and presented a heuristic method to route the traffic flows in the network in polynomial time. The framework monitors the QoS parameters of traffic flows and identifies policy violations due to link congestion in the network. The introduced approach dynamically implements policy rules to SDN switches upon detection of policy violations and reroutes the traffic flows. The results illustrate that the framework achieves a reduction in end-to-end delay, average jitter, and QoS violated flows by 24%, 37%, and 25%, respectively, as compared to the Delay Minimization method. Furthermore, the proposed approach has achieved better results when compared to SDN without policy-based framework and reduced end-to-end delay, average jitter, and QoS violated flows by 51%, 62%, and 28%, respectively.

     

Performance improvement of Deep Learning Models using image augmentation techniques

The major barrier while using deep learning models is lack of large number of images in the training dataset. In fact, there is a need of thousands of images in each image categories based on the complexity of problem. Prior studies have shown that picture augmentation techniques can be used to enhance the number of images in a training dataset artificially. These techniques can aid in improving the overall learning process and performance of a deep learning model. Hence, to address this problem we have proposed three algorithms. Firstly, two image acquisition algorithms have been proposed to systematically obtain real field images for testing and images from public datasets for training a model. Secondly, an algorithm is proposed to describe the procedure how the augmentations can be applied to enhance the datasets. During this study, we have investigated 52 augmentations that can allow enhancing the size of input dataset by improving the quantity of images. To perform the classification process of four maize crop diseases, a new convolutional neural network model is developed and several experiments have been performed to prove its effectiveness. Firstly, two tests were carried out using the original dataset from Kaggle public repository and the augmented dataset. When compared with the original dataset, the model improved by 5.14% with the augmented dataset. Secondly, three experiments carried out to evaluate the performance of proposed augmentation method. Experimental results demonstrated that the proposed approach outperforms the existing three approaches by 27.38%, 3.14%, and 1.34% during the classification process. The proposed IPA augmentation method has been compared with six existing methods: Full Stage Data Augmentation Framework, LeafGAN, Novel Augmentation method based on GAN, Wasserstein Generative Adversarial Network (WGAN), Activation Reconstruction-GAN, and Step-by-Step Data Augmentation Method and experimental results show that performance is better than existing methods by 28.31%, 19.76%, 20.18%, 13.75%, 2.42%, and 12.68% respectively.

     

Two dimensional analytical modeling of a high-K gate stack triple-material double gate strained silicon-on-nothing MOSFET with a vertical Gaussian doping

This paper presents the two-dimensional analytical modeling of high-k gate stack Triple material double gatestrained SON MOSFET with a vertical Gaussian-like doping profile. The expression for surface potential has been calculated by solving the 2-D Poisson’s equation and by considering the parabolic potential approximation. The threshold voltages as well as the electric field are also calculated for the proposed model. In addition, detailed studies of the device response towards the various short-channel effects are also examined. The analytical results are verified using the results obtained from a 2-D device simulator, namely ATLAS, Silvaco.     

Tent-Shaped Surface Morphologies of Silicon: Texturization by Metal Induced Etching

Silicon - Nano-metal/semiconductor junction dependent porosification of silicon has been studied here. The silicon nanostructures (SiNSs) have been textured on n- and p- type silicon wafers using...     

Efficacy of Ozone and Lactic Acid as Nonthermal Hurdles for Preservation of Sugarcane Juice

Thermal processing is the most widely adopted technology for preservation of juices; however, it is associated with significant changes in nutritional quality and flavor. Combination of nonthermal hurdles (ozone 1.2 g/h, 10 min, and lactic acid 0.5%) reduced total bacterial count of sugarcane juice by 4.3 log and controlled enzymatic activity to a moderate level (reduction of 60% and 72% activity of polyphenol oxidase and peroxidase, respectively). Combined treatment was comparable to thermal treatment in maintaining microbial and sensory quality of sugarcane juice during 1-month storage under refrigerated conditions; however, additional hurdles may be required for extended storage.     

Solution‐Processed High‐Performance Tetrathienothiophene‐Based Small Molecular Blends for Ambipolar Charge Transport

Four soluble dialkylated tetrathienoacene ( TTAR) ‐based small molecular semiconductors featuring the combination of a TTAR central core, π‐conjugated spacers comprising bithiophene ( bT ) or thiophene ( T ), and with/without cyanoacrylate ( CA ) end‐capping moieties are synthesized and characterized. The molecule DbT‐TTAR exhibits a promising hole mobility up to 0.36 cm² V^?1 s^?1 due to the enhanced crystallinity of the microribbon‐like films. Binary blends of the p‐type DbT‐TTAR and the n‐type dicyanomethylene substituted dithienothiophene‐quinoid ( DTTQ‐11 ) are investigated in terms of film morphology, microstructure, and organic field‐effect transistor (OFET) performance. The data indicate that as the DbT‐TTAR content in the blend film increases, the charge transport characteristics vary from unipolar (electron‐only) to ambipolar and then back to unipolar (hole‐only). With a 1:1 weight ratio of DbT‐TTAR DTTQ‐11 in the blend, well‐defined pathways for both charge carriers are achieved and resulted in ambipolar transport with high hole and electron mobilities of 0.83 and 0.37 cm² V^?1 s^?1, respectively. This study provides a viable way for tuning microstructure and charge carrier transport in small molecules and their blends to achieve high‐performance solution‐processable OFETs.     

N,N,N-trimethyl chitosan as an efficient antibacterial agent for polypropylene and polylactide nonwovens

The paper presents a method of depositing N,N,N-trimethyl chitosan (TMC) layers onto polypropylene and polylactide nonwovens. A two-step modification procedure is applied: first, grafting the nonwovens with acrylic acid and next layer-by-layer deposition. Turbidimetric measurements confirm the creation of polycomplexes between grafted poly(acrylic acid) and deposited TMC. The created material structure is evaluated using gravimetric analysis, reflectance Fourier transform infrared spectroscopy, scanning electron microscopy, energy dispersive spectroscopy measurements and pH-metric titration. The modified material exhibits good antibacterial properties against Gram-positive bacteria Staphylococcus aureus.     

Insight on Castor Oil Based Polyurethane and Nanocomposites: Recent Trends and Development

Castor oil has gained momentous attention as a valuable bio-based monomer and a potential alternative to the current petrobased polyol for synthesizing polyurethane due to the presence of inherent hydroxyl group. In spite of its huge potentiality very little has been reviewed regarding the development of polyurethane from castor oil. This review thus highlights the recent trends and development in the field of polyurethane and its nanocomposite based on castor oil including its biodegradability and weatherability studies. Further, this review also provides an insight regarding the utilization of castor oil based polyurethane and its nanocomposite for coating application.     

Performance of anaerobic–anoxic–aerobic batch fed moving-bed reactor at varying phenol feed concentrations and hydraulic retention time

A simulated wastewater containing phenol (1,000–2,500 mg/L), thiocyanate (SCN^?) of 800 mg/L, COD (4,200–8,150 mg/L), and ammonia–nitrogen (NH₄ ⁺–N) of 500 mg/L was treated in a sequential anaerobic (B1)–anoxic (B2)–aerobic (B3) batch fed moving-bed reactor (MBR) system. Total hydraulic retention time (HRT) was varied from 5 to 10 days with B1 2.5 to 5 days; B2 and B3: 1.25–2.5 days each. In B1, 25–63 % of phenol and 23–53 % of COD removals were achieved and feed phenol above 1,500 mg/L, inhibited COD and phenol removals in B1. In B2, more than 90 % phenol removal was achieved along with COD removal and denitrification. In B2, with increase in phenol loading, though phenol and COD removal rates increased, SCN^? removal rate decreased above phenol loading of 0.28 g/L day. In B3, NH₄ ⁺–N removal efficiency decreased above loading of 0.24 g NH₄ ⁺–N/L day. The overall efficiency of the fed batch MBR system was independent of feed phenol concentration up to 2,500 mg/L at constant total HRT of 6 days. NH₄ ⁺–N removal efficiency deteriorated significantly, when total HRT of fed batch MBR was less than 6 days. Modified Stover–Kincannon model showed the best fit for removal of substrates in three reactors and Haldane’s inhibition model predicted NH₄ ⁺–N removal in B3.     

Magnetohydrodynamic Slip Flow and Heat Transfer in a Porous Medium over a Stretching Cylinder: Homotopy Analysis Method

This study considers magnetohydrodynamic flow and heat transfer outside a hollow stretching cylinder immersed in a fluid saturated porous medium of sparse distribution of particles with high permeability. Partial slip boundary conditions for the velocity and temperature fields are assumed at the stretching surface of the cylinder. Using similarity transformations, the nonlinear partial differential equations governing the flow and heat transfer are converted into nonlinear ordinary differential equations which are then solved by the homotopy analysis method. The effects of the pertinent parameters on the velocity and temperature profiles are investigated and discussed graphically.