Heat transfer enhancement by using a rectangular wing vortex generator on the triangular shaped fins of a plate‐fin heat exchanger

The present numerical analysis pertains to the heat transfer enhancement in a plate‐fin heat exchanger employing triangular shaped fins with a rectangular wing vortex generator on its slant surfaces. The study has been carried out for three different angles of attack of the wing, i.e., 15°, 20° and 26°. The aspect ratio of the wing is not varied with its angle of attack. The flow considered herein is laminar, incompressible, and viscous with the Reynolds number not exceeding 200. The pressure and the velocity components are obtained by solving the continuity and the Navier– Stokes equations by the Marker and Cell method. The present analysis reveals that the use of a rectangular wing vortex generator at an attack angle of 26° results in about a 35% increase in the combined spanwise average Nusselt number as compared to the plate‐triangular fin heat exchanger without any vortex generator. © 2010 Wiley Periodicals, Inc. Heat Trans Asian Res; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/htj.20285     

Vitamin D2 stability in milk during processing,packaging and storage

Stability of vitamin D2 in milk was determined in vitamin D2 fortified milk. Reverse phase high pressure liquid chromatography was used to determine the vitamin D₂ loss during processing, packaging and under light. The percentage losses during pasteurization, boiling and sterilization were demonstrated to be statistically insignificant. Milk was stored for seven days in both glass and plastic bottles under refrigerated temperature, non significant loss of vitamin D₂ was observed, whereas, when stored in polyethylene pouches significant loss was observed as vitamin D₂ decreased from 596.66 to 548.04 IU. This clearly indicated that vitamin D₂ was sorbed up by polyethylene material during storage resulting in its loss. Milk samples were stored for 32 h under three different light intensities (14,852,970 and 4455 lux). Non significant loss of vitamin D₂ was observed in glass packaging, whereas significant loss was observed in polyethylene pouches. In milk fortified with both calcium and vitamin D₂, non significant effect of calcium was observed on the loss of vitamin D₂.     

Machine Learning with Dimensionality Reduction for DDoS Attack Detection

With the advancement of internet, there is also a rise in cybercrimes and digital attacks. DDoS (Distributed Denial of Service) attack is the most dominant weapon to breach the vulnerabilities of internet and pose a significant threat in the digital environment. These cyber-attacks are generated deliberately and consciously by the hacker to overwhelm the target with heavy traffic that genuine users are unable to use the target resources. As a result, targeted services are inaccessible by the legitimate user. To prevent these attacks, researchers are making use of advanced Machine Learning classifiers which can accurately detect the DDoS attacks. However, the challenge in using these techniques is the limitations on capacity for the volume of data and the required processing time. In this research work, we propose the framework of reducing the dimensions of the data by selecting the most important features which contribute to the predictive accuracy. We show that the ‘lite’ model trained on reduced dataset not only saves the computational power, but also improves the predictive performance. We show that dimensionality reduction can improve both effectiveness (recall) and efficiency (precision) of the model as compared to the model trained on ‘full’ dataset.     

A Bi-GRU with attention and CapsNet hybrid model for cyberbullying detection on social media

World Wide Web - As a constructive mode of information sharing, collaboration and communication, social media platforms offer users with limitless opportunities. The same hypermedia can be...     

Multimodal medical image fusion using non-subsampled shearlet transform and pulse coupled neural network incorporated with morphological gradient

This research proposes a novel fusion scheme for non-subsampled shearlet transform (NSST) which is based on simplified model of pulse coupled neural network (PCNN). The images to be fused are acquired from Postgraduate Institute of Medical Education and Research, Chandigarh, India, and internet repository. The image database contains computed tomography and T2-weighted magnetic resonance images. The images to be fused are decomposed into approximation and detail sub-bands using NSST. The regional energy-based activity measure with consistency verification is applied to fuse the approximation sub-band of NSST. The novel morphological gradient of detail sub-bands is fed as external stimulus to PCNN to fuse detail sub-bands. The proposed method is compared with five state-of-the-art fusion schemes visually and using five fusion performance parameters. It is observed that the resultant images of the proposed fusion scheme show appropriate fusion characteristics and retain the bone, CSF and edema details in the clinical format required for disease evaluation by the radiologists. The proposed scheme requires lesser computational time than other state-of-the-art PCNN-based fusion schemes.     

A comparison of FDTD-PML with TDIE

Presented in this paper, is a comparison of two popular numerical techniques, viz. the finite-difference time-domain method and the time domain integral equation method, for electromagnetic-scattering problems. The comparison is made via standard canonical shapes, a cube, and a sphere, to address the factors affecting accuracy, efficiency, and the required computer resources.     

Review of research work in sinking EDM and WEDM on metal matrix composite materials

Metal matrix composites (MMCs) are newly advanced materials having the properties of light weight, high specific strength, good wear resistance and a low thermal expansion coefficient. These materials are extensively used in industry. Greater hardness and reinforcement makes it difficult to machine using traditional techniques, which has impeded the development of MMCs. The use of traditional machinery to machine hard composite materials causes serious tool wear due to the abrasive nature of reinforcement. These materials can be machined by many non-traditional methods like water jet and laser cutting but these processes are limited to linear cutting only. Electrical discharge machining (EDM) shows higher capability for cutting complex shapes with high precision for these materials. The paper presents a review of EDM process and year wise research work done in EDM on MMCs. The paper also discusses the future trend of research work in the same area.     

Study on the adsorption of hemoglobin onto bentonite clay surfaces

The adsorption behavior of a hemoglobin (Hb) solution onto bentonite powder was studied from its alkaline solution (pH 12.6) and at room temperature. Different types of adsorption isotherms are discussed and various adsorption parameters, such as the adsorption coefficient, rate constants for adsorption and desorption, diffusion constant, penetration rate constant, were evaluated. The effects of pH and temperature of the adsorption medium on the extent of adsorption and the influence of solvents were studied, and the effect of salt concentrations on the rate of adsorption were also observed. © 2002 Wiley Periodicals, Inc. J Appl Polym Sci 85: 1607–1618, 2002     

Materialized view selection applying differential evolution algorithm combined with ensembled constraint handling techniques

Multimedia Tools and Applications - Materialized view selection problem is a NP-hard, constrained optimization problem where the pre-computation of views is censorious for query performance...     

A novel neural network controller and its efficient DSP implementation for vector-controlled induction motor drives

An artificial neural network controller is experimentally implemented on the Texas Instruments TMS320C30 digital signal processor (DSP). The controller emulates indirect field-oriented control for an induction motor, generating direct and quadrature current command signals in the stationary frame. In this way, the neural network performs the critical functions of slip estimation and matrix rotation internally. There are five input signals to the neural network controller, namely, a shaft speed signal, the synchronous frame present and delayed values of the quadrature axis stator current, as well as two neural network output signals fed back after a delay of one sample period. The proposed three-layer neural network controller contains only 17 neurons in an attempt to minimize computational requirements of the digital signal processor. This allows DSP resources to be used for other control purposes and system functions. For experimental investigation, a sampling period of 1 ms is employed. Operating at 33.3 MHz (16.7 MIPS), the digital signal processor is able to perform all neural network calculations in a total time of only 280 /spl mu/s or only 4700 machine instructions. Torque pulsations are initially observed, but are reduced by iterative re-training of the neural network using experimental data. The resulting motor speed step response (for several forward and reverse step commands) quickly tracks the expected response, with negligible error under steady-state conditions.