Dielectric and electrical studies on iron oxide (α-Fe2O3) nanoparticles synthesized by modified solution combustion reaction for microwave applications

Journal of Electroceramics - Hematite (α-Fe2O3) nanoparticles were synthesized by modified solution combustion method using a mixture of hexamethylenetetramine (HMTA) and glycine fuels at fuel...     

Uplift capacity of horizontal anchor plate in geocell reinforced sand

The paper investigates the uplift performance of horizontal anchor plate in geocell reinforced sand through a series of model tests. It is noted that the unreinforced anchor plate undergoes a clear failure at a displacement of about 3% of its width, whereas with the provision of geocell and a layer of geotextile right below the geocell mattress significantly increases the uplift capacity by about 4.5 times higher than that of unreinforced sand and could sustain anchor displacement of more than 60%. Results indicates that the geocell mattress by virtue of its rigidity distributes the uplift load in the lateral directions to a larger area, thereby reducing the stress in the overlying soil mass and hence increases the performance of anchor plate system. The provision of the additional geotextile layer right below the geocell mattress is found to be very effective in increasing the stiffness as well as load carrying capacity of anchor plate system. The optimum size (i.e., width and length) of geocell mattress giving adequate load carrying capacity of anchor plate is found to be 5.4 times of anchor width (5.4B). The comparison of model tests results with 3D numerical analysis shows good agreement, indicating that the proposed model is able to capture the uplift load-displacement behaviour of geocell reinforced anchor plate system.     

Analytical Modeling of Surface Potential and Drain Current of Hetero-Dielectric DG TFET and Its Analog and Radio-Frequency Performance Evaluation

Semiconductors - In the present paper, analytical modeling of surface potential and drain current for hetero-dielectric double gate tunnel FET (HDG-TFET) has been done. The two dimensional (2D)...     

MRMR Based Feature Vector Design for Efficient Citrus Disease Detection

In recent times, the images and videos have emerged as one of the most important information source depicting the real time scenarios. Digital images nowadays serve as input for many applications and replacing the manual methods due to their capabilities of 3D scene representation in 2D plane. The capabilities of digital images along with utilization of machine learning methodologies are showing promising accuracies in many applications of prediction and pattern recognition. One of the application fields pertains to detection of diseases occurring in the plants, which are destroying the widespread fields. Traditionally the disease detection process was done by a domain expert using manual examination and laboratory tests. This is a tedious and time consuming process and does not suffice the accuracy levels. This creates a room for the research in developing automation based methods where the images captured through sensors and cameras will be used for detection of disease and control its spreading. The digital images captured from the field's forms the dataset which trains the machine learning models to predict the nature of the disease. The accuracy of these models is greatly affected by the amount of noise and ailments present in the input images, appropriate segmentation methodology, feature vector development and the choice of machine learning algorithm. To ensure the high rated performance of the designed system the research is moving in a direction to fine tune each and every stage separately considering their dependencies on subsequent stages. Therefore the most optimum solution can be obtained by considering the image processing methodologies for improving the quality of image and then applying statistical methods for feature extraction and selection. The training vector thus developed is capable of presenting the relationship between the feature values and the target class. In this article, a highly accurate system model for detecting the diseases occurring in citrus fruits using a hybrid feature development approach is proposed. The overall improvement in terms of accuracy is measured and depicted.     

Improved energy recovery from dark fermented cane molasses using microbial fuel cells

A major limitation associated with fermentative hydrogen production is the low substrate conversion efficiency. This limitation can be overcome by integrating the process with a microbial fuel cell (MFC) which converts the residual energy of the substrate to electricity. Studies were carried out to check the feasibility of this integration. Biohydrogen was produced from the fermentation of cane molasses in both batch and continuous modes. A maximum yield of about 8.23 mol H₂/kg COD_removed was observed in the batch process compared to 11.6 mol H₂/kg COD_removed in the continuous process. The spent fermentation media was then used as a substrate in an MFC for electricity generation. The MFC parameters such as the initial anolyte pH, the substrate concentration and the effect of pre-treatment were studied and optimized to maximize coulombic efficiency. Reductions in COD and total carbohydrates were about 85% and 88% respectively. A power output of 3.02 W/m³ was obtained with an anolyte pH of 7.5 using alkali pre-treated spent media. The results show that integrating a MFC with dark fermentation is a promising way to utilize the substrate energy.     

A QoS-enhanced intelligent stochastic real-time packet scheduler for multimedia IP traffic

A re-configurable, QoS-enhanced intelligent stochastic real-time optimal fair packet scheduler, QUEST, for IP routers is proposed and investigated. The objective is to maximize the system QoS subject to the constraint that the processor utilization is kept at 100%. All past work on router schedulers for multimedia traffic were of earlier generation, in that they focused on maximizing utilization whereas being QoS-aware but without explicitly maximizing the QoS. Keeping utilization fixed at nearly 100%, QoS is dynamically maximized, thus moving to the next generation. QUEST’s other unique advantages are three-fold. First, it solves the challenging problem of starvation for low priority processes; second, it solves the major bottleneck of Earliest Deadline First scheduler’s failure at heavy traffic loads. Finally, QUEST offers the benefit of arbitrarily pre-programming the process utilization ratio. Three classes of multimedia IP traffic, namely, VoIP, IPTV and HTTP have been considered. Two most important QoS metrics, namely, packet loss rate (PLR) and mean waiting time, are addressed. All claims are supported by discrete event and Monte Carlo simulations. The proposed scheduler outperforms benchmark schedulers and offers 37% improvement in packet loss rate and 23% improvement in mean waiting time over the best competing current scheduler Accuracy-aware EDF. The proposed scheduler was validated in a test-bed platform of a NetFPGA® router and results were observed with Paessler® PRTG network monitor.