Process and die profile design for tube extrusion of γ iron

This study is related to material modeling and die and process design of tube extrusion of γ iron. Strain dependent rate power law is used for material modeling whose coefficients are arrived at through genetic algorithm (GA). Die profile of the tube extrusion process is optimized to produce microstructurally sound product at maximum production speed and minimum left out material in the die. The design problem is formulated as a nonlinear programming problem which is solved using GA. Selection of the processing parameters is carried out using dynamic material modeling (DMM). Using this approach tube extrusion process of γ iron is successfully designed.     

Erosion-corrosion behavior of SiC particle-reinforced Al-Si alloy in NaOH slurry

The erosion-corrsosion behavior of SiC particle-reinforced Al-Si alloy has been studied in NaOH slurry simulating the mining atmosphere. The study was performed at two different sand concentrations, namely, 20 and 30 wt pct, and at a speed of 900 rpm. It is depicted that the wear rates decreased with increasing sand content, indicating that corrosion is the dominating mode of material removal. Further composite exhibited lower wear resistance than the laloys irrespective of the sand concentration. Scanning electron microscope (SEM) observations indicated the dissolution of dendrites of Al due to severe corrosion, leaving behind the network of Si. This ultimately results in the falling of Si particles from the matrix, leaving behind voids. This also results in the formation of voids around the SiC particles and leads to pullout of SiC particles from the matrix during the wear process.     

Comparative study of artificial neural network for classification of hot and cold recombination regions in Saccharomyces cerevisiae

At the chromosomal level of evolution, recombination is a major factor for genetic variations. However, recombination does not occur with equal frequency at various regions of genome. The recombination has the tendency to occur at specific region with higher frequency and with low frequency at other regions, and former regions are named as hot recombination regions whereas later are called cold regions for recombination. In this paper, we have developed supervised machine learning-based models using artificial neural network, support vector machine and Naïve Bayes for efficient and effective classification of such hot and cold recombination regions based on the nucleotide composition of sequences. All models were validated and tested using tenfold cross-validation. Furthermore, neural network model was validated using leave one out and random sampling techniques in addition to tenfold cross-validation. Moreover, models were evaluated using receiver-operating curve. Our results indicate that artificial neural network achieves the best result.

     

FPGA Implementation of Cross Virtual Concatenation Transmitter/ Receiver for Data Transmission over Next Generation SDH Systems

Cross Virtual Concatenation is the new technique proposed for bandwidth efficient transmission of data over SDH networks. SDH networks came into existence for reliable voice transmission. As the demand of data traffic grew in wide area networks, new technologies were developed and standardized for data transmission over SDH networks. The technologies used namely, GFP (generic framing procedure), VCAT (virtual concatenation) and LCAS (link capacity adjustment scheme) enable network operator to provide integrated voice and data services over their legacy SDH infrastructure. Data packets are encapsulated using framing protocols GFP. VCAT is a process of distributing the GFP framed data payload in number of virtual channels of same capacity forming a Virtually Concatenated Group (VCG). LCAS is used for dynamic bandwidth allocation. LCAS enhances the VCAT scheme with hitless in service addition and removal of VC’s to/from the VCG.VCAT combines homogeneous virtual channels together which in some cases limits the performance of VCAT. This paper describes the implementation of new concatenation technology named cross virtual concatenation (CVC), which combines heterogeneous VC’s together to utilize the SDH bandwidth more efficiently. CVC implementation requires only end node equipments to be upgraded as VCG members travel through the link similar to the conventional VCAT. This paper proposes FPGA implementation of transmitter and receiver circuits for 100 Mbps Ethernet data transmission over next Generation SDH systems using CVC, where two types of VC’s namely VC-3 and VC-12 are used for data transmission. Total Transmission delay is calculated as 125 μs. There is no complexity added at the receiver side due to this delay. The receiver is designed for 32 ms differential delay compensation which can be increased up to maximum 256 ms by increasing the buffer size at the receiver.     

Performance evaluation of different machine learning techniques for prediction of heart disease

Neural Computing and Applications - Heart diseases are of notable public health disquiet worldwide. Heart patients are growing speedily owing to deficient health awareness and bad consumption...     

Good intentions with limited outcomes: Three limitations of trying to reduce mass migration with industrial thinking

Industrial thinking is being applied in efforts to try to stem the flow of migrants to Europe. In particular, industrial production in the Middle East is being subsidized by the European Union. This is being done with good intentions. However, positive outcomes are limited. In this paper, it is explained that limited positive outcomes are inevitable, because industrial thinking is too out-of-date and out-of-place to address the causes of mass migration in the Middle East. By contrast, “leapfrog” socio-technical systems could be applied to address the complex causes of mass migration, not as socio-economic crises, but as opportunities for mutual prosperity growth.     

Solar still with latent heat energy storage: A review

The requirement of fresh water is growing exponentially in industrial as well as domestic sector, resulting in more pollution of natural water resources and creating a scarcity of drinking water. Additionally, the number of arid and desert regions on the world map which already face the shortage of rainfalls and ground water. The problem is substantially increased as most of the water bodies like rivers, lakes are saline and brackish which are not suitable for drinking purpose. In recent past, solar desalination has been found to be a sustainable and economical way of generating the fresh water to cater the need of drinking water at large. Much technological advancement in the field of solar stills has been made which can ably produce a large quantity of fresh water depending on the availability of solar radiation. Various desalination schemes have been utilized to utilise water from such available resources to convert the available water in to the drinkable water. Additionally, attention has also been put on developing efficient solar still with latent heat based thermal energy storage systems which can work in the absence of sunlight as well. In the present paper, a short review on solar stills utilizing latent heat storage has been presented. The present study covers the design specifications, efficiency, along with the comparative analysis of solar stills with latent heat storage system, investigated in the last decade. A discussion on the future research outlook in the area of solar stills with latent heat storage has also been given, so as to make it more economically viable for generating sustainable potable water.     

Synthesis and Characterization of Magnetite/Polyvinyl Alcohol Core–Shell Composite Nanoparticles

Magnetite (Fe₃O₄)/polyvinyl alcohol (PVA) core–shell composite nanoparticles were successfully synthesized using a coprecipitation of ferrous and ferric chloride followed by coating with PVA. The resulting nanoparticles were characterized using X‐ray diffraction, Fourier Transform Infrared Spectroscopy, Transmission Electron Microscopy, X‐ray photo electron spectroscopy, Zeta potential measurements, UV–Vis spectroscopy, Thermogravimetric Analysis, and Vibrating Sample Magnetometry (VSM). The average particle size was 13 nm. The presence of characteristic functional groups of PVA around the core of magnetite nanoparticles was confirmed by FTIR spectroscopy while the amount of PVA (%) bound to it was estimated by TGA analysis. Zeta potential measurements made by dispersing dilute sonicated samples in a Phosphate Buffer Saline (PBS pH 7.4) confirmed that the particles were negatively charged. The stability and retention of the coating material PVA in PBS (pH7.4) over a period of time were substantiated by UV–Vis spectroscopy. Room‐temperature magnetic measurements were made with a VSM which demonstrated the superparamagnetic nature of the particles with higher saturation magnetization of 56.41 emu/g. Furthermore, in vitro cytocompatibility testing of Fe₃O₄/PVA core–shell composite nanoparticles was carried out on human cervix cancer cells. This confirmed a 97% cell viability with no significant cytotoxicity and thereby substantiated their biocompatibility.