Dynamic Model of Basic Oxygen Steelmaking Process Based on Multizone Reaction Kinetics: Modeling of Manganese Removal

In the earlier study, a dynamic model for the BOF process based on the multizone reaction kinetics has been developed. In the preceding part, the mechanism of manganese transfer in three reactive zones of the converter has been analyzed. The study predicts that temperature at the slag–metal reaction interface plays a major role in the Mn reaction kinetics. Further, mathematical treatments to simulate the transient rate parameters associated with each reaction interface have been developed. The model calculations of Mn removal rate obtained from different zones of the converter predicts that the first stage of the blow is dominated by the oxidation of Mn at the jet impact zone, albeit some additional Mn refining has been observed as a result of the oxidation of metal droplets in emulsion phase. The simulation result shows that the reversion of Mn from slag to metal primarily takes place at the metal droplet in the emulsion due to an increase in slag–metal interface temperature during the middle stage of blowing. In the final stage of the blow, the competition between simultaneous reactions in jet impact and emulsion zone controls the direction of mass flow of manganese. Further, the model prediction shows that the Mn refining in the emulsion is a strong function of droplet diameter and the residence time. Smaller sized droplets approach equilibrium quickly and thus contribute to a significant Mn conversion between slag and metal compared to the larger sized ones. The overall model prediction for Mn in the hot metal has been found to be in good agreement with two data sets obtained from different size converters reported in the literature.     

Nucleolar organizer regions in meningiomas

Paraffin sections of 305 meningeal tumours were analysed for the presence of nucleolar organizer region (Ag-NOR) in the neoplastic cells, using a one step silver-colloidal staining method. The mean (+/- SEM) Ag-NOR counts were 2.73 +/- 0.21 for atypical and 2.91 +/- 0.18 for papillary variants of meningioma. In meningotheliomatous and transitional variants of meningioma, the mean Ag-NOR counts were 1.41 +/- 0.34 and 1.38 +/- 0.31, respectively. The recurrence rates were significantly higher in atypical meningiomas than in other histopathological variants (p < 0.05). Differences in the mean Ag-NOR numbers between meningothelial and transitional variants in their primary and recurrent tumours were not significantly different (p > 0.05). The results of this study indicates that estimation of Ag-NORs can be applied in predicting the aggressive clinical behaviour of primary meningeal tumours.     

Deceptive review detection using labeled and unlabeled data

Availability of millions of products and services on e-commerce sites makes it difficult to search the best suitable product according to the requirements because of existence of many alternatives. To get rid of this the most popular and useful approach is to follow reviews of others in opinionated social medias, who have already tried them. Almost all e-commerce sites provide facility to the users for giving views and experience of the product and services they experienced. The customers reviews are increasingly used by individuals, manufacturers and retailers for purchase and business decisions. As there is no scrutiny over the reviews received, anybody can write anything unanimously which conclusively leads to review spam. Moreover, driven by the desire of profit and/or publicity, spammers produce synthesized reviews to promote some products/brand and demote competitors products/brand. Deceptive review spam has seen a considerable growth overtime. In this work, we have applied supervised as well as unsupervised techniques to identify review spam. Most effective feature sets have been assembled for model building. Sentiment analysis has also been incorporated in the detection process. In order to get best performance some well-known classifiers were applied on labeled dataset. Further, for the unlabeled data, clustering is used after desired attributes were computed for spam detection. Additionally, there is a high chance that spam reviewers may also be held responsible for content pollution in multimedia social networks, because nowadays many users are giving the reviews using their social network logins. Finally, the work can be extended to find suspicious accounts responsible for posting fake multimedia contents into respective social networks.     

Diagnosis and treatment of depression by general practitioners in England

This paper describes a preliminary study of diagnosis and treatment of depression by general practitioners in England. They regarded primary care depression as a reactive mood disorder with both physical and psychological symptoms and associated with those groups who are most vulnerable to life stressors. Four groups were seen as at risk from depression: elderly persons, menopausal women, young mothers, and those in early adulthood. The practitioners relied primarily on their experience to diagnose depression rather than following any official diagnostic criteria. Although they were in favour of nondrug therapy in treating depression, they mainly practised drug therapy due to time pressure and limited availability of resources.     

Multiresolution visual enhancement of hazy underwater scene

Multimedia Tools and Applications - Haze is an obvious phenomenon in the underwater scenario. The scene visibility reduces to a great extent due to haze, which makes the underwater visual...     

Modeling Fischer–Tropsch kinetics and product distribution over a cobalt catalyst

A detailed kinetic model describing the consumption of key components and product distribution in the Fischer–Tropsch synthesis (FTS) over a 20%Co/0.5Re γ-Al₂O₃ commercial catalyst is developed. The developed model incorporates the H₂O-assisted CO dissociation mechanism developed by Rytter and Holmen and a novel approach to product distribution modeling. The model parameters are optimized against an experimental dataset comprising a range of process conditions: total pressure 2.0–2.2 MPa, temperature 210–230°C, CO conversion range of 10%–75% and feed with and without added water. The quality of the model fit measured in terms of mean absolute relative residuals (MARR) value is 23.1%, which is comparable to literature reported values. The developed model can accurately describe both positive and negative effects of water on the rate kinetics, the positive effect of water on the growth factor, temperature and syngas composition on the kinetics and product distribution over a wide range of process conditions, which is critical for the design and optimization of the Fisher–Tropsch reactors.     

Financial sustainability of rural water supply: An analysis of cost recovery,revenue collection,and efficiency

Maintaining a financial sustainable pipe water supply (PWS) is one of the serious challenges in sustainable provision of water supply in rural areas. Poor revenue collection and willingness to pay for the service is adding severity to the problem. This study analyses the factors affecting revenue collection in rural water utilities and measures its efficiency in maximizing revenue and average hour of water supply per day. The findings convey that cost recovery is a failure in rural water supply even they are not able to generate revenue. Inactive community participation, the notion of free water supply, unaccountable payment is main reason for poor revenue collection. Therefore, active community participations, educating the household on water supply, adoption of accountable payment mode will be a step towards revenue generation. To attain efficiency, the utilities can expand their output revenue and hours of water supply by 22% without altering their input. This study is an empirical contribution in the field of sustainable provision of water supplies, which address the problem of poor revenue generation in rural water supply and find out the reason for it.     

Big data analytics for video surveillance

This article addresses the usage and scope of Big Data Analytics in video surveillance and its potential application areas. The current age of technology provides the users, ample opportunity to generate data at every instant of time. Thus in general, a tremendous amount of data is generated every instant throughout the world. Among them, amount of video data generated is having a major share. Education, healthcare, tours and travels, food and culture, geographical exploration, agriculture, safety and security, entertainment etc., are the key areas where a tremendous amount of video data is generated every day. A major share among it are taken by the daily used surveillance data captured from the security purpose camera and are recorded everyday. Storage, retrieval, processing, and analysis of such gigantic data require some specific platform. Big Data Analytics is such a platform, which eases this analysis task. The aim of this article is to investigate the current trends in video surveillance and its applications using Big Data Analytics. It also aims to focus on the research opportunities for visual surveillance in Big Data frameworks. We have reported here the state-of-the-art surveillance schemes for four different imaging modalities: conventional video scene, remotely sensed video, medical diagnostics, and underwater surveillance. Several works were reported in this research field over recent years and are categorized based on the challenges solved by the researchers. A list of tools used for video surveillance using Big Data framework is presented. Finally, research gaps in this domain are discussed.

     

Mechanistic interpretation of electrochemical behaviour of galvannealing coating in saline environment

A comparative study on galvannealed (GA) and galvanised plain-skin passed (GP-SP) coatings was carried out to evaluate coating microstructures, the corrosion resistance and electrochemical behaviour in 3.5% NaCl solution. The corrosion resistance behaviour of GA coating was found to be superior compared to GP-SP coating. The Fe-Zn intermetallic phases formed in GA coating provided galvanic protection i.e., a cell reaction between Fe and Zn within a single phase. This gives rise to protective potential plateau and are believed to be responsible for the electrochemical polarisation resulting in sluggish corrosion reaction kinetics, thereby reducing the corrosion rate significantly after prolonged exposure in saline environment. It was also observed from the electrochemical impedance spectroscopy (EIS) study that the coating capacitance (C_c) decreased and polarisation resistance (R_p) increased with exposure time indicating a continuous charge transfer reaction across the coating and electrolyte interface. Although the corrosion potential of both coatings increased towards more noble direction with exposure time, it was observed that the potential for GA coatings was always nobler than GP-SP coating as E_corr shifted towards more positive potential corresponding to a flat potential band of −850 ± 20 mV.