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| 1 | Prediction of air flow, methane, and coal dust dispersion in a room and pillar mining face显示文摘In underground coal mines, uncontrolled accumulation of methane and fine coal dust often leads to serious incidents such as explosion. Therefore, methane and dust dispersion in underground mines is closely monitored and strictly regulated. Accordingly, significant efforts have been devoted to study methane and dust dispersion in underground mines. In this study, methane emission and dust concentration are numerically investigated using a computational fluid dynamics(CFD) approach. Various possible scenarios of underground mine configurations are evaluated. The results indicate that the presence of continuous miner adversely affects the air flow and leads to increased methane and dust concentrations.Nevertheless, it is found that such negative effect can be minimized or even neutralized by operating the scrubber fan in suction mode. In addition, it was found that the combination of scrubber fan in suction mode and brattice results in the best performance in terms of methane and dust removal from the mining face. | Lu Yueze Akhtar Saad Sasmito Agus P. Kurnia Jundika C. | 2017 | International Journal of Mining Science and Technology2017，27，4： | 10 |
| 2 | Ozonation of ibuprofen in presence of SrWO4/ZnO photo-catalyst显示文摘The study was performed for removing ibuprofen from water using ozonation with visible light SrWO4/ZnO catalyst.For the removal of Ibuprofen,the overall reaction was carried out in a glass reactor in the presence of UV light and constant supply of ozone.The maximum removal efficiency of Ibuprofen was 93%at 0.1 mg/L initial Ibuprofen concentration,and 0.35 g/L catalyst concentration keeping the contact time 30 min.After a certain value,an increase in a concentration of doping agent,catalyst as well as initial Ibuprofen concentration results in a decrease of efficiency of the process.The prepared photo catalysts were characterized by X-ray diffraction,FTIR spectra and SEM analysis.XRD peaks and FTIR spectra has clearly shown that the doping of SrWO4 with ZnO showed better result as compared to individual.SEM analysis showed that they spherical nano-composite crystals were dominant in character.BOD character was found to reduce after ozonation of solution.Various by products were formed and were identified through GC-MS analysis.From results,it was found that combination of SrWO4/ZnO was able to remove 93%of ibuprofen and 0.4%dopping of ZnO on SrWO4 was found to be sufficient.Degradation pattern of by products were identitified in GC-MS with various mass ratios as 177,92,57,44.Nearly 55%removal of BOD was observed in this study.This study was found to be useful for removal of pharmaceuticals and other similar pollutants from water effectively. | Hesham Alhumade Javaid Akhtar Saad Al-Shahrani Iqbal Ahmed Moujdin M.B.Tahir | 2022 | Emerging Contaminants2022，8，1： | 1 |
| 3 | Multiple Sebaceous Adenomas and Extraocular Sebaceous Carcinoma in a Patient with Multiple Sclerosis: Case Report and Review of Literature显示文摘 | Saad Akhtar Krishna K. Oza Randolph G. Roulier | 2001 | Journal of Cutaneous Medicine and Surgery: Incorporating Medical and Surgical Dermatology2001，，6： | 1 |
| 4 | A systematic study on the role of SentiWordNet in opinion mining显示文摘Sentiment lexicons(SL)(aka lexical resources)are the repositories of one or several dictionaries that consist of known and precompiled sentiment terms.These lexicons play an important role in performing several different opinion mining tasks.The efficacy of the lexicon-based approaches in performing opinion mining(OM)tasks solely depends on selecting an appropriate opinion lexicon to analyze the text.Therefore,one has to explore the available sentiment lexicons and then select the most suitable resource.Among available resources,SentiWordNet(SWN)is the most widely used lexicon to perform tasks related to opinion mining.In SWN,each synset of WordNet is being assigned the three sentiment numerical scores;positive,negative and objective that are calculated using by a set of classifiers.In this paper,a detailed and comprehensive review of the work related to opinion mining using Senti-WordNet is provided in a very distinctive way.This survey will be useful for the researchers contributing to the field of opinion mining.Following features make our contribution worthwhile and unique among the reviews of similar kind:(i)our review classifies the existing literature with respect to opinion mining tasks and subtasks(ii)it covers a very different outlook of the opinion mining field by providing in-depth discussions of the existing works at different granularity levels(word,sentences,document,aspect,clause,and concept levels)(iii)this state-ofart review covers each article in the following dimensions:the designated task performed,granularity level of the task completed,results obtained,and feature dimensions,and(iv)lastly it concludes the summary of the related articles according to the granularity levels,publishing years,related tasks(or subtasks),and types of classifiers used.In the end,major challenges and tasks related to lexicon-based approaches towards opinion mining are also discussed. | Mujtaba HUSNAIN Malik Muhammad Saad MISSEN Nadeem AKHTAR Mickael COUSTATY Shahzad MUMTAZ V.B.Surya PRASATH | 2021 | Frontiers of Computer Science2021，15，4： | 0 |
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